Search results for: fuel volume estimation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32912

Search results for: fuel volume estimation

31892 Dry Binder Mixing of Field Trial Investigation Using Soil Mix Technology: A Case Study on Contaminated Site Soil

Authors: M. Allagoa, A. Al-Tabbaa

Abstract:

The study explores the use of binders and additives, such as Portland cement, pulverized fuel ash, ground granulated blast furnace slag, and MgO, to reduce the concentration and leachability of pollutants in contaminated site soils. The research investigates their effectiveness and associated risks of binders, with a focus on Total Heavy Metals (THM) and Total Petroleum Hydrocarbon (TPH). The goal of this research is to evaluate the performance and effectiveness of binders and additives in remediating soil pollutants. The study aims to assess the suitability of the mixtures for ground improvement purposes, determine the optimal dosage, and investigate the associated risks. The research utilizes physical (unconfined compressive strength) and chemical tests (batch leachability test) to assess the efficacy of the binders and additives. A completely randomized design one-way ANOVA is used to determine the significance within mix binders of THM. The study also employs incremental lifetime cancer risk (ILCR) assessments and other indices to evaluate the associated risks. The study finds that Ground Granulated Blast Furnace Slag (GGBS): MgO is the most effective binder for remediation, particularly when using low dosages of MgO combined with higher dosages of GGBS binders on TPH. The results indicate that binders and additives can encapsulate and immobilize pollutants, thereby reducing their leachability and toxicity. The mean unconfined compressive strength of the soil ranges from 285.0-320.5 kPa, while THM levels with a combination of Ground granulated blast furnace slag and Magnesium oxide, Portland cement and Pulverised fuel ash were less than 10 µg/l. Portland cement was below 1 µg/l. The ILCR ranged from 6.77E-02 - 2.65E-01 and 5.444E-01 - 3.20 E+00, with the highest values observed under extreme conditions. The hazard index (HI), risk allowable daily dose intake (ADI), and risk chronic daily intake (CDI) were all less than 1 for the THM. The study identifies MgO as the best additive for use in soil remediation.

Keywords: Risk daily dose intake, risk chronic daily intake, incremental lifetime cancer risk, ILCR, novel binders, additives binders, hazard index.

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31891 Estimating Frequency, Amplitude and Phase of Two Sinusoids with Very Close Frequencies

Authors: Jayme G. A. Barbedo, Amauri Lopes

Abstract:

This paper presents an algorithm to estimate the parameters of two closely spaced sinusoids, providing a frequency resolution that is more than 800 times greater than that obtained by using the Discrete Fourier Transform (DFT). The strategy uses a highly optimized grid search approach to accurately estimate frequency, amplitude and phase of both sinusoids, keeping at the same time the computational effort at reasonable levels. The proposed method has three main characteristics: 1) a high frequency resolution; 2) frequency, amplitude and phase are all estimated at once using one single package; 3) it does not rely on any statistical assumption or constraint. Potential applications to this strategy include the difficult task of resolving coincident partials of instruments in musical signals.

Keywords: Closely spaced sinusoids, high-resolution parameter estimation, optimized grid search.

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31890 Application of Artificial Neural Network for Predicting Maintainability Using Object-Oriented Metrics

Authors: K. K. Aggarwal, Yogesh Singh, Arvinder Kaur, Ruchika Malhotra

Abstract:

Importance of software quality is increasing leading to development of new sophisticated techniques, which can be used in constructing models for predicting quality attributes. One such technique is Artificial Neural Network (ANN). This paper examined the application of ANN for software quality prediction using Object- Oriented (OO) metrics. Quality estimation includes estimating maintainability of software. The dependent variable in our study was maintenance effort. The independent variables were principal components of eight OO metrics. The results showed that the Mean Absolute Relative Error (MARE) was 0.265 of ANN model. Thus we found that ANN method was useful in constructing software quality model.

Keywords: Software quality, Measurement, Metrics, Artificial neural network, Coupling, Cohesion, Inheritance, Principal component analysis.

