Search results for: 3D smart network composite structures

Authors: Yousuf Nasser Al Khamisi

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Purpose: This paper presents a Knowledge Transfer (KT) Framework in healthcare sectors by applying a systematic literature review process to the healthcare organizations domain to identify enablers and barriers of KT in Healthcare. Methods: The paper conducted a systematic literature search of peer-reviewed papers that described key elements of KT using four databases (Medline, Cinahl, Scopus, and Proquest) for a 10-year period (1/1/2008–16/10/2017). The results of the literature review were used to build a conceptual framework of KT in healthcare organizations. The author used a systematic review of the literature, as described by Barbara Kitchenham in Procedures for Performing Systematic Reviews. Findings: The paper highlighted the impacts of using Knowledge Management (KM) concept at a healthcare organization in controlling infectious diseases in hospitals, improving family medicine performance and enhancing quality improvement practices. Moreover, it found that good-coding performance is analytically linked with a knowledge sharing network structure rich in brokerage and hierarchy rather than in density. The unavailability or ignored of the latest evidence on more cost-effective or more efficient delivery approaches leads to increase the healthcare costs and may lead to unintended results. Originality: Search procedure produced 12,093 results, of which 3523 were general articles about KM and KT. The titles and abstracts of these articles had been screened to segregate what is related and what is not. 94 articles identified by the researchers for full-text assessment. The total number of eligible articles after removing un-related articles was 22 articles.

Keywords: healthcare organisation, knowledge management, knowledge transfer, KT framework

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Authors: Deepti Mishra, K. K Pant, Xiu Song Zhao, Muxina Konarova

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Catalytic transformation of simplest hydrocarbon methane into benzene and valuable chemicals over Mo/HZSM-5 has a great economic potential, however, it suffers serious hurdles due to the blockage in the micropores because of extensive coking at high temperature during methane dehydroaromatization (MDA). Under such conditions, it necessitates the design of micro/mesoporous ZSM-5, which has the advantages viz. uniform dispersibility of MoOx species, consequently the formation of active Mo sites in the micro/mesoporous channel and lower carbon deposition because of improved mass transfer rate within the hierarchical pores. In this study, we report a unique strategy to control the porous structures of ZSM-5 through a dual templating approach, utilizing C6 and C12 -surfactants as porogen. DFT studies were carried out to correlate the ZSM-5 framework development using the C6 and C12 surfactants with structure directing agent. The structural and morphological parameters of the synthesized ZSM-5 were explored in detail to determine the crystallinity, porosity, Si/Al ratio, particle shape, size, and acidic strength, which were further correlated with the physicochemical and catalytic properties of Mo modified HZSM-5 catalysts. After Mo incorporation, all the catalysts were tested for MDA reaction. From the activity test, it was observed that C6 surfactant-modified hierarchically porous Mo/HZSM-5(H) showed the highest benzene formation rate (1.5 μmol/gcat. s) and longer catalytic stability up to 270 min of reaction as compared to the conventional microporous Mo/HZSM-5(C). In contrary, C12 surfactant modified Mo/HZSM-5(D) is inferior towards MDA reaction (benzene formation rate: 0.5 μmol/gcat. s). We ascribed that the difference in MDA activity could be due to the hierarchically interconnected meso/microporous feature of Mo/HZSM-5(H) that precludes secondary reaction of coking from benzene and hence contributing substantial stability towards MDA reaction.

Keywords: hierarchical pores, Mo/HZSM-5, methane dehydroaromatization, coke deposition

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Authors: Prateek Goyal, Archini Paruthi, Superb K. Misra

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Contamination of water resources has been a major concern, which has drawn attention to the need to develop new material models for treatment of effluents. Existing conventional waste water treatment methods remain ineffective sometimes and uneconomical in terms of remediating contaminants like heavy metal ions (mercury, arsenic, lead, cadmium and chromium); organic matter (dyes, chlorinated solvents) and high salt concentration, which makes water unfit for consumption. We believe that nanotechnology based strategy, where we use nanoparticles as a tool to remediate a class of pollutants would prove to be effective due to its property of high surface area to volume ratio, higher selectivity, sensitivity and affinity. In recent years, scientific advancement has been made to study the application of photocatalytic (ZnO, TiO2 etc.) nanomaterials and magnetic nanomaterials in remediating contaminants (like heavy metals and organic dyes) from water/wastewater. Our study focuses on the synthesis and monitoring remediation efficiency of ZnO, Fe3O4 and Fe3O4 coated ZnO nanoparticulate system for the removal of heavy metals and dyes simultaneously. Multitude of ZnO nanostructures (spheres, rods and flowers) using multiple routes (microwave & hydrothermal approach) offers a wide range of light active photo catalytic property. The phase purity, morphology, size distribution, zeta potential, surface area and porosity in addition to the magnetic susceptibility of the particles were characterized by XRD, TEM, CPS, DLS, BET and VSM measurements respectively. Further on, the introduction of crystalline defects into ZnO nanostructures can also assist in light activation for improved dye degradation. Band gap of a material and its absorbance is a concrete indicator for photocatalytic activity of the material. Due to high surface area, high porosity and affinity towards metal ions and availability of active surface sites, iron oxide nanoparticles show promising application in adsorption of heavy metal ions. An additional advantage of having magnetic based nanocomposite is, it offers magnetic field responsive separation and recovery of the catalyst. Therefore, we believe that ZnO linked Fe3O4 nanosystem would be efficient and reusable. Improved photocatalytic efficiency in addition to adsorption for environmental remediation has been a long standing challenge, and the nano-composite system offers the best of features which the two individual metal oxides provide for nanoremediation.

Keywords: adsorption, nanocomposite, nanoremediation, photocatalysis

Procedia PDF Downloads 238

Authors: Y. Mehdipour, S. Ebrahimi, A. Jahanpour, F. Seyedzaei, B. Sabayan, A. Karimi, H. Amirifard

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Ischemic stroke is one of the common reasons for disability and mortality. The fourth leading cause of death in the world and the third in some other sources. Only 1/3 of the patients with ischemic stroke fully recover, 1/3 of them end in permanent disability and 1/3 face death. Thus, the use of predictive models to predict stroke has a vital role in reducing the complications and costs related to this disease. Thus, the aim of this study was to specify the effective factors and predict ischemic stroke with the help of DM methods. The present study was a descriptive-analytic study. The population was 213 cases from among patients referring to Ali ibn Abi Talib (AS) Hospital in Zahedan. Data collection tool was a checklist with the validity and reliability confirmed. This study used DM algorithms of decision tree for modeling. Data analysis was performed using SPSS-19 and SPSS Modeler 14.2. The results of the comparison of algorithms showed that CHAID algorithm with 95.7% accuracy has the best performance. Moreover, based on the model created, factors such as anemia, diabetes mellitus, hyperlipidemia, transient ischemic attacks, coronary artery disease, and atherosclerosis are the most effective factors in stroke. Decision tree algorithms, especially CHAID algorithm, have acceptable precision and predictive ability to determine the factors affecting ischemic stroke. Thus, by creating predictive models through this algorithm, will play a significant role in decreasing the mortality and disability caused by ischemic stroke.

