Sharif Digital Repository

Minimum variance control is an established method in control of systems corrupted by noise. In these cases, as it is not possible to directly control the actual value of the system variables, one aims to reduce the variations instead. However, when the system noises are non-Gaussian, this approach fails because non-Gaussian noise cannot be characterised by simple measures such as variance. In these cases, the Entropy is proposed as a generalisation of the variance measure and the control objective becomes that of minimising the Entropy. Previously a limited form of this problem has been solved using first order Newtonian methods. In this paper, the control objective is first expanded to also... 

In order to examine the impact of structural and thermal scale parameters on thermoelastic vibrations of Euler-Bernoulli nanobeams, this article intends to provide a size-dependent generalized thermoelasticity model with the help of nonlocal strain gradient theory (NSGT) in conjunction with dual-phase-lag (DPL) heat conduction model. To highlight the role of each scale parameter in size-dependent motion and heat conduction equations, normalized forms of these nonclassical coupled thermoelastic equations are extracted by introducing and exploiting some dimensionless parameters. By exploiting power series expansion as a general solution for arbitrary boundary conditions, system of partial... 

In order to examine the impact of structural and thermal scale parameters on thermoelastic vibrations of Euler-Bernoulli nanobeams, this article intends to provide a size-dependent generalized thermoelasticity model with the help of nonlocal strain gradient theory (NSGT) in conjunction with dual-phase-lag (DPL) heat conduction model. To highlight the role of each scale parameter in size-dependent motion and heat conduction equations, normalized forms of these nonclassical coupled thermoelastic equations are extracted by introducing and exploiting some dimensionless parameters. By exploiting power series expansion as a general solution for arbitrary boundary conditions, system of partial... 

At present, nanoparticles are used for various biomedical applications where they facilitate laboratory diagnostics and therapeutics. More specifically for drug delivery purposes, the use of nanoparticles is attracting increasing attention due to their unique capabilities and their negligible side effects not only in cancer therapy but also in the treatment of other ailments. Among all types of nanoparticles, biocompatible superparamagnetic iron oxide nanoparticles (SPIONs) with proper surface architecture and conjugated targeting ligands/proteins have attracted a great deal of attention for drug delivery applications. This review covers recent advances in the development of SPIONs together... 

Experiments were conducted to investigate the effect of adding fines on the tribo-charging of coarse glass beads. Four types of fines, i.e., copper, stainless steel, uncoated and silver-coated fine glass beads, mixed with 240–830 μm glass beads were conveyed by air through a stainless-steel spiral pipe acting as a tribo-charger. Regardless of the type or electrical conductivity of the fine particles tested, adding small amounts of fines (up to 10 wt%) to coarse glass beads resulted in a sharp increase in the mass and surface charge densities of the particles. In general, the profiles of the mass and surface charge densities of the fine–coarse particle mixtures as a function of the mixture... 

In this paper, a systematic method is presented for modeling a multi-machine power system with multiple UPFC's installed and the dynamic interaction between different control functions of the UPFCs investigated. Study undertaken on New England power systems demonstrates that the existence of dynamic interaction may lead to the instability of the whole system  

This paper develops an economic production quantity model for a multi-product multi-objective inventory control problem with fuzzy-stochastic demand and backorders. In this model, the annual demand is represented by trapezoidal fuzzy random numbers. The centroid defuzzification and the expected value methods are applied to defuzzify and make decisions in a random environment. In the case where the warehouse space is limited, the Lagrangian relaxation procedure is first employed to determine the optimal order and the maximum backorder quantities of the products such that the total inventory cost is minimized. The optimal solution obtained by the proposed approach is compared with that... 

DeePore2 is a deep learning workflow for rapid estimation of a wide range of porous material properties based on the binarized micro–tomography images. By combining naturally occurring porous textures we generated 17,700 semi–real 3–D micro–structures of porous geo–materials with size of 2563 voxels and 30 physical properties of each sample are calculated using physical simulations on the corresponding pore network models. Next, a designed feed–forward convolutional neural network (CNN) is trained based on the dataset to estimate several morphological, hydraulic, electrical, and mechanical characteristics of the porous material in a fraction of a second. In order to fine–tune the CNN design,... 

Connected and autonomous vehicles (CAVs) have the potential to drastically change the structure of future cities and regions. Researchers predict different outcomes to result from the emergence of CAV technology. While some see their potential as amounting to a complete overhaul of the transport system, others predict the technology will be slow to be adopted and may face competition from other mobility options such as drones. Therefore, the future can be viewed along a spectrum, ranging from no CAVs to a fully driverless transport system. This paper presents an overview of the past attempts on studying CAVs and their impacts to provide a comprehensive view about possible futures with CAVs.... 

Accurate customer baseline load (CBL) estimation is critical for implementing incentive-based demand response (DR) programs. The increasing penetration of grid-tied distributed photovoltaic systems (DPVS) complicates customers’ load patterns, making the CBL estimation more difficult because the volatile actual load and the intermittent PV output power are coupled together. A PV-load decoupling framework is proposed in this paper to address the above issue. The basic idea is to decouple the actual load power and the PV output power, then estimate them separately. To this end, historical PV output power data of each individual DPVS is required. However, pure historical PV output power data is... 

