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Magnetorheological (MR) fluid applications in various medical equipments have been widely studied... more Magnetorheological (MR) fluid applications in various medical equipments have been widely studied because its easiness to utilize and fast response. The application can be divided into, at least, two forms, which are haptic and prosthetic devices. In each equipment design process, rheological models are essential to determine the required inputs to produce enough force or yield stress. However, each existing model has its own limitations, such as agreeable performance on limited inputs ranges of magnetic fields and shear rates. A modeling method using extreme learning machine (ELM) as an intelligent model may be able to solve this problem. Therefore, this paper aims to investigate the ELM performance to model MR fluids behavior using various activation functions. Five activation functions are applied, which are hard limit, sigmoid, sine, triangular basis and radial basis function. Then, the investigation is divided into two cases, a wide and low operating shear rate based on the medical devices applications. The comparisons with the experimental data show that the models produce considerably high accuracy, especially for hard limit activation function. The model capability to predict dynamic yield stress predictions has also shown an agreeable result.

\textcopyright} 2017 IEEE. Magnetorheological (MR) fluid applications in various medical equipmen... more \textcopyright} 2017 IEEE. Magnetorheological (MR) fluid applications in various medical equipment have been widely studied because its easiness to utilize and fast response. The application can be divided into, at least, two forms, which are haptic and prosthetic devices. In each equipment design process, rheological models are essential to determine the required inputs to produce enough force or yield stress. However, each existing model has its own limitations, such as agreeable performance on limited inputs ranges of magnetic fields and shear rates. A modeling method using extreme learning machine (ELM) as an intelligent model may be able to solve this problem. Therefore, this paper aims to investigate the ELM performance to model MR fluids behavior using various activation functions. Five activation functions are applied, which are hard limit, sigmoid, sine, triangular basis and radial basis function. Then, the investigation is divided into two cases, which are a wide and low operating shear rate based on the medical devices applications. The comparisons with the experimental data show that the models produce considerably low RMSE or less than 3 kPa, especially for hard limit activation function. The paper also demonstrates the model capability to predict dynamic yield stress.

ariable geometry turbochargers have been widely researched to fulfil the current engine stringent... more ariable geometry turbochargers have been widely researched to fulfil the current engine stringent regulations. The passively controlled turbocharger (PCT) concept has been proposed to reduce energy consumption by utilizing the emission energy to move the actuator. However, it only covered a small range operating condition. Therefore, a magnetorheological(MR) Valve device, as typical smart material devices to enhance a passive device, is proposed to improve the PCT. Even though the benefits have been considered for the compactness and easiness to connect to an electrical system, the number of publications regarding the MR application within engine system is hard to be found. Therefore, this paper introduces a design of an MR Valve in a turbocharger. The main challenge is to make sure its capability to produce a sufficient total pressure drop. To overcome the challenge, its material properties, shape and pressure drop calculation has been analyzed to fulfil the requirement. Finally, to get a more understanding of actuator performance, the actuator response was simulated by treating the exhaust gas pressure as an input. It shows that the new MR actuator has a potential dynamic to improve the PCT controllability.

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articles by Irfan Bahiuddin

In the past decade, advanced technologies in robotics have been explored to enhance the rehabilit... more In the past decade, advanced technologies in robotics have been explored to enhance the rehabilitation of post-stroke patients. Previous works have shown that gait assistance for post-stroke patients can be provided through the use of robotics technology in ancillary equipment, such as Ankle Foot Orthosis (AFO). An AFO is usually used to assist patients with spasticity or foot drop problems. There are several types of AFOs, depending on the flexibility of the joint, such as rigid, flexible rigid, and articulated AFOs. A rigid AFO has a fixed joint, and a flexible rigid AFO has a more flexible joint, while the articulated AFO has a freely rotating ankle joint, where the mechanical properties of the AFO are more controllable compared to the other two types of AFOs. This paper reviews the control of the mechanical properties of existing AFOs for gait assistance in post-stroke patients. Several aspects that affect the control of the mechanical properties of an AFO, such as the controller input, number of gait phases, controller output reference, and controller performance evaluation are discussed and compared. Thus, this paper will be of interest to AFO researchers or developers who would like to design their own AFOs with the most suitable mechanical properties based on their application. The controller input and the number of gait phases are discussed first. Then, the discussion moves forward to the methods of estimating the controller output reference, which is the main focus of this study. Based on the estimation method, the gait control strategies can be classified into subject-oriented estimations and phase-oriented estimations. Finally, suggestions for future studies are addressed, one of which is the application of the adaptive controller output reference to maximize the benefits of the AFO to users.