Keywords: data mining, ischemic stroke, decision tree, Bayesian network

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Authors: Kimmo J. Kurppa

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This paper describes the development of the buyer-supplier dyad concept over the years and proposes improvements, clarifications and extensions to the prevailing definitions published in 1970’s and 1980’s. This paper suggests a partition of the buyer-supplier dyad to concepts of Commercial Dyad (dyadic interaction in vertical relationships) and Innovative Dyad (dyadic interaction in horizontal relationship) since dyadic interaction takes place in two major types of contexts between industrial firms. Especially the context of joint product development in a dyadic relationship has not been adequately recognized being totally different from the interaction taking place in commercial buyer-supplier interaction. This paper provides therefore a solution to the existing gap in research by clarifying the descriptions and the context where dyadic interaction takes place between industrial firms. This paper also illustrates and explains how the firm’s organization and the interaction taking place inside it, is connected to the dyadic interaction structure between the firm and its partner firm. This theme has been discussed earlier but the phenomenon has not been adequately described and has not been illustrated in earlier research. This conceptual study has been interested in how the dyad concept of Industrial Marketing has been defined in the earlier research and how the definition could be improved. This conceptual paper has been constructed by using the systematic review methodology and proposes avenues for future research. The concept and existence of relationship and interaction between firm’s internal interaction network and external interaction between firm’s dyadic counterparts, need to be verified through empirical research.

Keywords: dyadic interaction, industrial dyad, buyer-supplier relationship, strategic reciprocity, experience, socially adjusted opportunism

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Authors: Lekgowa Collen Makola, Cecil Naphtaly Moro Ouma, Sharon Moeno, Langelihle Dlamini

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In recent years, advancement in the field of nanotechnology has evolved new strategies to address energy and environmental issues. Amongst the developing technologies, visible-light-driven photocatalysis is regarded as a sustainable approach for energy production and environmental detoxifications, where transition metal oxides (TMOs) and metal-free carbon-based semiconductors such as graphitic carbon nitride (CN) evidenced notable potential in this matter. Herein, g-C₃N₄@WO₃@Ti₃C₂Tx three-component multijunction photocatalyst was fabricated via facile ultrasonic-assisted self-assembly, followed by calcination to facilitate extensive integrations of the materials. A series of different Ti₃C₂ wt% loading in the g-C₃N4@WO₃@Ti₃C₂Tx were prepared and represented as 1-CWT, 3-CWT, 5-CWT, and 7-CWT corresponding to 1, 3, 5, and 7wt%, respectively. Systematic characterization using spectroscopic and microscopic techniques were employed to validate the successful preparation of the photocatalysts. Enhanced optoelectronic and photoelectrochemical properties were observed for the WO₃@Ti₃C2@g-C₃N4 heterostructure with respect to the individual materials. Photoluminescence spectra and Nyquist plots show restrained recombination rates and improved photocarrier conductivities, respectively, and this was credited to the synergistic coupling effect and the presence of highly conductive Ti₃C2 MXene. The strong interfacial contact surfaces upon the formation of the composite were confirmed using XPS. Multiple charge transfer mechanisms were proposed for the WO3@Ti3C₂@g-C3N4, which couples Z-scheme and Schottky-junction mediated with Ti3C2 MXene. Bode phase plots show improved charge carrier life-times upon the formation of the multijunctional photocatalyst. Moreover, transient photocurrent density of 7-CWT is 40 and seven (7) times higher compared to that of g-C₃N4 and WO3, correspondingly. Unlike in the traditional Z-Scheme, the formed ternary heterostructure possesses interfaces through the metallic 2D Ti₃C₂ MXene, which provided charge transfer channels for efficient photocarrier transfers with carrier concentrations (ND) of 17.49×1021 cm-3 and 4.86% photo-to-chemical conversion efficiency. The as-prepared ternary g-C₃N₄@WO₃@Ti₃C₂Tx exhibited excellent photoelectrochemical properties with reserved redox band potential potencies to facilitate efficient photo-oxidation and -reduction reactions. The fabricated multijunction photocatalyst exhibits potentials to be used in an extensive range of photocatalytic process vis., production of valuable hydrocarbons from CO₂, production of H₂, and degradation of a plethora of pollutants from wastewater.

Keywords: photocatalysis, Z-scheme, multijunction heterostructure, Ti₃C₂ MXene, g-C₃N₄

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Authors: Shiv Jyoti Pandey, Shveta Puri, G. M. Bhat, Neha Raina

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The Jammu and Kashmir (J&K) region of Northwest Himalaya has a long history of earthquake activity which falls within Seismic Zones IV and V. To know the crustal structure beneath this region, we utilized teleseismic receiver function method. This paper presents the results of the analyses of the teleseismic earthquake waves recorded by 10 seismic observatories installed in the vicinity of major thrusts and faults. The teleseismic waves at epicentral distance between 30o and 90o with moment magnitudes greater than or equal to 5.5 that contains large amount of information about the crust and upper mantle structure directly beneath a receiver has been used. The receiver function (RF) technique has been widely applied to investigate crustal structures using P-to-S converted (Ps) phases from velocity discontinuities. The arrival time of the Ps, PpPs and PpSs+ PsPs converted and reverberated phases from the Moho can be combined to constrain the mean crustal thickness and Vp/Vs ratio. Over 500 receiver functions from 10 broadband stations located in the Jammu & Kashmir region of Northwest Himalaya were analyzed. With the help of H-K stacking method, we determined the crustal thickness (H) and average crustal Vp/Vs ratio (K) in this region. We also used Neighbourhood algorithm technique to verify our results. The receiver function results for these stations show that the crustal thickness under Jammu & Kashmir ranges from 45.0 to 53.6 km with an average value of 50.01 km. The Vp/Vs ratio varies from 1.63 to 1.99 with an average value of 1.784 which corresponds to an average Poisson’s ratio of 0.266 with a range from 0.198 to 0.331. High Poisson’s ratios under some stations may be related to partial melting in the crust near the uppermost mantle. The crustal structure model developed from this study can be used to refine the velocity model used in the precise epicenter location in the region, thereby increasing the knowledge to understand current seismicity in the region.

