scholarly journals Effects of Processing Parameters for Vacuum-Bagging-Only Method on Shape Conformation of Laminated Composites

Processes ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1147
Author(s):  
Yasir Mujahid ◽  
Nabihah Sallih ◽  
Mazli Mustapha ◽  
Mohamad Zaki Abdullah ◽  
Faizal Mustapha
Keyword(s):  
Composite Structures ◽  
Laminated Composites ◽  
Statistical Significance ◽  
Processing Parameters ◽  
Coefficient Of Determination ◽  
Thickness Variation ◽  
Optimum Selection ◽  
Concave Corner ◽  
Laminate Thickness ◽  
Thickness Variations

Complex composite structures manufactured using a low-pressure vacuum bag-only (VBO) method are more susceptible to defects than flat laminates because of the presence of complex compaction conditions at corners. This study investigates the contribution of multivariate processing parameters such as bagging techniques, curing profiles, and laminate structures on laminates’ shape conformation. Nine sets of laminates were produced with a concave corner and another nine sets with a convex corner, both with a 45° inclined structure. Three-way analysis of variance (ANOVA) was performed to quantify thickness variation and spring effect of laminated composites. The analysis for concave and convex corners showed that the bagging techniques is the main factor in controlling the laminate thickness for complex shape applications. The modified (single) vacuum-bag-only (MSVB) technique appeared to be superior when compared to other bagging techniques, exhibiting the least coefficients of variation of 0.015 and 0.016 in composites with concave and convex corners, respectively. Curing profiles and their interaction with bagging techniques showed no statistical significance in the contribution toward laminate thickness variation. The spring effect of laminated composites was investigated by calculating the coefficient of determination (R2) relative to that of the mold. The specimens exhibited a good agreement with R2 values ranging from 0.9824 to 0.9946, with no major data offset. This study provides guidelines to reduce thickness variations and spring effect in laminated composites with complex shapes by the optimum selection of processing parameters for prepreg processing.

scholarly journals Experimental Investigation of the Effects of Irradiating Schemes in Laser Tube Bending Process

Metals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1123
Author(s):  
Mehdi Safari ◽  
Ricardo J. Alves de Sousa ◽  
Jalal Joudaki
Keyword(s):  
Laser Beam ◽  
Contact Process ◽  
Steel Tube ◽  
Thickness Variation ◽  
Tube Bending ◽  
Lateral Bending ◽  
Bending Angle ◽  
Laser Tube ◽  
Bending Process ◽  
Thickness Variations

The laser tube bending process (LTBP) process is a thermal non-contact process for bending tubes with less springback and less thinning of the tube. In this paper, the laser tube bending process will be studied experimentally. The length of irradiation and irradiation scheme are two main affecting process parameters in the LTBP process. For this purpose, different samples according to two main irradiation schemes (Circular irradiating scheme (CIS) and axial irradiating scheme (AIS)) and different lengths of laser beam irradiation (from 4.7 to 28.2 mm) are fabricated. The main bending angle of laser-bent tube, lateral bending angle, ovality, and thickness variations is measured experimentally, and the effects of the irradiating scheme and the length of irradiation are investigated. An 18 mm diameter, 1 mm thick mild steel tube was bent with 1100 Watts laser beam. The results show that for both irradiating schemes, by increasing the irradiating length of the main and lateral bending angle, the ovality and thickness variation ratio of the bent tube are increased. In addition, for a similar irradiating length, the main bending angle with AIS is considerably higher than CIS. The lateral bending angle by AIS is much less than the lateral bending angle with CIS. The results demonstrate that the ovality percentage and the thickness variation ratio for the laser-bent tube obtained by CIS are much more than the values associated with by AIS laser-bent tube.

Warpage and Shrinkage Analysis and Optimization of Rapid Tooling Molded thin Wall Component Using Modified Particle Swarm Algorithm

2019 ◽  
Vol 18 (01) ◽  
pp. 85-102 ◽  
Author(s):  
Sagar Kumar ◽  
Amit Kumar Singh
Keyword(s):  
Injection Molding ◽  
Process Parameters ◽  
Simulation Analysis ◽  
Statistical Significance ◽  
Particle Swarm ◽  
Processing Parameters ◽  
Particle Swarm Algorithm ◽  
Thin Wall ◽  
Polybutylene Terephthalate ◽  
Melt Temperature

This paper presents a systematic methodology to determine optimal injection molding conditions for minimum warpage and shrinkage in a thin wall relay part using modified particle swarm optimization algorithm (MPSO). Polybutylene terephthalate (PBT) and polyethylene terephthalate (PET) were injected in a thin wall relay component for different processing parameters: melt temperature, packing pressure and packing time. Further, Taguchi’s L9 (3[Formula: see text] orthogonal array is used for conducting simulation analysis to consider the interaction effects of the above parameters. A predictive mathematical model for shrinkage and warpage is developed in terms of the above process parameters using regression analysis. ANOVA analysis is performed to establish statistical significance within the injection molding parameters. The analytical model is further optimized using a newly developed MPSO algorithm and the process parameters values are predicted for minimizing shrinkage and warpage. The predicted values of shrinkage and warpage using MPSO algorithm are improved by approximately 30% as compared to the initial simulation values and comparable to previous literature results.

