Effects of injection rate profile on combustion process and emissions in a diesel engine

When multi-injection is implemented in diesel engine via high pressure common-rail injection system, changed interval between injection pulses can induce variation of injection rate profile for sequential injection pulse, though other control parameters are same. Variations of injection rate shape which influence the air-fuel mixing and combustion process will be important for designing injection strategy. In this research, CFD numerical simulations using KIVA-3V were conducted for examining the effects of injection rate shape on diesel combustion and emissions. After the model was validated by experimental results, five different shapes (including rectangle, slope, triangle, trapezoid and wedge) of injection rate profiles were investigated. Modelling results demonstrate that injection rate shape can have obvious influence on heat release process and heat release traces which cause different combustion process and emissions. It is observed that the baseline - rectangle (flat) shape of injection rate can have better balance between NOx and soot emissions than other investigated shapes. As wedge shape brings about the lowest NOx emissions due to retarded heat release, it produces highest soot emissions among five shapes. Trapezoid shape has the lowest soot emissions, while its NOx is not the highest one. The highest NOx emissions was produced by triangle shape due to higher peak injection rate

Effects of microfractures on permeability in carbonate rocks based on digital core technology

Carbonate reservoirs develop many different types of microfractures that play an important role in increasing the effective reservoir space and permeability. Thus, the qualitative and quantitative characterisation of the effect of microfractures on permeability in rocks is essential. In this study, a quantitative method for evaluating the impact of different microfracture parameters on carbonate rock permeability was proposed. Lattice Boltzmann simulations were carried on two carbonate digital cores with different types of artificially added microfractures. Based on the simulation results, a partial least squares regression analysis was used to investigate the impact of microfractures on the permeability of the cores. Increases in the fracture length, aperture, and density were found to linearly increase the permeability of the carbonate rocks, and as the fracture length increased to penetrate the whole core, an exponential increase in permeability was observed. Additionally, the effect of microfractures on the digital core permeability was more significant in cores with high permeability compared to that in low-permeability cores. Although both fractures and matrix permeability contribute to the permeability of the digital cores, the former were found to have a greater effect on the permeability.Cited as: Liu, C., Zhang, L., Li, Y., Liu, F., Martyushev, D. A., Yang, Y. Effects of microfractures on permeability in carbonate rocks based on digital core technology. Advances in Geo-Energy Research, 2022, 6(1): 86-90. https://doi.org/10.46690/ager.2022.01.0

A KRR-UKF robust state estimation method for distribution networks

State estimation is an integral component of energy management systems. Employing a state estimation methodology that is both accurate and resilient is essential for facilitating informed decision-making processes. However, the complex scenarios (unknown noise, low data redundancy, and reconfiguration) of the distribution network pose new challenges for state estimation. In the context of this study, we introduce a state estimation technique known as the kernel ridge regression and unscented Kalman filter. In normal conditions, the non-linear correlation among data and unknown noise increases the difficulty of modeling the distribution network. Thence, kernel ridge regression is developed to map the data into high-dimensional space that transforms the non-linear problem into linear formulations base on the data rather the complicate grid model, which improves model generalization performance and filters out unknown noises. In addition, with the unique prediction correction mechanism of the Kalman method, the kernel ridge regression-mapped state value can be revised by the measurement, which further enhances model accuracy and robustness. During abnormal operating conditions and taking into account the presence of faulty data within the measurement system, we initiate the use of a long short-term memory network and combined convolutional neural network (CNN) model, referred to as the ATT-CNN-GRU. This model is utilized for the prediction of pseudo-measurements. Subsequently, we use an outlier detection method known as ordering points to identify the clustering structure to effectively identify and substitute erroneous data points. Cases on the IEEE-33 bus system and 109-bus system from a city in China show that the method has superior accuracy and robustness

Low-grade waste heat recovery for wastewater treatment using clathrate hydrate based technology

Effectively recycling low-grade waste heat is crucial for advancing decarbonization and achieving net-zero emissions, yet current methodologies are limited by inefficiencies in extracting energy from sources with low exergy. This study introduces an innovative approach leveraging hydrate formation and dissociation to utilize low-grade waste heat in purifying wastewater. By directly heating (low-grade waste heat) liquid R134a, our method induces bubble formation, thereby enhancing hydrate nucleation and growth. Our system demonstrates exceptional energy efficiencies, reaching up to 23.5%, and exhibits a high removal efficiency for wastewater with high concentrations of organic and heavy metal contaminants, including methylene blue (86.4%), Cr3+ (98.0%), Ni2+ (98.3%), Zn2+ (98.0%), and Cu2+ (97.1%). This approach not only offers a sustainable pathway for waste heat utilization but also addresses critical challenges in wastewater treatment. This technology demonstrates substantial potential in both low-grade waste heat recovery and wastewater treatment

