bluuebunny/crossref_metadata_2025 huggingface dataset:
Physlr: Next-Generation Physical Maps
Authors: Afshinfard Amirhossein , Jackman Shaun D. , Wong Johnathan , Coombe Lauren , Chu Justin , Nikolic Vladimir , Dilek Gokce , Malkoç Yaman , Warren René L. , Birol Inanc
Published: June 2022

While conventional physical maps helped build most of the reference genomes we use today, generating the maps was prohibitively expensive, and the technology was abandoned in favor of whole-genome shotgun sequencing (WGS). However, genome assemblies generated using WGS data are often less contiguous. We introduce Physlr, a tool that leverages long-range information provided by some WGS technologies to construct next-generation physical maps. These maps have many potential applications in genome assembly and analysis, including, but not limited to, scaffolding. In this study, using experimental linked-read datasets from two humans, we used Physlr to construct chromosome-scale physical maps (NGA50s of 52 Mbp and 70 Mbp). We also demonstrated how these physical maps can help scaffold human genome assemblies generated using various sequencing technologies and assembly tools. Across all experiments, Physlr substantially improved the contiguity of baseline assemblies over state-of-the-art linked-read scaffolders.
Generative Adversarial Network of Industrial Positron Images on Memory Module
Authors: Zhu Mingwei , Zhao Min , Yao Min , Guo Ruipeng
Published: June 2022

PET (Positron Emission Computed Tomography) imaging is a challenge due to the ill-posed nature and the low data of photo response lines. Generative adversarial networks have been widely used in computer vision and made great success recently. In our paper, we trained an adversarial model to improve the industrial positron images quality based on the attention mechanism. The innovation of the proposed method is that we build a memory module that focuses on the contribution of feature details to interested parts of images. We use an encoder to get the hidden vectors from a basic dataset as the prior knowledge and train the nets jointly. We evaluate the quality of the simulation positron images by MS-SSIM and PSNR. At the same time, the real industrial positron images also show a good visual effect.
Particle Swarm Optimization-Based Approach for Optic Disc Segmentation
Authors: Yi Junyan , Ran Ya , Yang Gang
Published: June 2022

Fundus segmentation is an important step in the diagnosis of ophthalmic diseases, especially glaucoma. A modified particle swarm optimization algorithm for optic disc segmentation is proposed, considering the fact that the current public fundus datasets do not have enough images and are unevenly distributed. The particle swarm optimization algorithm has been proved to be a good tool to deal with various extreme value problems, which requires little data and does not require pre-training. In this paper, the segmentation problem is converted to a set of extreme value problems. The scheme performs data preprocessing based on the features of the fundus map, reduces noise on the picture, and simplifies the search space for particles. The search space is divided into multiple sub-search spaces according to the number of subgroups, and the particles inside the subgroups search for the optimal solution in their respective sub-search spaces. The gradient values are used to calculate the fitness of particles and contours. The entire group is divided into some subgroups. Every particle flies in their exploration for the best solution. During the iteration, particles are not only influenced by local and global optimal solutions but also additionally attracted by particles between adjacent subgroups. By collaboration and information sharing, the particles are capable of obtaining accurate disc segmentation. This method has been tested with the Drishti-GS and RIM-ONE V3 dataset. Compared to several state-of-the-art methods, the proposed method substantially improves the optic disc segmentation results on the tested datasets, which demonstrates the superiority of the proposed work.
Gamow Temperature in Tsallis and Kaniadakis Statistics
Authors: Moradpour Hooman , Javaherian Mohsen , Namvar Ebrahim , Ziaie Amir Hadi
Published: June 2022

Relying on the quantum tunnelling concept and Maxwell–Boltzmann–Gibbs statistics, Gamow shows that the star-burning process happens at temperatures comparable to a critical value, called the Gamow temperature (T) and less than the prediction of the classical framework. In order to highlight the role of the equipartition theorem in the Gamow argument, a thermal length scale is defined, and then the effects of non-extensivity on the Gamow temperature have been investigated by focusing on the Tsallis and Kaniadakis statistics. The results attest that while the Gamow temperature decreases in the framework of Kaniadakis statistics, it can be bigger or smaller than T when Tsallis statistics are employed.
A Hybrid Deep Learning Model for Brain Tumour Classification
Authors: Rasool Mohammed , Ismail Nor Azman , Boulila Wadii , Ammar Adel , Samma Hussein , Yafooz Wael M. S. , Emara Abdel-Hamid M.
Published: June 2022

