Search results for: tomato yield prediction

Authors: Luisa Maria Arrechea Fajardo, Luz Stella Cadavid Rodriguez

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Fish is one of the most commercialized foods worldwide. However, this industry only takes advantage of about 55% of the product's weight, the rest is converted into waste, which is mainly composed of viscera, gills, scales and spines. Consequently, if these wastes are not used or disposed of properly, they cause serious environmental impacts. This is the case of Tumaco (Colombia), the second largest producer of marine fisheries on the Colombian Pacific coast, where artisanal fishermen process more than 50% of the commercialized volume. There, fishing waste is disposed primarily in the ocean, causing negative impacts on the environment and society. Therefore, in the present research, a proposal was made to take advantage of fishing waste through anaerobic treatments, through which it is possible to obtain products with high added value from organic waste. The research was carried out in four stages. First, the production of volatile fatty acids (VFA) in semi-continuous 4L reactors was studied, evaluating three hydraulic retention times (HRT) (10, 7 and 5 days) with four organic loading rates (OLR) (16, 14, 12 and 10 gVS/L/day), the experiment was carried out for 150 days. Subsequently, biogas production was evaluated from the solid digestate generated in the VFA production reactors, initially evaluating the biochemical methane potential (BMP) of 4 total solid concentrations (1, 2, 4 and 6% TS), for 40 days and then, with the optimum TS concentration (2 gVS/L/day), 2 HRT (15 and 20 days) in semi-continuous reactors, were evaluated for 100 days. Finally, the integration of the processes was carried out with the best conditions found, a first phase of VFA production from fishing waste and a second phase of biogas production from unrecovered VFAs and unprocessed material Additionally, an VFA membrane extraction system was included. In the first phase, a liquid digestate with a concentration and VFA production yield of 59.04 gVFA/L and 0.527 gVFA/gVS, respectively, was obtained, with the best condition found (HRT:7 days and OLR: 16 gVS/L/día), where acetic acid and isobutyric acid were the predominant acids. In the second phase of biogas production, a BMP of 0.349 Nm3CH4/KgVS was reached, and it was found as best HRT 20 days. In the integration, the isovaleric, butyric and isobutyric acid were the VFA with the highest percentage of extraction, additionally a 106.67% increase in biogas production was achieved. This research shows that anaerobic treatments are a promising technology for an environmentally safe management of fishing waste and presents the basis of a possible biorefinery.

Keywords: biogas production, fishing waste, VFA membrane extraction, VFA production

Procedia PDF Downloads 117

Authors: Janet Modu, Jean-Francois Georgin, Laurent Briancon, Eric Antoinet

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The current practice during the repowering phase of wind turbines is deconstruction of existing foundations and construction of new foundations to accept larger wind loads or once the foundations have reached the end of their service lives. The ongoing research project FUI25 FEDRE (Fondations d’Eoliennes Durables et REpowering) therefore serves to propose scalable wind turbine foundation designs to allow reuse of the existing foundations. To undertake this research, numerical models and laboratory-scale models are currently being utilized and implemented in the GEOMAS laboratory at INSA Lyon following instrumentation of a reference wind turbine situated in the Northern part of France. Sensors placed within both the foundation and the underlying soil monitor the evolution of stresses from the foundation’s early age to stresses during service. The results from the instrumentation form the basis of validation for both the laboratory and numerical works conducted throughout the project duration. The study currently focuses on the effect of coupled mechanisms (Thermal-Hydro-Mechanical-Chemical) that induce stress during the early age of the reinforced concrete foundation, and scale factor considerations in the replication of the reference wind turbine foundation at laboratory-scale. Using THMC 3D models on COMSOL Multi-physics software, the numerical analysis performed on both the laboratory-scale and the full-scale foundations simulate the thermal deformation, hydration, shrinkage (desiccation and autogenous) and creep so as to predict the initial damage caused by internal processes during concrete setting and hardening. Results show a prominent effect of early age properties on the damage potential in full-scale wind turbine foundations. However, a prediction of the damage potential at laboratory scale shows significant differences in early age stresses in comparison to the full-scale model depending on the spatial position in the foundation. In addition to the well-known size effect phenomenon, these differences may contribute to inaccuracies encountered when predicting ultimate deformations of the on-site foundation using laboratory scale models.

Keywords: cement hydration, early age behavior, reinforced concrete, shrinkage, THMC 3D models, wind turbines

Procedia PDF Downloads 175

Authors: Mohammad Borhani, Ahmad Jamshidzaei, Mehdi Koohsari

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The study of climate has captivated human interest throughout history. In response to this fascination, individuals historically organized their daily activities in alignment with prevailing climatic conditions and seasonal variations. Understanding the elements and specific climatic parameters of each region, such as precipitation, which directly impacts human life, is essential because, in recent years, there has been a significant increase in heavy rainfall in various parts of the world attributed to the effects of climate change. Climate prediction models suggest a future scenario characterized by an increase in severe precipitation events and related floods on a global scale. This is a result of human-induced greenhouse gas emissions causing changes in the natural precipitation patterns. The Intergovernmental Panel on Climate Change reported global warming in 2001. The average global temperature has shown an increasing trend since 1861. In the 20th century, this increase has been between (0/2 ± 0/6) °C. The present study focused on examining the trend of monthly, seasonal, and annual precipitation in Sistan and Baluchestan provinces. The study employed data obtained from 13 precipitation measurement stations managed by the Iran Water Resources Management Company, encompassing daily precipitation records spanning the period from 1997 to 2016. The results indicated that the total monthly precipitation at the studied stations in Sistan and Baluchestan province follows a sinusoidal trend. The highest intense precipitation was observed in January, February, and March, while the lowest occurred in September, October, and then November. The investigation of the trend of seasonal precipitation in this province showed that precipitation follows an upward trend in the autumn season, reaching its peak in winter, and then shows a decreasing trend in spring and summer. Also, the examination of average precipitation indicated that the highest yearly precipitation occurred in 1997 and then in 2004, while the lowest annual precipitation took place between 1999 and 2001. The analysis of the annual precipitation trend demonstrates a decrease in precipitation from 1997 to 2016 in Sistan and Baluchestan province.

Keywords: climate change, extreme precipitation, greenhouse gas, trend analysis

Procedia PDF Downloads 67

Authors: Ella Tyuryumina, Alexey Neznanov

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This paper is devoted to mathematical modelling of the progression and stages of breast cancer. We propose Consolidated mathematical growth model of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases (CoM-III) as a new research tool. We are interested in: 1) modelling the whole natural history of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases; 2) developing adequate and precise CoM-III which reflects relations between primary tumor and secondary distant metastases; 3) analyzing the CoM-III scope of application; 4) implementing the model as a software tool. Firstly, the CoM-III includes exponential tumor growth model as a system of determinate nonlinear and linear equations. Secondly, mathematical model corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for secondary distant metastases growth in patients with lymph nodes metastases; 3) ‘visible period’ for secondary distant metastases growth in patients with lymph nodes metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-III model and predictive software: a) detect different growth periods of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases; b) make forecast of the period of the distant metastases appearance in patients with lymph nodes metastases; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoM-III: the number of doublings for ‘non-visible’ and ‘visible’ growth period of secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of secondary distant metastases. The CoM-III enables, for the first time, to predict the whole natural history of primary tumor and secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-III describes correctly primary tumor and secondary distant metastases growth of IA, IIA, IIB, IIIB (T1-4N1-3M0) stages in patients with lymph nodes metastases (N1-3); b) facilitates the understanding of the appearance period and inception of secondary distant metastases.

