Investigating the fatigue failure characteristics of A283 Grade C steel using magnetic flux dete

A. Arifin,W.Z.W. Jusoh,S. ABDULLAH,N. Jamaluddin,A. K. ARIFFIN 국제구조공학회 2015 Steel and Composite Structures, An International J Vol.19 No.3

The Metal Magnetic Memory (MMM) method is a non-destructive testing method based on an analysis of the self-magnetic leakage field distribution on the surface of a component. It is used for determining the stress concentration zones or any irregularities on the surface or inside the components fabricated from ferrous-based materials. Thus, this paper presents the MMM signal behaviour due to the application of fatigue loading. A series of MMM data measurements were performed to obtain the magnetic leakage signal characteristics at the elastic, pre-crack and crack propagation regions that might be caused by residual stresses when cyclic loadings were applied onto the A283 Grade C steel specimens. It was found that the MMM method was able to detect the defects that occurred in the specimens. In addition, a justification of the Self Magnetic Flux Leakage patterns is discussed for demonstrating the effectiveness of this method in assessing the A283 Grade C steel under cyclic loadings.

DEVELOPMENT OF OCCUPANT CLASSIFICATION AND POSITION DETECTION FOR INTELLIGENT SAFETY SYSTEM

M. A. HANNAN,A. HUSSAIN,S. A. SAMAD,A. MOHAMED,D. A. WAHAB,A. K. ARIFFIN 한국자동차공학회 2006 International journal of automotive technology Vol.7 No.7

Occupant classification and position detection have been significant research areas in intelligent safety systems in the automotive field. The detection and classification of seat occupancy open up new ways to control the safety system. This paper deals with a novel algorithm development, hardware implementation and testing of a prototype intelligent safety system for occupant classification and position detection for in-vehicle environment. Borland C++ program is used to develop the novel algorithm interface between the sensor and data acquisition system. MEMS strain gauge hermatic pressure sensor containing micromachined integrated circuits is installed inside the passenger seat. The analog output of the sensor is connected with a connector to a PCI-9111 DG data acquisition card for occupancy detection, classification and position detection. The algorithm greatly improves the detection of whether an occupant is present or absent, and the classification of either adult, child or non-human object is determined from weights using the sensor. A simple computation algorithm provides the determination of the occupant’s appropriate position using centroidal calculation. A real time operation is achieved with the system. The experimental results demonstrate that the performance of the implemented prototype is robust for occupant classification and position detection. This research may be applied in intelligent airbag design for efficient deployment.

DEVELOPMENT OF OCCUPANT CLASSIFICATION AND POSITION DETECTION FOR INTELLIGENT SAFETY SYSTEM

Hannan, M.A.,Hussain, A.,Samad, S.A.,Mohamed, A.,Wahab, D.A.,Ariffin, A.K. The Korean Society of Automotive Engineers 2006 International journal of automotive technology Vol.7 No.7

Occupant classification and position detection have been significant research areas in intelligent safety systems in the automotive field. The detection and classification of seat occupancy open up new ways to control the safety system. This paper deals with a novel algorithm development, hardware implementation and testing of a prototype intelligent safety system for occupant classification and position detection for in-vehicle environment. Borland C++ program is used to develop the novel algorithm interface between the sensor and data acquisition system. MEMS strain gauge hermatic pressure sensor containing micromachined integrated circuits is installed inside the passenger seat. The analog output of the sensor is connected with a connector to a PCI-9111 DG data acquisition card for occupancy detection, classification and position detection. The algorithm greatly improves the detection of whether an occupant is present or absent, and the classification of either adult, child or non-human object is determined from weights using the sensor. A simple computation algorithm provides the determination of the occupant's appropriate position using centroidal calculation. A real time operation is achieved with the system. The experimental results demonstrate that the performance of the implemented prototype is robust for occupant classification and position detection. This research may be applied in intelligent airbag design for efficient deployment.

