bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of Ferrites Structure by Using a New Core-Less Design Algorithm for Electric Vehicle Wireless Power Transfer
Authors: Chen Kaiwen , Pan Jianfei , Yang Yun , Cheng Ka Wai Eric
Published: May 2021

In order to improve the customers’ continuous usage of electrical vehicles (EVs) and reduce the weight of the energy storage devices, wireless charging technology has been widely studied, updated, and commercialized in recent decades, regarding to its distinct superiority of great convenience and low risk. A higher coupling coefficient is the key factor that impacts the transmission efficiency, thus in most medium-power (hundreds of watts) to high-power (several kilowatts) wireless charging systems, ferrites are used to guide the magnetic flux and intensify the magnetic density. However, the weight of the ferrite itself puts an extra burden on the system, and the core loss during operation also reduces the total efficiency and output power. This paper proposes an optimized design algorithm based on a core-less method for the magnetic core, where the core loss and the coupling coefficient are consequently balanced, and the overall weight and efficiency of the system can be optimized. The iteration procedure is applied on the basis of removed ferrite length and thickness in the algorithm. In the simulation, a square coupler with a total volume of 300 mm × 150 mm, a circular coupler of 150 mm × 150 mm and a Double-D (DD) coupler of 300 mm × 150 mm are used to verify the advantages of the proposed method. The optimized ferrite structures are specific for each coupler shape, and the improvement is proved to be universal in current scale by means of 3-D finite element analysis.
Concepts and Methods to Assess the Dynamic Thermal Rating of Underground Power Cables
Authors: Enescu Diana , Colella Pietro , Russo Angela , Porumb Radu Florin , Seritan George Calin
Published: May 2021

With the increase in the electrical load and the progressive introduction of power generation from intermittent renewable energy sources, the power line operating conditions are approaching the thermal limits. The definition of thermal limits variable in time has been addressed under the concept of dynamic thermal rating (DTR), with which it is possible to provide a more detailed assessment of the line rating and exploit the electrical system more flexibly. Most of the literature on DTR has addressed overhead lines exposed to different weather conditions. The interest in the dynamic thermal rating of power cables is increasing, considering the evolution of computational methods and advanced systems for cable monitoring. This paper contains an overview of the concepts and methods referring to dynamic cable rating (DCR). Starting from the analytical formulations developed many years ago for determining the power cable rating in steady-state conditions, also reported in International Standards, this paper considers the improvements of these formulations proposed during the years. These improvements are leading to include more specific details in the models used for DCR analysis and the computational methods used to assess the power cable’s thermal conditions buried in soil. This paper is focused on highlighting the path from the initial theories and models to the latest literature contributions. Attention is paid to thermal modelling with different levels of detail, applications of 2D and 3D solvers and simplified models, and their validation based on experimental measurements. A salient point of the overview is considering the DCR impact on reliability aspects, risk estimation, real-time calculations, forecasting, and planning with different time horizons.
Adaptive Driving Cycles of EVs for Reducing Energy Consumption
Authors: Komorska Iwona , Puchalski Andrzej , Niewczas Andrzej , Ślęzak Marcin , Szczepański Tomasz
Published: May 2021

A driving cycle is a time series of a vehicle’s speed, reflecting its movement in real road conditions. In addition to certification and comparative research, driving cycles are used in the virtual design of drive systems and embedded control algorithms, traffic management and intelligent road transport (traffic engineering). This study aimed to develop an adaptive driving cycle for a known route to optimize the energy consumption of an electric vehicle and improve the driving range. A novel distance-based adaptive driving cycle method was developed. The proposed algorithm uses the segmentation and iterative synthesis procedures of Markov chains. Energy consumption during driving is monitored on an ongoing basis using Gaussian process regression, and speed and acceleration are corrected adaptively to maintain the planned energy consumption. This paper presents the results of studies of simulated driving cycles and the performance of the algorithm when applied to the real recorded driving cycles of an electric vehicle.
Induced Seismicity and Detailed Fracture Mapping as Tools for Evaluating HDR Reservoir Volume
Authors: Węglińska Elżbieta , Leśniak Andrzej
Published: May 2021

The main goal of this paper was to estimate the heat exchange rock mass volume of a hot dry rock (HDR) geothermal reservoir based on microseismicity location. There are two types of recorded microseismicity: induced by flowing fluid (wet microseismicity) and induced by stress mechanisms (dry microseismicity). In this paper, an attempt was made to extract events associated with the injected fluid flow. The authors rejected dry microseismic events with no hydraulic connection with the stimulated fracture network so as to avoid overestimating the reservoir volume. The proposed algorithm, which includes the collapsing method, automatic cluster detection, and spatiotemporal cluster evolution from the injection well, was applied to the microseismic dataset recorded during stimulation of the Soultz-sous-Forets HDR field in September 1993. The stimulated reservoir volume obtained from wet seismicity using convex hulls is approximately five times smaller than the volume obtained from the primary cloud of located events.
A Comparative Performance Analysis of Counter-Rotating Dual-Rotor Wind Turbines with Speed-Adding Increasers
Authors: Saulescu Radu , Neagoe Mircea , Jaliu Codruta , Munteanu Olimpiu
Published: May 2021

