Search results for: micro scale parameters

Authors: Alberto Alfano, Sergio D’ambrosio, Darshankumar Parecha, Donatella Cimini, Chiara Schiraldi.

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The main objective of this study regards the setup of an efficient small-scale platform for the conversion of local renewable waste materials, such as whey, into added-value products, thereby reducing environmental impact and costs deriving from the disposal of processing waste products. The buffalo milk whey derived from the cheese-making process, called second cheese whey, is the main by-product of the dairy industry. Whey is the main and most polluting by-product obtained from cheese manufacturing consisting of lactose, lactic acid, proteins, and salts, making whey an added-value product. In Italy, and in particular, in the Campania region, soft cheese production needs a large volume of liquid waste, especially during late spring and summer. This project is part of a circular economy perspective focused on the conversion of potentially polluting and difficult to purify waste into a resource to be exploited, and it embodies the concept of the three “R”: reduce, recycle, and reuse. Special focus was paid to the production of health-promoting biomolecules and biopolymers, which may be exploited in different segments of the food and pharmaceutical industries. These biomolecules may be recovered through appropriate processes and reused in an attempt to obtain added value products. So, ultrafiltration and nanofiltration processes were performed to fractionate bioactive components starting from buffalo milk whey. In this direction, the present study focused on the implementation of a downstream process that converts waste generated from food and food processing industries into added value products with potential applications. Owing to innovative downstream and biotechnological processes, rather than a waste product may be considered a resource to obtain high added value products, such as food supplements (probiotics), cosmeceuticals, biopolymers, and recyclable purified water. Besides targeting gastrointestinal disorders, probiotics such as Lactobacilli have been reported to improve immunomodulation and protection of the host against infections caused by viral and bacterial pathogens. Interestingly, also inactivated microbial (probiotic) cells and their metabolic products, indicated as parabiotic and postbiotics, respectively, have a crucial role and act as mediators in the modulation of the host’s immune function. To boost the production of biomass (both viable and/or heat inactivated cells) and/or the synthesis of growth-related postbiotics, such as EPS, efficient and sustainable fermentation processes are necessary. Based on a “zero-waste” approach, wastes generated from local industries can be recovered and recycled to develop sustainable biotechnological processes to obtain probiotics as well as post and parabiotic, to be tested as bioactive compounds against gastrointestinal disorders. The results have shown it was possible to recover an ultrafiltration retentate with suitable characteristics to be used in skin dehydration, to perform films (i.e., packaging for food industries), or as a wound repair agent and a nanofiltration retentate to recover lactic acid and carbon sources (e.g., lactose, glucose..) used for microbial cultivation. On the side, the last goal is to obtain purified water that can be reused throughout the process. In fact, water reclamation and reuse provide a unique and viable opportunity to augment traditional water supplies, a key issue nowadays.

Keywords: biotech process, downstream process, probiotic growth, from waste to product, buffalo whey

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Authors: Roberta Martino, Viviana Ventre

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Every day we face choices whose consequences are deferred in time. These types of choices are the intertemporal choices and play an important role in the social, economic, and financial world. The Discounted Utility Model is the mathematical model of reference to calculate the utility of intertemporal prospects. The discount rate is the main element of the model as it describes how the individual perceives the indeterminacy of subsequent periods. Empirical evidence has shown a discrepancy between the behavior expected from the predictions of the model and the effective choices made from the decision makers. In particular, the term temporal inconsistency indicates those choices that do not remain optimal with the passage of time. This phenomenon has been described with hyperbolic models of the discount rate which, unlike the linear or exponential nature assumed by the discounted utility model, is not constant over time. This paper explores the problem of inconsistency by tracing the decision-making process through the concept of impatience. The degree of impatience and the degree of decrease of impatience are two parameters that allow to quantify the weight of emotional factors and cognitive limitations during the evaluation and selection of alternatives. In fact, although the theory assumes perfectly rational decision makers, behavioral finance and cognitive psychology have made it possible to understand that distortions in the decision-making process and emotional influence have an inevitable impact on the decision-making process. The degree to which impatience is diminished is the focus of the first part of the study. By comparing consistent and inconsistent preferences over time, it was possible to verify that some anomalies in the discounted utility model are a result of the combination of cognitive bias and emotional factors. In particular: the delay effect and the interval effect are compared through the concept of misperception of time; starting from psychological considerations, a criterion is proposed to identify the causes of the magnitude effect that considers the differences in outcomes rather than their ratio; the sign effect is analyzed by integrating in the evaluation of prospects with negative outcomes the psychological aspects of loss aversion provided by Prospect Theory. An experiment implemented confirms three findings: the greatest variation in the degree of decrease in impatience corresponds to shorter intervals close to the present; the greatest variation in the degree of impatience occurs for outcomes of lower magnitude; the variation in the degree of impatience is greatest for negative outcomes. The experimental phase was implemented with the construction of the hyperbolic factor through the administration of questionnaires constructed for each anomaly. This work formalizes the underlying causes of the discrepancy between the discounted utility model and the empirical evidence of preference reversal.

