Search results for: energy demand forecasting

Authors: Kianoosh Samimi, Farhad Estakhr, Mahdi Mahdikhani, Faramaz Moodi

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Due to their fluidity and simplicity of use, self-compacting concretes (SCCs) have undeniable advantages. In recent years, the role of metakaolin as a one of pozzolanic materials in concrete has been considered by researchers. It can modify various properties of concrete, due to high pozzolanic reactions and also makes a denser microstructure. The objective of this paper is to examine the influence of three type of Portland cement and metakaolin on fresh state, compressive strength and sulfuric acid attacks in self- consolidating concrete at early age up to 90 days of curing in lime water. Six concrete mixtures were prepared with three types of different cement as Portland cement type II, Portland Slag Cement (PSC), Pozzolanic Portland Cement (PPC) and 15% substitution of metakaolin by every cement. The results show that the metakaolin admixture increases the viscosity and the demand amount of superplasticizer. According to the compressive strength results, the highest value of compressive strength was achieved for PSC and without any metakaolin at age of 90 days. Conversely, the lowest level of compressive strength at all ages of conservation was obtained for PPC and containing 15% metakaolin. According to this study, the total substitution of PSC and PPC by Portland cement type II is beneficial to the increasing in the chemical resistance of the SCC with respect to the sulfuric acid attack. On the other hand, this increase is more noticeable by the use of 15% of metakaolin. Therefore, it can be concluded that metakaolin has a positive effect on the chemical resistance of SCC containing of Portland cement type II, PSC, and PPC.

Keywords: SCC, metakaolin, cement type, durability, compressive strength, sulfuric acid attacks.

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Authors: Chanchal Biswas, Anrin Bhattacharyya, Gopes Chandra Das, Mahua Ghosh Chaudhuri, Rajib Dey

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Boiler coals with low fixed carbon and higher ash content have always challenged the metallurgists to develop a suitable method for their utilization. In the present study, an attempt is made to establish an energy effective method for the reduction of iron ore fines in the form of nuggets by using ‘Syngas’. By devolatisation (expulsion of volatile matter by applying heat) of boiler coal, gaseous product (enriched with reducing agents like CO, CO2, H2, and CH4 gases) is generated. Iron ore nuggets are reduced by this syngas. For that reason, there is no direct contact between iron ore nuggets and coal ash. It helps to control the minimization of the sulphur intake of the reduced nuggets. A laboratory scale devolatisation furnace designed with reduction facility is evaluated after in-depth studies and exhaustive experimentations including thermo-gravimetric (TG-DTA) analysis to find out the volatile fraction present in boiler grade coal, gas chromatography (GC) to find out syngas composition in different temperature and furnace temperature gradient measurements to minimize the furnace cost by applying one heating coil. The nuggets are reduced in the devolatisation furnace at three different temperatures and three different times. The pre-reduced nuggets are subjected to analytical weight loss calculations to evaluate the extent of reduction. The phase and surface morphology analysis of pre-reduced samples are characterized using X-ray diffractometry (XRD), energy dispersive x-ray spectrometry (EDX), scanning electron microscopy (SEM), carbon sulphur analyzer and chemical analysis method. Degree of metallization of the reduced nuggets is 78.9% by using boiler grade coal. The pre-reduced nuggets with lesser sulphur content could be used in the blast furnace as raw materials or coolant which would reduce the high quality of coke rate of the furnace due to its pre-reduced character. These can be used in Basic Oxygen Furnace (BOF) as coolant also.

Keywords: Alternative ironmaking, coal devolatisation, extent of reduction, nugget making, syngas based DRI, solid state reduction.

