bluuebunny/crossref_metadata_2025 huggingface dataset:
Residual Learning and Multi-Path Feature Fusion-Based Channel Estimation for Millimeter-Wave Massive MIMO System
Authors: Zheng Xuhui , Liu Ziyan , Liang Jing , Wu Yingyu , Chen Yunlei , Zhang Qian
Published: February 2022

Channel estimation is a challenging task in a millimeter-wave (mm Wave) massive multiple-input multiple-output (MIMO) system. The existing deep learning scheme, which learns the mapping from the input to the target channel, has great difficulty in estimating the exact channel state information (CSI). In this paper, we consider the quantized received measurements as a low-resolution image, and we adopt the deep learning-based image super-resolution technique to reconstruct the mm Wave channel. Specifically, we exploit a state-of-the-art channel estimation framework based on residual learning and multi-path feature fusion (RL-MFF-Net). Firstly, residual learning makes the channel estimator focus on learning high-frequency residual information between the quantized received measurements and the mm Wave channel, while abundant low-frequency information is bypassed through skip connections. Moreover, to address the estimator’s gradient dispersion problem, a dense connection is added to the residual blocks to ensure the maximum information flow between the layers. Furthermore, the underlying mm Wave channel local features extracted from different residual blocks are preserved by multi-path feature fusion. The simulation results demonstrate that the proposed scheme outperforms traditional methods as well as existing deep learning methods, especially in the low signal-to-noise-ration (SNR) region.
Identifying Influential Nodes in Complex Networks Based on Multiple Local Attributes and Information Entropy
Authors: Zhang Jinhua , Zhang Qishan , Wu Ling , Zhang Jinxin
Published: February 2022

Identifying influential nodes in complex networks has attracted the attention of many researchers in recent years. However, due to the high time complexity, methods based on global attributes have become unsuitable for large-scale complex networks. In addition, compared with methods considering only a single attribute, considering multiple attributes can enhance the performance of the method used. Therefore, this paper proposes a new multiple local attributes-weighted centrality (LWC) based on information entropy, combining degree and clustering coefficient; both one-step and two-step neighborhood information are considered for evaluating the influence of nodes and identifying influential nodes in complex networks. Firstly, the influence of a node in a complex network is divided into direct influence and indirect influence. The degree and clustering coefficient are selected as direct influence measures. Secondly, based on the two direct influence measures, we define two indirect influence measures: two-hop degree and two-hop clustering coefficient. Then, the information entropy is used to weight the above four influence measures, and the LWC of each node is obtained by calculating the weighted sum of these measures. Finally, all the nodes are ranked based on the value of the LWC, and the influential nodes can be identified. The proposed LWC method is applied to identify influential nodes in four real-world networks and is compared with five well-known methods. The experimental results demonstrate the good performance of the proposed method on discrimination capability and accuracy.
Numerical Study of Entropy Generation in Fully Developed Turbulent Circular Tube Flow Using an Elliptic Blending Turbulence Model
Authors: Yang Xianglong , Yang Lei
Published: February 2022

As computational fluid dynamics (CFD) advances, entropy generation minimization based on CFD becomes attractive for optimizing complex heat-transfer systems. This optimization depends on the accuracy of CFD results, such that accurate turbulence models, such as elliptic relaxation or elliptic blending turbulence models, become important. The performance of a previously developed elliptic blending turbulence model (the SST k–ω–φ–α model) to predict the rate of entropy generation in the fully developed turbulent circular tube flow with constant heat flux was studied to provide some guidelines for using this class of turbulence model to calculate entropy generation in complex systems. The flow and temperature fields were simulated by using a CFD package, and then the rate of entropy generation was calculated in post-processing. The analytical correlations and results of two popular turbulence models (the realizable k–ε and the shear stress transport (SST) k–ω models) were used as references to demonstrate the accuracy of the SST k–ω–φ–α model. The findings indicate that the turbulent Prandtl number (Prt) influences the entropy generation rate due to heat-transfer irreversibility. Prt = 0.85 produces the best results for the SST k–ω–φ–α model. For the realizable k–ε and SST k–ω models, Prt = 0.85 and Prt = 0.92 produce the best results, respectively. For the realizable k–ε and the SST k–ω models, the two methods used to predict the rate of entropy generation due to friction irreversibility produce the same results. However, for the SST k–ω–φ–α model, the rates of entropy generation due to friction irreversibility predicted by the two methods are different. The difference at a Reynolds number of 100,000 is about 14%. The method that incorporates the effective turbulent viscosity should be used to predict the rate of entropy generation due to friction irreversibility for the SST k–ω–φ–α model. Furthermore, when the temperature in the flow field changes dramatically, the temperature-dependent fluid properties must be considered.
Magnetic Entropic Forces Emerging in the System of Elementary Magnets Exposed to the Magnetic Field
Authors: Bormashenko Edward
Published: February 2022

