Systematic Approach to Measuring ILI Tool Performance

2014 ◽  
Author(s):  
Sean Keane ◽  
Karmun Cheng ◽  
Kaitlyn Korol
Keyword(s):  
Performance Measurement ◽  
Performance Measures ◽  
New Technologies ◽  
Efficient Reduction ◽  
Tool Performance ◽  
Typical Performance ◽  
Substantial Investment ◽  
Integrity Management ◽  
Insight Into

In-line inspection (ILI) tools play an important role within integrity management and substantial investment is made to continuously advance performance of the existing technologies and, where necessary, to develop new technologies. Performance measurement is typically focused for the purpose of understanding the measured performance in relation to the ILI vendor specification and for the determination of residual uncertainty regarding pipeline integrity. These performance measures may not provide the necessary insight into what type of investment into a technology is necessary to further reduce residual uncertainty regarding pipeline integrity, and beyond that, what investment, as an operator, results in an effective and efficient reduction in uncertainty. The paper proposes a reliability based approach for investigating uncertainty associated with ultrasonic crack ILI technology for the purpose of identifying efficient investment into the technology that results in an effective and measurable improvement. Typical performance measures and novel performance measurement methods are presented and reviewed with respect to what information they can provide to assist in investment decisions. Finally, general observations are made regarding Enbridge’s experience using ultrasonic crack ILI technology and areas currently being investigated.

Methodology for uncertainty characterization of performance measures

2016 ◽  
Vol 33 (9) ◽  
pp. 1346-1363 ◽  
Author(s):  
Isabel Silva Lopes ◽  
Sérgio Dinis Sousa ◽  
Eusébio Nunes
Keyword(s):  
Graph Theory ◽  
Performance Measurement ◽  
Performance Measures ◽  
Content Type ◽  
Uncertainty Index ◽  
The Matrix ◽  
Function Calculation ◽  
Permanent Function

Purpose The purpose of this paper is to present a methodology to represent the uncertainty generated in performance measures (PMs) during the operational step or “use step” of the performance measurement process (PMP). The different steps of the methodology are described and exemplified through an application example. Design/methodology/approach An index that reflects the level of uncertainty originated by the factors and the strength of their inter-relationships is developed through the use of graph theory. A graph is developed considering all sources or factors of uncertainty that may be present in this process. Based on the graph, the methodology includes the use of a matrix and the determination of the associated permanent function which is used for determining the uncertainty index. Findings During the development of the methodology, it was found that the use of a scale that includes zero for assigning values of the elements of the matrix is not appropriate when using graph theory and permanent function calculation, since in this case the permanent function is insensible to changes in some matrix elements. Originality/value This paper identifies all the sources that can affect the quality of performance measurement values during the operational step of the PMP and proposes a method to characterize the strength of this uncertainty. Beyond alerting decision makers to the level of uncertainty associated with a PM, it also allows defining appropriate actions to improve PMs’ quality.

Financial and Economic Support of Innovation Processes in the Russian Fuel and Energy Complex

2019 ◽  
Vol 12 (3) ◽  
pp. 77-85
Author(s):  
L. D. Kapranova ◽  
T. V. Pogodina
Keyword(s):  
Oil Recovery ◽  
Large Scale ◽  
Oil And Gas ◽  
New Technologies ◽  
Innovative Development ◽  
Oil Reserves ◽  
Energy Complex ◽  
Innovation Activities ◽  
Substantial Investment ◽  
The Government

The subject of the research is the current state of the fuel and energy complex (FEC) that ensures generation of a significant part of the budget and the innovative development of the economy.The purpose of the research was to establish priority directions for the development of the FEC sectors based on a comprehensive analysis of their innovative and investment activities. The dynamics of investment in the fuel and energy sector are considered. It is noted that large-scale modernization of the fuel and energy complex requires substantial investment and support from the government. The results of the government programs of corporate innovative development are analyzed. The results of the research identified innovative development priorities in the power, oil, gas and coal sectors of the fuel and energy complex. The most promising areas of innovative development in the oil and gas sector are the technologies of enhanced oil recovery; the development of hard-to-recover oil reserves; the production of liquefied natural gas and its transportation. In the power sector, the prospective areas are activities aimed at improving the performance reliability of the national energy systems and the introduction of digital technologies. Based on the research findings, it is concluded that the innovation activities in the fuel and energy complex primarily include the development of new technologies, modernization of the FEC technical base; adoption of state-of-the-art methods of coal mining and oil recovery; creating favorable economic conditions for industrial extraction of hard-to-recover reserves; transition to carbon-free fuel sources and energy carriers that can reduce energy consumption and cost as well as reducing the negative FEC impact on the environment.