Keywords: breast cancer, exponential growth model, mathematical model, primary tumor, secondary metastases, survival

Procedia PDF Downloads 302

Authors: Oscar Norman Nekesa, Yoshitaka Kajita

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Tom Mboya Street is a vital urban corridor within the spectrum of Nairobi city, it experiences high volumes of pedestrian and vehicular traffic. Despite past intervention measures to lessen this catastrophe, rates have remained high. This highlights significant safety concerns that need urgent attention. This study investigates the correlation and pedestrian accident predictability with significant independent variables using multiple linear regression to model to develop effective mobility management strategies for accident mitigation. The methodology involves collecting and analyzing data on pedestrian accidents and various related independent variables. Data sources include the National Transport and Safety Authority (NTSA), Kenya National Bureau of Statistics, and Nairobi City County records, covering five years. This study aims to investigate that traffic volumes (pedestrian and vehicle), Vehicular speed, human factors, illegal parking, policy issues, urban-land use, built environment, traffic signals conditions, inadequate lighting, and insufficient traffic control measures significantly have predictability with the rate of pedestrian accidents. Explanatory variables related to road design and geometry are significant in predictor models for the Tom Mboya Road link but less influential in junction along the 5 km stretch road models. The most impactful variable across all models was vehicular traffic flow. The study recommends infrastructural improvements, enhanced enforcement, and public awareness campaigns to reduce accidents and improve urban mobility. These insights can inform policy-making and urban planning to enhance pedestrian safety along the dense packed Tom Mboya Street and similar urban settings. The findings will inform evidence-based interventions to enhance pedestrian safety and improve urban mobility.

Keywords: multiple linear regression, urban mobility, traffic management, Nairobi, Tom Mboya street, infrastructure conditions., pedestrian safety, correlation and prediction

Procedia PDF Downloads 25

Authors: Vaidehi Murarka, Sneha Mehta, Dishant Upadhyay

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Our project topic is “Alphabet Recognition using pixel probability distribution”. The project uses techniques of Image Processing and Machine Learning in Computer Vision. Alphabet recognition is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files etc. Alphabet Recognition based OCR application is sometimes used in signature recognition which is used in bank and other high security buildings. One of the popular mobile applications includes reading a visiting card and directly storing it to the contacts. OCR's are known to be used in radar systems for reading speeders license plates and lots of other things. The implementation of our project has been done using Visual Studio and Open CV (Open Source Computer Vision). Our algorithm is based on Neural Networks (machine learning). The project was implemented in three modules: (1) Training: This module aims “Database Generation”. Database was generated using two methods: (a) Run-time generation included database generation at compilation time using inbuilt fonts of OpenCV library. Human intervention is not necessary for generating this database. (b) Contour–detection: ‘jpeg’ template containing different fonts of an alphabet is converted to the weighted matrix using specialized functions (contour detection and blob detection) of OpenCV. The main advantage of this type of database generation is that the algorithm becomes self-learning and the final database requires little memory to be stored (119kb precisely). (2) Preprocessing: Input image is pre-processed using image processing concepts such as adaptive thresholding, binarizing, dilating etc. and is made ready for segmentation. “Segmentation” includes extraction of lines, words, and letters from the processed text image. (3) Testing and prediction: The extracted letters are classified and predicted using the neural networks algorithm. The algorithm recognizes an alphabet based on certain mathematical parameters calculated using the database and weight matrix of the segmented image.

Keywords: contour-detection, neural networks, pre-processing, recognition coefficient, runtime-template generation, segmentation, weight matrix

Procedia PDF Downloads 389

Authors: Mir Ahmad Lashteh Neshaei, Hamed Afsoos Biria, Ata Ghabraei, Mir Abdolhamid Mehrdad

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Awareness of effective land using issues in coastal area including protection of natural ecosystems and coastal environment due to the increasing of human life along the coast is of great importance. There are numerous valuable structures and heritages which are located in defence sites and waterfront area. Marine structures such as groins, sea walls and detached breakwaters are constructed in coast to improve the coast stability against bed erosion due to changing wave and climate pattern. Marine mechanisms and interaction with the shore protection structures need to be intensively studied. Groins are one of the most prominent structures that are used in shore protection to create a safe environment for coastal area by maintaining the land against progressive coastal erosion. The main structural function of a groin is to control the long shore current and littoral sediment transport. This structure can be submerged and provide the necessary beach protection without negative environmental impact. However, for submerged structures adopted for beach protection, the shoreline response to these structures is not well understood at present. Nowadays, modelling and computer simulation are used to assess beach morphology in the vicinity of marine structures to reduce their environmental impact. The objective of this study is to predict the beach morphology in the vicinity of submerged groins and comparison with non-submerged groins with focus on a part of the coast located in Dahane sar Sefidrood, Guilan province, Iran where serious coast erosion has occurred recently. The simulations were obtained using a one-line model which can be used as a first approximation of shoreline prediction in the vicinity of groins. The results of the proposed model are compared with field measurements to determine the shape of the coast. Finally, the results of the present study show that using submerged groins can have a good efficiency to control the beach erosion without causing severe environmental impact to the coast. The important outcome from this study can be employed in optimum designing of defence sites in the coastal cities to improve their efficiency in terms of re-using the heritage lands.

Keywords: submerged structures, groin, shore protective structures, coastal cities

Procedia PDF Downloads 316

Authors: Iyad Al-Attar

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Air filters are widely used in gas turbines applications to ensure that the large mass (500kg/s) of clean air reach the compressor. The continuous demand of high availability and reliability has highlighted the critical role of air filter performance in providing enhanced air quality. In addition to being challenged with different environments [tropical, coastal, hot], gas turbines confront wide array of atmospheric contaminants with various concentrations and particle size distributions that would lead to performance degradation and components deterioration. Therefore, the role of air filters is of a paramount importance since fouled compressor can reduce power output and availability of the gas turbine to over 70 % throughout operation. Consequently, accurate filter performance prediction is critical tool in their selection considering their role in minimizing the economic impact of outages. In fact, actual performance of Efficient Particulate Air [EPA] filters used in gas turbine tend to deviate from the performance predicted by laboratory results. This experimental work investigates the initial pressure drop and fractional efficiency curves of full-scale pleated V-shaped EPA filters used globally in gas turbine. The investigation involved examining the effect of different operational conditions such as flow rates [500 to 5000 m3/h] and design parameters such as pleat count [28, 30, 32 and 34 pleats per 100mm]. This experimental work has highlighted the underlying reasons behind the reduction in filter permeability due to the increase of flow rates and pleat density. The reasons, which led to surface area losses of filtration media, are due to one or combination of the following effects: pleat-crowding, deflection of the entire pleated panel, pleat distortion at the corner of the pleat and/or filtration medium compression. This paper also demonstrates that the effect of increasing the flow rate has more pronounced effect on filter performance compared to pleating density. This experimental work suggests that a valid comparison of the pleat densities should be based on the effective surface area, namely, the area that participates in the filtration process, and not the total surface area the pleat density provides. Throughout this study, optimal pleat count that satisfies both initial pressure drop and efficiency requirements may not have necessarily existed.

