Search results for: fluid intelligence

Authors: Rachid Fermous, Rima Mebrek

Abstract:

Plasma expansion is an important physical process that takes place in laser interactions with solid targets. Within a self-similar model for the hydrodynamic multi-fluid equations, we investigated the expansion of dense plasma. The weakly relativistic electrons are produced by ultra-intense laser pulses, while ions are supposed to be in a non-relativistic regime. It is shown that dense plasma expansion is found to be governed mainly by quantum contributions in the fluid equations that originate from the degenerate pressure in addition to the nonlinear contributions from exchange and correlation potentials. The quantum degeneracy parameter profile provides clues to set the limit between under-dense and dense relativistic plasma expansions at a given density and temperature.

Keywords: plasma expansion, quantum degeneracy, weakly relativistic, under-dense plasma

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Authors: Kshama Sharma

Abstract:

Education is one of the most powerful tools to transform the world into a just, sustainable, and more peaceful place for existing lives across the globe. However, its recent objective approach focused on materialistic, factual, and existing knowledge, has a constraint of human experiences that is limited to certain dimensions only. And leads to a materialistic world which is deprived of spiritual approaches and makes it less compassionate, and more grades oriented. To make it more comprehensive, education should explore the subjective approaches towards spiritualism to connect lives with the greater self and consciousness of cosmic intelligence. This approach will bring a major shift in the orientation of pedagogical processes, assessment strategies, and administrative management of the present education system. Spirituality often related to the religious aspect of human civilization and development, however, when universal consciousness /cosmic intelligence (which is often claimed as dark energy) and the human mind competencies works in coherence and coordination then the efficiency of human mind reaches to a different dimension and achieve extraordinary level of human understanding. Quantitative analysis of the existing secondary data from the different agencies working in the field of meditation had been analyzed to conclude its implications on human mind and further how it can effectively use in education to bring the desired and expected results. Any kind of meditation practice affects the cognitive, mental, physical, emotional, and conscious state of mind. If aligned with the teaching and learning methodology will lead to conscious learner and peaceful world.

Keywords: spirituality, cosmic intelligence, consciousness, mind competencies

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Authors: Wolfram Jahn, Jose Manuel Munita

Abstract:

While computational fluid dynamics (CFD) simulations of fire scenarios are commonly used in the design of buildings, less attention has been given to the use of CFD simulations as an operational tool for the fire services. The reason of this lack of attention lies mainly in the fact that CFD simulations typically take large periods of time to complete, and their results would thus not be available in time to be of use during an emergency. Firefighters often face uncertain conditions when entering a building to attack a fire. They would greatly benefit from a technology based on predictive fire simulations, able to assist their decision-making process. The principal constraint to faster CFD simulations is the fine grid necessary to solve accurately the physical processes that govern a fire. This paper explores the possibility of overcoming this constraint and using coarse grid CFD simulations for fire scenarios, and proposes a methodology to use the simulation results in a meaningful way that can be used by the fire fighters during an emergency. Data from real scale compartment fire tests were used to compare CFD fire models with different grid arrangements, and empirical correlations were obtained to interpolate data points into the grids. The results show that the strongly predominant effect of the heat release rate of the fire on the fluid dynamics allows for the use of coarse grids with relatively low overall impact of simulation results. Simulations with an acceptable level of accuracy could be run in real time, thus making them useful as a forecasting tool for emergency response purposes.

Keywords: CFD, fire simulations, emergency response, forecast

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Authors: Dahia Chibouti, Benoit Trouette, Eric Chenier

Abstract:

