Search results for: grid-interactive efficient buildings (GEB)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6584

Search results for: grid-interactive efficient buildings (GEB)

1784 First Principle-Based Dft and Microkinetic Simulation of Co-Conversion of Carbon Dioxide and Methane on Single Iridium Atom Doped Hematite with Surface Oxygen Defect

Authors: Kefale W. Yizengaw, Delele Worku Ayele, Jyh-Chiang Jiang

Abstract:

The catalytic co-conversion of CO₂ and CH₄ to value-added compounds has become one of the promising approaches to addressing global climate change by having valuable fossil fuels. Thedirect co-conversion of CO₂ and CH₄ to value-added compounds is attractive but tremendously challenging because of both molecules' thermodynamic stability and kinetic inertness. In the present study, a single iridium atom doped and a single oxygen atom defect hematite (110)surface model catalyst, which can comprehend direct C–O coupling based on simultaneous activation of CO2 and CH4 was studied using density functional theory plus U (DFT + U)calculations. The presence of dual active sites on the Ir/Fe₂O₃(110)-OV surface catalyst enablesCO₂ activation on the Ir site and CH₄ activation at the defect site. The electron analysis for the theco-adsorption of CO₂ and CH₄ deals with the electron redistribution on the surface and clearly shows the synergistic effect for simultaneous CO₂ and CH₄ activation on Ir/α- Fe₂O₃(110)-OVsurface. The microkinetic analysis shows that the dissociation of CH4 to CH3 * and H* plays an excellent role in the C–O coupling. The coverage analysis for the intermediate products of the microkinetic simulation results indicates that C–O coupling is the reaction limiting step. Finally, after the CH₃O* intermediate product species is produced, the radical hydrogen species spontaneously diffuse to the CH3O* intermediate product to form methanol at around 490 [K]. The present work provides mechanistic and kinetic insights into the direct C–O coupling of CO₂and CH₄, which could help design more-efficient catalysts.

Keywords: co-conversion, C–O coupling, doping, oxygen vacancy, microkinetic

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1783 Optimization of the Culture Medium, Incubation Period, pH and Temperatures for Maximal Dye Bioremoval Using A. Fumigates

Authors: Wafaa M. Abd El-Rahim, Magda A. El-Meleigy, Eman Refaat

Abstract:

This study dealing with optimization the conditions affecting the formation of extracellular lignin- degrading enzymes to achieve maximal decolorization activity of Direct Violet dye by one fungal strain. In this study Aspergillus fumigates fungal strain used for production extracellular ligninolytic enzymes for removing Direct Violet dye under different conditions: culture medium, incubation period, pH and temperatures. The results indicted that the removal efficiency of A. fumigatus was enhanced by addition glucose and peptone to the culture medium. The addition of peptone and glucose was found to increase the decolorization activity of the fungal isolate from 51.38% to 93.74% after 4 days of incubation. The highest production of extracellular lignin degrading enzymes also recorded in Direct Violet dye medium supplemented with peptone and glucose. It was also found the decolorization activity of A. fumigatus was decreased gradually by increasing the incubation period up to 4 days. Also it was found that the fungal strain can grow and produce extracellular ligninolytic enzymes which accompanied by efficient removal of Direct Violet dye in a wide pH range of 4-8. The results also found that the maximal biosynthesis of ligninolytic enzymes which accompanied with maximal removal of Direct Violet dye was obtained at a temperature of 28C. This indicates that the different conditions of culture medium, incubation period, pH and temperatures are effective on dye decolorization on the fungal biomass and played a role in Direct Violet dye removal along with enzymatic activity of A. fumigatus.

Keywords: A. fumigates, extracellular lignin- degrading enzymes, textile dye, dye removing

Procedia PDF Downloads 280
1782 Assessment of Climate Change Impact on Meteorological Droughts

Authors: Alireza Nikbakht Shahbazi

Abstract:

There are various factors that affect climate changes; drought is one of those factors. Investigation of efficient methods for estimating climate change impacts on drought should be assumed. The aim of this paper is to investigate climate change impacts on drought in Karoon3 watershed located south-western Iran in the future periods. The atmospheric general circulation models (GCM) data under Intergovernmental Panel on Climate Change (IPCC) scenarios should be used for this purpose. In this study, watershed drought under climate change impacts will be simulated in future periods (2011 to 2099). Standard precipitation index (SPI) as a drought index was selected and calculated using mean monthly precipitation data in Karoon3 watershed. SPI was calculated in 6, 12 and 24 months periods. Statistical analysis on daily precipitation and minimum and maximum daily temperature was performed. LRAS-WG5 was used to determine the feasibility of future period's meteorological data production. Model calibration and verification was performed for the base year (1980-2007). Meteorological data simulation for future periods under General Circulation Models and climate change IPCC scenarios was performed and then the drought status using SPI under climate change effects analyzed. Results showed that differences between monthly maximum and minimum temperature will decrease under climate change and spring precipitation shall increase while summer and autumn rainfall shall decrease. The precipitation occurs mainly between January and May in future periods and summer or autumn precipitation decline and lead up to short term drought in the study region. Normal and wet SPI category is more frequent in B1 and A2 emissions scenarios than A1B.

Keywords: climate change impact, drought severity, drought frequency, Karoon3 watershed

Procedia PDF Downloads 246
1781 One-Hit Multiple Instance Logistic Regression for Binary Classification and Its Application to Atomic Force Microscopy Images for Bladder Cancer Determination

Authors: Eugene Demidenko, John Seigne, Igor Sokolov

Abstract:

Multiple instance classification is a known machine learning tech-nique when only a bag of features is labeled. The method of binary multiple instance classification, termed multiple instance logistic regression (LR), received the most attention as a well-defined statistical model. This algorithm is realized in several computer languages, including R (milr) and MATLAB. This work suggests improving this model, which is called the one-hit multiple instance LR. Unlike the existing ap-proach, where unknown labels are treated as missing observations, our model directly implements the ML approach. As such, it is methodologically straightforward and computationally stable, especially when features are highly correlated and/or bags are heterogeneous. Since the one-hit LR admits a closed form for the log-likelihood function, an efficient Fisher scoring algorithm applies with the variances of the regres-sion coefficients computed through the inverse of the Fisher information matrix at the final iteration. Numerical experiments demonstrate the superiority of the one-hit LR in terms of regression coefficients and classification accuracy. Another advantage of our approach is developing the optimal probability threshold for classification (the traditional threshold equals 0 5). The one-hit LR is illustrated with a noninvasive bladder cancer identification where each patient, in the multiple instance terminol-ogy ’bag,’ contains feature images of multiple cells from a urine sample of the same individual. We show that the one-hit LR with two Atomic Force Microscopy (AFM) image features leads to a perfect (AUC=1) or almost perfect (AUC=0.978) classifica-tion of normal and cancer patients among 20 individuals. The -value 0.0018 confirms that the latter AUC is unlikely to be obtained by chance.

