scholarly journals Health and Structural Integrity of Monitoring Systems: The Case Study of Pressurized Pipelines

2020 ◽  
Vol 10 (17) ◽  
pp. 6023
Author(s):  
Vladimír Chmelko ◽  
Martin Garan ◽  
Miroslav Šulko ◽  
Marek Gašparík

In the operation of some structures, particularly in energy or chemical industry where pressurized pipeline systems are employed, certain unexpected critical situations may occur, which must be definitely avoided. Otherwise, such situations would result in undesirable damage to the environment or even the endangerment of human life. For example, the occurrence of such nonstandard states can significantly affect the safety of high-pressure pipeline systems. The following paper discusses basic physical prerequisites for assembling the systems that can sense loading states and monitor the operational safety conditions of pressure piping systems in the long-run. The appropriate monitoring system hardware with cost-effective data management was designed in order to enable the real-time monitoring of operational safety parameters. Furthermore, the paper presents the results obtained from the measurements of existing real-time safety monitoring systems for selected pipeline systems.

Author(s):  
Xuedong Chen ◽  
Tiecheng Yang ◽  
Zhichao Fan ◽  
Yunrong Lv

Characteristic safety parameter refers to the parameter that reflects the inherent safety margin of pressure equipments subjected to certain failure mechanism. It has three main characteristics. Firstly, it is sensitive to the change in failure mechanism. Secondly, the safety of pressure equipments can be guaranteed by controlling this parameter. Thirdly, it is easy to measure. By real-time monitoring of this characteristic safety parameter, the quantitative assessment of the structural integrity and furhter the diagnosis and warning on the safety of in-service pressure equipments can be realized. In this paper, the definition of characteristic safety parameter is given first for the pressure equipments subjected to several typical failure modes. After that, the selection principle, measurement technique and determination of its critical value, etc., are then introduced by analyzing typical examples. In combination with the technical concepts of the Internet of Things and Big-Data, some research suggestions are proposed with respect to the remote monitoring and diagnosis techniques based on the characteristic safety parameter, including the sensing measurement, monitoring and analysis of big data, real-time diagnosis and early warning of safety condition, etc.


2021 ◽  
Vol 13 (9) ◽  
pp. 5048
Author(s):  
Srikanta Bhaskara ◽  
Kamaljit S. Bawa

During the last several decades, international and national agricultural research infrastructures have rapidly expanded, bringing the outputs of agricultural research to the world’s farmers. However, despite huge investments in agricultural research, there have been few systematic efforts to create digital platforms to meet the information requirements of farmers in a changing world. We describe an interactive information system in real time to provide agricultural information to farmers. The goals were to increase yields, reduce or optimize farm inputs, inform farmers about markets and government policies, and enable digital literacy among farmers, which (in the long run) would enhance rural incomes. Farmer clubs were created at the village level to increase engagement in the program and to access information. A call-in help center enabled farmers to get information in real time. In addition, a digital platform named eKisaan delivered relevant and contextual information in the local language, mostly in the video format via mobile and cloud technologies. The platform provided information about crop management and a variety of other parameters. The combined incremental savings and incremental earnings resulted in an estimated increase of 15% in income after 18 months, totaling INR₹26,250,000 (US$365,000), followed by an additional increase of 7% in the third year. The approximate cost of the information technology program and help center was INR₹15,000,000 (US$208,000). Over time, costs can decrease by spreading fixed costs over several years, with benefits reaching more farmers. Thus, the digital systems focused on information alone can be cost-effective, reduce inputs, increase productivity and income, and foster sustainability.


1984 ◽  
Vol 16 (8-9) ◽  
pp. 349-362 ◽  
Author(s):  
John L Vogel

Continued growth of urban regions and more stringent water quality regulations have resulted in an increased need for more real-time information about past, present, and future patterns and intensities of precipitation. Detailed, real-time information about precipitation can be obtained using radar and raingages for monitoring and prediction of precipitation amounts. The philosophy and the requirements for the development of real-time radar prediction-monitoring systems are described for climatic region similar to the Midwest of the united States. General data analysis and interpretation techniques associated with rainfall from convective storm systems are presented.


