Imitating the Cricket Cercal System: The Beauty of the Beast with a Twist of the Engineer

MEMS offers exciting possibilities for the fabrication of bioinspired mechanosensors. Over the last years we have been working on cricket inspired hair-sensor arrays for spatio-temporal flow-field observations (i.e flow-camera) and source localization. Whereas making flow-sensors as energy efficient as cricket hair-sensors appears to be a real challenge we have managed to fabricate capacitively interrogated sensors with sub millimeter per second flow sensing thresholds, to use them in lateral line experiments, address them individually while in arrays tracking transient flows, and use nonlinear effects to achieve parametric filtering and amplification. During these developments we have been working in close collaboration with insect biologists, generating a bidirectional flow of information and knowledge, beneficial to both parties. E.g. where the engineering has greatly benefitted from the insights derived from biology and biophysical models, the biologists have been able to take advantage of MEMS structures allowing for the sort of analysis that is hard to do on living material (e.g. the study of viscous coupling between closely spaced hair-sensors).

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Influence of ZNMF jet flow control on the spatio-temporal flow structure over a NACA-0015 airfoil

Experiments in Fluids ◽

10.1007/s00348-013-1485-7 ◽

2013 ◽

Vol 54 (3) ◽

Cited By ~ 31

Author(s):

N. A. Buchmann ◽

C. Atkinson ◽

J. Soria

Keyword(s):

Flow Control ◽

Flow Structure ◽

Jet Flow ◽

Spatio Temporal ◽

Naca 0015 ◽

Temporal Flow

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Technique for Reducing the Effects of Nonlinear Terms on Electric Field Measurements of Electric Field Sensor Arrays on Aircraft Platforms

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-14-00029.1 ◽

2015 ◽

Vol 32 (5) ◽

pp. 993-1003 ◽

Cited By ~ 4

Author(s):

D. M. Mach

Keyword(s):

Electric Field ◽

External Electric Field ◽

Electric Fields ◽

Sensor Arrays ◽

Field Measurements ◽

Nonlinear Effects ◽

Electric Field Sensor ◽

Cloud Properties ◽

Field Sensor ◽

Nonlinear Components

AbstractA generalized technique has been developed that reduces the contributions of nonlinear effects that occur during measurements of natural electric fields around thunderstorms by an array of field mills on an aircraft. The nonlinear effects can be due to nearby charge emitted by the aircraft as it acquires and sheds charge, but the nonlinear effects are not limited to such sources. The generalized technique uses the multiple independent measurements of the external electric field obtained during flight to determine and remove nonlinear contaminations in the external vector electric field. To demonstrate the technique, a simulated case with nonlinear contaminations was created and then corrected for the nonlinear components. In addition, data from two different field programs utilizing two different aircraft and field mill configurations, each containing observable and different nonlinear effects, were also corrected for the significant nonlinear effects found in the field mill outputs. The expanded independent measurements in this new technique allow for the determination and correction of components in the field mill outputs from almost any measurable source. Alternate utilization of the technique can include removing effects in the aircraft charging such as aircraft altitude, cloud properties, engine power settings, or aircraft flap deployment. This technique provides a way to make more precise measurements of the true external electric field for scientific studies of cloud electrification.

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A hybrid integrated deep learning model for the prediction of citywide spatio-temporal flow volumes

International Journal of Geographical Information Science ◽

10.1080/13658816.2019.1652303 ◽

2019 ◽

Vol 34 (4) ◽

pp. 802-823 ◽

Cited By ~ 3

Author(s):

Yibin Ren ◽

Huanfa Chen ◽

Yong Han ◽

Tao Cheng ◽

Yang Zhang ◽

...

Keyword(s):

Deep Learning ◽

Learning Model ◽

Spatio Temporal ◽

Temporal Flow ◽

Deep Learning Model

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Flow field diagnostics - Topological flow changes and spatio-temporal flow structure

10.2514/6.1995-791 ◽

1995 ◽

Cited By ~ 15

Author(s):

U Dallmann ◽

ThGebing, Herberg, ing, H ◽

W Su ◽

H Zhang

Keyword(s):

Flow Field ◽

Flow Structure ◽

Flow Changes ◽

Spatio Temporal ◽

Temporal Flow

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AUTOMATIC SPATIO-TEMPORAL FLOW VELOCITY MEASUREMENT IN SMALL RIVERS USING THERMAL IMAGE SEQUENCES

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iv-2-201-2018 ◽

2018 ◽

Vol IV-2 ◽

pp. 201-208 ◽

Cited By ~ 2

Author(s):

D. Lin ◽

A. Eltner ◽

H. Sardemann ◽

H.-G. Maas

Keyword(s):

