Search Results (79)

In deep-sea environments characterized by global climate change and frequent typhoons, the long-term structural stability of offshore buildings depends on the adaptability of their morphology to complex, multi-directional wind loads. Current offshore engineering predominantly emphasizes passive structural resistance, with a notable lack of research on proactive wind-diversion strategies from a morphological design perspective. Utilizing the PHOENICS-FLAIR platform and the Chen–Kim k-ε turbulence model, this study conducted numerical simulations across eight typical wind direction scenarios. The independence of the medium-mesh scheme was verified through Grid Convergence Index (GCI) analysis, and the high reliability of the numerical model was validated against the AIJ Case A wind tunnel experiments. Quantitative results demonstrate that, compared to the benchmark rectangular prism, the optimized composite polyhedral form featuring “curved sloped facades” performs superiorly under multi-directional conditions: the maximum positive wind pressure is reduced by up to 50%, and the total surface wind pressure differential decreases by 62–65%. This research proves that a polyhedral continuous envelope configuration can achieve balanced aerodynamic performance across all wind directions, providing a feasible direction for the design strategy of offshore buildings to shift from “passive resistance” to “proactive diversion”. Full article

After large-scale disasters, swift and robust humanitarian logistics are crucial to provide timely assistance to injured people and displaced individuals. This study proposes a bi-objective optimization model for humanitarian logistics network design to simultaneously consider the facility location-allocation decisions, along with the transportation operation issues under uncertainty. The framework addresses the needs of both severely and mildly injured casualties and homeless populations. A hybrid robust optimization approach is accordingly developed that incorporates scenario-based, box-type, and polyhedral uncertainty representations to handle the uncertainty of factors such as casualty volume, travel times, facility failures, and demands for resources. More recently, machine learning methods have been applied to classify casualties and displaced individuals with respect to their geographic distribution and severity, further improving demand estimates and operational efficacy. This study seeks to develop a data-driven and robust optimization framework for designing humanitarian logistics networks under uncertainty, enabling decision-makers and emergency planners to gain insights into enhancing casualty evacuation, medical treatment, and shelter allocation in disaster response operations. The case of the Kermanshah earthquake in Iran is used for assessing the applicability of the model. The computational experiments and comparative analyses conducted show that the developed model exhibits high efficiency and robustness. The results are useful for guiding disaster preparedness and strategic decisions in humanitarian logistics. Besides operational performance, the model optimizes sustainability in the area of emergency response based on cost efficiency and social fairness, as underlined by SDGs 3 and 11. Full article

Silica-based sorbents covalently modified with polyhedral boron clusters represent a promising platform for highly selective separation materials, yet robust and synthetically accessible immobilization protocols remain underdeveloped. In this work, novel sorbents based on commercially available silica gels functionalized with closo-dodecaborate anions were synthesized and systematically characterized. Two immobilization strategies were compared: direct nucleophilic addition of surface aminopropyl groups to the nitrilium derivative (Bu₄N)[B₁₂H₁₁NCCH₃] and sol–gel condensation of a pre-formed boron-containing APTES-derived silane. Covalent attachment via amidine bond formation was confirmed by solution and MAS ¹¹B NMR spectroscopy, IR spectroscopy, elemental analysis/ICP-OES, and SEM. The direct grafting route afforded a boron loading of 4.5 wt% (≈20% of the theoretical capacity), with the efficiency limited by electrostatic repulsion between anionic amidine fragments on the negatively charged silica surface, whereas the APTES route gave lower absolute loading (0.085 mmol/g) due to the low specific surface area of the coarse silica support. Despite the moderate degree of functionalization, the resulting boron cluster–modified silica gels are attractive candidates for specialized chromatographic applications, where the unique hydrophobic and dihydrogen-bonding properties of closo-dodecaborates may enable selective retention of challenging analytes and motivate further optimization of surface morphology and immobilization conditions. Full article

Toughening modification of epoxy resin (EP) matrices is important for advancing high-performance fiber-reinforced composites. A promising strategy involves the use of multi-component additive systems. However, synergistic effects in such additive systems are difficult to achieve for multidimensional performance optimization due to insufficient interfacial interactions and competing toughening mechanisms. Herein, a “hard–soft” biphasic synergistic toughening system was engineered for epoxy resin, composed of furan-ring-grafted polyhedral oligomeric silsesquioxane (FPOSS) and liquid polysulfide rubber. The hybrid toughening agent significantly enhanced the integrated performance of the epoxy system: Young’s modulus, tensile strength, and elongation at break increased by 13%, 56%, and 101%, respectively. These improvements are attributed to the formation of enriched molecular chain entanglement sites and optimized dispersion, facilitated by nucleophilic addition reactions between flexible rubber segments and rigid FPOSS units with the epoxy matrix. The marked enhancement in toughness primarily stems from the synergistic toughening mechanism involving “crazing pinning” and “crazing-shear band”. Concurrently, FPOSS incorporation effectively modulated the curing reaction kinetics, rendering the process more gradual while substantially elevating the glass transition temperature (T_g) of the cured system by 16.82 °C and endowing it with superior thermal degradation stability. This work provides a simple and unique strategy to leverage multi-scale mechanisms for the construction of epoxy-based composites with good toughness and strength, and enhanced heat resistance. Full article

