Application of the ANOVA method in the optimization of a thermoelectric cooler-based dehumidification system

© 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).In recent studies, Thermo-Electric Coolers (TEC) have been utilized for dehumidification purposes, which is mainly based on the extraction of moisture from humid atmospheric air. The reviewed literature showed that the rate of water collection from the TEC-based system can be affected by various parameters such as the module’s input voltage, the heat sink orientation, and tilt angles. In this research, the analysis of variance (ANOVA) was used to examine the significance of these factors and their interaction within the system on the TEC-based dehumidification system. Four levels were investigated for both, the Peltier’s input voltage and the rotation angle, and three levels for the tilt angle. This study indicated the significance of the studied factors and their interactions within the dehumidification system along with performing an overall numerical optimization. The experiments were conducted under the same working conditions in an enclosed environment to minimize errors. According to the overall numerical optimization, which was validated experimentally, the optimum system performance was predicted to be obtained at approximately 6.8V Peltier input volt, 65° rotation angle, and 90° tilt angles, with predicted optimum productivities of 0.32278 L/kWh and 13.03 mL/hr. For the same set of parameters, the variation between the experiment and the numerical optimization was less than 4%. The experiments show that when optimizing water collection rates for thermoelectric cooling heat sinks​ under high humidity conditions, the orientation of the heat sink should be considered.Peer reviewe

Thermohydraulic analysis of covalent and noncovalent functionalized graphene nanoplatelets in circular tube fitted with turbulators

© The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.Covalent and non-covalent nanofluids were tested inside a circular tube fitted with twisted tape inserts with 45° and 90° helix angles. Reynolds number was 7000 ≤ Re ≤ 17,000, and thermophysical properties were assessed at 308 K. The physical model was solved numerically via a two-equation eddy-viscosity model (SST k-omega turbulence). GNPs-SDBS@DW and GNPs-COOH@DW nanofluids with concentrations (0.025 wt.%, 0.05 wt.% and 0.1 wt.%) were considered in this study. The twisted pipes' walls were heated under a constant temperature of 330 K. The current study considered six parameters: outlet temperature, heat transfer coefficient, average Nusselt number, friction factor, pressure loss, and performance evaluation criterion. In both cases (45° and 90° helix angles), GNPs-SDBS@DW nanofluids presented higher thermohydraulic performance than GNPs-COOH@DW and increased by increasing the mass fractions such as 1.17 for 0.025 wt.%, 1.19 for 0.05 wt.% and 1.26 for 0.1 wt.%. Meanwhile, in both cases (45° and 90° helix angles), the value of thermohydraulic performance using GNPs-COOH@DW was 1.02 for 0.025 wt.%, 1.05 for 0.05 wt.% and 1.02 for 0.1 wt.%.Peer reviewe

Multi-strategy Slime Mould Algorithm for hydropower multi-reservoir systems optimization

The challenge to determine the best policies for hydropower multiple reservoir systems is a high-dimensional and nonlinear problem, making it challenging to attain a global solution. To efficiently optimize such a complicated solution, the creation of a high-precision optimization algorithm is critical. Hence, this research proposes a Multi-strategy Slime Mould Algorithm (MSMA) to determine the optimal operating rules for a complicated hydropower multiple reservoir prediction problem. The MSMA system proposed employs an effective wrap food mechanism to strengthen local and global capability; an enhanced solution quality (ESQ) to promote solution quality; and the interior-point method to implement an influential exploitation mechanism. The numerical testing of 23 test functions demonstrates the efficiency of the MSMA algorithm in solving global optimization issues. The newly developed method is then used to optimize the operation of a complex eight-reservoir hydropower system, with the proposed MSMA approach resulting in 0.999% of an ideal global solution, according to the optimal findings. The results of the multi-reservoir system show that proposed MSMA method was able to generate about 16.6% more power than the SMA. Consequently, the recommended method outperforms the other well-known optimization methods for maximizing power in the multi-reservoir system. Finally, this study also provides a useful tool for optimizing the complicated hydropower multiple reservoir problems

Deep clustering of cooperative multi-agent reinforcement learning to optimize multi chiller HVAC systems for smart buildings energy management

