Search results for: fuel modeling

Authors: Francielle A. Vargas, Thiago A. S. Pardo

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According to the standard philosophical definition, lying is saying something that you believe to be false with the intent to deceive. For deception detection, the FBI trains its agents in a technique named statement analysis, which attempts to detect deception based on parts of speech (i.e., linguistics style). This method is employed in interrogations, where the suspects are first asked to make a written statement. In this poster, we model false statements using linguistics style. In order to achieve this, we methodically analyze linguistic features in a corpus of fake news in the Portuguese language. The results show that they present substantial lexical, syntactic and semantic variations, as well as punctuation and emotion distinctions.

Keywords: deception detection, linguistics style, computational linguistics, natural language processing

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Authors: Mohammed Aliyu, Kazunori Iwabuchi, Ibrahim Shaba Mohammed, Abubakar Sadeeq Mohammed, Solomon Musa Dauda, Zinash Delebo Osunde

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Hydrothermal carbonization (HTC) is recognised as a low temperature and effective technique for the conversion of biomass to solid biofuel. In this study, the effect of process temperature and biomass-to-water ratio (B/W) on the fuel properties of hydrochar produced from wood shavings was investigated. HTC was conducted in an autoclave using reaction temperature of 230 °C and 260 °C for 20 minutes with B/W ratio of 0.11 to 0.43. The produced hydrochars were characterised by the mass yield (MY), higher heating value (HHV), proximate and ultimate properties. The results showed that the properties of the hydrochars improved with increasing process temperature and B/W ratio. The higher heating value (HHV) increased to 26.74 MJ/kg as the severity of the reaction was increased to the process temperature of 260 °C. Also, the atomic H/C and O/C ratios of hydrochars produced at 230 °C and 260 °C were closed to the regions of a peat and lignite on the plotted van Krevelen diagram. Hence, the produced hydrochar has a promising potential as a sustainable solid biofuel for energy application.

Keywords: wood shavings, biomass/water ratio, thermochemical conversion, hydrothermal carbonization, hydrochar

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Authors: Ahmad Badawi Saluy

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This study aims to develop strategies for the prevention or elimination of environmental pollution as well as changes in external variables of the environment in order to implement the environmental management system ISO 14001:2004 by integrating analysis of environmental issues data, RKL-RPL transactional data and regulation as part of ERP on the management dashboard. This research uses a quantitative descriptive approach with analysis method comparing with air quality standard (PP 42/1999, LH 21/2008), water quality standard (permenkes RI 416/1990, KepmenLH 51/2004, kepmenLH 55/2013 ), and biodiversity indicators. Based on the research, the parameters of RPL monitoring have been identified, among others, the quality of emission air (SO₂, NO₂, dust, particulate) due to the influence of fuel quality, combustion performance in a combustor and the effect of development change around the generating area. While in water quality (TSS, TDS) there was an increase due to the flow of water in the cooling intake carrying sedimentation from the flow of Banjir Kanal Timur. Including compliance with the ISO 14001:2004 clause on application design significantly contributes to the improvement of the quality of power plant management.

Keywords: environmental management systems, power plant management, regulatory compliance , enterprises resource planning

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Authors: Heba M. Gobara, Ahmed A. M. El-Naggar, Rasha S. El-Sayed, Amal A. AlKahlawy

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In this study, metal organic framework (Cr-MIL-101) and TiO₂ nanoparticles were utilized as two semiconductors for water splitting process. The coupling of both semiconductors in order to improve the photocatalytic reactivity for the hydrogen production in presence of methanol as a hole scavenger under visible light (sunlight) has been performed. The forementioned semiconductors and the collected samples after water splitting application are characterized by several techniques viz., XRD, N₂ adsorption-desorption, TEM, ED, EDX, Raman spectroscopy and the total content of carbon. The results revealed an efficient yield of H₂ production with maximum purity 99.3% with the in-situ formation of graphene oxide nanosheets and multiwalled carbon nanotubes coated over the surface of the physically mixed Cr-MIL-101–TiO₂ system. The amount of H₂ gas produced was stored when using Cr-MIL-101 catalyst individually. The obtained data in this work provides promising candidate materials for pure hydrogen production as a clean fuel acquired from the water splitting process. In addition, the in-situ production of graphene nanosheets and carbon nanotubes is counted as promising advances for the presented process.