Keywords: filter efficiency, EPA Filters, pressure drop, permeability

Procedia PDF Downloads 239

Authors: Adriana Sosa, Susana Rincon, Chérif Ben, Diana Cabañas, Juan E. Ruiz, Alejandro Zepeda

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The complex chemical composition (mixtures of ammonium and recalcitrant compounds) of the effluents from the chemical, pharmaceutical and petrochemical industries represents a challenge in their biological treatment. This treatment involves nitrification process that can suffer an inhibition due to the presence of aromatic compounds giving as a result the decrease of the process efficiency. The inhibitory effects on nitrification in the presence of aromatic compounds have already been studied; however a few studies have considered the presence of phenolic compounds in the form of mixtures, which is the form that they are present in real context. For this reason, we realized a kinetic study on the nitrifying process in the presence of different concentrations of a mixture of phenol, o-cresol, m-cresol and p-cresol (0 - 320 mg C/L) in a sequencing batch reactor (SBR). Firstly, the nitrifying process was evaluated in absence of the phenolic mixture (control 1) in a SBR with 2 L working volume and 176 mg/L of nitrogen of microbial protein. Total oxidation of initial ammonium (efficiency; ENH4+ of 100 %) to nitrate (nitrifying yield; YNO3- of 0.95) were obtained with specific rates of ammonium consumption (qN-NH4+) and nitrate production (qN-NO3-) (of 1.11 ± 0.04 h-1 and 0.67 h-1 ± 0.11 respectively. During the phase of acclimation with 40 mg C/L of the phenolic mixture, an inhibitory effect on the nitrifying process was observed, provoking a decrease in ENH4+ and YNO3- (11 and 54 % respectively) as well as in the specific rates (89 y 46 % respectively), being the ammonia oxidizing bacteria (BAO) the most affected. However, in the next cycles without the phenolic mixture (control 2), the nitrifying consortium was able to recover its nitrifying capacity (ENH4+ = 100% and YNO3-=0.98). Afterwards the SBR was fed with 10 mg C/L of the phenolic mixture, obtaining and ENH4+ of 100%, YNO3- and qN-NH4+ 0.62 ± 0.006 and 0.13 ± 0.004 respectively, while the qN-NO3- was 0.49 ± 0.007. Moreover, with the increase of the phenolic concentrations (10-160 mg C/L) and the number of cycles the nitrifying consortium was able to oxidize the ammonia with ENH4+ of 100 % and YNO3- close to 1. However a decrease in the values of the nitrification specific rates and increase in the oxidation in phenolic compounds (70 to 94%) were observed. Finally, in the presence of 320 mg C/L, the nitrifying consortium was able to simultaneously oxidize the ammonia (ENH4+= 100%) and the phenolic mixture (p-cresol>phenol>m-cresol>o-cresol) being the o-cresol the most recalcitrant compound. In all the experiments the use of a SBR allowed a respiratory adaptation of the consortium to oxidize the phenolic mixture achieving greater adaptation of the nitrite-oxidizing bacteria (NOB) than in the ammonia-oxidizing bacteria (AOB).

Keywords: cresol, inhibition, nitrification, phenol, sequencing batch reactor

Procedia PDF Downloads 361

Authors: Fekadu Gadissa, Kassahun Tesfaye, Kifle Dagne, Mulatu Geleta

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‘Ethiopian dinich’ also called ‘Ethiopian potato’ is one of the economically important ‘orphan’ edible tuber crops indigenous to Ethiopia. We evaluated the morphological and agronomic traits performances of 174 samples from Ethiopia at multiple locations using 12 qualitative and 16 quantitative traits, recorded at the correct growth stages. We observed several morphotypes and phenotypic variations for qualitative traits along with a wide range of mean performance values for all quantitative traits. Analysis of variance for each quantitative trait showed a highly significant (p<0.001) variation among the collections with eventually non-significant variation for environment-traits interaction for all but flower length. A comparatively high phenotypic and genotypic coefficient of variation was observed for plant height, days to flower initiation, days to 50% flowering and tuber number per hill. Moreover, the variability and coefficients of variation due to genotype-environment interaction was nearly zero for all the traits except flower length. High genotypic coefficients of variation coupled with a high estimate of broad sense heritability and high genetic advance as a percent of collection mean were obtained for tuber weight per hill, number of primary branches per plant, tuber number per hill and number of plants per hill. Association of tuber yield per hectare of land showed a large magnitude of positive phenotypic and genotypic correlation with those traits. Principal components analysis revealed 76% of the total variation for the first six principal axes with high factor loadings again from tuber number per hill, number of primary branches per plant and tuber weight. The collections were grouped into four clusters with the weak region (zone) of origin based pattern. In general, there is high genetic-based variability for ‘Ethiopian dinich’ improvement and conservation. DNA based markers are recommended for further genetic diversity estimation for use in breeding and conservation.

Keywords: agro-morphological traits, Ethiopian dinich, genetic diversity, variance components

Procedia PDF Downloads 190

Authors: Siti Aisya Gany, Swee Ching Tan, Sook Yee Gan

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Diminished antioxidant defense or increased production of reactive oxygen species in the biological system can result in oxidative stress which may lead to various neurodegenerative diseases including Alzheimer’s disease (AD). Microglial activation also contributes to the progression of AD by producing several pro-inflammatory cytokines, nitric oxide (NO), and prostaglandin E2 (PGE2). Oxidative stress and inflammation have been reported to be possible pathophysiological mechanisms underlying AD. In addition, the cholinergic hypothesis postulates that memory impairment in patient with AD is also associated with the deficit of cholinergic function in the brain. Although a number of drugs have been approved for the treatment of AD, most of these synthetic drugs have diverse side effects and yield relatively modest benefits. Marine algae have great potential in pharmaceutical and biomedical applications as they are valuable sources of bioactive properties such as anti-coagulation, anti-microbial, anti-oxidative, anti-cancer and anti-inflammatory. Hence, this study aimed to provide an overview of the properties of Malaysian seaweeds (Padina australis, Sargassum polycystum and Caulerpa racemosa) in inhibiting oxidative stress, neuroinflammation and cholinesterase enzymes. All tested samples significantly exhibit potent DPPH and moderate Superoxide anion radical scavenging ability (P<0.05). Hexane and methanol extracts of S. polycystum exhibited the most potent radical scavenging ability with IC50 values of 0.1572 ± 0.004 mg/ml and 0.8493 ± 0.02 for DPPH and ABTS assays, respectively. Hexane extract of C. racemosa gave the strongest superoxide radical inhibitory effect (IC50 of 0.3862± 0.01 mg/ml). Most seaweed extracts significantly inhibited the production of cytokine (IL-6, IL-1 β, TNFα) and NO in a concentration-dependent manner without causing significant cytotoxicity to the lipopolysaccharide (LPS)-stimulated microglia cells (P<0.05). All extracts suppressed cytokine and NO level by more than 80% at the concentration of 0.4mg/ml. In addition, C. racemosa and S. polycystum also showed anti-acetylcholinesterase activities with the IC50 values ranging from 0.086-0.115 mg/ml. Moreover, C. racemosa and P. australis were also found to be active against butyrylcholinesterase with IC50 values ranging from 0.118-0.287 mg/ml.

