bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Necklace-Type Distribution of SiC Particles on Dry Sliding Wear Behavior of As-Cast AZ91D/SiCp Composites
Authors: Sun Chao , Lu Nannan , Liu Huan , Wang Xiaojun , Hu Xiaoshi , Chen Deqiang
Published: April 2020

In this study, the dry sliding wear behaviors of SiC particle reinforced AZ91D matrix composites fabricated by stirring casting method were systematically investigated. The SiC particles in as-cast composites exhibited typical necklace-type distribution, which caused the weak interface bonding between SiC particles and matrix in particle-segregated zones. During dry sliding at higher applied loads, SiC particles were easy to debond from the matrix, which accelerated the wear rates of the composites. While at the lower load of 10 N, the presence of SiC particles improved the wear resistance. Moreover, the necklace-type distribution became more evident with the decrease of particle sizes and the increase of SiC volume fractions. Larger particles had better interface bonding with the matrix, which could delay the transition of wear mechanism from oxidation to delamination. Therefore, composites reinforced by larger SiC particles exhibited higher wear resistance. Similarly, owing to more weak interfaces in the composites with high content of SiC particles, more severe delamination occurred and the wear resistance of the composites was impaired.
Morphological Patterns of Sarcoidosis and Clinical Outcome: Retrospective Analysis through a Multidisciplinary Approach
Authors: Distefano Giulio , Vancheri Ada , Palermo Monica , Tiralongo Francesco , Foti Pietro Valerio , Mauro Letizia Antonella , Vancheri Carlo , Basile Antonio , Palmucci Stefano
Published: April 2020

The aim of this work was to verify the correlations between different pulmonary morphological patterns and functional outcomes in sarcoidosis patients, using a validated score for the comparison between the high-resolution computed tomography (HRCT) of patients belonging to different imaging patterns. From the electronic database of the reference center for interstitial lung diseases of our University Hospital, we retrospectively selected 55 patients with a diagnosis of sarcoidosis according to the American Thoracic Society (ATS) criteria; we evaluated the initial HRCT examination and pulmonary function tests collected at baseline and after a year. Patients were divided into typical (48% of patients) and atypical (52%) HRCT patterns, and a computer tomography activity score (CTAS) was associated with each HRCT appearance detected; clinical history, impact of therapy, and extra-thoracic locations were also considered. We found that worsening of diffusing capacity for carbon monoxide (DLCO) is related to the CTAS (r = −0.20, p = 0.01), and there was an inverse correlation between the variation of forced vital capacity (FVC) and the value of the CTAS (r = −0.30, p = 0.23) in the subgroup of patients with atypical patterns. CTAS were higher in patients with extra-pulmonary localizations (p = 0.05) and the subgroup of patients with extra-thoracic locations and atypical manifestations had a greater worsening in terms of variation of FVC (p = 0.03) and DLCO% (p = 0.04). No difference between treated and untreated patients was found.
Liquid Biopsy as Novel Tool in Precision Medicine: Origins, Properties, Identification and Clinical Perspective of Cancer’s Biomarkers
Authors: Fernández-Lázaro Diego , García Hernández Juan Luis , García Alberto Caballero , Córdova Martínez Alfredo , Mielgo-Ayuso Juan , Cruz-Hernández Juan Jesús
Published: April 2020

In recent years, there has been an increase in knowledge of cancer, accompanied by a technological development that gives rise to medical oncology. An instrument that allows the implementation of individualized therapeutic strategies is the liquid biopsy. Currently, it is the most innovative methodology in medical oncology. Its high potential as a tool for screening and early detection, the possibility of assessing the patient’s condition after diagnosis and relapse, as well as the effectiveness of real-time treatments in different types of cancer. Liquid biopsy is capable of overcoming the limitations of tissue biopsies. The elements that compose the liquid biopsy are circulating tumor cells, circulating tumor nucleic acids, free of cells or contained in exosomes, microvesicle and platelets. Liquid biopsy studies are performed on various biofluids extracted in a non-invasive way, and they can be performed both from the blood and in urine, saliva or cerebrospinal fluid. The development of genotyping techniques, using the elements that make up liquid biopsy, make it possible to detect mutations, intertumoral and intratumoral heterogeneity, and provide molecular information on cancer for application in medical oncology in an individualized way in different types of tumors. Therefore, liquid biopsy has the potential to change the way medical oncology could predict the course of the disease.
Fifteen Years of Gene Set Analysis for High-Throughput Genomic Data: A Review of Statistical Approaches and Future Challenges
Authors: Das Samarendra , McClain Craig J. , Rai Shesh N.
Published: April 2020