A temperature dependent entropic force acting between the straight direct current I and the linear system (string with length of L) of N elementary non-interacting magnets/spins μ→ is reported. The system of elementary magnets is supposed to be in the thermal equilibrium with the infinite thermal bath T. The entropic force at large distance from the current scales as Fmagnen~1r3, where r is the distance between the edge of the string and the current I, and kB is the Boltzmann constant; (r≫L is adopted). The entropic magnetic force is the repulsion force. The entropic magnetic force scales as Fmagnen~1T, which is unusual for entropic forces. The effect of “entropic pressure” is predicted for the situation when the source of the magnetic field is embedded into the continuous media, comprising elementary magnets/spins. Interrelation between bulk and entropy magnetic forces is analyzed. Entropy forces acting on the 1D string of elementary magnets that exposed the magnetic field produced by the magnetic dipole are addressed.
Energy-Efficient Optimization for Energy-Harvesting-Enabled mmWave-UAV Heterogeneous Networks
Authors: Zhang Jinxi , Chuai Gang , Gao Weidong
Published: February 2022

Energy Harvesting (EH) is a promising paradigm for 5G heterogeneous communication. EH-enabled Device-to-Device (D2D) communication can assist devices in overcoming the disadvantage of limited battery capacity and improving the Energy Efficiency (EE) by performing EH from ambient wireless signals. Although numerous research works have been conducted on EH-based D2D communication scenarios, the feature of EH-based D2D communication underlying Air-to-Ground (A2G) millimeter-Wave (mmWave) networks has not been fully studied. In this paper, we considered a scenario where multiple Unmanned Aerial Vehicles (UAVs) are deployed to provide energy for D2D Users (DUs) and data transmission for Cellular Users (CUs). We aimed to improve the network EE of EH-enabled D2D communications while reducing the time complexity of beam alignment for mmWave-enabled D2D Users (DUs). We considered a scenario where multiple EH-enabled DUs and CUs coexist, sharing the full mmWave frequency band and adopting high-directive beams for transmitting. To improve the network EE, we propose a joint beamwidth selection, power control, and EH time ratio optimization algorithm for DUs based on alternating optimization. We iteratively optimized one of the three variables, fixing the other two. During each iteration, we first used a game-theoretic approach to adjust the beamwidths of DUs to achieve the sub-optimal EE. Then, the problem with regard to power optimization was solved by the Dinkelbach method and Successive Convex Approximation (SCA). Finally, we performed the optimization of the EH time ratio using linear fractional programming to further increase the EE. By performing extensive simulation experiments, we validated the convergence and effectiveness of our algorithm. The results showed that our proposed algorithm outperformed the fixed beamwidth and fixed power strategy and could closely approach the performance of exhaustive search, particle swarm optimization, and the genetic algorithm, but with a much reduced time complexity.
Flipping the Classroom in Senior High School Textile Education to Enhance Students’ Learning Achievement and Self-Efficacy
Authors: Boateng Annette Akuamoah , Essel Harry Barton , Vlachopoulos Dimitrios , Johnson Esi Eduafua , Okpattah Vincentia
Published: February 2022

The study analysed the impact of the flipped classroom (FC) approach on weaving experience, self-efficacy and students’ learning achievement. To achieve this purpose, a quasi-experimental (pre-test/post-test) design, with a control group and an experimental group, was implemented. A mixed methods approach was used to evaluate the outcomes of the intervention. Forty- four first year senior high school students of an elective textile education subject participated in the study. An academic achievement test and a semi-structured group interview were employed as data-gathering instruments. Descriptive and inferential statistics (parametric and nonparametric tests), as well as thematic analysis were used to analyse the data collected. Findings of the study indicated that, regarding the acquisition of skill set and the maintenance of academic achievement, the students in the treatment group taught using the FC approach obtained higher levels of achievement juxtaposed with the students in the control group tutored with a traditional teacher-centred approach. The study further established that a flipped-classroom approach was engaging, interactive and exciting for students. The students in the experimental group, via the qualitative inquiry, expressed satisfaction with the practice in weaving and felt elevated in their knowledge, attitudes, self-learning, problem-solving and critical thinking skills acquisition. Therefore, the study recommended that the school adopt the FC approach as a method of teaching studio-based Visual Art subjects to support instructional hours.
Does It Make a Difference? Relations of Institutional Frameworks and the Regional Provision of Continuing Higher Education in England and Spain
Authors: Treviño-Eberhard Diana , Kaufmann-Kuchta Katrin
Published: February 2022

In this research, we compare interrelations between institutional settings and regional provision structures of continuing higher education (CHE) in England and Spain. The aim of the qualitative analysis is to identify and to compare country-specific linkages between national and regional policies, legal and financial regulations and their impact on providers, types of provision and target groups of CHE at the regional level. Theoretical assumptions of educational governance, environmental neo-institutionalism, and the sociology of conventions guide the analysis, based on expert interviews in England and Spain. Our research questions are: What modes of coordination of action to provide CHE are caused by national and regional regulations in England and Spain? How are these actions justified, and how do they influence regional CHE provision types and target groups in both countries? Interview-based findings show that national and regional regulations embrace hybrid modes of coordination of action regarding CHE provision in both countries. Specifically, centralised national policies in England and a mixture of centralised and decentralised legal frameworks in Spain impact regional CHE provision by universities, as does the scope of university autonomy in both countries. However, national frameworks only explain regional disparities in CHE provision to a limited extent. Less formal normative dimensions and social orders of university orientations and labour market demands also influence regional types of provision, concepts, provider cooperation, and adult CHE learners.
Evolutionary Coalitional Game-Based Cooperative Localization in Vehicular Networks
Authors: Yin Ting , Zou Decai , Lu Xiaochun , Bi Cheng
Published: February 2022

