bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Reduction Annealing on the Coloration Mechanism of Yellow Sapphire with High Iron Content
Authors: Wu Xiao , Han Xiaozhen , Kang Yan , Feng Xiqi , Guo Shouguo
Published: September 2022

The color of yellow sapphire from Africa characterized by high iron content and low levels of other transition metal elements was changed from yellow to grayish-blue after high-temperature reduction annealing. Before reduction annealing, the optical absorption spectra showed that the outer d–d electron transitions of Fe3+ were the main coloring cause of yellow sapphires, but the charge transfer between O2− and Fe3+ may have a greater contribution. The change in lattice parameter indicates that Fe3+ is reduced to Fe2+ during reduction annealing, and adjacent Fe2+ and Fe3+ form an Fe2+-Fe3+ ion pair. The absorption caused by intervalence charge transfer of Fe2+-Fe3+ is the essential reason for the grayish-blue appearance of yellow sapphires after reduction annealing. The charge compensation mechanism of Fe2+-Fe3+ in natural sapphire is also discussed, and oxygen vacancy is considered to be the most suitable charge compensator for Fe2+-Fe3+.
New Bounds on Capacity Region of Multiple Access Channels in Visible Light Communications
Authors: Yang Ruixin , Li Bing , Ma Shuai , Wu Youlong , Li Zongyan , Li Shiyin
Published: September 2022

In this paper, we propose new inner and outer bounds of the capacity region for multiple access channels in visible light communication (VLC) networks under both peak and average optical power constraints. Specifically, the proposed inner bounds are established by employing the single-user capacity achieving input distribution for each user. The proposed outer bounds are derived by determining single-user capacities for each user and calculating a sum capacity upper bound by relaxing the input constraints. Numerical results show that the proposed new bounds are extremely tight and outperform existing bounds over wide ranges of SNRs.
A Conditional Mutual Information Estimator for Mixed Data and an Associated Conditional Independence Test
Authors: Zan Lei , Meynaoui Anouar , Assaad Charles K. , Devijver Emilie , Gaussier Eric
Published: September 2022

In this study, we focus on mixed data which are either observations of univariate random variables which can be quantitative or qualitative, or observations of multivariate random variables such that each variable can include both quantitative and qualitative components. We first propose a novel method, called CMIh, to estimate conditional mutual information taking advantages of the previously proposed approaches for qualitative and quantitative data. We then introduce a new local permutation test, called LocAT for local adaptive test, which is well adapted to mixed data. Our experiments illustrate the good behaviour of CMIh and LocAT, and show their respective abilities to accurately estimate conditional mutual information and to detect conditional (in)dependence for mixed data.
Decoding ‘Maximum Entropy’ Deconvolution
Authors: Le Long V. , Kim Tae Jung , Kim Young Dong , Aspnes David E.
Published: September 2022

For over five decades, the mathematical procedure termed “maximum entropy” (M-E) has been used to deconvolve structure in spectra, optical and otherwise, although quantitative measures of performance remain unknown. Here, we examine this procedure analytically for the lowest two orders for a Lorentzian feature, obtaining expressions for the amount of sharpening and identifying how spurious structures appear. Illustrative examples are provided. These results enhance the utility of this widely used deconvolution approach to spectral analysis.
A Neural Network-Based Mesh Quality Indicator for Three-Dimensional Cylinder Modelling
Authors: Chen Xinhai , Wang Zhichao , Liu Jie , Gong Chunye , Pang Yufei
Published: September 2022

Evaluating mesh quality prior to performing the computational fluid dynamics (CFD) simulation is an essential step to ensure the acceptable accuracy of cylinder modelling. However, traditional mesh quality indicators are often insufficient since they only check geometric information on individual distorted elements. To yield more accurate results, the current evaluation process usually requires careful manual re-evaluation for quality properties such as mesh distribution and local refinement, which heavily increase the meshing overhead. In this paper, we introduce an efficient quality indicator for varisized cylinder meshes, consisting of a mesh pre-processing method and a neural network-based indicator, Mesh-Net. We also publish a cylinder mesh benchmark dataset. The proposed indicator is trained to study the role of CFD meshes on the accuracy of numerical simulations. It considers both the effect of element geometry (e.g., orthogonality) and quality properties (e.g., smoothness and distribution). Thereafter, the well-trained indicator is used as a black-box to predict the overall quality of the input mesh automatically. Experimental results demonstrate that the proposed indicator is accurate and can be applied in the mesh quality evaluation process without manual interactions.
An Image Encryption Algorithm Based on Complex Network Scrambling and Multi-Directional Diffusion
Authors: Sheng Yaohui , Li Jinqing , Di Xiaoqiang , Li Xusheng , Xu Rui
Published: September 2022

