Search results for: atmospheric vortex engine

Authors: Sudha T., Naveen C.

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Dengue is a serious public health issue that causes significant annual economic and welfare burdens on nations. However, enhanced optimization techniques and quantitative modeling approaches can predict the incidence of dengue. By advocating for a data-driven approach, public health officials can make informed decisions, thereby improving the overall effectiveness of sudden disease outbreak control efforts. The National Oceanic and Atmospheric Administration and the Centers for Disease Control and Prevention are two of the U.S. Federal Government agencies from which this study uses environmental data. Based on environmental data that describe changes in temperature, precipitation, vegetation, and other factors known to affect dengue incidence, many predictive models are constructed that use different machine learning methods to estimate weekly dengue cases. The first step involves preparing the data, which includes handling outliers and missing values to make sure the data is prepared for subsequent processing and the creation of an accurate forecasting model. In the second phase, multiple feature selection procedures are applied using various machine learning models and optimization techniques. During the third phase of the research, machine learning models like the Huber Regressor, Support Vector Machine, Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR) are compared with several optimization techniques for feature selection, such as Harmony Search and Genetic Algorithm. In the fourth stage, the model's performance is evaluated using Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) as assistance. Selecting an optimization strategy with the least number of errors, lowest price, biggest productivity, or maximum potential results is the goal. In a variety of industries, including engineering, science, management, mathematics, finance, and medicine, optimization is widely employed. An effective optimization method based on harmony search and an integrated genetic algorithm is introduced for input feature selection, and it shows an important improvement in the model's predictive accuracy. The predictive models with Huber Regressor as the foundation perform the best for optimization and also prediction.

Keywords: deep learning model, dengue fever, prediction, optimization

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Authors: Pooja Verma, Rajnesh Tyagi, Sunil Mohan

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Al-Si alloys are widely used in various components such as liner-less engine blocks, piston, compressor bodies and pumps for automobile sector and aerospace industries due to their excellent combination of properties like low thermal expansion coefficient, low density, excellent wear resistance, high corrosion resistance, excellent cast ability, and high hardness. The low density and high hardness of primary Si phase results in significant reduction in density and improvement in wear resistance of hypereutectic Al-Si alloys. Keeping in view of the industrial importance of the alloys, hypereutectic Al-Si alloys containing 14, 16, 18 and 20 wt. % of Si were prepared in a resistance furnace using adequate amount of deoxidizer and degasser and their erosion behavior was evaluated by conducting tests at impingement angles of 30°, 60°, and 90° with an erodent discharge rate of 7.5 Hz, pressure 1 bar using erosion test rig. Microstructures of the cast alloys were examined using Optical microscopy (OM) and scanning electron microscopy (SEM) and the presence of Si particles was confirmed by x-ray diffractometer (XRD). The mechanical properties and hardness were measured using uniaxial tension tests at a strain rate of 10-3/s and Vickers hardness tester. Microstructures of the alloys and X-ray examination revealed the presence of primary and eutectic Si particles in the shape of cuboids or polyhedral and finer needles. Yield strength (YS), ultimate tensile strength (UTS), and uniform elongation of the hypereutectic Al-Si alloys were observed to increase with increasing content of Si. The optimal strength and ductility was observed for Al-20 wt. % Si alloy which is significantly higher than the Al-14 wt. % Si alloy. The increased hardness and the strength of the alloys with increasing amount of Si has been attributed presence of Si in the solid solution which creates strain, and this strain interacts with dislocations resulting in solid-solution strengthening. The interactions between distributed primary Si particles and dislocations also provide Orowan strengthening leading to increased strength. The steady state erosion rate was found to decrease with increasing angle of impact as well as Si content for all the alloys except at 900 where it was observed to increase with the increase in the Si content. The minimum erosion rate is observed in Al-20 wt. % Si alloy at 300 and 600 impingement angles because of its higher hardness in comparison to other alloys. However, at 90° impingement angle the wear rate for Al-20 wt. % Si alloy is found to be the minimum due to deformation, subsequent cracking and chipping off material.

Keywords: Al-Si alloy, erosion wear, cast alloys, dislocation, strengthening

Procedia PDF Downloads 49

Authors: José M. Liñeira Del Río, Ramón Rial, Khodor Nasser, María J.G. Guimarey

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The need to develop new lubricants that offer better anti-friction and anti-wear performance in internal combustion vehicles is one of the great challenges of lubrication in the automotive field. The addition of nanoparticles has emerged as a possible solution and, combined with the lubricating power of ionic liquids, may become one of the alternatives to reduce friction losses and wear of the contact surfaces in the conditions to which tribo-pairs are subjected, especially in the contact of the piston rings and the cylinder liner surface. In this study, the improvement in SAE 10W-40 engine oil tribological performance after the addition of magnesium oxide (MgO) nanoadditives and two different phosphonium-based ionic liquids (ILs) was investigated. The nanoparticle characterization was performed by means of transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FTIR), Raman spectroscopy, X-ray diffraction (XRD), and scanning electron microscopy (SEM). The tribological properties, friction coefficients and wear parameters of the formulated oil modified with 0.01 wt.% MgO and 1 wt.% ILs compared with the neat 10W-40 oil were performed and analyzed using a ball-on-three-pins tribometer and a 3D optical profilometer, respectively. Further analysis on the worn surface was carried out by Raman spectroscopy and SEM microscopy, illustrating the formation of the protective IL and MgO tribo-films as hybrid additives. In friction tests with sliding steel-steel tribo-pairs, IL3-based hybrid nanolubricant decreased the friction coefficient and wear volume by 7% and 59%, respectively, in comparison with the neat SAE 10W-40, while the one based on IL1 only achieved a reduction of these parameters by 6% and 39%, respectively. Thus, the tribological characterization also revealed that the MgO and IL3 addition has a positive synergy over the commercial lubricant, adequately meeting the requirements for their use in internal combustion engines. In summary, this study has shown that the addition of ionic liquids to MgO nanoparticles can improve the stability and lubrication behavior of MgO nanolubricant and encourages more investigations on using nanoparticle additives with green solvents such as ionic liquids to protect the environment as well as prolong the lifetime of machinery. The improvement in the lubricant properties was attributed to the following wear mechanisms: the formation of a protective tribo-film and the ability of nanoparticles to fill out valleys between asperities, thereby effectively smoothing out the shearing surfaces.

Keywords: lubricant, nanoparticles, phosphonium-based ionic liquids, tribology

Procedia PDF Downloads 69

Authors: Divyans Mahansaria

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User authentication is an important security measure for protecting confidential data and systems. However, the vulnerability while authenticating into a system has significantly increased. Thus, necessary mechanisms must be deployed during the process of authenticating a user to safeguard him/her from the vulnerable attacks. The proposed solution implements a novel authentication mechanism to counter various forms of security breach attacks including phishing, Trojan horse, replay, key logging, Asterisk logging, shoulder surfing, brute force search and others. QR code (Quick Response Code) is a type of matrix barcode or two-dimensional barcode that can be used for storing URLs, text, images and other information. In the proposed solution, during each new authentication request, a QR code is dynamically generated and presented to the user. A piece of generic information is mapped to plurality of elements and stored within the QR code. The mapping of generic information with plurality of elements, randomizes in each new login, and thus the QR code generated for each new authentication request is for one-time use only. In order to authenticate into the system, the user needs to decode the QR code using any QR code decoding software. The QR code decoding software needs to be installed on handheld mobile devices such as smartphones, personal digital assistant (PDA), etc. On decoding the QR code, the user will be presented a mapping between the generic piece of information and plurality of elements using which the user needs to derive cipher secret information corresponding to his/her actual password. Now, in place of the actual password, the user will use this cipher secret information to authenticate into the system. The authentication terminal will receive the cipher secret information and use a validation engine that will decipher the cipher secret information. If the entered secret information is correct, the user will be provided access to the system. Usability study has been carried out on the proposed solution, and the new authentication mechanism was found to be easy to learn and adapt. Mathematical analysis of the time taken to carry out brute force attack on the proposed solution has been carried out. The result of mathematical analysis showed that the solution is almost completely resistant to brute force attack. Today’s standard methods for authentication are subject to a wide variety of software, hardware, and human attacks. The proposed scheme can be very useful in controlling the various types of authentication related attacks especially in a networked computer environment where the use of username and password for authentication is common.

