Dr. Berndt Bartos Profile

Dr. Berndt Bartos

at Fraunhofer-IOSB

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Author

Publications (4)

Proceedings Article | 19 October 2023 Presentation + Paper

An electrooptical propagation and signature experiment in a humid environment

Christian Eisele, Dirk Seiffer, Erik Sucher, Carmen Ullwer, Peter Großmann, Berndt Bartos

Proceedings Volume 12731, 1273104 (2023) https://doi.org/10.1117/12.2675880

KEYWORDS: Simulations, Sensors, Turbulence, Electro optics, Electro optical modeling, Atmospheric propagation, Thermal modeling

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Proceedings Article | 9 October 2018 Paper

Adaptive camouflage panel in the visible spectral range

Alexander Schwarz, Berndt Bartos, Michael Kunzer, Martin Zechmeister, Jakub Pawlikowski

Proceedings Volume 10794, 107940W (2018) https://doi.org/10.1117/12.2326591

KEYWORDS: Light emitting diodes, Sensors, Camouflage, Visible radiation, Reflection, Microcontrollers, Color reproduction, Diffusers, Temperature metrology, Eye

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Proceedings Article | 9 October 2018 Presentation + Paper

Visualizing simulated temperatures of a complex object calculated with FTOM using open source software (BLENDER)

B. Bartos, K. Stein

Proceedings Volume 10794, 1079407 (2018) https://doi.org/10.1117/12.2325380

KEYWORDS: Temperature metrology, Visualization, Solid modeling, Sun, Data modeling, Thermal modeling, 3D modeling, Cameras, Open source software, Convection

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The Fraunhofer thermal object model (FTOM) predicts the temperature of an object as a function of the environmental conditions. The model has an outer layer exchanging radiation and heat with the environment and a stack of layers beyond modifying the thermal behavior. The orientation of the layer is defined by the normal vector of the surface. The innermost layer is at a constant or variable temperature called core temperature. All the layers have heat capacity and thermal conductivity. The outer layers properties are color (visible), emissivity (IR), coefficients of free and forced convection, and a factor for latent heat. The environmental parameters are air temperature, wind speed, relative humidity, irradiation of the sun, and thermal radiation of the sky and ground. The properties of the model (7 parameters) are fitted to minimize the difference between the prediction and a time series of measured temperatures. The size of the time series is one or more days with 288 values per day (5 minute resolution). The model is useable for very different objects like backgrounds (meadow, forest, rocks, sand, or bricks) or parts of objects like vehicles. The STANDCAM is a decoy of a vehicle and is used to constitute a thermal signature and is not classified. The STANDCAM has a complex CAD-Model with thousands of triangular facets that had to be simplified for the thermal simulation. The CAD model was available through WTD 52, an agency of the Federal Office of Bundeswehr Equipment, Information Technology and In-Service Support (BAAINBw). Groups of elements of the model facing in the same direction and behaving similarly were cut out and grouped in distinct objects. The calculation of the temperature of the objects is based on measured environmental data and the model parameters are fitted on measured radiation temperatures of the objects and backgrounds. For the visualization the object is surrounded by a world texture. For the radiation temperature of the environment and the ground under the object measured air and meadow temperatures were used. The temperature is coded as a color from a palette (here we use a grey palette) and is updated regularly throughout the calculation of the scene for the selected view and is stored as a texture bitmap. The animation of the temperature textures is directly performed by BLENDER.The result of the visualization is available as movie that is watchable in real time or time lapse.

Proceedings Article | 21 October 2015 Paper

FTOM-2D: a two-dimensional approach to model the detailed thermal behavior of nonplanar surfaces

B. Bartos, K. Stein

Proceedings Volume 9653, 96530G (2015) https://doi.org/10.1117/12.2197177

KEYWORDS: Temperature metrology, Thermal modeling, Thermography, Solar radiation, Data modeling, Solar radiation models, Sun, Convection, MATLAB, Time metrology

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