scholarly journals Fatigue Reliability Assessment of an Automobile Coil Spring under Random Strain Loads Using Probabilistic Technique

Metals ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 12 ◽  
Author(s):  
Reza Manouchehrynia ◽  
Shahrum Abdullah ◽  
Salvinder Singh Karam Singh
Keyword(s):  
Fatigue Life ◽  
Probabilistic Model ◽  
Probabilistic Method ◽  
Gumbel Distribution ◽  
Experimental Tests ◽  
Information Criterion ◽  
Model Parameters ◽  
Coil Spring ◽  
Fatigue Reliability ◽  
Mean Square Errors

This paper presents a mathematical model to estimate strain-life probabilistic modeling based on the fatigue reliability prediction of an automobile coil spring under random strain loads. The proposed technique was determined using a probabilistic method of the Gumbel distribution for strain-life models of automobile suspension systems. Strain signals from different road excitations in experimental tests were measured. The probability density function of the Gumbel distribution was considered to estimate model parameters using maximum likelihood estimation (MLE). The Akaike information criterion (AIC) method was performed to specify which model can estimate the best fit model parameters. Results demonstrated a good agreement between the predicted fatigue lives of the proposed probabilistic model and the measured strain fatigue life models. The root-mean-square errors (RMSE) based on the Coffin–Manson, Morrow, and Smith–Watson–Topper strain-life models were approximately 0.00114, 0.00107, and 0.00509, respectively, indicating a high correlation with the proposed model and experimental data. The results demonstrated that the proposed probabilistic model is effective for the fatigue life prediction of automobile coil springs using strain and stress fatigue life approaches.

Reliability-based fatigue life of vehicle spring under random loading

2019 ◽  
Vol 10 (5) ◽  
pp. 737-748 ◽  
Author(s):  
Reza Manouchehry Nya ◽  
Shahrum Abdullah ◽  
Salvinder Singh Karam Singh
Keyword(s):  
Fatigue Life ◽  
Life Prediction ◽  
Reliability Assessment ◽  
Fatigue Life Prediction ◽  
Coil Spring ◽  
Fatigue Reliability ◽  
Random Loading ◽  
Content Type ◽  
Road Surfaces ◽  
Road Data

Purpose The purpose of this paper is to analyse fatigue-life prediction based on a reliability assessment for coil springs of vehicle suspension systems using different road excitations under random loading. Design/methodology/approach In this study, a reliability assessment was conducted to predict the fatigue life of an automobile coil spring during different road data surfaces. Campus, urban and highway road surfaces were considered to capture fatigue load strain histories using a data acquisition system. Random loadings are applied on top of a coil spring where coil is fixed from down. Fatigue reliability was established as a system of correlated events during the service life to predict the probability of fatigue life using Coffin–Manson, Morrow and Smith–Watson–Topper (SWT) models. Findings Fatigue-life prediction based on a reliability assessment revealed that the Morrow model can predict a safe region of a life data point for the three road surfaces. Highway road data indicated the highest rate of reliability at 0.8 for approximately 1.69 × 105 cycles for the SWT model. Originality/value Reliability assessment of the fatigue life of vehicle coil springs is vital for safe operation. The reliability analysis of a coil spring under random loading excitations can be used for fatigue-life prediction.

scholarly journals Probabilistic fatigue life prediction of metallic components based on continuum damage mechanics

2021 ◽  
Vol 39 (2) ◽  
pp. 326-333
Author(s):  
Xiaoran Liu ◽  
Qin Sun
Keyword(s):  
Fatigue Life ◽  
Fatigue Test ◽  
Damage Mechanics ◽  
High Cycle Fatigue ◽  
Hot Spot ◽  
Probabilistic Method ◽  
Continuum Damage Mechanics ◽  
Model Parameters ◽  
Continuum Damage ◽  
Cycle Fatigue