Keywords: hydrogen production, water splitting, photocatalysts, Graphene

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Authors: P. Ninduangdee, V. I. Kuprianov

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Palm kernel shell is an important bioenergy resource in Thailand. However, due to elevated alkali content in biomass ash, this oil palm residue shows high tendency to bed agglomeration in a fluidized-bed combustion system using conventional bed material (silica sand). In this study, palm kernel shell was burned in the conical fluidized-bed combustor (FBC) using alumina and dolomite as alternative bed materials to prevent bed agglomeration. For each bed material, the combustion tests were performed at 45kg/h fuel feed rate with excess air within 20–80%. Experimental results revealed rather weak effects of the bed material type but substantial influence of excess air on the behaviour of temperature, O2, CO, CxHy, and NO inside the reactor, as well as on the combustion efficiency and major gaseous emissions of the conical FBC. The optimal level of excess air ensuring high combustion efficiency (about 98.5%) and acceptable level of the emissions was found to be about 40% when using alumina and 60% with dolomite. By using these alternative bed materials, bed agglomeration can be prevented when burning the shell in the proposed conical FBC. However, both bed materials exhibited significant changes in their morphological, physical and chemical properties in the course of the time.

Keywords: palm kernel shell, fluidized-bed combustion, alternative bed materials, combustion and emission performance, bed agglomeration prevention

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Authors: Nieves M. C. Talavera-Prieto, Abel G. M. Ferreira, António T. G. Portugal, Rui J. Moreira, Jaime B. Santos

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The knowledge of biodiesel density over large ranges of temperature and pressure is important for predicting the behavior of fuel injection and combustion systems in diesel engines, and for the optimization of such systems. In this study, cottonseed oil was transesterified into biodiesel and its density was measured at temperatures between 288 K and 358 K and pressures between 0.1 MPa and 30 MPa, with expanded uncertainty estimated as ±1.6 kg.m^-3. Experimental pressure-volume-temperature (pVT) cottonseed data was used along with literature data relative to other 18 biodiesels, in order to build a database used to test the correlation of density with temperarure and pressure using the Goharshadi–Morsali–Abbaspour equation of state (GMA EoS). To our knowledge, this is the first that density measurements are presented for cottonseed biodiesel under such high pressures, and the GMA EoS used to model biodiesel density. The new tested EoS allowed correlations within 0.2 kg•m-3 corresponding to average relative deviations within 0.02%. The built database was used to develop and test a new full predictive model derived from the observed linear relation between density and degree of unsaturation (DU), which depended from biodiesel FAMEs profile. The average density deviation of this method was only about 3 kg.m-3 within the temperature and pressure limits of application. These results represent appreciable improvements in the context of density prediction at high pressure when compared with other equations of state.

Keywords: biodiesel density, correlation, equation of state, prediction

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Authors: Amit R. Bhende, G. K. Awari

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Remaining useful life (RUL) prediction is one of key technologies to realize prognostics and health management that is being widely applied in many industrial systems to ensure high system availability over their life cycles. The present work proposes a data-driven method of RUL prediction based on multiple health state assessment for rolling element bearings. Bearing degradation data at three different conditions from run to failure is used. A RUL prediction model is separately built in each condition. Feed forward back propagation neural network models are developed for prediction modeling.

Keywords: bearing degradation data, remaining useful life (RUL), back propagation, prognosis

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Authors: D. Habibinia, M. R. Feyzi

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Nowadays, specialized software is vastly used to verify the performance of an electric machine prototype by evaluating a model of the system. These models mainly consist of electrical parameters such as inductances and resistances. However, when the operating frequency of the device is above one kHz, the effect of parasitic capacitances grows significantly. In this paper, a software-based procedure is introduced to model these capacitances within the electromagnetic simulation of the device. The case study is a high-frequency high-voltage pulse transformer. The Finite Element Analysis (FEA) software with coupled field analysis is used in this method.

