Superconducting fluctuations and charge-4ee plaquette state at strong coupling

Recent experiments indicate that superconducting fluctuations also play an important role in overdoped cuprates. Here we apply the static auxiliary field Monte Carlo approach to study phase correlations of the pairing fields in a microscopic model with spin-singlet pairing interaction. We find that the short- and long-range phase correlations are well captured by the phase mutual information, which allows us to construct a theoretical phase diagram containing the uniform $d$-wave superconducting region, the phase fluctuating region, the local pairing region, and the disordered region. We show that the gradual development of phase coherence has a number of consequences on spectroscopic measurements, such as the development of the Fermi arc and the anisotropy in the angle-resolved spectra, scattering rate, entropy, specific heat, and quasiparticle dispersion, in good agreement with experimental observations. For strong coupling, our Monte Carlo simulation reveals an unexpected charge-4$e$ plaquette state with $d$-wave bonds, which competes with the uniform $d$-wave superconductivity and exhibits a U-shaped density of states

Research on structural optimization design for shield beam of hydraulic support based on response surface method

Abstract The shield beam is the main load-bearing component of the hydraulic support. The structural optimization design of one shield beam is fulfilled by the response surface method. Using the weight as the objective function, the structural optimization mathematical models of shield beam is set up. The experimental design is performed in the ANSYS software and uniform design. The maximum stresses of shield beam are gotten in the different sizes. The response surface models of design parameters and maximum stresses are fitted by the least squares method. The structural optimization design of shield beam is completed by the random direction method. This research implements the structural optimization design of hydraulic support shield beam in a modern design method, and provides a valuable guidance for the hydraulic support research and development

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Balanced Control System Based on Bidirectional Flyback DC Converter

The inconsistency of the battery pack will cause the “barrel effect“ when the battery pack is working. The battery with lower power will first reach the discharge cut-off condition, resulting in the battery pack not being fully discharged, reducing the battery utilization rate. This paper uses the state of charge (SOC) as an equilibrium variable and the forgetting factor recursive least square–extended Kalman filter (FFRLS-EKF) method to estimate the SOC. Using a balanced topology based on a bidirectional impact direct current (DC) converter, the energy transfer can occur between any battery and only between batteries that need to be balanced, increasing energy utilization and the effect of equalization. The equalization system is simulated under various conditions, which proves the effectiveness of the equalization control system

Balanced Control System Based on Bidirectional Flyback DC Converter

The inconsistency of the battery pack will cause the “barrel effect“ when the battery pack is working. The battery with lower power will first reach the discharge cut-off condition, resulting in the battery pack not being fully discharged, reducing the battery utilization rate. This paper uses the state of charge (SOC) as an equilibrium variable and the forgetting factor recursive least square–extended Kalman filter (FFRLS-EKF) method to estimate the SOC. Using a balanced topology based on a bidirectional impact direct current (DC) converter, the energy transfer can occur between any battery and only between batteries that need to be balanced, increasing energy utilization and the effect of equalization. The equalization system is simulated under various conditions, which proves the effectiveness of the equalization control system

Thermal Performance Analysis of Gradient Porosity Aluminium Foam Heat Sink for Air-Cooling Battery Thermal Management System

The three dimensional thermal model of a forced air-cooling battery thermal management system (BTMS) using aluminium foam heat sink (AFHS) is established, and the effects of porosity, pore density, and mass flow rate on the thermal and flow performance are discussed numerically from the aspects of pressure drop and temperature control effectiveness. The results reveal that an AFHS can markedly reduce the battery temperature compared with the BTMS without AFHS, but it also causes huge pressure loss and increases the temperature difference between the upstream and downstream of the battery. Reducing the porosity of aluminium foam reduces the battery’s average temperature, but increases the temperature difference. The increase of pore density leads to the increase of pressure drop, but has little effect on the battery temperature. Based on this, a study of the gradient porosity of the AFHS is carried out, and the thermal and flow performance are compared with the homogeneous AFHS. The results show that the AFHS with porosity-increasing gradient pattern (PIGP) in the direction perpendicular to flow reduces the pressure loss and improves flow performance. The AFHS with a porosity-decreasing gradient pattern (PDGP) in the flow direction has no obvious effect on the flow characteristics, but it can reduce the temperature difference of the battery. The direction of gradient porosity can be selected according to need. In addition, due to the energy absorption characteristics of aluminium foam, AFHS can improve the crashworthiness of the battery pack. Therefore, AFHS has great potential in air-cooled BTM