Keywords: authentication, QR code, cipher / decipher text, one time password, secret information

Procedia PDF Downloads 250

Authors: K. Volkonitskaya, S. Lyapina

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According to the National Monitoring Centre of innovation infrastructure, scientific and technical activities and regional innovation systems by December 2014. 166 technology parks were established in Russia. Comparative analysis of technological parks performance in Russia, the USA, Israel and the European Union countries revealed significant reduction of key performance indicators in Russian innovation infrastructure institutes. The largest deviations were determined in the following indicators: new products and services launched, number of companies and jobs, amount of venture capital invested. Lower performance indicators of Russian technology parks can be partly explained by slack demand for national high-tech products and services, lack of qualified specialists in the sphere of innovation management and insufficient cooperation between different innovation infrastructure institutes. In spite of all constraints in innovation segment of Russian economy in 2010-2012 private investors for the first time proceeded to finance building of technological parks. The general purpose of the research is to answer two questions: why despite the significant investment risks private investors continue to implement such comprehensive infrastructure projects in Russia and is business model of private technological park more efficient than strategies of state innovation infrastructure institutes? The goal of the research was achieved by analyzing business models of private technological parks in Moscow, Kaliningrad, Astrakhan and Kazan. The research was conducted in two stages: the on-line survey of key performance indicators of private and state Russian technological parks and in-depth interviews with top managers and investors, who have already build private technological parks in by 2014 or are going to complete investment stage in 2014-2016. The results anticipated are intended to identify the reasons of efficient and inefficient technological parks performance. Furthermore, recommendations for improving the efficiency of state technological and industrial parks were formulated. Particularly, the recommendations affect the following issues: networking with other infrastructural institutes, services and infrastructure provided, mechanisms of public-private partnership and investment attraction. In general intensive study of private technological parks performance and development of effective mechanisms of state support can have a positive impact on the growth rates of the number of Russian technological, industrial and science parks.

Keywords: innovation development, innovation infrastructure, private technology park, public-private partnership

Procedia PDF Downloads 413

Authors: Joudia Akil, Stephane Siffert, Laurence Pirault-Roy, Renaud Cousin, Christophe Poupin

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The CO2 emitted from anthropic activities is perceived as a constraint in industrial activity due to taxes, stringent environmental regulations, impact on global warming… To limit these CO2 emissions, reuse of CO2 represents a promising alternative, with important applications in chemical industry and for power generation. However, CO2 valorization process requires a gas as pure as possible Oxyfuel-combustion that enables obtaining a CO2 rich stream, with water vapor (10%) is then interesting. Nevertheless to decrease the amount of the by-products found with the CO2 (especially CO and NOx which are harmful to the environment) a catalytic treatment must be applied. Nowadays three-way catalysts are well-developed material for simultaneous conversion of unburned hydrocarbons, carbon monoxide (CO) and nitrogen oxides (NOx). The use of Pd attracted considerable attention on the basis of economic factors (the high cost and scarcity of Pt and Rh). This explains the large number of studies concerning the CO-NO reaction on Pd in the recent years. In the present study, we will compare a series of Pd materials supported on different oxides for CO2 purification from the oxyfuel combustion system, by reducing NO with CO in an oxidizing environment containing CO2 rich stream and presence of 8.2% of water. Al2O3, CeO2, MgO, SiO2 and TiO2 were used as support materials of the catalysts. 1wt% Pd/Support catalysts were obtained by wet impregnation on supports with a precursor of palladium [Pd(acac)2]. The obtained samples were subsequently characterized by H2 chemisorption, BET surface area and TEM. Finally, their catalytic performances were evaluated in CO2 purification which is carried out in a fixed-bed flow reactor containing 150 mg of catalyst at atmospheric pressure. The flow of the reactant gases is composed of: 20% CO2, 10% O2, 0.5% CO, 0.02% NO and 8.2% H2O (He as eluent gas) with a total flow of 200mL.min−1, in the same GHSV. The catalytic performance of the Pd catalysts for CO2 purification revealed that: -The support material has a strong influence on the catalytic activity of 1wt.% Pd supported catalysts. depending of the nature of support, the Pd-based catalysts activity changes. -The highest reduction of NO with CO is obtained in the following ranking: TiO2>CeO2>Al2O3. -The supports SiO2 and MgO should be avoided for this reaction, -Total oxidation of CO occurred over different materials, -CO2 purification can reach 97%, -The presence of H2O has a positive effect on the NO reduction due to the production of the reductant H2 from WGS reaction H2O+CO → H2+CO2

Keywords: carbon dioxide, environmental chemistry, heterogeneous catalysis, oxyfuel combustion

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Authors: Sven Borén, Lisiana Nurhadi, Henrik Ny

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From a theoretical perspective, electric buses can be more sustainable and can be cheaper than fossil fuelled buses in city traffic. The authors have not found other studies based on actual urban public transport in Swedish winter climate. Further on, noise measurements from buses for the European market were found old. The aims of this follow-up study was therefore to test and possibly verify in a real-life environment how energy efficient and silent electric buses are, and then conclude on if electric buses are preferable to use in public transport. The Ebusco 2.0 electric bus, fitted with a 311 kWh battery pack, was used and the tests were carried out during November 2014-April 2015 in eight municipalities in the south of Sweden. Six tests took place in urban traffic and two took place in more of a rural traffic setting. The energy use for propulsion was measured via logging of the internal system in the bus and via an external charging meter. The average energy use turned out to be 8% less (0,96 kWh/km) than assumed in the earlier theoretical study. This rate allows for a 320 km range in public urban traffic. The interior of the bus was kept warm by a diesel heater (biodiesel will probably be used in a future operational traffic situation), which used 0,67 kWh/km in January. This verified that electric buses can be up to 25% cheaper when used in public transport in cities for about eight years. The noise was found to be lower, primarily during acceleration, than for buses with combustion engines in urban bus traffic. According to our surveys, most passengers and drivers appreciated the silent and comfortable ride and preferred electric buses rather than combustion engine buses. Bus operators and passenger transport executives were also positive to start using electric buses for public transport. The operators did however point out that procurement processes need to account for eventual risks regarding this new technology, along with personnel education. The study revealed that it is possible to establish a charging infrastructure for almost all studied bus lines. However, design of a charging infrastructure for each municipality requires further investigations, including electric grid capacity analysis, smart location of charging points, and tailored schedules to allow fast charging. In conclusion, electric buses proved to be a preferable alternative for all stakeholders involved in public bus transport in the studied municipalities. However, in order to electric buses to be a prominent support for sustainable development, they need to be charged either by stand-alone units or via an expansion of the electric grid, and the electricity should be made from new renewable sources.

