Search results for: computational finance

Authors: Hussaini Tunde Subairu

Abstract:

Small and Medium Enterprises (SMEs) sectors serve as catalyst for employment generation, national growth, poverty reduction and economic development in developing and developed countries. However, in Nigeria despite copious and plethora of government policies and stimulus schemes directed at SMEs, the sector is still characterized by high rate of failure and discontinuities. This study therefore investigated owners/managers profile, firms characteristics and external factors as possible determinants of SMEs growth from selected SMEs in Kwara State. Primary data were sourced from 200 SMEs respondents registered with the National Association of Small and Medium Enterprises (NASMES) in Kwara State Central Senatorial District. Multiple Regressions Analysis (MRA) was used to analyze the relationship between dependent and independent variables, and pair wise correlation was employed to examine the relationship among independent variables. The Analysis of Variable (ANOVA) was employed to indicate the overall significant of the model The findings revealed that Analysis of variance (ANOVA) put the value of F-statistics at 420.45 and p-value at 0.000 was significant. The values of R2 and Adjusted R2 of 0.9643 and 0.9620 respectively suggested that 96 percent of variations in employment growth were explained by the explanatory variables. The level of technical and managerial education has t- value of 24.14 and p-value of 0.001, length of managers/owners experience in similar trade with t- value of 21.37 and p-value of 0.001, age of managers/owners with t- value of 42.98 and p-value of 0.001, firm age with t- value of 25.91 and p-value of 0.001, numbers of firms in a cluster with t- value of 7.20 and p-value of 0.001, access to formal finance with t-value of 5.56 and p-value of 0.001, firm technology innovation with t- value of 25.32 and p-value of 0.01, institutional support with t- value of 18.89 and p-value of 0.01, globalization with t- value of 9.78 and p-value of 0.01, and infrastructure with t-value of 10.75 and p-value of 0.01. The result also indicated that initial size has t-value of -1.71 and p-value of 0.090 which is consistent with Gibrat’s Law. The study concluded that owners/managers profile, firm specific characteristics and external factors substantially influenced employment growths of SMEs in the study area. Therefore, policy implication should enhance human capital development of SMEs owners/managers, and strengthen fiscal policy thrust through imposition on tariff regime to minimize effect of globalization. Governments at all level must support SMEs growth radically and enhance institutional support for SMEs growth and radically and significantly upgrading key infrastructure as rail/roads, rail, telecommunications, water and power.

Keywords: external factors, firm specific characteristics, owners / manager profile, small and medium enterprises

Procedia PDF Downloads 229

Authors: Mouna Hamed, Ammar B. Brahim

Abstract:

The objective of this work was to develop a theoretical model to study the dynamic thermal behavior of a flat plate solar collector integrated with a phase change material (PCM). The PCM acted as a heat source for the solar system during low intensity solar radiation and night. The energy balance equations for the various components of the collector as well as for the PCM were formulated and numerically solved using MATLAB computational program. The effect of natural convection on heat during the melting process was taken into account by using an effective thermal conductivity. The model was used to investigate the effect of inlet water temperature, water mass flow rate, and PCM thickness on the outlet water temperature and the melt fraction during charging and discharging modes. A comparison with a collector without PCM was made. Results showed that charging and discharging processes of PCM have six stages. The adding of PCM caused a decrease in temperature during charge and an increase during discharge. The rise was most enhanced for higher inlet water temperature, PCM thickness and for lower mass flow rate. Analysis indicated that the complete melting time was shorter than the solidification time due to the high heat transfer coefficient during melting. The increases in PCM height and mass flow rate were not linear with the melting and solidification times.

Keywords: thermal energy storage, phase change material, melting, solidification

Procedia PDF Downloads 338

Authors: Selfa Johnson Zwalnan, Nanchen Nimyel Caleb, Gideon Duvuna Ayuba

Abstract:

Air conditioning accounts for a significant share of the overall energy consumed in residential buildings. Solar thermal gains in buildings account for a significant component of the air conditioning load in buildings. This study compares the solar thermal gain and air conditioning load of a proposed building design with a typical conventional building in the climatic conditions of Jos, Nigeria, using a combined experimental and computational method using TRNSYS software. According to the findings of this study, the proposed design building's annual average solar thermal gains are lower compared to the reference building's average solar heat gains. The study case building's decreased solar heat gain is mostly attributable to the somewhat lower temperature of the building zones because of the greater building volume and lower fenestration ratio (ratio of external opening area to the area of the external walls). This result shows that the innovative building design adjusts to the local climate better than the standard conventional construction in Jos to maintain a suitable temperature within the building. This finding means that the air-conditioning electrical energy consumption per volume of the proposed building design will be lower than that of a conventional building design.

Keywords: building simulation, solar gain, comfort temperature, temperature, carbon foot print

Procedia PDF Downloads 84

Authors: Manoj Malviya, Shubham Shinde

Abstract:

The present study focuses on the determination of torsional stiffness of a space frame chassis and comparison of elements used in the Finite Element Analysis of frame. The study also discusses various concepts and design aspects of a space frame chassis with the emphasis on their applicability in BAJA SAE vehicles. Torsional stiffness is a very important factor that determines the chassis strength, vehicle control, and handling. Therefore, it is very important to determine the torsional stiffness of the vehicle before designing an optimum chassis so that it should not fail during extreme conditions. This study determines the torsional stiffness of frame with respect to suspension shocks, roll-stiffness and anti-roll bar rates. A spring model is developed to study the effects of suspension parameters. The engine greatly contributes to torsional stiffness, and therefore, its effects on torsional stiffness need to be considered. Deflections in the tire have not been considered in the present study. The proper element shape should be selected to analyze the effects of various loadings on chassis while implementing finite element methods. The study compares the accuracy of results and computational time for different element types. Shape functions of these elements are also discussed. Modelling methodology is discussed for the multibody analysis of chassis integrated with suspension arms and engine. Proper boundary conditions are presented so as to replicate the real life conditions.

