Sharif Digital Repository

Dolomite base refractories have advantages such as high refractoriness, potential to produce pure steel molten, high alkaline corrosion resistance, and economical for consumers. However, application of these refractories has been limited due to their high potential to hydration with atmosphere humidity. In this research work, the impact of ZrSiO4 nanoparticles addition on the physical, thermo-mechanical, mechanical, and microstructure of the dolomite base refractories is investigated. Also, XRD and SEM/EDX analyses were used for determining generated ceramic phases and microstructure evaluation, respectively. Up to 3 wt% ZrSiO4 nanoparticles were added to the compositions. Compositions fired... 

The high hydration potential of CaO and MgO phases restricted the application of Mag-Dol refractory composites. In this study, the impact of nano-silica (SiO2) addition on the physical, mechanical, thermo-mechanical as well as microstructure of Mag-Dol refractory composites is investigated. Mag-Dol compositions were prepared by using calcined dolomite and magnesite particles (micron, 0–1, 1–3, 3–5, and 5–8 mm), liquid resin, and 0, 0.5, 1, 1.5, 2, and 2.5 wt% nano SiO2 as additives. Specimens were heated up to 1650 °C for the 3 h soaking period. Fired specimens were characterized by physical (apparent porosity, bulk density, and hydration resistance), mechanical (cold crushing strength), and... 

Many benefits of the MgO-C refractory bricks such as excellent corrosion resistance, high thermal shock resistance, good mechanical strength at high temperatures, and permeability have attracted attention of consumers in various industries. But on the other hand, the low oxidation resistance of these refractory bricks at high temperatures has restricted their application. For this purpose, in this research study, the impact of Nano-ZrSiO4 addition on microstructure and performance of MgO-C refractory was investigated. 0, 0.5, 1, 1.5, and 2 wt % of Nano-ZrSiO4 was added to compositions. After samples preparation, all specimens tempered and fired (in a coke bed) at the 250 °C and 1600 °C for 8... 

In this work the effect of nano- and microZrO2 addition on the densification and hydration resistance of MgO–CaO refractories was investigated. 0, 2, 4, 6 and 8 wt% ZrO2 was added to MgO–CaO refractories that contain 35 wt% CaO. The crystalline phases and microstructure characteristics of specimens sintered at 1650 °C for 5 h in an electric furnace were studied by X-ray diffraction (XRD) and scanning electron microscopy (SEM), respectively. The physical properties are reported in terms of bulk density, apparent porosity and hydration resistance. Results show that with addition of ZrO2 the bulk density and hydration resistance of the samples increased while apparent porosity decreased. Also... 

In this research study, a comparative evaluation of the additional impact of nanometer-sized tetravalent oxides [Zirconia (ZrO2), Titania (TiO2), and Silica (SiO2)] on the properties and performance of Doloma-Magnesia (MgO-CaO) ceramic refractories, with an emphasis on their hydration resistance improvement, has been done. For this purpose, from 0 to 2.5 wt% ZrO2, TiO2, and SiO2 nanometer-sized particles have been added to the Doloma-Magnesia compositions. After formulation and mixing of the starting materials, the pressed samples (at 150 MPa) were tempered (at 250 °C for 12 h) and fired in a shuttle furnace (at 1650 °C for 3 h). The physical, mechanical, and thermo-mechanical properties of... 

The existing learning methods usually assume that training data and test data follow the same distribution, while this is not always true. Thus, in many cases the performance of these methods on the test data will be severely degraded. In this paper, we study the problem of unsupervised domain adaptation, where no labeled data in the target domain is available. The proposed method first finds a new representation for both the source and the target domain and then learns a prediction function for the classifier by optimizing an objective function which simultaneously tries to minimize the loss function on the source domain while also maximizes the consistency of manifold (which is based on... 

Traditional learning algorithms cannot perform well in scenarios where training data (source domain data) that are used to learn the model have a different distribution with test data (target domain data). The domain adaptation that intends to compensate this problem is an important capability for an intelligent agent. This paper presents a domain adaptation method which learns to adapt the data distribution of the source domain to that of the target domain where no labeled data of the target domain is available (and just unlabeled data are available for the target domain). Our method jointly learns a low dimensional representation space and an adaptive classifier. In fact, we try to find a... 

Almost all of the existing domain adaptation methods assume that all test data belong to a single stationary target distribution. However, in many real world applications, data arrive sequentially and the data distribution is continuously evolving. In this paper, we tackle the problem of adaptation to a continuously evolving target domain that has been recently introduced. We assume that the available data for the source domain are labeled but the examples of the target domain can be unlabeled and arrive sequentially. Moreover, the distribution of the target domain can evolve continuously over time. We propose the Evolving Domain Adaptation (EDA) method that first finds a new feature space... 

Sensor networks usually generate mass of data, which if not structured for future applications, will require much effort on analytical processing and interpretations. Thus, storing sensor data in an effective and structured format is a key issue in the area of sensor networks. In the meantime, even a little improvement on data storing structure may lead to a significant effect on the lifetime and performance of the sensor network. This paper describes a new method for sensor storage that combines semantic web concepts, a data aggregation method along with aligning sensors in hierarchical form. This solution is able to reduce the amount of data stored at the sink nodes significantly. At the... 

