scholarly journals Mechanical Damage Assessment for Pneumatic Control Valve Based on Statistical Reliability Model

2020 ◽  
Author(s):  
Nirbhay Mathur ◽  
Vijanth Sagayan Asirvadam ◽  
Azrina Abt Aziz
Keyword(s):  
Damage Assessment ◽  
Failure Modes ◽  
Reliability Assessment ◽  
Mechanical Damage ◽  
Control Valve ◽  
Pneumatic Control ◽  
Statistical Reliability ◽  
Process Plants ◽  
Log Normal ◽  
Best Fit

Reliability assessment is an important component and tool used for process plants since the facility consists of many loops and instruments attached and operates based on each other availability, thus it requires a statistical method to visualize the reliability. The paper focuses on reliability assessment and prediction based on available statistical models such as normal, log-normal, exponential, and Weibull distribution. This paper also visualizes, which model fits best for assessment and prediction and also considers failure modes caused during a simulation mode process control operation. A simulation model is designed in this paper to observe the failure of the control valve causing stiction to visualize the failure modes and predict the best-fit model for reliability assessment.

scholarly journals Mechanical Damage Assessment for Pneumatic Control Valves Based on a Statistical Reliability Model

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3307
Author(s):  
Nirbhay Mathur ◽  
Vijanth Sagayan Asirvadam ◽  
Azrina Abd Aziz
Keyword(s):  
Weibull Distribution ◽  
Reliability Assessment ◽  
Mechanical Damage ◽  
Control Valve ◽  
Reliability Models ◽  
Statistical Reliability ◽  
Processing Plants ◽  
Simulated Process ◽  
Pneumatic Control Valves ◽  
Log Normal

A reliability assessment is an important tool used for processing plants, since the facility consists of many loops and instruments attached and operated based on other availability; thus, a statistical model is needed to visualize the reliability of its operation. The paper focuses on the reliability assessment and prediction based on the existing statistical models, such as normal, log-normal, exponential, and Weibull distribution. This paper evaluates and visualizes the statistical reliability models optimized using MLE and considers the failure mode caused during a simulated process control operation. We simulated the failure of the control valve caused by stiction running with various flow rates using a pilot plant, which depicted the Weibull distribution as the best model to estimate the simulated process failure.

Prediction of Haemoglobin Level by Some Probability Distribution

2020 ◽  
Vol 9 (1) ◽  
pp. 84-88
Author(s):  
Govinda Prasad Dhungana ◽  
Laxmi Prasad Sapkota
Keyword(s):  
Probability Distribution ◽  
Normal Distribution ◽  
Goodness Of Fit ◽  
Continuous Variable ◽  
Hemoglobin Level ◽  
Chi Square ◽  
Chi Square Test ◽  
Log Normal ◽  
Two Parameters ◽  
Best Fit

 Hemoglobin level is a continuous variable. So, it follows some theoretical probability distribution Normal, Log-normal, Gamma and Weibull distribution having two parameters. There is low variation in observed and expected frequency of Normal distribution in bar diagram. Similarly, calculated value of chi-square test (goodness of fit) is observed which is lower in Normal distribution. Furthermore, plot of PDFof Normal distribution covers larger area of histogram than all of other distribution. Hence Normal distribution is the best fit to predict the hemoglobin level in future.

Operating Reliability Assessment of FPGA-Based NPP I&C Systems: Approach, Technique and Implementation

2017 ◽  
Author(s):  
Eugene Babeshko ◽  
Ievgenii Bakhmach ◽  
Vyacheslav Kharchenko ◽  
Eugene Ruchkov ◽  
Oleksandr Siora
Keyword(s):  
Integrated Circuits ◽  
Nuclear Power ◽  
Power Plants ◽  
Failure Modes ◽  
New Technologies ◽  
Systems Approach ◽  
Reliability Assessment ◽  
Design Stage ◽  
Fpga Design ◽  
Operating Reliability

