Aerodynamic shape optimization is usually a loop of an optimization model, an optimizer and an evaluation workflow. A new optimizer is proposed and tested for a typical aerodynamic shape optimization ...of missile control surfaces with computational fluid dynamics (CFD). The new optimizer emphasizes the use of machine learning techniques, reinforcement learning and transfer learning, to improve performance and efficiency. Reinforcement learning is applied to extract the optimization experience from the semi-empirical method DATCOM using deep neural networks. Transfer learning is implemented to reuse the experience as priori knowledge in the CFD-based optimization by sharing neural network parameters. For the considered aerodynamic shape optimization problem of missile control surfaces, a remarkable reduction in the computational time has been accomplished. The new approach significantly decreases the required CFD calls by over 62.5%. Meanwhile, the time spent in the experience extraction and parameter transfer process is negligible.
Rapid diagnosis of diseases at their initial stage is critical for effective clinical outcomes and promotes general public health. Classical in vitro diagnostics require centralized laboratories, ...tedious work and large, expensive devices. In recent years, numerous electrochemical biosensors have been developed and proposed for detection of various diseases based on specific biomarkers taking advantage of their features, including sensitivity, selectivity, low cost and rapid response. This article reviews research trends in disease-related detection with electrochemical biosensors. Focus has been placed on the immobilization mechanism of electrochemical biosensors, and the techniques and materials used for the fabrication of biosensors are introduced in details. Various biomolecules used for different diseases have been listed. Besides, the advances and challenges of using electrochemical biosensors for disease-related applications are discussed.
Conventional wastewater treatment plants (WWTPs) clean wastewater and minimize water pollution; but, while doing so, they also contribute to air pollution and need energy/material input with ...associated emissions. However, energy recovery (e.g. anaerobic digestion) and resource recovery (e.g. water reuse) allow us to offset the adverse environmental impacts of wastewater treatment. Life cycle assessments (LCA) have been used more and more to evaluate the environmental impacts of WWTPs and to suggest improvement options. There is a need to search for resource recovery applications that genuinely realize a net-zero impact on the total environment of WWTPs. In this work, a scheme with highly efficient energy and resource recovery (especially for thermal energy) is proposed and evaluated. The environmental impact of a conventional WWTP in comparison with the scheme proposed here, with energy/resource recovery included, was calculated, and discussed with reference to LCA methodology. In the process of using LCA, it was necessary to choose a regional situation to focus on. In this case, a Chinese situation was focused as a reference, but the qualitative information gained is of worldwide relevance. The results clearly revealed that conventional WWTP does not benefit the total environment as a whole while the new scheme benefited the total environment via resource/energy recovery-based processes. Among others, thermal energy recovery played a significant role towards a net-zero LCA analysis (contributing around 40%) which suggests that more attention and research should be focused on it.
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•Impacts of resource recovery on the environment was assessed by an improved LCA.•Resource recovery can help WWTPs in their goal of a zero net environmental impact.•Effluent reuse alone is not sufficient to attain a zero net environmental impact.•Thermal energy recovery would contribute the most to improving the impact of WWTPs.
To exert the imbibition between cracks and matrix effectively and enhance the development effect of tight oil reservoirs, a physical simulation method for imbibition in different scales of cores is ...developed by combining a high-pressure large-model physical simulation system and nuclear magnetic resonance technology (NMR) to investigate the influencing factors of imbibition process in tight reservoirs, and construct a quantitative evaluation method for the imbibition in water flooding. The results show that in the process of counter-current imbibition, the lower the permeability, the later the oil droplet precipitation, the longer the imbibition equilibrium time, and the lower the recovery degree. Fractures can effectively expand the area of imbibition and the front edge of imbibition in the contact between the dense matrix and water, reduce the resistance of oil discharge, and improve the imbibition speed and the degree of recovery. The more hydrophilic the rock, the higher the imbibition rate and imbibition recovery of tight rocks. In the process of co-current imbibition, the lower the permeability, the more obvious the imbibition, and the displacement recovery is positively correlated with permeability, while the imbibition recovery is negatively correlated with the permeability. It also shows that the imbibition distance of the cyclic water injection is greater than that of the counter-current imbibition, and the higher the permeability and the injection multiple, the longer the imbibition distance. The combination of large-scale volume fracturing with changing reservoir wettability and cyclic water injection is conducive to improving the imbibition ability of tight reservoirs.