Over the last decade, gene set analysis has become the first choice for gaining insights into underlying complex biology of diseases through gene expression and gene association studies. It also reduces the complexity of statistical analysis and enhances the explanatory power of the obtained results. Although gene set analysis approaches are extensively used in gene expression and genome wide association data analysis, the statistical structure and steps common to these approaches have not yet been comprehensively discussed, which limits their utility. In this article, we provide a comprehensive overview, statistical structure and steps of gene set analysis approaches used for microarrays, RNA-sequencing and genome wide association data analysis. Further, we also classify the gene set analysis approaches and tools by the type of genomic study, null hypothesis, sampling model and nature of the test statistic, etc. Rather than reviewing the gene set analysis approaches individually, we provide the generation-wise evolution of such approaches for microarrays, RNA-sequencing and genome wide association studies and discuss their relative merits and limitations. Here, we identify the key biological and statistical challenges in current gene set analysis, which will be addressed by statisticians and biologists collectively in order to develop the next generation of gene set analysis approaches. Further, this study will serve as a catalog and provide guidelines to genome researchers and experimental biologists for choosing the proper gene set analysis approach based on several factors.
Perceptions of ICT Practitioners Regarding Software Privacy
Authors: Dias Canedo Edna , Toffano Seidel Calazans Angelica , Toffano Seidel Masson Eloisa , Teixeira Costa Pedro Henrique , Lima Fernanda
Published: April 2020

During software development activities, it is important for Information and Communication Technology (ICT) practitioners to know and understand practices and guidelines regarding information privacy, as software requirements must comply with data privacy laws and members of development teams should know current legislation related to the protection of personal data. In order to gain a better understanding on how industry ICT practitioners perceive the practical relevance of software privacy and privacy requirements and how these professionals are implementing data privacy concepts, we conducted a survey with ICT practitioners from software development organizations to get an overview of how these professionals are implementing data privacy concepts during software design. We performed a systematic literature review to identify related works with software privacy and privacy requirements and what methodologies and techniques are used to specify them. In addition, we conducted a survey with ICT practitioners from different organizations. Findings revealed that ICT practitioners lack a comprehensive knowledge of software privacy and privacy requirements and the Brazilian General Data Protection Law (Lei Geral de Proteção de Dados Pessoais, LGPD, in Portuguese), nor they are able to work with the laws and guidelines governing data privacy. Organizations are demanded to define an approach to contextualize ICT practitioners with the importance of knowledge of software privacy and privacy requirements, as well as to address them during software development, since LGPD must change the way teams work, as a number of features and controls regarding consent, documentation, and privacy accountability will be required.
Dynamic Shear Deformation of a Precipitation Hardened Al0.7CoCrFeNi Eutectic High-Entropy Alloy Using Hat-Shaped Specimen Geometry
Authors: Gwalani Bharat , Wang Tianhao , Jagetia Abhinav , Gangireddy Sindhura , Muskeri Saideep , Mukherjee Sundeep , Lloyd Jeffrey T. , Banerjee Rajarshi , Mishra Rajiv S.
Published: April 2020

Lamellar eutectic structure in Al0.7CoCrFeNi high-entropy alloy (HEA) is emerging as a promising candidate for structural applications because of its high strength-ductility combination. The alloy consists of a fine-scale lamellar fcc + B2 microstructure with high flow stresses > 1300 MPa under quasi-static tensile deformation and >10% ductility. The response to shear loading was not investigated so far. This is the first report on the shear deformation of a eutectic structured HEA and effect of precipitation on shear deformation. A split-Hopkinson pressure bar (SHPB) was used to compress the hat-shaped specimens to study the local dynamic shear response of the alloy. The change in the width of shear bands with respect to precipitation and deformation rates was studied. The precipitation of L12 phase did not delay the formation of adiabatic shear bands (ASB) or affect the ASB width significantly, however, the deformed region around ASB, consisting of high density of twins in fcc phase, was reduced from 80 µm to 20 µm in the stronger precipitation strengthened condition. We observe dynamic recrystallization of grains within ASBs and local mechanical response of individual eutectic lamellae before and after shear deformation and within the shear bands was examined using nano-indentation.
Preface of Special Issue “Cares in the Age of Communication: Health Education and Healthy Lifestyles”: Social Media and Health Communication in a Pandemic?
Authors: Herrera-Peco Iván , de la Torre-Montero Julio C.
Published: April 2020

In the midst and the mist of the Covid-19 outbreak, we are living in the age of global communication in a hyperconnected society in which the transmissions channels between people have been changed very clearly due to both the internet itself in general and social networks in particular [...]
Scaled GaN-HEMT Large-Signal Model Based on EM Simulation
Authors: Lee Wooseok , Kang Hyunuk , Choi Seokgyu , Lee Sangmin , Kwon Hosang , Hwang Keum cheol , Lee Kang-Yoon , Yang Youngoo
Published: April 2020

This paper presents a scaled GaN-HEMT large-signal model based on EM simulation. A large-signal model of the 10-finger GaN-HEMT consists of a large-signal model of the two-finger GaN-HEMT and an equivalent circuit of the interconnection circuit. The equivalent circuit of the interconnection circuit was extracted according to the EM simulation results. The large-signal model for the two-finger device is based on the conventional Angelov channel current model. The large-signal model for the 10-finger device was verified through load-pull measurement. The 10-finger GaN-HEMT produced an output power of about 20 W for both simulation and load-pull measurements.
Fluid Selection of Transcritical Rankine Cycle for Engine Waste Heat Recovery Based on Temperature Match Method
Authors: Wang Zhijian , Tian Hua , Shi Lingfeng , Shu Gequn , Kong Xianghua , Li Ligeng
Published: April 2020

