Search results for: single and tandem organic solar cells

Authors: Imdat Taymaz, Erman Aslan, Kemal Cakir

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The Lattice Boltzmann Method (LBM) is performed to computationally investigate the laminar flow and heat transfer of an incompressible fluid with constant material properties in a 2D channel with a built-in triangular prism. Both momentum and energy transport is modelled by the LBM. A uniform lattice structure with a single time relaxation rule is used. Interpolation methods are applied for obtaining a higher flexibility on the computational grid, where the information is transferred from the lattice structure to the computational grid by Lagrange interpolation. The flow is researched on for different Reynolds number, while Prandtl number is keeping constant as a 0.7. The results show how the presence of a triangular prism effects the flow and heat transfer patterns for the steady-state and unsteady-periodic flow regimes. As an evaluation of the accuracy of the developed LBM code, the results are compared with those obtained by a commercial CFD code. It is observed that the present LBM code produces results that have similar accuracy with the well-established CFD code, as an additionally, LBM needs much smaller CPU time for the prediction of the unsteady phonema.

Keywords: laminar forced convection, lbm, triangular prism

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Authors: A. Abdulkadir, Y. M. Bello, A. A. Okhimamhe, H. Ibrahim, M. B. Matazu, L. S. Barau

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The increasing volume of solid waste generated, collected and disposed daily complicate adequate management of solid waste by the relevant agency like Niger State Environmental Protection Agency (NISEPA). In addition, the impacts of solid waste on the natural environment and human livelihood require identification of cost-effective ways for sustainable municipal waste management in Nigeria. These signal the need for identifying environment-friendly initiative and local solution to address municipal solid waste. A research field was secured at Pago, Minna, Niger State which is located in the guinea savanna belt of Nigeria, within longitude 60 3614311- 4511 and latitude 90 291 37.6111- .6211 N. Poultry droppings, decomposed household waste manure and NPK treatment were used. The experimental field was divided into three replications and four (4) treatments on each replication making a total of twelve (12) plots. The treatments were allotted using Randomized Complete Block Design (RCBD) and Data collected was analyzed using SPSS software and RCBD. The result depicts variation in plant height and number of leaves at 50% flowering; Poultry dropping records the highest height as a number of leaves for waste manure competes fairly well with NPK treatment. Similarly, the varying treatments significantly increase vegetable yield, as the control (Nontreatment) records the least yield for the three vegetable samples. Adoption of this organic manure for cultivation does not only enhance environment quality and attainment of food security but will contribute to local economic development, poverty alleviation, and social inclusion.

Keywords: environmental issues, food security, NISEPA, solid waste

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Authors: Marzieh Karimihaghighi, Carlos Castillo

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This work studies how Machine Learning (ML) may be used to increase the effectiveness of a criminal recidivism risk assessment tool, RisCanvi. The two key dimensions of this analysis are predictive accuracy and algorithmic fairness. ML-based prediction models obtained in this study are more accurate at predicting criminal recidivism than the manually-created formula used in RisCanvi, achieving an AUC of 0.76 and 0.73 in predicting violent and general recidivism respectively. However, the improvements are small, and it is noticed that algorithmic discrimination can easily be introduced between groups such as national vs foreigner, or young vs old. It is described how effectiveness and algorithmic fairness objectives can be balanced, applying a method in which a single error disparity in terms of generalized false positive rate is minimized, while calibration is maintained across groups. Obtained results show that this bias mitigation procedure can substantially reduce generalized false positive rate disparities across multiple groups. Based on these results, it is proposed that ML-based criminal recidivism risk prediction should not be introduced without applying algorithmic bias mitigation procedures.

Keywords: algorithmic fairness, criminal risk assessment, equalized odds, recidivism

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Authors: Sizhu Wang, Cuisong Tang, Lin Zhang, Guangyu Tang

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Objective: We aimed to detect the composition of bone marrow fatty acids early after ovariectomized (OVX) surgery and explore the potential mechanism. Methods: Thirty-two female Sprague-Dawley (SD) rats (12 weeks) were randomly divided into OVX group and Sham group (N=16/group), and received ovariectomy or sham surgery respectively. After 3 and 28 days, eight rats in each group were sacrificed to detect the composition of bone marrow fatty acids by gas chromatography–mass spectrometry (GC–MS) and evaluate the trabecular bone microarchitecture by micro-CT. Significant different fatty acids in the early stage of post-menopausal osteoporosis were selected by OPLS-DA and t test. Then selected fatty acids were further studied in the process of osteogenic differentiation through RT-PCR and Alizarin Red S staining. Results: An apparent sample clustering and group separation were observed between OVX group and sham group three days after surgery, which suggested the role of bone marrow fatty acids in the early stage of postmenopausal osteoporosis. Specifically, myristate, palmitoleate and arachidonate were found to play an important role in classification between OVX group and sham group. We further investigated the effect of palmitoleate and arachidonate on osteogenic differentiation and found that palmitoleate promoted the osteogenic differentiation of MC3T3-E1 cells while arachidonate inhibited this process. Conclusion: Profound bone marrow fatty acids changes have taken place in the early stage of post-menopausal osteoporosis. Bone marrow fatty acids may begin to affect osteogenic differentiation shortly after deficiency of estrogen.