Increasing the efficiency of wind power conversion into electricity poses major challenges to researchers and developers of wind turbines, who are striving for new solutions that can ensure better use of local wind potential in terms of both feasibility and affordability. The paper proposes a novel concept of wind systems with counter-rotating wind rotors that can integrate either conventional or counter-rotating electric generators, by means of the same differential planetary speed increaser, aiming at providing a comparative analysis of the energy performance of counter-rotating wind turbines with counter-rotating vs. conventional electric generators. To this end, a generalized analytical model for angular speeds and torques has been developed, which can be customized for both system configurations. Three numerical simulation scenarios have been contrasted: (a) a scenario with identical wind rotors in both systems, (b) a scenario with the secondary wind rotors being identical in the two applications, but different from the primary rotors, and (c) a scenario with different secondary rotors in the two wind turbines. The results have shown that the wind systems with counter-rotating generator are more efficient and have a higher amplification ratio, compared to systems with conventional generators. In addition, the analyzed wind system with a counter-rotating generator displays better energy performance with low values for output power and ratio of input speeds, whereas the wind turbine with a conventional generator proves to be more efficient in the high-value range of the above-mentioned parameters.
Challenges for Energy Transition in Poverty-Ridden Regions—The Case of Rural Mixteca, Mexico
Authors: Oviedo-Toral Laura-Patricia , François Davi Ezequiel , Poganietz Witold-Roger
Published: May 2021

This paper presents distinct scenario pathways and their storylines resulting from an analysis of interdependencies. We identified the main drivers of a proposed renewable energy transition in rural Mixteca-Puebla, Mexico. By analyzing the main factors involved in alleviating impoverished communities in the rural region, we show the varying degrees to which these drivers influence, support, or hinder a promising energy transition. A Cross-Impact Balance Analysis was conducted to explore the multiple inter-relationships among a set of conditions. This methodology allowed us to evaluate the relationships between social, political, cultural, and environmental variables. The main drivers were identified as clusters of several elements, in which the uncertainties in governance and the legal system trigger the inter-relationship of forces in the area. The focus of this paper is to show how the societal aspects affect the structural energy transformation and its capacity for adaptation in future trends envisioned for the area. This research contributes to the use of technological transformation as a means to alleviate poverty in a rural area. These outcomes give insights regarding the conditions to be considered, in respect to possible–encouraging, but also pessimistic pathways for the region in coming decades.
Rapid Model-Free State of Health Estimation for End-of-First-Life Electric Vehicle Batteries Using Impedance Spectroscopy
Authors: Rastegarpanah Alireza , Hathaway Jamie , Stolkin Rustam
Published: May 2021

The continually expanding number of electric vehicles in circulation presents challenges in terms of end-of-life disposal, driving interest in the reuse of batteries for second-life applications. A key aspect of battery reuse is the quantification of the relative battery condition or state of health (SoH), to inform the subsequent battery application and to match batteries of similar capacity. Impedance spectroscopy has demonstrated potential for estimation of state of health, however, there is difficulty in interpreting results to estimate state of health reliably. This study proposes a model-free, convolutional-neural-network-based estimation scheme for the state of health of high-power lithium-ion batteries based on a dataset of impedance spectroscopy measurements from 13 end-of-first-life Nissan Leaf 2011 battery modules. As a baseline, this is compared with our previous approach, where parameters from a Randles equivalent circuit model (ECM) with and without dataset-specific adaptations to the ECM were extracted from the dataset to train a deep neural network refined using Bayesian hyperparameter optimisation. It is demonstrated that for a small dataset of 128 samples, the proposed method achieves good discrimination of high and low state of health batteries and superior prediction accuracy to the model-based approach by RMS error (1.974 SoH%) and peak error (4.935 SoH%) metrics without dataset-specific model adaptations to improve fit quality. This is accomplished while maintaining the competitive performance of the previous model-based approach when compared with previously proposed SoH estimation schemes.
Fabrication of Photoactive Electrospun Cellulose Acetate Nanofibers for Antibacterial Applications
Authors: Czapka Tomasz , Winkler Angelika , Maliszewska Irena , Kacprzyk Ryszard
Published: May 2021