Engines waste a major part of their fuel energy in the jacket water and exhaust gas. Transcritical Rankine cycles are a promising technology to recover the waste heat efficiently. The working fluid selection seems to be a key factor that determines the system performances. However, most of the studies are mainly devoted to compare their thermodynamic performances of various fluids and to decide what kind of properties the best-working fluid shows. In this work, an active working fluid selection instruction is proposed to deal with the temperature match between the bottoming system and cold source. The characters of ideal working fluids are summarized firstly when the temperature match method of a pinch analysis is combined. Various selected fluids are compared in thermodynamic and economic performances to verify the fluid selection instruction. It is found that when the ratio of the average specific heat in the heat transfer zone of exhaust gas to the average specific heat in the heat transfer zone of jacket water becomes higher, the irreversibility loss between the working fluid and cold source is improved. The ethanol shows the highest net power output of 25.52 kW and lowest electricity production cost of $1.97/(kWh) among candidate working fluids.
Market Trading Model of Urban Energy Internet Based on Tripartite Game Theory
Authors: Liu Jun , Chen Jinchun , Wang Chao , Chen Zhang , Liu Xinglei
Published: April 2020

As an important driving force to promote the energy revolution, the emergence of the energy internet has provided new ideas for the marketization and flexibility of multi-energy transactions. How to realize multi-energy joint trading is a key issue in the development of the energy market. An urban energy internet market trading model among energy suppliers, energy service providers and the large users in the urban area, based on tripartite game theory, is established in this paper. Considering the cost–income function of each market entity and the basic market trading mechanism, a new game-tree search method is proposed to solve the Nash equilibria for the game model. The Nash equilibria of the tripartite game can be obtained, and the market transaction status corresponding to the Nash equilibria is analyzed from the perspective of the market transactions. The multi-energy joint transaction and market equilibria can be easily implemented for the bids and offers of the multiple energy entities in the urban energy internet market.
Configurable DDS as Uniform Middleware for Data Communication in Smart Grids
Authors: Alaerjan Alaa , Kim Dae-Kyoo , Ming Hua , Kim Hwimin
Published: April 2020

Data Distribution Service (DDS) has emerged as a potential solution for data communication challenges in smart grids. DDS is designed to support quality communication for large scale real-time systems through a wide range of QoS policies. However, a smart grid involves various types of communication applications running on different computing environments. Some environments have limited computing resources such as small memory and low performance, which makes it difficult to accommodate DDS. In this paper, we present a feature-based approach for tailoring DDS to configure lightweight DDS by selecting only the necessary features for the application in consideration of the resource constraints of its running environment. This allows DDS to serve as a uniform communication middleware across the smart grid, which is critical for interoperability. We analyze DDS in terms of features and design them using Unified Modeling Language (UML) and Object Constraint Language (OCL) based on inheritance and overriding. We define a formal notion of feature composition to build DDS configurations. We implemented the approach in OpenDDS and demonstrate its application to different application environments. We also experimented the approach for the efficiency of configured DDS in terms of resource utilization. The results show that configured DDS is viable for efficient and quality data communication for applications that run on an environment with limited computing capability.
Discrete Element Method Investigation of Binary Granular Flows with Different Particle Shapes
Authors: Liu Yi , Yu Zhaosheng , Yang Jiecheng , Wassgren Carl , Curtis Jennifer Sinclair , Guo Yu
Published: April 2020

The effects of particle shape differences on binary mixture shear flows are investigated using the Discrete Element Method (DEM). The binary mixtures consist of frictionless rods and disks, which have the same volume but significantly different shapes. In the shear flows, stacking structures of rods and disks are formed. The effects of the composition of the mixture on the stacking are examined. It is found that the number fraction of stacking particles is smaller for the mixtures than for the monodisperse rods and disks. For binary mixtures with small particle shape differences, the mixture stresses are bounded by the stresses of the two corresponding monodisperse systems. However, for binary mixtures with large particle shape differences, the stresses of the mixtures can be larger than the stresses of the monodisperse systems at large solid volume fractions because larger differences in particle shape cause geometrical interference in packing, leading to stronger particle–particle interactions in the flow. The stresses in dense binary mixtures are found to be exponential functions of the order parameter, which is a measure of particle alignment. Based on the simulation results, an empirical expression for the bulk friction coefficient (ratio of the shear stress to normal stress) for dense binary flows is proposed by accounting for the effects of particle alignment and solid volume fraction.
A Hybrid Methodology to Study Stakeholder Cooperation in Circular Economy Waste Management of Cities
Authors: Palafox-Alcantar P. Giovani , Hunt Dexter V. L. , Rogers Chris D. F.
Published: April 2020