Keywords: bone marrow fatty acids, GC-MS, osteoblast, osteoporosis, post-menopausal

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

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Authors: Ali Rabiee, Hessam Ghasemnejad

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Extensive experimental investigation on the effect of stitching pattern on tubular composite structures was conducted. The effect of stitching reinforcement through thickness on using glass flux yarn on energy absorption of fiber-reinforced polymer (FRP) was investigated under high speed loading conditions at axial loading. Keeping the mass of the structure at 125 grams and applying different pattern of stitching at various locations in theory enables better energy absorption, and also enables the control over the behaviour of force-crush distance curve. The study consists of simple non-stitch absorber comparison with single and multi-location stitching behaviour and its effect on energy absorption capabilities. The locations of reinforcements are 10 mm, 20 mm, 30 mm, 10-20 mm, 10-30 mm, 20-30 mm, 10-20-30 mm and 10-15-20-25-30-35 mm from the top of the specimen. The effect of through the thickness reinforcements has shown increase in energy absorption capabilities and crushing load. The significance of this is that as the stitching locations are closer, the crushing load increases and consequently energy absorption capabilities are also increased. The implementation of this idea would improve the mean force by applying stitching and controlling the behaviour of force-crush distance curve.

Keywords: through-thickness stitching, 3D enforcement​, energy absorption, tubular composite structures

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Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

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Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies.

Keywords: runoff, roughness coefficient, PAR, WRM model

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Authors: Artemova Anastasiia, Shen Zexiang, Savilov Serguei

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The marine environment is very aggressive for a number of factors, such as moisture, temperature, winds, ultraviolet radiation, chloride ion concentration, oxygen concentration, pollution, and biofouling, all contributing to marine corrosion. Protective organic coatings provide protection either by a barrier action from the layer, which is limited due to permeability to water and oxygen or from active corrosion inhibition and cathodic protection due to the pigments in the coating. Carbon nanotubes can play not only barrier effect but also passivation effect via adsorbing molecular species of oxygen, hydroxyl, chloride and sulphate anions. Multiwall carbon nanotubes composite provide very important properties such as mechanical strength, non-cytotoxicity, outstanding thermal and electrical conductivity, and very strong absorption of ultraviolet radiation. The samples of stainless steel (316L) coated by epoxy resin with carbon nanotubes-based pigments were exposed to UV irradiation (340nm), and immersion to the sodium chloride solution for 1000h and corrosion behavior in 3.5 wt% sodium chloride (NaCl) solution was investigated. Experimental results showed that corrosion current significantly decreased in the presence of carbon nanotube-based materials, especially nitrogen-doped ones, in the composite coating. Importance of the structure and composition of the pigment materials and its composition was established, and the mechanism of the protection was described. Finally, the effect of nitrogen doping on the corrosion behavior was investigated. The pigment-polymer crosslinking improves the coating performance and the corrosion rate decreases in comparison with pure epoxy coating from 5.7E-05 to 1.4E-05mm/yr for the coating without any degradation; in more than 6 times for the coating after ultraviolet degradation; and more than 16% for the coatings after immersion degradation.

Keywords: corrosion, coating, carbon nanotubes, degradation

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Authors: Ozgu Turgut

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Water scarcity is a problem for many regions which requires immediate action, and solutions cannot be postponed for a long time. It is known that farming consumes a significant portion of usable water. Although in recent years, the efforts to make the transition to dripping or spring watering systems instead of using surface watering started to pay off. It is also known that this transition is not necessarily translated into an increase in the capacity dedicated to other water consumption channels such as city water or power usage. In order to control and allocate the water resource more purposefully, new watering systems have to be used with monitoring abilities that can limit the usage capacity for each farm. In this study, a decision support model which relies on a bi-objective stochastic linear optimization is proposed, which takes crop yield and price volatility into account. The model generates annual planting plans as well as water usage limits for each farmer in the region while taking the total value (i.e., profit) of the overall harvest. The mathematical model is solved using the L-shaped method optimally. The decision support model can be especially useful for regional administrations to plan next year's planting and water incomes and expenses. That is why not only a single optimum but also a set of representative solutions from the Pareto set is generated with the proposed approach.

Keywords: decision support, farming, water, tactical planning, optimization, stochastic, pareto

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Authors: Ebrahim Safarian, Kadir Bilen, Akif Ceviz

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The turbocharger and turbocharging have been the inherent component of diesel engines, so that critical parameters of such engines, as BSFC(Brake Specific Fuel Consumption) or thermal efficiency, fuel consumption, BMEP(Brake Mean Effective Pressure), the power density output and emission level have been improved extensively. In general, the turbocharger can be considered as the most complex component of diesel engines, because it has closely interrelated turbomachinery concepts of the turbines and the compressors to thermodynamic fundamentals of internal combustion engines and stress analysis of all components. In this paper, a waste gate for a conventional single stage radial turbine is investigated by consideration of turbochargers operation constrains and engine operation conditions, without any detail designs in the turbine and the compressor. Amount of opening waste gate which extended between the ranges of full opened and closed valve, is demonstrated by limiting compressor boost pressure ratio. Obtaining of an optimum point by regard above mentioned items is surveyed by three linked meanline modeling programs together which consist of Turbomatch®, Compal®, Rital®madules in concepts NREC® respectively.