In recent years, the increasing frequency of extreme weather events, the large-scale integration of distributed generation into distribution networks, and the widespread application of new power electronic devices have posed severe challenges to the security of power supply in distribution networks. To enhance the power supply reliability of the distribution network while considering its economic efficiency, this paper proposes a collaborative planning method for a flexible distribution network focused on power supply restoration and resilience enhancement In this method, a planning model for flexible distribution networks is established by optimally determining the siting and sizing of soft open point (SOP), with the objective of minimizing the annual comprehensive cost of the distribution network under multiple operational and planning constraints. Second-order cone programming (SOCP) relaxation and polyhedral approximation-based linearization techniques are employed to reformulate and solve the model, thereby obtaining the optimal siting and sizing Case for SOPs. Finally, simulations are conducted on a modified IEEE 33-bus test system to verify the effectiveness of the proposed method. The results show that, through appropriate siting and sizing of SOPs, outage loss costs can be significantly reduced, nodal voltage profiles can be improved, and load support can be provided to de-energized areas, leading to a reduction of more than 70% in the annual comprehensive cost of the distribution network and an improvement in the system reliability index from 99% to 99.999%, thus effectively enhancing both the economic efficiency and reliability of the distribution system. Full article

In the realm of financial management, optimizing the allocation of funds in banking companies is vital to their operational efficiency. Banks manage their funds by allocating them into reserve and credit funds as the main activities of banking. Optimizing these allocations ensures that all assets are effectively utilized. However, real-life optimization problems often involve uncertainty, making deterministic data assumptions insufficient. Robust Optimization is a methodology that addresses these uncertainties by incorporating computational tools to solve optimization problems with uncertain data. The uncertainty approach used in robust optimization is polyhedral sets. In the context of banking, uncertainties influencing the allocation of reserve and credit funds include financial risks and returns. These risks can be quantified using Conditional Value-at-Risk (CVaR), a suitable measure for banking fund allocation due to its ability to accommodate varying risk characteristics under different business conditions. This study focuses on developing an optimization model for reserve and credit fund allocation in banking companies using a Multi-objective Robust CVaR approach with lexicographic, informed by business risk data and credit instruments. The resulting optimization model yields optimal allocations for reserve and credit funds, ensuring efficient asset utilization to support banking operations. This approach offers new perspectives for banks to achieve fund allocations that are not only regulatory compliant but also optimal. The implications of such optimal allocations include mitigating risks associated with reserve fund imbalances and enhancing profitability through optimal credit returns. Full article

Particle shape is a critical factor governing the macroscopic behavior of granular materials. While the Discrete Element Method (DEM) has proven to be a powerful tool for modeling these materials, the accurate representation of particles with realistic geometries remains a significant challenge. Numerous shape description techniques have been developed to address this, including sphere-clustering, polyhedral, spheropolyhedral, and superquadric approaches. However, these methods often introduce artificial surface roughness or are limited to highly regular geometries, particularly when modeling general-shaped particles with rounded features. The proposed method reformulates collision detection in the Metaball Discrete Element Method (MDEM) as a constrained optimization problem, ensuring stable and physically consistent contact handling. Validation results show excellent agreement with analytical solutions and significantly improved robustness over unconstrained MDEM approaches. Finally, the model is applied to analyze the effects of particle shape on compaction and segregation, demonstrating that the proposed MDEM effectively captures the influence of complex shapes on macroscopic behavior and offers strong potential for engineering and scientific applications. Full article

Polyhedral oligomeric silsesquioxanes (POSS) harness their molecularly precise organic–inorganic hybrid cage architecture to deliver hardness, scratch resistance, and programmable functionality for next-generation transparent coatings. Tailoring of solubility, thermal stability, mechanical robustness, electronic characteristics, and interfacial properties is achieved through strategic peripheral modifications enabled by versatile synthetic methodologies—spanning metal catalysis, metal-free routes, and selective bond activation. Advanced integration techniques, including covalent grafting, chemical crosslinking, UV–thermal dual curing, and in situ polymerization, ensure uniform dispersion while optimizing coating–substrate adhesion and network integrity. The resultant coatings exhibit exceptional optical transparency, mechanical durability, tunable electrical performance, thermal endurance, and engineered surface hydrophobicity. These synergistic attributes underpin transformative applications across critical domains: atomic-oxygen-resistant spacecraft shielding, UV-managing agricultural films, flame-retardant architectural claddings, mechanically adaptive foldable displays, and efficiency-enhanced energy devices. Future progress will prioritize sustainable synthesis pathways, emergent asymmetric cage architectures, and multifunctional designs targeting extreme-environment resilience, thereby expanding the frontier of high-performance transparent protective technologies. Full article

