Search results for: wind turbine (WT) modeling

Authors: Mohsen Khaledian, Razali Ismail, Mehdi Saeidmanesh, Mahdiar Hosseinghadiry

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A semi-analytical model for impact ionization coefficient of graphene nanoribbon (GNR) is presented. The model is derived by calculating probability of electrons reaching ionization threshold energy Et and the distance traveled by electron gaining Et. In addition, ionization threshold energy is semi-analytically modeled for GNR. We justify our assumptions using analytic modeling and comparison with simulation results. Gaussian simulator together with analytical modeling is used in order to calculate ionization threshold energy and Kinetic Monte Carlo is employed to calculate ionization coefficient and verify the analytical results. Finally, the profile of ionization is presented using the proposed models and simulation and the results are compared with that of silicon.

Keywords: nanostructures, electronic transport, semiconductor modeling, systems engineering

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Authors: Chandra Shekhar Prasad, Ludek Pesek Prasad

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In the present day fan blade of aero engine, turboprop propellers, gas turbine or steam turbine low-pressure blades are getting bigger, lighter and thus, become more flexible. Therefore, flutter, forced blade response and vibration related failure of the high aspect ratio blade are of main concern for the designers, thus need to be address properly in order to achieve successful component design. At the preliminary design stage large number of design iteration is need to achieve the utter free safe design. Most of the numerical method used for aeroelastic analysis is based on field-based methods such as finite difference method, finite element method, finite volume method or coupled. These numerical schemes are used to solve the coupled fluid Flow-Structural equation based on full Naiver-Stokes (NS) along with structural mechanics’ equations. These type of schemes provides very accurate results if modeled properly, however, they are computationally very expensive and need large computing recourse along with good personal expertise. Therefore, it is not the first choice for aeroelastic analysis during preliminary design phase. A reduced order aeroelastic model (ROAM) with acceptable accuracy and fast execution is more demanded at this stage. Similar ROAM are being used by other researchers for aeroelastic and force response analysis of turbomachinery. In the present paper new medium fidelity ROAM is successfully developed and implemented in numerical tool to simulated the aeroelastic stability phenomena in turbomachinery and well as flexible wings. In the present, a hybrid flow solver based on 3D viscous-inviscid coupled 3D panel method (PM) and 3d discrete vortex particle method (DVM) is developed, viscous parameters are estimated using boundary layer(BL) approach. This method can simulate flow separation and is a good compromise between accuracy and speed compared to CFD. In the second phase of the research work, the flow solver (PM) will be coupled with ROM non-linear beam element method (BEM) based FEM structural solver (with multibody capabilities) to perform the complete aeroelastic simulation of a steam turbine bladed disk, propellers, fan blades, aircraft wing etc. The partitioned based coupling approach is used for fluid-structure interaction (FSI). The numerical results are compared with experimental data for different test cases and for the blade cascade test case, experimental data is obtained from in-house lab experiments at IT CAS. Furthermore, the results from the new aeroelastic model will be compared with classical CFD-CSD based aeroelastic models. The proposed methodology for the aeroelastic stability analysis of gas turbine or steam turbine blades, or propellers or fan blades will provide researchers and engineers a fast, cost-effective and efficient tool for aeroelastic (classical flutter) analysis for different design at preliminary design stage where large numbers of design iteration are required in short time frame.

Keywords: aeroelasticity, beam element method (BEM), discrete vortex particle method (DVM), classical flutter, fluid-structure interaction (FSI), panel method, reduce order aeroelastic model (ROAM), turbomachinery, viscous-inviscid coupling

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Authors: Mathias B. Michael, Esther T. Akinlabi, Tien-Chien Jen

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Thermal energy consumption in palm oil production plant comprises mainly of steam, hot water and hot air. In most efficient plants, hot water and air are generated from the steam supply system. Research has shown that thermal energy utilize in palm oil production plants is about 70 percent of the total energy consumption of the plant. In order to manage the plants’ energy efficiently, the energy systems are modelled and optimized. This paper aimed to present the model of steam supply systems of a typical palm oil production plant in Ghana. The models include exergy and energy models of steam boiler, steam turbine and the palm oil mill. The paper further simulates the virtual plant model to obtain the thermal energy performance of the plant under study. The simulation results show that, under normal operating condition, the boiler energy performance is considerably below the expected level as a result of several factors including intermittent biomass fuel supply, significant moisture content of the biomass fuel and significant heat losses. The total thermal energy performance of the virtual plant is set as a baseline. The study finally recommends number of energy efficiency measures to improve the plant’s energy performance.

