Search results for: parameter selection

Authors: Liudmila Shabalinskaya, Victor Golovanov, Liudmila Milinis, Sergey Loponos, Alexander Maslov, D. O. Frolov

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The work is devoted to the rapid laboratory diagnosis of the condition of aircraft friction units, based on the application of the nondestructive testing method by analyzing the parameters of wear particles, or tribodiagnostics. The most important task of tribodiagnostics is to develop recommendations for the selection of more advanced designs, materials and lubricants based on data on wear processes for increasing the life and ensuring the safety of the operation of machines and mechanisms. The object of tribodiagnostics in this work are the tooth gears of the central drive and the gearboxes of the gas turbine engine of the civil aviation PS-90A type, in which rolling friction and sliding friction with slip occur. The main criterion for evaluating the technical state of lubricated friction units of a gas turbine engine is the intensity and rate of wear of the friction surfaces of the friction unit parts. When the engine is running, oil samples are taken and the state of the friction surfaces is evaluated according to the parameters of the wear particles contained in the oil sample, which carry important and detailed information about the wear processes in the engine transmission units. The parameters carrying this information include the concentration of wear particles and metals in the oil, the dispersion composition, the shape, the size ratio and the number of particles, the state of their surfaces, the presence in the oil of various mechanical impurities of non-metallic origin. Such a morphological analysis of wear particles has been introduced into the order of monitoring the status and diagnostics of various aircraft engines, including a gas turbine engine, since the type of wear characteristic of the central drive and the drive box is surface fatigue wear and the beginning of its development, accompanied by the formation of microcracks, leads to the formation of spherical, up to 10 μm in size, and in the aftermath of flocculent particles measuring 20-200 μm in size. Tribodiagnostics using the morphological analysis of wear particles includes the following techniques: ferrography, filtering, and computer analysis of the classification and counting of wear particles. Based on the analysis of several series of oil samples taken from the drive box of the engine during their operating time, a study was carried out of the processes of wear kinetics. Based on the results of the study and comparing the series of criteria for tribodiagnostics, wear state ratings and statistics of the results of morphological analysis, norms for the normal operating regime were developed. The study allowed to develop levels of wear state for friction surfaces of gearing and a 10-point rating system for estimating the likelihood of the occurrence of an increased wear mode and, accordingly, prevention of engine failures in flight.

Keywords: aviation, box of drives, morphological analysis, tribodiagnostics, tribology, ferrography, filtering, wear particle

Procedia PDF Downloads 261

Authors: K. H. Reeta, Bhavana Prasher, Mitali Mukerji, Dhwani Dholakia, Sangeeta Khanna, Archana Vats, Shivam Pandey, Sandeep Seth, Subir Kumar Maulik

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Introduction Research has demonstrated a connection between coronary artery disease (CAD) and genetics. We did a deep literature mining using both bioinformatics and manual efforts to identify the susceptible polymorphisms in coronary artery disease. Further, the study sought to validate these findings in an Asian population. Methodology In first phase, we used an automated pipeline which organizes and presents structured information on SNPs, Population and Diseases. The information was obtained by applying Natural Language Processing (NLP) techniques to approximately 28 million PubMed abstracts. To accomplish this, we utilized Python scripts to extract and curate disease-related data, filter out false positives, and categorize them into 24 hierarchical groups using named Entity Recognition (NER) algorithms. From the extensive research conducted, a total of 466 unique PubMed Identifiers (PMIDs) and 694 Single Nucleotide Polymorphisms (SNPs) related to coronary artery disease (CAD) were identified. To refine the selection process, a thorough manual examination of all the studies was carried out. Specifically, SNPs that demonstrated susceptibility to CAD and exhibited a positive Odds Ratio (OR) were selected, and a final pool of 324 SNPs was compiled. The next phase involved validating the identified SNPs in DNA samples of 96 CAD patients and 37 healthy controls from Indian population using Global Screening Array. ResultsThe results exhibited out of 324, only 108 SNPs were expressed, further 4 SNPs showed significant difference of minor allele frequency in cases and controls. These were rs187238 of IL-18 gene, rs731236 of VDR gene, rs11556218 of IL16 gene and rs5882 of CETP gene. Prior researches have reported association of these SNPs with various pathways like endothelial damage, susceptibility of vitamin D receptor (VDR) polymorphisms, and reduction of HDL-cholesterol levels, ultimately leading to the development of CAD. Among these, only rs731236 had been studied in Indian population and that too in diabetes and vitamin D deficiency. For the first time, these SNPs were reported to be associated with CAD in Indian population. Conclusion: This pool of 324 SNP s is a unique kind of resource that can help to uncover risk associations in CAD. Here, we validated in Indian population. Further, validation in different populations may offer valuable insights and contribute to the development of a screening tool and may help in enabling the implementation of primary prevention strategies targeted at the vulnerable population.

Keywords: coronary artery disease, single nucleotide polymorphism, susceptible SNP, bioinformatics

Procedia PDF Downloads 76

Authors: Mohamed M. Zaki, Maha M. Hady

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Salmonella spp. have been categorized as the world’s biggest threats to human health and poultry products are mostly incriminated sources. In Egypt, it was found that S. enteritidis and S. typhimurium are the most prevalent ones in poultry farms. It is recommended to eliminate salmonella from living bird by competing for salmonella contamination in feed in order to establish a healthy gut. The Feed acidifiers are the group of feed additives containing low-molecular-weight organic acids and/ or their salts which act as performance promoters by lowering the pH in the gut, optimizes digestion and inhibit bacterial growth. The inclusion of organic acid in pure form nonetheless effective in feed, yet, it is difficult to handle in feed mills as it is corrosive and produce more losses during pelleting process. The current study aimed at to evaluate the impact of incorporation of sodium diformate (SDF) and a commercial acidifier, CA (a mixture of butyric and propionic acids and their ammonium salts) at 0.4% dietary levels on broilers performance and the control S. enteritidis infection. Two hundreds and seventy unsexed cobb chickens were allotted in one of three treatments (90/ group) which were, the control (no acidifier, C- &C+), the 0.4% SDF (SDF- & SDF +) and the 0.4% CA (CA- & CA +) dietary levels for 35 days. Before the allocation of the groups, ten extra birds and a diet sample were bacteriologically examined to ensure negative contamination with salmonella. The birds were raised on deep-litter separated pens and had free access to feed and water all the time. The experimentally formulated diets were kept at 40C. After 24h access to the different dietary treatments, all the birds in the positive groups (n=15/ replicate) were inoculated intra-crop with 0.2 ml of 24 h broth culture of S. entertidis containing 1X 107 organisms while the negative-treated groups were inoculated with the same amount of the negative broth and second inoculation was done at 22 d of age. Colocal swabs were collected individually from all birds 2 h pre-inoculation to assure the absence of salmonella, then 1, 3, 5, 7, 21 days post-inoculation to recover salmonella. Performance parameter (body weight gain and feed efficiency) were calculated. Mortalities were recorded and reisolation of the salmonella was adopted to ensure it was the inoculated ones. The results revealed that the dietary acidification with sodium diformate significantly improved broilers performance and tends to produce heavier birds as compared to the negative control and CA groups. Moreover, the dietary inclusion of both acidifiers at level of 0.4% was able to eliminate mortalities completely at the relevant inoculation time. Regarding the shedding of S. enteritidius in positive groups, the SDF treatment resulted in significant (p<0.05) cessation of the shedding at 3 days post-inoculation compared to 7 days post-inoculation for the CA-group. In conclusion, sodium diformate at 0.4% dietary level in broiler diets has a valuable effect not only on broilers performance but also by eliminating S. enteritidis the main source of salmonella contamination in poultry farms which is feed.

Keywords: acidifier, broilers, Salmonalla spp, sodium diformate

Procedia PDF Downloads 288

Authors: Nada Verdel, Tomaz Rijavec, Albin Pintar, Ales Lapanje

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Objectives: White water circuits of woodfree paper mills contain suspended, dissolved, and colloidal particles, such as cellulose, starch, paper sizings, and dyes. By closing the white water circuits, these particles start to accumulate and affect the production. Due to high amount of organic matter that scavenge radicals and adsorbs onto catalyst surfaces, treatment of white water with photocatalysis is inappropriate. The most suitable approach should be bioaugmentation-assisted bioremediation. Accordingly, objectives were: - to isolate bacteria capable of degrading organic compounds used for the papermaking process - to select the most active bacteria for bioaugmentation. Status: The state-of-the-art of bioaugmentation of pulp and paper mill effluents is mostly based on biodegradation of lignin. Whereas in white water circuits of woodfree paper mills only papermaking compounds are present. As far as one can tell from the literature, the study on degradation activities of bacteria for all possible compounds of the papermaking process is a novelty. Methodology: The main parameters of the selected white water were systematically analyzed during a period of two months. Bacteria were isolated on selective media with particular carbon source. Organic substances used as carbon source either enter white water circuits as base paper or as recycled broke. The screening of bacterial activities for starch, cellulose, latex, polyvinyl alcohol, alkyl ketene dimers, and resin acids was followed by addition of lugol. Degraders of polycyclic aromatic dyes were selected by cometabolism tests; cometabolism is simultaneous biodegradation of two compounds, in which the degradation of the second compound depends on the presence of the first. The obtained strains were identified by 16S rRNA sequencing. Findings: 335 autochthonous strains were isolated on plates with selected carbon source. The isolated strains were selected according to degradation of the particular carbon source. The ultimate degraders of cationic starch, cellulose, and sizings are Pseudomonas sp. NV-CE12-CF and Aeromonas sp. NV-RES19-BTP. The most active strains capable of degrading azo dyes are Aeromonas sp. NV-RES19-BTP and Sphingomonas sp. NV-B14-CF. Klebsiella sp. NV-Y14A-BTP degrade polycyclic aromatic direct blue 15 and also yellow dye, Agromyces sp. NV-RED15A-BF and Cellulosimicrobium sp. NV-A4-BF are specialists for whitener and Aeromonas sp. NV-RES19-BTP is general degrader of all compounds. To the white water adapted bacteria were isolated and selected according to their degradation activities for particular organic substances. Mostly isolated bacteria are specialized to lower the competition in the microbial community. Degraders of readily-biodegradable compounds do not degrade recalcitrant polycyclic aromatic dyes and vice versa. General degraders are rare.