Keywords: space frame chassis, torsional stiffness, multi-body analysis of chassis, element selection

Procedia PDF Downloads 342

Authors: Heather Fulford, Melanie Liddell

Abstract:

The recruitment and retention of high quality employees can prove to be challenging for social enterprises, particularly in some of the core business support functions such as marketing, communications, IT and finance. This holds true for social enterprises in urban contexts, where roles with more attractive remuneration in these business functions can often be found quite readily in the private sector. For social enterprises situated in rural locations, the challenges of staff recruitment and retention are even more acute. Such challenges can lead to a skills deficit in rural social enterprises, which can, at best, hinder their growth potential, and worse, jeopardise their chances of survival. This in turn, can have a negative impact on the sustainability and resilience of the surrounding rural community in which the social enterprise is located. The purpose of this paper is to report on aspects of a collaborative initiative established to stimulate innovation and business growth in remote rural businesses in Scotland. Launched in 2010, this initiative was designed to attract young students and graduates from the region to stay in the region upon completion of their studies, and to attract others from outside the region to re-locate there post-university. To facilitate this, SMEs in the region were offered wage subsidies to encourage them to recruit a student or graduate on a work placement for up to one year to participate in an innovation or business growth-oriented project. A number of the employers offering work placements were social enterprises. Through analysis of the placement project and role specifications devised by the participating social enterprises, an overview is provided of their business development needs and the skills they require to stimulate innovation and growth. Scrutiny of the reflective accounts compiled by the students and graduates at the close of their work placements highlights the benefits they derived from being able to put their academic knowledge and skills into action within a social enterprise. Examination of interviews conducted with a sample of placement employers reveals the contribution the students and graduates made during the business development projects with the social enterprises. The challenges of hosting such placements are also discussed. The paper concludes with indications of the lessons learned and an outline of the wider implications for other remote rural locations in which social enterprises play an important role in the local economy and life of the community.

Keywords: resilience, rural development, regeneration, regional development, recruitment, resource management, retention, remuneration

Procedia PDF Downloads 305

Authors: Kevin Molina, Daniel Ortega, Manuel Martinez, Andres Gonzalez-Estrada, William Pinto

Abstract:

Due to the increasing environmental impact, the wind energy is getting strong. This research studied the relationship between the power produced by a horizontal axis wind turbine (HAWT) and the aerodynamic profiles used for its construction. The analysis is studied using the Computational Fluid Dynamic (CFD), presenting the parallel between the energy generated by a turbine designed with selected profiles and another one optimized. For the study, a selection process was carried out from profile NACA 6 digits recommended by the National Renewable Energy Laboratory (NREL) for the construction of this type of turbines. The selection was taken into account different characteristics of the wind (speed and density) and the profiles (aerodynamic coefficients Cl and Cd to different Reynolds and incidence angles). From the selected profiles, was carried out a sensitivity analysis optimization process between its geometry and the aerodynamic forces that are induced on it. The 3D model of the turbines was realized using the Blade Element Momentum method (BEM) and both profiles. The flow fields on the turbines were simulated, obtaining the forces induced on the blade, the torques produced and an increase of 3% in power due to the optimized profiles. Therefore, the results show that the sensitivity analysis optimization process can assist to increment the wind turbine power.

Keywords: blade element momentum, blade, fluid structure interaction, horizontal axis wind turbine, profile design

Procedia PDF Downloads 250

Authors: Ahmed Negm, George Aggidis, Xiandong Ma

Abstract:

With the diverse nature of urban cities, customer demand patterns, landscape topologies or even seasonal weather trends; managing our water distribution networks (WDNs) has proved a complex task. These unpredictable circumstances manifest as pipe failures, intermittent supply and burst events thus adding to water loss, energy waste and increased carbon emissions. Whilst these events are unavoidable, advanced pressure management has proved an effective tool to control and mitigate them. Henceforth, water utilities have struggled with developing a real-time control method that is resilient when confronting the challenges of water distribution. In this paper we use deep reinforcement learning (DRL) algorithms as a novel pressure control strategy to minimise pressure violations and leakage under both burst and background leakage conditions. Agents based on asynchronous actor critic (A2C) and recurrent proximal policy optimisation (Recurrent PPO) were trained and compared to benchmarked optimisation algorithms (differential evolution, particle swarm optimisation. A2C manages to minimise leakage by 32.48% under burst conditions and 67.17% under background conditions which was the highest performance in the DRL algorithms. A2C and Recurrent PPO performed well in comparison to the benchmarks with higher processing speed and lower computational effort.