Keywords: H-K stacking, Poisson’s ratios, receiver function, teleseismic

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Authors: Houria Rezala, Jose Luis Valverde, Amaya Romero, Alessandra Molinari, Andrea Maldotti

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A pillared montmorillonite containing iron doped titania (Fe/Ti-PILC) has been prepared from a natural clay. This material has been characterized by X-ray diffraction, nitrogen adsorption, temperature programmed desorption of ammonia, inductively coupled plasma atomic emission spectroscopy, atomic absorption, and diffuse reflectance UV-VIS spectroscopy. The layer structure of Fe/Ti-PILC resulted to be ordered with an insertion of pillars, which caused a slight increase in the basal spacing of the clay. Its specific surface area was about three times larger than that of the parent Na-montmorillonite due principally to the creation of a remarkable microporous network. The doped material was a robust photocatalyst able to oxidize liquid alkyl aromatics to the corresponding carbonylic derivatives, using O2 as the oxidizing species, at mild pressure and temperature conditions. Accumulation of valuable carbonylic derivatives was possible since their over-oxidation to carbon dioxide was negligible. Fe/Ti-PILC was able to discriminate between toluene and cyclohexane in favor of the aromatic compound with an efficiency that is about three times higher than that of titanium pillared clays (Ti-PILC). It is likely that the addition of iron favored the formation of new acid sites able to interact with the aromatic substrate. Iron doping caused a significant TiO2 visible light-induced activity (wavelength > 400 nm) with only minor negative effects on its performance under UV-light irradiation (wavelength > 290 nm).

Keywords: alkyl aromatics oxidation, heterogeneous photocatalysis, iron doping, pillared clays

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Authors: Robin C. Ladwig

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Diversity Management, as a substantial element of Human Resource Management, aims to secure the economic benefit that assumingly comes with a diverse workforce. Consequently, diversity managers focus on the protection of employees and securing equality measurements to assure organisational gender diversity. Gender diversity as one aspect of Diversity Management seems to adhere to gender binarism and cis-normativity. Workplaces are gendered spaces which are echoing the binary gender-normativity presented in Diversity Management, sold under the label of gender diversity. While the expectation of Diversity Management implies the inclusion of a multiplicity of marginalised groups, such as trans and gender diverse people, in current literature and practice, the reality is curated by gender binarism and cis-normativity. The qualitative multi-method research showed a lack of knowledge about trans and gender diverse matters within the profession of Diversity Management and Human Resources. The semi-structured interviews with trans and gender diverse individuals from various backgrounds and occupations in Australia exposed missing considerations of trans and gender diverse experiences in the inclusivity and gender equity of various workplaces. Even if practitioners consider trans and gender diverse matters under gender diversity, the practical execution is limited to gender binary structures and cis-normative actions as the photo-elicit questionnaire with diversity managers, human resource officers, and personnel management demonstrates. Diversity Management should approach a broader source of informed practice by extending their business focus to the knowledge of humanity studies. Humanity studies could include diversity, queer, or gender studies to increase the inclusivity of marginalised groups such as trans and gender diverse employees and people. Furthermore, the definition of gender diversity should be extended beyond the gender binary and cis-normative experience. People may lose trust in Diversity Management as a supportive ally of marginalised employees if the understanding of inclusivity is limited to a gender binary and cis-normativity value system that misrepresents the richness of gender diversity.

Keywords: cis-normativity, diversity management, gender binarism, trans and gender diversity

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Authors: Hilal Köse, Şeyma Dombaycıoğlu, Ali Osman Aydın, Hatem Akbulut

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Rechargeable lithium-ion batteries (LIBs) have become promising power sources for a wide range of applications, such as mobile communication devices, portable electronic devices and electrical/hybrid vehicles due to their long cycle life, high voltage and high energy density. Graphite, as anode material, has been widely used owing to its extraordinary electronic transport properties, large surface area, and high electrocatalytic activities although its limited specific capacity (372 mAh g-1) cannot fulfil the increasing demand for lithium-ion batteries with higher energy density. To settle this problem, many studies have been taken into consideration to investigate new electrode materials and metal oxide/graphene composites are selected as a kind of promising material for lithium ion batteries as their specific capacities are much higher than graphene. Among them, SnO₂, an n-type and wide band gap semiconductor, has attracted much attention as an anode material for the new-generation lithium-ion batteries with its high theoretical capacity (790 mAh g-1). However, it suffers from large volume changes and agglomeration associated with the Li-ion insertion and extraction processes, which brings about failure and loss of electrical contact of the anode. In addition, there is also a huge irreversible capacity during the first cycle due to the formation of amorphous Li₂O matrix. To obtain high capacity anode materials, we studied on the synthesis and characterization of SnO₂-Graphene nanocomposites and investigated the capacity of this free-standing anode material in this work. For this aim, firstly, graphite oxide was obtained from graphite powder using the method described by Hummers method. To prepare the nanocomposites as free-standing anode, graphite oxide particles were ultrasonicated in distilled water with SnO2 nanoparticles (1:1, w/w). After vacuum filtration, the GO-SnO₂ paper was peeled off from the PVDF membrane to obtain a flexible, free-standing GO paper. Then, GO structure was reduced in hydrazine solution. Produced SnO2- graphene nanocomposites were characterized by scanning electron microscopy (SEM), energy dispersive X-ray spectrometer (EDS), and X-ray diffraction (XRD) analyses. CR2016 cells were assembled in a glove box (MBraun-Labstar). The cells were charged and discharged at 25°C between fixed voltage limits (2.5 V to 0.2 V) at a constant current density on a BST8-MA MTI model battery tester with 0.2C charge-discharge rate. Cyclic voltammetry (CV) was performed at the scan rate of 0.1 mVs-1 and electrochemical impedance spectroscopy (EIS) measurements were carried out using Gamry Instrument applying a sine wave of 10 mV amplitude over a frequency range of 1000 kHz-0.01 Hz.

Keywords: SnO₂-graphene, nanocomposite, anode, Li-ion battery

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Authors: E. Farg, M. M. El-Sharkawy, M. S. Mostafa, S. M. Arafat

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Mapping water stress provides important baseline data for sustainable agriculture. Recent developments in the new Sentinel-1 data which allow the acquisition of high resolution images and varied polarization capabilities. This study was conducted to detect and quantify vegetation water content from canopy backscatter for extracting spatial information to encourage drought mapping activities throughout new reclaimed sandy soils in western Nile delta, Egypt. The performance of radar imagery in agriculture strongly depends on the sensor polarization capability. The dual mode capabilities of Sentinel-1 improve the ability to detect water stress and the backscatter from the structure components improves the identification and separation of vegetation types with various canopy structures from other features. The fieldwork data allowed identifying of water stress zones based on land cover structure; those classes were used for producing harmonious water stress map. The used analysis techniques and results show high capability of active sensors data in water stress mapping and monitoring especially when integrated with multi-spectral medium resolution images. Also sub soil drip irrigation systems cropped areas have lower drought and water stress than center pivot sprinkler irrigation systems. That refers to high level of evaporation from soil surface in initial growth stages. Results show that high relationship between vegetation indices such as Normalized Difference Vegetation Index NDVI the observed radar backscattering. In addition to observational evidence showed that the radar backscatter is highly sensitive to vegetation water stress, and essentially potential to monitor and detect vegetative cover drought.