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Authors: Saeed Sayyad Hagh Shomar

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Traffic congestion pricing in urban streets is one of the most suitable options for solving the traffic problems and environment pollutions in the cities of the country. Unlike its acceptable outcomes, there are problems concerning the necessity to pay by the mass. Regarding the fact that public response in order to succeed in this strategy is so influential, studying their response and behavior to get the feedback and improve the strategies is of great importance. In this study, a questionnaire was used to examine the public reactions to the traffic congestion pricing schemes at the center of Tehran metropolis and the factors involved in people’s decision making in accepting or rejecting the congestion pricing schemes were assessed based on the data obtained from the questionnaire as well as the international experiences. Then, by analyzing and comparing the schemes, guidelines to reduce public objections to them are discussed. The results of reviewing and evaluating the public reactions show that all the pros and cons must be considered to guarantee the success of these projects. Consequently, with targeted public education and consciousness-raising advertisements, prior to initiating a scheme and ensuring the mechanism of the implementation after the start of the project, the initial opposition is reduced and, with the gradual emergence of the real and tangible benefits of its implementation, users’ satisfaction will increase.

Keywords: Demand management, international experiences, traffic congestion pricing, public acceptance, public objection.

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Authors: Mohanapriya Subramanian, V. Raj

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Direct methanol fuel cells (DMFCs) are considered to be one of the most promising candidates for portable and stationary applications in the view of their advantages such as high energy density, easy manipulation, high efficiency and they operate with liquid fuel which could be used without requiring any fuel-processing units. Electrolyte membrane of DMFC plays a key role as a proton conductor as well as a separator between electrodes. Increasing concern over environmental protection, biopolymers gain tremendous interest owing to their eco-friendly bio-degradable nature. Pectin is a natural anionic polysaccharide which plays an essential part in regulating mechanical behavior of plant cell wall and it is extracted from outer cells of most of the plants. The aim of this study is to develop and demonstrate pectin based polymer composite membranes as methanol impermeable polymer electrolyte membranes for DMFCs. Pectin based nanocomposites membranes are prepared by solution-casting technique wherein pectin is blended with chitosan followed by the addition of optimal amount of sulphonic acid modified Titanium dioxide nanoparticle (S-TiO2). Nanocomposite membranes are characterized by Fourier Transform-Infra Red spectroscopy, Scanning electron microscopy, and Energy dispersive spectroscopy analyses. Proton conductivity and methanol permeability are determined into order to evaluate their suitability for DMFC application. Pectin-chitosan blends endow with a flexible polymeric network which is appropriate to disperse rigid S-TiO2 nanoparticles. Resulting nanocomposite membranes possess adequate thermo-mechanical stabilities as well as high charge-density per unit volume. Pectin-chitosan natural polymeric nanocomposite comprising optimal S-TiO2 exhibits good electrochemical selectivity and therefore desirable for DMFC application.

Keywords: Biopolymers, fuel cells, nanocomposite, methanol crossover.

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Authors: Anil Kumar, C. Nagaraja Kumar

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The position and momentum space information entropies of hydrogen atom are exactly evaluated. Using isospectral Hamiltonian approach, a family of isospectral potentials is constructed having same energy eigenvalues as that of the original potential. The information entropy content is obtained in position space as well as in momentum space. It is shown that the information entropy content in each level can be re-arranged as a function of deformation parameter.

Keywords: Information Entropy, BBM inequality, Isospectral Potential.

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Authors: Majid Amidpour, Parisa Karimi, Marzieh Joda