Keywords: finite element analysis, parasitic capacitance, pulse transformer, high frequency

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Authors: Pradeep Kumar, Shalinee Shukla

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Pavement plays a vital role in the socio-economic development of a country. Bituminous roads construction with conventional paving grade bitumen obtained from hot mix plant creates pollution and involves emission of greenhouse gases, also the construction of pavements at very high temperature is not feasible or desirable for high rainfall and snowfall areas. This problem of overheating can be eliminated by the construction of pavements with the usage of emulsified cold mixes which will eliminate emissions and help in the reduction of fuel requirement at mixing plant, which leads to energy conservation. Cold mix is a mixture of unheated aggregate and emulsion or cutback and filler. The primary objective of this research is to assess the volumetric mix design parameters of recycled aggregates with cold mixing technology and also to assess the impact of additives on volumetric mix characteristics. In this present study, bituminous pavement materials are reclaimed using cold mix technology, and Marshall specimens are prepared with the help of slow setting type 2 (SS-2) cationic bitumen emulsion as a binder for recycled aggregates. This technique of road construction is more environmentally friendly and can be done in adverse weather conditions.

Keywords: cold mixes, bitumen emulsion, recycled aggregates, volumetric properties

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Authors: Moudar H. A. Zgoul, Amin Al Zamer

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Adhesive materials and adhesion have been the focal point of multiple research works related to numerous applications, particularly, aerospace, and aviation industries. To enhance the properties of conventional adhesive materials, additives have been introduced to the mix in order to enhance their mechanical and physical properties by creating a hybrid adhesive material. The evaluation of the mechanical properties of such hybrid adhesive materials is thus of an essential requirement for the purpose of properly modeling their behavior accurately. This paper presents an approach/tool to simulate the behavior such hybrid adhesives in a way that will allow researchers to better understand their behavior while in service.

Keywords: adhesive materials, analysis, hybrid adhesives, mechanical properties, simulation

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Authors: Beena Sethi

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This work involves the degradation of plastic waste in the presence of three different nanocatalysts. A thin film of LLDPE was formed with all three nanocatalysts separately in the solvent. Thermo Gravimetric Analysis (TGA) and Differential Scanning Calorimetric (DSC) analysis of polymers suggest that the presence of these catalysts lowers the degradation temperature and the change mechanism of degradation. Gas chromatographic analysis was carried out for two films. In gas chromatography (GC) analysis, it was found that degradation of pure polymer produces only 32% C3/C4 hydrocarbons and 67.6% C5/C9 hydrocarbons. In the presence of these catalysts, more than 80% of polymer by weight was converted into either liquid or gaseous hydrocarbons. Change in the mechanism of degradation of polymer was observed therefore more C3/C4 hydrocarbons along with valuable feedstock are produced. Adjustment of dose of nanocatalyst, use of nano-admixtures and recycling of catalyst can make this catalytic feedstock recycling method a good tool to get sustainable environment. The obtained products can be utilized as fuel or can be transformed into other useful products. In accordance with the principles of sustainable development, chemical recycling i.e. tertiary recycling of polymers along with the reuse (zero order recycling) of plastics can be the most appropriate and promising method in this direction. The tertiary recycling is attracting much attention from the viewpoint of the energy resource.

Keywords: degradation, differential scanning calorimetry, feedstock recycling, gas chromatography, thermogravimetric analysis

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Authors: Djalal Boualili

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This article considers the problem of sizing prime movers for combined heating and power (CHP) systems operating at full load to satisfy a fraction of a facility's electric load, i.e. a base load. Prime mover sizing is examined using three criteria: operational cost, carbon dioxide emissions (CDE), and primary energy consumption (PEC). The sizing process leads to consider ratios of conversion factors applied to imported electricity to conversion factors applied to fuel consumed. These ratios are labelled RCost, R CDE, R PEC depending on whether the conversion factors are associated with operational cost, CDE, or PEC, respectively. Analytical results show that in order to achieve savings in operational cost, CDE, or PEC, the ratios must be larger than a unique constant R Min that only depends on the CHP components efficiencies. Savings in operational cost, CDE, or PEC due to CHP operation are explicitly formulated using simple equations. This facilitates the process of comparing the tradeoffs of optimizing the savings of one criterion over the other two – a task that has traditionally been accomplished through computer simulations. A hospital building, located in Chlef, Algeria, was used as an example to apply the methodology presented in this article.

