bluuebunny/crossref_metadata_2025 huggingface dataset:
Development and Validation of an Aeropropulsive and Aeroacoustic Simulation Model of a Quadcopter Drone
Authors: Fruncillo Felice , Federico Luigi , Cicala Marco , Citarella Roberto
Published: June 2022

In the present work a dynamic simulation model for a quadcopter drone is developed and validated through experimental flight data. The aerodynamics of the rotors is modeled with the blade element theory combined with the Peters and He dynamic wake model, using an appropriate number of states. The aerodynamic forces and moments thus calculated feed the dynamic equations of a drone and an aeroacoustics model, to obtain an estimate of the noise generated during the flight. Loading and thickness noise are calculated as a time domain solution of the wave equation (Farassat 1A formulation), with mobile sources in stagnant flow. The results of numerical simulations are compared with experimental data recorded during flights performed at the Aerospace Italian Research Center (CIRA), both for the flight dynamics and the aeroacoustics models. To customize the model to the drone used, a laser scanner is used to obtain the geometric characteristics of the blades and the XFOIL program is used to calculate the blade profile aerodynamic coefficients.
A Distributed Architecture for Secure Delegated Quantum Computation
Authors: Ma Shuquan , Zhu Changhua , Quan Dongxiao , Nie Min
Published: June 2022

In this paper, we propose a distributed secure delegated quantum computation protocol, by which an almost classical client can delegate a (dk)-qubit quantum circuit to d quantum servers, where each server is equipped with a 2k-qubit register that is used to process only k qubits of the delegated quantum circuit. None of servers can learn any information about the input and output of the computation. The only requirement for the client is that he or she has ability to prepare four possible qubits in the state of (|0⟩+eiθ|1⟩)/2, where θ∈{0,π/2,π,3π/2}. The only requirement for servers is that each pair of them share some entangled states (|0⟩|+⟩+|1⟩|−⟩)/2 as ancillary qubits. Instead of assuming that all servers are interconnected directly by quantum channels, we introduce a third party in our protocol that is designed to distribute the entangled states between those servers. This would simplify the quantum network because the servers do not need to share a quantum channel. In the end, we show that our protocol can guarantee unconditional security of the computation under the situation where all servers, including the third party, are honest-but-curious and allowed to cooperate with each other.
Mathematical Models for Unstable Quantum Systems and Gamow States
Authors: Gadella Manuel , Fortín Sebastián , Jorge Juan Pablo , Losada Marcelo
Published: June 2022

We review some results in the theory of non-relativistic quantum unstable systems. We account for the most important definitions of quantum resonances that we identify with unstable quantum systems. Then, we recall the properties and construction of Gamow states as vectors in some extensions of Hilbert spaces, called Rigged Hilbert Spaces. Gamow states account for the purely exponential decaying part of a resonance; the experimental exponential decay for long periods of time physically characterizes a resonance. We briefly discuss one of the most usual models for resonances: the Friedrichs model. Using an algebraic formalism for states and observables, we show that Gamow states cannot be pure states or mixtures from a standard view point. We discuss some additional properties of Gamow states, such as the possibility of obtaining mean values of certain observables on Gamow states. A modification of the time evolution law for the linear space spanned by Gamow shows that some non-commuting observables on this space become commuting for large values of time. We apply Gamow states for a possible explanation of the Loschmidt echo.
A Traffic Splitting Algorithm for Load Balancing in Tor
Authors: Meng Xiance , Liang Mangui
Published: June 2022

As the most popular anonymous communication system, Tor provides anonymous protection for users by sending their messages through a series of relays. Due to the use of the bandwidth-weighted path selection algorithm, many more users choose routers with high bandwidth as relays. This will cause the utilization of high bandwidth routers to be much higher than that of low bandwidth routers, which will bring congestion risk. The Quality of Service (QoS) is difficult to guarantee for users who need delay-sensitive services such as web browsing and instant messaging. To reduce the average load of routers and improve the network throughput, we propose a circuit construction method with multiple parallel middle relays and conduct a dynamic load allocation method. The experiment demonstrates that our proposed method can provide better load balancing. Compared with other multipath anonymous communication networks, our proposed method can provide better anonymity.
The Linear Relationship Model with LASSO for Studying Stock Networks
Authors: Chen Muzi , Tian Hongjiong , Wu Boyao , Tian Tianhai
Published: June 2022

The correlation-based network is a powerful tool to reveal the influential mechanisms and relations in stock markets. However, current methods for developing network models are dominantly based on the pairwise relationship of positive correlations. This work proposes a new approach for developing stock relationship networks by using the linear relationship model with LASSO to explore negative correlations under a systemic framework. The developed model not only preserves positive links with statistical significance but also includes link directions and negative correlations. We also introduce blends cliques with the balance theory to investigate the consistency properties of the developed networks. The ASX 200 stock data with 194 stocks are applied to evaluate the effectiveness of our proposed method. Results suggest that the developed networks not only are highly consistent with the correlation coefficient in terms of positive or negative correlations but also provide influence directions in stock markets.
A Generalized Information-Theoretic Framework for the Emergence of Hierarchical Abstractions in Resource-Limited Systems
Authors: Larsson Daniel T. , Maity Dipankar , Tsiotras Panagiotis
Published: June 2022