Successful transitioning to a circular economy city requires a holistic and inclusive approach that involves bringing together diverse actors and disciplines who may not have shared aims and objectives. It is desirable that stakeholders work together to create jointly-held perceptions of value, and yet cooperation in such an environment is likely to prove difficult in practice. The contribution of this paper is to show how collaboration can be engendered, or discord made transparent, in resource decision-making using a hybrid Game Theory approach that combines its inherent strengths with those of scenario analysis and multi-criteria decision analysis. Such a methodology consists of six steps: (1) define stakeholders and objectives; (2) construct future scenarios for Municipal Solid Waste Management; (3) survey stakeholders to rank the evaluation indicators; (4) determine the weights for the scenarios criteria; (5) reveal the preference order of the scenarios; and (6) analyse the preferences to reveal the cooperation and competitive opportunities. To demonstrate the workability of the method, a case study is presented: The Tyseley Energy Park, a major Energy-from-Waste facility that treats over two-thirds of the Municipal Solid Waste of Birmingham in the UK. The first phase of its decision-making involved working with the five most influential actors, resulting in recommendations on how to reach the most preferred and jointly chosen sustainable scenario for the site. The paper suggests a supporting decision-making tool so that cooperation is embedded in circular economy adoption and decisions are made optimally (as a collective) and are acceptable to all the stakeholders, although limited by bounded rationality.
An Assessment of Wind Energy Potential for the Three Topographic Regions of Eritrea
Authors: Negash Teklebrhan , Möllerström Erik , Ottermo Fredric
Published: April 2020

This paper presents the wind energy potential and wind characteristics for 25 wind sites in Eritrea, based on wind data from the years 2000–2005. The studied sites are distributed all over Eritrea, but can roughly be divided into three regions: coastal region, western lowlands, and central highlands. The coastal region sites have the highest potential for wind power. An uncertainty, due to extrapolating the wind speed from the 10-m measurements, should be noted. The year to year variations are typically small and, for the sites deemed as suitable for wind power, the seasonal variations are most prominent in the coastal region with a peak during the period November–March. Moreover, Weibull parameters, prevailing wind direction, and wind power density recalculated for 100 m above ground are presented for all 25 sites. Comparing the results to values from the web-based, large-scale dataset, the Global Wind Atlas (GWA), both mean wind speed and wind power density are typically higher for the measurements. The difference is especially large for the more complex-terrain central highland sites where GWA results are also likely to be more uncertain. The result of this study can be used to make preliminary assessments on possible power production potential at the given sites.
Daily Crude Oil Price Forecasting Based on Improved CEEMDAN, SCA, and RVFL: A Case Study in WTI Oil Market
Authors: Wu Jiang , Miu Feng , Li Taiyong
Published: April 2020

Crude oil is one of the strategic energies and plays an increasingly critical role effecting on the world economic development. The fluctuations of crude oil prices are caused by various extrinsic and intrinsic factors and usually demonstrate complex characteristics. Therefore, it is a great challenge for accurately forecasting crude oil prices. In this study, a self-optimizing ensemble learning model incorporating the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), sine cosine algorithm (SCA), and random vector functional link (RVFL) neural network, namely ICEEMDAN-SCA-RVFL, is proposed to forecast crude oil prices. Firstly, we employ ICEEMDAN to decompose the raw series of crude oil prices into a group of relatively simple subseries. Secondly, RVFL is used to forecast the target values for each decomposed subseries individually. Due to the complex parameter settings of ICEEMDAN and RVFL, SCA is introduced to optimize the parameters for ICEEMDAN and RVFL in the above decomposition and prediction stages simultaneously. Finally, we assemble the predicted values of all individual subseries as the final predicted values of crude oil prices. Our proposed ICEEMDAN-SCA-RVFL significantly outperforms the single and ensemble benchmark models, as demonstrated by a case study conducted using the time series of West Texas Intermediate (WTI) daily crude oil spot prices.
A Numerical Study on Fire Development in a Confined Space Leading to Backdraft Phenomenon
Authors: Król Aleksander , Król Małgorzata , Krawiec Stanisław
Published: April 2020

This paper presents the results of numerical experiments on fire development and the backdraft phenomenon. The numerical model of fire development built with the use of Ansys Fluent was then validated based on literature data taken from real fire experiments. Some theoretical foundations of airflow and combustion modelling were added. Some features of the numerical model, which allowed for its high accuracy to be achieved, were widely discussed. Since large buoyancy forces were involved, to reproduce the decrease of the atmospheric pressure with height, a variable static pressure was applied using UDF (user-defined function).The results showed good accordance taking into account both the temperature profiles and the distribution of the airflow velocity. Once the model was validated, the research was extended to examine the backdraft phenomenon. The results revealed characteristic phases of the phenomenon and the occurrence of the gravity current as well, which were reported by empirical experiments.
Run to Failure: Aging of Commercial Battery Cells beyond Their End of Life
Authors: Ziegler Andreas , Oeser David , Hein Thiemo , Montesinos-Miracle Daniel , Ackva Ansgar
Published: April 2020

