There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Where does the mind stop and the rest of the world begin? The question invites two standard replies. Some accept the intuitive demarcations of skin and skull, and say that what is outside the body is outside the mind. Others are impressed by arguments suggesting that the meaning of our words "just ain't in the head", and hold that this externalism about meaning carries over into an externalism about mind. We propose to pursue a third position. We will advocate an externalism about mind, but one that is in no way grounded in the debatable role of external reference in fixing the contents of our mental states. Rather, we advocate an *active externalism*, based on the active role of the environment in driving cognitive processes.

The Extended Mind

From the Publisher:
The old opposition of matter versus mind stubbornly persists in the way we study mind and brain. In treating cognition as problem solving, Andy Clark suggests, we may often abstract too far from the very body and world in which our brains evolved to guide us. Whereas the mental has been treated as a realm that is distinct from the body and the world, Clark forcefully attests that a key to understanding brains is to see them as controllers of embodied activity. From this paradigm shift he advances the construction of a cognitive science of the embodied mind.

/pdf/being-there-putting-brain-body-and-world-together-again-31tt4y51ml.pdf

Being There: Putting Brain, Body, and World Together Again

The boundary layer equations for plane, incompressible, and steady flow are 

$$\matrix{ {u{{\partial u} \over {\partial x}} + v{{\partial u} \over {\partial y}} = - {1 \over \varrho }{{\partial p} \over {\partial x}} + v{{{\partial ^2}u} \over {\partial {y^2}}},} \cr {0 = {{\partial p} \over {\partial y}},} \cr {{{\partial u} \over {\partial x}} + {{\partial v} \over {\partial y}} = 0.} \cr }$$

Boundary Layer Theory

Sensor, herstellungsverfahren dafür und verfahren zur steuerung davon

The Vortex-induced vibration (VIV) prediction of long flexible cylindrical structures relies on the accuracy of the hydrodynamic database constructed via rigid cylinder forced vibration experiments. However, to create a comprehensive hydrodynamic database with tens of input parameters including vibration amplitudes and frequencies and Reynolds number, surface roughness and so forth is technically challenging and virtually impossible due to the large number of experiments required. The current work presents an alternative approach to approximate the crossflow (CF) hydrodynamic coefficient database in a carefully chosen parameterized form. The learning of the parameters is posed as a constraint optimization, where the objective function is constructed based on the error between the experimental response and theoretical prediction assuming energy balance between fluid and structure. Such a method yields the optimal estimation of the CF parametric hydrodynamic database and produces the VIV response prediction based on the updated hydrodynamic database. The method then was tested on several experiments, including freely-mounted rigid cylinder in large Reynolds number with combined crossflow and inline vibrations and large-scale flexible cylinder test in the Norwegian Deepwater Program, and the result is shown to robustly and significantly reduce the error in predicting cylinder VIVs.

Learning Optimal Parametric Hydrodynamic Database for Vortex-Induced Crossflow Vibration Prediction

Currents and waves cause flow-structure interaction problems in systems installed in the ocean. Particularly for bluff bodies, vortices form in the body wake, which can cause strong structural vibrations (Vortex-Induced Vibrations, VIV). The magnitude and frequency content of VIV is determined by the shape, material properties, and size of the bluff body, and the nature and velocity of the oncoming flow. Riser systems are extensively used in the ocean to drill for oil wells, or produce oil and gas from the bottom of the ocean. Risers often consist of a central pipe, surrounded by several smaller cylinders, including the kill and choke lines. We present a series of experiments involving forced in-line and cross flow motions of short rigid sections of a riser containing 6 symmetrically arranged kill and choke lines. The experiments were carried out at the MIT Towing Tank. We present a systematic database of the hydrodynamic coefficients, consisting of the forces in phase with velocity and the added mass coefficients that are also suitable to be used with semi-empirical VIV predicting codes. INTRODUCTION Vortex-induced vibrations are generated as oncoming fluid flow interacts with a flexible body or structure. In the classical case of a flexibly mounted rigid cylinder, alternating vortices form on either side of the bluff body causing it to vibrate. This phenomenon can lead to the aeolian tones in the wind, or to fatigue damage in larger ocean structures. The potential for fatigue damage is one of the main motivations for research on VIV [1]. Systematic experiments have generated a substantial databases of VIV coefficients to predict the effect on a variety of structural systems [2, 3]. A drilling riser consists of a largerdiameter pipe containing the drilling string, and stretching from the well at the sea floor to the surface structure. The purpose of the riser is to protect the drilling string and also return the circulating mud back to the surface [4]. The kill line pumps kill fluid such that fluid can then flow through the choke line to the surface. Both of these lines are high-pressure pipes essential for maintaining fluid pressure in the riser. These lines run along the outside of the central riser from the bottom of the sea floor to the surface, creating a specific cross-sectional shape that is also subject to VIV. In order to accurately model VIV, databases have been compiled of various structural shapes, based on rigid cylinder experiments, and are utilized in semi-empirical programs, such as Shear7 (Vandiver 1999) [5], VIVA (Triantafyllou 1999) [6], and VIVANA (Larsen 2000) [7]. These programs are widely used in industry and for research purposes today. To ensure that these programs are kept up to date and relevant to structures regularly used today, it is important to compile databases specific to the structures studied. Previous research shows that VIV is depenProceedings of the ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering OMAE2017 June 25-30, 2017, Trondheim, Norway

Kill Line Model Cross Flow Inline Coupled Vortex-Induced Vibration

Accurate prediction of the structural response of flexible cylinder vortex-induced vibrations (VIVs) relies heavily on the accuracy of the acquired hydrodynamic coe ffi cient database. Due to a large number of variables, the construction of systematic hydrodynamic databases from rigid cylinder forced vibration experiments can be time-consuming or even intractable. A novel approach has been implemented in this paper to improve the flexible cylinder VIV prediction by inferring the optimal parametric hydrodynamic database using measurements along with the structure; such a methodology has been demonstrated for uniform straight (flexible) risers in uniform flow using displacement data. This work extends the framework and applies it to the straight riser problem using only limited strain measurements. The predicted amplitude and frequency responses are compared with experimental results.

Data-driven prediction of flexible cylinder vortex induced vibrations using limited sensor measurements.

http://dspace.mit.edu/openaccess-disseminate/1721.1/110726

Michael S. Triantafyllou

Papers

Sensor, herstellungsverfahren dafür und verfahren zur steuerung davon

Learning Optimal Parametric Hydrodynamic Database for Vortex-Induced Crossflow Vibration Prediction

Kill Line Model Cross Flow Inline Coupled Vortex-Induced Vibration

Data-driven prediction of flexible cylinder vortex induced vibrations using limited sensor measurements.

Vortex Dynamics in Flow Instabilities and Biomimetic Flows (Prof. Jin S. Chung Award Lecture, 2015)