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For the last few years, release of burned undesirable by-products has become a challenging issue in oil industries. Flaring, as one of the main sources of air contamination, involves detrimental and long-lasting effects on human health and is considered a substantial reason for energy losses worldwide. This research involves studying the implications of two main flare gas recovery methods at three oil refineries, all in Iran as the case I, case II, and case III in which the production capacities are increasing respectively. In the proposed methods, flare gases are converted into more valuable products, before combustion by the flare networks. The first approach involves collecting, compressing and converting the flare gas to smokeless fuel which can be used in the fuel gas system of the refineries. The other scenario includes utilizing the flare gas as a feed into liquefied petroleum gas (LPG) production unit already established in the refineries. The processes of these scenarios are simulated, and the capital investment is calculated for each procedure. The cumulative profits of the scenarios are evaluated using Net Present Value method. Furthermore, the sensitivity analysis based on total propane and butane mole fraction is carried out to make a rational comparison for LPG production approach, and the results are illustrated for different mole fractions of propane and butane. As the mole fraction of propane and butane contained in LPG differs in summer and winter seasons, the results corresponding to LPG scenario are demonstrated for each season. The results of the simulations show that cumulative profit in fuel gas production scenario and LPG production rate increase with the capacity of the refineries. Moreover, the investment return time in LPG production method experiences a decline, followed by a rising trend with an increase in C₃ and C₄ content. The minimum value of time return occurs at propane and butane sum concentration values of 0.7, 0.6, and 0.7 in case I, II, and III, respectively. Based on comparison of the time of investment return and cumulative profit, fuel gas production is the superior scenario for three case studies.

Keywords: Flare gas reduction, liquefied petroleum gas, fuel gas, net present value method, sensitivity analysis.

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Authors: J. Olamaei , T. Niknam, M. Nayeripour

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This paper presents an approach for daily optimal operation of distribution networks considering Distributed Generators (DGs). Due to private ownership of DGs, a cost based compensation method is used to encourage DGs in active and reactive power generation. The objective function is summation of electrical energy generated by DGs and substation bus (main bus) in the next day. A genetic algorithm is used to solve the optimal operation problem. The approach is tested on an IEEE34 buses distribution feeder.

Keywords: Distributed Generator, Daily Optimal Operation, Genetic Algorithm.

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Authors: C.-C. Lin, S.-C. Kan, C.-W. Yeh, C.-I Chen, C.-J. Shieh, Y.-C. Liu

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In this study, lipid-deprived residuals of microalgae were hydrolyzed for the production of reducing sugars by using the recombinant Bacillus cellulosome, carrying eight genes from the Clostridium thermocellum ATCC27405. The obtained cellulosome was found to exist mostly in the broth supernatant with a cellulosome activity of 2.4 U/mL. Furthermore, the Michaelis-Menten constant (Km) and Vmax of cellulosome were found to be 14.832 g/L and 3.522 U/mL. The activation energy of the cellulosome to hydrolyze microalgae LDRs was calculated as 32.804 kJ/mol.

Keywords: Lipid-deprived residuals of microalgae, cellulosome, cellulose, reducing sugars, kinetics.

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Authors: Reza Keihani, Ali Bahadori-Jahromi, Timothy James Clacy

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Plastic as an environmental burden is a well-rehearsed topic in the research area. This is due to its global demand and destructive impacts on the environment, which has been a significant concern to the governments. Typically, the use of plastic in the construction industry is seen across low-density, non-structural applications due to its diverse range of benefits including high strength-to-weight ratios, manipulability and durability. It can be said that with the level of plastic consumption experienced in the construction industry, an ongoing responsibility is shown for this sector to continually innovate alternatives for application of recycled plastic waste such as using plastic made replacement from polyethylene, polystyrene, polyvinyl and polypropylene in the concrete mix design. In this study, the impact of partially replaced fine aggregate with polypropylene in the concrete mix design was investigated to evaluate the concrete’s compressive strength by conducting an experimental work which comprises of six concrete mix batches with polypropylene replacements ranging from 0.5 to 3.0%. The results demonstrated a typical decline in the compressive strength with the addition of plastic aggregate, despite this reduction generally mitigated as the level of plastic in the concrete mix increased. Furthermore, two of the six plastic-containing concrete mixes tested in the current study exceeded the ST5 standardised prescribed concrete mix compressive strength requirement at 28-days containing 1.50% and 2.50% plastic aggregates, which demonstrated the potential for use of recycled polypropylene in structural applications, as a partial by mass, fine aggregate replacement in the concrete mix.

Keywords: Compressive strength, concrete, polypropylene, sustainability.