Various security threats are encountered when keys are transmitted in public channels. In this paper, we propose an image encryption algorithm based on complex network scrambling and multi-directional diffusion. Combining the idea of public key cryptography, the RSA algorithm is used to encrypt the key related to plaintext. The algorithm consists of three stages: key generation stage, complex network scrambling stage, and multi-directional diffusion stage. Firstly, during the key generation phase, SHA-512 and the original image are used to generate plaintext-related information, which is then converted to plaintext-related key through transformation mapping. Secondly, in the complex network scrambling stage, the chaotic random matrix establishes the node relationships in the complex network, which is then used to construct an image model based on the complex network, and then combines pixel-level and block-level methods to scramble images. Finally, in the multi-directional diffusion stage, the multi-directional diffusion method is used to perform forward diffusion, middle spiral diffusion, and backward diffusion on the image in turn to obtain the final ciphertext image. The experimental results show that our encryption algorithm has a large keyspace, the encrypted image has strong randomness and robustness, and can effectively resist brute force attack, statistical attack, and differential attack.
Performance of Bearing Ball Defect Classification Based on the Fusion of Selected Statistical Features
Authors: Mezni Zahra , Delpha Claude , Diallo Demba , Braham Ahmed
Published: September 2022

Among the existing bearing faults, ball ones are known to be the most difficult to detect and classify. In this work, we propose a diagnosis methodology for these incipient faults’ classification using time series of vibration signals and their decomposition. Firstly, the vibration signals were decomposed using empirical mode decomposition (EMD). Time series of intrinsic mode functions (IMFs) were then obtained. Through analysing the energy content and the components’ sensitivity to the operating point variation, only the most relevant IMFs were retained. Secondly, a statistical analysis based on statistical moments and the Kullback–Leibler divergence (KLD) was computed allowing the extraction of the most relevant and sensitive features for the fault information. Thirdly, these features were used as inputs for the statistical clustering techniques to perform the classification. In the framework of this paper, the efficiency of several family of techniques were investigated and compared including linear, kernel-based nonlinear, systematic deterministic tree-based, and probabilistic techniques. The methodology’s performance was evaluated through the training accuracy rate (TrA), testing accuracy rate (TsA), training time (Trt) and testing time (Tst). The diagnosis methodology has been applied to the Case Western Reserve University (CWRU) dataset. Using our proposed method, the initial EMD decomposition into eighteen IMFs was reduced to four and the most relevant features identified via the IMFs’ variance and the KLD were extracted. Classification results showed that the linear classifiers were inefficient, and that kernel or data-mining classifiers achieved 100% classification rates through the feature fusion. For comparison purposes, our proposed method demonstrated a certain superiority over the multiscale permutation entropy. Finally, the results also showed that the training and testing times for all the classifiers were lower than 2 s, and 0.2 s, respectively, and thus compatible with real-time applications.
Do Urbanization and Energy Consumption Change the Role in Environmental Degradation in the European Union Countries?
Authors: Jóźwik Bartosz , Gavryshkiv Antonina-Victoria , Galewska Kinga
Published: September 2022

Nowadays, increased urbanization is visible in most European Union countries. At the same time, it can be noticed that in the studied period (2000–2018), GDP per capita increased, and CO2 emissions per capita and energy consumption per capita decreased. These trends should be assessed in an unequivocally positive way. Considering these trends, especially with regard to economic development, our research goal is to answer the following questions: is there a long-run relationship between urbanization, energy consumption, economic growth, and carbon dioxide emissions, and what roles do urbanization and energy consumption play in the concept of the environmental Kuznets curve? This study aims to contribute to this growing area of research by exploring the European Union countries in the period covering the accession of new member states from Central Europe that needs intensifying European environmental policy. In order to test cointegration, we used Pedroni and Westerlund’s panel tests. To estimate the long-run coefficients, we employed the FMOLS, MG, CCEMG, and AMG tests. Our findings confirmed the long-run relationship between variables. We find that urbanization has a high negative impact on carbon dioxide emissions per capita. Interestingly, our studies’ results differ from those in most of the previously published articles about European countries. For this reason, our results provide a new insight for policymakers in European Union institutions.
3D Modeling of Fracture-Cave Reservoir from a Strike-Slip Fault-Controlled Carbonate Oilfield in Northwestern China
Authors: Wang Rujun , Yang Jianping , Chang Lunjie , Zhang Yintao , Sun Chong , Wan Xiaoguo , Wu Guanghui , Bai Bingchen
Published: September 2022

A giant strike-slip fault-controlled Fuman Oilfield has been found in the Ordovician fractured carbonates of the Tarim Basin. However, conventional seismic methods are hardly able to distinguish the fractured reservoir and its connectivity in the ultra-depth (>7000 m) carbonate fault zones. We propose thin-likelihood and tensor-thickness process methods to describe the fracture network and large cave reservoir, respectively. Together with the two methods for 3D visualization of fracture-cave reservoirs, we had an application in the ultra-deep well deployment in Fuman Oilfield. The results show that the fracture network and cave reservoir can be 3D-imaged more clearly than conventional methods. The fracture network and cave reservoir show distinct segmentation by the fault assemblage in Fuman Oilfield. Furthermore, 3D modeling is favorable for the reservoir connectivity description along the carbonate fault zones. There are three distinct reservoir models: fault core-, fault damage zone- and overlap zone-controlling fractured reservoirs along the fault zones. This revealed variable fractured reservoirs that are related to fault maturity and segmentation. The method has been widely used in fracture-cave reservoir description and subsequent well optimization, suggesting a favorable method for economic oil exploitation in the ultra-depth reservoirs. This case study is not only useful for the complicated reservoir 3D description and modeling but also helpful for well employment to provide support for the target evaluation and optimization in ultra-depth fractured reservoirs.
Harmonic Compensation via Grid-Tied Three-Phase Inverter with Variable Structure I&I Observer-Based Control Scheme
Authors: Flota-Bañuelos Manuel , Miranda-Vidales Homero , Fernández Bernardo , Ricalde Luis J. , Basam A. , Medina J.
Published: September 2022