Keywords: turbocharger, wastegate, diesel engine, concept NREC programs

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Authors: B. Hekner, J. Myalski, P. Wrzesniowski

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This study presents aluminum matrix composites reinforced by glassy carbon (GC) and titanium (Ti). In the first step, the heterophase (GC+Ti), spatial form (similar to skeleton) of reinforcement was obtained via own method. The polyurethane foam (with spatial, open-cells structure) covered by suspension of Ti particles in phenolic resin was pyrolyzed. In the second step, the prepared heterogeneous foams were infiltrated by aluminium alloy. The manufactured composites are designated to industrial application, especially as a material used in tribological field. From this point of view, the glassy carbon was applied to stabilise a coefficient of friction on the required value 0.6 and reduce wear. Furthermore, the wear can be limited due to titanium phase application, which reveals high mechanical properties. Moreover, fabrication of thin titanium layer on the carbon skeleton leads to reduce contact between aluminium alloy and carbon and thus aluminium carbide phase creation. However, the main modification involves the manufacturing of reinforcement in the form of 3D, skeleton foam. This kind on reinforcement reveals a few important advantages compared to classical form of reinforcement-particles: possibility to control homogeneity of reinforcement phase in composite material; low-advanced technique of composite manufacturing- infiltration; possibility to application the reinforcement only in required places of material; strict control of phase composition; High quality of bonding between components of material. This research is founded by NCN in the UMO-2016/23/N/ST8/00994.

Keywords: metal matrix composites, MMC, glassy carbon, heterophase composites, tribological application

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Authors: Tabugbo B. Ifeyinwa, Josephat O. Ogbuagu, Okeke A. Princewill, Victor C. Eze

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The increasing amount of plastic pollution in maritime settings poses a substantial risk to the functioning of ecosystems and the preservation of biodiversity. This comprehensive analysis combines the most recent data on the environmental effects of pollution from macroplastics, microplastics, and nanoplastics within marine ecosystems. Our goal is to provide a comprehensive understanding of the cumulative impacts that plastic waste accumulates on marine life by outlining the origins, processes, and ecological repercussions connected with each size category of plastic debris. Microplastics and nanoplastics have more sneaky effects that are controlled by chemicals. These effects can get through biological barriers and affect the health of cells and the whole body. Compared to macroplastics, which primarily contribute to physical harm through entanglement and ingestion by marine fauna, microplastics, and nanoplastics are associated with non-physical effects. The review underlines a vital need for research that crosses disciplinary boundaries to untangle the intricate interactions that the various sizes of plastic pollution have with marine animals, evaluate the long-term ecological repercussions, and identify effective measures for mitigating the effects of plastic pollution. Additionally, we urge governmental interventions and worldwide cooperation to solve this pervasive environmental concern. Specifically, we identify significant knowledge gaps in the detection and effect assessment of nanoplastics. To protect marine biodiversity and preserve ecosystem services, this review highlights how urgent it is to address the broad spectrum of plastic pollution.

Keywords: macroplastic pollution, marine ecosystem, microplastic pollution, nanoplastic pollution

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Authors: Aude Pérard Lecomte, Georges Fokoua, Amine Mehel, Anne Tanière

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Air quality in urban areas is deteriorated by pollution, mainly due to the constant increase of the traffic of different types of ground vehicles. In particular, particulate matter pollution with important concentrations in urban areas can cause serious health issues. Characterizing and understanding particle dynamics is therefore essential to establish recommendations to improve air quality in urban areas. To analyze the effects of turbulence on particulate pollutants dispersion, the first step is to focus on the single-phase flow structure and turbulence characteristics in the wake of a heavy truck model. To achieve this, Computational Fluid Dynamics (CFD) simulations were conducted with the aim of modeling the wake airflow of a full- and reduced-scale heavy truck. The Reynolds Average Navier-Stokes (RANS) approach with the Reynolds Stress Model (RSM)as the turbulence model closure was used. The simulations highlight the apparition of a large vortex coming from the under trailer. This vortex belongs to the recirculation region, located in the near-wake of the heavy truck. These vortical structures are expected to have a strong influence on particle dynamics that are emitted by the truck.

Keywords: CDF, heavy truck, recirculation region, reduced scale

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Authors: William Michael Short