Keywords: sustainability, electric, bus, noise, greencharge

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Authors: Antonio Piga

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This study explores the correlation between Systemic Functional Linguistics (SFL) and Critical Discourse Analysis (CDA) as tools for analysing the evolution of rhetoric in the communicative strategies adopted in a company’s Reports on social and environmental responsibility. In more specific terms, transitivity and ergativity- concepts from Systemic Functional Linguistics (SFL) - through the lenses of CDA, are employed as a theoretical means for the analysis of a longitudinal study in the communicative strategies employed by Saras SpA pre- and during the Covid-19 pandemic crisis. Saras is an Italian joint-stock company operating in oil refining and power generation. The qualitative and quantitative linguistic analysis carried out through the use of Sketch Engine software aims to identify and explain how rhetoric - and ideology - is constructed and presented through language use in Saras SpA Sustainability Reports. Specific focus is given to communication strategies to local and global communities and stakeholders in the years immediately before and during the Covid-19 pandemic. The rationale behind the study lies in the fact that 2020 and 2021 have been among the most difficult years since the end of World War II. Lives were abruptly turned upside down by the pandemic, which had grave negative effects on people’s health and on the economy. The result has been a threefold crisis involving health, the economy and social tension, with the refining sector being one of the hardest hit, since the oil refining industry was one of the most affected industries due to the general reduction in mobility and oil consumption brought about by the virus-fighting measures. Emphasis is placed on the construction of rhetorical strategies pre- and during the pandemic crisis using the representational process of transitivity and ergativity (SFL), thus revealing the close relationship between the use language in terms of Social Actors and semantic roles of syntactic transformation on the one hand, and ideological assumptions on the other. The results show that linguistic decisions regarding transitivity and ergativity choices play a crucial role in how effective writing achieves its rhetorical objectives in terms of spreading and maintaining dominant and implicit ideologies and underlying persuasive actions, and that some ideological motivation is perpetuated – if not actually overtly or subtly strengthened - in social-environmental Reports issued in the midst of the Covid-19 pandemic crisis.

Keywords: systemic functional linguistics, sustainability, critical discourse analysis, transitivity, ergativity

Procedia PDF Downloads 87

Authors: Dipo Dunsin, Mohamed C. Ghanem, Karim Ouazzane

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Digital investigators often have a hard time spotting evidence in digital information. It has become hard to determine which source of proof relates to a specific investigation. A growing concern is that the various processes, technology, and specific procedures used in the digital investigation are not keeping up with criminal developments. Therefore, criminals are taking advantage of these weaknesses to commit further crimes. In digital forensics investigations, artificial intelligence is invaluable in identifying crime. It has been observed that an algorithm based on artificial intelligence (AI) is highly effective in detecting risks, preventing criminal activity, and forecasting illegal activity. Providing objective data and conducting an assessment is the goal of digital forensics and digital investigation, which will assist in developing a plausible theory that can be presented as evidence in court. Researchers and other authorities have used the available data as evidence in court to convict a person. This research paper aims at developing a multiagent framework for digital investigations using specific intelligent software agents (ISA). The agents communicate to address particular tasks jointly and keep the same objectives in mind during each task. The rules and knowledge contained within each agent are dependent on the investigation type. A criminal investigation is classified quickly and efficiently using the case-based reasoning (CBR) technique. The MADIK is implemented using the Java Agent Development Framework and implemented using Eclipse, Postgres repository, and a rule engine for agent reasoning. The proposed framework was tested using the Lone Wolf image files and datasets. Experiments were conducted using various sets of ISA and VMs. There was a significant reduction in the time taken for the Hash Set Agent to execute. As a result of loading the agents, 5 percent of the time was lost, as the File Path Agent prescribed deleting 1,510, while the Timeline Agent found multiple executable files. In comparison, the integrity check carried out on the Lone Wolf image file using a digital forensic tool kit took approximately 48 minutes (2,880 ms), whereas the MADIK framework accomplished this in 16 minutes (960 ms). The framework is integrated with Python, allowing for further integration of other digital forensic tools, such as AccessData Forensic Toolkit (FTK), Wireshark, Volatility, and Scapy.

Keywords: artificial intelligence, computer science, criminal investigation, digital forensics

Procedia PDF Downloads 188

Authors: Mokgadi Miranda Hlongwane, Ntebogeng Sharon Mokgalaka, Felix Dapare Dakora

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Lessertia (L.) frutescens (syn. Sutherlandia frutescens) is a leguminous medicinal plant indigenous to South Africa. Traditionally, L. frutescens has been used to treat cancer, diabetes, epilepsy, fever, HIV, stomach problems, wounds and other ailments. This legume is endemic to the Cape fynbos, with large populations occurring wild and cultivated in the Cape Florist Region. Its widespread distribution in the Western Cape, Northern Cape, Eastern Cape and Kwazulu-Natal is linked to its increased use as a phytomedicine in the treatment of various diseases by traditional healers. The frequent harvesting of field plants for use as a medicine has made it necessary to undertake studies towards the conservation of Lessertia frutescens. As a legume, this species can form root nodules and fix atmospheric N₂ when in symbiosis with soil bacteria called rhizobia. So far, however, few studies (if any) have been done on the efficacy and diversity of native bacterial symbionts nodulating L. frutescens in South Africa. The aim of this project was to isolate and characterize L. frutescens-nodulating bacteria from five different locations in the Western Cape Province. This was done by trapping soil rhizobia using rhizosphere soil suspension to inoculate L. frutescens seedlings growing in sterilized sand and receiving sterile N-free Hoagland nutrient solution under glasshouse conditions. At 60 days after planting, root nodules were harvested from L. frutescens plants, surface-sterilized, macerated, and streaked on yeast mannitol agar (YMA) plates and incubated at 28 ˚C for observation of bacterial growth. The majority of isolates were slow-growers that took 6-14 days to appear on YMA plates. However, seven isolates were fast-growers, taking 2-4 days to appear on YMA plates. Single-colony cultures of the isolates were assessed for their ability to nodulate L. frutescens as a homologous host under glasshouse conditions. Of the 92 bacterial isolates tested, 63 elicited nodule formation on L. frutescens. Symbiotic effectiveness varied markedly between and among test isolates. There were also significant (p≤0.005) differences in nodulation, shoot biomass, photosynthetic rates, leaf transpiration and stomatal conductance of L. frutescens plants inoculated with the test isolates, which is an indication of their functional diversity.

Keywords: lessertia frutescens, nodulating, rhizobia, symbiotic effectiveness

Procedia PDF Downloads 169

Authors: Sidharth Talan, Devendra Kumar Yadav, Yuvraj Singh Rajput, Subhajit Bhattacharjee

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Mining industry is known for its appetite to spend sizeable capital on mine equipment. However, in the current scenario, the mining industry is challenged by daunting factors of non-uniform geological conditions, uneven ore grade, uncontrollable and volatile mineral commodity prices and the ever increasing quest to optimize the capital and operational costs. Thus, the role of equipment reliability and maintenance planning inherits a significant role in augmenting the equipment availability for the operation and in turn boosting the mine productivity. This paper presents the Risk Based Maintenance (RBM) planning conducted on mine loading equipment namely Load Haul Dumpers (LHDs) at Vedanta Resources Ltd subsidiary Hindustan Zinc Limited operated Sindesar Khurd Mines, an underground zinc and lead mine situated in Dariba, Rajasthan, India. The mining equipment at the location is maintained by the Original Equipment Manufacturers (OEMs) namely Sandvik and Atlas Copco, who carry out the maintenance and inspection operations for the equipment. Based on the downtime data extracted for the equipment fleet over the period of 6 months spanning from 1^st January 2017 until 30^th June 2017, it was revealed that significant contribution of three downtime issues related to namely Engine, Hydraulics, and Transmission to be common among all the loading equipment fleet and substantiated by Pareto Analysis. Further scrutiny through Bubble Matrix Analysis of the given factors revealed the major influence of selective factors namely Overheating, No Load Taken (NTL) issues, Gear Changing issues and Hose Puncture and leakage issues. Utilizing the equipment wise analysis of all the downtime factors obtained, spares consumed, and the alarm logs extracted from the machines, technical design changes in the equipment and pre shift critical alarms checklist were proposed for the equipment maintenance. The given analysis is beneficial to allow OEMs or mine management to focus on the critical issues hampering the reliability of mine equipment and design necessary maintenance strategies to mitigate them.