Keywords: bioaugmentation, biodegradation of azo dyes, cometabolism, smart wastewater treatment technologies

Procedia PDF Downloads 206

Authors: Amin Salighehdar, Ziwen Ye, Mingzhe Liu, Ionut Florescu, Alan F. Blumberg

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Storm surge is an abnormal water level caused by a storm. Accurate prediction of a storm surge is a challenging problem. Researchers developed various ensemble modeling techniques to combine several individual forecasts to produce an overall presumably better forecast. There exist some simple ensemble modeling techniques in literature. For instance, Model Output Statistics (MOS), and running mean-bias removal are widely used techniques in storm surge prediction domain. However, these methods have some drawbacks. For instance, MOS is based on multiple linear regression and it needs a long period of training data. To overcome the shortcomings of these simple methods, researchers propose some advanced methods. For instance, ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast. This application creates a better forecast of sea level using a combination of several instances of the Bayesian Model Averaging (BMA). An ensemble dressing method is based on identifying best member forecast and using it for prediction. Our contribution in this paper can be summarized as follows. First, we investigate whether the ensemble models perform better than any single forecast. Therefore, we need to identify the single best forecast. We present a methodology based on a simple Bayesian selection method to select the best single forecast. Second, we present several new and simple ways to construct ensemble models. We use correlation and standard deviation as weights in combining different forecast models. Third, we use these ensembles and compare with several existing models in literature to forecast storm surge level. We then investigate whether developing a complex ensemble model is indeed needed. To achieve this goal, we use a simple average (one of the simplest and widely used ensemble model) as benchmark. Predicting the peak level of Surge during a storm as well as the precise time at which this peak level takes place is crucial, thus we develop a statistical platform to compare the performance of various ensemble methods. This statistical analysis is based on root mean square error of the ensemble forecast during the testing period and on the magnitude and timing of the forecasted peak surge compared to the actual time and peak. In this work, we analyze four hurricanes: hurricanes Irene and Lee in 2011, hurricane Sandy in 2012, and hurricane Joaquin in 2015. Since hurricane Irene developed at the end of August 2011 and hurricane Lee started just after Irene at the beginning of September 2011, in this study we consider them as a single contiguous hurricane event. The data set used for this study is generated by the New York Harbor Observing and Prediction System (NYHOPS). We find that even the simplest possible way of creating an ensemble produces results superior to any single forecast. We also show that the ensemble models we propose generally have better performance compared to the simple average ensemble technique.

Keywords: Bayesian learning, ensemble model, statistical analysis, storm surge prediction

Procedia PDF Downloads 309

Authors: Yelena Agranovich, Larissa Ageyeva, Aigul Syzdykbayeva, Violetta Tyan

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The modernization of the education system in the Republic of Kazakhstan is aimed at improving the quality of teacher training and enhancing key competencies among teachers. The current professional standard ‘Teacher’ defines the general characteristics of teachers’ activities, key competencies, and criteria according to relevant qualification categories structured on the principle of progression, thereby enabling Continuous Professional Development (CPD). The essence of CPD lies in the constant integration of new knowledge and skills that help teachers adapt to changes in the education system, in technologies, and teaching methods. This developmental process enables teachers to stay updated on recent scientific achievements, innovations, and modern pedagogical practices. Continuous learning helps teachers remain flexible and open to new developments, creating conditions for improving educational quality and fostering students' personal growth. This study aims to address the following objectives: analysis of international CPD practices, identification of conceptual foundations, and investigation of CPD implementation mechanisms in Kazakhstan. The core principles of CPD are identified as longitudinality, systematicity, and fragmentation. CPD implementation is based on various theoretical approaches: axiological, systemic, competency-based, activity-based, and learner-centered. The study analyzes leading models of teacher CPD, with a target sample that includes countries such as Australia, Japan, South Korea, England, Singapore, Sweden, Finland, and Kazakhstan. The research methods include analysis (comparative, historical, content analysis, systematic), case studies of CPD models, and synthesis and systematization of scientific data. As research results, the mechanisms for CPD implementation in Kazakhstan will be identified, along with further perspectives on transforming resources within the teacher professional development system. In comparing CPD models from various countries, it is noted that teacher CPD in the Republic of Kazakhstan: (1) is implemented through educational programs, professional development courses, teacher certification, professional networks, in-school professional development, self-education, and self-assessment; (2) includes the development of pedagogical values and competencies (tolerance, inclusivity, communication, critical thinking, creativity, reflection, etc.); (3) is carried out based on traditional forms (professional development courses, retraining) and informal forms (self-learning, self-development, experience sharing and exchange). Further research will focus on creating a digital ecosystem for teacher CPD, based on an educational platform that facilitates individualized professional development pathways for teachers (competency diagnostics, course selection, and a methodological system of course and post-course support for teachers).

Keywords: continuous professional development, CPD models, professional development, professional upgrading, teacher, teacher training

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Authors: Zhaoyang Liu, Detao Qin, Darren Delai Sun

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The onshore production of oil and gas (for example, shale gas) generates large quantities of wastewater, referred to be ‘produced water’, which contains high contents of oils and salts. The direct discharge of produced water, if not appropriately treated, can be toxic to the environment and human health. Membrane filtration has been deemed as an environmental-friendly and cost-effective technology for treating oily wastewater. However, conventional polymeric membranes have their drawbacks of either low salt rejection rate or high membrane fouling tendency when treating oily wastewater. Recent years, forward osmosis (FO) membrane filtration has emerged as a promising technology with its unique advantages of low operation pressure and less membrane fouling tendency. However, until now there is still no report about FO membranes specially designed and fabricated for treating the oily and salty produced water. In this study, a novel nanocomposite FO membrane was developed specially for treating oil- and salt-polluted produced water. By leveraging the recent advance of nanomaterials and nanotechnology, this nanocomposite FO membrane was designed to be made of double layers: an underwater oleophobic selective layer on top of a nanomaterial infused polymeric support layer. Wherein, graphene oxide (GO) nanosheets were selected to add into the polymeric support layer because adding GO nanosheets can optimize the pore structures of the support layer, thus potentially leading to high water flux for FO membranes. In addition, polyvinyl alcohol (PVA) hydrogel was selected as the selective layer because hydrated and chemically-crosslinked PVA hydrogel is capable of simultaneously rejecting oil and salt. After nanocomposite FO membranes were fabricated, the membrane structures were systematically characterized with the instruments of TEM, FESEM, XRD, ATR-FTIR, surface zeta-potential and Contact angles (CA). The membrane performances for treating produced waters were tested with the instruments of TOC, COD and Ion chromatography. The working mechanism of this new membrane was also analyzed. Very promising experimental results have been obtained. The incorporation of GO nanosheets can reduce internal concentration polarization (ICP) effect in the polymeric support layer. The structural parameter (S value) of the new FO membrane is reduced by 23% from 265 ± 31 μm to 205 ± 23 μm. The membrane tortuosity (τ value) is decreased by 20% from 2.55 ± 0.19 to 2.02 ± 0.13 μm, which contributes to the decrease of S value. Moreover, the highly-hydrophilic and chemically-cross-linked hydrogel selective layer present high antifouling property under saline oil/water emulsions. Compared with commercial FO membrane, this new FO membrane possesses three times higher water flux, higher removal efficiencies for oil (>99.9%) and salts (>99.7% for multivalent ions), and significantly lower membrane fouling tendency (<10%). To our knowledge, this is the first report of a nanocomposite FO membrane with the combined merits of high salt rejection, high oil repellency and high water flux for treating onshore oil/gas produced waters. Due to its outstanding performance and ease of fabrication, this novel nanocomposite FO membrane possesses great application potential in wastewater treatment industry.