The aim of the study was to investigate the process of electrostatic fabrication of cellulose acetate (CA) nanofibers containing methylene blue (MB) as a photosensitizer. The electrical, physicochemical, and biocidal properties of the prepared material were given. CA nanofibers were prepared by electrospinning method using a solvent mixture of acetone and distilled water (9:1 vv−1) and different concentrations of CA (i.e., 10–21%). Additionally, methylene blue was implemented into the polymer solution with a CA concentration of 17% to obtain fibers with photo-bactericidal properties. Pure electrospun CA fibers were more uniform than fibers with MB (i.e., ribbon shape). Fiber diameters did not exceed 900 nm for the tested polymer solutions and flow rate below 1.0 mL h−1. The polymer properties (i.e., concentration, resistivity) and other parameters of the process (i.e., flow rate, an applied voltage) strongly influenced the size of the fibers. Plasma treatment of nanofibers resulted in reduced biofilm formation on their surface. The results of photo-bactericidal activity (i.e., up to 180 min) confirmed the high efficiency of inactivation of Staphylococcus aureus cells using fibers containing methylene blue (i.e., with and without plasma treatment). The most effective reduction in the number of biofilm cells was equal to 99.99 ± 0.3%.
Compatibility of 3D-Printed Oxide Ceramics with Molten Chloride Salts for High-Temperature Thermal Energy Storage in Next-Generation CSP Plants
Authors: Ding Wenjin , Shi Yuan , Braun Markus , Kessel Fiona , Frieß Martin , Bonk Alexander , Bauer Thomas
Published: May 2021

Oxide ceramics could be attractive high-temperature construction materials for critical structural parts in high-temperature molten salt thermal energy storage systems due to their excellent corrosion resistance and good mechanical properties. The 3D-printing technology allows the production of ceramic components with highly complex geometries, and therefore extends their applications. In this work, 3D-printed ZrO2 and Al2O3 ceramics were immersed in molten MgCl2/KCl/NaCl under argon or exposed in argon without molten chlorides at 700 °C for 600 h. Their material properties and microstructure were investigated through three-point-bend (3PB) testing and material analysis with SEM-EDX and XRD. The results show that the 3D-printed Al2O3 maintained its mechanical property after exposure in the strongly corrosive molten chloride salt. The 3D-printed ZrO2 had an enhanced 3PB strength after molten salt exposure, whereas no change was observed after exposure in argon at 700 °C. The material analysis shows that some of the ZrO2 on the sample surface changed its crystal structure and shape (T→M phase transformation) after molten salt exposure, which could be the reason for the enhanced 3PB strength. The thermodynamic calculation shows that the T→M transformation could be caused by the reaction of the Y2O3-stabilized ZrO2 with MgCl2 (mainly Y2O3 and ZrO2 with gaseous MgCl2). In conclusion, the 3D-printed ZrO2 and Al2O3 ceramics have excellent compatibility with corrosive molten chlorides at high temperatures and thus show a sound application potential as construction materials for molten chlorides.
Probabilistic Flood Assessment Methodology for Nuclear Power Plants Considering Extreme Rainfall
Authors: Kim Beom-Jin , Kim Minkyu , Hahm Daegi , Park Junhee , Han Kun-Yeun
Published: May 2021

Abnormal weather conditions due to climate change are currently increasing on both global and local scales. It is therefore important to ensure the safety of the areas where major national facilities are located by analyzing risk quantitatively and re-evaluating the existing major facilities, such as nuclear power plants, considering the load and capacity of extreme flood conditions. In this study, a risk analysis method is developed that combines flood hazard curves with fragility curves using hydraulic and hydrological models by GIS tools and the @RISK model for the probabilistic flood analysis of nuclear power plant sites. A two-dimensional (2D) analysis is first carried out to estimate flood depths in various watershed scenarios, and a representative hazard curve for both external and internal flooding is made by applying a verified probability distribution type for the flood watersheds. For the analysis of flooding within buildings, an internal grid is constructed using GIS with related design drawings, and based on the flood depth results of the 2D analysis, a hazard curve for the representative internal inundation using a verified probability distribution type is presented. In the present study, walkdowns with nuclear experts are conducted around the nuclear power plant area to evaluate the fragile structures and facilities under possible flooding. After reviewing the 2D inundation analysis results based on the selected major equipment and facilities, the zones requiring risk assessment are re-assigned. A fragility curve applying probability distribution for the site’s major equipment and facilities is also presented. Failure risk analysis of the major facilities is then conducted by combining the proposed hazard and fragility curves. Results in the form of quantitative values are obtained, and the indicators for risks as well as the reliability and optimal measures to support decision-making are also presented. Through this study, it is confirmed that risk assessment based on the proposed probabilistic flood analysis technique is possible for flood events occurring at nuclear power plant sites.
Methods for Integrating Extraterrestrial Radiation into Neural Network Models for Day-Ahead PV Generation Forecasting
Authors: Jo Seung Chan , Jin Young Gyu , Yoon Yong Tae , Kim Ho Chan
Published: May 2021