Operating reliability assessment of instrumentation and control systems (I&Cs) is always one of the most important activities, especially for critical domains like nuclear power plants (NPPs). Intensive use of relatively new technologies like field programmable gate arrays (FPGAs) in I&C which appear in upgrades and in newly built NPPs makes task to develop and validate advanced operating reliability assessment methods that consider specific technology features very topical. Increased integration densities make the reliability of integrated circuits the most crucial point in modern NPP I&Cs. Moreover, FPGAs differ in some significant ways from other integrated circuits: they are shipped as blanks and are very dependent on design configured into them. Furthermore, FPGA design could be changed during planned NPP outage for different reasons. Considering all possible failure modes of FPGA-based NPP I&C at design stage is a quite challenging task. Therefore, operating reliability assessment is one of the most preferable ways to perform comprehensive analysis of FPGA-based NPP I&Cs. This paper summarizes our experience on operating reliability analysis of FPGA based NPP I&Cs.

FMEDA and FIT-Based Safety Assessment of NPP I&C Systems Considering Expert Uncertainty

2018 ◽  
Author(s):  
Alexander Yasko ◽  
Eugene Babeshko ◽  
Vyacheslav Kharchenko
Keyword(s):  
Emotional Disorders ◽  
Nuclear Power ◽  
Safety Assessment ◽  
Failure Modes ◽  
Reliability Assessment ◽  
Software Tool ◽  
Critical Systems ◽  
System Specification ◽  
Multiple Faults ◽  
Safety And Reliability

The complexity of modern safety critical systems is becoming higher with technology level growth. Nowadays the most important and vital systems of automotive, aerospace, nuclear industries count millions of lines of software code and tens of thousands of hardware components and sensors. All of these constituents operate in integrated environment interacting with each other — this leads to enormous calculation task when testing and safety assessment are performed. There are several formal methods that are used to assess reliability and safety of NPP I&C (Nuclear Power Plant Instrumentation and Control) systems. Most of them require significant involvement of experts and confidence in their experience which vastly affects trustworthiness of assessment results. The goal of our research is to improve the quality of safety and reliability assessment as result of experts involvement mitigation by process automation. We propose usage of automated FMEDA (Failure Modes, Effects and Diagnostic Analysis) and FIT (Fault Insertion Testing) combination extended whith multiple faults approach as well as special methods for quantitative assessment of experts involvement level and their decisions uncertainty. These methods allow to perform safety and reliability assessment without specifying the degree of confidence in experts. Traditional FMEDA approach has several bottlenecks like the need of manual processing of huge number of technical documents (system specification, datasheets etc.), manual assignment of failure modes and effects based on personal experience. Human factor is another source of uncertainty. Such things like tiredness, emotional disorders, distraction or lack of experience could be the reasons of under- and over-estimation. Basing on our research in field of expert-related errors we propose expert involvement degree (EID) metric that indicates the level of technique automation and expert uncertainty degree (EUD) metric which is complex measure of experts decisions uncertainty within assessment. We propose usage of total expert trustworthiness degree (ETD) indicator as function of EID and EUD. Expert uncertainty assessment and Multi-FIT as FMEDA verification are implemented in AXMEA (Automated X-Modes and Effects Analysis) software tool. Proposed Multi-FIT technique in combination with FMEDA was used during internal activities of SIL3 certification of FPGA-based (Field Programmable Gate Array) RadICS platform for NPP I&C systems. The proposed expert trustworthiness degree calculation is going to be used during production activities of RPC Radiy (Research and Production Corporation). Our future work is related to research in expert uncertainty field and extension of AXMEA tool with new failure data sources as well as software optimization and further automation.

Multiple Data Set ILI for Mechanical Damage Assessment

2012 ◽  
Author(s):  
Chris Goller ◽  
James Simek ◽  
Jed Ludlow
Keyword(s):  
Damage Assessment ◽  
Public Awareness ◽  
Mechanical Damage ◽  
Data Sets ◽  
Data Set ◽  
Multiple Data ◽  
Pipe Joints ◽  
Multiple Data Sets ◽  
Multiple Field ◽  
Flux Leakage