Based on continuum damage mechanics, a probabilistic method of predicting high-cycle fatigue life for metallic components is proposed. First, macro-meso two-scale stress-strain equations are established by combining Eshelby-Kroner localization law and classic elastic-plastic constitutive equation. Second, some parameters in Lemaitre's fatigue damage evolution model are randomized. Probabilistic properties of which are obtained by inverse-analysis and optimization. Then, the probabilistic method of predicting high-cycle fatigue life is established by coupling the model with macro-meso two-scale equations. And the proposed algorithm is coded with Fortran language, which is non-intrusive post-program of FEM analysis. Next, constant amplitude fatigue test of Al 2024-T3 coupon is performed to determine probabilistic properties of model parameters. Finally, as the object of study, wallboard is analyzed by FEM. Taking skin-strip component as research object, the fatigue life of hot spot is predicted by proposed method. The corresponding fatigue test of the component is performed, which verifies the effectiveness of proposed method to predict probabilistic life of metallic components.

scholarly journals Life Prediction Model of Mineral Admixture Cement Based-Materials under Early Age CO2-Erosion

Coatings ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 413
Author(s):  
Saisai Wang ◽  
Jian Chen ◽  
Xiaodong Wen
Keyword(s):  
Prediction Model ◽  
Life Prediction ◽  
Experimental Tests ◽  
Mineral Admixture ◽  
Model Parameters ◽  
Influence Coefficient ◽  
Test Pieces ◽  
Cement Based Materials ◽  
Particle Group ◽  
Life Prediction Model

Most of the existing models of structural life prediction in early carbonized environment are based on accelerated erosion after standard 28 days of cement-based materials, while cement-based materials in actual engineering are often exposed to air too early. These result in large predictions of the life expectancy of mineral-admixture cement-based materials under early CO2-erosion and affecting the safe use of structures. To this end, different types of mineral doped cement-based material test pieces are formed, and early CO2-erosion experimental tests are carried out. On the basis of the analysis of the existing model, the influence coefficient of CO2-erosion of the mineral admixture Km is introduced, the relevant function is given, and the life prediction model of the mineral admixture cement-based material under the early CO2-erosion is established and the model parameters are determined by using the particle group algorithm (PSO). It has good engineering applicability and guiding significance.

The Fatigue Reliability Evaluation & Improvement of the Single-Arm Subway Current Collector

2012 ◽  
Vol 215-216 ◽  
pp. 826-831 ◽  
Author(s):  
Yu Chen ◽  
Zhi Ming Liu ◽  
Qiang Li
Keyword(s):  
Fatigue Life ◽  
Calculation Result ◽  
Dynamic Stress ◽  
Current Collector ◽  
Reliability Evaluation ◽  
Fatigue Reliability ◽  
Railway Vehicles ◽  
Load Spectra ◽  
Reliability Method

This study developed a fatigue reliability method for evaluating and improving the key parts on railway vehicles, which was applied to real structures. The study involved a type of single-arm current collector, while its contact shoe often collapsed in operation and needs improvements. The dynamic stress data from the actual line was tested and converted to load spectra based on damage consistency rule, and then the fatigue life of the contact shoe structure was achieved. The calculation result comes to correspond to its operation life. Based on the method, an improving plan for the structure was developed under optimizing algorithms.

Fatigue Reliability Functions in Semilogarithmic Coordinates

1991 ◽  
Author(s):  
Vladimir A. Avakov
Keyword(s):  
Fatigue Life ◽  
Coordinate System ◽  
Strength Distribution ◽  
Fatigue Reliability ◽  
Life Distribution ◽  
Similar Transformation ◽  
Asymptotic Type ◽  
Life Distributions ◽  
Strength Distributions

Abstract In the previous publication [2], the transformation between fatigue life and strength distribution was established using double-logarithmic coordinate system (lnN-lnS). Here, a similar transformation is established using a semi logarithmic (lnN-S) coordinate system. With the aid of the developed orthogonal relations, lognormal, Weibull and three-parameter logweibull life distributions have been transformed into normal, asymptotic type 1 of smallest value, and three-parameter Weibull strength distributions, respectively. This procedure may be applied to other types of fatigue life distribution.

