Sharif Digital Repository

FeNiCo base powder alloy with nominal composition Fe-27Ni-17Co-4Ti (wt%) was prepared from elemental powders by mechanical alloying. The structure of milled powders was characterized by XRD and SEM. The effect of nanosize structure on magnetic properties and shape memory behavior was studied using VSM and DSC. After milling for 240 minutes by high energy vibrational ball mill under argon atmosphere, supersaturated solid solution formed with mean crystallite size of ∼20 nm. Results of VSM examinations showed that by milling for 240 minutes saturation magnetization and intrinsic coercivity reached 304 emu/gr and 21 Oe, respectively. XRD analyses made it clear that transformation from BCC to... 

Finemet soft magnetic alloy has been in the focus of interest in the last years due to its high saturation magnetization, high permeability and low core loss. The great quantity of papers has been devoted to the study of its structural and magnetic properties, confirms this claim. This paper reviews the different researches performed on Finemet up to now. The criteria that should be satisfied in order to have the high glass forming ability in an alloy and also the techniques applied for production of Finemet ribbons, powders and bulk samples have been explained. In addition, the mechanism of devitrification, nanocrystallization and magnetic softness in this applicable magnetic alloy has been... 

Finemet bulk soft magnetic alloy was fabricated by spark plasma sintering of the milled ribbons. The amorphous melt-spun ribbons were milled for 36min by high energy vibrational mill and then sieved to separate particles smaller than 125μm. The size distribution of particles was determined by a laser diffraction particle size analyzer. Spark plasma sintering was carried out at super-cooled liquid region for short times of 7 and 21min. The structure of bulk samples was characterized using X-ray diffraction, scanning electron microscopy, differential scanning calorimetry and transmission electron microscopy techniques. The magnetization and coercivity of samples were measured using SQUID... 

Iron-borosilicate soft magnetic composites are suitable magnetic materials for high temperature and high frequency applications. In this research two different techniques have been applied to fabricate these composites: uniaxial pressing following by sintering and spark plasma sintering. Different processing parameters including the content of borosilicate, the amount of compaction pressure and the size of iron particles have been evaluated through the study of microstructure and magnetic properties. The microstructural observations showed that the borosilicate is distributed on the iron grain boundaries enhancing the resistivity and causing the loss of eddy currents. Increasing the... 

In this research, FINEMET alloy with composition of Fe73.5Si13.5B9Nb3Cu1 was produced by mechanical alloying from elemental powders. The effect of milling time on the magnetic and structural properties of alloy has been investigated using X-ray diffraction, scanning electron microscopy, transmission electron microscopy and vibrating sample magnetometery. The results showed that milling for 53 hr leads to the formation of Fe supersaturated solid solution which includes Si, B and Nb atoms with mean crystallite size of ~30 nm. The shift of the main peak of Fe to the higher angles indicated that Si and B atoms dissolve in the Fe solid solution, at primary stage of mechanical alloying, up to the... 

The effect of milling time on the magnetic properties of FINEMET amorphous ribbons has been investigated using X-ray diffraction, Mössbauer spectroscopy, thermo-magnetic measurements, transmission electron microscopy and SQUID magnetometery. Ribbons were melt-spun at a wheel speed of 38 ms-1 and then mechanically milled for different periods up to 45 min. The results showed that the partially crystallization of the amorphous powder occurs during milling. TEM observations confirmed the formation of small volume fraction of the crystalline phase with ∼9 nm crystallite size in the amorphous matrix for the ribbon milled for 45 min. Thermo-magnetic measurements indicated the enhancement of the... 

The effects of relaxation and nanocrystallization on magnetic properties of (Fe0.5Co0.5)73.5Si13.5B 9Nb3Cu1 ribbons have been investigated. Ribbons were melt-spun at wheel speed of 38 m/s and then annealed at different temperatures. The results indicated that the relaxation processes shift the Curie temperature of amorphous phase to the higher temperatures. It was also found that through crystallization phenomena the saturation magnetization increases due to the super-exchange between Fe and Co atoms in the crystalline phase. A slight variation in magnetization was observed at ~700 °lC during heating due to the ordering transition in FeCo system. At early stage of crystalline phase... 

The effect of quenching wheel speed on the structure and Curie temperature of Fe73.5Si13.5B9Nb3Cu1 alloy has been investigated using X-ray diffraction, differential scanning calorimetry, transition electron microscopy and a SQUID magnetometer. Ribbons were melt-spun at different wheel speeds and then were annealed to nucleate nano crystals embedded in the amorphous matrix. The results indicated that the thickness of the ribbons was inversely proportional to the wheel speed following the power law of the type t ∝ Vs -1.231. DSC and XRD results showed that at higher wheel speeds the greater potential energy triggers the formation of Fe (Si) crystallites and thus, increases the crystallinity.... 