In this paper, a generalized information-theoretic framework for the emergence of multi-resolution hierarchical tree abstractions is developed. By leveraging ideas from information-theoretic signal encoding with side information, this paper develops a tree search problem which considers the generation of multi-resolution tree abstractions when there are multiple sources of relevant and irrelevant, or possibly confidential, information. We rigorously formulate an information-theoretic driven tree abstraction problem and discuss its connections with information-theoretic privacy and resource-limited systems. The problem structure is investigated and a novel algorithm, called G-tree search, is proposed. The proposed algorithm is analyzed and a number of theoretical results are established, including the optimally of the G-tree search algorithm. To demonstrate the utility of the proposed framework, we apply our method to a real-world example and provide a discussion of the results from the viewpoint of designing hierarchical abstractions for autonomous systems.
Effect of Ion and Binding Site on the Conformation of Chosen Glycosaminoglycans at the Albumin Surface
Authors: Sionkowski Piotr , Bełdowski Piotr , Kruszewska Natalia , Weber Piotr , Marciniak Beata , Domino Krzysztof
Published: June 2022

Albumin is one of the major components of synovial fluid. Due to its negative surface charge, it plays an essential role in many physiological processes, including the ability to form molecular complexes. In addition, glycosaminoglycans such as hyaluronic acid and chondroitin sulfate are crucial components of synovial fluid involved in the boundary lubrication regime. This study presents the influence of Na+, Mg2+ and Ca2+ ions on human serum albumin–hyaluronan/chondroitin-6-sulfate interactions examined using molecular docking followed by molecular dynamics simulations. We analyze chosen glycosaminoglycans binding by employing a conformational entropy approach. In addition, several protein–polymer complexes have been studied to check how the binding site and presence of ions influence affinity. The presence of divalent cations contributes to the decrease of conformational entropy near carboxyl and sulfate groups. This observation can indicate the higher affinity between glycosaminoglycans and albumin. Moreover, domains IIIA and IIIB of albumin have the highest affinity as those are two domains that show a positive net charge that allows for binding with negatively charged glycosaminoglycans. Finally, in discussion, we suggest some research path to find particular features that would carry information about the dynamics of the particular type of polymers or ions.
A Peer-to-Peer Smart Food Delivery Platform Based on Smart Contract
Authors: Zhang Linchao , Kim Dohyeun
Published: June 2022

The era of mobile information has arrived, and people’s lifestyles have undergone tremendous changes. Ordering takeaways through takeout apps on smartphones is one of them. However, most existing takeaway platforms charge high commissions in the middle. There are many fake reviews in restaurants, the authenticity of restaurant ratings is low, and the recommended dishes have low customer satisfaction. This paper aims to solve this problem by introducing a peer-to-peer architecture based on blockchain smart contracts. The proposed architecture leverages the automation of smart contracts to provide autonomous, commission-free food ordering and delivery services. In addition, the smart contract reward mechanism is used to collect order information and rating information, and a deep learning recommendation model is introduced to analyze the data to recommend restaurants and menus to the client accurately. To demonstrate the usability and efficiency of the proposed method, we conducted a case study using public chain-based technologies. At the same time, comprehensive evaluation experiments are carried out, and the results show the importance of the proposed food delivery system.
A Novel Machine Learning Scheme for mmWave Path Loss Modeling for 5G Communications in Dense Urban Scenarios
Authors: Jin Woobeen , Kim Hyeonjin , Lee Hyukjoon
Published: June 2022

Accurate and efficient path loss prediction in mmWave communication plays an important role in large-scale deployment of the mmWave-based 5G mobile communication systems. Existing methods often present limitations in accuracy and efficiency and fail to fulfill the requirements of cell planning, especially in dense urban environments. In this paper, we propose a novel training method called multi-way local attentive learning, which allows for learning from multiple perspectives on the same set of training samples with local attention paid to each subset of the entire dataset. The sample data set can be partitioned in various ways with respect to different attributes, such that a larger amount of knowledge can be extracted from the same data set. The proposed scheme outperforms the existing schemes in terms of prediction accuracy at the average RMSE of 6.01 dBm.
SCA-MMA: Spatial and Channel-Aware Multi-Modal Adaptation for Robust RGB-T Object Tracking
Authors: Shi Run , Wang Chaoqun , Zhao Gang , Xu Chunyan
Published: June 2022

