scholarly journals Sensitivity of a Subject-specific Ankle Sprain Simulation to Extrinsic Versus Intrinsic Biomechanical Factors

2021 ◽  
Vol 9 ◽  
Author(s):  
Adam J. Yoder ◽  
Anthony J. Petrella ◽  
Shawn Farrokhi
Keyword(s):  
Monte Carlo ◽  
Ankle Sprain ◽  
Deterministic Model ◽  
Mean Value ◽  
Ankle Sprains ◽  
Probabilistic Simulation ◽  
Subject Specific ◽  
Advanced Mean Value ◽  
Mean Value Method ◽  
Biomechanical Factors

Ankle sprains are the most common musculoskeletal injury in sport and military activity, despite existing prophylactic strategies. The purpose of this report was to develop a probabilistic simulation of lateral ankle sprains during single-limb drop landing, towards accelerating innovation in ankle sprain prevention. A deterministic, subject-specific musculoskeletal model was extended with automation and probabilistic distributions on sprain-related biomechanical factors. Probabilistic simulations were generated using traditional Monte Carlo techniques and the advanced mean value method, a more computationally-efficient approach. Predicted distributions of peak ankle joint rotations, velocities, and moments borne by supporting passive structures agreed favorably with the deterministic model and with reports of real sprain biomechanics. Parameter sensitivities identified that predictions were most strongly influenced by drop height, subtalar joint posture at contact, invertor/evertor co-activation, and passive ankle stiffness. The advanced mean value method predicted confidence bounds comparable to a 1000-trial Monte Carlo simulation, and required only 14 model evaluations and 4-min processing time. The extended probabilistic simulation may be useful to virtually test new prophylactic strategies for ankle sprains, and is made available for open-source use (https://simtk.org/projects/sprain-sim).

Design Optimization of Hierarchically Decomposed Multilevel Systems Under Uncertainty

2005 ◽  
Vol 128 (2) ◽  
pp. 503-508 ◽  
Author(s):  
Michael Kokkolaras ◽  
Zissimos P. Mourelatos ◽  
Panos Y. Papalambros
Keyword(s):  
Design Optimization ◽  
Uncertainty Propagation ◽  
Mean Value ◽  
Multilevel Systems ◽  
System A ◽  
Engine Design ◽  
Advanced Mean Value ◽  
Mean Value Method ◽  
Propagation Technique ◽  
Bottom To Top

This paper presents a methodology for design optimization of hierarchically decomposed systems under uncertainty. We propose an extended, probabilistic version of the deterministic analytical target cascading (ATC) formulation by treating uncertain quantities as random variables and posing probabilistic design constraints. A bottom-to-top coordination strategy is used for the ATC process. Given that first-order approximations may introduce unacceptably large errors, we use a technique based on the advanced mean value method to estimate uncertainty propagation through the multilevel hierarchy of elements that comprise the decomposed system. A simple yet illustrative hierarchical bilevel engine design problem is used to demonstrate the proposed methodology. The results confirm the applicability of the proposed probabilistic ATC formulation and the accuracy of the uncertainty propagation technique.

Structural/Acoustic Sensitivity Analysis of a Panel With Manufacturing Variability

2002 ◽  
Author(s):  
Sameer B. Mulani ◽  
Michael J. Allen
Keyword(s):  
Sensitivity Analysis ◽  
Mean Value ◽  
Design Parameters ◽  
Sound Power ◽  
Deterministic System ◽  
Acoustic Response ◽  
Element Analysis ◽  
Advanced Mean Value ◽  
Mean Value Method ◽  
Acoustic Sensitivity