Considering persistent years, many researchers continuously seek an optimum way to utilize the id... more Considering persistent years, many researchers continuously seek an optimum way to utilize the idea of magnetorheology (MR) materials to be practically used for everyday life, particularly concerning resistivity sensing application. The rheology and resistivity of a graphite (Gr)-based magnetorheological elastomer (Gr-MRE) were experimentally evaluated in the present research. Magnetorheological elastomer (MRE) samples were prepared by adding Gr as a new additive during MRE fabrication. The effect of additional Gr on the rheological and resistivity properties were investigated and compared with those of typical MREs without a Gr additive. Morphological aspects of Gr-MRE were characterized using field emission scanning electron microscopy (FESEM) and energy dispersive X-ray spectroscopy (EDX). Rheological properties under different magnetic fields were evaluated using a parallel-plate rheometer. Subsequently, the resistivity of all samples was measured under different applied forces and magnetic fields. From the resistivity evaluation, two relationship curves resistance (R) under different applied forces (F) and different magnetic fields (B) were established and plotted by using an empirical model. It was observed from the FESEM images that the presence of Gr fractions arrangement contributes to the conductivity of MRE. It was also observed that, with the addition of Gr, rheological properties such as the field-dependent modulus can be improved, particularly at low strain amplitudes. It is also demonstrated that the addition of Gr in MRE can contribute to the likely use of force detection in tactile sensing devices.

The yield stress and plastic viscosity of magnetorheological (MR) fluids are identified by fittin... more The yield stress and plastic viscosity of magnetorheological (MR) fluids are identified by fitting rheological models based on a selected dataset on a certain range of shear rates. However, the datasets are often arbitrarily determined as there is no standardized procedure available. To overcome this problem, a platform that capable to minimize the fitting error while considering the classification of the shear rate regions is needed. Therefore, this work proposed a new platform for the systematic prediction of field-dependent rheological characteristics using particle swarm optimization (PSO). PSO is a meta-heuristic algorithm for solving optimization problems based on a guided search of the defined problem space, which is governed by the objective function. An intersection point of low and high shear rate regions critical shear rate is formulated as part of the objective function to standardize the characterization within the defined regions. The objective function is inspired by the modified Bingham biplastic and Papanastasiou models to predict five magnetic field dependent-rheological parameters. In the development stage, the shear stress model was first established using a previously developed extreme learning machine method. Then, the codes of the PSO, objective functions and search space identification were developed and implemented. To validate the effectiveness of the proposed procedure, the platform performance was analysed at different algorithmic parameters and compared with the existing optimization methods. The simulation results indicated that the proposed platform performed better than the existing ones with R2 of 0.943 and was able to systematically and accurately predict the rheological parameters.

This paper introduces a new design of variable stiffness damper using controlled accumulator fill... more This paper introduces a new design of variable stiffness damper using controlled accumulator filled with Magnetorheological (MR) fluids. The originality of the new design is in its capability to offer less consumption of MR fluids than the conventional design of MR damper. The new design does not fill the whole cylinder with MR fluids but only use the accumulator space as the volume compensation control zone with MR fluids. The MR fluids control the compressive movement of the accumulator piston which alter the flow of the hydraulic oil to the accumulator chamber. As a result, the regulated flow of oil to the accumulator chamber will only have a direct effect to the compression stiffness of the damper. The experimental results show that the proposed design is capable to adjust the compression force while maintaining the rebound force of the damper.