Keywords: AUC, classification accuracy, classification p-value, Fisher information, ML, ROC curve

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1780 Application of Federated Learning in the Health Care Sector for Malware Detection and Mitigation Using Software-Defined Networking Approach

Authors: A. Dinelka Panagoda, Bathiya Bandara, Chamod Wijetunga, Chathura Malinda, Lakmal Rupasinghe, Chethana Liyanapathirana

Abstract:

This research takes us forward with the concepts of Federated Learning and Software-Defined Networking (SDN) to introduce an efficient malware detection technique and provide a mitigation mechanism to give birth to a resilient and automated healthcare sector network system by also adding the feature of extended privacy preservation. Due to the daily transformation of new malware attacks on hospital Integrated Clinical Environment (ICEs), the healthcare industry is at an undefinable peak of never knowing its continuity direction. The state of blindness by the array of indispensable opportunities that new medical device inventions and their connected coordination offer daily, a factor that should be focused driven is not yet entirely understood by most healthcare operators and patients. This solution has the involvement of four clients in the form of hospital networks to build up the federated learning experimentation architectural structure with different geographical participation to reach the most reasonable accuracy rate with privacy preservation. While the logistic regression with cross-entropy conveys the detection, SDN comes in handy in the second half of the research to stack up the initial development phases of the system with malware mitigation based on policy implementation. The overall evaluation sums up with a system that proves the accuracy with the added privacy. It is no longer needed to continue with traditional centralized systems that offer almost everything but not privacy.

Keywords: software-defined network, federated learning, privacy, integrated clinical environment, decentralized learning, malware detection, malware mitigation

Procedia PDF Downloads 191
1779 Thermolysin Entrapment in a Gold Nanoparticles/Polymer Composite: Construction of an Efficient Biosensor for Ochratoxin a Detection

Authors: Fatma Dridi, Mouna Marrakchi, Mohammed Gargouri, Alvaro Garcia Cruz, Sergei V. Dzyadevych, Francis Vocanson, Joëlle Saulnier, Nicole Jaffrezic-Renault, Florence Lagarde

Abstract:

An original method has been successfully developed for the immobilization of thermolysin onto gold interdigitated electrodes for the detection of ochratoxin A (OTA) in olive oil samples. A mix of polyvinyl alcohol (PVA), polyethylenimine (PEI) and gold nanoparticles (AuNPs) was used. Cross-linking sensors chip was made by using a saturated glutaraldehyde (GA) vapor atmosphere in order to render the two polymers water stable. Performance of AuNPs/ (PVA/PEI) modified electrode was compared to a traditional immobilized enzymatic method using bovine serum albumin (BSA). Atomic force microscopy (AFM) experiments were employed to provide a useful insight into the structure and morphology of the immobilized thermolysin composite membranes. The enzyme immobilization method influence the topography and the texture of the deposited layer. Biosensors optimization and analytical characteristics properties were studied. Under optimal conditions AuNPs/ (PVA/PEI) modified electrode showed a higher increment in sensitivity. A 700 enhancement factor could be achieved with a detection limit of 1 nM. The newly designed OTA biosensors showed a long-term stability and good reproducibility. The relevance of the method was evaluated using commercial doped olive oil samples. No pretreatment of the sample was needed for testing and no matrix effect was observed. Recovery values were close to 100% demonstrating the suitability of the proposed method for OTA screening in olive oil.

Keywords: thermolysin, A. ochratoxin , polyvinyl alcohol, polyethylenimine, gold nanoparticles, olive oil

Procedia PDF Downloads 594
1778 Bias-Corrected Estimation Methods for Receiver Operating Characteristic Surface

Authors: Khanh To Duc, Monica Chiogna, Gianfranco Adimari

Abstract:

With three diagnostic categories, assessment of the performance of diagnostic tests is achieved by the analysis of the receiver operating characteristic (ROC) surface, which generalizes the ROC curve for binary diagnostic outcomes. The volume under the ROC surface (VUS) is a summary index usually employed for measuring the overall diagnostic accuracy. When the true disease status can be exactly assessed by means of a gold standard (GS) test, unbiased nonparametric estimators of the ROC surface and VUS are easily obtained. In practice, unfortunately, disease status verification via the GS test could be unavailable for all study subjects, due to the expensiveness or invasiveness of the GS test. Thus, often only a subset of patients undergoes disease verification. Statistical evaluations of diagnostic accuracy based only on data from subjects with verified disease status are typically biased. This bias is known as verification bias. Here, we consider the problem of correcting for verification bias when continuous diagnostic tests for three-class disease status are considered. We assume that selection for disease verification does not depend on disease status, given test results and other observed covariates, i.e., we assume that the true disease status, when missing, is missing at random. Under this assumption, we discuss several solutions for ROC surface analysis based on imputation and re-weighting methods. In particular, verification bias-corrected estimators of the ROC surface and of VUS are proposed, namely, full imputation, mean score imputation, inverse probability weighting and semiparametric efficient estimators. Consistency and asymptotic normality of the proposed estimators are established, and their finite sample behavior is investigated by means of Monte Carlo simulation studies. Two illustrations using real datasets are also given.

Keywords: imputation, missing at random, inverse probability weighting, ROC surface analysis

Procedia PDF Downloads 421
1777 Role of Vision Centers in Eliminating Avoidable Blindness Caused Due to Uncorrected Refractive Error in Rural South India

Authors: Ranitha Guna Selvi D, Ramakrishnan R, Mohideen Abdul Kader

Abstract:

Purpose: To study the role of Vision centers in managing preventable blindness through refractive error correction in Rural South India. Methods: A retrospective analysis of patients attending 15 Vision centers in Rural South India from a period of January 2021 to December 2021 was done. Medical records of 10,85,81 patients both new and reviewed, 79,562 newly registered patients and 29,019 review patient’s from15 Vision centers were included for data analysis. All the patients registered at the vision center underwent basic eye examination, including visual acuity, IOP measurement, Slit-lamp examination, retinoscopy, Fundus examination etc. Results: A total of 1,08,581 patients were included in the study. Of the total 1,08,581 patients, 79,562 were newly registered patients at Vision center and 29,019 were review patients. Males were 52,201(48.1%) and Females were 56,308(51.9) among them. The mean age of all examined patients was 41.03 ± 20.9 years (Standard deviation) and ranged from 01 – 113 years. Presenting mean visual acuity was 0.31 ± 0.5 in the right eye and 0.31 ± 0.4 in the left eye. Of the 1,08,581 patients 22,770 patients had refractive error in right eye and 22,721 patients had uncorrected refractive error in left eye. Glass prescription was given to 17,178 (15.8%) patients. 8,109 (7.5%) patients were referred to the base hospital for specialty clinic expert opinion or for cataract surgery. Conclusion: Vision center utilizing teleconsultation for comprehensive eye screening unit is a very effective tool in reducing the avoidable visual impairment caused due to uncorrected refractive error. Vision Centre model is believed to be efficient as it facilitates early detection and management of uncorrected refractive errors.

