bluuebunny/crossref_metadata_2025 huggingface dataset:
Estrutura produtiva e comércio exterior no Brasil: uma investigação sobre as elasticidades-renda da demanda por exportações e importações setoriais
Authors: Marconi Nelson , Araújo Eliane Cristina
Published: March 2020

Este trabalho analisa a composição da pauta brasileira de exportações e importações e estima as elasticidades-renda da demanda por exportações e importações nos diferentes setores da indústria de transformação. Procura-se responder quais são os setores exportadores e importadores da indústria de transformação que possuem as maiores elasticidades-renda da demanda e que, portanto, deveriam ser estimulados para levarem a uma mudança positiva na estrutura produtiva do país, no sentido de aumentar o crescimento econômico. O trabalho apresenta alguns aspectos teóricos dos modelos de crescimento com restrição de balanço de pagamentos, discute a abordagem estruturalista associados às características setoriais que influem sobre o processo de desenvolvimento e estima e analisa as elasticidades-renda da demanda para os setores exportadores e importadores da indústria de transformação, individualmente e agregados por intensidade tecnológica. As conclusões da pesquisa são as de que a elasticidade-renda da demanda dos produtos exportados pela indústria intensiva em engenharia, ciência e conhecimento é maior que as elasticidades dos demais ramos da indústria de transformação. O mesmo ocorre em relação às importações. Esse resultado sugere, à luz das teorias estruturalista e de crescimento com restrição de balanço de pagamentos, que uma pauta de exportações concentrada em produtos com maior conteúdo tecnológico pode implicar crescimento mais elevadas que uma pauta na qual predominam commodities, como é o caso no Brasil.
Expectations and Stability in the Kaleckian Growth Model
Authors: Lima Gilberto Tadeu , Setterfield Mark
Published: March 2020

A central element in the canonical Kaleckian growth model is the demand-led output-adjustment stability condition known as the Keynesian stability condition. This condition requires that, all else constant, saving be less responsive to changes in capital capacity utilization than investment. This paper further explores the plausibility of the Keynesian stability condition by enriching the Kaleckian growth model with a more fully developed Keynesian theory of expectations formation. As a result, the responsiveness of investment to changes in capacity utilization is reduced, and through mechanisms that have clear and plausible behavioural underpinnings. It therefore becomes more likely (in principle) that the Keynesian stability condition will hold in practice. The paper also explores the consequences of such re-specification of investment behaviour for certain comparative static results associated with the canonical Kaleckian growth model.
Economic Growth from a Kaldorian Perspective: Theory, Evidence and Agenda
Authors: Romero João P.
Published: March 2020

This paper presents a literature review of the Kaldorian literature, which identifies three important gaps, or areas for future research. Firstly, the determinants of the magnitude of the key parameters of Kaldor-Verdoorn’s Law (the Verdoorn coefficient) and of Thirlwall’s Law (the income elasticities) have not been fully understood. Secondly, the fact that cumulative causation works through price competitiveness in the Kaldor-Dixon-Thirlwall model represents an important limitation of the model, which has not yet been solved. Thirdly, sectoral differences have not been fully explored in Kaldorian theory. The review indicates that, in the first two research areas, exploring the effects of additional variables could help clarify what determines the magnitudes of the parameters, as have been sought by the works that combine Kaldorian and Schumpeterian insights, indicating also new channels through which cumulative causation could work. Finally, the last issue requires more attention to similarities and differences between manufacturing sectors, as well as exploring more carefully how sectoral dynamics work.
Oral Contraception Use in Benign Breast Tumor Patients in Dr. Soetomo General Academic Hospital
Authors: Putri Ayu Maghfira Nida , Mustokoweni Sjahjenny , Ernawati Ernawati
Published: March 2020

The growth of breast tumors is influenced by estrogen and progesterone hormones. One source of this hormone is hormonal contraception, including oral contraception which still in demand by Indonesian women. This study wants to identify oral contraception use in patients with benign breast tumors. This used descriptive study with a retrospective cross-sectional design. Samples were taken using the total sampling method in patients with benign breast tumors according to ICD 10 D-24 which was confirmed by FNAB examination at the POSA Dr. Soetomo General Academic Hospital between 2015-2017. Fifty three case of benign breast tumor were found with dominant characteristics at the age of group 40-49 years old (47.2%), had a breastfeeding history (50.9%), multiparous woman(64.2%), mean of menarche age at 13.28 years old and fertile periode women (83.0%). The most common type of benign tumors found were fibrocystic change. Patients who used oral contraceptives were 24.5% with an average length of use for 8 years 2 months, while another 75.5% used non-hormonal contraception or did not use any contraception. So the conclusion is majority of patients with benign breast tumors do not use oral contraception.