Identification of Tire Model Parameters Through Full Vehicle Experimental Tests

2011 ◽  
Vol 133 (3) ◽  
Author(s):  
Francesco Braghin ◽  
Federico Cheli ◽  
Edoardo Sabbioni
Keyword(s):  
Laboratory Tests ◽  
Experimental Tests ◽  
Contact Forces ◽  
Lateral Acceleration ◽  
Design Stage ◽  
Model Parameters ◽  
Tire Model ◽  
Identification Procedure ◽  
Sideslip Angle ◽  
Tyre Model

Individual tire model parameters are traditionally derived from expensive component indoor laboratory tests as a result of an identification procedure minimizing the error with respect to force and slip measurements. These parameters are then transferred to vehicle models used at a design stage to simulate the vehicle handling behavior. A methodology aimed at identifying the Magic Formula-Tyre (MF-Tyre) model coefficients of each individual tire for pure cornering conditions based only on the measurements carried out on board vehicle (vehicle sideslip angle, yaw rate, lateral acceleration, speed and steer angle) during standard handling maneuvers (step-steers) is instead presented in this paper. The resulting tire model thus includes vertical load dependency and implicitly compensates for suspension geometry and compliance (i.e., scaling factors are included into the identified MF coefficients). The global number of tests (indoor and outdoor) needed for characterizing a tire for handling simulation purposes can thus be reduced. The proposed methodology is made in three subsequent steps. During the first phase, the average MF coefficients of the tires of an axle and the relaxation lengths are identified through an extended Kalman filter. Then the vertical loads and the slip angles at each tire are estimated. The results of these two steps are used as inputs to the last phase, where, the MF-Tyre model coefficients for each individual tire are identified through a constrained minimization approach. Results of the identification procedure have been compared with experimental data collected on a sport vehicle equipped with different tires for the front and the rear axles and instrumented with dynamometric hubs for tire contact forces measurement. Thus, a direct matching between the measured and the estimated contact forces could be performed, showing a successful tire model identification. As a further verification of the obtained results, the identified tire model has also been compared with laboratory tests on the same tire. A good agreement has been observed for the rear tire where suspension compliance is negligible, while front tire data are comparable only after including a suspension compliance compensation term into the identification procedure.

scholarly journals A Study on the Generalized Approximation Modeling Method Based on Fitting Sensitivity for Prediction of Engine Performance

2017 ◽  
Vol 2017 ◽  
pp. 1-12
Author(s):  
Lin Lin ◽  
Fang Wang ◽  
Shisheng Zhong
Keyword(s):  
Engine Performance ◽  
Grey Model ◽  
Model Parameters ◽  
Bayesian Regularization ◽  
Safety Engineering ◽  
The Novel ◽  
Mean Square ◽  
Approximation Model ◽  
Mean Square Errors ◽  
Fitting Accuracy

Prediction technology for aeroengine performance is significantly important in operational maintenance and safety engineering. In the prediction of engine performance, to address overfitting and underfitting problems with the approximation modeling technique, we derived a generalized approximation model that could be used to adjust fitting precision. Approximation precision was combined with fitting sensitivity to allow the model to obtain excellent fitting accuracy and generalization performance. Taking the Grey model (GM) as an example, we discussed the modeling approach of the novel GM based on fitting sensitivity, analyzed the setting methods and optimization range of model parameters, and solved the model by using a genetic algorithm. By investigating the effect of every model parameter on the prediction precision in experiments, we summarized the change regularities of the root-mean-square errors (RMSEs) varying with the model parameters in novel GM. Also, by analyzing the novel ANN and ANN with Bayesian regularization, it is concluded that the generalized approximation model based on fitting sensitivity can achieve a reasonable fitting degree and generalization ability.

The Structure and Mechanical Properties of VT23 Welded Joints with Surface Layer Modified by Ultrasonic Mechanical Forging

2017 ◽  
Vol 743 ◽  
pp. 264-268 ◽  
Author(s):  
Anastasia Smirnova ◽  
Yury Pochivalov ◽  
Victor Panin ◽  
Anatoly Orishich ◽  
Aleksandr Malikov ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Titanium Alloy ◽  
Fatigue Life ◽  
Welded Joints ◽  
Experimental Tests ◽  
Relaxation Property ◽  
Surface Layers ◽  
Β Phase ◽  
Fatigue Life Test ◽  
Vt23 Titanium Alloy