Keywords: refractive error, uncorrected refractive error, vision center, vision technician, teleconsultation

Procedia PDF Downloads 149
1776 An Effective Synthesis Method of Microwave Solution Combustion with the Application of Visible Light-Responsive Photocatalyst of Rb21 Dye

Authors: Rahul Jarariya

Abstract:

The textile industry uses various types of dyes and discharges a lot of highly coloured wastewater. It impacts the environment like allergic reaction, respiratory, skin problems, irritation to a mucous membrane, the upper respiratory tract has to the fore, Intoxicated dye discharges 40 to 50,000 tons with great concern. Spinel ferrites gained a lot of attention due to their wide application area from biomedical to wastewater treatment. Generally, spinel ferrite is known as M-Fe2O4. Spinel type nanoparticles possess high suspension stability. The synthesis method of Microwave solution combustion (MC) method is effective for nanoscale materials, including oxides, metals, alloys, and sulfides, works as fast and energy-efficient during the process. The review focuses on controlling, nanostructure and doping. The influence of the fuel concentration and the post-treatment temperature on the structural and magnetic properties. The effects of amounts of fuel and phase changes, particle size and shape, and magnetic properties can be characterized by various techniques. Urea is the most commonly used fuel. Ethanol or n-butanol is apt for removing impurities. As a result of the materials gives fine purity. Photocatalysis phenomena act with catalyst dosage to degrade dye from wastewater. Visible light responsive produces a large amount of hydroxyl (•OH) radical made the degradation efficiency of Rh21 type dye. It develops a narrow bandgap to make it suitable for enhanced photocatalytic activity.

Keywords: microwave solution combustion method, normal spinel, doped spinels, magnetic property, Rb21

Procedia PDF Downloads 190
1775 Integration of Technology through Instructional Systems Design

Authors: C. Salis, D. Zedda, M. F. Wilson

Abstract:

The IDEA project was conceived for teachers who are interested in enhancing their capacity to effectively implement the use of specific technologies in their teaching practice. Participating teachers are coached and supported as they explore technologies applied to the educational context. They access tools such as the technological platform developed by our team. Among the platform functionalities, teachers access an instructional systems design (ISD) tool (learning designer) that was adapted to the needs of our project. The tool is accessible from computers or mobile devices and used in association with other technologies to create new, meaningful learning environments. The objective of an instructional systems design is to guarantee the quality and effectiveness of education and to enhance learning. This goal involves both teachers who want to become more efficient in transferring knowledge or skills and students as the final recipient of their teaching. The use of Blooms’s taxonomy enables teachers to classify the learning objectives into levels of complexity and specificity, thus making it possible to highlight the kind of knowledge teachers would like their students to reach. The fact that the instructional design features can be visualized through the IDEA platform is a guarantee for those who are looking for specific educational materials to be used in their lessons. Despite the benefits offered, a number of teachers are reluctant to use ISD because the preparatory work of having to thoroughly analyze the teaching/learning objectives, the planning of learning material, assessment activities, etc., is long and felt to be time-consuming. This drawback is minimized using a learning designer, as the tool facilitates to reuse of the didactic contents having a clear view of the processes of analysis, planning, and production of educational or testing materials uploaded on our platform. In this paper, we shall present the feedback of the teachers who used our tool in their didactic.

Keywords: educational benefits, educational quality, educational technology, ISD tool

Procedia PDF Downloads 192
1774 Woodfuels as Alternative Source of Energy in Rural and Urban Areas in the Philippines

Authors: R. T. Aggangan

Abstract:

Woodfuels continue to be a major component of the energy supply mix of the Philippines due to increasing demand for energy that are not adequately met by decreasing supply and increasing prices of fuel oil such as liquefied petroleum gas (LPG) and kerosene. The Development Academy of the Philippines projects the demand of woodfuels in 2016 as 28.3 million metric tons in the household sector and about 105.4 million metric tons combined supply potentials of both forest and non-forest lands. However, the Revised Master Plan for Forestry Development projects a demand of about 50 million cu meters of fuelwood in 2016 but the capability to supply from local sources is only about 28 million cu meters indicating a 44 % deficiency. Household demand constitutes 82% while industries demand is 18%. Domestic household demand for energy is for cooking needs while the industrial demand is for steam power generation, curing barns of tobacco: brick, ceramics and pot making; bakery; lime production; and small scale food processing. Factors that favour increased use of wood-based energy include the relatively low prices (increasing oil-based fuel prices), availability of efficient wood-based energy utilization technology, increasing supply, and increasing population that cannot afford conventional fuels. Moreover, innovations in combustion technology and cogeneration of heat and power from biomass for modern applications favour biomass energy development. This paper recommends policies and strategic directions for the development of the woodfuel industry with the twin goals of sustainably supplying the energy requirements of households and industry.

Keywords: biomass energy development, fuelwood, households and industry, innovations in combustion technology, supply and demand

Procedia PDF Downloads 338
1773 Numerical Study of Elastic Performances of Sandwich Beam with Carbon-Fibre Reinforced Skins

Authors: Soukaina Ounss, Hamid Mounir, Abdellatif El Marjani

Abstract:

Sandwich materials with composite reinforced skins are mostly required in advanced construction applications with a view to ensure resistant structures. Their lightweight, their high flexural stiffness and their optimal thermal insulation make them a suitable solution to obtain efficient structures with performing rigidity and optimal energy safety. In this paper, the mechanical behavior of a sandwich beam with composite skins reinforced by unidirectional carbon fibers is investigated numerically through analyzing the impact of reinforcements specifications on the longitudinal elastic modulus in order to select the adequate sandwich configuration that has an interesting rigidity and an accurate convergence to the analytical approach which is proposed to verify performed numerical simulations. Therefore, concerned study starts by testing flexion performances of skins with various fibers orientations and volume fractions to determine those to use in sandwich beam. For that, the combination of a reinforcement inclination of 30° and a volume ratio of 60% is selected with the one with 60° of fibers orientation and 40% of volume fraction, this last guarantees to chosen skins an important rigidity with an optimal fibers concentration and a great enhance in convergence to analytical results in the sandwich model for the reason of the crucial core role as transverse shear absorber. Thus, a resistant sandwich beam is elaborated from a face-sheet constituted from two layers of previous skins with fibers oriented in 60° and an epoxy core; concerned beam has a longitudinal elastic modulus of 54 Gpa (gigapascal) that equals to the analytical value by a negligible error of 2%.

