Due to its NP-hard nature, the electric vehicle charging scheduling problem requires a robust optimization algorithm capable of producing accurate solutions within a reasonable computational cost. Existing algorithms reviewed in the literature often suffer from either slow convergence speed or an inability to escape local optima. Therefore, this study proposes a novel evolutionary algorithm, termed FL-SHADE, designed to address these limitations by achieving a better balance between exploration and exploitation. This algorithm combines the FGO algorithm with the adaptive L-SHADE algorithm to present a new variant, namely FL-SHADE. The FGO algorithm has robust exploration that helps escape from local optima but suffers from a poor exploitation operator, leading to slow convergence. In contrast, the AL-SHADE algorithm is known for its effective exploitation but limited exploration. By leveraging the complementary strengths of both algorithms, FL-SHADE features strong abilities to avoid stagnation in local optima and accelerate convergence toward high-quality solutions. FL-SHADE is initially assessed using the CEC2017 benchmark and compared with several competing algorithms based on several performance indicators to evaluate its stability and effectiveness. According to the experimental results, FL-SHADE can outperform all algorithms on 15 of 29 test functions, be competitive on 12, and perform worse on only 2, demonstrating that it is a robust alternative for addressing continuous optimization challenges. Subsequently, FL-SHADE is evaluated on 12 charge scheduling problems under four different penetration levels and three scenarios to assess performance at small, medium, and large scales. In addition, it is compared with several high-performing and recently proposed optimization algorithms to validate its effectiveness and stability. The experimental results indicate that FL-SHADE outperforms competing algorithms in eight test cases, whereas AL-SHADE performs better in the remaining cases, suggesting that both algorithms are strong candidates for solving electric vehicle charge scheduling problems.
Ti6Al4V, with its high specific strength and excellent comprehensive mechanical properties, is the primary material for critical thin-walled components in the aerospace sector. The high forming efficiency and the efficient fabrication of laser directed energy deposition (LDED) technology makes it one of the key technologies for forming complex titanium alloy components today. However, during the deposition of thin-walled specimens, continuous deposition modes and heat accumulation would cause component deformation, affecting their mechanical properties. Rather than increasing interlayer cooling time, this study employs a molten pool monitoring and closed-loop control mode to address the heat accumulation issue directly at the heat source. Specifically, it uses the melt pool width captured by a CCD camera as a visual target and adjusts the laser power to maintain a stable width, thereby improving the forming accuracy of thin-walled specimens. In this work, to intuitively compare the differences in thermal effects among various deposition modes, conventional, cooling, and control modes were established, and the dimensional accuracy, microstructure, and wear resistance of the components were compared. The results indicated that the control mode exhibited a more favorable temperature gradient. Under favorable cooling rates, the microstructure exhibited a reticulated basket-weave pattern dominated by acicular α' phase, with a 45.5% reduction in grain size. The microhardness and wear resistance of thin-walled specimens were respectively increased by 13.1% and 27.5% under the grain refinement. The control mode exhibited both abrasive and adhesive wear mechanisms.
Against the backdrop of the increasing energy crisis and environmental pollution, the exploration of low-cost, green, and sustainable energy sources has become more and more imperative. The rapid development of green energy has also stimulated the demand on energy storage and conversion systems. Carbon-based aerogels (CAs), as emerging electrode materials and characterized by sustainable and high performance, have attracted significant attentions. The present review provides a comprehensive overview of the fabrication of CAs, and especially focuses on the recent advances in optimizing the electrochemical performance of CAs for applications in supercapacitors, batteries, and electrocatalysis from the perspectives of the structural design, conductivity enhancement, and chemical modifications. Critical discussion and analyses are conducted on the surface/interface properties of CAs as electrodes and catalytic material, as well as their advantages and disadvantages of advanced synthesis strategies. Discussion is also expanded on key challenges, current issues, and the prospects for their laboratory and industrial applications. This work offers valuable insights into the rational structural design and functionalization of CAs and is expected to serve as a foundation for the commercial development of electrode materials in energy storage and conversion devices. The present review provides an overview of recent advances in optimizing the electrochemical properties of carbon based aerogels for energy storage and energy conversion.The surface/interface properties, structural design and synthesis strategies used as electrode and catalysis materials were discussed. Meanwhile, challenges and prospects of their applications were also proposed.
PurposeThe global construction industry has been facing significant workforce supply and demand imbalances in recent years, impeding the successful delivery of construction projects and sustainable development of the industry. However, research examining the supply-demand dynamics of the construction workforce remains limited. Using China as a case study, this research employed a system dynamics (SD) approach to developing an SD model of construction workforce supply and demand, forecasting and analyzing workforce trends and evaluating multiple scenarios for addressing workforce imbalance problems.Design/methodology/approachAn SD model was developed based on an extensive literature review and the group model building technique. Data collected from the Chinese construction industry were used for model validation and simulation.FindingsThe results indicated a projected substantial widening of the construction workforce supply-demand gap by 2035, with both supply and demand growth declining significantly over the next decade. Scenario-based simulations demonstrated that only two scenarios achieve supply-demand equilibrium during the study period, with the coordinated development scenario enabling stable balance by 2035. Notably, the workplace improvement priority is the most effective scenario in alleviating workforce shortages, while the technological innovation priority scenario can achieve the most significant workforce demand reduction.Originality/valueThese findings provide valuable insights for policymakers and industry practitioners to developing multidimensional strategies so as to optimize workforce development in the construction industry.
In this study magnetic-loaded nanomaterials were synthesized using three different sizes of porous guests (165 nm, 200 nm, and 310 nm), subsequently converting them into porous liquids (PLs) using polyetheramine M2070 and (3-glycidoxypropyl)trimethoxysilane (KH560) as a steric hindrance solvent. M2070 imparted excellent fluidity to the PLs at room temperature, which were employed in the extraction of Pb(ii) ions from wastewater. The physicochemical properties of the adsorbents were characterized using SEM, TEM, FTIR, XPS, BET, and TGA analyses. The adsorption behavior of PLs with different guest sizes for Pb(ii) was studied and compared. The adsorption capacities (Qe) of Fe3O4@HS(165 nm)-M2070, Fe3O4@HS(200 nm)-M2070, and Fe3O4@HS(310 nm)-M2070 for Pb(ii) were 160.12, 211.47, and 173.10 mg g-1, respectively. This confirms that the size of the guest has an influence on the adsorption performance. All three adsorption materials were found to better fit the pseudo-first-order kinetic model and the Freundlich isotherm model, indicating that physisorption and multilayer adsorption are the prevailing mechanisms, with the process tending toward heterogeneous multilayer adsorption. Thermodynamic analysis further revealed the spontaneous and endothermic characteristics of the adsorption process, highlighting the thermodynamic feasibility and effectiveness of these materials for the removal of Pb(ii). Additionally, the adsorbents exhibited a rich mesoporous structure, abundant surface functional groups, and excellent recyclability, all contributing to the effective elimination of Pb(ii) ions from wastewater. Overall, this study elucidates the intrinsic correlation between porous guest size and Pb(ii) adsorption efficiency, offering valuable insights for the preparation of high-performance magnetic PL adsorbents. It also facilitates the practical utilization of PLs for heavy metal pollution remediation.