Sensitivity analysis is an essential component in the design of structural/acoustic systems. Current structural/acoustic sensitivity algorithms assume deterministic system design parameters and therefore predict changes in the deterministic response of the system. Due to variability associated with manufacturing tolerances most structural/acoustic systems consist of random and deterministic structural design parameters and therefore produce a probabilistic acoustic response. In this work, a structural/acoustic sensitivity algorithm is presented that considers systems comprised of random and deterministic design parameters. The new sensitivity algorithm calculates the change in the probabilistic vibro-acoustic response of a system due to a change in a deterministic design parameter. The new algorithm uses boundary element analysis, finite element analysis, and an advanced mean value method. An elastically supported panel subject to a non-uniform load is used to illustrate the algorithm. Variability is considered in the elastic support while structural sizing parameters are taken to be deterministic. The response of the panel is defined in terms of probabilistic radiated sound power. Probabilistic sound power sensitivity results are calculated and used to predict new sound power values via finite difference analysis. These results are compared successfully to results obtained through re-analysis.

Numerical Probabilistic Analysis of Structural/Acoustic Systems

2001 ◽  
Author(s):  
Michael Allen ◽  
Nickolas Vlahopoulos
Keyword(s):  
Probabilistic Analysis ◽  
Mean Value ◽  
Cumulative Distribution ◽  
Acoustic Response ◽  
Element Analysis ◽  
Performance Function ◽  
The Difference ◽  
Advanced Mean Value ◽  
Mean Value Method ◽  
Viable Method

Abstract A formulation that accounts for manufacturing variability in the analysis of structural/acoustic systems is presented. The methodology incorporates the concept of fast probability integration with finite element (FEA) and boundary element analysis (BEA) for producing the probabilistic acoustic response of a structural/acoustic system. The advanced mean value method is used for integrating the system probability density function. FEA and BEA are combined for producing the acoustic response that constitutes the performance function. The probabilistic acoustic response is calculated in terms of a cumulative distribution function. The new methodology is used to illustrate the difference between the results from a probabilistic analysis that accounts for manufacturing uncertainty, and an equivalent deterministic simulation through applications. The probabilistic computations are validated by comparison to Monte Carlo simulations. Based on its computational efficiency and its accuracy the new methodology is concluded to be a viable method of calculating numerically the probabilistic response of structural/acoustic systems due to manufacturing variability.

Rigorous time-domain analysis of statistically oriented graphene sheet fluctuations

2017 ◽  
Vol 36 (5) ◽  
pp. 1351-1363 ◽  
Author(s):  
Athanasios N. Papadimopoulos ◽  
Stamatios A. Amanatiadis ◽  
Nikolaos V. Kantartzis ◽  
Theodoros T. Zygiridis ◽  
Theodoros D. Tsiboukis
Keyword(s):  
Monte Carlo ◽  
Standard Deviation ◽  
Finite Difference ◽  
Surface Waves ◽  
Time Domain ◽  
Finite Difference Time Domain ◽  
Mean Value ◽  
Content Type ◽  
The Mean ◽  
Difference Time

Purpose Important statistical variations are likely to appear in the propagation of surface plasmon polariton waves atop the surface of graphene sheets, degrading the expected performance of real-life THz applications. This paper aims to introduce an efficient numerical algorithm that is able to accurately and rapidly predict the influence of material-based uncertainties for diverse graphene configurations. Design/methodology/approach Initially, the surface conductivity of graphene is described at the far infrared spectrum and the uncertainties of its main parameters, namely, the chemical potential and the relaxation time, on the propagation properties of the surface waves are investigated, unveiling a considerable impact. Furthermore, the demanding two-dimensional material is numerically modeled as a surface boundary through a frequency-dependent finite-difference time-domain scheme, while a robust stochastic realization is accordingly developed. Findings The mean value and standard deviation of the propagating surface waves are extracted through a single-pass simulation in contrast to the laborious Monte Carlo technique, proving the accomplished high efficiency. Moreover, numerical results, including graphene’s surface current density and electric field distribution, indicate the notable precision, stability and convergence of the new graphene-based stochastic time-domain method in terms of the mean value and the order of magnitude of the standard deviation. Originality/value The combined uncertainties of the main parameters in graphene layers are modeled through a high-performance stochastic numerical algorithm, based on the finite-difference time-domain method. The significant accuracy of the numerical results, compared to the cumbersome Monte Carlo analysis, renders the featured technique a flexible computational tool that is able to enhance the design of graphene THz devices due to the uncertainty prediction.