The aim of this work is to age commercial battery cells far beyond their expected lifetime. There is a gap in the literature regarding run to failure tests of lithium-ion batteries that this work intends to address. Therefore, twenty new Samsung ICR18650-26F cells were aged as a battery pack in a run to failure test. Aging took place with a constant load current and a constant charge current to accelerate capacity decrease. Important aging parameters such as capacity and internal resistance were measured at each cycle to monitor their development. The end of the test was initiated by the explosion of a single battery cell, after which the battery pack was disassembled and all parameters of the still intact single cells were measured. The distribution of all measured capacities and internal resistances is displayed graphically. This clearly shows the influence of the exploded cell on the cells in its immediate vicinity. Selected cells from this area of the battery were subjected to computed tomography (CT) to detect internal defects. The X-rays taken with computed tomography showed clear damage within the jelly roll, as well as the triggered safety mechanisms.
Numerical Investigation of Frequency and Amplitude Influence on a Plunging NACA0012
Authors: Camacho Emanuel , Neves Fernando , Silva André , Barata Jorge
Published: April 2020

Natural flight has always been the source of imagination for Mankind, but reproducing the propulsive systems used by animals that can improve the versatility and response at low Reynolds number is indeed quite complex. The main objective of the present work is the computational study of the influence of the Reynolds number, frequency, and amplitude of the oscillatory movement of a NACA0012 airfoil in the aerodynamic performance. The thrust and power coefficients are obtained which together are used to calculate the propulsive efficiency. The simulations were performed using ANSYS Fluent with a RANS approach for Reynolds numbers between 8500 and 34,000, reduced frequencies between 1 and 5, and Strouhal numbers from 0.1 to 0.4. The aerodynamic parameters were thoroughly explored as well as their interaction, concluding that when the Reynolds number is increased, the optimal propulsive efficiency occurs for higher nondimensional amplitudes and lower reduced frequencies, agreeing in some ways with the phenomena observed in the animal kingdom.
Reduction of Cold-Start Emissions for a Micro Combined Heat and Power Plant
Authors: Zobel Tammo , Schürch Christian , Boulouchos Konstantinos , Onder Christopher
Published: April 2020

Decentralized power generation by combined heat and power plants becomes increasingly popular as a measure to advance the energy transition. In this context, a substantial advantage of small combined heat and power plants is based on the relatively low pollutant emissions. However, a large proportion of the pollutant emissions is produced during a cold-start. This fact is not reflected in governmental and institutional emission guidelines, as these strongly focus on the emission levels under steady-state conditions. This study analyzes the spark advance, the reference air/fuel ratio and an electrically heated catalyst in terms of their potential to reduce the cold-start emissions of a micro combined heat and power plant which uses a natural gas fueled reciprocating internal combustion engine as prime mover and a three-way catalytic converter as aftertreatment system. Based on these measures, control approaches were developed that account for the specific operating conditions of the class of small combined heat and power plants, e.g., full-load operation and flexible, demand-driven runtimes. The experimental data demonstrates that even solutions with marginal adaptation/integration effort can reduce cold-start emissions to a great extent.
An Off-Board Multi-Functional Electric Vehicle Charging Station for Smart Homes: Analysis and Experimental Validation
Authors: Monteiro Vitor , Lima Pedro , Sousa Tiago J. C. , Martins Julio S. , Afonso Joao L.
Published: April 2020

This paper presents the analysis and experimental validation of a single-phase off-board multi-functional electric vehicle (EV) charging station (MF-EVCS), which has a single ac interface and two dc interfaces. As innovative aspects, the proposed MF-EVCS handles the interface of the ac power grid, the dc interface of a renewable energy source (RES), as well as the dc interface of an EV to perform dc charging or discharging of the batteries (in off-board grid-to-vehicle (G2V) or vehicle-to-grid (V2G) modes). Considering the power grid, the individual operation modes of the RES and the EV interfaces can be considered. Moreover, a combination of these modes is also possible. Besides, the MF-EVCS has as key innovative aspect the possibility of operating as an active power filter (APF), supporting the operation with reactive power and/or selected current harmonics. This possibility can be associated with any of the previous mentioned modes. These new features are framed in two distinct scenarios: in a smart home, where the ac-side current can be determined as a function of the other electrical appliances; in a smart grid, where the ac-side current can be determined as a requisite of the power grid. The proposed power theory, as well as the current control strategies for both ac-side and dc-side of the MF-EVCS, are presented in the paper for all the possible operation scenarios. A laboratory prototype was developed to validate the proposed MF-EVCS and the experimental results confirm its suitability for smart homes.
Modeling of Magnetic Elements Including Losses—Application to Variable Inductor
Authors: Saeed Sarah , Georgious Ramy , Garcia Jorge
Published: April 2020

