Development of hybrid energy system with cycle charging strategy using particle swarm optimization for a remote area in India

In recent years, renewable energy can be seen as one of the important prospect of today's research, as it is likely to enlighten the lives of millions of people by fulfilling demand of electricity in their daily life. The present work focuses on the development of optimal hybrid energy system sizing model based on comparative analysis of particle swarm optimization, genetic algorithm and Homer software for energy index ratio of 1. The model also incorporates renewable fraction, emissions of carbon di oxide from diesel generator, net present cost and cost of energy. The system is developed to supply the demand of 7 un-electrified villages of Dhauladevi block of Almora district in Uttarakhand, India with the help of the available resources of solar, hydro, biomass and biogas energy along with the addition of diesel generator, for meeting out the energy deficit. From the optimization results, minimum cost of energy and maximum renewable fraction are obtained as 5.77 Rs/kWh and 92.6% respectively.     

Fluorination as an effective tool to increase the photovoltaic performance of indacenodithiophene-alt-quinoxaline based wide-bandgap copolymers

To investigate the effect of the fluoride phenyl side-chains into quinoxaline (PQx) unit on the photovoltaic performances of polymers, we demonstrated the synthesis and characterization of two novel wide-bandgap (WBG) copolymers, PIDT-DTPQx and PIDT-DTFPQx, in which indacenodithiophene (IDT), 2,3-diphenylquinoxaline (PQx) (and/or 2,3-bis(4-fluorophenyl)quinoxaline (FPQx)) and thiophene (T) were used as the donor (D) unit, acceptor (A) unit and π-bridge, respectively. Compared to the non-fluorine substituted PIDT-DTPQx, fluorine substituted PIDT-DTFPQx presents a deep HOMO energy level and a high hole mobility. Obviously, improved the V_oc, J_sc, and FF simultaneously, giving rise to overall efficiencies in the PIDT-DTFPQx/PC₇₁BM-based PSCs. A highest PCE of 5.78% was obtained with a V_oc of 0.86 V, J_sc of 10.84 mA cm⁻² and FF of 61.7% in the PIDT-DTFPQx/PC₇₁BM-based PSCs, while PIDT-DTPQx based devices also demonstrated a PCE of 5.11%, under the illumination of AM 1.5G (100 mW cm⁻²). Note that these PCE values were achieved for PSCs without any extra treatments. Furthermore, these optimal devices have a film thickness of about 175 nm for the polymer/PC₇₁BM-based active layers. The results provide that introduction of the fluorine atom into quinoxaline unit by side-chain engineering is one of the effective strategies to construct the promising polymer donor materials for future application of large-area polymer solar cells.     

Crystal structure, 57Fe Mössbauer spectroscopy and magnetization of UxFe6Sn6 (0≤x≤0.6)

The U_xFe₆Sn₆ (0≤x≤0.6) intermetallics were prepared as polycrystalline samples by arc melting followed by annealing. They crystallize in the P6/mmm space group as a lacunary variant of the HfFe₆Ge₆-type, with an ordered insertion of U within the Sn₈ voids of the FeSn framework, and are isostructural with the R_xFe₆Sn₆ compounds (R=Sc, Zr, Tm, Yb, Lu). ⁵⁷Fe Mössbauer spectroscopy shows that the Fe magnetic moments, μ_Fe, are already ordered at room temperature. Anisotropic contributions to the total hyperfine field at the Fe site indicates that μ_Fe are perpendicular to the crystallographic c axis in contrast to the Sc, Zr and rare-earth (except Yb) containing compounds, where μ_Fe are directed along the c axis. The values deduced for the angles between the main axes of the electric field gradient and μ_Fe further show that, within each (001) plane, μ_Fe have a ferromagnetic arrangement similar to that in FeSn and Yb_0.6Fe₆Sn₆. In U_xFe₆Sn₆, the hyperfine fields increase with U content. Magnetization data in the 2–300 K show small ferromagnetic components for the U_0.4Fe₆Sn₆ and U_0.6Fe₆Sn₆ compositions.     

A novel approach to CNC machining center processing parameters optimization considering energy-saving and low-cost

NC machining is currently a machining method widely used in mechanical manufacturing systems. Reasonable selection of process parameters can significantly reduce the processing cost and energy consumption. In order to realize the energy-saving and low-cost of CNC machining, the cutting parameters are optimized from the aspects of energy-saving and low-cost, and a process parameter optimization method of CNC machining center that takes into account both energy-saving and low -cost is proposed. The energy flow characteristics of the machining center processing system are analyzed, considering the actual constraints of machine tool performance and tool life in the machining process, a multi-objective optimization model with milling speed, feed per tooth and spindle speed as optimization variables is established, and a weight coefficient is introduced to facilitate the solution to convert it into a single objective optimization model. In order to ensure the accuracy of the model solution, a combinatorial optimization algorithm based on particle swarm optimization and NSGA-II is proposed to solve the model. Finally, take plane milling as an example to verify the feasibility of this method. The experimental results show that the multi-objective optimization model is feasible and effective, and it can effectively help operators to balance the energy consumption and processing cost at the same time, so as to achieve the goal of energy conservation and low-cost. In addition, the combinatorial optimization algorithm is compared with the NSGA-II, the results show that the combinatorial optimization algorithm has better performance in solving speed and optimization accuracy.     