Keywords: fibers orientation, fibers volume ratio, longitudinal elastic modulus, sandwich beam

Procedia PDF Downloads 177
1772 Exploring the Spatial Relationship between Built Environment and Ride-hailing Demand: Applying Street-Level Images

Authors: Jingjue Bao, Ye Li, Yujie Qi

Abstract:

The explosive growth of ride-hailing has reshaped residents' travel behavior and plays a crucial role in urban mobility within the built environment. Contributing to the research of the spatial variation of ride-hailing demand and its relationship to the built environment and socioeconomic factors, this study utilizes multi-source data from Haikou, China, to construct a Multi-scale Geographically Weighted Regression model (MGWR), considering spatial scale heterogeneity. The regression results showed that MGWR model was demonstrated superior interpretability and reliability with an improvement of 3.4% on R2 and from 4853 to 4787 on AIC, compared with Geographically Weighted Regression model (GWR). Furthermore, to precisely identify the surrounding environment of sampling point, DeepLabv3+ model is employed to segment street-level images. Features extracted from these images are incorporated as variables in the regression model, further enhancing its rationality and accuracy by 7.78% improvement on R2 compared with the MGWR model only considered region-level variables. By integrating multi-scale geospatial data and utilizing advanced computer vision techniques, this study provides a comprehensive understanding of the spatial dynamics between ride-hailing demand and the urban built environment. The insights gained from this research are expected to contribute significantly to urban transportation planning and policy making, as well as ride-hailing platforms, facilitating the development of more efficient and effective mobility solutions in modern cities.

Keywords: travel behavior, ride-hailing, spatial relationship, built environment, street-level image

Procedia PDF Downloads 86
1771 Preparation and Characterization of Chitosan Nanoparticles for Delivery of Oligonucleotides

Authors: Gyati Shilakari Asthana, Abhay Asthana, Dharm Veer Kohli, Suresh Prasad Vyas

Abstract:

Purpose: The therapeutic potential of oligonucleotide (ODN) is primarily dependent upon its safe and efficient delivery to specific cells overcoming degradation and maximizing cellular uptake in vivo. The present study is focused to design low molecular weight chitosan nanoconstructs to meet the requirements of safe and effectual delivery of ODNs. LMW-chitosan is a biodegradable, water soluble, biocompatible polymer and is useful as a non-viral vector for gene delivery due to its better stability in water. Methods: LMW chitosan ODN nanoparticles (CHODN NPs) were formulated by self-assembled method using various N/P ratios (moles ratio of amine groups of CH to phosphate moieties of ODNs; 0.5:1, 1:1, 3:1, 5:1, and 7:1) of CH to ODN. The developed CHODN NPs were evaluated with respect to gel retardation assay, particle size, zeta potential and cytotoxicity and transfection efficiency. Results: Complete complexation of CH/ODN was achieved at the charge ratio of 0.5:1 or above and CHODN NPs displayed resistance against DNase I. On increasing the N/P ratio of CH/ODN, the particle size of the NPs decreased whereas zeta potential (ZV) value increased. No significant toxicity was observed at all CH concentrations. The transfection efficiency was increased on increasing N/P ratio from 1:1 to 3:1, whereas it was decreased with further increment in N/P ratio upto 7:1. Maximum transfection of CHODN NPs with both the cell lines (Raw 267.4 cells and Hela cells) was achieved at N/P ratio of 3:1. The results suggest that transfection efficiency of CHODN NPs is dependent on N/P ratio. Conclusion: Thus the present study states that LMW chitosan nanoparticulate carriers would be acceptable choice to improve transfection efficiency in vitro as well as in vivo delivery of oligonucleotide.

Keywords: LMW-chitosan, chitosan nanoparticles, biocompatibility, cytotoxicity study, transfection efficiency, oligonucleotide

Procedia PDF Downloads 853
1770 Geospatial Modeling Framework for Enhancing Urban Roadway Intersection Safety

Authors: Neeti Nayak, Khalid Duri

Abstract:

Despite the many advances made in transportation planning, the number of injuries and fatalities in the United States which involve motorized vehicles near intersections remain largely unchanged year over year. Data from the National Highway Traffic Safety Administration for 2018 indicates accidents involving motorized vehicles at traffic intersections accounted for 8,245 deaths and 914,811 injuries. Furthermore, collisions involving pedal cyclists killed 861 people (38% at intersections) and injured 46,295 (68% at intersections), while accidents involving pedestrians claimed 6,247 lives (25% at intersections) and injured 71,887 (56% at intersections)- the highest tallies registered in nearly 20 years. Some of the causes attributed to the rising number of accidents relate to increasing populations and the associated changes in land and traffic usage patterns, insufficient visibility conditions, and inadequate applications of traffic controls. Intersections that were initially designed with a particular land use pattern in mind may be rendered obsolete by subsequent developments. Many accidents involving pedestrians are accounted for by locations which should have been designed for safe crosswalks. Conventional solutions for evaluating intersection safety often require costly deployment of engineering surveys and analysis, which limit the capacity of resource-constrained administrations to satisfy their community’s needs for safe roadways adequately, effectively relegating mitigation efforts for high-risk areas to post-incident responses. This paper demonstrates how geospatial technology can identify high-risk locations and evaluate the viability of specific intersection management techniques. GIS is used to simulate relevant real-world conditions- the presence of traffic controls, zoning records, locations of interest for human activity, design speed of roadways, topographic details and immovable structures. The proposed methodology provides a low-cost mechanism for empowering urban planners to reduce the risks of accidents using 2-dimensional data representing multi-modal street networks, parcels, crosswalks and demographic information alongside 3-dimensional models of buildings, elevation, slope and aspect surfaces to evaluate visibility and lighting conditions and estimate probabilities for jaywalking and risks posed by blind or uncontrolled intersections. The proposed tools were developed using sample areas of Southern California, but the model will scale to other cities which conform to similar transportation standards given the availability of relevant GIS data.