Keywords: sizing, heating and power, ratios, energy consumption, carbon dioxide emissions

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Authors: Sanam Haseen, Abdul Bari

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In this paper a three stage multivariate programming problem with random survey cost and variances as random variables has been formulated as a non-linear stochastic programming problem. The problem has been converted into an equivalent deterministic form using chance constraint programming and modified E-modeling. An empirical study of the problem has been done at the end of the paper using R-simulation.

Keywords: chance constraint programming, modified E-model, stochastic programming, stratified sample surveys, three stage sample surveys

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Authors: Mohamed Amarouayache, Badia Amrouche, Gharbi Akila, Boukadoume Mohamed

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This work is devoted to the modeling of DC-DC converter (boost) used for MPPT applications to set conditions of stability. For this, we establish a linear mathematical model of the DC-DC converter with an average small signal model. This model has allowed us to apply conventional linear methods of automation. A mathematical relationship between the duty cycle and the voltage of the panel has been set up. With this relationship we specify the conditions of the stability in closed-loop depending on the system parameters (the elements of storage capacity and inductance, PWM control).

Keywords: MPPT, PWM, stability, criterion of Routh, average small signal model

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Authors: Abu Hashan Md Mashud, M. Sharif Uddin, Aminur Rahman Khan

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In this paper, we formulate a new problem as a linear programming and Integer Programming problem and maximize profit within the limited budget and limited resources based on the construction of a tea garden problem. It describes a new idea about how to optimize profit and focuses on the practical aspects of modeling and the challenges of providing a solution to a complex real life problem. Finally, a comparative study is carried out among Graphical method, Simplex method and Branch and bound method.

Keywords: integer programming, tea garden, graphical method, simplex method, branch and bound method

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Authors: Regina Kulugomba, Richard Blanchard, Harold Mapoma, Gregory Gamula, Stanley Mlatho

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Malawi is a country with low energy access with only 10% of people having access to electricity and 97% of people relying on charcoal and fuel wood. The over dependence on the traditional biomass has brought in a number of negative consequences on people’s health and the environment. To curb the situation, the Government of Malawi (GoM), through its national policy of 2018 and charcoal strategies of 2007, identified biogas as a suitable alternative energy source for cooking. The GoM intends to construct tubular digesters across the country and one of the most crucial factors is the availability of livestock manure. The study was conducted to assess biogas potential from livestock manure by using Quantum Geographic information system (QGIS) software. Potential methane was calculated based on the population of livestock, amount of manure produced per capita and year, total solids, biogas yield and availability coefficient. The results of the study estimated biogas potential at 687 million m3 /year. Districts identified with highest biogas potential were Lilongwe, Ntcheu, Mangochi, Neno, Mwanza, Blantyre, Chiradzulu and Mulanje. The information will help investors and the Government of Malawi to locate potential sites for biogas plants installation.

Keywords: biogas, energy, feedstock, livestock

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Authors: Ali Reza Sattarzadeh, Ronny J. Kutadinata, Pubudu N. Pathirana, Van Thanh Huynh

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Traffic congestion has become a severe worldwide problem, affecting everyday life, fuel consumption, time, and air pollution. The primary causes of these issues are inadequate transportation infrastructure, poor traffic signal management, and rising population. Traffic flow forecasting is one of the essential and effective methods in urban congestion and traffic management, which has attracted the attention of researchers. With the development of technology, undeniable progress has been achieved in existing methods. However, there is a possibility of improvement in the extraction of temporal and spatial features to determine the importance of traffic flow sequences and extraction features. In the proposed model, we implement the convolutional neural network (CNN) and long short-term memory (LSTM) deep learning models for mining nonlinear correlations and their effectiveness in increasing the accuracy of traffic flow prediction in the real dataset. According to the experiments, the results indicate that implementing Conv-LSTM networks increases the productivity and accuracy of deep learning models for traffic flow prediction.