We theoretically study a Kitaev chain with a quasiperiodic potential, where the quasiperiodicity is introduced by a Fibonacci sequence. Based on an analysis of the Majorana zero-energy mode, we find the critical p-wave superconducting pairing potential separating a topological phase and a non-topological phase. The topological phase diagram with respect to Fibonacci potentials follow a self-similar fractal structure characterized by the box-counting dimension, which is an example of the interplay of fractal and topology like the Hofstadter's butterfly in quantum Hall insulators. © 2017 The Physical Society of Japan  

Transferring large models in federated learning (FL) networks is often hindered by clients' limited bandwidth. We propose $ extsf {FedAA}$ , an FL algorithm which achieves fast convergence by exploiting the regularized Anderson acceleration (AA) on the global level. First, we demonstrate that FL can benefit from acceleration methods in numerical analysis. Second, $ extsf {FedAA}$ improves the convergence rate for quadratic losses and improves the empirical performance for smooth and strongly convex objectives, compared to FedAvg, an FL algorithm using gradient descent (GD) local updates. Experimental results demonstrate that employing AA can significantly improve the performance of FedAvg,... 

Natural convection in a porous enclosure in the presence of thermal dispersion is investigated. The Fourier–Galerkin (FG) spectral element method is adapted to solve the coupled equations of Darcy’s flow and heat transfer with a full velocity-dependent dispersion tensor, employing the stream function formulation. A sound implementation of the FG method is developed to obtain accurate solutions within affordable computational costs. In the spectral space, the stream function is expressed analytically in terms of temperature, and the spectral system is solved using temperature as the primary unknown. The FG method is compared to finite element solutions obtained using an in-house code... 

Control charts are useful tools of monitoring quality characteristics. One of the problems of employing a control chart is that the time it alarms is not synchronic with the time when assignable cause manifests itself in the process. This makes difficult to search and find assignable causes. Knowing the real time of manifestation of assignable cause (change point) helps to find assignable cause(s) sooner and eases corrective actions to be taken. In this paper, a probabilistic neural network (PNN)-based procedure was developed to estimate the variance change point of a normally distributed quality characteristic. The PNN was selected based on trial and error among different types of... 

Object-oriented frameworks are widely used to develop new applications. They provide reusable concepts that are instantiated in application code through potentially complex implementation steps such as subclassing, implementing interfaces, and calling framework operations. Unfortunately, many modern frameworks are difficult to use because of their large and complex APIs and frequently incomplete user documentation. To cope with these problems, developers often use existing framework applications as a guide. However, locating concept implementations in those sample applications is typically challenging due to code tangling and scattering. To address this challenge, we introduce the notion of... 

This paper studies the energy-limited performance of multi-relay networks. Taking the properties of the power amplifiers (PAs) into account, we derive closed-form expressions for the optimal power allocation, the outage probability and the throughput in the cases with a sum consumed energy constraint. Moreover, we analyze the diversity and the multiplexing gains of the PA-aware systems. Finally, we investigate the performance of large-scale multi-relay networks and develop efficient multi-relay systems with low cooperation overhead. The numerical and the analytical results show that the inefficiency of the PAs affects the outage probability and the throughput of the multi-relay systems... 

Rapid assessment of structural safety and performance right after the occurrence of significant earthquake shaking is crucial for building owners and decision-makers to make informed risk management decisions. Hence, it is vital to develop online and pseudo-online health monitoring methods to quantify the health of the building right after significant earthquake shaking. Many Bayesian inference–based methods have been developed in the past which allow the users to estimate the unknown states and parameters. However, one of the most challenging part of the Bayesian inference–based methods is the determination of the parameter noise covariance matrix. It is especially difficult when the number... 

Online selection of the appropriate model and identifying its parameters based on measured vibrational data are among the challenging issues in dynamic system identification. After a severe earthquake, quick monitoring and assessment of structural health status play a crucial role in effective critical risk management for the building owners and decision-makers. The Bayesian multiple modeling approach is a suitable tool for optimal model class selection, which is used in this article mainly for improving data fitting precision, decreasing dimensions of structural unknown vector through removing unnecessary parameters, detecting the occurrence and type of predominant phenomenon related to... 

Online selection of the appropriate model and identifying its parameters based on measured vibrational data are among the challenging issues in dynamic system identification. After a severe earthquake, quick monitoring and assessment of structural health status play a crucial role in effective critical risk management for the building owners and decision-makers. The Bayesian multiple modeling approach is a suitable tool for optimal model class selection, which is used in this article mainly for improving data fitting precision, decreasing dimensions of structural unknown vector through removing unnecessary parameters, detecting the occurrence and type of predominant phenomenon related to... 

Rapid assessment of structural safety and performance right after the occurrence of significant earthquake shaking is crucial for building owners and decision-makers to make informed risk management decisions. Hence, it is vital to develop online and pseudo-online health monitoring methods to quantify the health of the building right after significant earthquake shaking. Many Bayesian inference–based methods have been developed in the past which allow the users to estimate the unknown states and parameters. However, one of the most challenging part of the Bayesian inference–based methods is the determination of the parameter noise covariance matrix. It is especially difficult when the number... 

We address the noninvasive temperature estimation from pulse-echo radio frequency signals from standard diagnostic ultrasound imaging equipment. In particular, we investigate the use of a high-resolution spectral estimation method for tracking frequency shifts at two or more harmonic frequencies associated with temperature change. The new approach, employing generalized second-order statistics, is shown to produce superior frequency shift estimates when compared to conventional high-resolution spectral estimation methods Seip and Ebbini (1995). Furthermore, temperature estimates from the new algorithm are compared with results from the more commonly used echo shift method described in Simon...