Search results for: traffic modeling

Authors: Lubov Magerramova, Vladimir Isakov, Michail Petrov

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A methodology for calculating and modeling technological modes of laser 3D printing of Ti6Al4V powder alloy samples has been developed. ProXDPM320 3D printer was used. The technological model that takes into account the multifactorial influence of modes and conditions of additive cultivation on characteristics and strength properties of titanium samples has been created. Process control parameters and an order parameter, to which the others are subordinate, were established. Using the iterative method, the optimal technological parameters for the additive growth of cylindrical samples were calculated. The calculations were combined with data obtained during virtual 3D printing in the Altair Inspire software environment. The samples were subjected to short-term tensile strength tests at normal temperature on a servo-hydraulic machine “LFV-100”. As a result, deformation diagrams were constructed, and mechanical characteristics such as proportionality limit, conditional yield strength, tensile strength, elastic modulus, relative elongation, and stress at break were obtained. Comparison of these characteristics with those for the industrial alloy Ti6Al4V showed acceptable agreement. Some of the synthesized samples were subjected to laser shock treatment to increase fatigue strength. The results obtained were used to validate the mathematical model of 3D printing of titanium alloys.

Keywords: additive technology, titanium alloy, numerical simulation, strength tests

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Authors: Ziba Khalili, Mohsen Sheikholeslami, Ladan Momayez

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Combining the photovoltaic/thermal (PVT) systems with a thermoelectric (TE) module can raise energy yields since the TE module boosts the system's energy conversion efficiency. In the current study, a PVT system integrated with a TE module was designed and simulated in ANSYS Fluent 19.2. A copper heat transfer tube (HTT) was employed for cooling the photovoltaic (PV) cells. Four different shapes of HTT cross-section, i.e., circular, square, elliptical, and triangular, with equal cross-section areas were investigated. Also, the influence of Cu-Al2O3/water hybrid nanofluid (0.024% volume concentration), fluid inlet velocity (uᵢ ), and amount of solar radiation (G), on the PV temperature (Tₚᵥ) and system performance were investigated. The ambient temperature (Tₐ), wind speed (u𝓌), and fluid inlet temperature (Tᵢ), were considered to be 25°C, 1 m/s, and 27°C, respectively. According to the obtained data, the triangular case had the greatest impact on reducing the compared to other cases. In the triangular case, examination of the effect of hybrid nanofluid showed that the use of hybrid nanofluid at 800 W/m2 led to a reduction of the TPV by 0.6% compared to water, at 0.19 m/s. Moreover, the thermal efficiency ( ) and the overall electrical efficiency (nₜ) of the system improved by 0.93% and 0.22%, respectively, at 0.19 m/s. In a triangular case where G and were 800 W/m2 and 19 m/s, respectively, the highest amount of, thermal power (Eₜ), and, were obtained as 72.76%, 130.84 W and 12.03%, respectively.

Keywords: electrical performance, photovoltaic/thermal, thermoelectric, hybrid nanofluid, thermal efficiency

Procedia PDF Downloads 81

Authors: Zehai Yu, Hui Zhu, Linglong Lin, Huawei Liang, Biao Yu, Weixin Huang

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With the development of intelligent vehicle systems, a high-precision road map is increasingly needed in many aspects. The automatic lane lines extraction and modeling are the most essential steps for the generation of a precise lane-level road map. In this paper, an automatic lane-level road map generation system is proposed. To extract the road markings on the ground, the multi-region Otsu thresholding method is applied, which calculates the intensity value of laser data that maximizes the variance between background and road markings. The extracted road marking points are then projected to the raster image and clustered using a two-stage clustering algorithm. Lane lines are subsequently recognized from these clusters by the shape features of their minimum bounding rectangle. To ensure the storage efficiency of the map, the lane lines are approximated to cubic polynomial curves using a Bayesian estimation approach. The proposed lane-level road map generation system has been tested on urban and expressway conditions in Hefei, China. The experimental results on the datasets show that our method can achieve excellent extraction and clustering effect, and the fitted lines can reach a high position accuracy with an error of less than 10 cm.

Keywords: curve fitting, lane-level road map, line recognition, multi-thresholding, two-stage clustering

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Authors: M. R. Daneshgar, S. E. Habibi, E. Daneshgar, A. Daneshgar

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In this paper, a two-dimensional method is developed to simulate the fillet welds in a stiffened cylindrical shell, using finite element method. The stiffener material is aluminum 2519. The thermo-elasto-plastic analysis is used to analyze the thermo-mechanical behavior. Due to the high heat flux rate of the welding process, two uncouple thermal and mechanical analysis are carried out instead of performing a single couple thermo-mechanical simulation. In order to investigate the effects of the welding procedures, two different welding techniques are examined. The resulted residual stresses and distortions due to different welding procedures are obtained. Furthermore, this study employed the technique of element birth and death to simulate the weld filler variation with time in fillet welds. The obtained results are in good agreement with the published experimental and three-dimensional numerical simulation results. Therefore, the proposed 2D modeling technique can effectively give the corresponding results of 3D models. Furthermore, by inspection of the obtained residual hoop and transverse stresses and angular distortions, proper welding procedure is suggested.