Keywords: palm biomass, steam supply, exergy and energy models, energy performance benchmark

Procedia PDF Downloads 347

Authors: Salman Mohamadi, Seyed Mohammad Ali Tayaranian Hosseini, Hamidreza Amindavar

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In this paper, we provide a procedure to analyze and model EEG (electroencephalogram) signal as a time series using ARIMA-GARCH to predict an epileptic attack. The heteroskedasticity of EEG signal is examined through the ARCH or GARCH, (Autore- gressive conditional heteroskedasticity, Generalized autoregressive conditional heteroskedasticity) test. The best ARIMA-GARCH model in AIC sense is utilized to measure the volatility of the EEG from epileptic canine subjects, to forecast the future values of EEG. ARIMA-only model can perform prediction, but the ARCH or GARCH model acting on the residuals of ARIMA attains a con- siderable improved forecast horizon. First, we estimate the best ARIMA model, then different orders of ARCH and GARCH modelings are surveyed to determine the best heteroskedastic model of the residuals of the mentioned ARIMA. Using the simulated conditional variance of selected ARCH or GARCH model, we suggest the procedure to predict the oncoming seizures. The results indicate that GARCH modeling determines the dynamic changes of variance well before the onset of seizure. It can be inferred that the prediction capability comes from the ability of the combined ARIMA-GARCH modeling to cover the heteroskedastic nature of EEG signal changes.

Keywords: epileptic seizure prediction , ARIMA, ARCH and GARCH modeling, heteroskedasticity, EEG

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Authors: Ebrahim H. Kapeel, Ehab Safwat, Hossam Hendy, Ahmed M. Kamel, Yehia Z. Elhalwagy

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Motivated by the problem of the availability of high-fidelity flight simulation models for small unmanned aerial vehicles (UAVs). This paper focuses on the geometric-mass inertia modeling and the actuation system modeling for the small fixed-wing UAVs. The UAV geometric parameters for the body, wing, horizontal and vertical tail are physically measured. Pendulum experiment with high-grade sensors and data analysis using MATLAB is used to estimate the airplane moment of inertia (MOI) model. Finally, UAV’s actuation system is modeled by estimating each servo transfer function by using the system identification, which uses experimental measurement for input and output angles through using field-programmable gate array (FPGA). Experimental results for the designed models are given to illustrate the effectiveness of the methodology. It also gives a very promising result to finalize the open-loop flight simulation model through modeling the propulsion system and the aerodynamic system.

Keywords: unmanned aerial vehicle, geometric-mass inertia model, system identification, Simulink

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Authors: L. Srikanth, D. Neelima Satyam

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The transmission line towers are one of the important life line structures in the distribution of power from the source to the various places for several purposes. The predominant external loads which act on these towers are wind and earthquake loads. In this present study tower is analyzed using Indian Standards IS: 875:1987 (Wind Load), IS: 802:1995 (Structural Steel), IS:1893:2002 (Earthquake) and dynamic analysis of tower has been performed considering ground motion of 2001 Bhuj Earthquake (India). The dynamic analysis was performed considering a tower system consisting two towers spaced 800m apart and 35m height each. This analysis has been performed using numerical time stepping finite difference method which is central difference method were employed by a developed MATLAB program to get the normalized ground motion parameters includes acceleration, frequency, velocity which are important in designing the tower. The tower is analyzed using response spectrum analysis.

Keywords: response spectra, dynamic analysis, central difference method, transmission tower

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Authors: Kamran Siddique, Hiroyuki Asada, Yoshifumi Ogami

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Micro gas turbine (MGT) nowadays has a wide variety of applications from drones to hybrid electric vehicles. As microfabrication technology getting better, the size of MGT is getting smaller. Overall performance of MGT is dependent on the individual components. Each component’s performance is dependent and interrelated with another component. Therefore, careful consideration needs to be given to each and every individual component of MGT. In this study, the focus is on improving the performance of the compressor in order to improve the overall performance of MGT. Computational Fluid Dynamics (CFD) is being performed using the software FLUENT to analyze the design of a micro compressor. Operating parameters like mass flow rate and RPM, and design parameters like inner blade angle (IBA), outer blade angle (OBA), blade thickness and number of blades are varied to study its effect on the performance of the compressor. Pressure ratio is used as a tool to measure the performance of the compressor. Higher the pressure ratio, better the design is. In the study, target mass flow rate is 0.2 g/s and RPM to be less than or equal to 900,000. So far, a pressure ratio of above 3 has been achieved at 0.2 g/s mass flow rate with 5 rotor blades, 0.36 mm blade thickness, 94.25 degrees OBA and 10.46 degrees IBA. The design in this study differs from a regular centrifugal compressor used in conventional gas turbines such that compressor is designed keeping in mind ease of manufacturability. So, this study proposes a compressor design which has a good pressure ratio, and at the same time, it is easy to manufacture using current microfabrication technologies.

