ALBERT

Description: Despite the fact that cascade reservoirs are built in a large number of river basins nowadays, there is still an absence of studies on sequential embankment dam-break in cascade reservoirs. Therefore, numerical simulations and risk analyses of cascade reservoir dam-break are of practical engineering significance. In this study, by means of contacting the hydraulic features of upstream and downstream reservoirs with flood routing simulation (FRS) and flood-regulating calculation (FRC), a numerical model for the whole process of cascade reservoir breaching simulation (CRBS) is established based on a single-embankment dam-break model (Dam Breach Analysis—China Institute of Water Resources and Hydropower Research (DB-IWHR)). In a case study of a fundamental cascade reservoir system, in the upstream Tangjiashan barrier lake and the downstream reservoir II, the whole process of cascade reservoir dam-break is simulated and predicted under working schemes of different discharge capacities, and the risk of cascading breaching was also evaluated through CRBS. The results show that, in the dam-break of Tangjiashan barrier lake, the calculated values of the peak outflow rate are about 10% more than the recorded data, which are in an acceptable range. In the simulation of flood routing, the dam-break flood arrived at the downstream reservoir after 3 h. According to the predicted results of flood-regulating calculations and the dam-break simulation in the downstream reservoir, the risk of sequential dam-break can be effectively reduced by setting early warnings to decrease reservoir storage in advance and adding a second discharge tunnel to increase the discharge capacity. Alongside the simulation of flood routing and flood regulation, the whole process of cascade dam-break was completely simulated and the results of CRBS tend to be more reasonable; CRBS shows the great value of engineering application in the risk assessment and flood control of cascade reservoirs as an universal numerical prediction model.

Description: The mine cage has an important role in the production of coal mines. It has many safety problems in the transportation of people, such as overloading of personnel and illegal outreach of human limbs. However, the harsh mine environment makes it very difficult to monitor personnel overload and limb extension. To solve these two problems, we propose a novel safety monitoring algorithm of the mine cage based on visible light. With visible light technology, our algorithm cleverly utilizes the existing underground lighting equipment (i.e., miner’s headlamp and the miner’s lamp deployed on the mine cage) as the transmitter to broadcast the light beacons representing unique identity information through visible light frequency modulation. Next, cheap photodiodes deployed in the mine cage are used as the receiver to perceive the modulated optical signals. Then we use the frequency matching method for personnel counting and the frequency power comparison method for illegal limb extension monitoring. Moreover, a novel method of monitoring the delineated safe area of the mine cage is also proposed to ensure that all the miners are in the delineated safe area. Finally, we conducted extensive experiments with a simulated mine cage model. Results show that our algorithm has superior performance. With the photodiode SD5421-002, the accuracy of personnel overload judgment and safe area monitoring of our algorithm can reach 99%, and the accuracy of limb extension monitoring is more than 96%.

Description: Because of the urgent need to protect the environment, it has become vital to deal with the dangers and particularities associated with the growth in hazardous industrial waste. Governments have begun to expand their investments in the environmental protection industry and have tightened enterprise environmental management requirements. The 13th Five-Year Plan period in China, in particular, increased the focus on the environmental supervision and enterprise environmental management. Because of the specific qualities of many types of hazardous waste, most enterprises do not have the ability to process hazardous waste and therefore must outsource the disposal to third-party contractors. However, choosing suitable hazardous waste disposal enterprises (HWDE) can be difficult. Therefore, to assist in the selection of appropriate hazardous waste disposal enterprises, this paper developed a comprehensive evaluation index system for hazardous waste disposal enterprises (EISHWDE). As multi-criteria decision-making problems involve qualitative evaluations that have semantic ambiguity, hesitant fuzzy linguistic term sets (HFLTS) were introduced to increase the accuracy of the evaluation process, an analytic hierarchy process (AHP) used to determine the objective indicator weights, and PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation) employed to determine the final order for the selected enterprises. This research developed a scientific evaluation model that industrial waste enterprises (IWE) and related organizations could use to objectively and systematically select suitable hazardous waste disposal enterprises. Then, the problems of uncertainty and fuzzy semantics in the evaluation process were solved, and the weight of each selection criteria and the ranking of alternative enterprises are given.

Description: With the development of technology, the network structure has changed a lot. Many people regard the Internet of Things as the next-generation network structure, which means all the embedded devices can communicate with each other directly. However, some problems remain in IoT before it can be applied in a large scale. Blockchain, which has become a hot research topic in recent years, may be one of the solutions. However, currently, the transaction speed of blockchain is still a disadvantage compared to traditional transaction methods. This paper focuses on to implement a high-performance blockchain platform. After investigation of the current blockchain consensus algorithm and blockchain architecture, we propose: (1) an improved blockchain consensus algorithm, which is implemented based on the mortgage model instead of probability model; (2) a cross-chain protocol with transverse expansion capacity, which would support the message transmission among chains; (3) a high-performance cross-chain blockchain network structure, which could handle more than 1000 transactions per second per chain by verification. Experiments have been carried out, and shown that the cross-chain blockchain network structure we provided is feasible to meet the requirement of large-scale distributed IoT applications.