Keywords: decreasing impatience, discount utility model, hyperbolic discount, hyperbolic factor, impatience

Procedia PDF Downloads 103

Authors: Emmanuel O. Ezim, Idowu A. Olayinka, Michael Oladunjoye, Izuchukwu I. Obiadi

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Monitoring of reservoir properties prior to well placements and production is a requirement for optimisation and efficient oil and gas production. This is usually done using well log analyses and 3-D seismic, which are often prone to errors. However, 4-D (Time-lapse) seismic, incorporating numerous 3-D seismic surveys of the same field with the same acquisition parameters, which portrays the transient changes in the reservoir due to production effects over time, could be utilised because it generates better resolution. There is, however dearth of information on the applicability of this approach in the Niger Delta. This study was therefore designed to apply 4-D seismic, well-log and geologic data in monitoring of reservoirs in the EK field of the Niger Delta. It aimed at locating bypassed accumulations and ensuring effective reservoir management. The Field (EK) covers an area of about 1200km2 belonging to the early (18ma) Miocene. Data covering two 4-D vintages acquired over a fifteen-year interval were obtained from oil companies operating in the field. The data were analysed to determine the seismic structures, horizons, Well-to-Seismic Tie (WST), and wavelets. Well, logs and production history data from fifteen selected wells were also collected from the Oil companies. Formation evaluation, petrophysical analysis and inversion alongside geological data were undertaken using Petrel, Shell-nDi, Techlog and Jason Software. Well-to-seismic tie, formation evaluation and saturation monitoring using petrophysical and geological data and software were used to find bypassed hydrocarbon prospects. The seismic vintages were interpreted, and the amounts of change in the reservoir were defined by the differences in Acoustic Impedance (AI) inversions of the base and the monitor seismic. AI rock properties were estimated from all the seismic amplitudes using controlled sparse-spike inversion. The estimated rock properties were used to produce AI maps. The structural analysis showed the dominance of NW-SE trending rollover collapsed-crest anticlines in EK with hydrocarbons trapped northwards. There were good ties in wells EK 27, 39. Analysed wavelets revealed consistent amplitude and phase for the WST; hence, a good match between the inverted impedance and the good data. Evidence of large pay thickness, ranging from 2875ms (11420 TVDSS-ft) to about 2965ms, were found around EK 39 well with good yield properties. The comparison between the base of the AI and the current monitor and the generated AI maps revealed zones of untapped hydrocarbons as well as assisted in determining fluids movement. The inverted sections through EK 27, 39 (within 3101 m - 3695 m), indicated depletion in the reservoirs. The extent of the present non-uniform gas-oil contact and oil-water contact movements were from 3554 to 3575 m. The 4-D seismic approach led to better reservoir characterization, well development and the location of deeper and bypassed hydrocarbon reservoirs.

Keywords: reservoir monitoring, 4-D seismic, well placements, petrophysical analysis, Niger delta basin

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Authors: Christine F. Boos, Fernando M. Azevedo