Variability, intermittency, and limited controllability are inherent characteristics of photovoltaic (PV) generation that result in inaccurate solutions to scheduling problems and the instability of the power grid. As the penetration level of PV generation increases, it becomes more important to mitigate these problems by improving forecasting accuracy. One of the alternatives to improving forecasting performance is to include a seasonal component. Thus, this study proposes using information on extraterrestrial radiation (ETR), which is the solar radiation outside of the atmosphere, in neural network models for day-ahead PV generation forecasting. Specifically, five methods for integrating the ETR into the neural network models are presented: (1) division preprocessing, (2) multiplication preprocessing, (3) replacement of existing input, (4) inclusion as additional input, and (5) inclusion as an intermediate target. The methods were tested using two datasets in Australia using four neural network models: Multilayer perceptron and three recurrent neural network(RNN)-based models including vanilla RNN, long short-term memory, and gated recurrent unit. It was found that, among the integration methods, including the ETR as the intermediate target improved the mean squared error by 4.1% on average, and by 12.28% at most in RNN-based models. These results verify that the integration of ETR into the PV forecasting models based on neural networks can improve the forecasting performance.
A Synthetic Approach for Datacenter Power Consumption Regulation towards Specific Targets in Smart Grid Environment
Authors: Zhao Mengmeng , Wang Xiaoying
Published: May 2021

With the large-scale grid connection of renewable energy sources, the frequency stability problem of the power system has become increasingly prominent. At the same time, the development of cloud computing and its applications has attracted people’s attention to the high energy consumption characteristics of datacenters. Therefore, it was proposed to use the characteristics of the high power consumption and high flexibility of datacenters to respond to the demand response signal of the smart grid to maintain the stability of the power system. Specifically, this paper establishes a synthetic model that integrates multiple methods to precisely control and regulate the power consumption of the datacenter while minimizing the total adjustment cost. First, according to the overall characteristics of the datacenter, the power consumption models of servers and cooling systems were established. Secondly, by controlling the temperature, different kinds of energy storage devices, load characteristics and server characteristics, the working process of various regulation methods and the corresponding adjustment cost models were obtained. Then, the cost and penalty of each power regulation method were incorporated. Finally, the proposed dynamic synthetic approach was used to achieve the goal of accurately adjusting the power consumption of the datacenter with least adjustment cost. Through comparative analysis of evaluation experiment results, it can be observed that the proposed approach can better regulate the power consumption of the datacenter with lower adjustment cost than other alternative methods.
De-Risking Wood-Based Bioenergy Development in Remote and Indigenous Communities in Canada
Authors: Buss Jennifer , Mansuy Nicolas , Madrali Sebnem
Published: May 2021

Remote and Indigenous communities in Canada have a unique opportunity to mobilize the vast amount of wood-based biomass to meet their energy needs, while supporting a local economy, and reducing greenhouse gas (GHG) emissions. This study realized in collaboration with five remote and Indigenous communities across Canada investigates the main barriers and potential solutions to developing stable and sustainable wood-based bioenergy systems. Our results highlight that despite the differences in available biomass and geographical context, these communities face common policy, economic, operational, cultural, social, and environmental risks and barriers to developing bioenergy. The communities identified and ranked the biggest barriers as follows; the high initial investment of bioenergy projects, the logistical and operational challenges of developing a sustainable wood supply chain in remote locations, and the limited opportunities for community leadership of bioenergy projects. Environmental risks have been ranked as the least important by all the communities, except for the communities in Manitoba, which ranked it as the second most important risk. However, all the communities agreed that climate change is the main environmental driver disturbing the wood-based bioenergy supply chain. To de-risk the wood-based bioenergy system, we suggest that stable and sustainable supply chains can be implemented by restoring community-based resources management supported by local knowledge and workforce. Using local knowledge can also help reduce the impacts caused by biomass harvesting on the ecosystem and avoid competition with traditional land uses. Including positive externalities to cost benefit analysis, when comparing bioenergy systems to existing energy installation, will likely make bioenergy projects more attractive for the community financially. Alternatively, supporting co-learning between partners and among communities can improve knowledge and innovation sharing.
Experimental and Numerical Studies on the Influence of Blade Number in a Small Water Turbine
Authors: Peczkis Grzegorz , Wiśniewski Piotr , Zahorulko Andriy
Published: May 2021

This paper demonstrates the procedure of blade adjustment in a Kaplan-type water turbine, based on calculations of the flow system. The geometrical adjustment of a twisted blade with varying chord length is described in the study. Computational fluid dynamics (CFD) analysis was used to characterise aerofoil and turbine performance. Furthermore, two turbines, with a different number of blades, were designed, manufactured, and tested experimentally. The numerical model results were then compared with the experimental data. The studies were carried out with different rotational velocities and different stator blade incidence angles. The paper shows a comparison of the turbine efficiencies that were assessed, using numerical and experimental methods, of a flow system with four- and five-bladed rotors. The numerical model results matched up well with those of the experimental study. The efficiency of the proposed turbines reached up to 72% and 84% for four-bladed and five-bladed designs, respectively. These efficiencies, when considered with the turbine’s simplicity, low production and maintenance costs, as well as their potential for harvesting energy from low energy flows, mean that Kaplan turbines provide a promising technology for processing renewable energy.
Optimization of Design Variables of a Phase Change Material Storage Tank and Comparison of a 2D Implicit vs. 2D Explicit Model
Authors: Crespo Alicia , Zsembinszki Gabriel , Vérez David , Borri Emiliano , Fernández Cèsar , Cabeza Luisa F. , de Gracia Alvaro
Published: May 2021