A brain tumour is one of the major reasons for death in humans, and it is the tenth most common type of tumour that affects people of all ages. However, if detected early, it is one of the most treatable types of tumours. Brain tumours are classified using biopsy, which is not usually performed before definitive brain surgery. An image classification technique for tumour diseases is important for accelerating the treatment process and avoiding surgery and errors from manual diagnosis by radiologists. The advancement of technology and machine learning (ML) can assist radiologists in tumour diagnostics using magnetic resonance imaging (MRI) images without invasive procedures. This work introduced a new hybrid CNN-based architecture to classify three brain tumour types through MRI images. The method suggested in this paper uses hybrid deep learning classification based on CNN with two methods. The first method combines a pre-trained Google-Net model of the CNN algorithm for feature extraction with SVM for pattern classification. The second method integrates a finely tuned Google-Net with a soft-max classifier. The proposed approach was evaluated using MRI brain images that contain a total of 1426 glioma images, 708 meningioma images, 930 pituitary tumour images, and 396 normal brain images. The reported results showed that an accuracy of 93.1% was achieved from the finely tuned Google-Net model. However, the synergy of Google-Net as a feature extractor with an SVM classifier improved recognition accuracy to 98.1%.
F-Wave Extraction from Single-Lead Electrocardiogram Signals with Atrial Fibrillation by Utilizing an Optimized Resonance-Based Signal Decomposition Method
Authors: Zhu Junjiang , Lv Jintao , Kong Dongdong
Published: June 2022

(1) Background: A typical cardiac cycle consists of a P-wave, a QRS complex, and a T-wave, and these waves are perfectly shown in electrocardiogram signals (ECG). When atrial fibrillation (AF) occurs, P-waves disappear, and F-waves emerge. F-waves contain information on the cause of atrial fibrillation. Therefore it is essential to extract F-waves from the ECG signal. However, F-waves overlap the QRS complex and T-waves in both the time and frequency domain, causing this matter to be a difficult one. (2) Methods: This paper presents an optimized resonance-based signal decomposition method for detecting F-waves in single-lead ECG signals with atrial fibrillation (AF). It represents the ECG signal utilizing morphological component analysis as a linear combination of a finite number of components selected from the high-resonance and low-resonance dictionaries, respectively. The linear combination of components in the low-resonance dictionary reconstructs the oscillatory part (F-wave) of the ECG signal. In contrast, the linear combination of components in the high-resonance dictionary reconstructs the transient components part (QRST wave). The tunable Q-factor wavelet transform generates the high and low resonance dictionaries, with a high Q-factor producing a high resonance dictionary and a low Q-factor producing a low resonance dictionary. The different Q-factor settings affect the dictionaries’ characteristics, hence the F-wave extraction. A genetic algorithm was used to optimize the Q-factor selection to select the optimal Q-factor. (3) Results: The presented method helps reduce RMSE between the extracted and the simulated F-waves compared to average beat subtraction (ABS) and principal component analysis (PCA). According to the amplitude of the F-wave, RMSE is reduced by 0.24–0.32. Moreover, the dominant frequency of F-waves extracted by the presented method is clearer and more resistant to interference. The presented method outperforms the other two methods, ABS and PCA, in F-wave extraction from AF-ECG signals with the ventricular premature heartbeat. (4) Conclusion: The proposed method can potentially improve the accuracy of F-wave extraction for mobile ECG monitoring equipment, especially those with fewer leads.
Hybrid Power Management Strategy with Fuel Cell, Battery, and Supercapacitor for Fuel Economy in Hybrid Electric Vehicle Application
Authors: Mounica V. , Obulesu Y. P.
Published: June 2022

The power management strategy (PMS) is intimately linked to the fuel economy in the hybrid electric vehicle (HEV). In this paper, a hybrid power management scheme is proposed; it consists of an adaptive neuro-fuzzy inference method (ANFIS) and the equivalent consumption minimization technique (ECMS). Artificial intelligence (AI) is a key development for managing power among various energy sources. The hybrid power supply is an eco-acceptable system that includes a proton exchange membrane fuel cell (PEMFC) as a primary source and a battery bank and ultracapacitor as electric storage systems. The Haar wavelet transform method is used to calculate the stress σ on each energy source. The proposed model is developed in MATLAB/Simulink software. The simulation results show that the proposed scheme meets the power demand of a typical driving cycle, i.e., Highway Fuel Economy Test Cycle (HWFET) and Worldwide Harmonized Light Vehicles Test Procedures (WLTP—Class 3), for testing the vehicle performance, and assessment has been carried out for various PMS based on the consumption of hydrogen, overall efficiency, state of charge of ultracapacitors and batteries, stress on hybrid sources and stability of the DC bus. By combining ANFIS and ECMS, the consumption of hydrogen is minimized by 8.7% compared to the proportional integral (PI), state machine control (SMC), frequency decoupling fuzzy logic control (FDFLC), equivalent consumption minimization strategy (ECMS) and external energy minimization strategy (EEMS).
Prospects of Using Gas Hydrates in Power Plants
Authors: Antonov Dmitrii , Gaidukova Olga , Nyashina Galina , Razumov Dmitrii , Strizhak Pavel
Published: June 2022