Keywords: nanocomposite, membrane, polymer, graphene oxide

Procedia PDF Downloads 250

Authors: Piyush Sharma, Laltu Chandra, P. S. Ghoshdastidar, Rajiv Shekhar

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Metals processing operations such as melting and heat treatment of metals are energy-intensive, requiring temperatures greater than 500oC. The desired temperature in these industrial furnaces is attained by circulating electrically-heated air. In most of these furnaces, electricity produced from captive coal-based thermal power plants is used. Solar thermal energy could be a viable heat source in these furnaces. A retrofitted solar convective furnace (SCF) concept, which uses solar thermal generated hot air, has been proposed. Critical to the success of a SCF is the design of an open volumetric air receiver (OVAR), which can heat air in excess of 800oC. The OVAR is placed on top of a tower and receives concentrated solar radiation from a heliostat field. Absorbers, mixer assembly, and the return air flow chamber (RAFC) are the major components of an OVAR. The absorber is a porous structure that transfers heat from concentrated solar radiation to ambient air, referred to as primary air. The mixer ensures uniform air temperature at the receiver exit. Flow of the relatively cooler return air in the RAFC ensures that the absorbers do not fail by overheating. In an earlier publication, the detailed design basis, fabrication, and characterization of a 2 kWth open volumetric air receiver (OVAR) based laboratory solar air tower simulator was presented. Development of an experimentally-validated, CFD based mathematical model which can ultimately be used for the design and scale-up of an OVAR has been the major objective of this investigation. In contrast to the published literature, where flow and heat transfer have been modeled primarily in a single absorber module, the present study has modeled the entire receiver assembly, including the RAFC. Flow and heat transfer calculations have been carried out in ANSYS using the LTNE model. The complex return air flow pattern in the RAFC requires complicated meshes and is computational and time intensive. Hence a simple, realistic 1-D mathematical model, which circumvents the need for carrying out detailed flow and heat transfer calculations, has also been proposed. Several important results have emerged from this investigation. Circumferential electrical heating of absorbers can mimic frontal heating by concentrated solar radiation reasonably well in testing and characterizing the performance of an OVAR. Circumferential heating, therefore, obviates the need for expensive high solar concentration simulators. Predictions suggest that the ratio of power on aperture (POA) and mass flow rate of air (MFR) is a normalizing parameter for characterizing the thermal performance of an OVAR. Increasing POA/MFR increases the maximum temperature of air, but decreases the thermal efficiency of an OVAR. Predictions of the 1-D mathematical are within 5% of ANSYS predictions and computation time is reduced from ~ 5 hours to a few seconds.

Keywords: absorbers, mixer assembly, open volumetric air receiver, return air flow chamber, solar thermal energy

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Authors: Giada Feletti, Daniela Tedesco, Paolo Trucco

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The present study aims to develop a dashboard of Key Performance Indicators (KPI) to enhance information and predictive capabilities in Emergency Medical Services (EMS) systems, supporting both operational and strategic decisions of different actors. The employed research methodology consists of the first phase of revision of the technical-scientific literature concerning the indicators currently used for the performance measurement of EMS systems. From this literature analysis, it emerged that current studies focus on two distinct perspectives: the ambulance service, a fundamental component of pre-hospital health treatment, and the patient care in the Emergency Department (ED). The perspective proposed by this study is to consider an integrated view of the ambulance service process and the ED process, both essential to ensure high quality of care and patient safety. Thus, the proposal focuses on the entire healthcare service process and, as such, allows considering the interconnection between the two EMS processes, the pre-hospital and hospital ones, connected by the assignment of the patient to a specific ED. In this way, it is possible to optimize the entire patient management. Therefore, attention is paid to the dependency of decisions that in current EMS management models tend to be neglected or underestimated. In particular, the integration of the two processes enables the evaluation of the advantage of an ED selection decision having visibility on EDs’ saturation status and therefore considering the distance, the available resources and the expected waiting times. Starting from a critical review of the KPIs proposed in the extant literature, the design of the dashboard was carried out: the high number of analyzed KPIs was reduced by eliminating the ones firstly not in line with the aim of the study and then the ones supporting a similar functionality. The KPIs finally selected were tested on a realistic dataset, which draws us to exclude additional indicators due to the unavailability of data required for their computation. The final dashboard, which was discussed and validated by experts in the field, includes a variety of KPIs able to support operational and planning decisions, early warning, and citizens’ awareness of EDs accessibility in real-time. By associating each KPI to the EMS phase it refers to, it was also possible to design a well-balanced dashboard covering both efficiency and effective performance of the entire EMS process. Indeed, just the initial phases related to the interconnection between ambulance service and patient’s care are covered by traditional KPIs compared to the subsequent phases taking place in the hospital ED. This could be taken into consideration for the potential future development of the dashboard. Moreover, the research could proceed by building a multi-layer dashboard composed of the first level with a minimal set of KPIs to measure the basic performance of the EMS system at an aggregate level and further levels with KPIs that can bring additional and more detailed information.

Keywords: dashboard, decision support, emergency medical services, key performance indicators

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Authors: Marcel Meinhardt, Manfred Keuser, Thomas Braml

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Cracking of reinforced concrete is a complex phenomenon induced by direct loads or restraints affecting reinforced concrete structures as soon as the tensile strength of the concrete is exceeded. Hence it is important to predict where cracks will be located and how they will propagate. The bond theory and the crack formulas in the actual design codes, for example, DIN EN 1992-1-1, are all based on the assumption that the reinforcement bars are embedded in homogeneous concrete without taking into account the influence of transverse reinforcement and the real stress situation. However, it can often be observed that real structures such as walls, slabs or beams show a crack spacing that is orientated to the transverse reinforcement bars or to the stirrups. In most Finite Element Analysis studies, the smeared crack approach is used for crack prediction. The disadvantage of this model is that the typical strain localization of a crack on element level can’t be seen. The crack propagation in concrete is a discontinuous process characterized by different factors such as the initial random distribution of defects or the scatter of material properties. Such behavior presupposes the elaboration of adequate models and methods of simulation because traditional mechanical approaches deal mainly with average material parameters. This paper concerned with the modelling of the initiation and the propagation of cracks in reinforced concrete structures considering the influence of transverse reinforcement and the real stress distribution in reinforced concrete (R/C) beams/plates in bending action. Therefore, a parameter study was carried out to investigate: (I) the influence of the transversal reinforcement to the stress distribution in concrete in bending mode and (II) the crack initiation in dependence of the diameter and distance of the transversal reinforcement to each other. The numerical investigations on the crack initiation and propagation were carried out with a 2D reinforced concrete structure subjected to quasi static loading and given boundary conditions. To model the uncertainty in the tensile strength of concrete in the Finite Element Analysis correlated normally and lognormally distributed random filed with different correlation lengths were generated. The paper also presents and discuss different methods to generate random fields, e.g. the Covariance Matrix Decomposition Method. For all computations, a plastic constitutive law with softening was used to model the crack initiation and the damage of the concrete in tension. It was found that the distributions of crack spacing and crack widths are highly dependent of the used random field. These distributions are validated to experimental studies on R/C panels which were carried out at the Laboratory for Structural Engineering at the University of the German Armed Forces in Munich. Also, a recommendation for parameters of the random field for realistic modelling the uncertainty of the tensile strength is given. The aim of this research was to show a method in which the localization of strains and cracks as well as the influence of transverse reinforcement on the crack initiation and propagation in Finite Element Analysis can be seen.

Keywords: crack initiation, crack modelling, crack propagation, cracks, numerical simulation, random fields, reinforced concrete, stochastic

Procedia PDF Downloads 158

Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

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To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

Procedia PDF Downloads 143

Authors: Deniz Dincel, Sena Ardicli, Hale Samli, Mustafa Ogan, Faruk Balci

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The aim of the study was to determine the effects of some environmental and genetic factors on growth, fertility traits, milk yield and composition in Saanen goats. For this purpose, the total of 173 Saanen goats and kids were investigated for growth, fertility and milk traits in Marmara Region of Turkey. Fertility parameters (n=70) were evaluated during two years. Milk samples were collected during the lactation and the milk yield/components (n=59) of each goat were calculated. In terms of CSN3 and AGPAT6 gene; the genotypes were defined by PCR-RFLP. Saanen kids (n=86-112) were measured from birth to 6 months of life. The birth, weaning, 60ᵗʰ, 90ᵗʰ, 120ᵗʰ and 180tᵗʰ days of average live weights were calculated. The effects of maternal age on pregnancy rate (p < 0.05), birth rate (p < 0.05), infertility rate (p < 0.05), single born kidding (p < 0.001), twinning rate (p < 0.05), triplet rate (p < 0.05), survival rate of kids until weaning (p < 0.05), number of kids per parturition (p < 0.01) and number of kids per mating (p < 0.01) were found significant. The impacts of year on birth rate (p < 0.05), abortion rate (p < 0.001), single born kidding (p < 0.01), survival rate of kids until weaning (p < 0.01), number of kids per mating (p < 0.01) were found significant for fertility traits. The impacts of lactation length on all milk yield parameters (lactation milk, protein, fat, totally solid, solid not fat, casein and lactose yield) (p < 0.001) were found significant. The effects of age on all milk yield parameters (lactation milk, protein, fat, total solid, solid not fat, casein and lactose yield) (p < 0.001), protein rate (p < 0.05), fat rate (p < 0.05), total solid rate (p < 0.01), solid not fat rate (p < 0.05), casein rate (p < 0.05) and lactation length (p < 0.01), were found significant too. However, the effect of AGPAT6 gene on milk yield and composition was not found significant in Saanen goats. The herd was found monomorphic (FF) for CSN3 gene. The effects of sex on live weights until 90ᵗʰ days of life (birth, weaning and 60ᵗʰ day of average weight) were found significant statistically (p < 0.001). The maternal age affected only birth weight (p < 0,001). The effects month at birth on all of the investigated day [the birth, 120ᵗʰ, 180ᵗʰ days (p < 0.05); the weaning, 60ᵗʰ, 90ᵗʰ days (p < 0,001)] were found significant. The birth type was found significant on the birth (p < 0,001), weaning (p < 0,01), 60ᵗʰ (p < 0,01) and 90ᵗʰ (p < 0,01) days of average live weights. As a result, screening the other regions of CSN3, AGPAT6 gene and also investigation the phenotypic association of them should be useful to clarify the efficiency of target genes. Environmental factors such as maternal age, year, sex and birth type were found significant on some growth, fertility and milk traits in Saanen goats. So consideration of these factors could be used as selection criteria in dairy goat breeding.