Keywords: anti-cholinesterase, anti-oxidative, neuroinflammation, seaweeds

Procedia PDF Downloads 663

Authors: Swati Tomar, Sunil Kumar Gupta

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Anammox is a promising and cost effective alternative to conventional treatment systems that facilitates direct oxidation of ammonium nitrogen under anaerobic conditions with nitrite as an electron acceptor without addition of any external carbon sources. The present study investigates the process kinetics of laboratory scale anammox hybrid reactor (AHR) which combines the dual advantages of attached and suspended growth. The performance & behaviour of AHR was studied under varying hydraulic retention time (HRTs) and nitrogen loading rate (NLRs). The experimental unit consisted of 4 numbers of 5L capacity anammox hybrid reactor inoculated with mixed seed culture containing anoxic and activated sludge. Pseudo steady state (PSS) ammonium and nitrite removal efficiencies of 90.6% and 95.6%, respectively, were achieved during acclimation phase. After establishment of PSS, the performance of AHR was monitored at seven different HRTs of 3.0, 2.5, 2.0, 1.5, 1.0, 0.5 and 0.25 d with increasing NLR from 0.4 to 4.8 kg N/m3d. The results showed that with increase in NLR and decrease in HRT (3.0 to 0.25 d), AHR registered appreciable decline in nitrogen removal efficiency from 92.9% to 67.4 %, respectively. The HRT of 2.0 d was considered optimal to achieve substantial nitrogen removal of 89%, because on further decrease in HRT below 1.5 days, remarkable decline in the values of nitrogen removal efficiency were observed. Analysis of data indicated that attached growth system contributes an additional 15.4 % ammonium removal and reduced the sludge washout rate (additional 29% reduction). This enhanced performance may be attributed to 25% increase in sludge retention time due to the attached growth media. Three kinetic models, namely, first order, Monod and Modified Stover-Kincannon model were applied to assess the substrate removal kinetics of nitrogen removal in AHR. Validation of the models were carried out by comparing experimental set of data with the predicted values obtained from the respective models. For substrate removal kinetics, model validation revealed that Modified Stover-Kincannon is most precise (R2=0.943) and can be suitably applied to predict the kinetics of nitrogen removal in AHR. Lawrence and McCarty model described the kinetics of bacterial growth. The predicted value of yield coefficient and decay constant were in line with the experimentally observed values.

Keywords: anammox, kinetics, modelling, nitrogen removal, sludge wash out rate, AHR

Procedia PDF Downloads 316

Authors: Desplanches Maxime

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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

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Authors: Liliana Rusu

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The goal of the proposed work is to provide a more comprehensive picture of the wind and wave climate in the Romanian nearshore, using the results provided by numerical models. The Romanian coastal environment is located in the western side of the Black Sea, the more energetic part of the sea, an area with heavy maritime traffic and various offshore operations. Information about the wind and wave climate in the Romanian waters is mainly based on observations at Gloria drilling platform (70 km from the coast). As regards the waves, the measurements of the wave characteristics are not so accurate due to the method used, being also available for a limited period. For this reason, the wave simulations that cover large temporal and spatial scales represent an option to describe better the wave climate. To assess the wind climate in the target area spanning 1992–2016, data provided by the NCEP-CFSR (U.S. National Centers for Environmental Prediction - Climate Forecast System Reanalysis) and consisting in wind fields at 10m above the sea level are used. The high spatial and temporal resolution of the wind fields is good enough to represent the wind variability over the area. For the same 25-year period, as considered for the wind climate, this study characterizes the wave climate from a wave hindcast data set that uses NCEP-CFSR winds as input for a model system SWAN (Simulating WAves Nearshore) based. The wave simulation results with a two-level modelling scale have been validated against both in situ measurements and remotely sensed data. The second level of the system, with a higher resolution in the geographical space (0.02°×0.02°), is focused on the Romanian coastal environment. The main wave parameters simulated at this level are used to analyse the wave climate. The spatial distributions of the wind speed, wind direction and the mean significant wave height have been computed as the average of the total data. As resulted from the amount of data, the target area presents a generally moderate wave climate that is affected by the storm events developed in the Black Sea basin. Both wind and wave climate presents high seasonal variability. All the results are computed as maps that help to find the more dangerous areas. A local analysis has been also employed in some key locations corresponding to highly sensitive areas, as for example the main Romanian harbors.

Keywords: numerical simulations, Romanian nearshore, waves, wind

Procedia PDF Downloads 344

Authors: Andleeb Zahra, Itrat Rubab, Sumaira Malik, Amina Khan, Muhammad Jawad Khan, M. Qaiser Fatmi

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Oral squamous cell carcinoma (OSCC) is one of the most common cancers worldwide. Recent studies have highlighted the role of miRNA in disease pathology, indicating its potential use in an early diagnostic tool. miRNAs are small, double stranded, non-coding RNAs that regulate gene expression by deregulating mRNAs. miRNAs play important roles in modifying various cellular processes such as cell growth, differentiation, apoptosis, and immune response. Dis-regulated expression of miRNAs is known to affect the cell growth, and this may function as tumor suppressors or oncogenes in various cancers. Objectives: The main objectives of this study were to characterize the extracellular miRNAs involved in oral cancer (OC) to assist early detection of cancer as well as to propose a list of genes that can potentially be used as biomarkers of OC. We used gene expression data by microarrays already available in literature. Materials and Methods: In the first step, a total of 318 miRNAs involved in oral carcinoma were shortlisted followed by the prediction of their target genes. Simultaneously, the differentially expressed genes (DEGs) of oral carcinoma from all experiments were identified. The common genes between lists of DEGs of OC based on experimentally proven data and target genes of each miRNA were identified. These common genes are the targets of specific miRNA, which is involved in OC. Finally, a list of genes was generated which may be used as biomarker of OC. Results and Conclusion: In results, we included some of pathways in cancer to show the change in gene expression under the control of specific miRNA. Ingenuity pathway analysis (IPA) provided a list of major biomarkers like CDH2, CDK7 and functional enrichment analysis identified the role of miRNA in major pathways like cell adhesion molecules pathway affected by cancer. We observed that at least 25 genes are regulated by maximum number of miRNAs, and thereby, they can be used as biomarkers of OC. To better understand the role of miRNA with respect to their target genes further experiments are required, and our study provides a platform to better understand the miRNA-OC relationship at genomics level.

Keywords: biomarkers, gene expression, miRNA, oral carcinoma

Procedia PDF Downloads 375

Authors: Mariangela Viviani, Daniele Germano, Simone Colace, Agostino Forestiero, Giuseppe Papuzzo, Sara Laurita

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Nowadays, people spend most of their time in closed environments, in offices, or at home. Therefore, secure and highly livable environmental conditions are needed to reduce the probability of aerial viruses spreading. Also, to lower the human impact on the planet, it is important to reduce energy consumption. Heating, Ventilation, and Air Conditioning (HVAC) systems account for the major part of energy consumption in buildings [1]. Devising systems to control and regulate the airflow is, therefore, essential for energy efficiency. Moreover, an optimal setting for thermal comfort and air quality is essential for people’s well-being, at home or in offices, and increases productivity. Thanks to the features of Artificial Intelligence (AI) tools and techniques, it is possible to design innovative systems with: (i) Improved monitoring and prediction accuracy; (ii) Enhanced decision-making and mitigation strategies; (iii) Real-time air quality information; (iv) Increased efficiency in data analysis and processing; (v) Advanced early warning systems for air pollution events; (vi) Automated and cost-effective m onitoring network; and (vii) A better understanding of air quality patterns and trends. We propose AIR SAFE, an IoT-based infrastructure designed to optimize air quality and thermal comfort in indoor environments leveraging AI tools. AIR SAFE employs a network of smart sensors collecting indoor and outdoor data to be analyzed in order to take any corrective measures to ensure the occupants’ wellness. The data are analyzed through AI algorithms able to predict the future levels of temperature, relative humidity, and CO₂ concentration [2]. Based on these predictions, AIR SAFE takes actions, such as opening/closing the window or the air conditioner, to guarantee a high level of thermal comfort and air quality in the environment. In this contribution, we present the results from the AI algorithm we have implemented on the first s et o f d ata c ollected i n a real environment. The results were compared with other models from the literature to validate our approach.

