Search results for: surface potential
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 17020

Search results for: surface potential

8440 Preparation of Ni, Mg, and Fe Ions Doped Carbon-Based Catalyst with Ordered Mesoporous Configuration for Catalyzing the Production of Green Diesel from Fatty Acid and Waste Cooking Oil

Authors: Ya-Ting Liao, Chien-Chang Huang

Abstract:

Green diesel is a renewable biofuel obtained from plant oil or fatty acid deoxygenation. Because the molecular structure of green diesel is similar to that of fossil fuel, green diesel can be directly used in present vehicle engines without blending with fossil fuel. In this study, mesoporous carbon-based catalysts with doped metal ions, such as Mg, Ni, or Fe, were prepared using co-polymers and gallic acid as molecular templates and carbon sources, respectively. The prepared catalysts were then applied to carry out the deoxygenation of fatty acid and waste cooking oil. To obtain the highest net energy from the produced green diesel, the catalyzed deoxygenation reaction and catalyst preparation processes were carried out under ambient conditions, respectively, to avoid using H₂ as a reagent and reducing agent. XRD, BET, SEM, EDS, FT-IR, and pyridine-IR characterized the composition and configuration of the prepared catalyst. The results display that the doped metal ions were well-dispersed in the carbon-based catalyst and the surface of the catalysts was rich in Lewis acid sites after the catalysts were calcined at the proper temperature. The pore size present on the catalyst was 9-11 nm. To catalyze the deoxygenation of fatty acid by the prepared catalysts at 320℃ under H₂-free conditions, high fatty acid conversion (99%) and high selectivity for hydrocarbons (78%) were obtained when the ratio of doped Ni to doped Mg was optimized.

Keywords: ordered mesoporous carbon, catalysts, hydrocarbons, deoxygenation

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8439 Sukūk Markets 2023: A Global Perspective on Growth and Adaptability

Authors: Abdulamjid Obaid Hasan Saleh, Younes Soualhi

Abstract:

This study explores the performance of the global Ṣukūk markets in 2023, focusing on their significance within the global financial ecosystem amidst complex economic challenges. The research highlights the modest annual growth of the total outstanding Ṣukūk value, which reached USD 850 billion by the end of the year, representing a 2.45% increase. However, it also identifies a 3.25% decline in new issuances compared to 2022, attributed to factors such as elevated oil prices, rising global interest rates, and heightened geopolitical tensions. Utilizing a descriptive and analytical methodology, the study compares the resilience of the Ṣukūk market with global bond markets, which experienced a sharp 17% drop in new issuances by the third quarter of 2023. The findings underscore the strategic positioning of Ṣukūk as a stable and competitive alternative within the global financial landscape. The study concludes by discussing potential avenues for growth and resilience in Ṣukūk markets.

Keywords: Ṣukūk market, performance, global Sukuk, resilience, global bond market

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8438 Rapid and Efficient Removal of Lead from Water Using Chitosan/Magnetite Nanoparticles

Authors: Othman M. Hakami, Abdul Jabbar Al-Rajab

Abstract:

Occurrence of heavy metals in water resources increased in the recent years albeit at low concentrations. Lead (PbII) is among the most important inorganic pollutants in ground and surface water. However, removal of this toxic metal efficiently from water is of public and scientific concern. In this study, we developed a rapid and efficient removal method of lead from water using chitosan/magnetite nanoparticles. A simple and effective process has been used to prepare chitosan/magnetite nanoparticles (NPs) (CS/Mag NPs) with effect on saturation magnetization value; the particles were strongly responsive to an external magnetic field making separation from solution possible in less than 2 minutes using a permanent magnet and the total Fe in solution was below the detection limit of ICP-OES (<0.19 mg L-1). The hydrodynamic particle size distribution increased from an average diameter of ~60 nm for Fe3O4 NPs to ~75 nm after chitosan coating. The feasibility of the prepared NPs for the adsorption and desorption of Pb(II) from water were evaluated using Chitosan/Magnetite NPs which showed a high removal efficiency for Pb(II) uptake, with 90% of Pb(II) removed during the first 5 minutes and equilibrium in less than 10 minutes. Maximum adsorption capacities for Pb(II) occurred at pH 6.0 and under room temperature were as high as 85.5 mg g-1, according to Langmuir isotherm model. Desorption of adsorbed Pb on CS/Mag NPs was evaluated using deionized water at different pH values ranged from 1 to 7 which was an effective eluent and did not result the destruction of NPs, then, they could subsequently be reused without any loss of their activity in further adsorption tests. Overall, our results showed the high efficiency of chitosan/magnetite nanoparticles (NPs) in lead removal from water in controlled conditions, and further studies should be realized in real field conditions.

Keywords: chitosan, magnetite, water, treatment

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8437 Critical Analysis of Heat Exchanger Cycle for its Maintainability Using Failure Modes and Effect Analysis and Pareto Analysis

Authors: Sayali Vyas, Atharva Desai, Shreyas Badave, Apurv Kulkarni, B. Rajiv

Abstract:

The Failure Modes and Effect Analysis (FMEA) is an efficient evaluation technique to identify potential failures in products, processes, and services. FMEA is designed to identify and prioritize failure modes. It proves to be a useful method for identifying and correcting possible failures at its earliest possible level so that one can avoid consequences of poor performance. In this paper, FMEA tool is used in detection of failures of various components of heat exchanger cycle and to identify critical failures of the components which may hamper the system’s performance. Further, a detailed Pareto analysis is done to find out the most critical components of the cycle, the causes of its failures, and possible recommended actions. This paper can be used as a checklist which will help in maintainability of the system.

