RUDN University professors increased the “lifetime” of steel parts using a neural network
Repeated stress on metal parts causes “fatigue failure.” Each stress leads to microcracks that accumulate over time. Larger damage appears, and finally the part fails. Fatigue failure inevitably occurs in almost all mechanisms, this applies to all areas of industry, so technologists and scientists are looking for ways to strengthen the metal using various coatings and processing methods. RUDN University professors, together with colleagues from Italy, Canada and Turkey, built an artificial neural network that is able to predict the life of a part made of AISI 1045 steel, which makes up half of the mechanical engineering products, and select the optimal coating.
“Most machine components in the marine, oil and gas, and wind power industries are subject to repeated applied loads that cause fatigue failure. Since the phenomenon of fatigue failure is very sensitive to various parameters, including material, load, temperature, humidity, vibration, and so on, it is convenient to use neural networks for its analysis,” Reza Kashi Zadeh Kazem, professor of the Department of Transport of RUDN University.
Engineers have created a neural network that can estimate the “lifetime” of AISI 1045 carbon steel with different types of coatings under repeated loads. Nickel, hardened chrome and zinc were used as protective coatings in the model. RUDN University researchers have achieved 99% accuracy in neural network predictions. Moreover, the authors were able to select the optimal protective coating — a layer of nickel or zinc
First, RUDN scientists conducted a series of experiments with real steel parts. 23% of the obtained data was used to train the neural network, and the rest was used to test the resulting predictions. The scientists tested several neural networks, with different numbers of internal layers and neurons in each layer.
“We investigated the effect of various traditional industrial coatings, including nickel, chromium and zinc, which are commonly used to improve corrosion resistance, on the fatigue life of AISI 1045 carbon steel. The experimental results showed that nickel and hot-dip galvanized coatings with a thickness of 13 microns improved fatigue life. On the contrary, hardened chromium reduces the fatigue life of AISI 1045 steel,” Igor Danilov, Doctor of Technical Sciences, Director of the Department of Transport of the RUDN University.
The results were published in the journal JMSE.
Imagine a world where everyone has enough food, clean water, access to education, and decent work. A world where nature is protected and the future of our planet is cared for. These are the Sustainable Development Goals—to achieve a sustainable future for all! To this end, in 2015, the United Nations (UN) defined 17 Sustainable Development Goals (SDGs). The SDGs are a global plan that helps countries and people work together towards a better future. All 193 UN member states have joined the plan.
Researchers from the Faculty of Artificial Intelligence at RUDN University conducted a large-scale study that revealed systemic errors in large language models (LLMs) when diagnosing depression based on text. This work, carried out in collaboration with colleagues from AIRI, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow Institute of Physics and Technology, and MBZUAI, not only identifies the problem but also lays the foundation for the creation of more reliable and secure tools for detecting depression and anxiety.
Alexandra Sentyabreva, a junior researcher at the Laboratory of Cell Technologies and Tissue Engineering at RUDN Research Institute of Molecular and Cellular Medicine at the Russian University of People's Friendship, won the competition for young scientists at the All-Russian Scientific Conference “Topical Issues of Morphogenesis in Norm and Pathology.” She was awarded the Academician A.P. Avtsyn Prize.
Imagine a world where everyone has enough food, clean water, access to education, and decent work. A world where nature is protected and the future of our planet is cared for. These are the Sustainable Development Goals—to achieve a sustainable future for all! To this end, in 2015, the United Nations (UN) defined 17 Sustainable Development Goals (SDGs). The SDGs are a global plan that helps countries and people work together towards a better future. All 193 UN member states have joined the plan.
Researchers from the Faculty of Artificial Intelligence at RUDN University conducted a large-scale study that revealed systemic errors in large language models (LLMs) when diagnosing depression based on text. This work, carried out in collaboration with colleagues from AIRI, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow Institute of Physics and Technology, and MBZUAI, not only identifies the problem but also lays the foundation for the creation of more reliable and secure tools for detecting depression and anxiety.
Alexandra Sentyabreva, a junior researcher at the Laboratory of Cell Technologies and Tissue Engineering at RUDN Research Institute of Molecular and Cellular Medicine at the Russian University of People's Friendship, won the competition for young scientists at the All-Russian Scientific Conference “Topical Issues of Morphogenesis in Norm and Pathology.” She was awarded the Academician A.P. Avtsyn Prize.