Thermal Performance Analysis of Gradient Porosity Aluminium Foam Heat Sink for Air-Cooling Battery Thermal Management System

The three dimensional thermal model of a forced air-cooling battery thermal management system (BTMS) using aluminium foam heat sink (AFHS) is established, and the effects of porosity, pore density, and mass flow rate on the thermal and flow performance are discussed numerically from the aspects of pressure drop and temperature control effectiveness. The results reveal that an AFHS can markedly reduce the battery temperature compared with the BTMS without AFHS, but it also causes huge pressure loss and increases the temperature difference between the upstream and downstream of the battery. Reducing the porosity of aluminium foam reduces the battery’s average temperature, but increases the temperature difference. The increase of pore density leads to the increase of pressure drop, but has little effect on the battery temperature. Based on this, a study of the gradient porosity of the AFHS is carried out, and the thermal and flow performance are compared with the homogeneous AFHS. The results show that the AFHS with porosity-increasing gradient pattern (PIGP) in the direction perpendicular to flow reduces the pressure loss and improves flow performance. The AFHS with a porosity-decreasing gradient pattern (PDGP) in the flow direction has no obvious effect on the flow characteristics, but it can reduce the temperature difference of the battery. The direction of gradient porosity can be selected according to need. In addition, due to the energy absorption characteristics of aluminium foam, AFHS can improve the crashworthiness of the battery pack. Therefore, AFHS has great potential in air-cooled BTM

NONLINEAR FREQUENCY SPECTRAL ANALYSIS OF CRACKED ROTOR BASED ON NOFRF

The nonlinear approximation model of cracked rotor,to explain the nonlinear phenomena,is constructed. The nonlinear output frequency response function（ NOFRF） and the theory of nonlinear frequency spectral analysis are illustrated.Based on this theory,the simulation analysis of cracked rotor is accomplished. The analysis provides insight into how new frequency generates. Additionally,the nonlinear phenomena of cracked rotor,including the generation of super-harmonic components and sub-resonances are explained. Experimental result shows that the higher order NOFRF is sensitive to the racked rotor with cracks of different depth. This research study establishes an important theory basis for accurate fault diagnosis of cracked rotor

Thermal Modeling and Prediction of The Lithium-ion Battery Based on Driving Behavior

Real-time monitoring of the battery thermal status is important to ensure the effectiveness of battery thermal management system (BTMS), which can effectively avoid thermal runaway. In the study of BTMS, driver behavior is one of the factors affecting the performance of the battery thermal status, and it is often neglected in battery temperature studies. Therefore, it is necessary to predict the dynamic heat generation of the battery in actual driving cycles. In this work, a thermal equivalent circuit model (TECM) and an artificial neural network (ANN) thermal model based on the driving data, which can predict the thermal behavior of the battery in real-world driving cycles, are proposed and established by MATLAB/Simulink tool. Driving behaviors analysis of different drivers are simulated by PI control as input, and battery temperature is used as output response. The results show that aggressive driving behavior leads to an increase in battery temperature of nearly 1.2 K per second, and the average prediction error of TECM model and ANN model is 0.13 K and 0.11 K, respectively. This indicates that both models can accurately estimate the real-time battery temperature. However, the computational speed of the ANN thermal model is only 0.2 s, which is more efficient for battery thermal management

Thermal Management of Fuel Cells Based on Diploid Genetic Algorithm and Fuzzy PID

The operation of a proton exchange membrane fuel cell (PEMFC) is greatly affected by temperature. Reliable thermal management of fuel cells can improve the life, efficiency, and power output of fuel cells. The model established in this paper is based on the inner layer of the fuel cell, and through the analysis of the heat change and material flow between layers, the simulink model can reflect the temperature change of the end plate, the bipolar plate, and the membrane electrode assembly (MEA) plate. In terms of the thermal management control strategy, the deviation and deviation rate between the MEA plate’s temperature and the target temperature are taken as input, and the fuzzy PID (proportional integral differential) controller is used to control the cooling water flow, to achieve a cooling effect. Due to the low efficiency and instability of a haploid genetic algorithm (GA) in solving dynamic optimization problems, a diploid genetic algorithm to optimize the membership function of the controller, and improve the adaptability of the control system, was designed. The simulation results show that compared with the haploid genetic algorithm, the optimal results of 100 iterations of the fuzzy PID control strategy reduce by 27.9%. Compared with the haploid genetic algorithm and fuzzy PID control, the MEA layer temperature, under the control of a diploid genetic algorithm, is reduced by 18% and 28%, respectively, and the minimum temperature difference of the reactor is 2.28 K