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Electroencephalogram (EEG) is a record of the electrical activity of the brain that has many applications, such as monitoring alertness, coma and brain death; locating damaged areas of the brain after head injury, stroke and tumor; monitoring anesthesia depth; researching physiology and sleep disorders; researching epilepsy and localizing the seizure focus. Epilepsy is a chronic condition, or a group of diseases of high prevalence, still poorly explained by science and whose diagnosis is still predominantly clinical. The EEG recording is considered an important test for epilepsy investigation and its visual analysis is very often applied for clinical confirmation of epilepsy diagnosis. Moreover, this EEG analysis can also be used to help define the types of epileptic syndrome, determine epileptiform zone, assist in the planning of drug treatment and provide additional information about the feasibility of surgical intervention. In the context of diagnosis confirmation the analysis is made using long term EEG recordings with at least 24 hours long and acquired by a minimum of 24 electrodes in which the neurophysiologists perform a thorough visual evaluation of EEG screens in search of specific electrographic patterns called epileptiform discharges. Considering that the EEG screens usually display 10 seconds of the recording, the neurophysiologist has to evaluate 360 screens per hour of EEG or a minimum of 8,640 screens per long term EEG recording. Analyzing thousands of EEG screens in search patterns that have a maximum duration of 200 ms is a very time consuming, complex and exhaustive task. Because of this, over the years several studies have proposed automated methodologies that could facilitate the neurophysiologists’ task of identifying epileptiform discharges and a large number of methodologies used neural networks for the pattern classification. One of the differences between all of these methodologies is the type of input stimuli presented to the networks, i.e., how the EEG signal is introduced in the network. Five types of input stimuli have been commonly found in literature: raw EEG signal, morphological descriptors (i.e. parameters related to the signal’s morphology), Fast Fourier Transform (FFT) spectrum, Short-Time Fourier Transform (STFT) spectrograms and Wavelet Transform features. This study evaluates the application of these five types of input stimuli and compares the classification results of neural networks that were implemented using each of these inputs. The performance of using raw signal varied between 43 and 84% efficiency. The results of FFT spectrum and STFT spectrograms were quite similar with average efficiency being 73 and 77%, respectively. The efficiency of Wavelet Transform features varied between 57 and 81% while the descriptors presented efficiency values between 62 and 93%. After simulations we could observe that the best results were achieved when either morphological descriptors or Wavelet features were used as input stimuli.

Keywords: Artificial neural network, electroencephalogram signal, pattern recognition, signal processing

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Authors: Mitali Saha, Soma Das

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The fabrication of nanoscale materials for use in chemical sensing, biosensing and biological analyses has proven a promising avenue in the last few years. Cholesterol has aroused considerable interest in recent years on account of its being an important parameter in clinical diagnosis. There is a strong positive correlation between high serum cholesterol level and arteriosclerosis, hypertension, and myocardial infarction. Enzyme-based electrochemical biosensors have shown high selectivity and excellent sensitivity, but the enzyme is easily denatured during its immobilization procedure and its activity is also affected by temperature, pH, and toxic chemicals. Besides, the reproducibility of enzyme-based sensors is not very good which further restrict the application of cholesterol biosensor. It has been demonstrated that carbon nanotubes could promote electron transfer with various redox active proteins, ranging from cytochrome c to glucose oxidase with a deeply embedded redox center. In continuation of our earlier work on the synthesis and applications of carbon and metal based nanoparticles, we have reported here the synthesis of carbon nanotubes (CCNT) by burning coconut oil under insufficient flow of air using an oil lamp. The soot was collected from the top portion of the flame, where the temperature was around 6500C which was purified, functionalized and then characterized by SEM, p-XRD and Raman spectroscopy. The SEM micrographs showed the formation of tubular structure of CCNT having diameter below 100 nm. The XRD pattern indicated the presence of two predominant peaks at 25.20 and 43.80, which corresponded to (002) and (100) planes of CCNT respectively. The Raman spectrum (514 nm excitation) showed the presence of 1600 cm-1 (G-band) related to the vibration of sp2-bonded carbon and at 1350 cm-1 (D-band) responsible for the vibrations of sp3-bonded carbon. A nonenzymatic cholesterol biosensor was then fabricated on an insulating Teflon material containing three silver wires at the surface, covered by CCNT, obtained from coconut oil. Here, CCNTs worked as working as well as counter electrodes whereas reference electrode and electric contacts were made of silver. The dimensions of the electrode was 3.5 cm×1.0 cm×0.5 cm (length× width × height) and it is ideal for working with 50 µL volume like the standard screen printed electrodes. The voltammetric behavior of cholesterol at CCNT electrode was investigated by cyclic voltammeter and differential pulse voltammeter using 0.001 M H2SO4 as electrolyte. The influence of the experimental parameters on the peak currents of cholesterol like pH, accumulation time, and scan rates were optimized. Under optimum conditions, the peak current was found to be linear in the cholesterol concentration range from 1 µM to 50 µM with a sensitivity of ~15.31 μAμM−1cm−2 with lower detection limit of 0.017 µM and response time of about 6s. The long-term storage stability of the sensor was tested for 30 days and the current response was found to be ~85% of its initial response after 30 days.