With the development of micro-electro-mechanical systems (MEMS), understanding fluid flow and heat transfer at the micrometer scale is crucial. In the case where the flow characteristic length scale is narrowed to around ten times the mean free path of gas molecules, the classical fluid mechanics and energy equations are still valid in the bulk flow, but particular attention must be paid to the gas/solid interface boundary conditions. Indeed, in the vicinity of the wall, on a thickness of about the mean free path of the molecules, called the Knudsen layer, the gas molecules are no longer in local thermodynamic equilibrium. Therefore, macroscopic models based on the continuity of velocity, temperature and heat flux jump conditions must be applied at the fluid/solid interface to take this non-equilibrium into account. Although these macroscopic models are widely used, the assumptions on which they depend are not necessarily verified in realistic cases. In order to get rid of these assumptions, simulations at the molecular scale are carried out to study how molecule interaction with walls can change the fluid flow and heat transfers at the vicinity of the walls. The developed approach is based on a kind of heterogeneous multi-scale method: micro-domains overlap the continuous domain, and coupling is carried out through exchanges of information between both the molecular and the continuum approaches. In practice, molecular dynamics describes the fluid flow and heat transfers in micro-domains while the Navier-Stokes and energy equations are used at larger scales. In this framework, two kinds of micro-simulation are performed: i) in bulk, to obtain the thermo-physical properties (viscosity, conductivity, ...) as well as the equation of state of the fluid, ii) close to the walls to identify the relationships between the slip velocity and the shear stress or between the temperature jump and the normal temperature gradient. The coupling strategy relies on an implicit formulation of the quantities extracted from micro-domains. Indeed, using the results of the molecular simulations, a Bayesian regression is performed in order to build continuous laws giving both the behavior of the physical properties, the equation of state and the slip relationships, as well as their uncertainties. These latter allow to set up a learning strategy to optimize the number of micro simulations. In the present contribution, the first results regarding this coupling associated with the learning strategy are illustrated through parametric studies of convergence criteria, choice of basis functions and noise of input data. Anisothermic flows of a Lennard Jones fluid in micro-channels are finally presented.

Keywords: multi-scale, microfluidics, micro-channel, hybrid approach, coupling

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Authors: H. Alabed, K. Abuzayan. L. Fgie, K. Zarug

Abstract:

Ramadan requires individuals to abstain from food and fluid intake between sunrise and sunset; physiological considerations predict that poorer mood, physical performance and mental performance will result. In addition, any difficulties will be worsened because preparations for fasting and recovery from it often mean that nocturnal sleep is decreased in length, and this independently affects mood and performance. A difficulty of interpretation in many studies is that the observed changes could be due to fasting but also to the decreased length of sleep and altered food and fluid intakes before and after the daytime fasting. These factors were separated in this study, which took place over three separate days and compared the effects of different durations of fasting (4, 8 or 16h) upon a wide variety of measures (including subjective and objective assessments of performance, body composition, dehydration and responses to a short bout of exercise) - but with an unchanged amount of nocturnal sleep, controlled supper the previous evening, controlled intakes at breakfast and daytime naps not being allowed. Many of the negative effects of fasting observed in previous studies were present in this experiment also. These findings indicate that fasting was responsible for many of the changes previously observed, though some effect of sleep loss, particularly if occurring on successive days (as would occur in Ramadan) cannot be excluded.

Keywords: drinking, eating, mental performance, physical performance, social activity, blood, sleepiness

Procedia PDF Downloads 396

Authors: Sung-Pill Kim, Dae-Gyu Sung, Hee-Sung Shin, Jong-Chun Park

Abstract:

When a sloshing tank filled partially with liquid is excited with the motion of platform, it can be observed that the center of mass inside the tank is changed and impact loads is instantaneously applied to the wall, which causes dynamic loads additionally to the supporting links of platform. In this case, therefore, the dynamic behavior of platform associated with fluid motion should be considered in the early stage of design for safety and economics of the system. In this paper, the dynamic loads due to liquid sloshing motion in a rectangular tank which is loaded up on the upper deck of a Stewart platform are simulated using a coupled analysis of Moving Particle Simulation (MPS) and Flexible Multi-Body Dynamics (FMBD). The co-simulation is performed using two commercial softwares, Recurdyn for solving FMBD and Particleworks for analyzing fluid motion based on MPS method. For validating the present coupled system, a rectangular sloshing tank being enforced with inline sway motion by 1-DOF motion platform is assumed, and time-varied free-surface elevation and reaction force at a fixed joint are compared with experiments.

Keywords: dynamic loads, liquid sloshing tank, Stewart platform, moving particle semi-implicit (MPS) method, flexible multi-body dynamics (FMBD)

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Authors: M. Ben Slimene, M.-S. Ouali

Abstract:

Asset management of urban infrastructures faces a multitude of challenges that need to be overcome to obtain a reliable measurement of performances. Predicting the performance of slowly aging systems is one of those challenges, which helps the asset manager to investigate specific failure modes and to undertake the appropriate maintenance and rehabilitation interventions to avoid catastrophic failures as well as to optimize the maintenance costs. This article presents a methodology for modeling the deterioration of slowly degrading assets based on an operating history. It consists of extracting degradation profiles by grouping together assets that exhibit similar degradation sequences using an unsupervised classification technique derived from artificial intelligence. The obtained clusters are used to build the performance prediction models. This methodology is applied to a sample of a stormwater drainage culvert dataset.