Keywords: stiffened cylindrical shell, fillet welds, residual stress, angular distortion, finite element method

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Authors: Jacinta Ifeoma Obidile

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Teachers (vocational and technical educators inclusive) use Information and Communications Technology (ICT) for tasks outside of their normal working hours. This expansion of work duties to non-work time challenges their work-life balance. However, there has been inconsistency in the results on how these relationships correlate. This, therefore, calls for further research studies to examine the moderating mechanisms of such relationships. The present study, therefore, ascertained how vocational and technical educators’ technology acceptance relates to their work-related ICT use beyond their working hours and work-life balance, as well as how their integration affects these relationships. The population of the study comprised 320 Vocational and Technical Educators from the Southeast geopolitical zone of Nigeria. Data were collected from the respondents using the structured questionnaire. The questionnaire was validated by three experts. The reliability of the study was conducted using 20 vocational and technical educators from the South who were not part of the population. The overall reliability coefficient of 0.81 was established using Cronbach’s alpha method. The data collected was analyzed using Structural equation modeling. Findings, among others, revealed that vocational and technical educators’ work-life balance was mediated by increased digital learning environment use after work hours, although reduced by social influence.

Keywords: vocational and technical educators, digital learning environment, working hours, work-life balance, integration preference

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Authors: Balgaisha G. Mukanova, Yelbek B. Utepov, Aida G. Nazarova, Alisher Z. Imanov

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The problem of identifying local noise sources on a construction site using a sensor system is considered. Mathematical modeling of detected signals on sensors was carried out, considering signal decay and signal delay time between the source and detector. Recordings of noises produced by construction tools were used as a dependence of noise on time. Synthetic sensor data was constructed based on these data, and a model of the propagation of acoustic waves from a point source in the three-dimensional space was applied. All sensors and sources are assumed to be located in the same plane. A source localization method is checked based on the signal time delay between two adjacent detectors and plotting the direction of the source. Based on the two direct lines' crossline, the noise source's position is determined. Cases of one dominant source and the case of two sources in the presence of several other sources of lower intensity are considered. The number of detectors varies from three to eight detectors. The intensity of the noise field in the assessed area is plotted. The signal of a two-second duration is considered. The source is located for subsequent parts of the signal with a duration above 0.04 sec; the final result is obtained by computing the average value.

Keywords: acoustic model, direction of arrival, inverse source problem, sound localization, urban noises

Procedia PDF Downloads 65

Authors: Samantha Shallop, Hakinya Karra, Tytus Bernas, Gladys Shaw, Gretchen Neigh, Jeffrey Dupree, Mathula Thangarajh

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Abnormal neuronal homeostasis is considered a structural correlate of cognitive deficits in Duchenne Muscular Dystrophy. Neurons are highly polarized cells with multiple dendrites but a single axon. Trafficking of cellular organelles are highly regulated, with the cargo in the somatodendritic region of the neuron not permitted to enter the axonal compartment. We investigated the molecular mechanisms that regular organelle trafficking in neurons using a multimodal approach, including high-resolution structural illumination, proteomics, immunohistochemistry, and computational modeling. We investigated the expression of ankyrin-G, the master regulator controlling neuronal polarity. The expression of ankyrin G and the morphology of the axon initial segment was profoundly abnormal in the CA1 hippocampal neurons in the mdx52 animal model of DMD. Ankyrin-G colocalized with kinesin KIF5a, the anterograde protein transporter, with higher levels in older mdx52 mice than younger mdx52 mice. These results suggest that the functional trafficking from the somatodendritic compartment is abnormal. Our data suggests that dystrophin deficiency compromised neuronal homeostasis via ankyrin-G-based mechanisms.

Keywords: neurons, axonal transport, duchenne muscular dystrophy, organelle transport

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Authors: Fatima Mehmood, Khalid Farooq

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After the Mangla dam raising in 2010, the maximum reservoir impoundment level of 378.5 m SPD (Survey of Pakistan Datum) was achieved in September 2014. The reservoir drawdown was started on September 29, 2014 and a landslide occurred on Mirpur-Kotli Road near Khaliqabad on November 27, 2014. This landslide took place due to the failure of a slope along the reservoir rim. This study was undertaken to investigate the causative factors of Khaliqabad landslide. Site visits were carried out for recording the field observations and collection of the soil samples. The soil was subjected to different laboratory tests for the determination of index and engineering properties. The shear strength tests were performed at various levels of density and degrees of saturation. These soil parameters were used in an integrated SEEP-SLOPE/W analysis to obtain the drop in factor of safety with time and reservoir drawdown. The results showed the factor of safety dropped from 1.28 to 0.85 over a period of 60 days. The ultimate reduction in the shear strength of soil due to saturation with the simultaneous removal of the stabilizing effect of reservoir caused the disturbing forces to increase, and thus failure happened. The findings of this study can serve as a guideline for the modeling of the slopes experiencing rapid drawdown scenario with the consideration of more realistic distribution of soil moisture/ properties across the slope

