Listening with Curiosity – Tracking the Acoustic Response of Portable Laser Ablation

Nowadays, one of the methods of choice for minimal invasive sampling of solid matter is laser ablation (LA). Routine LA sampling is performed commonly in the laboratory and the amount of ablated mass can directly be monitored and analysed. By contrast laser-based sampling in the field, using a portable laser ablation system (pLA), still remains challenging concerning low-absorbing or NIR-transparent samples. The current hardware is limited in regards to photon energy and density resulting in unsteady ablation. But as the actual amount of collected mass is the major crux of on-site sampling, with this performance it is often unknown and estimates can only be made based on the experience from prior method development and the experience of the user. In the following work an easy-to-use method to monitor the amount of ablated material collected during laser-based sampling by measuring the acoustic response is presented. The pLA-system was coupled to inductively coupled plasma mass spectrometry (ICPMS) via a diffusion driven gas exchange device (GED) which allowed to monitor mass removal and acoustic response quasi-simultaneously. For the current instrumentation only actual mass removal leads to the formation of shockwaves (SW) and, thus, acoustic signals. These events can be used as indicator for executed LA events and counted on an individual basis. The intensity of acoustic signals has been shown to correlate with the LA mass, i.e., the amount of ablated material. This allows to perform re-adjustment of the laser focus during sampling for optimal ablation based on the intensity of the acoustic signal. Likewise, acoustic intensity together with counting allows the operator to make estimates about total mass sampled. Therefore, unsuccessful laser aerosol collection in the field shall become a thing of the past

A flume experiment to examine underwater sound generation by flowing water

The hydrogeomorphology and ecology of rivers and streams has been subject of intensive research for many decades. However, hydraulically-generated acoustics have been mostly neglected, even though this physical attribute is a robust signal in fluvial ecosystems. Physical generated underwater sound can be used to quantify hydro-geomorphic processes, to differentiate among aquatic habitat types, and it has implications on the behavior of organisms. In this study, acoustic signals were quantified in a flume by varying hydro-geomorphic drivers and the related turbulence and bubble formation. The acoustic signals were recorded using two hydrophones and analyzed using a signal processing software, over 31 third-octave bands (20Hz-20kHz), and then combined in 10 octave bands. The analytical method allowed for a major improvement of the signal-to-noise ratio, therefore greatly reducing the uncertainty in our analyses. Water velocity, relative submergence, and flow obstructions were manipulated in the flume and the resultant acoustic signals recorded. Increasing relative submergence ratio and water velocity were important for reaching a turbulence threshold above which distinct sound levels were generated. Increases in water velocity resulted in increased sound levels over a wide range of frequencies. The increases in sound levels due to relative submergence of obstacles were most pronounced in midrange frequencies (125Hz-2kHz). Flow obstructions in running waters created turbulence and air bubble formation, which again produced specific sound signature

Determining an empirical emission model for the auralization of jet aircraft

Aircraft noise is a major issue in urban areas and is one of the research topics within the FP7 SONORUS project. Current methods for determining the impact of aircraft noise on annoyance and sleep disturbance are based on energetic quantities neglecting the dynamic character of the sound.To obtain a more complete representation of annoyance, it would be helpful to predict the audible aircraft sound and determine the impact of the aircraft sound on people. In a related project at Empa, sonAIR, recordings were made of aircraft taking off and landing. These recordings were made at several positions and with several microphones simultaneously. Combined with cockpit data, flight path information and an inverse sound propagation model, this gives the possibility to determine the emission as function of aircraft conditions and observer angle. An inverse sound propagationmodel is used to estimate the emission in the time-domain. The obtained signal corresponds to the immission of a microphone flying along with the aircraft and rotating about it. The time-domain approach allows extracting narrowband information like tones and time-dependent variations like modulations

Determining an empirical emission model for the auralization of jet aircraft

Aircraft noise is a major issue in urban areas and is one of the research topics within the FP7 SONORUS project. Current methods for determining the impact of aircraft noise on annoyance and sleep disturbance are based on energetic quantities neglecting the dynamic character of the sound.To obtain a more complete representation of annoyance, it would be helpful to predict the audible aircraft sound and determine the impact of the aircraft sound on people. In a related project at Empa, sonAIR, recordings were made of aircraft taking off and landing. These recordings were made at several positions and with several microphones simultaneously. Combined with cockpit data, flight path information and an inverse sound propagation model, this gives the possibility to determine the emission as function of aircraft conditions and observer angle. An inverse sound propagationmodel is used to estimate the emission in the time-domain. The obtained signal corresponds to the immission of a microphone flying along with the aircraft and rotating about it. The time-domain approach allows extracting narrowband information like tones and time-dependent variations like modulations

Auralization of Accelerating Passenger Cars Using Spectral Modeling Synthesis

While the technique of auralization has been in use for quite some time in architectural acoustics, the application to environmental noise has been discovered only recently. With road traffic noise being the dominant noise source in most countries, particular interest lies in the synthesis of realistic pass-by sounds. This article describes an auralizator for pass-bys of accelerating passenger cars. The key element is a synthesizer that simulates the acoustical emission of different vehicles, driving on different surfaces, under different operating conditions. Audio signals for the emitted tire noise, as well as the propulsion noise are generated using spectral modeling synthesis, which gives complete control of the signal characteristics. The sound of propulsion is synthesized as a function of instantaneous engine speed, engine load and emission angle, whereas the sound of tires is created in dependence of vehicle speed and emission angle. The sound propagation is simulated by applying a series of time-variant digital filters. To obtain the corresponding steering parameters of the synthesizer, controlled experiments were carried out. The tire noise parameters were determined from coast-by measurements of passenger cars with idling engines. To obtain the propulsion noise parameters, measurements at different engine speeds, engine loads and emission angles were performed using a chassis dynamometer. The article shows how, from the measured data, the synthesizer parameters are calculated using audio signal processing

Determining an empirical emission model for the auralization of jet aircraft

<p>Aircraft noise is a major issue in urban areas and is one of the research topics <br> within the FP7 SONORUS project. Current methods for determining the impact of <br> aircraft noise on annoyance and sleep disturbance are based on energetic <br> quantities neglecting the dynamic character of the sound. To obtain a more <br> complete representation of annoyance, one should predict the audible aircraft <br> sound and determine the impact of the aircraft sound on people.</p> <p>In a related project at Empa, sonAIR, recordings were made of aircraft taking off and landing. These recordings were made at several positions and with several <br> microphones simultaneously. Combined with cockpit data, flight path information <br> and an inverse sound propagation model, this gives the possibility to determine <br> the emission as function of aircraft conditions and observer angle.</p> <p>An inverse sound propagation model is used to determine the emission in the <br> time-domain. The obtained signal corresponds to the immission of a microphone <br> flying along with the aircraft and rotating about it. The time-domain approach <br> allows extracting narrowband information like tones and time-dependent variations like modulations.</p