In this paper, the optimum coordination of an energy hub system, fed with multiple fuel options (natural gas, wood chips biomass, and electricity) to guarantee economically, environmentally friendly, and reliable operation of an energy hub, is presented. The objective is to lessen the total operating expenses and CO2 emissions of the hub system. Additionally, the effect of renewable energy sources as photovoltaics (PVs) and wind turbines (WTs) on energy hub performance is investigated. A comparison of various configurations of the hub system is done. The proper planning of the hub elements is determined by a multi-objective particle swarm optimization (PSO) algorithm to achieve the lowest level of the gross running cost and total system emissions, simultaneously. The outcomes show that the natural gas turbine (NGT) is superior to the biomass generating unit in lowering the gross operating expenses, while using the biomass wood chips plant is most effective in lessening the total CO2 emissions than the NGT plant. Furthermore, the combination of the natural gas turbine, biomass generator, photovoltaics, and wind turbines enhances the operation of the hub infrastructures by lessening both the gross operating cost and overall CO2 emission simultaneously.
This paper deals with the numerical simulation of the dynamic failure of an aluminium plate under air-blast loading. Constitutive modelling based on the fractional viscoplasticity is used. The material model is non-local due to the properties of the applied fractional differential operator and is implemented as user material in the engineering finite element computation code ABAQUS. It is important that the numerical simulations are contrasted with experiments. Numerical outcomes clearly show the applicability of the adopted modelling for the description of salient stages of dynamic structural failure.
In this paper, a system dynamics approach is introduced for the macro-planning of the selection of new product families in the consumer electronics industry in developing countries. A decision methodology structure is built that includes the impact factors of rapid technology changes and uncertainty. System dynamics models are designed to select the product family's planning strategy, considering the different variables in marketing, product design, supply chain, and manufacturing method. The developed model is validated for a real case study of television manufacturing in Egypt. The results reveal that using system dynamics reflects the dynamics of the consumer electronics industry and can be used for its strategic planning.
Fused deposition modeling (FDM) is one of the most additive manufacturing techniques that adopted to produce prototypes and/or final parts, particularly under geometrical complexity restrictions. One of the most challenging aspects of FDM technology is the attainable roughness. In this paper, a hot-air jet was applied simultaneously during the printing process of FDM products to investigate the effect of its factors on surface roughness. Experimentally, a test rig was utilized to evaluate the effect of these factors on surface roughness. Two main factors were addressed: air jet temperature; and nozzle translational velocity over the part surface and investigated their effect on the roughness. Statistically, ANOVA and regression analysis were conducted to study the contribution of the individual factors to the process response and to introduce regression model to predict the resulting surface roughness in terms of different …
The large number of interdigitated electrodes (IDEs) in a macro fiber composite (MFC) piezoelectric actuator dictates using a very fine finite element (FE) mesh that requires extremely large computational costs, especially with a large number of actuators. The situation becomes infeasible if repeated finite element simulations are required, as in control tasks. In this paper, an efficient technique is proposed for modeling MFC using a finite element method. The proposed technique replaces the MFC actuator with an equivalent simple monolithic piezoceramic actuator using two electrodes only, which dramatically reduces the computational costs. The proposed technique was proven theoretically since it generates the same electric field, strain, and displacement as the physical MFC. Then, it was validated with the detailed FE model using the actual number of IDEs, as well as with experimental tests using triaxial rosette strain gauges. The computational costs for the simplified model compared with the detailed model were dramatically reduced by about 74% for memory usage, 99% for result file size, and 98.6% for computational time. Furthermore, the experimental results successfully verified the proposed technique with good consistency. To show the effectiveness of the proposed technique, it was used to simulate a morphing wing covered almost entirely by MFCs with low computational cost
In rural and remote areas, solar photovoltaic energy (PV) water pumping systems (SPWPSs) are being favored over diesel-powered water pumping due to environmental and economic considerations. PV is a clean source of electric energy offering low operational and maintenance cost. However, the direct-coupled SPWPS requires inventive solutions to improve the system’s efficiency under solar power variations while producing the required amount of pumped water concurrently. This paper introduces a new quadratic V/f (Q V/f) control method to drive an induction motor powered directly from a solar PV source using a two-stage power converter without storage batteries. Conventional controllers usually employ linear V/f control, where the reference motor speed is derived from the PV input power and the dc-link voltage error using a simple proportional–integral (PI) controller. The proposed Q V/f-based system is compared with the conventional linear V/f control using a simulation case study under different operating conditions. The proposed controller expectedly enhances the system output power and efficiency, particularly under low levels of solar irradiance. Some alternative controllers rather than the simple PI controller are also investigated in an attempt to improve the system dynamics as well as the water flow output. An experimental prototype system is used to validate the proposed Q V/f under diverse operating conditions.
Fused deposition modeling (FDM) is one of the most adopted additive manufacturing techniques to produce prototypes and/or final parts regardless of geometrical complexity restrictions. One of the most challenging aspects of this technology is the attainable roughness. The purpose of this study is to evaluate the capability of the slurry impacts to improve the surface roughness of parts fabricated using FDM. Moreover, a regression model for predicting the values of surface roughness was developed.
The developed technique imposes a silica–water mixture which softens the staircase on the surface and leaves it smoother. The process introduces three main factors: building orientation; layer thickness; and impact angle of the slurry particles. Experimentally, a test rig was used to evaluate the effect of these factors on surface roughness. Statistically, Analysis of variance (ANOVA) and regression analysis were conducted to study the contribution of the individual factors on the roughness.
The results reveal that the effect of slurry impacts has a good impact on surface roughness, and the three factors have significant effect on surface roughness.
This paper contributes to new knowledge by providing a new technique for enhancing the surface roughness of FDMed products. ANOVA and regression analysis is a useful tool to parametrically study the surface roughness in terms of building and testing factors.
In this experimental and statistical investigation, Silver (Ag) nanoparticles with varying particle sizes of 20 nm with the base fluid of EG and DI water are tested to improve the heat transfer properties of the car radiator. The thermophysical properties are tested at temperatures varying from 35 to 75 C. Results showed that small nanoparticles had higher thermophysical properties than large nanoparticles. The heat transfer properties along with friction factor characteristics are measured. A total of 20 nm of Ag has higher thermal transfer properties than other nanofluids; it can be concluded that smaller nanoparticles can improve thermal properties and minimize the radiator size compared to traditional coolants. A systematic optimized RSM-based architecture has been developed to define the quantitative estimate of the specific design parameters influencing nanofluid heat transfer properties and friction factor characteristics. Finally, correlations are developed for experimental Nusselt number and friction factor values by regression analysis.
