Fatigue strength prediction of KhN73MBTYu-VD alloy compressor disks

Boguslaev, V. A.; Sakhno, A. G.; Yatsenko, V. K.; Gontchar, N. V.

doi:10.1007/bf02511143

Cited by 2 publications

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“…These techniques have been widely used to solve a wide variety of problems regarding the strength of materials in many engineering fields. The following literature lists some of ANN and MLR applications in predicting strength properties of various materials [9,11,[14][15][16][17][18]. These modeling approaches have been also employed for predicting strength properties of wood and wood products.…”

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confidence: 99%

Predictive Performance of Artificial Neural Network and Multiple Linear Regression Models in Predicting Adhesive Bonding Strength of Wood

et al. 2016

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Ðàçðàáîòàíû íåéðîííàÿ ñåòü è ìíîaeåñòâåííûå ëèíåéíûå ðåãðåññèîííûå ìîäåëè äëÿ îöåíêè àäãåçèîííîé ïðî÷íîñòè äåðåâÿííûõ êîíñòðóêöèé ñ ó÷åòîì èõ âëàaeíîñòè è âðåìåíè ïîëíîé ñáîðêè ýëåìåíòîâ êîíñòðóêöèè äî èõ ïðåññîâàíèÿ. Ðåçóëüòàòû ïðîâåäåííûõ ýêñïåðèìåíòàëüíûõ èññëåäîâàíèé èñïîëüçîâàëè â ðàçðàáîòàííûõ ìîäåëÿõ. Ïîêàçàíî, ÷òî ïðè óâåëè÷åíèè âëàaeíîñòè è âðåìåíè ñáîðêè àäãåçèîííàÿ ïðî÷íîñòü âíà÷àëå ðàñòåò, à çàòåì óìåíüøàåòñÿ. Ñ ïîâûøåíèåì âðåìåíè ïîëíîé ñáîðêè àäãåçèîííàÿ ïðî÷íîñòü ñíèaeàåòñÿ. Ñðàâíåíèå ðàñ÷åòíûõ ðåçóëüòàòîâ, ïîëó÷åííûõ ñ ïîìîùüþ èñêóññòâåííîé íåéðîííîé ñåòè è ìíîaeåñòâåííûõ ëèíåéíûõ ðåãðåññèîííûõ ìîäåëåé, ñâèäåòåëüñòâóåò î ïðåèìóùåñòâå ïåðâîãî ïîäõîäà, ñîãëàñíî êîòîðîìó êîýôôèöèåíò êîððåëÿöèè R 2 = 97,7%, ñðåäíåå îòêëîíåíèå ñîñòàâëÿåò 3,587%. Óñòàíîâëåíî, ÷òî èñêóññòâåííàÿ íåéðîííàÿ ñåòü ÿâëÿåòñÿ ýôôåêòèâíîé äëÿ ïðîãíîçèðîâàíèÿ àäãåçèîííîé ïðî÷íîñòè äåðåâÿííûõ êîíñòðóêöèé, ÷òî ïîçâîëÿåò ñîêðàòèòü êîëè÷åñòâî òðóäîåìêèõ è äîðîãîñòîÿùèõ ýêñïåðèìåíòàëüíûõ èññëåäîâàíèé.Êëþ÷åâûå ñëîâà: èñêóññòâåííàÿ íåéðîííàÿ ñåòü, ïðîãíîçèðîâàíèå, íàïðÿaeåíèå ñöåïëåíèÿ, ìíîaeåñòâåííàÿ ëèíåéíàÿ ðåãðåññèÿ, ñðàâíåíèå ìîäåëåé.Introduction. The adhesive bond of wood is one of the main connection methods used in modern load-bearing constructions [1]. The quality and durability of a wooden product primarily depends on the quality of its adhesive bonding [2]. The moisture content is among the most important factors affecting the final strength and durability of adhesive bonding [3]. The prolonged exposure to high moisture content severely reduces the

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mentioning

confidence: 99%

Predictive Performance of Artificial Neural Network and Multiple Linear Regression Models in Predicting Adhesive Bonding Strength of Wood

et al. 2016

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“…Аналіз експлуатації двигунів показав, що I ступінь суттєво відрізняється від інших щаблів за кількістю лопаток, що мають вибоїни. Число лопаток з вибоїнами глибиною не менше 0,3...0,5 мм на І ступені компресора приблизно в 4 рази більше, ніж на будьякої наступної ступені [16]. Тому проблема ремонту лопаток, що мають експлуатаційні ушкодження, наприклад, із застосуванням обробки пера методами поверхневого пластичного деформування, зокрема сталевими кульками в магнітному полі, дуже актуальна.…”

Section: аналіз досліджень та публікаційunclassified

Study of the Technological Possibilities of the Ball Processing Method in the Magnetic Field of Blades With Operational Damage

Pukhalska¹,

Subbotin²,

Leoshchenko³

et al. 2023

НМТ

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Purpose. To conduct a study of the technological possibilities of the method of treatment with balls in the magnetic field of the pen of vanes that have operational damage. Research methods. A mechanical method for the study of residual stresses, developed by аcad. Davydenkov, an experimental method for determining the endurance of blades, stepwise regression methods for building regression models. Results. The study of the geometry of the blade feathers shows that the biggest change in the geometry of the blades occurs in the peripheral zone (intersections A7-A7 and A8-A8). The measurement results show that the microhardness of the surface on the side of the trough is significantly lower than on the backs, and the highest values of roughness are recorded in the peripheral zone of the trough on the side of the entrance edge, which corresponds to the place of maximum operational damage. The parameters of the surface layer were studied and the scheme and optimal mode of processing blades with steel balls in a magnetic field was determined, which leads to a 39% increase in the endurance limit compared to blades that have experience in operation. Regression models of self-oscillation frequencies and blade run-in were built for two engines operated under the same conditions, but with different run-in. Special attention should be paid to measures that can minimize erosive wear of blade edges and increase the service life of engines. Scientific novelty. A new method of processing the blade feathers with balls in a magnetic field is proposed, which allows differential processing of the blade feathers: only the edge or the entire feather. Also, the method allows you to process blade feathers with operational damage, which leads to increased durability of blades. Practical value. The conducted studies allow us to recommend the use of the method of processing blade feathers with steel balls in a magnetic field as a technological operation for the restoration of compressor blades that have operational damage in the form of potholes on the inlet edges.

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Fatigue strength prediction of KhN73MBTYu-VD alloy compressor disks

Cited by 2 publications

References 0 publications

Predictive Performance of Artificial Neural Network and Multiple Linear Regression Models in Predicting Adhesive Bonding Strength of Wood

Predictive Performance of Artificial Neural Network and Multiple Linear Regression Models in Predicting Adhesive Bonding Strength of Wood

Study of the Technological Possibilities of the Ball Processing Method in the Magnetic Field of Blades With Operational Damage

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