Search results for: diurnal temperature cycle model

Authors: Enrique Barbieri

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The basic disease-spread model described by three states denoting the susceptible (S), infectious (I), and removed (recovered and deceased) (R) sub-groups of the total population N, or SIR model, has been considered. Heuristic mitigating action profiles of the pharmaceutical and non-pharmaceutical types may be developed in a control design setting for the purpose of reducing the transmission rate or improving the recovery rate parameters in the model. Even though the transmission and recovery rates are not control inputs in the traditional sense, a linear observer and feedback controller can be tuned to generate an asymptotic estimate of the transmission rate for a linearized, discrete-time version of the SIR model. Then, a set of mitigating actions is suggested to steer the basic reproduction number toward unity, in which case the disease does not spread, and the infected population state does not suffer from multiple waves. The special case of piecewise constant transmission rate is described and applied to a seventh-order SEIQRDP model, which segments the population into four additional states. The offline simulations in discrete time may be used to produce heuristic policies implemented by public health and government organizations.

Keywords: control of SIR, observer, SEIQRDP, disease spread

Procedia PDF Downloads 92

Authors: Anastasis D. Petrou

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Innovation and strategy discussions do highlight open innovation as a new paradigm in business. Yet, a number of stumbling blocks in the form of closed innovation principles weaved into the fabric of a traditional business model stand in the way of the new paradigm’s momentum to increase value in various business contexts. The paper argues that businesses considering an engagement with the open innovation paradigm would need to take steps to improve their multiplicative, absorptive and relational capabilities, respectively. The needed improvements would amount to a business model evolutionary transformation and eventually bring about a paradigm overhaul in business. The transformation is worth staging over time to ensure that open innovation is developed across interconnected and partnered areas of strategic importance. This article develops an open innovation strategy (OIS) capabilities model, and employs examples from different industries to briefly discuss OIS’s potential to augment business value in a number of suggested areas for future research.

Keywords: close innovation, open innovation paradigm, open innovation strategy (OIS) paradigm, OIS capabilities model, multiplicative capability, absorptive capability, relational capability

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Authors: Craig Jantzen, Tim Abram, Dirk Engelberg, Hugues Lambert, Daniel Cooper

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Molten salts are of high interest for use as coolants in nuclear reactors due to favourable high temperature and thermodynamic properties. The corrosive behaviour of molten salts however pose a materials integrity challenge. Three Ni / Ni-Fe based and two Mo based alloys have been exposed to molten eutectics (LiCl-KCl at 59.5:40.5 mol% and KCl-MgCl2 at 68:32 mol%) at 600°C and 800°C for durations up to 500hrs. Corrosion was observed to preferentially attack alloy constituents in order of their reactivity, with chromium the most vulnerable and depleted element. Alloy weight-loss per unit area was calculated to give linear corrosion rates, discounting any initial rapid corrosion of impurities. Further analysis was carried out using ICP-MS, SEM and EDX techniques to give a more detailed view of the corrosion mechanisms.

Keywords: molten salt, salt, corrosion, high temperature, licl, KCL, MgCl, molybdenum, nickel, superalloys

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Authors: V. Samulionis, J. Banys, A. Sánchez-Ferrer