By adding water to fuels, several objectives are pursued, with the main ones being to stabilize combustion, minimize the anthropogenic gaseous emissions, homogenize and stabilize the fuel, as well as improve its fire and explosion safety. Water can be injected into the furnace as droplets or vapor and introduced as part of fuel samples. Water often serves as a coupling or carrier medium for the delivery of the main fuel components. In this paper, we compare the combustion behaviors of high-potential slurry fuels and gas hydrates. We also analyze the contribution of in slurries and gas hydrates to the combustion process. The values of relative combustion efficiency indicators are determined for gas hydrates and slurry fuels. The conditions are identified in which these fuels can be burned effectively in power plants. The research findings can be used to rationalize the alternative ways of using water resources, i.e., gas hydrate powder and promising composite fuel droplets. The results can also help predict the conditions for the shortest possible ignition delay, as well as effective combustion of gas hydrates as the most environmentally friendly new-generation alternative fuel.
Transcritical Behavior of Methane in the Cooling Jacket of a Liquid-Oxygen/Liquid-Methane Rocket-Engine Demonstrator
Authors: Ricci Daniele , Battista Francesco , Fragiacomo Manrico
Published: June 2022

The successful design of a liquid rocket engine is strictly linked to the development of efficient cooling systems, able to dissipate huge thermal loads coming from the combustion in the thrust chamber. Generally, cooling architectures are based on regenerative strategies, adopting fuels as coolants; and on cooling jackets, including several narrow axial channels allocated around the thrust chambers. Moreover, since cryogenic fuels are used, as in the case of oxygen/methane-based liquid rocket engines, the refrigerant is injected in liquid phase at supercritical pressure conditions and heated by the thermal load coming from the combustion chamber, which tends to experience transcritical conditions until behaving as a supercritical vapor before exiting the cooling jacket. The comprehension of fluid behavior inside the cooling jackets of liquid-oxygen/methane rocket engines as a function of different operative conditions represents not only a current topic but a critical issue for the development of future propulsion systems. Hence, the current manuscript discusses the results concerning the cooling jacket equipping the liquid-oxygen/liquid-methane demonstrator, designed and manufactured within the scope of HYPROB-NEW Italian Project. In particular, numerical results considering the nominal operating conditions and the influence of variables, such as the inlet temperature and pressure values of refrigerant as well as mass-flow rate, are shown to discuss the fluid transcritical behavior inside the cooling channels and give indications on the numerical methodologies, supporting the design of liquid-oxygen/liquid-methane rocket-engine cooling systems. Validation has been accomplished by means of experimental results obtained through a specific test article, provided with a cooling channel, characterized by dimensions representative of HYPROB DEMO-0A regenerative combustion chamber.
Heat Control Effect of Phase Change Microcapsules upon Cement Slurry Applied to Hydrate-Bearing Sediment
Authors: Yang Guokun , Liu Tianle , Zhu Hai , Zhang Zihan , Feng Yingtao , Leusheva Ekaterina , Morenov Valentin
Published: June 2022

This study aims to develop a novel low-heat cement slurry using phase change microcapsule additives to reduce the decomposition of hydrate-bearing sediments during cementing. Microcapsules were prepared by coating mixed alkanes with polymethyl methacrylate, and lipophilic-modified graphite was incorporated to enhance the thermal conductivity of microcapsules. The effects of microcapsules upon the hydration heat, pore distribution, and compressive strength of the cement slurry/stone were studied through a variety of tests. The results showed that the phase-change temperature, thermal enthalpy, and encapsulation efficiency of the microcapsules were 8.99–16.74 °C, 153.58 Jg−1, and 47.2%, respectively. The introduction of lipophilic-modified graphite reduced the initial phase-change temperature of microcapsules by 0.49 °C, indicating an improvement in their temperature sensitivity. The maximum hydration heat of cement slurry decreased by 41.3% with 7% dosage of microcapsules; the proposed microcapsules outperformed comparable low-heat additives. Moreover, the presence of microcapsules could reduce the number of large pores in (and thereby improve the compressive strength of) cement stone. The innovation of this study is that it comprehensively and intuitively confirms the feasibility of the application of low-heat cement slurry with MPCM as the key in hydrate sediments rather than just focusing on the reduction of hydration heat; furthermore, a self-made cementing device was developed to simulate the cementing process of hydrate deposition. The results show that the thermal regulation of microcapsules inhibited the temperature increase rate of the cement slurry, significantly reducing the damage caused to the hydrate. These findings should improve the safety and quality of cement in offshore oil and gas well applications.
Non-Iterative Technique for Determination of Full Lightning Impulse Voltage Parameters
Authors: Yutthagowith Peerawut
Published: June 2022

This paper introduces an effective and non-iterative technique for the determination of full lightning impulse voltage parameters in high-voltage tests. In the waveform parameter determination, the base curve parameters are determined on the basis of precomputed models that are utilized to correct the base curve parameters. Using the data from the cases collected from the standard, the correction factors are computed from the deviation of the parameters which are determined by the proposed and standard recommended method. With the accurate base curve parameters, the waveform parameters can be calculated precisely. Because there is no iterative process in the technique, the proposed method has a simplified computational algorithm and becomes an attractive method.
Numerical Study of the Thermal and Fluid Behavior of Three-Dimensional Microstructures for Efficient Catalytic Converters
Authors: Jeong Gwang , Kim Seok , Cho Young
Published: June 2022