Keywords: deep learning algorithms, intelligent transportation systems, spatiotemporal features, traffic flow prediction

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Authors: Mingyue Sheng, Basil Sharp

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Greenhouse gas (GHG) emissions from national transport account for the largest share of emissions from energy use in New Zealand. Whether the environmental Kuznets curve (EKC) relationship exists between environmental degradation indicators from the transport sector and economic growth in New Zealand remains unclear. This paper aims at exploring the causality relationship between CO₂ emissions from the transport sector, fossil fuel consumption, and the Gross Domestic Product (GDP) per capita in New Zealand, using annual data for the period 1977 to 2013. First, conventional unit root tests (Augmented Dickey–Fuller and Phillips–Perron tests), and a unit root test with the breakpoint (Zivot-Andrews test) are employed to examine the stationarity of the variables. Second, the autoregressive distributed lag (ARDL) bounds test for co-integration, followed by Granger causality investigated causality among the variables. Empirical results of the study reveal that, in the short run, there is a unidirectional causality between economic growth and transport CO₂ emissions with direction from economic growth to transport CO₂ emissions, as well as a bidirectional causality from transport CO₂ emissions to road energy consumption.

Keywords: economic growth, transport carbon dioxide emissions, environmental Kuznets curve, causality

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Authors: Manjare Chandraprabha A., S. D. Shirbahadurkar, Manjare Anil S., Paithne Ajay N.

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This paper proposes Intonation Modeling for Prosody generation in Neutral speech for Marathi (language spoken in Maharashtra, India) story telling applications. Nowadays audio story telling devices are very eminent for children. In this paper, we proposed tilt model for stressed words in Marathi for speech modification. Tilt model predicts modification in tone of neutral speech. GMM is used to identify stressed words for modification.

Keywords: tilt model, fundamental frequency, statistical parametric speech synthesis, GMM

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Authors: Dianxun Zheng, Wuxing Jing, Lin Hetong

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Optical remote sensing satellite, always running on the Sun-synchronous orbit, equipped laser warning equipment to alert CCD camera from laser attack. There have three ways to protect the CCD camera, closing the camera cover satellite attitude maneuver and satellite orbit avoidance. In order to enhance the safety of optical remote sensing satellite in orbit, this paper explores the strategy of satellite avoidance. The avoidance strategy is expressed as the evasion of pre-determined target points in the orbital coordinates of virtual satellite. The so-called virtual satellite is a passive vehicle which superposes a satellite at the initial stage of avoidance. The target points share the consistent cycle time and the same semi-major axis with the virtual satellite, which ensures the properties of the Sun-synchronous orbit remain unchanged. Moreover, to further strengthen the avoidance capability of satellite, it can perform multi-object avoid maneuvers. On occasions of fulfilling the orbit tasks of the satellite, the orbit can be restored back to virtual satellite through orbit maneuvers. There into, the avoid maneuvers adopts pulse guidance. and the fuel consumption is also optimized. The avoidance strategy discussed in this article is applicable to avoidance for optical remote sensing satellite when encounter the laser hostile attacks.