The advancement of overall water-splitting technologies relies on the development of earth-abundant electrocatalysts that efficiently produce H₂ as a chemical fuel while offering high catalytic efficiency, structural robustness, and low-cost synthesis. Therefore, we aim to develop a cost-effective and durable non-noble electrocatalyst for overall water splitting. A straightforward hydrothermal approach was employed to fabricate freestanding polyhedral Co₃O₄ on a microporous Ni foam scaffold, followed by anion-exchange transformation in the presence of Na₂S solution to yield its conductive sulfide analog. The engineered Co₃S₄ electrode delivers remarkable HER activity in 1.0 M KOH, requiring a low overpotential (<100 mV) to drive 10 mA cm⁻², far outperforming its pristine oxide counterpart and even closely benchmarking with a commercial Pt/C catalyst. This exceptional performance is governed by the synergistic effects of enhanced electrical conductivity, abundant catalytic sites, and accelerated charge-transfer kinetics introduced through sulfur substitution. Furthermore, the optimized Co₃S₄ electrodes enable a bifunctional overall water-splitting device that achieves a cell voltage of >1.76 V at 100 mA cm⁻² and maintains prolonged operational stability for over 100 hrs. of continuous operation. Post-stability analyses confirm insignificant phase preservation during testing, ensuring sustained activity throughout the electrolysis process. This study highlights the potential of anion-exchanged Co₃S₄ as a cost-effective and durable catalyst for high-performance HER and full-cell water-splitting applications. Full article

This paper solves the stabilization problem of the continuous-time switched systems with partly unstabilizable subsystems subject to actuator saturation and data quantization. The static quantizer is designed by properly restraining the density of the finite partition. The relationship between an ellipse and a polyhedral is established and a suitable expression for the controller suffered by data quantization and actuator saturation is obtained. By defining the attraction domain and the invariant set based on the union or intersection of ellipses, we guarantee the decrement of the Lyapunov function in the optimal case if the state is within a given annular area. On this basis, if average dwell time and activation time of stabilizable subsystems meet some constraints, we derive that every trajectory whose initial state is within the given region will fall into a small ellipsoid and stay in a slightly larger ellipsoid. An illustrative example is given to verify the validity of the theoretical analysis. Full article

Driven by the “dual carbon” goal, virtual power plants (VPPs) are the core vehicle for integrating distributed energy resources, but the multiple uncertainties in wind power, electricity/heat load, and electricity price, coupled with the impact of carbon-trading cost, make it difficult for traditional scheduling methods to balance the robustness and economy of VPPs. Therefore, this paper proposes an oxy-fuel combustion capture (OCC)-VPP architecture, integrating an OCC unit to improve the energy efficiency of the system through the “electricity-oxygen-carbon” cycle. Ten typical scenarios are generated by Latin hypercube sampling and K-means clustering to describe the uncertainties of source and load probability distribution, combined with the polyhedral uncertainty set to delineate the boundary of source and load fluctuations, and the stepped carbon-trading mechanism is introduced to quantify the cost of carbon emission. Then, a three-stage stochastic–robust scheduling model is constructed. The simulation based on the arithmetic example of OCC-VPP in North China shows that (1) OCC-VPP significantly improves the economy through the synergy of electric–hydrogen production and methanation (52% of hydrogen is supplied with heat and 41% is methanated), and the cost of carbon sequestration increases with the prediction error, but the carbon benefit of stepped carbon trading is stabilized at the base price of 320 DKK/ton; (2) when the uncertainty is increased from 0 to 18, the total cost rises by 45%, and the cost of purchased gas increases by the largest amount, and the cost of energy abandonment increases only by 299.6 DKK, which highlights the smoothing effect of energy storage; (3) the proposed model improves the solution speed by 70% compared with stochastic optimization, and reduces cost by 4.0% compared with robust optimization, which balances economy and robustness efficiently. Full article