Keywords: artificial Intelligence, clustering, culvert, regression model, slow degradation

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Authors: Reggie Chandra

Abstract:

Trafficaccidents and traffic signal optimization are correlated. However, 70-90% of the traffic signals across the USA are not synchronized. The reason behind that is insufficient resources to create and implement timing plans. In this work, we will discuss the use of a breakthrough Artificial Intelligence (AI) technology to optimize traffic flow and collect 24/7/365 accurate traffic data using a vehicle detection system. We will discuss what are recent advances in Artificial Intelligence technology, how does AI work in vehicles, pedestrians, and bike data collection, creating timing plans, and what is the best workflow for that. Apart from that, this paper will showcase how Artificial Intelligence makes signal timing affordable. We will introduce a technology that uses Convolutional Neural Networks (CNN) and deep learning algorithms to detect, collect data, develop timing plans and deploy them in the field. Convolutional Neural Networks are a class of deep learning networks inspired by the biological processes in the visual cortex. A neural net is modeled after the human brain. It consists of millions of densely connected processing nodes. It is a form of machine learning where the neural net learns to recognize vehicles through training - which is called Deep Learning. The well-trained algorithm overcomes most of the issues faced by other detection methods and provides nearly 100% traffic data accuracy. Through this continuous learning-based method, we can constantly update traffic patterns, generate an unlimited number of timing plans and thus improve vehicle flow. Convolutional Neural Networks not only outperform other detection algorithms but also, in cases such as classifying objects into fine-grained categories, outperform humans. Safety is of primary importance to traffic professionals, but they don't have the studies or data to support their decisions. Currently, one-third of transportation agencies do not collect pedestrian and bike data. We will discuss how the use of Artificial Intelligence for data collection can help reduce pedestrian fatalities and enhance the safety of all vulnerable road users. Moreover, it provides traffic engineers with tools that allow them to unleash their potential, instead of dealing with constant complaints, a snapshot of limited handpicked data, dealing with multiple systems requiring additional work for adaptation. The methodologies used and proposed in the research contain a camera model identification method based on deep Convolutional Neural Networks. The proposed application was evaluated on our data sets acquired through a variety of daily real-world road conditions and compared with the performance of the commonly used methods requiring data collection by counting, evaluating, and adapting it, and running it through well-established algorithms, and then deploying it to the field. This work explores themes such as how technologies powered by Artificial Intelligence can benefit your community and how to translate the complex and often overwhelming benefits into a language accessible to elected officials, community leaders, and the public. Exploring such topics empowers citizens with insider knowledge about the potential of better traffic technology to save lives and improve communities. The synergies that Artificial Intelligence brings to traffic signal control and data collection are unsurpassed.

Keywords: artificial intelligence, convolutional neural networks, data collection, signal control, traffic signal

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Authors: Arun Kumar, Ravindra Pal Verma, Harsh Sharma, Shani Kumar

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For the present study samples was collected from 20 donors with unknown blood group and secretor status had been determined from saliva by using biological fluid. ABO typing on the concentrated samples was successfully performed after 1 month of storage. Urine stained clothing samples are often submitted to forensic science laboratories for ABH blood group antigen determination. The serogenetic markers of semen stains submitted can be used to determine the origin of any of these samples. ABH blood group substances have previously been identified from urine. ABH blood group substance is low in urine in comparison with other body fluids.

Keywords: ABH blood group, crime scene, serological markers, body fluids and urine

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Authors: Y. P. Wang, J. K. Chen, C. H. Lee, G. H. Huang, M. C. Wang, S. W. Chen, Y. T. Kuan, H. C. Lin, C. Y. Huang, W. H. Liang, W. C. Lin, H. C. Yu

Abstract:

The hi-tech industries in the Science Park at southern Taiwan were heavily damaged by a strong earthquake early 2016. The financial loss in this event was attributed primarily to the automated stocker system handling fully processed products, and recovery of the automated stocker system from the aftermath proved to contribute major lead time. Therefore, development of effective means for protection of stockers against earthquakes has become the highest priority for risk minimization and business continuity. This study proposes to mitigate the seismic response of the stockers by introducing viscous fluid dampers in between the ceiling and the top of the stockers. The stocker is expected to vibrate less violently with a passive control force on top. Linear damper is considered in this application with an optimal damping coefficient determined from a preliminary parametric study. The damper is small in size in comparison with those adopted for building or bridge applications. Component test of the dampers has been carried out to make sure they meet the design requirement. Shake table tests have been further conducted to verify the proposed scheme under realistic earthquake conditions. Encouraging results have been achieved by effectively reducing the seismic responses of up to 60% and preventing the FOUPs from falling off the shelves that would otherwise be the case if left unprotected. Effectiveness of adopting a viscous fluid damper for seismic control of the stocker on top against the ceiling has been confirmed. This technique has been adopted by Macronix International Co., LTD for seismic retrofit of existing stockers. Demonstrative projects on the application of the proposed technique are planned underway for other companies in the display industry as well.

Keywords: hi-tech industries, seismic protection, automated stocker system, viscous fluid damper

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Authors: Mitesh Rathod, Jungho Ahn, Noo Li Jeon, Junghoon Lee

Abstract:

Endothelial cells respond to cues from both biochemical as well as micro mechanical environment. Significant effort has been directed to understand the effects of biochemical signaling, however, relatively little is known about regulation of endothelial cell biology by the micro mechanical environment. Numerous studies have been performed to understand how physical forces regulate endothelial cell behavior. In this regard, past studies have majorly focused on exploring how fluid shear stress governs endothelial cell behavior. Parallel plate flow chambers and rectangular microchannels are routinely employed for applying fluid shear force on endothelial cells. However, these studies fall short in mimicking the in vivo like micro environment from topological aspects. Few studies have only used circular microchannels to replicate in vivo like condition. Seldom efforts have been directed to elucidate the combined effect of topology, substrate rigidity and fluid shear stress on endothelial cell response. In this regard, we demonstrate a facile fabrication process to develop a hybrid polydimethylsiloxane microfluidic platform to study endothelial cell biology. On a single chip microchannels with different cross sections i.e., circular, rectangular and square have been fabricated. In addition, our fabrication approach allows variation in the substrate rigidity along the channel length. Two different variants of polydimethylsiloxane, namely Sylgard 184 and Sylgard 527, were utilized to achieve the variation in rigidity. Moreover, our approach also enables in creating Y bifurcation circular microchannels. Our microfluidic platform thus facilitates for conducting studies pertaining to endothelial cell morphology with respect to change in topology, substrate rigidity and fluid flow on a single chip. The hybrid platform was tested by culturing Human Umbilical Vein Endothelial Cells in circular microchannels with varying substrate rigidity, and exposed to fluid shear stress of 12 dynes/cm² and static conditions. Results indicate the cell area response to flow induced shear stress was governed by the underlying substrate mechanics.

Keywords: hybrid, microfluidic platform, PDMS, shear flow, substrate rigidity

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Authors: S. Wakim, M. Nemer, B. Zeghondy, B. Ghannam, C. Bouallou

Abstract:

Designing the optimal heat exchanger is still an essential objective to be achieved. Parametrical optimization involves the evaluation of the heat exchanger dimensions to find those that best satisfy certain objectives. This method contributes to an enhanced design rather than an optimized one. On the contrary, topology optimization finds the optimal structure that satisfies the design objectives. The huge development in metal additive manufacturing allowed topology optimization to find its way into engineering applications especially in the aerospace field to optimize metal structures. Using topology optimization in 3d heat and mass transfer problems requires huge computational time, therefore coupling it with CFD simulations can reduce this it. However, existed CFD models cannot be coupled with topology optimization. The CFD model must allow creating a uniform mesh despite the initial geometry complexity and also to swap the cells from fluid to solid and vice versa. In this paper, a porous media approach compatible with topology optimization criteria is developed. It consists of modeling the fluid region of the heat exchanger as porous media having high porosity and similarly the solid region is modeled as porous media having low porosity. The switching from fluid to solid cells required by topology optimization is simply done by changing each cell porosity using a user defined function. This model is tested on a plate and fin heat exchanger and validated by comparing its results to experimental data and simulations results. Furthermore, this model is used to perform a material reallocation based on local criteria to optimize a plate and fin heat exchanger under a constant heat duty constraint. The optimized fin uses 20% fewer materials than the first while the pressure drop is reduced by about 13%.