Keywords: fertility, growth, milk yield, Saanen goats

Procedia PDF Downloads 166

Authors: Yan Torres, Fernanda Simoes, Francisco Petrucci-Fonseca, Freddie-Jeanne Richard

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The non-invasive samples are an alternative of collecting genetic samples directly. Non-invasive samples are collected without the manipulation of the animal (e.g., scats, feathers and hairs). Nevertheless, the use of non-invasive samples has some limitations. The main issue is degraded DNA, leading to poorer extraction efficiency and genotyping. Those errors delayed for some years a widespread use of non-invasive genetic information. Possibilities to limit genotyping errors can be done using analysis methods that can assimilate the errors and singularities of non-invasive samples. Genotype matching and population estimation algorithms can be highlighted as important analysis tools that have been adapted to deal with those errors. Although, this recent development of analysis methods there is still a lack of empirical performance comparison of them. A comparison of methods with dataset different in size and structure can be useful for future studies since non-invasive samples are a powerful tool for getting information specially for endangered and rare populations. To compare the analysis methods, four different datasets used were obtained from the Dryad digital repository were used. Three different matching algorithms (Cervus, Colony and Error Tolerant Likelihood Matching - ETLM) are used for matching genotypes and two different ones for population estimation (Capwire and BayesN). The three matching algorithms showed different patterns of results. The ETLM produced less number of unique individuals and recaptures. A similarity in the matched genotypes between Colony and Cervus was observed. That is not a surprise since the similarity between those methods on the likelihood pairwise and clustering algorithms. The matching of ETLM showed almost no similarity with the genotypes that were matched with the other methods. The different cluster algorithm system and error model of ETLM seems to lead to a more criterious selection, although the processing time and interface friendly of ETLM were the worst between the compared methods. The population estimators performed differently regarding the datasets. There was a consensus between the different estimators only for the one dataset. The BayesN showed higher and lower estimations when compared with Capwire. The BayesN does not consider the total number of recaptures like Capwire only the recapture events. So, this makes the estimator sensitive to data heterogeneity. Heterogeneity in the sense means different capture rates between individuals. In those examples, the tolerance for homogeneity seems to be crucial for BayesN work properly. Both methods are user-friendly and have reasonable processing time. An amplified analysis with simulated genotype data can clarify the sensibility of the algorithms. The present comparison of the matching methods indicates that Colony seems to be more appropriated for general use considering a time/interface/robustness balance. The heterogeneity of the recaptures affected strongly the BayesN estimations, leading to over and underestimations population numbers. Capwire is then advisable to general use since it performs better in a wide range of situations.

Keywords: algorithms, genetics, matching, population

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Authors: Leo Nnamdi Ozurumba-Dwight

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Single-cell genomic analytical systems have proved to be a platform to isolate bulk cells into selected single cells for genomic, proteomic, and related metabolomic studies. This is enabling systematic investigations of the level of heterogeneity in a diverse and wide pool of cell populations. Single cell technologies, embracing techniques such as high parameter flow cytometry, single-cell sequencing, and high-resolution images are playing vital roles in these investigations on messenger ribonucleic acid (mRNA) molecules and related gene expressions in tracking the nature and course of disease conditions. This entails targeted molecular investigations on unit cells that help us understand cell behavoiur and expressions, which can be examined for their health implications on the health state of patients. One of the vital good sides of single-cell RNA sequencing (scRNA seq) is its probing capacity to detect deranged or abnormal cell populations present within homogenously perceived pooled cells, which would have evaded cursory screening on the pooled cell populations of biological samples obtained as part of diagnostic procedures. Despite conduction of just single-cell transcriptome analysis, scRNAseq now permits comparison of the transcriptome of the individual cells, which can be evaluated for gene expressional patterns that depict areas of heterogeneity with pharmaceutical drug discovery and clinical treatment applications. It is vital to strictly work through the tools of investigations from wet lab to bioinformatics and computational tooled analyses. In the precise steps for scRNAseq, it is critical to do thorough and effective isolation of viable single cells from the tissues of interest using dependable techniques (such as FACS) before proceeding to lysis, as this enhances the appropriate picking of quality mRNA molecules for subsequent sequencing (such as by the use of Polymerase Chain Reaction machine). Interestingly, scRNAseq can be deployed to analyze various types of biological samples such as embryos, nervous systems, tumour cells, stem cells, lymphocytes, and haematopoietic cells. In haematopoietic cells, it can be used to stratify acute myeloid leukemia patterns in patients, sorting them out into cohorts that enable re-modeling of treatment regimens based on stratified presentations. In immunotherapy, it can furnish specialist clinician-immunologist with tools to re-model treatment for each patient, an attribute of precision medicine. Finally, the good predictive attribute of scRNAseq can help reduce the cost of treatment for patients, thus attracting more patients who would have otherwise been discouraged from seeking quality clinical consultation help due to perceived high cost. This is a positive paradigm shift for patients’ attitudes primed towards seeking treatment.

Keywords: immunotherapy, transcriptome, re-modeling, mRNA, scRNA-seq

Procedia PDF Downloads 177

Authors: Pedro Gomes, Luís Sá Castelo, António Lopes, Marta Maio, Pedro Mota, Adélia Avelar, António Marques Dias

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Introduction: Total Knee Arthroplasty (TKA) has contributed to improvement of patient`s quality of life, although it has been associated with some complications including component loosening and polyethylene wear. To prevent these complications various fixation techniques have been employed. Hybrid TKA with cemented tibial and cementless femoral components have shown favourable outcomes, although it still lack of consensus in the literature. Objectives: To evaluate the clinical and radiographic results of hybrid versus cemented TKA with an average 5 years follow-up and analyse the survival rates. Methods: A retrospective study of 125 TKAs performed in 92 patients at our institution, between 2006 to 2008, with a minimum follow-up of 2 years. The same prosthesis was used in all knees. Hybrid TKA fixation was performed in 96 knees, with a mean follow-up of 4,8±1,7 years (range, 2–8,3 years) and 29 TKAs received fully cemented fixation with a mean follow-up of 4,9±1,9 years (range, 2-8,3 years). Selection for hybrid fixation was nonrandomized and based on femoral component fit. The Oxford Knee Score (OKS 0-48) was evaluated for clinical assessment and Knee Society Roentgenographic Evaluation Scoring System was used for radiographic outcome. The survival rate was calculated using the Kaplan-Meier method, with failures defined as revision of either the tibial or femoral component for aseptic failures and all-causes (aseptic and infection). Analysis of survivorship data was performed using the log-rank test. SPSS (v22) was the computer program used for statistical analysis. Results: The hybrid group consisted of 72 females (75%) and 24 males (25%), with mean age 64±7 years (range, 50-78 years). The preoperative diagnosis was osteoarthritis (OA) in 94 knees (98%), rheumatoid arthritis (RA) in 1 knee (1%) and Posttraumatic arthritis (PTA) in 1 Knee (1%). The fully cemented group consisted of 23 females (79%) and 6 males (21%), with mean age 65±7 years (range, 47-78 years). The preoperative diagnosis was OA in 27 knees (93%), PTA in 2 knees (7%). The Oxford Knee Scores were similar between the 2 groups (hybrid 40,3±2,8 versus cemented 40,2±3). The percentage of radiolucencies seen on the femoral side was slightly higher in the cemented group 20,7% than the hybrid group 11,5% p0.223. In the cemented group there were significantly more Zone 4 radiolucencies compared to the hybrid group (13,8% versus 2,1% p0,026). Revisions for all causes were performed in 4 of the 96 hybrid TKAs (4,2%) and 1 of the 29 cemented TKAs (3,5%). The reason for revision was aseptic loosening in 3 hybrid TKAs and 1 of the cemented TKAs. Revision was performed for infection in 1 hybrid TKA. The hybrid group demonstrated a 7 years survival rate of 93% for all-cause failures and 94% for aseptic loosening. No significant difference in survivorship was seen between the groups for all-cause failures or aseptic failures. Conclusions: Hybrid TKA yields similar intermediate-term results and survival rates as fully cemented total knee arthroplasty and remains a viable option in knee joint replacement surgery.