Cooperative localization under complex urban environments has become a solution able to replace Global Navigation Satellite System (GNSS) positioning. Due to the lack of an efficient cooperative localization scheme, traditional cooperative vehicle networks result in high computational complexity and heavy communication overhead. In this paper, we concentrate on the cooperative localization design of a vehicle. This paper proposes a cooperative localization method based on evolutionary coalitional game theory to implement vehicle location estimation with a lower communication cost. We select the neighboring vehicles to form a coalition based on the node’s square position error bound and communication cost. The location is obtained via exchanging information between vehicles. It is evident from the simulations and results that the proposed method requires a low communication overhead while maintaining localization accuracy.
Automatically Learning Formal Models from Autonomous Driving Software
Authors: Selvaraj Yuvaraj , Farooqui Ashfaq , Panahandeh Ghazaleh , Ahrendt Wolfgang , Fabian Martin
Published: February 2022

The correctness of autonomous driving software is of utmost importance, as incorrect behavior may have catastrophic consequences. Formal model-based engineering techniques can help guarantee correctness and thereby allow the safe deployment of autonomous vehicles. However, challenges exist for widespread industrial adoption of formal methods. One of these challenges is the model construction problem. Manual construction of formal models is time-consuming, error-prone, and intractable for large systems. Automating model construction would be a big step towards widespread industrial adoption of formal methods for system development, re-engineering, and reverse engineering. This article applies active learning techniques to obtain formal models of an existing (under development) autonomous driving software module implemented in MATLAB. This demonstrates the feasibility of automated learning for automotive industrial use. Additionally, practical challenges in applying automata learning, and possible directions for integrating automata learning into the automotive software development workflow, are discussed.
A Novel Carrier Scheme Combined with DPWM Technique in a ZVS Grid-Connected Three-Phase Inverter
Authors: Liao Yi-Hung , Chen Jiong-Ye , Zhou Ying
Published: February 2022

In this paper, a novel switching scheme using discontinuous pulse-width modulation (DPWM) for a zero-voltage switching (ZVS) grid-connected three-phase inverter is proposed. ZVS in the main and auxiliary switches was achieved. Moreover, the reverse recovery currents of the anti-parallel diodes in the main switches were suppressed. A circuit analysis was performed, and a simulation was carried out. Furthermore, a prototype of the ZVS grid-connected three-phase inverter was constructed to verify the effectiveness of the proposed PWM control scheme. Both the simulation and experimental results verified the validity of the proposed PWM control scheme.
Research on an Urban Low-Altitude Target Detection Method Based on Image Classification
Authors: Jin Haiyan , Wu Yuxin , Xu Guodong , Wu Zhilu
Published: February 2022

With the expansion of the civil UAV (Unmanned Aerial Vehicle) market, UAVs are also increasingly being used in illegal activities such as espionage and snooping on privacy. Therefore, how to effectively control the activities of UAVs in cities has become an urgent problem to be solved. Considering the urban background and the radar performance of communication signals, a low-altitude target detection scheme based on 5G base stations is proposed in this paper. A 5G signal is used as the external radiation source, the method of transceiver separation is adopted, and the forward-scattered waves are used to complete the detection of UAV. This paper mainly analyzes the principle of forward scattering detection in an urban environment, where the forward-scattered wave of a target is stronger than the backward-reflected wave and contains both height difference and midline height information on the target. Based on the above theory, this paper proposes a forward-scattered wave recognition algorithm based on YOLOv3-FCWImageNet, which transforms the forward-scattered wave recognition problem into a target detection problem and accomplishes the recognition of forward-scattered waves by using the excellent performance of algorithms in the field of image recognition. Simulation results show that FCWImageNet can distinguish two different low-altitude targets effectively, and realize the monitoring and classification of UAVs.
Assessing Validity of Employing Surveying Methods to Capture Data on Topography to Determine Hydrological and Topographic Parameters Essential for Selecting Locations for the Construction of Small Hydropower Plants
Authors: Kwartnik-Pruc Anita , Mączyńska Aneta
Published: February 2022