Keywords: computational methods, finite element method, heat exchanger, porous media, topology optimization

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Authors: M. H. Alhajeri, Hamad M. Alhajeri, A. H. Alenezi

Abstract:

This paper reports a Computational Fluid Dynamics (CFD) investigation for a high-temperature high-pressure filtration (ceramic candle filter). However, parallel flow to the filter is considered in this study. Different face (filtration) velocities are examined using the CFD code, FLUENT. Different sizes of particles are tracked through the domain to find the height at which the particles will impinge on the filter surface. Furthermore, particle distribution around the filter (or filter cake) is studied to design efficient cleaning mechanisms. Gravity effect to the particles with various inlet velocities and pressure drop are both considered. In the CFD study, it is found that the gravity influence should not be ignored if the particle sizes exceed 1 micron.

Keywords: fluid flow, CFD, filtration, HTHP

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Authors: H. Aminfar, M. Mohammadpourfard, K. Khajeh

Abstract:

This paper has focused on the most important parameters in the LSC uptake; inlet Re number and Sc number in the presence of non-uniform magnetic field. The magnetic field is arising from the thin wire with electric current placed vertically to the arterial blood vessel. According to the results of this study, applying magnetic field can be a treatment for atherosclerosis by reducing LSC along the vessel wall. Homogeneous porous layer as a arterial wall has been regarded. Blood flow has been considered laminar and incompressible containing Ferro fluid (blood and 4 % vol. Fe₃O₄) under steady state conditions. Numerical solution of governing equations was obtained by using the single-phase model and control volume technique for flow field.

Keywords: LDL surface concentration (LSC), magnetic field, computational fluid dynamics, porous wall

Procedia PDF Downloads 408

Authors: H. Alabed, K. Abuzayan, J. Ezarrugh, S. Ali, M. Touba

Abstract:

Ramadan requires individuals to abstain from food and fluid intake between sunrise and sunset, Physiological considerations predict that poorer mood, Physical performance and mental performance will result. In addition, Any difficulties will be worsened because preparations for fasting and recovery from it often mean that nocturnal sleep is decreased in length and this independently affects mood and performance. A difficulty of interpretation in many studies is that the observed changes could be due to fasting but also to the decreased length of sleep and altered food and fluid intakes before and after the daytime fasting. These factors were separated in this study, Which took place over three separate days and compared the effects of different durations of fasting (4, 8 or 16 h) upon a wide variety of measures (including subjective and objective assessments of performance, body composition, Dehydration and responses to a short bout of exercise) but with an unchanged amount of nocturnal sleep, Controlled supper the previous evening, Controlled intakes at breakfast and daytime naps not being allowed. Many of the negative effects of fasting observed in previous studies were present in this experiment also. These findings indicate that fasting was responsible for many of the changes previously observed, Though some effect of sleep loss, Particularly if occurring on successive days (as would occur in Ramadan) cannot be excluded.

Keywords: Drinking, eating, mental performance, physical performance, social activity, blood, sleepiness

Procedia PDF Downloads 314

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

Abstract:

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

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

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Authors: Gopikrishnan, Bharathiraja, Boopalan, Jensin Joshua

Abstract:

The Pitot static tube has proven their values and practicability in measuring velocity of fluids for many years. With the aim of extensive usage of such Pitot tube systems, one of the major enabling technologies is to use the design and fabricate a high sensitive pitot tube for the purpose of calibration of the subsonic wind tunnel. Calibration of wind tunnel is carried out by using different instruments to measure variety of parameters. Using too many instruments inside the tunnel may not only affect the fluid flow but also lead to drag or losses. So, it is essential to replace the different system with a single system that would give all the required information. This model of high sensitive Pitot tube has been designed to ease the calibration process. It minimizes the use of different instruments and this single system is capable of calibrating the wind tunnel test section. This Pitot static tube is completely digitalized and so that the velocity data`s can be collected directly from the instrument. Since the turbulence factors are dependent on velocity, the data’s that are collected from the pitot static tube are then processed and the level of turbulence in the fluid flow is calculated. It is also capable of measuring the pressure distribution inside the wind tunnel and the flow angularity of the fluid. Thus, the well-designed high sensitive Pitot static tube is utilized in calibrating the tunnel and also for the measurement of turbulence.