Keywords: deep reinforcement learning, pressure management, water distribution networks, leakage management

Procedia PDF Downloads 70

Authors: Zia Ullah, Muhammad Asim, Shi Sujuan, Rayyan Khan, Aaqib Shaheen, LIU Haobao

Abstract:

The plant-specific auxin efflux proteins PIN-FORMED (PIN) have been well depicted in many plant species for their essential roles in regulating the transport of auxins in several phases of plant growth. Little is known about the various functions of the PIN family genes in the Nicotiana tabacum (N. tabacum) species during plant growth. To define the expression pattern of the NtPIN1a gene under abiotic stresses and hormone treatment, transgenic tobacco with promoterNtPIN1a::GUS construct was employed. Comprehensive computational analyses of the NtPIN1a promoter confirmed the existence of common core promoter elements including CAAT-box, TATA-box, hormone, and abiotic stress-responsive elements such as ABRE, P-box, MYC, MYB, ARE, and GC-motifs. The transgenic plants with the promoter of NtPIN1a displayed a promising expression of β-glucuronidase (GUS) in germinating seeds, root tips, shoot-apex, and developing leaves under optimal conditions. While the differential expression of GUS in moderate salt, drought, low potassium stresses, and externally high auxin level at two different time points, suggested NtPIN1a played a key role in growth processes and the plants’ response to abiotic stresses. This analysis provides a foundation for more in-depth discoveries of the biological functions of NtPIN1a in Nicotiana species and this promoter may be employed in genetic engineering of other crops for enhanced stress tolerance.

Keywords: tobacco, nicotiana tabacum, pin, promoter, GUS, abiotic stresses, auxin

Procedia PDF Downloads 81

Authors: Chaitanya R. Mali, V. Vinod, Ashwin W. Patwardhan

Abstract:

Design of long vertical steam generator (SG) tubes in nuclear power plant involves an understanding of different aspects of flow boiling phenomenon such as flow instabilities, flow regimes, dry out, critical heat flux, pressure drop, etc. The knowledge of the prediction of local thermal hydraulic characteristics is necessary to understand these aspects. For this purpose, the methodology has been developed which covers all the flow boiling regimes to model full range flow boiling phenomenon. In this methodology, the vertical tube is divided into four sections based on vapor fraction value at the end of each section. Different modeling strategies have been applied to the different sections of the vertical tube. Computational fluid dynamics simulations have been performed on a vertical SG tube of 0.0126 m inner diameter and 23 m length. The thermal hydraulic parameters such as vapor fraction, liquid temperature, heat transfer coefficient, pressure drop, heat flux distribution have been analyzed for different designed heat duties (1.1 MW (20%) to 3.3 MW (60%)) and flow conditions (10 % to 80 %). The sensitivity of different boiling parameters such as bubble departure diameter, nucleation site density, bubble departure frequency on the thermal hydraulic parameters was also studied. Flow instability has been observed at 20 % designed heat duty and 20 % flow conditions.

Keywords: thermal hydraulics, boiling, vapor fraction, sensitivity

Procedia PDF Downloads 133

Authors: Dawei Cai, Yuya Tokuda

Abstract:

The market of localization based service (LBS) is expanding. The acquisition of physical location is the fundamental basis for LBS. GPS, the de facto standard for outdoor localization, does not work well in indoor environment due to the blocking of signals by walls and ceiling. To acquire high accurate localization in an indoor environment, many techniques have been developed. Triangulation approach is often used for identifying the location, but a heavy and complex computation is necessary to calculate the location of the distances between the object and several source points. This computation is also time and power consumption, and not favorable to a mobile device that needs a long action life with battery. To provide a low power consumption approach for a mobile device, this paper presents a fast calculation approach to identify the location of the object without online solving solutions to simultaneous quadratic equations. In our approach, we divide the location identification into two parts, one is offline, and other is online. In offline mode, we make a mapping process that maps the location area to distance space and find a simple formula that can be used to identify the location of the object online with very light computation. The characteristic of the approach is a good tradeoff between the accuracy and computational amount. Therefore, this approach can be used in smartphone and other mobile devices that need a long work time. To show the performance, some simulation experimental results are provided also in the paper.

Keywords: indoor localization, location based service, triangulation, fast calculation, mobile device

Procedia PDF Downloads 163

Authors: Yuan Wan, Shumei Cui, Shaopeng Wu

Abstract:

Toroidal windings were taken advantage of to reduce of axial length of the motor, so as to match the applications that have severe restrictions on the axial length. But slotting in the out edge of the stator will decrease the heat-dissipation capacity of the water cooling of the housing. Besides, the windings in the outer slots will increase the copper loss, which will further increase the difficult for heat dissipation of the motor. At present, carbon-fiber composite retaining sleeve are increasingly used to be mounted over the magnets to ensure the rotor strength at high speeds. Due to the poor thermal conductivity of carbon-fiber sleeve, the cooling of the rotor becomes very difficult, which may result in the irreversible demagnetization of magnets for the excessively high temperature. So it is necessary to analyze the temperature rise of such motor. This paper builds a computational fluid dynamic (CFD) model of a toroidal-winding high-speed permanent magnet synchronous motor (PMSM) with water cooling of housing and forced air cooling of rotor. Thermal analysis was carried out based on the model and the factors that affects the temperature rise were investigated. Then thermal optimization for the prototype was achieved. Finally, a small-size prototype was manufactured and the thermal analysis results were verified.