Keywords: computational fluid dynamics, FLUENT microfabrication, RPM

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Authors: Oulad Naoui Noureddine, Cherif ELAmine, Djehiche Abdelkader

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Water resources management includes several disciplines; the modeling of rainfall-runoff relationship is the most important discipline to prevent natural risks. There are several models to study rainfall-runoff relationship in watersheds. However, the majority of these models are not applicable in all basins of the world.  In this study, a new stochastic method called The Only Corresponding Competitor method (OCC) was used for the hydrological modeling of M’ZAB   Watershed (South East of Algeria) to adapt a few empirical models for any hydrological regime.  The results obtained allow to authorize a certain number of visions, in which it would be interesting to experiment with hydrological models that improve collectively or separately the data of a catchment by the OCC method.

Keywords: modelling, optimization, rainfall-runoff relationship, empirical model, OCC

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Authors: K. Thakkar, C. Ghenai

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An integrated modeling approach was used in this study to (1) track energy consumption, production, and resource extraction, (2) track greenhouse gases emissions and (3) analyze emissions for local and regional air pollutions. The model was used in this study for short and long term energy and GHG emissions reduction analysis for the state of Florida. The integrated modeling methodology will help to evaluate the alternative energy scenarios and examine emissions-reduction strategies. The mitigation scenarios have been designed to describe the future energy strategies. They consist of various demand and supply side scenarios. One of the GHG mitigation scenarios is crafted by taking into account the available renewable resources potential for power generation in the state of Florida to compare and analyze the GHG reduction measure against ‘Business As Usual’ and ‘Florida State Policy’ scenario. Two more ‘integrated’ scenarios, (‘Electrification’ and ‘Efficiency and Lifestyle’) are crafted through combination of various mitigation scenarios to assess the cumulative impact of the reduction measures such as technological changes and energy efficiency and conservation.

Keywords: energy planning, climate change mitigation assessment, integrated modeling approach, energy alternatives, and GHG emission reductions

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Authors: Erisasadat Sahebzamani, Núria Forcada, Francisco Lendinez

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Global climate change has become increasingly problematic over the past few decades. The construction industry has contributed to greenhouse gas emissions in recent decades. Considering these issues and the high demand for materials in the construction industry, Circular Economy (CE) is considered necessary to keep materials in the loop and extend their useful lives. By providing tangible benefits, Construction 4.0 facilitates the adoption of CE by reducing waste, updating standard work, sharing knowledge, and increasing transparency and stability. This study aims to present a framework for integrating CE and digital tools like Building Information Modeling (BIM) and Virtual Reality (VR) to examine the impact on the construction industry based on stakeholders' perspectives.

Keywords: circular economy, building information modeling, virtual reality, stakeholder engagement

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Authors: Fawzi Srairi, Abderrahmane Dib

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Recently, the desire for a self-powered micro and nanodevices has attracted a great interest of using sustainable energy sources. Further, the ultimate goal of nanogenerator is to harvest energy from the ambient environment in which a self-powered device based on these generators is needed. With the development of nanogenerator-based circuits design and optimization, the building of new device simulator is necessary for the study and the synthesis of electromechanical parameters of this type of models. In the present article, both numerical modeling and optimization of piezoelectric nanogenerator based on zinc oxide have been carried out. They aim to improve the electromechanical performances, robustness, and synthesis process for nanogenerator. The proposed model has been developed for a systematic study of the nanowire morphology parameters in stretching mode. In addition, heuristic optimization technique, namely, particle swarm optimization has been implemented for an analytic modeling and an optimization of nanogenerator-based process in stretching mode. Moreover, the obtained results have been tested and compared with conventional model where a good agreement has been obtained for excitation mode. The developed nanogenerator model can be generalized, extended and integrated into simulators devices to study nanogenerator-based circuits.

Keywords: electrical potential, heuristic algorithms, numerical modeling, nanogenerator

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Authors: Payam Nejat, Fatemeh Jomehzadeh, Muhamad Zaimi Abd. Majid, Mohd.Badruddin Yusof, Hasrul Haidar Ismail

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Currently, building energy consumption has become an international issue especially in developing countries such as Saudi Arabia. In Saudi Arabia 14% of total final energy consumption is utilized in the building sector. Due to hot arid climate, 60% of total building energy consumption in this country is associated with cooling systems. In addition in 2011, this country was one of top ten CO2 emitting countries which illustrate the significance of renewable resources to sustaining the energy consumption. Wind as an important renewable energy can play a prominent role to supply natural ventilation inside the building and windcatcher as a traditional technique can be implemented for this purpose. In this paper the different types of windcatchers, its performance and function was reviewed. It can be concluded due high temperature and low humidity in most area of Saudi Arabia this technique can be successfully be employed and help to reduce fossil energy consumption and related CO2 emissions.