Keywords: bubble matrix analysis, LHDs, OEMs, Pareto chart analysis, spares consumption matrix, critical alarms checklist

Procedia PDF Downloads 128

Authors: Basil Nkosilathi Dube, Wilson R. Nyemba, Panashe Mandevu

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In highway driving, over 50 percent of the power produced by the engine is used to overcome aerodynamic drag, which is a force that opposes a body’s motion through the air. Aerodynamic drag and thus fuel consumption increase rapidly at speeds above 90kph. It is desirable to minimize fuel consumption. Aerodynamic drag reduction in highway driving is the best approach to minimize fuel consumption and to reduce the negative impacts of greenhouse gas emissions on the natural environment. Fuel economy is the ultimate concern of automotive development. This study aims to design and analyze drag-reducing devices for a Mazda T3500 truck, namely, the cab roof and rear (trailer tail) fairings. The aerodynamic effects of adding these append devices were subsequently investigated. To accomplish this, two 3D CAD models of the Mazda truck were designed using the Design Modeler. One, with these, append devices and the other without. The models were exported to ANSYS Fluent for computational fluid dynamics analysis, no wind tunnel tests were performed. A fine mesh with more than 10 million cells was applied in the discretization of the models. The realizable k-ε turbulence model with enhanced wall treatment was used to solve the Reynold’s Averaged Navier-Stokes (RANS) equation. In order to simulate the highway driving conditions, the tests were simulated with a speed of 100 km/h. The effects of these devices were also investigated for low-speed driving. The drag coefficients for both models were obtained from the numerical calculations. By adding the cab roof and rear (trailer tail) fairings, the simulations show a significant reduction in aerodynamic drag at a higher speed. The results show that the greatest drag reduction is obtained when both devices are used. Visuals from post-processing show that the rear fairing minimized the low-pressure region at the rear of the trailer when moving at highway speed. The rear fairing achieved this by streamlining the turbulent airflow, thereby delaying airflow separation. For lower speeds, there were no significant differences in drag coefficients for both models (original and modified). The results show that these devices can be adopted for improving the aerodynamic efficiency of the Mazda T3500 truck at highway speeds.

Keywords: aerodynamic drag, computation fluid dynamics, fluent, fuel consumption

Procedia PDF Downloads 121

Authors: Adan Valdez, Shawn Gallaher, James Morison, Jordan Aragon

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Global climate change has impacted atmospheric temperatures contributing to rising sea levels, decreasing sea ice, and increased freshening of high latitude oceans. This freshening has contributed to increased stratification inhibiting local mixing and nutrient transport and modifying regional circulations in polar oceans. In recent years, the Western Arctic has seen an increase in freshwater volume at an average rate of 397+-116 km3/year. The majority of the freshwater volume resides in the Beaufort Gyre surface lens driven by anticyclonic wind forcing, sea ice melt, and Arctic river runoff. The total climatological freshwater content is typically defined as water fresher than 34.8. The near-isothermal nature of Arctic seawater and non-linearities in the equation of state for near-freezing waters result in a salinity driven pycnocline as opposed to the temperature driven density structure seen in the lower latitudes. In this study, we investigate the relationship between freshwater content and remotely sensed dynamic ocean topography (DOT). In-situ measurements of freshwater content are useful in providing information on the freshening rate of the Beaufort Gyre; however, their collection is costly and time consuming. NASA’s Advanced Topographic Laser Altimeter System (ATLAS) derived dynamic ocean topography (DOT), and Air Expendable CTD (AXCTD) derived Freshwater Content are used to develop a linear regression model. In-situ data for the regression model is collected across the 150° West meridian, which typically defines the centerline of the Beaufort Gyre. Two freshwater content models are determined by integrating the freshwater volume between the surface and an isopycnal corresponding to reference salinities of 28.7 and 34.8. These salinities correspond to those of the winter pycnocline and total climatological freshwater content, respectively. Using each model, we determine the strength of the linear relationship between freshwater content and satellite derived DOT. The result of this modeling study could provide a future predictive capability of freshwater volume changes in the Beaufort-Chukchi Sea using non in-situ methods. Successful employment of the ICESat-2’s DOT approximation of freshwater content could potentially reduce reliance on field deployment platforms to characterize physical ocean properties.

Keywords: ICESat-2, dynamic ocean topography, freshwater content, beaufort gyre

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Authors: Furkan Ozkan, M. Selcuk Arslan, Hatice Mercan

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Electric vehicles are becoming increasingly popular asa sustainable alternative to traditional combustion engine vehicles. However, to fully realize the potential of EVs in reducing environmental impact and energy consumption, efficient control strategies are essential. This study explores the application of green wave control using model predictive control for electric vehicles, coupled with energy consumption modeling using neural networks. The use of MPC allows for real-time optimization of the vehicles’ energy consumption while considering dynamic traffic conditions. By leveraging neural networks for energy consumption modeling, the EV's performance can be further enhanced through accurate predictions and adaptive control. The integration of these advanced control and modeling techniques aims to maximize energy efficiency and range while navigating urban traffic scenarios. The findings of this research offer valuable insights into the potential of green wave control for electric vehicles and demonstrate the significance of integrating MPC and neural network modeling for optimizing energy consumption. This work contributes to the advancement of sustainable transportation systems and the widespread adoption of electric vehicles. To evaluate the effectiveness of the green wave control strategy in real-world urban environments, extensive simulations were conducted using a high-fidelity vehicle model and realistic traffic scenarios. The results indicate that the integration of model predictive control and energy consumption modeling with neural networks had a significant impact on the energy efficiency and range of electric vehicles. Through the use of MPC, the electric vehicle was able to adapt its speed and acceleration profile in realtime to optimize energy consumption while maintaining travel time objectives. The neural network-based energy consumption modeling provided accurate predictions, enabling the vehicle to anticipate and respond to variations in traffic flow, further enhancing energy efficiency and range. Furthermore, the study revealed that the green wave control strategy not only reduced energy consumption but also improved the overall driving experience by minimizing abrupt acceleration and deceleration, leading to a smoother and more comfortable ride for passengers. These results demonstrate the potential for green wave control to revolutionize urban transportation by enhancing the performance of electric vehicles and contributing to a more sustainable and efficient mobility ecosystem.

Keywords: electric vehicles, energy efficiency, green wave control, model predictive control, neural networks

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Authors: Mariya V. Yanyukina, Michael A. Bolotov

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Assembling accuracy is the degree of accordance between the actual values of the parameters obtained during assembly, and the values specified in the assembly drawings and technical specifications. However, the assembling accuracy depends not only on the quality of the production process but also on the correctness of the assembly process. Therefore, preliminary calculations of assembly stages are carried out to verify the correspondence of real geometric parameters to their acceptable values. In the aviation industry, most calculations involve interacting dimensional chains. This greatly complicates the task. Solving such problems requires a special approach. The purpose of this article is to carry out the problem of improving the technology of assembly of aviation units by use of computer calculations. One of the actual examples of the assembly unit, in which there is an interacting dimensional chain, is the turbine wheel of gas turbine engine. Dimensional chain of turbine wheel is formed by geometric parameters of disk and set of blades. The interaction of the dimensional chain consists in the formation of two chains. The first chain is formed by the dimensions that determine the location of the grooves for the installation of the blades, and the dimensions of the blade roots. The second dimensional chain is formed by the dimensions of the airfoil shroud platform. The interaction of the dimensional chain of the turbine wheel is the interdependence of the first and second chains by means of power circuits formed by a plurality of middle parts of the turbine blades. The timeliness of the calculation of the dimensional chain of the turbine wheel is the need to improve the technology of assembly of this unit. The task at hand contains geometric and mathematical components; therefore, its solution can be implemented following the algorithm: 1) research and analysis of production errors by geometric parameters; 2) development of a parametric model in the CAD system; 3) creation of set of CAD-models of details taking into account actual or generalized distributions of errors of geometrical parameters; 4) calculation model in the CAE-system, loading of various combinations of models of parts; 5) the accumulation of statistics and analysis. The main task is to pre-simulate the assembly process by calculating the interacting dimensional chains. The article describes the approach to the solution from the point of view of mathematical statistics, implemented in the software package Matlab. Within the framework of the study, there are data on the measurement of the components of the turbine wheel-blades and disks, as a result of which it is expected that the assembly process of the unit will be optimized by solving dimensional chains.

