59 research outputs found
Constitutive models for the prediction of the hot deformation behavior of the 10%Cr steel alloy
The aim of this paper is to establish a reliable model that provides the best fit to the specific behavior of the flow stresses of the 10%Cr steel alloy at the time of hot deformation. Modified Johnson-Cook and strain-compensated Arrhenius-type (phenomenological models), in addition to two Artificial Neural Network (ANN) models were established with the view toward investigating their stress prediction performances. The ANN models were trained using Scaled Conjugate Gradient (SCG) and Levenberg-Marquardt (LM) algorithms. The prediction accuracy of the established models was evaluated using the following well-known statistical parameters: (a) correlation coefficient (R), (b) Average Absolute Relative Error (AARE), (c) Root Mean Squared Error (RMSE), and Relative Error (RE). The results showed that both of the modified Johnson-Cook and strain-compensated Arrhenius models could not competently predict the flow behavior. On the contrary, the results indicated that the two proposed ANN models precisely predicted the flow stress values and that the LM-trained ANN provided a superior performance over the SCG-trained model, as it yielded an RMSE of as low as 0.441 MPa. - 2019 by the authors
Theoretical analysis of the spatial variability in tillage forces for fatigue analysis of tillage machines
This paper presents a new theoretical model to describe the spatial variability
in tillage forces for the purpose of fatigue analysis of tillage machines. The
proposed model took into account both the variability in tillage system
parameters (soil engineering properties, tool design parameters and operational
conditions) and the cyclic effects of mechanical behavior of the soil during
failure ahead of tillage tools on the spatial variability in tillage forces. The
stress-based fatigue life approach was used to determine the life time of
tillage machines, based on the fact that the applied stress on tillage machines
is primarily within the elastic range of the material. Stress cycles with their
mean values and amplitudes were determined by the rainflow algorithm. The damage
friction caused by each cycle of stress was computed according to the Soderberg
criterion and the total damage was calculated by the Miner's law. The proposed
model was applied to determine the spatial variability in tillage forces on the
shank of a chisel plough. The equivalent stress history resulted from these
forces were calculated by means of a finite element model and the Von misses
criterion. The histograms of mean stress and stress amplitude obtained by the
rainflow algorithm showed significant dispersions. Although the equivalent
stress is smaller than the yield stress of the material, the failure by fatigue
will occur after a certain travel distance. The expected distance to failure was
found to be df=0.825×106km. It is concluded that the spatial variability in
tillage forces has significant effect on the life time of tillage machines and
should be considered in the design analysis of tillage machines to predict the
life time. Further investigations are required to correlate the results achieved
by the proposed model with field tests and to validate the proposed assumptions
to model the spatial variability in tillage force
Reliability-based design optimization of shank chisel plough using optimum safety factor strategy
Reliability integration into tillage machine design process is a new strategy to overcome the drawbacks of
classical design approaches and to achieve designs with a required reliability level. Furthermore, design
optimization of soil tillage equipments under uncertainty seeks to design structures which should be
both economic and reliable. The originality of this research is to develop an efficient methodology that
controls the reliability levels for complex statistical distribution cases of random tillage forces. This
developed strategy is based on design sensitivity concepts in order to determine the influence of each
random parameter. The application of this method consists in taking into account the uncertainties on
the soil tillage forces. The tillage forces are calculated in accordance with analytical model of McKyes
and Ali with some modifications to include the effect of both soil–metal adhesion and tool speed. The
different developments and applications show the importance of the developed method to improve
the performance of the soil tillage equipments considering both random geometry and loading parameters.
The developed method so-called OSF (Optimum Safety Factor) can satisfy a required reliability level
without additional computing time relative to the deterministic design optimization study. Since the
agricultural equipment parameters are extremely nonlinear, we extended the OSF approach to several
nonlinear probabilistic distributions such as lognormal, uniform, Weibull and Gumbel probabilistic
distribution laws
Integration of multi-objective structural optimization into cementless hip prosthesis design : Improved Austin-Moore model
A new strategy of multi-objective structural optimization is integrated into Austin-Moore prosthesis in order to improve its performance. The new resulting model is so-called Improved Austin-Moore. The topology optimization is considered as a conceptual design stage to sketch several kinds of hollow stems according to the daily loading cases. The shape optimization presents the detailed design stage considering several objectives. Here, A new multiplicative formulation is proposed as a performance scale in order to define the best compromise between several requirements. Numerical applications on 2D and 3D problems are carried out to show the advantages of the proposed model
Estimating the variability of tillage forces on a chisel plough shank by modeling the variability of tillage system parameters
In this paper, a probabilistic approach is proposed for quantifying the
variability of the tillage forces for the shank of a chisel plough with narrow
tines and to estimate the failure probability. An existing three-dimensional
analytical model of tool forces from McKyes was used to model the interaction
between the tillage tools and the soil. The variability of tillage forces was
modeled, taking into account the variability of soil engineering properties,
tool design parameters and operational conditions. The variability of the soil
engineering properties was modeled by means of experimental observations. The
dispersion effect of each tillage system parameter on the tillage forces was
determined by a sensitivity analysis. The results show that the variability of
the horizontal and vertical forces follows a lognormal distribution (μ=0.872,
ξ=0.449; μ=0.004, ξ=0.447) and the relationship between these forces is positive
and quasi-linear (ρ(PH,Pv)=0.93).This lognormal variability was integrated into
the estimation of the failure probability for the shank by using Monte Carlo
simulation (MCS) and the first-order reliability method (FORM). The results
obtained by these two methods, with the assumption of non-correlation between
the horizontal and vertical forces, were almost identical. However, the FORM
method was faster and simpler, compared to the MCS technique. Furthermore, the
correlation between the horizontal and vertical forces has no significant effect
on the failure probability, regardless of the correlation strength. Therefore,
it is concluded that the FORM method can be used to estimate the failure
probability without considering the correlation between horizontal and vertical
f
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