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31889 Manufacturing Process and Cost Estimation through Process Detection by Applying Image Processing Technique

Authors: Chalakorn Chitsaart, Suchada Rianmora, Noppawat Vongpiyasatit

Abstract:

In order to reduce the transportation time and cost for direct interface between customer and manufacturer, the image processing technique has been introduced in this research where designing part and defining manufacturing process can be performed quickly. A3D virtual model is directly generated from a series of multi-view images of an object, and it can be modified, analyzed, and improved the structure, or function for the further implementations, such as computer-aided manufacturing (CAM). To estimate and quote the production cost, the user-friendly platform has been developed in this research where the appropriate manufacturing parameters and process detections have been identified and planned by CAM simulation.

Keywords: Image processing technique, Feature detections, Surface registrations, Capturing multi-view images, Production costs, and Manufacturing processes.

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31888 A Numerical Model Simulation for an Updraft Gasifier Using High Temperature Steam

Authors: T. M. Ismail, M. Abd El-Salam

Abstract:

A mathematical model study was carried out to investigate gasification of biomass fuels using high temperature air and steam as a gasifying agent using high-temperature air up to 1000°C. In this study, a 2D computational fluid dynamics model was developed to study the gasification process in an updraft gasifier, considering drying, pyrolysis, combustion, and gasification reactions. The gas and solid phases were resolved using a Euler−Euler multiphase approach, with exchange terms for the momentum, mass, and energy. The standard k−ε turbulence model was used in the gas phase, and the particle phase was modeled using the kinetic theory of granular flow. The results show that the present model giving a promise way in its capability and sensitivity for the parameter affects that influence the gasification process.

Keywords: Computational fluid dynamics, gasification, biomass fuel, fixed bed gasifier

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31887 Analysis of Distribution of Thrust, Torque and Efficiency of a Constant Chord, Constant Pitch C.R.P. Fan by H.E.S. Method

Authors: Morteza Abbaszadeh, Parvin Nikpoorparizi, Mina Shahrooz

Abstract:

For the first time since 1940 and presentation of theodorson-s theory, distribution of thrust, torque and efficiency along the blade of a counter rotating propeller axial fan was studied with a novel method in this research. A constant chord, constant pitch symmetric fan was investigated with Reynolds Stress Turbulence method in this project and H.E.S. method was utilized to obtain distribution profiles from C.F.D. tests outcome. C.F.D. test results were validated by estimation from Playlic-s analytical method. Final results proved ability of H.E.S. method to obtain distribution profiles from C.F.D test results and demonstrated interesting facts about effects of solidity and differences between distributions in front and rear section.

Keywords: C.F.D Test, Counter Rotating Propeller, H.E.S. Method, R.S.M. Method

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31886 Model Predictive Fuzzy Control of Air-ratio for Automotive Engines

Authors: Hang-cheong Wong, Pak-kin Wong, Chi-man Vong, Zhengchao Xie, Shaojia Huang

Abstract:

Automotive engine air-ratio plays an important role of emissions and fuel consumption reduction while maintains satisfactory engine power among all of the engine control variables. In order to effectively control the air-ratio, this paper presents a model predictive fuzzy control algorithm based on online least-squares support vector machines prediction model and fuzzy logic optimizer. The proposed control algorithm was also implemented on a real car for testing and the results are highly satisfactory. Experimental results show that the proposed control algorithm can regulate the engine air-ratio to the stoichiometric value, 1.0, under external disturbance with less than 5% tolerance.

Keywords: Air-ratio, Fuzzy logic, online least-squares support vector machine, model predictive control.

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31885 Odor Discrimination Using Neural Decoding of Olfactory Bulbs in Rats

Authors: K.-J. You, H.J. Lee, Y. Lang, C. Im, C.S. Koh, H.-C. Shin

Abstract:

This paper presents a novel method for inferring the odor based on neural activities observed from rats- main olfactory bulbs. Multi-channel extra-cellular single unit recordings were done by micro-wire electrodes (tungsten, 50μm, 32 channels) implanted in the mitral/tufted cell layers of the main olfactory bulb of anesthetized rats to obtain neural responses to various odors. Neural response as a key feature was measured by substraction of neural firing rate before stimulus from after. For odor inference, we have developed a decoding method based on the maximum likelihood (ML) estimation. The results have shown that the average decoding accuracy is about 100.0%, 96.0%, 84.0%, and 100.0% with four rats, respectively. This work has profound implications for a novel brain-machine interface system for odor inference.