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Authors: GuoQiang Peng, Yi Sun

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In this paper, based on the work in [1], we further give a general model for acquiring knowledge, which first focuses on the research of how and when things involved in problems are made then describes the goals, the energy and the time to give an optimum model to decide how many related things are supposed to be involved in. Finally, we acquire knowledge from this model in which there are the attributes, actions and connections of the things involved at the time when they are born and the time in their life. This model not only improves AI theories, but also surely brings the effectiveness and accuracy for AI system because systems are given more knowledge when reasoning or computing is used to bring about results.

Keywords: Time, knowledge, model.

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Authors: Sotirios Raptis

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Linking social needs to social classes using different criteria may lead to social services misuse. The paper discusses using ML and Neural Networks (NNs) in linking public services in Scotland in the long term and advocates, this can result in a reduction of the services cost connecting resources needed in groups for similar services. The paper combines typical regression models with clustering and cross-correlation as complementary constituents to predict the demand. Insurance companies and public policymakers can pack linked services such as those offered to the elderly or to low-income people in the longer term. The work is based on public data from 22 services offered by Public Health Services (PHS) Scotland and from the Scottish Government (SG) from 1981 to 2019 that are broken into 110 years series called factors and uses Linear Regression (LR), Autoregression (ARMA) and 3 types of back-propagation (BP) Neural Networks (BPNN) to link them under specific conditions. Relationships found were between smoking related healthcare provision, mental health-related health services, and epidemiological weight in Primary 1(Education) Body Mass Index (BMI) in children. Primary component analysis (PCA) found 11 significant factors while C-Means (CM) clustering gave 5 major factors clusters.

Keywords: Probability, cohorts, data frames, services, prediction.

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Authors: Abdullah A. Al Orainy

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Small cell backhaul solutions need to be cost-effective, scalable, and easy to install. This paper presents an overview of small cell backhaul technologies. Wireless solutions including TV white space, satellite, sub-6 GHz radio wave, microwave and mmWave with their backhaul characteristics are discussed. Recent research on issues like beamforming, backhaul architecture, precoding and large antenna arrays, and energy efficiency for dense small cell backhaul with mmWave communications is reviewed. Recent trials of 5G technologies are summarized.

Keywords: Backhaul, Small Cells, Wireless, 5G.

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Authors: P. K. Singhal, R. Naresh, V. Sharma

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This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: Artificial bee colony algorithm, economic dispatch, unit commitment, wind power.

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Authors: P. K. Singhal, R. Naresh, V. Sharma

Abstract:

This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: Artificial bee colony algorithm, economic dispatch, unit commitment, wind power.

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Authors: Siqing Chen

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The vast rural landscape in the southern United States is conspicuously characterized by the hedgerow trees or groves. The patchwork landscape of fields surrounded by high hedgerows is a traditional and familiar feature of the American countryside. Hedgerows are in effect linear strips of trees, groves, or woodlands, which are often critical habitats for wildlife and important for the visual quality of the landscape. As landscape interfaces, hedgerows define the spaces in the landscape, give the landscape life and meaning, and enrich ecologies and cultural heritages of the American countryside. Although hedgerows were originally intended as fences and to mark property and townland boundaries, they are not merely the natural or man-made additions to the landscape--they have gradually become “naturalized" into the landscape, deeply rooted in the rural culture, and now formed an important component of the southern American rural environment. However, due to the ever expanding real estate industry and high demand for new residential development, substantial areas of authentic hedgerow landscape in the southern United States are being urbanized. Using Hudson Farm as an example, this study illustrated guidelines of how hedgerows can be integrated into town planning as green infrastructure and landscape interface to innovate and direct sustainable land use, and suggest ways in which such vernacular landscapes can be preserved and integrated into new development without losing their contextual inspiration.