The adhesion and mechanical properties of hydrogels used for vascular wound repair often deteriorate dramatically on wet surfaces, resulting in ineffective repair. In this work, a poly(N-isopropyl acrylamide-co-dopamine methacrylamide) nanogel with dopamine groups was synthesized and introduced into a polyacrylamide (PAAm) hydrogel to produce temperature-responsive hydrogels, which greatly improved mechanical and adhesive properties of PAAm hydrogels. Nanogel-reinforced PAAm (NR-PAAm hydrogel) can adhere to the surface of various solid materials and biological tissues through special physical interactions, which exhibited different mechanical and adhesion properties as temperature changes... 

Bipolar Plates (BPPs) are the most crucial component of the Polymer Electrolyte Membrane (PEM) fuel cell system. To improve fuel cell stack performance and lifetime, corrosion resistance and Interfacial Contact Resistance (ICR) enhancement are two essential factors for metallic BPPs. One of the most effective methods to achieve this purpose is adding a thin solid film of conductive coating on the surfaces of these plates. In the present study, 410 Stainless Steel (SS) was selected as a metallic bipolar plate. The coating process was performed using titanium nitride and chromium nitride by the Cathodic Arc Evaporation (CAE) method. The main focus of this study was to select the best coating... 

Traditional fluorescence switching molecules achieving the state change between on and off states commonly based on UV irradiation. However, it is worth noting that UV irradiation is harmful to both the cancer cells and the normal cells. To achieve fluorescence switching under visible wavelength and avoid complicate molecular design, a fluorophore of 2,4,5,6-tetrakis(carbazol-9-yl)-1,3-dicyanobenzene (4CzIPN) and a quencher of diarylethene (DAE) were physically incorporated within the biocompatible block copolymer poly(lactic-co-glycolic acid)-b-poly(ethylene glycol) (PLGA-b-PEG) to form 4CzIPN-DAE nanoparticles (NPs) through flash nanoprecipitation (FNP). By using the FNP method, the NPs... 

The effect of moisture on Shengli lignite breakage behavior and energy efficiency was studied experimentally using a standard Hardgrove mill fitted with a wattmeter. The grinding process concerned both the inputs, namely the occurrence and content of water and instantaneous energy consumption and the outputs, size-reduction and product fineness. Results show that the energy-size reduction process for grinding lignite is markedly influenced by moisture occurrence and content. Removing surface moisture from 37.90% to 16.61% (the air-dried condition) resulted in a slight increase of input energy by 0.04 kWh.t−1 per 10 s. However, with further drying inherent moisture to 0%, the consumed energy... 

Often, recommendation systems employ continuous training, leading to a self-feedback loop bias in which the system becomes biased toward its previous recommendations. Recent studies have attempted to mitigate this bias by collecting small amounts of unbiased data. While these studies have successfully developed less biased models, they ignore the crucial fact that the recommendations generated by the model serve as the training data for subsequent training sessions. To address this issue, we propose a framework that learns an unbiased estimator using a small amount of uniformly collected data and focuses on generating improved training data for subsequent training iterations. To accomplish... 

The earned value management (EVM) model is an essential technique for managing and forecasting project features such as scheduling and cost performances indexes. This paper presents a novel fuzzy earned-value model based on Z-number theory incorporating both the impreciseness of real life conditions and a degree of reliability through considering an expert judgment process. The latter factor has not been used by other researchers in the field. The proposed model provides a reliable assessment for the progress performance of a project and its 'at completion' cost in an uncertain environment. Finally, an illustrative case demonstrates the applicability of the proposed model in real life... 

This study proposes a multi-objective control algorithm for simultaneous process and quality control in non-Gaussian stochastic batch processes. The objective is to control a non-Gaussian process so that each batch is delivered within a pre-specified time. During each batch, the process is controlled by a fixed-parameter PI controller. Between any two adjacent batches the controller parameters are updated by a differential evolution algorithm so that the integral squared of tracking error, entropy of tracking error, integral of absolute processing time error and entropy of processing time error are minimised. the proposed algorithm is applied to a batch continuously stirred tank reactor... 

The aeroelastic flutter characteristics of a functionally graded carbon nanotube reinforced composite (FG-CNTRC) truncated conical shell under simultaneous actions of a hydrostatic pressure and yawed supersonic airflow are scrutinized. The nonlinearity in geometry of the conical shell is considered in Green–Lagrange sense and the model is derived according to the Novozhilov nonlinear shell theory. The aerodynamic pressure is modeled based on the quasi-steady Krumhaar's modified supersonic piston theory by considering the effect of the panel curvature and flow yaw angle. Parametric studies are conducted to investigate the effects of boundary conditions, semi-vertex angle, distribution and... 

The present research deals with bifurcation and vibration responses of a composite truncated conical shell with embedded single-walled carbon nanotubes (SWCNTs) subjected to an external pressure and axial compression simultaneously. The distribution of reinforcements through the thickness of the shell is assumed to be either uniform or functionally graded. The equations of motion are established using Green-Lagrange type nonlinear kinematics within the framework of Novozhilov nonlinear shell theory. Linear membrane prebuckling analysis is conducted to extract the prebuckling deformations. The stability equations are derived by applying the adjacent equilibrium criterion to the prebuckling... 

The Stochastic Distribution Control (SDC) problem is a generalised form of the minimum variance control problem where non-Gaussian noise distributions are encountered. The problem has been previously solved using two alternative approaches. When it is assumed that the output Probability Distribution Function (PDF) is measurable, then a parameterized controller is obtained. If on the other hand this assumption is removed (which corresponds to most practical cases), then the controller found is no longer parameterisable (i.e. it is a control action sequence). Both these approaches have thus far been solved using local Newtonian methods. In this paper a third alternative is presented which...