Keywords: biomedical signal processing, neural engineering, olfactory, neural decoding, BMI

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31884 Methodology of the Energy Supply Disturbances Affecting Energy System

Authors: J. Augutis, R. Krikstolaitis, L. Martisauskas

Abstract:

Recently global concerns for the energy security have steadily been on the increase and are expected to become a major issue over the next few decades. Energy security refers to a resilient energy system. This resilient system would be capable of withstanding threats through a combination of active, direct security measures and passive or more indirect measures such as redundancy, duplication of critical equipment, diversity in fuel, other sources of energy, and reliance on less vulnerable infrastructure. Threats and disruptions (disturbances) to one part of the energy system affect another. The paper presents methodology in theoretical background about energy system as an interconnected network and energy supply disturbances impact to the network. The proposed methodology uses a network flow approach to develop mathematical model of the energy system network as the system of nodes and arcs with energy flowing from node to node along paths in the network.

Keywords: Energy Security, Energy Supply Disturbances, Modeling of Energy System, Network Flow

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31883 Using Morphological and Microsatellite (SSR) Markers to Assess the Genetic Diversity in Alfalfa (Medicago sativa L.)

Authors: T. Cholastova, D. Knotova

Abstract:

Utilization of diverse germplasm is needed to enhance the genetic diversity of cultivars. The objective of this study was to evaluate the genetic relationships of 98 alfalfa germplasm accessions using morphological traits and SSR markers. From the 98 tested populations, 81 were locals originating in Europe, 17 were introduced from USA, Australia, New Zealand and Canada. Three primers generated 67 polymorphic bands. The average polymorphic information content (PIC) was very high (> 0.90) over all three used primer combinations. Cluster analysis using Unweighted Pair Group Method with Arithmetic Means (UPGMA) and Jaccard´s coefficient grouped the accessions into 2 major clusters with 4 sub-clusters with no correlation between genetic and morphological diversity. The SSR analysis clearly indicated that even with three polymorphic primers, reliable estimation of genetic diversity could be obtained.

Keywords: genetic diversity, Medicago sativa L., morphological traits, SSR markers

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31882 Non-Linear Control Based on State Estimation for the Convoy of Autonomous Vehicles

Authors: M-M. Mohamed Ahmed, Nacer K. M’Sirdi, Aziz Naamane

Abstract:

In this paper, a longitudinal and lateral control approach based on a nonlinear observer is proposed for a convoy of autonomous vehicles to follow a desired trajectory. To authors best knowledge, this topic has not yet been sufficiently addressed in the literature for the control of multi vehicles. The modeling of the convoy of the vehicles is revisited using a robotic method for simulation purposes and control design. With these models, a sliding mode observer is proposed to estimate the states of each vehicle in the convoy from the available sensors, then a sliding mode control based on this observer is used to control the longitudinal and lateral movement. The validation and performance evaluation are done using the well-known driving simulator Scanner-Studio. The results are presented for different maneuvers of 5 vehicles.

Keywords: Autonomous vehicles, convoy, nonlinear control, nonlinear observer, sliding mode.

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31881 Energy Consumption and GHG Production in Railway and Road Passenger Regional Transport

Authors: Martin Kendra, Tomas Skrucany, Jozef Gnap, Jan Ponicky

Abstract:

Paper deals with the modeling and simulation of energy consumption and GHG production of two different modes of regional passenger transport – road and railway. These two transport modes use the same type of fuel – diesel. Modeling and simulation of the energy consumption in transport is often used due to calculation satisfactory accuracy and cost efficiency. Paper deals with the calculation based on EN standards and information collected from technical information from vehicle producers and characteristics of tracks. Calculation included maximal theoretical capacity of bus and train and real passenger’s measurement from operation. Final energy consumption and GHG production is calculated by using software simulation. In evaluation of the simulation is used system “well to wheel”.

Keywords: Bus, energy consumption, GHG, production, simulation, train.