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Inorganic nanoparticles are used for fabrication of various composites based on polymer materials because they exhibit a good homogeneity and solubility of the composite material. Multifunctional materials based on composites of a polymer containing inorganic nanotubes are expected to have a great impact on industrial applications in the future. An emerging family of such composites are polyurea elastomers with inorganic MoS2 nanotubes or MoSI nanowires. Polyurea elastomers are a new kind of materials with higher performance than polyurethanes. The improvement of mechanical, chemical and thermal properties is due to the presence of hydrogen bonds between the urea motives which can be erased at high temperature softening the elastomeric network. Such materials are the combination of amorphous polymers above glass transition and crosslinkers which keep the chains into a single macromolecule. Polyurea exhibits a phase separated structure with rigid urea domains (hard domains) embedded in a matrix of flexible polymer chains (soft domains). The elastic properties of polyurea can be tuned over a broad range by varying the molecular weight of the components, the relative amount of hard and soft domains, and concentration of nanoparticles. Ultrasonic methods as non-destructive techniques can be used for elastomer composites characterization. In this manner, we have studied the temperature dependencies of the longitudinal ultrasonic velocity and ultrasonic attenuation of these new polyurea elastomers and composites with inorganic nanoparticles. It was shown that in these polyurea elastomers large ultrasonic attenuation peak and corresponding velocity dispersion exists at 10 MHz frequency below room temperature and this behaviour is related to glass transition Tg of the soft segments in the polymer matrix. The relaxation parameters and Tg depend on the segmental molecular weight of the polymer chains between crosslinking points, the nature of the crosslinkers in the network and content of MoS2 nanotubes or MoSI nanowires. The increase of ultrasonic velocity in composites modified by nanoparticles has been observed, showing the reinforcement of the elastomer. In semicrystalline polyurea elastomer matrices, above glass transition, the first order phase transition from quasi-crystalline to the amorphous state has been observed. In this case, the sharp ultrasonic velocity and attenuation anomalies were observed near the transition temperature TC. Ultrasonic attenuation maximum related to glass transition was reduced in quasicrystalline polyureas indicating less influence of soft domains below TC. The first order phase transition in semicrystalline polyurea elastomer samples has large temperature hysteresis (> 10 K). The impact of inorganic MoS2 nanotubes resulted in the decrease of the first order phase transition temperature in semicrystalline composites.

Keywords: inorganic nanotubes, polyurea elastomer composites, ultrasonic velocity, ultrasonic attenuation

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Authors: Ahmet Yonetken, Ayhan Erol

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Intermetallic materials advanced technology materials that have outstanding mechanical and physical properties for high temperature applications. Especially creep resistance, low density and high hardness properties stand out in such intermetallics. The microstructure, mechanical properties of %80Cr-%10Ti and %10WC powders were investigated using specimens produced by tube furnace sintering at 1000-1400°C temperature. A composite consisting of ternary additions, a metallic phase, Ti,Cr and WC have been prepared under Ar shroud and then tube furnace sintered. XRD, SEM (Scanning Electron Microscope), were investigated to characterize the properties of the specimens. Experimental results carried out for composition %80Cr-%10Ti and %10WC at 1400°C suggest that the best properties as 292HV and 5,34g/cm3 density were obtained at 1400°C.

Keywords: ceramic-metal, composites, powder metallurgy, sintering

Procedia PDF Downloads 452

Authors: Xian Li, Qing-Guo Wang, Jiangshuai Huang, Jidong Liu, Ming Yu, Tan Kok Poh

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In power industry, accurate electricity demand forecasting for a certain leading time is important for system operation and control, etc. In this paper, we investigate the modeling and forecasting of Singapore’s electricity demand. Several standard models, such as HWT exponential smoothing model, the ARMA model and the ANNs model have been proposed based on historical demand data. We applied them to Singapore electricity market and proposed three refinements based on simulation to improve the modeling accuracy. Compared with existing models, our refined model can produce better forecasting accuracy. It is demonstrated in the simulation that by adding forecasting error into the forecasting equation, the modeling accuracy could be improved greatly.

Keywords: power industry, electricity demand, modeling, forecasting

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Authors: B. Van Kessel, P. T. Kockelkorn, T. R. Speelman, T. C. Wierikx, C. Mai Van, T. A. Bogaard

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Saltwater intrusion is a common problem in estuaries around the world, as it could hinder the freshwater supply of coastal zones. This problem is likely to grow due to climate change and sea-level rise. The influence of these factors on the saltwater intrusion was investigated for the Cai River in the Khanh Hoa province in Vietnam. In addition, the Cai River has high seasonal fluctuations in discharge, leading to increased saltwater intrusion during the dry season. Sea level rise, river discharge changes, river mouth widening and a proposed saltwater intrusion prevention dam can have influences on the saltwater intrusion but have not been quantified for the Cai River estuary. This research used both an analytical and numerical model to investigate the effect of the aforementioned factors. The analytical model was based on a model proposed by Savenije and was calibrated using limited in situ data. The numerical model was a 3D hydrodynamic model made using the Delft3D4 software. The analytical model and numerical model agreed with in situ data, mostly for tidally average data. Both models indicated a roughly similar dependence on discharge, also agreeing that this parameter had the most severe influence on the modeled saltwater intrusion. Especially for discharges below 10 m/s3, the saltwater was predicted to reach further than 10 km. In the models, both sea-level rise and river widening mainly resulted in salinity increments up to 3 kg/m3 in the middle part of the river. The predicted sea-level rise in 2070 was simulated to lead to an increase of 0.5 km in saltwater intrusion length. Furthermore, the effect of the saltwater intrusion dam seemed significant in the model used, but only for the highest position of the gate.