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Semantic Web’ technologies such as the Unified Medical Language System Metathesaurus, SNOMED-CT, and MeSH have been touted as transformational for the way users access online medical and health information, enabling both the automated analysis of natural-language data and the integration of heterogeneous healthrelated resources distributed across the Internet through the use of standardized terminologies that capture concepts and relationships between concepts that are expressed differently across datasets. However, the approaches that have so far characterized ‘semantic bioinformatics’ have not yet fulfilled the promise of the Semantic Web for medical and health information retrieval applications. This paper argues within the perspective of cognitive linguistics and cognitive anthropology that four features of human meaning-making must be taken into account before the potential of semantic technologies can be realized for this domain. First, many semantic technologies operate exclusively at the level of the word. However, texts convey meanings in ways beyond lexical semantics. For example, transitivity patterns (distributions of active or passive voice) and modality patterns (configurations of modal constituents like may, might, could, would, should) convey experiential and epistemic meanings that are not captured by single words. Language users also naturally associate stretches of text with discrete meanings, so that whole sentences can be ascribed senses similar to the senses of words (so-called ‘discourse topics’). Second, natural language processing systems tend to operate according to the principle of ‘one token, one tag’. For instance, occurrences of the word sound must be disambiguated for part of speech: in context, is sound a noun or a verb or an adjective? In syntactic analysis, deterministic annotation methods may be acceptable. But because natural language utterances are typically characterized by polyvalency and ambiguities of all kinds (including intentional ambiguities), such methods leave the meanings of texts highly impoverished. Third, ontologies tend to be disconnected from everyday language use and so struggle in cases where single concepts are captured through complex lexicalizations that involve profile shifts or other embodied representations. More problematically, concept graphs tend to capture ‘expert’ technical models rather than ‘folk’ models of knowledge and so may not match users’ common-sense intuitions about the organization of concepts in prototypical structures rather than Aristotelian categories. Fourth, and finally, most ontologies do not recognize the pervasively figurative character of human language. However, since the time of Galen the widespread use of metaphor in the linguistic usage of both medical professionals and lay persons has been recognized. In particular, metaphor is a well-documented linguistic tool for communicating experiences of pain. Because semantic medical knowledge-bases are designed to help capture variations within technical vocabularies – rather than the kinds of conventionalized figurative semantics that practitioners as well as patients actually utilize in clinical description and diagnosis – they fail to capture this dimension of linguistic usage. The failure of semantic technologies in these respects degrades the efficiency and efficacy not only of medical research, where information retrieval inefficiencies can lead to direct financial costs to organizations, but also of care provision, especially in contexts of patients’ self-management of complex medical conditions.

Keywords: ambiguity, bioinformatics, language, meaning, metaphor, ontology, semantic web, semantics

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Authors: Anshul Ashu

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Computers are applied to the vehicle aerodynamics in two ways. One of two is Computational Fluid Dynamics (CFD) and other is Computer Aided Flow Visualization (CAFV). Out of two CFD is chosen because it shows the result with computer graphics. The simulation of flow field around the vehicle is one of the important CFD applications. The flow field can be solved numerically using panel methods, k-ε method, and direct simulation methods. The spoiler is the tool in vehicle aerodynamics used to minimize unfavorable aerodynamic effects around the vehicle and the parallel spoiler is set of two spoilers which are designed in such a manner that it could effectively reduce the drag. In this study, the standard k-ε model of the simplified version of Bugatti Veyron, Audi R8 and Porsche 911 are used to simulate the external flow field. Flow simulation is done for variable Reynolds number. The flow simulation consists of three different levels, first over the model without a rear spoiler, second for over model with single rear spoiler, and third over the model with parallel rear-spoiler. The second and third level has following parameter: the shape of the spoiler, the angle of attack and attachment position. A thorough analysis of simulations results has been found. And a new parallel spoiler is designed. It shows a little improvement in vehicle aerodynamics with a decrease in vehicle aerodynamic drag and lift. Hence, it leads to good fuel economy and traction force of the model.

Keywords: drag, lift, flow simulation, spoiler

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Authors: Khaled Darwish, Islam El Madahh, Hoda Mohamed, Hadia El Hennawy

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Cloud computing has been one of the fastest growing parts in IT industry mainly in the context of the future of the web where computing, communication, and storage services are main services provided for Internet users. Mobile Cloud Computing (MCC) is gaining stream which can be used to extend cloud computing functions, services and results to the world of future mobile applications and enables delivery of a large variety of cloud application to billions of smartphones and wearable devices. This paper describes reliability for MCC by determining the ability of a system or component to function correctly under stated conditions for a specified period of time to be able to deal with the estimation and management of high levels of lifetime engineering uncertainty and risks of failure. The assessment procedures consists of determine Mean Time between Failures (MTBF), Mean Time to Failure (MTTF), and availability percentages for main components in both cloud computing and MCC structures applied on single node OpenStack installation to analyze its performance with different settings governing the behavior of participants. Additionally, we presented several factors have a significant impact on rates of change overall cloud system reliability should be taken into account in order to deliver highly available cloud computing services for mobile consumers.

Keywords: cloud computing, mobile cloud computing, reliability, availability, OpenStack

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Authors: Ruyang Ren, Yaohua Zhao, Yanhua Diao

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The intermittent and unstable characteristics of renewable energy such as solar energy can be effectively solved through battery energy storage system. Lithium-ion battery is widely used in battery energy storage system because of its advantages of high energy density, small internal resistance, low self-discharge rate, no memory effect and long service life. However, the performance and service life of lithium-ion battery is seriously affected by its operating temperature. Thus, the safety operation of the lithium-ion battery module is inseparable from an effective thermal management system (TMS). In this study, a new type of TMS based on micro heat pipe array (MHPA) for lithium-ion battery is established, and the TMS is applied to a battery energy storage box that needs to operate at a high temperature environment of 40 °C all year round. MHPA is a flat shape metal body with high thermal conductivity and excellent temperature uniformity. The battery energy storage box is composed of four battery modules, with a nominal voltage of 51.2 V, a nominal capacity of 400 Ah. Through the excellent heat transfer characteristics of the MHPA, the heat generated by the charge and discharge process can be quickly transferred out of the battery module. In addition, if only the MHPA cannot meet the heat dissipation requirements of the battery module, the TMS can automatically control the opening of the external fan outside the battery module according to the temperature of the battery, so as to further enhance the heat dissipation of the battery module. The thermal management performance of lithium-ion battery TMS based on MHPA is studied experimentally under different ambient temperatures and the condition to turn on the fan or not. Results show that when the ambient temperature is 40 °C and the fan is not turned on in the whole charge and discharge process, the maximum temperature of the battery in the energy storage box is 53.1 °C and the maximum temperature difference in the battery module is 2.4 °C. After the fan is turned on in the whole charge and discharge process, the maximum temperature is reduced to 50.1 °C, and the maximum temperature difference is reduced to 1.7 °C. Obviously, the lithium-ion battery TMS based on MHPA not only could control the maximum temperature of the battery below 55 °C, but also ensure the excellent temperature uniformity of the battery module. In conclusion, the lithium-ion battery TMS based on MHPA can ensure the safe and stable operation of the battery energy storage box in high temperature environment.