This work designs an experimental model of tight sandstone with a closed cemented pre-existing fracture network (CCPF) to explore the influence of closed cemented natural fractures on the propagation ...behavior of hydraulic fracture (HF) in tight sandstone formations. The influence of CCPFs with different directions on the initiation, deflection, and propagation of HF is studied based on tri-axial hydraulic fracturing experiments with acoustic emission (AE) monitoring technology. The experimental results show four types of interaction behavior between HFs and CCPFs: deflection I; deflection II; penetration; and composite pattern. When the angle (α) between the HFs and CCPF is 0° ± 15°, their interaction is deflection I. During the process of hydraulic fracturing, the CCPF open with few AE events. When α = 90° ± 15°, the interaction between the HF and CCPFs includes deflection II and penetration patterns. The HF mainly extends in the rock matrix and is accompanied by significant AE events. When α = 45° ± 15°, the interaction is complicated and includes composite and deflection I patterns. The accumulated AE energy of composite interaction pattern shows a ladder-type increase. Under the same in-situ stress conditions, the HF geometry is the most complicated with the largest number of communicated natural fractures when the angle between the maximum principal horizontal stress direction and CCPF is 30°–60°. The experimental model designed in this paper can reproduce the complex propagation patterns of HFs in fractured tight sandstone formations, and the results provide a reliable basis for follow-up theoretical studies and engineering applications.
•A new experimental model of fractured tight sandstone formation is established which includes several groups of cemented closed fractures in different directions.•The complex fracture propagation patterns revealed the physical experiment of hydraulic fracturing combing the AE monitoring technology.•The relationship between the characteristics of injection pressure curve and fracture propagation patterns was explored.•Findings about the propagation mechanism of hydraulic fracture under the influence of closed cemented fracture was discussed.
We propose a new feature selection strategy based on rough sets and particle swarm optimization (PSO). Rough sets have been used as a feature selection method with much success, but current ...hill-climbing rough set approaches to feature selection are inadequate at finding optimal reductions as no perfect heuristic can guarantee optimality. On the other hand, complete searches are not feasible for even medium-sized datasets. So, stochastic approaches provide a promising feature selection mechanism. Like Genetic Algorithms, PSO is a new evolutionary computation technique, in which each potential solution is seen as a particle with a certain velocity flying through the problem space. The Particle Swarms find optimal regions of the complex search space through the interaction of individuals in the population. PSO is attractive for feature selection in that particle swarms will discover best feature combinations as they fly within the subset space. Compared with GAs, PSO does not need complex operators such as crossover and mutation, it requires only primitive and simple mathematical operators, and is computationally inexpensive in terms of both memory and runtime. Experimentation is carried out, using UCI data, which compares the proposed algorithm with a GA-based approach and other deterministic rough set reduction algorithms. The results show that PSO is efficient for rough set-based feature selection.
There are a series of challenges in microgrid transactions, and blockchain technology holds the promise of addressing these challenges. However, with the increasing number of users in microgrid ...transactions, existing blockchain systems may struggle to meet the growing demands for transactions. Therefore, this paper proposes an efficient and secure blockchain consensus algorithm designed to meet the demands of large-scale microgrid electricity transactions. The algorithm begins by utilizing a Spectral clustering algorithm to partition the blockchain network into different lower-level consensus set based on the transaction characteristics of nodes. Subsequently, a dual-layer consensus process is employed to enhance the efficiency of consensus. Additionally, we have designed a secure consensus set leader election strategy to promptly identify leaders with excellent performance. Finally, we have introduced an authentication method that combines zero-knowledge proofs and key sharing to further mitigate the risk of malicious nodes participating in the consensus. Theoretical analysis indicates that our proposed consensus algorithm, incorporating multiple layers of security measures, effectively withstands blockchain attacks such as denial of service. Simulation experiment results demonstrate that our algorithm outperforms similar blockchain algorithms significantly in terms of communication overhead, consensus latency, and throughput.