This paper proposes and develops a circuit-based model aiming to simulate variable magnetic power elements in power electronic converters. The derived model represents the magnetic element by a reluctance-based equivalent circuit. The model takes into consideration device core losses, with the main emphasis given to hysteresis losses, which are modeled using the Jiles-Atherton model. The core loss model is further validated on different ferromagnetic materials to prove its range of applicability. The winding losses of the magnetic device are also taken into consideration, which are obtained using Dowell empirical formulas. In addition, the frequency dependence of the device losses is also considered. The proposed modeling procedure has been applied to study and characterize a double E-core variable power inductor structure in a 1 kW SiC full bridge DC-DC converter. The procedure has been verified by comparing the simulation results to the experimental measurements, confirming the validity and accuracy of the full circuit-based model.
A Hybrid Time Integration Scheme for the Discontinuous Galerkin Discretizations of Convection-Dominated Problems
Authors: Li Liang , Wu Songping
Published: April 2020

Discontinuous Galerkin (DG) method is a popular high-order accurate method for solving unsteady convection-dominated problems. After spatially discretizing the problem with the DG method, a time integration scheme is necessary for evolving the result. Owing to the stability-based restriction, the time step for an explicit scheme is limited by the smallest element size within the mesh, making the calculation inefficient. In this paper, a hybrid scheme comprising a three-stage, third-order accurate, and strong stability preserving Runge–Kutta (SSP-RK3) scheme and the three-stage, third-order accurate, L-stable, and diagonally implicit Runge–Kutta (LDIRK3) scheme is proposed. By dealing with the coarse and the refined elements with the explicit and implicit schemes, respectively, the time step for the hybrid scheme is free from the limitation of the smallest element size, making the simulation much more efficient. Numerical tests and comparison studies were made to show the performance of the hybrid scheme.
Natural Gas Transmission Pipelines: Risks and Remedies for Host Communities
Authors: Anderson David A.
Published: April 2020

Transmission pipelines deliver natural gas to consumers around the world for the production of heat, electricity, and organic chemicals. In the United States, 2.56 million miles (4.12 million km) of pipelines carry natural gas to more than 75 million customers. With the benefits of pipelines come the risks to health and property posed by leaks and explosions. Proposals for new and recommissioned pipelines challenge host communities with uncertainty and difficult decisions about risk management. The appropriate community response depends on the risk level, the potential cost, and the prospect for compensation in the event of an incident. This article provides information on the risks and expected costs of pipeline leaks and explosions in the United States, including the incident rates, risk factors, and magnitude of harm. Although aggregated data on pipeline incidents are available, broadly inclusive data do not serve the needs of communities that must make critical decisions about hosting a pipeline for natural gas transmission. This article breaks down the data relevant to such communities and omits incidents that occurred offshore or as part of gas gathering or local distribution. The article then explains possible approaches to risk management relevant to communities, pipeline companies, and policymakers.
Short-Term Photovoltaic Power Forecasting Using a Convolutional Neural Network–Salp Swarm Algorithm
Authors: Aprillia Happy , Yang Hong-Tzer , Huang Chao-Ming
Published: April 2020

The high utilization of renewable energy to manage climate change and provide green energy requires short-term photovoltaic (PV) power forecasting. In this paper, a novel forecasting strategy that combines a convolutional neural network (CNN) and a salp swarm algorithm (SSA) is proposed to forecast PV power output. First, the historical PV power data and associated weather information are classified into five weather types, such as rainy, heavy cloudy, cloudy, light cloudy and sunny. The CNN classification is then used to determine the prediction for the next day’s weather type. Five models of CNN regression are established to accommodate the prediction for different weather types. Each CNN regression is optimized using a salp swarm algorithm (SSA) to tune the best parameter. To evaluate the performance of the proposed method, comparisons were made to the SSA based support vector machine (SVM-SSA) and long short-term memory neural network (LSTM-SSA) methods. The proposed method was tested on a PV power generation system with a 500 kWp capacity located in south Taiwan. The results showed that the proposed CNN-SSA could accommodate the actual generation pattern better than the SVM-SSA and LSTM-SSA methods.
The Impact of Imperfect Weather Forecasts on Wind Power Forecasting Performance: Evidence from Two Wind Farms in Greece
Authors: Spiliotis Evangelos , Petropoulos Fotios , Nikolopoulos Konstantinos
Published: April 2020

Weather variables are an important driver of power generation from renewable energy sources. However, accurately predicting such variables is a challenging task, which has a significant impact on the accuracy of the power generation forecasts. In this study, we explore the impact of imperfect weather forecasts on two classes of forecasting methods (statistical and machine learning) for the case of wind power generation. We perform a stress test analysis to measure the robustness of different methods on the imperfect weather input, focusing on both the point forecasts and the 95% prediction intervals. The results indicate that different methods should be considered according to the uncertainty characterizing the weather forecasts.
The Effect of Suction Side Tubercles on Torque Output of a Steam Turbine Low-Pressure Last Stage Blade
Authors: Zhang Jing , Wu Fan , Wang Chun , Mei Ziyue , Han An , Xie Danmei
Published: April 2020

