Design optimization of TBM disc cutters for different geological conditions

A novel optimization methodology for the disc cutter designs of tunnel boring machines (TBM) was presented. To fully understand the characteristics and performance of TBM cutters, a comprehensive list of performance parameters were investigated, including maximum equivalent stress and strain, specific energy and wear life which were closely related to the cutting forces and profile geometry of the cutter rings. A systematic method was employed to evaluate an overall performance index by incorporating objectives at all possible geological conditions. The Multi-objective & Multi-geologic Conditions Optimization (MMCO) program was then developed, which combined the updating of finite element model, system evaluation, finite element solving, post-processing and optimization algorithm. Finally, the MMCO was used to optimize the TBM cutters used in a TBM tunnel project in China. The results show that the optimization significantly improves the working performances of the cutters under all geological conditions considered

Establishment of Coal-rock Constitutive Models for Numerical Simulation of Coal-rock Cutting by Conical Picks

One of the key points in numerical simulation of coal-rock cutting by conical picks is to select a proper coal-rock constitutive model. In order to find a reasonable coal-rock constitutive model, a uniaxial compression test was conducted to obtain the constitutive model. The several stages for linear elastic deformation and creep, plastic yielding, hardening, and finally brittle cracking of the constitutive units were studied, and the coal-rock constitutive model was established. As a result, the coal-rock cutting by one conical pick or two conical picks was simulated and the results were compared with coal-rock cutting experiment on a Coal-rock Cutting Machine. According to the simulation and experimental results, it is believed that the numerical simulation can reveal coal-rock crushing process. And the total error rate of coal-rock cutting by one conical pick between the simulation and experiment is 8.5%. The maximum deviation of coal-rock cutting by two conical picks between the simulation and experiment is 9.8%. All simulation values are within a reasonable range. The comparison indicates that the coal-rock constitutive model should better be defined considering the coal-rock crushing process by conical picks

Experimental Evaluation of Fragments from TBM Disc Cutting under Different Load Cases

The Tunnel Boring Machine (TBM) tunneling process always contains a certain degree of vibrations due to the step broken phenomenon of the cutting tools. Undoubtedly, there is a quite difference in the fragment characteristics which are related to the construction efficiency of TBM under the static load and the combination of static and impact load. In this study, a series of rock breaking tests with a 216 mm diameter disc cutter and marble samples were conducted under different load cases. Based on the Rosin–Rammler distribution curve, the fragments from the cutting tests were also sieved to calculate the absolute size constant (x’) and coarseness index (CI). The relationship between coarseness index, absolute size parameter and the cutting parameters, specific energy, production rate was evaluated. The results show that there is an increasing trend of x’ and CI with the increase of cut spacing and penetration as well as adding impact load component. An overall downtrend in specific energy and upward trend in production rate which are associated with the high efficiency can be observed with the increasing CI and x’. It is believed that the conclusions are of great significance for improving TBM construction efficiency and cutterhead design

Cutting Characteristics and Layout of Pre-cutting Machine Cutter

The pre-cutting machine is becoming valued due to its ability to effectively prevent surface settlement and reduce vibration in tunnel construction. To obtain the cutting characteristics and layout of pre-cutting machine cutter, the cutting tests by the pre-cutting machine cutter are conducted and the cutting laws are also studied. The research results show that the cutting force rather than normal force and side force is responsible for the rock breaking. With the increase of the cutting depth and cutting spacing, the cutting forces increase generally. But for the little value of cutting spacing, the cutting force can not increase continuously when the cutting depth increase to a relatively large value. Furthermore, for a given cutting depth, the cutting force will keep at an approximate constant rather than continuous increase with the increase of the cutting spacing when the cutting spacing increases to a relatively large value. The specific energy decreases nonlinearly with the increase of cutting depth and the decrease of specific energy is not significant when the cutting depth is more than 12 mm. Moreover, there exists an optimal cutting spacing for a given cutting depth. To maintain a desirable cutting efficiency, the ratio of cutting spacing to cutting depth should be controlled between 1 and 2. Finally, the layout plan of the pre-cutting machine cutter is proposed based on the research results and is applied in the actual manufacturing of the pre-cutting machine