scholarly journals A Comparison of Vibroacoustic Response of Isotropic Plate with Attached Discrete Patches and Point Masses Having Different Thickness Variation with Different Taper Ratios

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Bipin Kumar ◽  
Vinayak Ranjan ◽  
Mohammad Sikandar Azam ◽  
Piyush Pratap Singh ◽  
Pawan Mishra ◽  
...  
Keyword(s):  
Power Level ◽  
Low Frequency ◽  
Sound Radiation ◽  
Radiation Efficiency ◽  
Thickness Variation ◽  
Sound Power ◽  
Sound Power Level ◽  
Radiation Behavior ◽  
Thickness Variations ◽  
Different Thickness

A comparison of sound radiation behavior of plate in air medium with attached discrete patches/point masses having different thickness variations with different taper ratio of 0.3, 0.6, and 0.9 is analysed. Finite element method is used to find the vibration characteristics while Rayleigh integral is used to predict the sound radiation characteristics. Minimum peak sound power level obtained is at a taper ratio of 0.6 with parabolic increasing-decreasing thickness variation for plate with four discrete patches. At higher taper ratio, linearly increasing-decreasing thickness variation is another alternative for minimum peak sound power level suppression with discrete patches. It is found that, in low frequency range, average radiation efficiency remains almost the same, but near first peak, four patches or four point masses cause increase in average radiation efficiency; that is, redistribution of point masses/patches does have effect on average radiation efficiency at a given taper ratio.

A study about the linearity of trends between extreme and mean temperatures in Argentina

2021 ◽  
Author(s):  
Solange Suli ◽  
Matilde Rusticucci ◽  
Soledad Collazo
Keyword(s):  
Linear Regression ◽  
Linear Relationship ◽  
Statistical Significance ◽  
Coefficient Of Determination ◽  
Maximum Temperature ◽  
Mean Temperature ◽  
Change In The Mean ◽  
The Mean ◽  
Student’S T ◽  
Cold Extremes

<p>Small variations in the mean state of the atmosphere can cause large changes in the frequency of extreme events. In order to deepen and extend previous results in time, in this work we analyzed the linear relationship between extreme and mean temperature (Τ) on a climate change scale in Argentina. Two monthly extreme indices, cold nights (TN10) and warm days (TX90), were calculated based on the quality-controlled daily minimum and maximum temperature data provided by the Argentine National Meteorological Service from 58 conventional weather stations located over Argentina in the 1977–2017 period. Subsequently, we evaluated the relationship between the linear trends of extremes and mean temperature on a seasonal basis (JFM, AMJ, JAS, and OND). Student's T-test was performed to analyze their statistical significance at 5%. Firstly, positive (negative) and significant linear regressions were found between TX90 (TN10) trends and mean temperature trends for the four studied seasons. Therefore, an increase in the Τ-trend maintains a linear relationship with significant increase (decrease) of warm days (cold nights). Moreover, we found that JFM was the one with the highest coefficient of determination (0.602 for hot extremes and 0.511 for cold extremes), implying that 60.2% (51.1%) of the TX90 (TN10) trend could be explained as a function of the Τ-trend by a linear regression. In addition, in the JFM (OND) quarter, the TX90 index increased by 7.02 (6.02) % of days each with a 1 ºC increase in the mean temperature. Likewise, the TN10 index decreased by 4.94 (and 4.99) % of days from a 1ºC increase in the mean temperature for the JFM (AMJ) quarter. Finally, it is worthwhile to highlight the uneven behavior between hot and cold extremes and the mean temperature. Specifically, it was observed that the slopes of the linear regression calculated for the TX90 index and Τ presented a higher absolute value than those registered for the TN10 index and Τ. Therefore, a change in the mean temperature affects hot extremes to a greater extent than cold ones in Argentina.</p>

PROGRESSIVE DAMAGE FAILURE ANALYSIS OF POST-BUCKLED COMPOSITE SINGLE-STRINGER PANEL WITH TEFLON INSERTS

2021 ◽  
Author(s):  
VIJAY K. GOYAL ◽  
AUSTIN PENNINGTON ◽  
JASON ACTION
Keyword(s):  
Experimental Data ◽  
Composite Structures ◽  
Laminated Composites ◽  
Compressive Loading ◽  
Weight Ratio ◽  
High Strength ◽  
Material Model ◽  
Stiffened Panels ◽  
Damage Initiation ◽  
Critical Aspects