Keywords: benign breast tumor; oral contraception; estrogen
Optimizing Convolutional Neural Network Hyperparameters by Enhanced Swarm Intelligence Metaheuristics
Authors: Bacanin Nebojsa , Bezdan Timea , Tuba Eva , Strumberger Ivana , Tuba Milan
Published: March 2020

Computer vision is one of the most frontier technologies in computer science. It is used to build artificial systems to extract valuable information from images and has a broad range of applications in various areas such as agriculture, business, and healthcare. Convolutional neural networks represent the key algorithms in computer vision, and in recent years, they have attained notable advances in many real-world problems. The accuracy of the network for a particular task profoundly relies on the hyperparameters’ configuration. Obtaining the right set of hyperparameters is a time-consuming process and requires expertise. To approach this concern, we propose an automatic method for hyperparameters’ optimization and structure design by implementing enhanced metaheuristic algorithms. The aim of this paper is twofold. First, we propose enhanced versions of the tree growth and firefly algorithms that improve the original implementations. Second, we adopt the proposed enhanced algorithms for hyperparameters’ optimization. First, the modified metaheuristics are evaluated on standard unconstrained benchmark functions and compared to the original algorithms. Afterward, the improved algorithms are employed for the network design. The experiments are carried out on the famous image classification benchmark dataset, the MNIST dataset, and comparative analysis with other outstanding approaches that were tested on the same problem is conducted. The experimental results show that both proposed improved methods establish higher performance than the other existing techniques in terms of classification accuracy and the use of computational resources.
Interface Failure of Heated GLARETM Fiber–Metal Laminates under Bird Strike
Authors: Hasan Md.Zahid
Published: March 2020

Many high-strength composite materials have been developed for aircraft structures. GLAss fiber REinforced aluminum (GLARE) is one of the high-performance composites. The review of articles, however, yielded no study on the impact damage of heated GLARE laminates. This study, therefore, aimed at developing a numerical model that can delineate the continuum damage of GLARE 5A-3/2-0.3 laminates at elevated temperatures. In the first stage, the inter-laminar interface failure of heated GLARE laminate had been investigated at room temperature and 80 °C. The numerical analysis employed a three-dimensional GLARE 5A-3/2-0.3 model that accommodated volumetric cohesive interfaces between mating material layers. Lagrangian smoothed particles populated the projectile. The model considered the degradation of tensile and shear modulus of glass fiber reinforced epoxy (GF/EP) at 80 °C, while incorporated temperature-dependent critical strain energy release rate of cohesive interfaces. When coupled with the material particulars, an 82 m/s bird impact at room temperature exhibited delamination first in the GF/EP 90°/0° interface farthest from the impacted side. Keeping the impact velocity, interface failure propagated at a slower rate at 80 °C than that at room temperature, which was in agreement with the impact damage determined in the experiments. The outcomes of this study will help optimize a GLARE laminate based on the anti-icing temperature of aircraft.
Application of Digital Particle Image Velocimetry to Insect Motion: Measurement of Incoming, Outgoing, and Lateral Honeybee Traffic
Authors: Mukherjee Sarbajit , Kulyukin Vladimir
Published: March 2020

The well-being of a honeybee (Apis mellifera) colony depends on forager traffic. Consistent discrepancies in forager traffic indicate that the hive may not be healthy and require human intervention. Honeybee traffic in the vicinity of a hive can be divided into three types: incoming, outgoing, and lateral. These types constitute directional traffic, and are juxtaposed with omnidirectional traffic where bee motions are considered regardless of direction. Accurate measurement of directional honeybee traffic is fundamental to electronic beehive monitoring systems that continuously monitor honeybee colonies to detect deviations from the norm. An algorithm based on digital particle image velocimetry is proposed to measure directional traffic. The algorithm uses digital particle image velocimetry to compute motion vectors, analytically classifies them as incoming, outgoing, or lateral, and returns the classified vector counts as measurements of directional traffic levels. Dynamic time warping is used to compare the algorithm’s omnidirectional traffic curves to the curves produced by a previously proposed bee motion counting algorithm based on motion detection and deep learning and to the curves obtained from a human observer’s counts on four honeybee traffic videos (2976 video frames). The currently proposed algorithm not only approximates the human ground truth on par with the previously proposed algorithm in terms of omnidirectional bee motion counts but also provides estimates of directional bee traffic and does not require extensive training. An analysis of correlation vectors of consecutive image pairs with single bee motions indicates that correlation maps follow Gaussian distribution and the three-point Gaussian sub-pixel accuracy method appears feasible. Experimental evidence indicates it is reasonable to treat whole bees as tracers, because whole bee bodies and not parts thereof cause maximum motion. To ensure the replicability of the reported findings, these videos and frame-by-frame bee motion counts have been made public. The proposed algorithm is also used to investigate the incoming and outgoing traffic curves in a healthy hive on the same day and on different days on a dataset of 292 videos (216,956 video frames).
O3 Sensitivity and Contributions of Different NMHC Sources in O3 Formation at Urban and Suburban Sites in Shanghai
Authors: Lin Haotian , Wang Ming , Duan Yusen , Fu Qingyan , Ji Wenhao , Cui Huxiong , Jin Dan , Lin Yanfen , Hu Kun
Published: March 2020

