Acoustic waves in planetary atmospheres (Andi Petculescu)
As evidenced by recent missions such as Cassini-Huygens, Mars Phoenix, Venus Express, there is growing interest in detecting and analyzing signatures of wave motion in planetary atmospheres. At UL Lafayette, we are combining data analysis, theoretical and computational modeling to predict the characteristics of acoustic and gravity wave propagation in terrestrial atmospheres (Earth, Mars, Venus, and Titan). These studies are important in planetary science because they guide instrumentation development and data analysis. We have recently completed a study of the generation and propagation of thunder on Titan. The results, published here, show the optimum frequency bands in which future detectors should look. Limiting the working bandwidth helps save onboard power and optimize the measurement process.
- Infrasound absorption and dispersion in Earth's lower thermosphere (between 80 and 160 km). The premise of this project, whose preliminary results were published here, is that at thermospheric altitudes the molecular mean-free-path is large enough to require non-continuum fluid mechanics. Therefore, in our pilot study, we have developed a framework based on the Boltzmann transport equations whereby thermal conduction and viscous stress are coupled. Furthermore, the lower thermosphere corresponds to the D and E ionospheric layers, for which reason, in the current project stage we include magnetohydrodynamics to treat the mixture of neutral and charged particles.
- Acoustic dispersion and absorption profiles in Venus' lower and middle atmospheres (0 to 100 km). Venus Express has shown evidence of distinct cold and warm layers in Venus' atmosphere, and has also probed the planet's polar vortex in detail. The measurements show a dynamic and yet mysterious environment. Acoustic measurements will help to better constrain the Venusian atmospheric dynamics, fluxes, as well as cloud composition. For instance, fast and robust active acoustic sensors based on molecular acoustics could help identify the mean molecular weight and the geometry of an unknown UV-absorbing molecule at around 50 km.
Magnetometry and electron microscopy of magnetic materials (Michalis Charilaou)
Modeling and imaging of Earth and space materials (Michalis Charilaou)
Simulation of magnetic textures and dynamics in nanostructures (Michalis Charilaou)
In this project we are aiming at connecting the length scales of magnetism by combining atomistic Monte Carlo simulations and micromagnetic simulations. With the Monte Carlo method we can model the energetics of classical spin systems with up to 1 million atoms, i.e., a few nanometers large. With micromagnetic simulations we can simulate entire structures with sizes up to several micrometers. By combining the two methods we will be able to have a full description of magnetism in nanostructures, ranging from individual atomic magnetic moments to bulk solids. For the micromagnetic simulations we will be using open-source software that is already available. For the Monte Carlo simulations, the goal is to develop further an existing code developed by Michalis Charilaou. Importantly, we want to harness the power of GPU computing to accelerate the simulations and be able to produce results for larger systems in a shorter amount of time.
What you will learn:
- Physics of magnetism and magnetic materials
- Spintronics and other nanomagnetic applications
- Monte Carlo simulations
- Finite-difference micromagnetic simulations
- Programming, GPU applications
Ultrasonic studies of lattice dynamics and physical properties of novel materials (Gabriela Petculescu)
We use ultrasonic techniques such as Resonant Ultrasound Spectroscopy (RUS) and pulse-echo to obtain information about lattice dynamics and physical properties such as elastic moduli and magnetoelastic constants of novel materials (elements, alloys, and compounds). To study the elastic properties of samples with varied geometries and under a range of conditions, we probe the structures with bulk, surface, and Lamb waves, in both the linear and nonlinear acoustic regimes.
A particular class of materials of current interest are Fe-Ga alloys (known as Galfenol). Their strong magnetostrictive coupling make them promising candidates as transducer materials, whether as precision drivers or energy-harvesting devices. Gabriela Petculescu is currently measuring the elastic properties of Fe-Ga alloys as a function of composition, over a range of temperatures and magnetic fields.
Find out more here.
Physics of the Earth and Planetary Interiors (Gabriele Morra)
Study of the initial stages of terrestrial planetary formation
The focus is on the modeling the dynamic interaction between the liquid metal (core) and liquid silicates (mantle) during planetary accretion. Physical considerations show that an impactor metallic core (radius~1000 km) can emulsify into extremely small drops down to ~cm size. We develop numerical models to track metal-silicate fluid dynamics using our novel implementation of the Lattice Boltzmann Model, which uses a new formulation for modeling surface tension at extreme conditions. This is then combined with chemical and mineral physics data from collaborating groups at Tulane University and LSU to identify fine-scale metal-silicate scenarios. This is part of a larger project involving Tulane University, Louisiana State University, University of Louisiana at Lafayette and NASA Johnson Space Center. The project is supported by NASA.
- P. Mora, G. Morra, 2021, D.A. Yuen, Optimized surface tension isotropy in the Rothman-Keller colour gradient Lattice Boltzmann Method for multi-phase flow, Physical Review E.