Flow separation and different kinds of stall flows occur under low load conditions for steam turbine last stage blades. In order to delay the flow separation and increase turbine power production, we applied suction side tubercles on steam turbine low-pressure last stage blades in the present study. The amplitude, wavelength, position, and thickness were considered as our design variables. We used the orthogonal test method (OTM) to generate modified blades with different tubercle variables that were then numerically simulated by a three-dimensional computational fluid dynamics (CFD) analysis. The blade axial torque of the nine modified tests was compared with the original blade. The results showed that the application of bionic tubercles on the suction side of the steam turbine blade is a promising solution to improve the blade axial torque for all modified tests with a maximum increase of 33.32% due to the turbulent vortices generated by bionic tubercles.
Ideology and Value Determinants of Public Support for Energy Policies in the U.S.: A Focus on Western States
Authors: Allen Wolters Erika , Steel Brent S. , Warner Rebecca L.
Published: April 2020

Energy policy is often a contentious issue in the U.S. in the areas of infrastructure, conservation, and price discrimination. From the siting of new pipelines, conservation regulations, and variable pricing based on times and usage, many policies have been met by intense opposition as well as support from a variety of sources. In this context, this study examines individual-level attributes (e.g., political ideology, environmental values, and demographic characteristics) that lead to support for or opposition to infrastructure, conservation, and price discrimination policies. The identification of demographic and value correlates of energy policy preferences is important for the successful development of energy policies. Data from 2019 random household surveys in the U.S. western states of California, Idaho, Oregon and Washington are used to examine the variation in views on a variety of energy policies. Multivariate analyses reveal that those with more liberal political ideology and people holding stronger pro-environmental values (as measured by the New Ecological Paradigm) were more likely to support conservation campaigns, energy efficiency, funding for renewable energy technology and price discrimination policies than those who held more conservative views. Several demographic variables also have a significant impact on support for or opposition to policies concerning infrastructure, conservation, and price discrimination. Younger people and people with higher levels of formal education are more likely to support voluntary energy conservation campaigns and increased funding for research into renewable energy technologies, and people with higher incomes are more supportive of requiring high-energy efficiency standards in new construction. Finally, state residency independently affected policy preferences with Idahoans’ views more consistent with political conservatives and those lower on the NEP than residents of the other three western states. These findings should be useful to policy makers as they work toward the development of energy policies.
Evaluation of Different Development Possibilities of Distribution Grid State Forecasts
Authors: Hermanns Jessica , Modemann Marcel , Korotkiewicz Kamil , Paulat Frederik , Kotthaus Kevin , Pack Sven , Zdrallek Markus
Published: April 2020

The number of renewable energy systems is still increasing. To reduce the worldwide CO2 emissions, there will be even more challenges in the distribution grids like currently upcoming charging stations or heat pumps. All these new electric systems in the low voltage (LV) and medium voltage (MV) levels are characterized by an unsteady behavior. To monitor and predict the behavior of these new flexible systems, a grid state forecast is needed. This software tool calculates wind, photovoltaic, and load forecasts. These power forecasts are already in the focus of research, but there are some specific use cases, which require a more specific solution. To get a variously applicable software tool, different new functions to improve an already existing grid state forecast tool were developed and evaluated. For example, it will be proofed if a grid state forecast tool can be improved by calculating the number or the base load of the loads in grid areas by just one available measurement. Another big subject exists in the exchange of forecast information between different voltage levels. How this can be realized and how big the effect on the forecast quality is, will be analyzed. The results of these evaluations will be shown in this paper.
EU-28 Residential Heat Supply and Consumption: Historical Development and Status
Authors: Bertelsen Nis , Vad Mathiesen Brian
Published: April 2020

EU is moving towards a climate neutrality goal in 2050 with heating of buildings posing a major challenge. This paper provides a deep understanding of the historical development, path dependency and current status of the EU-28 residential heat sectors to inform strategy and policy makers and to open up this black box. Data is combined for buildings, installed technologies, fuel consumption and energy supply for Member States from 1990 to 2015, to analyse the importance of large-scale infrastructures and supply chains. Primary energy supply for residential heating is mainly based on fossil fuels; 70% in 2015 with 69% imported. The building level technologies are dominated by non-condensing boilers and stoves. Primary and final energy consumption decreased in spite of an increase in the total occupied living area in most countries. Path-dependency effects are found in the residential heat supply in EU. The analysis show path-dependent trajectories are present in most Member States, especially regarding natural gas infrastructure. The period shows many options for decarbonisation are not used to the full potential, e.g., energy efficiency in buildings, district heating, heat pumps. Past experiences should be considered when developing new decarbonisation strategies in Member States and on the EU level.
Consumers’ Willingness to Accept Time-of-Use Tariffs for Shifting Electricity Demand
Authors: Sundt Swantje , Rehdanz Katrin , Meyerhoff Jürgen
Published: April 2020

