Search results for: computational simulations

Authors: U. Ali Rahoma, Nabil Esawy, Fawzia Ibrahim Moursy, A. H. Hassan, Samy A. Khalil, Ashraf S. Khamees

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The design of any solar energy conversion system requires the knowledge of solar radiation data obtained over a long period. Satellite data has been widely used to estimate solar energy where no ground observation of solar radiation is available, yet there are limitations on the temporal coverage of satellite data. Reanalysis is a “retrospective analysis” of the atmosphere parameters generated by assimilating observation data from various sources, including ground observation, satellites, ships, and aircraft observation with the output of NWP (Numerical Weather Prediction) models, to develop an exhaustive record of weather and climate parameters. The evaluation of the performance of reanalysis datasets (ERA-5) for North Africa against high-quality surface measured data was performed using statistical analysis. The estimation of global solar radiation (GSR) distribution over six different selected locations in North Africa during ten years from the period time 2011 to 2020. The root means square error (RMSE), mean bias error (MBE) and mean absolute error (MAE) of reanalysis data of solar radiation range from 0.079 to 0.222, 0.0145 to 0.198, and 0.055 to 0.178, respectively. The seasonal statistical analysis was performed to study seasonal variation of performance of datasets, which reveals the significant variation of errors in different seasons—the performance of the dataset changes by changing the temporal resolution of the data used for comparison. The monthly mean values of data show better performance, but the accuracy of data is compromised. The solar radiation data of ERA-5 is used for preliminary solar resource assessment and power estimation. The correlation coefficient (R2) varies from 0.93 to 99% for the different selected sites in North Africa in the present research. The goal of this research is to give a good representation for global solar radiation to help in solar energy application in all fields, and this can be done by using gridded data from European Centre for Medium-Range Weather Forecasts ECMWF and producing a new model to give a good result.

Keywords: solar energy, solar radiation, ERA-5, potential energy

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Authors: A. Selmi

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Free vibration analysis of homogenous and axially functionally graded simply supported beams within the context of Euler-Bernoulli beam theory is presented in this paper. The material properties of the beams are assumed to obey the linear law distribution. The effective elastic modulus of the composite was predicted by using the rule of mixture. Here, the complexities which appear in solving differential equation of transverse vibration of composite beams which limit the analytical solution to some special cases are overcome using a relatively new approach called the Differential Transformation Method. This technique is applied for solving differential equation of transverse vibration of axially functionally graded beams. Natural frequencies and corresponding normalized mode shapes are calculated for different Young’s modulus ratios. MATLAB code is designed to solve the transformed differential equation of the beam. Comparison of the present results with the exact solutions proves the effectiveness, the accuracy, the simplicity, and computational stability of the differential transformation method. The effect of the Young’s modulus ratio on the normalized natural frequencies and mode shapes is found to be very important.

Keywords: differential transformation method, functionally graded material, mode shape, natural frequency

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Authors: Young Mun Lee, Seon Ho Kim, Seok Min Choi, JeongJu Kim, Seungyeong Choi, Hyung Hee Cho

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To decrease sulfur oxide in the flue gas from coal power plant, a flue gas de-sulfurization facility is operated. In the reactor, a chemical reaction occurs with a temperature change of the gas so that sulfur oxide is removed and cleaned air is emitted. In this process, temperature change induces a serious problem which is a cold erosion of stack. To solve this problem, the rotary heat exchanger is managed before the stack. In the heat exchanger, a heating element is equipped to increase a heat transfer area. Heat transfer and pressure loss is a big issue to improve a performance. In this research, thermal-fluid characteristics of the heating element are analyzed by computational fluid dynamics. Fouling simulation is also conducted to calculate a performance of heating element. Numerical analysis is performed on the situation where plugging phenomenon has already occurred and existed in the inlet region of the heating element. As the pressure of the rear part of the plugging decreases suddenly and the flow velocity becomes slower, it is found that the flow is gathered from both sides as it develops in the flow direction, and it is confirmed that the pressure difference due to plugging is increased.

Keywords: heating element, plugging, rotary heat exchanger, thermal fluid characteristics

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Authors: Bipasha Sen, Aditya Agarwal

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Multilingual automatic speech recognition (ASR) system is a single entity capable of transcribing multiple languages sharing a common phone space. Performance of such a system is highly dependent on the compatibility of the languages. State of the art speech recognition systems are built using sequential architectures based on recurrent neural networks (RNN) limiting the computational parallelization in training. This poses a significant challenge in terms of time taken to bootstrap and validate the compatibility of multiple languages for building a robust multilingual system. Complex architectural choices based on self-attention networks are made to improve the parallelization thereby reducing the training time. In this work, we propose Reed, a simple system based on 1D convolutions which uses very short context to improve the training time. To improve the performance of our system, we use raw time-domain speech signals directly as input. This enables the convolutional layers to learn feature representations rather than relying on handcrafted features such as MFCC. We report improvement on training and inference times by atleast a factor of 4x and 7.4x respectively with comparable WERs against standard RNN based baseline systems on SpeechOcean's multilingual low resource dataset.