The structure and mechanical properties of welded joints of VT23 titanium alloy received by method of laser welding after modifying the surface layers by ultrasonic mechanical forging (Treatment 1 and Treatment 2) were investigated. The experimental tests have revealed that the Treatment 2 provides a multiple increase in the relaxation property in fatigue life test. The formation of nonuniform distribution of vanadium, chromium and molybdenum in the welded joint increases the strength and, at the same time, the brittleness of β-phase. Mechanical treatment of the surface layers in the second mode provides a multiple increase in ductility up to 13%, in the as-received condition up to 9.9%. In consequence of plastic deformation, the β-phase intensity reduces twice with Treatment 2 which is related to its clustering. As follows from a presented data, the fatigue life of the VT23 titanium alloy has increased more than threefold.

scholarly journals Elasto-plastic-adhesive DEM model for simulating hillslope debris flows: cross comparison with field experiments

2018 ◽  
Author(s):  
Adel Albaba ◽  
Massimiliano Schwarz ◽  
Corinna Wendeler ◽  
Bernard Loup ◽  
Luuk Dorren
Keyword(s):  
Numerical Model ◽  
Flow Velocity ◽  
Debris Flows ◽  
Field Experiments ◽  
Initial Conditions ◽  
Experimental Tests ◽  
Height Velocity ◽  
Model Parameters ◽  
Fine Content ◽  
Adhesive Model

Abstract. This paper presents a Discrete Element-based elasto-plastic-adhesive model which is adapted and tested for producing hillslope debris flows. The numerical model produces three phases of particle contacts: elastic, plastic and adhesion. The model capabilities of simulating different types of cohesive granular flows were tested with different ranges of flow velocities and heights. The basic model parameters, being the basal friction (ϕb) and normal restitution coefficient (ϵn), were calibrated using field experiments of hillslope debris flows impacting two sensors. Simulations of 50 m3 of material were carried out on a channelized surface that is 41 m long and 8 m wide. The calibration process was based on measurements of flow height, flow velocity and the pressure applied to a sensor. Results of the numerical model matched well those of the field data in terms of pressure and flow velocity while less agreement was observed for flow height. Those discrepancies in results were due in part to the deposition of material in the field test which are not reproducible in the model. A parametric study was conducted to further investigate that effect of model parameters and inclination angle on flow height, velocity and pressure. Results of best-fit model parameters against selected experimental tests suggested that a link might exist between the model parameters ϕb and ϵn and the initial conditions of the tested granular material (bulk density and water and fine contents). The good performance of the model against the full-scale field experiments encourages further investigation by conducting lab-scale experiments with detailed variation of water and fine content to better understand their link to the model's parameters.

Effects of asphalt concrete characteristics on cohesive zone model parameters of hot mix asphalt mixtures

2016 ◽  
Vol 43 (3) ◽  
pp. 226-232 ◽  
Author(s):  
S. Pirmohammad ◽  
H. Khoramishad ◽  
M.R. Ayatollahi
Keyword(s):  
Asphalt Concrete ◽  
Cohesive Energy ◽  
Cohesive Zone ◽  
Hot Mix Asphalt ◽  
Cohesive Zone Model ◽  
Experimental Tests ◽  
Model Parameters ◽  
Zone Model ◽  
Binder Type ◽  
Air Void

In this paper, the effects of the main asphalt concrete characteristics including the binder type and the air void percentage on the cohesive zone model (CZM) parameters were studied. Experimental tests were conducted on semi-circular bend (SCB) specimens made of asphalt concrete and the fracture behavior was simulated using a proper CZM. The CZM parameters of various hot mix asphalt (HMA) mixtures were determined using the SCB experimental results. Five types of HMA mixtures were tested and modeled to consider the effects of binder type and air void percentage on the CZM parameters. The results showed that as the binder in HMA mixture softened, the cohesive energy strength increased, whereas enhancing the air void percentage led to reduction of the cohesive energy and strength values. Among the studied HMA mixtures, the highest values of CZM parameters were found for the HMA mixture containing a copolymer called styrene-butadiene-styrene.

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