Keywords: pitot static tube, turbulence, wind tunnel, velocity

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Authors: Rashmi Dubey

Abstract:

The study aims at investigating the onset of thermal convection in an inclined porous layer saturated with a non-Newtonian fluid. The layer is infinitely extended and has a finite width confined between two boundaries with constant pressure conditions, where the lower one is maintained at a higher temperature. Over the years, this area of research has attracted many scientists and researchers, for it has a plethora of applications in the fields of sciences and engineering, such as in civil engineering, geothermal sites, petroleum industries, etc.Considering the possibilities in a practical scenario, an inclined porous layer is considered, which can be used to develop a generalized model applicable to any inclination. Using the isobaric boundaries, the hydrodynamic boundary conditions are derived for the power-law model and are used to obtain the basic state flow. The convection in the basic state flow is driven by the thermal buoyancy in the flow system and is carried away further due to hydrodynamic boundaries. A linear stability analysis followed by a normal-mode analysis is done to investigate the onset of convection in the buoyancy-driven flow. The analysis shows that the convective instability is always initiated by the non-traveling modes for the Newtonian fluid, but prevails in the form of oscillatory modes, for up to a certain inclination of the porous layer. However, different behavior is observed for the dilatant and pseudoplastic fluids.

Keywords: thermal convection, linear stability, porous media flow, Inclined porous layer

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Authors: Liu-Chao Qiu

Abstract:

The damage caused by surge waves generated in water bodies by flow-like landslides can be very high in terms of human lives and economic losses. The complicated phenomena occurred in this highly unsteady process are difficult to model because three interacting phases: air, water and sediment are involved. The problem therefore is challenging since the effects of non-Newtonian fluid describing the rheology of the flow-like landslides, multi-phase flow and free surface have to be included in the simulation. In this work, the commercial computational fluid dynamics (CFD) package FLUENT is used to model the surge waves due to flow-like landslides. The comparison between the numerical results and experimental data reported in the literature confirms the accuracy of the method.

Keywords: flow-like landslide, surge wave, VOF, non-Newtonian fluids, multi-phase flows, free surface flow

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Authors: Ahmed Atef, Mohamed Alhasheem, Eman Beshr

Abstract:

In this paper, an enhanced DC microgrid design is proposed using the DAB converter as a conversion unit in order to harvest the maximum power from the PV array. Each connected DAB converter is controlled with an enhanced control strategy. The controller is based on the artificial intelligence (AI) technique to regulate the terminal PV voltage through the phase shift angle of each DAB converter. In this manner, no need for a Maximum Power Point Tracking (MPPT) unit to set the reference of the PV terminal voltage. This strategy overcomes the stability issues of the DC microgrid as the response of converters is superior compared to the conventional strategies. The proposed PV interface system is modelled and simulated using MATLAB/SIMULINK. The simulation results reveal an accurate and fast response of the proposed design in case of irradiance changes.

Keywords: DC microgrid, DAB converter, parallel operation, artificial intelligence, fast response

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Authors: Balamurugan L.

Abstract:

Artificial intelligence (AI) and its applications in Intellectual Property Rights (IPR) has been significantly growing in recent years. In last couple of years, AI tools for Patent Research and Patent Analytics have been well-stabilized in terms of accuracy of references and representation of identified patent insights. However, AI tools for Patent Prosecution and Patent Litigation are still in the nascent stage and there may be a significant potential if such market is explored further. Our research is primarily focused on identifying potential whitespaces and schematic algorithms to automate the Patent Prosecution and Patent Litigation Process of the Intellectual Property. The schematic algorithms may assist leading AI tool developers, to explore such opportunities in the field of Intellectual Property. Our research is also focused on identification of pitfalls of the AI. For example, Information Security and its impact in IPR, and Potential remediations to sustain the IPR in the digital environment.

Keywords: artificial intelligence, patent analytics, patent drafting, patent litigation, patent prosecution, patent research

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Authors: M. Amrita, R. R. Srikant, A. V. Sita Rama Raju

Abstract:

Water miscible cutting fluids are conventionally used to lubricate and cool the machining zone. But issues related to health hazards, maintenance and disposal costs have limited their usage, leading to application of Minimum Quantity Lubrication (MQL). To increase the effectiveness of MQL, nanocutting fluids are proposed. In the present work, water miscible nanographite cutting fluids of varying concentration are applied at cutting zone by two systems A and B. System A utilizes high pressure air and supplies cutting fluid at a flow rate of 1ml/min. System B uses low pressure air and supplies cutting fluid at a flow rate of 5ml/min. Their performance in machining is evaluated by measuring cutting temperatures, tool wear, cutting forces and surface roughness and compared with dry machining and flood machining. Application of nano cutting fluid using both systems showed better performance than dry machining. Cutting temperatures and cutting forces obtained by both techniques are more than flood machining. But tool wear and surface roughness showed improvement compared to flood machining. Economic analysis has been carried out in all the cases to decide the applicability of the techniques.

