Probabilistic study of the strength of steel scaffold systems

Alcohol is a toxic substance associated with acute and chronic disorders affecting the Central Nervous System and significantly altering brain function. Objective: To determine the relationship between cognitive impairment and alcohol consumption in university students of the Juárez University of the State of Durango. Methodology: It is a cross-sectional, descriptive, comparative, non-probabilistic study, for convenience. A database was designed on the results obtained in a clinical interview on alcohol consumption and the application of the Montreal Cognitive Assessment (MoCA) test. Contribution: The evaluation of cognitive functions show similar results, the male sex presented a better score in Attention and the female one in Orientation. More involvement was identified in the Deferred Memory functions in both groups. In relation to alcohol consumption, the cognitive functions evaluated show lower levels. The female gender was more evident cognitive impairment in relation to alcohol consumption being statistically significant (p <0.025). Alcohol consumption is a risky behavior that deserves to be recognized by the main actors about neurocognitive effects. Alcohol consumption prevention programs and cognitive diagnostic tools are appropriate strategies to reduce risk behaviors in mental health.

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A probabilistic study of the influence of parameter uncertainty on thermal radiation heat transfer

International Journal of Heat and Mass Transfer ◽

10.1016/j.ijheatmasstransfer.2009.12.004 ◽

2010 ◽

Vol 53 (7-8) ◽

pp. 1461-1472 ◽

Cited By ~ 10

Author(s):

M.M.R. Williams

Keyword(s):

Heat Transfer ◽

Thermal Radiation ◽

Parameter Uncertainty ◽

Radiation Heat Transfer ◽

Radiation Heat ◽

Probabilistic Study

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Probabilistic study of well capture zones distribution at the Lauswiesen field site

Journal of Contaminant Hydrology ◽

10.1016/j.jconhyd.2006.06.005 ◽

2006 ◽

Vol 88 (1-2) ◽

pp. 92-118 ◽

Cited By ~ 50

Author(s):

M. Riva ◽

L. Guadagnini ◽

A. Guadagnini ◽

T. Ptak ◽

E. Martac

Keyword(s):

Field Site ◽

Capture Zones ◽

Probabilistic Study

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Probabilistic Study of Tensile and Flexure Properties of Untreated Jute Fiber Reinforced Polyester Composite

Materials Today Proceedings ◽

10.1016/j.matpr.2017.08.066 ◽

2017 ◽

Vol 4 (10) ◽

pp. 11050-11055 ◽

Cited By ~ 3

Author(s):

A.P. Abhishek ◽

B.S. Keerthi Gowda ◽

G.L. Easwara Prasad ◽

R. Velmurugan

Keyword(s):

Jute Fiber ◽

Fiber Reinforced ◽

Polyester Composite ◽

Probabilistic Study

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Effect of Manufacturing Variability on Turbine Engine Performance: A Probabilistic Study

Volume 7A: Structures and Dynamics ◽

10.1115/gt2013-95145 ◽

2013 ◽

Cited By ~ 2

Author(s):

Michael Gorelik ◽

Jacob Obayomi ◽

Jack Slovisky ◽

Dan Frias ◽

Howie Swanson ◽

...

Keyword(s):

Performance Metrics ◽

Model Development ◽

Engine Performance ◽

Performance Model ◽

Probabilistic Methods ◽

System Level ◽

Turbine Engine ◽

Probabilistic Study ◽

Blade Geometry

While turbine engine Original Equipment Manufacturers (OEMs) accumulated significant experience in the application of probabilistic methods (PM) and uncertainty quantification (UQ) methods to specific technical disciplines and engine components, experience with system-level PM applications has been limited. To demonstrate the feasibility and benefits of an integrated PM-based system, a numerical case study has been developed around the Honeywell turbine engine application. The case study uses experimental observations of engine performance such as horsepower and fuel flow from a population of engines. Due to manufacturing variability, there are unit-to-unit and supplier-to-supplier variations in compressor blade geometry. Blade inspection data are available for the characterization of these geometric variations, and CFD analysis can be linked to the engine performance model, so that the effect of blade geometry variation on system-level performance characteristics can be quantified. Other elements of the case study included the use of engine performance and blade geometry data to perform Bayesian updating of the model inputs, such as efficiency adders and turbine tip clearances. A probabilistic engine performance model was developed, system-level sensitivity analysis performed, and the predicted distribution of engine performance metrics was calibrated against the observed distributions. This paper describes the model development approach and key simulation results. The benefits of using PM and UQ methods in the system-level framework are discussed. This case study was developed under Defense Advanced Research Projects Agency (DARPA) funding which is gratefully acknowledged.