Keywords: Cai River, hydraulic models, river discharge, saltwater intrusion, tidal barriers

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Authors: Radovan Cobanovic, Milica Rankov Sicar

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Biodiesel refers to a vegetable oil - or animal fat-based diesel fuel consisting of long-chain alkyl (methyl, ethyl, or propyl) esters. It is derived by alcoholysis of triacylglycerols (triglycerides) from various lipid based materials that can be traditionally categorized into the following main groups: vegetable oils, animal fats, waste and algal oils. The goal of this study was to evaluate microbiological stability of biodiesel samples since it has been made from vegetable oil or animal fat which was stored on room temperature. For the purposes of this study, analyzes were conducted on six samples of biodiesel first at zero sample at the reception day than fifth, thirtieth, sixtieth, ninetieth and one hundred twentieth day from the day of reception. During this period, biodiesel samples were subjected to microbiological analyses (Salmonella spp., Listeria monocytogenes, Enterobacteriaceae and total plate count). All analyses were tested according to ISO methodology: Salmonella spp ISO 6579, Listeria monocytogenes ISO 11290-2, Enterobacteriaceae ISO 21528-1, total plate count ISO 4833-1. The results obtained after the analyses which were done according to the plan during the 120 days indicate that are no changes of products concerning microbiological analyses. Salmonella spp., Listeria monocytogenes, Enterobacteriaceae were not detected and results for total plate count showed values < 10 cfu/g for all six samples. On the basis of this monitoring under defined storage conditions at room temperatures, the results showed that biodiesel is very stable as far as microbiological analysis were concerned.

Keywords: biodiesel, microbiology, room temperature, stability

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Authors: Omar Alzeley, Sergey Utev

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Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.

Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series

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Authors: Lely A. Luengas, Pedro R. Vizcaya, Giovanni Sánchez

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In this paper, a methodology is presented to obtain the Static Alignment Model for any transtibial amputee person. The proposed methodology starts from experimental data collected on the Hospital Militar Central, Bogotá, Colombia. The effects of transtibial prosthesis malalignment on amputees were measured in terms of joint angles, center of pressure (COP) and weight distribution. Some statistical tools are used to obtain the model parameters. Mathematical predictive models of prosthetic alignment were created. The proposed models are validated in amputees and finding promising results for the prosthesis Static Alignment. Static alignment process is unique to each subject; nevertheless the proposed methodology can be used in each transtibial amputee.

Keywords: information theory, prediction model, prosthetic alignment, transtibial prosthesis

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Authors: Christopher Deekia Nwimae, Nigel Simms, Liyun Lao

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Erosion in pipe bends caused by particles is a major obstacle in the oil and gas fields and might cause the breakdown of production equipment. This work studied the effects imposed by flow velocity and impact of solid particles diameter in an elbow; erosion rate was verified with experimental data using the computational fluid dynamics (CFD) approach. Two-way coupled Euler-Lagrange and discrete phase model was employed to calculate the air/solid particle flow in an elbow. One erosion model and three-particle rebound models were used to predict the erosion rate on the 90° elbows. The generic erosion model was used in the CFD-based erosion model, and after comparing it with experimental data, results showed agreement with the CFD-based predictions as observed.

Keywords: erosion, prediction, elbow, computational fluid dynamics

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Authors: Yoshimoto Kurihara, Tad Gonsalves

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Currently, in the field of object posture estimation, there is research on estimating the position and angle of an object by storing a 3D model of the object to be estimated in advance in a computer and matching it with the model. However, in this research, we have succeeded in creating a module that is much simpler, smaller in scale, and faster in operation. Our 6D pose estimation model consists of two different networks – a classification network and a regression network. From a single RGB image, the trained model estimates the class of the object in the image, the coordinates of the object, and its rotation angle in 3D space. In addition, we compared the estimation accuracy of each camera position, i.e., the angle from which the object was captured. The highest accuracy was recorded when the camera position was 75°, the accuracy of the classification was about 87.3%, and that of regression was about 98.9%.