Among the various available synthesis approaches, hydrolytic precipitation offers a simple, cost-effective, and scalable route for producing phase-pure NiO with a controlled morphology and crystallite size. However, the influence of calcination temperature on its crystalline phase, particle size, and antimicrobial activity remains an active field of research. This study aims to investigate the structural, morphological, and antibacterial properties of NiO nanoparticles synthesized via hydrolytic methods and thermally treated at different temperatures. XRD data indicate the presence of the hexagonal crystallographic phase of NiO (space group 166: R-3m), a structural variant less commonly reported in the literature, stabilized under mild hydrolytic synthesis conditions. The average crystallite size increases significantly from 4.97 nm at 300 °C to values of ~17.8 nm at 500–700 °C, confirming the development of the crystal lattice. The ATR-FTIR analysis confirms the presence of the characteristic Ni–O band for all samples, positioned between 367 and 383 cm⁻¹, with a reference value of 355 cm⁻¹ for commercial NiO. The displacements and variations in intensity reflect a thermal evolution of the crystalline structure, but also an important influence of the size of the crystallites and the agglomeration state. The results reveal a systematic evolution in particle morphology from porous, flake-like nanostructures at 300 °C to dense, well-faceted polyhedral crystals at 900 °C. With an increasing temperature, particle size increases. EDS spectra confirm the high purity of the NiO phase across all samples. Additionally, the NiO nanoparticles exhibit calcination-temperature-dependent antibacterial activity, with the complete inhibition of Escherichia coli and Enterococcus faecalis observed after 24 h for the sample calcined at 300 °C and over 90% CFU reduction within 4 h. A significant reduction in E. faecalis viability across all samples indicates time- and strain-specific bactericidal effects. Due to its remarkable multifunctionality, NiO has emerged as a strategic nanomaterial in fields ranging from energy storage and catalysis to antimicrobial technologies, where precise control over its structural phase and particle size is essential for optimizing performance. Full article

Ultra-high-molecular-weight polyethylene (UHMWPE) is a pivotal material in engineering and biomedical applications due to its exceptional mechanical strength, wear resistance, and impact performance. However, its extreme melt viscosity, caused by extensive chain entanglements, severely limits processability via conventional melt-processing techniques. Recent advances in catalytic synthesis have enabled the production of disentangled UHMWPE (dis-UHMWPE), which exhibits enhanced processability while retaining superior mechanical properties. Notably, heterogeneous catalytic systems, utilizing supported fluorinated bis (phenoxy-imine) titanium (FI) catalysts, polyhedral oligomeric silsesquioxanes (POSS)-modified Z-N catalysts, and other novel catalysts, have emerged as promising solutions, combining structural control with industrial feasibility. Moreover, optimizing polymerization conditions further enhances chain disentanglement while maintaining ultra-high molecular weights. These systems utilize nanoscale supports and ligand engineering to spatially isolate active sites, tailor the chain propagation/crystallization kinetics, and suppress interchain entanglement during polymerization. Furthermore, characterization techniques such as melt rheology and differential scanning calorimetry (DSC) provide critical insights into chain entanglement, revealing distinct reorganization kinetics and bimodal melting behavior in dis-UHMWPE. This development of hybrid catalytic systems opens up new avenues for solid-state processing and industrial-scale production. This review highlights recent advances concerning interaction between catalyst design, polymerization control, and material performance, ultimately unlocking the full potential of UHMWPE for next-generation applications. Full article

The throughput of the pneumatic brake valve is a key parameter in ensuring fast and safe vehicle braking. The instantaneous value of this parameter determines the short response time of the system to an operator’s force. The scientific objective of this paper was to determine the throughput of brake valve tracts using numerical and experimental methods. These tracts are supposed to provide the tracking and acceleration function of the valve depending on the setting of the correction system. The first numerical method was based on polyhedral meshes using computational fluid dynamics (CFD) and Ansys Fluent software. The second research method—experimental tests on the author’s bench using the reservoir method—consisted of identifying throughputs based on pressure waveforms in the measurement tanks. The determined throughputs were averaged over the range of pressure differences tested and allowed the final calculation of the mass flow rate. The analysis of the obtained results showed an average discrepancy between the two research methods for both tracts, in which the flow in both directions was considered to be 9.43%, taking into account the use of a polyhedral numerical mesh ensuring high-quality results with an optimal simulation duration. The analysis of the pressure distribution inside the working chambers showed local areas of increased pressure and negative pressure resulting from the acceleration of the flow in narrow flow channels and the occurrence of the Venturi effect. Full article

We propose a novel space-time discretization method for a time-fractional dissipative wave equation. The approach employs a structured framework in which a fully discrete formulation is produced by combining virtual elements for spatial discretization and the Newmark predictor–corrector method for the temporal domain. The virtual element technique is regarded as a generalization of the finite element method for polygonal and polyhedral meshes within the Galerkin approximation framework. To discretize the time-fractional dissipation term, we utilize the Grünwald-Letnikov approximation in conjunction with the predictor–corrector scheme. The existence and uniqueness of the discrete solution are theoretically proved, together with the optimal convergence order achieved and an error analysis associated with the $H^1$-seminorm and the $L^2$-norm. Numerical experiments are presented to support the theoretical findings and demonstrate the effectiveness of the proposed method with both convex and non-convex polygonal meshes. Full article