The power inverter topologies are indispensable devices to incorporate distributed generation schemes, like photovoltaic energy sources into the AC main. The nonlinear behavior of the power inverter draws a challenge when it comes to their control policy, rendering linear control methods often inadequate for the application. The control complexity can be further increased by the LCL filters, which are the preferred way to mitigate the current ripple caused by the inverter switching. This paper presents a robust variable structure control for a three-phase grid-tied inverter with an LCL filter. As well to the benefits of the sliding mode control (SMC), which is one of the control methods applied by power converters founded in literature, the proposed control scheme features a novel partial state observer based on the immersion and invariance technique, which thanks to its inherent robustness and speed of convergence is adequate for this application. This observer eliminates the need for physical current sensors, decreasing the overall cost and size, as well as probable sources of noise. The proposed controller is meant for a three-phase grid-tied inverter to inject active power to the grid while harmonics generated by nonlinear loads are compensated. The simulation results prove the effectiveness of the proposed method by compensating for current harmonics produced by the nonlinear loads and maintaining a low total harmonic distortion as recommended by the STD-IEEE519-2014, regardless of whether the system provides active power or not.
Literature Review of Energy Management in Combined Heat and Power Systems Based on High-Temperature Proton Exchange Membrane Fuel Cells for Residential Comfort Applications
Authors: Sanz i López Víctor , Costa-Castelló Ramon , Batlle Carles
Published: September 2022

Combined heat and power technologies represent an efficient way to ensure energy efficiency, as they promote usage of both electrical and thermal energy, something not done by most traditional energy sources, especially in residential environments. In this context, high-temperature proton exchange membrane fuel cells allow the implementation of combined heat and power systems. Additionally, in this environment, fuel cells are more efficient and less polluting than their traditional counterparts. We present a literature review of energy management in residential systems based on this type of fuel cell. In addition, we classify and detail the current state of fuel cell technologies, paying special attention to their characteristics, mathematical modelling and control, as well as combined heat and power systems and energy management strategies.
Model Predictive Control for Photovoltaic Plants with Non-Ideal Energy Storage Using Mixed Integer Linear Programming
Authors: Cedeño Angel L. , López Ahuar Reinier , Rojas José , Carvajal Gonzalo , Silva César , Agüero Juan C.
Published: September 2022

This paper proposes a model-based predictive control strategy based on mixed-integer linear programming for a photovoltaic power plant with battery energy storage. The control objective is to maximize the revenues from energy delivered from both photovoltaic panels and batteries to the grid in a deregulated electricity market. For each control interval, the proposed algorithm incorporates information on solar radiation, market prices, and the state of charge of the batteries to determine the intervals of energy injection into the grid to maximize the economic benefits. The proposed strategy considers the rate-based variable efficiency in the battery model and time-varying energies prices, thus providing a more general implementation than previous schemes proposed in the literature for the same purpose. Simulations considering the operational procedures of the Spanish market as a case study show that, by integrating the battery efficiency in the model, the proposed control strategy increments the economic benefits in 21% compared to previous results reported in the literature for the same operational conditions. Additionally, the proposed approach reduces the number of charge and discharge cycles, potentially extending the lifespan of batteries.
Design and Assessment of a LIDAR-Based Model Predictive Wind Turbine Control
Authors: Bao Jie , Yue Hong
Published: September 2022

The development of the Light Detection and Ranging (LIDAR) technology has enabled wider options for wind turbine control, in particular regarding disturbance rejection. The LIDAR measurements provide a spatial, preview wind information, based on which the controller has a better chance to cope with the wind disturbance before it affects the turbine operation. In this paper, a model predictive controller for above-rated wind turbine control was developed with the use of pseudo-LIDAR wind measurements data. A predictive control algorithm was developed based on a linearised wind turbine model, in which the disturbance from the incoming wind was computed by the LIDAR simulator. The optimal control action was applied to the nonlinear turbine model. The developed controller was compared with the baseline control and a previously developed LIDAR-assisted control combining a feedback-and-feedforward design. Our simulation studies on a 5 MW nonlinear wind turbine model, under different wind conditions, demonstrated that the developed LIDAR-based predictive control achieved improved performance in the presence of small variations in the out-of-plane rotor torque and fore-aft tower acceleration, as well as a smoother generator speed regulation and satisfied pitch activity control constraints.
CFD Modeling of Pressure Drop through an OCP Server for Data Center Applications
Authors: Dogan Aras , Yilmaz Sibel , Kuzay Mustafa , Yilmaz Cagatay , Demirel Ender
Published: September 2022