Keywords: convolutional neural networks, language compatibility, low resource languages, multilingual automatic speech recognition

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Authors: Lynda Golea, Rachid Chebaki

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Schiff bases contain heterocyclic structural units with N and O donor atoms which plays an important role in coordination chemistry. Azomethine groups are a broad class of widely used compounds with applications in many fields, including analytical, inorganic chemistry and biological. Schiff's base is of promising research interest due to the widespread antibacterial resistance in medical science. In addition, the research is essential to generate Schiff base metal complexes with various applications. Schiff complexes have been used as drugs and have antibacterial, antifungal, antiviral, and anti-inflammatory properties. The various donor atoms they contain offer a special ability for metal binding. In this research on the physicochemical properties of azomethine groups, we synthesized and studied the Schiff base compounds by a condensation reaction of tryptamines and acetophenone in ethanol. The structure of the prepared compound was interpreted using 1H NMR, 13C NMR, UV-vis and FT-IR. A computational analysis at the level of DFT with functional B3LYP in conjunction with the base 6-311+G (d, p) was conducted to study its electronic and molecular structure. The biological study was performed on three bacterial strains usually causing infection, including Gram-positive and Gram-negative, for antibacterial activity. Results showed moderate biological activity and proportional activity with increasing concentration.

Keywords: azomethine, HOMO, LUMO, RMN, molecular docking

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Authors: Ismael Zamora, Elisabeth Ortega, Tatiana Radchenko, Guillem Plasencia

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The structure elucidation based on Mass Spectra (MS) data of unknown substances is an unresolved problem that affects many different fields of application. The recent overview of software available for structure elucidation of small molecules has shown the demand for efficient computational tool that will be able to perform structure elucidation of unknown small molecules and peptides. We developed an algorithm for De-Novo fragment analysis based on MS data that proposes a set of scored and ranked structures that are compatible with the MS and MSMS spectra. Several different algorithms were developed depending on the initial set of fragments and the structure building processes. Also, in all cases, several scores for the final molecule ranking were computed. They were validated with small and middle databases (DB) with the eleven test set compounds. Similar results were obtained from any of the databases that contained the fragments of the expected compound. We presented an algorithm. Or De-Novo fragment analysis based on only mass spectrometry (MS) data only that proposed a set of scored/ranked structures that was validated on different types of databases and showed good results as proof of concept. Moreover, the solutions proposed by Mass Spectrometry were submitted to the prediction of NMR spectra in order to elucidate which of the proposed structures was compatible with the NMR spectra collected.

Keywords: De Novo, structure elucidation, mass spectrometry, NMR

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Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee

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Surrogate model has received increasing attention for use in detecting damage of structures based on vibration modal parameters. However, uncertainties existing in the measured vibration data may lead to false or unreliable output result from such model. In this study, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The kriging technique allows one to genuinely quantify the surrogate error, therefore it is chosen as metamodeling technique. Enhanced version of ideal gas molecular movement (EIGMM) algorithm is used as main algorithm for model updating. The developed approach is applied to detect simulated damage in numerical models of 72-bar space truss and 120-bar dome truss. The simulation results show the proposed method can perform well in probability-based damage detection of structures with less computational effort compared to direct finite element model.

Keywords: probability-based damage detection (PBDD), Kriging, surrogate modeling, uncertainty quantification, artificial intelligence, enhanced ideal gas molecular movement (EIGMM)

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Authors: Niranjana Devi N.

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Test case selection is to select the subset of only the fit test cases and remove the unfit, ambiguous, redundant, unnecessary test cases which in turn improve the quality and reduce the cost of software testing. Test cases optimization is the problem of finding the best subset of test cases from a pool of the test cases to be audited. It will meet all the objectives of testing concurrently. But most of the research have evaluated the fitness of test cases only on single parameter fault detecting capability and optimize the test cases using a single objective. In the proposed approach, nine parameters are considered for test case selection and the best subset of parameters for test case selection is obtained using Interval Type-2 Fuzzy Rough Set. Test case selection is done in two stages. The first stage is the fuzzy entropy-based filtration technique, used for estimating and reducing the ambiguity in test case fitness evaluation and selection. The second stage is the ant colony optimization-based wrapper technique with a forward search strategy, employed to select test cases from the reduced test suite of the first stage. The results are evaluated using the Coverage parameters, Precision, Recall, F-Measure, APSC, APDC, and SSR. The experimental evaluation demonstrates that by this approach considerable computational effort can be avoided.