Keywords: thermal analysis, temperature rise, toroidal windings, high-speed PMSM, CFD

Procedia PDF Downloads 481

Authors: Erica Siqueira, Adriana Bin, Rachel Stefanuto

Abstract:

The paper aims to identify and to discuss the impact and results of ex-ante, mid-term and ex-post evaluation initiatives in Brazilian Social Enterprises from the point of view of the entrepreneurs and investors, highlighting the processes involved in these activities and their aftereffects. The study was conducted using a descriptive methodology, primarily qualitative. A multiple-case study was used, and, for that, semi-structured interviews were conducted with ten entrepreneurs in the (i) social finance, (ii) education, (iii) health, (iv) citizenship and (v) green tech fields, as well as three representatives of various impact investments, which are (i) venture capital, (ii) loan and (iii) equity interest areas. Convenience (non-probabilistic) sampling was adopted to select both businesses and investors, who voluntarily contributed to the research. The evaluation is still incipient in most of the studied business cases. Some stand out by adopting well-known methodologies like Global Impact Investing Report System (GIIRS), but still, have a lot to improve in several aspects. Most of these enterprises use nonexperimental research conducted by their own employees, which is ordinarily not understood as 'golden standard' to some authors in the area. Nevertheless, from the entrepreneur point of view, it is possible to identify that most of them including those routines in some extent in their day-by-day activities, despite the difficulty they have of the business in general. In turn, the investors do not have overall directions to establish evaluation initiatives in respective enterprises; they are funding. There is a mechanism of trust, and this is, usually, enough to prove the impact for all stakeholders. The work concludes that there is a large gap between what the literature states in regard to what should be the best practices in these businesses and what the enterprises really do. The evaluation initiatives must be included in some extension in all enterprises in order to confirm social impact that they realize. Here it is recommended the development and adoption of more flexible evaluation mechanisms that consider the complexity involved in these businesses’ routines. The reflections of the research also suggest important implications for the field of Social Enterprises, whose practices are far from what the theory preaches. It highlights the risk of the legitimacy of these enterprises that identify themselves as 'social impact', sometimes without the proper proof based on causality data. Consequently, this makes the field of social entrepreneurship fragile and susceptible to questioning, weakening the ecosystem as a whole. In this way, the top priorities of these enterprises must be handled together with the results and impact measurement activities. Likewise, it is recommended to perform further investigations that consider the trade-offs between impact versus profit. In addition, research about gender, the entrepreneur motivation to call themselves as Social Enterprises, and the possible unintended consequences from these businesses also should be investigated.

Keywords: evaluation practices, impact, results, social enterprise, social entrepreneurship ecosystem

Procedia PDF Downloads 108

Authors: Mokhtar Djeddou, Amine Mehel, Georges Fokoua, Anne Tanière, Patrick Chevrier

Abstract:

Commuters' exposure to air pollution, particularly to particle matter, inside vehicles is a significant health issue. Assessing particles concentrations and characterizing their distribution is an important first step to understand and propose solutions to improve car cabin air quality. It is known that particles dynamics is intimately driven by particles-turbulence interactions. In order to analyze and model pollutants distribution inside the car the cabin, it is crucialto examine first the single-phase flow topology and turbulence characteristics. Within this context, Computational Fluid Dynamics (CFD) simulations were conducted to model airflow inside a full-scale car cabin using Reynolds Averaged Navier-Stokes (RANS)approach combined with the first order Realizable k- εmodel to close the RANS equations. To validate the numerical model, a campaign of velocity field measurements at different locations in the front and back of the car cabin has been carried out using hot-wire anemometry technique. Comparison between numerical and experimental results shows a good agreement of velocity profiles. Additionally, visualization of streamlines shows the formation of jet flow developing out of the dashboard air vents and the formation of large vortex structures, particularly in the back seats compartment. These vortex structures could play a key role in the accumulation and clustering of particles in a turbulent flow

Keywords: car cabin, CFD, hot wire anemometry, vortical flow

Procedia PDF Downloads 272

Authors: Yuri Boiko, Ci Lin, Iluju Kiringa, Tet Yeap

Abstract:

The performance of a BLDC motor controlled by the Kalman filter-based position-sensorless drive is studied in terms of its dependence on the system’s parameters' variations. The effects of system’s parameters changes on the dynamic behavior of state variables are verified. Simulated is a closed-loop control scheme with a Kalman filter in the feedback line. Distinguished are two separate data sampling modes in analyzing feedback output from the BLDC motor: (1) equal angular separation and (2) equal time intervals. In case (1), the data are collected via equal intervals Δθ of rotor’s angular position θᵢ, i.e., keeping Δθ=const. In case (2), the data collection time points tᵢ are separated by equal sampling time intervals Δt=const. Demonstrated are the effects of the parameters changes on the sensorless control flow, in particular, reduction of the torque ripples, switching spikes, torque load balancing. It is specifically shown that an efficient suppression of commutation induced torque ripples is achievable selection of the sampling rate in the Kalman filter settings above certain critical value. The computational cost of such suppression is shown to be higher for the motors with lower induction values of the windings.

Keywords: BLDC motor, Kalman filter, sensorless drive, state variables, torque ripples reduction, sampling rate

Procedia PDF Downloads 136

Authors: Akinbo Razak Yinka, Adesanya Kehinde Kazeem, Oladokun Oluwagbenga Peter

Abstract:

Time series data are sequences of observations collected over a period of time. Such data can be used to predict health outcomes, such as disease progression, mortality, hospitalization, etc. The Statistical approach is based on mathematical models that capture the patterns and trends of the data, such as autocorrelation, seasonality, and noise, while Neural methods are based on artificial neural networks, which are computational models that mimic the structure and function of biological neurons. This paper compared both parametric and non-parametric time series models of patients treated for malaria in Maternal and Child Health Centres in Lagos State, Nigeria. The forecast methods considered linear regression, Integrated Moving Average, ARIMA and SARIMA Modeling for the parametric approach, while Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) Network were used for the non-parametric model. The performance of each method is evaluated using the Mean Absolute Error (MAE), R-squared (R2) and Root Mean Square Error (RMSE) as criteria to determine the accuracy of each model. The study revealed that the best performance in terms of error was found in MLP, followed by the LSTM and ARIMA models. In addition, the Bootstrap Aggregating technique was used to make robust forecasts when there are uncertainties in the data.