Magnetorheological (MR) fluid devices are now applied in various applications. Although a lot of ... more Magnetorheological (MR) fluid devices are now applied in various applications. Although a lot of studies have been discussed in long-term implementation of MR devices, only few studies have concerned on MR fluid application in valve operation mode, such as at MR valve. The experiments were conducted on a dynamic test machine in a custom MR damper with meandering MR valve. The experiment test was applied at continuous-load in long term-operation with parameters of 20 mm length of stroke, 0.4 Hz of frequency, 0.5 A of applied current and 175,000 cycles. The rheological properties of MR fluid were characterized using rotational and oscillatory shear rheometer. The result showed that the rheological properties of MR fluid changed after applied in long-term operation. The changed of MR fluid also investigated through morphological characteristics using SEM and EDX.

This article aims to present a brief review on sensors used for gait detection in Ankle Foot Orth... more This article aims to present a brief review on sensors used for gait detection in Ankle Foot Orthosis (AFO) application. Both the advantages and disadvantages of sensors such as EMG sensor, rotary encoder, foot switches, and force plate are highlighted in this article. Authors also addressed the four characteristics of sensors for gait detection; uniformity, installation, flexibility, and multi-measurement. In addition, the sensors were then compared based on the characteristics. The foot switch was identified as the most compatible sensor for gait detection. However, the sensor was also discovered to contain problems in its durability and uneven grounding. Consequently, the authors propose an introduction to a new material, hybrid Magnetorheological Elastomer (MRE). Coincidentally, the mentioned material possesses attributes of thin dimensions with adjustable stiffness. The thin dimension allows the hybrid MRE to be placed under the AFO sole. Furthermore, with an accurate degree of stiffness, the hybrid MRE allows for adjustment leading to a higher level of durability of the sensors which remains fine even if stomped on the user. In conclusion, the authors propose a further study on hybrid MRE AFO for the next study.

Magnetorheological (MR) grease is a promising material to replace MR fluid because the advantage ... more Magnetorheological (MR) grease is a promising material to replace MR fluid because the advantage in term of stability and less possibility to leaking. To improve the material properties, an accurate model can be critical for reducing the time and cost of the development process. A model has been developed to predict MR fluid material properties by including the composition. However, the model may need adjustment and cannot predict other essential rheology parameters, such as viscosity, apparent viscosity, shear rate, and shear stress. Therefore, the technical novelty of this paper is to propose a model with composition as one of the inputs using extreme learning machine method. A scoring system is also introduced to quantify the significance of the composition effect toward the MR grease performance. Then, the model is simulated and compared with experimental data. The performance shows high accuracy estimation with normalized root mean square error about 1.25{\%}.

This paper investigates the field-dependent rheological properties of magnetorheological (MR) flu... more This paper investigates the field-dependent rheological properties of magnetorheological (MR) fluid used to fill in MR dampers after long-term cyclic operation. For testing purposes, a meandering MR valve was customized to create a double-ended MR damper in which MR fluid flowed inside the valve due to the magnetic flux density. The test was conducted for 170,000 cycles using a fatigue dynamic testing machine which has 20 mm of stroke length and 0.4 Hz of frequency. Firstly, the damping force was investigated as the number of operating cycles increased. Secondly, the change in viscosity of the MR fluid was identified as in-use thickening (IUT). Finally, the morphological observation of MR particles was undertaken before and after the long-term operation. From these tests, it was demonstrated that the damping force increased as the number of operating cycles increases, both when the damper is turn on (on-state) and off (off-state). It is also observed that the particle size and shape changed due to the long operation, showing irregular particles.

The flow input of a variable geometry turbocharger turbine is highly unsteady due to rapid and pe... more The flow input of a variable geometry turbocharger turbine is highly unsteady due to rapid and periodic pressure dynamics in engine combustion chambers. Several VGT control methods have been developed to recover more energy from the highly pulsating exhaust gas flow. To develop a control system for the highly pulsating flow condition, an accurate and valid unsteady model is required. This study focuses on the derivation of governing the unsteady control-oriented model (COM) for a turbine of an actively controlled turbocharger (ACT). The COM has the capability to predict the turbocharger behaviour regarding the instantaneous turbine actual and isentropic powers in different effective throat areas. The COM is a modified version of a conventional mean value model (MVM) with an additional feature to calculate the turbine angular velocity and torque for determining the actual power. The simulation results were further compared with experimental data in two general scenarios. The first scenario was simulations on fixed geometry positions. The second simulation scenario considered the nozzle movement after receiving a signal from the controller in different cases. The comparison between simulation and experimental results showed similarities in the recovered power behaviours the turbine inlet area increases or vice versa. The model also has proved its reliability to replicate general behaviour as in the example of ACT cases presented in this paper. However, the model is incapable to replicate the detailed and complicated phenomena, such as choking effect and hysteresis effect.