Keywords: coconut oil, CCNT, cholesterol, biosensor

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Authors: Ahmad Saadiq, Neeraj Sahu

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Sediment, which comprises of solid particles of mineral and organic material are transported by water. In river systems, the amount of sediment transported is controlled by both the transport capacity of the flow and the supply of sediment. The transport of sediment in rivers is important with respect to pollution, channel navigability, reservoir ageing, hydroelectric equipment longevity, fish habitat, river aesthetics and scientific interests. The sediment load transported in a river is a very complex hydrological phenomenon. Hence, sediment transport has attracted the attention of engineers from various aspects, and different methods have been used for its estimation. So, several experimental equations have been submitted by experts. Though the results of these methods have considerable differences with each other and with experimental observations, because the sediment measures have some limits, these equations can be used in estimating sediment load. In this present study, two black box models namely, an SRC (Sediment Rating Curve) and ANN (Artificial Neural Network) are used in the simulation of the suspended sediment load. The study is carried out for Seonath subbasin. Seonath is the biggest tributary of Mahanadi river, and it carries a vast amount of sediment. The data is collected for Jondhra hydrological observation station from India-WRIS (Water Resources Information System) and IMD (Indian Meteorological Department). These data include the discharge, sediment concentration and rainfall for 10 years. In this study, sediment load is estimated from the input parameters (discharge, rainfall, and past sediment) in various combination of simulations. A sediment rating curve used the water discharge to estimate the sediment concentration. This estimated sediment concentration is converted to sediment load. Likewise, for the application of these data in ANN, they are normalised first and then fed in various combinations to yield the sediment load. RMSE (root mean square error) and R² (coefficient of determination) between the observed load and the estimated load are used as evaluating criteria. For an ideal model, RMSE is zero and R² is 1. However, as the models used in this study are black box models, they don’t carry the exact representation of the factors which causes sedimentation. Hence, a model which gives the lowest RMSE and highest R² is the best model in this study. The lowest values of RMSE (based on normalised data) for sediment rating curve, feed forward back propagation, cascade forward back propagation and neural network fitting are 0.043425, 0.00679781, 0.0050089 and 0.0043727 respectively. The corresponding values of R² are 0.8258, 0.9941, 0.9968 and 0.9976. This implies that a neural network fitting model is superior to the other models used in this study. However, a drawback of neural network fitting is that it produces few negative estimates, which is not at all tolerable in the field of estimation of sediment load, and hence this model can’t be crowned as the best model among others, based on this study. A cascade forward back propagation produces results much closer to a neural network model and hence this model is the best model based on the present study.

Keywords: artificial neural network, Root mean squared error, sediment, sediment rating curve

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Authors: Sheikh Nawaz Ali, Pratima Pandey, P. Morthekai, Jyotsna Dubey, Md. Firoze Quamar

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The high mountain glaciers are one of the most sensitive recorders of climate changes, because they have the tendency to respond to the combined effect of snow fall and temperature. The Himalayan glaciers have been studied with a good pace during the last decade. However, owing to its large ecological diversity and geographical vividness, major part of the Indian Himalaya is uninvestigated, and hence the palaeoclimatic patterns as well as the chronology of past glaciations in particular remain controversial for the entire Indian Himalayan transect. Although the Himalayan glaciers are nourished by two important climatic systems viz. the southwest summer monsoon and the mid-latitude westerlies, however, the influence of these systems is yet to be understood. Nevertheless, existing chronology (mostly exposure ages) indicate that irrespective of the geographical position, glaciers seem to grow during enhanced Indian summer monsoon (ISM). The Himalayan mountain glaciers are referred to the third pole or water tower of Asia as they form a huge reservoir of the fresh water supplies for the Asian countries. Mountain glaciers are sensitive probes of the local climate, and, thus, they present an opportunity and a challenge to interpret climates of the past as well as to predict future changes. The principle object of all the palaeoclimatic studies is to develop a futuristic models/scenario. However, it has been found that the glacial chronologies bracket the major phases of climatic events only, and other climatic proxies are sparse in Himalaya. This is the reason that compilation of data for rapid climatic change during the Holocene shows major gaps in this region. The sedimentation in proglacial lakes, conversely, is more continuous and, hence, can be used to reconstruct a more complete record of past climatic variability that is modulated by changing ice volume of the valley glacier. The Himalayan region has numerous proglacial lacustrine deposits formed during the late Quaternary period. However, there are only few such deposits which have been studied so far. Therefore, this is the high time when efforts have to be made to systematically map the moraines located in different climatic zones, reconstruct the local and regional moraine stratigraphy and use multiple dating techniques to bracket the events of glaciation. Besides this, emphasis must be given on carrying multiproxy studies on the lacustrine sediments that will provide a high resolution palaeoclimatic data from the alpine region of the Himalaya. Although the Himalayan glaciers fluctuated in accordance with the changing climatic conditions (natural forcing), however, it is too early to arrive at any conclusion. It is very crucial to generate multiproxy data sets covering wider geographical and ecological domains taking into consideration multiple parameters that directly or indirectly influence the glacier mass balance as well as the local climate of a region.