Ground-level ozone (O3) pollution is still one of the priorities and challenges for air pollution control in the Yangtze River Delta (YRD) region of China. Understanding the relationship of O3 with its precursors and contributions of different sources in O3 formation is essential for the development of an O3 control strategy. This study analyzed O3 sensitivity to its precursors using a box model based on online observations of O3, non-methane hydrocarbons (NMHCs), nitrogen oxides (NOx), and carbon monoxide (CO) at an urban site and a suburban site in Shanghai in July 2017. Anthropogenic sources of NMHCs were identified using the positive matrix factorization (PMF) receptor model, and then contributions of different sources in O3 formation were estimated by the observation-based model (OBM). The relative incremental reactivity (RIR) values calculated by the OBM suggest that O3 formation at the urban site was in the NMHC-limited regime, while O3 formation at the suburban site tended between the transition regime and the NMHC-limited regime. Vehicular emission and liquefied petrochemical gas (LPG) use or aged air mass were found to be the two largest contributors at the urban and suburban sites in July, followed by paint and solvent use, and the petrochemical industry. However, from the perspective of O3 formation, vehicular emission and paint and solvent use were the largest two contributors at two sites due to the higher RIR values for paint and solvent use. In addition, the influence of transport on O3 sensitivity was identified by comparing O3 sensitivity at the suburban site across two days with different air mass paths. The result revealed that O3 formation in Shanghai is not only related to local emissions but also influenced by emissions from neighboring provinces. These findings on O3–NMHC–NOX sensitivity, contributions of different sources in O3 formation, and influence of transport could be useful for O3 pollution control in the YRD region. Nevertheless, more quantitative analyses on transport and further evaluation of the uncertainty of the OBM are still needed in future.
The Truncated Cauchy Power Family of Distributions with Inference and Applications
Authors: Aldahlan Maha A. , Jamal Farrukh , Chesneau Christophe , Elgarhy Mohammed , Elbatal Ibrahim
Published: March 2020

As a matter of fact, the statistical literature lacks of general family of distributions based on the truncated Cauchy distribution. In this paper, such a family is proposed, called the truncated Cauchy power-G family. It stands out for the originality of the involved functions, its overall simplicity and its desirable properties for modelling purposes. In particular, (i) only one parameter is added to the baseline distribution avoiding the over-parametrization phenomenon, (ii) the related probability functions (cumulative distribution, probability density, hazard rate, and quantile functions) have tractable expressions, and (iii) thanks to the combined action of the arctangent and power functions, the flexible properties of the baseline distribution (symmetry, skewness, kurtosis, etc.) can be really enhanced. These aspects are discussed in detail, with the support of comprehensive numerical and graphical results. Furthermore, important mathematical features of the new family are derived, such as the moments, skewness and kurtosis, two kinds of entropy and order statistics. For the applied side, new models can be created in view of fitting data sets with simple or complex structure. This last point is illustrated by the consideration of the Weibull distribution as baseline, the maximum likelihood method of estimation and two practical data sets wit different skewness properties. The obtained results show that the truncated Cauchy power-G family is very competitive in comparison to other well implanted general families.
A Novel Microwave Treatment for Sleep Disorders and Classification of Sleep Stages Using Multi-Scale Entropy
Authors: Geng Daoshuang , Yang Daoguo , Cai Miao , Zheng Lixia
Published: March 2020

The aim of this study was to develop an integrated system of non-contact sleep stage detection and sleep disorder treatment for health monitoring. Hence, a method of brain activity detection based on microwave scattering technology instead of scalp electroencephalogram was developed to evaluate the sleep stage. First, microwaves at a specific frequency were used to penetrate the functional sites of the brain in patients with sleep disorders to change the firing frequency of the activated areas of the brain and analyze and evaluate statistically the effects on sleep improvement. Then, a wavelet packet algorithm was used to decompose the microwave transmission signal, the refined composite multiscale sample entropy, the refined composite multiscale fluctuation-based dispersion entropy and multivariate multiscale weighted permutation entropy were obtained as features from the wavelet packet coefficient. Finally, the mutual information-principal component analysis feature selection method was used to optimize the feature set and random forest was used to classify and evaluate the sleep stage. The results show that after four times of microwave modulation treatment, sleep efficiency improved continuously, the overall maintenance was above 80%, and the insomnia rate was reduced gradually. The overall classification accuracy of the four sleep stages was 86.4%. The results indicate that the microwaves with a certain frequency can treat sleep disorders and detect abnormal brain activity. Therefore, the microwave scattering method is of great significance in the development of a new brain disease treatment, diagnosis and clinical application system.
Starting Pulse Vibration Torque Analysis of Aviation Variable Frequency Asynchronous Motor Based on Low-Frequency Step-Down Starting Methods
Authors: Cao Zheng , Zhou Yuanjun , Wang Na
Published: March 2020