Progressive Learning with Visual Prompt Tuning for Variable-Rate Image Compression

In this paper, we propose a progressive learning paradigm for transformer-based variable-rate image compression. Our approach covers a wide range of compression rates with the assistance of the Layer-adaptive Prompt Module (LPM). Inspired by visual prompt tuning, we use LPM to extract prompts for input images and hidden features at the encoder side and decoder side, respectively, which are fed as additional information into the Swin Transformer layer of a pre-trained transformer-based image compression model to affect the allocation of attention region and the bits, which in turn changes the target compression ratio of the model. To ensure the network is more lightweight, we involves the integration of prompt networks with less convolutional layers. Exhaustive experiments show that compared to methods based on multiple models, which are optimized separately for different target rates, the proposed method arrives at the same performance with 80% savings in parameter storage and 90% savings in datasets. Meanwhile, our model outperforms all current variable bitrate image methods in terms of rate-distortion performance and approaches the state-of-the-art fixed bitrate image compression methods trained from scratch

Synergistic tailoring of band structure and charge carrier extraction in "green" core/shell quantum dots for highly efficient solar energy conversion

Environment-friendly colloidal core/shell quantum dots (QDs) with controllable optoelectronic characteristics are promising building blocks for future commercial solar technologies. Herein, we synergistically tailor the electronic band structure and charge carrier extraction of eco-friendly AgInS2 (AIS)/ZnS core/shell QDs via Mn-alloying and Cu-doping in the core and shell, respectively. It is demonstrated that the Mn-alloying in AIS core can broaden the band gap to facilitate delocalization of photogenerated electrons into the shell and further incor-poration of Cu in the ZnS shell enables the creation of Cu-related states that capture the photogenerated holes from core, thus leading to charge carrier recombination and accelerated transfer of photogenerated electrons in the core/shell QDs. As-prepared Mn-AIS/ZnS@Cu QDs were assembled as light harvesters in a photo-electrochemical (PEC) device for light-driven hydrogen evolution, delivering a maximum photocurrent density of ~ 6.4 mA cm-2 with superior device stability under standard one sun irradiation (AM 1.5G, 100 mW cm(-2)). Our findings highlight that simultaneously engineering the band alignment and charge carrier dynamics of "green " core/shell QDs endow the feasibility to design future high-efficiency and durable solar hydrogen pro-duction systems

Effects of captivity and artificial breeding on microbiota in feces of the red-crowned crane (Grus japonensis)

Reintroduction of the threatened red-crowned crane has been unsuccessful. Although gut microbiota correlates with host health, there is little information on gut microbiota of cranes under different conservation strategies. The study examined effects of captivity, artificial breeding and life stage on gut microbiota of red-crown cranes. The gut microbiotas of wild, captive adolescent, captive adult, artificially bred adolescent and artificially bred adult cranes were characterized by next-generation sequencing of 16S rRNA gene amplicons. The gut microbiotas were dominated by three phyla: Firmicutes (62.9%), Proteobacteria (29.9%) and Fusobacteria (9.6%). Bacilli dominated the ‘core’ community consisting of 198 operational taxonomic units (OTUs). Both captivity and artificial breeding influenced the structures and diversities microbiota of the gut. Especially, wild cranes had distinct compositions of gut microbiota from captive and artificially bred cranes. The greatest alpha diversity was found in captive cranes, while wild cranes had the least. According to the results of ordination analysis, influences of captivity and artificial breeding were greater than that of life stage. Overall, captivity and artificial breeding influenced the gut microbiota, potentially due to changes in diet, vaccination, antibiotics and living conditions. Metagenomics can serve as a supplementary non-invasive screening tool for disease control