Keywords: heat dissipation, lithium-ion battery thermal management, micro heat pipe array, temperature uniformity

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Authors: Rajandeep Kaur, Rajeev Gupta

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Background: Chronic myeloid leukemia (CML) is the most common leukaemia in India. The annual incidence of chronic myeloid leukemia in India was originally reported to be 0.8 to 2.2 per 1,00,000 population. CML is a clonal disorder that is usually easily diagnosed because the leukemic cells of more than 95% of patients have a distinctive cytogenetic abnormality, the Philadelphia chromosome (Ph1). The approval of tyrosine kinase inhibitors (TKIs), which target BCR-ABL1 kinase activity, has significantly reduced the mortality rate associated with chronic myeloid leukemia (CML) and revolutionized treatment. Material and Methods: 80 diagnosed cases of CML were taken. Investigations were done. Bone marrow and molecular studies were also done and with EUTOS, patients were stratified into low and high-risk groups and then treatment with Imatinib was given to all patients and the molecular response was evaluated at 6 months and 12 months follow up with BCR-ABL by RT-PCR quantitative assay. Results: In the study population, out of 80 patients in the study population, 40 were females and 40 were males, with M: F is 1:1. Out of total 80 patients’ maximum patients (54) were in 31-60 years age group. Our study showed a most common symptom of presentation is abdominal discomfort followed by fever. Out of the total 80 patients, 25 (31.3%) patients had high EUTOS scores and 55 (68.8%) patients had low EUTOS scores. On 6 months follow up 36.3% of patients had Complete Molecular Response, 16.3% of patients had Major Molecular Response and 47.5% of patients had No Molecular Response but on 12 months follow up 71.3% of patients had Complete Molecular Response, 16.25% of patients had Major Molecular Response and 12.5% patients had No Molecular Response. Conclusion: In this study, we found a significant correlation between EUTOS score and Molecular response at 6 months and 12 months follow up after Imatinib therapy.

Keywords: chronic myeloid leukemia, European treatment and outcome study score, hematological response, molecular response, tyrosine kinase inhibitor

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Authors: Alok Tiwari, Ming Show Wong

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Lanthanum (La) doped Barium Tin Oxide (BaSnO₃) film is an excellent alternative for expensive Transparent Conducting Oxides (TCOs) film such as Indium Tin Oxide (ITO). However single crystal film of La-doped BaSnO₃ has been reported with a good amount of conductivity and transparency but in order to improve its reachability, it is important to grow doped BaSO₃ films on an inexpensive substrate. La-doped BaSnO₃ thin films have been grown on quartz substrate by Radio Frequency (RF) sputtering at a different substrate temperature (from 200⁰C to 750⁰C). The thickness of the film measured was varying from 360nm to 380nm with varying substrate temperature. Structure, optical and electrical properties have been studied. The carrier concentration is seen to be decreasing as we enhance the substrate temperature while mobility found to be increased up to 9.3 cm²/V-S. At low substrate temperature resistivity found was lower (< 3x10⁻³ ohm-cm) while sudden enhancement was seen as substrate temperature raises and the trend continues further with increasing substrate temperature. Optical transmittance is getting better with higher substrate temperature from 70% at 200⁰C to > 80% at 750⁰C. Overall, understanding of changes in microstructure, electrical and optical properties of a thin film by varying substrate temperature has been reported successfully.

Keywords: conductivity, perovskite, mobility, TCO film

Procedia PDF Downloads 158

Authors: Hesham Hamdy Abdelmohsen, Ahmed Shawky Abdul Azizb, Mona Fawzy Aldaghma

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Helical piles have earned considerable attention as an effective deep foundation alternative due to their rapid installation process and their dual purpose in compression and tension. These piles find common uses as foundations for structures like solar panels, wind turbines, offshore platforms, and some kinds of retaining walls. These structures usually transfer different combinations of loads to their helical-pile foundations in the form of axial and lateral loads. Extensive research has been conducted to investigate and understand the behavior of these piles under the influence of either axial or lateral loads. However, the impacts of loading patterns that may act on the helical piles as combinations of axial compression and lateral loads still need more efforts of research work. This paper presents the results of an experimental (Lab tests) and numerical (PLAXIS-3D) study performed on vertical helical-pile groups under the action of combined loads as axial compression (bearing loads), acting successively with lateral (horizontal) loads. The study aims to clarify the effects of key factors, like helix location and direction of lateral load, on the lateral capacity of helical-pile groups and, consequently, on group efficiency. Besides the variation of helix location and lateral load direction, three patterns of successive bearing combined loads were considered, in which the axial vertical compression load was either zero, V1 or V2, whereas the lateral horizontal loads were varied under each vertical compression load. The study concluded that the lateral capacity of the helical-pile group is significantly affected by helix location within the length of the pile shaft. The optimal lateral performance is achieved with helices at a depth ratio of H/L = 0.4. Furthermore, groups of rectangular plan distribution exhibit greater lateral capacity if subjected to lateral horizontal load in the direction of its long axis. Additionally, the research emphasizes that the presence of vertical compression loading can enhance the lateral capacity of the group. This enhancement depends on the value of the vertical compression load, lateral load direction, and helix location, which highlights the complex interaction effect of these factors on the efficiency of helical-pile groups.