Keywords: canopy backscatter, drought, polarization, NDVI

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Authors: Ekaterina S. Marchenko, Gulsharat A. Baigonakova, Kirill M. Dubovikov, Igor A. Khlusov

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NiTi alloys combine biomechanical and biochemical properties. This makes them a perfect candidate for medical applications. However, there is a serious problem with these alloys, such as the release of Ni from the matrix. Ni ions are known to be toxic to living tissues and leach from the matrix into the surrounding implant tissues due to corrosion after prolonged use. To prevent the release of Ni ions, corrosive strong coatings are usually used. Titanium nitride-based coatings are perfect corrosion inhibitors and also have good bioactive properties. However, there is an opportunity to improve the biochemical compatibility of the surface by depositing another layer. This layer can consist of elements such as calcium and phosphorus. The Ca and P ions form different calcium phosphate phases, which are present in the mineral part of human bones. We therefore believe that these elements must promote osteogenesis and osteointegration. In view of the above, the aim of this study is to investigate the effect of crystallinity on the biocompatibility of a two-layer coating deposited on NiTi substrate by sputtering. The first step of the research, apart from the NiTi polishing, is the layer-by-layer deposition of Ti-Ni-Ti by magnetron sputtering and the subsequent synthesis of this composite in an N atmosphere at 900 °C. The total thickness of the corrosion resistant layer is 150 nm. Plasma assisted RF sputtering was then used to deposit a bioactive film on the titanium nitride layer. A Ca-P powder target was used to obtain such a film. We deposited three types of Ca-P layers with different crystallinity and compared them in terms of cytotoxicity. One group of samples had no Ca-P coating and was used as a control. We obtained different crystallinity by varying the sputtering parameters such as bias voltage, plasma source current and pressure. XRD analysis showed that all coatings are calcium phosphate, but the sample obtained at maximum bias and plasma source current and minimum pressure has the most intense peaks from the coating phase. SEM and EDS showed that all three coatings have a homogeneous and dense structure without cracks and consist of calcium, phosphorus and oxygen. Cytotoxic tests carried out on three types of samples with Ca-P coatings and a control group showed that the control sample and the sample with Ca-P coating obtained at maximum bias voltage and plasma source current and minimum pressure had the lowest number of dead cells on the surface, around 11 ± 4%. Two other types of samples with Ca-P coating have 40 ± 9% and 21 ± 7% dead cells on the surface. It can therefore be concluded that these two sputtering modes have a negative effect on the corrosion resistance of the whole samples. The third sputtering mode does not affect the corrosion resistance and has the same level of cytotoxicity as the control. It can be concluded that the most suitable sputtering mode is the third with maximum bias voltage and plasma source current and minimum pressure.

Keywords: calcium phosphate coating, cytotoxicity, NiTi alloy, two-layer coating

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Authors: A. Hamadelnil, Z. Razak, E. Matsoom

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Boat landings on fixed offshore structure are designed to absorb the impact energy from the boats approaching the platform for crew transfer. As the size and speed of operating boats vary, the design and maintenance of the boat landings become more challenging. Different oil and gas operators adopting different design criteria for the boat landing design in the region of South East Asia. Rubber strip is used to increase the capacity of the boat landing in absorbing bigger impact energy. Recently, it has been reported that all the rubber strips peel off the boat landing frame within one to two years, and replacement is required to avoid puncturing of the boat’s hull by the exposed sharp edges and bolts used to secure the rubber strip. The capacity of the boat landing in absorbing the impact energy is reduced after the failure of the rubber strip and results in failure of the steel members. The replacement of the rubber strip is costly as it requires a diving spread. The objective of this study is to propose the most practicable criteria to be adopted by oil and gas operators in the design of the boat landings in the region of South East Asia to improve the performance of the boat landing and assure safe operation and cheaper maintenance. This study explores the current design and maintenance challenges of boat landing and compares between the criteria adopted by different operators. In addition, this study explains the reasons behind the denting of many of the boat landing. It also evaluates the effect of grout and rubber strip in the capacity of the boat landing and jacket legs and highlight. Boat landing model and analysis using USFOS and SACS software are carried out and presented in this study considering different design criteria. This study proposes the most practicable criteria to be used in designing the boat landing in South East Asia region to save cost and achieve better performance, safe operation and less cost and maintenance.

Keywords: boat landing, grout, plastic hinge, rubber strip

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Authors: Chris Miskelly, Eoin Cunningham, Beatrice Smyth, John. D. Holbrey, Gosia Swadzba-Kwasny, Emily L. Byrne, Yoan Delavoux, Mantian Li.

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Recently, the use of ionic liquids (ILs) for the preparation of lignocellulose derived cellulosic materials as alternatives to petrochemical feedstocks has been the focus of considerable research interest. While the technical viability of IL-based lignocellulose treatment methodologies has been well established, the high cost of reagents inhibits commercial feasibility. This work aimed to assess the technoeconomic viability of the preparation of cellulose rich materials (CRMs) using protic ionic liquids (PILs) synthesized from low cost alkylamines and sulphuric acid. For this purpose, the tertiary alkylamines, triethylamine, and dimethylbutylamine were selected. Bulk scale production cost of the synthesized PILs, triethylammonium hydrogen sulphate and dimetheylbutylammonium hydrogen sulphate, was reported as $0.78 kg-1 to $1.24 kg-1. CRMs were prepared through the treatment of common wheat (Triticum aestivum) straw with these PILs. By controlling treatment parameters, CRMs with a cellulose content of ≥ 80 wt% were prepared. This was achieved using a T. aestivum straw to PIL loading ratio of 1:15 w/w, a treatment duration of 180 minutes, and ethanol as a cellulose antisolvent. Infrared spectra data and decreased onset degradation temperature of CRMs (ΔTONSET ~ 70 °C) suggested the formation of cellulose sulphate esters during treatment. Chemical derivatisation can aid the dispersion of prepared CRMs in non-polar polymer/ composite matrices, but act as a barrier to thermal processing at temperatures above 150 °C. It was also shown that treatment increased the crystallinity of CRMs (ΔCrI ~ 40 %) without altering the native crystalline structure or crystallite size (~ 2.6 nm) of cellulose; peaks associated with the cellulose I crystalline planes (110), (200), and (004) were observed at Bragg angles 16.0 °, 22.5 ° and 35.0 ° respectively. This highlighted the inability of assessed PILs to dissolve crystalline cellulose and was attributed to the high acidity (pKa ~ - 1.92 to - 6.42) of sulphuric acid derived anions. Electron micrographs revealed that the stratified multilayer tissue structure of untreated T. aestivum straw was significantly modified during treatment. T. aestivum straw particles were disassembled during treatment, with prepared CRMs adopting a golden-brown film-like appearance. This work demonstrated the degradation of non-cellulosic fractions of lignocellulose without dissolution of cellulose. It is the first to report on the derivatisation of cellulose during treatment with protic hydrogen sulphate ionic liquids, and the potential implications of this with reference to biopolymer feedstock preparation.

