Sharif Digital Repository

Evaporative condensers are regarded as highly-efficient and eco-friendly heat exchangers in refrigeration systems. Data-driven methods can play a key role in performance prediction of evaporative condensers, conducted without the complexity of theoretical analysis. In this study, four machine learning models including multi-layer perceptron artificial neural network (ANNMLP), support vector regression (SVR), decision tree (DT), and random forest (RF) models have been employed to predict heat transfer rate and overall heat transfer coefficient of a small-scale evaporative condenser functioning under a wide range of working conditions. A set of experimental tests were conducted, where inlet... 

In the present study, the effects of rotary tubes and magnetic-induced nanofluid on heat transfer characteristics of a compact heat exchanger are individually investigated. Two-phase Eulerian model is employed to predict the hydrothermal and entropic characteristics of Fe3O4/water ferrofluid in the heat exchanger. Results indicate that utilizing each rotary tubes and magnetic field method can improve the energy and exergy efficiencies of the compact heat exchanger under specific circumstances by forming different types of secondary flow. It is found that employing each method individually can increase the maximum heat transfer rate by more than 60%. In comparison with methods like passive... 

This letter discusses the surface-reconstruction-induced self-twisting behavior of Si100 nanobelts and nanowires (NWs) with rectangular cross section. Giving a thorough physical interpretation, we explain the reason behind this phenomenon and present a continuum-based model. It is revealed that these structures can self-assemble into both right- and left-handed helicoids depending on their crystal arrangements. More specifically, for NWs with the same number of layers in each of their cross sections directions, two distinct values of torsion angle are possible for each of right- and left-handed twisted morphologies. In conclusion, four modes of torsion can be observed in Si100 NWs.... 

This article presents a novel identification approach which can deal with nonlinear and time-varying characteristics of complex dynamic systems, especially an aerial vehicle in the entire flight envelope. A set of local sub-models are first developed at different operating points of the system, and subsequently a self-organizing multi-model ensemble is introduced to aggregate the outputs of the local models as a single model. The number of employed local models in the proposed multi-model ensemble is optimized using a novel self-organizing approach. Also, wavelet neural networks, which combine both the universal approximation property of neural networks and the wavelet decomposition... 

With the exception of a few works, the current approaches to aerial manipulation control do not typically consider the system constraints in the control design process. Also, the issue of closed-loop stability in the presence of system constraints is not thoroughly analyzed. In this paper, a novel multi-stage model predictive control (MPC)-based approach for aerial manipulation is proposed to ensure the closed-loop stability in the presence of model uncertainties and external disturbances, while satisfying the operational constraints. The detailed nonlinear model of a general aerial manipulator, consisting of a quadrotor equipped with a 3 degrees of freedom manipulator, is first developed... 

In this study, the application of data-driven methods for performance prediction of a heat pump assisted humidification-dehumidification (HDH-HP) desalination system was investigated for the first time. Although HDH-HP desalination systems have been widely studied both theoretically and experimentally, the application of data-driven models as a powerful predictive tool has not yet been investigated in these systems. To fill this gap, three data-driven models (MLPANN, RBFANN, and ANFIS) were applied using 180 experimental samples. The gain output ratio (GOR), heat transfer rates of the evaporator Q̇e, and evaporative condenser Q̇c, were considered as outputs. The results indicate that the... 

This manuscript presents a framework to develop vector error correction (VEC) models applicable to forecasting the short- and long-run movements of the average hourly earnings of construction labor, which is an essential predictor of the construction labor costs. These models characterize the relationship between average hourly earnings and a set of explanatory variables. The framework is applied to develop VEC forecasting models for the average hourly earnings of construction labor in the USA based on the identified variables that govern its movements, such as Global Energy Price Index, Gross Domestic Product, and Personal Consumption Expenditures. More than 150 candidate VEC models were... 

Quality of Service (QoS) of Web services plays an essential role in selecting Web services by consumers. The dynamic QoS attributes of Web services have different values for different users. Therefore, the value of many Web services' QoS features for many users are undetermined, and these values should be predicted. The collaborative filtering (CF) method is one of the most successful approaches to predict these values. CF-based methods use the QoS values contributed by the other users for prediction and, consequently, the values contributed by unreliable users can decrease the accuracy of prediction. To utilize the reputation of users can be regarded as one of the conventional approaches to... 

In the present work, a fuzzy supervisory control approach combined with an adaptive model predictive controller (AMPC), has been proposed to maximize the productivity of an anaerobic digestion (AD) process, while keeping the operation stable. In the proposed hierarchal control strategy, the set-point of the inner loop is provided by a supervisory controller. In the inner loop an AMPC has been applied to achieve the desired methane production rate by manipulating the feed flow rate. The AMPC is designed based on the auto-regressive moving average (ARMA) model whose parameters are updated at each sampling time to make the controller more robust against uncertainties and external loads. In the... 

Predicting seismic damage spectra, capturing both structural and earthquake features, is useful in performance-based seismic design and quantifying the potential seismic damage of structures. The objective of this paper is to accurately predict the seismic damage spectra using computational intelligence methods. For this purpose, an inelastic single-degree-of-freedom system subjected to a set of earthquake ground motion records is used to compute the (exact) spectral damage. The Park-Ang damage index is used to quantify the seismic damage. Both structural and earthquake features are involved in the prediction models where multi-gene genetic programming (MGGP) and artificial neural networks... 