Keywords: helical piles, experimental, numerical, lateral loading, group efficiency

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Authors: K. D. R. Jagath-Kumara, D. D. Dias

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The sea waves carry thousands of GWs of power globally. Although there are a number of different approaches to harness offshore energy, they are likely to be expensive, practically challenging and vulnerable to storms. Therefore, this paper considers using the near shore waves for generating mechanical and electrical power. It introduces two new approaches, the wave manipulation and using a variable duct turbine, for intercepting very wide wave fronts and coping with the fluctuations of the wave height and the sea level, respectively. The first approach effectively allows capturing much more energy yet with a much narrower turbine rotor. The second approach allows using a rotor with a smaller radius but captures energy of higher wave fronts at higher sea levels yet preventing it from totally submerging. To illustrate the effectiveness of the approach, the paper contains a description and the simulation results of a scale model of a wave manipulator. Then, it includes the results of testing a physical model of the manipulator and a single duct, axial flow turbine, in a wave flume in the laboratory. The paper also includes comparisons of theoretical predictions, simulation results and wave flume tests with respect to the incident energy, loss in wave manipulation, minimal loss, brake torque and the angular velocity.

Keywords: near-shore sea waves, renewable energy, wave energy conversion, wave manipulation

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Authors: George Eduful, Yuanyuan Fan, Ahmed Abu-Siada

Abstract:

Ferroresonance poses a substantial threat to the quality and reliability of power distribution systems due to its inherent characteristics of sustained overvoltages and currents. This paper aims to enhance the understanding and reduce the ferroresonance threat by investigating the susceptibility of different transformer configurations using MATLAB/Simulink simulations. To achieve this, four 200 kVA transformers with different vector groups (D-Yn, Yg-Yg, Yn-Yn, and Y-D11) and core types (3-limb, 5-limb, single-phase) were systematically exposed to controlled ferroresonance conditions. The impact of varying the length of the 11 kV cable connected to the transformers was also examined. Through comprehensive voltage, current, and total harmonic distortion analyses, the performance of each configuration was evaluated and compared. The results of the study indicate that transformers with Y-D11 and Yg-Yg configurations exhibited lower susceptibility to ferroresonance, in comparison to those with D-Y11 and Yg-Yg configurations. This implies that the Y-D11 and Yg-Yg transformers are better suited for applications with high risks of ferroresonance. The insights provided by this study are of significant value for the strategic selection and deployment of transformers in power systems, particularly in settings prone to ferroresonance. By identifying and recommending transformer configurations that demonstrate better resilience, this paper contributes to enhancing the overall robustness and reliability of power grid infrastructure.

Keywords: about cable-connected, core type, ferroresonance, over voltages, power transformer, vector group

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Authors: M. Mischopoulou, P. Naidis, S. Kalamaras, T. Kotsopoulos, P. Samaras

Abstract:

The treatment of high strength wastewater by an Upflow Anaerobic Sludge Blanket (UASB) reactor has several benefits, such as high organic removal efficiency, short hydraulic retention time along with low operating costs. In addition, high volumes of biogas are released in these reactors, which can be utilized in several industrial facilities for energy production. This study aims at the examination of the application potential of anaerobic treatment of wastewater, with high molasses content derived from yeast manufacturing, by a lab-scale UASB reactor. The molasses wastewater and the sludge used in the experiments were collected from the wastewater treatment plant of a baker’s yeast manufacturing company. The experimental set-up consisted of a 15 L thermostated UASB reactor at 37 ◦C. Before the reactor start-up, the reactor was filled with sludge and molasses wastewater at a ratio 1:1 v/v. Influent was fed to the reactor at a flowrate of 12 L/d, corresponding to a hydraulic residence time of about 30 h. Effluents were collected from the system outlet and were analyzed for the determination of the following parameters: COD, pH, total solids, volatile solids, ammonium, phosphates and total nitrogen according to the standard methods of analysis. In addition, volatile fatty acid (VFA) composition of the effluent was determined by a gas chromatograph equipped with a flame ionization detector (FID), as an indicator to evaluate the process efficiency. The volume of biogas generated in the reactor was daily measured by the water displacement method, while gas composition was analyzed by a gas chromatograph equipped with a thermal conductivity detector (TCD). The effluent quality was greatly enhanced due to the use of the UASB reactor and high rate of biogas production was observed. The anaerobic treatment of the molasses wastewater by the UASB reactor improved the biodegradation potential of the influent, resulting at high methane yields and an effluent with better quality than the raw wastewater.