The RGB and thermal (RGB-T) object tracking task is challenging, especially with various target changes caused by deformation, abrupt motion, background clutter and occlusion. It is critical to employ the complementary nature between visual RGB and thermal infrared data. In this work, we address the RGB-T object tracking task with a novel spatial- and channel-aware multi-modal adaptation (SCA-MMA) framework, which builds an adaptive feature learning process for better mining this object-aware information in a unified network. For each type of modality information, the spatial-aware adaptation mechanism is introduced to dynamically learn the location-based characteristics of specific tracking objects at multiple convolution layers. Further, the channel-aware multi-modal adaptation mechanism is proposed to adaptively learn the feature fusion/aggregation of different modalities. In order to perform object tracking, we employ a binary classification module with two fully connected layers to predict the bounding boxes of specific targets. Comprehensive evaluations on GTOT and RGBT234 datasets demonstrate the significant superiority of our proposed SCA-MMA for robust RGB-T object tracking tasks. In particular, the precision rate (PR) and success rate (SR) on GTOT and RGBT234 datasets can reach 90.5%/73.2% and 80.2%/56.9%, significantly higher than the state-of-the-art algorithms.
Design for Ultrahigh-Density Vertical Phase Change Memory: Proposal and Numerical Investigation
Authors: Lei Xin-Qing , Zhu Jia-He , Wang Da-Wei , Zhao Wen-Sheng
Published: June 2022

The integration level is a significant index that can be used to characterize the performance of non-volatile memory devices. This paper proposes innovative design schemes for high-density integrated phase change memory (PCM). In these schemes, diploid and four-fold memory units, which are composed of nano-strip film GST-based memory cells, are employed to replace the memory unit of a conventional vertical PCM array. As the phase transformation process of the phase change material involves the coupling of electrical and thermal processes, an in-house electrothermal coupling simulator is developed to analyze the performance of the proposed memory cells and arrays. In the simulator, a proven mathematical model is used to describe the phase change mechanism, with a finite element approach implemented for numerical calculations. The characteristics of the GST-strip-based memory cell are simulated first and compared with a conventional vertical cell, with a decrease of 32% in the reset current amplitude achieved. Next, the influences of geometric parameters on the characteristics of memory cell are investigated systematically. After this, the electrothermal characteristics of the proposed vertical PCM arrays are simulated and the results indicate that they possess both excellent performance and scalability. At last, the integration densities of the proposed design schemes are compared with the reference array, with a maximum time of 5.94 achieved.
A Vehicle–Ground Integration Information Network Scheme Based on Small Base Stations
Authors: Dong Xingzhi , Li Ping , Yu Qirui , Zhu Yuhao
Published: June 2022

The transmission bandwidth of a vehicle–ground connection is low when an EMU (electric multiple unit) is running in a high-speed scenario. To this end, this paper focuses on the need to solve the problem of the poor bandwidth of the vehicle–ground integration information network, and proposes a vehicle–ground integration information network scheme for EMUs based on small base stations. Based on the existing wi-fi system of the EMU, in order to realize the coverage of the 5G signal in the carriage, this paper—through the deployment of the technical characteristics of 5G—sinks the customized UPF (user plane function) and MEC (mobile edge computing) to the train carriage, and expands the internet channels of the train carriage. Relying on the technologies of MEC and CDN (content delivery network) for high-speed railways, network extension service products can satisfy passengers’ needs around network rate and delay. On the one hand, this can relieve the pressure of the network backhaul and save the bandwidth resources of the vehicle–ground integration information network. On the other hand, it can help operators to reduce the investment of network construction, operation, and maintenance. As a result, the proposed scheme can inspire the products that match the extended service needs of the passenger, realize the technical and innovation value of the 5G mobile network, and achieve business model innovation in high-speed mobile scenarios.
An Inverse Design Framework for Isotropic Metasurfaces Based on Representation Learning
Authors: Zhang Jian , Yuan Jin , Li Chuanzhen , Li Bin
Published: June 2022

A hybrid framework for solving the non-uniqueness problem in the inverse design of isomorphic metasurfaces is proposed. The framework consists of a representation learning (RL) module and a variational autoencoder-particle swarm optimization (VAE-PSO) algorithm module. The RL module is used to reduce the complex high-dimensional space into a low-dimensional space with obvious features, with the purpose of eliminating the many-to-one relationship between the original design space and response space. The VAE-PSO algorithm first encodes all meta-atoms into a continuous latent space through VAE and then applies PSO to search for an optimized latent vector whose corresponding metasurface fulfills the target response. This framework gives the solution paradigm of the ideal non-uniqueness situation, simplifies the complexity of the network, improves the running speed of the PSO algorithm, and obtains the global optimal solution with 94% accuracy on the test set.
Failure Analysis of a Centrifugal Compressor Impeller Made of 17-4PH Steel in the Moist Hydrogen Sulfide Environment
Authors: Łagodziński Jakub , Kozanecki Zbigniew , Tkacz Eliza
Published: June 2022

The impeller under consideration is a rotor wheel of a centrifugal compressor, made of 17-4PH martensitic precipitated hardening stainless steel. Its total operating lifetime was estimated to 80,000 h, but it fractured beforehand, 4 days after the scheduled overhaul without any observed pre-symptoms. The important causes of the failure were its working conditions: a moist H2S environment, the applied shaft fitting stress, and the martensitic structure of its material. In the article the post-failure analysis of an impeller is described, explaining the root cause of the impeller failure by means of both experimental and Finite Element Methods (FEM). Sulfide Stress Cracking (SSC) was found to be the primary failure mechanism for the impeller under investigation. Details of the investigations and possible corrective measures to improve performance impellers used under harsh environment conditions are discussed.
Centralized Multiple Back-Up Protection Scheme with Sharing Data between Adjacent Substations Based on IEC 61850
Authors: Kim Min-Soo , Kang Sang-Hee
Published: June 2022