Keywords: ARIMA, bootstrap aggregation, MLP, LSTM, SARIMA, time-series analysis

Procedia PDF Downloads 63

Authors: K. K. Lee, H. W. Han, H. L. Kang, T. A. Kim, S. H. Han

Abstract:

For the robust optimization of the manufacturing product design, there are design objectives that must be achieved, such as a minimization of the mean and standard deviation in objective functions within the required sensitivity constraints. The authors utilized the sensitivity of objective functions and constraints with respect to the effective design variables to reduce the computational burden associated with the evaluation of the probabilities. The individual mean and sensitivity values could be estimated easily by using the 9 level orthogonal array based response surface models optimized by the stepwise regression. The present study evaluates a proposed procedure from the robust optimization of rubber domes that are commonly used for keyboard switching, by using the 9 level orthogonal array and stepwise regression along with a desirability function. In addition, a new robust optimization process, i.e., the I2GEO (Identify, Integrate, Generate, Explore and Optimize), was proposed on the basis of the robust optimization in rubber domes. The optimized results from the response surface models and the estimated results by using the finite element analysis were consistent within a small margin of error. The standard deviation of objective function is decreasing 54.17% with suggested sensitivity based robust optimization. (Business for Cooperative R&D between Industry, Academy, and Research Institute funded Korea Small and Medium Business Administration in 2017, S2455569)

Keywords: objective function, orthogonal array, response surface model, robust optimization, stepwise regression

Procedia PDF Downloads 279

Authors: Somnath Mukhuti, Prem Kumar Ghosh

Abstract:

Background and significance of the study Indian stock market has undergone sudden changes after the current China crisis in terms of turnover, market capitalization, share prices, etc. The average returns on equity investment in both markets have more than three and half times after global financial crisis owing to the development of industrial activity, corporate sectors development, enhancement in global consumption, change of global financial association and fewer imports from developed countries. But the economic policies of both the economies are far different, that is to say, where Indian economy maintaining a conservative policy, Chinese economy maintaining an aggressive policy. Besides this, Chinese economy recently lowering its currency for increasing mysterious growth but Indian does not. But on August 24, 2015 Indian stock market and world stock markets were fall down due to the reason of Chinese stock market. Keeping in view of the above, this study seeks to examine the influence of Chinese stock on Indian stock market. Methodology This research work is based on daily time series data obtained from yahoo finance database between 2009 (April 1) to 2015 (September 28). This study is based on two important stock markets, that is, Indian stock market (Bombay Stock Exchange) and Chinese stock market (Shanghai Stock Exchange). In the course of analysis, the daily raw data were converted into natural logarithm for minimizing the problem of heteroskedasticity. While tackling the issue, correlation statistics, ADF and PP unit root test, bivariate cointegration test and causality test were used. Major findings Correlation statistics show that both stock markets are associated positively. Both ADF and PP unit root test results demonstrate that the time series data were not normal and were not stationary at level however stationary at 1st difference. The bivariate cointegration test results indicate that the Indian stock market was associated with Chinese stock market in the long-run. The Granger causality test illustrates there was a unidirectional causality between Indian stock market and Chinese stock market. Concluding statement The empirical results recommend that India’s stock market was not very much dependent on Chinese stock market because of Indian economic conservative policies. Nevertheless, Indian stock market might be sturdy if Indian economic policies are changed slightly and if increases the portfolio investment with Chinese economy. Indian economy might be a third largest economy in 2030 if India increases its portfolio investment and trade relations with both Chinese economy and US economy.

Keywords: Indian stock market, China stock market, bivariate cointegration, causality test

Procedia PDF Downloads 362

Authors: Balram Panjwani, Bernd Wittgens, Jan Erik Olsen, Stein Tore Johansen

Abstract:

The Norwegian ferroalloy industry is a world leader in sustainable production of ferrosilicon, silicon and manganese alloys with the lowest global specific energy consumption. One of the byproducts during the metal reduction process is energy rich off-gas and usually this energy is not harnessed. A novel concept for sustainable energy recovery from ferroalloy off-gas is discussed. The concept is founded on the idea of introducing a combustion chamber in the off-gas section in which energy rich off-gas mainly consisting of CO will be combusted. This will provide an additional degree of freedom for optimizing energy recovery. A well-controlled and high off-gas temperature will assure a significant increase in energy recovery and reduction of emissions to the atmosphere. Design and operation of the combustion chamber depend on many parameters, including the total power capacity of the combustion chamber, sufficient residence time for combusting the complex Poly Aromatic Hydrocarbon (PAH), NOx, as well as converting other potential pollutants. The design criteria for the combustion chamber have been identified and discussed and sizing of the combustion chamber has been carried out considering these design criteria. Computational Fluid Dynamics (CFD) has been utilized extensively for sizing the combustion chamber. The results from our CFD simulations of the flow in the combustion chamber and exploring different off-gas fuel composition are presented. In brief, the paper covers all aspect which impacts the sizing of the combustion chamber, including insulation thickness, choice of insulating material, heat transfer through extended surfaces, multi-staging and secondary air injection.