Keywords: crosswalks, cyclist safety, geotechnology, GIS, intersection safety, pedestrian safety, roadway safety, transportation planning, urban design

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1769 Modelling of Geotechnical Data Using Geographic Information System and MATLAB for Eastern Ahmedabad City, Gujarat

Authors: Rahul Patel

Abstract:

Ahmedabad, a city located in western India, is experiencing rapid growth due to urbanization and industrialization. It is projected to become a metropolitan city in the near future, resulting in various construction activities. Soil testing is necessary before construction can commence, requiring construction companies and contractors to periodically conduct soil testing. The focus of this study is on the process of creating a spatial database that is digitally formatted and integrated with geotechnical data and a Geographic Information System (GIS). Building a comprehensive geotechnical (Geo)-database involves three steps: collecting borehole data from reputable sources, verifying the accuracy and redundancy of the data, and standardizing and organizing the geotechnical information for integration into the database. Once the database is complete, it is integrated with GIS, allowing users to visualize, analyze, and interpret geotechnical information spatially. Using a Topographic to Raster interpolation process in GIS, estimated values are assigned to all locations based on sampled geotechnical data values. The study area was contoured for SPT N-Values, Soil Classification, Φ-Values, and Bearing Capacity (T/m2). Various interpolation techniques were cross-validated to ensure information accuracy. This GIS map enables the calculation of SPT N-Values, Φ-Values, and bearing capacities for different footing widths and various depths. This study highlights the potential of GIS in providing an efficient solution to complex phenomena that would otherwise be tedious to achieve through other means. Not only does GIS offer greater accuracy, but it also generates valuable information that can be used as input for correlation analysis. Furthermore, this system serves as a decision support tool for geotechnical engineers.

Keywords: ArcGIS, borehole data, geographic information system, geo-database, interpolation, SPT N-value, soil classification, Φ-Value, bearing capacity

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1768 Wetting Induced Collapse Behavior of Loosely Compacted Kaolin Soil: A Microstructural Study

Authors: Dhanesh Sing Das, Bharat Tadikonda Venkata

Abstract:

Collapsible soils undergo significant volume reduction upon wetting under the pre-existing mechanically applied normal stress (inundation pressure). These soils exhibit a very high strength in air-dried conditions and can carry up to a considerable magnitude of normal stress without undergoing significant volume change. The soil strength is, however, lost upon saturation and results in a sudden collapse of the soil structure under the existing mechanical stress condition. The intrusion of water into the dry deposits of such soil causes ground subsidence leading to damages in the overlying buildings/structures. A study on the wetting-induced volume change behavior of collapsible soils is essential in dealing with the ground subsidence problems in various geotechnical engineering practices. The collapse of loosely compacted Kaolin soil upon wetting under various inundation pressures has been reported in recent studies. The collapse in the Kaolin soil is attributed to the alteration in the soil particle-particle association (fabric) resulting due to the changes in the various inter-particle (microscale) forces induced by the water saturation. The inundation pressure plays a significant role in the fabric evolution during the wetting process, thus controls the collapse potential of the compacted soil. A microstructural study is useful to understand the collapse mechanisms at various pore-fabric levels under different inundation pressure. Kaolin soil compacted to a dry density of 1.25 g/cc was used in this work to study the wetting-induced volume change behavior under different inundation pressures in the range of 10-1600 kPa. The compacted specimen of Kaolin soil exhibited a consistent collapse under all the studied inundation pressure. The collapse potential was observed to be increasing with an increase in the inundation pressure up to a maximum value of 13.85% under 800 kPa and then decreased to 11.7% under 1600 kPa. Microstructural analysis was carried out based on the fabric images and the pore size distributions (PSDs) obtained from FESEM analysis and mercury intrusion porosimetry (MIP), respectively. The PSDs and the soil fabric images of ‘as-compacted’ specimen and post-collapse specimen under 400 kPa were analyzed to understand the changes in the soil fabric and pores due to wetting. The pore size density curve for the post-collapse specimen was found to be on the finer side with respect to the ‘as-compacted’ specimen, indicating the reduction of the larger pores during the collapse. The inter-aggregate pores in the range of 0.1-0.5μm were identified as the major contributing pore size classes to the macroscopic volume change. Wetting under an inundation pressure results in the reduction of these pore sizes and lead to an increase in the finer pore sizes. The magnitude of inundation pressure influences the amount of reduction of these pores during the wetting process. The collapse potential was directly related to the degree of reduction in the pore volume contributed by these pore sizes.

Keywords: collapse behavior, inundation pressure, kaolin, microstructure

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1767 Doped and Co-doped ZnO Based Nanoparticles and their Photocatalytic and Gas Sensing Property

Authors: Neha Verma, Manik Rakhra

Abstract:

Statement of the Problem: Nowadays, a tremendous increase in population and advanced industrialization augment the problems related to air and water pollutions. Growing industries promoting environmental danger, which is an alarming threat to the ecosystem. For safeguard, the environment, detection of perilous gases and release of colored wastewater is required for eutrophication pollution. Researchers around the globe are trying their best efforts to save the environment. For this remediation advanced oxidation process is used for potential applications. ZnO is an important semiconductor photocatalyst with high photocatalytic and gas sensing activities. For efficient photocatalytic and gas sensing properties, it is necessary to prepare a doped/co-doped ZnO compound to decrease the electron-hole recombination rates. However, lanthanide doped and co-doped metal oxide is seldom studied for photocatalytic and gas sensing applications. The purpose of this study is to describe the best photocatalyst for the photodegradation of dyes and gas sensing properties. Methodology & Theoretical Orientation: Economical framework has to be used for the synthesis of ZnO. In the depth literature survey, a simple combustion method is utilized for gas sensing and photocatalytic activities. Findings: Rare earth doped and co-doped ZnO nanoparticles were the best photocatalysts for photodegradation of organic dyes and different gas sensing applications by varying various factors such as pH, aging time, and different concentrations of doping and codoping metals in ZnO. Complete degradation of dye was observed only in min. Gas sensing nanodevice showed a better response and quick recovery time for doped/co-doped ZnO. Conclusion & Significance: In order to prevent air and water pollution, well crystalline ZnO nanoparticles were synthesized by rapid and economic method, which is used as photocatalyst for photodegradation of organic dyes and gas sensing applications to sense the release of hazardous gases from the environment.