The more electric aircraft provides 115 V/360~800 Hz variable frequency power supply for the variable frequency asynchronous motor, and the motor operation characteristics change with the power frequency variation. It causes the starting pulse vibration torque with the low-frequency power supply (360 Hz) to increase greatly and the mechanical shock and fatigue damage. Therefore, this paper proposes step-down starting method with the low-frequency power supply. Based on the electromagnetic principles generated by the starting pulse vibration torque, this paper uses a novel method of simulation data fitting to establish an approximate model of the starting pulse vibration torque. The parameter design formulas of the low-frequency step-down starting methods, including the reducing voltage, the series resistance, and the series inductance are proposed. The effectiveness of the different methods are verified, and the performance is compared through the simulation. The experimental verification of a small power asynchronous motor is completed. The simulation and experiment results show that the low-frequency step-down starting methods effectively reduce the starting peak torque, and also suppress the shock impact of starting current on the power supply.
A New Simulation Model for Vertical Spiral Ground Heat Exchangers Combining Cylindrical Source Model and Capacity Resistance Model
Authors: Katsura Takao , Higashitani Takashi , Fang Yuzhi , Sakata Yoshitaka , Nagano Katsunori , Akai Hitoshi , OE Motoaki
Published: March 2020

Considering the heat capacity inside vertical spiral ground heat exchanger (VSGHEX) in the simulation is one of the most noteworthy challenge to design the ground source heat pump (GSHP) system with VSGHEXs. In this paper, a new simulation model for VSGHEXs is developed by combining the ICS model with the CaRM. The developed simulation model can consider the heat capacity inside VSGHEX and provide dynamic calculation with high speed and appropriate precision. In order to apply the CaRM, the equivalent length was introduced. Then, the equivalent length was approximated by comparing the results of the CaRM and the numerical calculation. In addition, the calculation model of the VSGHEX was integrated into the design and simulation tool for the GSHP system. The accuracy of the tool was verified by comparing with the measurements. The error between supply temperatures of the measurements and calculation is approximately 2 °C at the maximum. Finally, assuming GSHP systems with VSGHEXs, whose spiral diameter was 500 mm and depth was 4 m, were installed in residential houses in Japan, the required numbers of VSGHEXs were estimated. The results showed a strong correlation between the total heating or cooling load and the required number. Therefore, the required number can be estimated by using the simplified approximate equation.
Finite Element Modeling of Geothermal Source of Heat Pump in Long-Term Operation
Authors: Hałaj Elżbieta , Pająk Leszek , Papiernik Bartosz
Published: March 2020

Model simulation allows to present the time-varying temperature distribution of the ground source for heat pumps. A system of 25 double U-shape borehole heat exchangers (BHEs) in long-term operation and three scenarios were created. In these scenarios, the difference between balanced and non-balanced energy load was considered as well as the influence of the hydrogeological factors on the temperature of the ground source. The aim of the study was to compare different thermal regimes of BHEs operation and examine the influence of small-scale and short-time thermal energy storage on ground source thermal balance. To present the performance of the system according to geological and hydrogeological factors, a Feflow® software (MIKE Powered by DHI Software) was used. The temperature for the scenarios was visualized after 10 and 30 years of the system’s operation. In this paper, a case is presented in which waste thermal energy from space cooling applications during summer months was used to upgrade thermal performance of the ground (geothermal) source of a heat pump. The study shows differences in the temperature in the ground around different Borehole Heat Exchangers. The cold plume from the not-balanced energy scenario is the most developed and might influence the future installations in the vicinity. Moreover, seasonal storage can partially overcome the negative influence of the travel of a cold plume. The most exposed to freezing were BHEs located in the core of the cold plumes. Moreover, the influence of the groundwater flow on the thermal recovery of the several BHEs is visible. The proper energy load of the geothermal source heat pump installation is crucial and it can benefit from small-scale storage. After 30 years of operation, the minimum average temperature at 50 m depth in the system with waste heat from space cooling was 2.1 °C higher than in the system without storage and 1.6 °C higher than in the layered model in which storage was not applied.
Design and Experimental Investigation of a Hybrid Rotor Permanent Magnet Modular Machine with 3D Flux Paths Accounting for Recyclability of Permanent Magnet Material
Authors: Gonzalez Adolfo Garcia , Wang Dong , Dubus Jean-Marc , Rasmussen Peter Omand
Published: March 2020

Rare-earth metals used for manufacturing Permanent Magnets (PMs) remain classified as critical raw materials by the European Commission. In order to secure the supply of electrical machines due to the increasing demand of Hybrid and Full Electrical Vehicles ((H)EVs), recycling has emerged as a valuable alternative. Hence, this paper presents the concept of a modular PM machine with a hybrid rotor and 3D flux paths, for application in ((H)EVs). The proposed machine topology is intended to facilitate the extraction of PM material towards a recycling process. The selection of a machine for prototyping is carried out by investigating the effect of the variation of the number of rotor teeth and stator modules on various parameters, with models developed in Finite Element (FE). Finally, the models developed of the selected combination were validated with a detailed experimental evaluation of the prototype.
Infrared Thermography Based Defects Testing of Solar Photovoltaic Panel with Fuzzy Rule-Based Evaluation
Authors: Balasubramani Gomathy , Thangavelu Venkatesan , Chinnusamy Muniraj , Subramaniam Umashankar , Padmanaban Sanjeevikumar , Mihet-Popa Lucian
Published: March 2020