Keywords: cellulose, extraction, protic ionic liquids, esterification, thermal stability, waste valorisation, biopolymer feedstock

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Authors: Tyler Palma, Praveen Damasus, Michael Munther, Mehrdad Mohsenizadeh, Keivan Davami

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The advancement of additive manufacturing, in both research and commercial realms, is highly dependent upon continuing innovations and creativity in materials and designs. Additive manufacturing shows great promise towards revolutionizing various industries, due largely to the fact that design data can be used to create complex products and components, on demand and from the raw materials, for the end user at the point of use. However, it will be critical that the material properties of additively-made parts for engineering purposes be fully understood. As it is a relatively new additive manufacturing method, the response of properties of Multi Jet Fusion (MJF) produced parts to different printing parameters has not been well studied. In this work, testing of mechanical and tribological properties MJF-printed Polyamide 12 parts was performed to determine whether printing orientation in this method results in significantly different part performances. Material properties were studied at macro- and nanoscales. Tensile tests, in combination with tribology tests including steady-state wear, were performed. Results showed a significant difference in resultant part characteristics based on whether they were printed in a vertical or horizontal orientation. Tensile performance of vertically and horizontally printed samples varied, both in ultimate strength and strain. Tribology tests showed that printing orientation has notable effects on the resulting mechanical and wear properties of tested surfaces, due largely to layer orientation and the presence of unfused fused powder grain inclusions. This research advances the understanding of how print orientation affects the mechanical properties of additively manufactured structures, and also how print orientation can be exploited in future engineering design.

Keywords: additive manufacturing, indentation, nano mechanical characterization, print orientation

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Authors: Maedeh Pourmajidian, Joseph R. McDermid

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Advanced High Strength Steels are revolutionizing both the steel and automotive industries due to their high specific strength and ability to absorb energy during crash events. This allows manufacturers to design vehicles with significantly increased fuel efficiency without compromising passenger safety. To maintain the structural integrity of the fabricated parts, they must be protected from corrosion damage through continuous hot-dip galvanizing process, which is challenging due to selective oxidation of Mn and Si on the surface of this AHSSs. The effects of process atmosphere oxygen partial pressure and small additions of Sn on the selective oxidation of a medium-Mn C-6Mn-2Si advanced high strength steel was investigated. Intercritical annealing heat treatments were carried out at 690˚C in an N2-5%H2 process atmosphere under dew points ranging from –50˚C to +5˚C. Surface oxide chemistries, morphologies, and thicknesses were determined at a variety of length scales by several techniques, including SEM, TEM+EELS, and XPS. TEM observations of the sample cross-sections revealed the transition to internal oxidation at the +5˚C dew point. EELS results suggested that the internal oxides network was composed of a multi-layer oxide structure with varying chemistry from oxide core towards the outer part. The combined effect of employing a known surface active element as a function of process atmosphere on the surface structure development and the possible impact on reactive wetting of the steel substrates by the continuous galvanizing zinc bath will be discussed.

Keywords: 3G AHSS, hot-dip galvanizing, oxygen partial pressure, selective oxidation

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Authors: Lei Zhu, Nan Li

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Cold stamping has been widely applied in the automotive industry for the mass production of a great range of automotive panels. Predicting the springback to ensure the dimensional accuracy of the cold-stamped components is a critical step. The main approaches for the prediction and compensation of springback in cold stamping include running Finite Element (FE) simulations and conducting experiments, which require forming process expertise and can be time-consuming and expensive for the design of cold stamping tools. Machine learning technologies have been proven and successfully applied in learning complex system behaviours using presentative samples. These technologies exhibit the promising potential to be used as supporting design tools for metal forming technologies. This study, for the first time, presents a novel application of a Convolutional Neural Network (CNN) based surrogate model to predict the springback fields for variable U-shape cold bending geometries. A dataset is created based on the U-shape cold bending geometries and the corresponding FE simulations results. The dataset is then applied to train the CNN surrogate model. The result shows that the surrogate model can achieve near indistinguishable full-field predictions in real-time when compared with the FE simulation results. The application of CNN in efficient springback prediction can be adopted in industrial settings to aid both conceptual and final component designs for designers without having manufacturing knowledge.

Keywords: springback, cold stamping, convolutional neural networks, machine learning

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Authors: Martin Georgiev, Milena Nanova, Damyan Damov

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Architects, engineers, and developers need to analyse and implement a wide spectrum of data in different formats, if they want to produce viable residential developments. Usually, this data comes from a number of different sources and is not well structured. The main objective of this research project is to provide parametric tools working with real geodesic data that can generate residential solutions. Various codes, regulations and design constraints are described by variables and prioritized. In this way, we establish a common workflow for architects, geodesists, and other professionals involved in the building and investment process. This collaborative medium ensures that the generated design variants conform to various requirements, contributing to a more streamlined and informed decision-making process. The quantification of distinctive characteristics inherent to typical residential structures allows a systematic evaluation of the generated variants, focusing on factors crucial to designers, such as daylight simulation, circulation analysis, space utilization, view orientation, etc. Integrating real geodesic data offers a holistic view of the built environment, enhancing the accuracy and relevance of the design solutions. The use of generative algorithms and parametric models offers high productivity and flexibility of the design variants. It can be implemented in more conventional CAD and BIM workflow. Experts from different specialties can join their efforts, sharing a common digital workspace. In conclusion, our research demonstrates that a generative parametric approach based on real geodesic data and collaborative decision-making could be introduced in the early phases of the design process. This gives the designers powerful tools to explore diverse design possibilities, significantly improving the qualities of the building investment during its entire lifecycle.

