Fatigue life prediction of woven composite laminates with initial delamination

An engineering approach for fatigue life prediction of fibre‐reinforced polymer composite materials is highly desirable for industries due to the complexity in damage mechanisms and their interactions. This paper presents a fatigue‐driven residual strength model considering the effect of initial delamination size and stress ratio. Static and constant amplitude fatigue tests of woven composite specimens with delamination diameters of 0, 4 and 6 mm were carried out to determine the model parameters. Good agreement with experimental results has been achieved when the modified residual strength model has been applied for fatigue life prediction of the woven composite laminate with an initial delamination diameter of 8 mm under constant amplitude load and block fatigue load. It has been demonstrated that the residual strength degradation‐based model can effectively reflect the load sequence effect on fatigue damage and hence provide more accurate fatigue life prediction than the traditional linear damage accumulation models

Inverse Problem Approach for Non-Perturbative QCD: Foundation

We propose a novel theoretical framework to calculate the non-perturbative QCD quantities. It starts from the dispersion relation of quantum field theory, separating the high-energy and low-energy scales and using the known perturbative theories to solve the unknown non-perturbative quantities by the inverse problem. We prove that the inverse problem of dispersion relation is ill-posed, with unique but unstable solutions. The regularization methods must be used to get the stable approximate solutions. The method is based on the strict mathematics, without any artificial assumptions. We have test some toy models to vividly show the main features of the inverse problem. It can be found that this approach can systematically improve the precision of the solutions.Comment: 23 pages, 8 figure

On the Stochastic Gradient Descent and Inverse Variance-flatness Relation in Artificial Neural Networks

Stochastic gradient descent (SGD), a widely used algorithm in deep-learning neural networks has attracted continuing studies for the theoretical principles behind its success. A recent work uncovered a generic inverse variance-flatness (IVF) relation between the variance of neural weights and the landscape flatness of loss function near solutions under SGD [Feng & Tu, PNAS 118,0027 (2021)]. To investigate this seemly violation of statistical principle, we deploy a stochastic decomposition to analyze the dynamical properties of SGD. The method constructs the true "energy" function which can be used by Boltzmann distribution. The new energy differs from the usual cost function and explains the IVF relation under SGD. We further verify the scaling relation identified in Feng's work. Our approach may bridge the gap between the classical statistical mechanics and the emerging discipline of artificial intelligence, with potential for better algorithm to the latter

Notch effect on strength and fatigue life of woven composite laminates

This paper presents an experimental and numerical study of the notch effect on strength and fatigue life of double edge notched (DEN) composite laminates made of woven glass fibre lamina 3238A/EW250F and woven carbon fibre lamina 3238A/CF3052. Experimental results show that the notch effect is dependent on fibre type, notch depth, load type and load sequence. As-n-R-d-r" role="presentation"> s - n - R -d-r residual strength model was proposed to account for the effects of the notch and the stress ratio, and a progressive damage algorithm was developed to predict damage propagation and residual life of composites under spectrum fatigue load. Good agreement between the experimental results and the numerical predictions has been achieved

Water and sediment quality in Qinghai Lake, China: a revisit after half a century.

Qinghai Lake, situated on the Qinghai-Tibet plateau, is the largest lake in China. In this study, the water and sediment quality were investigated in Qinghai Lake, three sublakes, and five major tributaries. Both Na+ and Cl- were found to be the major ions present in Qinghai Lake and the three sublakes, while Ca2+ and HCO3- dominated the tributaries. Compared with historical data from the 1960s, the concentrations of NH4 (+), NO3 (-), and soluble reactive silica have increased considerably, likely caused by increased human activities in the area. Compared to the historical data, chemical oxygen demand has increased and lake water transparency has decreased, likely related to an increase in nutrient levels. Relatively high concentrations of total nitrogen (TN) and total phosphorus (TP) were observed in Qinghai Lake sediments, although P fraction types and low water concentrations of these two indicate low possibility of transfer into the water column. The ratios of C/N suggest that the organic matter in the sediments are primarily from autochthonous sources. TN and total organic carbon in the sediment cores increased slowly up the core while TP and total inorganic carbon have been fairly constant