Keywords: air quality, internet of things, artificial intelligence, smart home

Procedia PDF Downloads 93

Authors: Zeenat Rupawalla, Nicole Robinson, Susanne Schmidt, Sijie Li, Selina Carruthers, Elodie Buisset, John Roles, Ben Hankamer, Juliane Wolf

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Agriculture has radically changed the global biogeochemical cycle of nitrogen (N). Fossil fuel-enabled synthetic N-fertiliser is a foundation of modern agriculture but applied to soil crops only use about half of it. To address N-pollution from cropping and the large carbon and energy footprint of N-fertiliser synthesis, new technologies delivering enhanced energy efficiency, decarbonisation, and a circular nutrient economy are needed. We characterised algae fertiliser (AF) as an alternative to synthetic N-fertiliser (SF) using empirical and modelling approaches. We cultivated microalgae in nutrient solution and modelled up-scaled production in nutrient-rich wastewater. Over four weeks, AF released 63.5% of N as ammonium and nitrate, and 25% of phosphorous (P) as phosphate to the growth substrate, while SF released 100% N and 20% P. To maximise crop N-use and minimise N-leaching, we explored AF and SF dose-response-curves with spinach in glasshouse conditions. AF-grown spinach produced 36% less biomass than SF-grown plants due to AF’s slower and linear N-release, while SF resulted in 5-times higher N-leaching loss than AF. Optimised blends of AF and SF boosted crop yield and minimised N-loss due to greater synchrony of N-release and crop uptake. Additional benefits of AF included greener leaves, lower leaf nitrate concentration, and higher microbial diversity and water holding capacity in the growth substrate. Life-cycle-analysis showed that replacing the most effective SF dosage with AF lowered the carbon footprint of fertiliser production from 2.02 g CO₂ (C-producing) to -4.62 g CO₂ (C-sequestering), with a further 12% reduction when AF is produced on wastewater. Embodied energy was lowest for AF-SF blends and could be reduced by 32% when cultivating algae on wastewater. We conclude that (i) microalgae offer a sustainable alternative to synthetic N-fertiliser in spinach production and potentially other crop systems, and (ii) microalgae biofertilisers support the circular nutrient economy and several sustainable development goals.

Keywords: bioeconomy, decarbonisation, energy footprint, microalgae

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Authors: Arunas Burinskas, Aurelija Burinskiene

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On average, ten percent of drugs - commercial products are not available in pharmacies due to shortage. The shortage event disbalance sales and requires a recovery period, which is too long. Therefore, one of the critical issues that pharmacies do not record potential sales transactions during shortage and recovery periods. The authors suggest estimating outliers during shortage and recovery periods. To shorten the recovery period, the authors suggest using average sales per sales day prediction, which helps to protect the data from being downwards or upwards. Authors use the outlier’s visualization method across different drugs and apply the Grubbs test for significance evaluation. The researched sample is 100 drugs in a one-month time frame. The authors detected that high demand variability products had outliers. Among analyzed drugs, which are commercial products i) High demand variability drugs have a one-week shortage period, and the probability of facing a shortage is equal to 69.23%. ii) Mid demand variability drugs have three days shortage period, and the likelihood to fall into deficit is equal to 34.62%. To avoid shortage events and minimize the recovery period, real data must be set up. Even though there are some outlier detection methods for drug data cleaning, they have not been used for the minimization of recovery period once a shortage has occurred. The authors use Grubbs’ test real-life data cleaning method for outliers’ adjustment. In the paper, the outliers’ adjustment method is applied with a confidence level of 99%. In practice, the Grubbs’ test was used to detect outliers for cancer drugs and reported positive results. The application of the Grubbs’ test is used to detect outliers which exceed boundaries of normal distribution. The result is a probability that indicates the core data of actual sales. The application of the outliers’ test method helps to represent the difference of the mean of the sample and the most extreme data considering the standard deviation. The test detects one outlier at a time with different probabilities from a data set with an assumed normal distribution. Based on approximation data, the authors constructed a framework for scaling potential sales and estimating outliers with Grubbs’ test method. The suggested framework is applicable during the shortage event and recovery periods. The proposed framework has practical value and could be used for the minimization of the recovery period required after the shortage of event occurrence.

Keywords: drugs, Grubbs' test, outlier, shortage event

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Authors: Lexi Li, Vanessa H. K. Pang

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This study aims to demonstrate how native and learner corpora can be used to enhance modal verb treatment in EFL textbooks in mainland China. It contributes to a corpus-informed and learner-centered design of grammar presentation in EFL textbooks that enhances the authenticity and appropriateness of textbook language for target learners. The linguistic focus is will, would, can, could, may, might, shall, should, must. The native corpus is the spoken component of BNC2014 (hereafter BNCS2014). The spoken part is chosen because pedagogical purpose of the textbooks is communication-oriented. Using the standard query option of CQPweb, 5% of each of the nine modals was sampled from BNCS2014. The learner corpus is the POS-tagged Ten-thousand English Compositions of Chinese Learners (TECCL). All the essays under the 'secondary school' section were selected. A series of five secondary coursebooks comprise the textbook corpus. All the data in both the learner and the textbook corpora are retrieved through the concordance functions of WordSmith Tools (version, 5.0). Data analysis was divided into two parts. The first part compared the patterns of modal verbs in the textbook corpus and BNC2014 with respect to distributional features, semantic functions, and co-occurring constructions to examine whether the textbooks reflect the authentic use of English. Secondly, the learner corpus was analyzed in terms of the use (distributional features, semantic functions, and co-occurring constructions) and the misuse (syntactic errors, e.g., she can sings*.) of the nine modal verbs to uncover potential difficulties that confront learners. The analysis of distribution indicates several discrepancies between the textbook corpus and BNCS2014. The first four most frequent modal verbs in BNCS2014 are can, would, will, could, while can, will, should, could are the top four in the textbooks. Most strikingly, there is an unusually high proportion of can (41.1%) in the textbooks. The results on different meanings shows that will, would and must are the most problematic. For example, for will, the textbooks contain 20% more occurrences of 'volition' and 20% less of 'prediction' than those in BNCS2014. Regarding co-occurring structures, the textbooks over-represented the structure 'modal +do' across the nine modal verbs. Another major finding is that the structure of 'modal +have done' that frequently co-occur with could, would, should, and must is underused in textbooks. Besides, these four modal verbs are the most difficult for learners, as the error analysis shows. This study demonstrates how the synergy of native and learner corpora can be harnessed to improve EFL textbook presentation of modal verbs in a way that textbooks can provide not only authentic language used in natural discourse but also appropriate design tailed for the needs of target learners.