A centralized multiple back-up protection scheme with sharing data between adjacent substations based on IEC 61850 is suggested in this paper to overcome the inherent defects of a conventional back-up protection scheme such as uncertainty of a remote end condition, especially for a distance relay, long operating time delay, and IED/CT fails. A current differential protection element, a distance-based directional protection element, local back-up, and remote back-up protection elements are applied for the multiple back-up protection scheme suggested in this paper. The phasor voltage/current data of the IMU are transferred to a CPCU. In this paper, the IMU has two functions, which are local protection IED and merging unit, as well. The CPCU performs the back-up protection functions by using the phasor voltage/current data collected from other CPCUs located at the adjacent substations. IMU/CT fails are also considered. To verify the back-up protection scheme proposed, a testbed was composed of IMUs (implemented with ADS8688 and TMDSIDK572X), grand-master-clocks (LANTIME M1000-IMS), network switches (Syn 1588 Gbit switch), RTDS, and CPCUs. A target power system was modelled with RSCAD. The results of this research can be expected to provide a practical guide to constructing the future centralized protection for a digital substation.
Self-Attention-Based Short-Term Load Forecasting Considering Demand-Side Management
Authors: Yu Fan , Wang Lei , Jiang Qiaoyong , Yan Qunmin , Qiao Shi
Published: June 2022

Accurate and rapid forecasting of short-term loads facilitates demand-side management by electricity retailers. The complexity of customer demand makes traditional forecasting methods incapable of meeting the accuracy requirements, so a self-attention based short-term load forecasting (STLF) considering demand-side management is proposed. In the data preprocessing stage, non-parametric kernel density estimation is used to construct customer electricity consumption feature curves, and then historical load data are used to delineate the feasible domain range for outlier detection. In the feature selection stage, the feature data are selected using variational modal decomposition and a maximum information coefficient to enhance the model prediction accuracy. In the model prediction stage, the decomposed intrinsic mode function components are independently predicted and reconstructed using an Informer based on improved self-attention. Additionally, the novel AdaBlief optimizer is used to optimize the model parameters. Cross-sectional and longitudinal experiments are conducted on a regional-level load dataset set in Spain. The experimental results prove that the proposed method is superior to other methods in STLF.
A Hybrid AOSAOA Scheme Based on the Optimal Location for Electric Vehicle Parking Lots and Capacitors in a Grid to Care of Voltage Profile and Power Loss
Authors: Rao Ch. S. V. Prasad , Pandian A. , Reddy Ch. Rami , Prasad A. Giri , Alahmadi Ahmad , Alharbi Yasser
Published: June 2022

In this manuscript, a hybrid system depending on the optimal location of electric vehicle parking lots (PL) and capacitors under voltage profile care and power loss is proposed. The proposed hybrid scheme is the joint execution of both the atomic orbital search (AOS) and arithmetic optimization algorithm (AOA). Commonly it is called the AOSAOA technique. In the paper, the allocation of the parking lot and capacitor is introduced to congestion management with reactive power compensation. To optimally regulate that parking lot size, the AOSAOA technique is adopted. Furthermore, parking lot and capacitor allocation are introduced to congestion management and reactive power compensation. With this proper control, the perfect sitting of capacitor and EV parking lots under the grid, including the deterioration of real and reactive power loss and voltage profiles are optimally chosen. Furthermore, the implementation of the proposed AOSAOA model is developed by the MATLAB/Simulink platform, and the efficiency of the proposed model is likened to other techniques.
High-Precision Voltage Measurement for Optical Quantum Computation
Authors: Wereszczyński Kamil , Michalczuk Agnieszka , Paszkuta Marcin , Gumiela Jacek
Published: June 2022

This paper presents a theoretical study into the use of optical systems for quantum computation. The study results pertain to quantum sampling and quantum communication and provide a basis for further research and the development of a physical implementation. We propose an optical superstructure that can implement specific computation processes and algorithms. The superstructure is composed of nonlinear optical units, such as beta barium borate crystals. The units are positioned in series, powered by a pulse laser pump, and culminate in a beam splitter that generates the output state of a number of entangled photon pairs. Computation is achieved by entanglement propagation via beam splitters and adjustable phase shifters, which set related parameters. Demonstrating a two-component case, we show how a series of cosine-based components can be implemented. The obtained results open a broad front for future research. Future work should investigate the construction of a quantum optimizer using quantum sampling methods and also investigate high-precision temporal voltage measurement, which is a key procedure for the construction of high-fidelity devices.
Modulation and Control Strategy of 3CH4 Combined Current Source Grid-Connected Inverter
Authors: Li Pengcheng , Huo Liming , Guo Yingjun , An Guoqing , Guo Xiaoqiang , Li Zheng , Sun Hexu
Published: June 2022