Keywords: optical remote sensing satellite, always running on the sun-synchronous

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Authors: Sujeeta Karki, Jeeban Poudel, Ja Hyung Choi, Sea Cheon Oh

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A lab-scale fluidized bed was used for the study of sewage sludge, a non-lignocellulosic biomass, torrefaction. The influence of torrefaction temperature ranging from 200–350 °C and residence time of 0–50 minutes on the physical and chemical properties of the torrefied product was investigated. Properties of the torrefied product were analyzed on the basis of degree of torrefaction, ultimate and proximate analysis, gas analysis and chemical exergy. The degree of torrefaction and chemical exergy had a positive influence on increasing the torrefaction temperature. Moreover, the effect of torrefaction temperature and residence time on the elemental variation of sewage sludge exhibited an increase in the weight percentage of carbon while the content of H/C and O/C molar ratios decreased. The product gas emitted during torrefaction was analyzed to study the pathway of hydrocarbons and oxygen-containing compounds. The compounds with oxygen were emitted at higher temperatures in contrast to hydrocarbon gases. An attempt was made to obtain the chemical exergy of sewage sludge. In addition, the study of various correlations for predicting the calorific value of torrefied sewage sludge was made.

Keywords: chemical exergy, degree of torrefaction, fluidized bed, higher heating value (HHV), O/C and H/C molar ratios, sewage sludge

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Authors: Alia Alghosoun, Nabil El Moçayd, Mohammed Seaid

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Modeling dam-break flows over non-flat beds requires an accurate representation of the topography which is the main source of uncertainty in the model. Therefore, developing robust and accurate techniques for reconstructing topography in this class of problems would reduce the uncertainty in the flow system. In many hydraulic applications, experimental techniques have been widely used to measure the bed topography. In practice, experimental work in hydraulics may be very demanding in both time and cost. Meanwhile, computational hydraulics have served as an alternative for laboratory and field experiments. Unlike the forward problem, the inverse problem is used to identify the bed parameters from the given experimental data. In this case, the shallow water equations used for modeling the hydraulics need to be rearranged in a way that the model parameters can be evaluated from measured data. However, this approach is not always possible and it suffers from stability restrictions. In the present work, we propose an adaptive optimal control technique to numerically identify the underlying bed topography from a given set of free-surface observation data. In this approach, a minimization function is defined to iteratively determine the model parameters. The proposed technique can be interpreted as a fractional-stage scheme. In the first stage, the forward problem is solved to determine the measurable parameters from known data. In the second stage, the adaptive control Ensemble Kalman Filter is implemented to combine the optimality of observation data in order to obtain the accurate estimation of the topography. The main features of this method are on one hand, the ability to solve for different complex geometries with no need for any rearrangements in the original model to rewrite it in an explicit form. On the other hand, its achievement of strong stability for simulations of flows in different regimes containing shocks or discontinuities over any geometry. Numerical results are presented for a dam-break flow problem over non-flat bed using different solvers for the shallow water equations. The robustness of the proposed method is investigated using different numbers of loops, sensitivity parameters, initial samples and location of observations. The obtained results demonstrate high reliability and accuracy of the proposed techniques.

Keywords: erodible beds, finite element method, finite volume method, nonlinear elasticity, shallow water equations, stresses in soil

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Authors: A. El-S. Makled, M. K. Al-Tamimi

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Ignition phenomena are of great interest area over the past many years, and it has a direct impact on many propulsion and combustion applications. The direct goal of the paper is to realize and evaluate a functioning ignition method, shut-off, throttling and re-start operations for the hybrid rocket motor. A small-scale hybrid rocket motor (SSHRM) is designed, manufactured, demonstrated at various operating conditions and finally equipped for laboratory firing tests with high level of safety. Various solid fuel grains as Polymethyle-methacrylate (PMMA) and Polyethylene (PE) are selected, and it is decided to use the commercial gaseous oxygen (GO2) for its availability and low cost. Examine different types of ignition methods, pyrotechnic charge, fuse wire, heat wire and finally hot oxidizer method by using the heat exchanger, which are proposed as very safe ignition methods. Finally; recognize phenomena of throttling and re-start operations. Ignition by hot GO2 impingement is proved to be a very attractive ignition method for laboratory SSHRM, for its high safety, reliability and acceptable delay time. Finally; the throttling and re-start operations are demonstrated several times and can be carried out more easily with hot air ignition method.