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31880 Utilization of Schnerr-Sauer Cavitation Model for Simulation of Cavitation Inception and Super Cavitation

Authors: Mohammadreza Nezamirad, Azadeh Yazdi, Sepideh Amirahmadian, Nasim Sabetpour, Amirmasoud Hamedi

Abstract:

In this study, the Reynolds-Stress-Navier-Stokes framework is utilized to investigate the flow inside the diesel injector nozzle. The flow is assumed to be multiphase as the formation of vapor by pressure drop is visualized. For pressure and velocity linkage, the coupled algorithm is used. Since the cavitation phenomenon inherently is unsteady, the quasi-steady approach is utilized for saving time and resources in the current study. Schnerr-Sauer cavitation model is used, which was capable of predicting flow behavior both at the initial and final steps of the cavitation process. Two different turbulent models were used in this study to clarify which one is more capable in predicting cavitation inception and super-cavitation. It was found that K-ε was more compatible with the Shnerr-Sauer cavitation model; therefore, the mentioned model is used for the rest of this study.

Keywords: CFD, RANS, cavitation, fuel, injector.

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31879 Fault Location Identification in High Voltage Transmission Lines

Authors: Khaled M. El Naggar

Abstract:

This paper introduces a digital method for fault section identification in transmission lines. The method uses digital set of the measured short circuit current to locate faults in electrical power systems. The digitized current is used to construct a set of overdetermined system of equations. The problem is then constructed and solved using the proposed digital optimization technique to find the fault distance. The proposed optimization methodology is an application of simulated annealing optimization technique. The method is tested using practical case study to evaluate the proposed method. The accurate results obtained show that the algorithm can be used as a powerful tool in the area of power system protection.

Keywords: Optimization, estimation, faults, measurement, high voltage, simulated annealing.

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31878 Time and Distance Dependence of Protons Energy Loss for Laser (pw-ps) Fusion Driven Ion Acceleration

Authors: B. Malekynia

Abstract:

The anomalous generation of plasma blocks by interaction of petawatt-picosecond laser pulses permits side-on ignition of uncompressed solid fusion fuel following an improved application of the hydrodynamic Chu-model for deuterium-tritium. The new possibility of side-on laser ignition depends on accelerated ions and produced ions beams of high energy particles by the nonlinear ponderomotive force of the laser pulse in the plasma block, a re-evaluation of the early hydrodynamic analysis for ignition of inertial fusion by including inhibition factor, collective effect of stopping power of alpha particles and the energy loss rate reabsorption to plasma by the protons of plasma blocks being reduced by about a factor 40.

Keywords: Block ignition, Charged particles, Reabsorption, Skin layer ponderomotive acceleration.

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31877 Angle of Arrival Estimation Using Maximum Likelihood Method

Authors: H. K. Hwang, Zekeriya Aliyazicioglu, Solomon Wu, Hung Lu, Nick Wilkins, Daniel Kerr

Abstract:

Multiple-input multiple-output (MIMO) radar has received increasing attention in recent years. MIMO radar has many advantages over conventional phased array radar such as target detection,resolution enhancement, and interference suppression. In this paper, the results are presented from a simulation study of MIMO uniformly-spaced linear array (ULA) antennas. The performance is investigated under varied parameters, including varied array size, pseudo random (PN) sequence length, number of snapshots, and signal to noise ratio (SNR). The results of MIMO are compared to a traditional array antenna.

Keywords: Multiple-input multiple-output (MIMO) radar, phased array antenna, target detection, radar signal processing.

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31876 Robust Adaptation to Background Noise in Multichannel C-OTDR Monitoring Systems

Authors: Andrey V. Timofeev, Viktor M. Denisov

Abstract:

A robust sequential nonparametric method is proposed for adaptation to background noise parameters for real-time. The distribution of background noise was modelled like to Huber contamination mixture. The method is designed to operate as an adaptation-unit, which is included inside a detection subsystem of an integrated multichannel monitoring system. The proposed method guarantees the given size of a nonasymptotic confidence set for noise parameters. Properties of the suggested method are rigorously proved. The proposed algorithm has been successfully tested in real conditions of a functioning C-OTDR monitoring system, which was designed to monitor railways.

Keywords: Guaranteed estimation, multichannel monitoring systems, non-asymptotic confidence set, contamination mixture.