scholarly journals Predictive Factors of Recovery after an Acute Lateral Ankle Sprain: A Longitudinal Study

Sports ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 41
Author(s):  
Philippe Terrier ◽  
Sébastien Piotton ◽  
Ilona M. Punt ◽  
Jean-Luc Ziltener ◽  
Lara Allet
Keyword(s):  
Ankle Sprain ◽  
Strength Function ◽  
Selection Procedure ◽  
Ankle Sprains ◽  
Lateral Ankle Sprain ◽  
Lateral Ankle ◽  
Functional Scores ◽  
Logistic Regressions ◽  
Poor Outcomes ◽  
Clinical Measures

A prominent feature of ankle sprains is their variable clinical course. The difficulty of providing a reliable early prognosis may be responsible for the substantial rate of poor outcomes after an ankle sprain. The aim of the present study was to evaluate the prognostic value of objective clinical measures, pain, and functional scores for ankle sprain recovery. Fifty-two participants suffering from lateral ankle sprain were included. Sprain status was assessed four weeks following injury and included evaluations of ankle range of motion, strength, function, and pain. Seven months following injury, a second assessment classified the patients into recovered and non-recovered groups using ankle ability measures. Following a predictor pre-selection procedure, logistic regressions evaluated the association between the four-week predictors and the seven-month recovery status. Twenty-seven participants (52%) fully recovered and 25 did not (48%). The results of the logistic regressions showed that walking pain was negatively associated with the probability of recovering at seven months (odds ratio: 0.71, 95% CI: 0.53–0.95). Pain four weeks after ankle sprain had relevant predictive value for long-term recovery. Special attention should be paid to patients reporting persistent pain while walking four weeks following sprain to reduce the risk of chronicity.

scholarly journals A Mean Extragradient Method for Solving Variational Inequalities

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 462
Author(s):  
Apichit Buakird ◽  
Nimit Nimana ◽  
Narin Petrot
Keyword(s):  
Hilbert Space ◽  
Variational Inequality ◽  
Weak Convergence ◽  
Numerical Experiments ◽  
Variational Inequality Problem ◽  
Extragradient Method ◽  
Mean Value ◽  
Inequality Problem ◽  
The Mean ◽  
Mean Value Method

We propose a modified extragradient method for solving the variational inequality problem in a Hilbert space. The method is a combination of the well-known subgradient extragradient with the Mann’s mean value method in which the updated iterate is picked in the convex hull of all previous iterates. We show weak convergence of the mean value iterate to a solution of the variational inequality problem, provided that a condition on the corresponding averaging matrix is fulfilled. Some numerical experiments are given to show the effectiveness of the obtained theoretical result.

Some Important Issues on First-Order Reliability Analysis With Nonprobabilistic Convex Models

2014 ◽  
Vol 136 (3) ◽  
Author(s):  
C. Jiang ◽  
G. Y. Lu ◽  
X. Han ◽  
R. G. Bi
Keyword(s):  
Reliability Analysis ◽  
Reliability Index ◽  
Probability Model ◽  
Mean Value ◽  
Convex Model ◽  
First Order ◽  
Reliability Method ◽  
Complex Engineering ◽  
Mean Value Method ◽  
Form Type

Compared with the probability model, the convex model approach only requires the bound information on the uncertainty, and can make it possible to conduct the reliability analysis for many complex engineering problems with limited samples. Presently, by introducing the well-established techniques in probability-based reliability analysis, some methods have been successfully developed for convex model reliability. This paper aims to reveal some different phenomena and furthermore some severe paradoxes when extending the widely used first-order reliability method (FORM) into the convex model problems, and whereby provide some useful suggestions and guidelines for convex-model-based reliability analysis. Two FORM-type approximations, namely, the mean-value method and the design-point method, are formulated to efficiently compute the nonprobabilistic reliability index. A comparison is then conducted between these two methods, and some important phenomena different from the traditional FORMs are summarized. The nonprobabilistic reliability index is also extended to treat the system reliability, and some unexpected paradoxes are found through two numerical examples.