Keywords: FMEA, heat exchanger cycle, Ishikawa diagram, pareto analysis, RPN (Risk Priority Number)

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8436 Safety Considerations of Furanics for Sustainable Applications in Advanced Biorefineries

Authors: Anitha Muralidhara, Victor Engelen, Christophe Len, Pascal Pandard, Guy Marlair

Abstract:

Production of bio-based chemicals and materials from lignocellulosic biomass is gaining tremendous importance in advanced bio-refineries while aiming towards progressive replacement of petroleum based chemicals in transportation fuels and commodity polymers. One such attempt has resulted in the production of key furan derivatives (FD) such as furfural, HMF, MMF etc., via acid catalyzed dehydration (ACD) of C6 and C5 sugars, which are further converted into key chemicals or intermediates (such as Furandicarboxylic acid, Furfuryl alcohol etc.,). In subsequent processes, many high potential FD are produced, that can be converted into high added value polymers or high energy density biofuels. During ACD, an unavoidable polyfuranic byproduct is generated which is called humins. The family of FD is very large with varying chemical structures and diverse physicochemical properties. Accordingly, the associated risk profiles may largely vary. Hazardous Material (Haz-mat) classification systems such as GHS (CLP in the EU) and the UN TDG Model Regulations for transport of dangerous goods are one of the preliminary requirements for all chemicals for their appropriate classification, labelling, packaging, safe storage, and transportation. Considering the growing application routes of FD, it becomes important to notice the limited access to safety related information (safety data sheets available only for famous compounds such as HMF, furfural etc.,) in these internationally recognized haz-mat classification systems. However, these classifications do not necessarily provide information about the extent of risk involved when the chemical is used in any specific application. Factors such as thermal stability, speed of combustion, chemical incompatibilities, etc., can equally influence the safety profile of a compound, that are clearly out of the scope of any haz-mat classification system. Irrespective of the bio-based origin, FD has so far received inconsistent remarks concerning their toxicity profiles. With such inconsistencies, there is a fear that, a large family of FD may also follow extreme judgmental scenarios like ionic liquids, by ranking some compounds as extremely thermally stable, non-flammable, etc., Unless clarified, these messages could lead to misleading judgements while ranking the chemical based on its hazard rating. Safety is a key aspect in any sustainable biorefinery operation/facility, which is often underscored or neglected. To fill up these existing data gaps and to address ambiguities and discrepancies, the current study focuses on giving preliminary insights on safety assessment of FD and their potential targeted by-products. With the available information in the literature and obtained experimental results, physicochemical safety, environmental safety as well as (a scenario based) fire safety profiles of key FD, as well as side streams such as humins and levulinic acid, will be considered. With this, the study focuses on defining patterns and trends that gives coherent safety related information for existing and newly synthesized FD in the market for better functionality and sustainable applications.

Keywords: furanics, humins, safety, thermal and fire hazard, toxicity

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8435 Numerical Modelling of Dry Stone Masonry Structures Based on Finite-Discrete Element Method

Authors: Ž. Nikolić, H. Smoljanović, N. Živaljić

Abstract:

This paper presents numerical model based on finite-discrete element method for analysis of the structural response of dry stone masonry structures under static and dynamic loads. More precisely, each discrete stone block is discretized by finite elements. Material non-linearity including fracture and fragmentation of discrete elements as well as cyclic behavior during dynamic load are considered through contact elements which are implemented within a finite element mesh. The application of the model was conducted on several examples of these structures. The performed analysis shows high accuracy of the numerical results in comparison with the experimental ones and demonstrates the potential of the finite-discrete element method for modelling of the response of dry stone masonry structures.

Keywords: dry stone masonry structures, dynamic load, finite-discrete element method, static load

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8434 Genetic Algorithm Methods for Determination Over Flow Coefficient of Medium Throat Length Morning Glory Spillway Equipped Crest Vortex Breakers

Authors: Roozbeh Aghamajidi

Abstract:

Shaft spillways are circling spillways used generally for emptying unexpected floods on earth and concrete dams. There are different types of shaft spillways: Stepped and Smooth spillways. Stepped spillways pass more flow discharges through themselves in comparison to smooth spillways. Therefore, awareness of flow behavior of these spillways helps using them better and more efficiently. Moreover, using vortex breaker has great effect on passing flow through shaft spillway. In order to use more efficiently, the risk of flow pressure decreases to less than fluid vapor pressure, called cavitations, should be prevented as far as possible. At this research, it has been tried to study different behavior of spillway with different vortex shapes on spillway crest on flow. From the viewpoint of the effects of flow regime changes on spillway, changes of step dimensions, and the change of type of discharge will be studied effectively. Therefore, two spillway models with three different vortex breakers and three arrangements have been used to assess the hydraulic characteristics of flow. With regard to the inlet discharge to spillway, the parameters of pressure and flow velocity on spillway surface have been measured at several points and after each run. Using these kinds of information leads us to create better design criteria of spillway profile. To achieve these purposes, optimization has important role and genetic algorithm are utilized to study the emptying discharge. As a result, it turned out that the best type of spillway with maximum discharge coefficient is smooth spillway with ogee shapes as vortex breaker and 3 number as arrangement. Besides it has been concluded that the genetic algorithm can be used to optimize the results.