Keywords: hybrid rocket motor, ignition system, re-start phenomena, throttling

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Authors: Kholod J. Alotaibi, Andrew M. Gravell

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Usability is an important software quality that is often neglected at the design stage. Although methods exist to incorporate elements of usability engineering, there is a need for more balanced usability focused methods that can enhance the experience of software usability for users. In this regard, the potential for Usage-Centered Design is explored with respect to requirements gathering and is shown to lead to high software usability besides other benefits. It achieves this through its focus on usage, defining essential use cases, by conducting task modeling, encouraging user collaboration, refining requirements, and so on. The requirements gathering process in UgCD is described in detail.

Keywords: requirements gathering, usability, usage-centred design, computer science

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Authors: A. B. Bolkhir, A. Elshafie, T. K. Yousif

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This paper highlights the methods of error estimation in finite element analysis (FEA) results. It indicates that the modeling error could be eliminated by performing finite element analysis with successively finer meshes or by extrapolating response predictions from an orderly sequence of relatively low degree of freedom analysis results. In addition, the paper eliminates the round-off error by running the code at a higher precision. The paper provides application in finite element analysis results. It draws a conclusion based on results of application of methods of error estimation.

Keywords: finite element analysis (FEA), discretization error, round-off error, mesh refinement, richardson extrapolation, monotonic convergence

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Authors: O. Mowla, E. Kennedy, M. Stockenhuber

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Finding alternative renewable resources of energy has attracted the attentions in consequence of limitation of the traditional fossil fuel resources, increasing of crude oil price and environmental concern over greenhouse gas emissions. Biodiesel (or Fatty Acid Methyl Esters (FAME)), an alternative energy source, is synthesised from renewable sources such as vegetable oils and animal fats and can be produced from waste oils. FAME can be produced via hydroesterification of oils. The process involves two stages. In the first stage of this process, fatty acids and glycerol are being obtained by hydrolysis of the feed stock oil. In the second stage, the recovered fatty acids are then esterified with an alcohol to methyl esters. The presence of a catalyst accelerates the rate of the hydroesterification reaction of oils. The overarching aim of this study is to find the effect of using zeolite as a catalyst in the heterogeneous hydroesterification of soybean oil. Both stages of the catalytic hydroesterification of soybean oil had been conducted at atmospheric and high-pressure conditions using reflux glass reactor and Parr reactor, respectively. The effect of operating parameters such as temperature and reaction time on the overall yield of biodiesel formation was also investigated.

Keywords: biodiesel, heterogeneous catalytic hydroesterification, soybean oil, zeolite

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Authors: Y. Madani, H. Achache, B. Boutabout

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The purpose of this paper is to analyze numerically by the three-dimensional finite element method, using ABAQUS calculation code, the mechanical behavior of a unidirectional and multidirectional delaminated stratified composite under mechanical loading in Mode II. This study consists of the determination of the energy release rate G in mode II as well as the distribution of equivalent von Mises stresses along the damaged zone by varying several parameters such as the applied load and the delamination length. It allowed us to deduce that the high energy release rate favors delamination at the free edges of a stratified plate subjected to bending.

Keywords: delamination, energy release rate, finite element method, stratified composite

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Authors: Cristóbal Moënne-Loccoz, Rodrigo C. Vergara, Vladimir López, Domingo Mery, Diego Cosmelli

