Mitigating Safety Concerns of SRU Stack Using Advanced Analytical/Optical Technologies

Objective/Scope (25-75 word) In SRU, Tail gas exhaust stacks are provided with external cladding, preventing condensation beneath refractory surfaces. External cladding is made of individual Aluminium sheet panels, each 1.7mx1.5mx3mm thk, weighing 60Kg, attached by screws / rivets. Stack size is 6.5mdia × 90m height. Due to high wind, panel sometimes detaches from stack, falling down from 90m height, posing serious HSE threat to plant personal safety. This paper details an analytical design approach, supported with high resolution, remote controlled drone inspection technic to resolve one such issue. Methods, Procedures, Process (75-100 word) Initially, detached and dropped screws were observed, due to wind loads & vibration, which lead to falling of a clad panel from 80m height, fortunately, when no personal was below. Detailed finite element analysis of external cladding was performed, considering wind loads and thermal loads on panels with stack to panel joint configuration. Periodic inspection of the joints is vital to confirm reliability of the joints, which is not possible during operation with conventional inspection methods in an SRU exhaust stack. Hence, a latest technology, high-resolution, optical camera assisted, drone, controlled & monitored by remote computers were employed to assess the panel integrity. Results, Observations & Conclusions (100-200 words) Analysis Results Finite element analysis was performed for the stack cladding. As this analysis was non-conventional, there is no well-established industry acceptance criteria for the analysis results. Hence, an acceptance criteria was jointly developed with Contractor, which is fundamentally the minimum number of screws per panel, required to be intact, during the 2 year period, to confirm the panel integrity. Distance Drone inspection Manned inspection was not feasible in a running plant. Also, conventional aerial survey drones could not be engaged, as it was unsafe to fly the drone above live plant. Hence, an aerial drone with high-resolution optical camera, with overlapping method was employed. Advanced post processing software was used to analyse the images for best results. Conclusion To ensure clad panels integrity and 100% personal safety, Based on Finite element analysis, the original screws have been replaced with rivets with the following acceptance criteria. The integrity of the cladding remains intact even if 20% of the screws / rivets are lost whether it is consecutive or random. Above 20% there may be impact and further investigation is advised. Panels were monitored three times periodically in 2 year span to assess the fasteners intactness. The images from the optical camera, after software processing confirmed the fasteners integrity. Novel/Additive Information (25-75 words) 100% Plant and personal safety is ADNOC's principal objective. Occasionally, achieving this target require unorthodox analysis and acceptance criteria development. Most of all, the conventional monitoring technics, due to their limitations, pushes us to explore alternate technologies. The new high-resolution, optical camera assisted, drone technic can be engaged in a running plant and the images are processed using proprietary software to achieve best results of minute details.

Area-Efficient Post-Processing Circuits for Physically Unclonable Function with 2-Mpixel CMOS Image Sensor

In order to realize image information security starting from the data source, challenge–response (CR) device authentication, based on a Physically Unclonable Function (PUF) with a 2 Mpixel CMOS image sensor (CIS), is studied, in which variation of the transistor in the pixel array is utilized. As each CR pair can be used only once to make the CIS PUF resistant to the modeling attack, CR authentication with CIS can be carried out 4050 times, with basic post-processing to generate the PUF ID. If a larger number of authentications is required, advanced post-processing using Lehmer encoding can be utilized to carry out authentication 14,858 times. According to the PUF performance evaluation, the authentication error rate is less than 0.001 ppm. Furthermore, the area overhead of the CIS chip for the basic and advanced post-processing is only 1% and 2%, respectively, based on a Verilog HDL model circuit design.

Novel Processing Algorithm to Improve Detectability of Disbonds in Adhesive Dissimilar Material Joints

Adhesively bonded dissimilar materials have attracted high interest in the aerospace and automotive industries due to their ability to provide superior structural characteristics and reduce the weight for energy savings. This work focuses on the improvement of disbond-type defect detectability using the immersion pulse-echo ultrasonic technique and an advanced post-processing algorithm. Despite the extensive work done for investigation, it is still challenging to locate such defects in dissimilar material joints due to the large differences in the properties of metals and composites as well as the multi-layered structure of the component. The objective of this work is to improve the detectability of defects in adhesively bonded aluminum and carbon fiber-reinforced plastic (CFRP) by the development of an advanced post-processing algorithm. It was determined that an analysis of multiple reflections has a high potential to improve detectability according to results received by inspection simulations and the evaluation of boundary characteristics. The impact of a highly influential parameter such as the sample curvature can be eliminated by the alignment of arrival time of signals reflected from the sample. The processing algorithm for the improvement of disbond detectability was developed based on time alignment followed by selection of the time intervals with a significant amplitude change of the signals reflected from defective and defect-free areas and shows significant improvement of disbond detectability.

Enhanced Infrared Sparse Pattern Extraction and Usage for Impact Evaluation of Basalt-Carbon Hybrid Composites by Pulsed Thermography

Nowadays, infrared thermography, as a widely used non-destructive testing method, is increasingly studied for impact evaluation of composite structures. Sparse pattern extraction is attracting increasing attention as an advanced post-processing method. In this paper, an enhanced sparse pattern extraction framework is presented for thermographic sequence processing and defect detection. This framework adapts cropping operator and typical component extraction as a preprocessing step to reduce the dimensions of raw data and applies sparse pattern extraction algorithms to enhance the contrast on the defect area. Different cases are studied involving several defects in four basalt-carbon hybrid fiber-reinforced polymer composite laminates. Finally, comparative analysis with intensity distribution is carried out to verify the effectiveness of contrast enhancement using this framework.