Global regulations for emission reduction are continually becoming stricter, and conventional catalytic converters may be efficient in the future because of their low conversion efficiencies at cold-start. In this study, to overcome the performance limitations of conventional catalytic converters, a three-dimensional (3D) microstructured catalytic substrate was designed, and simulations of the fluid flow, heat transfer, and chemical reaction for the proposed catalytic substrates were performed using computational fluid dynamics (CFD) analysis. The effect of the pressure drop on the catalytic conversion efficiency of various 3D microarchitectures was investigated. Due to the three-dimensional microstructure, the fluid flow changed and fluid pressure increased, which led to energy loss. It was confirmed that the abrupt change in flow increased the heat transfer. The findings showed that the fluid flow changed due to the existence of a complex periodic microlattice structure instead of the existing monolithic structure, which promoted the conversion of harmful substances. Based on the CFD analysis of the thermal and fluid properties, it was confirmed that 3D microarchitectures can provide alternatives to conventional catalytic supports structures for efficient catalytic converters.
Reduction of Power Consumption and CO2 Emissions as a Result of Putting into Service High-Speed Trains: Polish Case
Authors: Pomykala Agata , Szelag Adam
Published: June 2022

This article presents the results of analyses of energy efficiency and environmental outcomes of putting into operation high-speed trains—first of that kind in Poland—in 2014 on upgraded 3 kV DC lines. Comparative analyses of these trains in Poland have not been carried out so far and provide a new approach to assessing the feasibility of their adoption and, in a broader context, the advisability of replacing conventional with high-speed rail transport. The analysis supports the advantages of high-speed railway (HSR) and the need to develop a network of high-speed connections using energy-efficient trains in Poland. Putting these trains into service reduced CO2 emissions, which is significant in Poland as a country relying heavily on power generated in coal power plants and complies with the assumptions of the sustainable development policies and EU Green Deal. The outcomes of our analysis can be used for transportation planning to mitigate climate change and the presented approach provides a method of quantification of environmental impacts of HS trains.
Experimental Determination of an Optimal Performance Map of a Steam Ejector Refrigeration System
Authors: Sutthivirode Kittiwoot , Thongtip Tongchana
Published: June 2022

An experimental determination of optimal performance of a steam ejector refrigerator was proposed which aims to indicate the optimal performance under various heat source temperatures. A small-scale steam ejector refrigerator test bench was constructed to carry out the experiment and to determine the optimal performance map. Three primary nozzles with throat diameters of 1.4, 1.6, and 1.8 mm, were tested with an ejector throat diameter of 14.5 mm, providing the ejector area ratios of 107, 82, and 65, respectively. For a particular working condition, the boiler temperature was varied to determine the maximum COP which is recognized as the optimal operation. It was found that the secondary fluid stream is first choked at the optimal boiler temperature. This optimal point varied significantly with the evaporator temperature, condenser pressure, and ejector area ratios. It was found that this steam ejector refrigerator could be operated under the optimal boiler temperature between 102.5 and 117.5 °C depending on the ejector area ratio, evaporator temperature, and condenser pressure. The optimal performance map is beneficial to further control the heat source temperature so that the maximum COP is achieved.
Study on Distribution Law of Stress and Permeability around Hydraulic Fracturing Borehole in Coal and Rock
Authors: Wu Xiaomin , Zhao Yuan , Yu Yongjun , Zhang Bo , Jia Li , Du Xidong
Published: June 2022

By constructing the permeability model to distinguish the fracture zone, plastic zone, and elastic zone around the hydraulic fracturing borehole, we study the influence of some important parameters on the stress distribution around the borehole and the permeability of the coal rock. The research results show that the greater the ground stress, the greater the radial stress in the fracture zone and plastic zone, and the smaller the radial stress in the elastic zone, while the trend of the stress variation in permeability is the opposite to the radial stress. The greater the gas pressure, the greater the permeability of the coal rock in each stress area. The larger the borehole radius, the smaller the radial stress at the same distance from the borehole center, and the greater the permeability of the coal rock. The greater the fracturing pressure, the greater the radial stress on the coal rock at the same distance from the borehole center, and the smaller the permeability of the coal rock. The research results can provide a theoretical reference for hydraulic fracturing construction in coal mines with different reservoir environments.
Influence of the Cable Accessories Installing Method on the Partial Discharge Activity in Medium Voltage Cables
Authors: Rybarz Jacek , Borucki Sebastian , Kunicki Michał , Kucińska-Landwójtowicz Aneta , Wajnert Dawid
Published: June 2022

This article proposes a method to modify the construction of a medium voltage (MV) heat shrinkable cable termination in cases of atypical damage to the shields of cross-linked polyethylene (XLPE) insulated cables. The proposed solutions include a modified method of assembling electric field control coating. An attempt was made to check the effect of such damage to the shields of MV cables with XLPE insulation on the level of occurrence of partial discharges within the cable termination. The investigations included testing the XRUHAKXS 1 × 240/25 cable type using the electric method (ME) and high frequency (HF) method with sinusoidal AC test voltage. As a result of the measurements, the values of total charges in the period and phase-resolved partial discharge (PRPD) patterns were obtained. The presented experimental results show the influence of the damage of the semiconducting coating surface on the occurrence of a defect in the cable termination without a modified method of control mantissa pinning. We suggest new methods of assembling MV cable accessories in the case of the presented coating damage in MV cable insulation.
Effectiveness and Feasibility of Market Makers for P2P Electricity Trading
Authors: Kuno Shinji , Tanaka Kenji , Yamada Yuji
Published: June 2022