Keywords: accuracy, assembly, interacting dimension chains, turbine

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Authors: Erin M. Durke, Monica L. McEntee, Meilu He, Suresh Dhaniyala

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Aerosols are one of the most important and significant surfaces in the atmosphere. They can influence weather, absorption, and reflection of light, and reactivity of atmospheric constituents. A notable feature of aerosol particles is the presence of a surface charge, a characteristic imparted via the aerosolization process. The existence of charge can complicate the interrogation of aerosol particles, so many researchers remove or neutralize aerosol particles before characterization. However, the charge is present in real-world samples, and likely has an effect on the physical and chemical properties of an aerosolized material. In our studies, we aerosolized different materials in an attempt to characterize the charge imparted via the aerosolization process and determine what impact it has on the aerosolized materials’ properties. The metal oxides, TiO₂ and SiO₂, were aerosolized expulsively and then characterized, using several different techniques, in an effort to determine the surface charge imparted upon the particles via the aerosolization process. Particle charge distribution measurements were conducted via the employment of a custom scanning mobility particle sizer. The results of the charge distribution measurements indicated that expulsive generation of 0.2 µm SiO₂ particles produced aerosols with upwards of 30+ charges on the surface of the particle. Determination of the degree of surface charging led to the use of non-traditional techniques to explore the impact of additional surface charge on the overall reactivity of the metal oxides, specifically TiO₂. TiO₂ was aerosolized, again expulsively, onto a gold-coated tungsten mesh, which was then evaluated with transmission infrared spectroscopy in an ultra-high vacuum environment. The TiO₂ aerosols were exposed to O₂, H₂, and CO, respectively. Exposure to O₂ resulted in a decrease in the overall baseline of the aerosol spectrum, suggesting O₂ removed some of the surface charge imparted during aerosolization. Upon exposure to H₂, there was no observable rise in the baseline of the IR spectrum, as is typically seen for TiO₂, due to the population of electrons into the shallow trapped states and subsequent promotion of the electrons into the conduction band. This result suggests that the additional charge imparted via aerosolization fills the trapped states, therefore no rise is seen upon exposure to H₂. Dosing the TiO₂ aerosols with CO showed no adsorption of CO on the surface, even at lower temperatures (~100 K), indicating the additional charge on the aerosol surface prevents the CO molecules from adsorbing to the TiO₂ surface. The results observed during exposure suggest that the additional charge imparted via aerosolization impacts the interaction with each probe gas.

Keywords: aerosols, charge, reactivity, infrared

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Authors: James Rate, Apostolos Pesiridis

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In this paper, the propulsion requirements required to achieve sustained hypersonic flight for commercial air transportation are evaluated. In addition, a design methodology is developed and used to determine the propulsive capabilities of both ramjet and scramjet engines. Twelve configurations are proposed for hypersonic flight using varying combinations of turbojet, turbofan, ramjet and scramjet engines. The optimal configuration was determined based on how well each of the configurations met the projected requirements for hypersonic commercial transport. The configurations were separated into four sub-configurations each comprising of three unique derivations. The first sub-configuration comprised four afterburning turbojets and either one or two ramjets idealised for Mach 5 cruise. The number of ramjets required was dependent on the thrust required to accelerate the vehicle from a speed where the turbojets cut out to Mach 5 cruise. The second comprised four afterburning turbojets and either one or two scramjets, similar to the first configuration. The third used four turbojets, one scramjet and one ramjet to aid acceleration from Mach 3 to Mach 5. The fourth configuration was the same as the third, but instead of turbojets, it implemented turbofan engines for the preliminary acceleration of the vehicle. From calculations which determined the fuel consumption at incremental Mach numbers this paper found that the ideal solution would require four turbojet engines and two Scramjet engines. The ideal mission profile was determined as being an 8000km sortie based on an averaging of popular long haul flights with strong business ties, which included Los Angeles to Tokyo, London to New York and Dubai to Beijing. This paper deemed that these routes would benefit from hypersonic transport links based on the previously mentioned factors. This paper has found that this configuration would be sufficient for the 8000km flight to be completed in approximately two and a half hours and would consume less fuel than Concord in doing so. However, this propulsion configuration still result in a greater fuel cost than a conventional passenger. In this regard, this investigation contributes towards the specification of the engine requirements throughout a mission profile for a hypersonic passenger vehicle. A number of assumptions have had to be made for this theoretical approach but the authors believe that this investigation lays the groundwork for appropriate framing of the propulsion requirements for sustained hypersonic flight for commercial air transportation. Despite this, it does serve as a crucial step in the development of the propulsion systems required for hypersonic commercial air transportation. This paper provides a methodology and a focus for the development of the propulsion systems that would be required for sustained hypersonic flight for commercial air transportation.

Keywords: hypersonic, ramjet, propulsion, Scramjet, Turbojet, turbofan

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Authors: Benedictus Asriparusa, Lathifah Al Hakimi, Aulia Husada

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A large amount of energy is being wasted by the release of natural gas associated with the oil industry. This release interrupts the environment particularly atmosphere layer condition globally which contributes to global warming impact. This research presents an overview of the methods employed by researchers in PT. Chevron Pacific Indonesia in the Minas area to determine a new prediction method of measuring and reducing gas flaring and its emission. The method emphasizes advanced research which involved analytical studies, numerical studies, modeling, and computer simulations, amongst other techniques. A flaring system is the controlled burning of natural gas in the course of routine oil and gas production operations. This burning occurs at the end of a flare stack or boom. The combustion process releases emissions of greenhouse gases such as NO2, CO2, SO2, etc. This condition will affect the chemical composition of air and environment around the boundary layer mainly during transition season. Transition season in Indonesia is absolutely very difficult condition to predict its pattern caused by the difference of two air mass conditions. This paper research focused on transition season in 2013. A simulation to create the new pattern of the pollutants distribution is needed. This paper has outlines trends in gas flaring modeling and current developments to predict the dominant variables in the pollutants distribution. A Fluent model is used to simulate the distribution of pollutants gas coming out of the stack, whereas WRF model output is used to overcome the limitations of the analysis of meteorological data and atmospheric conditions in the study area. Based on the running model, the most influence factor was wind speed. The goal of the simulation is to predict the new pattern based on the time of fastest wind and slowest wind occurs for pollutants distribution. According to the simulation results, it can be seen that the fastest wind (last of March) moves pollutants in a horizontal direction and the slowest wind (middle of May) moves pollutants vertically. Besides, the design of flare stack in compliance according to EPA Oil and Gas Facility Stack Parameters likely shows pollutants concentration remains on the under threshold NAAQS (National Ambient Air Quality Standards).

Keywords: flare motion, new prediction, pollutants distribution, transition season, WRF model

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Authors: Francesco Lubrano, Fabrizio Bertone, Federico Stirano

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Modern societies strongly depend on Critical Infrastructures (CI). Hospitals, power supplies, water supplies, telecommunications are just few examples of CIs that provide vital functions to societies. CIs like hospitals are very complex environments, characterized by a huge number of cyber and physical systems that are becoming increasingly integrated. Ensuring a high level of security within such critical infrastructure requires a deep knowledge of vulnerabilities, threats, and potential attacks that may occur, as well as defence and prevention or mitigation strategies. The possibility to remotely monitor and control almost everything is pushing the adoption of network-connected devices. This implicitly introduces new threats and potential vulnerabilities, posing a risk, especially to those devices connected to the Internet. Modern medical devices used in hospitals are not an exception and are more and more being connected to enhance their functionalities and easing the management. Moreover, hospitals are environments with high flows of people, that are difficult to monitor and can somehow easily have access to the same places used by the staff, potentially creating damages. It is therefore clear that physical and cyber threats should be considered, analysed, and treated together as cyber-physical threats. This means that an integrated approach is required. SAFECARE, an integrated cyber-physical security solution, tries to respond to the presented issues within healthcare infrastructures. The challenge is to bring together the most advanced technologies from the physical and cyber security spheres, to achieve a global optimum for systemic security and for the management of combined cyber and physical threats and incidents and their interconnections. Moreover, potential impacts and cascading effects are evaluated through impact propagation models that rely on modular ontologies and a rule-based engine. Indeed, SAFECARE architecture foresees i) a macroblock related to cyber security field, where innovative tools are deployed to monitor network traffic, systems and medical devices; ii) a physical security macroblock, where video management systems are coupled with access control management, building management systems and innovative AI algorithms to detect behavior anomalies; iii) an integration system that collects all the incoming incidents, simulating their potential cascading effects, providing alerts and updated information regarding assets availability.