Keywords: English as Foreign Language, EFL textbooks, learner corpus, modal verbs, native corpus

Procedia PDF Downloads 142

Authors: Zainab S. Ahmed, Mohammed S. Ali, Nadia A. Elshiekh, Sami Adam Ibrahim, Ghada M. El-Tayeb, Ahmed H. Elsadig, Rihab A. Omer, Sofia B. Mohamed

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Maple syrup urine (MSUD) is an autosomal recessive disease that causes a deficiency in the enzyme branched-chain alpha-keto acid (BCKA) dehydrogenase. The development of disease has been associated with SNPs in the DBT gene. Despite that, the computational analysis of SNPs in coding and noncoding and their functional impacts on protein level still remains unknown. Hence, in this study, we carried out a comprehensive in silico analysis of missense that was predicted to have a harmful influence on DBT structure and function. In this study, eight different in silico prediction algorithms; SIFT, PROVEAN, MutPred, SNP&GO, PhD-SNP, PANTHER, I-Mutant 2.0 and MUpo were used for screening nsSNPs in DBT including. Additionally, to understand the effect of mutations in the strength of the interactions that bind protein together the ELASPIC servers were used. Finally, the 3D structure of DBT was formed using Mutation3D and Chimera servers respectively. Our result showed that a total of 15 nsSNPs confirmed by 4 software (R301C, R376H, W84R, S268F, W84C, F276C, H452R, R178H, I355T, V191G, M444T, T174A, I200T, R113H, and R178C) were found damaging and can lead to a shift in DBT gene structure. Moreover, we found 7 nsSNPs located on the 2-oxoacid_dh catalytic domain, 5 nsSNPs on the E_3 binding domain and 3 nsSNPs on the Biotin Domain. So these nsSNPs may alter the putative structure of DBT’s domain. Furthermore, we detected all these nsSNPs are on the core residues of the protein and have the ability to change the stability of the protein. Additionally, we found W84R, S268F, and M444T have high significance, and they affected Leucine, Isoleucine, and Valine, which reduces or disrupt the function of BCKD complex, E2-subunit which the DBT gene encodes. In conclusion, based on our extensive in-silico analysis, we report 15 nsSNPs that have possible association with protein deteriorating and disease-causing abilities. These candidate SNPs can aid in future studies on Maple Syrup Urine Disease type II base in the genetic level.

Keywords: DBT gene, ELASPIC, in silico analysis, UCSF chimer

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Authors: John K. Avor, Choong-Koo Chang

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The transfer of electrical loads at power generation stations from Standby Auxiliary Transformer (SAT) to Unit Auxiliary Transformer (UAT) and vice versa is through a fast bus transfer scheme. Fast bus transfer is a time-critical application where the transfer process depends on various parameters, thus transfer schemes apply advance algorithms to ensure power supply reliability and continuity. In a nuclear power generation station, supply continuity is essential, especially for critical class 1E electrical loads. Bus transfers must, therefore, be executed accurately within 4 to 10 cycles in order to achieve safety system requirements. However, the main problem is that there are instances where transfer schemes scrambled due to inaccurate interpretation of key parameters; and consequently, have failed to transfer several critical loads from UAT to the SAT during main generator trip event. Although several techniques have been adopted to develop robust transfer schemes, a combination of Artificial Neural Network and Fuzzy Systems (Neuro-Fuzzy) has not been extensively used. In this paper, we apply the concept of Neuro-Fuzzy to determine plant operating mode and dynamic prediction of the appropriate bus transfer algorithm to be selected based on the first cycle of voltage information. The performance of Sequential Fast Transfer and Residual Bus Transfer schemes was evaluated through simulation and integration of the Neuro-Fuzzy system. The objective for adopting Neuro-Fuzzy approach in the bus transfer scheme is to utilize the signal validation capabilities of artificial neural network, specifically the back-propagation algorithm which is very accurate in learning completely new systems. This research presents a combined effect of artificial neural network and fuzzy systems to accurately interpret key bus transfer parameters such as magnitude of the residual voltage, decay time, and the associated phase angle of the residual voltage in order to determine the possibility of high speed bus transfer for a particular bus and the corresponding transfer algorithm. This demonstrates potential for general applicability to improve reliability of the auxiliary power distribution system. The performance of the scheme is implemented on APR1400 nuclear power plant auxiliary system.

Keywords: auxiliary power system, bus transfer scheme, fuzzy logic, neural networks, reliability

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Authors: Caroline Provost, Francois Dumont

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Production of insects for human and animal consumption is an increasingly important activity in Canada. Protein production is more efficient and less harmful to the environment using insect rearing compared to the impact of traditional livestock, poultry and fish farms. Insects are rich in essential amino acids, essential fatty acids and trace elements. Thus, insect-based products could be used as a food supplement for livestock and domestic animals and may even find their way into the diets of high performing athletes or fine dining. Nevertheless, several parameters remain to be determined to ensure efficient and profitable production that meet the potential of these sectors. This project proposes to improve the production processes, rearing diets and processing methods for three species with valuable gastronomic and nutritional potential: the common mealworms (Tenebrio molitor), the small mealworm (Alphitobius diaperinus), and the giant mealworm (Zophobas morio). The general objective of the project is to acquire specific knowledge for mass rearing of insects dedicated to animal and human consumption in order to respond to current market opportunities and meet a growing demand for these products. Mass rearing of the three species of mealworm was produced to provide the individuals needed for the experiments. Mealworms eat flour from different cereals (e.g. wheat, barley, buckwheat). These cereals vary in their composition (protein, carbohydrates, fiber, vitamins, antioxidant, etc.), but also in their purchase cost. Seven different diets were compared to optimize the yield of the rearing. Diets were composed of cereal flour (e.g. wheat, barley) and were either mixed or left alone. Female fecundity, larvae mortality and growing curves were observed. Some flour diets have positive effects on female fecundity and larvae performance while each mealworm was found to have specific diet requirements. Trade-offs between mealworm performance and costs need to be considered. Experiments on the effect of flour composition on several parameters related to performance and nutritional and gastronomic value led to the identification of a more appropriate diet for each mealworm.

Keywords: mass rearing, mealworm, human consumption, diet

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Authors: Saeed Farivar, Mohsen Kahrom

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The purpose of this work is to develop a physical simulation model for the purpose of studying the effect of various design parameters on the performance of packaged-liquid chillers. This paper presents a steady-state model for predicting the performance of package-Liquid chiller over a wide range of operation condition. The model inputs are inlet conditions; geometry and output of model include system performance variable such as power consumption, coefficient of performance (COP) and states of refrigerant through the refrigeration cycle. A computer model that simulates the steady-state cyclic performance of a vapor compression chiller is developed for the purpose of performing detailed physical design analysis of actual industrial chillers. The model can be used for optimizing design and for detailed energy efficiency analysis of packaged liquid chillers. The simulation model takes into account presence of all chiller components such as compressor, shell-and-tube condenser and evaporator heat exchangers, thermostatic expansion valve and connection pipes and tubing’s by thermo-hydraulic modeling of heat transfer, fluids flow and thermodynamics processes in each one of the mentioned components. To verify the validity of the developed model, a 7.5 USRT packaged-liquid chiller is used and a laboratory test stand for bringing the chiller to its standard steady-state performance condition is build. Experimental results obtained from testing the chiller in various load and temperature conditions is shown to be in good agreement with those obtained from simulating the performance of the chiller using the computer prediction model. An entropy-minimization-based optimization analysis is performed based on the developed analytical performance model of the chiller. The variation of design parameters in construction of shell-and-tube condenser and evaporator heat exchangers are studied using the developed performance and optimization analysis and simulation model and a best-match condition between the physical design and construction of chiller heat exchangers and its compressor is found to exist. It is expected that manufacturers of chillers and research organizations interested in developing energy-efficient design and analysis of compression chillers can take advantage of the presented study and its results.