Keywords: glacial chronology, palaeoclimate, multiproxy, Himalaya

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Authors: Andreas Schomburg, Claire Le Bayon, Claire Guenat, Philip Brunner

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Numerous river restoration projects have been established in Switzerland in recent years after decades of human activity in floodplains. The success of restoration projects in terms of biodiversity and ecosystem functions largely depend on the development of the floodplain soil system. Plants and earthworms as ecosystem engineers are known to be able to build up a stable soil structure by incorporating soil organic matter into the soil matrix that creates water stable soil aggregates. Their engineering efficiency however largely depends on changing soil properties and frequent floods along an evolutive floodplain transect. This study, therefore, aims to quantify the effect of flood frequency and duration as well as of physico-chemical soil parameters on plants’ and earthworms’ engineering efficiency. It is furthermore predicted that these influences may have a different impact on one of the engineers that leads to a varying contribution to aggregate formation within the floodplain transect. Ecosystem engineers were sampled and described in three different floodplain habitats differentiated according to the evolutionary stages of the vegetation ranging from pioneer to forest vegetation in a floodplain restored 15 years ago. In addition, the same analyses were performed in an embanked adjacent pasture as a reference for the pre-restored state. Soil aggregates were collected and analyzed for their organic matter quantity and quality using Rock Eval pyrolysis. Water level and discharge measurements dating back until 2008 were used to quantify the return period of major floods. Our results show an increasing amount of water stable aggregates in soil with increasing distance to the river and show largest values in the reference site. A decreasing flood frequency and the proportion of silt and clay in the soil texture explain these findings according to F values from one way ANOVA of a fitted mixed effect model. Significantly larger amounts of labile organic matter signatures were found in soil aggregates in the forest habitat and in the reference site that indicates a larger contribution of plants to soil aggregation in these habitats compared to the pioneer vegetation zone. Earthworms’ contribution to soil aggregation does not show significant differences in the floodplain transect, but their effect could be identified even in the pioneer vegetation with its large proportion of coarse sand in the soil texture and frequent inundations. These findings indicate that ecosystem engineers seem to be able to create soil aggregates even under unfavorable soil conditions and under frequent floods. A restoration success can therefore be expected even in ecosystems with harsh soil properties and frequent external disturbances.

Keywords: ecosystem engineers, flood frequency, floodplains, river restoration, rock eval pyrolysis, soil organic matter incorporation, soil structuration

Procedia PDF Downloads 269

Authors: Eashwar V. Somasundaram, Raoul R. Wadhwa, Jacob G. Scott

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The use of radiomics in measuring geometric properties of tumor images such as size, surface area, and volume has been invaluable in assessing cancer diagnosis, treatment, and prognosis. In addition to analyzing geometric properties, radiomics would benefit from measuring topological properties using persistent homology. Intuitively, features uncovered by persistent homology may correlate to tumor structural features. One example is necrotic cavities (corresponding to 2D topological features), which are markers of very aggressive tumors. We develop a data pipeline in R that clusters tumors images based on persistent homology is used to identify meaningful clinical distinctions between tumors and possibly new relationships not captured by established clinical categorizations. A preliminary analysis was performed on 16 Magnetic Resonance Imaging (MRI) breast tissue segments downloaded from the 'Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis' (I-SPY TRIAL or ISPY1) collection in The Cancer Imaging Archive. Each segment represents a patient’s breast tumor prior to treatment. The ISPY1 dataset also provided the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status data. A persistent homology matrix up to 2-dimensional features was calculated for each of the MRI segmentation. Wasserstein distances were then calculated between all pairwise tumor image persistent homology matrices to create a distance matrix for each feature dimension. Since Wasserstein distances were calculated for 0, 1, and 2-dimensional features, three hierarchal clusters were constructed. The adjusted Rand Index was used to see how well the clusters corresponded to the ER/PR/HER2 status of the tumors. Triple-negative cancers (negative status for all three receptors) significantly clustered together in the 2-dimensional features dendrogram (Adjusted Rand Index of .35, p = .031). It is known that having a triple-negative breast tumor is associated with aggressive tumor growth and poor prognosis when compared to non-triple negative breast tumors. The aggressive tumor growth associated with triple-negative tumors may have a unique structure in an MRI segmentation, which persistent homology is able to identify. This preliminary analysis shows promising results in the use of persistent homology on tumor imaging to assess the severity of breast tumors. The next step is to apply this pipeline to other tumor segment images from The Cancer Imaging Archive at different sites such as the lung, kidney, and brain. In addition, whether other clinical parameters, such as overall survival, tumor stage, and tumor genotype data are captured well in persistent homology clusters will be assessed. If analyzing tumor MRI segments using persistent homology consistently identifies clinical relationships, this could enable clinicians to use persistent homology data as a noninvasive way to inform clinical decision making in oncology.