Keywords: CFD, combustion chamber, arc furnace, energy recovery

Procedia PDF Downloads 306

Authors: M. Wasy Akhtar

Abstract:

Multi-modal film boiling simulations are carried out on adaptive octree grids. The liquid-vapor interface is captured using the volume-of-fluid framework adjusted to account for exchanges of mass, momentum, and energy across the interface. Surface tension effects are included using a volumetric source term in the momentum equations. The phase change calculations are conducted based on the exact location and orientation of the interface; however, the source terms are calculated using the mixture variables to be consistent with the one field formulation used to represent the entire fluid domain. The numerical model on octree representation of the computational grid is first verified using test cases including advection tests in severely deforming velocity fields, gravity-based instabilities and bubble growth in uniformly superheated liquid under zero gravity. The model is then used to simulate both single and multi-modal film boiling simulations. The octree grid is dynamically adapted in order to maintain the highest grid resolution on the instability fronts using markers of interface location, volume fraction, and thermal gradients. The method thus provides an efficient platform to simulate fluid instabilities with or without phase change in the presence of body forces like gravity or shear layer instabilities.

Keywords: boiling flows, dynamic octree grids, heat transfer, interface capturing, phase change

Procedia PDF Downloads 237

Authors: Rajvir Kaur, Jeewani Anupama Ginige

Abstract:

With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: artificial neural networks, breast cancer, classifiers, cervical cancer, f-score, machine learning, precision, recall

Procedia PDF Downloads 266

Authors: Sahar Heidary, Ramin Ghasemi Shayan

Abstract:

The overall goal Monte Carlo N-atom radioactivity transference PC program (MCNP4C) was done for the regeneration of x-ray groups in diagnostic radiology and mammography. The electrons were transported till they slow down and stopover in the target. Both bremsstrahlung and characteristic x-ray creation were measured in this study. In this issue, the x-ray spectra forecast by several computational models recycled in the diagnostic radiology and mammography energy kind have been calculated by appraisal with dignified spectra and their outcome on the scheming of absorbed dose and effective dose (ED) told to the adult ORNL hermaphroditic phantom quantified. This comprises practical models (TASMIP and MASMIP), semi-practical models (X-rayb&m, X-raytbc, XCOMP, IPEM, Tucker et al., and Blough et al.), and Monte Carlo modeling (EGS4, ITS3.0, and MCNP4C). Images got consuming synchrotron radiation (SR) and both screen-film and the CR system were related with images of the similar trials attained with digital mammography equipment. In sight of the worthy feature of the effects gained, the CR system was used in two mammographic inspections with SR. For separately mammography unit, the capability acquiesced bilateral mediolateral oblique (MLO) and craniocaudal(CC) mammograms attained in a woman with fatty breasts and a woman with dense breasts. Referees planned the common groups and definite absences that managed to a choice to miscarry the part that formed the scientific imaginings.

Keywords: mammography, monte carlo, effective dose, radiology

Procedia PDF Downloads 115

Authors: Abhishek Agarwal, Manoj Sarda, Juhi Kaushik, Vatsal Sanjay, Arup Kumar Das

Abstract:

Propagation of fire through a non-air conditioned railway compartment is studied by virtue of numerical simulations. Simultaneous computational fire dynamics equations, such as Navier-Stokes, lumped species continuity, overall mass and energy conservation, and heat transfer are solved using finite volume based (for radiation) and finite difference based (for all other equations) solver, Fire Dynamics Simulator (FDS). A single coupe with an eight berth occupancy is used to establish the numerical model, followed by the selection of a three coupe system as the fundamental unit of the locomotive compartment. Heat Release Rate Per Unit Area (HRRPUA) of the initial fire is varied to consider a wide range of compartmental fires. Parameters, such as air inlet velocity relative to the locomotive at the windows, the level of interaction with the ambiance and closure of middle berth are studied through a wide range of numerical simulations. Almost all the loss of lives and properties due to fire breakout can be attributed to the direct or indirect exposure to flames or to the inhalation of toxic gases and resultant suffocation due to smoke and soot. Therefore, the temporal stature of fire and smoke are reported for each of the considered cases which can be used in the present or extended form to develop guidelines to be followed in case of a fire breakout.

Keywords: fire dynamics, flame propagation, locomotive fire, soot flow pattern, non-air-conditioned coaches

Procedia PDF Downloads 285

Authors: Hamid El Qarnia

Abstract:

This study investigates the impact of the eccentricity of the central tube on the thermal and fluid characteristics of a triplex tube used in latent heat energy storage technologies. Two triplex tube orientations are considered in the proposed study: vertical and horizontal. The energy storage material, which is a phase change material (PCM), is placed in the space between the inside and outside tubes. During the thermal energy storage period, a heat transfer fluid (HTF) flows inside the two tubes, transmitting the heat to the PCM through two heat exchange surfaces instead of one heat exchange surface as it is the case for double tube heat storage systems. A CFD model is developed and validated against experimental data available in the literature. The mesh independency study is carried out to select the appropriate mesh. In addition, different time steps are examined to determine a time step ensuring accuracy of the numerical results and reduction in the computational time. The numerical model is then used to conduct numerical investigations of the thermal behavior and thermal performance of the storage unit. The effects of eccentricity of the central tube and HTF mass flow rate on thermal characteristics and performance indicators are examined for two flow arrangements: co-current and counter current flows. The results are given in terms of isotherm plots, streamlines, melting time and thermal energy storage efficiency.