The Role of Industry-Academia Collaborative Research in Mineral Exploration

2020 ◽  
Author(s):  
James Marlatt
Keyword(s):  
Collaborative Research ◽  
New Technologies ◽  
Mineral Exploration ◽  
Board Members ◽  
Technological Innovations ◽  
Development Programs ◽  
The University ◽  
Insight Into ◽  
Economic Mineral

ABSTRACT Many people may not be aware of the extent of Kurt Kyser's collaboration with mineral exploration companies through applied research and the development of innovative exploration technologies, starting at the University of Saskatchewan and continuing through the Queen's Facility for Isotope Research. Applied collaborative, geoscientific, industry-academia research and development programs can yield technological innovations that can improve the mineral exploration discovery rates of economic mineral deposits. Alliances between exploration geoscientists and geoscientific researchers can benefit both parties, contributing to the pure and applied geoscientific knowledge base and the development of innovations in mineral exploration technology. Through a collaboration that spanned over three decades, we gained insight into the potential for economic uranium deposits around the world in Canada, Australia, USA, Finland, Russia, Gabon, Namibia, Botswana, South Africa, and Guyana. Kurt, his research team, postdoctoral fellows, and students developed technological innovations related to holistic basin analysis for economic mineral potential, isotopes in mineral exploration, and biogeochemical exploration, among others. In this paper, the business of mineral exploration is briefly described, and some examples of industry-academic collaboration innovations brought forward through Kurt's research are identified. Kurt was a masterful and capable knowledge broker, which is a key criterion for bringing new technologies to application—a grand, curious, credible, patient, and attentive communicator—whether talking about science, business, or life and with first ministers, senior technocrats, peers, board members, first nation peoples, exploration geologists, investors, students, citizens, or friends.

AI Narratives

2020 ◽  
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Ancient Greece ◽  
Historical Overview ◽  
Intelligent Machines ◽  
Narrative History ◽  
History Of ◽  
Imaginative Thinking ◽  
The Relationship ◽  
Insight Into

This book is the first to examine the history of imaginative thinking about intelligent machines. As real artificial intelligence (AI) begins to touch on all aspects of our lives, this long narrative history shapes how the technology is developed, deployed, and regulated. It is therefore a crucial social and ethical issue. Part I of this book provides a historical overview from ancient Greece to the start of modernity. These chapters explore the revealing prehistory of key concerns of contemporary AI discourse, from the nature of mind and creativity to issues of power and rights, from the tension between fascination and ambivalence to investigations into artificial voices and technophobia. Part II focuses on the twentieth and twenty-first centuries in which a greater density of narratives emerged alongside rapid developments in AI technology. These chapters reveal not only how AI narratives have consistently been entangled with the emergence of real robotics and AI, but also how they offer a rich source of insight into how we might live with these revolutionary machines. Through their close textual engagements, these chapters explore the relationship between imaginative narratives and contemporary debates about AI’s social, ethical, and philosophical consequences, including questions of dehumanization, automation, anthropomorphization, cybernetics, cyberpunk, immortality, slavery, and governance. The contributions, from leading humanities and social science scholars, show that narratives about AI offer a crucial epistemic site for exploring contemporary debates about these powerful new technologies.

An insight into the determination of size and number concentration of silver nanoparticles in blood using single particle ICP-MS (spICP-MS): Feasibility of application to samples relevant to in vivo toxicology studies

2021 ◽  
Author(s):  
Isabel Abad-Álvaro ◽  
Diego Leite ◽  
Dorota Bartczak ◽  
Susana Cuello ◽  
Beatriz Gomez-Gomez ◽  
...  
Keyword(s):  
Silver Nanoparticles ◽  
Single Particle ◽  
Number Concentration ◽  
Biological Matrices ◽  
Icp Ms ◽  
Toxicological Studies ◽  
Insight Into

Toxicological studies concerning nanomaterials in complex biological matrices usually require a carefully designed workflow that involves handling, transportation and preparation of a large number of samples without affecting the nanoparticle...

scholarly journals Insight into Glutamatergic Involvement in Rewarding Effects of Mephedrone in Rats: In Vivo and Ex Vivo Study

2021 ◽  
Author(s):  
Olga Wronikowska ◽  
Maria Zykubek ◽  
Agnieszka Michalak ◽  
Anna Pankowska ◽  
Paulina Kozioł ◽  
...  
Keyword(s):  
Ex Vivo ◽  
Interdisciplinary Approach ◽  
Nmda Antagonist ◽  
Exchange Chromatography ◽  
Resonance Spectroscopy ◽  
Monoamine Transporters ◽  
Ex Vivo Study ◽  
Insight Into

