Accurate bolus arrival time estimation using piecewise linear model fitting

2017 ◽  
Author(s):  
Elhassan Abdou ◽  
Johan de Mey ◽  
Mark De Ridder ◽  
Jef Vandemeulebroucke
Keyword(s):  
Linear Model ◽  
Arrival Time ◽  
Piecewise Linear ◽  
Model Fitting ◽  
Time Estimation ◽  
Piecewise Linear Model ◽  
Bolus Arrival Time

scholarly journals Piecewise linear model of self-organized hierarchy formation

2020 ◽  
Vol 102 (3) ◽  
Author(s):  
Tomoshige Miyaguchi ◽  
Takamasa Miki ◽  
Ryota Hamada
Keyword(s):  
Linear Model ◽  
Piecewise Linear ◽  
Self Organized ◽  
Piecewise Linear Model ◽  
Hierarchy Formation

scholarly journals Effect of Mean Stress on the Fatigue Life Prediction of Notched Fiber-Reinforced 2060 Al-Li Alloy Laminates under Spectrum Loading

2018 ◽  
Vol 2018 ◽  
pp. 1-16
Author(s):  
Weiying Meng ◽  
Liyang Xie ◽  
Yu Zhang ◽  
Yawen Wang ◽  
Xiaofang Sun ◽  
...  
Keyword(s):  
Fatigue Life ◽  
Linear Model ◽  
Life Prediction ◽  
Piecewise Linear ◽  
Forecast Accuracy ◽  
Cyclic Stress ◽  
Fatigue Life Prediction ◽  
Fiber Reinforced ◽  
Piecewise Linear Model ◽  
Spectrum Loading

This paper presents a study on the fatigue life prediction of notched fiber-reinforced 2060 Al-Li alloy laminates under spectrum loading by applying the constant life diagram. Firstly, a review on the state of the art of constant life diagram models for the life prediction of composite materials is given, which highlights the effect on the forecast accuracy. Then, the fatigue life of notched fiber-reinforced Al-Li alloy laminates (2/1 laminates and 3/2 laminates) is tested under cyclic stress, which has different stress cycle characteristics (constant amplitude loading and Mini-Twist spectrum loading). The introduced models are successfully realized based on the available experimental data of examined laminates. In the case of Mini-Twist spectrum loading, the effect of the constant life diagram on the life prediction accuracy of examined laminates is studied based on the rainflow-counting method and Miner damage criteria. The results show that the simple Goodman model and piecewise linear model have certain advantages compared to other complex models for the life prediction of notched fiber metal laminates with different structures under Mini-Twist loading. From the engineering perspective, the S-N curve prediction based on the piecewise linear model is most applicable and accurate among all the models.

scholarly journals Retrieval of Sea Surface Wind Fields Using Multi-Source Remote Sensing Data

2020 ◽  
Vol 12 (9) ◽  
pp. 1482 ◽  
Author(s):  
Tangao Hu ◽  
Yue Li ◽  
Yao Li ◽  
Yiyue Wu ◽  
Dengrong Zhang
Keyword(s):  
Linear Model ◽  
Temporal Resolution ◽  
Science Studies ◽  
Piecewise Linear ◽  
Surface Wind ◽  
Sea Surface ◽  
Mean Bias Error ◽  
High Temporal Resolution ◽  
Sea Surface Wind ◽  
Piecewise Linear Model

Timely and accurate sea surface wind field (SSWF) information plays an important role in marine environmental monitoring, weather forecasting, and other atmospheric science studies. In this study, a piecewise linear model is proposed to retrieve SSWF information based on the combination of two different satellite sensors (a microwave scatterometer and an infrared scanning radiometer). First, the time series wind speed dataset, extracted from the HY-2A satellite, and the brightness temperature dataset, extracted from the FY-2E satellite, were matched. The piecewise linear regression model with the highest R2 was then selected as the best model to retrieve SSWF information. Finally, experiments were conducted with the Usagi, Fitow, and Nari typhoons in 2013 to evaluate accuracy. The results show that: (1) the piecewise linear model is successfully established for all typhoons with high R2 (greater than 0.61); (2) for all three cases, the root mean square error () and mean bias error (MBE) are smaller than 2.2 m/s and 1.82 m/s, which indicates that it is suitable and reliable for SSWF information retrieval; and (3) it solves the problem of the low temporal resolution of HY-2A data (12 h), and inherits the high temporal resolution of the FY-2E data (0.5 h). It can provide reliable and high temporal SSWF products.

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