Open Access

The combination of fossil-derived fuels with ethanol and methanol has acquired relevance and attention in several countries in recent years. This trend is strongly affected by market prices, constant geopolitical events, new sustainability policies, new laws and regulations, etc. Besides bio-fuels these materials also include different additives as anti-shock agents and as octane enhancer. Some of the chemical compounds in these additives may have harmful properties for both environment and public health (besides the inherent properties, like volatility). We present detailed Raman spectral information from toluene (C7H8) and ethanol (C2H6O) contained in samples of ElO gasoline-ethanol blends. The spectral information has been extracted by using a robust, high resolution Fourier-Transform Raman spectrometer (FT-Raman) prototype. This spectral information has been also compared with Raman spectra from pure additives and with standard Raman lines in order to validate its accuracy in frequency. The spectral information is presented in the range of 0 cm-1 to 3500 cm-1 with a resolution of 1.66cm-1. This allows resolving tight adjacent Raman lines like the ones observed around 1003cm-1 and 1030cm-1 (characteristic lines of toluene). The Raman spectra obtained show a reduced frequency deviation when compared to standard Raman spectra from different calibration materials. The FT-Raman spectrometer prototype used for the analysis consist basically of a Michelson interferometer and a self-designed photon counter cooled down on a Peltier element arrangement. The light coupling is achieved with conventional62.5/125μm multi-mode fibers. This FT-Raman setup is able to extract high resolution and frequency precise Raman spectra from the additives in the fuels analyzed. The proposed prototype has no additional complex hardware components or costly software modules. The mechanical and thermal disturbances affecting the FT-Raman system are mathematically compensated by accurately extracting the optical path information of the Michelson interferometer. This is accomplished by generating an additional interference pattern with a λ = 632.8 nm Helium-Neon laser (HeNe laser). It enables the FT-Raman system to perform reliable and clean spectral measurements from the materials under observation.

Practical exercises are a crucial part of many curricula. Even simple exercises can improve the understanding of the underlying subject. Most experimental setups require special hardware. To carry out e. g. a lens experiments the students need access to an optical bench, various lenses, light sources, apertures and a screen. In our previous publication we demonstrated the use of augmented reality visualization techniques in order to let the students prepare with a simulated experimental setup. Within the context of our intended blended learning concept we want to utilize augmented or virtual reality techniques for stationary laboratory exercises. Unlike applications running on mobile devices, stationary setups can be extended more easily with additional interfaces and thus allow for more complex interactions and simulations in virtual reality (VR) and augmented reality (AR). The most significant difference is the possibility to allow interactions beyond touching a screen. The LEAP Motion controller is a small inexpensive device that allows for the tracking of the user’s hands and fingers in three dimensions. It is conceivable to allow the user to interact with the simulation’s virtual elements by the user’s very hand position, movement and gesture. In this paper we evaluate possible applications of the LEAP Motion controller for simulated experiments in augmented and virtual reality. We pay particular attention to the devices strengths and weaknesses and want to point out useful and less useful application scenarios. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

For an ultra-efficient car-engineering project, we aim to utilize AR technology for the driver and engineering team. A real-time monitoring of the car’s operational parameters is crucial for best possible fuel efficiency and overall performance.

Walking interfaces offer advantages in navigation of VE systems over other types of locomotion. However, VR helmets have the disadvantage that users cannot see their immediate surroundings. Our publication describes the prototypical implementation of a virtual environment (VE) system, capable of detecting possible obstacles using an RGB-D sensor. In order to warn users of potential collisions with real objects while they are moving throughout the VE tracking area, we designed 4 different visual warning metaphors: Placeholder, Rubber Band, Color Indicator and Arrow. A small pilot study was carried out in which the participants had to solve a simple task and avoid any arbitrarily placed physical obstacles when crossing the virtual scene. Our results show that the Placeholder metaphor (in this case: trees), compared to the other variants, seems to be best suited for the correct estimation of the position of obstacles and in terms of the ability to evade them.