Keywords: ant colony optimization, fuzzy entropy, interval type-2 fuzzy rough set, test case selection

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Authors: Domenico Carmelo Mongelli, Laura Carnieletto, Michele De Carli, Filippo Busato

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Starting from the current context in which the Russian invasion in Ukraine has highlighted Europe's dependence on natural gas imports for heating buildings, this study proposes solutions to resolve this dependency and evaluates related scenarios in the near future. In the first part of this work the methodologies and results of the economic impact are indicated by simulating a massive replacement of boilers powered by fossil fuels with electrically powered hightemperature air-water heat pumps for heating residential buildings in different European climates, without changing the current energy mix. For each individual European region, the costs for the purchase and installation of heat pumps for all residential buildings have been determined. Again for each individual European region, the economic savings during the operation phase that would be obtained in this future scenario of energy transition from fossil fuels to the electrification of domestic heating were calculated. For the European regions for which the economic savings were identified as positive, the payback times of the economic investments were analysed. In the second part of the work, hypothesizing different scenarios for a possible greater use of renewable energy sources and therefore with different possible future scenarios of the energy mix, the methodologies and results of the simulations on the economic analysis and on the environmental analysis are reported which have allowed us to evaluate the future effects of the energy transition from boilers to heat pumps for each European region. In the third part, assuming a rapid short-term diffusion of cooling for European residential buildings, the penetration shares in the cooling market and future projections of energy needs for cooling for each European region have been identified. A database was created where the results of this research relating to 38 European Nations divided into 179 regions were reported. Other previous works on the topics covered were limited to analyzing individual European nations, without ever going into detail about the individual regions within each nation, while the original contribution of the present work lies in the fact that the results achieved allow a specific numerical analysis and punctual for every single European region.

Keywords: buildings, energy, Europe, future

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Authors: Dimitrios I. Tselentis, Simon P. Washington

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Considerable literature has been focused over the last few decades on forecasting the consumer demand of Energy Efficient Vehicles (EEVs). These methodological issues range from how to capture recent purchase decisions in revealed choice studies and how to set up experiments in stated preference (SP) studies, and choice of analysis method for analyzing such data. This paper reviews the plethora of published studies on the field of forecasting demand of EEVs since 1980, and provides a review and annotated bibliography of that literature as it pertains to this particular demand forecasting problem. This detailed review addresses the literature not only to Transportation studies, but specifically to the problem and methodologies around forecasting to the time horizons of planning studies which may represent 10 to 20 year forecasts. The objectives of the paper are to identify where existing gaps in literature exist and to articulate where promising methodologies might guide longer term forecasting. One of the key findings of this review is that there are many common techniques used both in the field of new product demand forecasting and the field of predicting future demand for EEV. Apart from SP and RP methods, some of these new techniques that have emerged in the literature in the last few decades are survey related approaches, product diffusion models, time-series modelling, computational intelligence models and other holistic approaches.

Keywords: demand forecasting, Energy Efficient Vehicles (EEVs), forecasting methodologies review, methodological approaches

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Authors: Marcelo T. Okano, Jaqueline C. Bueno, Oduvaldo Vendrametto, Osmildo S. Santos, Marcelo E. Fernandes, Heide Landi

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Developing countries are increasingly finding that entrepreneurship and innovation are the ways to speed up their developments and initiate or encourage technological development. The educational institutions such as universities, colleges and colleges of technology, has two main roles in this process, to guide and train entrepreneurs and provide technological knowledge and encourage innovation. Thus there was completing the triple helix model of innovation with universities, government and industry. But the teaching of entrepreneurship and innovation can not be only the traditional model, with blackboard, chalk and classroom. The new methods and methodologies such as Canvas, elevator pitching, design thinking, etc. require students to get involved and to experience the simulations of business, expressing their ideas and discussing them. The objective of this research project is to identify the main methods and methodologies used for the teaching of entrepreneurship and innovation, to propose a framework, test it and make a case study. To achieve the objective of this research, firstly was a survey of the literature on the entrepreneurship and innovation, business modeling, business planning, Canvas business model, design thinking and other subjects about the themes. Secondly, we developed the framework for teaching entrepreneurship and innovation based on bibliographic research. Thirdly, we tested the framework in a higher education class IT management for a semester. Finally, we detail the results in the case study in a course of IT management. As important results we improve the level of understanding and business administration students, allowing them to manage own affairs. Methods such as canvas and business plan helped students to plan and shape the ideas and business. Pitching for entrepreneurs and investors in the market brought a reality for students. The prototype allowed the company groups develop their projects. The proposed framework allows entrepreneurship education and innovation can leave the classroom, bring the reality of business roundtables to university relying on investors and real entrepreneurs.

Keywords: entrepreneurship, innovation, Canvas, traditional model

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Authors: Ashok K. Satapathy, Prerana Nashine

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Radiative heat transfer in participating medium was anticipated using the finite volume method. The radiative transfer equations are formulated for absorbing and anisotropically scattering and emitting medium. The solution strategy is discussed and the conditions for computational stability are conferred. The equations have been solved for transient radiative medium and transient radiation incorporated with transient conduction. Results have been obtained for irradiation and corresponding heat fluxes for both the cases. The solutions can be used to conclude incident energy and surface heat flux. Transient solutions were obtained for a slab of heat conducting in slab by thermal radiation. The effect of heat conduction during the transient phase is to partially equalize the internal temperature distribution. The solution procedure provides accurate temperature distributions in these regions. A finite volume procedure with variable space and time increments is used to solve the transient energy equation. The medium in the enclosure absorbs, emits, and anisotropically scatters radiative energy. The incident radiations and the radiative heat fluxes are presented in graphical forms. The phase function anisotropy plays a significant role in the radiation heat transfer when the boundary condition is non-symmetric.