Keywords: ZnO, photocatalyst, photodegradation of dye, gas sensor

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1766 Parametric Appraisal of Robotic Arc Welding of Mild Steel Material by Principal Component Analysis-Fuzzy with Taguchi Technique

Authors: Amruta Rout, Golak Bihari Mahanta, Gunji Bala Murali, Bibhuti Bhusan Biswal, B. B. V. L. Deepak

Abstract:

The use of industrial robots for performing welding operation is one of the chief sign of contemporary welding in these days. The weld joint parameter and weld process parameter modeling is one of the most crucial aspects of robotic welding. As weld process parameters affect the weld joint parameters differently, a multi-objective optimization technique has to be utilized to obtain optimal setting of weld process parameter. In this paper, a hybrid optimization technique, i.e., Principal Component Analysis (PCA) combined with fuzzy logic has been proposed to get optimal setting of weld process parameters like wire feed rate, welding current. Gas flow rate, welding speed and nozzle tip to plate distance. The weld joint parameters considered for optimization are the depth of penetration, yield strength, and ultimate strength. PCA is a very efficient multi-objective technique for converting the correlated and dependent parameters into uncorrelated and independent variables like the weld joint parameters. Also in this approach, no need for checking the correlation among responses as no individual weight has been assigned to responses. Fuzzy Inference Engine can efficiently consider these aspects into an internal hierarchy of it thereby overcoming various limitations of existing optimization approaches. At last Taguchi method is used to get the optimal setting of weld process parameters. Therefore, it has been concluded the hybrid technique has its own advantages which can be used for quality improvement in industrial applications.

Keywords: robotic arc welding, weld process parameters, weld joint parameters, principal component analysis, fuzzy logic, Taguchi method

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1765 Spontaneous Generation of Wrinkled Patterns on pH-Sensitive Smart-Hydrogel Films

Authors: Carmen M. Gonzalez-Henriquez, Mauricio A. Sarabia-Vallejos, Juan Rodriguez-Hernandez

Abstract:

DMAEMA, as a monomer, has been widely studied and used in several application fields due to their pH-sensitive capacity (tertiary amine protonation), being relevant in the biomedical area as a potential carrier for drugs focused on the treatment of genetic or acquired diseases (efficient gene transfection), among others. Additionally, the inhibition of bacterial growth and, therefore, their antimicrobial activity, can be used as dual-functional antifogging/antimicrobial polymer coatings. According to their interesting physicochemical characteristics and biocompatible properties, DMAEMA was used as a monomer to synthesize a smart pH-sensitive hydrogel, namely poly(HEMA-co-PEGDA575-co-DMAEMA). Thus, different mole ratios (ranging from 5:1:0 to 0:1:5, according to the mole ratio between HEMA, PEGDA, and DEAEMA, respectively) were used in this research. The surface patterns formed via a two-step polymerization (redox- and photo-polymerization) were first chemically studied via 1H-NMR and elemental analysis. Secondly, the samples were morphologically analyzed by using Field-Emission Scanning Electron Microscopy (FE-SEM) and Atomic Force Microscopy (AFM) techniques. Then, a particular relation between HEMA, PEGDA, and DEAEMA (0:1:5) was also characterized at three different pH (5.4, 7.4 and 8.3). The hydrodynamic radius and zeta potential of the micro-hydrogel particles (emulsion) were carried out as a possible control for morphology, exploring the effect that produces hydrogel micelle dimensions in the wavelength, height, and roughness of the wrinkled patterns. Finally, contact angle and cross-hatch adhesion test was carried out for the hydrogels supported on glass using TSM-silanized surfaces in order to measure their mechanical properties.

Keywords: wrinkled patterns, smart pH-sensitive hydrogels, hydrogel micelle diameter, adhesion tests

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1764 The Application of a Neural Network in the Reworking of Accu-Chek to Wrist Bands to Monitor Blood Glucose in the Human Body

Authors: J. K Adedeji, O. H Olowomofe, C. O Alo, S.T Ijatuyi

Abstract:

The issue of high blood sugar level, the effects of which might end up as diabetes mellitus, is now becoming a rampant cardiovascular disorder in our community. In recent times, a lack of awareness among most people makes this disease a silent killer. The situation calls for urgency, hence the need to design a device that serves as a monitoring tool such as a wrist watch to give an alert of the danger a head of time to those living with high blood glucose, as well as to introduce a mechanism for checks and balances. The neural network architecture assumed 8-15-10 configuration with eight neurons at the input stage including a bias, 15 neurons at the hidden layer at the processing stage, and 10 neurons at the output stage indicating likely symptoms cases. The inputs are formed using the exclusive OR (XOR), with the expectation of getting an XOR output as the threshold value for diabetic symptom cases. The neural algorithm is coded in Java language with 1000 epoch runs to bring the errors into the barest minimum. The internal circuitry of the device comprises the compatible hardware requirement that matches the nature of each of the input neurons. The light emitting diodes (LED) of red, green, and yellow colors are used as the output for the neural network to show pattern recognition for severe cases, pre-hypertensive cases and normal without the traces of diabetes mellitus. The research concluded that neural network is an efficient Accu-Chek design tool for the proper monitoring of high glucose levels than the conventional methods of carrying out blood test.

Keywords: Accu-Check, diabetes, neural network, pattern recognition

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1763 A Qualitative Evidence of the Markedness of Code Switching during Commercial Bank Service Encounters in Ìbàdàn Metropolis

Authors: A. Robbin

Abstract:

In a multilingual setting like Nigeria, the success of service encounters is enhanced by the use of a language that ensures the linguistic and persuasive demands of the interlocutors. This study examined motivations for code switching as a negotiation strategy in bank-hall desk service encounters in Ìbàdàn metropolis using Myers-Scotton’s exploration on markedness in language use. The data consisted of transcribed audio recording of bank-hall service encounters, and direct observation of bank interactions in two purposively sampled commercial banks in Ìbàdàn metropolis. The data was subjected to descriptive linguistic analysis using Myers Scotton’s Markedness Model.  Findings reveal that code switching is frequently employed during different stages of service encounter: greeting, transaction and closing to fulfil relational, bargaining and referential functions. Bank staff and customers code switch to make unmarked, marked and explanatory choices. A strategy used to identify with customer’s cultural affiliation, close status gap, and appeal to begrudged customer; or as an explanatory choice with non-literate customers for ease of communication. Bankers select English to maintain customers’ perceptions of prestige which is retained or diverged from depending on their linguistic preference or ability.  Yoruba is seen as an efficient negotiation strategy with both bankers and their customers, making choices within conversation to achieve desired conversational and functional aims.