OFF-SET CRACK PROPAGATION ANALYSIS UNDER MIXED MODE LOADINGS

A. E. ISMAIL,A. K. ARIFFIN,S. ABDULLAH,M. J. GHAZALI 한국자동차공학회 2011 International journal of automotive technology Vol.12 No.2

An assessment was carried out herein to study the eccentricity of cracks subjected to mixed-mode loadings. Several loading locations relative to a central line were selected to induce mixed-mode loadings, which were computed using a finite element method. An adaptive meshing technique was adopted during the simulation of crack propagation to ensure the singularity of stress at the tip of the crack. The stress intensity failure criterion was used and programmed, and the node splitting technique was used when the stress intensity factor reached the fracture toughness of the material to simulate crack propagations. It was found that large variations in the stress intensity factor were observed when off-set cracks were used, and that KII decreased when loading distance increased, but increased when the off-set crack distance was increased. Both crack eccentricity and loading distance played important roles in producing mixed-mode loading, compared to the influence of central cracks. Correction factors were introduced to modify the calculation of stress intensity factors under mixed-mode loadings. Simulations of crack propagation were also conducted to study the effects of crack eccentricities and loading distances. It was found that the crack length, the loading distance relative to the central crack and the crack eccentricity dominated calculations of the integrity of cracked structures.

VEHICLE CRASH ANALYSIS FOR AIRBAG DEPLOYMENT DECISION

A. HUSSAIN,M. A. HANNAN,A. MOHAMED,H. SANUSI,A. K. ARIFFIN 한국자동차공학회 2006 International journal of automotive technology Vol.7 No.2

Airbag deployment has been responsible for huge death, incidental injuries and broken bones due to low crash severity and wrong deployment decision. This misfortune has led the authorities and the industries to pursue uniquely designed airbags incorporating crash-sensing technologies. This paper provides a thorough discussion underlying crash sensing algorithm approaches for the subject matter. Unfortunately, most algorithms used for crash sensing still have some problems. They either deploy at low severity or fail to trigger the airbag on time. In this work, the crash-sensing algorithm is studied by analyzing the data obtained from the variables such as (ⅰ) change of velocity, (ⅱ) speed of the vehicle and (ⅲ) acceleration. The change of velocity is used to detect crash while speed of the vehicle provides relevant information for deployment decision. This paper also demonstrates crash severity with respect to the changing speed of the vehicle. Crash sensing simulations were carried out using Simulink, Stateflow, SimMechanics and Virtual Reality toolboxes. These toolboxes are also used to validate the results obtained from the simulated experiments of crash sensing, airbag deployment decision and its crash severity detection of the proposed system.

Synthesis of the Hydrazones of 2-((3,5-Di-tert-butyl-4-hydroxybenzyl)thio) acetohydrazide and the Study of their Radical Scavenging Activity by the DPPH Assay and the Computational Method

Muhammad K. Abdulwahab,Azhar Ariffin,Wageeh A. Yehye,Azlina Abdul-Aziz,Huda S. Kareem,Nurdiana Nordin 대한화학회 2015 Bulletin of the Korean Chemical Society Vol.36 No.11

The synthesis of antioxidant compounds bearing pharmacologically active groups has become a research interest in the last decade. A series of hydrazones containing a butylated hydroxyl group were synthesized from 2-((3,5-di-tert-butyl-4-hydroxybenzyl)thio)acetohydrazide and various benzaldehyde derivatives, and their radical scavenging activity was explored by 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay and computational calculations. Based on the results, the effects of different substituents on the DPPH IC50 values were discussed. The bond dissociation enthalpies (BDE) of OH and NH bonds and the spin density (SD) values of the compounds were calculated using the density functional theory (DFT) to determine the theoretical capability of the hydrazones as radical scavengers. Based on the results, the effects of the thioether group and the substituent groups next to the NH bond on the BDE values were also discussed.

VEHICLE CRASH ANALYSIS FOR AIRBAG DEPLOYMENT DECISION

Hussain, A.,Hannan, M.A.,Mohamed, A.,Sanusi, H.,Ariffin, A.K. The Korean Society of Automotive Engineers 2006 International journal of automotive technology Vol.7 No.2

Airbag deployment has been responsible for huge death, incidental injuries and broken bones due to low crash severity and wrong deployment decision. This misfortune has led the authorities and the industries to pursue uniquely designed airbags incorporating crash-sensing technologies. This paper provides a thorough discussion underlying crash sensing algorithm approaches for the subject matter. Unfortunately, most algorithms used for crash sensing still have some problems. They either deploy at low severity or fail to trigger the airbag on time. In this work, the crash-sensing algorithm is studied by analyzing the data obtained from the variables such as (i) change of velocity, (ii) speed of the vehicle and (iii) acceleration. The change of velocity is used to detect crash while speed of the vehicle provides relevant information for deployment decision. This paper also demonstrates crash severity with respect to the changing speed of the vehicle. Crash sensing simulations were carried out using Simulink, Stateflow, SimMechanics and Virtual Reality toolboxes. These toolboxes are also used to validate the results obtained from the simulated experiments of crash sensing, airbag deployment decision and its crash severity detection of the proposed system.

