Closed-Form Takeoff Weight Estimation Model for Air Transportation Simulation

2010 ◽  
Author(s):  
Hak-tae Lee ◽  
Gano Chatterji
Keyword(s):  
Closed Form ◽  
Air Transportation ◽  
Weight Estimation ◽  
Estimation Model ◽  
Transportation Simulation

scholarly journals Categorification of the Müller-Wichards System Performance Estimation Model: Model Symmetries, Invariants, and Closed Forms

Systems ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 6
Author(s):  
Allen D. Parks ◽  
David J. Marchette
Keyword(s):  
Closed Form ◽  
System Performance ◽  
Algebraic Method ◽  
Expressive Power ◽  
Computer Applications ◽  
Performance Estimation ◽  
Parallel Computer ◽  
Estimation Model ◽  
Data Movement ◽  
Fundamental Symmetry

The Müller-Wichards model (MW) is an algebraic method that quantitatively estimates the performance of sequential and/or parallel computer applications. Because of category theory’s expressive power and mathematical precision, a category theoretic reformulation of MW, i.e., CMW, is presented in this paper. The CMW is effectively numerically equivalent to MW and can be used to estimate the performance of any system that can be represented as numerical sequences of arithmetic, data movement, and delay processes. The CMW fundamental symmetry group is introduced and CMW’s category theoretic formalism is used to facilitate the identification of associated model invariants. The formalism also yields a natural approach to dividing systems into subsystems in a manner that preserves performance. Closed form models are developed and studied statistically, and special case closed form models are used to abstractly quantify the effect of parallelization upon processing time vs. loading, as well as to establish a system performance stationary action principle.

Estimation of Hemi-Abdominal-Based Free Flap Weight Using Two Computed Tomography-Derived Measurements

2021 ◽  
Author(s):  
Nicolas Greige ◽  
Bryce Liu ◽  
David Nash ◽  
Katie E. Weichman ◽  
Joseph A. Ricci
Keyword(s):  
Computed Tomography ◽  
Breast Reconstruction ◽  
Free Flap ◽  
Subcutaneous Tissue ◽  
Free Tissue Transfer ◽  
Absolute Error ◽  
Estimation Methods ◽  
Weight Estimation ◽  
Estimation Model ◽  
Split Sample

Abstract Background Accurate flap weight estimation is crucial for preoperative planning in microsurgical breast reconstruction; however, current flap weight estimation methods are time consuming. It was our objective to develop a parsimonious and accurate formula for the estimation of abdominal-based free flap weight. Methods Patients who underwent hemi-abdominal-based free tissue transfer for breast reconstruction at a single institution were retrospectively reviewed. Subcutaneous tissue thicknesses were measured on axial computed tomography angiograms at several predetermined points. Multivariable linear regression was used to generate the parsimonious flap weight estimation model. Split-sample validation was used to for internal validation. Results A total of 132 patients (196 flaps) were analyzed, with a mean body mass index of 31.2 ± 4.0 kg/m2 (range: 22.6–40.7). The mean intraoperative flap weight was 990 ± 344 g (range: 368–2,808). The full predictive model (R 2 = 0.68) estimated flap weight using the Eq. 91.3x + 36.4y + 6.2z – 1030.0, where x is subcutaneous tissue thickness (cm) 5 cm lateral to midline at the level of the anterior superior iliac spine (ASIS), y is distance (cm) between the skin overlying each ASIS, and z is patient weight (kg). Two-thirds split-sample validation was performed using 131 flaps to build a model and the remaining 65 flaps for validation. Upon validation, we observed a median percent error of 10.2% (interquartile range [IQR]: 4.5–18.5) and a median absolute error of 108.6 g (IQR: 45.9–170.7). Conclusion We developed and internally validated a simple and accurate formula for the preoperative estimation of hemi-abdominal-based free flap weight for breast reconstruction.

A conceptual wing-box weight estimation model for transport aircraft

2013 ◽  
Vol 117 (1191) ◽  
pp. 533-551 ◽  
Author(s):  
R. M. Ajaj ◽  
M. I. Friswell ◽  
D. Smith ◽  
A. T. Isikveren
Keyword(s):  
Error Estimate ◽  
Beam Theory ◽  
Average Error ◽  
Weight Estimation ◽  
Estimation Model ◽  
Transport Aircraft ◽  
Aeroelastic Analysis ◽  
Prediction Module ◽  
Weight Prediction ◽  
Wing Box

Abstract This paper presents an overview of an advanced, conceptual wing-box weight estimation and sizing model for transport aircraft. The model is based on linear thin-walled beam theory, where the wing-box is modelled as a simple, swept tapered multi-element beam. It consists of three coupled modules, namely sizing, aeroelastic analysis, and weight prediction. The sizing module performs generic wing-box sizing using a multi-element strategy. Three design cases are considered for each wing-box element. The aeroelastic analysis module accounts for static aeroelastic requirements and estimates their impact on the wing-box sizing. The weight prediction module estimates the wing-box weight based on the sizing process, including static aeroelastic requirements. The breakdown of the models into modules increases its flexibility for future enhancements to cover complex wing geometries and advanced aerospace materials. The model has been validated using five different transport aircraft. It has shown to be sufficiently robust, yielding an error bandwidth of ±3%, an average error estimate of -0·2%, and a standard error estimate of 1·5%.