Modeling IT equipment is of critical importance for the simulations of flow and thermal structures in air cooled data centers. Turbulent flow undergoes a significant pressure drop through the server due to the energy losses originating from the internal components. Therefore, there is an urgent need to develop a fast and an accurate method for the calculation of pressure losses inside server components for data center applications. In this study, high resolution numerical simulations were performed on an OCP (Open Compute Project) server under various inlet flow rates for inactive and active conditions. Meanwhile, one key challenge of modeling complete geometry of the server results from using an intense mesh even for a single server. To address this challenge, the server was modeled as a porous zone to mimic inertia and viscous resistance in a realistic way. Comparison of the results of porous and complete models showed that the proposed model could calculate pressure drop accurately even when the number of cells in the server was reduced to 0.3% of the complete model. Porosity coefficients were determined from the numerical simulations conducted in a broad range of air discharge for both active and inactive conditions. Errors in the calculation of pressure drop may result in a significant deviation in the prediction of the temperature rise over the server. Thus, the present model can effectively be used for the fast and accurate prediction of pressure drop inside a server component rather than solving internal flow on an intense mesh, while simulating airflow inside an air-cooled data center, which is crucial for the design safety of data centers. Finally, calculated porosity coefficients can be used for the prediction of the pressure drop in a server, while designing data centers based on numerical simulations.
Minimum-Output-Current-Ripple Control of Current-Fed Three-Level Phase-Shift Full-Bridge Converter
Authors: Wang Haichao , Yang Guorun , Kang Wei , Zhang Xinsheng , Fan Xuexin , Xiao Fei
Published: September 2022

Electrified ports using medium-voltage DC (MVDC) renewable energy microgrids require current-fed dc/dc converters in application scenarios such as battery or ultracapacitor charging units and hydrogen production systems. This paper designs a three-level phase-shift full-bridge (TL-PSFB) converter that interfaces with the MVDC microgrid. Its operation in the current source mode requires a wide output voltage range and small output current ripple. Firstly, the dual-output TL-PSFB topology is introduced, and the principle of phase-shift pulse width modulation (PS-PWM) is presented. Secondly, the principle of the traditional constant-conduction-duty-cycle (CCDC) strategy is analyzed. Then, a minimum-output-current-ripple (MOCR) strategy is proposed by analyzing the relationship between output current ripple, conducting-duty cycle, and phase-shift duty cycle, and a constant current control combined with the MOCR strategy is designed. The output current ripple of the MOCR strategy is smaller than that of the CCDC strategy in a full range of operating conditions. Under the same output current ripple design index, the value and loss of the filter inductor can be reduced with the MOCR strategy. In addition, the MOCR strategy can widen the output voltage regulation range and increase the bus voltage utilization without causing significant changes to the total harmonic distortion (THD) of primary voltage. Finally, experimental results verify the correctness of the theoretical analysis.
Determining Factors of Consumers’ Choice of Sport Utility Vehicles in an Isolated Energy System: How Can We Contribute to the Decarbonization of the Economy?
Authors: Ramírez-Díaz Alfredo J. , Ramos-Real Francisco J. , Rodríguez-Brito María Gracia , Rodríguez-Donate María Carolina , Lorente de las Casas Andrés
Published: September 2022

This paper analyses the profile of individuals who decide to purchase a Sport Utility Vehicle (SUV) in a medium-sized isolated island system such as Tenerife Island. To achieve this objective, we used a survey conducted in 2017 to identify the characteristics of the individuals most likely to choose an SUV or another type of vehicle or be undecided. Subsequently, a discrete choice model was estimated to assess the probability that an individual chooses one of the three options as a function of their socio-economic characteristics, mobility routines, vehicle attributes and psychosocial traits. The results show the need to adopt energy policy measures related to vehicle choice, as they put the fulfilment of the decarbonization objectives for the energy transition in the Canary Islands at risk. Firstly, the authorities should carry out campaigns to achieve a more environmentally conscious behaviour by highlighting the higher consumption and emission levels of this type of vehicle. Secondly, subsidies for more efficient new vehicles and taxation should promote the purchase of low-emission vehicles to compensate for the greater willingness to pay of SUV buyers. In particular, purchase taxation should be linked to emission levels rather than only considering power, engine characteristics or labelling.
The Railway Timetable Evaluation Method in Terms of Operational Robustness against Overloads of the Power Supply System
Authors: Restel Franciszek , Haładyn Szymon Mateusz
Published: September 2022

The main aim of this study was to develop a method for assessing the level of robustness of timetabled transport performance in rail transport. When the railway lines are supplied by DC networks, lower voltages are observed, and consequently, current values are often ten times higher than in AC networks. This is an operational problem, as high currents make it easier to overload the supply network. Based on a literature review, the authors show that the problem of running railway traffic when the capacity of the power supply network is limited (by the size of the permitted currents) is not well studied. The authors propose a method based on the Markov approach supplemented by classical theoretical vehicle traffic dynamics to improve the operational robustness of the rail transport system using DC power supply system. Each train run was parameterised in such a way that it is possible to determine the state that the train is in during the run, the transitions between states, and the determination of the probabilities of occurrence of such states. On the other hand, classical vehicle dynamics was used to assess the load generated by the train on the power grid. The proposed method—reduced to a function—was verified using a case study. The method of timetable reconfiguration proposed by the authors increased the operational robustness from 0.9454 to 0.9774.
Possibilities of Biogas Upgrading on a Bio-Waste Sorbent Derived from Anaerobic Sewage Sludge
Authors: Zieliński Marcin , Karczmarczyk Aleksandra , Kisielewska Marta , Dębowski Marcin
Published: September 2022