© 2022 Elsevier Ltd. All rights reserved. All rights reserved. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1016/j.jobe.2022.105689Chillers are responsible for almost half of the total energy demand in buildings. Hence, the obligation of control systems of multi-chiller due to changes indoor environments is one of the most significant parts of a smart building. Such a controller is described as a nonlinear and multi-objective algorithm, and its fabrication is crucial to achieving the optimal balance between indoor thermal comfort and running a minimum number of chillers. This work proposes deep clustering of cooperative multi-agent reinforcement learning (DCCMARL) as well-suited to such system control, which supports centralized control by learning of agents. In MARL, since the learning of agents is based on discrete sets of actions and stats, this drawback significantly affects the model of agents for representing their actions with efficient performance. This drawback becomes considerably worse when increasing the number of agents, due to the increased complexity of solving MARL, which makes modeling policy very challenging. Therefore, the DCCMARL of multi-objective reinforcement learning is leveraging powerful frameworks of a hybrid clustering algorithm to deal with complexity and uncertainty, which is a critical factor that influences to the achievement of high levels of a performance action. The results showed that the ability of agents to manipulate the behavior of the smart building could improve indoor thermal conditions, as well as save energy up to 44.5% compared to conventional methods. It seems reasonable to conclude that agents' performance is influenced by what type of model structure.Peer reviewe

An Enhanced Multioperator Runge–Kutta Algorithm for Optimizing Complex Water Engineering Problems

Water engineering problems are typically nonlinear, multivariable, and multimodal optimization problems. Accurate water engineering problem optimization helps predict these systems’ performance. This paper proposes a novel optimization algorithm named enhanced multioperator Runge–Kutta optimization (EMRUN) to accurately solve different types of water engineering problems. The EMRUN’s novelty is focused mainly on enhancing the exploration stage, utilizing the Runge–Kutta search mechanism (RK-SM), the covariance matrix adaptation evolution strategy (CMA-ES) techniques, and improving the exploitation stage by using the enhanced solution quality (IESQ) and sequential quadratic programming (SQP) methods. In addition to that, adaptive parameters were included to improve the stability of these two stages. The superior performance of EMRUN is initially tested against a set of CEC-17 benchmark functions. Afterward, the proposed algorithm extracts parameters from an eight-parameter Muskingum model. Finally, the EMRUM is applied to a practical hydropower multireservoir system. The experimental findings show that EMRUN performs much better than advanced optimization approaches. Furthermore, the EMRUN has demonstrated the ability to converge up to 99.99% of the global solution. According to the findings, the suggested method is a competitive algorithm that should be considered in optimizing water engineering problems

Influence of water based binary composite nanofluids on thermal performance of solar thermal technologies: sustainability assessments

Recent technological advances have made it possible to produce particles with nanometer dimensions that are uniformly and steadily suspended in traditional solar liquids and have enhanced the impact of thermo-physical parameters. In this research, a three-dimensional flat plate solar collector was built using a thin flat plate and a single working fluid pipe. The physical model was solved computationally under conditions of conjugated laminar forced convection in the range 500 ≤ Re ≤ 1900 and a heat flux of 1000 W/m2. Distilled water (DW) and different types of hybrid nanofluids (namely, 0.1%-Al2O3@Cu/DW, 0.1%-MWCNTs@Fe3O4/DW, 0.3%-MWCNTs@Fe3O4/DW, 0.5%-Ag@MgO/DW, 1%-Ag@MgO/DW, 1%-S1 and 1%-S2, where MWCNTs are multi-wall carbon nanotubes, S1 means 2CuO–1Cu and S2 means 1CuO–2Cu nanocomposites) were evaluated via a set of parameters. The numerical results revealed that, by increasing the working fluid velocity (the Reynolds number), the average heat transfer coefficient, pressure loss, heat gain and solar collector efficiency were increased. Meanwhile, outlet fluid temperature and flat plate surface temperature were decreased. At Re = 1900, 1%-S2 and 1%-S1 presented higher thermal performance enhancement by 44.28% and 36.72% relative to DW. Moreover, low thermal performance enhancement of 7.59% and 7.44% were reported by 0.1%-Al2O3@Cu/DW and 0.3%-MWCNTs@Fe3O4/DW, respectively.Validerad;2023;Nivå 2;2023-01-25 (joosat);Licens fulltext: CC BY License</p

Thermohydraulic performance of thermal system integrated with twisted turbulator inserts using ternary hybrid nanofluids