Keywords: anaerobic digestion, biogas production, molasses wastewater, UASB reactor

Procedia PDF Downloads 267

Authors: Gopikrishnan Seshadhri, V. M. Topkar

Abstract:

Facility management post occupation is a facet that has gained tremendous ground in the recent times. While the efficiency of expenditure and utilization of all types of resources are monitored to ensure timely completion with minimum cost and acceptable quality during construction phase, value for money comes out only when the facility performs satisfactorily post occupation, meeting aspirations and expectations of users of the facility. It is more so for the public facilities. Due to the paradigm shift in focus to outcome based performance evaluation, user satisfaction obtained mainly through questionnaires has become the single important criterion in performance evaluation. Questionnaires presently being used to gauge user satisfaction being subjective, the feedback obtained do not necessarily reflect actual performance. Hence, there is a requirement of developing a survey instrument that can gauge user satisfaction as objectively as possible and truly reflects the ground reality. A near correct picture of actual performance of the built facility from the user point of view will enable facility managers to address pertinent issues. This paper brings out the need for an effective survey instrument that will elicit more objective user response. It also lists steps involved in formulation of such an instrument.

Keywords: facility performance evaluation, attributes, attribute descriptors, user satisfaction surveys, statistical methods, performance indicators

Procedia PDF Downloads 283

Authors: N.Quaranta, M. Caligaris, R. Varoli, A. Cristobal, M. Unsen, H. López

Abstract:

Corncobs are agricultural wastes and they can be used as fuel or as raw material in different industrial processes like cement manufacture, contaminant adsorption, chemical compound synthesis, etc. The aim of this work is to characterize this waste and analyze the feasibility of its use as a pore-forming material in the manufacture of lightweight ceramics for the civil construction industry. The characterization of raw materials is carried out by using various techniques: electron diffraction analysis X-ray, differential and gravimetric thermal analyses, FTIR spectroscopy, ecotoxicity evaluation, among others. The ground corncobs, particle size less than 2 mm, are mixed with clay up to 30% in volume and shaped by uniaxial pressure of 25 MPa, with 6% humidity, in moulds of 70mm x 40mm x 18mm. Then the green bodies are heat treated at 950°C for two hours following the treatment curves used in ceramic industry. The ceramic probes are characterized by several techniques: density, porosity and water absorption, permanent volumetric variation, loss on ignition, microscopies analysis, and mechanical properties. DTA-TGA analysis of corncobs shows in the range 20°-250°C a small loss in TGA curve and exothermic peaks at 250°-500°C. FTIR spectrum of the corncobs sample shows the characteristic pattern of this kind of organic matter with stretching vibration bands of adsorbed water, methyl groups, C–O and C–C bonds, and the complex form of the cellulose and hemicellulose glycosidic bonds. The obtained ceramic bodies present external good characteristics without loose edges and adequate properties for the market requirements. The porosity values of the sintered pieces are higher than those of the reference sample without waste addition. The results generally indicate that it is possible to use corncobs as porosity former in ceramic bodies without modifying the usual sintering temperatures employed in the industry.

Keywords: ceramic industry, biomass, recycling, hemicellulose glycosidic bonds

Procedia PDF Downloads 402

Authors: Ludovic Favre, Thibaut M. Schafer, Jean-Luc Robyr, Elena-Lavinia Niederhäuser

Abstract:

This paper presents an optimization method based on genetic algorithm for the energy management inside buildings developed in the frame of the project Smart Living Lab (SLL) in Fribourg (Switzerland). This algorithm optimizes the interaction between renewable energy production, storage systems and energy consumers. In comparison with standard algorithms, the innovative aspect of this project is the extension of the smart regulation over three simultaneous criteria: the energy self-consumption, the decrease of greenhouse gas emissions and operating costs. The genetic algorithm approach was chosen due to the large quantity of optimization variables and the non-linearity of the optimization function. The optimization process includes also real time data of the building as well as weather forecast and users habits. This information is used by a physical model of the building energy resources to predict the future energy production and needs, to select the best energetic strategy, to combine production or storage of energy in order to guarantee the demand of electrical and thermal energy. The principle of operation of the algorithm as well as typical output example of the algorithm is presented.

Keywords: building's energy, control system, energy management, energy storage, genetic optimization algorithm, greenhouse gases, modelling, renewable energy

Procedia PDF Downloads 250

Authors: Muhammad Akram, Abdurrahman Ilgan, Oyku Ozu-Cengiz

Abstract:

The quality of Work life is the general state of wellbeing of employees in the workplace. The quality of work life focuses on changing climate at work so that employees can lead improved work life. This study was designed to compare the quality of work life between Turkish and Pakistani public school teachers based on their location, gender, and marital status. A 30 items scale named The Quality of School Work Life (QSWL) was used for this study. 995 teachers from 8 Turkish provinces and 716 from four Pakistani districts were conveniently selected. The overall reliability coefficient of the scale was measured as .81. Exploratory and confirmatory factor analysis yielded five subscales of the construct. The Study revealed that Turkish and Pakistani teachers significantly differed, separately, on all the five subscales of Quality of School Work Life. However, no significant differences were found between Turkish and Pakistani teachers perspectives on the composite score of the QSWL. Further, Male, married, and Single teachers did not significantly differ on their perceptions of QSWL in both countries. However, Pakistani female teachers significantly perceived better QSWL than female teachers in Turkey. The study provided initial validity and reliability evidence of the QSWL.