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31875 Integrated Power Saving for Multiple Relays and UEs in LTE-TDD

Authors: Chun-Chuan Yang, Jeng-Yueng Chen, Yi-Ting Mai, Chen-Ming Yang

Abstract:

In this paper, the design of integrated sleep scheduling for relay nodes and user equipments under a Donor eNB (DeNB) in the mode of Time Division Duplex (TDD) in LTE-A is presented. The idea of virtual time is proposed to deal with the discontinuous pattern of the available radio resource in TDD, and based on the estimation of the traffic load, three power saving schemes in the top-down strategy are presented. Associated mechanisms in each scheme including calculation of the virtual subframe capacity, the algorithm of integrated sleep scheduling, and the mapping mechanisms for the backhaul link and the access link are presented in the paper. Simulation study shows the advantage of the proposed schemes in energy saving over the standard DRX scheme.

Keywords: LTE-A, Relay, TDD, Power Saving.

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31874 Fractal - Wavelet Based Techniques for Improving the Artificial Neural Network Models

Authors: Reza Bazargan Lari, Mohammad H. Fattahi

Abstract:

Natural resources management including water resources requires reliable estimations of time variant environmental parameters. Small improvements in the estimation of environmental parameters would result in grate effects on managing decisions. Noise reduction using wavelet techniques is an effective approach for preprocessing of practical data sets. Predictability enhancement of the river flow time series are assessed using fractal approaches before and after applying wavelet based preprocessing. Time series correlation and persistency, the minimum sufficient length for training the predicting model and the maximum valid length of predictions were also investigated through a fractal assessment.

Keywords: Wavelet, de-noising, predictability, time series fractal analysis, valid length, ANN.

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31873 A Posterior Predictive Model-Based Control Chart for Monitoring Healthcare

Authors: Yi-Fan Lin, Peter P. Howley, Frank A. Tuyl

Abstract:

Quality measurement and reporting systems are used in healthcare internationally. In Australia, the Australian Council on Healthcare Standards records and reports hundreds of clinical indicators (CIs) nationally across the healthcare system. These CIs are measures of performance in the clinical setting, and are used as a screening tool to help assess whether a standard of care is being met. Existing analysis and reporting of these CIs incorporate Bayesian methods to address sampling variation; however, such assessments are retrospective in nature, reporting upon the previous six or twelve months of data. The use of Bayesian methods within statistical process control for monitoring systems is an important pursuit to support more timely decision-making. Our research has developed and assessed a new graphical monitoring tool, similar to a control chart, based on the beta-binomial posterior predictive (BBPP) distribution to facilitate the real-time assessment of health care organizational performance via CIs. The BBPP charts have been compared with the traditional Bernoulli CUSUM (BC) chart by simulation. The more traditional “central” and “highest posterior density” (HPD) interval approaches were each considered to define the limits, and the multiple charts were compared via in-control and out-of-control average run lengths (ARLs), assuming that the parameter representing the underlying CI rate (proportion of cases with an event of interest) required estimation. Preliminary results have identified that the BBPP chart with HPD-based control limits provides better out-of-control run length performance than the central interval-based and BC charts. Further, the BC chart’s performance may be improved by using Bayesian parameter estimation of the underlying CI rate.

Keywords: Average run length, Bernoulli CUSUM chart, beta binomial posterior predictive distribution, clinical indicator, health care organization, highest posterior density interval.

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31872 Application Quality Function Deployment (QFD) Tool in Design of Aero Pumps Based on System Engineering

Authors: Z. Soleymani, M. Amirzadeh

Abstract:

Quality Function Deployment (QFD) was developed in 1960 in Japan and introduced in 1983 in America and Europe. The paper presents a real application of this technique in a way that the method of applying QFD in design and production aero fuel pumps has been considered. While designing a product and in order to apply system engineering process, the first step is identification customer needs then its transition to engineering parameters. Since each change in deign after production process leads to extra human costs and also increase in products quality risk, QFD can make benefits in sale by meeting customer expectations. Since the needs identified as well, the use of QFD tool can lead to increase in communications and less deviation in design and production phases, finally it leads to produce the products with defined technical attributes.

Keywords: Customer voice, engineering parameters, QFD, gear pump.