In this article, a topology based on the single-phase full-bridge is proposed to decouple control of phase current in current source grid-connected inverters. The DC side of this current source inverter topology can operate with a common DC bus or independently, and the AC side can be independently integrated into the three-phase grid or operate in parallel. This topology needs only a simple control logic and phase information to achieve 3-phase current decoupling control, which can accommodate a wide range of voltage fluctuations. Then, dual-carrier driving and hybrid damping correction strategies are designed to achieve flexible combinatorial operation and eliminate the common-mode voltage. Meanwhile, the method is simple and easy to implement in practice. The effectiveness of the proposed algorithm is validated with experiments.
Price Responsiveness of Residential Demand for Natural Gas in the United States
Authors: Li Raymond , Woo Chi-Keung , Tishler Asher , Zarnikau Jay
Published: June 2022

While price responsiveness of residential demand for natural gas has important implications on resource planning and energy modelling, its estimates from prior studies are very diverse. Applying panel data analysis and five parametric specifications to monthly data for the lower 48 states in 1990–2019, we estimate own-price elasticities of residential demand for natural gas in the United States (US). Using results from cross-section dependence (CD) test, panel unit root tests, panel time-series estimators, and rolling-window analysis, we document: (1) the statistically significant (p-value ≤ 0.05) static own-price elasticity estimates are −0.271 to −0.486, short-run −0.238 to −0.555 and long-run −0.323 to −0.796; (2) these estimates vary by elasticity type, sample period, parametric specification, treatment of CD and assumption of partial adjustment; (3) erroneously ignoring the highly significant (p-value < 0.01) CD shrinks the size of these estimates that vary seasonally, regionally, and nonlinearly over time; and (4) residential natural gas shortage costs decline with the size of own-price elasticity estimates. These findings suggest that achieving deep decarbonization may require strategies that do not rely solely on prices, such as energy efficiency standards and demand-side-management programs. Demand response programs may prove useful for managing natural gas shortages.
An Efficient Framework to Estimate the State of Charge Profiles of Hydro Units for Large-Scale Zonal and Nodal Pricing Models
Authors: Jansen Luca Lena , Thomaßen Georg , Antonopoulos Georgios , Buzna Ľuboš
Published: June 2022

The power system is undergoing significant changes so as to accommodate an increasing amount of renewably generated electricity. In order to facilitate these changes, a shift from the currently employed zonal pricing to nodal pricing is a topic that is receiving increasing interest. To explore alternative pricing mechanisms for the European electricity market, one needs to solve large-scale nodal optimization problems. These are computationally intensive to solve, and a parallelization or sequencing of the models can become necessary. The seasonality of hydro inflows and the issue of myopic foresight that does not display the value in storing water today and utilizing it in the future is a known problem in power system modeling. This work proposes a heuristic step-wise methodology to obtain state of charge profiles for hydro storage units for large-scale nodal and zonal models. Profiles obtained from solving an aggregated model serve as guidance for a nodal model with high spatial and temporal resolution that is solved in sequences. The sequenced problem is guided through soft constraints that are enforced with different sets of penalty factors. The proposed methodology allows for adjustments to congestions on short timescales and proves to perform well in comparison to other approaches to this issue suggested in the literature. Following the input profile closely on a long timescale renders good results for the nodal model.
Physical Properties of Ti45Zr38Fe17 Alloy and Its Amorphous Hydride
Authors: Żywczak Antoni , Gondek Łukasz , Czub Joanna , Janusz Piotr , Selvaraj Nivas Babu , Takasaki Akito
Published: June 2022

The alloys based on Ti-Zr are considered an excellent candidate for hydrogen storage applications. In this communication, we report the results of Fe substitution for Ni in the well-known Ti45Zr38Ni17 compound. The parent and related compounds can be obtained as amorphous powders, transforming into the quasicrystalline phase (i-phase) after annealing. The amorphous Ti45Zr38Fe17 phase is transformed into the icosahedral quasicrystalline state, and it is a quasi-continuous process. The i-phase is well-developed close to 500 °C. At higher temperatures, the quasicrystal structure transforms into the other phase: the w-phase (an approximant to the crystalline phase) and another crystal phase with a small addition of the FeZr3 and the Fe2(ZrTi)3. The amorphous Ti45Zr38Fe17 phases can be hydrogenated while maintaining the amorphous nature, which constitutes another very fascinating research field for our group. The investigated alloy shows a good capacity for gaseous H2 at level 2.54 wt.% at elevated temperatures. The ferromagnetic signal of the amorphous TiZrFe comes from magnetic nanocrystallites in the amorphous matrix. After heating, the magnetic signal significantly decreases due to the lack of long-range magnetic ordering in the i-phase of the Ti45Zr38Fe17 alloy.
Reduction of the Electromagnetic Torque Oscillation during the Direct on Line (DOL) Starting of a 6 kV Motor by Means of a Controlled Vacuum Circuit-Breaker
Authors: Kłosowski Zbigniew , Fajfer Maciej , Ludwikowski Zbigniew
Published: June 2022

