In this paper, recommended spiral passive micromixer was designed and simulated. spiral design has the potential to create and strengthen the centrifugal force and the secondary flow. A series of simulations were carried out to evaluate the effects of channel width, channel depth, the gap between loops, and flowrate on the micromixer performance. These features impact the contact area of the two fluids and ultimately lead to an increment in the quality of the mixture. In this study, for the flow rate of 25 μl/min and molecular diffusion coefficient of 1×10-10 m2/s, mixing efficiency of more than 90% is achieved after 30 (approximately one-third of the total channel length). Finally, the optimized design fabricated using proposed 3D printing method.

Application of the network equivalent concept for external system representation for power system transient analysis is well known. However, the challenge to utilize an equivalent network, approximated by a rational function, is to guarantee the passivity of the corresponding model. In this regard, special techniques are required to enforce the passivity of the equivalent model through a post processing approach that minimizes its impact on the original model characteristics. In this paper, the passivity is enforced by expressing the problem in terms of a convex optimization problem that guarantees the global optimal solution. The convex optimization problem is efficiently solved by recently developed numerical interior–point methods. This passivity enforcement is also global which indicates that the passivity enforcement in one region does not lead to passivity violation in other regions.

The increasing growth of computers and the internet has provided a new and widely used platform for providing network services. This has significantly increased the provision of administrative, social, financial, educational and recreational services on the network, particularly the internet. The expansion of the use of Internet applications creates an opportunity to abuse the network and its information for criminal purposes. Based on this, intrusion into the network and unauthorized access to information have become the main concerns of network users as well as network managers. Intrusion detection systems include a set of tools and mechanisms for monitoring computer systems and network traffic. Various methods are used for intrusion detection, such as statistical techniques, cognitive-based methods, and machine learning methods. In the present research, a method for intrusion detection using machine learning algorithms was reviewed and proposed. The proposed model is a multi-class method that, in addition to intrusion detection, also determines the type of attack. This method is a hybrid model in which the combination of the Seagull optimization algorithm, thermal exchange optimization algorithms and random forest algorithm are used. CICIDS-2017 dataset was used for analysis in this research. The proposed method was compared with several different algorithms and the accuracy value of the proposed method was equal to 98.8, which is higher than that of many machine learning methods.

Heat transfer in foams consists of conduction through solid and gaseous phases, convection within the cells as well as radiation through the whole medium. Radiation thermal conduction affects the overall thermal conductivity by 40% in a high porosity. Therefore, the investigation of that term seems to be necessary. Radiation thermal conduction depends on the extinction coefficient which its determination is experimentally complex. In this study, this coefficient is theoretically estimated using Glicksman model for polyolefin foams and is verified in comparison with the experimental data. Extinction coefficient which plays an effective role in the radiation thermal conduction depends on the morphological properties including foam and solid densities, cell and strut diameters. The results demonstrate that the radiation thermal conduction decreases by reducing cell size and increasing foam density and strut diameter. An L25 orthogonal array of Taguchi approach is used for optimization of radiation thermal conduction respect to foam density, cell and strut diameters as variable parameters. The analysis of variance results illuminate that foam density and cell diameter with 58 and 32% contribution are the most effective parameters on the radiation thermal conduction, respectively. At optimum conditions according to the prediction tool of Taguchi approach, the radiation thermal conduction significantly decreases to 1.0908 mW/mK.

In this paper, the optimization of long term operation and determination of the reliability level of a hydro-thermal power system are integrated into a unified model. Inflow to reservoirs is modeled as a random variable. Furthermore, the demand for energy is also assumed to be a random variable with normal distribution. In order to minimize the total cost, the reliability level of the system is determined, rather than considering it as a priori input data. Since the resulting model is a large-scale stochastic nonlinear programming, it is necessary to develop a special method to solve it. This method, which provides an optimal solution within three stages, consists of a decomposition technique, Lagrangian relaxation and nonlinear and dynamic programming methods. To test the method, it has been implemented in Khuzestan power system and the results are compared with the existing operation procedures.

The efficiency of a household thermostat solar water heater model with two flat panel collectors and a double-glazed storage tank of 200 liters capacity was investigated experimentally. Water and glycol (antifreeze) are used as operating fluid in the water heater to be transformed into thermosyphon with free movement and increase the temperature of consumed water. Water is not discharged during the test period. Flow temperatures of collector input and output, city water temperature, water temperatures at different points in the reservoir and ambient temperature for sunny days in the autumn in Tehran. Measurement and flow rate of the thermosyphon, thermal energy of the water consumed and total water efficiency The aforementioned heater has been calculated and the corresponding graphs are given over time. The results show that the highest water temperature is 60 °C on sunny days and 50 °C on cloudy days. The overall efficiency of the thermostat solar thermal heater will be around 45درصد during the month of November 1396. The highest photovoltaic panel efficiency in the sunny days is 13.5% in the autumn and 11.6% in the cloudy days, which is due to the decrease in efficiency compared to the ideal conditions. The surface temperature of the panel is high.

Thermal energy storage is among the highly efficient approaches to overcome the energy crisis. Using phase change material (PCM) is one of the most effective techniques in thermal energy storage applications. Several types of PCM with distinct characteristics and different ranges of melting and solidification temperature have found their way in various industries. However, commercialized PCMs generally suffer from low thermal conductivity which limits their application. In this study, the effect of adding different weight percentages of various nanoparticles, such as CuO, TiO2, Al2O3 and graphene to paraffin, as a standard PCM, on the improvement of the thermal properties of PCM was investigated. Thermophysical properties and morphology of the nanocomposites, such as phase change temperature and latent heat of melting were characterized by Differential Scanning Calorimetry (DSC), Scanning Electron Microscope (SEM), and Fourier Transform Infrared Spectroscopy (FT-IR). SEM images display the proper distribution of nanoparticles in phase change material. FTIR results verified the formation of nanocomposites. A comparison between the investigated PCM nanocomposites showed that the nanocomposites containing 2 wt. % TiO2 with the enthalpy of 179. 88 J/g, and 1 wt. % graphene nanocomposite with the enthalpy of 120. 38 J/g had the highest and lowest energy storage capacity compared to paraffin, respectively. The results indicated that Nano-enhanced phase change materials (NEPCMs) could be particularly useful in applications in which temperature control is crucial. The new types of nanocomposites used in this study showed remarkable thermal performance, and they are capable of being used in thermal management applications. © 2020 Journal of Energy Management and Technology.

An industrial ethane thermal cracking reactor was modeled assuming a molecular mechanism for the reaction kinetics coupled with material, energy, and momentum balances of the reactant-product flow along the reactor. To carry out the multi-objective optimization for two objectives such as conversion and ethylene selectivity, the elitist non-dominated sorting genetic algorithm was used. The Pareto optimum set was obtained successfully and finally the effect of the decision variable was discussed.

In recent years, multi-energy microgrids including electricity, gas and thermal are more grown; that presents demand response (DR) models considering multi-energy storages and renewable resources. Appropriate DR management with storages may lead to optimal flexibility. In this paper, a probabilistic linear model is introduced to assess the effect of flexibility and DR. In the proposed model, electrical and thermal DR, multi-energy storages, and participation in reserve market are considered as the main contribution. The proposed model guarantees thermal comfort as well as increasing flexibility and reserve commitment. By applying the proposed method on a distribution network in UK, it is illustrated that by utilization of the proposed DR program the flexibility of microgrid increases and the cost of operation decreases.