Keywords: shaft spillway, vortex breaker, flow, genetic algorithm

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8433 Investigating the Expression of NR1/NR2 Receptors in Boys Between 6 to 16 with ADHD Compared to a Healthy Controlled Group

Authors: Sajad Haghshenas

Abstract:

Emerging evidence from clinical, genetic, and animal model studies suggests that the N-methyl-D-aspartate (NMDA) glutamate receptors (NMDAR) may contribute to the pathophysiology and aetiology of neurological and psychiatric disorders and the patients with impaired NMDR receptors experience psychological symptoms. Therefore, we hypothesised that NMDAR receptors play a key role in the development of attention deficit hyperactivity disorder (ADHD). In this comparative analytical study, we utilized western blotting method to assay the expression levels of NMDA subunits NR1 and NR2 in the blood plasma of 50 male individuals diagnosed with ADHD in comparison to 20 healthy controls. The findings from the western blotting analysis provide support for the hypothesis that individuals with ADHD exhibit significantly lower levels of NR1/2 receptors compared to those without the disorder. Further research is needed to explore the potential causal relationship between reduced NR1/NR2 receptor levels and the development of ADHD.

Keywords: expression, glutamate receptors, NR1, NR2, ADHD

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8432 Message Passing Neural Network (MPNN) Approach to Multiphase Diffusion in Reservoirs for Well Interconnection Assessments

Authors: Margarita Mayoral-Villa, J. Klapp, L. Di G. Sigalotti, J. E. V. Guzmán

Abstract:

Automated learning techniques are widely applied in the energy sector to address challenging problems from a practical point of view. To this end, we discuss the implementation of a Message Passing algorithm (MPNN)within a Graph Neural Network(GNN)to leverage the neighborhood of a set of nodes during the aggregation process. This approach enables the characterization of multiphase diffusion processes in the reservoir, such that the flow paths underlying the interconnections between multiple wells may be inferred from previously available data on flow rates and bottomhole pressures. The results thus obtained compare favorably with the predictions produced by the Reduced Order Capacitance-Resistance Models (CRM) and suggest the potential of MPNNs to enhance the robustness of the forecasts while improving the computational efficiency.

Keywords: multiphase diffusion, message passing neural network, well interconnection, interwell connectivity, graph neural network, capacitance-resistance models

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8431 Multi-Temporal Mapping of Built-up Areas Using Daytime and Nighttime Satellite Images Based on Google Earth Engine Platform

Authors: S. Hutasavi, D. Chen

Abstract:

The built-up area is a significant proxy to measure regional economic growth and reflects the Gross Provincial Product (GPP). However, an up-to-date and reliable database of built-up areas is not always available, especially in developing countries. The cloud-based geospatial analysis platform such as Google Earth Engine (GEE) provides an opportunity with accessibility and computational power for those countries to generate the built-up data. Therefore, this study aims to extract the built-up areas in Eastern Economic Corridor (EEC), Thailand using day and nighttime satellite imagery based on GEE facilities. The normalized indices were generated from Landsat 8 surface reflectance dataset, including Normalized Difference Built-up Index (NDBI), Built-up Index (BUI), and Modified Built-up Index (MBUI). These indices were applied to identify built-up areas in EEC. The result shows that MBUI performs better than BUI and NDBI, with the highest accuracy of 0.85 and Kappa of 0.82. Moreover, the overall accuracy of classification was improved from 79% to 90%, and error of total built-up area was decreased from 29% to 0.7%, after night-time light data from the Visible and Infrared Imaging Suite (VIIRS) Day Night Band (DNB). The results suggest that MBUI with night-time light imagery is appropriate for built-up area extraction and be utilize for further study of socioeconomic impacts of regional development policy over the EEC region.

Keywords: built-up area extraction, google earth engine, adaptive thresholding method, rapid mapping

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8430 Enzymatic Saccharification of Dilute Alkaline Pre-treated Microalgal (Tetraselmis suecica) Biomass for Biobutanol Production

Authors: M. A. Kassim, R. Potumarthi, A. Tanksale, S. C. Srivatsa, S. Bhattacharya

Abstract:

Enzymatic saccharification of biomass for reducing sugar production is one of the crucial processes in biofuel production through biochemical conversion. In this study, enzymatic saccharification of dilute potassium hydroxide (KOH) pre-treated Tetraselmis suecica biomass was carried out by using cellulase enzyme obtained from Trichoderma longibrachiatum. Initially, the pre-treatment conditions were optimised by changing alkali reagent concentration, retention time for reaction, and temperature. The T. suecica biomass after pre-treatment was also characterized using Fourier Transform Infrared Spectra and Scanning Electron Microscope. These analyses revealed that the functional group such as acetyl and hydroxyl groups, structure and surface of T. suecica biomass were changed through pre-treatment, which is favourable for enzymatic saccharification process. Comparison of enzymatic saccharification of untreated and pre-treated microalgal biomass indicated that higher level of reducing sugar can be obtained from pre-treated T. suecica. Enzymatic saccharification of pre-treated T. suecica biomass was optimised by changing temperature, pH, and enzyme concentration to solid ratio ([E]/[S]). Highest conversion of carbohydrate into reducing sugar of 95% amounted to reducing sugar yield of 20 (wt%) from pre-treated T. suecica was obtained from saccharification, at temperature: 40°C, pH: 4.5 and [E]/[S] of 0.1 after 72 h of incubation. Hydrolysate obtained from enzymatic saccharification of pretreated T. suecica biomass was further fermented into biobutanol using Clostridium saccharoperbutyliticum as biocatalyst. The results from this study demonstrate a positive prospect of application of dilute alkaline pre-treatment to enhance enzymatic saccharification and biobutanol production from microalgal biomass.