Keywords: economic analysis, machining, minimum quantity lubrication, nanofluid

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Authors: Hae-Won Seo, Yong-Gu Lee

Abstract:

Recent progress in the next generation of automobile technology is geared towards incorporating information technology into cars. Collectively called smart cars are bringing intelligence to cars that provides comfort, convenience and safety. A branch of smart cars is connected-car system. The key concept in connected-cars is the sharing of driving information among cars through decentralized manner enabling collective intelligence. This paper proposes a foundation of the information model that is necessary to define the driving information for smart-cars. Road conditions are modeled through a unique data structure that unambiguously represent the time variant traffics in the streets. Additionally, the modeled data structure is exemplified in a navigational scenario and usage using UML. Optimal driving route searching is also discussed using the proposed data structure in a dynamically changing road conditions.

Keywords: connected-car, data modeling, route planning, navigation system

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Authors: Ahmed Radwan, Ahmed Abdel Ghaney

Abstract:

This paper delves into the transformative potential of artificial intelligence (AI) in fostering creativity within the domain of architecture education, especially with a specific emphasis on its implications within the Design Studios; the convergence of AI and architectural pedagogy has introduced avenues for redefining the boundaries of creative expression and problem-solving. By harnessing AI-driven tools, students and educators can collaboratively explore a spectrum of design possibilities, stimulate innovative ideation, and engage in multidimensional design processes. This paper investigates the ways in which AI contributes to architectural creativity by facilitating generative design, pattern recognition, virtual reality experiences, and sustainable design optimization. Furthermore, the study examines the balance between AI-enhanced creativity and the preservation of core principles of architectural design/education, ensuring that technology is harnessed to augment rather than replace foundational design skills. Through an exploration of Egypt's architectural heritage and contemporary challenges, this research underscores how AI can synergize with cultural context and historical insights to inspire cutting-edge architectural solutions. By analyzing AI's impact on nurturing creativity among Egyptian architecture students, this paper seeks to contribute to the ongoing discourse on the integration of technology within global architectural education paradigms. It is hoped that this research will guide the thoughtful incorporation of AI in fostering creativity while preserving the authenticity and richness of architectural design education in Egypt and beyond.

Keywords: architecture, artificial intelligence, architecture education, Egypt

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Authors: Kate Benedicta Amenador, Dianjian Wang, Bright Nkrumah

Abstract:

This extensive bibliometric study explores the dynamic influence of artificial intelligence in the field of English as a Foreign Language (EFL) between 2012 and 2024. The study, which examined 4,500 articles from Google Scholar, Modern Language Association Linguistics Abstracts, Web of Science, Scopus, Researchgate, and library genesis databases, indicates that AI integration in EFL is on the rise. This notable increase is ascribed to a variety of transformative events, including increased academic funding for higher education and the COVID-19 epidemic. The results of the study identify leading contributors, prominent authors, publishers and sources, with the United States, China and the United Kingdom emerging as key contributors. The co-occurrence analysis of key terms reveals five clusters highlighting patterns in AI-enhanced language instruction and learning, including evaluation strategies, educational technology, learning motivation, EFL teaching aspects, and learner feedback. The study also discusses the impact of various AIs in enhancing EFL writing skills with software such as Grammarly, Quilbot, and Chatgpt. The current study recognizes limitations in database selection and linguistic constraints. Nevertheless, the results provide useful insights for educators, researchers and policymakers, inspiring and guiding a cross-disciplinary collaboration and creative pedagogical techniques and approaches to teaching and learning in the future.

Keywords: artificial intelligence, bibliometrics study, VOSviewer visualization, English as a foreign language

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Authors: Emanuele Bonamente, Andrea Aquino, Franco Cotana

Abstract:

The exploitation of the low-temperature geothermal resource via ground-source heat pumps is often limited by the high investment cost mainly due to borehole drilling. From the monitoring of a prototypal system currently used by a commercial building, it was found that a simple upgrade of the conventional layout, obtained including a thermal storage between the ground-source heat exchangers and the heat pump, can optimize the ground energy exploitation requiring for shorter/fewer boreholes. For typical applications, a reduction of up to 66% with respect to the conventional layout can be easily achieved. Results from the monitoring campaign of the prototype are presented in this paper, and upgrades of the thermal storage using phase change materials (PCMs) are proposed using computational fluid dynamics simulations. The PCM thermal storage guarantees an improvement of the system coefficient of performance both for summer cooling and winter heating (up to 25%). A drastic reduction of the storage volume (approx. 1/10 of the original size) is also achieved, making it possible to easily place it within the technical room, avoiding extra costs for underground displacement. A preliminary optimization of the PCM geometry is finally proposed.