This article deals with the issue of the reduction of the oscillation of electromagnetic torque in the case of a direct on line (DOL) starting of a 6 kV induction motor. Such engines are used in drive systems where frequent starting may be required. Direct starting in such systems may reduce the mechanical and thermal durability. Therefore, the article presents a method of DOL starting of a 6 kV induction motor with the use of vacuum circuit-breakers and appropriate switching of the voltages supplying the electric machine. To confirm the advantages of the proposed solution, computer simulation and experimental tests were carried out, which are presented and discussed in the article. The obtained results confirm the advantages of the proposed solution, compared to the classic starting known from the literature.
Analysis of the Dynamic Characteristics of the Pump Valve System of an Ultra-High Pressure Liquid Hydrogen Reciprocating Pump
Authors: Qiu Nanbin , Shang Xianwei , Liu Ruimin , Jin Ping , Gao Wanli
Published: June 2022

This paper developed a 3D physical model of the hydraulic end of a high-pressure liquid hydrogen reciprocating pump to research the dynamic characteristics of the pump valve system. Based on dynamic mesh technology, we analyzed the coupling characteristics of pump valve and plunger motion and spool force considering the leakage model, closure model of valve gap, and compressibility of liquid hydrogen. Further, we analyzed the effect of the spring stiffness and preload force on the laws of motion of the pump valve. Finally, a liquid hydrogen pressurization test was conducted to revise the simulation model and verify the accuracy of the simulation. The results of the simulation and test show that the simulation method in this paper can simulate the liquid hydrogen pressurization process more accurately and obtain the motion law of the suction and discharge valves. Both the suction and discharge valves have an opening hysteresis angle of about 40°, and there is a strong coupling relationship between the spool motion and the piston motion and forces. The greater the preload force of the suction valve, the more obvious the oscillation effect of the suction valve. As the preload of the discharge valve increases, the opening hysteresis angle of the discharge valve increases significantly and the closing hysteresis angle decreases. The results of the research can provide some useful reference for the design of pump valves of high-pressure liquid hydrogen reciprocating pumps.
Influence of Densification on the Pyrolytic Behavior of Agricultural Biomass Waste and the Characteristics of Pyrolysis Products
Authors: Bielecki Marcin , Zubkova Valentina , Strojwas Andrzej
Published: June 2022

TG/FT-IR techniques, UV-spectroscopy, microwave extraction, XRD and SEM were used to study how densification of the three types of agricultural biomass wastes (wheat straw, soft wood, and sunflower husk) changes the composition and structure of their pyrolysis products. It was determined that densification changes the composition of volatile products of pyrolysis at the temperature of 420 °C: sunflower husk emits 4.9 times less saturated and unsaturated hydrocarbons and 1.9 times less compounds with carbonyl group; soft wood emits 1.8 times more saturated and unsaturated hydrocarbons and compounds with carbonyl groups and 1.3 times more alcohols and phenols; and wheat straw emits 2 times more compounds with carbonyl groups. These changes are probably caused by the differences in interaction of formed volatiles with the surface of chars. These differences can be caused by distinct places of cumulation of inorganic components in the densified samples. In the densified char, the inorganics cumulate on the surface of sunflower husk whereas for wheat straw they cumulate inside the sample. In the case of soft wood, the inorganics cumulate both inside and on the surface. The decreased contribution of hydrocarbons in volatiles can be connected with the morphology of nano-particles formed in inorganics.
Effect of Temperature Change on Acoustic Emission Signal in IGBT Transistors of Marine Propulsion System Converters
Authors: Gordon Radosław , Bejger Artur
Published: June 2022

The article presents the results of tests related to failure analysis and finding ways to diagnose used semiconductor elements, among others, in power electronics converter systems on vessels and offshore facilities (drilling and production rigs and wind turbines). Diagnostic relationships were found between the temperature change in the above systems and the signals generated in the form of elastic waves of acoustic emission. The authors confirmed the influence of the transistor’s working temperature on its amplitude-frequency spectrum of acoustic emission signals emitted. The range of ‘safe temperatures’ was considered which means temperatures that do not directly affect the damage of the component.
Divergent Tree Growth and the Response to Climate Warming and Humidification in the Tianshan Mountains, China
Authors: Peng Zhongtong , Zhang Yuandong , Zhu Liangjun , Lu Qingao , Mo Qifeng , Cai Jiaqing , Guo Mingming
Published: June 2022