The development of biogas upgrading technologies is now an essential issue in recovering fuel-grade methane. Nowadays, trends in biogas upgrading include investigations of low-cost and renewable materials as sorbents for biogas enrichment to produce biomethane. Therefore, in this work, wastewater anaerobic sludge stabilized with calcium oxide was used as the bio-waste sorbent to capture carbon dioxide from biogas, employing a fixed bed column. The biogas flow rate was the parameter considered for examining the breakthrough responses. It was observed that breakthrough time decreases with increasing biogas inflow rate from 570 ± 10 min at 5 mL/min to 120 ± 12 min at 35 mL/min. The maximum sorption capacity of 127.22 ± 1.5 mg CO2/g TS of sorbent was estimated at 15 mL/min. Biomethane concentration in biogas increased from 56.5 ± 1.7 v% in the raw biogas to 98.9 ± 0.2 v% with simultaneous low carbon dioxide content of 0.44 ± 0.2 v%. A strong positive correlation (R2 = 0.9919) between the sorption capacity and the biogas flow rate was found in the range of biogas inflow rates between 5 mL/min and 15 mL/min. Moreover, the correlation analysis showed a strong negative relationship (R2 = 0.9868) between breakthrough time and the mass of carbon dioxide removal, and the biogas flow rates ranged from 10 mL/min to 20 mL/min.
Operation Method of On-Load Tap Changer on Main Transformer Considering Reverse Power Flow in Distribution System Connected with High Penetration on Photovoltaic System
Authors: Yoon Kwang-Hoon , Shin Joong-Woo , Nam Tea-Yang , Kim Jae-Chul , Moon Won-Sik
Published: September 2022

The increasing use of photovoltaics (PVs) in distribution systems owing to the low-carbon policy has given rise to the need for various technological changes. In particular, the operation of on-load tap changers (OLTCs) has attracted attention. In traditional distribution systems, the OLTC operates via a line-drop compensator (LDC), which focuses on the load to solve the low-voltage problem; however, the problem of over-voltage caused by PVs persists. Currently, a method for operating an OLTC using the measured voltage is being researched; however, solving the voltage problem for several feeders connected to a main transformer (MT) is not viable. Therefore, this study proposes an OLTC operation method to address the feeder with the largest voltage problem depending on the direction of power flow. The proposed method selects a point where the OLTC operates using the difference between the measured and reference voltages. Setting the reference voltage can solve the problem that occurs due to the direction of power flow. Finally, the effectiveness of the proposed method is verified via case studies. Based on the results, we can conclude that the proposed method effectively solves the voltage problem, and an increase in hosting capacity can be expected.
Characteristics of Cavitation Flow for a Regulating Valve Based on Entropy Production Theory
Authors: He Jie , Liu Qihang , Long Zheng , Zhang Yujia , Liu Xiumei , Xiang Shaobing , Li Beibei , Qiao Shuyun
Published: September 2022

A regulating valve is a key control element in the coal liquefaction industry, whose flow field distribution is related to the entropy production. In order to make a quantitative evaluation of the energy loss in the cavitation flow and calculate the magnitude and location of the hydraulic loss in the flow field more accurately, entropy production theory is employed to analyze the flow field in the regulating valve numerically. The entropy production under cavitation condition and its influence on steady-state flow force are also discussed. When the opening of the valve increases, the entropy production and energy loss change dramatically. The entropy production rate (EPR) is mainly distributed at the orifice and downstream of the regulating valve, the entropy production rate (EPR) reaches the maximum value at the orifice, and turbulent pulsation entropy production (TPEP) is the main part of the total entropy production for flow. When the valve’s opening increases from 40% to 70%, the total entropy production (TEP) increases from 467.14 W/K to 630.04 W/K. The entropy production by cavitation (EPC) increases firstly and then decreases. The smallest value of EPC is 0.103 W/K at the 40% opening, while the maximum value is 0.119 W/K at 60% opening. Furthermore, the relationship between total entropy production (TEP) and steady-state flow force can be approximated by an exponential distribution. When the steady-state flow force increases, the total entropy production for flow also increases. Cavitation effect on the steady-state flow force is strengthened firstly and then weakened with increasing the valve’s opening. Finally, a discriminant method based on the change of the steady-state flow force is proposed to detect whether cavitation occurs in the valve or not. The results in this paper could provided a directional and quantitative evaluation of energy loss in the regulating valve, which is help for the structural shape optimization and service life extension combining with external characteristics of the valve and internal flow field.
Artificial Intelligence Control System Applied in Smart Grid Integrated Doubly Fed Induction Generator-Based Wind Turbine: A Review
Authors: Behara Ramesh Kumar , Saha Akshay Kumar
Published: September 2022