Keywords: computational fluid dynamics (CFD), geothermal energy, ground-source heat pumps, phase change materials (PCM)

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Authors: Omar Hussein El Ayadi, Ali Mustafa Alkekly, Nader Ahmad Musa

Abstract:

Search and evaluate locale source of raw material which can be used as drilling fluid is one of most important economical target. Hopefully, to use Libyan clay that cost less than importing it from outside. Resistivity measurement and control is of primary concern in connection with electrical logging. The influences of resistivity utilizing Umm Arrazam clay were laboratory investigated at ambient condition (room temperature, atmospheric pressure) to fulfill the aim of the study. Several tests were carried-out on three sets of mud mixture with different densities (8.7, 9.0, and 9.3 ppg) as base mud. The resistivity of mud, mud filtrate, and mud cake were measured using resistivity- meter. Mud water losses were also measured. Several results obtained to describe the relationship between the resistivity ratios of mud filtrate to the mud, and the mud cake to mud. The summary of conclusion is that there are no great differences were obtained during comparison of resistivity and water loss of Umm Arrazam and Wyoming Clay.

Keywords: petroleum, drilling, mug, geological engineering

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Authors: Rashid S. Mohammad, Shicheng Zhang, Xinzhe Zhao

Abstract:

In tight oil reservoirs, wettability alteration has generally been considered as an effective way to remove fracturing fluid retention on the surface of the fracture and consequently improved oil production. However, there is a lack of a reliable productivity prediction model to show the relationship between the wettability and oil production in tight oil well. In this paper, a new oil productivity prediction model of immiscible oil-water flow and miscible CO₂-oil flow accounting for wettability is developed. This mathematical model is established by considering two different length scales: nonporous network and propped fractures. CO₂ flow diffuses in the nonporous network and high velocity non-Darcy flow in propped fractures are considered by taking into account the effect of wettability alteration on capillary pressure and relative permeability. A laboratory experiment is also conducted here to validate this model. Laboratory experiments have been designed to compare the water saturation profiles for different contact angle, revealing the fluid retention in rock pores that affects capillary force and relative permeability. Four kinds of brines with different concentrations are selected here to create different contact angles. In water-wet porous media, as the system becomes more oil-wet, water saturation decreases. As a result, oil relative permeability increases. On the other hand, capillary pressure which is the resistance for the oil flow increases as well. The oil production change due to wettability alteration is the result of the comprehensive changes of oil relative permeability and capillary pressure. The results indicate that wettability is a key factor for fracturing fluid retention removal and oil enhancement in tight reservoirs. By incorporating laboratory test into a mathematical model, this work shows the relationship between wettability and oil production is not a simple linear pattern but a parabolic one. Additionally, it can be used for a better understanding of optimization design of fracturing fluids.

Keywords: wettability, relative permeability, fluid retention, oil production, unconventional and tight reservoirs

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Authors: J. K. Adedeji, S. T. Ijatuyi

Abstract:

The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p₁), fractured layer (p₂), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable g_r (gravitational resistance) can be deduced from the elevation and apparent resistivity p_a. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: gravitational resistance, neural network, non-linear, pattern recognition

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Authors: Matthew Stephenson

Abstract:

We study the electrical conductivity of strongly disordered, strongly coupled quantum field theories, holographically dual to non-perturbatively disordered uncharged black holes. The computation reduces to solving a diffusive hydrostatic equation for an emergent horizon fluid. We demonstrate that a large class of theories in two spatial dimensions have a universal conductivity independent of disorder strength, and rigorously rule out disorder-driven conductor-insulator transitions in many theories. We present a (fine-tuned) axion-dilaton bulk theory which realizes the conductor-insulator transition, interpreted as a classical percolation transition in the horizon fluid. We address aspects of strongly disordered holography that can and cannot be addressed via mean-field modeling, such as massive gravity.

Keywords: theoretical physics, black holes, holography, high energy

Procedia PDF Downloads 178