Flow Velocity ◽

Velocity Measurement ◽

Feature Tracking ◽

Image Sequences ◽

Small Rivers ◽

Thermal Camera ◽

Flow Velocity Measurement ◽

Spatio Temporal ◽

Temporal Flow ◽

Thermal Feature

An automatic spatio-temporal flow velocity measurement approach, using an uncooled thermal camera, is proposed in this paper. The basic principle of the method is to track visible thermal features at the water surface in thermal camera image sequences. Radiometric and geometric calibrations are firstly implemented to remove vignetting effects in thermal imagery and to get the interior orientation parameters of the camera. An object-based unsupervised classification approach is then applied to detect the interest regions for data referencing and thermal feature tracking. Subsequently, GCPs are extracted to orient the river image sequences and local hot points are identified as tracking features. Afterwards, accurate dense tracking outputs are obtained using pyramidal Lucas-Kanade method. To validate the accuracy potential of the method, measurements obtained from thermal feature tracking are compared with reference measurements taken by a propeller gauge. Results show a great potential of automatic flow velocity measurement in small rivers using imagery from a thermal camera.

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The NO<sub>2</sub> camera based on Gas Correlation Spectroscopy

10.5194/amt-2021-298 ◽

2021 ◽

Author(s):

Leon Kuhn ◽

Jonas Kuhn ◽

Thomas Wagner ◽

Ulrich Platt

Keyword(s):

Temporal Resolution ◽

Sensor Arrays ◽

Visible Spectral Range ◽

Correlation Spectroscopy ◽

High Concentration ◽

Gas Cell ◽

Signal Ratio ◽

Large Power ◽

Spectral Window ◽

Spatio Temporal

Abstract. Monitoring of NO2 is in the interest of public health, because NO2 contributes to the decline of air quality in many urban regions. Its abundance can be a direct cause of asthmatic and cardiovascular diseases and plays a significant part in forming other pollutants such as ozone or particulate matter. Spectroscopic methods have proven to be reliable and of high selectivity by utilizing the characteristic spectral absorption signature of trace gasses such as NO2. However, they typically lack the spatio-temporal resolution required for real-time imaging measurements of NO2 emissions. We propose imaging measurements of NO2 in the visible spectral range using a novel instrument, an NO2 camera based on the principle of Gas Correlation Spectroscopy (GCS). For this purpose two gas cells (cuvettes) are placed in front of two camera modules. One gas cell is empty, while the other is filled with a high concentration of the target gas. The filled gas cell operates as a non-dispersive spectral filter to the incoming light, maintaining the two-dimensional imaging capability of the sensor arrays. NO2 images are generated on the basis of the signal ratio between the two images in the spectral window between 430 and 445 nm, where the NO2 absorption cross section is strongly structured. The capabilities and limits of the instrument are investigated in a numerical forward model. The predictions of this model are verified in a proof-of-concept measurement, in which the column densities in specially prepared reference cells were measured with the NO2 camera and a conventional DOAS instrument. Finally, results from measurements at a large power plant, the Großkraftwerk Mannheim (GKM), are presented. NO2 column densities of the plume emitted from a GKM chimney are quantified at a spatio-temporal resolution of 1/6 frames per second (FPS) and 0.92 m × 0.92 m. A detection limit of 1.89 · 1016 molec cm−2 was reached. An NO2 mass flux of Fm = (7.41 ± 4.23) kg h−1 was estimated on the basis of momentary wind speeds obtained from consecutive images. The camera results are verified by comparison to NO2 slant column densities obtained from elevation scans with a MAX-DOAS instrument. The instrument prototype is highly portable and cost-efficient at building costs of below 2,000 Euro.

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Spatio-temporal proper orthogonal decomposition of turbulent channel flow

Journal of Fluid Mechanics ◽

10.1017/jfm.2019.48 ◽

2019 ◽

Vol 864 ◽

pp. 614-639 ◽

Cited By ~ 6

Author(s):

Srikanth Derebail Muralidhar ◽

Bérengère Podvin ◽

Lionel Mathelin ◽

Yann Fraigneau

Keyword(s):

Proper Orthogonal Decomposition ◽

Channel Flow ◽

Nonlinear Effects ◽

Turbulent Channel Flow ◽

Wall Layer ◽

Orthogonal Decomposition ◽

Closed Form Expression ◽

Temporal Decomposition ◽

Spatio Temporal ◽

Proper Orthogonal

An extension of proper orthogonal decomposition is applied to the wall layer of a turbulent channel flow ($Re_{\unicode[STIX]{x1D70F}}=590$), so that empirical eigenfunctions are defined in both space and time. Due to the statistical symmetries of the flow, the eigenfunctions are associated with individual wavenumbers and frequencies. Self-similarity of the dominant eigenfunctions, consistent with wall-attached structures transferring energy into the core region, is established. The most energetic modes are characterized by a fundamental time scale in the range 200–300 viscous wall units. The full spatio-temporal decomposition provides a natural measure of the convection velocity of structures, with a characteristic value of 12$u_{\unicode[STIX]{x1D70F}}$ in the wall layer. Finally, we show that the energy budget can be split into specific contributions for each mode, which provides a closed-form expression for nonlinear effects.

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