Keywords: microalgal biomass, enzymatic saccharification, biobutanol, fermentation

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8429 Simulative Study of the Influence of Degraded Twin-Tube Shock Absorbers on the Lateral Forces of Vehicle Axles

Authors: Tobias Schramm, Günther Prokop

Abstract:

Degraded vehicle shock absorbers represent a risk for road safety. The exact effect of degraded vehicle dampers on road safety is still the subject of research. This work is intended to contribute to estimating the effect of degraded twin-tube dampers of passenger cars on road safety. An axle model was built using a damper model to simulate different degradation levels. To parameterize the model, a realistic parameter space was estimated based on test rig measurements and database analyses, which is intended to represent the vehicle field in Germany. Within the parameter space, simulations of the axle model were carried out, which calculated the transmittable lateral forces of the various axle configurations as a function of vehicle speed, road surface, damper conditions and axle parameters. A degraded damper has the greatest effect on the transmittable lateral forces at high speeds and in poor road conditions. If a vehicle is traveling at a speed of 100 kph on a Class D road, a degraded damper reduces the transmissible lateral forces of an axle by 20 % on average. For individual parameter configurations, this value can rise to 50 %. The axle parameters that most influence the effect of a degraded damper are the vertical stiffness of the tire, the unsprung mass and the stabilizer stiffness of the axle.

Keywords: vehicle dynamics, vehicle simulation, vehicle component degradation, shock absorber model, shock absorber degradation

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8428 Melting and Making Zn-Based Alloys and Examine Their Biodegradable and Biocompatible Properties

Authors: Abdulrahman Sumayli

Abstract:

Natural Zinc has many significant biological functions, including developments and sustainable of bones and wound healing. Metallic zinc has recently been explored as potential biomaterials that have preferable biodegradable, biocompatible, and mechanical properties. Pure metal zinc has a preferable physical and mechanical properties for biodegradable and biocompatible applications such as density and modulus of elasticity. The aim of the research is to make different Zn-based metallic alloys and test them effectively to be used as biocompatible and biodegradable materials in the field biomedical application. Microstructure study of the as-cast alloys will be examined using SEM (scanning electron microscope) followed by X-ray diffraction investigated so as to evaluate phase constitution of the designed alloys. After that, immersion test and electrochemical test will be applied to the designed alloys so as to study bio corrosion behaviour of the proposed alloys. Finally, in vitro cytocompatibility well conducted to study biocompatibility of the made alloys.

Keywords: Zn-based alloys, biodegradable and biocompatible materials, cytotoxicity test, neutron synchrotron imaging

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8427 Application of MALDI-MS to Differentiate SARS-CoV-2 and Non-SARS-CoV-2 Symptomatic Infections in the Early and Late Phases of the Pandemic

Authors: Dmitriy Babenko, Sergey Yegorov, Ilya Korshukov, Aidana Sultanbekova, Valentina Barkhanskaya, Tatiana Bashirova, Yerzhan Zhunusov, Yevgeniya Li, Viktoriya Parakhina, Svetlana Kolesnichenko, Yeldar Baiken, Aruzhan Pralieva, Zhibek Zhumadilova, Matthew S. Miller, Gonzalo H. Hortelano, Anar Turmuhambetova, Antonella E. Chesca, Irina Kadyrova

Abstract:

Introduction: The rapidly evolving COVID-19 pandemic, along with the re-emergence of pathogens causing acute respiratory infections (ARI), has necessitated the development of novel diagnostic tools to differentiate various causes of ARI. MALDI-MS, due to its wide usage and affordability, has been proposed as a potential instrument for diagnosing SARS-CoV-2 versus non-SARS-CoV-2 ARI. The aim of this study was to investigate the potential of MALDI-MS in conjunction with a machine learning model to accurately distinguish between symptomatic infections caused by SARS-CoV-2 and non-SARS-CoV-2 during both the early and later phases of the pandemic. Furthermore, this study aimed to analyze mass spectrometry (MS) data obtained from nasal swabs of healthy individuals. Methods: We gathered mass spectra from 252 samples, comprising 108 SARS-CoV-2-positive samples obtained in 2020 (Covid 2020), 7 SARS-CoV- 2-positive samples obtained in 2023 (Covid 2023), 71 samples from symptomatic individuals without SARS-CoV-2 (Control non-Covid ARVI), and 66 samples from healthy individuals (Control healthy). All the samples were subjected to RT-PCR testing. For data analysis, we employed the caret R package to train and test seven machine-learning algorithms: C5.0, KNN, NB, RF, SVM-L, SVM-R, and XGBoost. We conducted a training process using a five-fold (outer) nested repeated (five times) ten-fold (inner) cross-validation with a randomized stratified splitting approach. Results: In this study, we utilized the Covid 2020 dataset as a case group and the non-Covid ARVI dataset as a control group to train and test various machine learning (ML) models. Among these models, XGBoost and SVM-R demonstrated the highest performance, with accuracy values of 0.97 [0.93, 0.97] and 0.95 [0.95; 0.97], specificity values of 0.86 [0.71; 0.93] and 0.86 [0.79; 0.87], and sensitivity values of 0.984 [0.984; 1.000] and 1.000 [0.968; 1.000], respectively. When examining the Covid 2023 dataset, the Naive Bayes model achieved the highest classification accuracy of 43%, while XGBoost and SVM-R achieved accuracies of 14%. For the healthy control dataset, the accuracy of the models ranged from 0.27 [0.24; 0.32] for k-nearest neighbors to 0.44 [0.41; 0.45] for the Support Vector Machine with a radial basis function kernel. Conclusion: Therefore, ML models trained on MALDI MS of nasopharyngeal swabs obtained from patients with Covid during the initial phase of the pandemic, as well as symptomatic non-Covid individuals, showed excellent classification performance, which aligns with the results of previous studies. However, when applied to swabs from healthy individuals and a limited sample of patients with Covid in the late phase of the pandemic, ML models exhibited lower classification accuracy.