Renewable energy sources have begun to arouse interest worldwide. The UN Sustainable Development Agenda has defined access to affordable, reliable, sustainable and modern energy as one of its main goals. This paper contains a description of the research on the assessment of the validity of employing surveying methods to capture topographic data in order to select locations suitable for small hydropower plants. For the purpose of this study, a section of a natural watercourse with the surrounding area was measured by means of the photogrammetric method using unmanned aerial vehicles (UAVs) and, for comparison, by means of the precise positioning method using the GNSS system with the RTN kinematic technique (GNSS RTN). Publicly available measurement data from airborne laser scanning (LIDAR) were also used for the analyses. In order to assess the accuracy of the methods employed, the discrete data describing the relief were analysed, and then continuous data in raster form were analysed. The analyses were performed with the use of an automatic method of height comparison and analysis of cross-sections on DEM and DSM. In the last stage of the work, the hydrological parameters were analysed, i.e., the slope of the land and the watercourse flow values determined based on the DEM captured from various surveying methods. What is unique about this work is: (1) the use of spatial data with a high resolution acquired from UAVs to search for locations for the construction of small hydroelectric power plants and assessment of their usefulness in this regard; (2) assessment of the accuracy and quality of the hydrological and morphological parameters of the area important for the selection of the location for the construction of small hydropower plants, performed based on spatial data depicting the actual area of the land measured in the field; (3) assessment of the quality of the hydrological modelling necessary to find the location. The performed surveys and analyses allowed for the identification of the advantages and disadvantages of the surveying methods employed to capture data on the topography of land as well as indications of the optimal data source.
State of Charge Dual Estimation of a Li-ion Battery Based on Variable Forgetting Factor Recursive Least Square and Multi-Innovation Unscented Kalman Filter Algorithm
Authors: Yuan Hongyuan , Han Youjun , Zhou Yu , Chen Zongke , Du Juan , Pei Hailong
Published: February 2022

Battery management is the key technical link for electric vehicles. A good battery management system can realize the balanced charge and discharge of batteries, reducing the capacity degradation and the loss of health caused by battery overcharge and discharge, which all depend on the real-time and accurate estimation of the battery’s state of charge (SOC). However, the battery’s SOC has highly complex nonlinear time-varying characteristics related to the complex chemical and physical state and dynamic environmental conditions, which are difficult to measure directly, and this has become a difficulty in design and research. According to the characteristics of ternary lithium-ion batteries of electric vehicles, a battery SOC dual estimation algorithm based on the Variable Forgetting Factor Recursive Least Square (VFFRLS) and Multi-Innovation Unscented Kalman Filter (MIUKF) is proposed in this paper. The VFFRLS algorithm is used to estimate battery model parameters, and the MIUKF algorithm is used to estimate the battery’s SOC in real time. The two algorithms are coupled to update battery model parameters and estimate the SOC. The experiment results show that the algorithm has high accuracy and stability.
An NMR-Based Method for Multiphase Methane Characterization in Coals
Authors: Zheng Sijian , Sang Shuxun , Liu Shiqi , Jin Xin , Wang Meng , Lu Shijian , Feng Guangjun , Yang Yi , Hou Jun
Published: February 2022

Discriminating multiphase methane (adsorbed and free phases) in coals is crucial for evaluating the optimal gas recovery strategies of coalbed methane (CBM) reservoirs. However, the existing volumetric-based adsorption isotherm method only provides the final methane adsorption result, limiting real-time dynamic characterization of multiphase methane in the methane adsorption process. In this study, via self-designed nuclear magnetic resonance (NMR) isotherm adsorption experiments, we present a new method to evaluate the dynamic multiphase methane changes in coals. The results indicate that the T2 distributions of methane in coals involve three different peaks, labeled as P1 (T2 < 8 ms), P2 (T2 = 20–300 ms), and P3 (T2 > 300 ms) peaks, corresponding to the adsorbed phase methane, free phase methane between particles, and free phase methane in the sample cell, respectively. The methane adsorption Langmuir volumes calculated from the conventional volumetric-based method qualitatively agree with those obtained from the NMR method, within an allowable limit of approximately ~6.0%. Real-time dynamic characterizations of adsorbed methane show two different adsorption rates: an initial rapid adsorption of methane followed by a long stable state. It can be concluded that the NMR technique can be applied not only for methane adsorption capacity determination, but also for dynamic monitoring of multiphase methane in different experimental situations, such as methane adsorption/desorption and CO2-enhanced CBM.
Experimental Study on Oil Drop Discharge Behavior during Dynamic Imbibition in Tight Oil Sandstone with Aid of Surfactant
Authors: Xin Yan , Sun Yongpeng , Ding Fei , Chen Ang , Zhao Wenxun , Fang Yanchao , Wei Li’nan , Dai Caili
Published: February 2022

