Numerical prediction of effects of CO2 or H2 content on combustion characteristics and generation efficiency of biogas-fueled engine generator

The fundamental effect of additives and the lean burn capability of methane combustion are investigated using cycle simulation and Latin hypercube sampling. The target engine is a spark-ignition engine fueled by methane and biogas mixed with hydrogen. The dominant variables were CO₂ and H₂ content, spark timing, and excess air ratio (EAR). Varying the amount of additives (CO₂ and H₂), spark timing, and EAR demonstrated that hydrogen plays an important role in extending the lean operating limit. The fractional factorial design of the experiment, Latin hypercube sampling, was applied to obtain the maximum brake torque (MBT) spark timing with variants in excess air ratios and additive content. When MBT spark timing is employed, the maximum mass fraction burned can be enhanced in the lean-burn region by increasing the hydrogen content with improved generating efficiencies under lean operating conditions.     

Experimental and numerical study of detailed reaction mechanism optimization for syngas (H2 + CO) production by non-catalytic partial oxidation of methane in a flow reactor

The National Institute of Standards and Technology (NIST) detailed reaction mechanism of methane combustion was optimized based on a flow reactor experiment to obtain syngas (H₂ + CO). The experimental methane partial oxidation was conducted with pre-mixed gas in a flow reactor. Specifically, 0.2% methane and 0.1% oxygen were diluted with 99.7% argon, restraining the exothermic effect. The experiment was conducted from 1223 K to 1523 K under pressure. Through a comparison of the experimental results with calculated values, the NIST mechanism was selected as a starting point. Rate coefficients of O + OH = O₂ + H, CH₃ + O₂ = CH₃O + O, and C₂H₂ + O₂ = HCCO + OH were replaced with results from other studies. The replaced rate coefficient for CH₃ + O₂ = CH₃O + O was again optimized, within its reported uncertainty of 3.16, based on the experimental results of this study. The revised value of the rate coefficient for CH₃ + O₂ = CH₃O + O was k₃₇ = 7.92 × 10¹³ × e^{(−31400/RT)}. The optimized mechanism showed better performance in predicting the results of other studies, as well as this study. The optimization reduced the RMS error for the results of this study from 6.7 to 1.18.     

Flow Boiling in an Inclined Channel With Downward-Facing Heated Upper Wall

Wall boiling and bubble population balance equations combined with a two-fluid model are employed to predict boiling two-phase flow in an inclined channel with a downward-facing heated upper wall. In order to observe the boiling behavior on the inclined, downward-facing heated wall, a visualization experiment was carried out with a 100 mm × 100 mm of the cross section, 1.2-m-long rectangular channel, inclined by 10° from the horizontal plane. The size of the heated wall was 50 mm by 750 mm and the heat flux was provided by Joule heating using DC electrical current. The temperatures of the heater surface were measured and used in calculating heat transfer coefficients. The wall superheat for 100 kW/m² heat flux and 200 kg/m²s mass flux ranged between 9.3°C and 15.1°C. High-speed video images showed that bubbles were sliding, continuing to grow, and combining with small bubbles growing at their nucleation sites in the downstream. Then large bubbles coalesced together when the bubbles grew too large to have a space between them. Finally, an elongated slug bubble formed and it continued to slide along the heated wall. For these circumstances of wall boiling and two-phase flow in the inclined channel, the existing wall boiling model encompassing bubble growth and sliding was improved by considering the influence of large bubbles near the heated wall and liquid film evaporation under the large slug bubbles. With this improved model, the predicted wall superheat agreed well with the experimental data, while the RPI model largely overpredicted the wall superheat.     

The Trade-Off Between Performance and Security of Virtualized Trusted Execution Environment on Android

Nowadays, with the significant growth of the mobile market, security issues on the Android Operation System have also become an urgent matter. Trusted execution environment (TEE) technologies are considered an option for satisfying the inviolable property by taking advantage of hardware security. However, for Android, TEE technologies still contain restrictions and limitations. The first issue is that non-original equipment manufacturer developers have limited access to the functionality of hardware-based TEE. Another issue of hardware-based TEE is the cross-platform problem. Since every mobile device supports different TEE vendors, it becomes an obstacle for developers to migrate their trusted applications to other Android devices. A software-based TEE solution is a potential approach that allows developers to customize, package and deliver the product efficiently. Motivated by that idea, this paper introduces a VTEE model, a software-based TEE solution, on Android devices. This research contributes to the analysis of the feasibility of using a virtualized TEE on Android devices by considering two metrics: computing performance and security. The experiment shows that the VTEE model can host other software-based TEE services and deliver various cryptography TEE functions on the Android environment. The security evaluation shows that adding the VTEE model to the existing Android does not add more security issues to the traditional design. Overall, this paper shows applicable solutions to adjust the balance between computing performance and security.     

