George Karniadakis - Newton MA, US Kenneth Breuer - Newton Highlands MA, US Vasileios Symeonidis - Providence RI, US
International Classification:
B64C021/00
US Classification:
244/204000
Abstract:
The systems and methods of the invention include systems and techniques for controlling a turbulent boundary layer flow with a transverse traveling wave, oscillating at certain selected frequencies, amplitudes and wavelengths, to provide substantial reductions of drag. To this end, the systems and processes can include a boundary layer control system having an object with at least one surface exposed to a medium flowing over the surface. A plurality of excitation elements may be arranged on the surface and these elements are capable of exciting a traveling wave force field in a span-wise direction that is substantially parallel to the surface and perpendicular to direction of the flow. A first component of the traveling wave force field in the span-wise direction is substantially greater than a second component of the traveling wave force field, that is substantially perpendicular to the span-wise direction.
Lorentz Acoustic Transmitter For Underwater Communications
Chryssostomos Chryssostomidis - Boston MA, US Daniel Sura - Palm City FL, US George Karniadakis - Newton MA, US Richard Kimball - Nottingham NH, US
Assignee:
Massachusetts Institute of Technology - Cambridge MA
International Classification:
B06B 1/06
US Classification:
367134000, 367147000
Abstract:
Described is a device for generating an acoustic signal in an electrically conductive medium such as salt water. The device of the present invention has a broadband frequency response and supports high bandwidth data transmission. Reliability is improved in comparison to conventional underwater acoustic transmitters as the device includes no moving components. In one embodiment, the device includes a parallel and alternating arrangement of electrodes and magnets. Neighboring electrodes have different voltages and neighboring magnets have opposite pole configurations such that the magnetic fields overlap the currents between the electrodes in the medium. The currents or the magnetic fields are modulated according to a data signal to generate an acoustic signal in the medium.
Subra Suresh - Wellesley MA, US George E. Karniadakis - Newton MA, US Bruce Caswell - Providence RI, US Igor V. Pivkin - Providence RI, US Dmitry Fedosov - Juelich, DE David J. Quinn - Cambridge MA, US Ming Dao - Chestnut Hill MA, US
Assignee:
Brown University Research Foundation - Providence RI Massachusetts Institute of Technology - Cambridge MA
International Classification:
G06N 5/04 G06F 17/10
US Classification:
706 52, 703 2
Abstract:
The invention in some aspects relates to methods, devices and compositions for evaluating material properties, such as mechanical and rheological properties of substances, particularly biological substances, such as cells, tissues, and biological fluids. In some aspects, the invention relates to methods, devices and compositions for evaluating material properties of deformable objects, such as cells. In further aspects, the invention relates to methods, devices and compositions for diagnosing and/or characterizing disease based on material properties of biological cells.
Machine Learning Techniques For Estimating Mechanical Properties Of Materials
- Singapore, SG - Cambridge MA, US - Providence RI, US George Karniadakis - Newton MA, US
Assignee:
Nanyang Technological University - Singapore Massachusetts Institute of Technology - Cambridge MA Brown University - Providence RI
International Classification:
G06F 30/27 G06F 30/17 B29C 64/386 B33Y 50/00
Abstract:
Methods and apparatus for extracting one or more mechanical properties for a material based on one or more indentation parameters for the material. The method comprises receiving load-displacement data from one or more instrumented indentation tests on the material, determining, by at least one computer processor, the indentation parameters for the material based, at least in part, on the received load-displacement data, providing as input to a trained neural network, the indentation parameters for the material, determining, based on an output of the trained neural network, the one or more mechanical properties of the material, and displaying an indication of the determined one or more mechanical properties of the material to a user of the computer system.
- Providence RI, US Paris PERDIKARIS - Providence RI, US George E. KARNIADAKIS - Newton MA, US
International Classification:
G06F 17/13 G06N 7/00 G06K 9/62 G06F 30/27
Abstract:
A method for analyzing an object includes modeling the object with a differential equation, such as a linear partial differential equation (PDE), and sampling data associated with the differential equation. The method uses a probability distribution device to obtain the solution to the differential equation. The method eliminates use of discretization of the differential equation.
Massachusetts Institute of Technology (Mit) 2000 - 2012
Research Scientist
Brown University 1994 - 2012
Professor
Peking University 2007 - 2007
Visiting Professor
Peking Universuty 2007 - 2007
Visiting Professor
Mit Sea Grant 2007 - 2007
Researcher
Education:
Massachusetts Institute of Technology 1983 - 1987
Doctorates, Doctor of Philosophy, Mathematics, Philosophy, Mechanical Engineering
Princeton University