Description: The equipment condition monitoring based on computer hearing is a new pattern recognition approach, and the system formed by it has the advantages of noncontact and strong early warning abilities. Extracting effective features from the sound data of the running power equipment help to improve the equipment monitoring accuracy. However, the sound of running equipment often has the characteristics of serious noise, non-linearity and instationary, which makes it difficult to extract features. To solve this problem, a feature extraction method based on the improved complementary ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and multiscale improved permutation entropy (MIPE) is proposed. Firstly, the ICEEMDAN is utilized to obtain a group of intrinsic mode functions (IMFs) from the sound of running power equipment. The noise IMFs are then identified and eliminated through mutual information (MI) and mean mutual information (meanMI) of IMFs. Next, the normalized mutual information (norMI) and MIPE are calculated respectively, and norMI is utilized to weigh the corresponding MIPE result. Finally, based on the separability criterion, the weighted MIPE results are feature-dimensionally reduced to obtain the multiscale entropy feature of the sound. The experimental results show that the classification accuracies of the method under the conditions of no noise and 5 dB reach 96.7% and 89.9%, respectively. In practice, the proposed method has higher reliability and stability for the sound feature extraction of the running power equipment.

Description: Motor end cover mounting fracture is a problem recently encountered by novel pure electric vehicles. Regarding the study of the traditional vehicle engine mount bracket and on the basis of the methods of design and optimisation available, we have analysed and optimised the pure electric vehicle end cover mount system. Multi-body dynamic software and finite element software have been combined. First, we highlight the motor end cover mount bracket fracture engineering problems, analyse the factors that may produce fracture, and propose solutions. By using CATIA software to establish a 3D model of the power train mount system, we imported it into ADAMS multi-body dynamic software, conducted 26 condition analysis, obtained five ultimate load conditions, and laid the foundations for subsequent analysis. Next, a mount and shell system was established by the ANSYS finite element method, and modal, strength, and fatigue analyses were performed on the end cover mount. We found that the reason for fracture lies in the intensity of the end cover mount joint, which leads to the safety factor too small and the fatigue life not being up to standard. The main goal was to increase the strength of the cover mount junction, stiffness, safety coefficient, and fatigue life. With this aim, a topology optimisation was conducted to improve the motor end cover. A 3D prototype was designed accordingly. Finally, stiffness, strength, modal, and fatigue were simulated. Our simulation results were as follows. The motor end cover suspension stiffness increases by 20%, the modal frequency increases by 2.3%, the quality increases by 3%, the biggest deformation decreases by 52%, the maximum stress decreases by 28%, the minimum safety factor increases by 40%, and life expectancy increases 50-fold. The results from sample and vehicle tests highlight that the component fracture problem has been successfully solved and the fatigue life dramatically improved.

Description: Er3+-sensitized upconversion nanoparticles (UCNPs) have attracted great attention due to their tunable upconversion (UC) emissions, low cytotoxicity, high resistance to photobleaching and especially multiple effective excitation wavelengths. However, detailed energy conversion between Er3+ and Tm3+ ions in Y2O3 UCNPs is still a problem, especially under multi-wavelength and variable pulse width excitation. In this work, we successfully fabricated a series of Er3+-sensitized Y2O3 nanocrystals by a spray flame synthesis method with a production rate of 40.5 g h−1. The as-prepared UCNPs are a pure cubic phase with a mean size of 14 nm. Excited by both 980 and 808 nm lasers, the tunable upconversion luminescence (UCL) from Er3+ ions was achieved by increasing the Er3+ doping concentration, co-doping Tm3+ ions and extending excitation pulse-width. The investigations of the lifetimes and the laser power dependence of UC emissions further support the proposed mechanism, which provides guidance for achieving effective color control in anticounterfeiting and multiplexed labeling applications. In addition, the red UC emission at about 5 mm beneath the tissue surface was observed in an ex vivo imaging experiment under the excitation of 808 nm laser, indicating that the Y2O3:Er3+/Tm3+ UCNPs have great prospects in further biological applications.

Description: The adsorption behavior and the mechanism of a CO2/CH4 mixture in shale organic matter play significant roles to predict the carbon dioxide sequestration with enhanced gas recovery (CS-EGR) in shale reservoirs. In the present work, the adsorption performance and the mechanism of a CO2/CH4 binary mixture in realistic shale kerogen were explored by employing grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations. Specifically, the effects of shale organic type and maturity, temperature, pressure, and moisture content on pure CH4 and the competitive adsorption performance of a CO2/CH4 mixture were investigated. It was found that pressure and temperature have a significant influence on both the adsorption capacity and the selectivity of CO2/CH4. The simulated results also show that the adsorption capacities of CO2/CH4 increase with the maturity level of kerogen. Type II-D kerogen exhibits an obvious superiority in the adsorption capacity of CH4 and CO2 compared with other type II kerogen. In addition, the adsorption capacities of CO2 and CH4 are significantly suppressed in moist kerogen due to the strong adsorption strength of H2O molecules on the kerogen surface. Furthermore, to characterize realistic kerogen pore structure, a slit-like kerogen nanopore was constructed. It was observed that the kerogen nanopore plays an important role in determining the potential of CO2 subsurface sequestration in shale reservoirs. With the increase in nanopore size, a transition of the dominated gas adsorption mechanism from micropore filling to monolayer adsorption on the surface due to confinement effects was found. The results obtained in this study could be helpful to estimate original gas-in-place and evaluate carbon dioxide sequestration capacity in a shale matrix.

Description: Fucoidan, a sulfated polysaccharide extracted from brown seaweeds, has been shown to possess various antioxidant, anticoagulant, antiviral, and anticancer functions. In this study, we focused on low molecular weight fucoidan (LMWF) which was extracted from New Zealand Undaria pinnatifida, and investigated its anti-proliferative effects, combined with a quadruplex-forming oligonucleotide aptamer (GroA, AS1411), a powerful cell surface Nucleolin inhibitor, in prostate cancer cells. We examined LMWF (