Keywords: natural ventilation, windcatcher, wind, badgir

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Authors: Abeer Samy, Oliver C. Saavedra Valeriano, Abdelazim Negm

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The Blue Nile Basin is the most important tributary of the Nile River. Egypt and Sudan are almost dependent on water originated from the Blue Nile. This multi-dependency creates conflicts among the three countries Egypt, Sudan, and Ethiopia making the management of these conflicts as an international issue. Good assessment of the water resources of the Blue Nile is an important to help in managing such conflicts. Hydrological models are good tool for such assessment. This paper presents a critical review of the nature and variability of the climate and hydrology of the Blue Nile Basin as a first step of using hydrological modeling to assess the water resources of the Blue Nile. Many several attempts are done to develop basin-scale hydrological modeling on the Blue Nile. Lumped and semi distributed models used averages of meteorological inputs and watershed characteristics in hydrological simulation, to analyze runoff for flood control and water resource management. Distributed models include the temporal and spatial variability of catchment conditions and meteorological inputs to allow better representation of the hydrological process. The main challenge of all used models was to assess the water resources of the basin is the shortage of the data needed for models calibration and validation. It is recommended to use distributed model for their higher accuracy to cope with the great variability and complexity of the Blue Nile basin and to collect sufficient data to have more sophisticated and accurate hydrological modeling.

Keywords: Blue Nile Basin, climate change, hydrological modeling, watershed

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Authors: Wennan Long, Yuhao Nie, Yunan Li, Adam Brandt

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To fight against climate change, California government issued the Senate Bill No. 100 (SB-100) in 2018 September, which aims at achieving a target of 100% renewable electricity by the end of 2045. A capacity expansion problem is solved in this case study using a binary quadratic programming model. The optimal locations and capacities of the potential renewable power plants (i.e., solar, wind, biomass, geothermal and hydropower), the phase-out schedule of existing fossil-based (nature gas) power plants and the transmission of electricity across the entire network are determined with the minimal total annualized cost measured by net present value (NPV). The results show that the renewable electricity contribution could increase to 85.9% by 2030 and reach 100% by 2035. Fossil-based power plants will be totally phased out around 2035 and solar and wind will finally become the most dominant renewable energy resource in California electricity mix.

Keywords: 100% renewable electricity, California, capacity expansion, mixed integer non-linear programming

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Authors: Yu-Wen Chen, Szu-Wei Huang, Chung-Hsiang Mu, Kelvin Cheng

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This paper developed a data-driven based model to deal with the causality between the Continuous Emission Monitoring System (CEMS, by Environmental Protection Administration, Taiwan) in industrial factories, and the air quality around environment. Compared to the heavy burden of traditional numerical models of regional weather and air pollution simulation, the lightweight burden of the proposed model can provide forecasting hourly with current observations of weather, air pollution and emissions from factories. The observation data are included wind speed, wind direction, relative humidity, temperature and others. The observations can be collected real time from Open APIs of civil IoT Taiwan, which are sourced from 439 weather stations, 10,193 qualitative air stations, 77 national quantitative stations and 140 CEMS quantitative industrial factories. This study completed a causal inference engine and gave an air pollution forecasting for the next 12 hours related to local industrial factories. The outcomes of the pollution forecasting are produced hourly with a grid resolution of 1km*1km on IIoTC (Industrial Internet of Things Cloud) and saved in netCDF4 format. The elaborated procedures to generate forecasts comprise data recalibrating, outlier elimination, Kriging Interpolation and particle tracking and random walk techniques for the mechanisms of diffusion and advection. The solution of these equations reveals the causality between factories emission and the associated air pollution. Further, with the aid of installed real-time flue emission (Total Suspension Emission, TSP) sensors and the mentioned forecasted air pollution map, this study also disclosed the converting mechanism between the TSP and PM2.5/PM10 for different region and industrial characteristics, according to the long-term data observation and calibration. These different time-series qualitative and quantitative data which successfully achieved a causal inference engine in cloud for factory management control in practicable. Once the forecasted air quality for a region is marked as harmful, the correlated factories are notified and asked to suppress its operation and reduces emission in advance.

Keywords: continuous emission monitoring system, total suspension particulates, causal inference, air pollution forecast, IoT

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Authors: Evar C. Umeozor, Experience I. Nduagu, Ian D. Gates

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The energy requirements of carbon dioxide utilization (CDU) technologies/processes are diverse, so also are their environmental footprints. This paper explores the energy and environmental impacts of systems for CO₂ conversion to fuels, chemicals, and materials. Energy needs of the technologies and processes deployable in CO₂ conversion systems are met by one or combinations of hydrogen (chemical), electricity, heat, and light. Likewise, the environmental footprint of any CO₂ utilization pathway depends on the systems involved. So far, evaluation of CDU systems has been constrained to particular energy source/type or a subset of the overall system needed to make CDU possible. This introduces limitations to the general understanding of the energy and environmental implications of CDU, which has led to various pitfalls in past studies. A CDU system has an energy source, CO₂ supply, and conversion units. We apply a holistic approach to consider the impacts of all components in the process, including various sources of energy, CO₂ feedstock, and conversion technologies. The electricity sources include nuclear power, renewables (wind and solar PV), gas turbine, and coal. Heat is supplied from either electricity or natural gas, and hydrogen is produced from either steam methane reforming or electrolysis. The CO₂ capture unit uses either direct air capture or post-combustion capture via amine scrubbing, where applicable, integrated configurations of the CDU system are explored. We demonstrate how the overall energy and environmental impacts of each utilization pathway are obtained by aggregating the values for all components involved. Proper accounting of the energy and emission intensities of CDU must incorporate total balances for the utilization process and differences in timescales between alternative conversion pathways. Our results highlight opportunities for the use of clean energy sources, direct air capture, and a number of promising CO₂ conversion pathways for producing methanol, ethanol, synfuel, urea, and polymer materials.

