Not all pipelines are created equal. Pipelines have different characteristics, and would therefore show different levels of integrity and fail differently. The failure mode and cause of a given pipeline depends on several factors including the design, operating and environmental parameters. A new tool was developed to evaluate pipeline integrity and assess its potential failure mode, patterns, and rate based on the critical pipeline parameters. These parameters include the pipeline material of construction, wall thickness, operating pressure, service material, backfill medium/material, age, coating, pipeline size and other relevant parameters. The new tool was developed using pipeline data collected from the European Union, UK, and USA for pipeline failures over four decades. Failure models and patterns were analyzed, and over 60,000 failure modes/pattern combination were identified. The tool predicts the failure mode and patterns in terms of failure rate distribution by size of leak and its causes. It also shows the relative Pipeline Risk Index, defined as the pipeline’s potential failure rate relative to average pipeline population in the industry within similar pipeline categories. Ignition probabilities for pipeline failures were also analyzed and are predicted by this tool for each pipeline leak depending on the leak characteristics.

PresentationNot all pipelines are created equal. Pipelines have different characteristics, and would therefore show different levels of integrity and fail differently. The failure mode and cause of a given pipeline depends on several factors including the design, operating and environmental parameters. A new tool was developed to evaluate pipeline integrity and assess its potential failure mode, patterns, and rate based on the critical pipeline parameters. These parameters include the pipeline material of construction, wall thickness, operating pressure, service material, backfill medium/material, age, coating, pipeline size and other relevant parameters. The new tool was developed using pipeline data collected from the European Union, UK, and USA for pipeline failures over four decades. Failure models and patterns were analyzed, and over 60,000 failure modes/pattern combination were identified. The tool predicts the failure mode and patterns in terms of failure rate distribution by size of leak and its causes. It also shows the relative Pipeline Risk Index, defined as the pipeline’s potential failure rate relative to average pipeline population in the industry within similar pipeline categories. Ignition probabilities for pipeline failures were also analyzed and are predicted by this tool for each pipeline leak depending on the leak characteristics

Development of Empirical Method to Calculate Natural Gas Pipelines Rupture Exposure Radius

PresentationNatural Gas pipeline location classification are designed following an approach similar to ASME B31.8, which considers segmenting the pipeline length and count the population in each segment within a given distance from the pipeline (width of segment). ASMEB 31.8 utilizes fixed distance of 400m for the segment width, while other operators use the pipeline Rupture Exposure Radius (RER). This is a distance determined by the consequences modeling for pipeline full rupture. Since, the population density within the segment width affects the design factors of the pipeline, i.e. wall thickness requirements, over-predicting the distance can have significant cost implications. Some operators use default RER values on conservative estimates, while industrial best practices allow for detailed dispersion to calculate representative RER distances. Detailed dispersion modeling was performed for a large number of Natural Gas Pipeline scenarios, and an empirical formula was developed to estimate the RER for these pipelines as a function of the pipeline diameter and pressure. The dispersion calculations results show that the default RER values current used by some operators are very conservative, and that the cost of pipeline design/construction can be optimized by using the empirical formula developed in this work. The formula, which produces the RER value in terms of the distance from the pipeline to the point of 1⁄2 lower flammable limit is easy to use, and accurately represents the dispersion results. This eliminates the need to using sophisticated modeling software/tools to assess the RER values of Natural Gas pipelines. The formula also uses minimum number of data/information available about the pipelines (diameter and pressure only) increasing its effectiveness as a tool replacing the modeling software. In addition, for pipeline projects, lower RER distances result in more flexibility in route selection, lower pipeline location class and hence thinner wall thicknesses, less emergency isolation valves required and longer span between sectionalizing valves, which all translate to cost savings and reduces potential sources of leak (sectionalizing valves)

Thermal injury in tonsils and its relation to postoperative pain—a histopathological and clinical study

Objectives: The aim of this study was to compare thermal injury and depth of necrosis of using different monopolar power settings in partial tonsillectomy and correlate the results with the postoperative pain score. Results: The study included a total of 15 patients with mean of age of 5.7 ± 2.57 years. The mean depth of injury was significantly higher for the 25 W side (0.973 ± 0.613) versus the 15 W side (0.553 ± 0.218) (p = 0.023). The postoperative pain score showed no significant differences between both sides. Conclusion: The histopathologic depth of thermal injury is significantly higher with the 25 W monopolar microdissection in comparison to the 15 W; however, it does not seem to correlate with the postoperative pain level. Apparently, power settings of 25 W can be safely used for pediatric intracapsular tonsillectomies, without added postoperative morbidity despite the deeper tissue injury observed in the tonsil.The authors are grateful to the Histology and Electron Microscopy Service (HEMS) team at the i3S (Institute for Research and Innovation in Health, University of Porto) for providing the necessary equipment and the technical support for the electron microscopic analysis

A new best proximity point results in partial metric spaces endowed with a graph

For a given mapping f in the framework of different spaces, the fixed-point equations of the form f x = x can model several problems in different areas, such as differential equations, optimization, and computer science. In this work, the aim is to find the best proximity point and to prove its uniqueness on partial metric spaces where the symmetry condition is preserved for several types of contractive non-self mapping endowed with a graph. Our theorems generalize different results in the literature. In addition, we will illustrate the usability of our outcomes with some examples. The proposed model can be considered as a theoretical foundation for applications to real cases

An Edge Computing Based Smart Healthcare Framework for Resource Management

The revolution in information technologies, and the spread of the Internet of Things (IoT) and smart city industrial systems, have fostered widespread use of smart systems. As a complex, 24/7 service, healthcare requires efficient and reliable follow-up on daily operations, service and resources. Cloud and edge computing are essential for smart and efficient healthcare systems in smart cities. Emergency departments (ED) are real-time systems with complex dynamic behavior, and they require tailored techniques to model, simulate and optimize system resources and service flow. ED issues are mainly due to resource shortage and resource assignment efficiency. In this paper, we propose a resource preservation net (RPN) framework using Petri net, integrated with custom cloud and edge computing suitable for ED systems. The proposed framework is designed to model non-consumable resources and is theoretically described and validated. RPN is applicable to a real-life scenario where key performance indicators such as patient length of stay (LoS), resource utilization rate and average patient waiting time are modeled and optimized. As the system must be reliable, efficient and secure, the use of cloud and edge computing is critical. The proposed framework is simulated, which highlights significant improvements in LoS, resource utilization and patient waiting time

PriNergy: A Priority-based Energy Efficient Routing Method for IoT Systems

The Internet of Things (IoT) devices gather a plethora of data by sensing and monitoring the surrounding environment. Transmission of collected data from the IoT devices to the cloud through relay nodes is one of the many challenges that arise from IoT systems. Fault tolerance, security, energy consumption and load balancing are all examples of issues revolving around data transmissions. This paper focuses on energy consumption, where a priority-based and energy-efficient routing (PriNergy) method is proposed. The method is based on the routing protocol for low-power and lossy network (RPL) model, which determines routing through contents. Each network slot uses timing patterns when sending data to the destination, while considering network traffic, audio and image data. This technique increases the robustness of the routing protocol and ultimately prevents congestion. Experimental results demonstrate that the proposed PriNergy method reduces overhead on the mesh, end-to-end delay and energy consumption. Moreover, it outperforms one of the most successful routing methods in an IoT environment, namely the quality of service RPL (QRPL)