Keywords: 6D posture estimation, image recognition, deep learning, AlexNet

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Authors: Aneesh Babu, S. P. Anusha

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A dynamic signal control system combines traditional traffic lights with an array of sensors to intelligently control vehicle and pedestrian traffic. The present study focus on evaluating the performance of dynamic signal control systems for mixed traffic conditions. Data collected from four different approaches to a typical four-legged signalized intersection at Trivandrum city in the Kerala state of India is used for the study. Performance of three other dynamic signal control methods, namely (i) Non-sequential method (ii) Webster design for consecutive signal cycle using flow as input, and (iii) dynamic signal control using RFID delay as input, were evaluated. The evaluation of the dynamic signal control systems was carried out using a calibrated VISSIM microsimulation model. Python programming was used to integrate the dynamic signal control algorithm through the COM interface in VISSIM. The intersection delay obtained from different dynamic signal control methods was compared with the delay obtained from fixed signal control. Based on the study results, it was observed that the intersection delay was reduced significantly by using dynamic signal control methods. The dynamic signal control method using delay from RFID sensors resulted in a higher percentage reduction in delay and hence is a suitable choice for implementation under mixed traffic conditions. The developed dynamic signal control strategies can be implemented in ITS applications under mixed traffic conditions.

Keywords: dynamic signal control, intersection delay, mixed traffic conditions, RFID sensors

Procedia PDF Downloads 87

Authors: Mohammad Y. Badiee, Saeed Golestani, Mir Saman Pishvaee

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In recent years consumers and governments have been pushing companies to design their activities in such a way as to reduce negative environmental impacts by producing renewable product or threat free disposal policy more and more. It is therefore important to focus more accurate to the optimization of various aspect of total supply chain. Modeling a supply chain can be a challenging process due to the fact that there are a large number of factors that need to be considered in the model. The use of multi-objective optimization can lead to overcome those problems since more information is used when designing the model. Uncertainty is inevitable in real world. Considering uncertainty on parameters in addition to use multi-objectives are ways to give more flexibility to the decision making process since the process can take into account much more constraints and requirements. In this paper we demonstrate a stochastic scenario based robust model to cope with uncertainty in a closed-loop multi-objective supply chain. By applying the proposed model in a real world case, the power of proposed model in handling data uncertainty is shown.

Keywords: supply chain management, closed-loop supply chain, multi-objective optimization, goal programming, uncertainty, robust optimization

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Authors: Selin Guney, Andres Riquelme

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The traditional bio-economic method for fisheries modeling uses some estimate of the growth parameters and the system carrying capacity from a biological model for the population dynamics (usually a logistic population growth model) which is then analyzed as a traditional production function. The stock dynamic is transformed into a revenue function and then compared with the extraction costs to estimate the maximum economic yield. In this paper, the logistic population growth model for the population is combined with a forecast of the abundance and location of the stock by using a generalized additive model approach. The paper focuses on the Chilean hake population. This method allows for the incorporation of climatic variables and the interaction with other marine species, which in turn will increase the reliability of the estimates and generate better extraction paths for different conservation objectives, such as the maximum biological yield or the maximum economic yield.

Keywords: bio-economic, fisheries, GAM, production

Procedia PDF Downloads 235

Authors: Shyh-Ming Chern, H. Y. Cheng

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Biomass is renewable and sustainable. As an energy source, it will not release extra carbon dioxide into the atmosphere. Hence, tremendous efforts have been made to develop technologies capable of transforming biomass into suitable forms of bio-fuel. One of the viable technologies is gasifying biomass in supercritical water (SCW), a green medium for reactions. While previous studies overwhelmingly selected glucose as a model compound for biomass, the present study adopted fructose for the sake of comparison. The gasification of fructose in SCW was investigated experimentally to evaluate the applicability of supercritical water processes to biomass gasification. Experiments were conducted with an autoclave reactor. Gaseous product mainly consists of H2, CO, CO2, CH4 and C2H6. The effect of two major operating parameters, the reaction temperature (673-873 K) and the dosage of oxidizing agent (0-0.5 stoichiometric oxygen), on the product gas composition, yield and heating value was also examined, with the reaction pressure fixed at 25 MPa.