Keywords: carbon dioxide utilization, processes, energy options, environmental impacts

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Authors: M. Fathi, Z. Farhaninejad, M. Shahedi, M. Sadeghi

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Drying is one of the oldest preservation methods for food and agriculture products. Appropriate control of operation can be obtained by modeling. Limitation of continues models for complex boundary condition and non-regular geometries leading to appearance of discrete novel methods such as cellular automata, which provides a platform for obtaining fast predictions by rule-based mathematics. In this research a one D dimensional CA was used for simulating thin layer drying of banana. Banana slices were dried with a convectional air dryer and experimental data were recorded for validating of final model. The model was programmed by MATLAB, run for 70000 iterations and von-Neumann neighborhood. The validation results showed a good accordance between experimental and predicted data (R=0.99). Cellular automata are capable to reproduce the expected pattern of drying and have a powerful potential for solving physical problems with reasonable accuracy and low calculating resources.

Keywords: banana, cellular automata, drying, modeling

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Authors: Leal Leonardo, Pires Carlos Augusto de Moraes, Casiraghi Magela

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In this work were realized the modeling and simulation of the catalytic reformer process, of ample form, considering all the equipment that influence the operation performance. Considered it a semi-regenerative reformer, with four reactors in series intercalated with four furnaces, two heat exchanges, one product separator and one recycle compressor. A simplified reactional system was considered, involving only ten chemical compounds related through five reactions. The considered process was the applied to aromatics production (benzene, toluene, and xylene). The models developed to diverse equipment were interconnecting in a simulator that consists of a computer program elaborate in FORTRAN 77. The simulation of the global model representative of reformer unity achieved results that are compatibles with the literature ones. It was then possible to study the effects of operational variables in the products concentration and in the performance of the unity equipment.

Keywords: catalytic reforming, modeling, simulation, petrochemical engineering

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Authors: Dawit Abay Tesfamariam

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Ethiopia’s Climate- Resilient Green Economy strategy focuses mainly on generating and utilization of Renewable Energy (RE). The data collected in 2016 by Ethiopian Electric Power (EEP) indicates that the intermittent RE sources on the grid from solar and wind energy were only 8 % of the total energy produced. On the other hand, the EEP electricity generation plan in 2030 indicates that 36 % of the energy generation share will be covered by solar and wind sources. Thus, a case study was initiated to model and compute the balance and consumption of electricity in three different scenarios: 2016, 2025, and 2030 using the Energy PLAN Model (EPM). Initially, the model was validated using the 2016 annual power-generated data to conduct the EPM analysis for two predictive scenarios. The EPM simulation analysis using EPM for 2016 showed that there was no significant excess power generated. Hence, the model’s results are in line with the actual 2016 output. Thus, the EPM was applied to analyze the role of energy storage in RE in Ethiopian grid systems. The results of the EPM simulation analysis showed there will be excess production of 402 /7963 MW average and maximum, respectively, in 2025. The excess power was dominant in all months except in the three rainy months of the year (June, July, and August). Consequently, based on the validated outcomes of EPM indicates, there is a good reason to think about other alternatives for the utilization of excess energy and storage of RE. Thus, from the scenarios and model results obtained, it is realistic to infer that; if the excess power is utilized with a storage mechanism that can stabilize the grid system; as a result, the extra RE generated can be exported to support the economy. Therefore, researchers must continue to upgrade the current and upcoming energy storage system to synchronize with RE potentials that can be generated from RE.

Keywords: renewable energy, storage, wind, energyplan

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Authors: B. S.Akhmetov, S. T. Akhmetova, D. N. Nadeyev, V. Yu. Yegorov, V. V. Smogoonov

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Estimated probabilities of errors of the first and second kind for nonideal biometrics-neural transducers 256 outputs, the construction of nomograms based error probability of 'own' and 'alien' from the mathematical expectation and standard deviation of the normalized measures Hamming.