Keywords: geotechnical investigation, landslide, reservoir drawdown, shear strength, slope stability

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Authors: Mahdieh Zamzamzadeh, Ahmad Abdullah Saifizul, Rahizar Ramli

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The road accidents involving heavy vehicles have been showing worrying trends and, year after year, have increased the concern and awareness levels on safety of roads and transportations especially in developing countries like Malaysia. Statistics of road crashes continue to show that there are many contributing factors on the capability of a heavy vehicle to stop on safe distance and ultimately prevent traffic crashes. However, changes in the road condition due to weather variations and the vehicle dynamic specifications such as loading conditions and speed are the main risk factors because they will affect a heavy vehicle’s braking performance due to losing control and not being able to stop the vehicle, and in many cases will cause wheel lock up and accordingly skidding. Predicting heavy vehicle skidding distance is crucial for accident reconstruction and roadside safety engineers. Despite this, formal tools to study heavy vehicle skidding distance before stopping completely are totally limited, and most researchers have only considered braking distance in their studies. As a possible new tool, this work presents the iterative use of vehicle dynamic simulations to study heavy vehicle-roadway interaction in order to predict wheel lock up effects on skidding distance and safety. This research addresses the influence of the vehicle and road conditions on skidding distance after wheel lock up and presents a precise analysis of skidding phenomenon. The vehicle speed, vehicle loading condition and road friction parameters were all varied in a simulation-based analysis. In order to simulate the wheel lock up situation, a heavy vehicle model was constructed and simulated using multibody vehicle dynamics simulation software, and careful analysis was made on the conditions which caused the skidding distance to increase or decrease through a method using to predict skidding distance as part of braking distance. By applying many simulations, the results were quite revealing relation between the heavy vehicles loading condition, various sets of speed and road coefficient of friction and their interaction effect on the skidding distance. A number of results are presented which illustrate how the heavy vehicle overloading can seriously affect the skidding distance. Moreover, the results of simulation give the skid mark length, which is a necessary input data during accident reconstruction involving emergency braking.

Keywords: accident reconstruction, Braking, heavy vehicle, skidding distance, skid mark, wheel lock up

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Authors: Nick Woodier, Paul Sampson, Iain Moppett

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Background: For years, healthcare across the world has recognised that patients are coming to harm from the very processes meant to help them. In response, healthcare tells itself that it needs to ‘be more like aviation.’ Aviation safety is highly regarded by those in healthcare and is seen as an exemplar. Specifically, healthcare is keen to learn from how aviation uses near misses to make their industry safer. Healthcare is rife with near misses; however, there has been little progress addressing them, with most research having focused on reporting. Addressing the factors that contribute to near misses will potentially help reduce the number of significant, harm patientsafety incidents. While the healthcare literature states the need to learn from aviation’s use of near misses, there is nothing that describes how best to do this. The authors, as part of a larger study of near-miss management in healthcare, sought to learn from aviation to develop principles for how healthcare can identify, report, and learn from near misses to improve patient safety. Methods: A Grounded Theory (GT) methodology, augmented by a scoping review, was used. Data collection included interviews, field notes, and the literature. The review protocol is accessible online. The GT aimed to develop theories about how aviation, amongst other safety-critical industries, manages near misses. Results: Twelve aviation interviews contributed to the GT across passenger airlines, air traffic control, and bodies involved in policy, regulation, and investigation. The scoping review identified 83 articles across a range of safety-critical industries, but only seven focused on aviation. The GT identified that aviation interprets the term ‘near miss’ in different ways, commonly using it to specifically refer to near-miss air collisions, also known as Airproxes. Other types of near misses exist, such as health and safety, but the reporting of these and the safety climate associated with them is not as mature. Safety culture in aviation was regularly discussed, with evidence that culture varies depending on which part of the industry is being considered (e.g., civil vs. business aviation). Near misses are seen as just one part of an extensive safety management system, but processes to support their reporting and their analysis are not consistent. Their value alone is also questionable, with the challenge to long-held beliefs originating from the ‘common cause hypothesis.’ Conclusions: There is learning that healthcare can take from how parts of aviation manage and learn from near misses. For example, healthcare would benefit from a formal safety management system that currently does not exist. However, it may not be as simple as ‘healthcare should learn from aviation’ due to variation in safety maturity across the industry. Healthcare needs to clarify how to incorporate near misses into learning and whether allocating resources to them is of value; it was heard that catastrophes have led to greater improvements in safety in aviation.