Keywords: biomass, fructose, gasification, supercritical water

Procedia PDF Downloads 338

Authors: S. Patel, T. Mitra, R. Dubey, J. Keller

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In the present investigations, an attempt has been made to study the charge storage mechanism and mechanism for the flow of transient charging and discharging current in an amorphous polymer (Polysulfone) (PSF) and a semi-crystalline polar Polyvinylidene fluoride (PVDF) blends in ratio PSF: PVDF: 80:20;85:15;90:10 and 95:05 at various poling temperatures (i.e. 60, 75, 90 and 1150C) and with field strength (100, 150, 200 and 250kVcm⁻¹). Thermally stimulated depolarizing current TSDC thermograms for (Polysulfone (PSF) and Polyvinylidene fluoride (PVDF) Blends sample have been obtained under different polarizing conditions. Peaks are found at high-temperature side. The variation of structure on blending and poling condition affects the magnitude of TSDC. The activation energy values have been calculated using the initial rise method of Garlick and Gibson. The transient current with the similar polarizing condition has been investigated over a period of 3X10³ sec. The observed characteristics obey Curie-Von Schweidler law in the studied temperature range. The charging current versus polarizing temperature curves at a constant time, i.e., isochronal current characteristics were studied and the activation energies were calculated. The activation energy in transient thermograms calculated by different methods is in good agreement with the values obtained from TSDC studies.

Keywords: activation energy, polysulfone (PSF), polyvinylidenefluoride (PVDF), thermally stimulated depolarizing current (TSDC)

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Authors: S. Sonkham, U. Pinsopon, W. Chatlatanagulchai

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This paper presents a method of sliding mode control (SMC) designing and developing for the servo system in a dual-stage actuator (DSA) hard disk drive. Mathematical modelling of hard disk drive actuators is obtained, extracted from measuring frequency response of the voice-coil motor (VCM) and PZT micro-actuator separately. Matlab software tools are used for mathematical model estimation and also for controller design and simulation. A model-reference approach for tracking requirement is selected as a proposed technique. The simulation results show that performance of a model-reference SMC controller design in DSA servo control can be satisfied in the tracking error, as well as keeping the positioning of the head within the boundary of +/-5% of track width under the presence of internal and external disturbance. The overall results of model-reference SMC design in DSA are met per requirement specifications and significant reduction in %off track is found when compared to the single-state actuator (SSA).

Keywords: hard disk drive, dual-stage actuator, track following, hdd servo control, sliding mode control, model-reference, tracking control

Procedia PDF Downloads 349

Authors: Shahrokh Barati

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In this paper, we introduced AIDS disease at first, then proposed dynamic model illustrate its progress, after expression of a short history of nonlinear modeling by polynomial phasing systems, we considered the stability conditions of the systems, which contained a huge amount of researches in order to modeling and control of AIDS in dynamic nonlinear form, in this approach using a frame work of control any polynomial phasing modeling system which have been generalized by part of phasing model of T-S, in order to control the system in better way, the stability conditions were achieved based on polynomial functions, then we focused to design the appropriate controller, firstly we considered the equilibrium points of system and their conditions and in order to examine changes in the parameters, we presented polynomial phase model that was the generalized approach rather than previous Takagi Sugeno models, then with using case we evaluated the equations in both open loop and close loop and with helping the controlling feedback, the close loop equations of system were calculated, to simulate nonlinear model of AIDS disease, we used polynomial phasing controller output that was capable to make the parameters of a nonlinear system to follow a sustainable reference model properly.

Keywords: polynomial fuzzy, AIDS, nonlinear AIDS model, fuzzy control systems

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Authors: Guru Prakash, Revanth Dugalam

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A road’s condition often deteriorates due to harsh loading such as overload due to trucks, and severe environmental conditions such as heavy rain, snow load, and cyclic loading. In absence of proper maintenance planning, this results in potholes, wide cracks, bumps, and increased roughness of roads. In this paper, a data-driven model will be developed to detect these damages using vibration and image signals. The key idea of the proposed methodology is that the road anomaly manifests in these signals, which can be detected by training a machine learning algorithm. The use of various machine learning techniques such as the support vector machine and Radom Forest method will be investigated. The proposed model will first be trained and tested with artificially simulated data, and the model architecture will be finalized by comparing the accuracies of various models. Once a model is fixed, the field study will be performed, and data will be collected. The field data will be used to validate the proposed model and to predict the future road’s health condition. The proposed will help to automate the road condition monitoring process, repair cost estimation, and maintenance planning process.