The pore and throat structure of tight oil reservoir cores is complex, and the resistance of oil drop to discharge from the core is very high during dynamic imbibition. Surfactant has good ability in interfacial tension reduction and wettability reversal. It can reduce oil drop discharge resistance and enhance oil recovery effectively during dynamic imbibition in tight reservoirs. Here, we first analyzed the pore throat structure and mineral composition of tight core, and then the oil drop visualization instrument was used to study the discharge behavior of oil drop during dynamic imbibition. The oil drop discharge form was analyzed, and the influence of various factors on the oil drop discharge behavior was explored, and then the dynamic imbibition performance of surfactant in tight cores was obtained. The core throat diameter was mainly distributed in 0.07–1.1 μm, and the hydrophilic mineral content in core reached 50.8%. In the case of fluid flow in fracture, the oil drop discharge from near fracture matrix was faster, and its growth rate in height and width was faster than that without external fluid flow. Within a certain range, with the increase of IFT, the rate of core imbibition increased gradually. When the IFT increased from 0.32 mN/m to 0.59 mN/m, the oil drop rapture time decreased by 66.3%. The growth rate of oil drop discharged from the top and side of the core was faster than that from the bottom surface. Furthermore, it was easier to discharge. With the core thickness reduced by half, the rapture time of oil drop was reduced by 74.7%. For tight reservoirs, hydraulic fracturing can create more fracture surfaces and reduce the size of matrix blocks, which contributes to reduce the oil drop discharge resistance during imbibition and improve the oil recovery. This study provides a basis for surfactant to improve dynamic imbibition and oil production performance of tight sandstone oil reservoir.
Raman Spectroscopy Characterization of Mineral Oil and Palm Oil with Added Multi-Walled Carbon Nanotube for Application in Oil-Filled Transformers
Authors: Suhaimi Nur Sabrina , Ishak Mohd Taufiq , Md Din Muhamad Faiz , Hashim Fakhroul Ridzuan , Abdul Rahman Abdul Rashid
Published: February 2022

This century is experiencing a generation of nanotechnologies that makes use of the remarkable properties of nanofluids in applications such as electrical systems, industrialization, and others. In this paper, mineral oil (MO) and palm oil (PO), with multi-walled carbon nanotube (CNT), have been synthesized for use in oil-filled transformer applications. This research aims to use Raman characterization to assess the feasibility of CNT nanofluids samples at 0.02 g/L and 0.03 g/L concentrations. The chemical structure bonding that exists in the Raman band between 700 cm−1 and 3100 cm−1 regions is identified and analyzed, accordingly. After baseline removal and normalization, the precision band location and intensity of oil samples are fitted with a Gaussian profile. It was discovered that the peak at ~1440 cm−1 has the highest intensity for six oil samples, which is attributed to the (C–H) methylene scissors vibration of the CH2 group. Based on the FWHM profile and integrated area under the curve of PO, it was discovered that CNT contributes to the structural stability defect of PO. Principal component analysis (PCA) is also used in this study to classify different samples based on chemical composition and identify the spectral characteristics with the highest degree of variability.
Preliminary Evaluation of the Impact of Sustained Overvoltage on Low Voltage Electronics-Based Equipment
Authors: David Jason , Ciufo Philip , Elphick Sean , Robinson Duane
Published: February 2022

Low voltage devices connected to public electricity supply networks can be subjected to a wide range of voltage quality, including sustained overvoltage. Assessing the impact of sustained overvoltage on devices connected to the distribution network is important in determining the appropriate variance of standard voltage levels without unduly impacting the utility and customers from a technical and economic perspective. Therefore, a clear understanding of the impact that sustained overvoltage has on the lifetime of the connected equipment is a necessary task. This paper investigates the impact of sustained overvoltage through a series of accelerated-life testing experiments on a custom designed test device representative of a common interface between the power supply and distribution network, a switch mode power supply. The switch mode power supply with combined rectifier and filtering capacitor represents one of the most common front ends of LV equipment in modern appliances, and the work here concentrates on the impact of overvoltage on capacitor ageing. The results of the testing indicate that there is an accelerated ageing impact correlated with the applied voltage magnitude. Furthermore, analysis shows that mismatches between appliance voltage rating and sustained network voltage, leading to accelerated ageing, may result in premature device failure without the consumer being aware of the root cause.
Comparative Fuel Yield from Anaerobic Digestion of Emerging Waste in Food and Brewery Systems
Authors: Herman Tess , Nungesser Emily , Miller Kimberley E. , Davis Sarah C.
Published: February 2022

Food waste (FW), a major part of the US waste stream, causes greenhouse gases within landfills, but there is an opportunity to divert FW to anaerobic digestion (AD) facilities that produce biogas and digestate fertilizer. The composition of FW inputs to AD determines the value of these products. This study provides insight into the effect of waste composition on the quality of AD products by first characterizing the biogas and digestate quality of anaerobically digested FW from four diets (paleolithic, ketogenic, vegetarian, and omnivorous), and then estimating the difference in biogas produced from codigested FW and brewery waste (BW). Waste feedstock mixtures were incubated in lab-scale bioreactors for 21 days with live inoculum. Biogas quality was monitored for 21–30 days in four trials. Samples were analyzed using a gas chromatograph for detection of methane (CH4) and carbon dioxide (CO2). The composition of the waste inputs had a significant impact on the quality of biogas but not on the quality of the digestate, which has implications for the value of post-AD fertilizer products. Wastes with higher proportions of proteins and fats enhanced biogas quality, unlike wastes that were rich in soluble carbohydrates. Codigestion of omnivorous food waste with carbon-rich agricultural wastes (AW) improved biogas quality, but biogas produced from BW does not necessarily improve with increasing amounts of AW in codigestion.
Study of the Stability of the Surface Perilous Rock in a Mining Area
Authors: Gao Lu , Kang Xiangtao , Gao Lin , Ma Zhenqian
Published: February 2022