Keywords: optimization, packaged liquid chiller, performance, simulation

Procedia PDF Downloads 278

Authors: Shreya Srivastava, Sushovan Ghosh, Sagnik Dey

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Aerosols directly affect Earth’s radiation budget by scattering and absorbing incoming solar radiation and outgoing terrestrial radiation. While the uncertainty in aerosol radiative forcing (ARF) has decreased over the years, it is still higher than that of greenhouse gas forcing, particularly in the South Asian region, due to high heterogeneity in their chemical properties. Understanding the Spatio-temporal heterogeneity of aerosol composition is critical in improving climate prediction. Studies using satellite data, in-situ and aircraft measurements, and models have investigated the Spatio-temporal variability of aerosol characteristics. In this study, we have taken aerosol data from Multi-angle Imaging Spectro-Radiometer (MISR) level-2 version 23 aerosol products retrieved at 4.4 km and radiation data from Clouds and the Earth’s Radiant Energy System (CERES, spatial resolution=1ox1o) for 21 years (2000-2021) over the Indian subcontinent. MISR aerosol product includes size and shapes segregated aerosol optical depth (AOD), Angstrom exponent (AE), and single scattering albedo (SSA). Additionally, 74 aerosol mixtures are included in version 23 data that is used for aerosol speciation. We have seasonally mapped aerosol optical and microphysical properties from MISR for India at quarter degrees resolution. Results show strong Spatio-temporal variability, with a constant higher value of AOD for the Indo-Gangetic Plain (IGP). The contribution of small-size particles is higher throughout the year, spatially during winter months. SSA is found to be overestimated where absorbing particles are present. The climatological map of short wave (SW) ARF at the top of the atmosphere (TOA) shows a strong cooling except in only a few places (values ranging from +2.5o to -22.5o). Cooling due to aerosols is higher in the absence of clouds. Higher negative values of ARF are found over the IGP region, given the high aerosol concentration above the region. Surface ARF values are everywhere negative for our study domain, with higher values in clear conditions. The results strongly correlate with AOD from MISR and ARF from CERES.

Keywords: aerosol Radiative forcing (ARF), aerosol composition, single scattering albedo (SSA), CERES

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Authors: Yutaro Kyuma, Sung-Jun Yoo, Kazuhide Ito

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A commuter bus remains important as a means to network public transportation between railway stations and terminals within cities. In some cases, the boarding time becomes longer, and the boarding rate tends to be higher corresponding to the development of urban cities. The interior environmental quality, e.g. temperature and air quality, in a commuter bus is relatively heterogeneous and complex compared to that of an indoor environment in buildings due to several factors: solar radiative heat – which comes from large-area windows –, inadequate ventilation rate caused by high density of commuters, and metabolic heat generation from travelers themselves. In addition to this, under conditions where many passengers ride in the enclosed space, contact and airborne infectious risk have attracted considerable attention in terms of public health. From this point of view, it is essential to develop the prediction method for assessment of interior environmental quality and infection risk in commuter bus cabins. In this study, we developed a numerical commuter bus model integrated with computer simulated persons to reproduce realistic indoor environment conditions with high occupancy during commuting. Here, computer simulated persons were newly designed considering different types of geometries, e.g., standing position, seating position, and individual differences. Here we conducted coupled computational fluid dynamics (CFD) analysis with radiative heat transfer analysis under steady state condition. Distributions of heterogeneous air flow patterns, temperature, and moisture surrounding the human body under some different ventilation system were analyzed by using CFD technique, and skin surface temperature distributions were analyzed using thermoregulation model that integrated into computer simulated person. Through these analyses, we discussed the interior environmental quality in specific commuter bus cabins. Further, inhaled air quality of each passenger was also analyzed. This study may have possibility to design the ventilation system in bus for improving thermal comfort of occupants.

Keywords: computational fluid dynamics, CFD, computer simulated person, CSP, contaminant, indoor environment, public health, ventilation

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Authors: Waheed Ahmad Safi, Shunichi Nakamura

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Concrete filled steel I-girder (CFIG) bridge was proposed and the bending and shear strength was confirmed by experiments. The area surrounded by the upper and lower flanges and the web is filled with concrete in CFIG, which is used to the intermediate support of a continuous girder. Three-dimensional finite element models were established to simulate the bending and shear behaviors of CFIG and to clarify the load transfer mechanism. Steel plates and filled concrete were modeled as a three-dimensional 8-node solid element and steel reinforcement bars as a three-dimensional 2-node truss element. The elements were mostly divided into the 50 x 50 mm mesh size. The non-linear stress-strain relation is assumed for concrete in compression including the softening effect after the peak, and the stress increases linearly for concrete in tension until concrete cracking but then decreases due to tension stiffening effect. The stress-strain relation for steel plates was tri-linear and that for reinforcements was bi-linear. The concrete and the steel plates were rigidly connected. The developed FEM model was applied to simulate and analysis the bending behaviors of the CFIG specimens. The vertical displacements and the strains of steel plates and the filled concrete obtained by FEM agreed very well with the test results until the yield load. The specimens collapsed when the upper flange buckled or the concrete spalled off. These phenomena cannot be properly analyzed by FEM, which produces a small discrepancy at the ultimate states. The FEM model was also applied to simulate and analysis the shear tests of the CFIG specimens. The vertical displacements and strains of steel and concrete calculated by FEM model agreed well with the test results. A truss action was confirmed by the FEM and the experiment, clarifying that shear forces were mainly resisted by the tension strut of the steel plate and the compression strut of the filled concrete acting in the diagonal direction. A trail design with the CFIG was carried out for a four-span continuous highway bridge and the design method was established. Construction cost was estimated about 12% lower than that of a conventional steel I-section girder.

