Online Prediction and Verification of Cured Quality of Advanced Composites in Autoclave Process

2016 ◽  
Vol 703 ◽  
pp. 3-10
Author(s):  
Yong An Zhang ◽  
Li Hua Zhan

The strain in curing process of composite part would be influenced by curing compaction, resin flow, curing action and tool-part interaction, meanwhile these factors would also influence the final cured quality of composite part. In this paper, FBG(fiber Bragg grating) sensors are used to in-situ monitoring the strain of composite parts, which are cured in four different pressure situation by autoclave: 0.0Mpa,0.2Mpa,0.4Mpa,0.6MPa. by analyzing the strain change rule, the part quality is predicted, then the predictive result is compared with some verification method: measurement of part’s boundary dimension, ultrasonic phased array scanning, metallographic analysis. The result shows that, the prediction is consistent with verification, the in-situ monitoring method by using FBG sensor is available for predicting cured quality of composite parts accurately: increase curing pressure is benefit of part compaction, resin flow, and reduce delamination,pores in composite part, finally improving the part quality dramatically.

2010 ◽  
Vol 450 ◽  
pp. 482-485
Author(s):  
Li Peng Cai ◽  
Ii Young Jang ◽  
Ying Wei Yun ◽  
Seong Kyum Kim

An effective in-situ monitoring method for MPCP is urgently needed in civil engineering field. In this research, a quick and accurate in-situ measuring method for mix proportion of concrete is put forward. This method can succeed in measuring real mix proportion of any concrete paste precisely within 20 minutes according to four parameters of concrete before initial setting time of concrete. By comparing the designed mix proportion of concrete with the real measured one in construction site by this method, the quality of concrete can be demonstrated. This method can evaluate the reliability of mix proportion for real concrete in construction site quickly and precisely, and ensure the quality of concrete structures to avoid the occurrence of engineering accidents.


2017 ◽  
Vol 885 ◽  
pp. 234-238
Author(s):  
Péter Kucsera ◽  
Tamás Sándor ◽  
Gusztáv Varga Tényi ◽  
Márton Csutorás ◽  
Gergely Bátori ◽  
...  

The in-situ monitoring of the MBE grown nanostructures can be carried out using the RHEED method. During the droplet epitaxal growth, the observation of the nanostructure formation is very important to understand the growth kinetics. In the present work, a novel in-situ RHEED evaluation and further MBE related developments are introduced, with which the quality of the nanostructure preparation can be improved.


2018 ◽  
Vol 40 (3) ◽  
pp. 180-187
Author(s):  
Tadeusz Majcherczyk ◽  
Zbigniew Niedbalski ◽  
Łukasz Bednarek

AbstractBack in the early 1980s, coal deposits occurring at depths of ~700 m below surface were already regarded as large-depth deposits. Meanwhile, today the borderline depth of large-depth mining has extended to >1,000 m. Design, excavation and maintenance of mining roadways at the depth of >1,000 m have, therefore, become crucial issues in a practical perspective in recent years. Hence, it is now extremely important to intensify research studies on the influence of large depths on the behaviour of rock mass and deformation of support in underground excavations. The paper presents the results of the study carried out in five mining excavations at depths ranging from 950 to 1,290 m, where monitoring stations with measurement equipment were built. The analysis of data from laboratory and coal mine tests, as well as in situ monitoring, helped to formulate a set of criteria for stability assessment of underground excavations situated at large depths. The proposed methodology of load and deformation prediction in support systems of the excavations unaffected by exploitation is based on the criteria referring to the depth of excavation and the quality of rock mass. The depth parameter is determined by checking whether the analysed excavation lies below the critical depth, whereas the rock mass quality is determined on the basis of the roof lithology index (WL) and the crack intensity factor (n)


Author(s):  
Chaitanya Krishna Prasad Vallabh ◽  
Yubo Xiong ◽  
Xiayun Zhao

Abstract In-situ monitoring of a Laser Powder-Bed Fusion (LPBF) additive manufacturing process is crucial in enhancing the process efficiency and ensuring the built part integrity. In this work, we present an in-situ monitoring method using an off-axis camera for monitoring layer-wise process anomalies. The in-situ monitoring is performed with a spatial resolution of 512 × 512 pixels, with each pixel representing 250 × 250 μm and a relatively high data acquisition rate of 500 Hz. An experimental study is conducted by using the developed in-situ off-axis method for monitoring the build process for a standard tensile bar. Real-time video data is acquired for each printed layer. Data analytics methods are developed to identify layer-wise anomalies, observe powder bed characteristics, reconstruct 3D part structure, and track the spatter dynamics. A deep neural network architecture is trained using the acquired layer-wise images and tested by images embedded with artificial anomalies. The real-time video data is also used to perform a preliminary spatter analysis along the laser scan path. The developed methodology is aimed to extract as much information as possible from a single set of camera video data. It will provide the AM community with an efficient and capable process monitoring tool for process control and quality assurance while using LPBF to produce high-standard components in industrial (such as, aerospace and biomedical industries) applications.


1990 ◽  
Author(s):  
Valery V. Balaniuk ◽  
Victor F. Krasnov ◽  
Nikolai A. Kul'chitzkii ◽  
Semion L. Musher ◽  
Vasily I. Proc' ◽  
...  

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1396 ◽  
Author(s):  
Biao Xiao ◽  
Bin Yang ◽  
Fu-Zhen Xuan ◽  
Yun Wan ◽  
Chaojie Hu ◽  
...  

As a result of the high specific strength/stiffness to mass ratio, filament wound composite pressure vessels are extensively used to contain gas or fluid under pressure. The ability to in-situ monitor the composite pressure vessels for possible damage is important for high-pressure medium storage industries. This paper describes an in-situ monitoring method to permanently monitor composite pressure vessels for their structural integrity. The sensor is made of a multi-walled carbon nanotube (MWCNT) that can be embedded in the composite skin of the pressure vessels. The sensing ability of the sensor is firstly evaluated in various mechanical tests, and in-situ monitoring experiments of a full-scale composite pressure vessel during hydraulic fatigue cycling and pressurization are performed. The monitoring results of the MWCNT sensor are compared with the strains measured by the strain gauges. The results show that the measured signal by the developed sensor matches the mechanical behavior of the composite laminates under various load conditions. In the hydraulic fatigue test, the relationship between the resistance and the strain is built, and could be used to quantitative monitor the filament wound pressure vessel. The bursting of the pressure vessel can be detected by the sharp increase of the MWCNT sensor resistance. Embedding the MWCNT sensor into the composite pressure vessel is successfully demonstrated as a promising method for structural health monitoring.


Author(s):  
H. Ikeda ◽  
S. Kunisue ◽  
D. Nohara ◽  
K. Ooba ◽  
T. Kokubo

Abstract. We have devised a new in situ monitoring method for the amount of stratified compaction in borehole drilled several hundred meters underground. This newly developed epoch-making monitoring system differs from conventional monitoring methods for land subsidence in that it is designed to continuously monitor the amounts of displacement in several intervals separately, using optical fibers fitted in the sensor assembly. This report presents results from a deep observation well. This is a continued report from the previous one on EISOLS 2010.


2019 ◽  
Vol 21 (6) ◽  
pp. 064003
Author(s):  
G KANG ◽  
S AN ◽  
K KIM ◽  
S HONG

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