\textcopyright}2017 The Authors. This paper presents the characterization and hysteresis modeling... more \textcopyright}2017 The Authors. This paper presents the characterization and hysteresis modeling of magnetorheological (MR) damper with meandering type valve. The meandering type MR valve, which employs the combination of multiple annular and radial flow passages, has been introduced as the new type of high performance MR valve with higher achievable pressure drop and controllable performance range than similar counterparts in its class. Since the performance of a damper is highly determined by the valve performance, the utilization of the meandering type MR valve in an MR damper could potentially improve the damper performance. The damping force characterization of the MR damper is conducted by measuring the damping force as a response to the variety of harmonic excitations. The hysteresis behavior of the damper is identified by plotting the damping force relationship to the excitation displacement and velocity. For the hysteresis modeling purpose, some parts of the data are taken as the training data source for the optimization parameters in the neuro-fuzzy model. The performance of the trained neuro-fuzzy model is assessed by validating the model output with the remaining measurement data and benchmarking the results with the output of the parametric hysteresis model. The validation results show that the neuro-fuzzy model is demonstrating good agreement with the measurement results indicated by the average relative error of only around 7{\%}. The model also shows robustness with no tendency of growing error when the input values are changed.

Papers by Irfan Bahiuddin

Jurnal Nasional Teknologi Terapan (JNTT)

Fluida magnet-reologi (MR) adalah suatu material cerdas yang bisa dikontrol kekerasannya direpres... more Fluida magnet-reologi (MR) adalah suatu material cerdas yang bisa dikontrol kekerasannya direpresentasikan oleh tegangan luluh dan viskositas yang bisa diubah. Kedua parameter tersebut diperoleh dengan membandingkan data eksperimen dengan persamaan Bingham plastik. Pemilihan data eksperimen yang tepat adalah kunci keakuratan prediksi tegangan luluh dan viskositas. Pemilihan data eksperimen umumnya dilakukan dengan metode coba-coba. Parameter yang diprediksi bisa mempunyai nilai yang berbeda meskipun materialnya sama. Oleh karena itu, diperlukan suatu metode yang bisa memprediksi secara sistematik kedua parameter tersebut secara optimum. Penelitian ini mengusulkan suatu metode untuk memilih data secara otomatis dan menghasilkan prediksi. Metode yang digunakan adalah particle swarm optimization (PSO). Fungsi objektif untuk proses optimasi dikembangkan berdasarkan model biplastic Bingham. Set parameter yang diprediksi ada dua grup, yaitu grup untuk aplikasi kecepatan rendah dan tinggi....

Jurnal Nasional Teknologi Terapan (JNTT)

Advances in Science and Technology

This paper presents an investigation of the dimension variations on modular magnetorheological (M... more This paper presents an investigation of the dimension variations on modular magnetorheological (MR) valve with meandering flow path structure. The size variations including the inner and outer radius of the valve at radial path. The first step is conducting FEMM (Finite Element Method Magnetics) to find out the density of magnetic flux on MR valve. The obtained magnetic field density is applied to steady state models to predict pressure drop. To determine the best configuration, pressure drop and operation range are the objective of the selection process. Based on the results, MR valve with 2.75 mm inner radius radial and 9 mm outer radius radial was chosen as the best MR valve design if compared to the other MR valve designs. The results obtained from the MR valve with 2.75 mm inner radius radial and 9 mm outer radius radial are 1.79 Mpa for the pressure drop and 6.68 for the operational range. Keywords: modular magnetorheological valve, optimization, objective function, smart mate...