Infrared Thermography has been used as a tool for predictive and preventive maintenance of Photovoltaic panels. International Electrotechnical Commission provides some guidelines for using thermography to detect defects in Photovoltaic panels. However, the proposed guidelines focus only on the location of the hot spot than diagnosing the types of faults. The long-term reliability and efficiency of panels can be affected by progressive defects such as discolouring and delamination. This paper proposed the new Thermal Pixel Counting algorithm to detect the above faults based on three thermal profile index values. The real-time experimental testing was carried out using FLIR T420bx® thermal imager and results have been provided to validate the proposed method. In this work, the fuzzy rule-based classification system is proposed to automate the classification process. Fuzzy reasoning method based on a single winner rule fuzzy classifier is designed with modified rule weights by particular grade. The performance of the proposed classifier is compared with the conventional fuzzy classifier and neural network model.
Prediction of Performance Variation Caused by Manufacturing Tolerances and Defects in Gas Diffusion Electrodes of Phosphoric Acid (PA)–Doped Polybenzimidazole (PBI)-Based High-Temperature Proton Exchange Membrane Fuel Cells
Authors: Gurau Vladimir , De Castro Emory
Published: March 2020

The automated process of coating catalyst layers on gas diffusion electrodes (GDEs) for high-temperature proton exchange membrane fuel cells results inherently into a number of defects. These defects consist of agglomerates in which the platinum sites cannot be accessed by phosphoric acid and which are the consequence of an inconsistent coating, uncoated regions, scratches, knots, blemishes, folds, or attached fine particles—all ranging from μm to mm size. These electrochemically inactive spots cause a reduction of the effective catalyst area per unit volume (cm2/cm3) and determine a drop in fuel cell performance. A computational fluid dynamics (CFD) model is presented that predicts performance variation caused by manufacturing tolerances and defects of the GDE and which enables the creation of a six-sigma product specification for Advent phosphoric acid (PA)-doped polybenzimidazole (PBI)-based membrane electrode assemblies (MEAs). The model was used to predict the total volume of defects that would cause a 10% drop in performance. It was found that a 10% performance drop at the nominal operating regime would be caused by uniformly distributed defects totaling 39% of the catalyst layer volume (~0.5 defects/μm2). The study provides an upper bound for the estimation of the impact of the defect location on performance drop. It was found that the impact on the local current density is higher when the defect is located closer to the interface with the membrane. The local current density decays less than 2% in the presence of an isolated defect, regardless of its location along the active area of the catalyst layer.
Short-Circuit Fault Current Calculation Method for the Multi-Terminal DC Grid Considering the DC Circuit Breaker
Authors: Jia Haipeng , Yin Jingyuan , Wei Tongzhen , Huo Qunhai , Li Jinke , Wu Lixin
Published: March 2020

The analysis and calculation of the short-circuit fault current in the DC grid is of great significance to the design and configuration of the converter station and DC circuit breaker parameters. The existing flexible DC system not only includes the modular multilevel converter (MMC) converter, but also needs power equipment such as the fault current limiter and DC circuit breaker. Therefore, the system modeling and short circuit calculation of the multi-terminal DC system after adding the DC circuit breaker are also of great significance for the design of DC power system parameters and the grid troubleshooting ability. In this paper, firstly, the parameters of the four-terminal DC system of the modular multilevel converter (MMC) are simplified, and the analytical solution of the short circuit fault current of the multi-terminal DC system is given. Then, the external characteristics of the cascaded hybrid DC circuit breaker are modeled. Based on the equivalent circuit of the fault current in different stages, the short circuit calculation method of four-terminal MMC system with DC circuit breaker is obtained. This method can effectively describe the overall trend of fault current and provide the basis for the configuration of DC line protection settings and DC circuit breaker related parameters.
Fractal Characteristics of Micro- and Mesopores in the Longmaxi Shale
Authors: Wang Xiaoqi , Zhu Yanming , Wang Yang
Published: March 2020