Wind-driven turbines utilizing the doubly-fed induction generators aligned with the progressed IEC 61400 series standards have engrossed specific consideration as of their benefits, such as adjustable speed, consistent frequency mode of operation, self-governing competencies for voltage and frequency control, active and reactive power controls, and maximum power point tracking approach at the place of shared connection. Such resource combinations into the existing smart grid system cause open-ended problems regarding the security and reliability of power system dynamics, which needs attention. There is a prospect of advancing the art of wind turbine-operated doubly-fed induction generator control systems. This section assesses the smart grid-integrated power system dynamics, characteristics, and causes of instabilities. These instabilities are unclear in the wind and nonlinear load predictions, leading to a provisional load-rejection response. Here, machine learning computations and transfer functions measure physical inertia and control system design’s association with power, voltage, and frequency response. The finding of the review in the paper indicates that artificial intelligence-based machine and deep learning predictive diagnosis fields have gained prominence because of their low cost, less infrastructure, reduced diagnostic time, and high level of accuracy. The machine and deep learning methodologies studied in this paper can be utilized and extended to the smart grid-integrated power context to create a framework for developing practical and accurate diagnostic tools to enhance the power system’s accuracy and stability, software requirements, and deployment strategies.
Application of Pre-Splitting and Roof-Cutting Control Technology in Coal Mining: A Review of Technology
Authors: Xie Shengrong , Wu Yiyi , Guo Fangfang , Zou Hang , Chen Dongdong , Zhang Xiao , Ma Xiang , Liu Ruipeng , Wu Chaowen
Published: September 2022

According to the development requirements of green mining of coal resources, it is imperative to improve the extraction rate of coal and the application of safe and efficient mining technology. Pre-splitting and roof cutting technology is widely used in reducing residual coal pillars and safe pressure relief mining, which has become the crucial technology for pillar-free mining methods. Therefore, it is essential to review and discuss the research hotspots, cutting-edge methods, principles of action, and application areas of the development of this technology. Above all, the research data on pre-splitting and roof-cutting development in the past ten years are summarized and outlined. The research’s hot spots are pressure relief technology and gob-side entry retaining technology. Then, the functional forms of pre-splitting and roof cutting technology are discussed and compared, including explosive blasting (directional energy gathering blasting, liquid explosive blasting, and composite blasting), hydraulic fracturing, liquid CO2 gas fracturing, and mechanized roof cutting (chain arm saw machine and directional cutting roof rig). Through the analysis of field application cases, the application field is divided into three major areas: non-coal pillar mining (gob-side entry driving with narrow coal pillar, gob-side entry retaining with the filling body, completely gob-side entry retaining, and “N00” construction method), pressure relief at working face (thick and hard main roof cracking and end area hard roof cracking), and pressure relief at roadway (gob-side roadway pressure relief and blasting pressure relief technology for roadways). By detailing the process of each application technology one by one, the principle and mode of pre-splitting in each technology are expounded. Finally, the development prospects of pre-splitting and roof cutting in new technical methods, deep pressure relief mining, intelligent unmanned mining, and green and efficient mining are prospected, providing references for similar projects.
The Application of the γ-Reθt Transition Model Using Sustaining Turbulence
Authors: Zhang Meihong , Nie Shengyang , Meng Xiaoxuan , Zuo Yingtao
Published: September 2022

The freestream turbulence intensity is an important parameter for Tollmien–Schlichting waves and is also used as one of the key variables for the local- and transport-equation-based transition model in the simulations. To obtain the similar turbulence level in the vicinity to the aircraft as the turbulence intensity measured in a wind tunnel or in free-flight conditions, the sustaining turbulence term can be used for the transition model. It is important to investigate the model behavior when the sustaining turbulence is coupled with the frequently used SST-variants for transitional flows. Additionally, it is essential to obtain a nearly independent solution using the same transition model for different users on different meshes with similar grid resolution for purposes of verification and validation. So far, the relevant work has not been performed sufficiently and the sustaining turbulence technology introduces non-independent results into the freestream values. Thus, a modified sustaining turbulence approach is adopted and investigated in several test cases, including a computational effort on NACA0021 test case at 10 angles of attack. The results indicate that the modified sustaining turbulence in conjunction with the SST-2003 turbulence model yields results nearly independent to the freestream value of ω for the prediction of both streamwise and crossflow transition for two-dimensional flows without increasing computational effort too much. For three-dimensional flow, the sensitivity to initial value of ω is reduced significantly as well in comparison to the SST-based transition model, and it is highly recommended to use present sustaining turbulence technology in conjunction with the SST-2003-based transition model for engineering applications.
Natural Ventilation Enhancement of a Roof Solar Chimney with Wind-Induced Channel
Authors: Gao Ning , Yan Yao , Sun Rui , Lei Yonggang
Published: September 2022