Keywords: SVM, data-driven, road health monitoring, pot-hole

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Authors: Babek Erdebilli

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The aim of this study is to develop and describe a new methodology for the Multi-Criteria Decision-Making (MCDM) problem using IFE (Elimination Et Choix Traduisant La Realite (ELECTRE) model. The proposed models enable Decision-Makers (DMs) on the assessment and use Intuitionistic Fuzzy Numbers (IFN). A numerical example is provided to demonstrate and clarify the proposed analysis procedure. Also, an empirical experiment is conducted to validation the effectiveness.

Keywords: multi-criteria decision-making, IFE, DM’s, fuzzy electre model

Procedia PDF Downloads 630

Authors: W. H. Wan Zakiyatussariroh, A. A. Nasuhar, W. Y. Wan Fairos, Z. A. Nazatul Shahreen

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Forecasting dengue incidence in a population can provide useful information to facilitate the planning of the public health intervention. Many studies on dengue cases in Malaysia were conducted but are limited in modeling the outbreak and forecasting incidence. This article attempts to propose the most appropriate time series model to explain the behavior of dengue incidence in Malaysia for the purpose of forecasting future dengue outbreaks. Several seasonal auto-regressive integrated moving average (SARIMA) models were developed to model Malaysia’s number of dengue incidence on weekly data collected from January 2001 to December 2011. SARIMA (2,1,1)(1,1,1)52 model was found to be the most suitable model for Malaysia’s dengue incidence with the least value of Akaike information criteria (AIC) and Bayesian information criteria (BIC) for in-sample fitting. The models further evaluate out-sample forecast accuracy using four different accuracy measures. The results indicate that SARIMA (2,1,1)(1,1,1)52 performed well for both in-sample fitting and out-sample evaluation.

Keywords: time series modeling, Box-Jenkins, SARIMA, forecasting

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Authors: Ranojoy Dutta

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HVAC equipment capacity has a direct impact on occupant comfort and energy consumption of a building. Glazing gains, especially in buildings with high window area, can be a significant contributor to the total peak load on the HVAC system, leading to over-sized systems that mostly operate at poor part load efficiency. In addition, radiant temperature, which largely drives occupant comfort in glazed perimeter zones, is often not effectively controlled despite the HVAC being designed to meet the air temperature set-point. This is due to short wave solar radiation transmitted through windows, that is not sensed by the thermostat until much later when the thermal mass in the room releases the absorbed solar heat to the indoor air. The implication of this phenomenon is increased cooling energy despite poor occupant comfort. EC glazing can significantly eliminate direct solar transmission through windows, reducing both the space cooling loads for the building and improving comfort for occupants near glazing. This paper will review the exact mechanism of how EC glazing would reduce the peak load under design day conditions, leading to reduced cooling capacity vs regular high-performance glazing. Since glazing heat transfer only affects the sensible load, system sizing will be evaluated both with and without the availability of a DOAS to isolate the downsizing potential of the primary cooling equipment when outdoor air is conditioned separately. Given the dynamic nature of glazing gains due to the sun’s movement, effective peak load mitigation with EC requires an automated control system that can predict solar movement and radiation levels so that the right tint state with the appropriate SHGC is utilized at any given time for a given façade orientation. Such an automated EC product will be evaluated for a prototype commercial office model situated in four distinct climate zones.