scholarly journals Evaluation of Bearing Capacity of Strip Footing Using Random Layers Concept

2015 ◽  
Vol 37 (3) ◽  
pp. 31-39 ◽  
Author(s):  
Marek Kawa ◽  
Dariusz Łydżba
Keyword(s):  
Monte Carlo ◽  
Bearing Capacity ◽  
Failure Mechanism ◽  
Design Theory ◽  
Cohesive Soil ◽  
Probability Of Failure ◽  
Mean Value ◽  
Strip Footing ◽  
Random Field Theory ◽  
The Mean

Abstract The paper deals with evaluation of bearing capacity of strip foundation on random purely cohesive soil. The approach proposed combines random field theory in the form of random layers with classical limit analysis and Monte Carlo simulation. For given realization of random the bearing capacity of strip footing is evaluated by employing the kinematic approach of yield design theory. The results in the form of histograms for both bearing capacity of footing as well as optimal depth of failure mechanism are obtained for different thickness of random layers. For zero and infinite thickness of random layer the values of depth of failure mechanism as well as bearing capacity assessment are derived in a closed form. Finally based on a sequence of Monte Carlo simulations the bearing capacity of strip footing corresponding to a certain probability of failure is estimated. While the mean value of the foundation bearing capacity increases with the thickness of the random layers, the ultimate load corresponding to a certain probability of failure appears to be a decreasing function of random layers thickness.

scholarly journals Incidence of Ankle Sprains Among Active-Duty Members of the United States Armed Services From 1998 Through 2006

2010 ◽  
Vol 45 (1) ◽  
pp. 29-38 ◽  
Author(s):  
Kenneth L. Cameron ◽  
Brett D. Owens ◽  
Thomas M. DeBerardino
Keyword(s):  
At Risk ◽  
Incidence Rate ◽  
Ankle Sprain ◽  
Military Service ◽  
Active Duty ◽  
Service Members ◽  
Ankle Sprains ◽  
Injury Patterns ◽  
The Us ◽  
Armed Services

Abstract Context: Ankle sprains have been reported as one of the most common injuries sustained by members of the US Armed Services. However, little is known about the incidence rate and injury patterns associated with ankle sprains in this population. Objective: To examine the incidence of ankle sprains among active-duty members of the US Armed Services from 1998 through 2006. A secondary objective was to describe the sex, age, and service-specific injury patterns in this young, physically active population. Design: Cohort study. Patients or Other Participants: All active-duty service members from the day they enter military service until the day they leave military service and US Army Reserve and National Guard service members during periods of active duty and mobilization. Main Outcome Measure(s): Injury data were extracted from the Defense Medical Epidemiological Database from 1998 through 2006. All data for ankle sprains, coded according to the International Classification of Diseases (9th revision), were included. Cases were limited to those injuries reported as first occurrences. Incidence rates (IRs) were calculated per 1000 person-years by sex, age, and service. Incidence rate ratios (IRRs) and 95% confidence intervals (95% CIs) were used to assess the strength of association between the incidence of ankle sprain and the independent variables of sex, age, and service. Results: From 1998 through 2006, 423 581 service members sustained ankle sprains and 12 118 863 person-years at risk to injury were documented in this population. The incidence rate was 34.95 (95% CI  =  34.85, 35.06) per 1000 person-years at risk. Females were 21% more likely (IRR  =  1.21, 95% CI  =  1.21, 1.23) to sustain an ankle sprain than males. Sex-specific IR varied by age and service. Differences in the rate of ankle sprains were also noted by age and service. Conclusions: The incidence of ankle sprains among US service members was 5 times greater than that previously reported in civilian population studies. Sex, age, and branch of military service are important factors related to the incidence of ankle sprains in this population.

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