Keywords: cancer biology, oncology, persistent homology, radiomics, topological data analysis, tumor imaging

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Authors: Muhammad Aji Fajari, Ririt Aprilin Sumarsono

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Particular instability of structural building under lateral load (e.g earthquake) will rise due to irregularity in vertical and horizontal direction as stated in SNI 03-1762-2012. The conventional slab has been considered for its less contribution in increasing the stability of the structure, except special slab system such as flat slab turned into account. In this paper, the analysis of flat slab system at Sequis Tower located in South Jakarta will be assessed its performance under earthquake. It consists of 6 floors of the basement where the flat slab system is applied. The flat slab system will be the main focus in this paper to be compared for its performance with conventional slab system under earthquake. Regarding the floor plan of Sequis Tower basement, re-entrant corner signed for this building is 43.21% which exceeded the allowable re-entrant corner is 15% as stated in ASCE 7-05 Based on that, the horizontal irregularity will be another concern for analysis, otherwise vertical irregularity does not exist for this building. Flat slab system is a system where the slabs use drop panel with shear head as their support instead of using beams. Major advantages of flat slab application are decreasing dead load of structure, removing beams so that the clear height can be maximized, and providing lateral resistance due to lateral load. Whilst, deflection at middle strip and punching shear are problems to be detail considered. Torsion usually appears when the structural member under flexure such as beam or column dimension is improper in ratio. Considering flat slab as alternative slab system will keep the collapse due to torsion down. Common seismic load resisting system applied in the building is a shear wall. Installation of shear wall will keep the structural system stronger and stiffer affecting in reduced displacement under earthquake. Eccentricity of shear wall location of this building resolved the instability due to horizontal irregularity so that the earthquake load can be absorbed. Performing linear dynamic analysis such as response spectrum and time history analysis due to earthquake load is suitable as the irregularity arise so that the performance of structure can be significantly observed. Utilization of response spectrum data for South Jakarta which PGA 0.389g is basic for the earthquake load idealization to be involved in several load combinations stated on SNI 03-1726-2012. The analysis will result in some basic seismic parameters such as period, displacement, and base shear of the system; besides the internal forces of the critical member will be presented. Predicted period of a structure under earthquake load is 0.45 second, but as different slab system applied in the analysis then the period will show a different value. Flat slab system will probably result in better performance for the displacement parameter compare to conventional slab system due to higher contribution of stiffness to the whole system of the building. In line with displacement, the deflection of the slab will result smaller for flat slab than a conventional slab. Henceforth, shear wall will be effective to strengthen the conventional slab system than flat slab system.

Keywords: conventional slab, flat slab, horizontal irregularity, response spectrum, shear wall

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Authors: Sibgha Noreen, Muhammad Salim Akhter, Seema Mahmood