Keywords: modeling, errors, probability, biometrics, neural network, authentication

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Authors: Xiaoqin Wang, Li Yin

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Background and purpose: In many practices, one estimates causal effects arising from a complex stochastic process, where a sequence of treatments are assigned to influence a certain outcome of interest, and there exist time-dependent covariates between treatments. When covariates are plentiful and/or continuous, statistical modeling is needed to reduce the huge dimensionality of the problem and allow for the estimation of causal effects. Recently, Wang and Yin (Annals of statistics, 2020) derived a new general formula, which expresses these causal effects in terms of the point effects of treatments in single-point causal inference. As a result, it is possible to conduct the modeling via point effects. The purpose of the work is to study the modeling of these causal effects via point effects. Challenges and solutions: The time-dependent covariates often have influences from earlier treatments as well as on subsequent treatments. Consequently, the standard parameters – i.e., the mean of the outcome given all treatments and covariates-- are essentially all different (null paradox). Furthermore, the dimension of the parameters is huge (curse of dimensionality). Therefore, it can be difficult to conduct the modeling in terms of standard parameters. Instead of standard parameters, we have use point effects of treatments to develop likelihood-based parametric approach to the modeling of these causal effects and are able to model the causal effects of a sequence of treatments by modeling a small number of point effects of individual treatment Achievements: We are able to conduct the modeling of the causal effects from a sequence of treatments in the familiar framework of single-point causal inference. The simulation shows that our method achieves not only an unbiased estimate for the causal effect but also the nominal level of type I error and a low level of type II error for the hypothesis testing. We have applied this method to a longitudinal study of COVID-19 mortality among Scandinavian countries and found that the Swedish approach performed far worse than the other countries' approach for COVID-19 mortality and the poor performance was largely due to its early measure during the initial period of the pandemic.

Keywords: causal effect, point effect, statistical modelling, sequential causal inference

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Authors: M. Eckert, M. Oliveira

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The intensive use of natural aggregates, near cities and towns, associated to the increase of the global population, leads to its depletion and increases the transport distances. The uncontrolled deposition of construction and demolition waste in landfills and city outskirts, causes pollution and takes up space. The use of recycled aggregates in concrete preparation would contribute to mitigate the problem. However, it arises the problem that the high water absorption of recycled aggregate decreases the bleeding rate of concrete, and when this gets lower than the evaporation rate, plastic shrinkage cracking occurs. This phenomenon can be particularly problematic in hot and windy curing environments. Cracking facilitates the flow of liquid and gas into concrete which attacks the reinforcement and degrades the concrete. These factors reduce the durability of concrete structures and consequently the lifetime of buildings. A ring test was used, cured in a wind tunnel, to evaluate the plastic shrinkage cracking sensitivity of recycled aggregate concrete, in order to implement preventive means to control this phenomenon. The role of several aggregate properties on the concrete segregation and cracking mechanisms were also discussed.

Keywords: recycled aggregate, plastic shrinkage cracking, wind tunnel, durability

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Authors: S. Ramteke, K. S. Patel

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Aerosols are complex mixture of particulate matters (PM) inclusive of carbons, silica, elements, various salts, etc. Aerosols get deep into the human lungs and cause a broad range of health effects, in particular, respiratory and cardiovascular illnesses. They are one of the major culprits for the climate change. They are emitted by the high thermal processes i.e. vehicles, steel, sponge, cement, thermal power plants, etc. Raipur (22˚33'N to 21˚14'N and 82˚6'E) to 81˚38'E) is a growing industrial city in central India with population of two million. In this work, the distribution of inorganics (i.e. Cl⁻, NO³⁻, SO₄²⁻, NH₄⁺, Na⁺, K⁺, Mg²⁺, Ca²⁺, Al, Cr, Mn, Fe, Ni, Cu, Zn, and Pb) associated to the PM in the ambient air is described. The PM₁₀ in ambient air of Raipur city was collected for duration of one year (December 2014 - December 2015). The PM₁₀ was segregated into nine modes i.e. PM₁₀.₀₋₉.₀, PM₉.₀₋₅.₈, PM₅.₈₋₄.₇, PM₄.₇₋₃.₃, PM₃.₃₋₂.₁, PM₂.₁₋₁.₁, PM₁.₁₋₀.₇, PM₀.₇₋₀.₄ and PM₀.₄ to know their emission sources and health hazards. The analysis of ions and metals was carried out by techniques i.e. ion chromatography and TXRF. The PM₁₀ concentration (n=48) was ranged from 100-450 µg/m³ with mean value of 73.57±20.82 µg/m³. The highest concentration of PM₄.₇₋₃.₃, PM₂.₁₋₁.₁, PM₁.₁₋₀.₇ was observed in the commercial, residential and industrial area, respectively. The effect of meteorology i.e. temperature, humidity, wind speed and wind direction in the PM₁₀ and associated elemental concentration in the air is discussed.