In this study, a thermal energy storage tank filled with commercial phase change material flat slabs is investigated. The tank provides heat at around 15 °C to the evaporator of a seasonal thermal energy storage system developed under the EU-funded project SWS-Heating. A 2D numerical model of the phase changed material storage tank based on the finite control volume approach was developed and validated with experimental data. Based on the validated model, an optimization was performed to identify the number, type and configuration of slabs. The final goal of the phase change material tank model is to be implemented into the whole generic heating system model. A trade-off between results’ accuracy and computational time of the phase change material model is needed. Therefore, a comparison between a 2D implicit and 2D explicit scheme of the model was performed. The results showed that using an explicit scheme instead of an implicit scheme with a reasonable number of nodes (15 to 25) in the heat transfer fluid direction allowed a considerable decrease in the computational time (7 times for the best case) with only a slight reduction in the accuracy in terms on mean average percentage error (0.44%).
Performance Analysis of High-Speed Electric Machines Supplied by PWM Inverters Based on the Harmonic Modeling Method
Authors: Merdžan Marko
Published: May 2021

This paper presents a method for the performance analysis of high-speed electric machines supplied with pulse-width modulated voltage source inverters by utilizing a fast analytical model. By applying a strict mathematical procedure, effective expressions for the calculation of rotor eddy current losses and electromagnetic torque are derived. Results obtained by the approach suggested in this study are verified by the finite element model, and it is shown that the proposed method is superior in comparison to the finite element method in terms of computation time. The proposed method enables fast parameter variation analysis, which is demonstrated by changing the inverter switching frequency and electric conductivity of the rotor and analyzing the effects of these changes on rotor eddy current losses. The presented work separately models effects of the permanent magnet and pulse-width modulated stator currents, making it suitable for the analysis of both high-speed permanent magnet machines and high-speed induction machines.
Influencing Factors of Performance Degradation of Zinc–Air Batteries Exposed to Air
Authors: Zhong Yuwei , Liu Bin , Zhao Zequan , Shen Yuanhao , Liu Xiaorui , Zhong Cheng
Published: May 2021

Zinc–air batteries feature high energy density, but they usually suffer from their short storage life after they start working, restricting their commercial applications. In the past, scholars did not reach an agreement on the influencing factors of the performance degradation of zinc–air batteries when exposed to air. Here, a series of comparative experiments were conducted to confirm the changes of the battery during storage after being exposed to air. The morphology and composition of the components of the battery were characterized by scanning electron microscopy (SEM) and X-ray diffraction analyses. SEM images revealed that with the increase of storage days, the corrosion of the zinc anode gradually deepens, but the surface morphology of the air cathode does not change much. The electrolyte of the batteries stored for different periods was examined through inductively coupled plasma spectroscopy and titration. After 20 days of storage, the concentration of CO32− reached 2.694 mol L−1, which indicates that more than 80% of the OH− in the electrolyte was consumed. The results show that after being exposed to air, the carbonation of the electrolyte is the main cause of the battery capacity decay.
Price Leadership and Volatility Linkages between Oil and Renewable Energy Firms during the COVID-19 Pandemic
Authors: De Blasis Riccardo , Petroni Filippo
Published: May 2021

The COVID-19 pandemic is having a strong influence in all areas of society, like wealth, economy, travel, lifestyle habits, and, amongst many others, financial and energy markets. The influence in standard energies, like crude oil, and renewable energies markets has been twofold: from one side, the predictability of volatility has strongly decreased; secondly, the linkages of the price time series have been modified. In this paper, by using DCC-GARCH and Price Leadership Share methodology, we can investigate the changes in the influences between standard energies and renewable energies markets by analyzing one-minute time series of West Texas Intermediate crude oil futures contract (WTI), the Brent crude oil futures contract (BRENT), the STOXX Europe 600 oil & gas index (SXEV), and the European renewable energy index (ERIX). Our results confirm volatility spillover between the time series. However, when assessing the accuracy of the predictability of the DCC-GARCH model, the results show that the model fails its prediction in the period of higher instability. Besides, we found that price leadership has been strongly influenced by the virus spreading stages. These results have been obtained by dividing the period between September 2019 and January 2021 into 6 subperiods according to the pandemic stages.
Definition of the Future Skills Needs of Job Profiles in the Renewable Energy Sector
Authors: Arcelay Irene , Goti Aitor , Oyarbide-Zubillaga Aitor , Akyazi Tugce , Alberdi Elisabete , Garcia-Bringas Pablo
Published: May 2021

