Russian Scientists Assess Dangers of Internal Waves During Underwater Volcanic Eruptions
Mathematicians at HSE University in Nizhny Novgorod and the A.V. Gaponov-Grekhov Institute of Applied Physics of the Russian Academy of Sciences studied internal waves generated in the ocean after the explosive eruption of an underwater volcano. The researchers calculated how the waves vary depending on ocean depth and the radius of the explosion source. It turns out that the strongest wave in the first group does not arrive immediately, but after a significant delay. This data can help predict the consequences of eruptions and enable advance preparation for potential threats. The article has been published in Natural Hazards. The research was carried out with support from the Russian Science Foundation (link in Russian).
Layers of water with varying temperature, density, and salinity form in an ocean column. Internal waves arise at the boundaries of these layers due to external forces such as wind, currents, earthquakes, and volcanic eruptions, which cause the upper and lower layers to shift relative to each other. The boundary starts to oscillate, attempting to return to its original position under the influence of buoyancy forces. Since the density difference between the layers is small, internal waves have a larger amplitude (usually 5–20 metres but sometimes up to 150 metres) compared to surface waves, where the density contrast between water and air is much greater.
Although the speeds of internal waves are relatively slow (typically only a few dozen centimetres per second), they can still pose a serious threat to hydraulic structures, underwater gas and oil pipelines, and can also lead to the erosion of the ocean floor. Disasters involving at least three submarines have been attributed to the effects of internal waves: the two American atomic submarines, USS Thresher in 1963 and USS Scorpion in 1968, and the Indonesian diesel submarine KRI Nanggala-402 in 2021.
‘During underwater volcanic eruptions and earthquakes, the primary danger comes from surface tsunami waves, which can have amplitudes of up to 30 meters on the coast and can be highly destructive. Internal waves are typically not considered in such cases. However, a recent article by Chinese colleagues reported for the first time the observation of internal waves during a volcanic eruption in the Tonga Archipelago in 2022. This sparked our interest in studying the characteristics of internal waves,’ explains co-author of the study Ekaterina Didenkulova, Leading Research Fellow at the International Laboratory of Dynamical Systems and Applications at HSE University in Nizhny Novgorod.
Le Mehaute’s parabolic cavern was chosen as a source of tsunami waves. This model is commonly used to calculate surface tsunami waves generated by underwater explosions, volcanic eruptions, and meteorite impacts in water. It was considered that the curves connecting points with the same seawater density (isopycnals) bend over an underwater volcano in the same way as the water surface.
Calculations reveal that internal waves generated by the eruption of an underwater volcano form frequency-modulated groups, with the first group exhibiting the largest amplitude. The characteristics of internal waves depend on the ratio of layer thicknesses, the source radius, and the distance from the source. Even at relatively small distances from the source, the wave amplitudes change gradually, allowing the source of a tsunami to be identified from internal waves using remote sensing of the sea surface. This approach makes it possible to obtain additional information about the tsunami and mitigate potential damage caused by the disaster.
'The amplitudes of the waves in the remote zone are a percentage of their height at the source, but when translated into real numbers, they can correspond to several metres. Thus, the eruption site of the Krakatoa volcano in 1883 had a height of 200 metres and a radius of three kilometres. Our calculations indicate that the height of an internal wave at a distance of 300 kilometres can be around 10 meters, which could still pose a danger,' comments Efim Pelinovsky, Chief Research Fellow at the International Laboratory of Dynamical Systems and Applications at HSE University in Nizhny Novgorod.
See also:
HSE Linguists Study How Bilinguals Use Phrases with Numerals in Russian
Researchers at HSE University analysed over 4,000 examples of Russian spoken by bilinguals for whom Russian is a second language, collected from seven regions of Russia. They found that most non-standard numeral constructions are influenced not only by the speakers’ native languages but also by how frequently these expressions occur in everyday speech. For example, common phrases like 'two hours' or 'five kilometres’ almost always match the standard literary form, while less familiar expressions—especially those involving the numerals two to four or collective forms like dvoe and troe (used for referring to people)—often differ from the norm. The study has been published in Journal of Bilingualism.