Keywords: hybrid, survival rate, total knee arthroplasty, orthopaedic surgery

Procedia PDF Downloads 594

Authors: Elaine Lima Da Fonseca, Eliomar Pereira Da Silva Filho

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The modeling of areas susceptible to soil loss by hydro erosive processes consists of a simplified instrument of reality with the purpose of predicting future behaviors from the observation and interaction of a set of geoenvironmental factors. The models of potential areas for soil loss will be obtained through binary logistic regression, artificial neural networks, and support vector machines. The choice of the municipality of Colorado do Oeste in the south of the western Amazon is due to soil degradation due to anthropogenic activities, such as agriculture, road construction, overgrazing, deforestation, and environmental and socioeconomic configurations. Initially, a soil erosion inventory map constructed through various field investigations will be designed, including the use of remotely piloted aircraft, orbital imagery, and the PLANAFLORO/RO database. 100 sampling units with the presence of erosion will be selected based on the assumptions indicated in the literature, and, to complement the dichotomous analysis, 100 units with no erosion will be randomly designated. The next step will be the selection of the predictive parameters that exert, jointly, directly, or indirectly, some influence on the mechanism of occurrence of soil erosion events. The chosen predictors are altitude, declivity, aspect or orientation of the slope, curvature of the slope, composite topographic index, flow power index, lineament density, normalized difference vegetation index, drainage density, lithology, soil type, erosivity, and ground surface temperature. After evaluating the relative contribution of each predictor variable, the erosion susceptibility model will be applied to the municipality of Colorado do Oeste - Rondônia through the SPSS Statistic 26 software. Evaluation of the model will occur through the determination of the values of the R² of Cox & Snell and the R² of Nagelkerke, Hosmer and Lemeshow Test, Log Likelihood Value, and Wald Test, in addition to analysis of the Confounding Matrix, ROC Curve and Accumulated Gain according to the model specification. The validation of the synthesis map resulting from both models of the potential risk of soil erosion will occur by means of Kappa indices, accuracy, and sensitivity, as well as by field verification of the classes of susceptibility to erosion using drone photogrammetry. Thus, it is expected to obtain the mapping of the following classes of susceptibility to erosion very low, low, moderate, very high, and high, which may constitute a screening tool to identify areas where more detailed investigations need to be carried out, applying more efficient social resources.

Keywords: modeling, susceptibility to erosion, artificial intelligence, Amazon

Procedia PDF Downloads 68

Authors: Kamal Agrawal, Ved Prakash Nayak, Akshay Patil

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Raipur is known as a city of water bodies. The city had around 200 man-made and natural lakes of varying sizes. These structures were constructed to collect rainwater and control flooding in the city. Due to the transition from community participation to state government, as well as rapid urbanisation, Raipur now has only about 80 lakes left. Rapid and unplanned growth has resulted in pollution, encroachment, and eutrophication of the city's lakes. The state government keeps these lakes in good condition by cleaning them and proposing lakefront developments. However, maintaining individual lakes is insufficient because urban lakes are not distinct entities. It is a system comprised of the lake, shore, catchment, and other components. While Urban lake system (ULS) is a combination of multiple such lake systems interacting in a complex urban setting. Thus, the project aims to propose a co-evolution model for urban lake systems (ULS) and rapid urbanization in Raipur. The goals are to comprehend the ULS and to identify elements and dimensions of urbanization that influence the ULS. Evaluate the impact of rapid urbanization on the ULS & vice versa in the study area. Determine how to maximize the positive impact while minimizing the negative impact identified in the study area. Propose short-, medium-, and long-term planning interventions to support the ULS's co-evolution with rapid urbanization. A complexity approach is used to investigate the ULS. It is a technique for understanding large, complex systems. A complex system is one with many interconnected and interdependent elements and dimensions. Thus, elements of ULS and rapid urbanization are identified through a literature study to evaluate statements of their impacts (Beneficial/ Adverse) on one another. Rapid urbanization has been identified as having elements such as demography, urban legislation, informal settlement, urban infrastructure, and tourism. Similarly, the catchment area of the lake, the lake's water quality, the water spread area, and lakefront developments are all being impacted by rapid urbanisation. These nine elements serve as parameters for the subsequent analysis. Elements are limited to physical parameters only. The city has designated a study area based on the definition provided by the National Plan for the Conservation of Aquatic Ecosystems. Three lakes are discovered within a one-kilometer radius, establishing a tiny urban lake system. Because the condition of a lake is directly related to the condition of its catchment area, the catchment area of these three lakes is delineated as the study area. Data is collected to identify impact statements, and the interdependence diagram generated between the parameters yields results in terms of interlinking between each parameter and their impact on the system as a whole. The planning interventions proposed for the ULS and rapid urbanisation co-evolution model include spatial proposals as well as policy recommendations for the short, medium, and long term. This study's next step will be to determine how to implement the proposed interventions based on the availability of resources, funds, and governance patterns.

Keywords: urban lake system, co-evolution, rapid urbanization, complex system

Procedia PDF Downloads 73

Authors: Maria A. Castillo H., Andres R. Leandro, Jose F. Bienvenido B.

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During the last 20 years, the globalization of economies, population growth, and the increase in the consumption of fresh agricultural products have generated greater demand for ornamentals, flowers, fresh fruits, and vegetables, mainly from tropical areas. This market situation has demanded greater competitiveness and control over production, with more efficient protected agriculture technologies, which provide greater productivity and allow us to guarantee the quality and quantity that is required in a constant and sustainable way. Guatemala, located in the north of Central America, is one of the largest exporters of agricultural products in the region and exports fresh vegetables, flowers, fruits, ornamental plants, and foliage, most of which were grown in greenhouses. Although there are no official agricultural statistics on greenhouse production, several thesis works, and congress reports have presented consistent estimates. A wide range of protection structures and roofing materials are used, from the most basic and simple ones for rain control to highly technical and automated structures connected with remote sensors for monitoring and control of crops. With this breadth of technological models, it is necessary to analyze georeferenced data related to the cultivated area, to the different existing models, and to the covering materials, integrated with altitude, climate, and soil data. The georeferenced registration of the production units, the data collection with digital tools, the use of satellite images, and geographic information systems (GIS) provide reliable tools to elaborate more complete, agile, and dynamic information maps. This study details a methodology proposed for gathering georeferenced data of high protection structures (greenhouses) in Guatemala, structured in four phases: diagnosis of available information, the definition of the geographic frame, selection of satellite images, and integration with an information system geographic (GIS). It especially takes account of the actual lack of complete data in order to obtain a reliable decision-making system; this gap is solved through the proposed methodology. A summary of the results is presented in each phase, and finally, an evaluation with some improvements and tentative recommendations for further research is added. The main contribution of this study is to propose a methodology that allows to reduce the gap of georeferenced data in protected agriculture in this specific area where data is not generally available and to provide data of better quality, traceability, accuracy, and certainty for the strategic agricultural decision öaking, applicable to other crops, production models and similar/neighboring geographic areas.

Keywords: greenhouses, protected agriculture, GIS, Guatemala, satellite image, digital tools, precision agriculture

Procedia PDF Downloads 194

Authors: Nina Sankat, Gerd Wilsch, Cassian Gottlieb, Steven Millar, Tobias Guenther

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Laser-Induced Breakdown Spectroscopy (LIBS) is a combination of laser ablation and optical emission spectroscopy, which in principle can simultaneously analyze all elements on the periodic table. Materials can be analyzed in terms of chemical composition in a two-dimensional, time efficient and minor destructive manner. These advantages predestine LIBS as a monitoring technique in the field of civil engineering. The decreasing service life of concrete infrastructures is a continuously growing problematic. A variety of intruding, harmful substances can damage the reinforcement or the concrete itself. To insure a sufficient service life a regular monitoring of the structure is necessary. LIBS offers many applications to accomplish a successful examination of the conditions of concrete structures. A selection of those applications are the 2D-evaluation of chlorine-, sodium- and sulfur-concentration, the identification of carbonation depths and the representation of the heterogeneity of concrete. LIBS obtains this information by using a pulsed laser with a short pulse length (some mJ), which is focused on the surfaces of the analyzed specimen, for this only an optical access is needed. Because of the high power density (some GW/cm²) a minimal amount of material is vaporized and transformed into a plasma. This plasma emits light depending on the chemical composition of the vaporized material. By analyzing the emitted light, information for every measurement point is gained. The chemical composition of the scanned area is visualized in a 2D-map with spatial resolutions up to 0.1 mm x 0.1 mm. Those 2D-maps can be converted into classic depth profiles, as typically seen for the results of chloride concentration provided by chemical analysis like potentiometric titration. However, the 2D-visualization offers many advantages like illustrating chlorine carrying cracks, direct imaging of the carbonation depth and in general allowing the separation of the aggregates from the cement paste. By calibrating the LIBS-System, not only qualitative but quantitative results can be obtained. Those quantitative results can also be based on the cement paste, while excluding the aggregates. An additional advantage of LIBS is its mobility. By using the mobile system, located at BAM, onsite measurements are feasible. The mobile LIBS-system was already used to obtain chloride, sodium and sulfur concentrations onsite of parking decks, bridges and sewage treatment plants even under hard conditions like ongoing construction work or rough weather. All those prospects make LIBS a promising method to secure the integrity of infrastructures in a sustainable manner.