Keywords: energy storage, heat transfer, melting, solidification

Procedia PDF Downloads 46

Authors: Madhuka G. P. D. Udantha, Gihan V. Dias, Surangika Ranathunga

Abstract:

Today Websites contain very interesting applications. But there are only few methodologies to analyze User navigations through the Websites and formulating if the Website is put to correct use. The web logs are only used if some major attack or malfunctioning occurs. Web Logs contain lot interesting dealings on users in the system. Analyzing web logs has become a challenge due to the huge log volume. Finding interesting patterns is not as easy as it is due to size, distribution and importance of minor details of each log. Web logs contain very important data of user and site which are not been put to good use. Retrieving interesting information from logs gives an idea of what the users need, group users according to their various needs and improve site to build an effective and efficient site. The model we built is able to detect attacks or malfunctioning of the system and anomaly detection. Logs will be more complex as volume of traffic and the size and complexity of web site grows. Unsupervised techniques are used in this solution which is fully automated. Expert knowledge is only used in validation. In our approach first clean and purify the logs to bring them to a common platform with a standard format and structure. After cleaning module web session builder is executed. It outputs two files, Web Sessions file and Indexed URLs file. The Indexed URLs file contains the list of URLs accessed and their indices. Web Sessions file lists down the indices of each web session. Then DBSCAN and EM Algorithms are used iteratively and recursively to get the best clustering results of the web sessions. Using homogeneity, completeness, V-measure, intra and inter cluster distance and silhouette coefficient as parameters these algorithms self-evaluate themselves to input better parametric values to run the algorithms. If a cluster is found to be too large then micro-clustering is used. Using Cluster Signature Module the clusters are annotated with a unique signature called finger-print. In this module each cluster is fed to Associative Rule Learning Module. If it outputs confidence and support as value 1 for an access sequence it would be a potential signature for the cluster. Then the access sequence occurrences are checked in other clusters. If it is found to be unique for the cluster considered then the cluster is annotated with the signature. These signatures are used in anomaly detection, prevent cyber attacks, real-time dashboards that visualize users, accessing web pages, predict actions of users and various other applications in Finance, University Websites, News and Media Websites etc.

Keywords: anomaly detection, clustering, pattern recognition, web sessions

Procedia PDF Downloads 278

Authors: Egor Stadnichuk

Abstract:

Relativistic runaway electron avalanches (RREA) are a widely accepted source of thunderstorm gamma-radiation. In regions with huge electric field strength, RREA can multiply via relativistic feedback. The relativistic feedback is caused both by positron production and by runaway electron bremsstrahlung gamma-rays reversal. In complex multilayer thunderstorm electric field structures, an additional reactor feedback mechanism appears due to gamma-ray exchange between separate strong electric field regions with different electric field directions. The study of this reactor mechanism in conjunction with the relativistic feedback with Monte Carlo simulations or by direct solution of the kinetic Boltzmann equation requires a significant amount of computational time. In this work, a theoretical approach to study feedback mechanisms in RREA physics is developed. It is based on the matrix of feedback operators construction. With the feedback matrix, the problem of the dynamics of avalanches in complex electric structures is reduced to the problem of finding eigenvectors and eigenvalues. A method of matrix elements calculation is proposed. The proposed concept was used to study the dynamics of RREAs in multilayer thunderclouds.

Keywords: terrestrial Gamma-ray flashes, thunderstorm ground enhancement, relativistic runaway electron avalanches, gamma-rays, high-energy atmospheric physics, TGF, TGE, thunderstorm, relativistic feedback, reactor feedback, reactor model

Procedia PDF Downloads 155

Authors: Chen Bo, Wen Zengping

Abstract:

Based on the results of previous studies, we focus on the research of real ground motion selection and scaling method for structural performance-based seismic evaluation using nonlinear dynamic analysis. The input of earthquake ground motion should be determined appropriately to make them compatible with the site-specific hazard level considered. Thus, an optimized selection and scaling method are established including the use of not only Monte Carlo simulation method to create the stochastic simulation spectrum considering the multivariate lognormal distribution of target spectrum, but also a spectral shape parameter. Its applications in structural fragility analysis are demonstrated through case studies. Compared to the previous scheme with no consideration of the uncertainty of target spectrum, the method shown here can make sure that the selected records are in good agreement with the median value, standard deviation and spectral correction of the target spectrum, and greatly reveal the uncertainty feature of site-specific hazard level. Meanwhile, it can help improve computational efficiency and matching accuracy. Given the important infection of target spectrum’s uncertainty on structural seismic fragility analysis, this work can provide the reasonable and reliable basis for structural seismic evaluation under scenario earthquake environment.