Proceedings of the 6th International Conference and Exhibition on Sustainable Energy and Advanced Materials, 2020

Scientific Reports, 2022

This study introduces a novel platform to predict complex modulus variables as a function of the ... more This study introduces a novel platform to predict complex modulus variables as a function of the applied magnetic field and other imperative variables using machine learning. The complex modulus prediction of magnetorheological (MR) elastomers is a challenging process, attributable to the material’s highly nonlinear nature. This problem becomes apparent when considering various possible fabrication parameters. Furthermore, traditional parametric modeling methods are limited when applied to solve larger-scale cases involving large databases. Consequently, the application of non-parametric modeling such as machine learning has gained increasing attraction in recent years. Therefore, this work proposes a data-driven approach for predicting multiple input-dependent complex moduli using feedforward neural networks. Besides excitation frequency and magnetic flux density as operating conditions, the inputs consider compositions and curing conditions represented by magnetic particle weight ...

Engineering Failure Analysis, 2022

2017 International Conference on Robotics, Automation and Sciences (ICORAS), 2017

Recently, magnetorheological (MR) fluid has been widely used in many fields because of its unique... more Recently, magnetorheological (MR) fluid has been widely used in many fields because of its unique characteristics. It exhibits rapid, reversible and tunable transition from liquid to semi-solid state when external force such as magnetic field is applied. Numerous investigations have been carried out by researchers to understand the rheological properties of MR fluid. Various modeling techniques have been built to predict the fluid behavior for the development purposes. Those techniques can be parametric or non-parametric which includes rheological, polynomial and phenomenological models with their own application and limitation. In this stage, models are important to shorten the development time and saving the experimental cost. A Graphical User Interface (GUI) containing one of the models can be a beneficial tool to predict the fluid behavior easier during an experiment or investigation. However, a GUI needs a flexible modeling method that can be adjusted and updated easily. Therefore, machine learning as data to knowledge-model can be the best solution. In this paper, extreme learning machine (ELM) is proposed to train the datasets of MR fluid used for the GUI because of its advantage in terms of its faster training and better generalization. The best configuration of ELM is carefully investigated and applied in the GUI. The developed interface can act as prediction platform for the output of MR fluid based on the learning process through the given data.

Proceedings of the 6th International Conference and Exhibition on Sustainable Energy and Advanced Materials, 2020

A magnetorheological (MR) damper with meandering valve type is known for its capability to produc... more A magnetorheological (MR) damper with meandering valve type is known for its capability to produce higher force than other MR valve types while maintaining the compactness. It is essential to investigate the properties of MR damper in long-term operation. Therefore, this paper aims to investigate the MR damper with single-stage meandering valve performance after long-term operation. The experiment will be executed by applying the usage of MR fluid in a bypass double-ended damper. Firstly, the damper was characterized to know the initial damper performance. Secondly, the damper performance will be observed in long-term operation up to 100,000 cycles. Based on the force versus displacement graph, the peak to peak force has increased by about 33.3% after 28,000 cycles. In other words, the damper becomes stiffer after a long-term operation test will affect the performance of MR damper.

Fluids, 2021

Coronavirus disease 2019 (Covid-19) has been identified as being transmitted among humans with dr... more Coronavirus disease 2019 (Covid-19) has been identified as being transmitted among humans with droplets from breath, cough, and sneezes. Understanding the droplets’ behavior can be critical information to avoid disease transmission, especially while designing a device deals with human air respiratory. Although various studies have provided enormous computational fluid simulations, most cases are too specific and quite challenging to combine with other similar studies directly. Therefore, this paper proposes a systematic approach to predict the droplet behavior for coughing cases using machine learning. The approach consists of three models, which are droplet generator, mask model, and free droplet model modeled using feedforward neural network (FFNN). The evaluation has shown that the three FFNNs models’ accuracies are relatively high, with R-values of more than 0.990. The model has successfully predicted the evaporation effect on the diameter reduction and the completely evaporated...

2021 International Conference on Instrumentation, Control, and Automation (ICA), 2021

Resistivity property of graphite based MRE is demonstrated in the present research. In this paper... more Resistivity property of graphite based MRE is demonstrated in the present research. In this paper, a study on the force sensitive property by using a composite of graphite (Gr) and magnetorheological elastomer (MRE) is suggested where graphite powder was used as a conductive element in the composite. The carbonyl iron particles and graphite powder were mixed in the silicon rubber to produce the Gr-MRE composite. The resistivity properties are then identified from a designated test rig that delivers different magnitude of the applied force on the sample. Results showed that the resistivity of the material decreased as the applied force increase from 700 to 1000g, where the magnitude of the resistance decreases approximately 79 to 66%. By having higher magnetic flux density in the material, the stiffness of the Gr–MRE could possibly be controlled depending on the magnitude of the force.