Keywords: electrochromic glazing, peak sizing, thermal comfort, glazing load

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Authors: Gabriele Iannotta

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This paper investigates credit cycles by means of an experiment based on a Kiyotaki & Moore (1997) model with heterogeneous expectations. The aim is to examine how a credit squeeze caused by high lender-level risk perceptions affects the real prices of a collateralised asset, with a special focus on the macroeconomic implications of rising price volatility in terms of total welfare and the number of bankruptcies that occur. To do that, a learning-to-forecast experiment (LtFE) has been run where participants are asked to predict the future price of land and then rewarded based on the accuracy of their forecasts. The setting includes one lender and five borrowers in each of the twelve sessions split between six control groups (G1) and six treatment groups (G2). The only difference is that while in G1 the lender always satisfies borrowers’ loan demand (bankruptcies permitting), in G2 he/she closes the entire credit market in case three or more bankruptcies occur in the previous round. Experimental results show that negative risk-driven supply shocks amplify the volatility of collateral prices. This uncertainty worsens the agents’ ability to predict the future value of land and, as a consequence, the number of defaults increases and the total welfare deteriorates.

Keywords: Behavioural Macroeconomics, Credit Cycle, Experimental Economics, Heterogeneous Expectations, Learning-to-Forecast Experiment

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Authors: Betül Özgenç, Soner Kuşlu, Sabri Çolak, Turan Çalban

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The aim of this study was investigate the leaching kinetics of ulexite in disodium hydrogen phosphate solutions in a mechanical agitation system. Reaction temperature, concentration of disodium hydrogen phosphate solutions, stirring speed, solid/liquid ratio and ulexite particle size were selected as parameters. The experimental results were successfully correlated by linear regression using Statistica program. Dissolution curves were evaluated shrinking core models for solid-fluid systems. It was observed that increase in the reaction temperature and decrease in the solid/liquid ratio causes an increase the dissolution rate of ulexite. The activation energy was found to be 63.4 kJ/mol. The leaching of ulexite was controlled by chemical reaction.

Keywords: ulexite, disodium hydrogen phosphate, leaching kinetics

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Authors: А. I. Dovgyalo, S. O. Nekrasova, D. V. Sarmin, A. A. Shimanov, D. A. Uglanov

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Usually liquefied natural gas (LNG) gasification is performed due to atmospheric heat. In order to produce a liquefied gas a sufficient amount of energy is to be consumed (about 1 kW∙h for 1 kg of LNG). This study offers a number of solutions, allowing using a cold energy of LNG. In this paper it is evaluated the application turbines installed behind the evaporator in LNG complex due to its work additional energy can be obtained and then converted into electricity. At the LNG consumption of G=1000kg/h the expansion work capacity of about 10 kW can be reached. Herewith-open Rankine cycle is realized, where a low capacity cryo-pump (about 500W) performs its normal function, providing the cycle pressure. Additionally discussed an application of Stirling engine within the LNG complex also gives a possibility to realize cold energy. Considering the fact, that efficiency coefficient of Stirling engine reaches 50 %, LNG consumption of G=1000 kg/h may result in getting a capacity of about 142 kW of such a thermal machine. The capacity of the pump, required to compensate pressure losses when LNG passes through the hydraulic channel, will make 500 W. Apart from the above-mentioned converters, it can be proposed to use thermoelectric generating packages (TGP), which are widely used now. At present, the modern thermoelectric generator line provides availability of electric capacity with coefficient of efficiency up to 15%. In the proposed complex, it is suggested to install the thermoelectric generator on the evaporator surface is such a way, that the cold end is contacted with the evaporator’s surface, and the hot one – with the atmosphere. At the LNG consumption of G=1000 kgг/h and specified coefficient of efficiency the capacity of the heat flow Qh will make about 32 kW. The derivable net electric power will be P=4,2 kW, and the number of packages will amount to about 104 pieces. The carried out calculations demonstrate the research perceptiveness in this field of propulsion plant development, as well as allow realizing the energy saving potential with the use of liquefied natural gas and other cryogenics technologies.