Keywords: SARS-CoV-2, MALDI-TOF MS, ML models, nasopharyngeal swabs, classification

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8426 The Potential for Recycling Household Wastes Generated from the Residential Areas of Obafemi Awolowo University, Ile-Ife

Authors: Asaolu Olugbenga Stephen, Afolabi Olusegun Temitope

Abstract:

Lack of proper solid waste management is one of the main causes of environmental pollution and degradation in many cities, especially in developing countries. The aim of this study was to estimate the quantity of waste generated per capita per day, determine the composition and identify the potentials for recycling of waste generated. Characterization of wastes from selected households in the residential areas was done for over a 7 day period. The weight of each sorted category of waste was recorded in a structured database that calculated the proportion of each waste component. The results indicated that 85.4% of the sampled waste characterized was found to be recyclable; with an estimated average waste generated of 1.82kg/capita/day. The various solid waste fractions were organic (64.6%), plastics (15.6%), metals (9.2%), glass materials (1.6%) and unclassified (8.9%). It was concluded from this study that a large proportion of the waste generated from OAU campus residential area was recyclable and that there is a need to enact policy on waste recycling within the university campus.

Keywords: recycling, household wastes, residential, solid waste management

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8425 Performance Analysis of N-Tier Grid Protocol for Resource Constrained Wireless Sensor Networks

Authors: Jai Prakash Prasad, Suresh Chandra Mohan

Abstract:

Modern wireless sensor networks (WSN) consist of small size, low cost devices which are networked through tight wireless communications. WSN fundamentally offers cooperation, coordination among sensor networks. Potential applications of wireless sensor networks are in healthcare, natural disaster prediction, data security, environmental monitoring, home appliances, entertainment etc. The design, development and deployment of WSN based on application requirements. The WSN design performance is optimized to improve network lifetime. The sensor node resources constrain such as energy and bandwidth imposes the limitation on efficient resource utilization and sensor node management. The proposed N-Tier GRID routing protocol focuses on the design of energy efficient large scale wireless sensor network for improved performance than the existing protocol.

Keywords: energy efficient, network lifetime, sensor networks, wireless communication

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8424 An Approach to Electricity Production Utilizing Waste Heat of a Triple-Pressure Cogeneration Combined Cycle Power Plant

Authors: Soheil Mohtaram, Wu Weidong, Yashar Aryanfar

Abstract:

This research investigates the points with heat recovery potential in a triple-pressure cogeneration combined cycle power plant and determines the amount of waste heat that can be recovered. A modified cycle arrangement is then adopted for accessing thermal potentials. Modeling the energy system is followed by thermodynamic and energetic evaluation, and then the price of the manufactured products is also determined using the Total Revenue Requirement (TRR) method and term economic analysis. The results of optimization are then presented in a Pareto chart diagram by implementing a new model with dual objective functions, which include power cost and produce heat. This model can be utilized to identify the optimal operating point for such power plants based on electricity and heat prices in different regions.

Keywords: heat loss, recycling, unused energy, efficient production, optimization, triple-pressure cogeneration

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8423 High-Temperature Behavior of Boiler Steel by Friction Stir Processing

Authors: Supreet Singh, Manpreet Kaur, Manoj Kumar

Abstract:

High temperature corrosion is an imperative material degradation method experienced in thermal power plants and other energy generation sectors. Metallic materials such as ferritic steels have special properties such as easy fabrication and machinibilty, low cost, but a serious drawback of these materials is the worsening in properties initiating from the interaction with the environments. The metallic materials do not endure higher temperatures for extensive period of time because of their poor corrosion resistance. Friction Stir Processing (FSP), has emerged as the potent surface modification means and control of microstructure in thermo mechanically heat affecting zones of various metal alloys. In the current research work, FSP was done on the boiler tube of SA 210 Grade A1 material which is regularly used by thermal power plants. The strengthening of SA210 Grade A1 boiler steel through microstructural refinement by Friction Stir Processing (FSP) and analyze the effect of the same on high temperature corrosion behavior. The high temperature corrosion performance of the unprocessed and the FSPed specimens were evaluated in the laboratory using molten salt environment of Na₂SO₄-82%Fe₂(SO₄). The unprocessed and FSPed low carbon steel Gr A1 evaluation was done in terms of microstructure, corrosion resistance, mechanical properties like hardness- tensile. The in-depth characterization was done by EBSD, SEM/EDS and X-ray mapping analyses with an aim to propose the mechanism behind high temperature corrosion behavior of the FSPed steel.