To better understand the variability and heterogeneity of pore size distributions (PSDs) in the Longmaxi Shale, twelve shale samples were collected from the Xiaoxi and Fendong section, Sichuan Province, South China. Multifractal analysis was employed to study PSDs of mesopores (2–50 nm) and micropores (<2 nm) based on low-pressure N2/CO2 adsorption (LP-N2/CO2GA). The results show that the PSDs of mesopores and micropores exhibit a multifractal behavior. The multifractal parameters can be divided into the parameters of heterogeneity (D−10–D10, D0–D10 and D−10–D0) and the parameters of singularity (D1 and H). For both the mesopores and micropores, decreasing the singularity of the pore size distribution contributes to larger heterogeneous parameters. However, micropores and mesopores also vary widely in terms of the pore heterogeneity and its controlling factors. Shale with a higher total organic carbon (TOC) content may have a larger volume of micropores and more heterogeneous mesopores. Rough surface and less concentrated pore size distribution hinder the transport of adsorbent in mesopores. The transport properties of micropores are not affected by the pore fractal dimension.
Effective Permeability of Multi Air Gap Ferrite Core 3-Phase Medium Frequency Transformer in Isolated DC-DC Converters
Authors: Dworakowski Piotr , Wilk Andrzej , Michna Michal , Lefebvre Bruno , Sixdenier Fabien , Mermet-Guyennet Michel
Published: March 2020

The magnetizing inductance of the medium frequency transformer (MFT) impacts the performance of the isolated dc-dc power converters. The ferrite material is considered for high power transformers but it requires an assembly of type “I” cores resulting in a multi air gap structure of the magnetic core. The authors claim that the multiple air gaps are randomly distributed and that the average air gap length is unpredictable at the industrial design stage. As a consequence, the required effective magnetic permeability and the magnetizing inductance are difficult to achieve within reasonable error margins. This article presents the measurements of the equivalent B(H) and the equivalent magnetic permeability of two three-phase MFT prototypes. The measured equivalent B(H) is used in an FEM simulation and compared against a no load test of a 100 kW isolated dc-dc converter showing a good fit within a 10% error. Further analysis leads to the demonstration that the equivalent magnetic permeability and the average air gap length are nonlinear functions of the number of air gaps. The proposed exponential scaling function enables rapid estimation of the magnetizing inductance based on the ferrite material datasheet only.
Life Cycle Environmental Costs of Buildings
Authors: Wang Yuanfeng , Pang Bo , Zhang Xiangjie , Wang Jingjing , Liu Yinshan , Shi Chengcheng , Zhou Shuowen
Published: March 2020

Energy consumption and pollutant emissions from buildings have caused serious impacts on the environment. Currently, research on building environmental costs is quite insufficient. Based on life cycle inventory of building materials, fossil fuel and electricity power, a calculating model for environmental costs during different stages is presented. A single-objective optimization model is generated by converting environmental impact into environmental cost, with the same unit with direct cost. Two residential buildings, one located in Beijing and another in Xiamen, China, are taken as the case studies and analyzed to test the proposed model. Moreover, data uncertainty and sensitivity analysis of key parameters, including the discount rate and the unit virtual abatement costs of pollutants, are also conducted. The analysis results show that the environmental cost accounts for about 16% of direct cost. The environmental degradation cost accounts for about 70% of the total environmental cost. According to the probabilistic uncertainty analysis results, the coefficient of variation of material production stage is the largest. The sensitivity analysis results indicate that the unit virtual abatement cost of CO2 has the largest influence on the final environmental cost.
A New Network for Particle Filtering of Multivariable Nonlinear Objects †
Authors: Kozierski Piotr , Michalski Jacek , Zietkiewicz Joanna , Retinger Marek Retinger and Wojciech , Giernacki Wojciech
Published: March 2020

In this paper, a new object in the form of a theoretical network is presented, which is useful as a benchmark for particle filtering algorithms designed for multivariable nonlinear systems (potentially linear, nonlinear, and even semi-Markovian jump system). The main goal of the paper is to propose an object that potentially can have similar to the power system grid properties, but with the number of state variables reduced twice (only one state variable for each node, while there are two in the case of power systems). Transition and measurement functions are proposed in the paper, and two types of transition functions are considered: dependent on one or many state variables. In addition, 10 types of measurements are proposed both for branch and nodal cases. The experiments are performed for 14 different, four-dimensional systems. Plants are both linear and highly nonlinear. The results include information about the state estimation quality (based on the mean squared error indicator) and the values of the effective sample size. It is observed how the higher effective sample size resulted in the better estimation quality in subsequent cases. It is also concluded that the very low number of significant particles is the main problem in particle filtering of multivariable systems, and this should be countered. A few potential solutions for the latter are also presented.
The Impacts of a Building’s Thermal Mass on the Cooling Load of a Radiant System under Various Typical Climates
Authors: Hu Rong , Liu Gang , Niu Jianlei
Published: March 2020

Cooling load is difficult to predict for a radiant system, because the interaction between a building’s thermal mass and radiation heat gain has not been well defined in a zone with a cooling surface. This study aims to reveal the effect of thermal mass in an external wall on the transmission load in a space with an active cooling surface. We investigated the thermal performances in a typical office building under various weather conditions by dynamic simulation with Energy-Plus. It was found that the thermal mass in the inside concrete layer had positives in terms of indoor temperature performance and energy conservation. The peak cooling load of the hydronic system decreases 28% in the proper operating state, taking into account the effect of the thermal mass in an external wall. Compared to the performances in zones with equivalent convective air systems (CASs), the peak cooling load and the accumulated load of the combined system (radiant system coupled by fresh air system) are higher by 9%–11% and 3%–4%, respectively. The effect of thermal mass is evident in a transient season with mild weather, when the relative effects are about 45% and 60%, respectively, for a building with radiant systems and a building with equivalent CASs.
Analysis of the Work Productivity and Costs of a Stationary Chipper Applied to the Harvesting of Olive Tree Pruning for Bio-Energy Production
Authors: Suardi Alessandro , Latterini Francesco , Alfano Vincenzo , Palmieri Nadia , Bergonzoli Simone , Pari Luigi
Published: March 2020