Motivated by the growing demand for distributed energy resources (DERs), peer-to-peer (P2P) electricity markets have been explored worldwide. However, such P2P markets must be balanced in much smaller regions with a lot fewer participants than centralized wholesale electricity markets; hence, the market has inherent problems of low liquidity and price instability. In this study, we propose applying a market maker system to the P2P electricity market and developing an efficient market strategy to increase liquidity and mitigate extreme price fluctuations. To this end, we construct an artificial market simulator for P2P electricity trading and design a market agent and general agents (photovoltaic (PV) generators, consumers, and prosumers) to perform power bidding and contract processing. Moreover, we introduce market-maker agents in this study who follow the regulations set by a market administrator and simultaneously place both sell and buy orders in the same market. We implement two types of bidding strategies for market makers and examine their effects on liquidity improvement and price stabilization as well as profitability, using solar PV generation and consumption data observed in a past demonstration project. It is confirmed that liquidity and price stability may be improved by introducing a market maker although there is a trade-off relationship between these effects and the market maker’s profitability.
Mathematical Modeling of Sintering Air Leakage through Holes
Authors: Cai Jin , Kong Xiangwei , Yu Mingzhu
Published: June 2022

The air leakage in sintering machines affects the technological and economic indexes of the sintering process. It is of great significance to monitor and estimate the key areas. Mathematical models of sintering air leakage through holes in the steady-state process are given based on the fluid mechanics to predict the flow rate and effect on the key area. It was found that the hole model is the application of constant orifice outflow in the computation of sintering air leakage. The counter-flow bed model is suitable for predicting the flow rate through a complete break in sintering wind boxes. Furthermore, This paper proposes a new hole–bed generalized model to cover all the possible hole diameters for further high-precision application. The model connects the leakage hole diameter with the sintering process for the first time and establishes their coupling relationship. The pressure state in the sintering system depends on the ratio of the leakage hole area to the sintering bed area. The proposed fast estimation models are a step forward in developing more precise and powerful calculation tools to foresee the effects and consequences of sintering air leakage. It has a good prospect for reducing and replacing complex manual measurement and bringing some insight into the state of the art that could be improved in the future.
Observer-Based H∞ Load Frequency Control for Networked Power Systems with Limited Communications and Probabilistic Cyber Attacks
Authors: Ge Yixuan , Liu Guobao , Zhao Guishu , Liu Huai , Sun Ji
Published: June 2022

This paper studies load frequency control (LFC) for networked power systems with limited communications and probabilistic cyber attacks. Some restrictions exist during the information transmission, which can impair behavior and lead to instability of power systems. Throughout this paper, we consider such power systems that involve multi-path missing measurements and input–output time-varying delays as well as cyber attacks in the communication channels. A feedback controller is presented, which is based on the observer to implement H∞ LFC for power systems with disturbance rejection level γ. By Lyapunov stability theory, adequate criteria are given to ensure the stable operation of power systems. Finally, the validity of theoretical analysis is demonstrated and illustrated by numerical simulations.
A Grey-System Theory Approach to Assess the Safety of Gas-Supply Systems
Authors: Szpak Dawid , Tchórzewska-Cieślak Barbara , Pietrucha-Urbanik Katarzyna , Eid Mohamed
Published: June 2022

The continuity of gas-supply service is a major concern for all gas-supply operators. A safety review of a gas-supply system could help to mitigate the potential repercussions of supply disruptions. Disruptions occur at random due to systemic failures in gas distribution networks. Assessing the operational safety of gas distribution networks is challenging and complex, especially when operational data are limited or associated with high uncertainty. This paper focuses on gas leak incidents. Natural gas leaks disrupt the production process and endanger the ecosystem. Mechanically originated damage in pipelines is found to be the major cause of leaks, according to our investigations. This paper proposes a three-parameter risk matrix to be used in the safety analysis of gas-supply systems. This paper then raises the possibility of using grey-system theory. Grey-system theory has been used to overcome the limitations of the conventional matrix method. This choice is motivated by two facts: our data are heterogeneous with a high level of uncertainty, and some of the data are based on experts’ judgement and maintenance reports using qualitative metrics. It is underlined how GST provides insight for the decision-making process, even in the absence of complete information sets. The method developed here is advocated in the context of procedures ensuring the safety and the supply continuity of gas-supply systems.
Enhanced Flow Control for Low Latency in QUIC
Authors: Lee Sunwoo , An Donghyeok
Published: June 2022

Low-latency communication is becoming more popular as applications that demand real-time interaction, such as autonomous mobile vehicles and tactile Internet, have recently gained prominence. In this paper, we propose a fast autotuning algorithm to support low-latency communication in the Quick UDP Internet Connection (QUIC) protocol. The transmission rate is adjusted by the fast autotuning based on the quantity of unused buffers. If the buffer has large free space, the receive window is quickly enlarged to increase the transmission rate and reduce the transmission delay. The fast autotuning is evaluated in this paper through extensive simulations, and the results show that the fast autotuning effectively reduces the transmission latency and increases throughput.
Effect of the Nozzle Geometry on Flow Field and Heat Transfer in Annular Jet Impingement
Authors: Zhong Ying , Zhou Chao , Shi Yipeng
Published: June 2022