Keywords: participating media, finite volume method, radiation coupled with conduction, heat transfer

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Authors: Martin Mensinger, Marjolaine Pfaffinger, Matthias Haslbeck

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The maintenance and expansion of the railway network represents a central task for transport planning in the future. In addition to the ultimate limit states, the aspects of resource conservation and sustainability are increasingly more necessary to include in the basic engineering. Therefore, as part of the AiF research project, ‘Integrated assessment of steel and composite railway bridges in accordance with sustainability criteria’, the entire lifecycle of engineering structures is involved in planning and evaluation, offering a way to optimize the design of steel bridges. In order to reduce the life cycle costs and increase the profitability of steel structures, it is particularly necessary to consider the demands on hanger connections resulting from fatigue. In order for accurate analysis, a number simulations were conducted as part of the research project on a finite element model of a reference bridge, which gives an indication of the internal forces of the individual structural components of a tied arch bridge, depending on the stress incurred by various types of trains. The calculations were carried out on a detailed FE-model, which allows an extraordinarily accurate modeling of the stiffness of all parts of the constructions as it is made up surface elements. The results point to a large impact of the formation of details on fatigue-related changes in stress, on the one hand, and on the other, they could depict construction-specific specifics over the course of adding stress. Comparative calculations with varied axle-stress distribution also provide information about the sensitivity of the results compared to the imposition of stress and axel distribution on the stress-resultant development. The calculated diagrams help to achieve an optimized hanger connection design through improved durability, which helps to reduce the maintenance costs of rail networks and to give practical application notes for the formation of details.

Keywords: fatigue, influence line, life cycle, tied arch bridge

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Authors: Mohammad Jalali Varnamkhasti

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The genetic algorithms have been very successful in handling difficult optimization problems. The fundamental problem in genetic algorithms is premature convergence. This paper, present a new fuzzy genetic algorithm based on chaotic values instead of the random values in genetic algorithm processes. In this algorithm, for initial population is used chaotic sequences and then a new sexual selection proposed for selection mechanism. In this technique, the population is divided such that the male and female would be selected in an alternate way. The layout of the male and female chromosomes in each generation is different. A female chromosome is selected by tournament selection size from the female group. Then, the male chromosome is selected, in order of preference based on the maximum Hamming distance between the male chromosome and the female chromosome or The highest fitness value of male chromosome (if more than one male chromosome is having the maximum Hamming distance existed), or Random selection. The selections of crossover and mutation operators are achieved by running the fuzzy logic controllers, the crossover and mutation probabilities are varied on the basis of the phenotype and genotype characteristics of the chromosome population. Computational experiments are conducted on the proposed techniques and the results are compared with some other operators, heuristic and local search algorithms commonly used for solving p-median problems published in the literature.

Keywords: genetic algorithm, fuzzy system, chaos, sexual selection

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Authors: Rami Faraj, Cezary Graczykowski, Błażej Popławski, Grzegorz Mikułowski, Rafał Wiszowaty

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Progress in the field of sensors, electronics and computing results in more and more often applications of adaptive techniques for dynamic response mitigation. When it comes to systems excited with mechanical impacts, the control system has to take into account the significant limitations of actuators responsible for system adaptation. The paper provides a comprehensive discussion of the problem of appropriate design and implementation of adaptation techniques and mechanisms. Two case studies are presented in order to compare completely different adaptation schemes. The first example concerns a double-chamber pneumatic shock absorber with a fast piezo-electric valve and parameters corresponding to the suspension of a small unmanned aerial vehicle, whereas the second considered system is a safety air cushion applied for evacuation of people from heights during a fire. For both systems, it is possible to ensure adaptive performance, but a realization of the system’s adaptation is completely different. The reason for this is technical limitations corresponding to specific types of shock-absorbing devices and their parameters. Impact mitigation using a pneumatic shock absorber corresponds to much higher pressures and small mass flow rates, which can be achieved with minimal change of valve opening. In turn, mass flow rates in safety air cushions relate to gas release areas counted in thousands of sq. cm. Because of these facts, both shock-absorbing systems are controlled based on completely different approaches. Pneumatic shock-absorber takes advantage of real-time control with valve opening recalculated at least every millisecond. In contrast, safety air cushion is controlled using the semi-passive technique, where adaptation is provided using prediction of the entire impact mitigation process. Similarities of both approaches, including applied models, algorithms and equipment, are discussed. The entire study is supported by numerical simulations and experimental tests, which prove the effectiveness of both adaptive impact mitigation techniques.