A novel roof solar chimney with wind-induced channel was designed herein to augment indoor natural ventilation under combined action of wind and solar energy. Compared with the traditional solar chimney, the new rooftop solar chimney improves the air flow due to the wind-induced channel. The effects of channel width ratio, chimney inclination at different outdoor wind speeds on the natural ventilation performance of the roof solar chimney were studied by numerical simulation. Finite-volume method was used for the numerical calculation. It was found that the trends of ventilation rate are different when the channel widths increase. The mass flow rate of the new structure increases with the increase in the inclination angle. When the inclination angles increase from 30° to 90°, the ventilation rate increases by 212% for U = 1.0 m·s−1, 166% for U = 2.0 m·s−1, and 127% for U = 3.0 m·s−1 under the condition of and the solar radiation I = 600 W·m−2.
Evaluation of Leachate Recirculation as a Stabilisation Strategy for Landfills in Developing Countries
Authors: Sandoval-Cobo John , Caicedo-Concha Diana , Marmolejo-Rebellón Luis , Torres-Lozada Patricia , Fellner Johann
Published: September 2022

This study evaluated leachate recirculation (LR) as a stabilisation strategy for landfills using bioreactor experiments with excavated waste from a tropical landfill in Colombia. The experimental evaluation was performed in two 115 L bioreactors, one simulating the operation of a landfill with LR, Br2, where the leachate produced was recirculated at a rate of 0.8 L d−1, and a control system without LR, Br1. Both systems reached stabilisation indicator values on a dry matter (DM) basis for volatile solids VS (<25% DM) and a biochemical methane potential BMP (≤10 mL CH4 g−1 DM). Likewise, towards the end of the experiment, the leachate generated in Br2 reached stabilisation indicator values for BOD5 (<100 mg L−1) and the BOD (biological oxygen demand)/COD (chemical oxygen demand) ratio (<0.1). Although the stabilisation criterion for COD was not met in any bioreactor (<200 mg L−1), LR helped to release 19% more oxidisable organic matter in Br2 than in Br1, indicating a reduction in the contaminating potential of the waste in the case of uncontrolled discharges of leachate to the environment. Regarding biogas production, the generation of CH4 in Br2 was more intense and its cumulative production was 34.5% higher than Br1; thus, Br2 achieved CH4 emission rates, indicating waste stabilisation (<1.0 L CH4 m−2 h−1) sooner than Br1, showing an accelerating effect of LR on waste degradation. A carbon mass balance indicated that waste degradation, in terms of the initial total organic carbon mineralisation and the C gas discharge via CH4, was greater in Br2. These results demonstrate the LR potential to accelerate the stabilisation of a landfill but also to reduce greenhouse gas emissions in final disposal sites where biogas is also captured and utilised for energy production; a key aspect when improving the sustainability of landfill operations in developing countries.
Model Development for State-of-Power Estimation of Large-Capacity Nickel-Manganese-Cobalt Oxide-Based Lithium-Ion Cell Validated Using a Real-Life Profile
Authors: Kebede Abraham Alem , Hosen Md Sazzad , Kalogiannis Theodoros , Behabtu Henok Ayele , Jemal Towfik , Van Mierlo Joeri , Coosemans Thierry , Berecibar Maitane
Published: September 2022

This paper investigates the model development of the state-of-power (SoP) estimation for a 43 Ah large-capacity prismatic nickel-manganese-cobalt oxide (NMC) based lithium-ion cell with a thorough aging investigation of the cells’ internal resistance increase. For a safe operation of the vehicle system, a battery management system (BMS) integrated with SoP estimation functions is crucial. In this study, the developed SoP model used for the estimation of power throughout the lifetime of the cell is coupled with a dual-polarization equivalent-circuit model (DP_ECM) for achieving the precise estimation of desired parameters. The SoP model is developed based on the pulse-trained internal resistance evolution approach, and hence the power is estimated by determining the rate of internal resistance increase. Hybrid pulse power characterization (HPPC) test results are used for extraction of the impedance parameters. In the DP_ECM, Coulomb counting and extended Kalman filter (EKF) state estimation methods are developed for the accurate estimation of the state of charge (SoC) of the cell. The SoP model validation is performed by using both dynamic Worldwide harmonized Light vehicles Test Cycles (WLTC) and static current profiles, achieving promising results with root-mean-square errors (RMSE) of 2% and 1%, respectively.
Fatigue and Training Load Factors in Volleyball
Authors: Pawlik Damian , Mroczek Dariusz
Published: September 2022

The purpose of this article was to determine the internal and external loads experienced by volleyball players in a weekly cycle during the competitive season. Using accelerometers, as well as subjective rating perceived exertion (RPE) and total quality recovery scale (TQR) questionnaires, eleven female athletes were monitored during five days of training sessions over the course of the 2021 season. The data were evaluated for trends during the start period in preparation for the championship tournament. Analysis of the accelerometer data revealed a relationship between RPE and session rating perceived exertion (s-RPE), as well as the number of total accelerations. It was reported that on the training days of the same well-being level, the jump number values were significantly different. The results suggest that monitoring athletes for the number of accelerations can be used to understand the needs of volleyball players and to improve the design of training and recovery days to optimize athletes’ well-being.
Effective Removal of Methylene Blue on EuVO4/g-C3N4 Mesoporous Nanosheets via Coupling Adsorption and Photocatalysis
Authors: Ran Xia , Wang Li , Xiao Bo , Lei Li , Zhu Jinming , Liu Zuoji , Xi Xiaolan , Feng Guangwei , Li Rong , Feng Jian
Published: September 2022