The effects of nozzle shape modifications on the flow phenomena and heat transfer characteristics in annular jet impingement are investigated numerically. The numerical simulations are conducted applying the shear stress transport (SST) k−ω model in the ANSYS CFX. Two modified nozzles: the converging nozzle and the diverging nozzle, are investigated in this study, and the straight nozzle serves as the base case. The geometric parameters and settings are based on an annular jet ejected from an axial fan used for electronic cooling: the Reynolds number Re= 20,000 and the blockage ratio Br=0.35 in the computation, and the target plate is placed at three representative separation distances: H=0.5,2, and 4. Compared with the base nozzle, the converging nozzle can accelerate the cooling flow and promote turbulence to enhance local and overall heat transfer (about 20%) over the target surface. In addition, the converging nozzle reduces the sizes of the recirculation zones, and this promotes the convective heat transfer transport near the axis. The diverging nozzle experiences a similar flow pattern and thermal field as the base nozzle, while the diverging nozzle achieves a slightly lower heat transfer with a pronounced pressure drop reduction. In addition, given that the value of the Nusselt number over the target plate is dependent on the Reynolds number, the simulations are also performed at Re=5000 and 40,000 to establish the correlations between the Nusselt number and the Reynolds number as Nu∝Rem. The value of m varies depending on the nozzle shapes and the separation distances.
Investigation into the Current State of Nuclear Energy and Nuclear Waste Management—A State-of-the-Art Review
Authors: Alwaeli Mohamed , Mannheim Viktoria
Published: June 2022

Nuclear power can replace fossil fuels and will have a decisive impact on the change in the approach to conventional energy. However, nuclear (or radioactive) wastes are produced by the operation of the nuclear reactors should be safely and properly disposed of. This paper assesses the uranium resources and the global state of nuclear power plants and determines the energy mixes in different countries using the most nuclear energy. Furthermore, this paper analysed the nuclear waste management and disposal and the depletion of abiotic resources, and the primary energy sources of a basic production process using electricity mix and nuclear electricity for a basic production (PET bottle manufacturing) process. The life cycle assessment was completed by applying the GaBi 8.0 (version 10.6) software and the CML method. In this study, we limit our discussion to high-level nuclear waste (HLW) and spent nuclear fuel (SNF) waste. We do not consider waste generated from uranium mining and milling, which is usually disposed of in near-surface impoundments close to the mine or the mill. The investigation of waste management methods is limited to European countries. This research work is relevant because determining abiotic resources is important in a life cycle assessment and current literature available on LCA analysis for nuclear powers remains under-developed. These results can guide and compare manufacturing processes involving a nuclear electricity and electricity grid mix input. The results of this research can be used to develop production processes using nuclear energy with lower abiotic depletion impacts. This research work facilitates the industry in making predictions for a production-scale plant using an LCA of production processes with nuclear energy consumption.
Design and Implementation of Smart Buildings: A Review of Current Research Trend
Authors: Kim Dongsu , Yoon Yeobeom , Lee Jongman , Mago Pedro J. , Lee Kwangho , Cho Heejin
Published: June 2022

The building sector is one of the largest contributors to the world’s total energy use and greenhouse gas emissions. Advancements in building energy technologies have played a critical role in enhancing the energy sustainability of the built environment. Extensive research and new techniques in energy and environmental systems for buildings have recently emerged to address the global challenges. This study reviews existing articles in the literature, mostly since 2000, to explore technological advancement in building energy and environmental systems that can be applied to smart homes and buildings. This review study focuses on an overview of the design and implementation of energy-related smart building technologies, including energy management systems, renewable energy applications, and current advanced smart technologies for optimal function and energy-efficient performance. To review the advancement in building energy-related technologies, a systematic review process is adopted based on available published reviews and research types of articles. Review-type articles are first assessed to explore the current literature on the relevant keywords and to capture major research scopes. Research-type papers are then examined to investigate associated keywords and work scopes, including objectives, focuses, limitations, and future needs. Throughout the comprehensive literature review, this study identifies various techniques of smart home/building applications that have provided detailed solutions or guidelines in different applications to enhance the quality of people’s daily activities and the sustainability of the built environmental system. This paper shows trends in human activities and technology advancements in digital solutions with energy management systems and practical designs. Understanding the overall energy flow between a building and its environmentally connected systems is also important for future buildings and community levels. This paper assists in understanding the pathway toward future smart homes/buildings and their technologies for researchers in related research fields.
Smart Predictive Maintenance Device for Critical In-Service Motors
Authors: Cazacu Emil , Petrescu Lucian-Gabriel , Ioniță Valentin
Published: June 2022