Lattice dynamics and heat transport in zeolitic imidazolate framework glasses

The glassy state of zeolitic imidazolate frameworks (ZIFs) has shown great potential for energy-related applications, including solid electrolytes. However, their thermal conductivity (κ), an essential parameter influencing thermal dissipation, remains largely unexplored. In this work, using a combination of experiments, atomistic simulations, and lattice dynamics calculations, we investigate κ and the underlying heat conduction mechanism in ZIF glasses with varying ratios of imidazolate (Im) to benzimidazolate (bIm) linkers. The substitution of bIm for Im tunes the node-linker couplings but exhibits only a minor impact on the average diffusivity of low-frequency lattice modes. On the other hand, the linker substitution induces significant volume expansion, which, in turn, suppresses the contributions from lattice vibrations to κ, leading to decreased total heat conduction. Furthermore, spatial localization of internal high-frequency linker vibrations is promoted upon substitution, reducing their mode diffusivities. This is ascribed to structural deformations of the bIm units in the glasses. Our work unveils the detailed influences of linker substitution on the dual heat conduction characteristics of ZIF glasses and guides the κ regulation of related hybrid materials in practical applications.</p

Efficacy and safety of triazavirin therapy for coronavirus disease 2019 : A pilot randomized controlled trial

Acknowledgements: We are deeply grateful to the front-line clinicians who participated in the study while directly fighting the epidemic. This study was supported by the Chinese Academy of Engineering Projects for COVID-19 (2020-KYGG-01-04) and Heilongjiang Province Urgent Project-6 for COVID-19. Data and safety monitoring board members of this trial included Kang Li, Yong Zhang, Songjiang Liu, and Yaohui Shi.Peer reviewedPublisher PD

The Ph-3 gene from Solanum pimpinellifolium encodes CC-NBS-LRR protein conferring resistance to Phytophthora infestans

Late blight, caused by Phytophthora infestans, is one of the most destructive diseases in tomato. The resistance (R) gene Ph-3, derived from Solanum pimpinellifolium L3708, provides resistance to multiple P. infestans isolates and has been widely used in tomato breeding programmes. In our previous study, Ph-3 was mapped into a region harbouring R gene analogues (RGA) at the distal part of long arm of chromosome 9. To further narrow down the Ph-3 interval, more recombinants were identified using the flanking markers G2-4 and M8-2, which defined the Ph-3 gene to a 26 kb region according to the Heinz1706 reference genome. To clone the Ph-3 gene, a bacterial artificial chromosome (BAC) library was constructed using L3708 and one BAC clone B25E21 containing the Ph-3 region was identified. The sequence of the BAC clone B25E21 showed that only one RGA was present in the target region. A subsequent complementation analysis demonstrated that this RGA, encoding a CC-NBS-LRR protein, was able to complement the susceptible phenotype in cultivar Moneymaker. Thus this RGA was considered the Ph-3 gene. The predicted Ph-3 protein shares high amino acid identity with the chromosome-9-derived potato resistance proteins against P. infestans (Rpi proteins)

A Preliminary Analysis of the Immunoglobulin Genes in the African Elephant (Loxodonta africana)

The genomic organization of the IgH (Immunoglobulin heavy chain), Igκ (Immunoglobulin kappa chain), and Igλ (Immunoglobulin lambda chain) loci in the African elephant (Loxodonta africana) was annotated using available genome data. The elephant IgH locus on scaffold 57 spans over 2,974 kb, and consists of at least 112 VH gene segments, 87 DH gene segments (the largest number in mammals examined so far), six JH gene segments, a single μ, a δ remnant, and eight γ genes (α and ε genes are missing, most likely due to sequence gaps). The Igκ locus, found on three scaffolds (202, 50 and 86), contains a total of 153 Vκ gene segments, three Jκ segments, and a single Cκ gene. Two different transcriptional orientations were determined for these Vκ gene segments. In contrast, the Igλ locus on scaffold 68 includes 15 Vλ gene segments, all with the same transcriptional polarity as the downstream Jλ-Cλ cluster. These data suggest that the elephant immunoglobulin gene repertoire is highly diverse and complex. Our results provide insights into the immunoglobulin genes in a placental mammal that is evolutionarily distant from humans, mice, and domestic animals