Propulsion during push-off (PO) is a key factor to realize human locomotion. Through the detection of real-time gait stage, assistance could be provided to the human body at the proper time. In most ...cases, ankle-foot exoskeletons consist of electronic sensors, microprocessors, and actuators. Although these three essential elements contribute to fulfilling the function of the detection, control, and energy injection, they result in a huge system that reduces the wearing comfort. To simplify the sensor-controller system and reduce the mass of the exoskeleton, we designed a smart clutch in this paper, which is a sensor-controller integrated system that comprises a sensing part and an executing part. With a spring functioning as an actuator, the whole exoskeleton system is completely made up of mechanical parts and has no external power source. By controlling the engagement of the actuator based on the signal acquired from the sensing part, the proposed clutch enables the ankle-foot exoskeleton (AFE) to provide additional ankle torque during PO, and allows free rotation of the ankle joint during swing phase, thus reducing the metabolic cost of the human body. There are two striking advantages of the designed clutch. On the one hand, the clutch is lightweight and reliable-it resists the possible shock during walking since there is no circuit connection or power in the system. On the other hand, the detection of gait relies on the contact states between human feet and the ground, so the clutch is universal and does not need to be customized for individuals.
•The potential for using chitosan as a natural food preservative was assessed.•Antifungal ability and spore germination inhibition of chitosan were investigated.•Effect of chitosan derivatives ...coatings on postharvest green asparagus was evaluated.
The antifungal activity and effect of high-molecular weight chitosan (H-chitosan), low-molecular weight chitosan (L-chitosan) and carboxymethyl chitosan (C-chitosan) coatings on postharvest green asparagus were evaluated. L-chitosan and H-chitosan efficiently inhibited the radial growth of Fusarium concentricum separated from postharvest green asparagus at 4mg/ml, which appeared to be more effective in inhibiting spore germination and germ tube elongation than that of C-chitosan. Notably, spore germination was totally inhibited by L-chitosan and H-chitosan at 0.05mg/ml. Coated asparagus did not show any apparent sign of phytotoxicity and maintained good quality over 28days of cold storage, according to the weight loss and general quality aspects. Present results inferred that chitosan could act as an attractive preservative agent for postharvest green asparagus owing to its antifungal activity and its ability to stimulate some defense responses during storage.
A large area of coarse-grained saline soil is distributed in saline soil areas, and chlorine saline soil with a high salt content is a typical representative. The dynamic resilient modulus was ...accurately predicted using the California-bearing ratio (CBR) value to determine the relationship between the dynamic resilient modulus of coarse-grained chloride saline soil and its CBR value. Indoor dynamic triaxial tests and CBR tests were conducted to investigate the evolution of the dynamic resilient modulus (M
) and CBR of coarse-grained chlorine saline soil under the influence of the stress level, water content, and salt content. The test results showed that the dynamic resilient modulus increased with an increase in the confining pressure and bulk stress and decreased as the deviator stress increased; however, the CBR increased with an increase in the corresponding unit pressure. The higher the salt and water contents, the more obvious the influence of stress on the dynamic resilient modulus and CBR value. Under the same stress level, the decrease in the dynamic resilient modulus and CBR gradually increased with increasing salt and moisture content, and the effect of salt tended to be more significant than that of water. Based on the correlation between the dynamic resilient modulus and CBR revealed by the experiment, a more widely applicable model was selected from the existing theoretical models related to CBR for the regression analysis of the test data, and a prediction model of the dynamic resilient modulus based on the CBR value was proposed (M
= 21.06CBR
). This prediction model had a high correlation coefficient (R
= 0.893) and could effectively predict the dynamic resilient modulus of coarse-grained chlorine saline soil using CBR values. The results provide a simple and reliable method for determining the design parameters of a coarse-grained saline soil subgrade.
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