The paper proposed an innovative predictive maintenance system, designated to monitor and diagnose critical electrical equipment (generally large power electric motors) within industrial electrical installations. A smart and minimally invasive system is designed and developed. Its scope is to evaluate continuously the essential operating parameters (electrical, thermal, and mechanical) of the investigated equipment. It manages to report the deviations of inspected machine operating parameters values from the rated ones. The system also suggests the potential cause of these abnormal variations along with possible means (if the defect is identified in a database, constantly updated with each appearance of a malfunction). The developed maintenance device generates an operating report of the analyzed equipment, in which the values of power quality and energy indicators are computed and interpreted. Additionally, real-time remote transmission of analyzed data is facilitated, making them accessible from any location. The proposed maintenance system is a low-cost device that is easy to install and use in comparison with similar existing devices and equipment. The designed maintenance system was tested on dedicated to low-voltage equipment up to 100 kW.
AERES: Thermodynamic and Economic Optimization Software for Hybrid Solar–Waste Heat Systems
Authors: Vilasboas Icaro Figueiredo , dos Santos Victor Gabriel Sousa Fagundes , de Morais Vinicius Oliveira Braz , Ribeiro Armando Sá , da Silva Julio Augusto Mendes
Published: June 2022

Heliothermic technologies are affected by their low density, intermittence and low economic competitiveness. Hybrid solar–waste heat power systems can increase plant conversion efficiency and power generation while reducing intermittence. This study focused on the development of software (AERES) to economically optimize hybrid solar–waste heat power systems in terms of technology selection, sizing, operating conditions and power block characteristics. The technologies considered for algorithm selection were (i) heat exchangers that recover a wide range of waste heat sources, (ii) non-concentrating and concentrating solar collectors (a flat plate, an evacuated tube, a linear Fresnel and a parabolic trough), (iii) organic Rankine cycle power blocks and (iv) storage tanks (direct thermal storage systems). The last two technologies were represented by surrogate models so that a large number of decision variables could be optimized simultaneously. The optimization considered local climate conditions hourly to provide irradiation, local temperature and wind speed. The case studies indicated that optimized ORCs for waste heat recovery are economically competitive, reaching internal rates of return (IRRs) of 44%, 39% and 34% for a waste heat of 50 MWt at 350 °C, 300 °C and 250 °C, respectively. On the other hand, heliothermic technologies were not selected by the algorithm and provided non-competitive results for the analyzed cases.
Extended Newton–Kantorovich Theorem for Solving Nonlinear Equations
Authors: Regmi Samundra , Argyros Ioannis K. , George Santhosh , Argyros Christopher I.
Published: June 2022

The Newton–Kantorovich theorem for solving Banach space-valued equations is a very important tool in nonlinear functional analysis. Several versions of this theorem have been given by Adley, Argyros, Ciarlet, Ezquerro, Kantorovich, Potra, Proinov, Wang, et al. This result, e.g., establishes the existence and uniqueness of the solution. Moreover, the Newton sequence converges to the solution under certain conditions of the initial data. However, the convergence region in all of these approaches is small in general; the error bounds on the distances involved are pessimistic, and information about the location of the solutions appears improvable. The novelty of our study lies in the fact that, motivated by optimization concerns, we address all of these. In particular, we introduce a technique that extends the convergence region; provides weaker sufficient semi-local convergence criteria; offers tighter error bounds on the distances involved and more precise information on the location of the solution. These advantages are achieved without additional conditions. This technique can be used to extend other iterative methods along the same lines. Numerical experiments illustrate the theoretical results.
Sensitivity of Uniformly Convergent Mapping Sequences in Non-Autonomous Discrete Dynamical Systems
Authors: Jiang Yongxi , Yang Xiaofang , Lu Tianxiu
Published: June 2022

Let H be a compact metric space. The metric of H is denoted by d. And let (H,f1,∞) be a non-autonomous discrete system where f1,∞={fn}n=1∞ is a mapping sequence. This paper discusses infinite sensitivity, m-sensitivity, and m-cofinitely sensitivity of f1,∞. It is proved that, if fn(n∈N) are feebly open and uniformly converge to f:H→H, fi∘f=f∘fi for any i∈{1,2,…}, and ∑i=1∞D(fi,f)<∞, then (H,f) has the above sensitive property if and only if (H,f1,∞) has the same property where D(·,·) is the supremum metric.
Study of Lagrange Points in the Earth–Moon System with Continuation Fractional Potential
Authors: Bairwa Lata Kumari , Pal Ashok Kumar , Kumari Reena , Alhowaity Sawsan , Abouelmagd Elbaz I.
Published: June 2022

In this work, the restricted three-body system is studied in the framework of the continuation fractional potential with its application on the Earth–Moon system. With the help of a numerical technique, we obtained thirteen equilibrium points, such that nine of them are collinear while the remaining four are non-collinear points. We found that the collinear points near the smaller primary were shifted outward from the Moon, whereas the points near the bigger primary were shifted towards the Earth as the value of the continuation fractional parameter increased. We analyzed the zero-velocity curves and discussed the perturbation of the continuation fractional potential effect on the possible regions of the motion. We also discussed the linear stability of all the equilibrium points and found that out of thirteen only two were stable. Due to such a prevalence, the continuation fractional potential is a source of significant perturbation, which embodies the lack of sphericity of the body in the restricted three-body problem
The Pigments of the Painter Fleury Richard (1777–1852), a Model for Multidisciplinary Study
Authors: Carole Davy , Wicky Erika , Bensalah-Ledoux Amina , Paccoud Stéphane , Le Luyer Cécile , Pillonnet Anne , Panczer Gérard
Published: June 2022