Keywords: cyber security, defence strategies, impact propagation, integrated security, physical security

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Authors: Emmanuel Ophel Gilbert, Williams Speret

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The control for fluid flow behaviours of viscous fluids and heat transfer occurrences within heated mini-channel is considered. Heat transfer and flow characteristics of different viscous liquids, such as engine oil, automatic transmission fluid, one-half ethylene glycol, and deionized water were numerically analyzed. Some mathematical applications such as Fourier series and Laplace Z-Transforms were employed to ascertain the behaviour-wave like structure of these each viscous fluids. The steady, laminar flow and heat transfer equations are reckoned by the aid of numerical simulation technique. Further, this numerical simulation technique is endorsed by using the accessible practical values in comparison with the anticipated local thermal resistances. However, the roughness of this mini-channel that is one of the physical limitations was also predicted in this study. This affects the frictional factor. When an additive such as tetracycline was introduced in the fluid, the heat input was lowered, and this caused pro rata effect on the minor and major frictional losses, mostly at a very minute Reynolds number circa 60-80. At this ascertained lower value of Reynolds numbers, there exists decrease in the viscosity and minute frictional losses as a result of the temperature of these viscous liquids been increased. It is inferred that the three equations and models are identified which supported the numerical simulation via interpolation and integration of the variables extended to the walls of the mini-channel, yields the utmost reliance for engineering and technology calculations for turbulence impacting jets in the near imminent age. Out of reasoning with a true equation that could support this control for the fluid flow, Navier-stokes equations were found to tangential to this finding. Though, other physical factors with respect to these Navier-stokes equations are required to be checkmated to avoid uncertain turbulence of the fluid flow. This paradox is resolved within the framework of continuum mechanics using the classical slip condition and an iteration scheme via numerical simulation method that takes into account certain terms in the full Navier-Stokes equations. However, this resulted in dropping out in the approximation of certain assumptions. Concrete questions raised in the main body of the work are sightseen further in the appendices.

Keywords: frictional losses, heat transfer, laminar flow, mini-channel, number simulation, Reynolds number, turbulence, viscous fluids

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Authors: Ray Bryant

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3Strands Global Foundation (3SGF), a non-profit with a mission to mobilize communities to combat human trafficking through prevention education and reintegration programs, launched a groundbreaking study that calls out the usage and benefits of artificial intelligence in the war against human trafficking. Having gathered more than 30,000 stories from counselors and school staff who have gone through its PROTECT Prevention Education program, 3SGF sought to develop a methodology to measure the effectiveness of the training, which helps educators and school staff identify physical signs and behaviors indicating a student is being victimized. The program further illustrates how to recognize and respond to trauma and teaches the steps to take to report human trafficking, as well as how to connect victims with the proper professionals. 3SGF partnered with Levity, a leader in no-code Artificial Intelligence (AI) automation, to create the research study utilizing natural language processing, a branch of artificial intelligence, to measure the effectiveness of their prevention education program. By applying the logic created for the study, the platform analyzed and categorized each story. If the story, directly from the educator, demonstrated one or more of the desired outcomes; Increased Awareness, Increased Knowledge, or Intended Behavior Change, a label was applied. The system then added a confidence level for each identified label. The study results were generated with a 99% confidence level. Preliminary results show that of the 30,000 stories gathered, it became overwhelmingly clear that a significant majority of the participants now have increased awareness of the issue, demonstrated better knowledge of how to help prevent the crime, and expressed an intention to change how they approach what they do daily. In addition, it was observed that approximately 30% of the stories involved comments by educators expressing they wish they’d had this knowledge sooner as they can think of many students they would have been able to help. Objectives Of Research: To solve the problem of needing to analyze and accurately categorize more than 30,000 data points of participant feedback in order to evaluate the success of a human trafficking prevention program by using AI and Natural Language Processing. Methodologies Used: In conjunction with our strategic partner, Levity, we have created our own NLP analysis engine specific to our problem. Contributions To Research: The intersection of AI and human rights and how to utilize technology to combat human trafficking.

Keywords: AI, technology, human trafficking, prevention

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Authors: Benoît Mary, Thibaut Gras, Gaëtan Fagot, Yvon Goth, Ilyes Mnassri-Cetim

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A Gerotor pump is composed of an external and internal gear with conjugate cycloidal profiles. From suction to delivery ports, the fluid is transported inside cavities formed by teeth and driven by the shaft. From a geometric and conceptional side it is worth to note that the internal gear has one tooth less than the external one. Simcenter Amesim v.16 includes a new submodel for modelling the hydraulic Gerotor pumps behavior (THCDGP0). This submodel considers leakages between teeth tips using Poiseuille and Couette flows contributions. From the 3D CAD model of the studied pump, the “CAD import” tool takes out the main geometrical characteristics and the submodel THCDGP0 computes the evolution of each cavity volume and their relative position according to the suction or delivery areas. This module, based on international publications, presents robust results up to 6 000 rpm for pressure greater than atmospheric level. For higher rotational speeds or lower pressures, oil aeration and cavitation effects are significant and highly drop the pump’s performance. The liquid used in hydraulic systems always contains some gas, which is dissolved in the liquid at high pressure and tends to be released in a free form (i.e. undissolved as bubbles) when pressure drops. In addition to gas release and dissolution, the liquid itself may vaporize due to cavitation. To model the relative density of the equivalent fluid, modified Henry’s law is applied in Simcenter Amesim v.16 to predict the fraction of undissolved gas or vapor. Three parietal pressure sensors have been set up upstream from the pump to estimate the sound speed in the oil. Analytical models have been compared with the experimental sound speed to estimate the occluded gas content. Simcenter Amesim v.16 model was supplied by these previous analyses marks which have successfully improved the simulations results up to 14 000 rpm. This work provides a sound foundation for designing the next Gerotor pump generation reaching high rotation range more than 25 000 rpm. This improved module results will be compared to tests on this new pump demonstrator.

Keywords: gerotor pump, high speed, numerical simulations, aeronautic, aeration, cavitation

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Authors: Sunghun Jung, Wonkook Kim

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Due to the difficulty of the utilization of satellite and an aircraft, conventional ocean color remote sensing has a disadvantage in that it is difficult to obtain images of desired places at desired times. These disadvantages make it difficult to capture the anomalies such as the occurrence of the red tide which requires immediate observation. It is also difficult to understand the phenomena such as the resuspension-precipitation process of suspended solids and the spread of low-salinity water originating in the coastal areas. For the remote sensing reflectance of seawater, above-water radiometers (AWR) have been used either by carrying portable AWRs on a ship or installing those at fixed observation points on the Ieodo ocean research station, Socheongcho base, and etc. In particular, however, it requires the high cost to measure the remote reflectance in various seawater environments at various times and it is even not possible to measure it at the desired frequency in the desired sea area at the desired time. Also, in case of the stationary observation, it is advantageous that observation data is continuously obtained, but there is the disadvantage that data of various sea areas cannot be obtained. It is possible to instantly capture various marine phenomena occurring on the coast using the unmanned aerial system (UAS) including vertical takeoff and landing (VTOL) type unmanned aerial vehicles (UAV) since it could move and hover at the one location and acquire data of the desired form at a high resolution. To remotely estimate seawater constituents, it is necessary to install an ultra-spectral sensor. Also, to calculate reflected light from the surface of the sea in consideration of the sun’s incident light, a total of three sensors need to be installed on the UAV. The remote sensing reflectance of seawater is the most basic optical property for remotely estimating color components in seawater and we could remotely estimate the chlorophyll concentration, the suspended solids concentration, and the dissolved organic amount. Estimating seawater physics from the remote sensing reflectance requires the algorithm development using the accumulation data of seawater reflectivity under various seawater and atmospheric conditions. The UAS with three AWRs is developed for the remote reflection sensing on the surface of the sea. Throughout the paper, we explain the details of each UAS component, system operation scenarios, and simulation and experiment results. The UAS consists of a UAV, a solar tracker, a transmitter, a ground control station (GCS), three AWRs, and two gimbals.