Keywords: adaptive control, adaptive system, impact mitigation, pneumatic system, shock-absorber

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Authors: R. Gharari, N. Kojouri, R. Hosseini Aghdam, E. Alibeigi, B. Salmasian

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In this research, the WWER1000/V446 (a PWR Russian type reactor) is chosen as the case study. It is assumed that radioactive materials that release into the environment are more than allowable limit due to a complete failure of the ventilation system (reactor stack). In the following, the HOTSPOT and the RASCAL computational codes have been used and coupled with a developed program using MATLAB software to evaluate Total effective dose equivalent (TEDE) and cancer risk according to the BEIR equations for various human organs. In addition, effects of the containment spray system and climate conditions on the TEDE have been investigated. According to the obtained results, there is an inverse correlation between the received dose and the wind speed; the amount of the TEDE for wind speed 2 m/s and is more than wind speed for 14 m/s during the class A of the climate (2.168 and 0.444 mSv, respectively). Also, containment spray system can effect and reduce the amount of the fission products and TEDE. Furthermore, the probability of the cancer risk for women is more than men, and for children is more than adults. In addition, a specific emergency zonal planning is proposed. Results are promising in which the site selection of the WWER1000/V446 were considered safe for the public in this situation.

Keywords: TEDE, total effective dose equivalent, RASCAL and HOTSPOT codes, BEIR equations, cancer risk

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Authors: Anargha A. Dhorde, Deshpande Gauri, Amit G. Dhorde

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Mula-Mutha basin is one of the speedily urbanizing watersheds, wherein two major urban centers, Pune and Pimpri-Chinchwad, have developed at a shocking rate in the last two decades. Such changing land use/land cover (LULC) is prone to hydrological problems and flash floods are a frequent, eventuality in the lower reaches of the basin. The present research brings out the impact of varying LULC, impervious surfaces on urban surface hydrology and generates storm-runoff scenarios for the hydrological units. The two multi-temporal satellite images were processed and supervised classification is performed with > 75% accuracy. The built-up has increased from 14.4% to 34.37% in the 28 years span, which is concentrated in and around the Pune-PCMC region. Impervious surfaces that were obtained by population calibrated multiple regression models. Almost 50% area of the watershed is impervious, which attribute to increase surface runoff and flash floods. The SCS-CN method was employed to calculate surface runoff of the watershed. The comparison between calculated and measured values of runoff was performed in a statistically precise way which shows no significant difference. Increasing built-up areas, as well as impervious surface areas due to rapid urbanization and industrialization, may lead to generating high runoff volumes in the basin especially in the urbanized areas of the watershed and along the major transportation arteries. Simulations generated with 50 mm and 100 mm rainstorm depth conspicuously noted that most of the changes in terms of increased runoff are constricted to the highly urbanized areas. Considering whole watershed area, the runoff values 39 m³ generated with 1'' rainfall whereas only urbanized areas of the basin (Pune and Pimpari-Chinchwad) were generated 11154 m³ runoff. Such analysis is crucial in providing information regarding their intensity and location, which proves instrumental in their analysis in order to formulate proper mitigation measures and rehabilitation strategies.

Keywords: land use/land cover, LULC, impervious surfaces, surface hydrology, storm-runoff scenarios

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Authors: Chengfeng Fang, Mohamed Ali Sadakkathulla, Abdul Sheikh

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Ultra-high-performance fiber reinforced concrete (UHPFRC) is a specially formulated cement-based composite characterized with an ultra-high compressive strength (f_c^’ = 240 MPa) and a low water-cement ratio (W/B= 0.2). With such material characteristics, UHPFRC is favored for the design and constructions of structures required high structural performance and slender geometries. Unlike conventional concrete, the structural performance of members manufactured with UHPFRC has not yet been fully studied, particularly, for UHPFRC columns with high slenderness. In this study, the behaviors of slender UHPFRC columns under concentric or eccentric load will be investigated both experimentally and numerically. Four slender UHPFRC columns were tested under eccentric loads with eccentricities, of 0 mm, 35 mm, 50 mm, and 85 mm, respectively, and one UHPFRC beam was tested under four-point bending. Finite element (FE) analysis was conducted with concrete damage plasticity (CDP) modulus to simulating the load-middle height or middle span deflection relationships and damage patterns of all UHPFRC members. Simulated results were compared against the experimental results and observation to gain the confidence of FE model, and this model was further extended to conduct parametric studies, which aim to investigate the effects of slenderness regarding failure modes and load-moment interaction relationships. Experimental results showed that the load bearing capacities of the slender columns reduced with an increase in eccentricity. Comparisons between load-middle height and middle span deflection relationships as well as damage patterns of all UHPFRC members obtained both experimentally and numerically demonstrated high accuracy of the FE simulations. Based on the available FE model, the following parametric study indicated that a further increase in the slenderness of column resulted in significant decreases in the load-bearing capacities, ductility index, and flexural bending capacities.

Keywords: eccentric loads, ductility index, RC column, slenderness, UHPFRC

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Authors: Andrii Shalaginov, Katrin Franke, Xiongwei Huang

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One of the leading problems in Cyber Security today is the emergence of targeted attacks conducted by adversaries with access to sophisticated tools. These attacks usually steal senior level employee system privileges, in order to gain unauthorized access to confidential knowledge and valuable intellectual property. Malware used for initial compromise of the systems are sophisticated and may target zero-day vulnerabilities. In this work we utilize common behaviour of malware called ”beacon”, which implies that infected hosts communicate to Command and Control servers at regular intervals that have relatively small time variations. By analysing such beacon activity through passive network monitoring, it is possible to detect potential malware infections. So, we focus on time gaps as indicators of possible C2 activity in targeted enterprise networks. We represent DNS log files as a graph, whose vertices are destination domains and edges are timestamps. Then by using four periodicity detection algorithms for each pair of internal-external communications, we check timestamp sequences to identify the beacon activities. Finally, based on the graph structure, we infer the existence of other infected hosts and malicious domains enrolled in the attack activities.