Keywords: aviation safety, patient safety, near miss, safety management systems

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Authors: Zbigniew Olczykowski

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The paper presents the impact of work on the electric arc furnace power grid. The arc furnace operating will be modeled at different power conditions of steelworks. The paper will describe how to determine the increase in voltage fluctuations caused by working in parallel arc furnaces. The analysis of indicators characterizing the quality of electricity recorded during several cycles of measurement made at the same time at three points grid, with different power and different short-circuit rated voltage, will be carried out. The measurements analysis presented in this paper were conducted in the mains of one of the Polish steel. The indicators characterizing the quality of electricity was recorded during several cycles of measurement while making measurements at three points of different power network short-circuit power and various voltage ratings. Measurements of power quality indices included the one-week measurement cycles in accordance with the EN-50160. Data analysis will include the results obtained during the simultaneous measurement of three-point grid. This will determine the actual propagation of interference generated by the device. Based on the model studies and measurements of quality indices of electricity we will establish the effect of a specific arc on the mains. The short-circuit power network’s minimum value will also be estimated, this is necessary to limit the voltage fluctuations generated by arc furnaces.

Keywords: arc furnaces, long-term flicker, measurement and modeling of power quality, voltage fluctuations

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Authors: Peter L. Varkonyi, Andras A. Sipos

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The quasi-static growth of elastic fibers is studied in the presence of distributed contact with an immobile surface, subject to isotropic dry or viscous friction. Unlike classical problems of elastic stability modelled by autonomous dynamical systems with multiple time scales (slowly varying bifurcation parameter, and fast system dynamics), this problem can only be formulated as a non-autonomous system without time scale separation. It is found that the fibers initially converge to a trivial, straight configuration, which is later replaced by divergence reminiscent of buckling phenomena. In order to capture the loss of stability, a new definition of exponential stability against infinitesimal perturbations for systems defined over finite time intervals is developed. A semi-analytical method for the determination of the critical length based on eigenvalue analysis is proposed. The post-critical behavior of the fibers is studied numerically by using variational methods. The emerging post-critical shapes and the asymptotic behavior as length goes to infinity are identified for simple spatial distributions of growth. Comparison with physical experiments indicates reasonable accuracy of the theoretical model. Some applications from modeling plant root growth to the design of soft manipulators in robotics are briefly discussed.

Keywords: buckling, elastica, friction, growth

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Authors: Golaleh Ghaffari

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A basin sediment yield refers to the amount of sediment exported by a basin over a period of time, which will enter a reservoir located at the downstream limit of the basin. The Soil and Water Assessment Tool (SWAT, 2008) was used to hydrology and sediment transport modeling at daily and monthly time steps within the Gheshlagh dam basin in north-west of Iran. The SWAT model and Geographic Information System (GIS) techniques were applied to evaluate basin hydrology and sediment yield using historical flow and sediment data and to identify and prioritize critical sub-basins based on sediment transport. The results of this study indicated that simulated daily discharge and sediment values matched the observed values satisfactorily. The model predicted that mean annual basin precipitation for the total study period (413 mm) was partitioned in to evapotranspiration (36%), percolation/groundwater recharge (21%) and stream water (25%), yielding 18% surface runoff. Potential source areas of erosion were also identified with the model. The range of the annual contributing erosive zones varied spatially from 0.1 to 103 t/ha according to the slope and land use at the basin scale. Also the fifteen sub basins create the 60% of the total sediment yield between the all (102) sub basins. The results of the study indicated that SWAT can be a useful tool for assessing hydrology and sediment yield response of the watersheds in the region.

Keywords: erosion, Gheshlagh dam, sediment yield, SWAT

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Authors: Mohammad Heidari

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In this paper a method for high strength steel is proposed of residual stresses in autofrettaged tubes by combination of artificial neural networks is presented. Many different thick walled cylinders that were subjected to different conditions were studied. At first, the residual stress is calculated by analytical solution. Then by changing of the parameters that influenced in residual stresses such as percentage of autofrettage, internal pressure, wall ratio of cylinder, material property of cylinder, bauschinger and hardening effect factor, a neural network is created. These parameters are the input of network. The output of network is residual stress. Numerical data, employed for training the network and capabilities of the model in predicting the residual stress has been verified. The output obtained from neural network model is compared with numerical results, and the amount of relative error has been calculated. Based on this verification error, it is shown that the radial basis function of neural network has the average error of 2.75% in predicting residual stress of thick wall cylinder. Further analysis of residual stress of thick wall cylinder under different input conditions has been investigated and comparison results of modeling with numerical considerations shows a good agreement, which also proves the feasibility and effectiveness of the adopted approach.