The high strength-to-weight and stiffness-to-weight ratio materials, such as laminated composites, are advantageous for modern aircraft. Laminated composites with initial flaws are susceptible to delamination under buckling loads. PDA tools help enhance the industry’s understanding of the mechanisms for damage initiation and growth in composite structures while assisting in the design, analysis, and sustainment methods of these composite structures. The global-local modeling approach for the single-stringer post-buckled panel was evaluated through this effort, using Teflon inserts to simulate the defect of damage during manufacturing. This understanding is essential for designing the post-buckled structure, reducing weight while predicting damage initiation location, and addressing a potential design review for future aircraft repairs. In this work, the initial damage was captured with Teflon inserts as the starting configuration; and any reference to the damage initiation refers to any damage beyond the “initial unbonded region.” The effort aims to develop, evaluate, and enhance methods to predict damage initiation and progression and the failure of post-buckled hat-stiffened panels using multiple Abaqus FEA Virtual Crack Closure Technique (VCCT) definitions. Validation of the PDA using the VCCT material model was performed on a large single-stringer panel subjected to compressive loading. The compressive loading of the panel caused the skin to buckle before any damage began to occur locally. In addition, comparisons are made for critical aspects of the damage morphology, such as a growth pattern that included delamination from the skin-stiffener interface to the skin and ply interfaces. When compared against the experimental data produced through the NASA Advanced Composites Project (ACP), the present model captured damage migration from one surface to another, and model validations were ~5% of the experimental data.

Evaluating the Statistical Significance of Models Developed by Stepwise Regression

1983 ◽  
Vol 20 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Shelby H. McIntyre ◽  
David B. Montgomery ◽  
V. Srinivasan ◽  
Barton A. Weitz
Keyword(s):  
Monte Carlo ◽  
Null Hypothesis ◽  
Regression Models ◽  
Stepwise Regression ◽  
Statistical Significance ◽  
Selection Procedure ◽  
Coefficient Of Determination ◽  
Forward Selection ◽  
Monte Carlo Simulation Study ◽  
Independent Variables

Information for evaluating the statistical significance of stepwise regression models developed with a forward selection procedure is presented. Cumulative distributions of the adjusted coefficient of determination ([Formula: see text]) under the null hypothesis of no relationship between the dependent variable and m potential independent variables are derived from a Monté Carlo simulation study. The study design included sample sizes of 25, 50, and 100, available independent variables of 10, 20, and 40, and three criteria for including variables in the regression model. The results reveal that the biases involved in testing statistical significance by two well-known rules are very large, thus demonstrating the desirability of using the Monté Carlo cumulative [Formula: see text] distributions developed by the authors. Although the results were derived under the assumption of uncorrelated predictors, the authors show that the results continue to be useful for the correlated predictor case.

Thickness analysis of complex two-step micro-groove on plate during rubber pad forming process

2020 ◽  
pp. 095440622093392
Author(s):  
Fei Teng ◽  
Hongyu Wang ◽  
Juncai Sun ◽  
Xiangwei Kong ◽  
Jie Sun ◽  
...  
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Thickness Variation ◽  
Forming Process ◽  
Rubber Pad Forming ◽  
Groove Structure ◽  
Thickness Variations ◽  
Accuracy Of Results ◽  
Plane Slab ◽  
Element Method

The surface groove structure has numerous functions based on their shapes. In order to make these functions developed, both new shapes and processing forms of the surface structures are being innovated. In this paper, not only the advanced rubber pad forming process is used, but also a new kind of micro-groove with two-step structures is designed. A model based on multi-plane slab method is proposed to analyze the process. According to the stress acting condition, a half of two-step micro-groove structure is divided into seven areas in the width direction. The thickness variation of plate in each area is obtained. When the shape, depth, width, and height ratio of the first and second-step micro-groove are different, the thickness variations of the plate are analyzed. In order to verify the accuracy of the model, both finite element method and pressing experiment are done. Based on the results provided by both finite element method and experiment, the accuracy of results calculated by analytical model is verified.

Data Mining for Estimating Fatigue Strength Based on Composition and Process Parameters

2019 ◽  
Author(s):  
Arvind Keprate ◽  
R. M. Chandima Ratnayake
Keyword(s):  
Data Mining ◽  
Fatigue Strength ◽  
Process Parameters ◽  
Fatigue Testing ◽  
Absolute Error ◽  
Processing Parameters ◽  
Coefficient Of Determination ◽  
Low Alloy Steels ◽  
Strength Based ◽  
Alloy Steels

Abstract Accurately estimating the fatigue strength of steels is vital, due to the extremely high cost (and time) of fatigue testing and often fatal consequences of fatigue failures. The main objective of this manuscript is to perform data mining on the fatigue dataset for steel available from the National Institute of Material Science (NIMS) MatNavi. The cross-industry process for data mining (CRISP-DM) approach was followed in the paper, in order to gain meaningful insights from the dataset and to estimate the fatigue strength of carbon and low alloy steels, using composition and processing parameters. Of the six steps of the CRISP-DM approach, special emphasis has been placed on steps 2 to 5 (i.e. data understanding, data preparation, modeling and evaluation). In step 4 (i.e. modeling), a range of machine learning (parametric and non-parametric) is explored to predict the fatigue strength, based on the composition and process parameters. Various algorithms were trained and tested on the dataset and finally evaluated, using metrics such as root mean square error (RMSE), Mean Absolute Error (MAE), Coefficient of Determination (R2) and Explained Variance Score (EVS).

Sign in / Sign up

Export Citation Format

Share Document