Keywords: boiler steel, characterization, corrosion, EBSD/SEM/EDS/XRD, friction stir processing

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8422 Growth Mechanism, Structural and Compositional Properties of Cu₂ZnSnS₄ (CZTS) Thin Films Deposited by Sputtering Method from a Compound Target

Authors: Sanusi Abdullahi, Musa Momoh, Abubakar Umar Moreh, Aminu Muhammad Bayawa, Olubunmi Popoola

Abstract:

Kesterite-type Cu₂ZnSnS₄ (CZTS) thin films were deposited on corning glass from a single quaternary target. In this study, we investigated the growth mechanism and the influence of thin film thickness on the structural and compositional properties of CZTS films. All the four samples (as-deposited inclusive) show peaks corresponding to kesterite-type structure. The diffraction peaks of (112) are sharp and the small characteristics peaks of the kesterite structure such as (220)/ (204) and (312)/ (116) are also clearly observed in X-ray diffraction pattern. These results indicate that the quaternary CZTS would be a potential candidate for solar cell applications.

Keywords: RF sputtering, Cu2ZnSnS4 thin film, annealing, growth mechanism, annealing, growth mechanism, renewable energy

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8421 Synthetic Daily Flow Duration Curves for the Çoruh River Basin, Turkey

Authors: Ibrahim Can, Fatih Tosunoğlu

Abstract:

The flow duration curve (FDC) is an informative method that represents the flow regime’s properties for a river basin. Therefore, the FDC is widely used for water resource projects such as hydropower, water supply, irrigation and water quality management. The primary purpose of this study is to obtain synthetic daily flow duration curves for Çoruh Basin, Turkey. For this aim, we firstly developed univariate auto-regressive moving average (ARMA) models for daily flows of 9 stations located in Çoruh basin and then these models were used to generate 100 synthetic flow series each having same size as historical series. Secondly, flow duration curves of each synthetic series were drawn and the flow values exceeded 10, 50 and 95 % of the time and 95% confidence limit of these flows were calculated. As a result, flood, mean and low flows potential of Çoruh basin will comprehensively be represented.

Keywords: ARMA models, Çoruh basin, flow duration curve, Turkey

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8420 Influence of Synergistic/Antagonistic Mixtures of Oligomeric Stabilizers on the Biodegradation of γ-Sterilized Polyolefins

Authors: Sameh A. S. Thabit Alariqi

Abstract:

Our previous studies aimed to investigate the biodegradation of γ-sterilized polyolefins in composting and microbial culture environments at different doses and γ-dose rates. It was concluded from the previous studies that the pretreatment of γ-irradiation can accelerate the biodegradation of neat polymer matrix in biotic conditions significantly. A similar work was carried out to study the stabilization of γ-sterilized polyolefins using different mixtures of stabilizers which are approved for food-contact applications. Ethylene-propylene (EP) copolymer has been melt-mixed with hindered amine stabilizers (HAS), phenolic antioxidants and hydroperoxide decomposers. Results were discussed by comparing the stabilizing efficiency, combination and consumption of stabilizers and the synergistic and antagonistic effects was explained through the interaction between the stabilizers. In this attempt, we have aimed to study the influence of the synergistic and antagonistic mixtures of oligomeric stabilizers on the biodegradation of the γ-irradiated polyolefins in composting and microbial culture. Neat and stabilized films of EP copolymer irradiated under γ-radiation and incubated in compost and fungal culture environments. The changes in functional groups, surface morphology, mechanical properties and intrinsic viscosity in polymer chains were characterized by FT-IR spectroscopy, SEM, instron, and viscometric measurements respectively. Results were discussed by comparing the effect of different stabilizers, stabilizers mixtures on the biodegradation of the γ-irradiated polyolefins. It was found that the biodegradation significantly depends on the components of stabilization system, mobility, interaction, and consumption of stabilizers.

Keywords: biodegradation, γ-irradiation, polyolefins, stabilization

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8419 Anodization-Assisted Synthesis of Shape-Controlled Cubic Zirconia Nanotubes

Authors: Ibrahim Dauda Muhammad, Mokhtar Awang

Abstract:

To synthesize a specific phase of zirconia (ZrO₂) nanotubes, zirconium (Zr) foil was subjected to the anodization process in a fluorine-containing electrochemical bath for a fixed duration. The resulting zirconia nanotubes (ZNTs) were then characterized using various techniques, including UV-vis spectroscopy, Fourier-transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDX), and X-ray diffraction (XRD). The XRD diffraction pattern confirmed that the ZNTs were crystalline, with a predominant texture along the [111] direction, indicating that the majority of the phase was cubic. TEM images revealed that most of the nanotubes were vertically aligned and self-organized, with diameters ranging from 32.9 to 38.8 nm and wall thicknesses between 3.0 and 7.3 nm. Additionally, the synthesized ZNTs had a length-to-width ratio of 235, which closely matches the ratio of 240 observed in another study where anodization was not used. This study demonstrates that a specific phase of zirconia nanotube can be successfully synthesized, with promising potential applications in catalysis and other areas.