Keywords: developmental opportunities, fair wages, quality of work life, Pakistan

Procedia PDF Downloads 291

Authors: Hadeer Ibrahiem, Mahmoud Nasr, Masarrat M. M. Migahid, Mohamed A. Ghazy

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The release of textile wastewater loaded with 1,4 dioxane into aquatic ecosystems has been associated with various human health risks and adverse environmental impacts. In parallel, phytoremediation has been recently employed to treat highly polluted wastewater because various plant species tend to produce certain enzymes as a defense mechanism against a toxic environment. To our best knowledge, this study is the first to investigate the ability of phytoremediation using Eichhornia crassipes for the removal of various pollutants, including 1,4 dioxane, from textile wastewater. A phytoremediation system composed of Eichhornia crassipes was acclimatized for 10 d, and then operated in four lab-scale hydroponic systems, viz., negative control, positive control, and two different 1,4 dioxane concentration (400 and 500 mg/L). After 11 d of operation, the phytoremediation system achieved removal efficiencies of 67.5±3.4%, 89.4±4.4%, 83.6±3.8% for 1,4 dioxane (at initial concentration 400 mg/L), chemical oxygen demand (COD) (at initial concentration 679 mg/L), and cumulative heavy metals, respectively. The removal of these pollutants was mainly supported by the phyto-sorption and phytodegradation mechanisms. The economic feasibility of this phytoremediation system was validated by estimating the capital and operating costs, requiring 4.6 USD for the treatment of 1 m3 textile wastewater. The study concluded that the phytoremediation process could be used as a practical and economical approach to treat textile wastewater laden with various organic and inorganic pollutants. Due to the observed pollution reduction and human health protection, the study objectives would fulfill the targets of SDG 3 “Good Health and Well-being” and SDG 6 “Clean Water and Sanitation”. Further studies are required to (i) investigate the ability of plant species to withstand higher concentrations of 1,4 dioxane for an extended operation time and (ii) understand the biochemical pathways for the degradation of 1,4 dioxane via the action of plant enzymes and the associated microbial community.

Keywords: 1, 4 dioxane concentrations, hydrophytes, Eichhornia crassipes, phytoremediation effectiveness, SDGs, textile industrial effluent

Procedia PDF Downloads 95

Authors: Rukia Yosuf

Abstract:

Diabetes is a national healthcare crisis related to both macrovascular and microvascular complications. We hypothesized that higher levels of physical activity are associated with lower total and visceral fat mass, lower systolic blood pressure, and increased insulin sensitivity. Participant inclusion criteria: 21-50 years old, BMI ≥ 30 kg/m2, hemoglobin A1C 5.7-6.4, fasting glucose 100-125 mg/dL, and HOMA IR ≥ 2.5. Exclusion criteria: history of diabetes, hypertension, HIV, renal disease, hearing loss, alcoholic intake over four drinks daily, use of organic nitrates or PDE5 inhibitors, and decreased cardiac function. Total physical activity was measured using accelerometers, body composition using DXA, and insulin resistance via fsIVGTT. Clinical and biochemical cardiometabolic risk factors, blood pressure and heart rate were obtained using a calibrated sphygmomanometer. Anthropometric measures, fasting glucose, insulin, lipid profile, C-reactive protein, and BMP were analyzed using standard procedures. Within our study, we found correlations between levels of physical activity in a heterogeneous group of prediabetic adults. Patients with more physical activity had a higher degree of insulin sensitivity, lower blood pressure, total visceral adipose tissue, and overall lower total mass. Total physical activity levels showed small, but significant correlations with systolic blood pressure, visceral fat, lean mass and insulin sensitivity. After normalizing for the race, age, and gender using multiple regression, these associations were no longer significant considering our small sample size. More research into prediabetes will decrease the population of diabetics overall. In the future, we could increase sample size and conduct cross sectional and longitudinal studies in various populations with prediabetes.

Keywords: diabetes, kidney disease, nephrology, prediabetes

Procedia PDF Downloads 184

Authors: Muhammad Shafiq Ahmed, Sabastine Ezugwu

Abstract:

Thermophysical properties of Carbon Tetrachloride (CCl₄), a photothermal fluid used frequently in Photothermal Deflection Spectroscopy (PDS), containing different volume fractions of single walled carbon nanotube (SWCNTs) and their effect on the amplitude of PDS signal are investigated. It is found that the presence of highly thermally conducting SWCNTs in CCl₄ enhances the heat transfer from heated sample to the adjoining photothermal fluid, resulting in an increase in the intensity of amplitude of PDS signal. With the increasing volume fraction of SWCNTs in CCl₄, the amplitude of PDS signal is nearly doubled for volume fraction fopt =3.7X10⁻³ %., after that the signal drops with a further increase in the fraction of SWCNTs. It is shown that the use of highly thermally conducting carbon nanotubes enhances the heat exchange coefficient between the heated sample surface and adjoining fluid, resulting to an enhancement of PDS signal and consequently the improvement in the sensitivity of PDS technique.

Keywords: carbon nanotubes, heat transfer, nanofluid, photothermal deflection spectroscopy, thermophysical properties

Procedia PDF Downloads 152