2020 ◽  
Vol 6 (3) ◽  
pp. 180-191
Author(s):  
Kavitha Chandrasekaran

Background:: In the long run, synthetic tints were found to be harmful to the chemicals. As a result natural tints have come to be used for their many intrinsic values. The main reason being, then availability of local plants as the main source of natural colorants. Their easy availability in the country being zero cost – effective and planted for other purposes are the main reasons for utilizing them as natural tints. Almost all the parts of the plants, namely stem, leaves, fruits, seeds, barks etc. are used for extracting natural colour. In addition, they are antimicrobial antifungal, insect – repellant deodorant, disinfectant having medicinal values. Methods:: Sweet Indrajao leaves were cleaned by washing with water and dried under direct sunlight and ground as fine powder. A fine strainer was used to remove the wastages. After all these processes, 1-kilogram leaves weighed 318 grams. Then, it is put in 75% ethanol 25% water and heated in a breaker which in kept over a water bath for 2 hours. After this, the contents were filtered and kept in a separate beaker. Bleached fleece draperies stained with stain extract were made to become wet and put into different stain baths which contain the required amount of stain extract and water. Acetic acid was added to it after 20 minutes. The fleece drapery was stained for about one hour at 60oC. The draperies thus stained were removed, squeezed, and put to treatment with metal salts without washing. Different metal salts were used for the treatment using 3% of any one of the chemical mordants like alum, stannous chloride, potassium dichromate, ferrous sulphate, nickel sulphate, copper sulphate and natural mordants such as myrobolan, turmeric, cow dung, Banana sap juice at 60oC for 30 minutes with MLR of 1:30. The stained draperies were washed repeatedly in all the three methods in water and dried in air. At last, the stained draperies were put to soap with soap solution at 60oC for 10 minutes. The draperies were repeatedly washed in water and dried under the sun. Results:: Sweet Indrajao leaves discharged colour easily in alcoholic water. The fleece draperies were stained with chemical and natural mordants. It was observed that the stain uptake was found to be good in post-mordanting method. Ultrasonication has clearly improved the stainability of the draperies at pH 3 and 3.5 values. The pH decreases the stain ability under both Conventional and Ultrasonic conditions. The colour strength increases with an increase in staining temperature in both cases of US and CH methods. Conclusion:: Sweet Indrajao.L has been found to have good ultrasonic potential as a stain plant. The stain uptake as well as the fastness properties of the fleece drapery were found to enhance when metal mordant was used in conjugation with ultra-sonication for the extract of Sweet Indrajao. It was also found that the enhancement of staining ability was better without mordant draperies. The dye extract showed good antibacterial activity against the three bacterial pathogens. Among the three bacterial pathogens, dye extract showed more effective against Escherichia coli pathogens and dye extract showed more effective against Aspergillus pathogens. Hence, the ultrasonic method of drapery staining may be appropriate and beneficial for society at large in future.


Author(s):  
Guang Zou ◽  
Kian Banisoleiman ◽  
Arturo González

A challenge in marine and offshore engineering is structural integrity management (SIM) of assets such as ships, offshore structures, mooring systems, etc. Due to harsh marine environments, fatigue cracking and corrosion present persistent threats to structural integrity. SIM for such assets is complicated because of a very large number of rewelded plates and joints, for which condition inspections and maintenance are difficult and expensive tasks. Marine SIM needs to take into account uncertainty in material properties, loading characteristics, fatigue models, detection capacities of inspection methods, etc. Optimising inspection and maintenance strategies under uncertainty is therefore vital for effective SIM and cost reductions. This paper proposes a value of information (VoI) computation and Bayesian decision optimisation (BDO) approach to optimal maintenance planning of typical fatigue-prone structural systems under uncertainty. It is shown that the approach can yield optimal maintenance strategies reliably in various maintenance decision making problems or contexts, which are characterized by different cost ratios. It is also shown that there are decision making contexts where inspection information doesn’t add value, and condition based maintenance (CBM) is not cost-effective. The CBM strategy is optimal only in the decision making contexts where VoI > 0. The proposed approach overcomes the limitation of CBM strategy and highlights the importance of VoI computation (to confirm VoI > 0) before adopting inspections and CBM.


2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Andrew W. Kirkpatrick ◽  
Jessica L. McKee ◽  
John M. Conly

AbstractCOVID-19 has impacted human life globally and threatens to overwhelm health-care resources. Infection rates are rapidly rising almost everywhere, and new approaches are required to both prevent transmission, but to also monitor and rescue infected and at-risk patients from severe complications. Point-of-care lung ultrasound has received intense attention as a cost-effective technology that can aid early diagnosis, triage, and longitudinal follow-up of lung health. Detecting pleural abnormalities in previously healthy lungs reveal the beginning of lung inflammation eventually requiring mechanical ventilation with sensitivities superior to chest radiographs or oxygen saturation monitoring. Using a paradigm first developed for space-medicine known as Remotely Telementored Self-Performed Ultrasound (RTSPUS), motivated patients with portable smartphone support ultrasound probes can be guided completely remotely by a remote lung imaging expert to longitudinally follow the health of their own lungs. Ultrasound probes can be couriered or even delivered by drone and can be easily sterilized or dedicated to one or a commonly exposed cohort of individuals. Using medical outreach supported by remote vital signs monitoring and lung ultrasound health surveillance would allow clinicians to follow and virtually lay hands upon many at-risk paucisymptomatic patients. Our initial experiences with such patients are presented, and we believe present a paradigm for an evolution in rich home-monitoring of the many patients expected to become infected and who threaten to overwhelm resources if they must all be assessed in person by at-risk care providers.