In this paper, the evolution of elastic–plastic damage in the composite laminates under fatigue conditions is modeled. Continuum damage mechanics (CDM) has been coupled with the bridge micromechanics model to estimate the fatigue damage and life for laminated composite structures. Based on the elastic–plastic bridging model, three damage variables are defined. These variables estimate the fiber, matrix, and fiber/matrix damage response at the ply scale. To model the beginning of plastic deformation, a yield function is utilized, and evolution equations of the damage variables are obtained. Then the developed deformation plastic model is calculated. The model parameters are calibrated by... 

The increased amount of multi-modal medical data has opened the opportunities to simultaneously process various modalities such as imaging and non-imaging data to gain a comprehensive insight into the disease prediction domain. Recent studies using Graph Convolutional Networks (GCNs) provide novel semi-supervised approaches for integrating heterogeneous modalities while investigating the patients’ associations for disease prediction. However, when the meta-data used for graph construction is not available at inference time (e.g., coming from a distinct population), the conventional methods exhibit poor performance. To address this issue, we propose a novel semi-supervised approach named GKD... 

In United States (U.S.), government-funded organizations, such as NLDAC, reimburse travel and subsistence expenses incurred during living-organ donation process. However, in Iran, there is a non-governmental organization called Iranian Kidney Foundation (IKF) that funds the direct and indirect costs of donors through charitable donations and contributions from participants in the exchange program. In this article, for countries outside the U.S. that currently use an equality approach, we propose a potential new compensation-apportionment approach (equitable approach) for kidney-exchange chains and compare it with the currently available system (equality approach) in terms of the... 

A diffusion tensor imaging (DTI) -based statistical micromechanical model was developed to study the effect of axonal fiber architecture on the inter- and intra-regional mechanical heterogeneity of the white matter. Three characteristic regions within the white matter, i.e., corpus callosum, brain stem, and corona radiata, were studied considering the previous observations of locations of diffuse axonal injury. The embedded element technique was used to create a fiber-reinforced model, where the fiber was characterized by a Holzapfel hyperelastic material model with variable dispersion of axonal orientations. A relationship between the fractional anisotropy and the dispersion parameter of... 

This paper introduces a cyber-physical system for building automation and control that is developed based on a distributed model predictive control. The implemented distributed method significantly reduces computation overhead with respect to the centralized methods. However, continuous data transfer between subsystems, which are often far from each other, is required when using this method. Information transmission between subsystems is very often subject to the limitations of transmission bandwidth and/or short communication range resulting in significant communication overhead. This causes significant time latency between making measurements and applying control commands, which adversely... 

Resolver is an electromagnetic position sensor typically used in the closed-loop control of permanent magnet synchronous motors (PMSMs). In terms of structure and principle of operation, resolvers are very similar to electrical machines. In this regard, different numerical and analytical models have been developed for the performance prediction of a resolver, with a compromise between computational burden and accuracy. Therefore, a fast and accurate hybrid model of the resolver is presented in this article, which can be used for resolvers with different structures. Additionally, this model can easily be implemented in software such as MATLAB/SIMULINK. The performance of different variable... 

Industrial processes are inherently nonlinear with input, state, and output constraints. A proper control system should handle these challenging control problems over a large operating region. The robust model predictive controller (RMPC) could be an linear matrix inequality (LMI)-based method that estimates stability region of the closed-loop system as an ellipsoid. This presentation, however, restricts confident application of the controller on systems with large operating regions. In this paper, a dual-mode control strategy is employed to enlarge the stability region in first place and then, trajectory reversing method (TRM) is employed to approximate the stability region more accurately.... 

In this paper, a hierarchical predictive controller is designed in order to solve the tracking problem of a moving ground target by a quad-rotor in an unknown and uneven environment. This controller has internal and external predictive controller levels. In the lower layer of the controller, a constrained predictive controller is designed that is capable of rejecting perturbations and quickly tracking the reference path, and in the outer loop, a model predictive controller is designed to optimally detect the moving ground target where, the sub-cost functions were defined so that the quad-rotor would be able to track the moving ground target even if it was temporarily out of sight of the... 

Viscosity of mixed oil is an important parameter which is required in transportation and production processes of mixed crude oils. There is no universal and general model for prediction of viscosity of mixed oils at different conditions. Hence, developing simple, accurate and general models for prediction of mixed oil viscosity is of great importance. In this work three computer based models named MLP-NN, PSO-RBF and Hybrid-ANFIS were developed for prediction of viscosity of mixed oils. A number of 513 experimental data covering wide ranges of influencing parameters were utilized to develop the models. The accuracy of predictions of the developed models was examined by using different... 

AISI 304 stainless steel is very widely used for industrial applications due to its good integrated performance and corrosion resistance. However, shot peening (SP) is known as one of the effectual surface treatments processes to provide superior properties in metallic materials. In the present study, a comprehensive study on SP of AISI 304 steel including 42 different SP treatments with a wide range of Almen intensities of 14–36 A and various coverage of 100–2000% was carried out. Varieties of experiments were accomplished for the investigation of the microstructure, grain size, surface topography, hardness and residual stresses as well as axial fatigue behavior. After experimental...