Neuro-fuzzy fatigue life assessment using the wavelet-based multifractality parameters

C. H. Chin,S. ABDULLAH,S.S.K. Singh,A. K. ARIFFIN,D. Schramm 대한기계학회 2021 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.35 No.2

This study aims to establish a fatigue life predictive model based on multifractality of road excitations using neuro-fuzzy method to assess the durability of suspension spring. Traditional durability analysis in time domain is complicated and time-consuming due to the needs of large data amount. Thus, it is an idea to adopt an adaptive neuro-fuzzy inference system (ANFIS) for relating the performance of coil spring to the multifractal properties of road excitations, giving a meaningful fatigue life prediction. Different membership function numbers were tested to obtain the optimum membership function number. During the data training process, the checking data was used to test the trained model each Epoch of training for overfitting detection. As a result, the Morrow-based fatigue life prediction model was found to give the most suitable result with three membership functions. The SWT-based model needed five membership functions due to nonlinear properties in the SWT-based fatigue life data. Training process of Morrow-based-ANFIS was stopped at Epoch 8 given its lowest checking root-meansquare-error of 0.6953. SWT-based model recorded a higher error of 0.7940. The neuro-fuzzy models gave accurate fatigue life predictions with 96 % of the data distributed within the acceptance boundary, hence, contributing to an acceptable assessment of coil spring fatigue life based on load multifractality. This study had shown a nonlinear relationship between road multifractality and durability performance of coil spring. Multifractality had been proven an important feature to characterise various road excitations for durability prediction.

Discrepancies of fatigue crack growth behaviour of API X65 steel

N. I. I. Mansor,S. ABDULLAH,A. K. ARIFFIN 대한기계학회 2017 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.31 No.10

This paper discusses the fatigue life behaviour of the API X65 steel tested under constant amplitude loading in ambient temperature. The influence of repeated loading at a particular stress ratio would favour the initiation of fatigue cracks that would consequently affect the fatigue crack growth. The main objective of this paper is to evaluate the load ratio effects on fatigue crack growth rate, taking into account their statistical characteristics. The fatigue crack growth test was carried out using compact-tension specimen at different load ratios of 0.1, 0.4 and 0.7. The experimental results showed the crack growth rate was dependent on the applied load. It was observed that the load ratio effect was less significant in stable crack growth regions. The result was consistent with the multiple regression test obtained by the least square method at a significance level of 0.05. The empirical model of Paris and Walker was utilised to evaluate the effects of load ratio on the fatigue crack growth rates. The approximation of fatigue life lies between 10-25 % of error using conservative model and 6 % error using the Walker model. The experimental data was scattered within a factor-of-2 correlation line suggesting that the accuracy of the experimental data towards the estimated values was high.

Probabilistic-based fatigue reliability assessment of carbon steel coil spring from random strain loading excitation

C. H. Chin,S. ABDULLAH,S.S.K. Singh,A. K. ARIFFIN,D. Schramm 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.1

This paper aims to assess the fatigue reliability of random loading signals of a suspension coil spring using probabilistic approaches. Strain time histories were acquired while the car was travelling on different road conditions (i.e., in a rural area, in an industrial area, on a university campus, on a highway and on a newly constructed road). Fatigue lives were predicted from the strain histories and fitted into probability density functions. Lognormal distribution was found to be an appropriate way to represent fatigue data. Next, the reliability function and mean-cycles-to-failure (MCTF) were determined. The results indicated that fatigue reliability rapidly deteriorated under rural road conditions, which resulted in a short MCTF of 10 4 cycles. Meanwhile, the new road signals had the longest MCTF of about 10 8 cycles. Accordingly, this is due to the rural road having the most surface irregularities, which caused more severe fatigue damage to the coil spring. This study contributed to a greater in-depth understanding of the effect of loading signals on fatigue reliability. This is essential in determining the appropriate service life of the coil spring during its production to ensure vehicle safety and reduce maintenance costs.