Keywords: cold energy, gasification, liquefied natural gas, electricity

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Authors: Abdenour Achour, Kan Chen, Mike Reece, Zhaorong Huang

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Here we report the synthesis of pure and cost effective of BiCuSeO by a flux method in air, and the enhancement of the thermoelectric performance by Cs doping. The comparison between our synthesis and the usual vacuum furnace method has been studied for the pristine oxyselenides BiCuSeO. We report for very high Seebeck coefficients up to 516 μV K⁻¹ at room temperature with the electrical conductivity of 5.20 S cm⁻¹ which lead to a high power factor of 140 µWm⁻¹K⁻². We also report at the high temperatures the lowest thermal conductivity value of 0.42 µWm⁻¹K⁻¹. Upon doping with Cs, enhanced electrical conductivity coupled with a moderate Seebeck coefficient lead to a power factor of 338 µWm⁻¹K⁻² at 682 K. Moreover, it shows a very low thermal conductivity in the temperature range of 300 to 682 K (0.75 to 0.35 Wm⁻¹K⁻¹). By optimizing the power factor and reducing the thermal conductivity, this results in a high ZT of ~ 0.66 at 682 K for Bi0.995Cs0.005CuSeO.

Keywords: BiCuSeO, Cs doping, thermoelectric, oxyselenide

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Authors: Adedapo Jepson Olumide, Kurowska Ewa, K. Schoeneich, Ikpokonte A. Enoch

Abstract:

In this paper, subsurface temperature measured from continuous temperature logs were used to determine the geothermal gradient of NigerDelta sedimentary basin. The measured temperatures were corrected to the true subsurface temperatures by applying the American Association of Petroleum Resources (AAPG) correction factor, borehole temperature correction factor with La Max’s correction factor and Zeta Utilities borehole correction factor. Geothermal gradient in this basin ranges from 1.20C to 7.560C/100m. Six geothermal anomalies centres were observed at depth in the southern parts of the Abakaliki anticlinorium around Onitsha, Ihiala, Umuaha area and named A1 to A6 while two more centre appeared at depth of 3500m and 4000m named A7 and A8 respectively. Anomaly A1 describes the southern end of the Abakaliki anticlinorium and extends southwards, anomaly A2 to A5 were found associated with a NW-SE structural alignment of the Calabar hinge line with structures describing the edge of the Niger Delta basin with the basement block of the Oban massif. Anomaly A6 locates in the south-eastern part of the basin offshore while A7 and A8 are located in the south western part of the basin offshore. At the average exploratory depth of 3500m, the geothermal gradient values for these anomalies A1, A2, A3, A4, A5, A6, A7, and A8 are 6.50C/100m, 1.750C/100m, 7.50C/100m, 1.250C/100m, 6.50C/100m, 5.50C/100m, 60C/100m, and 2.250C/100m respectively. Anomaly A8 area may yield higher thermal value at greater depth than 3500m. These results show that anomalies areas of A1, A3, A5, A6 and A7 are potentially prospective and explorable for geothermal energy using abandoned oil wells in the study area. Anomalies A1, A3.A5, A6 occur at areas where drilled boreholes were not exploitable for oil and gas but for the remaining areas where wells are so exploitable there appears no geothermal anomaly. Geothermal energy is environmentally friendly, clean and reversible.

Keywords: temperature logs, geothermal gradient anomalies, alternative energy, Niger delta basin

Procedia PDF Downloads 264

Authors: Aicha Koulou, Norelislam El Hami, Nabil Hmina

Abstract:

This paper aims at presenting basic concepts and principles in order to develop a methodology to set up sustainable interoperability within collaborative networks. Definitions and clarifications related to the concept of interoperability and sustainability are given. Interoperability levels and cycle that are components supporting the methodology are presented; a structured approach and related phases are proposed.

Keywords: Interoperability, sustainability, collaborative networks, sustainable Interoperability

Procedia PDF Downloads 131

Authors: Andrés I. Ávila, Patricia Aros, César San Martín, Elizabeth Kehr, Yovana Leal

Abstract:

Planning models for fresh products is a very useful tool for improving the net profits. To get an efficient supply chain model, several functions should be considered to get a complete simulation of several operational units. We consider a linear programming model to help farmers to decide if it is convenient to choose what area should be planted for three kinds of export fruits considering their future investment. We consider area, investment, water, productivity minimal unit, and harvest restrictions to develop a monthly based model to compute the average income in five years. Also, conditions on the field as area, water availability, and initial investment are required. Using the Chilean costs and dollar-peso exchange rate, we can simulate several scenarios to understand the possible risks associated to this market. Also, this tool help to support decisions for government and individual farmers.

Keywords: mixed integer problem, fresh fruit production, support decision model, agricultural and biosystems engineering

Procedia PDF Downloads 422