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Salt stress is an abiotic stress that causes a heavy toll on growth and development and also reduces the productivity of arable and horticultural crops. Globally, a quarter of total arable land has fallen prey to this menace, and more is being encroached because of the usage of brackish water for irrigation purposes. Though barley is categorized as salt-tolerant crop, but cultivars show a wide genetic variability in response to it. In addressing salt stress, silicon nutrition would be a facile tool for enhancing salt tolerant to sustain crop production. A greenhouse study was conducted to evaluate the response of barley (Hordeum vulgare L.) cultivars to silicon nutrition under salt stress. The treatments included [(a) four barley cultivars (Jou-87, B-14002, B-14011, B-10008); (b) two salt levels (0, 200 mM, NaCl); and (c) two silicon levels (0, 200ppm, K2SiO3. nH2O), arranged in a factorial experiment in a completely randomized design with 16 treatments and repeated 4 times. Plants were harvested at 15 days after exposure to different experimental salinity and silicon foliar conditions. Results revealed that various physiological and biochemical attributes differed significantly (p<0.05) in response to different treatments and their interactive effects. Cultivar “B-10008” excelled in biological yield, chlorophyll constituents, antioxidant enzymes, and grain yield compared to other cultivars. The biological yield of shoot and root organs was reduced by 27.3 and 26.5 percent under salt stress, while it was increased by 14.5 and 18.5 percent by exogenous application of silicon over untreated check, respectively. The imposition of salt stress at 200 mM caused a reduction in total chlorophyll content, chl ‘a’ , ‘b’ and ratio a/b by 10.6,16.8,17.1 and 7.1, while spray of 200 ppm silicon improved the quantum of the constituents by 10.4,12.1,10.2,10.3 over untreated check, respectively. The quantum of free amino acids and protein content was enhanced in response to salt stress and the spray of silicon nutrients. The amounts of superoxide dismutase, catalases, peroxidases, hydrogen peroxide, and malondialdehyde contents rose to 18.1, 25.7, 28.1, 29.5, and 17.6 percent over non-saline conditions under salt stress. However, the values of these antioxidants were reduced in proportion to salt stress by 200 ppm silicon applied as rooting medium on barley crops. The salt stress caused a reduction in the number of tillers, number of grains per spike, and 100-grain weight to the amount of 29.4, 8.6, and 15.8 percent; however, these parameters were improved by 7.1, 10.3, and 9.6 percent by foliar spray of silicon over untreated crop, respectively. It is concluded that the barley cultivar “B-10008” showed greater tolerance and adaptability to saline conditions. The yield of barley crops could be potentiated by a foliar spray of 200 ppm silicon at the vegetative growth stage under salt stress.

Keywords: salt stress, silicon nutrition, chlorophyll constituents, antioxidant enzymes, barley crop

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Authors: Aleksandra Zieminska-Stolarska, Ireneusz Zbicinski

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Introduction: The objective of the present work was to develop and validate a 3D CFD numerical model for simulating flow through 17 kilometers long dam reservoir of a complex bathymetry. In contrast to flowing waters, dam reservoirs were not emphasized in the early years of water quality modeling, as this issue has never been the major focus of urban development. Starting in the 1970s, however, it was recognized that natural and man-made lakes are equal, if not more important than estuaries and rivers from a recreational standpoint. The Sulejow Reservoir (Central Poland) was selected as the study area as representative of many lowland dam reservoirs and due availability of a large database of the ecological, hydrological and morphological parameters of the lake. Method: 3D, 2-phase and 1-phase CFD models were analysed to determine hydrodynamics in the Sulejow Reservoir. Development of 3D, 2-phase CFD model of flow requires a construction of mesh with millions of elements and overcome serious convergence problems. As 1-phase CFD model of flow in relation to 2-phase CFD model excludes from the simulations the dynamics of waves only, which should not change significantly water flow pattern for the case of lowland, dam reservoirs. In 1-phase CFD model, the phases (water-air) are separated by a plate which allows calculations of one phase (water) flow only. As the wind affects velocity of flow, to take into account the effect of the wind on hydrodynamics in 1-phase CFD model, the plate must move with speed and direction equal to the speed and direction of the upper water layer. To determine the velocity at which the plate will move on the water surface and interacts with the underlying layers of water and apply this value in 1-phase CFD model, the 2D, 2-phase model was elaborated. Result: Model was verified on the basis of the extensive flow measurements (StreamPro ADCP, USA). Excellent agreement (an average error less than 10%) between computed and measured velocity profiles was found. As a result of work, the following main conclusions can be presented: •The results indicate that the flow field in the Sulejow Reservoir is transient in nature, with swirl flows in the lower part of the lake. Recirculating zones, with the size of even half kilometer, may increase water retention time in this region •The results of simulations confirm the pronounced effect of the wind on the development of the water circulation zones in the reservoir which might affect the accumulation of nutrients in the epilimnion layer and result e.g. in the algae bloom. Conclusion: The resulting model is accurate and the methodology develop in the frame of this work can be applied to all types of storage reservoir configurations, characteristics, and hydrodynamics conditions. Large recirculating zones in the lake which increase water retention time and might affect the accumulation of nutrients were detected. Accurate CFD model of hydrodynamics in large water body could help in the development of forecast of water quality, especially in terms of eutrophication and water management of the big water bodies.