AbstractMephedrone is a widely used drug of abuse, exerting its effects by interacting with monoamine transporters. Although this mechanism has been widely studied heretofore, little is known about the involvement of glutamatergic transmission in mephedrone effects. In this study, we comprehensively evaluated glutamatergic involvement in rewarding effects of mephedrone using an interdisciplinary approach including (1) behavioural study on effects of memantine (non-selective NMDA antagonist) on expression of mephedrone-induced conditioned place preference (CPP) in rats; (2) evaluation of glutamate concentrations in the hippocampus of rats following 6 days of mephedrone administration, using in vivo magnetic resonance spectroscopy (MRS); and (3) determination of glutamate levels in the hippocampus of rats treated with mephedrone and subjected to MRS, using ion-exchange chromatography. In the presented research, we confirmed priorly reported mephedrone-induced rewarding effects in the CPP paradigm and showed that memantine (5 mg/kg) was able to reverse the expression of this effect. MRS study showed that subchronic mephedrone administration increased glutamate level in the hippocampus when measured in vivo 24 h (5 mg/kg, 10 mg/kg and 20 mg/kg) and 2 weeks (5 mg/kg and 20 mg/kg) after last injection. Ex vivo chromatographic analysis did not show significant changes in hippocampal glutamate concentrations; however, it showed similar results as obtained in the MRS study proving its validity. Taken together, the presented study provides new insight into glutamatergic involvement in rewarding properties of mephedrone.

scholarly journals Prediction of Dead Oil Viscosity: Machine Learning vs. Classical Correlations

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 930
Author(s):  
Fahimeh Hadavimoghaddam ◽  
Mehdi Ostadhassan ◽  
Ehsan Heidaryan ◽  
Mohammad Ali Sadri ◽  
Inna Chapanova ◽  
...  
Keyword(s):  
Machine Learning ◽  
Viscosity Data ◽  
Oil Viscosity ◽  
Pvt Data ◽  
Proposed Model ◽  
Wide Range ◽  
Engineering Problems ◽  
Functional Forms ◽  
Insight Into

Dead oil viscosity is a critical parameter to solve numerous reservoir engineering problems and one of the most unreliable properties to predict with classical black oil correlations. Determination of dead oil viscosity by experiments is expensive and time-consuming, which means developing an accurate and quick prediction model is required. This paper implements six machine learning models: random forest (RF), lightgbm, XGBoost, multilayer perceptron (MLP) neural network, stochastic real-valued (SRV) and SuperLearner to predict dead oil viscosity. More than 2000 pressure–volume–temperature (PVT) data were used for developing and testing these models. A huge range of viscosity data were used, from light intermediate to heavy oil. In this study, we give insight into the performance of different functional forms that have been used in the literature to formulate dead oil viscosity. The results show that the functional form f(γAPI,T), has the best performance, and additional correlating parameters might be unnecessary. Furthermore, SuperLearner outperformed other machine learning (ML) algorithms as well as common correlations that are based on the metric analysis. The SuperLearner model can potentially replace the empirical models for viscosity predictions on a wide range of viscosities (any oil type). Ultimately, the proposed model is capable of simulating the true physical trend of the dead oil viscosity with variations of oil API gravity, temperature and shear rate.

Performance measurement for supply chain management and quality management integration

2019 ◽  
Vol 27 (7) ◽  
pp. 2130-2147 ◽  
Author(s):  
Marcio C. Machado ◽  
Renato Telles ◽  
Paulo Sampaio ◽  
Maciel M. Queiroz ◽  
Ana Cristina Fernandes
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Quality Management ◽  
Performance Measurement ◽  
Performance Measures ◽  
Chain Management ◽  
Content Type ◽  
Theoretical Perspectives ◽  
Overall Performance ◽  
Key Aspects

Purpose The purpose of this paper is to present a conceptual framework for performance measurement (PM) for the integration of supply chain management (SCM) and quality management (QM). Design/methodology/approach A systematic literature review on SCM and QM was conducted to develop key performance measures related to six areas of integration between QM and SCM: leadership; continuous improvement and innovation; sustainability performance; stakeholders; information system; and management and strategic planning. Findings Supported by the literature concerning to supply chain quality management (SCQM) integration, a set of nine propositions about performance measures, that contribute to the integration of SCQM, were developed. Originality/value This study contributes to QM practices within a supply chain environment from an integrated perspective. Additionally, the propositions have significant implications from both managerial and theoretical perspectives. This study also extends the concept of supply chain quality integration by focusing on key aspects of PM that may help to improve the overall performance of the supply chain.

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