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31871 Nonlinear Modeling of the PEMFC Based On NNARX Approach

Authors: Shan-Jen Cheng, Te-Jen Chang, Kuang-Hsiung Tan, Shou-Ling Kuo

Abstract:

Polymer Electrolyte Membrane Fuel Cell (PEMFC) is such a time-vary nonlinear dynamic system. The traditional linear modeling approach is hard to estimate structure correctly of PEMFC system. From this reason, this paper presents a nonlinear modeling of the PEMFC using Neural Network Auto-regressive model with eXogenous inputs (NNARX) approach. The multilayer perception (MLP) network is applied to evaluate the structure of the NNARX model of PEMFC. The validity and accuracy of NNARX model are tested by one step ahead relating output voltage to input current from measured experimental of PEMFC. The results show that the obtained nonlinear NNARX model can efficiently approximate the dynamic mode of the PEMFC and model output and system measured output consistently.

Keywords: PEMFC, neural network, nonlinear identification, NNARX.

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31870 Impairments Correction of Six-Port Based Millimeter-Wave Radar

Authors: Dan Ohev Zion, Alon Cohen

Abstract:

In recent years, the presence of short-range millimeter-wave radar in civil application has increased significantly. Autonomous driving, security, 3D imaging and high data rate communication systems are a few examples. The next challenge is the integration inside small form-factor devices, such as smartphones (e.g. gesture recognition). The main challenge is implementation of a truly low-power, low-complexity high-resolution radar. The most popular approach is the Frequency Modulated Continuous Wave (FMCW) radar, with an analog multiplication front-end. In this paper, we present an approach for adaptive estimation and correction of impairments of such front-end, specifically implemented using the Six-Port Device (SPD) as the multiplier element. The proposed algorithm was simulated and implemented on a 60 GHz radar lab prototype.

Keywords: Radar, millimeter-wave, six-port, FMCW Radar, IQ mismatch.

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31869 Monotonic and Cyclic J-integral Estimation for Through-Wall Cracked Straight Pipes

Authors: Rohit, S. Vishnuvardhan, P. Gandhi, Nagesh R. Iyer

Abstract:

The evaluation of energy release rate and centre Crack Opening Displacement (COD) for circumferential Through-Wall Cracked (TWC) pipes is an important issue in the assessment of critical crack length for unstable fracture. The ability to predict crack growth continues to be an important component of research for several structural materials. Crack growth predictions can aid the understanding of the useful life of a structural component and the determination of inspection intervals and criteria. In this context, studies were carried out at CSIR-SERC on Nuclear Power Plant (NPP) piping components subjected to monotonic as well as cyclic loading to assess the damage for crack growth due to low-cycle fatigue in circumferentially TWC pipes.

Keywords: 304LN stainless steel, cyclic J-integral, Elastic- Plastic Fracture Mechanics, J-integral, Through-wall crack

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31868 Modeling Cost Structure for Assessment Production Cost of Algal - Biofue

Authors: A. Eman Mohammed

Abstract:

Algae-based fuel are considered a promising sources of clean energy, and because it has many advantages over traditional biofuel, research and business ventures have driven into developing and producing Algal-biofuel. But its production stages create a cost structure that it is not competitive with traditional fuels. Therefore, cost becomes the main obstacle in commercial production purpose. However, the present research which aims at using cost structure model, and designed MS-Dose program, to investigate the a mount of production cost and determined the parameter had great effect on it, second to measured the amount of contribution rate of algae in process the pollution by capturing Co2 from air . The result generated from the model shows that the production cost of biomass is between $0.137 /kg for 100 ha and $0.132 /kg for 500 ha which was less than cost of other studies, while gallon costs between $3.4 - 3.5, more than traditional sources of oil about $1 ,which regarded as a rate of contribution of algal in capturing CO2 from air.

Keywords: Cost Structure Model, Operation Costs(Production Cost), Capital Costs, Algae.

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31867 The Role of Heat Pumps for the Decarbonization of European Regions

Authors: D. M. Mongelli, M. De Carli, L. Carnieletto, F. Busato

Abstract:

This research aims to provide a contribution to the reduction of fossil fuels and the consequent reduction of CO2eq emissions for each European region. Simulations have been carried out to replace fossil fuel fired heating boilers with air-to-water heat pumps, when allowed by favorable environmental conditions (outdoor temperature, water temperature in emission systems, etc.). To estimate the potential coverage of high-temperature heat pumps in European regions, the energy profiles of buildings were considered together with the potential coefficient of performance (COP) of heat pumps operating with flow temperature with variable climatic regulation. The electrification potential for heating buildings was estimated by dividing the 38 European countries examined into 179 territorial units. The yields have been calculated in terms of energy savings and CO2eq reduction.