The growth of the renewable energy industry is happening at a swift pace pushed, by the emergence of Industry 4.0. Smart technologies like artificial intelligence (AI), Big Data, the Internet of Things (IoT), Digital Twin (DT), etc. enable companies within the sector of renewable energies to drastically improve their operations. In this sectoral context, where upgraded sustainability standards also play a vital role, it is necessary to fulfil the human capital requirements of the imminent technological advances. This article aims to determine the current skills of the renewable energy industry workforce and to predict the upcoming skill requirements linked to a digital transition by creating a unified database that contains both types of skills. This will serve as a tool for renewable energy businesses, education centers, and policymakers to plan the training itinerary necessary to close the skills gap, as part of the sectoral strategy to achieve a competent future workforce.
Numerical Study of Elasto-Plastic Hydraulic Fracture Propagation in Deep Reservoirs Using a Hybrid EDFM–XFEM Method
Authors: Liu Wenzheng , Zeng Qingdong , Yao Jun , Liu Ziyou , Li Tianliang , Yan Xia
Published: May 2021

Rock yielding may well take place during hydraulic fracturing in deep reservoirs. The prevailing models based on the linear elastic fracture mechanics (LEFM) are incapable of describing the evolution process of hydraulic fractures accurately. In this paper, a hydro-elasto-plastic model is proposed to investigate the hydraulic fracture propagation in deep reservoirs. The Drucker–Prager plasticity model, Darcy’s law, cubic law and cohesive zone model are employed to describe the plastic deformation, matrix flow, fracture flow and evolution of hydraulic fractures, respectively. Combining the embedded discrete fracture model (EDFM), extended finite element method (XFEM) and finite volume method, a hybrid numerical scheme is presented to carry out simulations. A dual-layer iterative procedure is developed based on the fixed-stress split method, Picard iterative method and Newton–Raphson iterative method. The iterative procedure is used to deal with the coupling between nonlinear deformation with fracture extension and fluid flow. The proposed model is verified against analytical solutions and other numerical simulation results. A series of numerical cases are performed to investigate the influences of rock plasticity, internal friction angle, dilatancy angle and permeability on hydraulic fracture propagation. Finally, the proposed model is extended to simulate multiple hydraulic fracture propagation. The result shows that plastic deformation can enhance the stress-shadowing effect.
A Method for Battery Health Estimation Based on Charging Time Segment
Authors: Liu Shao-Xun , Zhou Ya-Fu , Liu Yan-Liang , Lian Jing , Huang Li-Jian
Published: May 2021

The problem of low accuracy and low convenience in the existing state of health (SOH) estimation method for vehicle lithium-ion batteries has become one of the important problems in the electric vehicle field. This paper proposes an improved cuckoo search particle filter (ICS-PF) algorithm based on a charging time segment from equal voltage data to estimate battery health status. Appropriate voltage ranges of charging time segments are selected according to the battery charging law, and in the meantime, the charging time segments are collected as a health indicator to establish the corresponding relationship with battery capacity attenuation value. An improved cuckoo search particle filter algorithm based on the traditional particle filter (PF) and cuckoo search (CS) algorithm is proposed by enhancing the search step size and discovery probability to estimate the capacity attenuation. The estimation result shows that this method is superior to the traditional particle filter and cuckoo search particle filter (CS-PF) method, as the maximum estimation error is less than 2%.
Numerical Study on the Effect of the Pipe Groove Height and Pitch on the Flow Characteristics of Corrugated Pipe
Authors: Hong Ki-Bea , Kim Dong-Woo , Kwark Jihyun , Nam Jun-Seok , Ryou Hong-Sun
Published: May 2021

For corrugated pipes with a square groove, it is known that there is no interaction between the main flow and groove flow when the aspect ratio is less than four. When the groove length and height are different, the interaction occurs in the pipe. In previous studies, it was investigated whether this interaction is dependent on groove length. However, when changing the groove height, the shape of the vortex generated inside the groove changes, which may cause the interaction to occur. Therefore, in this paper the interaction between the main and groove flow of corrugated pipes is investigated when changing both groove height as well as groove pitch, corresponding to an aspect ratio of less than four. For the groove height, the flow out of the groove after impingement changes with the shape of the secondary vortex in the groove. This flow deforms the velocity distribution in the main flow, and thus the friction factor is different. For the groove pitch, there is no difference in v-velocity distribution at the interface at the 5th and 20th groove. This means there is no interaction between the grooves, and, the friction factor differs as the number of grooves differs.
Early-Life Exposure to Environmental Contaminants Perturbs the Sperm Epigenome and Induces Negative Pregnancy Outcomes for Three Generations via the Paternal Lineage
Authors: Maurice Clotilde , Dalvai Mathieu , Lambrot Romain , Deschênes Astrid , Scott-Boyer Marie-Pier , McGraw Serge , Chan Donovan , Côté Nancy , Ziv-Gal Ayelet , Flaws Jodi A. , Droit Arnaud , Trasler Jacquetta , Kimmins Sarah , Bailey Janice L.
Published: May 2021