Keywords: Hedgerow, Town planning, Sustainable design, Ecological infrastructure

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Authors: B. Rezaei, N. Amiri, N. Azizi

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Using calculated phase- shift values, for pp, nn, and np elastic scattering in the energy range 1MeV to 350MeV, the charge independence breaking of nucleon-nucleon interaction is investigated. We have used Darboux transformation to calculate phase-shift for the first three values of

Keywords: Phase-shift, charge independence breaking, Darboux transformation.

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Authors: Chun-Der Chen, Yi-Wen Fan, Cheng-Kiang Farn

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In today-s competitive global business environment, the concept of supply chain management (SCM) continues to become increasingly market-oriented, shifting the primary driver of the value chain from supply to demand. Recent recommendations encourage researchers to focus investigations on the supply chain process integration (SCPI) capabilities that integrate a focal firm with its network of suppliers and business customers to create value for it. However, theoretical and empirical researches pertaining to the antecedents and consequences of a focal firm-s SCPI capabilities have been limited and piecemeal. The purpose of this study is to investigate the critical determinants and consequences of a focal firm-s SCPI capabilities. We test our proposed research framework using a sample of 139 sales managers of manufacturing industries in Taiwan, our research findings show that (1) both perceived business customer-s power and focal firm-s market-oriented culture positively influences a focal firm-s SCPI capabilities, and (2) SCPI capabilities positively influence a focal firm-s SCM performance, both operational and strategic benefits. Implications for practitioners and researchers and suggestions for future research are also addressed in this study.

Keywords: Supply chain process integration capabilities, Perceived business customer's power, Market-oriented culture, Supply chain management performance.

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Authors: A. R. Binesh, S. Hossainpour

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Due to the stringent legislation for emission of diesel engines and also increasing demand on fuel consumption, the importance of detailed 3D simulation of fuel injection, mixing and combustion have been increased in the recent years. In the present work, FIRE code has been used to study the detailed modeling of spray and mixture formation in a Caterpillar heavy-duty diesel engine. The paper provides an overview of the submodels implemented, which account for liquid spray atomization, droplet secondary break-up, droplet collision, impingement, turbulent dispersion and evaporation. The simulation was performed from intake valve closing (IVC) to exhaust valve opening (EVO). The predicted in-cylinder pressure is validated by comparing with existing experimental data. A good agreement between the predicted and experimental values ensures the accuracy of the numerical predictions collected with the present work. Predictions of engine emissions were also performed and a good quantitative agreement between measured and predicted NOx and soot emission data were obtained with the use of the present Zeldowich mechanism and Hiroyasu model. In addition, the results reported in this paper illustrate that the numerical simulation can be one of the most powerful and beneficial tools for the internal combustion engine design, optimization and performance analysis.

Keywords: Diesel engine, Combustion, Pollution, CFD.

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Authors: Wen-Chi Hou, Cheng Luo, Zhewei Jiang, Feng Yan

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In this research, we propose to use the discrete cosine transform to approximate the cumulative distributions of data cube cells- values. The cosine transform is known to have a good energy compaction property and thus can approximate data distribution functions easily with small number of coefficients. The derived estimator is accurate and easy to update. We perform experiments to compare its performance with a well-known technique - the (Haar) wavelet. The experimental results show that the cosine transform performs much better than the wavelet in estimation accuracy, speed, space efficiency, and update easiness.

Keywords: DCT, Data Cube

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Authors: Oleksandr Krykunov

Abstract:

The source voltage of high-power fuel cell shows strong load dependence at comparatively low voltage levels. In order to provide the voltage of 750V on the DC-link for feeding electrical energy into the mains via a three phase inverter a step-up converter with a large step-up ratio is required. The output voltage of this DC/DC-converter must be stabile during variations of the load current and the voltage of the fuel cell. This paper presents the methods and results of the calculation of the efficiency and the expense for the realization for the circuits of the DC/DC-converter that meet these requirements.

Keywords: DC/DC-converter, calculation, efficiency, fuel cell.

