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Алгоритмы планирования усталостных испытаний авиационных материалов

Алгоритмы планирования усталостных испытаний авиационных материалов

Abstract

Dissipation of characteristics of construction materials fatigue properties is caused by a number of objective factors. But this problem can be solved through developing and implementing into engineering practice effective mathemati-cal methods of analyzing experimental information. This paper considers optimum planning of fatigue tests. The problem of such tests optimization is important because of their expensiveness for aviation industry, so when planning the minimum number of tests their objectives must be taken into consideration. At the same time the developed statistical analysis metho d-ology is invariant to the type of tested objects. It allows increasing accuracy of defining design characteristics of endurance and fatigue limit, considerably reducing the number of fatigue tests necessary for achieving required accuracy, thus reducing their time duration and cost. The use of the existing worksheet of exact values of noncentral distribution fractiles, as well as mathematical calculation of exact values of fractiles is connected with high labour intensity of computational procedures. This paper contains new algorithms of test planning in fractile estimating and exact calculation of Student fractile of noncentral distribution. It allows offering simpler and perfect software products (considering the speed of calculations) in comparison with offered earlier.

Рассеяние характеристик усталостных свойств конструкционных материалов вызвано объективными факторами, но резерв для решения данной проблемы состоит в разработке и применении в инженерной практике эффективных математических методов анализа экспериментальной информации. В работе рассматривается проблема оптимального планирования усталостных испытаний. Оптимизация такого рода испытаний прежде всего актуальна в связи с их дороговизной в авиационной промышленности, и при определении минимального количества испытаний следует исходить из их целей. Вместе с тем разработанная методика статистического анализа инвариантна к типу испытываемых объектов. Она позволяет повысить точность определения расчетных характеристик долговечности и предела выносливости, существенно сократить объем потребных для достижения заданной точности усталостных испытаний, а значит, снизить их длительность и стоимость. Использование существующих таблиц точных значений квантилей нецентрального распределения, как и математический расчет точных значений квантилей, связано с большой трудоемкостью вычислительных процедур. В работе предложены новые алгоритмы планирования испытаний при оценке квантиля и точного расчета квантиля нецентрального распределения Стьюдента, что позволяет предложить более простые и совершенные программные продукты по скорости вычислений по сравнению с предлагаемыми ранее.

Keywords

ОПТИМАЛЬНЫЙ АЛГОРИТМ, НАДЕЖНОСТЬ, УСТАЛОСТНЫЕ ИСПЫТАНИЯ, НЕЦЕНТРАЛЬНОЕ РАСПРЕДЕЛЕНИЕ

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold