Search results for: deep soil mixing column
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6333

Search results for: deep soil mixing column

1413 Use of Carica papaya as a Bio-Sorbent for Removal of Heavy Metals in Wastewater

Authors: W. E. Igwegbe, B. C. Okoro, J. C. Osuagwu

Abstract:

The study was aimed at assessing the effectiveness of reducing the concentrations of heavy metals in waste water using Pawpaw (Carica papaya) wood as a bio-sorbent. The heavy metals considered include; zinc, cadmium, lead, copper, iron, selenium, nickel, and manganese. The physiochemical properties of carica papaya stem were studied. The experimental sample was obtained from a felled trunk of matured pawpaw tree. Waste water for experimental use was prepared by dissolving soil samples collected from a dump site at Owerri, Imo state in water. The concentration of each metal remaining in solution as residual metal after bio-sorption was determined using Atomic absorption Spectrometer. The effects of ph, contact time and initial heavy metal concentration were studied in a batch reactor. The results of Spectrometer test showed that there were different functional groups detected in the carica papaya stem biomass. Optimum bio-sorption occurred at pH 5.9 with 5g/100ml solution of bio-sorbent. The results of the study showed that the treated wastewater is fit for irrigation purpose based on Canada wastewater quality guideline for the protection of Agricultural standard. This approach thus provides a cost effective and environmentally friendly option for treating waste water.

Keywords: biomass, bio-sorption, Carica papaya, heavy metal, wastewater

Procedia PDF Downloads 372
1412 The Importance of Visual Communication in Artificial Intelligence

Authors: Manjitsingh Rajput

Abstract:

Visual communication plays an important role in artificial intelligence (AI) because it enables machines to understand and interpret visual information, similar to how humans do. This abstract explores the importance of visual communication in AI and emphasizes the importance of various applications such as computer vision, object emphasis recognition, image classification and autonomous systems. In going deeper, with deep learning techniques and neural networks that modify visual understanding, In addition to AI programming, the abstract discusses challenges facing visual interfaces for AI, such as data scarcity, domain optimization, and interpretability. Visual communication and other approaches, such as natural language processing and speech recognition, have also been explored. Overall, this abstract highlights the critical role that visual communication plays in advancing AI capabilities and enabling machines to perceive and understand the world around them. The abstract also explores the integration of visual communication with other modalities like natural language processing and speech recognition, emphasizing the critical role of visual communication in AI capabilities. This methodology explores the importance of visual communication in AI development and implementation, highlighting its potential to enhance the effectiveness and accessibility of AI systems. It provides a comprehensive approach to integrating visual elements into AI systems, making them more user-friendly and efficient. In conclusion, Visual communication is crucial in AI systems for object recognition, facial analysis, and augmented reality, but challenges like data quality, interpretability, and ethics must be addressed. Visual communication enhances user experience, decision-making, accessibility, and collaboration. Developers can integrate visual elements for efficient and accessible AI systems.

Keywords: visual communication AI, computer vision, visual aid in communication, essence of visual communication.

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1411 An End-to-end Piping and Instrumentation Diagram Information Recognition System

Authors: Taekyong Lee, Joon-Young Kim, Jae-Min Cha

Abstract:

Piping and instrumentation diagram (P&ID) is an essential design drawing describing the interconnection of process equipment and the instrumentation installed to control the process. P&IDs are modified and managed throughout a whole life cycle of a process plant. For the ease of data transfer, P&IDs are generally handed over from a design company to an engineering company as portable document format (PDF) which is hard to be modified. Therefore, engineering companies have to deploy a great deal of time and human resources only for manually converting P&ID images into a computer aided design (CAD) file format. To reduce the inefficiency of the P&ID conversion, various symbols and texts in P&ID images should be automatically recognized. However, recognizing information in P&ID images is not an easy task. A P&ID image usually contains hundreds of symbol and text objects. Most objects are pretty small compared to the size of a whole image and are densely packed together. Traditional recognition methods based on geometrical features are not capable enough to recognize every elements of a P&ID image. To overcome these difficulties, state-of-the-art deep learning models, RetinaNet and connectionist text proposal network (CTPN) were used to build a system for recognizing symbols and texts in a P&ID image. Using the RetinaNet and the CTPN model carefully modified and tuned for P&ID image dataset, the developed system recognizes texts, equipment symbols, piping symbols and instrumentation symbols from an input P&ID image and save the recognition results as the pre-defined extensible markup language format. In the test using a commercial P&ID image, the P&ID information recognition system correctly recognized 97% of the symbols and 81.4% of the texts.

Keywords: object recognition system, P&ID, symbol recognition, text recognition

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1410 Assessment of Land Use and Land Cover Change in Lake Ol Bolossat Catchment, Nyandarua County, Kenya

Authors: John Wangui, Charles Gachene, Stephen Mureithi, Boniface Kiteme

Abstract:

Land use changes caused by demographic, natural variability, economic, technological and policy factors affect the goods and services derived from an ecosystem. In the past few decades, Lake Ol Bolossat catchment in Nyandarua County Kenya has been facing challenges of land cover changes threatening its capacity to perform ecosystems functions and adversely affecting communities and ecosystems downstream. This study assessed land cover changes in the catchment for a period of twenty eight years (from 1986 to 2014). Analysis of three Landsat images i.e. L5 TM 1986, L5 TM 1995 and L8 OLI/TIRS 2014 was done using ERDAS 9.2 software. The results show that dense forest, cropland and area under water increased by 27%, 29% and 3% respectively. On the other hand, open forest, dense grassland, open grassland, bushland and shrubland decreased by 3%, 3%, 11%, 26% and 1% respectively during the period under assessment. The lake was noted to have increased due to siltation caused by soil erosion causing a reduction in Lake’s depth and consequently causing temporary flooding of the wetland. The study concludes that the catchment is under high demographic pressure which would lead to resource use conflicts and therefore formulation of mitigation measures is highly recommended.

Keywords: land cover, land use change, land degradation, Nyandarua, Remote sensing

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1409 Modeling Continuous Flow in a Curved Channel Using Smoothed Particle Hydrodynamics

Authors: Indri Mahadiraka Rumamby, R. R. Dwinanti Rika Marthanty, Jessica Sjah

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Smoothed particle hydrodynamics (SPH) was originally created to simulate nonaxisymmetric phenomena in astrophysics. However, this method still has several shortcomings, namely the high computational cost required to model values with high resolution and problems with boundary conditions. The difficulty of modeling boundary conditions occurs because the SPH method is influenced by particle deficiency due to the integral of the kernel function being truncated by boundary conditions. This research aims to answer if SPH modeling with a focus on boundary layer interactions and continuous flow can produce quantifiably accurate values with low computational cost. This research will combine algorithms and coding in the main program of meandering river, continuous flow algorithm, and solid-fluid algorithm with the aim of obtaining quantitatively accurate results on solid-fluid interactions with the continuous flow on a meandering channel using the SPH method. This study uses the Fortran programming language for modeling the SPH (Smoothed Particle Hydrodynamics) numerical method; the model is conducted in the form of a U-shaped meandering open channel in 3D, where the channel walls are soil particles and uses a continuous flow with a limited number of particles.

Keywords: smoothed particle hydrodynamics, computational fluid dynamics, numerical simulation, fluid mechanics

Procedia PDF Downloads 133
1408 Effects of Deficit Watering and Potassium Fertigation on Growth and Yield Response of Cassava

Authors: Daniel O. Wasonga, Jouko Kleemola, Laura Alakukku, Pirjo Makela

Abstract:

Cassava (Manihot esculenta Crantz) is a major food crop for millions of people in the tropics. Growth and yield of cassava in the arid-tropics are seriously constrained by intermittent water deficit and low soil K content. Therefore, experiments were conducted to investigate the effects of interaction between water deficit and K fertigation on growth and yield response of biofortified cassava at early growth phase. Yellow cassava cultivar was grown under controlled glasshouse conditions in 5-L pots containing 1.7 kg of pre-fertilized potting mix. Plants were watered daily for 30 days after planting. Treatments were three watering levels (30%, severe water deficit; 60%, mild water deficit; 100%, well-watered), on which K (0.01, 1, 4, 16 and 32 mM) was split. Plants were harvested at 90 days after planting. Leaf area was smallest in plants grown with 30% watering and 0.01 mM K, and largest in plants grown with 100% watering and 32 mM K. Leaf, root, and total dry mass decreased in water-stressed plants. However, dry mass was markedly higher when plants were grown with 16 mM K under all watering levels in comparison to other K concentrations. The highest leaf, root and total dry mass were in plants with 100% watering and 16 mM K. In conclusion, K improved the growth of plants under water deficit and thus, K application on soils with low moisture and low K may improve the productivity of cassava.

Keywords: dry mass, interaction, leaf area, Manihot esculenta

Procedia PDF Downloads 118
1407 Exploring the Process of Cultivating Tolerance: The Case of a Pakistani University

Authors: Uzma Rashid, Mommnah Asad

Abstract:

As more and more people fall victim to the intolerance that has become a plague globally, academicians are faced with the herculean task of sowing the roots for more tolerant individuals. Being the multilayered task that it is, promoting an acceptance of diversity and pushing an agenda to push back hate requires efforts on multiple levels. Not only does the curriculum need to be in line with such goals, but teachers also need to be trained to cater to the sensitivities surrounding conversations of tolerance and diversity. In addition, institutional support needs to be there to provide conducive conditions for a diversity driven learning process to take place. In reality, teachers have to struggle with forwarding ideas about diversity and tolerance which do not sound particularly risky to be shared but given the current socio-political and religious milieu, can put the teacher in a difficult position and can make the task exponentially challenging. This paper is based on an auto-ethnographic account of teaching undergraduate and graduate courses at a private university in Pakistan. These courses were aimed at teaching tolerance to adult learners through classes focused on key notions pertaining to religion, culture, gender, and society. Authors’ classroom experiences with the students in these courses indicate a marked heightening of religious sensitivities that can potentially threaten a teacher’s life chances and become a hindrance in deep, meaningful conversations, thus lending a superficiality to the whole endeavor. The paper will discuss in detail the challenges that this teacher dealt with in the process, how those were addressed, and locate them in the larger picture of how tolerance can be materialized in current times in the universities in Pakistan and in similar contexts elsewhere.

Keywords: tolerance, diversity, gender, Pakistani Universities

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1406 Non-Isothermal Stationary Laminar Oil Flow Numerical Simulation

Authors: Daniyar Bossinov

Abstract:

This paper considers a non-isothermal stationary waxy crude oil flow in a two-dimensional axisymmetric pipe with the transition of a Newtonian fluid to a non-Newtonian fluid. The viscosity and yield stress of waxy crude oil are highly dependent on temperature changes. During the hot pumping of waxy crude oil through a buried pipeline, a non-isothermal flow occurs due to heat transfer to the surrounding soil. This leads to a decrease in flow temperature, an increase in viscosity, the appearance of yield stress, the crystallization of wax, and the deposition of solid particles on the pipeline's inner wall. The deposition of oil solid particles reduces a pipeline flow area and leads to the appearance of a stagnant zone with thermal insulation in the near-wall area. Waxy crude oil properties change. A Newtonian fluid at low temperatures transits to a non-Newtonian fluid. The one-dimensional modeling of a non-isothermal waxy crude oil flow in a two-dimensional axisymmetric pipeline by traditional averaging of temperature and velocity over the pipeline cross-section does not allow for explaining a physics phenomenon. Therefore, in this work, a two-dimensional flow model and the heat transfer of waxy oil are constructed. The calculated data show the transition of a Newtonian fluid to a non-Newtonian fluid due to the heat exchange of waxy oil with the environment.

Keywords: non-isothermal laminar flow, waxy crude oil, stagnant zone, yield stress

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1405 Language Development and Learning about Violence

Authors: Karen V. Lee

Abstract:

The background and significance of this study involves research about a music teacher discovering how language development and learning can help her overcome harmful and lasting consequences from sexual violence. Education about intervention resources from language development that helps her cope with consequences influencing her career as teacher. Basic methodology involves the qualitative method of research as theoretical framework where the author is drawn into a deep storied reflection about political issues surrounding teachers who need to overcome social, psychological, and health risk behaviors from violence. Sub-themes involve available education from learning resources to ensure teachers receive social, emotional, physical, spiritual, and intervention resources that evoke visceral, emotional responses from the audience. Major findings share how language development and learning provide helpful resources to victims of violence. It is hoped the research dramatizes an episodic yet incomplete story that highlights the circumstances surrounding the protagonist’s life. In conclusion, the research has a reflexive storied framework that embraces harmful and lasting consequences from sexual violence. The reflexive story of the sensory experience critically seeks verisimilitude by evoking lifelike and believable feelings from others. Thus, the scholarly importance of using language development and learning for intervention resources can provide transformative aspects that contribute to social change. Overall, the circumstance surrounding the story about sexual violence is not uncommon in society. Language development and learning supports the moral mission to help teachers overcome sexual violence that socially impacts their professional lives as victims.

Keywords: intervention, language development and learning, sexual violence, story

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1404 Physics-Informed Convolutional Neural Networks for Reservoir Simulation

Authors: Jiangxia Han, Liang Xue, Keda Chen

Abstract:

Despite the significant progress over the last decades in reservoir simulation using numerical discretization, meshing is complex. Moreover, the high degree of freedom of the space-time flow field makes the solution process very time-consuming. Therefore, we present Physics-Informed Convolutional Neural Networks(PICNN) as a hybrid scientific theory and data method for reservoir modeling. Besides labeled data, the model is driven by the scientific theories of the underlying problem, such as governing equations, boundary conditions, and initial conditions. PICNN integrates governing equations and boundary conditions into the network architecture in the form of a customized convolution kernel. The loss function is composed of data matching, initial conditions, and other measurable prior knowledge. By customizing the convolution kernel and minimizing the loss function, the neural network parameters not only fit the data but also honor the governing equation. The PICNN provides a methodology to model and history-match flow and transport problems in porous media. Numerical results demonstrate that the proposed PICNN can provide an accurate physical solution from a limited dataset. We show how this method can be applied in the context of a forward simulation for continuous problems. Furthermore, several complex scenarios are tested, including the existence of data noise, different work schedules, and different good patterns.

Keywords: convolutional neural networks, deep learning, flow and transport in porous media, physics-informed neural networks, reservoir simulation

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1403 Application of Remote Sensing Technique on the Monitoring of Mine Eco-Environment

Authors: Haidong Li, Weishou Shen, Guoping Lv, Tao Wang

Abstract:

Aiming to overcome the limitation of the application of traditional remote sensing (RS) technique in the mine eco-environmental monitoring, in this paper, we first classified the eco-environmental damages caused by mining activities and then introduced the principle, classification and characteristics of the Light Detection and Ranging (LiDAR) technique. The potentiality of LiDAR technique in the mine eco-environmental monitoring was analyzed, particularly in extracting vertical structure parameters of vegetation, through comparing the feasibility and applicability of traditional RS method and LiDAR technique in monitoring different types of indicators. The application situation of LiDAR technique in extracting typical mine indicators, such as land destruction in mining areas, damage of ecological integrity and natural soil erosion. The result showed that the LiDAR technique has the ability to monitor most of the mine eco-environmental indicators, and exhibited higher accuracy comparing with traditional RS technique, specifically speaking, the applicability of LiDAR technique on each indicator depends on the accuracy requirement of mine eco-environmental monitoring. In the item of large mine, LiDAR three-dimensional point cloud data not only could be used as the complementary data source of optical RS, Airborne/Satellite LiDAR could also fulfill the demand of extracting vertical structure parameters of vegetation in large areas.

Keywords: LiDAR, mine, ecological damage, monitoring, traditional remote sensing technique

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1402 Comprehensive Framework for Pandemic-Resilient Cities to Avert Future Migrant Crisis: A Case of Mumbai

Authors: Vasudha Thapa, Kiran Chappa

Abstract:

There is a pressing need to prepare cities in the developing countries of the global south such as India against the chaos created by COVID 19 pandemic and future disaster risks. This pandemic posed the nation with an unprecedented challenge of dealing with a wave of stranded migrant workers. These workers comprise the most vulnerable section of the society in case of any pandemic or disaster risks. The COVID 19 pandemic exposed the vulnerability of migrant workers in the urban form and the need for capacity-building strategies against future pandemics. This paper highlights the challenges of these migrant workers in the case of Mumbai city in lockdown, post lockdown, and the current uncertain scenarios. The paper deals with a thorough investigation of the existing and the recent policies and strategies taken by the Urban Local Bodies (ULBs), state, and central government to assist these migrants in the city during this mayhem of uncertainties. The paper looks further deep into the challenges and opportunities presented in the current scenario through the assessment of existing data and response to policy measures taken by the government organizations. The ULBs are at the forefront in the response to any disaster risk, hence the paper assesses the capacity gaps of the Urban local bodies in mitigating the risks posed by any pandemic-like situation. The study further recommends capacity-building strategies at various levels of governance and uniform policy measures to assist the migrant population of the city.

Keywords: urban resilience, covid 19, migrant population, India, capacity building, governance

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1401 Landslide Study Using Unmanned Aerial Vehicle and Resistivity Survey at Bkt Kukus, Penang Island, Malaysia

Authors: Kamal Bahrin Jaafar

Abstract:

The study area is located at Bukit Kukus, Penang where the construction of twin road project in ongoing. A landslide event has occurred on 19th October 2018, which causes fatal deaths. The purpose of this study is to figure out the causes of failure, the estimated volume of failure, and its balance. The study comprises of unmanned aerial vehicle (UAV) sensing and resistivity survey. The resistivity method includes spreading three lines of 200m length resistivity survey with the depth of penetration in the subsurface not exceeding 35m. The result of UAV shows the current view of the site condition. Based on resistivity result, the dominant layer in the study area consists of residual soil/filling material with a thickness of more than 35m. Three selected cross sections from construction drawing are overlain with the current cross sections to understand more on the condition of the subsurface profile. By comparison, there is a difference between past and present topography. The combination of result from the previous data and current condition shows the calculated volume of failure is 85,000 m³, and its balance is 50,000 m³. In conclusion, the failure occurs since the contractor has conducted the construction works without following the construction drawing supplied by the consultant. Besides, the cause of failure is triggered by the geology condition, such as a fault that should be considered prior to the commencement of work.

Keywords: UAV, landslide, resistivity survey, cause of failure

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1400 Microwave Heating and Catalytic Activity of Iron/Carbon Materials for H₂ Production from the Decomposition of Plastic Wastes

Authors: Peng Zhang, Cai Liang

Abstract:

The non-biodegradable plastic wastes have posed severe environmental and ecological contaminations. Numerous technologies, such as pyrolysis, incineration, and landfilling, have already been employed for the treatment of plastic waste. Compared with conventional methods, microwave has displayed unique advantages in the rapid production of hydrogen from plastic wastes. Understanding the interaction between microwave radiation and materials would promote the optimization of several parameters for the microwave reaction system. In this work, various carbon materials have been investigated to reveal microwave heating performance and the ensuing catalytic activity. Results showed that the diversity in the heating characteristic was mainly due to the dielectric properties and the individual microstructures. Furthermore, the gaps and steps among the surface of carbon materials would lead to the distortion of the electromagnetic field, which correspondingly induced plasma discharging. The intensity and location of local plasma were also studied. For high-yield H₂ production, iron nanoparticles were selected as the active sites, and a series of iron/carbon bifunctional catalysts were synthesized. Apart from the high catalytic activity, the iron particles in nano-size close to the microwave skin depth would transfer microwave irradiation to the heat, intensifying the decomposition of plastics. Under microwave radiation, iron is supported on activated carbon material with 10wt.% loading exhibited the best catalytic activity for H₂ production. Specifically, the plastics were rapidly heated up and subsequently converted into H₂ with a hydrogen efficiency of 85%. This work demonstrated a deep understanding of microwave reaction systems and provided the optimization for plastic treatment.

Keywords: plastic waste, recycling, hydrogen, microwave

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1399 Production of Bricks Using Mill Waste and Tyre Crumbs at a Low Temperature by Alkali-Activation

Authors: Zipeng Zhang, Yat C. Wong, Arul Arulrajah

Abstract:

Since automobiles became widely popular around the early 20th century, end-of-life tyres have been one of the major types of waste humans encounter. Every minute, there are considerable quantities of tyres being disposed of around the world. Most end-of-life tyres are simply landfilled or simply stockpiled, other than recycling. To address the potential issues caused by tyre waste, incorporating it into construction materials can be a possibility. This research investigated the viability of manufacturing bricks using mill waste and tyre crumb by alkali-activation at a relatively low temperature. The mill waste was extracted from a brick factory located in Melbourne, Australia, and the tyre crumbs were supplied by a local recycling company. As the main precursor, the mill waste was activated by the alkaline solution, which was comprised of sodium hydroxide (8m) and sodium silicate (liquid). The introduction ratio of alkaline solution (relative to the solid weight) and the weight ratio between sodium hydroxide and sodium silicate was fixed at 20 wt.% and 1:1, respectively. The tyre crumb was introduced to substitute part of the mill waste at four ratios by weight, namely 0, 5, 10 and 15%. The mixture of mill waste and tyre crumbs were firstly dry-mixed for 2 min to ensure the homogeneity, followed by a 2.5-min wet mixing after adding the solution. The ready mixture subsequently was press-moulded into blocks with the size of 109 mm in length, 112.5 mm in width and 76 mm in height. The blocks were cured at 50°C with 95% relative humidity for 2 days, followed by a 110°C oven-curing for 1 day. All the samples were then placed under the ambient environment until the age of 7 and 28 days for testing. A series of tests were conducted to evaluate the linear shrinkage, compressive strength and water absorption of the samples. In addition, the microstructure of the samples was examined via the scanning electron microscope (SEM) test. The results showed the highest compressive strength was 17.6 MPa, found in the 28-day-old group using 5 wt.% tyre crumbs. Such strength has been able to satisfy the requirement of ASTM C67. However, the increasing addition of tyre crumb weakened the compressive strength of samples. Apart from the strength, the linear shrinkage and water absorption of all the groups can meet the requirements of the standard. It is worth noting that the use of tyre crumbs tended to decrease the shrinkage and even caused expansion when the tyre content was over 15 wt.%. The research also found that there was a significant reduction in compressive strength for the samples after water absorption tests. In conclusion, the tyre crumbs have the potential to be used as a filler material in brick manufacturing, but more research needs to be done to tackle the durability problem in the future.

Keywords: bricks, mill waste, tyre crumbs, waste recycling

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1398 Numerical Verification of a Backfill-Rectangular Tank-Fluid System

Authors: Ramazan Livaoğlu, Tufan Çakır

Abstract:

The performance of rectangular tanks during earthquakes has been observed to depend significantly on the existence of water in the container and the presence of the backfill acting on tank wall. Therefore, in design of rectangular tanks, the topics of fluid-structure-backfill interactions and determination of modal characteristics of the interaction system have traditionally been one of the great theoretical and practical controversy. Although finite element method has been and will continue to be used to a significant extent in treating the response of the system, experimental verification of numerical models remains prerequisite for their adoption and reliable application in practice. Thus, in this study, the numerical and experimental investigations were performed on the backfill-exterior wall-fluid interaction system. Firstly, three dimensional finite element model (3D-FEM) was developed to acquire modal frequencies and mode shapes of the system by means of ANSYS. Secondly, a series of in-situ tests were fulfilled to define modal characteristics of same system to determine the applicability of the FEM to a real physical situation under field conditions. Finally, comparing the theoretical predictions from the model to results from experimental measurement, a close agreement was found between theory and experiment. Thus, it can be easily stated that experimental verification provides strong support for the use of proposed model in further investigations.

Keywords: fluid-structure interaction, modal analysis, rectangular tank, soil structure interaction

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1397 A Review of Gas Hydrate Rock Physics Models

Authors: Hemin Yuan, Yun Wang, Xiangchun Wang

Abstract:

Gas hydrate is drawing attention due to the fact that it has an enormous amount all over the world, which is almost twice the conventional hydrocarbon reserves, making it a potential alternative source of energy. It is widely distributed in permafrost and continental ocean shelves, and many countries have launched national programs for investigating the gas hydrate. Gas hydrate is mainly explored through seismic methods, which include bottom simulating reflectors (BSR), amplitude blanking, and polarity reverse. These seismic methods are effective at finding the gas hydrate formations but usually contain large uncertainties when applying to invert the micro-scale petrophysical properties of the formations due to lack of constraints. Rock physics modeling links the micro-scale structures of the rocks to the macro-scale elastic properties and can work as effective constraints for the seismic methods. A number of rock physics models have been proposed for gas hydrate modeling, which addresses different mechanisms and applications. However, these models are generally not well classified, and it is confusing to determine the appropriate model for a specific study. Moreover, since the modeling usually involves multiple models and steps, it is difficult to determine the source of uncertainties. To solve these problems, we summarize the developed models/methods and make four classifications of the models according to the hydrate micro-scale morphology in sediments, the purpose of reservoir characterization, the stage of gas hydrate generation, and the lithology type of hosting sediments. Some sub-categories may overlap each other, but they have different priorities. Besides, we also analyze the priorities of different models, bring up the shortcomings, and explain the appropriate application scenarios. Moreover, by comparing the models, we summarize a general workflow of the modeling procedure, which includes rock matrix forming, dry rock frame generating, pore fluids mixing, and final fluid substitution in the rock frame. These procedures have been widely used in various gas hydrate modeling and have been confirmed to be effective. We also analyze the potential sources of uncertainties in each modeling step, which enables us to clearly recognize the potential uncertainties in the modeling. In the end, we explicate the general problems of the current models, including the influences of pressure and temperature, pore geometry, hydrate morphology, and rock structure change during gas hydrate dissociation and re-generation. We also point out that attenuation is also severely affected by gas hydrate in sediments and may work as an indicator to map gas hydrate concentration. Our work classifies rock physics models of gas hydrate into different categories, generalizes the modeling workflow, analyzes the modeling uncertainties and potential problems, which can facilitate the rock physics characterization of gas hydrate bearding sediments and provide hints for future studies.

Keywords: gas hydrate, rock physics model, modeling classification, hydrate morphology

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1396 Evaluating the Satisfaction of Chinese Consumers toward Influencers at TikTok

Authors: Noriyuki Suyama

Abstract:

The progress and spread of digitalization have led to the provision of a variety of new services. The recent progress in digitization can be attributed to rapid developments in science and technology. First, the research and diffusion of artificial intelligence (AI) has made dramatic progress. Around 2000, the third wave of AI research, which had been underway for about 50 years, arrived. Specifically, machine learning and deep learning were made possible in AI, and the ability of AI to acquire knowledge, define the knowledge, and update its own knowledge in a quantitative manner made the use of big data practical even for commercial PCs. On the other hand, with the spread of social media, information exchange has become more common in our daily lives, and the lending and borrowing of goods and services, in other words, the sharing economy, has become widespread. The scope of this trend is not limited to any industry, and its momentum is growing as the SDGs take root. In addition, the Social Network Service (SNS), a part of social media, has brought about the evolution of the retail business. In the past few years, social network services (SNS) involving users or companies have especially flourished. The People's Republic of China (hereinafter referred to as "China") is a country that is stimulating enormous consumption through its own unique SNS, which is different from the SNS used in developed countries around the world. This paper focuses on the effectiveness and challenges of influencer marketing by focusing on the influence of influencers on users' behavior and satisfaction with Chinese SNSs. Specifically, Conducted was the quantitative survey of Tik Tok users living in China, with the aim of gaining new insights from the analysis and discussions. As a result, we found several important findings and knowledge.

Keywords: customer satisfaction, social networking services, influencer marketing, Chinese consumers’ behavior

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1395 Enhancement of the Corrosion Resistance of Fastening System of Ballasted ‎Railway in Sandy Desert by Using Nano-Coating

Authors: Milad Alizadeh Galdiani, Navid Sabet, Mohamad Ali Mohit, Fatemeh Palizdar

Abstract:

Railway as one of the most important transportation modes, passes through ‎various areas with different conditions ‎inevitably, and in many countries such as ‎China, United States, Australia, and Iran, it passes through sandy ‎desert areas. One ‎of the main problems in these areas is the movement of sand, causing various ‎damages ‎to ballasted railway track such as corrosion in the railway fastening system. ‎The soil composition of some desert areas like Fahraj in Iran consists of sand ‎and ‎salt. Due to the movement of sand and corrosive ions of salt, the fastening system ‎of the railway is ‎corroded, which, in turn, reduces the thickness of the components ‎and their life span.‎ In this research, the Nano-coating for fastening system of ‎the railway is ‎introduced, and its performance has been investigated in both ‎laboratory and field tests. The Nano-coating of ‎the fastening system consists of zinc-rich, epoxy, polyurethane, and additive, which is produced through ‎Nano ‎technology. This layer covers the surface of the fastening system and ‎prohibits the chemical reactions, which result in ‎corrosion. The results of ‎Electrochemical Impedance Spectroscopy (EIS) ‎indicate that corrosion resistance ‎increases 315 times by using nano-coating, salt spray test results demonstrate that ‎nano-coated components remained intact after 1000 hours.‎

Keywords: ballasted railway, Nano-coating, railway fastening system, sandy desert

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1394 Hydrological Modelling to Identify Critical Erosion Areas in Gheshlagh Dam Basin

Authors: Golaleh Ghaffari

Abstract:

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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1393 Evolution and Merging of Double-Diffusive Layers in a Vertically Stable Compositional Field

Authors: Ila Thakur, Atul Srivastava, Shyamprasad Karagadde

Abstract:

The phenomenon of double-diffusive convection is driven by density gradients created by two different components (e.g., temperature and concentration) having different molecular diffusivities. The evolution of horizontal double-diffusive layers (DDLs) is one of the outcomes of double-diffusive convection occurring in a laterally/vertically cooled rectangular cavity having a pre-existing vertically stable composition field. The present work mainly focuses on different characteristics of the formation and merging of double-diffusive layers by imposing lateral/vertical thermal gradients in a vertically stable compositional field. A CFD-based twodimensional fluent model has been developed for the investigation of the aforesaid phenomena. The configuration containing vertical thermal gradients shows the evolution and merging of DDLs, where, elements from the same horizontal plane move vertically and mix with surroundings, creating a horizontal layer. In the configuration of lateral thermal gradients, a specially oriented convective roll was found inside each DDL and each roll was driven by the competing density change due to the already existing composition field and imposed thermal field. When the thermal boundary layer near the vertical wall penetrates the salinity interface, it can disrupt the compositional interface and can lead to layer merging. Different analytical scales were quantified and compared for both configurations. Various combinations of solutal and thermal Rayleigh numbers were investigated to get three different regimes, namely; stagnant regime, layered regime and unicellular regime. For a particular solutal Rayleigh number, a layered structure can originate only for a range of thermal Rayleigh numbers. Lower thermal Rayleigh numbers correspond to a diffusion-dominated stagnant regime. Very high thermal Rayleigh corresponds to a unicellular regime with high convective mixing. Different plots identifying these three regimes, number, thickness and time of existence of DDLs have been studied and plotted. For a given solutal Rayleigh number, an increase in thermal Rayleigh number increases the width but decreases both the number and time of existence of DDLs in the fluid domain. Sudden peaks in the velocity and heat transfer coefficient have also been observed and discussed at the time of merging. The present study is expected to be useful in correlating the double-diffusive convection in many large-scale applications including oceanography, metallurgy, geology, etc. The model has also been developed for three-dimensional geometry, but the results were quite similar to that of 2-D simulations.

Keywords: double diffusive layers, natural convection, Rayleigh number, thermal gradients, compositional gradients

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1392 1-D Convolutional Neural Network Approach for Wheel Flat Detection for Freight Wagons

Authors: Dachuan Shi, M. Hecht, Y. Ye

Abstract:

With the trend of digitalization in railway freight transport, a large number of freight wagons in Germany have been equipped with telematics devices, commonly placed on the wagon body. A telematics device contains a GPS module for tracking and a 3-axis accelerometer for shock detection. Besides these basic functions, it is desired to use the integrated accelerometer for condition monitoring without any additional sensors. Wheel flats as a common type of failure on wheel tread cause large impacts on wagons and infrastructure as well as impulsive noise. A large wheel flat may even cause safety issues such as derailments. In this sense, this paper proposes a machine learning approach for wheel flat detection by using car body accelerations. Due to suspension systems, impulsive signals caused by wheel flats are damped significantly and thus could be buried in signal noise and disturbances. Therefore, it is very challenging to detect wheel flats using car body accelerations. The proposed algorithm considers the envelope spectrum of car body accelerations to eliminate the effect of noise and disturbances. Subsequently, a 1-D convolutional neural network (CNN), which is well known as a deep learning method, is constructed to automatically extract features in the envelope-frequency domain and conduct classification. The constructed CNN is trained and tested on field test data, which are measured on the underframe of a tank wagon with a wheel flat of 20 mm length in the operational condition. The test results demonstrate the good performance of the proposed algorithm for real-time fault detection.

Keywords: fault detection, wheel flat, convolutional neural network, machine learning

Procedia PDF Downloads 131
1391 Adaptive Environmental Control System Strategy for Cabin Air Quality in Commercial Aircrafts

Authors: Paolo Grasso, Sai Kalyan Yelike, Federico Benzi, Mathieu Le Cam

Abstract:

The cabin air quality (CAQ) in commercial aircraft is of prime interest, especially in the context of the COVID-19 pandemic. Current Environmental Control Systems (ECS) rely on a prescribed fresh airflow per passenger to dilute contaminants. An adaptive ECS strategy is proposed, leveraging air sensing and filtration technologies to ensure a better CAQ. This paper investigates the CAQ level achieved in commercial aircraft’s cabin during various flight scenarios. The modeling and simulation analysis is performed in a Modelica-based environment describing the dynamic behavior of the system. The model includes the following three main systems: cabin, recirculation loop and air-conditioning pack. The cabin model evaluates the thermo-hygrometric conditions and the air quality in the cabin depending on the number of passengers and crew members, the outdoor conditions and the conditions of the air supplied to the cabin. The recirculation loop includes models of the recirculation fan, ordinary and novel filtration technology, mixing chamber and outflow valve. The air-conditioning pack includes models of heat exchangers and turbomachinery needed to condition the hot pressurized air bled from the engine, as well as selected contaminants originated from the outside or bled from the engine. Different ventilation control strategies are modeled and simulated. Currently, a limited understanding of contaminant concentrations in the cabin and the lack of standardized and systematic methods to collect and record data constitute a challenge in establishing a causal relationship between CAQ and passengers' comfort. As a result, contaminants are neither measured nor filtered during flight, and the current sub-optimal way to avoid their accumulation is their dilution with the fresh air flow. However, the use of a prescribed amount of fresh air comes with a cost, making the ECS the most energy-demanding non-propulsive system within an aircraft. In such a context, this study shows that an ECS based on a reduced and adaptive fresh air flow, and relying on air sensing and filtration technologies, provides promising results in terms of CAQ control. The comparative simulation results demonstrate that the proposed adaptive ECS brings substantial improvements to the CAQ in terms of both controlling the asymptotic values of the concentration of the contaminant and in mitigating hazardous scenarios, such as fume events. Original architectures allowing for adaptive control of the inlet air flow rate based on monitored CAQ will change the requirements for filtration systems and redefine the ECS operation.

Keywords: cabin air quality, commercial aircraft, environmental control system, ventilation

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1390 Temperature Susceptibility of Multigrade Bitumen Asphalt and an Approach to Account for Temperature Variation through Deep Pavements

Authors: Brody R. Clark, Chaminda Gallage, John Yeaman

Abstract:

Multigrade bitumen asphalt is a quality asphalt product that is not utilised in many places globally. Multigrade bitumen is believed to be less sensitive to temperature, which gives it an advantage over conventional binders. Previous testing has shown that asphalt temperature changes greatly with depth, but currently the industry standard is to nominate a single temperature for design. For detailed design of asphalt roads, perhaps asphalt layers should be divided into nominal layer depths and different modulus and fatigue equations/values should be used to reflect the temperatures of each respective layer. A collaboration of previous laboratory testing conducted on multigrade bitumen asphalt beams under a range of temperatures and loading conditions was analysed. The samples tested included 0% or 15% recycled asphalt pavement (RAP) to determine what impact the recycled material has on the fatigue life and stiffness of the pavement. This paper investigated the temperature susceptibility of multigrade bitumen asphalt pavements compared to conventional binders by combining previous testing that included conducting a sweep of fatigue tests, developing complex modulus master curves for each mix and a study on how pavement temperature changes through pavement depth. This investigation found that the final design of the pavement is greatly affected by the nominated pavement temperature and respective material properties. This paper has outlined a potential revision to the current design approach for asphalt pavements and proposes that further investigation is needed into pavement temperature and its incorporation into design.

Keywords: asphalt, complex modulus, fatigue life, flexural stiffness, four point bending, multigrade bitumen, recycled asphalt pavement

Procedia PDF Downloads 376
1389 An Efficient Machine Learning Model to Detect Metastatic Cancer in Pathology Scans Using Principal Component Analysis Algorithm, Genetic Algorithm, and Classification Algorithms

Authors: Bliss Singhal

Abstract:

Machine learning (ML) is a branch of Artificial Intelligence (AI) where computers analyze data and find patterns in the data. The study focuses on the detection of metastatic cancer using ML. Metastatic cancer is the stage where cancer has spread to other parts of the body and is the cause of approximately 90% of cancer-related deaths. Normally, pathologists spend hours each day to manually classifying whether tumors are benign or malignant. This tedious task contributes to mislabeling metastasis being over 60% of the time and emphasizes the importance of being aware of human error and other inefficiencies. ML is a good candidate to improve the correct identification of metastatic cancer, saving thousands of lives and can also improve the speed and efficiency of the process, thereby taking fewer resources and time. So far, the deep learning methodology of AI has been used in research to detect cancer. This study is a novel approach to determining the potential of using preprocessing algorithms combined with classification algorithms in detecting metastatic cancer. The study used two preprocessing algorithms: principal component analysis (PCA) and the genetic algorithm, to reduce the dimensionality of the dataset and then used three classification algorithms: logistic regression, decision tree classifier, and k-nearest neighbors to detect metastatic cancer in the pathology scans. The highest accuracy of 71.14% was produced by the ML pipeline comprising of PCA, the genetic algorithm, and the k-nearest neighbor algorithm, suggesting that preprocessing and classification algorithms have great potential for detecting metastatic cancer.

Keywords: breast cancer, principal component analysis, genetic algorithm, k-nearest neighbors, decision tree classifier, logistic regression

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1388 Modifying the Electrical Properties of Liquid Crystal Cells by Including TiO₂ Nanoparticles on a Substrate

Authors: V. Marzal, J. C. Torres, B. Garcia-Camara, Manuel Cano-Garcia, Xabier Quintana, I. Perez Garcilopez, J. M. Sanchez-Pena

Abstract:

At the present time, the use of nanostructures in complex media, like liquid crystals, is widely extended to manipulate their properties, either electrical or optical. In addition, these media can also be used to control the optical properties of the nanoparticles, for instance when they are resonant. In this work, the change on electrical properties of a liquid crystal cell by adding TiO₂ nanoparticles on one of the alignment layers has been analyzed. These nanoparticles, with a diameter of 100 nm and spherical shape, were deposited in one of the substrates (ITO + polyimide) by spin-coating in order to produce a homogeneous layer. These substrates were checked using an optical microscope (objective x100) to avoid potential agglomerates. The liquid crystal cell is then fabricated, using one of these substrates and another without nanoparticles, and filled with E7. The study of the electrical response was done through impedance measurements in a long range of frequencies (3 Hz- 6 MHz) and at ambient temperature. Different nanoparticle concentrations were considered, as well as pure E7 and an empty cell for comparison purposes. Results about the effective dielectric permittivity and conductivity are presented along with models of equivalent electric circuits and its physical interpretation. As a summary, it has been observed the clear influence of the presence of the nanoparticles, strongly modifying the electric response of the device. In particular, a variation of both the effective permittivity and the conductivity of the device have been observed. This result requires a deep analysis of the effect of these nanoparticles on the trapping of free ions in the device, allowing a controlled manipulation and frequency tuning of the electrical response of these devices.

Keywords: alignment layer, electrical behavior, liquid crystal, TiO₂ nanoparticles

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1387 Mammographic Multi-View Cancer Identification Using Siamese Neural Networks

Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin

Abstract:

Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.

Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network

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1386 To Design an Architectural Model for On-Shore Oil Monitoring Using Wireless Sensor Network System

Authors: Saurabh Shukla, G. N. Pandey

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In recent times, oil exploration and monitoring in on-shore areas have gained much importance considering the fact that in India the oil import is 62 percent of the total imports. Thus, architectural model like wireless sensor network to monitor on-shore deep sea oil well is being developed to get better estimate of the oil prospects. The problem we are facing nowadays that we have very few restricted areas of oil left today. Countries like India don’t have much large areas and resources for oil and this problem with most of the countries that’s why it has become a major problem when we are talking about oil exploration in on-shore areas also the increase of oil prices has further ignited the problem. For this the use of wireless network system having relative simplicity, smallness in size and affordable cost of wireless sensor nodes permit heavy deployment in on-shore places for monitoring oil wells. Deployment of wireless sensor network in large areas will surely reduce the cost it will be very much cost effective. The objective of this system is to send real time information of oil monitoring to the regulatory and welfare authorities so that suitable action could be taken. This system architecture is composed of sensor network, processing/transmission unit and a server. This wireless sensor network system could remotely monitor the real time data of oil exploration and monitoring condition in the identified areas. For wireless sensor networks, the systems are wireless, have scarce power, are real-time, utilize sensors and actuators as interfaces, have dynamically changing sets of resources, aggregate behaviour is important and location is critical. In this system a communication is done between the server and remotely placed sensors. The server gives the real time oil exploration and monitoring conditions to the welfare authorities.

Keywords: sensor, wireless sensor network, oil, sensor, on-shore level

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1385 Effect of Moisture Content Compaction in the Geometry Definition of Earth Dams

Authors: Julian B. García, Virginie Q. R. Pinto, André P. Assis

Abstract:

This paper presents numerical flow and slope stability simulations in three typical sections of earth dams built in tropical regions, two homogeneous with different slope inclinations, and the other one heterogeneous with impermeable core. The geotechnical material parameters used in this work were obtained from a lab testing of physical characterization, compaction, consolidation, variable load permeability and saturated triaxial type CD for compacted soil samples with standard proctor energy at optimum moisture content (23%), optimum moisture content + 2% and optimum moisture content +5%. The objective is to analyze the general behavior of earth dams built in rainy regions where optimum moisture is exceeded. The factor of safety is satisfactory for the three sections compacted in all moisture content during the stages of operation and end of construction. On The other hand, the rapid drawdown condition is the critical phase for homogeneus dams configuration, the factor of safety obtained were unsatisfactory. In general, the heterogeneous dam behavior is more efficient due to the fact that the slopes are made up of gravel, which favors the dissipation of pore pressures during the rapid drawdown. For the critical phase, the slopes should have lower inclinations of the upstream and downstream slopes to guarantee stability, although it increases the costs.

Keywords: earth dams, flow, moisture content, slope stability

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1384 Characterization of Biosurfactants Produced by Bacteria Degrading Gasoline

Authors: Ikram Kamal, Mohamed Blaghen

Abstract:

Biosurfactants are amphiphilic biological compounds consisting of hydrophobic and hydrophilic domains produced extracellularly or as part of the cell membrane by a variety of yeast, bacteria and filamentous fungi. Biosurfactant applications in the environmental industries are promising due to their biodegradability, low toxicity, and effectiveness in enhancing biodegradation and solubilization of low solubility compounds. Currently, the main application is for enhancement of oil recovery and hydrocarbon bioremediation due to their biodegradability and low critical micelle concentration (CMC). The use of biosurfactants has also been proposed for various industrial applications, such as in food additives, cosmetics, detergent formulations and in combinations with enzymes for wastewater treatment. In this study, we have investigated the potential of bacterial strains: Mannheimia haemolytica, Burkholderia cepacia and Serratia ficaria were collected aseptically from the lagoon Marchika (water and soil) in Nador, Morocco; for the production of biosurfactants. This study also aimed to optimize the biosurfactant production process by changing the variables that influence the type and amount of biosurfactant produced by these microorganisms such as: carbon sources and also other physical and chemical parameters such as temperature and pH. Emulsification index, methylene blue test, and thin layer chromatography (TLC) revealed the ability of strains used in this study to produce compounds that could emulsify gasoline. In addition, a GC/MS was used to separate and identify different biosurfactants purified.

Keywords: biosurfactants, Mannheimia haemolytica, biodegradability, Burkholderia cepacia, Serratia ficaria

Procedia PDF Downloads 257