Overcoming Baby Duck Syndrome: How Repeated Use Improves Acceptance of Interface Updates
Users often prefer older versions of interfaces due to a cognitive bias known as the baby duck syndrome, where their first experience with an interface becomes the benchmark against which all future updates are judged. However, an experiment conducted by researchers from HSE University produced an encouraging result: simply re-exposing users to the updated interface reduced the bias and improved their overall perception of the new version. The study has been published in Cognitive Processing.
Mathematicians from HSE Campus in Nizhny Novgorod Prove Existence of Robust Chaos in Complex Systems
Researchers from the International Laboratory of Dynamical Systems and Applications at the HSE Campus in Nizhny Novgorod have developed a theory that enables a mathematical proof of robust chaotic dynamics in networks of interacting elements. This research opens up new possibilities for exploring complex dynamical processes in neuroscience, biology, medicine, chemistry, optics, and other fields. The study findings have been accepted for publication in Physical Review Letters, a leading international journal. The findings are available on arXiv.org.
Large Language Models No Longer Require Powerful Servers
Scientists from Yandex, HSE University, MIT, KAUST, and ISTA have made a breakthrough in optimising LLMs. Yandex Research, in collaboration with leading science and technology universities, has developed a method for rapidly compressing large language models (LLMs) without compromising quality. Now, a smartphone or laptop is enough to work with LLMs—there's no need for expensive servers or high-powered GPUs.
AI to Enable Accurate Modelling of Data Storage System Performance
Researchers at the HSE Faculty of Computer Science have developed a new approach to modelling data storage systems based on generative machine learning models. This approach makes it possible to accurately predict the key performance characteristics of such systems under various conditions. Results have been published in the IEEE Access journal.
Researchers Present the Rating of Ideal Life Partner Traits
An international research team surveyed over 10,000 respondents across 43 countries to examine how closely the ideal image of a romantic partner aligns with the actual partners people choose, and how this alignment shapes their romantic satisfaction. Based on the survey, the researchers compiled two ratings—qualities of an ideal life partner and the most valued traits in actual partners. The results have been published in the Journal of Personality and Social Psychology.
Trend-Watching: Radical Innovations in Creative Industries and Artistic Practices
The rapid development of technology, the adaptation of business processes to new economic realities, and changing audience demands require professionals in the creative industries to keep up with current trends and be flexible in their approach to projects. Between April and May 2025, the Institute for Creative Industries Development (ICID) at the HSE Faculty of Creative Industries conducted a trend study within the creative sector.
From Neural Networks to Stock Markets: Advancing Computer Science Research at HSE University in Nizhny Novgorod
The International Laboratory of Algorithms and Technologies for Network Analysis (LATNA), established in 2011 at HSE University in Nizhny Novgorod, conducts a wide range of fundamental and applied research, including joint projects with large companies: Sberbank, Yandex, and other leaders of the IT industry. The methods developed by the university's researchers not only enrich science, but also make it possible to improve the work of transport companies and conduct medical and genetic research more successfully. HSE News Service discussed work of the laboratory with its head, Professor Valery Kalyagin.
Children with Autism Process Sounds Differently
For the first time, an international team of researchers—including scientists from the HSE Centre for Language and Brain—combined magnetoencephalography and morphometric analysis in a single experiment to study children with Autism Spectrum Disorder (ASD). The study found that children with autism have more difficulty filtering and processing sounds, particularly in the brain region typically responsible for language comprehension. The study has been published in Cerebral Cortex.
HSE Scientists Discover Method to Convert CO₂ into Fuel Without Expensive Reagents
Researchers at HSE MIEM, in collaboration with Chinese scientists, have developed a catalyst that efficiently converts CO₂ into formic acid. Thanks to carbon coating, it remains stable in acidic environments and functions with minimal potassium, contrary to previous beliefs that high concentrations were necessary. This could lower the cost of CO₂ processing and simplify its industrial application—eg in producing fuel for environmentally friendly transportation. The study has been published in Nature Communications.