Keywords: concrete, damage assessment, harmful substances, LIBS

Procedia PDF Downloads 176

Authors: Francesca Marsili

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The reliability assessment of existing structures with probabilistic methods is becoming an increasingly important and frequent engineering task. However probabilistic reliability methods are based on an exhaustive knowledge of the stochastic modeling of the variables involved in the assessment; at the moment standards for the modeling of variables are absent, representing an obstacle to the dissemination of probabilistic methods. The framework according to probability distribution functions (PDFs) are established is represented by the Bayesian statistics, which uses Bayes Theorem: a prior PDF for the considered parameter is established based on information derived from the design stage and qualitative judgments based on the engineer past experience; then, the prior model is updated with the results of investigation carried out on the considered structure, such as material testing, determination of action and structural properties. The application of Bayesian statistics arises two different kind of problems: 1. The results of the updating depend on the engineer previous experience; 2. The updating of the prior PDF can be performed only if the structure has been tested, and quantitative data that can be statistically manipulated have been collected; performing tests is always an expensive and time consuming operation; furthermore, if the considered structure is an ancient building, destructive tests could compromise its cultural value and therefore should be avoided. In order to solve those problems, an interesting research path is represented by investigating Artificial Intelligence (AI) techniques that can be useful for the automation of the modeling of variables and for the updating of material parameters without performing destructive tests. Among the others, one that raises particular attention in relation to the object of this study is constituted by Case-Based Reasoning (CBR). In this application, cases will be represented by existing buildings where material tests have already been carried out and an updated PDFs for the material mechanical parameters has been computed through a Bayesian analysis. Then each case will be composed by a qualitative description of the material under assessment and the posterior PDFs that describe its material properties. The problem that will be solved is the definition of PDFs for material parameters involved in the reliability assessment of the considered structure. A CBR system represent a good candi¬date in automating the modelling of variables because: 1. Engineers already draw an estimation of the material properties based on the experience collected during the assessment of similar structures, or based on similar cases collected in literature or in data-bases; 2. Material tests carried out on structure can be easily collected from laboratory database or from literature; 3. The system will provide the user of a reliable probabilistic description of the variables involved in the assessment that will also serve as a tool in support of the engineer’s qualitative judgments. Automated modeling of variables can help in spreading probabilistic reliability assessment of existing buildings in the common engineering practice, and target at the best intervention and further tests on the structure; CBR represents a technique which may help to achieve this.

Keywords: reliability assessment of existing buildings, Bayesian analysis, case-based reasoning, historical structures

Procedia PDF Downloads 339

Authors: Justine Kiiza, Xu Jiafang

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The world’s demand for energy is increasing rapidly due to population growth and a reduction in shallow conventional oil and gas reservoirs, resorting to deeper and mostly unconventional reserves like shale oil and gas. Most shale formations contain a large amount of expansive sodium montmorillonite (Na-Mnt), due to high water adsorption, hydration, and when the drilling fluid filtrate enters the formation with high Mnt content, the wellbore wall can be unstable due to hydration and swelling, resulting to shrinkage, sticking, balling, time wasting etc., and well collapse in extreme cases causing complex downhole accidents and high well costs. Recently, polyamines like 1, 6 – hexane diamine (HEDA) have been used as typical drilling fluid shale inhibitors to minimize and/or cab clay mineral swelling and maintain the wellbore stability. However, their application is limited to shallow drilling due to their sensitivity to elevated temperature and pressure. Inorganic potassium salts i.e., KCl, have long been applied for restriction of shale formation hydration expansion in deep wells, but their use is limited due to toxicity. Understanding the adsorption behaviour of HEDA on Na-Mnt surfaces in present of organo-salts, organic K-salts e.g., HCO₂K - main component of organo-salt drilling fluid, is of great significance in explaining the inhibitory performance of polyamine inhibitors. Molecular dynamic simulations (MD) were applied to investigate the influence of HCO₂K and KCl on the adsorption mechanism of HEDA on the Na-Mnt surface. Simulation results showed that adsorption configurations of HEDA are mainly by terminal amine groups with a flat-lying alkyl hydrophobic chain. Its interaction with the clay surface decreased the H-bond number between H₂O-clay and neutralized the negative charge of the Mnt surface, thus weakening the surface hydration ability of Na-Mnt. The introduction of HCO₂K greatly improved inhibition ability, coordination of interlayer ions with H₂O as they were replaced by K+, and H₂O-HCOO- coordination reduced H₂O-Mnt interactions, mobility and transport capability of H₂O molecules were more decreased. While KCl showed little ability and also caused more hydration with time, HCO₂K can be used as an alternative for offshore drilling instead of toxic KCl, with a maximum concentration noted in this study as 1.65 wt%. This study provides a theoretical elucidation for the inhibition mechanism and adsorption characteristics of HEDA inhibitor on Na-Mnt surfaces in the presence of K+-salts and may provide more insight into the evaluation, selection, and molecular design of new clay-swelling high-performance WBDF systems used in oil and gas complex offshore drilling well sections.

Keywords: shale, hydration, inhibition, polyamines, organo-salts, simulation

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Authors: Fatih Kılıç, Burak Birol, Necmettin Maraşlı

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The directional solidification process is generally used for homogeneous compound production, single crystal growth, and refining (zone refining), etc. processes. The most important two parameters that control eutectic structures are temperature gradient and grain growth rate which are called as solidification parameters The solidification behavior and microstructure characteristics is an interesting topic due to their effects on the properties and performance of the alloys containing eutectic compositions. The solidification behavior of multicomponent and multiphase systems is an important parameter for determining various properties of these materials. The researches have been conducted mostly on the solidification of pure materials or alloys containing two phases. However, there are very few studies on the literature about multiphase reactions and microstructure formation of multicomponent alloys during solidification. Because of this situation, it is important to study the microstructure formation and the thermodynamical, thermophysical and microstructural properties of these alloys. The production process is difficult due to easy oxidation of magnesium and therefore, there is not a comprehensive study concerning alloys containing high Mg (> 30 wt.% Mg). With the increasing amount of Mg inside Al alloys, the specific weight decreases, and the strength shows a slight increase, while due to formation of β-Al8Mg5 phase, ductility lowers. For this reason, production, examination and development of high Mg containing alloys will initiate the production of new advanced engineering materials. The original value of this research can be described as obtaining high Mg containing (> 30% Mg) Al based multicomponent alloys by melting under vacuum; controlled directional solidification with various growth rates at a constant temperature gradient; and establishing relationship between solidification rate and microstructural, mechanical, electrical and thermal properties. Therefore, within the scope of this research, some > 30% Mg containing ternary or quaternary Al alloy compositions were determined, and it was planned to investigate the effects of directional solidification rate on the mechanical, electrical and thermal properties of these alloys. Within the scope of the research, the influence of the growth rate on microstructure parameters, microhardness, tensile strength, electrical conductivity and thermal conductivity of directionally solidified high Mg containing Al-32,2Mg-0,37Si; Al-30Mg-12Zn; Al-32Mg-1,7Ni; Al-32,2Mg-0,37Fe; Al-32Mg-1,7Ni-0,4Si; Al-33,3Mg-0,35Si-0,11Fe (wt.%) alloys with wide range of growth rate (50-2500 µm/s) and fixed temperature gradient, will be investigated. The work can be planned as; (a) directional solidification of Al-Mg based Al-Mg-Si, Al-Mg-Zn, Al-Mg-Ni, Al-Mg-Fe, Al-Mg-Ni-Si, Al-Mg-Si-Fe within wide range of growth rates (50-2500 µm/s) at a constant temperature gradient by Bridgman type solidification system, (b) analysis of microstructure parameters of directionally solidified alloys by using an optical light microscopy and Scanning Electron Microscopy (SEM), (c) measurement of microhardness and tensile strength of directionally solidified alloys, (d) measurement of electrical conductivity by four point probe technique at room temperature (e) measurement of thermal conductivity by linear heat flow method at room temperature.

Keywords: directional solidification, electrical conductivity, high Mg containing multicomponent Al alloys, microhardness, microstructure, tensile strength, thermal conductivity

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Authors: C. Silveira, A. Ascenso, J. Ferreira, A. I. Miranda, P. Tuccella, G. Curci

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Poor air quality is one of the main environmental causes of premature deaths worldwide, and mainly in cities, where the majority of the population lives. It is a consequence of successive land cover (LC) and use changes, as a result of the intensification of human activities. Knowing these landscape modifications in a comprehensive spatiotemporal dimension is, therefore, essential for understanding variations in air pollutant concentrations. In this sense, the use of air quality models is very useful to simulate the physical and chemical processes that affect the dispersion and reaction of chemical species into the atmosphere. However, the modelling performance should always be evaluated since the resolution of the input datasets largely dictates the reliability of the air quality outcomes. Among these data, the updated LC is an important parameter to be considered in atmospheric models, since it takes into account the Earth’s surface changes due to natural and anthropic actions, and regulates the exchanges of fluxes (emissions, heat, moisture, etc.) between the soil and the air. This work aims to evaluate the performance of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), when different LC classifications are used as an input. The influence of two LC classifications was tested: i) the 24-classes USGS (United States Geological Survey) LC database included by default in the model, and the ii) CLC (Corine Land Cover) and specific high-resolution LC data for Portugal, reclassified according to the new USGS nomenclature (33-classes). Two distinct WRF-Chem simulations were carried out to assess the influence of the LC on air quality over Europe and Portugal, as a case study, for the year 2015, using the nesting technique over three simulation domains (25 km², 5 km² and 1 km² horizontal resolution). Based on the 33-classes LC approach, particular emphasis was attributed to Portugal, given the detail and higher LC spatial resolution (100 m x 100 m) than the CLC data (5000 m x 5000 m). As regards to the air quality, only the LC impacts on tropospheric ozone concentrations were evaluated, because ozone pollution episodes typically occur in Portugal, in particular during the spring/summer, and there are few research works relating to this pollutant with LC changes. The WRF-Chem results were validated by season and station typology using background measurements from the Portuguese air quality monitoring network. As expected, a better model performance was achieved in rural stations: moderate correlation (0.4 – 0.7), BIAS (10 – 21µg.m^-3) and RMSE (20 – 30 µg.m^-3), and where higher average ozone concentrations were estimated. Comparing both simulations, small differences grounded on the Leaf Area Index and air temperature values were found, although the high-resolution LC approach shows a slight enhancement in the model evaluation. This highlights the role of the LC on the exchange of atmospheric fluxes, and stresses the need to consider a high-resolution LC characterization combined with other detailed model inputs, such as the emission inventory, to improve air quality assessment.