Time-of-use (TOU) electricity tariffs represent an instrument for demand side management. By reducing energy demand during peak times, less investments in otherwise necessary, costly, and CO2 intensive redispatch would be required. We use a choice experiment (CE) to analyze private consumers’ acceptance of TOU tariffs in Germany. In our CE, respondents choose between a fixed rate tariff and two TOU tariffs that differ by peak time scheme and by a control of appliances’ electricity consumption during that time. We use a mixed logit model to account for taste heterogeneity. Moreover, investigating decision strategies, we identify three different strategies that shed light on drivers of unobserved taste heterogeneity: (1) Always choosing the status quo, (2) always choosing the maximum discount, and (3) choosing a TOU tariff but not always going for the maximum discount. Overall, about 70% of our 1398 respondents would choose a TOU tariff and shift their electricity demand, leading to a decline in energy demand during peak times. Rough estimates indicate that this would lead to significant savings in electricity generation, avoiding up to a mid to large-sized fossil-fuel power plant.
MILP-PSO Combined Optimization Algorithm for an Islanded Microgrid Scheduling with Detailed Battery ESS Efficiency Model and Policy Considerations
Authors: Kim Rae-Kyun , Glick Mark B. , Olson Keith R. , Kim Yun-Su
Published: April 2020

This paper presents the optimal scheduling of a diesel generator and an energy storage system (ESS) while using a detailed battery ESS energy efficiency model. Optimal scheduling has been hampered to date by the nonlinearity and complexity of the battery ESS. This is due to the battery ESS efficiency being a multiplication of inverter and battery efficiency and the dependency of an inverter and any associated battery efficiencies on load and charging and discharging. We propose a combined mixed-integer linear programming and particle swarm optimization (MILP-PSO) algorithm as a novel means of addressing these considerations. In the algorithm, MILP is used to find some initial points of PSO, so that it can find better solution. Moreover, some additional algorithms are added into PSO to modify and, hence, improve its ability of dealing with constraint conditions and the local minimum problem. The simulation results show that the proposed algorithm performs better than MILP and PSO alone for the practical microgrid. The results also indicated that simplification or neglect of ESS efficiency when applying MILP to scheduling may cause a constraint violation.
Describing Medicinal Non-Timber Forest Product Trade in Eastern Deciduous Forests of the United States
Authors: Kruger Steve D. , Munsell John F. , Chamberlain James L. , Davis Jeanine M. , Huish Ryan D.
Published: April 2020

Eastern deciduous forests in the United States have supplied marketable non-timber forest products (NTFP) since the 18th century. However, trade is still largely informal, and the market scope and structure are not well understood. One exception is American ginseng (Panax quinquefolius L.). Ginseng’s legal status as a threatened species requires that buyers apply for a license and keep sales records that are submitted to a state authority. Other marketable medicinal plants collected from the same forests, known colloquially as ‘off-roots’, are not similarly tracked. To study the characteristics of off-root trade in the eastern deciduous forests of the United States, registered ginseng buyers in 15 eastern states were surveyed in 2015 and 2016 about business attributes, purchase volume, and harvest distribution for 15 off-root species selected for their economic and conservation value. Buyers voluntarily reported harvesting 47 additional NTFP species. The most frequently purchased off-root species were the roots and rhizomes of two perennial understory plants: black cohosh (Actaea racemosa L.) and goldenseal (Hydrastis canadensis L.). Survey data were used to develop a buyer typology and describe the off-root market structure and material sourcing. The buyer typology included four distinct categories: side or specialty (small); seasonal venture (medium); large integrated or dedicated business (large); and dedicated bulk enterprise (regional aggregator). Market activity was mapped across the study area, demonstrating that most off-root trade is concentrated in central Appalachia, an area with extensive forests and a struggling economy. Study methods and data improve non-timber forest product market insights, are useful for forest management, and can support efforts to advance sustainable NTFP supply chains.
PACER: Platform for Android Malware Classification, Performance Evaluation and Threat Reporting
Authors: Kumar Ajit , Agarwal Vinti , Kumar Shandilya Shishir , Shalaginov Andrii , Upadhyay Saket , Yadav Bhawna
Published: April 2020

Android malware has become the topmost threat for the ubiquitous and useful Android ecosystem. Multiple solutions leveraging big data and machine-learning capabilities to detect Android malware are being constantly developed. Too often, these solutions are either limited to research output or remain isolated and incapable of reaching end users or malware researchers. An earlier work named PACE (Platform for Android Malware Classification and Performance Evaluation), was introduced as a unified solution to offer open and easy implementation access to several machine-learning-based Android malware detection techniques, that makes most of the research reproducible in this domain. The benefits of PACE are offered through three interfaces: Representational State Transfer (REST) Application Programming Interface (API), Web Interface, and Android Debug Bridge (ADB) interface. These multiple interfaces enable users with different expertise such as IT administrators, security practitioners, malware researchers, etc. to use their offered services. In this paper, we propose PACER (Platform for Android Malware Classification, Performance Evaluation, and Threat Reporting), which extends PACE by adding threat intelligence and reporting functionality for the end-user device through the ADB interface. A prototype of the proposed platform is introduced, and our vision is that it will help malware analysts and end users to tackle challenges and reduce the amount of manual work.