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Our daily interaction with computational interfaces is plagued of situations in which we go from inexperienced users to experts through self-motivated exploration of the same task. In many of these interactions, we must learn to find our way through a sequence of decisions and actions before obtaining the desired result. For instance, when drawing cash from an ATM machine, choices are presented in a step-by-step fashion so that a specific sequence of actions must be performed in order to produce the expected outcome. But, as they become experts in the use of such interfaces, do users adopt specific search and learning strategies? Moreover, if so, can we use this information to follow the process of expertise development and, eventually, predict future actions? This would be a critical step towards building truly adaptive interfaces that can facilitate interaction at different moments of the learning curve. Furthermore, it could provide a window into potential mechanisms underlying decision-making behavior in real world scenarios. Here we tackle this question using a simple game interface that instantiates a 4-level binary decision tree (BDT) sequential decision-making task. Participants have to explore the interface and discover an underlying concept-icon mapping in order to complete the game. We develop a Hidden Markov Model (HMM)-based approach whereby a set of stereotyped, hierarchically related search behaviors act as hidden states. Using this model, we are able to track the decision-making process as participants explore, learn and develop expertise in the use of the interface. Our results show that partitioning the problem space into such stereotyped strategies is sufficient to capture a host of exploratory and learning behaviors. Moreover, using the modular architecture of stereotyped strategies as a Mixture of Experts, we are able to simultaneously ask the experts about the user's most probable future actions. We show that for those participants that learn the task, it becomes possible to predict their next decision, above chance, approximately halfway through the game. Our long-term goal is, on the basis of a better understanding of real-world decision-making processes, to inform the construction of interfaces that can establish dynamic conversations with their users in order to facilitate the development of expertise.

Keywords: behavioral modeling, expertise acquisition, hidden markov models, sequential decision-making

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Authors: Aditya, Ganapati Joshi, Vinod Kumar

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IN THE MODERN-WARFARE ERA, THE PRIME REQUIREMENT IS A HIGH SPEED AND MACH NUMBER. WHEN THE MISSILES STRIKE IN THE HYPERSONIC REGIME THE OPPONENT CAN DETECT IT WITH THE ANTI-DEFENSE SYSTEM BUT CAN NOT STOP IT FROM CAUSING DAMAGE. SO, TO ACHIEVE THE SPEEDS OF THIS LEVEL THERE ARE TWO ENGINES THAT ARE AVAILABLE WHICH CAN WORK IN THIS REGION ARE RAMJET AND SCRAMJET. THE PROBLEM WITH RAMJET STARTS TO OCCUR WHEN MACH NUMBER EXCEEDS 4 AS THE STATIC PRESSURE AT THE INLET BECOMES EQUAL TO THE EXIT PRESSURE. SO, SCRAMJET ENGINE DEALS WITH THIS PROBLEM AS IT NEARLY HAS THE SAME WORKING BUT HERE THE FLOW IS NOT MUCH SLOWED DOWN AS COMPARED TO RAMJET IN THE DIFFUSER BUT IT SUFFERS FROM THE PROBLEMS SUCH AS INLET BUZZ, THERMAL CHOCKING, MIXING OF FUEL AND OXIDIZER, THERMAL HEATING, AND MANY MORE. HERE THE NEW ENGINE IS DEVELOPED ON THE SAME PRINCIPLE AS THE SCRAMJET ENGINE BUT BURNING HAPPENS DUE TO DETONATION INSTEAD OF DEFLAGRATION. THE PROBLEM WITH THE ENGINE STARTS WHEN THE MACH NUMBER BECOMES VARIABLE AND THE INLET GEOMETRY IS FIXED AND THIS LEADS TO INLET SPILLAGE WHICH WILL AFFECT THE THRUST ADVERSELY. SO, HERE ADAPTIVE INLET IS MADE OF SHAPE MEMORY ALLOYS WHICH WILL ENHANCE THE INLET MASS FLOW RATE AS WELL AS THRUST.

Keywords: detonation, ramjet engine, shape memory alloy, ignition delay, shock-boundary layer interaction, eddy dissipation, asymmetric nozzle

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Authors: Ioannis P. Panapakidis, Marios N. Moschakis

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With the continuous increment of smart meter installations across the globe, the need for processing of the load data is evident. Clustering-based load profiling is built upon the utilization of unsupervised machine learning tools for the purpose of formulating the typical load curves or load profiles. The most commonly used algorithm in the load profiling literature is the K-means. While the algorithm has been successfully tested in a variety of applications, its drawback is the strong dependence in the initialization phase. This paper proposes a novel modified form of the K-means that addresses the aforementioned problem. Simulation results indicate the superiority of the proposed algorithm compared to the K-means.

Keywords: clustering, load profiling, load modeling, machine learning, energy efficiency and quality

Procedia PDF Downloads 153