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Authors: D. Boutana, B. Barkat , F. Marir

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In this paper, we propose a novel time-frequency distribution (TFD) for the analysis of multi-component signals. In particular, we use synthetic as well as real-life speech signals to prove the superiority of the proposed TFD in comparison to some existing ones. In the comparison, we consider the cross-terms suppression and the high energy concentration of the signal around its instantaneous frequency (IF).

Keywords: Cohen's Class, Multicomponent signal, SeparableKernel, Speech signal, Time- frequency resolution.

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Authors: J. D. Marinaccio, I. Mabbett, C. Glover, D. Worsley

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Through use of novel modern/rapid processing techniques such as screen printing and Near-Infrared (NIR) radiative curing, process time for the sintering of sintered nickel plaques, applicable to alkaline nickel battery chemistries, has been drastically reduced from in excess of 200 minutes with conventional convection methods to below 2 minutes using NIR curing methods. Steps have also been taken to remove the need for forming gas as a reducing agent by implementing carbon as an in-situ reducing agent, within the ink formulation.

Keywords: Batteries, energy, iron, nickel, storage.

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Authors: E. Al Daoud

Abstract:

In many cases, theoretical treatments are available for models for which there is no perfect physical realization. In this situation, the only possible test for an approximate theoretical solution is to compare with data generated from a computer simulation. In this paper, Monte Carlo tools are used to study and compare the elementary particles models. All the experiments are implemented using 10000 events, and the simulated energy is 13 TeV. The mean and the curves of several variables are calculated for each model using MadAnalysis 5. Anomalies in the results can be seen in the muons masses of the minimal supersymmetric standard model and the two Higgs doublet model.

Keywords: Feynman rules, hadrons, Lagrangian, Monte Carlo, simulation.

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Authors: Wann-Ming Wey

Abstract:

In recent years, in addition to face the external threats such as energy shortages and climate change, traffic congestion and environmental pollution have become anxious problems for many cities. Considering private automobile-oriented urban development had produced many negative environmental and social impacts, the transit-oriented development (TOD) has been considered as a sustainable urban model. TOD encourages public transport combined with friendly walking and cycling environment designs, however, non-motorized modes help improving human health, energy saving, and reducing carbon emissions. Due to environmental changes often affect the planners’ decision-making; this research applies dynamic network process (DNP) which includes the time dependent concept to promoting friendly walking and cycling environmental designs as an advanced planning support system for environment improvements.

This research aims to discuss what kinds of design strategies can improve a friendly walking and cycling environment under TOD. First of all, we collate and analyze environment designing factors by reviewing the relevant literatures as well as divide into three aspects of “safety”, “convenience”, and “amenity” from fifteen environment designing factors. Furthermore, we utilize fuzzy Delphi Technique (FDT) expert questionnaire to filter out the more important designing criteria for the study case. Finally, we utilized DNP expert questionnaire to obtain the weights changes at different time points for each design criterion. Based on the changing trends of each criterion weight, we are able to develop appropriate designing strategies as the reference for planners to allocate resources in a dynamic environment. In order to illustrate the approach we propose in this research, Taipei city as one example has been used as an empirical study, and the results are in depth analyzed to explain the application of our proposed approach.

Keywords: Environment Planning Support Systems, Walking and Cycling, Transit-oriented Development (TOD), Dynamic Network Process (DNP).

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Authors: C. Silveira, A. Ascenso, J. Ferreira, A. I. Miranda, P. Tuccella, G. Curci

