In this project, which is financed by the Research Council of Norway (Fripro), hybrid methods will combine element-based methods for modeling vibrations with edge-diffraction based methods for representing the air load surrounding the vibrating body. The project runs 2015-2018 in collaboration with CCRMA at Stanford University.

A horn loudspeaker is a special type of acoustic duct which acts as a transformer between a loudspeaker element and the air. The modeling requires accurate methods over a wide frequency range, and this project develops such models, taking the acoustic environment of the loudspeaker into account.

For simulations of various underground storage scenarios of CO2, we are building a 2x4 m tank (1 m high), where we will build models and use ultrasonic sensors to monitor injection of CO2. The plan is to build realistic scaled model (scaling factor is approximately 1000) and use a matrix of several ultrasonic transducers to measure acoustic signals during injection of for instance air or CO2. In this set up the plan is to simulate various leakage scenarios.

This is a 5 years project supported by the Norwegian Research Council and several industry partners. The focus is on geophysical mapping and analysis of how the rocks offshore Norway has been uplifted and eroded. There will also be a strong focus on geophysical monitoring methods, and especially the use of permanent acoustic receiver arrays that are trenched into the seabed. Increased accuracy and predictability based on repeated seismic data is an important challenge. We will develop statistical machine learning techniques, and find ways to realistically constrain spatio-temporal statistical models by measured data as for instance geophysical data or well data. Including elastic wave propagation effects in the seismic imaging and inversion methods is another key topic in the project.