Keywords: ambient aerosol, ions, metals, segregation

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Authors: Maryam Safrai, Tewfik Mahdi

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This article presents the stochastic modeling of the Richelieu River flood in Quebec, Canada, occurred in the spring of 2011. With the aid of the one-dimensional Watershed Modeling System (WMS (v.10.1) and HEC-RAS (v.4.1) as a flood simulator, the delineation of the probabilistic flooded areas was considered. Based on the Monte Carlo method, WMS (v.10.1) delineated the probabilistic flooded areas with corresponding occurrence percentages. Furthermore, results of this one-dimensional model were compared with the results of two-dimensional model (SRH-2D) for the evaluation of efficiency and precision of each applied model. Based on this comparison, computational process in two-dimensional model is longer and more complicated versus brief one-dimensional one. Although, two-dimensional models are more accurate than one-dimensional method, but according to existing modellers, delineation of probabilistic flooded areas based on Monte Carlo method is achievable via one-dimensional modeler. The applied software in this case study greatly responded to verify the research objectives. As a result, flood risk maps of the Richelieu River with the two applied models (1d, 2d) could elucidate the flood risk factors in hydrological, hydraulic, and managerial terms.

Keywords: flood modeling, HEC-RAS, model comparison, Monte Carlo simulation, probabilistic flooded area, SRH-2D, WMS

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Authors: Neslihan Sahin Celik, Ali Eraslan

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As a result of PISA (Program for International Student Assessments) survey that tests how well students can apply the knowledge and skills they have learned at school to real-life challenges, the new and redesigned mathematics education programs in many countries emphasize the necessity for the students to face complex and multifaceted problem situations and gain experience in this sense allowing them to develop new skills and mathematical thinking to prepare them for their future life after school. At this point, mathematical models and modeling approaches can be utilized in the analysis of complex problems which represent real-life situations in which students can actively participate. In particular, model eliciting activities that bring about situations which allow the students to create solutions to problems and which involve mathematical modeling must be used right from primary school years, allowing them to face such complex, real-life situations from early childhood period. A qualitative study was conducted in a university foundation primary school in the city center of a big province in 2013-2014 academic years. The participants were 4th grade students in a primary school. After a four-week preliminary study applied to a fourth-grade classroom, three students included in the focus group were selected using criterion sampling technique. A focus group of three students was videotaped as they worked on the Crime Problem. The conversation of the group was transcribed, examined with students’ written work and then analyzed through the lens of Blum and Ferri’s modeling processing cycle. The results showed that primary fourth-grade students can successfully work with model eliciting problem while they encounter some difficulties in the modeling processes. In particular, they developed new ideas based on different assumptions, identified the patterns among variables and established a variety of models. On the other hand, they had trouble focusing on problems and occasionally had breaks in the process.

Keywords: primary school, modeling, mathematical modeling, crime problem

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Authors: G. N. Tiwari, Shyam

Abstract:

Photovoltaic thermal (PVT) roof type greenhouse dryer installed above the wind tower of SODHA BERS COMPLEX, Varanasi has been analyzed for all types of weather conditions. The product to be dried has been kept at three different trays. The upper tray receives energy from the PV cover while the bottom tray receives thermal energy from the hot air of the wind tower. The annual energy estimation has been done for the all types of weather condition of composite climate of northern India. It has been found that maximum energy saving is observed for c type of weather condition whereas minimum energy saving is observed for a type of weather condition. The energy saving on overall thermal energy basis and exergy basis are 1206.8 kWh and 360 kWh respectively for c type of weather condition. The energy saving from all types of weather condition are found to be 3175.3 kWh and 957.6 kWh on overall thermal energy and overall exergy basis respectively.

Keywords: exergy, greenhouse, photovoltaic thermal, solar dryer

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Authors: David F. Nettleton, Christian Wasiak, Jonas Dorissen, David Gillen, Alexandr Tretyak, Elodie Bugnicourt, Alejandro Rosales

Abstract:

In this work, preliminary results are given for the modeling and calibration of two inline processes, pultrusion, and laser ablation, using machine learning techniques. The end product of the processes is the core of a medical guidewire, manufactured to comply with a user specification of diameter and flexibility. An ensemble approach is followed which requires training several models. Two state of the art machine learning algorithms are benchmarked: Kernel Recursive Least Squares (KRLS) and Support Vector Regression (SVR). The final objective is to build a precise digital model of the pultrusion and laser ablation process in order to calibrate the resulting diameter and flexibility of a medical guidewire, which is the end product while taking into account the friction on the forming die. The result is an ensemble of models, whose output is within a strict required tolerance and which covers the required range of diameter and flexibility of the guidewire end product. The modeling and automatic calibration of complex in-line industrial processes is a key aspect of the Industry 4.0 movement for cyber-physical systems.