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Poor air quality is one of the main environmental causes of premature deaths worldwide, and mainly in cities, where the majority of the population lives. It is a consequence of successive land cover (LC) and use changes, as a result of the intensification of human activities. Knowing these landscape modifications in a comprehensive spatiotemporal dimension is, therefore, essential for understanding variations in air pollutant concentrations. In this sense, the use of air quality models is very useful to simulate the physical and chemical processes that affect the dispersion and reaction of chemical species into the atmosphere. However, the modelling performance should always be evaluated since the resolution of the input datasets largely dictates the reliability of the air quality outcomes. Among these data, the updated LC is an important parameter to be considered in atmospheric models, since it takes into account the Earth’s surface changes due to natural and anthropic actions, and regulates the exchanges of fluxes (emissions, heat, moisture, etc.) between the soil and the air. This work aims to evaluate the performance of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), when different LC classifications are used as an input. The influence of two LC classifications was tested: i) the 24-classes USGS (United States Geological Survey) LC database included by default in the model, and the ii) CLC (Corine Land Cover) and specific high-resolution LC data for Portugal, reclassified according to the new USGS nomenclature (33-classes). Two distinct WRF-Chem simulations were carried out to assess the influence of the LC on air quality over Europe and Portugal, as a case study, for the year 2015, using the nesting technique over three simulation domains (25 km², 5 km² and 1 km² horizontal resolution). Based on the 33-classes LC approach, particular emphasis was attributed to Portugal, given the detail and higher LC spatial resolution (100 m x 100 m) than the CLC data (5000 m x 5000 m). As regards to the air quality, only the LC impacts on tropospheric ozone concentrations were evaluated, because ozone pollution episodes typically occur in Portugal, in particular during the spring/summer, and there are few research works relating to this pollutant with LC changes. The WRF-Chem results were validated by season and station typology using background measurements from the Portuguese air quality monitoring network. As expected, a better model performance was achieved in rural stations: moderate correlation (0.4 – 0.7), BIAS (10 – 21µg.m^-3) and RMSE (20 – 30 µg.m^-3), and where higher average ozone concentrations were estimated. Comparing both simulations, small differences grounded on the Leaf Area Index and air temperature values were found, although the high-resolution LC approach shows a slight enhancement in the model evaluation. This highlights the role of the LC on the exchange of atmospheric fluxes, and stresses the need to consider a high-resolution LC characterization combined with other detailed model inputs, such as the emission inventory, to improve air quality assessment.

Keywords: Land cover, tropospheric ozone, WRF-Chem, air quality assessment.

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Authors: H. El Khattabi, A. Tamtaoui, D. Aboutajdine

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In this paper, we present the video quality measure estimation via a neural network. This latter predicts MOS (mean opinion score) by providing height parameters extracted from original and coded videos. The eight parameters that are used are: the average of DFT differences, the standard deviation of DFT differences, the average of DCT differences, the standard deviation of DCT differences, the variance of energy of color, the luminance Y, the chrominance U and the chrominance V. We chose Euclidean Distance to make comparison between the calculated and estimated output.

Keywords: video, neural network MLP, subjective quality, DCT, DFT, Retropropagation

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Authors: Vrajesh Mehta, Anal Chavan

Abstract:

Treatment of tar-containing wastewater is necessary for the successful operation of biomass gasification plants (BGPs). In the present study, tar-containing wastewater was treated using lime and alum for the removal of in-organics, followed by adsorption on powdered activated carbon (PAC) for the removal of organics. Limealum experiments were performed in a jar apparatus and activated carbon studies were performed in an orbital shaker. At optimum concentrations, both lime and alum individually proved to be capable of removing color, total suspended solids (TSS) and total dissolved solids (TDS), but in both cases, pH adjustment had to be carried out after treatment. The combination of lime and alum at the dose ratio of 0.8:0.8 g/L was found to be optimum for the removal of inorganics. The removal efficiency achieved at optimum concentrations were 78.6, 62.0, 62.5 and 52.8% for color, alkalinity, TSS and TDS, respectively. The major advantages of the lime-alum combination were observed to be as follows: no requirement of pH adjustment before and after treatment and good settleability of sludge. Coagulation-precipitation followed by adsorption on PAC resulted in 92.3% chemical oxygen demand (COD) removal and 100% phenol removal at equilibrium. Ammonia removal efficiency was found to be 11.7% during coagulation-flocculation and 36.2% during adsorption on PAC. Adsorption of organics on PAC in terms of COD and phenol followed Freundlich isotherm with Kf = 0.55 & 18.47 mg/g and n = 1.01 & 1.45, respectively. This technology may prove to be one of the fastest and most techno-economically feasible methods for the treatment of tar-containing wastewater generated from BGPs.