ASL Recognition by the Layered Learning Model Using Clustered Groups

American Sign Language (ASL) images can be used as a communication tool by determining numbers and letters using the shape of the fingers. Particularly, ASL can have an key role in communication for hearing-impaired persons and conveying information to other persons, because sign language is their only channel of expression. Representative ASL recognition methods primarily adopt images, sensors, and pose-based recognition techniques, and employ various gestures together with hand-shapes. This study briefly reviews these attempts at ASL recognition and provides an improved ASL classification model that attempts to develop a deep learning method with meta-layers. In the proposed model, the collected ASL images were clustered based on similarities in shape, and clustered group classification was first performed, followed by reclassification within the group. The experiments were conducted with various groups using different learning layers to improve the accuracy of individual image recognition. After selecting the optimized group, we proposed a meta-layered learning model with the highest recognition rate using a deep learning method of image processing. The proposed model exhibited an improved performance compared with the general classification model.     

Stratum-Confined Solid-State Reaction (SC-SSR) toward Colloidal Silicon-Based Hollow Nanostructures for Bioapplications

Silicon nanostructures (SiNSs) can provide multifaceted bioapplications; but preserving their subhundred nm size during high-temperature silica-to-silicon conversion is the major bottleneck. The SC-SSR utilizes an interior metal-silicide stratum space at a predetermined radial distance inside silica nanosphere to guide the magnesiothermic reduction reaction (MTR)-mediated synthesis of hollow and porous SiNSs. In depth mechanistic study explores solid-to-hollow transformation encompassing predefined radial boundary through the participation of metal-silicide species directing the in-situ formed Si-phase accumulation within the narrow stratum. Evolving thin-porous Si-shell remains well protected by the in-situ segregated MgO emerging as a protective cast against the heat-induced deformation and interparticle sintering. Retrieved hydrophilic SiNSs (<100 nm) can be conveniently processed in different biomedia as colloidal solutions and endocytosized inside cells as photoluminescence (PL)-based bioimaging probes. Inside the cell, rattle-like SiNSs encapsulated with Pd nanocrystals can function as biorthogonal nanoreactors to catalyze intracellular synthesis of probe molecules through C-C cross coupling reaction.     

Effect of rotating,non-axisymmetric cavitator on supercavity size

This study was conducted using a rotating non-axisymmetric cavitator to artificially increase the size of the cavity. Computational analysis was performed to predict the size of the cavity with a cavitation number of 0.3. To analyze the effect of the shape of the cavitator, six cavitator shapes were used by combining the cavitator thickness, the angle of the blades, the angle between the side surface of the blade and the rotating direction. The results of the study showed that the length of the cavity increased as the rotation velocity increased during the rotation of the cavitator. The drag force increased as the rotation velocity increased, but the increase was small. As a result, the length of the cavity for the same drag increased significantly as the side surface of the cavitator was perpendicular to the direction of rotation and the thickness of the cavitator was thick. The length of the cavity against the same drag was larger than that of a conventional disk cavitator.

     

Exceeding Theoretical Capacity in Exfoliated Ultrathin Manganese Ferrite Nanosheets via Galvanic Replacement-Derived Self-Hybridization for Fast Rechargeable Lithium-Ion Batteries

Mixed transition metal oxides are promising anodes to meet high-performance energy storage materials; however, their widespread uses are restrained owing to limited theoretical capacity, restricted synthesis methods and templates, low conductivity, and extreme volume expansion. Here, Mn_3-xFe_xO₄ nanosheets with interconnected conductive networks are synthesized via a novel self-hybridization approach of a facile, galvanic replacement-derived, tetraethyl orthosilicate-assisted hydrothermal process. An exceptionally high reversible capacity of 1492.9 mAh g⁻¹ at 0.1 A g⁻¹ is achieved by producing Li-rich phase through combined synergistic effects of amorphous phases with interface modification design for fully utilizing highly spin-polarized surface capacitance. Furthermore, it is demonstrated that large surface area can effectively facilitate Li-ion kinetics, and the formation of interconnected conductive networks improves the electrical conductivity and structural stability by alleviating volume expansion. This leads to a high rate capability of 412.3 mAh g⁻¹ even at an extremely high current density of 10 A g⁻¹ and stable cyclic stability with a capacity up to 921.9 mAh g⁻¹ at 2 A g⁻¹ after 500 cycles. This study can help to overcome theoretically limited electrochemical properties of conventional metal oxide materials, providing a new insight into the rational design with surface alteration to boost Li-ion storage capacity.