Pruning residues could represent an important biomass resources for energy production. Only in Italy it has been estimated that an annual quantity of biomass of over 2600 kt of dry matter could be obtained from olive residues. Several machines developed for pruning harvesting are available in the market, most of which are tractor-driven, while limited knowledge is available on performance, quality of work and costs of harvesting logistics based on stationary chippers. The aim of the present paper is to analyze machine performance of a forestry stationary chipper applied to pruning harvesting for what concerns work productivity, quality of the comminuted product and harvesting operating costs. This system is actually applied by Fiusis Company, an Italian enterprise which manages a biomass power plant exclusively powered by olive trees’ pruning residues, and it has never been analyzed in literature. The results obtained showed consistent work productivity, which resulted the highest ever found in olive pruning harvesting systems and equal to 5.23 ± 0.81 tdm·h−1. This high work productivity allowed also to obtain a little economic gain from a matter, which is actually considered a problem for olive groves’ owners and not a potential source of income. In particular, the use of a stationary chipper seemed very efficient in olive groves with a consistent amount of wooden residues to be processed and with big branches not harvestable by the most common towed pruning harvester. In addition, the stationary chipper has the advantage of avoiding the preliminary raking operation, which results in reduced costs for the farmer.
Effect of Cell Size on the Performance and Temperature Distribution of Molten Carbonate Fuel Cells
Authors: Yu Jae-Hyeong , Lee Chang-Whan
Published: March 2020

Molten carbonate fuel cells (MCFCs) are high-operating-temperature fuel cells with high efficiency and fuel diversity. Electrochemical reactions in MCFCs are exothermic. As the size of the fuel cells increases, the amount of the heat from the fuel cells and the temperature of the fuel cells increase. In this work, we investigated the relationship between the fuel cell stack size and performance by applying computational fluid dynamics (CFD). Three flow types, namely co-flow, cross-flow, and counter-flow, were studied. We found that when the size of the fuel cells increased beyond a certain value, the size of the fuel cell no longer affected the cell performance. The maximum fuel cell temperature converged as the size of the fuel cell increased. The temperature and current density distribution with respect to the size showed a very similar distribution. The converged maximum temperature of the fuel cells depended on the gas flow condition. The maximum temperature of the fuel cell decreased as the amount of gas in the cathode size increased.
Decision Support System for the Production of Miscanthus and Willow Briquettes
Authors: Francik Sławomir , Knapczyk Adrian , Knapczyk Artur , Francik Renata
Published: March 2020

The biomass is regarded as a part of renewable energy sources (RES), which can satisfy energy demands. Biomass obtained from plantations is characterized by low bulk density, which increases transport and storage costs. Briquetting is a technology that relies on pressing biomass with the aim of obtaining a denser product (briquettes). In the production of solid biofuels, the technological as well as material variables significantly influence the densification process, and as a result influence the end quality of briquette. This process progresses differently for different materials. Therefore, the optimal selection of process’ parameters is very difficult. It is necessary to use a decision support tool—decision support system (DSS). The purpose of the work was to develop a decision support system that would indicate the optimal parameters for conducting the process of producing Miscanthus and willow briquettes (pre-comminution, milling and briquetting), briquette parameters (durability and specific density) and total energy consumption based on process simulation. Artificial neural networks (ANNs) were used to describe the relationship between individual parameters of the briquette production process. DSS has the form of a web application and is opened from a web browser (it is possible to open it on various types of devices). The modular design allows the modification and expansion the application in the future.
How Much Human-Caused Global Warming Should We Expect with Business-As-Usual (BAU) Climate Policies? A Semi-Empirical Assessment
Authors: Connolly Ronan , Connolly Michael , Carter Robert M. , Soon Willie
Published: March 2020