In this study, we first manufactured ultrathin g-C3N4 (CN) nanosheets by thermal etching and ultrasonic techniques. Then, EuVO4 (EV) nanoparticles were loaded onto CN nanosheets to form EuVO4/g-C3N4 heterojunctions (EVCs). The ultrathin and porous structure of the EVCs increased the specific surface area and reaction active sites. The formation of the heterostructure extended visible light absorption and accelerated the separation of charge carriers. These two factors were advantageous to promote the synergistic effect of adsorption and photocatalysis, and ultimately enhanced the adsorption capability and photocatalytic removal efficiency of methylene blue (MB). EVC-2 (2 wt% of EV) exhibited the highest adsorption and photocatalytic performance. Almost 100% of MB was eliminated via the adsorption–photocatalysis synergistic process over EVC-2. The MB adsorption capability of EVC-2 was 6.2 times that of CN, and the zero-orderreaction rate constant was 5 times that of CN. The MB adsorption on EVC-2 followed the pseudo second-order kinetics model and the adsorption isotherm data complied with the Langmuir isotherm model. The photocatalytic degradation data of MB on EVC-2 obeyed the zero-order kinetics equation in 0–10 min and abided by the first-order kinetics equation for10–30 min. This study provided a promising EVC heterojunctions with superior synergetic effect of adsorption and photocatalysis for the potential application in wastewater treatment.
Comprehensive Transcriptome Analysis of Hair Follicle Morphogenesis Reveals That lncRNA-H19 Promotes Dermal Papilla Cell Proliferation through the Chi-miR-214-3p/β-Catenin Axis in Cashmere Goats
Authors: Zhang Yuelang , Li Fang , Shi Yujie , Zhang Tongtong , Wang Xin
Published: September 2022

Cashmere is initiated and develops in the fetal stages and the number and density of secondary hair follicles (SHFs) determine cashmere production and quality. Growing evidence indicates that both microRNA (miRNA) and long non-coding RNA (lncRNA) play an indispensable role in hair follicle (HF) growth and development. However, little is known about miRNAs, lncRNAs, and their functions as well as their interactions during cashmere initiation and development. Here, based on lncRNA and miRNA high-throughput sequencing and bioinformatics analysis, we identified 10,485 lncRNAs, 40,639 mRNAs, and 605 miRNAs in cashmere goat skin during HF induction, organogenesis, and cytodifferentiation stages. Among them, 521 lncRNAs, 5976 genes, and 204 miRNAs were differentially expressed (DE). KEGG analysis of DE genes indicated that ECM–receptor interaction and biosynthesis of amino acids were crucial for HF development. Notch, TGF-beta, and Wnt signaling pathways were also identified, which are conventional pathways associated with HF growth and development. Then, the ceRNA regulatory network was constructed, and the impact of lncRNA H19 was investigated in dermal papilla (DP) cells. The MTT, CCK-8, and EdU assays showed that the viability and proliferation of DP cells were promoted by H19, and mechanistic studies suggested that H19 performed its function through the chi-miR-214-3p/β-catenin axis. The present study created a resource for lncRNA, miRNA, and mRNA studies in cashmere morphogenesis. It could contribute to a better understanding of the molecular mechanism of ncRNAs involved in the regulation of HF growth and development.
Immunoglobulin Superfamily Containing Leucine-Rich Repeat (Islr) Participates in IL-6-Mediated Crosstalk between Muscle and Brown Adipose Tissue to Regulate Energy Homeostasis
Authors: Liu Chang , Liu Jin , Wang Tongtong , Su Yang , Li Lei , Lan Miaomiao , Yu Yingying , Liu Fan , Xiong Lei , Wang Kun , Chen Meijing , Li Na , Xu Qing , Hu Yue , Jia Yuxin , Meng Qingyong
Published: September 2022

Brown adipose tissue (BAT) is functionally linked to skeletal muscle because both tissues originate from a common progenitor cell, but the precise mechanism controlling muscle-to-brown-fat communication is insufficiently understood. This report demonstrates that the immunoglobulin superfamily containing leucine-rich repeat (Islr), a marker of mesenchymal stromal/stem cells, is critical for the control of BAT mitochondrial function and whole-body energy homeostasis. The mice loss of Islr in BAT after cardiotoxin injury resulted in improved mitochondrial function, increased energy expenditure, and enhanced thermogenesis. Importantly, it was found that interleukin-6 (IL-6), as a myokine, participates in this process. Mechanistically, Islr interacts with NADH: Ubiquinone Oxidoreductase Core Subunit S2 (Ndufs2) to regulate IL-6 signaling; consequently, Islr functions as a brake that prevents IL-6 from promoting BAT activity. Together, these findings reveal a previously unrecognized mechanism for muscle-BAT cross talk driven by Islr, Ndufs2, and IL-6 to regulate energy homeostasis, which may be used as a potential therapeutic target in obesity.