Author(s):  
Paul Oehlmann ◽  
Paul Osswald ◽  
Juan Camilo Blanco ◽  
Martin Friedrich ◽  
Dominik Rietzel ◽  
...  

AbstractWith industries pushing towards digitalized production, adaption to expectations and increasing requirements for modern applications, has brought additive manufacturing (AM) to the forefront of Industry 4.0. In fact, AM is a main accelerator for digital production with its possibilities in structural design, such as topology optimization, production flexibility, customization, product development, to name a few. Fused Filament Fabrication (FFF) is a widespread and practical tool for rapid prototyping that also demonstrates the importance of AM technologies through its accessibility to the general public by creating cost effective desktop solutions. An increasing integration of systems in an intelligent production environment also enables the generation of large-scale data to be used for process monitoring and process control. Deep learning as a form of artificial intelligence (AI) and more specifically, a method of machine learning (ML) is ideal for handling big data. This study uses a trained artificial neural network (ANN) model as a digital shadow to predict the force within the nozzle of an FFF printer using filament speed and nozzle temperatures as input data. After the ANN model was tested using data from a theoretical model it was implemented to predict the behavior using real-time printer data. For this purpose, an FFF printer was equipped with sensors that collect real time printer data during the printing process. The ANN model reflected the kinematics of melting and flow predicted by models currently available for various speeds of printing. The model allows for a deeper understanding of the influencing process parameters which ultimately results in the determination of the optimum combination of process speed and print quality.


Author(s):  
Negin Yousefpour ◽  
Steve Downie ◽  
Steve Walker ◽  
Nathan Perkins ◽  
Hristo Dikanski

Bridge scour is a challenge throughout the U.S.A. and other countries. Despite the scale of the issue, there is still a substantial lack of robust methods for scour prediction to support reliable, risk-based management and decision making. Throughout the past decade, the use of real-time scour monitoring systems has gained increasing interest among state departments of transportation across the U.S.A. This paper introduces three distinct methodologies for scour prediction using advanced artificial intelligence (AI)/machine learning (ML) techniques based on real-time scour monitoring data. Scour monitoring data included the riverbed and river stage elevation time series at bridge piers gathered from various sources. Deep learning algorithms showed promising in prediction of bed elevation and water level variations as early as a week in advance. Ensemble neural networks proved successful in the predicting the maximum upcoming scour depth, using the observed sensor data at the onset of a scour episode, and based on bridge pier, flow and riverbed characteristics. In addition, two of the common empirical scour models were calibrated based on the observed sensor data using the Bayesian inference method, showing significant improvement in prediction accuracy. Overall, this paper introduces a novel approach for scour risk management by integrating emerging AI/ML algorithms with real-time monitoring systems for early scour forecast.


Chemosensors ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 139
Author(s):  
Wiktoria Blaszczak ◽  
Zhengchu Tan ◽  
Pawel Swietach

A fundamental phenotype of cancer cells is their metabolic profile, which is routinely described in terms of glycolytic and respiratory rates. Various devices and protocols have been designed to quantify glycolysis and respiration from the rates of acid production and oxygen utilization, respectively, but many of these approaches have limitations, including concerns about their cost-ineffectiveness, inadequate normalization procedures, or short probing time-frames. As a result, many methods for measuring metabolism are incompatible with cell culture conditions, particularly in the context of high-throughput applications. Here, we present a simple plate-based approach for real-time measurements of acid production and oxygen depletion under typical culture conditions that enable metabolic monitoring for extended periods of time. Using this approach, it is possible to calculate metabolic fluxes and, uniquely, describe the system at steady-state. By controlling the conditions with respect to pH buffering, O2 diffusion, medium volume, and cell numbers, our workflow can accurately describe the metabolic phenotype of cells in terms of molar fluxes. This direct measure of glycolysis and respiration is conducive for between-runs and even between-laboratory comparisons. To illustrate the utility of this approach, we characterize the phenotype of pancreatic ductal adenocarcinoma cell lines and measure their response to a switch of metabolic substrate and the presence of metabolic inhibitors. In summary, the method can deliver a robust appraisal of metabolism in cell lines, with applications in drug screening and in quantitative studies of metabolic regulation.


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