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Probabilistic Model of Surface Crack on the Lumbar Vertebra

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.471.299 ◽

2013 ◽

Vol 471 ◽

pp. 299-305

Author(s):

A. Zulkifli ◽

Ahmad K. Ariffin ◽

M.R.M. Akramin

Keyword(s):

Finite Element Method ◽

Surface Crack ◽

Maximum Stress ◽

Crack Path ◽

Lumbar Vertebra ◽

Crack Size ◽

Probability Of Failure ◽

Biological Models ◽

Probabilistic Study ◽

Model Components

The objectives of this study are to determine the stress intensity factor (SIF) for different surface crack size of the lumbar vertebra and the probability of failure associated with finite element method. In this work, all the model components were meshed using the tetrahedral solid element. In order to simplify the model, all the spinal components were modeled as an isotropic and elastic material. Monte Carlo Simulation (MCS) technique was performed to conduct the probabilistic analysis using a probabilistic module in ANSYS with attempt for 100 trials. The results are observed that the maximum SIF were found in the end of crack path with 0.53 MPa.m1/2 and the corresponding probability of failure for the model is 1.22%. Sensitivity analysis had been revealed that the crack size was sensitive to the maximum stress and maximum SIF output parameters with correlation 0.989 and 0.811 respectively. The current probabilistic study is useful as a tool to understand the inherent uncertainties and variations in biological models.

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A Probabilistic Study of the Fatigue Behaviour of Improved Tubular Bridge Joints

Life-Cycle Performance of Deteriorating Structures ◽

10.1061/40707(240)22 ◽

2003 ◽

Author(s):

S. S. Walbridge ◽

A. Nussbaumer

Keyword(s):

Fatigue Behaviour ◽

Bridge Joints ◽

Probabilistic Study

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Mistuning Modeling and its Validation for Small Turbine Wheels

Volume 7B: Structures and Dynamics ◽

10.1115/gt2013-94019 ◽

2013 ◽

Cited By ~ 2

Author(s):

David Hemberger ◽

Dietmar Filsinger ◽

Hans-Jörg Bauer

Keyword(s):

Amplification Factor ◽

Numerical Models ◽

Lower Sensitivity ◽

Fe Model ◽

Mode Localization ◽

Geometric Deviations ◽

Probabilistic Study ◽

Calculated Amplitude ◽

Amplitude Amplification ◽

The Ideal

The production of bladed structures, e.g. turbine and compressor wheels, is a subject of statistical scatter. The blades are designed to be identical but differ due to small manufacturing tolerances. This so called mistuning can lead to increased vibration amplitudes compared to the ideal tuned case. The object of this study is to create and validate numerical models to evaluate such mistuning effects of turbine wheels for automotive turbocharger applications. As a basis for the numerical analysis vibration measurements under stand-still conditions were carried out by using a laser surface velocimeter (LSV). The scope of this investigation was to identify the mistuning properties of the turbine wheels namely the frequency deviation from the ideal, cyclic symmetrical tuned system. Experimental modal analyses as well as blade by blade measurements were performed. Moreover 3D scanning techniques were employed to determine geometric deviations. Numerical FE models and a simplified multi degree of freedom model (EBM) were created to reproduce the measured mistuning effects. The prediction of mode localization and the calculated amplitude amplification were evaluated. The best results were obtained with a FE model that employs individual sectorial stiffnesses. The results also indicate that the major contribution to mistuning is made by material inhomogeneities and not by geometric deviations from ideal dimensions. With the adjusted FE model a probabilistic study has been performed to investigate the influence of the mistuning on the amplitude amplification factor. It has been found that at a certain level of mistuning the amplification factor remains constant or slightly decreases. By introducing intentional mistuning a lower sensitivity as well as a decrease of the amplitude amplification could be achieved.

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