Keywords: ground motion selection, scaling method, seismic fragility analysis, spectral shape

Procedia PDF Downloads 281

Authors: Shinji Sato, M. M. A. Alam, Manabu Takao

Abstract:

In recent, investigation of an unsteady flow inside the resonance tube have become a strongly motivated research field for their potential application as high-frequency actuators. By generating a shock wave inside the resonance tube, a high temperature and pressure can be achieved inside the tube, and this high temperature can also be used to ignite a jet engine. In the present research, a computational fluid dynamics (CFD) analysis was carried out to investigate the flow inside the resonance tube. The density-based solver of rhoCentralFoam in OpenFOAM was used to numerically simulate the flow. The supersonic jet that was driven by a cylindrical nozzle with a nominal exit diameter of φd = 20.3 mm impinged onto the resonance tube. The jet pressure ratio was varied between 2.6 and 7.8. The gap s between the nozzle exit and tube entrance was changed between 1.5d and 3.0d. The diameter and length of the tube were taken as D = 1.25d and L=3.0D, respectively. As a result, when a supersonic jet has impinged onto the resonance tube, a compression wave was found generating inside the tube and propagating towards the tube end wall. This wave train resulted in a rise in the end wall gas temperature and pressure. While, in an outflow phase, the gas near tube enwall was found cooling back isentropically to its initial temperature. Thus, the compression waves repeated a reciprocating motion in the tube like a piston, and a fluctuation in the end wall pressures and temperatures were observed. A significant change was found in the end wall pressures and temperatures with a change of jet flow conditions. In this study, the highest temperature was confirmed at a jet pressure ratio of 4.2 and a gap of s=2.0d

Keywords: compressible flow, OpenFOAM, oscillations, a resonance tube, shockwave

Procedia PDF Downloads 138

Authors: E. Moradimaram, H. Sayehvand

Abstract:

In recent years the increasing use of fossil fuels has led to various environmental problems including urban pollution, ozone layer depletion and acid rains. Moreover, with the increased number of industrial centers and higher consumption of these fuels, the end point of the fossil energy reserves has become more evident. Considering the environmental pollution caused by fossil fuels and their limited availability, renewable sources can be considered as the main substitute for non-renewable resources. One of these resources is the Organic Rankine Cycles (ORCs). These cycles while having high safety, have low maintenance requirements. Combining the ORCs with other systems, such as ejector and reheater will increase overall cycle efficiency. In this study, ejector and reheater are used to improve the thermal efficiency (ηth), exergy efficiency (η_ex) and net output power (w_net); therefore, the ORCs with reheater (RORCs) are proposed. A computational program has been developed to calculate the thermodynamic parameters required in Engineering Equations Solver (EES). In this program, the analysis of the first and second law in RORC is conducted, and a comparison is made between them and the ORCs with Ejector (EORC). R245fa is selected as the working fluid and water is chosen as low temperature heat source with a temperature of 95 °C and a mass transfer rate of 1 kg/s. The pressures of the second evaporator and reheater are optimized in terms of maximum exergy efficiency. The environment is at 298.15 k and at 101.325 kpa. The results indicate that the thermodynamic parameters in the RORC have improved compared to EORC.

Keywords: Organic Rankine Cycle (ORC), Organic Rankine Cycle with Reheater (RORC), Organic Rankine Cycle with Ejector (EORC), exergy efficiency

Procedia PDF Downloads 154

Authors: Mirvat Shamseddine, Issam Lakkis

Abstract:

We present an efficient, three-dimensional parallel multi-scale Direct Simulation Monte Carlo (DSMC) algorithm for the simulation of unsteady rarefied gas flows in micro/nanosystems. The algorithm employs a novel spatiotemporal adaptivity scheme. The scheme performs a fully dynamic multi-level grid adaption based on the gradients of flow macro-parameters and an automatic temporal adaptation. The computational domain consists of a hierarchical octree-based Cartesian grid representation of the flow domain and a triangular mesh for the solid object surfaces. The hybrid mesh, combined with the spatiotemporal adaptivity scheme, allows for increased flexibility and efficient data management, rendering the framework suitable for efficient particle-tracing and dynamic grid refinement and coarsening. The parallel algorithm is optimized to run DSMC simulations of strongly unsteady, non-equilibrium flows over multiple cores. The presented method is validated by comparing with benchmark studies and then employed to improve the design of micro-scale hotwire thermal sensors in rarefied gas flows.

Keywords: DSMC, oct-tree hierarchical grid, ray tracing, spatial-temporal adaptivity scheme, unsteady rarefied gas flows

Procedia PDF Downloads 292

Authors: T. Gomes, J. Manzi

Abstract:

The inclusion of stirring systems in the calculation and optimization procedures has been undergone a significant lack of attention, what it can reflect in the results because such systems provide an additional energy to the process, besides promote a better distribution of mass and energy. This is meaningful for the reactive systems, particularly for the Continuous Stirred Tank Reactor (CSTR), for which the key variables and parameters, as well as the operating conditions of stirring systems, can play a pivotal role and it has been showed in the literature that neglect these factors can lead to sub-optimal results. It is also well known that the sole use of the First Law of Thermodynamics as an optimization tool cannot yield satisfactory results, since the joint use of the First and Second Laws condensed into a procedure so-called entropy generation minimization (EGM) has shown itself able to drive the system towards better results. Therefore, the main objective of this paper is to determine the effects of key parameters of the stirring system in the optimization procedures by means of EGM applied to the reactive systems. Such considerations have been possible by dimensional analysis according to Rayleigh and Buckingham's method, which takes into account the physical and geometric parameters and the variables of the reactive system. For the simulation purpose based on the production of propylene glycol, the results have shown a significant increase in the conversion rate from 36% (not-optimized system) to 95% (optimized system) with a consequent reduction of by-products. In addition, it has been possible to establish the influence of the work of the stirrer in the optimization procedure, in which can be described as a function of the fluid viscosity and consequently of the temperature. The conclusions to be drawn also indicate that the use of the entropic analysis as optimization tool has been proved to be simple, easy to apply and requiring low computational effort.

Keywords: stirring systems, entropy, reactive system, optimization

Procedia PDF Downloads 239