Keywords: zirconia nanotubes, anodization, characterization, cubic phase

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8418 Non-Linear Dynamic Analyses of Grouted Pile-Sleeve Connection

Authors: Mogens Saberi

Abstract:

The focus of this article is to present the experience gained from the design of a grouted pile-sleeve connection and to present simple design expressions which can be used in the preliminary design phase of such connections. The grout pile-sleeve connection serves as a connection between an offshore jacket foundation and pre-installed piles located in the seabed. The jacket foundation supports a wind turbine generator resulting in significant dynamic loads on the connection. The connection is designed with shear keys in order to optimize the overall design but little experience is currently available in the use of shear keys in such connections. It is found that the consequence of introducing shear keys in the design is a very complex stress distribution which requires special attention due to significant fatigue loads. An optimal geometrical shape of the shear keys is introduced in order to avoid large stress concentration factors and a relatively easy fabrication. The connection is analysed in ANSYS Mechanical where the grout is modelled by a non-linear material model which allows for cracking of the grout material and captures the elastic-plastic behaviour of the grout material. Special types of finite elements are used in the interface between the pile sleeve and the grout material to model the slip surface between the grout material and the steel. Based on the performed finite element modelling simple design expressions are introduced.

Keywords: fatigue design, non-linear finite element modelling, structural dynamics, simple design expressions

Procedia PDF Downloads 389
8417 Machine Learning Models for the Prediction of Heating and Cooling Loads of a Residential Building

Authors: Aaditya U. Jhamb

Abstract:

Due to the current energy crisis that many countries are battling, energy-efficient buildings are the subject of extensive research in the modern technological era because of growing worries about energy consumption and its effects on the environment. The paper explores 8 factors that help determine energy efficiency for a building: (relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, and glazing area distribution), with Tsanas and Xifara providing a dataset. The data set employed 768 different residential building models to anticipate heating and cooling loads with a low mean squared error. By optimizing these characteristics, machine learning algorithms may assess and properly forecast a building's heating and cooling loads, lowering energy usage while increasing the quality of people's lives. As a result, the paper studied the magnitude of the correlation between these input factors and the two output variables using various statistical methods of analysis after determining which input variable was most closely associated with the output loads. The most conclusive model was the Decision Tree Regressor, which had a mean squared error of 0.258, whilst the least definitive model was the Isotonic Regressor, which had a mean squared error of 21.68. This paper also investigated the KNN Regressor and the Linear Regression, which had to mean squared errors of 3.349 and 18.141, respectively. In conclusion, the model, given the 8 input variables, was able to predict the heating and cooling loads of a residential building accurately and precisely.

Keywords: energy efficient buildings, heating load, cooling load, machine learning models

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8416 Characterization of Copper Slag and Jarofix Waste Materials for Road Construction

Authors: V. K. Arora, V. G. Havanagi, A. K. Sinha

Abstract:

Copper slag and Jarofix are waste materials, generated during the manufacture of copper and zinc respectively, which have potential for utility in embankment and road construction. Accordingly, a research project was carried out to study the characteristics of copper slag and Jarofix to utilize in the construction of road. In this study, copper slag and Jarofix were collected from Tuticorin, State of Tamil Nadu and Hindustan Zinc Ltd., Chittorgarh, Rajasthan state, India respectively. These materials were investigated for their physical, chemical, and geotechnical characteristics. The materials were collected from the disposal area and laboratory investigations were carried out to study its feasibility for use in the construction of embankment and sub grade layers of road pavement. This paper presents the results of physical, chemical and geotechnical characteristics of copper slag and Jarofix. It was concluded that copper slag and Jarofix may be utilized in the construction of road.

Keywords: copper slag, Jarofix waste, material, road construction

Procedia PDF Downloads 455
8415 Optimization of Tangential Flow Filtration Process for Purifying DNA Vaccine

Authors: Piyakajornkul T., Noppiboon S., Hochareon L., Kitsubun P.

Abstract:

Nowadays, DNA vaccines become an interesting subject in the third vaccine generation. The platform of DNA vaccines production has been developed and its downstream process becomes challenging due to the quality of the products in terms of purity and percentage of supercoiled DNA. To overcome these challenges, tangential flow filtration (TFF), which is involved in the purification process, could be used since it provides effective separation of impurity prior to performing further purification steps. However, operating conditions of TFF is varied based on several factors such as sizes of target particle and impurities, a concentration of solution as well as a concentration polarization on the membrane surface. In this study, pVAX1/lacZ was used as a model of TFF optimization in order to prevent a concentration polarization that can lead to the membrane fouling and also minimize a diafiltration volume while maintaining the maximum permeate flux resulting in proper operating times and buffer volume. By using trans membrane pressure (TMP) excursion method, feed flow rates and TMP were varied. The results showed a correlation of permeate flux with TMP where the maximum volume concentration factor reached 2.5 times of the initial volume when feed flow rate and TMP were 7 liters/m²/min and 1 bar, respectively. It was optimal operating conditions before TFF system undergone pressure independent regime. In addition, the diafiltration volume was 14 times of the concentrated volume prior to performing a further anion chromatography process.