Keywords: concrete filled steel I-girder, bending strength, FEM, limit states design, steel I-girder, shear strength

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Authors: E. Ghoneim, C. Narron, I. Iqbal, I. Hassan, E. Hammam

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The scarcity of water is becoming a more prominent threat, especially in areas that are already arid in nature. Although the Kingdom of Saudi Arabia (KSA) is an arid country, its southwestern region offers a high variety of botanical landscapes, many of which are wooded forests, while the eastern and northern regions offer large areas of groundwater irrigated farmlands. At present, some parts of KSA, including forests and farmlands, have witnessed protracted and severe drought due to change in rainfall pattern as a result of global climate change. Such prolonged drought that last for several consecutive years is expected to cause deterioration of forested and pastured lands as well as cause crop failure in the KSA (e.g., wheat yield). An analysis to determine vegetation drought vulnerability and severity during the growing season (September-April) over a fourteen year period (2000-2014) in KSA was conducted using MODIS Terra imagery. The Vegetation Condition Index (VCI), derived from the Normalized Difference Vegetation Index (NDVI), and the Temperature Condition Index (TCI), derived from the Land Surface Temperature (LST) data was extracted from MODIS Terra Images. The VCI and TCI were then combined to compute the Vegetation Health Index (VHI). The VHI revealed the overall vegetation health for the area under investigation. A preliminary outcome of the modeled VHI over KSA, using averaged monthly vegetation data over a 14-year period, revealed that the vegetation health condition is deteriorating over time in both naturally vegetated areas and irrigated farmlands. The derived drought map for KSA indicates that both extreme and severe drought occurrences have considerably increased over the same study period. Moreover, based on the cumulative average of drought frequency in each governorate of KSA it was determined that Makkah and Jizan governorates to the east and southwest, witness the most frequency of extreme drought, whereas Tabuk to the northwest, exhibits the less extreme drought frequency. Areas where drought is extreme or severe would most likely have negative influences on agriculture, ecosystems, tourism, and even human welfare. With the drought risk map the kingdom could make informed land management decisions including were to continue with agricultural endeavors and protect forested areas and even where to develop new settlements.

Keywords: drought, vegetation health condition, TCI, Saudi Arabia

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Authors: Sourabh Jain, Parul Madan

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Traffic noise pollution has become a challenging problem for all metro cities of India due to rapid urbanization, growing population and rising number of vehicles and transport development. In Delhi the prime source of noise pollution is vehicular traffic. In Delhi it is found that the ambient noise level (Leq) is exceeding the standard permissible value at all the locations. Noise barriers or enclosures are definitely useful in obtaining effective deduction of traffic noise disturbances in urbanized areas. US’s Federal Highway Administration Model (FHWA) and Calculation of Road Traffic Noise (CORTN) of UK are used to develop spread sheets for noise prediction. Spread sheets are also developed for evaluating effectiveness of existing boundary walls abutting houses in mitigating noise, redesigning them as noise barriers. Study was also carried out to examine the changes in noise level due to designed noise barrier by using both models FHWA and CORTN respectively. During the collection of various data it is found that receivers are located far away from road at Rithala and Moolchand sites and hence extra barrier height needed to meet prescribed limits was less as seen from calculations and most of the noise diminishes by propagation effect.On the basis of overall study and data analysis, it is concluded that FHWA and CORTN models under estimate noise levels. FHWA model predicted noise levels with an average percentage error of -7.33 and CORTN predicted with an average percentage error of -8.5. It was observed that at all sites noise levels at receivers were exceeding the standard limit of 55 dB. It was seen from calculations that existing walls are reducing noise levels. Average noise reduction due to walls at Rithala was 7.41 dB and at Panchsheel was 7.20 dB and lower amount of noise reduction was observed at Friend colony which was only 5.88. It was observed from analysis that Friends colony sites need much greater height of barrier. This was because of residential buildings abutting the road. At friends colony great amount of traffic was observed since it is national highway. At this site diminishing of noise due to propagation effect was very less.As FHWA and CORTN models were developed in excel programme, it eliminates laborious calculations of noise. There was no reflection correction in FHWA models as like in CORTN model.

Keywords: IFHWA, CORTN, Noise Sources, Noise Barriers

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Authors: Tommaso Adamo, Gianpaolo Ghiani, Antonio Domenico Grieco, Emanuela Guerriero

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Batch production plants provide a wide range of scheduling problems. In pharmaceutical industries a batch process is usually described by a recipe, consisting of an ordering of tasks to produce the desired product. In this research work we focused on pharmaceutical production processes requiring the culture of a microorganism population (i.e. bacteria, yeasts or antibiotics). Several sources of uncertainty may influence the yield of the culture processes, including (i) low performance and quality of the cultured microorganism population or (ii) microbial contamination. For these reasons, robustness is a valuable property for the considered application context. In particular, a robust schedule will not collapse immediately when a cell of microorganisms has to be thrown away due to a microbial contamination. Indeed, a robust schedule should change locally in small proportions and the overall performance measure (i.e. makespan, lateness) should change a little if at all. In this research work we formulated a constraint programming optimization (COP) model for the robust planning of antibiotics production. We developed a discrete-time model with a multi-criteria objective, ordering the different criteria and performing a lexicographic optimization. A feasible solution of the proposed COP model is a schedule of a given set of tasks onto available resources. The schedule has to satisfy tasks precedence constraints, resource capacity constraints and time constraints. In particular time constraints model tasks duedates and resource availability time windows constraints. To improve the schedule robustness, we modeled the concept of (a, b) super-solutions, where (a, b) are input parameters of the COP model. An (a, b) super-solution is one in which if a variables (i.e. the completion times of a culture tasks) lose their values (i.e. cultures are contaminated), the solution can be repaired by assigning these variables values with a new values (i.e. the completion times of a backup culture tasks) and at most b other variables (i.e. delaying the completion of at most b other tasks). The efficiency and applicability of the proposed model is demonstrated by solving instances taken from Sanofi Aventis, a French pharmaceutical company. Computational results showed that the determined super-solutions are near-optimal.

Keywords: constraint programming, super-solutions, robust scheduling, batch process, pharmaceutical industries

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Authors: Jitendar Kumar Tiwari, Ajay Mandal, N. Sathish, A. K. Srivastava

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Since the last decade, graphene achieved great attention toward the progress of multifunction metal matrix composites, which are highly demanded in industries to develop energy-efficient systems. This study covers the two advanced aspects of the latest scientific endeavor, i.e., graphene as reinforcement in metallic materials and additive manufacturing (AM) as a processing technology. Herein, high-quality graphene and AlSi10Mg powder mechanically mixed by very low energy ball milling with 0.1 wt. % and 0.2 wt. % graphene. Mixed powder directly subjected to the powder bed fusion process, i.e., an AM technique to produce composite samples along with bare counterpart. The effects of graphene on porosity, microstructure, and mechanical properties were examined in this study. The volumetric distribution of pores was observed under X-ray computed tomography (CT). On the basis of relative density measurement by X-ray CT, it was observed that porosity increases after graphene addition, and pore morphology also transformed from spherical pores to enlarged flaky pores due to improper melting of composite powder. Furthermore, the microstructure suggests the grain refinement after graphene addition. The columnar grains were able to cross the melt pool boundaries in case of the bare sample, unlike composite samples. The smaller columnar grains were formed in composites due to heterogeneous nucleation by graphene platelets during solidification. The tensile properties get affected due to induced porosity irrespective of graphene reinforcement. The optimized tensile properties were achieved at 0.1 wt. % graphene. The increment in yield strength and ultimate tensile strength was 22% and 10%, respectively, for 0.1 wt. % graphene reinforced sample in comparison to bare counterpart while elongation decreases 20% for the same sample. The hardness indentations were taken mostly on the solid region in order to avoid the collapse of the pores. The hardness of the composite was increased progressively with graphene content. Around 30% of increment in hardness was achieved after the addition of 0.2 wt. % graphene. Therefore, it can be concluded that powder bed fusion can be adopted as a suitable technique to develop graphene reinforced AlSi10Mg composite. Though, some further process modification required to avoid the induced porosity after the addition of graphene, which can be addressed in future work.

Keywords: graphene, hardness, porosity, powder bed fusion, tensile properties

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