- P. Mora, G. Morra, D.A. Yuen, R. Juanes, 2021, Optimal wetting angles in Lattice Boltzmann simulations of viscous fingering, Transport in Porous Media, https://doi.org/10.1007/s11242-020-01541-7
Inferring the causes of the eruptions in Strombolian Volcanoes
These are the most active volcanoes in the world and provide insights into mechanisms occurring deep below the surface. In this research, we introduce Machine Learning as a method to detect eruptions in millions of infrared images of the magma lake on top of a volcano. All the numerical techniques are developed in-house by the students who work on the project. This allows them to build a unique set of skills that will help them in their future career. For this project, dedicated Convolutional Neural Networks have been designed to obtain compact and fast solutions, as well as developed an approach borrowed by solar physics, the combination of Zernike moments and Support Vector Machine. Bibliography:
- B. Dye and G. Morra, 2020, Machine learning as a detection method of Strombolian eruptions in infrared images from Mount Erebus, Antarctica, Big Data in Geosciences: From Earthquake Swarms to Consequences of Slab Dynamics, Physics of the Earth and Planetary Interiors, 106508
Mud volcanoes on Mars
Presence of water under Mars' surface has been hypothesized, but direct evidence is not available. Based on the observation of tens of thousands of mounds over Mars' surface, it has been proposed that wet granular flow (mud) has emerged to the surface after cataclysmic events such an asteroid impact. Mud volcanoes on Earth exist and are associated with instability in wet granular material that flows towards the surface. We apply Machine Learning tools to spaceborne Mars data aimed at creating an integrated dataset of to reduce the uncertainty associated with their identification by remote sensing. Identifying the location of water on Mars crucial to plan the upcoming Martian explorations.
Scaling in thermal convection
The interior of stars and planets dynamics is mainly driven by thermal convection, called Rayleigh-Benard regime. To better understand the regimes through which habitable planets go through during their evolution after formation, we introduced a 3D parallel implementation of the Lattice Boltzmann Method. The code is entirely written in Python, a clean programming paradigm whose scientific use is rapidly growing and scales linearly on thousands of cores on standard Beowulf clusters. The software builds on Message Passage Interface (MPI) and vectorized operations. Results are organized in the phase space described by macroscopic parameters such as the Nusselt number (Nu), the Reynolds number (Re), the Rayleigh number (Ra) and the Prandtl number (Pr). For very large Ra we explore non-normal-nonlinear transition to turbulence and infer the consequences for Earth and Super Earths. Bibliography:
- G. Morra, D.A. Yuen, H.R. Tufo, M.G. Knepley, 2020, Fresh Outlook in Numerical Methods for Geodynamics. Part 1: Introduction and Modeling, Encyclopedia of Geology, 2e. Pages 826-840, ISBN 9780081029091, Also published in Reference Module in Earth Systems and Environmental Sciences. https://doi.org/10.1016/B978-0-08-102908-4.00110-7
- G. Morra, D.A. Yuen, H.R. Tufo, M.G. Knepley, 2020, Fresh Outlook in Numerical Methods for Geodynamics. Part 2: Big Data, HPC, Education, Encyclopedia of Geology, 2e. Pages 841-855, ISBN 9780081029091. Also published in Reference Module in Earth Systems and Environmental Sciences. https://doi.org/10.1016/B978-0-08-102908-4.00111-9
- P. Mora, G. Morra, D. A. Yuen, 2019, A concise Python implementation of the Lattice Boltzmann Method on HPC for geo-fluid flow, Geophysical Journal International, Volume 220, Issue 1, Pages 682–702, https://doi.org/10.1093/gji/ggz423
Computational ocean acoustics (Natalia Sidorovskaia)
Underwater acoustics research at UL Lafayette is concentrated on developing computational models to accurately predict how different sounds propagate through different regions of the ocean. These models are used in detailed mapping of ocean temperature (ocean acoustic tomography) which impacts hurricane strengths and paths; in seismic data interpretation to find oil/gas reserves for deep water drilling; and in predicting the human environmental impact on marine life. In the past decade she has been also closely involved in designing, conducting and processing passive acoustic experiments to study marine mammals, particularly sperm and beaked whales in the Gulf of Mexico.
Computational ocean acoustics (Natalia Sidorovskaia)
Underwater acoustics is a research area where scientists collect acoustic signals produced by humans or nature in the ocean and decode them through sophisticated signal processing and interpretation techniques. Acoustic signals are the most viable sensing tools to explore the underwater world because, unlike electromagnetic signals, they can propagate far from the source. This fact explains why marine animals (dolphins, whales etc.) have the most advanced sound production and perception (hearing) organs.
In 2000 we formed a consortium of scientists called the Littoral Acoustic Demonstration Center (LADC). LADC research is mostly dedicated to studies of marine mammals in the world oceans based on recordings of their acoustic signals. One focus of LADC research is the search for subtle signatures in animal’s phonations that may give scientists clues how to recognize individual animals acoustically in collected data and to understand their communication codes (“languages”). The expertise of the LADC group has currently been acknowledged by awarding our consortium over $5,000,000 in funding from BP/GOMRI research program to continue monitoring effects of the 2010 Gulf of Mexico on deep diving marine mammals. This award will open unprecedented opportunity for our research group to complete the only long-term study of the oil spill impact on several species of deep diving marine mammals using acoustic methods.