Due to the grasshopper effect, the Arctic food chain in Canada is contaminated with persistent organic pollutants (POPs) of industrial origin, including polychlorinated biphenyls and organochlorine pesticides. Exposure to POPs may be a contributor to the greater incidence of poor fetal growth, placental abnormalities, stillbirths, congenital defects and shortened lifespan in the Inuit population compared to non-Aboriginal Canadians. Although maternal exposure to POPs is well established to harm pregnancy outcomes, paternal transmission of the effects of POPs is a possibility that has not been well investigated. We used a rat model to test the hypothesis that exposure to POPs during gestation and suckling leads to developmental defects that are transmitted to subsequent generations via the male lineage. Indeed, developmental exposure to an environmentally relevant Arctic POPs mixture impaired sperm quality and pregnancy outcomes across two subsequent, unexposed generations and altered sperm DNA methylation, some of which are also observed for two additional generations. Genes corresponding to the altered sperm methylome correspond to health problems encountered in the Inuit population. These findings demonstrate that the paternal methylome is sensitive to the environment and that some perturbations persist for at least two subsequent generations. In conclusion, although many factors influence health, paternal exposure to contaminants plays a heretofore-underappreciated role with sperm DNA methylation contributing to the molecular underpinnings involved.
Socio-Economic Analysis of Wood Charcoal Production as a Significant Output of Forest Bioeconomy in Africa
Authors: Nyarko Isaac , Nwaogu Chukwudi , Miroslav Hájek , Peseu Prince Opoku
Published: May 2021

Wood charcoal (WCH) is a sustainable biofuel for rural and urban users because of its higher energy density and emission of marginal smoke when compared with firewood. Besides helping the poor majority who cannot afford kerosene, electricity or liquid petroleum gas (LPG), WCH is a key source of income and livelihood. This work aimed at quantifying the volume of WCH production as well as appraising its socio-economics, including environmental impacts, especially the impact of long-term deforestation and forest degradation in Africa. Historically robust data from the databases of UN-FAO, FAOSTAT, International Energy Agency (IEA), United Nations Statistics Division, UN-DESA energy statistics yearbook, and the Forest Resources Assessment (FRA) were used. The data analysis involved descriptive statistics, multivariate analysis, and geospatial techniques. The result revealed that East Africa had the highest average wood charcoal production which was 32,058,244 tonnes representing 43.2% of the production whereas West Africa had 23,831,683 tonnes denoting 32.1%. Others were North Africa (8,650,207 tonnes), Middle Africa (8,520,329 tonnes), and South Africa (1,225,062 tonnes) representing 11.6%, 11.5% and 1.6% respectively. The correlation matrix showed that WCH production for the three decades had a significant positive correlation with all the measured parameters (such as areas of forest cover, export quantity, export value, GDP, human population, climate season, average income per citizen, and literacy rate). Wood charcoal is an essential livelihood support system. New policies including commercial wood charcoal production and licensing for revenue and ecological sustainability are required. Enterprise-based approaches for poverty reduction, smallholders’ tree-growing, wood charcoal-energy conserving technologies, improved electricity supply and agricultural productivity are encouraged. The novelty of this study can also be explained by the diverse parameters examined in relation to WCH production which no other studies in the region have done.
Genome-Wide Variation in DNA Methylation Predicts Variation in Leaf Traits in an Ecosystem-Foundational Oak Species
Authors: Browne Luke , MacDonald Brandon , Fitz-Gibbon Sorel , Wright Jessica W. , Sork Victoria L.
Published: May 2021

Epigenetic modifications such as DNA methylation are a potential mechanism for trees to respond to changing environments. However, it remains controversial the extent to which DNA methylation impacts ecologically important traits that influence fitness. In this study, we used reduced-representation bisulfite sequencing to associate genomic and epigenomic variation with seven phenotypic traits related to growth, leaf function, and disease susceptibility in 160 valley oak (Quercus lobata) saplings planted across two common gardens in California. We found that DNA methylation was associated with a significant fraction of phenotypic variance in plant height, leaf lobedness, powdery mildew infection, and trichome density. Two of the seven traits were significantly associated with DNA methylation in the CG context, three traits were significantly associated with CHG methylation, and two traits were significantly associated with CHH methylation. Notably, controlling for genomic variation in SNPs generally reduced the amount of trait variation explained by DNA methylation. Our results suggest that DNA methylation may serve as a useful biomarker to predict phenotypic variation in trees, though it remains unclear the degree to which DNA methylation is a causal mechanism driving phenotypic variation in forest tree species.
Modelling Shifts and Contraction of Seed Zones in Two Mexican Pine Species by Using Molecular Markers
Authors: Simental-Rodriguez Sergio Leonel , Pérez-Luna Alberto , Hernández-Díaz José Ciro , Jaramillo-Correa Juan Pablo , López-Sánchez Carlos A. , Flores-Rentería Lluvia , Carrillo-Parra Artemio , Wehenkel Christian
Published: May 2021