Keywords: architectural design, residential buildings, urban development, geodesic data, generative design, parametric models, workflow optimization

Procedia PDF Downloads 52

Authors: Gautier Girard, Marion Martiny, Sebastien Mercier, Mohamad Jrad, Mohamed-Slim Bahi, Laurent Bodin, Francois Lechleiter, David Nevo, Sophie Dareys

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Reliability of electronic devices has always been of highest interest for Aero-MIL and space applications. In any electronic device, Printed Circuit Board (PCB), providing interconnection between components, is a key for reliability. During the last decades, PCB technologies evolved to sustain and/or fulfill increased original equipment manufacturers requirements and specifications, higher densities and better performances, faster time to market and longer lifetime, newer material and mixed buildups. From the very beginning of the PCB industry up to recently, qualification, experiments and trials, and errors were the most popular methods to assess system (PCB) reliability. Nowadays OEM, PCB manufacturers and scientists are working together in a close relationship in order to develop predictive models for PCB reliability and lifetime. To achieve that goal, it is fundamental to characterize precisely base materials (laminates, electrolytic copper, …), in order to understand failure mechanisms and simulate PCB aging under environmental constraints by means of finite element method for example. The laminates are woven composites and have thus an orthotropic behaviour. The in-plane properties can be measured by combining classical uniaxial testing and digital image correlation. Nevertheless, the out-of-plane properties cannot be evaluated due to the thickness of the laminate (a few hundred of microns). It has to be noted that the knowledge of the out-of-plane properties is fundamental to investigate the lifetime of high density printed circuit boards. A homogenization method combining analytical and numerical approaches has been developed in order to obtain the complete elastic orthotropic behaviour of a woven composite from its precise 3D internal structure and its experimentally measured in-plane elastic properties. Since the mechanical properties of the resin surrounding the fibres are unknown, an inverse method is proposed to estimate it. The methodology has been applied to one laminate used in hyperfrequency spatial applications in order to get its elastic orthotropic behaviour at different temperatures in the range [-55°C; +125°C]. Next; numerical simulations of a plated through hole in a double sided PCB are performed. Results show the major importance of the out-of-plane properties and the temperature dependency of these properties on the lifetime of a printed circuit board. Acknowledgements—The support of the French ANR agency through the Labcom program ANR-14-LAB7-0003-01, support of CNES, Thales Alenia Space and Cimulec is acknowledged.

Keywords: homogenization, orthotropic behaviour, printed circuit board, woven composites

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Authors: Muhammad Umair, Yasir Nawab, Khubab Shaker, Muhammad Maqsood, Adeel Zulfiqar, Danish Mahmood Baitab

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Fabric is a flexible woven material consisting of a network of natural or artificial fibers often referred to as thread or yarn. Today fabrics are produced by weaving, braiding, knitting, tufting and non-woven. Weaving is a method of fabric production in which warp and weft yarns are interlaced perpendicular to each other. There is infinite number of ways for the interlacing of warp and weft yarn. Each way produces a different fabric structure. The yarns parallel to the machine direction are called warp yarns and the yarns perpendicular to the machine direction are called weft or filling yarns. Air jet weaving is the modern method of weft insertion and considered as high speed loom. The twist loss in air jet during weft insertion affects the strength. The aim of this study was to investigate the effect of twist change in weft yarn during air-jet weft insertion. A total number of 8 samples were produced using 1/1 plain and 3/1 twill weave design with two fabric widths having same loom settings. Two different types of yarns like cotton and PC blend were used. The effect of material type, weave design and fabric width on twist change of weft yarn was measured and discussed. Twist change in the different types of weft yarn and weave design was measured and compared the twist change in the weft yarn with the yarn before weft yarn insertion and twist loss is measured. Wider fabric leads to higher twist loss in the yarn.

Keywords: air jet loom, twist per inch, twist loss, weft yarn

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Authors: Chaomeng Liu, Li Li, Xiao Wang, Li Ren, Qinge Zhang

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Late-life depression (LLD) is a prevalent mental disorder among the elderly, frequently accompanied by significant cognitive decline, and has emerged as a worldwide public health concern. Microglia, astrocytes, and peripheral immune cells play pivotal roles in regulating inflammatory responses within the central nervous system (CNS) across diverse cerebral disorders. This review commences with the clinical research findings and accentuates the recent advancements pertaining to microglia and astrocytes in the neuroinflammation process of LLD. The reciprocal communication network between the CNS and immune system is of paramount importance in the pathogenesis of depression and cognitive decline. Stress-induced downregulation of tight and gap junction proteins in the brain results in increased blood-brain barrier permeability and impaired astrocyte function. Concurrently, activated microglia release inflammatory mediators, initiating the kynurenine metabolic pathway and exacerbating the quinolinic acid/kynurenic acid imbalance. Moreover, the balance between Th17 and Treg cells is implicated in the preservation of immune homeostasis within the cerebral milieu of individuals suffering from LLD. The ultimate objective of this review is to present future strategies for the management and treatment of LLD, informed by the most recent advancements in research, with the aim of averting or postponing the onset of AD.

Keywords: neuroinflammation, late-life depression, microglia, astrocytes, central nervous system, blood-brain barrier, Kynurenine pathway

Procedia PDF Downloads 47

Authors: Redouane Larbi Boufeniza, Jing-Jia Luo

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This study assesses the suitability of deep learning (DL) for downscaling sea surface temperature (SST) over the Mediterranean Sea in the context of seasonal forecasting. We design a set of experiments that compare different DL configurations and deploy the best-performing architecture to downscale one-month lead forecasts of June–September (JJAS) SST from the Nanjing University of Information Science and Technology Climate Forecast System version 1.0 (NUIST-CFS1.0) for the period of 1982–2020. We have also introduced predictors over a larger area to include information about the main large-scale circulations that drive SST over the Mediterranean Sea region, which improves the downscaling results. Finally, we validate the raw model and downscaled forecasts in terms of both deterministic and probabilistic verification metrics, as well as their ability to reproduce the observed precipitation extreme and spell indicator indices. The results showed that the convolutional neural network (CNN)-based downscaling consistently improves the raw model forecasts, with lower bias and more accurate representations of the observed mean and extreme SST spatial patterns. Besides, the CNN-based downscaling yields a much more accurate forecast of extreme SST and spell indicators and reduces the significant relevant biases exhibited by the raw model predictions. Moreover, our results show that the CNN-based downscaling yields better skill scores than the raw model forecasts over most portions of the Mediterranean Sea. The results demonstrate the potential usefulness of CNN in downscaling seasonal SST predictions over the Mediterranean Sea, particularly in providing improved forecast products.