As a result of the mining of a C3 coal seam in a mine in Guizhou, perilous rock masses on the surface collapsed. In this study, the stability of perilous rock masses on the surface of the coal mine before and after mining was calculated and examined, and the movement law of the overlying strata in the goaf, the movement and deformation law, and the failure mode of perilous rock were analyzed. This study provides a theoretical basis for the treatment of unstable rock and coal seam mining, and has important guiding significance for the safe and efficient production of the mine. The results show that: (1) The perilous rock is in a basically stable state without the influence of mining. Through theoretical analysis and the construction of the collapse model of perilous rock, it is judged that perilous rocks W1, W3, W4, and W7 were basically stable, perilous rocks W2 and W5 were in an unstable state, and perilous rock W6 was stable without heavy rainfall. (2) As a result of the mining of the C3 coal seam, the cracks in the upper strata began to develop to the surface, and the longitudinal separation cracks gradually appeared between the surface perilous rock and the rock matrix. Due to the existence of these cracks, the perilous rock had a downward shear force. In addition, due to the heavy rainfall in the Guizhou area, the transient saturated zone of perilous rock is expanding and the strength of perilous rock is reduced. The seepage increases the sliding force of the perilous rock and aggravates the opening of cracks at any time. (3) The stability of the surface perilous rock mass is largely affected by the mining of underground coal mines. The simulation analysis was repeated using the method of setting coal pillars. When 45 m permanent protection coal pillars are set at both ends, and 15 m local protection coal pillars are set at 60 m, the safety of coal mining can be ensured without affecting the surface and perilous rock.
Migration Behaviors of As, Se and Pb in Ultra-Low-Emission Coal-Fired Units and Effect of Co-Firing Sewage Sludge in CFB Boilers
Authors: Liu Xuan , Teng Yang , Zhang Kai
Published: February 2022

The migration behaviors of As, Se and Pb in ultra-low-emission coal-fired units were investigated and the effect of co-firing of sewage sludge and coal was explored in circulating fluidized-bed (CFB) boiler units. Samples of feed fuel including coal and sewage sludge, fly ash, bottom slag and desulfurization slurry were collected from five CFB units with a capacity between 150 MW and 350 MW and two pulverized coal boiler (PC) units with a capacity of 350 MW and 600 MW. The majority of As, Se and Pb in coal is released during coal combustion and enriched in fly ash. As, Se and Pb in fly ash and bottom slag are associated with inorganic matter, of which As, Se and Pb associated with silicates and aluminosilicates account for more than 60%. In the wet flue gas desulfurization (WFGD) unit, more than half of the As, Se and Pb migrates to the solid fraction and the concentrations of As, Se and Pb in fine solid particles are much higher than those in coarse solid particles and the liquid fraction. The proportions of exchangeable As, Se and Pb or associated with organic matter in gypsum are higher than those of fly ash and bottom slag. According to the two studied CFB units with blending ratios of sewage sludge below 10%, co-firing with sewage sludge has little effect on the migration and transformation characteristics of As, Se and Pb. Under a long-term acidic leaching environment, Pb in combustion by-products is in the range of low risk, while As and Se are in the range of medium risk.
Flow Deflection between Guide Vanes in a Pump Turbine Operating in Pump Mode with a Slight Opening
Authors: Ji Qingfeng , Wu Guoying , Liao Weili , Fan Honggang
Published: February 2022

During the startup and shutdown processes of a reversible-pump turbine (RPT) working in pump mode, abnormal sounds and vibrations usually occur in the distributor when the guide vanes (GVs) are at a slight opening (max opening of about 6%). The objective of this paper is to apply a three-dimensional numerical CFD method to study the unsteady flow behavior in the guide vane region of a pump turbine operating in pump mode. The dynamic meshing technique is introduced to simulate the startup and shutdown processes, and it is shown to be critical in accurately capturing the details of the flow pattern variations. In addition, the RNG k-epsilon two-equation turbulence model is applied and the governing equations are discretized with the finite volume method. Moreover, the boundary conditions are set through the calculation of the transient process of the power station. The results show that the main flow between the GVs is deflected during the startup and shutdown processes. In the shutdown process, the deflection occurs when the guide vane opening (GVO) is between 1.99 and 5.32 degrees, on average. In the startup process, the deflection occurs when the GVO is between 2.83 and 4.11 degrees, on average. In these processes, the velocity field and pressure field change dramatically. Simultaneously, the hydraulic torque (HT) on the GVs has a sharp change. The abrupt change in the HT leads to vibrations and abnormal sounds.
Energy Optimization of the Continuous-Time Perfect Control Algorithm
Authors: Krok Marek , Majewski Paweł , Hunek Wojciech P. , Feliks Tomasz
Published: February 2022

