An overview of maintenance management strategies for corroded steel structures in extreme marine environments

Criticality-based maintenance of a coal-fired power plant

A compound interpolation envelope local mean decomposition and its application for fault diagnosis of reciprocating compressors

Maintenance optimization of power systems with renewable energy sources integrated

An integration of multi-criteria decision making techniques with a delay time model for determination of inspection intervals for marine machinery systems

The wearing parts of a system have a very high failure frequency, making it necessary to carry out continual functional inspections and maintenance to protect the system from unscheduled downtime. This allows for the collection of a large amount of maintenance data. Taking the unique characteristics of the wearing parts into consideration, we establish their respective delay time models in ideal inspection cases and nonideal inspection cases. The model parameters are estimated entirely using the collected maintenance data. Then, a likelihood function of all renewal events is derived based on their occurring probability functions, and the model parameters are calculated with the maximum likelihood function method, which is solved by the CRM. Finally, using two wearing parts from the oil and gas drilling industry as examples—the filter element and the blowout preventer rubber core—the parameters of the distribution function of the initial failure time and the delay time for each example are estimated, and their distribution functions are obtained. Such parameter estimation based on objective data will contribute to the optimization of the reasonable function inspection interval and will also provide some theoretical models to support the integrity management of equipment or systems.

/pdf/parameter-estimation-of-a-delay-time-model-of-wearing-parts-2wmpg0kye0.pdf

Parameter Estimation of a Delay Time Model of Wearing Parts Based on Objective Data

In the petrochemical production system, the high-risk items malfunction may lead to major accidents so that the risk level of the items has become the highest focus of attention for the enterprises in petrochemical industry. Based on structural composition and risk relationship, a risk evaluation framework of the petrochemical production system can generally be divided into subsystems (SS), components and parts (CP), failure modes (FM), risk types, and risk factors. So it is a characteristic of multilevel, complex structure, and lack of evaluation criteria that the evaluated object has in the process of risk evaluation. However, there are few targeted modeling and calculation methods to carry out quantitative risk evaluation in the face of the evaluated object. In order to achieve risk quantitative evaluation of the complex structure hierarchical system, a multilevel Borda model (MLBM) is presented innovatively by us based on the traditional Borda method in this study. Moreover, the MLBM are applied to realize quantitative risk evaluation of the main structure system of truss type crane on the offshore platform. In this case study, the equivalent risk value (ERV) and risk priority number (RPN) of the evaluated object with multilevel, complex structure, and inadequate evaluation criteria are calculated and the risk ties in the RPN are effectively reduced. Then, the quantitative risk results can clarify the risk level and distribution of the high-risk items throughout the production system and provide data support for the development of risk control measures to better protect the production safety. Hence, the feasibility and practicability of the method are verified with the case study. The MLBM can be used to solve other comprehensive evaluation problems with a complex hierarchical structure as well.

/pdf/quantitative-risk-evaluation-model-of-the-multilevel-complex-1czmhc7iot.pdf

Quantitative Risk Evaluation Model of the Multilevel Complex Structure Hierarchical System in the Petrochemical Industry

Anthropogenic water vapor emissions became an important component of the urban atmosphere with the process of urbanization, and one of the main sources of anthropogenic water vapor emissions is the fossil fuel combustion-derived vapor (CDV). Due to the extremely low d-excess value of CDV, stable hydrogen and oxygen isotope can be a promising method to partition CDV from other natural sources. Considering the limitation of in-situ observation, this study explored the possibility to use IsoRSM, an isotopic-enable regional spectral model to simulate the emission situation of CDV in the urban area. A one-month experiment in Salt Lake City and a one-year experiment in Beijing were made respectively. The simulating result indicated that the addition of CDV could significantly decrease the d-excess of water vapor, especially when the boundary layer was stable. The simulation with CDV emission fitted better with the time series of in-situ observation than the simulation without CDV in Salt Lake City. Furthermore, the addition of CDV also resulted in an obvious negative correlation between vapor d-excess and specific humidity. High d-excess in the winter season in Beijing might be caused by other factors such as strong kinetic fractionation in evaporation caused by the hard winter monsoon. In the simulations, the CDV fraction in Salt Lake City could reach more than 13%. The results indicated that the anthropogenic emission could not be ignored particularly in studies on the urban atmospheric hydrological cycle. 

Isotopic simulation of combustion-derived vapor emission in urban area using regional spectral model

Bottom hole assembly (BHA) component failures continue to afflict the oil and gas industry, annually involving huge amount of direct and consequential cost. However, actual assemblies and drilling situations are too complex to rely on the simpler idealizations that do not account for varying collar dimensions, material properties, and multistabilizer arrangements. Recognizing this, cellular automata(CA), an idealizations of complex systems which is especially advantageous for modeling complex dynamic problems, is used to simulate BHA performance in this paper. At first, a drill string dynamic model is established, and the collision conditions between the drilling string and well wall are obtained. Then a new numerical solution method based on CA is proposed to solve the model. In the end, a practical example with a widely used tower type BHA is given, successfully solved, and the computational results are presented. The solutions for this assembly show various reaction forces, displacements and the position of tangent points. From the side force at the bit, the general inclination tendency can be determined, and the stability of the BHA can also be evaluated by the position of tangent points and their forces. This new method has advantages of programming simply, applying boundary condition easily, small calculation storage space and rapid convergence rate etc.

Application of Cellular Automata Modeling to Simulate Bottom Hole Assembly Performance

A framework for identification of maintenance significant items in reliability centered maintenance

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Yan Yang

Author Tools

Chat about Author