Keywords: Mediterranean Sea, sea surface temperature, seasonal forecasting, downscaling, deep learning

Procedia PDF Downloads 76

Authors: María Cárdenas Gaudry, Gonzalo Ramces Fano Miranda

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Sediment removal is very important in the purification of water, not only for reasons of visual perception but also because of its association with odor and taste problems. The Cuchoquesera reservoir, which is in the Andean region of Ayacucho (Peru) at an altitude of 3,740 meters above sea level, visually presents suspended particles and organic impurities indicating that it contains water of dubious quality to deduce that it is suitable for direct consumption of human beings. In order to quantitatively know the degree of impurities, water quality monitoring was carried out from February to August 2018, in which four sampling stations were established in the reservoir. The selected measured parameters were electrical conductivity, total dissolved solids, pH, color, turbidity, and sludge volume. The indicators of the studied parameters exceed the permissible limits except for electrical conductivity (190 μS/cm) and total dissolved solids (255 mg/L). In this investigation, the best combination and the optimal doses of reagents were determined that allowed the removal of sediments from the waters of the Cuchoquesera reservoir, through the physicochemical process of coagulation-flocculation. In order to improve this process during the rainy season, six combinations of reagents were evaluated, made up of three coagulants (ferric chloride, ferrous sulfate, and aluminum sulfate) and two natural flocculants: prickly pear powder (Opuntia ficus-indica) and tara gum (Caesalpinia spinoza). For each combination of reagents, jar tests were developed following the central composite experimental design (CCED), where the design factors were the doses of coagulant and flocculant and the initial turbidity. The results of the jar tests were adjusted to mathematical models, obtaining that to treat the water from the Cuchoquesera reservoir, with a turbidity of 150 UTN and a color of 137 U Pt-Co, 27.9 mg/L of the coagulant aluminum sulfate with 3 mg/L of the natural tara gum flocculant to produce a purified water quality of 1.7 UTN of turbidity and 3.2 U Pt-Co of apparent color. The estimated cost of the dose of coagulant and flocculant found was 0.22 USD/m³. This is how “grey-green” technologies can be used as a combination in nature-based solutions in water treatment, in this case, to achieve potability, making it more sustainable, especially economically, if green technology is available at the site of application of the nature-based hybrid solution. This research is a demonstration of the compatibility of natural coagulants/flocculants with other treatment technologies in the integrated/hybrid treatment process, such as the possibility of hybridizing natural coagulants with other types of coagulants.

Keywords: prickly pear powder, tara gum, nature-based solutions, aluminum sulfate, jar test, turbidity, coagulation, flocculation

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Authors: Anca Maria Cimpean, Serban Comsa

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Chick embryo chorioallantoic membrane (CAM) is a well vascularised in vivo experimental model used as a platform for testing the behavior of different implants inserted on it from tumor fragments to therapeutic agents or various biomaterials. Five types of collagen-based biomaterials with 2D and 3D structure (MotifMesh, Optimaix2D, Optimaix3D, Dual Layer Collagen and Xenoderm) were implanted on CAM and continuously evaluated by stereomicroscope for up to 5 days post-implant with an emphasis of their ability to requisite and develop new blood vessels (BVs) followed by microscopic analysis. MotifMEsh did not induce any angiogenic response lacking to be invaded by BVs from the CAM, but it induced intense inflammatory response necrosis and fibroblastic reaction around the implant. Optimaix2D has good adherence. CAM with minimal or no inflammatory reaction, a good integration of the CAM between the collagen mesh’s fibers, consistent adhesion of the cells to the collagen fibers,and a good ability to form pseudo-vascular channels filled with cells. Optimaix3D induced the highest angiogenic effects on CAM. The material shows good integration on CAM. The collagen fibers of the material show the ability to organize themselves into linear and tubular structures. It is possible to see blood elements, especially at the periphery of the implant. Dual-layer collagen behaves similar to Optimaix 3D, while Xenoderm induced a moderate angiogenic effect on CAM. Based on these data, we may conclude that collagen-based materials have variable ability to requisite and develop new blood vessels. A proper selection of collagen-based biomaterial scaffolds may crucially influence the acquisition and development of blood vessels during angiogenesis assays.

Keywords: chick embryo chorioallantoic membrane, collagen scaffolds, blood vessels, vascular microenvironment

Procedia PDF Downloads 193

Authors: Shashank. S. Bagane, H. N. Rajendra Prasad

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Building Information Modeling (BIM) has currently developed into a potent solution. The consistent development of BIM technology in the sphere of Architecture, Engineering, and Construction (AEC) industry has enhanced the effectiveness of construction and decision making. However, aggrandized global warming and energy crisis has impacted on building energy analysis. It is now becoming an important factor to be considered in the AEC industry. Amalgamating energy analysis in the planning and design phase of a structure has become a necessity. In the current construction industry, estimating energy usage and reducing its footprint is of high priority. The construction industry is giving more prominence to sustainability alongside energy efficiency. This demand is compelling the designers, planners, and engineers to inspect the sustainable performance throughout the building's life cycle. The current study primarily focuses on energy consumption, space arrangement, and spatial geometry of a residential building. Most commonly residential structures in India are constructed considering Vastu Shastra. Vastu designs are intended to integrate architecture with nature and utilizing geometric patterns, symmetry, and directional alignments. In the current study, a residential brick masonry structure is considered for BIM analysis, Architectural model of the structure will be created using Revit software, later the orientation and spatial arrangement will be finalized based on Vastu principles. Furthermore, the structure will be investigated for the impact of building orientation and spatial arrangements on energy using Green Building Studio software. Based on the BIM analysis of the structure, energy consumption of subsequent building orientations will be understood. A well-orientated building having good spatial arrangement can save a considerable amount of energy throughout its life cycle and reduces the need for heating and lighting which will prove to diminish energy usage and improve the energy efficiency of the residential building.

Keywords: building information modeling, energy impact, spatial geometry, vastu

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Authors: Ananchai Ukaew, Choopong Chauypen

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Design concepts of real-time embedded system can be realized initially by introducing novel design approaches. In this literature, model based design approach and in-the-loop testing were employed early in the conceptual and preliminary phase to formulate design requirements and perform quick real-time verification. The design and analysis methodology includes simulation analysis, model based testing, and in-the-loop testing. The design of conceptual drive-by-wire, or DBW, algorithm for electronic control unit, or ECU, was presented to demonstrate the conceptual design process, analysis, and functionality evaluation. The concepts of DBW ECU function can be implemented in the vehicle system to improve electric vehicle, or EV, conversion drivability. However, within a new development process, conceptual ECU functions and parameters are needed to be evaluated. As a result, the testing system was employed to support conceptual DBW ECU functions evaluation. For the current setup, the system components were consisted of actual DBW ECU hardware, electric vehicle models, and control area network or CAN protocol. The vehicle models and CAN bus interface were both implemented as real-time applications where ECU and CAN protocol functionality were verified according to the design requirements. The proposed system could potentially benefit in performing rapid real-time analysis of design parameters for conceptual system or software algorithm development.