Keywords: land use, spatial resolution, WRF-Chem, air quality assessment

Procedia PDF Downloads 159

Authors: Ambali Alade Odebowale, Andargachew Mekonnen Berhe, Haroldo T. Hattori, Andrey E. Miroshnichenko

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Solar thermophotovoltaic systems (STPV) have emerged as a promising solution to overcome the Shockley-Queisser limit, a significant impediment in the direct conversion of solar radiation into electricity using conventional solar cells. The STPV system comprises essential components such as an optical concentrator, selective emitter, and a thermophotovoltaic (TPV) cell. The pivotal element in achieving high efficiency in an STPV system lies in the design of a spectrally selective emitter or absorber. Traditional methods for designing and optimizing selective emitters are often time-consuming and may not yield highly selective emitters, posing a challenge to the overall system performance. In recent years, the application of machine learning techniques in various scientific disciplines has demonstrated significant advantages. This paper proposes a novel nanostructure composed of four-layered materials (SiC/W/SiO2/W) to function as a selective emitter in the energy conversion process of an STPV system. Unlike conventional approaches widely adopted by researchers, this study employs a machine learning-based approach for the design and optimization of the selective emitter. Specifically, a random forest algorithm (RFA) is employed for the design of the selective emitter, while the optimization process is executed using genetic algorithms. This innovative methodology holds promise in addressing the challenges posed by traditional methods, offering a more efficient and streamlined approach to selective emitter design. The utilization of a machine learning approach brings several advantages to the design and optimization of a selective emitter within the STPV system. Machine learning algorithms, such as the random forest algorithm, have the capability to analyze complex datasets and identify intricate patterns that may not be apparent through traditional methods. This allows for a more comprehensive exploration of the design space, potentially leading to highly efficient emitter configurations. Moreover, the application of genetic algorithms in the optimization process enhances the adaptability and efficiency of the overall system. Genetic algorithms mimic the principles of natural selection, enabling the exploration of a diverse range of emitter configurations and facilitating the identification of optimal solutions. This not only accelerates the design and optimization process but also increases the likelihood of discovering configurations that exhibit superior performance compared to traditional methods. In conclusion, the integration of machine learning techniques in the design and optimization of a selective emitter for solar thermophotovoltaic systems represents a groundbreaking approach. This innovative methodology not only addresses the limitations of traditional methods but also holds the potential to significantly improve the overall performance of STPV systems, paving the way for enhanced solar energy conversion efficiency.

Keywords: emitter, genetic algorithm, radiation, random forest, thermophotovoltaic

Procedia PDF Downloads 62

Authors: Chuyu Huang, Itsuki Minemi, Kuanlin Chen, Yuki Hirose

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It remains unclear how language speakers are able to perceive phonological contrasts that do not exist on their own. This experiment uses the vowel-length distinction in Japanese, which is phonologically contrastive and co-occurs with tonal change in some cases. For speakers whose first language does not distinguish vowel length, contrastive duration is usually misperceived, e.g., Mandarin speakers. Two alternative hypotheses for how Mandarin speakers would perceive a phonological contrast that does not exist in their language make different predictions. The stress parameter model does not have a clear prediction about the impact of tonal type. Mandarin speakers will likely be not able to perceive vowel length as well as Japanese native speakers do, but the performance might not correlate to tonal type because the prosody of their language is distinctive, which requires users to encode lexical prosody and notice subtle differences in word prosody. By contrast, cue-based phonetic models predict that Mandarin speakers may rely on pitch differences, a secondary cue, to perceive vowel length. Two groups of Mandarin speakers, including naive non-Japanese speakers and beginner learners, were recruited to participate in an AX discrimination task involving two Japanese sound stimuli that contain a phonologically contrastive environment. Participants were asked to indicate whether the two stimuli containing a vowel-length contrast (e.g., maapero vs. mapero) sound the same. The experiment was bifactorial. The first factor contrasted three syllabic positions (syllable position; initial/medial/final), as it would be likely to affect the perceptual difficulty, as seen in previous studies, and the second factor contrasted two pitch types (accent type): one with accentual change that could be distinguished with the lexical tones in Mandarin (the different condition), with the other group having no tonal distinction but only differing in vowel length (the same condition). The overall results showed that a significant main effect of accent type by applying a linear mixed-effects model (β = 1.48, SE = 0.35, p < 0.05), which implies that Mandarin speakers tend to more successfully recognize vowel-length differences when the long vowel counterpart takes on a tone that exists in Mandarin. The interaction between the accent type and the syllabic position is also significant (β = 2.30, SE = 0.91, p < 0.05), showing that vowel lengths in the different conditions are more difficult to recognize in the word-final case relative to the initial condition. The second statistical model, which compares naive speakers to beginners, was conducted with logistic regression to test the effects of the participant group. A significant difference was found between the two groups (β = 1.06, 95% CI = [0.36, 2.03], p < 0.05). This study shows that: (1) Mandarin speakers are likely to use pitch cues to perceive vowel length in a non-native language, which is consistent with the cue-based approaches; (2) an exposure effect was observed: the beginner group achieved a higher accuracy for long vowel perception, which implied the exposure effect despite the short period of language learning experience.

Keywords: cue-based perception, exposure effect, prosodic perception, vowel duration

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Authors: Fatin Mansour Daas

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Language education responds to and is reflective of emerging social and political trends. Language policies and practices are shaped by political, economic, social and cultural considerations. Following this, Israeli language education policy as implemented in Arab schools in Israel is influenced by the particular political and social situation of Arab-Palestinian citizens of Israel. This national group remained in their homeland following the war in 1948 between Israel and its Arab neighbors and became Israeli citizens following the establishment of the State of Israel. This study examines language policy in Arab schools in Israel from 1948 until the present time in light of the unique experience of the Palestinian Arab homeland minority in Israel with a particular focus on questions of politics and identity. The establishment of the State of Israel triggered far-reaching political, social and educational transformations within Arab Palestinian society in Israel, including in the area of language and language studies. Since 1948, the linguistic repertoire of Palestinian Arabs in Israel has become more complex and diverse, while the place and status of different languages have changed. Following the establishment of the State of Israel, only Hebrew and Arabic were retained as the official languages, and Israeli policy reflected this in schools as well: with the advent of the Jewish state, Hebrew language education among Palestinians in Israel has increased. Similarly, in Arab Palestinian schools in Israel, English is taught as a third language, Hebrew as a second language, and Arabic as a first language – even though it has become less important to native Arabic speakers. This research focuses on language studies and language policy in the Arab school system in Israel from 1948 onwards. It will analyze the relative focus of language education between the different languages, the rationale of various language education policies, and the pedagogic approach used to teach each language and student achievements vis-à-vis language skills. This study seeks to understand the extent to which Arab schools in Israel are multi-lingual by examining successes, challenges and difficulties in acquiring the respective languages. This qualitative study will analyze five different components of language education policy: (1) curriculum, (2) learning materials; (3) assessment; (4) interviews and (5) archives. Firstly, it consists of an analysis examining language education curricula, learning materials and assessments used in Arab schools in Israel from 1948-2018 including a selection of language textbooks for the compulsory years of study and the final matriculation (Bagrut) examinations. The findings will also be based on archival material which traces the evolution of language education policy in Arabic schools in Israel from the years 1948-2018. This archival research, furthermore, will reveal power relations and general decision-making in the field of the Arabic education system in Israel. The research will also include interviews with Ministry of Education staff who provide instructional oversight in the instruction of the three languages in the Arabic education system in Israel. These interviews will shed light on the goals of language education as understood by those who are in charge of implementing policy.

Keywords: language education policy, languages, multilingualism, language education, educational policy, identity, Palestinian-Arabs, Arabs in Israel, educational school system

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Authors: Antònio Inês, Davide Silva, Filipa Carvalho, Luís Filipe-Riberiro, Fernando M. Nunes, Luís Abrunhosa, Fernanda Cosme