Keywords: thick walled cylinder, residual stress, radial basis, artificial neural network

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Authors: Dennis Okora Amima Ondieki

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Fertility transition has been identified to be affected by numerous factors. This research aimed to investigate the most real factors affecting fertility transition in Kenya. These factors were firstly extracted from the literature convened into demographic features, social, and economic features, social-cultural features, reproductive features and modernization features. All these factors had 23 factors identified for this study. The data for this study was from the Kenya Demographic and Health Surveys (KDHS) conducted in 1999-2003 and 2003-2008/9. The data was continuous, and it involved the mean birth order for the ten periods. Principal component analysis (PCA) was utilized using 23 factors. Principal component analysis conveyed religion, region, education and marital status as the real factors. PC scores were calculated for every point. The identified principal components were utilized as forecasters in the multiple regression model, with the fertility level as the response variable. The four components were found to be affecting fertility transition differently. It was found that fertility is affected positively by factors of region and marital and negatively by factors of religion and education. These four factors can be considered in the planning policy in Kenya and Africa at large.

Keywords: fertility transition, principal component analysis, Kenya demographic health survey, birth order

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Authors: Alvaro Jose Cordova, Hsuan Teh Hu

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The use of concrete masonry constructions in developing countries has become very frequent, especially for domestic purpose. Most of them with asymmetric wall configurations in plan resulting in significant torsional actions when subjected to seismic loads. The study consisted on the finding of a material model for hollow unreinforced concrete masonry and a validation with experimental data found in literature. Numerical simulations were performed to 20 buildings with variations in wall distributions and heights. Results were analyzed by inspection and with a non-linear static method. The findings revealed that eccentricities as well as structure rigidities have a strong influence on the overall response of concrete masonry buildings. In addition, slab rotations depicted more accurate information about the torsional behavior than maximum versus average displacement ratios. The failure modes in low buildings were characterized by high tensile strains in the first floor. Whereas in tall buildings these strains were lowered significantly by higher compression stresses due to a higher self-weight. These tall buildings developed multiple plastic hinges along the height. Finally, the non-linear static analysis exposed a brittle response for all masonry assemblies. This type of behavior is undesired in any construction and the need for a material model for reinforced masonry is pointed out.

Keywords: concrete damaged plasticity, concrete masonry, macro-modeling, nonlinear static analysis, torsional capacity

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Authors: Greg Turner, Bin Lu, Cheer-Sun Yang

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As computing technology advances, smartphone applications can assist in student learning in a pervasive way. For example, the idea of using a mobile apps for the PA Common Trees, Pests, Pathogens, in the field as a reference tool allows middle school students to learn about trees and associated pests/pathogens without bringing a textbook. In the past, some researches study the mobile software Mobile Application Software Development Life Cycle (MADLC) including traditional models such as the waterfall model, or more recent Agile Methods. Others study the issues related to the software development process. Very little research is on the development of three heterogenous mobile systems simultaneously in a small university where the availability of developers is an issue. In this paper, we propose to use a hybride model of Waterfall Model and the Agile Model, known as the Relay Race Methodology (RRM) in practice, to reflect the concept of racing and relaying for scheduling. Based on the development project, we observe that the modeling of the transition between any two phases is manifested naturally. Thus, we claim that the RRM model can provide a de fecto rather than a de jure basis for the core concept in the MADLC. In this paper, the background of the project is introduced first. Then, the challenges are pointed out followed by our solutions. Finally, the experiences learned and the future work are presented.

Keywords: agile methods, mobile apps, software process model, waterfall model

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Authors: Rômulo Eustáquio Martins de Souza, Paulo Alexandre Rodrigues de Vasconcelos Figueiredo

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In recent years, there has been a surge in interest in applying artificial intelligence techniques, particularly machine learning algorithms. Machine learning is a data-analysis technique that automates the creation of analytical models, making it especially useful for designing complex situations. As a result, this technology aids in reducing human intervention while producing accurate results. This methodology is also extensively used in aerospace engineering since this is a field that encompasses several high-complexity operations, such as rocket propulsion. Rocket propulsion is a high-risk operation in which engine failure could result in the loss of life. As a result, it is critical to use computational methods capable of precisely representing the spacecraft's analytical model to guarantee its security and operation. Thus, this paper describes the use of machine learning algorithms for rocket propulsion to aid the realization that this technique is an efficient way to deal with challenging and restrictive aerospace engineering activities. The paper focuses on three machine-learning-aided rocket propulsion applications: set-point control of an expander-bleed rocket engine, supersonic retro-propulsion of a small-scale rocket, and leak detection and isolation on rocket engine data. This paper describes the data-driven methods used for each implementation in depth and presents the obtained results.