In recent decades, the global climate has changed significantly. The climate in Northwest China became warm-wet, especially in the Tianshan Mountains. In order to explore the response of tree growth to recent climate change, the two dominant trees species, Picea schrenkiana Fisch. et Mey. and Larix sibirica Ledeb., were studied with the dendrochronological method in the western Tianshan Mountains (WT) and the eastern Tianshan Mountains (ET). Our results showed that: (1) The tree growth of four sample sites in the WT significantly increased in recent decades, while the trees in the three sample sites in the ET significantly decreased. (2) In the WT, except for the Manas site, the tree-ring chronologies of the other three sites were significantly positively correlated with the mean annual minimum temperature. Tree-ring chronologies in the WT, except for Bangfanggou site, were significantly positively correlated with annual precipitation. In the ET, only the tree chronology of L. sibirica in the Balikun site was significantly negatively correlated with the annual temperatures, including the mean minimum, mean and mean maximum temperature. (3) The proportion of trees with a significant upward growth trend at each site decreased from west to east, and the proportion of trees with a significant downward growth trend at each site increased from west to east along the whole Tianshan Mountains. (4) The correlation of tree-ring chronologies with the annual temperature and annual precipitation was not stable during the study period. Warm-humidification promoted the growth of trees in the WT but inhibited tree growth in the ET, which may be exacerbated drought stress in the ET where the increase in precipitation was not enough to offset the increased evapotranspiration potential caused by warming.
Mapping the Long-Term Evolution of the Post-Event Deformation of the Guang’an Village Landslide, Chongqing, China Using Multibaseline InSAR Techniques
Authors: Zhang Kui , Gong Faming , Li Li , Ng Alex Hay-Man , Liu Pengfei
Published: June 2022

On 21 October 2017, days of heavy rainfall triggered a landslide in Guang’an Village, Wuxi County, Chongqing, China. According to the field investigation after the incident, there is still a massive accumulation body, which could possibly reactivate the landslide. In this study, to explore the long-term evolution of the deformation after the initial Guang’an Village Landslide, a time-series InSAR technique (TS-InSAR) was applied to the 128 ascending Sentinel-1A datasets spanning from October 2017 to March 2022. A new approach is proposed to enhance the conventional TS-InSAR method by integrating LiDAR data into the TS-InSAR process chain. The spatial–temporal evolution of post-event deformation over the Guang’an Village Landslide is analyzed based on the time-series results. It is found that the post-event deformation can be divided into three main stages: the post-failure stage, the post-failure and reactivation stage, and the reactivation stage. It is also suggested that, although the study area is currently under the reactivation stage, there are two active deformation zones that may become the origin of a secondary landslide triggered by heavy rainfall in the future. Moreover, the nearby Yaodunzi landslide might also play an important role in the generation and reactivation of a secondary Guang’an Village Landslide. Therefore, continuous monitoring for post-event deformation of the Guang’an Village Landslide is important for early warning of a secondary landslide in the near future.
Spatial Structure Dynamics and Maintenance of a Natural Mixed Forest
Authors: Zhou Chaofan , Liu Di , Chen Keyi , Hu Xuefan , Lei Xiangdong , Feng Linyan , Zhang Yuchao , Zhang Huiru
Published: June 2022

Spatial structure dynamics play a major role in understanding the mechanisms of forest structure and biodiversity formation. Recently, researches on the spatial structure dynamics utilizing multi-period data have been published. However, these studies only focused on comparative analyses of the spatial structure of multi-period living trees, without an in-depth analysis of the change processes. In this study, we propose a new comprehensive analysis method for dynamic change of the spatial structure at the individual level, which includes three processes (living trees’ flow, mortality process and recruitment process) that have not been considered in previous researches. Four spatial structural parameters (SSSPs, Uniform angle index, Mingling, Dominance and Crowding) and a natural spruce-fir-broadleaf mixed forest with two-phase data were taken as an example to find out the laws of the spatial structure dynamics. All types of dynamic change were named and their proportions were analyzed. The proportion of changes in the SSSPs of individuals was relatively high, even though the mean values of the stand did not change considerably. The five values (0, 0.25, 0.5, 0.75, 1) of the SSSPs are in mutual flow, and the flows are typically one-step, with three-steps and four-steps changes being uncommon. The processes of mortality and recruitment have a higher influence on the spatial structure than the flow of living trees. The dynamic change of spatial structure analysis method created in this study can capture more features not discovered in earlier approaches, as well as guiding forest management in some ways. Understanding the nuances of these changes is a critical part of reasonable spatial structure and biodiversity maintenance, and should be the focus of future research efforts.
Analysis of Forest Landscape Preferences and Emotional Features of Chinese Forest Recreationists Based on Deep Learning of Geotagged Photos
Authors: Zeng Xitong , Zhong Yongde , Yang Lingfan , Wei Juan , Tang Xianglong
Published: June 2022