A seed zone or provenance region is an area within which plants can be moved with little risk of maladaptation because of the low environmental variation. Delineation of seed zones is of great importance for commercial plantations and reforestation and restoration programs. In this study, we used AFLP markers associated with environmental variation for locating and delimiting seed zones for two widespread and economically important Mexican pine species (Pinus arizonica Engelm. and P. durangensis Martínez), both based on recent climate conditions and under a predicted climate scenario for 2030 (Representative Concentration Pathway of ~4.5 Wm−2). We expected to observe: (i) associations between seed zones and local climate, soil and geographical factors, and (ii) a meaning latitudinal shift of seed zones, along with a contraction of species distributions for the period 1990–2030 in a northward direction. Some AFLP outliers were significantly associated with spring and winter precipitation, and with phosphorus concentration in the soil. According to the scenario for 2030, the estimated species and seed zone distributions will change both in size and position. Our modeling of seed zones could contribute to reducing the probabilities of maladaptation of future reforestations and plantations with the pine species studied.
A Comparison of Three Circular Mitochondrial Genomes of Fagus sylvatica from Germany and Poland Reveals Low Variation and Complete Identity of the Gene Space
Authors: Mishra Bagdevi , Ulaszewski Bartosz , Meger Joanna , Ploch Sebastian , Burczyk Jaroslaw , Thines Marco
Published: May 2021

Similar to chloroplast loci, mitochondrial markers are frequently used for genotyping, phylogenetic studies, and population genetics, as they are easily amplified due to their multiple copies per cell. In a recent study, it was revealed that the chloroplast offers little variation for this purpose in central European populations of beech. Thus, it was the aim of this study to elucidate, if mitochondrial sequences might offer an alternative, or whether they are similarly conserved in central Europe. For this purpose, a circular mitochondrial genome sequence from the more than 300-year-old beech reference individual Bhaga from the German National Park Kellerwald-Edersee was assembled using long and short reads and compared to an individual from the Jamy Nature Reserve in Poland and a recently published mitochondrial genome from eastern Germany. The mitochondrial genome of Bhaga was 504,730 bp, while the mitochondrial genomes of the other two individuals were 15 bases shorter, due to seven indel locations, with four having more bases in Bhaga and three locations having one base less in Bhaga. In addition, 19 SNP locations were found, none of which were inside genes. In these SNP locations, 17 bases were different in Bhaga, as compared to the other two genomes, while 2 SNP locations had the same base in Bhaga and the Polish individual. While these figures are slightly higher than for the chloroplast genome, the comparison confirms the low degree of genetic divergence in organelle DNA of beech in central Europe, suggesting the colonisation from a common gene pool after the Weichsel Glaciation. The mitochondrial genome might have limited use for population studies in central Europe, but once mitochondrial genomes from glacial refugia become available, it might be suitable to pinpoint the origin of migration for the re-colonising beech population.
Field Testing of Selected Salt-Tolerant Screened Balsam Poplar (Populus balsamifera L.) Clones for Use in Reclamation around End-Pit Lakes Associated with Bitumen Extraction in Northern Alberta
Authors: Hu Yue , Kamelchuk David , Krygier Richard , Thomas Barb R.
Published: May 2021

For the oil sands mine sites in northern Alberta, the presence of salty process affected water, a byproduct of the hot-water bitumen extraction process, is anticipated to pose a challenge on some reconstructed landforms. The fundamental challenge when re-vegetating these sites is to ensure not only survival, but vigorous growth where plants are subjected to conditions of high electrical conductivity owing to salts in process affected water that may be contained in the substrate. Finding plants suitable for high salt conditions has offered the opportunity for Alberta-Pacific Forest Industries Inc. (Al-Pac) to investigate the potential role of using native balsam poplar (Populus balsamifera L.) as a key reclamation species for the oil sands region. Two years of greenhouse screening (2012 and 2013) of 222 balsam poplar clones from Al-Pac’s balsam poplar tree improvement program, using process affected discharge water from an oil sands processing facility in Ft. McMurray, has suggested an opportunity to select genetically suitable native clones of balsam poplar for use in reclamation of challenging sites affected by process water. In consideration of the results from both greenhouse and field testing, there is an opportunity to select genetically suitable native clones of balsam poplar that are tolerant to challenging growing conditions, making them more suitable for planting on saline sites.