Influence of aluminium sheet surface modification on the self-piercing riveting process and the joint static lap shear strength

Self-piercing riveting (SPR) has been widely used in automotive as one of the major joining technologies for aluminium structures due to its advantages over some of the more traditional joining technologies. Research has shown that friction is a very important factor that influences both the riveting process and the joint strength for SPR, but these influences have not been fully understood. In this paper, AA5754 sheets with different surface textures, such as original with solid wax, hot water washed, sandpaper ground and grit blasted, were used to study the influence of friction on therivet inserting process, joint features and static lap shear strength. The results of joint features and rivet setting displacement-force curve showed that hot water wash and sandpaper grinding on aluminium sheet did not have significant influence on the rivet inserting process and joint features; however, for joints with grit-blasted substrates, the rivet -setting forces were higher at the beginning, and a middle section of the curve and the joint features, such as interlocks and minimum remaining bottom material thickness (Tmin), were clearly altered. The lap shear tests showed that hot water washing can slightly increase the lap shear strength, sandpaper grinding increased the static lap shear strength further and grit blasting increased the static lap shear strength the most

Demographic details of 20 patient.

<p>Demographic details of 20 patient.</p

Summary of clinical features in 7 patients with rapid elevation of indicator “<i>a</i>”.

<p>Summary of clinical features in 7 patients with rapid elevation of indicator “<i>a</i>”.</p

The change of brain CT scans in a spontaneous ICH patient (case 1) in 9 days.

<p>Fig 2a shows that the initial brain CT revealed left thalamic hemorrhage, intraventricular hemorrhage, and bilateral dilated ventricle. Fig 2b shows that on POD 6, the brain CT revealed that left thalamic hemorrhage was stationary. The brain parenchyma was tight, especially on the left side. Severe peri-hematoma edema was noted and the brain was shifted to right side. Two EVD tubes were placed in the bilateral frontal horns and the ventricles became slim. Fig 2c shows that the follow-up brain CT on POD 9 revealed that the hematoma and perifocal edema regressed with significantly less mass effect. The brain parenchyma became slack with clear margin of sulci. The EVD tubes were in bilateral enlarged lateral ventricles.</p

The progression of brain CT scans in a traumatic brain injury patient (case 3).

<p>Fig 7a. and 7b show that the initial brain CT revealed left fronto-temporal EDH and bilateral frontal and temporal small contusion hemorrhages, and SAH. Fig 7c. and 7d show that the follow-up brain CT after left craniotomy on POD 1 revealed right frontal and temporal contusion hemorrhage progression and right SDH with a midline shift to the left, left frontal and temporal contusion hemorrhages, pneumocephalus, diffuse brain swelling and bilateral slender ventricles. The EVD tube was placed in the left frontal horn.</p

The change of brain CT scans in an intraventricular hemorrhage with hydrocephalus patient (case 2) in 7 days.

<p>Fig 4a. and 4b show that the initial brain CT revealed a thalamic vascular lesion and intraventricular hemorrhage in enlarged bilateral ventricles. A right VP shunt tube was placed in the right frontal horn. Fig 4c. and 4d show that the follow-up brain CT on POD 7 revealed a stationary thalamic vascular lesion and regression of intraventricular hemorrhage. Hydrocephalus was persistent and two EVD tubes were placed in the bilateral frontal horns.</p

Relationship between initial ICP and the indicator "a" in parabolic equations.

<p>N = 139. Regression line is shown; regression equation: y = 0.024x-0.145; R² = 0.156.</p

An example of F value for the significance of the regression equation.

<p>An example of F value for the significance of the regression equation.</p

Example of different P-V curves in parabolic regression equations with different indicator “<i>a</i>” in one patient from case illustration 2.

<p>The steepest P-V curve was derived from POD 1 with an indicator “<i>a</i>” of 0.417. From left to right, the P-V curve became more and more flat and the indicator “<i>a</i>” in each P-V curves declined from POD 1 to POD 5.</p