Prediction of fetal macrosomia: effect of sonographic fetal weight-estimation model and threshold used

2011 ◽  
Vol 38 (1) ◽  
pp. 74-81 ◽  
Author(s):  
N. Melamed ◽  
Y. Yogev ◽  
I. Meizner ◽  
R. Mashiach ◽  
J. Pardo ◽  
...  
Keyword(s):  
Fetal Weight ◽  
Fetal Macrosomia ◽  
Weight Estimation ◽  
Estimation Model ◽  
Fetal Weight Estimation

scholarly journals Development of a weight-estimation model to use in pregnant criollo-type mares

2017 ◽  
Vol 48 (1) ◽  
Author(s):  
Patricia Soares Vieira ◽  
Carlos Eduardo Wayne Nogueira ◽  
Alice Correa Santos ◽  
Luciana de Araujo Borba ◽  
Rebeca Scalco ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Body Weight ◽  
Regression Model ◽  
Late Pregnancy ◽  
Alternative Methods ◽  
Abdominal Circumference ◽  
Weight Estimation ◽  
Estimation Model ◽  
Actual Weight ◽  
Estimation Formula

ABSTRACT: The aims of this study were: 1) to compare the tape weight and associated weight-estimation formula to evaluate weight gain in pregnant mares, and 2) to develop a mathematical model to estimate the weight of pregnant mares using body measurements. Thirty-four criollo-type mares were evaluated every two weeks during the middle and late pregnancy. The mares were weighed on a livestock scale, and we estimated body weight using tape weights and an associated body-weight estimation formula. Also, heart-girth circumference (heartgirth) and abdominal circumference were measured; the latter at the 12th intercostal space (12th ICS) and 18th rib (18th Rib), to use in a mathematical model to estimate the weight of pregnant mares. Observations were divided into three periods of pregnancy: 5th to 7 h month, 7th to 9 h month, and 9th to 11th month. Mares in late pregnancy showed an increase in actual weight and an increase in 12th ICS and 18th Rib measurements. Tape weight and body-weight estimation formula underestimated the weight of pregnant mares. However, the regression model using heart-girth circumference, 12th ICS, and 18th Rib measurements showed high correlation (r2 = 0.87, P<0.001) with actual weight. Finally, the alternative methods usually used in horses are not accurate to estimate body weight in pregnant mares. In conclusion, the regression model Y=-540.143 + (heartgirth x 3.068) + (12th ICS x 1.278) + (18th Rib x 0.944) can be used to estimate body weight in pregnant mares from the 5th to 11th months of pregnancy.

scholarly journals Analysis of surveillance position error for airfield detection

2018 ◽  
Vol 90 (6) ◽  
pp. 962-966
Author(s):  
SungKwan Ku ◽  
Hojong Baik ◽  
Taehyoung Kim
Keyword(s):  
Traffic Control ◽  
Practical Method ◽  
Air Transportation ◽  
Relevant Information ◽  
Surveillance Systems ◽  
Trajectory Data ◽  
Content Type ◽  
Position Errors ◽  
Simulation Engine ◽  
Transportation Simulation

Purpose The surveillance equipment is one of the most important parts for current air traffic control systems. It provides aircraft position and other relevant information including flight parameters. However, the existing surveillance equipment has certain position errors between true and detected positions. Operators must understand and account for the characteristics on magnitude and frequency of the position errors in the surveillance systems because these errors can influence the safety of aircraft operation. This study aims to develop the simulation model for analysis of these surveillance position errors to improve the safety of aircrafts in airports. Design/methodology/approach This study investigates the characterization of the position errors observed in airport surface detection equipment of an airport ground surveillance system and proposes a practical method to numerically reproduce the characteristics of the errors. Findings The proposed approach represents position errors more accurately than an alternative simple approach. This study also discusses the application of the computational results in a microscopic simulation modeling environment. Practical implications The surveillance error is analyzed from the radar trajectory data, and a random generator is configured to implement these data. These data are used in the air transportation simulation through an application programing interface, which can be applied to the aircraft trajectory data in the simulation. Subsequently, additionally built environment data are used in the actual simulation to obtain the results from the simulation engine. Originality/value The presented surveillance error analysis and simulation with its implementation plan are expected to be useful for air transportation safety simulations.

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