Keywords: above-water radiometers (AWR), ground control station (GCS), unmanned aerial system (UAS), unmanned aerial vehicle (UAV)

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Authors: Yunha Ryu, Kyoungsik Kim

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Raman spectroscopy is one of the most powerful techniques for chemical detection, but the low sensitivity originated from the extremely small cross-section of the Raman scattering limits the practical use of Raman spectroscopy. To overcome this problem, Surface Enhanced Raman Scattering (SERS) has been intensively studied for several decades. Because the SERS effect is mainly induced from strong electromagnetic near-field enhancement as a result of localized surface plasmon resonance of metallic nanostructures, it is important to design the plasmonic structures with high density of electromagnetic hot spots for SERS substrate. One of the useful fabrication methods is using porous nanomaterial as a template for metallic structure. Internal pores on a scale of tens of nanometers can be strong EM hotspots by confining the incident light. Also, porous structures can capture more target molecules than non-porous structures in a same detection spot thanks to the large surface area. Herein we report the facile fabrication method of porous SERS substrate by integrating solvent-assisted nanoimprint lithography and selective etching of block copolymer. We obtained nanostructures with high porosity via simple selective etching of the one microdomain of the diblock copolymer. Furthermore, we imprinted of the nanocone patterns into the spin-coated flat block copolymer film to make three-dimensional SERS substrate for the high density of SERS hot spots as well as large surface area. We used solvent-assisted nanoimprint lithography (SAIL) to reduce the fabrication time and cost for patterning BCP film by taking advantage of a solvent which dissolves both polystyrenre and poly(methyl methacrylate) domain of the block copolymer, and thus block copolymer film was molded under the low temperature and atmospheric pressure in a short time. After Ag deposition, we measured Raman intensity of dye molecules adsorbed on the fabricated structure. Compared to the Raman signals of Ag coated solid nanocone, porous nanocone showed 10 times higher Raman intensity at 1510 cm(-1) band. In conclusion, we fabricated porous metallic nanocone arrays with high density electromagnetic hotspots by templating nanoimprinted diblock copolymer with selective etching and demonstrated its capability as an effective SERS substrate.

Keywords: block copolymer, porous nanostructure, solvent-assisted nanoimprint, surface-enhanced Raman spectroscopy

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Authors: Veslava Osinska, Adam Szalach, Dominik Piotrowski

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Contemporary VR technologies allow users to explore virtual 3D spaces where they can work, socialize, learn, and play. User's interaction with GUI and the pictures displayed implicate perceptual and also cognitive processes which can be monitored due to neuroadaptive technologies. These modalities provide valuable information about the users' intentions, situational interpretations, and emotional states, to adapt an application or interface accordingly. Virtual galleries outfitted by specialized assets have been designed using the Unity engine BITSCOPE project in the frame of CHIST-ERA IV program. Users interaction with gallery objects implies the questions about his/her visual interests in art works and styles. Moreover, an attention, curiosity, and other emotional states are possible to be monitored and analyzed. Natural gaze behavior data and eye position were recorded by built-in eye-tracking module within HTC Vive headset gogle for VR. Eye gaze results are grouped due to various users’ behavior schemes and the appropriate perpetual-cognitive styles are recognized. Parallelly usability tests and surveys were adapted to identify the basic features of a user-centered interface for the virtual environments across most of the timeline of the project. A total of sixty participants were selected from the distinct faculties of University and secondary schools. Users’ primary knowledge about art and was evaluated during pretest and this way the level of art sensitivity was described. Data were collected during two months. Each participant gave written informed consent before participation. In data analysis reducing the high-dimensional data into a relatively low-dimensional subspace ta non linear algorithms were used such as multidimensional scaling and novel technique technique t-Stochastic Neighbor Embedding. This way it can classify digital art objects by multi modal time characteristics of eye tracking measures and reveal signatures describing selected artworks. Current research establishes the optimal place on aesthetic-utility scale because contemporary interfaces of most applications require to be designed in both functional and aesthetical ways. The study concerns also an analysis of visual experience for subsamples of visitors, differentiated, e.g., in terms of frequency of museum visits, cultural interests. Eye tracking data may also show how to better allocate artefacts and paintings or increase their visibility when possible.

Keywords: eye tracking, VR, UX, visual art, virtual gallery, visual communication

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Authors: Zavkiddin Mirtoshev, Mirabbos Mirkamalov

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We have analyzed the time series of full disk integrated soft X-ray (SXR) and hard X-ray (HXR) emission from the solar corona during 2004 January 1 to 2009 December 31, covering the descending phase of solar cycle 23. We employed the daily X-ray index (DXI) derived from X-ray observations from the Solar X-ray Spectrometer (SOXS) mission in four different energy bands: 4-5.5; 5.5-7.5 keV (SXR) and 15-20; 20-25 keV (HXR). The application of Lomb-Scargle periodogram technique to the DXI time series observed by the Silicium detector in the energy bands reveals several short and intermediate periodicities of the X-ray corona. The DXI explicitly show the periods of 13.6 days, 26.7 days, 128.5 days, 151 days, 180 days, 220 days, 270 days, 1.24 year and 1.54 year periods in SXR as well as in HXR energy bands. Although all periods are above 70% confidence level in all energy bands, they show strong power in HXR emission in comparison to SXR emission. These periods are distinctly clear in three bands but somehow not unambiguously clear in 5.5-7.5 keV band. This might be due to the presence of Ferrum and Ferrum/Niccolum line features, which frequently vary with small scale flares like micro-flares. The regular 27-day rotation and 13.5 day period of sunspots from the invisible side of the Sun are found stronger in HXR band relative to SXR band. However, flare activity Rieger periods (150 and 180 days) and near Rieger period 220 days are very strong in HXR emission which is very much expected. On the other hand, our current study reveals strong 270 day periodicity in SXR emission which may be connected with tachocline, similar to a fundamental rotation period of the Sun. The 1.24 year and 1.54 year periodicities, represented from the present research work, are well observable in both SXR as well as in HXR channels. These long-term periodicities must also have connection with tachocline and should be regarded as a consequence of variation in rotational modulation over long time scales. The 1.24 year and 1.54 year periods are also found great importance and significance in the life formation and it evolution on the Earth, and therefore they also have great astro-biological importance. We gratefully acknowledge support by the Indian Centre for Space Science and Technology Education in Asia and the Pacific (CSSTEAP, the Centre is affiliated to the United Nations), Physical Research Laboratory (PRL) at Ahmedabad, India. This work has done under the supervision of Prof. Rajmal Jain and paper consist materials of pilot project and research part of the M. Tech program which was made during Space and Atmospheric Science Course.

Keywords: corona, flares, solar activity, X-ray emission

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Authors: H. M. Liman, Y. M. Suleiman A. A. David

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Poor air quality often considered one of the greatest environmental threats facing the world today is caused majorly by the emission of carbon monoxide into the atmosphere. The principal air pollutant is carbon monoxide. One prominent source of carbon monoxide emission is the transportation sector. Not much was known about the emission levels of carbon monoxide, the primary pollutant from the road transportation in the study area. Therefore, this study assessed the levels of carbon monoxide emission from road transportation in the Minna, Niger State. The database shows the carbon monoxide data collected. MSA Altair gas alert detector was used to take the carbon monoxide emission readings in Parts per Million for the peak and off-peak periods of vehicular movement at the road intersections. Their Global Positioning System (GPS) coordinates were recorded in the Universal Transverse Mercator (UTM). Bar chart graphs were plotted by using the emissions level of carbon dioxide as recorded on the field against the scientifically established internationally accepted safe limit of 8.7 Parts per Million of carbon monoxide in the atmosphere. Further statistical analysis was also carried out on the data recorded from the field using the Statistical Package for Social Sciences (SPSS) software and Microsoft excel to show the variance of the emission levels of each of the parameters in the study area. The results established that emissions’ level of atmospheric carbon monoxide from the road transportation in the study area exceeded the internationally accepted safe limits of 8.7 parts per million. In addition, the variations in the average emission levels of CO between the four parameters showed that morning peak is having the highest average emission level of 24.5PPM followed by evening peak with 22.84PPM while morning off peak is having 15.33 and the least is evening off peak 12.94PPM. Based on these results, recommendations made for poor air quality mitigation via carbon monoxide emissions reduction from transportation include Introduction of the urban mass transit would definitely reduce the number of traffic on the roads, hence the emissions from several vehicles that would have been on the road. This would also be a cheaper means of transportation for the masses and Encouraging the use of vehicles using alternative sources of energy like solar, electric and biofuel will also result in less emission levels as the these alternative energy sources other than fossil fuel originated diesel and petrol vehicles do not emit especially carbon monoxide.

Keywords: carbon monoxide, climate change emissions, road transportation, vehicular

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Authors: Annesha Ghosh, S. B. Agrawal

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Agricultural sector is facing a serious threat due to climate change and exacerbation of different atmospheric pollutants. Tropospheric ozone (O₃) is considered as a dynamic air pollutant imposing substantial phytotoxicity to natural vegetations and agriculture worldwide. Naturally, plants are exposed to different environmental factors and their interactions. Amongst such interactions, studies related to O₃ and water stress are still rare. In the present experiment, wheat cultivar HD2967 were grown in open top chambers (OTC) under two O₃ concentration; ambient O₃ level (A) and elevated O₃ (E) (ambient + 20 ppb O₃) along with two different water supply; well-watered (W) and 50% water stress conditions (WS), with an aim to assess the individual and interactive effect of two most prevailing stress factors in Indo-Gangetic Plains of India. Exposure to elevated O₃ dose caused early senescence symptoms and reduction in growth and biomass of the test cultivar. The adversity was more pronounced under the combined effect of EWS. Significant reduction of stomatal conductance (gs) and assimilation rate were observed under combined stress condition compared to the control (AW). However, plants grown under individual stress conditions displayed higher gs, biomass, and antioxidant defense mechanism compared to the plants grown under the presence of combined stresses. Higher induction in most of the enzyme activities of catalase (CAT), ascorbate peroxidase (APX), glutathione reductase (GR), peroxidase (POD) and superoxide dismutase (SOD) was displayed by HD 2967 under EW while, under the presence of combined stresses (EWS), a moderate increment of APX and CAT activity was observed only at its vegetative phase. Furthermore, variations in nutrient uptake and redistribution to different plants parts were also observed in the present study. Reduction in water availability has checked nutrient uptake (N, K, P, Ca, Cu, Mg, Zn) in above-ground parts (leaf) and below-ground parts (root). On the other hand, carbon (C) accumulation with subsequent C-N ratio was observed to be higher in the leaves under EWS. Such major nutrient check and limitation in carbon fixation due to lower gs under combined stress conditions might have weakened the defense mechanisms of the test cultivar. Grain yield was significantly reduced under EWS followed by AWS and EW as compared to their control, exhibiting an additive effect on the grain yield.

Keywords: antioxidants, open-top chambers, ozone, water stress, wheat, yield

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Authors: Mohamed El Morsy, Gabriela Achtenová

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Condition monitoring is used to increase machinery availability and machinery performance, whilst reducing consequential damage, increasing machine life, reducing spare parts inventories, and reducing breakdown maintenance. An efficient condition monitoring system provides early warning of faults by predicting them at an early stage. When a localized fault occurs in gears, the vibration signals always exhibit non-stationary behavior. The periodic impulsive feature of the vibration signal appears in the time domain and the corresponding gear mesh frequency (GMF) emerges in the frequency domain. However, one limitation of frequency-domain analysis is its inability to handle non-stationary waveform signals, which are very common when machinery faults occur. Particularly at the early stage of gear failure, the GMF contains very little energy and is often overwhelmed by noise and higher-level macro-structural vibrations. An effective signal processing method would be necessary to remove such corrupting noise and interference. In this paper, a new hybrid method based on optimal Morlet wavelet filter and autocorrelation enhancement is presented. First, to eliminate the frequency associated with interferential vibrations, the vibration signal is filtered with a band-pass filter determined by a Morlet wavelet whose parameters are selected or optimized based on maximum Kurtosis. Then, to further reduce the residual in-band noise and highlight the periodic impulsive feature, an autocorrelation enhancement algorithm is applied to the filtered signal. The test stand is equipped with three dynamometers; the input dynamometer serves as the internal combustion engine, the output dynamometers induce a load on the output joint shaft flanges. The pitting defect is manufactured on the tooth side of a gear of the fifth speed on the secondary shaft. The gearbox used for experimental measurements is of the type most commonly used in modern small to mid-sized passenger cars with transversely mounted powertrain and front wheel drive: a five-speed gearbox with final drive gear and front wheel differential. The results obtained from practical experiments prove that the proposed method is very effective for gear fault diagnosis.

Keywords: wavelet analysis, pitted gear, autocorrelation, gear fault diagnosis

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Authors: Li-hsing Shih, Wei-Jen Hsu

Abstract:

Recently, the sale of electrical vehicles (EVs) has increased dramatically due to maturing technology development and decreasing cost. Governments of many countries have made regulations and policies in favor of EVs due to their long-term commitment to net zero carbon emissions. However, due to uncertain factors such as the future price of EVs, forecasting the future market share of EVs is a challenging subject for both the auto industry and local government. This study tries to forecast the market share of EVs using conjoint models and Monte Carlo simulation. The research is conducted in three phases. (1) A conjoint model is established to represent the customer preference structure on purchasing vehicles while five product attributes of both EV and internal combustion engine vehicles (ICEV) are selected. A questionnaire survey is conducted to collect responses from Taiwanese consumers and estimate the part-worth utility functions of all respondents. The resulting part-worth utility functions can be used to estimate the market share, assuming each respondent will purchase the product with the highest total utility. For example, attribute values of an ICEV and a competing EV are given respectively, two total utilities of the two vehicles of a respondent are calculated and then knowing his/her choice. Once the choices of all respondents are known, an estimate of market share can be obtained. (2) Among the attributes, future price is the key attribute that dominates consumers’ choice. This study adopts the assumption of a learning curve to predict the future price of EVs. Based on the learning curve method and past price data of EVs, a regression model is established and the probability distribution function of the price of EVs in 2030 is obtained. (3) Since the future price is a random variable from the results of phase 2, a Monte Carlo simulation is then conducted to simulate the choices of all respondents by using their part-worth utility functions. For instance, using one thousand generated future prices of an EV together with other forecasted attribute values of the EV and an ICEV, one thousand market shares can be obtained with a Monte Carlo simulation. The resulting probability distribution of the market share of EVs provides more information than a fixed number forecast, reflecting the uncertain nature of the future development of EVs. The research results can help the auto industry and local government make more appropriate decisions and future action plans.

Keywords: conjoint model, electrical vehicle, learning curve, Monte Carlo simulation

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