Keywords: malware detection, network security, targeted attack, computational intelligence

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Authors: Nicolae Daniel Stoica, Ion Mierlus Mazilu

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This work is one of numerical research and aims to address the issue of the design of new buildings in a 3D location of existing buildings. In today's continuous development and congestion of urban centers is a big question about the influence of the new buildings on an already existent vicinity site. Thus, in this study, we tried to focus on how existent buildings may be affected by any newly constructed buildings and in how far this influence is really decreased. The problem of modeling the influence of interaction between buildings is not simple in any area in the world, and neither in Romania. Unfortunately, most often the designers not done calculations that can determine how close to reality these 3D influences nor the simplified method and the more superior methods. In the most literature making a "shield" (the pilots or molded walls) is absolutely sufficient to stop the influence between the buildings, and so often the soil under the structure is ignored in the calculation models. The main causes for which the soil is neglected in the analysis are related to the complexity modeling of interaction between soil and structure. In this paper, based on a new simple but efficient methodology we tried to determine for a lot of study cases the influence, in terms of assessing the interaction land structure on the behavior of structures that influence a new building on an existing one. The study covers additional subsidence that may occur during the execution of new works and after its completion. It also highlighted the efforts diagrams and deflections in the soil for both the original case and the final stage. This is necessary to see to what extent the expected impact of the new building on existing areas.

Keywords: soil, structure, interaction, piles, earthquakes

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Authors: Subrata Sarkar

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The aerospace industry is experiencing a profound product development transformation driven by the powerful integration of digitalization and 3D printing technologies. This paper delves into the significant impact of this convergence on aerospace innovation, specifically focusing on developing jet pumps for fuel systems. This case study is a compelling example of the immense potential of these technologies. In response to the industry's increasing demand for lighter, more efficient, and customized components, the combined capabilities of digitalization and 3D printing are reshaping how we envision, design, and manufacture critical aircraft parts, offering a distinct paradigm in aerospace engineering. Consider the development of a jet pump for a fuel system, a task that presents unique and complex challenges. Despite its seemingly simple design, the jet pump's development is hindered by many demanding operating conditions. The qualification process for these pumps involves many analyses and tests, leading to substantial delays and increased costs in fuel system development. However, by harnessing the power of automated simulations and integrating legacy design, manufacturing, and test data through digitalization, we can optimize the jet pump's design and performance, thereby revolutionizing product development. Furthermore, 3D printing's ability to create intricate structures using various materials, from lightweight polymers to high-strength alloys, holds the promise of highly efficient and durable jet pumps. The combined impact of digitalization and 3D printing extends beyond design, as it also reduces material waste and advances sustainability goals, aligning with the industry's increasing commitment to environmental responsibility. In conclusion, the convergence of digitalization and 3D printing is not just a technological advancement but a gateway to a new era in aerospace product development, particularly in the design of jet pumps. This revolution promises to redefine how we create aerospace components, making them safer, more efficient, and environmentally responsible. As we stand at the forefront of this technological revolution, aerospace companies must embrace these technologies as a choice and a strategic imperative for those striving to lead in innovation and sustainability in the 21st century.

Keywords: jet pump, digitalization, 3D printing, aircraft fuel system.

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Authors: Hossam Ali-Hassan, Michael Bliemel

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This poster reflects upon our experiences using INNOV8, IBM’s Business Process Management (BPM) simulation game, in online MBA and undergraduate MIS classes over a period of 2 years. The game is designed to gives both business and information technology players a better understanding of how effective BPM impacts an entire business ecosystem. The game includes three different scenarios: Smarter Traffic, which is used to evaluate existing traffic patterns and re-route traffic based on incoming metrics; Smarter Customer Service where players develop more efficient ways to respond to customers in a call centre environment; and Smarter Supply Chains where players balance supply and demand and reduce environmental impact in a traditional supply chain model. We use the game as an experiential learning tool, where students have to act as managers making real time changes to business processes to meet changing business demands and environments. The students learn how information technology (IT) and information systems (IS) can be used to intelligently solve different problems and how computer simulations can be used to test different scenarios or models based on business decisions without having to actually make the potentially costly and/or disruptive changes to business processes. Moreover, when students play the three different scenarios, they quickly see how practical process improvements can help meet profitability, customer satisfaction and environmental goals while addressing real problems faced by municipalities and businesses today. After spending approximately two hours in the game, students reflect on their experience from it to apply several BPM principles that were presented in their textbook through the use of a structured set of assignment questions. For each final scenario students submit a screenshot of their solution followed by one paragraph explaining what criteria you were trying to optimize, and why they picked their input variables. In this poster we outline the course and the module’s learning objectives where we used the game to place this into context. We illustrate key features of the INNOV8 Simulation Game, and describe how we used them to reinforce theoretical concepts. The poster will also illustrate examples from the simulation, assignment, and learning outcomes.

