2019
DOI: 10.1134/s1995080219070059
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Optimization of Thermal Protection Panels Subjected to Intense Heating and Mechanical Loading

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Cited by 17 publications
(5 citation statements)
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“…4 The authors do not take into account such situations when the route in a building that is exposed to smoke spread is known in advance and carefully planned even at the stage of preparing the fire-prevention strategy. 5,6 The attention is paid to those situations when firefighters are forced to enter buildings where the fire spreads rather randomly and it is not always possible to evaluate it adequately in real time. 7 In this situation, firefighters should develop and lay a route based on the actual situation and provide for the main protective function -to bypass potentially hazardous areas when smoke is spreading.…”
Section: Introductionmentioning
confidence: 99%
“…4 The authors do not take into account such situations when the route in a building that is exposed to smoke spread is known in advance and carefully planned even at the stage of preparing the fire-prevention strategy. 5,6 The attention is paid to those situations when firefighters are forced to enter buildings where the fire spreads rather randomly and it is not always possible to evaluate it adequately in real time. 7 In this situation, firefighters should develop and lay a route based on the actual situation and provide for the main protective function -to bypass potentially hazardous areas when smoke is spreading.…”
Section: Introductionmentioning
confidence: 99%
“…Depending on the tasks, in the work you can use such software systems: LUSAS (Great Britain); GTSTRUDL (USA); MIDAS/CIVIL (Korea); RM BRIDGE (Austria); SOFISTIK (Germany); LIRA (Ukraine); ANSYS, NAUSTRAN, SCAD, KATRAN, Tekla (Russia) and many other complexes that allow you to build finite-element computational models of artificial structures with minimal labor and time, for design engineers (Babaytsev et al, 2017;Babaytsev et al, 2019;Cabana et al, 2018;Gendler & Savenkov, 2017).…”
Section: Introductionmentioning
confidence: 99%
“…There are many different strategies to reduce the learning rate during training. It can also be beneficial to start with a low learning rate, increase it, then drop it again [7]. Comparing CNN and "traditional" analytical algorithm, the CNN are of course powerful but computationally intensive and require substantial data for training, making them wellsuited for complex computer vision tasks.…”
Section: Introductionmentioning
confidence: 99%