Keywords: Decarbonization, Space heating, Heat pumps, Energy policies.

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31866 Choosing Search Algorithms in Bayesian Optimization Algorithm

Authors: Hao Wu, Jonathan L. Shapiro

Abstract:

The Bayesian Optimization Algorithm (BOA) is an algorithm based on the estimation of distributions. It uses techniques from modeling data by Bayesian networks to estimating the joint distribution of promising solutions. To obtain the structure of Bayesian network, different search algorithms can be used. The key point that BOA addresses is whether the constructed Bayesian network could generate new and useful solutions (strings), which could lead the algorithm in the right direction to solve the problem. Undoubtedly, this ability is a crucial factor of the efficiency of BOA. Varied search algorithms can be used in BOA, but their performances are different. For choosing better ones, certain suitable method to present their ability difference is needed. In this paper, a greedy search algorithm and a stochastic search algorithm are used in BOA to solve certain optimization problem. A method using Kullback-Leibler (KL) Divergence to reflect their difference is described.

Keywords: Bayesian optimization algorithm, greedy search, KL divergence, stochastic search.

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31865 Normalizing Logarithms of Realized Volatility in an ARFIMA Model

Authors: G. L. C. Yap

Abstract:

Modelling realized volatility with high-frequency returns is popular as it is an unbiased and efficient estimator of return volatility. A computationally simple model is fitting the logarithms of the realized volatilities with a fractionally integrated long-memory Gaussian process. The Gaussianity assumption simplifies the parameter estimation using the Whittle approximation. Nonetheless, this assumption may not be met in the finite samples and there may be a need to normalize the financial series. Based on the empirical indices S&P500 and DAX, this paper examines the performance of the linear volatility model pre-treated with normalization compared to its existing counterpart. The empirical results show that by including normalization as a pre-treatment procedure, the forecast performance outperforms the existing model in terms of statistical and economic evaluations.

Keywords: Long-memory, Gaussian process, Whittle estimator, normalization, volatility, value-at-risk.

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31864 Promoting Electric Vehicles for Sustainable Urban Transport: How to Do It This Time Right

Authors: Reinhard Haas, Amela Ajanovic

Abstract:

In recent years various types of electric vehicles has gained again increasing attention as an environmentally benign technology in transport. Especially for urban areas with high local pollution this Zero-emission technology (at the point of use) is considered to provide proper solutions. Yet, the bad economics and the limited driving ranges are still major barriers for a broader market penetration of battery electric vehicles (BEV) and of fuel cell vehicles (FCV). The major result of our analyses is that the most important precondition for a further dissemination of BEV in urban areas are emission-free zones. This is an instrument which allows the promotion of BEV without providing excessive subsidies. In addition, it is important to note that the full benefits of EV can only be harvested if the electricity used is produced from renewable energy sources. That is to say, it has to be ensured that the use of BEV in urban areas is clearly linked to a green electricity purchase model. And moreover, the introduction of a CO2- emission-based tax system would support this requirement.

Keywords: Electric vehicles, economics, policies, history.

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31863 Refining Waste Spent Hydroprocessing Catalyst and Their Metal Recovery

Authors: Meena Marafi, Mohan S. Rana

Abstract:

Catalysts play an important role in producing valuable fuel products in petroleum refining; but, due to feedstock’s impurities catalyst gets deactivated with carbon and metal deposition. The disposal of spent catalyst falls under the category of hazardous industrial waste that requires strict agreement with environmental regulations. The spent hydroprocessing catalyst contains Mo, V and Ni at high concentrations that have been found to be economically significant for recovery. Metal recovery process includes deoiling, decoking, grinding, dissolving and treatment with complexing leaching agent such as ethylene diamine tetra acetic acid (EDTA). The process conditions have been optimized as a function of time, temperature and EDTA concentration in presence of ultrasonic agitation. The results indicated that optimum condition established through this approach could recover 97%, 94% and 95% of the extracted Mo, V and Ni, respectively, while 95% EDTA was recovered after acid treatment.

Keywords: Spent catalyst, deactivation, hydrotreating, spent catalyst.

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