Keywords: concentration polarization, DNA vaccines, optimization, permeate flux, pressure dependent, tangential flow filtration (TFF), trans membrane pressure (TMP)

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8414 Study of Cathodic Protection for Trunk Pipeline of Al-Garraf Oil Field

Authors: Maysoon Khalil Askar

Abstract:

The delineation of possible areas of corrosion along the external face of an underground oil pipeline in Trunk line of Al- Garraf oil field was investigated using the horizontal electrical resistivity profiling technique and study the contribution of pH, Moisture Content in Soil and Presence chlorides, sulfates and total dissolve salts in soil and water. The test sites represent a physical and chemical properties of soils. The hydrogen-ion concentration of soil and groundwater range from 7.2 to 9.6, and the resistivity values of the soil along the pipeline were obtained using the YH302B model resistivity meter having values between 1588 and 720 Ohm-cm. the chloride concentration in soil and groundwater is high (more than 1000 ppm), total soulable salt is more than 5000 ppm, and sulphate range from 0.17% and 0.98% in soil and more than 600 ppm in groundwater. The soil is poor aeration, the soil texture is fine (clay and silt soil), the water content is high (the groundwater is close to surface), the chloride and sulphate is high in the soil and groundwater, the total soulable salt is high in ground water and finally the soil electric resistivity is low that the soil is very corrosive and there is the possibility of the pipeline failure. These methods applied in the study are quick, economic and efficient for detecting along buried pipelines which need to be protected. Routine electrical geophysical investigations along buried oil pipelines should be undertaken for the early detection and prevention of pipeline failure with its attendant environmental, human and economic consequences.

Keywords: soil resistivity, corrosion, cathodic protection, chloride concentration, water content

Procedia PDF Downloads 440
8413 Showing Broccoli and Cabbage Genotypes Biodiversity Using Randomly Amplified Polymorphic DNAs (RAPD)

Authors: M. M. A. Abdalla, M. H. Aboul-Nasr, Shimaa H. Mosallam

Abstract:

Ten RAPD markers were used to detect the genetic variability and relationships among four broccoli and three cabbage genotypes. The results of RAPD analysis showed that all the five primers surveyed detected polymorphism for all broccoli genotypes. A total of 39 DNA bands were amplified by the 5 primers from all genotype and 21 of these fragments showed polymorphism (53.85%). The rest of these bands (46.15%) were common between the four genotypes. On the other hand, all of the 7 primers surveyed, used with cabbage, detected polymorphism among all cabbage genotype. A total of 69 DNA bands were amplified by the 7 primers from all genotypes and 23 of these fragments showed polymorphism (33.33%). The rest of these bands (66.67%) were common between the three genotypes. The investigation suggested that the RAPD approach showed considerable potential for identifying and discriminating broccoli and cabbage genotypes.

Keywords: Brassica oleracea, genotypes, genetic markers, varietal identification, DNA polymorphism, RAPD markers

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8412 Cloud Monitoring and Performance Optimization Ensuring High Availability and Security

Authors: Inayat Ur Rehman, Georgia Sakellari

Abstract:

Cloud computing has evolved into a vital technology for businesses, offering scalability, flexibility, and cost-effectiveness. However, maintaining high availability and optimal performance in the cloud is crucial for reliable services. This paper explores the significance of cloud monitoring and performance optimization in sustaining the high availability of cloud-based systems. It discusses diverse monitoring tools, techniques, and best practices for continually assessing the health and performance of cloud resources. The paper also delves into performance optimization strategies, including resource allocation, load balancing, and auto-scaling, to ensure efficient resource utilization and responsiveness. Addressing potential challenges in cloud monitoring and optimization, the paper offers insights into data security and privacy considerations. Through this thorough analysis, the paper aims to underscore the importance of cloud monitoring and performance optimization for ensuring a seamless and highly available cloud computing environment.

Keywords: cloud computing, cloud monitoring, performance optimization, high availability

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8411 Arbutin-loaded Butylglyceryl Dextran Nanoparticles for Topical Delivery

Authors: Mohammad F. Bostanudin, Tan S. Fei, Azwan M. Lazim

Abstract:

Toward the development of colloidal systems that are able to enhance permeation across the skin, a material combining the non-toxic and non-immunogenic of dextran with alkylglycerols permeation enhancing property has been designed. To this purpose, a range of butylglyceryl dextrans (DEX-OX4) were synthesized via functionalization with n-butylglycidyl ether and the successful functionalization was confirmed by NMR and FT-IR spectroscopies, along with GPC with a degree of modification in the range 6.3–35.7 %. A reduced viscosity and an increased molecular weight of DEX-OX4 were also recorded when compared to that of the native dextran. DEX-OX4 was further formulated into nanocarriers and loaded with α-arbutin prior to be investigated for their particle size, morphology, stability, loading ability, and release profiles. The resulting nanoparticles were found to be close-to-spherical and relatively stable at pH 5 and 7, with size 180–220 nm (ζ-potential -22 to -25 mV), and a loading degree of 11.7 %. Lack of toxicity at application-relevant concentrations and increased permeation across skin biological membrane model were demonstrated by nanoparticles in-vitro results against immortalized skin human keratinocytes cells (HaCaT).

Keywords: butylglycerols, dextran, nanoparticles, transdermal

Procedia PDF Downloads 127