Keywords: calibration, data modeling, industrial processes, machine learning

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Authors: Hala A. Hassan, Vasiliki K. Tsiouri, Konstantinos E. Konstantinos

Abstract:

Fugitive particulate matter (PM) is a major source of airborne pollution in the Middle East countries. The meteorological conditions and topography of the area make it highly susceptible to wind-blown particles which raise many air quality concerns. Air quality tools such as field monitoring, emission factors, and dispersion modeling have been used in previous research studies to analyze the release and impacts of fugitive PM in the region. However, these tools have been originally developed based on experiments made for European and North American regions. In this work, an experimental campaign was conducted on April-May 2014 in a construction site in Doha city, Qatar. The ultimate goal is to evaluate the applicability of the existing emission factors for construction sites in dry and arid areas like the Middle East. This publication was made possible by a NPRP award [NPRP 7-649-2-241] from the Qatar National Research Fund (a member of The Qatar Foundation). The statements made herein are solely the responsibility of the authors.

Keywords: particulate matter, emissions, fugitive, construction, air pollution

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Authors: Abbas Ahmadi, Nasser Aliasgharzad, Ali Asghar Jafarzadeh

Abstract:

Nowadays, drying of the Urmia Lake as a largest saline lake in the world and emerging its saline bed from water has caused the risk of salty dune storms, which threats the health of human society and also plants and animal communities living in the region. Biological soil crusts (BSCs) as a dust stabilizer attracted the attention of Soil conservation experts in recent years. Although the presence of water by the impenetrable lake bed and endorheic basin can be an advantage to create BSCs, but the extraordinary of the lake bed salinity is a factor for prevention of its establishment in the region. Therefore, the present research work has been carried out to investigate the effects of inoculating the Cyanobacteria, algae and their combination to create BSCs for dust control. In this study, an algae attributed to Chlamydomonas sp and a cyanobacteria attributed to Anabaena sp isolated from the soils of Urmia Lake margin were used to create BSC in four soil samples which collected from 0-10 cm of the current margin (A), the previous bed (B), affected lands by lake (C) and Quomtappe sand dune (D). The main characteristics of the A, B and C soil samples are their highly salinity (their ECe are 108, 140 and 118 dS/m, respectively) and sodicity. Also, texture class of the soil A was loamy sand, and other two soils had clay textures. Soil D was Non-saline, but it was sodic with a sandy texture class. This study was conducted separately in each soil in a completely randomized design under four inoculation treatments of non-inoculated (T0), Algae (T1), cyanobacteria (T2) and equal mixture of algae and cyanobacteria (T3) with three replications. In the experiment, the soil was placed into wind tunnel trays, and a suspension containing microorganisms mixed with the trays surface soil. During the experiment, water was sprayed to the trays at the morning and evening of every day. After passing the incubation period (30 days), some characteristics of samples such as pH, EC, cold water extractable carbohydrate (CWEC), hot water extractable carbohydrate (HWEC), sulfuric acid extractable carbohydrate (SAEC), organic matter, crust thickness, penetration resistance, wind erosion threshold velocity and soil loss in the wind tunnel were measured, and Correlation between the measured characteristics was obtained through the SPSS software. Analysis of variance and so comparison between the means of treatments were analyzed with MSTATC software. In this research, Chlorophyll, an amount, was used as an indicator of the microorganism's population in the samples. Based on obtained results, the amount of Chlorophyll a in the T2 treatment of soil A and all treatments of soil D was significantly increased in comparison to the control and crust thickness showed increase in all treatments by microorganism’s inoculation. But effect of the treatments was significant in soils A and D. At all treatment’s inoculation of microorganisms in soil A caused to increase %46, %34 and %55 of the wind erosion threshold velocity in T1, T2 and T3 treatments in comparison to the control, respectively, and in soil D all treatments caused wind erosion threshold velocity became two times more than control. However, soil loss in the wind tunnel experiments was significant in T2 and T3 treatments of these soils and T1 treatment had no effect in reducing soil loss. Correlation between Chlorophyll a and salinity shows the important role of salinity in microbial growth prevention and formation of BSCs in the studied samples. In general, according to the obtained results, it can be concluded that salinity reduces the growth of microorganisms in saline soils of the region, and in soils with fine textures, salinity role in prevention of the microbial growth is clear. Also, using the mix of algae and cyanobacteria together caused the synergistic growth of them and consequently, better protection of the soil against wind erosion was provided.

Keywords: wind erosion, algae, cyanobacteria, carbohydrate

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Authors: Mohd Zamri Che Wanik

Abstract:

This paper presents the management of the Fault Ride Through event within a Solar Farm during a grid fault. The modeling and simulation of a photovoltaic (PV) with battery energy storage connected to the power network will be described. The modeling approach and the study analysis performed are described. The model and operation scenarios are simulated using a digital simulator for different scenarios. The dynamic response of the system when subjected to sudden self-clearance temporary fault is presented. The capability of the PV system and battery storage riding through the power system fault and, at the same time, supporting the local grid by injecting fault current is demonstrated. For each case, the different control methods to achieve the objective of supporting the grid according to grid code requirements are presented and explained. The inverter modeling approach is presented and described.

Keywords: faut ride through, solar farm, grid code, power network

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