Keywords: data analysis, modeling, machine learning, aerospace, rocket propulsion

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Authors: Justine Ugochukwu Osuagwu, Sazali Abd Wahab

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The performance and operation of NNPC have faced series of attacks by all stakeholders as many have observed lots of inefficiency not only on the part of the management but the staff. This has raised questions of whether their operations and performance are being seriously affected by lack of transformational leadership, and the political competition prevalent in the country. The author has applied the administrative leadership theory and institutional theory as a guide to this study and empirically relates such theories to the study. The study also has utilized the quantitative approach where questionnaires were distributed to 370 participants, and the correctly filled and returned questionnaires were used for the analysis using structural equation modeling. The path coefficient of transformational leadership to performance is strong and positive with β = 0.672; t-value = 14.245; p-value = 0.000. Also, the result found that political competition does not mediate the relationship between transformational leadership and performance of NNPC. (β = -0.008; t-value = -0.600; p- value > 0.05). However, the indirect path is all insignificant, meaning that transformational leadership has relationship with corporate performance.The study found that,while political competition does not serve as a mediator in the relationship between transformational leadership and corporate performance, these styles of leadership have a direct and positive impact on corporate performance. The direct relationship between transformational leadership and political competition was not discovered, despite the fact that political competition has a direct and significant impact, both positive and negative, on corporate performance. As a result, both political competition and transformational leadership have the potential to significantly alter corporate performance.

Keywords: performance, transformational leadership, political competition, corporation performance, Nigeria national petroleum corporation

Procedia PDF Downloads 126

Authors: Regina Chua

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To reduce the costs of re-fielding a large survey, a Random Forest classifier was applied to measure the accuracy of classifying individuals into their assigned segments with the fewest possible questions. Given a long survey, one needed to determine the most predictive ten or fewer questions that would accurately assign new individuals to custom segments. Furthermore, the solution needed to be quick in its classification and usable in non-Python environments. In this paper, a supervised Random Forest classifier was modeled on a dataset with 7,000 individuals, 60 questions, and 254 features. The Random Forest consisted of an iterative collection of individual decision trees that result in a predicted segment with robust precision and recall scores compared to a single tree. A random 70-30 stratified sampling for training the algorithm was used, and accuracy trade-offs at different depths for each segment were identified. Ultimately, the Random Forest classifier performed at 87% accuracy at a depth of 10 with 20 instead of 254 features and 10 instead of 60 questions. With an acceptable accuracy in prioritizing feature selection, new tools were developed for non-Python environments: a worksheet with a formulaic version of the algorithm and an embedded function to predict the segment of an individual in real-time. Random Forest was determined to be an optimal classification model by its feature selection, performance, processing speed, and flexible application in other environments.

Keywords: machine learning, supervised learning, data science, random forest, classification, prediction, predictive modeling

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Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

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Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

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Authors: M. Mohsin Munir, Taimoor Ahmad, Javed Munir, Usman Rashid

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Determination of maximum elevation of a flowing fluid due to sudden rejection of load in a hydropower facility is of great interest to hydraulic engineers to ensure safety of the hydraulic structures. Several mathematical models exist that employ one-dimensional modeling for the determination of surge but none of these perfectly simulate real-time circumstances. The paper envisages investigation of surge inception and propagation for a Low Head Hydropower project using Computational Fluid Dynamics (CFD) analysis on FLOW-3D software package. The fluid dynamic model utilizes its analysis for surge by employing Reynolds’ Averaged Navier-Stokes Equations (RANSE). The CFD model is designed for a case study at Taunsa hydropower Project in Pakistan. Various scenarios have run through the model keeping in view upstream boundary conditions. The prototype results were then compared with the results of physical model testing for the same scenarios. The results of the numerical model proved quite accurate coherence with the physical model testing and offers insight into phenomenon which are not apparent in physical model and shall be adopted in future for the similar low head projects limiting delays and cost incurred in the physical model testing.

Keywords: surge, FLOW-3D, numerical model, Taunsa, RANSE

Procedia PDF Downloads 364

Authors: Luís Miguel Cabeça Marques, Alberto Manuel Martinho Vale, José Pedro Miragaia Trancoso Vaz, Ana Sofia Baptista Fernandes, Rui Alexandre de Barros Coito, Tiago Miguel Prates da Costa

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The detection and localization of hidden radioactive sources are of significant importance in countering the illicit traffic of Special Nuclear Materials and other radioactive sources and materials. Radiation portal monitors are commonly used at airports, seaports, and international land borders for inspecting cargo and vehicles. However, these equipment can be expensive and are not available at all checkpoints. Consequently, the localization of SNM and other radioactive sources often relies on handheld equipment, which can be time-consuming. The current study presents the advantages of real-time analysis of gamma-ray count rate data from a mobile radiation detection system based on simulated data and field tests. The incorporation of profit functions and decision criteria to optimize the detection system's path significantly enhances the radiation field information and reduces survey time during cargo inspection. For source position estimation, a maximum likelihood estimation algorithm is employed, and confidence intervals are derived using the Fisher information. The study also explores the impact of uncertainties, baselines, and thresholds on the performance of the profit function. The proposed detection system, utilizing a plastic scintillator with silicon photomultiplier sensors, boasts several benefits, including cost-effectiveness, high geometric efficiency, compactness, and lightweight design. This versatility allows for seamless integration into any mobile platform, be it air, land, maritime, or hybrid, and it can also serve as a handheld device. Furthermore, integration of the detection system into drones, particularly multirotors, and its affordability enable the automation of source search and substantial reduction in survey time, particularly when deploying a fleet of drones. While the primary focus is on inspecting maritime container cargo, the methodologies explored in this research can be applied to the inspection of other infrastructures, such as nuclear facilities or vehicles.