In this paper, an attempt at the energy optimization of perfect control systems is performed. The perfect control law is the maximum-speed and maximum-accuracy procedure, which allows us to obtain a reference value on the plant’s output just after a time delay. Based on the continuous-time state-space description, the minimum-error strategy is discussed in the context of possible solutions aiming for the minimization of the control energy. The approach presented within this study is focused on the nonunique matrix inverse-originated so-called degrees of freedom being the core of perfect control scenarios. Thus, in order to obtain the desired energy-saving parameters, a genetic algorithm has been employed during the inverse model control synthesis process. Now, the innovative continuous-time procedure can be applied to a wide range of multivariable plants without any stress caused by technological limitations. Simulation examples made in the MATLAB/Simulink environment have proven the usefulness of the new method shown within the paper. In the extreme case, the energy consumption has been reduced by approximately 80% in comparison with the well-known Moore–Penrose inverse.
A Techno-Economic Analysis of Energy Storage Components of Microgrids for Improving Energy Management Strategies
Authors: Ndiaye Alla , Locment Fabrice , De Bernardinis Alexandre , Sechilariu Manuela , Redondo-Iglesias Eduardo
Published: February 2022

Microgrids are essential elements of the energy transition because they allow optimal use of renewable energy sources (photovoltaic panels, wind turbines) and storage devices (batteries, supercapacitors) by connecting them to consumption poles (e.g., buildings, charging stations of electric vehicles). Lithium-ion batteries and supercapacitors are the main electrical storage devices usually used by microgrids for energy and power transient management. In the present paper, microgrid simulations have been performed. Electrothermal and aging models of storage components are presented. Strategies and scenarios for the batteries are presented either based on the state of charge limitation or hybrid association with supercapacitors. The contribution of this study is to provide a management strategy which considers the aging of storage systems in the real-time management of the microgrid in order to extend their life, while minimizing installation costs. The first approach for a techno-economic study provided in that study enables us to improve the strategies by optimizing the use of the battery. The results obtained in this paper demonstrate the key role of the techno-economic approach and knowledge of the aging processes of storage devices in improving the energy management and global feedback costs of microgrids. The simulation results show that battery life can be improved by 2.2 years. The improvement in battery life leads to a reduction in the total cost of the installation by reducing the cost of the batteries.
Chemical Looping Combustion: A Brief Overview
Authors: Czakiert Tomasz , Krzywanski Jaroslaw , Zylka Anna , Nowak Wojciech
Published: February 2022

The current development of chemical looping combustion (CLC) technology is presented in this paper. This technique of energy conversion enables burning of hydrocarbon fuels with dramatically reduced CO2 emission into the atmosphere, since the inherent separation of carbon dioxide takes place directly in a combustion unit. In the beginning, the general idea of the CLC process is described, which takes advantage of solids (so-called oxygen carriers) being able to transport oxygen between combustion air and burning fuel. The main groups of oxygen carriers (OC) are characterized and compared, which are Fe-, Mn-, Cu-, Ni-, and Co-based materials. Moreover, different constructions of reactors tailored to perform the CLC process are described, including fluidized-bed reactors, swing reactors, and rotary reactors. The whole systems are based on the chemical looping concept, such as syngas CLC (SG-CLC), in situ Gasification CLC (iG-CLC), chemical looping with oxygen uncoupling (CLOU), and chemical looping reforming (CLR), are discussed as well. Finally, a comparison with other pro-CCS (carbon capture and storage) technologies is provided.
Trust in Renewable Energy as Part of Energy-Saving Knowledge
Authors: Żywiołek Justyna , Rosak-Szyrocka Joanna , Khan Muhammad Asghar , Sharif Arshian
Published: February 2022

Managing the consumer’s knowledge is a factor that is difficult to measure and not easy to achieve, but it is the basis for building trust in energy sources, including alternative ones. Social and ecological attitudes, as well as the economic situation, force consumers to acquire knowledge and shape their views and knowledge about household energy management. The aim of this article was to analyze the level of knowledge of household managers and determine the level of trust in alternative energy sources. To achieve this goal, previous research and reports were analyzed, and a proprietary quantitative and qualitative research was carried out. In connection with the conducted research, it was found that a very important factor is trust, influencing the perception of energy sources, and the knowledge gained allows for proper management of household energy, thus reducing costs. Research has shown that the trust of people managing energy in households is influenced by trust in renewable energy sources, which consists of knowledge, i.e., the level of social awareness and the willingness to acquire and expand one’s knowledge in this field. In all of the countries surveyed, the degree of trust is adequate, but it is directly proportional to the amount of knowledge and readiness to learn new things in this field.
Functional Performance of Plant Proteins
Authors: Ma Kai Kai , Greis Maija , Lu Jiakai , Nolden Alissa A. , McClements David Julian , Kinchla Amanda J.
Published: February 2022