混炼胶质量预测和排胶控制的GMPLS模型研究

针对混炼胶密炼工艺特性，提出广义多路部分最小二乘（GMPLs）算法，建立混炼胶门尼粘度预测和排胶控制模型，克服了普通最小二乘算法在间歇生产质量控制建模中的局限性。试验结果表明，该模型预测混炼胶质量效果良好，并可根据工艺要求在线调整排胶工艺参数，实现智能排胶控制，提高混炼胶质量。     

Boron bridged NiN4B2Cx single-atom catalyst for superior electrochemical CO2 reduction

Single-atom nickel catalysts hold great promise in the application of electrocatalytic carbon dioxide reduction reaction (CO₂RR), but suffer from the sluggish kinetics and serious competitive hydrogen evolution reaction (HER), which restrict their overall catalytic performance. Herein, we report a boron-bridging strategy to manipulate the atomic coordination structure and construct a single-atom nickel catalyst with an active center of NiN₄B₂ to realize excellent CO₂RR performance. Density functional theory analysis suggests that the unique NiN₄B₂ sites with tuned electronic structure facilitate the adsorption of CO₂ molecules and effectively suppress the HER pathway by increasing corresponding energy barrier. As-obtained Ni-SAs@BNC catalyst with a NiN₄B₂ structure exhibits significantly enhanced catalytic activity and selectivity than commonly used single-atom nickel catalysts with a NiN₄ structure, especially at high applied potentials. A high current density of up to (214 ± 21) mA cm⁻² at a potential of −1.2 V with a high CO Faraday efficiency (FE_CO) of ∼97% was achieved in a flow cell. This work inspires new insights into the rational design of atomic coordination structure of single-atom catalysts with tunable electronic structure for superior electrocatalytic activities.     

A survey of game-theoretic approaches in wireless sensor networks

Wireless sensor networks (WSNs) comprising of tiny, power-constrained nodes are gaining popularity due to their potential for use in a wide variety of environments like monitoring of environmental attributes, intrusion detection, and various military and civilian applications. While the sensing objectives of these environments are unique and application-dependent, a common performance criteria for wireless sensor networks is prolonging network lifetime while satisfying coverage and connectivity in the deployment region. Security is another important performance parameter in wireless sensor networks, where adverse and remote environments pose various kinds of threats to reliable network operation. In this paper, we look at the problems of security and energy efficiency and different formulations of these problems based on the approach of game theory. The potential applicability of WSNs to intruder detection environments also lends itself to game-theoretic formulation of these environments, where pursuit-evasion games provide a relevant framework to model detection, tracking and surveillance applications.The suitability of using game theory to study security and energy efficiency problems and pursuit-evasion scenarios using WSNs stems from the nature of strategic interactions between nodes. Approaches from game theory can be used to optimize node-level as well as network-wide performance by exploiting the distributed decision-making capabilities of WSNs. The use of game theory has proliferated, with a wide range of applications in wireless sensor networking. In the wake of this proliferation, we survey the use of game-theoretic approaches to formulate problems related to security and energy efficiency in wireless sensor networks.     

Analysis of daylight factors and energy saving allowed by windows under overcast sky conditions

The aim of this research is to quantify the daylight factors produced inside a room for different models of windows, and to conduct an analysis of the results obtained. All trials were performed under overcast sky conditions, as these represent the worst case scenario for calculation. The shape, size and position of the window are variable, as is the reflectance of the inner surfaces of the room. A total of 28 simulations are provided by the lighting simulation program Daylight Visualizer 2.6, validated by the CIE test cases. After trials it was concluded that square windows produce daylight factors slightly higher than those obtained with horizontal windows and noticeably higher than those measured with vertical windows, considering the same surface of openings. It is confirmed that the daylight factors are directly proportional to the glass surface, except in the area near the window. It is also concluded that the windows in the upper position allow higher luminance at the back of the room than those in centered locations. Finally, the energy savings produced by the different models of windows is calculated.     

Gait planning based on kinematics for a quadruped gecko model with redundancy

Recent research on mobile robots has focused on locomotion in various environments. In this paper, a gait-generation algorithm for a mobile robot that can travel from the ground to a wall and climb vertical surfaces is proposed. The algorithm was inspired by a gecko lizard. Our gait planning was based on inverse kinematics using the Jacobian of the whole body, where the redundancy was solved by defining an object function for the gecko posture to avoid collisions with the surface. The optimal scalar factor for these two objects was obtained by defining a superior object function to minimize the angular acceleration of joints. The algorithm was verified through simulation of the gecko model travelling on given task paths and avoiding abnormal joint movements and collisions.