Keywords: plastic scintillators, profit functions, path planning, gamma-ray detection, source localization, mobile radiation detection system, security scenario

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Authors: Zerzouri Nora, Benalia Nadia, Bensiali Nadia

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This paper presents a grid-connected wind power generation scheme using Doubly Fed Induction Generator (DFIG). This can supply power at constant voltage and constant frequency with the rotor speed varying. This makes it suitable for variable speed wind energy application. The DFIG system consists of wind turbine, asynchronous wound rotor induction generator, and inverter with Space Vector Modulation (SVM) controller. In which the stator is connected directly to the grid and the rotor winding is in interface with rotor converter and grid converter. The use of back-to-back SVM converter in the rotor circuit results in low distortion current, reactive power control and operate at variable speed. Mathematical modeling of the DFIG is done in order to analyze the performance of the systems and they are simulated using MATLAB. The simulation results for the system are obtained and hence it shows that the system can operate at variable speed with low harmonic current distortion. The objective is to track and extract maximum power from the wind energy system and transfer it to the grid for useful work.

Keywords: Doubly Fed Induction Generator, Wind Energy Conversion Systems, Space Vector Modulation, distortion harmonics

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Authors: Porntip Ruengtam

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This article is an extension of previous research presenting the relevant factors related to environmental perceptions, residential community, and the design of a healing environment, which have effects on the well-being and requirements of Thai elderly. Research methodology began with observations and interviews in three case studies in terms of the management processes and environment design of similar existing projects in Thailand. The interview results were taken to summarize with related theories and literature. A questionnaire survey was designed for data collection to confirm the factors of requirements in a residential community intended for the Thai elderly. A structural equation model (SEM) was formulated to explain the cause-effect factors for the requirements of a residential community for Thai elderly. The research revealed that the requirements of a residential community for Thai elderly were classified into three groups when utilizing a technique for exploratory factor analysis. The factors were comprised of (1) requirements for general facilities and activities, (2) requirements for facilities related to health and security, and (3) requirements for facilities related to physical exercise in the residential community. The results from the SEM showed the background of elderly people had a direct effect on their requirements for a residential community from various aspects. The results should lead to the formulation of policies for design and management of residential communities for the elderly in order to enhance quality of life as well as both the physical and mental health of the Thai elderly.

Keywords: elderly, environmental design, residential community, structural equation modeling

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Authors: Najrullah Khan, Athar Ali Khan

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The Topp-Leone distribution was introduced by Topp- Leone in 1955. In this paper, an attempt has been made to fit Topp-Leone Generalized exponential (TPGE) distribution. A real survival data set is used for illustrations. Implementation is done using R and JAGS and appropriate illustrations are made. R and JAGS codes have been provided to implement censoring mechanism using both optimization and simulation tools. The main aim of this paper is to describe and illustrate the Bayesian modelling approach to the analysis of survival data. Emphasis is placed on the modeling of data and the interpretation of the results. Crucial to this is an understanding of the nature of the incomplete or 'censored' data encountered. Analytic approximation and simulation tools are covered here, but most of the emphasis is on Markov chain based Monte Carlo method including independent Metropolis algorithm, which is currently the most popular technique. For analytic approximation, among various optimization algorithms and trust region method is found to be the best. In this paper, TPGE model is also used to analyze the lifetime data in Bayesian paradigm. Results are evaluated from the above mentioned real survival data set. The analytic approximation and simulation methods are implemented using some software packages. It is clear from our findings that simulation tools provide better results as compared to those obtained by asymptotic approximation.

Keywords: Bayesian Inference, JAGS, Laplace Approximation, LaplacesDemon, posterior, R Software, simulation

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Authors: Ashish Kumar Agrahari, Amit Kumar

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Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired clonal blood disorder that manifests with hemolytic anemia, thrombosis, and peripheral blood cytopenias. The disease is caused by the deficiency of two glycosylphosphatidylinositols (GPI)-anchored proteins (CD55 and CD59) in the hemopoietic stem cells. The deficiency of GPI-anchored proteins has been associated with the somatic mutations in phosphatidylinositol glycan class A (PIGA). However, the mutations that do not cause PNH is associated with the multiple congenital anomalies-hypotonia-seizures syndrome 2 (MCAHS2). To best of our knowledge, no computational study has been performed to explore the atomistic level impact of PIGA mutations on the structure and dynamics of the protein. In the current work, we are mainly interested to get insights into the molecular mechanism of PIGA mutations. In the initial step, we screened the most pathogenic mutations from the pool of publicly available mutations. Further, to get a better understanding, pathogenic mutations were mapped to the modeled structure and subjected to 50ns molecular dynamics simulation. Our computational study suggests that four mutations are highly vulnerable to altering the structural conformation and stability of the PIGA protein, which illustrates its association with PNH and MCAHS2 phenotype.