Fleury Richard was a colorist painter of the early 19th century. He practiced the oil technique inspired by the Renaissance at a time when advances in chemistry were introducing many new synthetic pigments. His color-mixing cabinet has been kept intact at the Musée des Beaux Arts de Lyon. This original study is based on the analysis of more than 40 color powders using different spectroscopic techniques (X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and Raman spectroscopy), color index estimation, and the comparison of the results obtained from three pictural works painted by the artist. It allows us (i) to identify and reference the pigmented powders and pictural choices in connection with historical manuscripts describing the artist’s practice, and (ii) to identify the most judicious analysis methods and question the difficulty of analyzing paintings in a non-destructive way, where pigments are put into a matrix and mixed.
A COVID-19 Survey among People Who Use Drugs in Norway
Authors: Welle-Strand Gabrielle K. , Gjersing Linn , Olsen Ida K. , Clausen Thomas
Published: June 2022

Background: to combat the COVID-19 pandemic, adherence to COVID-19 recommendations and vaccination against COVID-19 have been important. Among people who use drugs (PWUD), little is known regarding compliance towards COVID-19 recommendations, COVID-19 testing, or attitudes towards COVID-19 vaccination. We aimed to examine these issues in a sample of PWUD. Methods: a cross-sectional study was conducted between January and March 2021. Through users’ organizations and different low-threshold services for substance users, we recruited former drug users and professionals to include participants and perform the interviews. Participants completed an interviewer-administered questionnaire. Any person above 16 years of age who used substances were recruited. Results: 477 Norwegian PWUD participated in the study. The mean age was 43.8 (SD 12.8) years and 77% were males. Thirty-four percent had injected drugs the past four weeks. Alcohol (41%) and cannabis (41%) were the most common drugs used the past four weeks, followed by tranquilizers (37%), central stimulants (35%) and opioids (30%). The majority (90%) had washed their hands frequently, used alcohol sanitizer during the past two weeks, had used face masks, kept one-meter distance to other people and stayed at home if feeling unwell. Fifty-four percent had been COVID-19 tested. More than half the sample (58%) had positive attitudes to COVID-19 vaccination, while 26% were fairly or very unlikely to accept vaccination. Those older (OR = 0.96, 95% CI 0.94; 0.98) and using face masks (OR = 0.49, 95% CI 0.30; 0.79) were more likely to have positive attitudes towards vaccination, while those reporting low life-satisfaction (OR = 3.86, 95% CI 1.43; 10.40), using opioids (OR = 2.97, 95% CI 1.43; 6.18) or almost never staying at home when feeling unwell (OR = 2.76, 95% 1.39; 5.45) expressed more negative attitudes towards vaccination. Conclusion: there was generally a high compliance towards COVID-19 recommendations, but one quarter of the sample was sceptical towards COVID-19 vaccination. This indicates a need for targeted and tailored information and well-designed vaccination roll-out programs to reach all PWUD.
Correlational Study of Emotional Stress, Pain, and the Presence of Inpatient Companions for Cancer Inpatients during the COVID-19 Pandemic
Authors: Chen Ya-Huei , Chen Shu-Ling , Chang Chia-Hui , Wu Pi-O , Yu Hsiu-Hui , Shih Sou-Jen , Chang Mei-Yu
Published: June 2022

The outbreak of COVID-19 poses an immense global threat. Visitors to hospitalized patients during a pandemic might themselves be carriers, and so hospitals strictly control patients and inpatient companions. However, it is not easy for cancer patients to adjust the times of their medical treatment or to suspend treatment, and the impact of the pandemic on cancer inpatients and inpatient companions is relatively high. The objectives for this investigation are to study the correlations among emotional stress, pain, and the presence of inpatient companions in cancer patients during the COVID-19 pandemic. This study was a retrospective descriptive study. The participants were cancer inpatients and inpatient companions in a medical center in Taiwan. The data for this study were extracted from cross-platform structured and normalized electronic medical record databases. Microsoft Excel 2016 and SPSS version 22.0 were used for analysis of the data. In all, 75.15% of the cancer inpatients were accompanied by family, and the number of hospitalization days were 7.87 ± 10.77 days, decreasing year by year, with statistical significance of p < 0.001. The daily nursing hours were 12.94 ± 10.76, and the nursing hours decreased year by year, p < 0.001. There was no significant difference in gender among those who accompanied the patients, but there were statistical differences in the length of hospitalization, nursing hours, and pain scores between those with and without inpatient companions, with p < 0.001. The inpatient companions were mostly family members (78%). The findings of this study on cancer patient care and inpatient companions should serve as an important basis for the transformation and reform of the inpatient companion culture and for epidemic prevention care in hospitals.