Keywords: experiential learning, business process management, BPM, INNOV8, simulation, game

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Authors: Frederico Fialho Teixeira, Islam Mashaly, Maryam Shafiei, Jurij Karlovsek

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The ubiquity of data gathering and smart technologies, advancements in virtual technologies, and the development of the internet of things (IoT) have created urgent demands for the development of frameworks and efficient workflows for data collection, visualisation, and analysis. Digital twin, in different scales of the city into the building, allows for bringing together data from different sources to generate fundamental and illuminating insights for the management of current facilities and the lifecycle of amenities as well as improvement of the performance of current and future designs. Over the past two decades, there has been growing interest in the topic of digital twin and their applications in city and building scales. Most such studies look at the urban environment through a homogeneous or generalist lens and lack specificity in particular characteristics or identities, which define an urban university campus. Bridging this knowledge gap, this paper offers a framework for developing a digital twin for a university campus that, with some modifications, could provide insights for any large-scale digital twin settings like towns and cities. It showcases how currently unused data could be purposefully combined, interpolated and visualised for producing analysis-ready data (such as flood or energy simulations or functional and occupancy maps), highlighting the potential applications of such a framework for campus planning and policymaking. The research integrates campus-level data layers into one spatial information repository and casts light on critical data clusters for the digital twin at the campus level. The paper also seeks to raise insightful and directive questions on how digital twin for campus can be extrapolated to city-scale digital twin. The outcomes of the paper, thus, inform future projects for the development of large-scale digital twin as well as urban and architectural researchers on potential applications of digital twin in future design, management, and sustainable planning, to predict problems, calculate risks, decrease management costs, and improve performance.

Keywords: digital twin, smart campus, framework, data collection, point cloud

Procedia PDF Downloads 66

Authors: Soraya Abtouche, Zeyneb Ghoualem, Syrine Daoudi, Lina Ouldmohamed, Xavier Assfeld

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This work reports density functional theory calculations of the optimized geometries, molecular reactivity, energy gap,and thermodynamic properties of the free base (H2P) and their Zn (II) metallated (ZnP), bearing one, two, or three carboxylic acid groups using the hybrid functional B3LYP, Cam-B3lYP, wb97xd with 6-31G(d,p) basis sets. When donating groups are attached to the molecular dye, the bond lengths are slightly decreased, which is important for the easy transfer of an electron from donating to the accepting group. For all dyes, the highest occupied molecular orbital/lowest occupied molecular orbital analysis results in positive outcomes upon electron injection to the semiconductor and subsequent dye regeneration by the electrolyte. The ionization potential increases with increasing conjugation; therefore, the compound dye attached to one carboxylic acid group has the highest ionization potential. The results show higher efficiencies of those sensitized with ZnP. These results have been explained, taking into account the electronic character of the metal ion, which acts as a mediator in the injection step, and, on the other hand, considering the number of anchoring groups to which it binds to the surface of TiO2.

Keywords: DSSC, porphyrin, TD-DFT, electronic properties, donor-acceptor groups

Procedia PDF Downloads 77

Authors: Hassan S. Hussein, Rania A. Abul Seoud, Amr M. Refaat

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Scientific researchers face in the analysis of very large data sets that is increasing noticeable rate in today’s and tomorrow’s technologies. Hadoop and Spark are types of software that developed frameworks. Hadoop framework is suitable for many Different hardware platforms. In this research, a scientific Linux cluster for Big Data analysis (SLBD) is presented. SLBD runs open source software with large computational capacity and high performance cluster infrastructure. SLBD composed of one cluster contains identical, commodity-grade computers interconnected via a small LAN. SLBD consists of a fast switch and Gigabit-Ethernet card which connect four (nodes). Cloudera Manager is used to configure and manage an Apache Hadoop stack. Hadoop is a framework allows storing and processing big data across the cluster by using MapReduce algorithm. MapReduce algorithm divides the task into smaller tasks which to be assigned to the network nodes. Algorithm then collects the results and form the final result dataset. SLBD clustering system allows fast and efficient processing of large amount of data resulting from different applications. SLBD also provides high performance, high throughput, high availability, expandability and cluster scalability.

Keywords: big data platforms, cloudera manager, Hadoop, MapReduce

Procedia PDF Downloads 355

Authors: Christian Liebchen

Abstract:

Both from an environmental perspective and with respect to road traffic flow quality, planning so-called green waves along major road axes is a well-established target for traffic engineers. For one-way road axes (e.g. the Avenues in Manhattan), this is a trivial downstream task. For bidirectional arterials, the well-known necessary condition for establishing a green wave in both directions is that the driving times between two subsequent crossings must be an integer multiple of half of the cycle time of the signal programs at the nodes. In this paper, we propose an integer linear optimization model to establish fixed-time green waves in both directions that are as long and as wide as possible, even in the situation where the driving time condition is not fulfilled. In particular, we are considering an arterial along whose nodes separate left-turn signal groups are realized. In our computational results, we show that scheduling left-turn phases before or after the straight phases can reduce waiting times along the arterial. Moreover, we show that there is always a solution with green waves in both directions that are as long and as wide as possible, where absolute priority is put on just one direction. Compared to optimizing both directions together, establishing an ideal green wave into one direction can only provide suboptimal quality when considering prioritized parts of a green band (e.g., first few seconds).