Keywords: banking, bilingualism, code-switching, markedness, service encounter

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1762 Anticancer Effect of Resveratrol-Loaded Gelatin Nanoparticles in NCI-H460 Non-Small Cell Lung Carcinoma Cell Lines

Authors: N. Rajendra Prasad

Abstract:

Resveratrol (RSV), a grape phytochemical, has drawn greater attention because of its beneficial ef-fects against cancer. However, RSV has some draw-backs such as unstabilization, poor water solubility and short biological half time, which limit the utili-zation of RSV in medicine, food and pharmaceutical industries. In this study, we have encapsulated RSV in gelatin nanoparticles (GNPs) and studied its anti-cancer efficacy in NCI-H460 lung cancer cells. SEM and DLS studies have revealed that the prepared RSV-GNPs possess spherical shape with a mean diameter of 294 nm. The successful encapsulation of RSV in GNPs has been achieved by the cross-linker glutaraldehyde probably through Schiff base reaction and hydrogen bond interaction. Spectrophotometric analysis revealed that the max-imum of 93.6% of RSV has been entrapped in GNPs. In vitro drug release kinetics indicated that there was an initial burst release followed by a slow and sustained release of RSV from GNPs. The prepared RSV-GNPs exhibited very rapid and more efficient cellular uptake than free RSV. Further, RSV-GNPs treatment showed greater antiproliferative efficacy than free RSV treatment in NCI-H460 cells. It has been found that greater ROS generation, DNA damage and apoptotic incidence in RSV-GNPs treated cells than free RSV treatment. Erythrocyte aggregation assay showed that the prepared RSV-GNPs formulation elicit no toxic response. HPLC analysis revealed that RSV-GNPs was more bioavailable and had a longer half-life than free RSV. Hence, GNPs carrier system might be a promising mode for controlled delivery and for improved therapeutic index of poorly water soluble RSV.

Keywords: resveratrol, coacervation, anticancer gelatin nanoparticles, lung cancer, controlled release

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1761 Numerical Modeling of a Molten Salt Power Tower Configuration Adaptable for Harsh Winter Climate

Authors: Huiqiang Yang, Domingo Santana

Abstract:

This paper proposes a novel configuration which introduces a natural draft dry cooling tower system in a molten salt power tower. A three-dimensional numerical modeling was developed based on the novel configuration. A plan of building 20 new concentrating solar power plants has been announced by Chinese government in September 2016, and among these 20 new plants, most of them are located in regions with long winter and harsh winter climate. The innovative configuration proposed includes an external receiver concrete tower at the center, a natural draft dry cooling tower which is surrounding the external receiver concrete tower and whose shell is fixed on the external receiver concrete tower, and a power block (including a steam generation system, a steam turbine system and hot/cold molten salt tanks, and water treatment systems) is covered by the roof of the natural draft dry cooling tower. Heat exchanger bundles are vertically installed at the furthest edge of the power block. In such a way, all power block equipment operates under suitable environmental conditions through whole year operation. The monthly performance of the novel configuration is simulated as compared to a standard one. The results show that the novel configuration is much more efficient in each separate month in a typical meteorological year. Moreover, all systems inside the power block have less thermal losses at low ambient temperatures, especially in harsh winter climate. It is also worthwhile mentioning that a photovoltaic power plant can be installed on the roof of the cooling tower to reduce the parasites of the molten salt power tower.

Keywords: molten salt power tower, natural draft dry cooling, commercial scale, power block, harsh winter climate

Procedia PDF Downloads 343
1760 Clean Sky 2 Project LiBAT: Light Battery Pack for High Power Applications in Aviation – Simulation Methods in Early Stage Design

Authors: Jan Dahlhaus, Alejandro Cardenas Miranda, Frederik Scholer, Maximilian Leonhardt, Matthias Moullion, Frank Beutenmuller, Julia Eckhardt, Josef Wasner, Frank Nittel, Sebastian Stoll, Devin Atukalp, Daniel Folgmann, Tobias Mayer, Obrad Dordevic, Paul Riley, Jean-Marc Le Peuvedic

Abstract:

Electrical and hybrid aerospace technologies pose very challenging demands on the battery pack – especially with respect to weight and power. In the Clean Sky 2 research project LiBAT (funded by the EU), the consortium is currently building an ambitious prototype with state-of-the art cells that shows the potential of an intelligent pack design with a high level of integration, especially with respect to thermal management and power electronics. For the latter, innovative multi-level-inverter technology is used to realize the required power converting functions with reduced equipment. In this talk the key approaches and methods of the LiBat project will be presented and central results shown. Special focus will be set on the simulative methods used to support the early design and development stages from an overall system perspective. The applied methods can efficiently handle multiple domains and deal with different time and length scales, thus allowing the analysis and optimization of overall- or sub-system behavior. It will be shown how these simulations provide valuable information and insights for the efficient evaluation of concepts. As a result, the construction and iteration of hardware prototypes has been reduced and development cycles shortened.

Keywords: electric aircraft, battery, Li-ion, multi-level-inverter, Novec

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1759 Effect of Instructional Materials on Academic Performance in Heat Transfer Concept among Secondary School Physics Students in Fagge Educational Zone, Kano State, Nigeria

Authors: Shehu Aliyu

Abstract:

This study investigated the effects of instructional materials on academic achievement among senior secondary school students on the concept of Heat Transfer in physics in Fagge Educational Zone, Kano State Nigeria. The population consisted of SSII students from 10 public schools. Out of this, 87 students were randomly selected from which 24 males and 22 females formed the experimental group and 41 students as control group. A quasi experiential design with pretest and post-test for both the groups was adopted. Two research questions and null hypotheses guided the conduct of the study. The experimental group was exposed to teaching using instructional materials while the control group was taught using the normal lecture mode. Head Transfer Performance Test (HTPT) was used for data collection. The instrument was validated by experts in the science education field. A Pearson Product Moment Correlation (PPMC) was used to determine the reliability co-efficient and was found to be r=0.83. The research questions were answered using descriptive statistics while the hypotheses were tested at p≤ 0.05 level of significance using t-test. The result obtained from the data analysis showed that students in experimental group performed significantly better than those in the control group and that there was no significant difference in the academic performance between male and female students in the experimental group. Based on the findings of this study, it was recommended among others that the physics teachers should be receiving regular training on the importance of using instructional materials whether ready made or improved in their teaching.