Keywords: drive-by-wire ECU, in-the-loop testing, model-based design, real-time embedded system

Procedia PDF Downloads 350

Authors: Erich Gomes Schaitza, Antônio Francisco Savi, Glaucia Aparecida Prates

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The penetration of renewable energy into the electricity supply in Brazil is high, one of the highest in the World. Centralized hydroelectric generation is the main source of energy, followed by biomass and wind. Surprisingly, mini and micro-generation are negligible, with less than 2,000 connections to the national grid. In 2015, a new regulatory framework was put in place to change this situation. In the agricultural sector, the framework was complemented by the offer of low interest rate loans to in-farm renewable generation. Brazil proposed to more than double its area of planted forests as part of its INDC- Intended Nationally Determined Contributions to the UNFCCC-U.N. Framework Convention on Climate Change (UNFCCC). This is an ambitious target which will be achieved only if forests are attractive to farmers. Therefore, this paper analyses whether planting forests for in-farm energy generation with a with a woodchip gasifier is economically viable for microgeneration under the new framework and at if they could be an economic driver for forest plantation. At first, a static case was analyzed with data from Eucalyptus plantations in five farms. Then, a broader analysis developed with the use of Monte Carlo technique. Planting short rotation forests to generate energy could be a viable alternative and the low interest loans contribute to that. There are some barriers to such systems such as the inexistence of a mature market for small scale equipment and of a reference network of good practices and examples.

Keywords: biomass, distribuited generation, small-scale, Monte Carlo

Procedia PDF Downloads 285

Authors: Iman Janghorban Esfahani

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Due to the increased use of irrigation in agriculture, the importance and need for highly reliable water pumping systems have significantly increased. The pumping of the groundwater is essential to provide water for both drip and furrow irrigation to increase the agricultural yield, especially in arid regions that suffer from scarcities of surface water. The most common irrigation pumping systems (IPS) consume conventional energies through the use of electric motors and generators or connecting to the electricity grid. Due to the shortage and transportation difficulties of fossil fuels, and unreliable access to the electricity grid, especially in the rural areas, and the adverse environmental impacts of fossil fuel usage, such as greenhouse gas (GHG) emissions, the need for renewable energy sources such as photovoltaic systems (PVS) as an alternative way of powering irrigation pumping systems is urgent. Integration of the photovoltaic systems with irrigation pumping systems as the Photovoltaic Powered-Irrigation Pumping System (PVP-IPS) can avoid fossil fuel dependency and the subsequent greenhouse gas emissions, as well as ultimately lower energy costs and improve efficiency, which made PVP-IPS systems as an environmentally and economically efficient solution for agriculture irrigation in every region. The greatest problem faced by integration of PVP with IPS systems is matching the intermittence of the energy supply with the dynamic water demand. The best solution to overcome the intermittence is to incorporate a storage system into the PVP-IPS to provide water-on-demand as a highly reliable stand-alone irrigation pumping system. The water storage tank (WST) is the most common storage device for PVP-IPS systems. In the integrated PVP-IPS with a water storage tank (PVP-IPS-WST), a water storage tank stores the water pumped by the IPS in excess of the water demand and then delivers it when demands are high. The Freshwater pinch analysis (FWaPA) as an alternative to mathematical modeling was used by other researchers for retrofitting the off-grid battery less photovoltaic-powered reverse osmosis system. However, the Freshwater pinch analysis has not been used to integrate the photovoltaic systems with irrigation pumping system with water storage tanks. In this study, FWaPA graphical and numerical tools were used for retrofitting an existing PVP-IPS system located in Salahadin, Republic of Iraq. The plant includes a 5 kW submersible water pump and 7.5 kW solar PV system. The Freshwater Composite Curve as the graphical tool and Freashwater Storage Cascade Table as the numerical tool were constructed to determine the minimum required outsourced water during operation, optimal amount of delivered electricity to the water pump, and optimal size of the water storage tank for one-year operation data. The results of implementing the FWaPA on the case study show that the PVP-IPS system with a WST as the reliable system can reduce outsourced water by 95.41% compare to the PVP-IPS system without storage tank.

Keywords: irrigation, photovoltaic, pinch analysis, pumping, solar energy

Procedia PDF Downloads 138

Authors: Mario Isaza-Ruget, Claudia C. Colmenares-Mejia, Nancy Yomayusa, Camilo A. González, Andres Cely, Jossie Murcia

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Quantification of risks associated with complications development from chronic kidney disease (CKD) through accurate survival models can help with patient management. A retrospective cohort that included patients diagnosed with CKD from a primary care program and followed up between 2013 and 2018 was carried out. Time-dependent and static covariates associated with demographic, clinical, and laboratory factors were included. Deep Learning (DL) survival analyzes were developed for three CKD outcomes: CKD stage progression, >25% decrease in Estimated Glomerular Filtration Rate (eGFR), and Renal Replacement Therapy (RRT). Models were evaluated and compared with Random Survival Forest (RSF) based on concordance index (C-index) metric. 2.143 patients were included. Two models were developed for each outcome, Deep Neural Network (DNN) model reported C-index=0.9867 for CKD stage progression; C-index=0.9905 for reduction in eGFR; C-index=0.9867 for RRT. Regarding the RSF model, C-index=0.6650 was reached for CKD stage progression; decreased eGFR C-index=0.6759; RRT C-index=0.8926. DNN models applied in survival analysis context with considerations of longitudinal covariates at the start of follow-up can predict renal stage progression, a significant decrease in eGFR and RRT. The success of these survival models lies in the appropriate definition of survival times and the analysis of covariates, especially those that vary over time.

Keywords: artificial intelligence, chronic kidney disease, deep neural networks, survival analysis

Procedia PDF Downloads 134

Authors: Etienne Mfoumou, Mo Shamma, Martin Tango, Michael Locke

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Water literacy is essential for addressing emerging water management challenges in southwest Nova Scotia (SWNS), where growing concerns over water scarcity and sustainability have highlighted the need for improved educational frameworks. Current approaches often fail to fully represent the complexity of water systems, focusing narrowly on the water cycle while neglecting critical aspects such as groundwater infiltration and the interconnectedness of surface and subsurface water systems. To address these gaps, this paper proposes a comprehensive framework for water literacy that integrates the physical dimensions of water systems with key aspects of understanding, including processes, energy, scale, and human dependency. Moreover, a suggested tool to enhance this framework is a real-time hydrometric data map supported by a network of water level monitoring devices deployed across the province. These devices, particularly for monitoring dug wells, would provide critical data on groundwater levels and trends, offering stakeholders actionable insights into water availability and sustainability. This real-time data would facilitate deeper understanding and engagement with local water issues, complementing the educational framework and empowering stakeholders to make informed decisions. By integrating this tool, the proposed framework offers a practical, interdisciplinary approach to improving water literacy and promoting sustainable water management in SWNS.

Keywords: water education, water literacy, water management, water systems, Southwest Nova Scotia

Procedia PDF Downloads 32