Keywords: traffic light coordination, synchronization, phase sequencing, green waves, integer programming

Procedia PDF Downloads 114

Authors: Mustapha Ouardouz, Mina Amharref, Abdessamed Bernoussi

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The future energy, for limited energy resources countries, goes through renewable energies (solar, wind etc.). The renewable energies constitute a major component of the energy strategy to cover a substantial part of the growing needs and contribute to environmental protection by replacing fossil fuels. Indeed, sustainable development involves the promotion of renewable energy and the preservation of the environment by the use of clean energy technologies to limit emissions of greenhouse gases and reducing the pressure exerted on the forest cover. So the impact studies, of the energy use on the environment and farm-related risks are necessary. For that, a global approach integrating all the various sectors involved in such project seems to be the best approach. In this paper we present an approach based on the multi criteria analysis and the realization of one pilot to achieve the development of an innovative geo-intelligent environmental platform. An implementation of this platform will collect, process, analyze and manage environmental data in connection with the nature of used energy in the studied region. As an application we consider a region in the north of Morocco characterized by intense agricultural and industrials activities and using diverse renewable energy. The strategic goals of this platform are; the decision support for better governance, improving the responsiveness of public and private companies connected by providing them in real time with reliable data, modeling and simulation possibilities of energy scenarios, the identification of socio-technical solutions to introduce renewable energies and estimate technical and implantable potential by socio-economic analyzes and the assessment of infrastructure for the region and the communities, the preservation and enhancement of natural resources for better citizenship governance through democratization of access to environmental information, the tool will also perform simulations integrating environmental impacts of natural disasters, particularly those linked to climate change. Indeed extreme cases such as floods, droughts and storms will be no longer rare and therefore should be integrated into such projects.

Keywords: renewable energies, decision aided tool, environment, simulation

Procedia PDF Downloads 459

Authors: Saikat Datta

Abstract:

Incompressible laminar time-varying flow is investigated over a rounded backward-facing step for a triangular piston motion at the inlet of a straight channel with very high acceleration, followed by a slow deceleration experimentally and through numerical simulation. The backward-facing step is an important test-case as it embodies important flow characteristics such as separation point, reattachment length, and recirculation of flow. A sliding piston imparts two successive triangular velocities at the inlet, constant acceleration from rest, 0≤t≤t0, and constant deceleration to rest, t0≤tKeywords: laminar boundary layer separation, rounded backward facing step, separation bubble, unsteady separation, unsteady vortex flows

Procedia PDF Downloads 65

Authors: Behnam Zahednejad, Saeed Kosari

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Widespread deployment of Internet of Things (IoT) has raised security and privacy issues in this environment. Designing a secure two-factor authentication scheme between the user and server is still a challenging task. In this paper, we focus on Cancelable Biometric (CB) as an authentication factor in IoT. We show that previous CB-based scheme fail to provide real two-factor security, Perfect Forward Secrecy (PFS) and suffer database attacks and traceability of the user. Then we propose our improved scheme based on CB and Physically Unclonable Functions (PUF), which can provide real two-factor security, PFS, user’s unlinkability, and resistance to database attack. In addition, Key Compromise Impersonation (KCI) resilience is achieved in our scheme. We also prove the security of our proposed scheme formally using both Real-Or-Random (RoR) model and the ProVerif analysis tool. For the usability of our scheme, we conducted a performance analysis and showed that our scheme has the least communication cost compared to the previous CB-based scheme. The computational cost of our scheme is also acceptable for the IoT environment.

Keywords: IoT, two-factor security, cancelable biometric, key compromise impersonation resilience, perfect forward secrecy, database attack, real-or-random model, ProVerif

Procedia PDF Downloads 100

Authors: A. D. Tayal

Abstract:

The energy industry is undergoing significant disruption. This research outlines that, whilst challenging; this disruption is also an emerging opportunity for electricity utilities. One such opportunity is leveraging the developments in data analytics and machine learning. As the uptake of renewable energy technologies and complimentary control systems increases, electricity grids will likely transform towards dense microgrids with high penetration of renewable generation sources, rich in network and customer data, and linked through intelligent, wireless communications. Data digitisation and analytics have already impacted numerous industries, and its influence on the energy sector is growing, as computational capabilities increase to manage big data, and as machines develop algorithms to solve the energy challenges of the future. The objective of this paper is to address how far the uptake of renewable technologies can go given the constraints of existing grid infrastructure and provides a qualitative assessment of how higher levels of renewable energy penetration can be facilitated by incorporating even broader technological advances in the fields of data analytics and machine learning. Western Australia is used as a contextualised case study, given its abundance and diverse renewable resources (solar, wind, biomass, and wave) and isolated networks, making a high penetration of renewables a feasible target for policy makers over coming decades.

Keywords: data, innovation, renewable, solar

Procedia PDF Downloads 363