Most studies reported that smoke opacity and particulate matter (PM) are substantially reduced wh... more Most studies reported that smoke opacity and particulate matter (PM) are substantially reduced when using emulsion fuel. The goal of this work was to predict the PM reduction of diesel emulsion fuel by measuring the smoke opacity, which is known to be proportional with PM. The smoke/PM measurements were mostly of the particulate trap type, which is lengthy, arduous and only offers cumulative results. In this study, the smoke opacity was measured in real-time by using a smoke opacimeter to obtain faster, simpler and continuous results. The results were compared to the results of Legal Particulate Sampling (LPS). The types of fuel used in this study were an emulsion fuel denoted as E10 and Malaysian EURO2 diesel (D2M). Even though the PM emission of E10 was 20% lower than D2M, the smoke opacity of E10 was 200% higher. It was concluded that the opacimeter could not be used to predict the PM reduction in emulsified D2M.

Materials, 2021

This paper investigated the effects of petroleum-based oils (PBOs) as a dispersing aid on the phy... more This paper investigated the effects of petroleum-based oils (PBOs) as a dispersing aid on the physicochemical characteristics of natural rubber (NR)-based magnetorheological elastomers (MREs). The addition of PBOs was expected to overcome the low performance of magnetorheological (MR) elastomers due to their inhomogeneous dispersion and the mobility of magnetic particles within the elastomer matrix. The NR-based MREs were firstly fabricated by mixing the NR compounds homogeneously with different ratios of naphthenic oil (NO), light mineral oil (LMO), and paraffin oil (PO) to aromatic oil (AO), with weight percentage ratios of 100:0, 70:30, 50:50, and 30:70, respectively. From the obtained results, the ratios of NO mixed with low amounts of AO improved the material physicochemical characteristics, such as thermal properties. Meanwhile, LMO mixed the AO led to the best results for curing characteristics, microstructure observation, and magnetic properties of the MREs. We found that th...

Open Engineering, 2021

Magnetorheological (MR) fluid is among the smart materials that can change its default properties... more Magnetorheological (MR) fluid is among the smart materials that can change its default properties with the influence of a magnetic field. Typical application of an MR fluid based device involves an adjustable damper which is commercially known as an MR fluid damper. It is used in vibration control as an isolator in vehicles and civil engineering applications. As part of the device development process, proper understanding of the device properties is essential for reliable device performance analysis. This study introduce an accurate and fast prediction model to analyse the dynamic characteristics of the MR fluid damper. This study proposes a new modelling technique called Extreme Learning Machine (ELM) to predict the dynamic behaviour of an MR fluid damper hysteresis loop. This technique was adopted to overcome the limitations of the existing models using Artificial Neural Networks (ANNs). The results indicate that the ELM is extremely faster than ANN, with the capability to produce...

2017 International Conference on Robotics, Automation and Sciences (ICORAS), 2017

Magnetorheological (MR) fluid applications in various medical equipment have been widely studied ... more Magnetorheological (MR) fluid applications in various medical equipment have been widely studied because its easiness to utilize and fast response. The application can be divided into, at least, two forms, which are haptic and prosthetic devices. In each equipment design process, rheological models are essential to determine the required inputs to produce enough force or yield stress. However, each existing model has its own limitations, such as agreeable performance on limited inputs ranges of magnetic fields and shear rates. A modeling method using extreme learning machine (ELM) as an intelligent model may be able to solve this problem. Therefore, this paper aims to investigate the ELM performance to model MR fluids behavior using various activation functions. Five activation functions are applied, which are hard limit, sigmoid, sine, triangular basis and radial basis function. Then, the investigation is divided into two cases, which are a wide and low operating shear rate based on the medical devices applications. The comparisons with the experimental data show that the models produce considerably low RMSE or less than 3 kPa, especially for hard limit activation function. The paper also demonstrates the model capability to predict dynamic yield stress.

Key Engineering Materials, 2018

Actuators, 2019