In order to assess the merits of national climate change mitigation policies, it is important to have a reasonable benchmark for how much human-caused global warming would occur over the coming century with “Business-As-Usual” (BAU) conditions. However, currently, policymakers are limited to making assessments by comparing the Global Climate Model (GCM) projections of future climate change under various different “scenarios”, none of which are explicitly defined as BAU. Moreover, all of these estimates are ab initio computer model projections, and policymakers do not currently have equivalent empirically derived estimates for comparison. Therefore, estimates of the total future human-caused global warming from the three main greenhouse gases of concern (CO2, CH4, and N2O) up to 2100 are here derived for BAU conditions. A semi-empirical approach is used that allows direct comparisons between GCM-based estimates and empirically derived estimates. If the climate sensitivity to greenhouse gases implies a Transient Climate Response (TCR) of ≥ 2.5 °C or an Equilibrium Climate Sensitivity (ECS) of ≥ 5.0 °C then the 2015 Paris Agreement’s target of keeping human-caused global warming below 2.0 °C will have been broken by the middle of the century under BAU. However, for a TCR < 1.5 °C or ECS < 2.0 °C, the target would not be broken under BAU until the 22nd century or later. Therefore, the current Intergovernmental Panel on Climate Change (IPCC) “likely” range estimates for TCR of 1.0 to 2.5 °C and ECS of 1.5 to 4.5 °C have not yet established if human-caused global warming is a 21st century problem.
Impurity Effects on the Mechanical Properties and Permeability Characteristics of Salt Rock
Authors: Zhang Qiangxing , Liu Jianfeng , Wang Lu , Luo Min , Liu Hejuan , Xu Huining , Zou Hang
Published: March 2020

Impure salt rock strata are extensively distributed in China, giving them great significance in the study of the physical properties of impure salt rock for the construction of underground gas storage in salt mines. To investigate the confining pressure and impurity effects on the mechanical properties and gas permeability characteristics of salt rock, permeability tests under hydrostatic confining pressure and conventional triaxial compression (CTC), on salt rock samples with different impurity contents, were carried out. The results demonstrate that the confining pressure effects cause an increase in triaxial compression strength, but a decrease in permeability. However, impurity enhances the bearing capacity and permeability of the salt rock; both rock strength and permeability increase with an increase in impurity content. Moreover, the broken salt rock specimens were analyzed after the CTC test using Computed Tomography (CT) equipment. To understand the relationships between pore volume and permeability, considering the confining pressure and impurity effects, the cracks were divided into four groups according to different crack diameter ranges: ~0.05 mm, 0.05–1 mm, 1–10 mm and ~10 mm. The CT analysis results show that while the pore volume of smaller cracks shows an “increasing–decreasing” trend by increasing confining pressure, the pore volume of large cracks gradually decreases, indicating that the rock permeability is highly related to macro-cracks. However, impurity has more complicated implications on rock permeability and cracks, and needs further investigation.
Reviewing Municipal Energy System Planning in a Bibliometric Analysis: Evolution of the Research Field between 1991 and 2019
Authors: Weinand Jann Michael
Published: March 2020

In the context of the energy transition, energy system planning is becoming increasingly relevant for decentralized systems. Motivated by the strong increase of publications on municipal energy system planning (MESP), these studies are subjected to a bibliometric analysis in this paper. The 1235 articles, which are based on the Web of Science database, are examined using the R-tool bibliometrix. The study shows that China is the most important contributor with 225 articles, followed by the USA (205) and Germany (120). Most cross-country collaborations were conducted between China and Canada, focusing mainly on uncertainties in MESP. Among the institutions, the North China Electric Power University is responsible for most articles (42). The core journals on MESP are Energy, Applied Energy, Energy Policy, Energies and Renewable Energy, which published 37% of the 1235 articles. Publications on MESP focus on renewable energies, optimization and hybrid energy systems. Furthermore, district heating seems to be a core topic in MESP and is addressed in three of the top five most cited articles. The demonstration of global research trends in MESP can support researchers in identifying the relevant issues regarding this expanding and transforming research area.
Improved Particle Swarm Optimization for Sea Surface Temperature Prediction
Authors: He Qi , Zha Cheng , Song Wei , Hao Zengzhou , Du Yanling , Liotta Antonio , Perra Cristian
Published: March 2020

The Sea Surface Temperature (SST) is one of the key factors affecting ocean climate change. Hence, Sea Surface Temperature Prediction (SSTP) is of great significance to the study of navigation and meteorology. However, SST data is well-known to suffer from high levels of redundant information, which makes it very difficult to realize accurate predictions, for instance when using time-series regression. This paper constructs a simple yet effective SSTP model, dubbed DSL (given its origination from methods known as DTW, SVM and LSPSO). DSL is based on time-series similarity measure, multiple pattern learning and parameter optimization. It consists of three parts: (1) using Dynamic Time Warping (DTW) to mine the similarities in historical SST series; (2) training a Support Vector Machine (SVM) using the top-k similar patterns, deriving a robust SSTP model that offers a 5-day prediction window based on multiple SST input sequences; and (3) developing an improved Particle Swarm Optimization (PSO) method, dubbed LSPSO, which uses a local search strategy to achieve the combined requirement of prediction accuracy and efficiency. Our method strives for optimal model parameters (pattern length and interval step) and is suited for long-term series, leading to significant improvements in SST trend predictions. Our experimental validation shows a 16.7% reduction in prediction error, at a 76% gain in operating efficiency. We also achieve a significant improvement in prediction accuracy of non-stationary SST time series, compared to DTW, SVM, DS (i.e., DTW + SVM), and a recent deep learning method dubbed Long-Short Term Memory (LSTM).