Keywords: homology modeling, molecular dynamics simulation, missense mutations PNH, MCAHS2, PIGA

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Authors: Amokrane Boufares, Elise Provost, Veronique Osswald, Pascal Clain, Anthony Delahaye, Laurence Fournaison, Didier Dalmazzone

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Gas hydrates have long been considered as problematic for flow assurance in natural gas and oil transportation. On the other hand, they are now seen as future promising materials for various applications (i.e. desalination of seawater, natural gas and hydrogen storage, gas sequestration, gas combustion separation and cold storage and transport). Nonetheless, a better understanding of the crystallization mechanism of gas hydrate and of their formation kinetics is still needed for a better comprehension and control of the process. To that purpose, measuring the real-time evolution of the dissolved gas concentration in the aqueous phase during hydrate formation is required. In this work, CO₂ hydrates were formed in a stirred reactor equipped with an Attenuated Total Reflection (ATR) probe coupled to a Fourier Transform InfraRed (FTIR) spectroscopy analyzer. A method was first developed to continuously measure in-situ the CO₂ concentration in the liquid phase during solubilization, supersaturation, hydrate crystallization and dissociation steps. Thereafter, the measured concentration data were compared with those of equilibrium concentrations. It was observed that the equilibrium is instantly reached in the liquid phase due to the fast consumption of dissolved gas by the hydrate crystallization. Consequently, it was shown that hydrate crystallization kinetics is limited by the gas transfer at the gas-liquid interface. Finally, we noticed that the liquid-hydrate equilibrium during the hydrate crystallization is governed by the temperature of the experiment under the tested conditions.

Keywords: gas hydrate, dissolved gas, crystallization, infrared spectroscopy

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Authors: F. Al-Mufadi, F. Djavanroodi

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During the last decade ultrafine grained (UFG) and nano-structured (NS) materials have experienced a rapid development. In this research work finite element analysis has been carried out to investigate the plastic strain distribution in equal channel angular process (ECAP). The magnitudes of standard deviation (S. D.) and inhomogeneity index (Ci) were compared for different ECAP passes. Verification of a three-dimensional finite element model was performed with experimental tests. Finally the mechanical property including impact energy of ultrafine grained pure commercially pure Aluminum produced by severe plastic deformation method has been examined. For this aim, equal channel angular pressing die with the channel angle, outer corner angle and channel diameter of 90°, 20° and 20 mm had been designed and manufactured. Commercial pure Aluminum billets were ECAPed up to four passes by route BC at the ambient temperature. The results indicated that there is a great improvement at the hardness measurement, yield strength and ultimate tensile strength after ECAP process. It is found that the magnitudes of HV reach 67 HV from 21 HV after the final stage of process. Also, about 330% and 285% enhancement at the YS and UTS values have been obtained after the fourth pass as compared to the as-received conditions, respectively. On the other hand, the elongation to failure and impact energy have been reduced by 23% and 50% after imposing four passes of ECAP process, respectively.

Keywords: SPD, ECAP, FEM, pure Al, mechanical properties

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Authors: M. Sreedhar Babu, Vishal Garg, S. B. Akella, Shibu Clement, N. K. S Rajan

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Producer gas is a biomass derived gaseous fuel which is extensively used in internal combustion engines for power generation application. Unlike the conventional hydrocarbon fuels (Gasoline and Natural gas), the combustion properties of producer gas fuel are much different. Therefore, setting of optimal spark time for efficient engine operation is required. Owing to the fluctuating tendency of producer gas composition during gasification process, the heat release patterns (dictating the power output and emissions) obtained are quite different from conventional fuels. It was found that, valve lift timing is yet another factor which influences the burn rate of producer gas fuel, and thus, the heat release rate of the engine. Therefore, the present study was motivated to estimate the influence of valve lift timing analytically (Wiebe model) on the burn rate of producer gas through curve fitting against experimentally obtained mass fraction burn curves of several producer gas compositions. Furthermore, Wiebe models are widely used in zero-dimensional codes for engine parametric studies and are quite popular. This study also addresses the influence of hydrogen and methane concentration of producer gas on combustion trends, which are known to cause dynamics in engine combustion.

Keywords: combustion duration (CD), crank angle (CA), mass fraction burnt (MFB), producer sas (PG), Wiebe Combustion Model (WCM), wide open throttle (WOT)

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