Mono, hybrid, and ternary nanofluids were tested inside the plain and twisted-tape pipes using k-omega shear stress transport turbulence models. The Reynolds number was 5,000 ≤ Re ≤ 15,000, and thermophysical properties were calculated under the condition of 303 K. Single nanofluids (Al2O3/distilled water [DW], SiO2/DW, and ZnO/DW), hybrid nanofluids (SiO2 + Al2O3/DW, SiO2 + ZnO/DW, and ZnO + Al2O3/DW) in the mixture ratio of 80:20, and ternary nanofluids (SiO2 + Al2O3 + ZnO/DW) in the mixture ratio of 60:20:20 were estimated in different volumetric concentrations (1, 2, 3, and 4%). The twisted pipe had a higher outlet temperature than the plain pipe, while SiO2/DW had a lower Tout value with 310.933 K (plain pipe) and 313.842 K (twisted pipe) at Re = 9,000. The thermal system gained better energy using ZnO/DW with 6178.060 W (plain pipe) and 8426.474 W (twisted pipe). Furthermore, using SiO2/DW at Re = 9,000, heat transfer improved by 18.017% (plain pipe) and 21.007% (twisted pipe). At Re = 900, the pressure in plain and twisted pipes employing SiO2/DW reduced by 167.114 and 166.994%, respectively. In general, the thermohydraulic performance of DW and nanofluids was superior to one. Meanwhile, with Re = 15,000, DW had a higher value of η Thermohydraulic = 1.678Validerad;2023;Nivå 2;2023-03-20 (hanlid);Funder: Universiti Teknologi Malaysia, UTM, (06E10)</p

Thermal and Hydraulic Performances of Carbon and Metallic Oxides-Based Nanomaterials

For companies, notably in the realms of energy and power supply, the essential requirement for highly efficient thermal transport solutions has become a serious concern. Current research highlighted the use of metallic oxides and carbon-based nanofluids as heat transfer fluids. This work examined two carbon forms (PEG@GNPs & PEG@TGr) and two types of metallic oxides (Al2O3 & SiO2) in a square heated pipe in the mass fraction of 0.1 wt.%. Laboratory conditions were as follows: 6401 ≤ Re ≤ 11,907 and wall heat flux = 11,205 W/m2. The effective thermal–physical and heat transfer properties were assessed for fully developed turbulent fluid flow at 20–60 °C. The thermal and hydraulic performances of nanofluids were rated in terms of pumping power, performance index (PI), and performance evaluation criteria (PEC). The heat transfer coefficients of the nanofluids improved the most: PEG@GNPs = 44.4%, PEG@TGr = 41.2%, Al2O3 = 22.5%, and SiO2 = 24%. Meanwhile, the highest augmentation in the Nu of the nanofluids was as follows: PEG@GNPs = 35%, PEG@TGr = 30.1%, Al2O3 = 20.6%, and SiO2 = 21.9%. The pressure loss and friction factor increased the highest, by 20.8–23.7% and 3.57–3.85%, respectively. In the end, the general performance of nanofluids has shown that they would be a good alternative to the traditional working fluids in heat transfer requests

Energy and cost management of different mixing ratios and morphologies on mono and hybrid nanofluids in collector technologies

The flat-plate solar collector (FPSC) three-dimensional (3D) model was used to numerically evaluate the energy and economic estimates. A laminar flow with 500 ≤ Re ≤ 1900, an inlet temperature of 293 K, and a solar flux of 1000 W/m2 were assumed the operating conditions. Two mono nanofluids, CuO-DW and Cu-DW, were tested with different shapes (Spherical, Cylindrical, Platelets, and Blades) and different volume fractions. Additionally, hybrid nanocomposites from CuO@Cu/DW with different shapes (Spherical, Cylindrical, Platelets and Blades), different mixing ratios (60% + 40%, 50% + 50% and 40% + 60%) and different volume fractions (1 volume%, 2 volume%, 3 volume% and 4 volume%) were compared with mono nanofluids. At 1 volume% and Re = 1900, CuO-Platelets demonstrated the highest pressure drop (33.312 Pa). CuO-Platelets achieved the higher thermal enhancement with (8.761%) at 1 vol.% and Re = 1900. CuO-Platelets reduced the size of the solar collector by 25.60%. Meanwhile, CuO@Cu-Spherical (40:60) needed a larger collector size with 16.69% at 4 vol.% and Re = 1900. CuO-Platelets with 967.61, CuO – Cylindrical with 976.76, Cu Platelets with 983.84, and Cu-Cylindrical with 992.92 presented the lowest total cost. Meanwhile, the total cost of CuO – Cu – Platelets with 60:40, 50:50, and 40:60 was 994.82, 996.18, and 997.70, respectively.Validerad;2023;Nivå 2;2023-01-25 (joosat);Licens fulltext: CC BY License</p

Iran’s agriculture in the anthropocene

Abstract The anthropogenic impacts of development and frequent droughts have limited Iran’s water availability. This has major implications for Iran’s agricultural sector which is responsible for about 90% of water consumption at the national scale. This study investigates if declining water availability impacted agriculture in Iran. Using the Mann‐Kendall and Sen’s slope estimator methods, we explored the changes in Iran’s agricultural production and area during the 1981–2013 period. Despite decreasing water availability during this period, irrigated agricultural production and area continuously increased. This unsustainable agricultural development, which would have been impossible without the overabstraction of surface and ground water resources, has major long‐term water, food, environmental, and human security implications for Iran