Forest landscape preference studies have an important role and significance for forest landscape conservation, quality improvement and utilization. However, there are few studies on objective forest landscape preferences from the perspective of plants and using photos. This study relies on Deep Learning technology to select six case sites in China and uses geotagged photos of forest landscapes posted by the forest recreationists on the “2BULU” app as research objects. The preferences of eight forest landscape scenes, including look down landscape, look forward landscape, look up landscape, single-tree-composed landscape, detailed landscape, overall landscape, forest trail landscape and intra-forest landscape, were explored. It also uses Deepsentibank to perform sentiment analysis on forest landscape photos to better understand Chinese forest recreationists’ forest landscape preferences. The research results show that: (1) From the aesthetic spatial angle, people prefer the flat view, while the attention of the elevated view is relatively low. (2) From the perspective of forest scale and level, forest trail landscape has a high preference, implying that trail landscape plays an important role in forest landscape recreation. The landscape within the forest has a certain preference, while the preference of individual, detailed and overall landscape is low. (3) Although forest landscape photographs are extremely high in positive emotions and emotional states, there are also negative emotions, thus, illustrating that people’s preferences can be both positive and negative.
A Study on the Vulnerability of the Gross Primary Production of Rubber Plantations to Regional Short-Term Flash Drought over Hainan Island
Authors: Cui Wei , Xiong Qian , Zheng Yinqi , Zhao Junfu , Nie Tangzhe , Wu Lan , Sun Zhongyi
Published: June 2022

Rapidly developing droughts, including flash droughts, have occurred frequently in recent years, causing significant damage to agroforestry ecosystems, and they are expected to increase in the future due to global warming. The artificial forest area in China is the largest in the world, and its carbon budget is crucial to the global carbon sink. As the most prominent plantation plant in the tropics, the rubber (Hevea brasiliensis (Willd. ex A. Juss.) Muell. Arg.) ecosystem not only has important economic significance, but also has the potential to be a major natural carbon sink in hot areas. Frequent drought events have a significant impact on rubber ecosystem productivity, yet there have been few reports on the vulnerability of rubber productivity to drought. The objective of this study is to evaluate the vulnerability of rubber ecosystem gross primary production (GPP) to short-term flash drought (STFD) in Hainan Island, utilizing the localized EC-LUE model (eddy covariance–light use efficiency) validated by flux tower observations as the research tool to conduct the scenario simulations which defined by standard relative humidity index (SRHI), in a total of 96 scenarios (timing × intensity). The results show that, in terms of time, the rubber ecosystem in Hainan Island has the highest vulnerability to STFD during the early rainy season and the lowest at the end of the rainy season. From the dry season to the rainy season, the impact of STFD gradually extends to the northeast. Spatially, the vulnerability of the northern island is higher than that of the southern island and that of the western part is higher than that of eastern Hainan Island. With the increase in STFD intensity, the spatial distribution center of the vulnerability of rubber ecosystem GPP in Hainan Island gradually moves southward. The spatiotemporal pattern of the vulnerability of the rubber ecosystem GPP to STFD over Hainan Island plotted by this study is expected to provide decision makers with more accurate information on the prevention and control of drought disaster risk in rubber ecosystems.
Phylogenetic and Functional Structure of Wood Communities among Different Disturbance Regimes in a Temperate Mountain Forest
Authors: Li Peikun , Geng Zihan , Wang Xueying , Zhang Panpan , Zhang Jian , Ding Shengyan , Fu Qiang
Published: June 2022

The mechanisms responsible for biodiversity formation and maintenance are central themes in biodiversity conservation. However, the relationships between community assembly, phylogeny, and functional traits remain poorly understood, especially following disturbance. In this study, we examined forest community assembly mechanisms in different disturbance regimes across spatial scales and including tree life history classes, using phylogenetic and functional trait metrics. Across disturbance regimes, phylogenetic structure tended to be over-dispersed, while functional structure tended to be clustered. The over-dispersion of phylogenetic structure also increased from small to large diameter species. Moreover, the explanation of spatial distance for the turnover of phylogenetic and functional structure was increased, while environmental distance explained less structure as disturbance intensity decreased. Our findings suggest that niche theory largely explains forest community assembly in different disturbance regimes. Furthermore, environmental filtering plays a major role in moderate to high disturbance regimes, while competitive exclusion is more important in undisturbed and slightly disturbed ecosystems.
Study on the Shear Strength of Root-Soil Composite and Root Reinforcement Mechanism
Authors: Li Pengcheng , Xiao Xuepei , Wu Lizhou , Li Xu , Zhang Hong , Zhou Jianting
Published: June 2022

This study investigates the effects of root distributions and stress paths on the shear strength of root-soil composites using a consolidated-undrained (CU) triaxial test. On the basis of the limit equilibrium, two root reinforcement coefficients (n and m) are proposed for characterizing the effects of shear strength parameters on the principal stress considering different root distribution angles and root diameters. Then, n and m are introduced into the conventional limit equilibrium equation to develop a new limit equilibrium equation for root-soil composites. The results demonstrate that the root distribution angles (α) and root diameters (d) affect the shear strength of the root-soil composites. Under a consolidated-undrained condition, the effective cohesion (crs′) of the rooted soil is high and decreases in the order of 90°, 0°, 30° and 60°. For the same root distribution angle, crs′ increases with the increasing root diameter. Meanwhile, the effective internal friction angle (φrs′) changes slightly. The failure principal stress of the root-soil composites is positively correlated with n and m. Furthermore, the deformation of the samples indicates that the run-through rate of α = 90° and α = 0° are both 0. Meanwhile, the lateral deformation rate declines from 17.0% for α = 60° to 10.9% for α = 90°.