Impact of temperature on analog/RF, linearity and reliability performance metrics of tunnel FET with ultra-thin source region

2021 ◽  
Vol 127 (9) ◽  
Author(s):  
Prabhat Singh ◽  
Dharmendra Singh Yadav
Keyword(s):  
Performance Metrics ◽  
Source Region ◽  
Tunnel Fet ◽  
Reliability Performance ◽  
Thin Source

A Novel Approach to Evaluating Leak Detection CPM System Sensitivity/Reliability Performance Trade-Offs

2014 ◽  
Author(s):  
Shyam Chadha ◽  
Daniel Hung ◽  
Samir Rashid
Keyword(s):  
False Alarm ◽  
Capital Investment ◽  
Performance Metrics ◽  
Leak Detection ◽  
American Petroleum Institute ◽  
False Alarms ◽  
Good Reliability ◽  
Trade Off ◽  
Trade Offs ◽  
Reliability Performance

As defined in American Petroleum Institute Recommended Practice 1130 (API RP 1130), CPM system leak detection performance is evaluated on the basis of four distinct but interrelated metrics: sensitivity, reliability, accuracy and robustness. These performance metrics are captured to evaluate performance, manage risk and prioritize mitigation efforts. Evaluating and quantifying sensitivity performance of a CPM system is paramount to ensure the performance of the CPM system is acceptable based on a company’s risk profile for detecting leaks. Employing API RP 1130 recommended testing methodologies including parameter manipulation techniques, software simulated leak tests and/or removal of test quantities of commodity from the pipeline are excellent approaches to understanding the leak sensitivity metric. Good reliability (false alarm) performance is critical to ensure that control center operator desensitization does not occur through long term exposure to false alarms. Continuous tracking and analyzing of root causes of leak alarms ensures that the effects of seasonal variations or changes to operation on CPM system performance are managed appropriately. The complexity of quantifying this metric includes qualitatively evaluating the relevance of false alarms. The interrelated nature of the above performance metrics imposes conflicting requirements and results in inherent trade-offs. Optimizing the trade-off between reliability and sensitivity involves identifying the point that thresholds must be set to obtain a balance of a desired sensitivity and false alarm rate. This paper presents an approach to illustrate the combined sensitivity/reliability performance for an example pipeline. The paper discusses considerations addressed while determining the methodology such as stakeholder input, ongoing CPM system enhancements, sensitivity/reliability trade-off, risk based capital investment and graphing techniques. The paper also elaborates on a number of identified benefits of the selected overall methodology.

scholarly journals Impactful Study of F-shaped Tunnel FET

2021 ◽  
Author(s):  
PRABHAT SINGH ◽  
DHARMENDRA SINGH YADAV
Keyword(s):  
Field Effect ◽  
Field Effect Transistor ◽  
Source Region ◽  
Gate Oxide ◽  
Crowding Effect ◽  
Turn On ◽  
Tunnel Fet ◽  
Effect Transistor ◽  
Tunnel Field Effect Transistor ◽  
The Impact

Abstract In this proposed work, a novel single gate F-shaped channel tunnel field effect transistor (SG-FC-TFET) is proposed and investigated. The impact of thickness of the source region and lateral tunneling length between the gate oxide and edge of the source region on analog and radio frequency parameters are investigated with appropriate source and drain lateral length through the 2D-TCAD tool. The slender shape of the source enhanced the electric le crowding effect at the corners of the source region which reflect in term of high On-current (Ion). The Ion of proposed device is increased up to 10-4 A=μm with reduced sub-threshold swing (SS) is 7.3 mV/decade and minimum turn-ON voltage (Von = 0.28 V). The analog/RF parameters of SG-FC-TFET are optimized.

Temperature impact on linearity and analog/RF performance metrics of a novel charge plasma tunnel FET

2021 ◽  
Vol 127 (4) ◽  
Author(s):  
Nitish Parmar ◽  
Prabhat Singh ◽  
Dip Prakash Samajdar ◽  
Dharmendra Singh Yadav
Keyword(s):  
Performance Metrics ◽  
Charge Plasma ◽  
Tunnel Fet ◽  
Temperature Impact ◽  
Rf Performance

scholarly journals Understanding Factors Affecting Arterial Reliability Performance Metrics

2019 ◽  
Author(s):  
Jason Anderson ◽  
◽  
Rohan Sirupa ◽  
Sirisha Kothuri ◽  
Avinash Unnikrishnan ◽  
...  
Keyword(s):  
Performance Metrics ◽  
Factors Affecting ◽  
Reliability Performance

Demonstration of a Novel Two Source Region Tunnel FET

2017 ◽  
Vol 64 (12) ◽  
pp. 5256-5262 ◽  
Author(s):  
Navjeet Bagga ◽  
Anil Kumar ◽  
Sudeb Dasgupta
Keyword(s):  
Source Region ◽  
Tunnel Fet

Criterion setting for objective, fourier analysis based pilot performance metrics

2004 ◽  
Author(s):  
Nicholas R. Johnson ◽  
Esa M. Rantanen ◽  
Donald A. Talleur
Keyword(s):  
Fourier Analysis ◽  
Performance Metrics ◽  
Pilot Performance ◽  
Criterion Setting

Framework for rare event detection using Artificial Neural Network based context free grammar

2020 ◽  
Vol 39 (6) ◽  
pp. 8463-8475
Author(s):  
Palanivel Srinivasan ◽  
Manivannan Doraipandian
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Event Detection ◽  
Performance Metrics ◽  
Rare Events ◽  
Rare Event ◽  
Video Stream ◽  
Context Free Grammar ◽  
Artificial Neural ◽  
Context Free

Rare event detections are performed using spatial domain and frequency domain-based procedures. Omnipresent surveillance camera footages are increasing exponentially due course the time. Monitoring all the events manually is an insignificant and more time-consuming process. Therefore, an automated rare event detection contrivance is required to make this process manageable. In this work, a Context-Free Grammar (CFG) is developed for detecting rare events from a video stream and Artificial Neural Network (ANN) is used to train CFG. A set of dedicated algorithms are used to perform frame split process, edge detection, background subtraction and convert the processed data into CFG. The developed CFG is converted into nodes and edges to form a graph. The graph is given to the input layer of an ANN to classify normal and rare event classes. Graph derived from CFG using input video stream is used to train ANN Further the performance of developed Artificial Neural Network Based Context-Free Grammar – Rare Event Detection (ACFG-RED) is compared with other existing techniques and performance metrics such as accuracy, precision, sensitivity, recall, average processing time and average processing power are used for performance estimation and analyzed. Better performance metrics values have been observed for the ANN-CFG model compared with other techniques. The developed model will provide a better solution in detecting rare events using video streams.

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