Overstraining gun tubes has a twofold advantage. First, it enables the increase of the Safe Maximum Pressure(SMP) in the tube, resulting in a higher muzzle velocity which extends the gun's range and its projectile...Overstraining gun tubes has a twofold advantage. First, it enables the increase of the Safe Maximum Pressure(SMP) in the tube, resulting in a higher muzzle velocity which extends the gun's range and its projectile kinetic energy. Second, it reduces the tube's susceptibility to internal cracking which prolongs its fatigue life. Unfortunately, autofrettage also bears an inherent detrimental effect as it considerably increases the tensile hoop stress at the outer portion of the barrel's wall, which enhances external cracking of the tube by increasing the prevailing Stress Intensity Factor(SIF). In order to quantify this disadvantageous effect, 3-D Mode I SIFs distributions along the front of a single external radial semielliptical crack initiating from the outer surface of an autofrettaged modern gun barrel, overstrained by either the Swage or the Hydraulic autofrettage processes, are evaluated. The analysis is performed by the finite element(FE) method, using singular elements along the crack front. Innovative residual stress fields(RSFs), incorporating the Bauschinger effect for both types of autofrettage are applied to the barrel.Hill's [1] RSF is also applied to the tube for comparison reasons. All three RSFs are incorporated in the FE analysis, using equivalent temperature fields, Values for K_(IA)-the SIF resulting from the tensile residual stresses induced by autofrettage are evaluated for: a typical barrel of radii ratio R_o/R_i = 2, crack depth to wall-thickness ratios(a/t = 0.005-0.1),crack ellipticities(a/c = 0.2-1.0),and five levels of Swage,Hydraulic and Hill's autofrettage(e = 40%,60%,70%,80%,and 100%). In total,375 different 3-D cases are analyzed. The analysis demonstrates undoubtedly the detrimental effect of all types of autofrettage in increasing the prevailing effective stress intensity factor of external cracks, resulting in crack initiation enhancement and crack growth rate acceleration which considerably shortens the total fatigue life of the barrel. Nonetheless, the detrimental effect is autofrettage-type dependent. Swage and Hydraulic autofrettage RSFs differ substantially from each other. The disadvantageous effect of Swage autofrettage is much greater than that resulting from Hydraulic autofrettage. The results also emphasize the significance of the Bauschinger effect and the importance of the 3-D analysis.展开更多
Despite widespread adoption and outstanding performance, machine learning models are considered as ‘‘blackboxes’’, since it is very difficult to understand how such models operate in practice. Therefore, in the po...Despite widespread adoption and outstanding performance, machine learning models are considered as ‘‘blackboxes’’, since it is very difficult to understand how such models operate in practice. Therefore, in the powersystems field, which requires a high level of accountability, it is hard for experts to trust and justify decisionsand recommendations made by these models. Meanwhile, in the last couple of years, Explainable ArtificialIntelligence (XAI) techniques have been developed to improve the explainability of machine learning models,such that their output can be better understood. In this light, it is the purpose of this paper to highlight thepotential of using XAI for power system applications. We first present the common challenges of using XAI insuch applications and then review and analyze the recent works on this topic, and the on-going trends in theresearch community. We hope that this paper will trigger fruitful discussions and encourage further researchon this important emerging topic.展开更多
文摘Overstraining gun tubes has a twofold advantage. First, it enables the increase of the Safe Maximum Pressure(SMP) in the tube, resulting in a higher muzzle velocity which extends the gun's range and its projectile kinetic energy. Second, it reduces the tube's susceptibility to internal cracking which prolongs its fatigue life. Unfortunately, autofrettage also bears an inherent detrimental effect as it considerably increases the tensile hoop stress at the outer portion of the barrel's wall, which enhances external cracking of the tube by increasing the prevailing Stress Intensity Factor(SIF). In order to quantify this disadvantageous effect, 3-D Mode I SIFs distributions along the front of a single external radial semielliptical crack initiating from the outer surface of an autofrettaged modern gun barrel, overstrained by either the Swage or the Hydraulic autofrettage processes, are evaluated. The analysis is performed by the finite element(FE) method, using singular elements along the crack front. Innovative residual stress fields(RSFs), incorporating the Bauschinger effect for both types of autofrettage are applied to the barrel.Hill's [1] RSF is also applied to the tube for comparison reasons. All three RSFs are incorporated in the FE analysis, using equivalent temperature fields, Values for K_(IA)-the SIF resulting from the tensile residual stresses induced by autofrettage are evaluated for: a typical barrel of radii ratio R_o/R_i = 2, crack depth to wall-thickness ratios(a/t = 0.005-0.1),crack ellipticities(a/c = 0.2-1.0),and five levels of Swage,Hydraulic and Hill's autofrettage(e = 40%,60%,70%,80%,and 100%). In total,375 different 3-D cases are analyzed. The analysis demonstrates undoubtedly the detrimental effect of all types of autofrettage in increasing the prevailing effective stress intensity factor of external cracks, resulting in crack initiation enhancement and crack growth rate acceleration which considerably shortens the total fatigue life of the barrel. Nonetheless, the detrimental effect is autofrettage-type dependent. Swage and Hydraulic autofrettage RSFs differ substantially from each other. The disadvantageous effect of Swage autofrettage is much greater than that resulting from Hydraulic autofrettage. The results also emphasize the significance of the Bauschinger effect and the importance of the 3-D analysis.
基金supported by Israel Science Foundation,grant No.1227/18.
文摘Despite widespread adoption and outstanding performance, machine learning models are considered as ‘‘blackboxes’’, since it is very difficult to understand how such models operate in practice. Therefore, in the powersystems field, which requires a high level of accountability, it is hard for experts to trust and justify decisionsand recommendations made by these models. Meanwhile, in the last couple of years, Explainable ArtificialIntelligence (XAI) techniques have been developed to improve the explainability of machine learning models,such that their output can be better understood. In this light, it is the purpose of this paper to highlight thepotential of using XAI for power system applications. We first present the common challenges of using XAI insuch applications and then review and analyze the recent works on this topic, and the on-going trends in theresearch community. We hope that this paper will trigger fruitful discussions and encourage further researchon this important emerging topic.