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The presence of mycotoxins in foodstuff is a matter of concern for food safety. Mycotoxins are toxic secondary metabolites produced by certain molds, being ochratoxin A (OTA) one of the most relevant. Wines can also be contaminated with these toxicants. Several authors have demonstrated the presence of mycotoxins in wine, especially ochratoxin A. Its chemical structure is a dihydro-isocoumarin connected at the 7-carboxy group to a molecule of L-β-phenylalanine via an amide bond. As these toxicants can never be completely removed from the food chain, many countries have defined levels in food in order to attend health concerns. OTA contamination of wines might be a risk to consumer health, thus requiring treatments to achieve acceptable standards for human consumption. The maximum acceptable level of OTA in wines is 2.0 μg/kg according to the Commission regulation No. 1881/2006. Therefore, the aim of this work was to reduce OTA to safer levels using different fining agents, as well as their impact on white wine physicochemical characteristics. To evaluate their efficiency, 11 commercial fining agents (mineral, synthetic, animal and vegetable proteins) were used to get new approaches on OTA removal from white wine. Trials (including a control without addition of a fining agent) were performed in white wine artificially supplemented with OTA (10 µg/L). OTA analyses were performed after wine fining. Wine was centrifuged at 4000 rpm for 10 min and 1 mL of the supernatant was collected and added of an equal volume of acetonitrile/methanol/acetic acid (78:20:2 v/v/v). Also, the solid fractions obtained after fining, were centrifuged (4000 rpm, 15 min), the resulting supernatant discarded, and the pellet extracted with 1 mL of the above solution and 1 mL of H2O. OTA analysis was performed by HPLC with fluorescence detection. The most effective fining agent in removing OTA (80%) from white wine was a commercial formulation that contains gelatin, bentonite and activated carbon. Removals between 10-30% were obtained with potassium caseinate, yeast cell walls and pea protein. With bentonites, carboxymethylcellulose, polyvinylpolypyrrolidone and chitosan no considerable OTA removal was verified. Following, the effectiveness of seven commercial activated carbons was also evaluated and compared with the commercial formulation that contains gelatin, bentonite and activated carbon. The different activated carbons were applied at the concentration recommended by the manufacturer in order to evaluate their efficiency in reducing OTA levels. Trial and OTA analysis were performed as explained previously. The results showed that in white wine all activated carbons except one reduced 100% of OTA. The commercial formulation that contains gelatin, bentonite and activated carbon reduced only 73% of OTA concentration. These results may provide useful information for winemakers, namely for the selection of the most appropriate oenological product for OTA removal, reducing wine toxicity and simultaneously enhancing food safety and wine quality.

Keywords: wine, ota removal, food safety, fining

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Authors: Regina Rekuviene, Vykintas Samaitis, Liudas Mažeika, Audrius Jankauskas, Virginija Jankauskaitė, Laura Gegeckienė, Abdolali Sadaghiani, Shaghayegh Saeidiharzand

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Icing brings significant damage to aviation and renewable energy installations. Air-conditioning, refrigeration, wind turbine blades, airplane and helicopter blades often suffer from icing phenomena, which cause severe energy losses and impair aerodynamic performance. The icing process is a complex phenomenon with many different causes and types. Icing mechanisms, distributions, and patterns are still relevant to research topics. The adhesion strength between ice and surfaces differs in different icing environments. This makes the task of anti-icing very challenging. The techniques for various icing environments must satisfy different demands and requirements (e.g., efficient, lightweight, low power consumption, low maintenance and manufacturing costs, reliable operation). It is noticeable that most methods are oriented toward a particular sector and adapting them to or suggesting them for other areas is quite problematic. These methods often use various technologies and have different specifications, sometimes with no clear indication of their efficiency. There are two major groups of anti-icing methods: passive and active. Active techniques have high efficiency but, at the same time, quite high energy consumption and require intervention in the structure’s design. It’s noticeable that vast majority of these methods require specific knowledge and personnel skills. The main effect of passive methods (ice-phobic, superhydrophobic surfaces) is to delay ice formation and growth or reduce the adhesion strength between the ice and the surface. These methods are time-consuming and depend on forecasting. They can be applied on small surfaces only for specific targets, and most are non-biodegradable (except for anti-freezing proteins). There is some quite promising information on ultrasonic ice mitigation methods that employ UGW (Ultrasonic Guided Wave). These methods are have the characteristics of low energy consumption, low cost, lightweight, and easy replacement and maintenance. However, fundamental knowledge of ultrasonic de-icing methodology is still limited. The objective of this work was to identify the ice formation processes and its progress by employing ultrasonic guided wave technique. Throughout this research, the universal set-up for acoustic measurement of ice formation in a real condition (temperature range from +240 C to -230 C) was developed. Ultrasonic measurements were performed by using high frequency 5 MHz transducers in a pitch-catch configuration. The selection of wave modes suitable for detection of ice formation phenomenon on copper metal surface was performed. Interaction between the selected wave modes and ice formation processes was investigated. It was found that selected wave modes are sensitive to temperature changes. It was demonstrated that proposed ultrasonic technique could be successfully used for the detection of ice layer formation on a metal surface.

Keywords: ice formation processes, ultrasonic GW, detection of ice formation, ultrasonic testing

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Authors: Mohammed Makha, Jakob Heier, Frank Nüesch, Roland Hany

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Organic solar cells (OSCs) have made rapid progress and currently achieve power conversion efficiencies (PCE) of over 10%. OSCs have several merits over other direct light-to-electricity generating cells and can be processed at low cost from solution on flexible substrates over large areas. Moreover, combining organic semiconductors with transparent and conductive electrodes allows for the fabrication of semitransparent OSCs (SM-OSCs). For SM-OSCs the challenge is to achieve a high average visible transmission (AVT) while maintaining a high short circuit current (Jsc). Typically, Jsc of SM-OSCs is smaller than when using an opaque metal top electrode. This is because the non-absorbed light during the first transit through the active layer and the transparent electrode is forward-transmitted out of the device. Recently, OSCs using a ternary blend of organic materials have received attention. This strategy was pursued to extend the light harvesting over the visible range. However, it is a general challenge to manipulate the performance of ternary OSCs in a predictable way, because many key factors affect the charge generation and extraction in ternary solar cells. Consequently, the device performance is affected by the compatibility between the blend components and the resulting film morphology, the energy levels and bandgaps, the concentration of the guest material and its location in the active layer. In this work, we report on a solvent-free lamination process for the fabrication of efficient and semitransparent ternary blend OSCs. The ternary blend was composed of PC70BM and the electron donors PBDTTT-C and an NIR cyanine absorbing dye (Cy7T). Using an opaque metal top electrode, a PCE of 6% was achieved for the optimized binary polymer: fullerene blend (AVT = 56%). However, the PCE dropped to ~2% when decreasing (to 30 nm) the active film thickness to increase the AVT value (75%). Therefore we resorted to the ternary blend and measured for non-transparent cells a PCE of 5.5% when using an active polymer: dye: fullerene (0.7: 0.3: 1.5 wt:wt:wt) film of 95 nm thickness (AVT = 65% when omitting the top electrode). In a second step, the optimized ternary blend was used of the fabrication of SM-OSCs. We used a plastic/metal substrate with a light transmission of over 90% as a transparent electrode that was applied via a lamination process. The interfacial layer between the active layer and the top electrode was optimized in order to improve the charge collection and the contact with the laminated top electrode. We demonstrated a PCE of 3% with AVT of 51%. The parameter space for ternary OSCs is large and it is difficult to find the best concentration ratios by trial and error. A rational approach for device optimization is the construction of a ternary blend phase diagram. We discuss our attempts to construct such a phase diagram for the PBDTTT-C: Cy7T: PC70BM system via a combination of using selective Cy7T selective solvents and atomic force microscopy. From the ternary diagram suitable morphologies for efficient light-to-current conversion can be identified. We compare experimental OSC data with these predictions.

Keywords: organic photovoltaics, ternary phase diagram, ternary organic solar cells, transparent solar cell, lamination

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Authors: Fabio N. Moreno, Letícia B. Marinho, Beatriz D. Ruiz, Maria Helena R. B. Martins

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Brazil is a top consumer of pesticides worldwide, and the São Paulo State is one of the highest consumers among the Brazilian federative states. However, representative data about the occurrence of pesticides in surface waters of the São Paulo State is scarce. This paper aims to present the results of pesticides monitoring executed within the Water Quality Monitoring Network of CETESB (The Environmental Agency of the São Paulo State) between the 2018-2022 period. Surface water sampling points (21 to 25) were selected within basins of predominantly agricultural land-use (5 to 85% of cultivated areas). The samples were collected throughout the year, including high-flow and low-flow conditions. The frequency of sampling varied between 6 to 4 times per year. Selection of pesticide molecules for monitoring followed a prioritizing process from EMBRAPA (Brazilian Agricultural Research Corporation) databases of pesticide use. Pesticides extractions in aqueous samples were performed according to USEPA 3510C and 3546 methods following quality assurance and quality control procedures. Determination of pesticides in water (ng L-1) extracts were performed by high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS) and by gas chromatography with nitrogen phosphorus (GC-NPD) and electron capture detectors (GC-ECD). The results showed higher frequencies (20- 65%) in surface water samples for Carbendazim (fungicide), Diuron/Tebuthiuron (herbicides) and Fipronil/Imidaclopride (insecticides). The frequency of observations for these pesticides were generally higher in monitoring points located in sugarcane cultivated areas. The following pesticides were most frequently quantified above the Aquatic life benchmarks for freshwater (USEPA Office of Pesticide Programs, 2023) or Brazilian Federal Regulatory Standards (CONAMA Resolution no. 357/2005): Atrazine, Imidaclopride, Carbendazim, 2,4D, Fipronil, and Chlorpiryfos. Higher median concentrations for Diuron and Tebuthiuron in the rainy months (october to march) indicated pesticide transport through surface runoff. However, measurable concentrations in the dry season (april to september) for Fipronil and Imidaclopride also indicates pathways related to subsurface or base flow discharge after pesticide soil infiltration and leaching or dry deposition following pesticide air spraying. With exception to Diuron, no temporal trends related to median concentrations of the most frequently quantified pesticides were observed. These results are important to assist policymakers in the development of strategies aiming at reducing pesticides migration to surface waters from agricultural areas. Further studies will be carried out in selected points to investigate potential risks as a result of pesticides exposure on aquatic biota.

Keywords: pesticides monitoring, são paulo state, water quality, surface waters

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