Four 5-, 10-, 20- and 30-story moment frames, representing low-, mid-, and two high-rise structures, were subjected to a great number of idealized directivity pulses. The amplitudes and periods of pulses vary from 0.02 g to 1.0 g and 0.5 to 12 sec, respectively. Over 1400 nonlinear dynamic analyses of low- to high-rise moment frames were performed which were feasible through using modified fish-bone model. The distribution of interstory drift along the height was studied and two applied contours were proposed: (i) the maximum interstory drift contour, and (ii) the critical story contour. These contours were demonstrated versus the ratio of natural period of the structure to the pulse period... 

In this article singular points of a parallel manipulator are obtained based on a novel geometrical method. Here we introduce the constrained plain method (CPM) and some of its application in parallel mechanism. Given the definition of constraint plane (CP) and infinite constraint plane (ICP) the dependency conditions of constraints is achieved with the use of a new theorem based on the Ceva geometrical theorem. The direction of angular velocity of a body is achieved by having three ICPs with the use of another theorem. Finally, with the use of the above two novel theorems singularities of the 3UPF_PU mechanism are obtained. It should be emphasized that this method is completely geometrical,... 

An analytical model is proposed to study the effect of particle size on melting enthalpy and entropy of metallic nanoparticles (NPs). The Mott's and Regel's equations for melting entropy in the combination of core average coordination number (CAC) and surface average coordination number (SAC) of freestanding NPs are considered. Clusters of icosahedral (IC), body centered cubic (BCC), and body centered tetragonal (BCT) structure without any vacancies and defects are modeled. Using the variable coordination number made this model to be in good agreement with experimental and molecular dynamic (MD) results of different crystal structures. The model predicts melting entropy and enthalpy of... 

Grinding is widely used for manufacturing of components that require fine surface finish and good dimensional accuracy. In this study a thermo-mechanical finite element analysis is conducted to find out how grinding parameters can affect temperature and residual stress distribution in the workpiece. Results of parametric study presented in this work indicate, by carefully selecting the grinding parameters, minimum thermal and mechanical damage can be achieved. Higher workpiece velocities produce higher surface residual stress. By increasing depths of cut, depth of tensile residual stresses increases. Convection heat coefficient does not have any considerable effect on surface residual stress... 

Adaptive Noise Cancellation (ANC) is a well-known technique for background noise reduction in automobile and vehicular environments. The noise fields in automobile and other vehicle interior obey the diffuse noise field model closely. On the other hand, the ANC does not provide sufficient noise reduction in the diffuse noise fields. In this paper, a new multistage post-filter is designed for ANC as a solution to diffuse noise conditions. The designed post-filter is a single channel Linear Prediction (LP) based speech enhancement system. The LP is performed by an adaptive lattice filter and attempts to extract speech components by using intermediate ANC signals. The post-filter has no... 

Self-Compacting Concrete (SCC) is a unique type of concrete that can flow and fill spaces without the need for vibrating compaction, resulting in a dense and uniform material. This article focuses on estimating the compressive strength of SCC utilizing Artificial Neural Networks. Specifically, the study employs multilayer perceptrons with back-propagation learning algorithms, which are commonly used in various problem-solving scenarios. The study covers essential components such as structure, algorithm, data preprocessing, over-fitting prevention, and sensitivity analysis in MLPs. The input variables considered in the research include water, fine aggregate, super-plasticizer, fly ash, coarse... 

Seismic retrofits can significantly reduce the vulnerability of masonry buildings. Multiple seismic retrofit alternatives are often available for a given building. Estimating the cost of each candidate action is essential to selecting and implementing the appropriate seismic retrofit initiatives. This research harnesses the capabilities of various regression models for cost estimation. A dataset from 167 retrofit projects for masonry school buildings was used to develop models. Three main retrofit actions were taken into consideration: shotcrete, steel belt and fiber-reinforced polymer. Various regression methods, including multiple linear regression, ridge regression, lasso regression, and... 

Shot peening is widely used to improve the fretting fatigue strength of critical surfaces. Fretting fatigue occurs in contacting parts that are subjected to fluctuating loads and sliding movements at the same time. This paper presents a sequential finite element simulation to investigate the shot peening effects on normal stress, shear stress, bulk stress and slip amplitude, which are considered to be the controlling parameters of fretting damage. The results demonstrated that among the modifications related to shot peening, compressive residual stress has a dominant effect on the fretting parameters  

One-dimensional (1D) MgO structures were successfully synthesized via carbothermic reduction of mechanically activated mixture of MgO and graphite. Mechanical activation of source materials before carbothermic reduction can substantially enhance the formation of MgO products at a temperature (1000 °C) relatively lower than that required in previous approaches (≥1200 °C). However, the morphology of MgO formed is dependent on the degree of mechanical activation and the condition of the subsequent carbothermic reduction. Two distinctive morphologies were found for MgO products synthesized using our method: single crystalline nanorods with rectangular cross-sections whose diameters range from 50... 

Attitude and vibration control of a general form of flexible satellites is addressed in this paper. Partial differential dynamic equations are derived considering new details such as multi sectioned solar panels and elastic connections between main hub and solar panels. Boundary control approach is adopted to eliminate simplification errors of discrete models, using just one actuator in the hub. Asymptotic stability of attitude dynamics is proved for a group of boundary controllers and necessary conditions for asymptotic stability of vibrations are discussed. Being independent of modeling accuracy and using easily measurable feedbacks are among advantages of the proposed class of...