Keywords: Activated carbon, Alum, Biomass gasification, Coagulation-flocculation, Lime, Tar-containing wastewater.

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Authors: Mohamed Al Mahdi Eshtawie, Masuri Bin Othman

Abstract:

Finite impulse response (FIR) filters have the advantage of linear phase, guaranteed stability, fewer finite precision errors, and efficient implementation. In contrast, they have a major disadvantage of high order need (more coefficients) than IIR counterpart with comparable performance. The high order demand imposes more hardware requirements, arithmetic operations, area usage, and power consumption when designing and fabricating the filter. Therefore, minimizing or reducing these parameters, is a major goal or target in digital filter design task. This paper presents an algorithm proposed for modifying values and the number of non-zero coefficients used to represent the FIR digital pulse shaping filter response. With this algorithm, the FIR filter frequency and phase response can be represented with a minimum number of non-zero coefficients. Therefore, reducing the arithmetic complexity needed to get the filter output. Consequently, the system characteristic i.e. power consumption, area usage, and processing time are also reduced. The proposed algorithm is more powerful when integrated with multiplierless algorithms such as distributed arithmetic (DA) in designing high order digital FIR filters. Here the DA usage eliminates the need for multipliers when implementing the multiply and accumulate unit (MAC) and the proposed algorithm will reduce the number of adders and addition operations needed through the minimization of the non-zero values coefficients to get the filter output.

Keywords: Pulse shaping Filter, Distributed Arithmetic, Optimization algorithm.

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Authors: Abid Hossain Khan, Syam Hasan, M. A. R. Sarkar

Abstract:

Fukushima disaster is one of the most publicly exposed accidents in a nuclear facility which has changed the outlook of people towards nuclear power. Some have used it as an example to establish nuclear energy as an unsafe source, while others have tried to find the real reasons behind this accident. Many papers have tried to shed light on the possible causes, some of which are purely based on assumptions while others rely on rigorous data analysis. To our best knowledge, none of the works can say with absolute certainty that there is a single prominent reason that has paved the way to this unexpected incident. This paper attempts to compile all the apparent reasons behind Fukushima disaster and tries to analyze and identify the most likely one.

Keywords: Fuel meltdown, Fukushima disaster, manmade calamity, nuclear facility, tsunami.

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Authors: S. Chahba, R. Sehab, A. Akrad, C. Morel

Abstract:

Nowadays, the electric machines used in urban electric vehicles are, in most cases, three-phase electric machines with or without a magnet in the rotor. Permanent Magnet Synchronous Machine (PMSM) and Induction Machine (IM) are the main components of drive trains of electric and hybrid vehicles. These machines have very good performance in healthy operation mode, but they are not redundant to ensure safety in faulty operation mode. Faced with the continued growth in the demand for electric vehicles in the automotive market, improving the reliability of electric vehicles is necessary over the lifecycle of the electric vehicle. Multiphase electric machines respond well to this constraint because, on the one hand, they have better robustness in the event of a breakdown (opening of a phase, opening of an arm of the power stage, intern-turn short circuit) and, on the other hand, better power density. In this work, a diagnosis approach using a neural network for an open circuit fault or more of a five-phase induction machine is developed. Validation on the simulator of the vehicle drivetrain, at reduced power, is carried out, creating one and more open circuit stator phases showing the efficiency and the reliability of the new approach to detect and to locate on-line one or more open phases of a five-induction machine.

Keywords: Electric vehicle drivetrain, multiphase drives, induction machine, control, open circuit fault diagnosis, artificial neural network.

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