Keywords: heat transfer, physics, instructional materials, academic performance

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1758 Some Extreme Halophilic Microorganisms Produce Extracellular Proteases with Long Lasting Tolerance to Ethanol Exposition

Authors: Cynthia G. Esquerre, Amparo Iris Zavaleta

Abstract:

Extremophiles constitute a potentially valuable source of proteases for the development of biotechnological processes; however, the number of available studies in the literature is limited compared to mesophilic counterparts. Therefore, in this study, Peruvian halophilic microorganisms were characterized to select suitable proteolytic strains that produce active proteases under exigent conditions. Proteolysis was screened using the streak plate method with gelatin or skim milk as substrates. After that, proteolytic microorganisms were selected for phenotypic characterization and screened by a semi-quantitative proteolytic test using a modified method of diffusion agar. Finally, proteolysis was evaluated using partially purified extracts by ice-cold ethanol precipitation and dialysis. All analyses were carried out over a wide range of NaCl concentrations, pH, temperature and substrates. Of a total of 60 strains, 21 proteolytic strains were selected, of these 19 were extreme halophiles and 2 were moderates. Most proteolytic strains demonstrated differences in their biochemical patterns, particularly in sugar fermentation. A total of 14 microorganisms produced extracellular proteases, 13 were neutral, and one was alkaline showing activity up to pH 9.0. Proteases hydrolyzed gelatin as the most specific substrate. In general, catalytic activity was efficient under a wide range of NaCl (1 to 4 M NaCl), temperature (37 to 55 °C) and after an ethanol exposition performed at -20 °C for 24 hours. In conclusion, this study reported 14 candidates extremely halophiles producing extracellular proteases capable of being stable and active on a wide range of NaCl, temperature and even long lasting ethanol exposition.

Keywords: biotechnological processes, ethanol exposition, extracellular proteases, extremophiles

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1757 Mitigating Ruminal Methanogenesis Through Genomic and Transcriptomic Approaches

Authors: Muhammad Adeel Arshad, Faiz-Ul Hassan, Yanfen Cheng

Abstract:

According to FAO, enteric methane (CH4) production is about 44% of all greenhouse gas emissions from the livestock sector. Ruminants produce CH4 as a result of fermentation of feed in the rumen especially from roughages which yield more CH4 per unit of biomass ingested as compared to concentrates. Efficient ruminal fermentation is not possible without abating CO2 and CH4. Methane abatement strategies are required to curb the predicted rise in emissions associated with greater ruminant production in future to meet ever increasing animal protein requirements. Ecology of ruminal methanogenesis and avenues for its mitigation can be identified through various genomic and transcriptomic techniques. Programs such as Hungate1000 and the Global Rumen Census have been launched to enhance our understanding about global ruminal microbial communities. Through Hungate1000 project, a comprehensive reference set of rumen microbial genome sequences has been developed from cultivated rumen bacteria and methanogenic archaea along with representative rumen anaerobic fungi and ciliate protozoa cultures. But still many species of rumen microbes are underrepresented especially uncultivable microbes. Lack of sequence information specific to the rumen's microbial community has inhibited efforts to use genomic data to identify specific set of species and their target genes involved in methanogenesis. Metagenomic and metatranscriptomic study of entire microbial rumen populations offer new perspectives to understand interaction of methanogens with other rumen microbes and their potential association with total gas and methane production. Deep understanding of methanogenic pathway will help to devise potentially effective strategies to abate methane production while increasing feed efficiency in ruminants.

Keywords: Genome sequences, Hungate1000, methanogens, ruminal fermentation

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1756 Impact of Nanoparticles in Enhancement of Thermal Conductivity of Phase Change Materials in Thermal Energy Storage and Cooling of Concentrated Photovoltaics

Authors: Ismaila H. Zarma, Mahmoud Ahmed, Shinichi Ookawara, Hamdi Abo-Ali

Abstract:

Phase change materials (PCM) are an ideal thermal storage medium. They are characterized by a high latent heat, which allows them to store large amounts of energy when the material transitions into different physical states. Concentrated photovoltaic (CPV) systems are widely recognized as the most efficient form of Photovoltaic (PV) for thermal energy which can be stored in Phase Change Materials (PCM). However, PCMs often have a low thermal conductivity which leads to a slow transient response. This makes it difficult to quickly store and access the energy stored within the PCM based systems, so there is need to improve transient responses and increase the thermal conductivity. The present study aims to investigate and analyze the melting and solidification process of phase change materials (PCMs) enhanced by nanoparticle contained in a container. Heat flux from concentrated photovoltaic is applied in an attempt to analyze the thermal performance and the impact of nanoparticles. The work will be realized by using a two dimensional model which take into account the phase change phenomena based on the principle of enthalpy method. Numerical simulations have been performed to investigate heat and flow characteristics by using governing equations, to ascertain the impacts of the nanoparticle loading. The Rayleigh number, sub-cooling as well as the unsteady evolution of the melting front and the velocity and temperature fields were also observed. The predicted results exhibited a good agreement, showing thermal enhancement due to present of nanoparticle which leads to decreasing the melting time.

Keywords: thermal energy storage, phase-change material, nanoparticle, concentrated photovoltaic

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1755 Optimizing Data Integration and Management Strategies for Upstream Oil and Gas Operations

Authors: Deepak Singh, Rail Kuliev

Abstract:

The abstract highlights the critical importance of optimizing data integration and management strategies in the upstream oil and gas industry. With its complex and dynamic nature generating vast volumes of data, efficient data integration and management are essential for informed decision-making, cost reduction, and maximizing operational performance. Challenges such as data silos, heterogeneity, real-time data management, and data quality issues are addressed, prompting the proposal of several strategies. These strategies include implementing a centralized data repository, adopting industry-wide data standards, employing master data management (MDM), utilizing real-time data integration technologies, and ensuring data quality assurance. Training and developing the workforce, “reskilling and upskilling” the employees and establishing robust Data Management training programs play an essential role and integral part in this strategy. The article also emphasizes the significance of data governance and best practices, as well as the role of technological advancements such as big data analytics, cloud computing, Internet of Things (IoT), and artificial intelligence (AI) and machine learning (ML). To illustrate the practicality of these strategies, real-world case studies are presented, showcasing successful implementations that improve operational efficiency and decision-making. In present study, by embracing the proposed optimization strategies, leveraging technological advancements, and adhering to best practices, upstream oil and gas companies can harness the full potential of data-driven decision-making, ultimately achieving increased profitability and a competitive edge in the ever-evolving industry.

Keywords: master data management, IoT, AI&ML, cloud Computing, data optimization

Procedia PDF Downloads 73