The purpose of this paper is to present a non-traditional pipeline mechanical damage ranking system using multiple-data-set in-line inspection (ILI) tools. Mechanical damage continues to be a major factor in reportable incidents for hazardous liquid and gas pipelines. While several ongoing programs seek to limit damage incidents through public awareness, encroachment monitoring, and one-call systems, others have focused efforts on the quantification of mechanical damage severity through modeling, the use of ILI tools, and subsequent feature assessment at locations selected for excavation. Current generation ILI tools capable of acquiring multiple-data-sets in a single survey may provide an improved assessment of the severity of damaged zones using methods developed in earlier research programs as well as currently reported information. For magnetic flux leakage (MFL) type tools, using multiple field levels, varied field directions, and high accuracy deformation sensors enables detection and provides the data necessary for enhanced severity assessments. This paper will provide a review of multiple-data-set ILI results from several pipe joints with simulated mechanical damage locations created mimicing right-of-way encroachment events in addition to field results from ILI surveys using multiple-data-set tools.

Numerical and experimental evaluation of mechanical performance of the multifunctional energy storage composites

2021 ◽  
pp. 002199832110495
Author(s):  
Yinan Wang ◽  
Fu-Kuo Chang
Keyword(s):  
Energy Storage ◽  
Carbon Fiber ◽  
Composite Laminates ◽  
Failure Modes ◽  
Mechanical Performance ◽  
Fiber Composite ◽  
Mechanical Damage ◽  
Experimental Tests ◽  
Structural Element ◽  
Carbon Fiber Composite

This work presents numerical simulation methods to model the mechanical behavior of the multifunctional energy storage composites (MESCs), which consist of a stack of multiple thin battery layers reinforced with through-the-hole polymer rivets and embedded inside carbon fiber composite laminates. MESC has been demonstrated through earlier experiments on its exceptional behavior as a structural element as well as a battery. However, the inherent complex infrastructure of the MESC design has created significant challenges in simulation and modeling. A novel homogenization technique was adopted to characterize the multi-layer properties of battery material using physics-based constitutive equations combined with nonlinear deformation theories to handle the interface between the battery layers. Second, mechanical damage and failure modes among battery materials, polymer reinforcements, and carbon fiber-polymer interfaces were characterized through appropriate models and experiments. The model of MESCs has been implemented in a commercial finite element code in ABAQUS. A comparison of structural response and failure modes from numerical simulations and experimental tests are presented. The results of the study showed that the predictions of elastic and damage responses of MESCs at various loading conditions agreed well with the experimental data. © 2021

Bond Behaviour of FRCM Composites: Effects of High Temperature

2019 ◽  
Vol 817 ◽  
pp. 161-166
Author(s):  
Antonio Iorfida ◽  
Sebastiano Candamano ◽  
Fortunato Crea ◽  
Luciano Ombres ◽  
Salvatore Verre ◽  
...  
Keyword(s):  
High Temperature ◽  
Failure Mode ◽  
Failure Modes ◽  
Construction Materials ◽  
Mechanical Damage ◽  
High Density ◽  
Bond Behaviour ◽  
Bond Slip ◽  
Masonry Construction ◽  
Lap Shear

The fire remains one of the serious potential risks to most buildings and structures, as recently it’s been witnessed in Paris’ historic Notre Dame Cathedral and London’s Grenfell Tower. Concrete and masonry construction materials suffer physiochemical changes and mechanical damage caused by heating that is usually confined to the outer surface but can eventually compromise their load-bearing capacity. FRCM systems could provide when applied, supplemental fire insulation on pre-existing structural members, but there is a lack of knowledge about their properties in those conditions. This experimental work, thus, aims to evaluate the mechanical behaviour of carbon-FRCM and basalt-FRCM composites bonded to masonry substrate after high temperature exposure. Temperatures of 100 °C, 300 °C and 500 °C over a period of three hours were used to investigate the degradation of their mechanical properties. Single lap shear bond tests were carried out to evaluate the bond-slip response and failure modes. For all the tested temperatures higher peak stresses were measured for carbon-FRCM composite than basalt ones. Furthermore, low-density basalt-FRCM composite showed higher peak stresses and lower global slips up to 300 °C than high-density one. Carbon-FRCM composite failure mode was not effected by temperature. High-density basalt-FRCM composite showed a change in failure mode between 300 °C and 500 °C.

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