Increasingly, consumers are moving towards a more plant-based diet. However, some consumers are avoiding common plant proteins such as soy and gluten due to their potential allergenicity. Therefore, alternative protein sources are being explored as functional ingredients in foods, including pea, chickpea, and other legume proteins. The factors affecting the functional performance of plant proteins are outlined, including cultivars, genotypes, extraction and drying methods, protein level, and preparation methods (commercial versus laboratory). Current methods to characterize protein functionality are highlighted, including water and oil holding capacity, protein solubility, emulsifying, foaming, and gelling properties. We propose a series of analytical tests to better predict plant protein performance in foods. Representative applications are discussed to demonstrate how the functional attributes of plant proteins affect the physicochemical properties of plant-based foods. Increasing the protein content of plant protein ingredients enhances their water and oil holding capacity and foaming stability. Industrially produced plant proteins often have lower solubility and worse functionality than laboratory-produced ones due to protein denaturation and aggregation during commercial isolation processes. To better predict the functional performance of plant proteins, it would be useful to use computer modeling approaches, such as quantitative structural activity relationships (QSAR).
Use of Healthy Emulsion Hydrogels to Improve the Quality of Pork Burgers
Authors: Foggiaro Danila , Domínguez Rubén , Pateiro Mirian , Cittadini Aurora , Munekata Paulo E. S. , Campagnol Paulo C. B. , Fraqueza Maria João , De Palo Pasquale , Lorenzo José M.
Published: February 2022

The present research evaluated the use of oil mixture emulsion hydrogels as animal fat replacers and their effect on the physicochemical, nutritional and sensory characteristics of pork burgers. Three different types of burgers were manufactured: control (samples elaborated with 100% pork fat), T1 and T2 (pork fat totally replaced by emulsion hydrogels of walnut or pistachio oil and algal oil, respectively). Fat replacement increased the moisture and ash contents and colour parameters (L* and b*) of pork burgers. Modified samples turned out to be firmer and chewier than those in the control group. The addition of oil emulsion hydrogels caused a significant decrease in fat and energy contents and the products obtained can be considered “reduced fat content”. Moreover, the content of saturated fatty acids decreased, while mono- and polyunsaturated fatty acids increased, constituting an improvement in health indices. Sensory differences were found between the samples and T2 was the most preferred for flavour and overall. However, both modified burgers had good levels of acceptability. To conclude, the use of the proposed oil mixture emulsion hydrogels as pork backfat substitutes represents a promising strategy to obtain healthier pork burgers without negatively affecting technological or sensory properties.
Probiotic Effects and Metabolic Products of Enterococcus faecalis LD33 with Respiration Capacity
Authors: Jiao Yuehua , Yang Han , Shigwedha Nditange , Zhang Shuang , Liu Fei , Zhang Lanwei
Published: February 2022

Respiration metabolism could improve the long-term survival of lactic acid bacteria (LAB); however, its effect on potential probiotic traits of LAB was not reported. The difference made by Enterococcus faecalis LD33 that was cultured under respiration-permissive and fermentation conditions, such as the biomass, metabolites, antimicrobial activity, tolerance to acid and bile salt, adhesion capabilities, and the ability to inhibit the proliferation of cancer cells were studied. Under a respiration-permissive condition, the final biomass of the culture was about twice as compared to that of fermentation condition. When the metabolites were measured, glucose was exhausted within 8 h. Two-folds of acetic acid, triple of both acetoin and diacetyl, and less than half of lactic acid, were accumulated under the respiratory-permissive condition. No discrimination of growth inhibition on Salmonella enterica serovar Typhimurium ATCC 14028 and Shigella sonnei ATCC 25931 was observed when Enterococcus faecalis LD33 was cultured under both conditions; however, under respiration-permissive condition, the strain presented significant antimicrobial activities to Listeria monocytogenes ATCC19111 and Staphylococcus aureus ATCC6538P. Enterococcus faecalis LD33 displayed relatively strong bile salt tolerance and adherence capability but weaker acid tolerance when undergoing respiration metabolism. There was no significant difference in the anti-cancer effect of the viable bacterial cells on both growth modes; however, the supernatant showed a higher inhibition effect on HT-29 cells than the live bacteria, and there was no significant difference between the supernatant and the 5-Fluorouracil (7 μg/mL). Consequently, the Enterococcus faecalis LD33 undergoing respiration metabolism could bring higher biomass, more flavor metabolites, and better antimicrobial and anti-cancer activities. This study extends our knowledge of respiratory metabolism in LAB and its impact on probiotic traits. E. faecalis LD33 qualifies as a suitable strain against foodborne pathogens, cancer therapy, and eventual application in the food and pharmaceutical industries.
Using Rheology to Understand Transient and Dynamic Gels
Authors: Bianco Simona , Panja Santanu , Adams Dave J.
Published: February 2022

Supramolecular gels can be designed such that pre-determined changes in state occur. For example, systems that go from a solution (sol) state to a gel state and then back to a sol state can be prepared using chemical processes to control the onset and duration of each change of state. Based on this, more complex systems such as gel-to-sol-to-gel and gel-to-gel-to-gel systems can be designed. Here, we show that we can provide additional insights into such systems by using rheological measurements at varying values of frequency or strain during the evolution of the systems. Since the different states are affected to different degrees by the frequency and/or strain applied, this allows us to better understand and follow the changes in state in such systems.