The operation range of two-stroke engines can be significantly narrowed with increasing adoption of electrified powertrains, enabling more targeted port design optimization. A one-dimensional (1D) engine system model and a three-dimensional (3D) computational fluid dynamics model were established in this study for a Curtis loopscavenged two-stroke engine and validated using experimental data. A coupled 1D-3D simulation method was developed to investigate the influence of exhaust port opening timing (EPO) and scavenging port opening timing (SPO) on the gas exchange process and engine performance. Temporal evolution and spatial distribution of the in-cylinder gas flow were jointly analyzed to reveal the mechanisms that govern the scavenging behavior. The results show that EPO timing has a dominant effect on the scavenging process, flow pattern, and exhaust gas purity, while SPO primarily affects the in-cylinder flow path and residual gas distribution. Variations in port timing affect effective compression ratio, pumping loss, and trapped volumetric efficiency, leading to changes in power and fuel consumption. Under the baseline port timing combination, the brake power is 25.6 kW, while the BSFC is 520 [g/(kW center dot h)]. The optimized port timing combination of EPO = 80 degrees CA and SPO = 117 degrees CA enhances engine power by 10.4%, whereas EPO = 80 degrees CA and SPO = 127 degrees CA reduces fuel consumption by 19.6%. The findings demonstrate that the coupled 1D-3D approach provides a novel tool for cross-dimensional analysis and offers valuable insights into the design and optimization of two-stroke engine scavenging systems.
This study systematically investigates the addition reaction between methyl radical and hydrogen cyanide, as well as the H-abstraction reactions of acetonitrile (CH3CN) by eight small radicals (H, OH, CH3, NH2, CH3O, HO2, NO, and NO2). Potential energy surfaces (PESs) were constructed at the CCSD(T)/cc-pVxZ (x = T-Q)//M08-HX/ aug-cc-pVTZ/def2-TZVP level of theory. Rate constants were calculated using a master equation (ME), while the CH3 + HCN reaction was treated using Rice-Ramsperger-Kassel-Marcus (RRKM) theory. For the H-abstraction reactions of CH3CN, rate constants were evaluated using both the hindered internal rotor (HIR) method combined with transition state theory (TST), and the pre-equilibrium model (PEM) coupled with RRKM theory. Onedimensional tunneling corrections (Eckart tunneling corrections) and the rigid-rotor-harmonic-oscillator (RRHO) model were also taken into account. The calculated temperature-and pressure-dependent rate constants were fitted using a modified Arrhenius expression. The results show that the initial addition channel exhibits strong pressure dependence and significant negative temperature dependence above 800 K. For the CH3 + HCN adduct CH3C(H)N, isomerization dominates under low-temperature conditions, while at higher temperatures, C-C bond fission leading to CH3 and HNC becomes the kinetically favored pathway. For the H-abstraction reactions of acetonitrile, the OH radical exhibits the lowest energy barrier and the most pronounced kinetic dominance. The calculated rate constants were incorporated into an CH3CN combustion model, which was validated under closed homogeneous reactor conditions. Compared to the original mechanism, the updated model yields comparable agreement with the experimental data, while incorporating improved rate constants derived from high-level quantum chemical calculations. The present work provides rigorously obtained ab initio kinetic parameters, offering valuable theoretical support for combustion modeling of CH3CN and for understanding the addition reactions of hydrogen cyanide.
In recent years, photocatalytic reduction of CO2 using renewable solar energy has emerged as a promising technology for addressing the energy crisis. To achieve efficient CO2 photoreduction, enhancing the sunlight absorption capacity and charge separation efficiency of g-C3N4-based photocatalysts was crucial. Hydrothermal preparation of dual Z-scheme Cu2-xS/g-C3N4/NiAl-LDH composite catalysts was used in this study. The optimized Cu2-xS/g-C3N4/NiAl-LDH photocatalyst demonstrated CH4 and CO yields of 28.13 and 4.47 & micro;mol g-1h-1, respectively. Notably, the CH4 yield was 12.5 times higher than that of the LDH monomer, and the selectivity of CH4 was as high as 96.2%. The promotion mechanism could be attributed to the photothermal effect of composite catalyst and the augmented light absorption, as well as the efficient internal charge transfer originated from the bi-heterostructure. Consequently, combining Cu2-xS/g-C3N4/NiAl-LDH and photothermal effects, this photocatalyst design provides insightful information for creating full-spectrum responsive photocatalysts for CO2 reduction.
Abstract Terrestrial laser scanning (TLS) technology is increasingly used to measure bridge geometric shapes. However, the commonly observed loss of critical geometric details in point clouds poses significant challenges for automate and accurate measurement. A robust measurement method based on prior design knowledge orientation is proposed in the present study. First, component point cloud slices are extracted from full-bridge point cloud data through manual segmentation and 3D-to-2D projection. Then, the prior design knowledge is generated from the bridge design data, including component cross-sectional point clouds and geometric information. This prior knowledge is integrated with the extracted slices through template matching to establish stable geometric constraints. Finally, the extracted feature points under constraints are connected to generate the component alignment. The proposed method was validated through a field test on an under-construction arch bridge and a robustness evaluation using a virtual scanning bridge model. The results show that the method achieves a measurement accuracy within 5 mm and exhibits significant tolerance to variations in data density and completeness.
Diesel-methanol partially premixed combustion (DM-PPC), characterized by prior mixing and controlled auto-ignition, is a promising strategy for improving combustion controllability and extending methanol utilization in compression-ignition engines. However, the spatiotemporal evolution of ignition and flame development under different injection intervals remains insufficiently quantified. In this work, diesel–methanol dual-fuel direct-injection jet flame tests were conducted in a constant-volume chamber at 750 K and 40 bar. A CNN-based denoising and recognition method centered on the Fast and Flexible Denoising Network (FFDNet) was developed for jet-flame Schlieren images, integrating noise-level map generation-estimation and robust segmentation. Three DM-PPC modes were identified. In the methanol-leading low-temperature DM-PPC mode, the blue flame lasted about 0.7–0.8 ms, the yellow flame was weak and short-lived for about 0.4 ms, the flame-contour area growth-rate peak was about 2.0–3.0 m2/s, and the total flame lift-off length (FLOL) was short, about 40–80 mm, toward the methanol side. In the co-injection premixed–diffusion-coupled DM-PPC mode, multi-point ignition kernels formed within the diesel–methanol mixing zone, with flame-contour growth-rate peaks of about 7.0–9.0 m2/s and average flame-speed spikes of 170–220 m/s. In the diesel-leading diffusion-flame-dominated DM-PPC mode, the short blue-flame stage was followed by strong yellow-flame clusters; the flame-contour growth-rate peak reached 1.5–1.8 m2/s, the initial average flame-speed spike increased to 200–230 m/s, and the early total FLOL was the largest, about 100 mm. The novelty of this study lies in integrating a spatially adaptive FFDNet-based denoising framework with high-speed Schlieren diagnostics to quantitatively identify injection-interval-governed DM-PPC flame modes under high-temperature and high-pressure conditions.