Keywords: CFD, mathematical modelling, dam reservoirs, hydrodynamics

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Authors: Manon Frédout, Laëtitia Bucari, Mathias Aloui, Gaëtan Duhamel, Olivier Rovellotti, Javier Blanco

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Ecosystems must be resilient to ensure cleaner air, better water and soil quality, and thus healthier citizens. Technology can be an excellent tool to support urban ecosystem restoration projects, especially when based on Open Source and promoting Open Data. This is the goal of the ecoTeka application: one single digital tool for tree management which allows decision-makers to improve their urban forestry practices, enabling more responsible urban planning and climate change adaptation. EcoTeka provides city councils with three main functionalities tackling three of their challenges: easier biodiversity inventories, better green space management, and more efficient planning. To answer the cities’ need for reliable tree inventories, the application has been first built with open data coming from the websites OpenStreetMap and OpenTrees, but it will also include very soon the possibility of creating new data. To achieve this, a multi-source algorithm will be elaborated, based on existing artificial intelligence Deep Forest, integrating open-source satellite images, 3D representations from LiDAR, and street views from Mapillary. This data processing will permit identifying individual trees' position, height, crown diameter, and taxonomic genus. To support urban forestry management, ecoTeka offers a dashboard for monitoring the city’s tree inventory and trigger alerts to inform about upcoming due interventions. This tool was co-constructed with the green space departments of the French cities of Alès, Marseille, and Rouen. The third functionality of the application is a decision-making tool for urban planning, promoting biodiversity and landscape connectivity metrics to drive ecosystem restoration roadmap. Based on landscape graph theory, we are currently experimenting with new methodological approaches to scale down regional ecological connectivity principles to local biodiversity conservation and urban planning policies. This methodological framework will couple graph theoretic approach and biological data, mainly biodiversity occurrences (presence/absence) data available on both international (e.g., GBIF), national (e.g., Système d’Information Nature et Paysage) and local (e.g., Atlas de la Biodiversté Communale) biodiversity data sharing platforms in order to help reasoning new decisions for ecological networks conservation and restoration in urban areas. An experiment on this subject is currently ongoing with Montpellier Mediterranee Metropole. These projects and studies have shown that only 26% of tree inventory data is currently geo-localized in France - the rest is still being done on paper or Excel sheets. It seems that technology is not yet used enough to enrich the knowledge city councils have about biodiversity in their city and that existing biodiversity open data (e.g., occurrences, telemetry, or genetic data), species distribution models, landscape graph connectivity metrics are still underexploited to make rational decisions for landscape and urban planning projects. This is the goal of ecoTeka: to support easier inventories of urban biodiversity and better management of urban spaces through rational planning and decisions relying on open databases. Future studies and projects will focus on the development of tools for reducing the artificialization of soils, selecting plant species adapted to climate change, and highlighting the need for ecosystem and biodiversity services in cities.

Keywords: digital software, ecological design of urban landscapes, sustainable urban development, urban ecological corridor, urban forestry, urban planning

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Authors: E. Obreque-Slier, P. Osorio-Umaña, G. Vidal-Acevedo, A. Peña-Neira, M. Medel-Marabolí

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Sensory and nutraceutical characteristics of a wine are determined by different chemical compounds, such as organic acids, sugars, alcohols, polysaccharides, aromas, and polyphenols. The polyphenols correspond to secondary metabolites that are associated with the prevention of several pathologies, and those are responsible for color, aroma, bitterness, and astringency in wines. These compounds come from grapes and wood during aging in barrels, which correspond to the format of wood most widely used in wine production. However, the barrels is a high-cost input with a limited useful life (3-4 years). For this reason, some oenological products have been developed in order to renew the barrels and increase their useful life in some years. These formats are being used slowly because limited information exists about the effect on the wine chemical characteristics. The objective of the study was to evaluate the effect of different laubarrel renewal systems (staves and zigzag) on the polyphenolic characteristics of a Carménère wine (Vitis vinifera), an emblematic cultivar of Chile. For this, a completely randomized experimental design with 5 treatments and three replicates per treatment was used. The treatments were: new barrels (T0), used barrels during 4 years (T1), scraped used barrels (T2), used barrels with staves (T3) and used barrels with zigzag (T4). The study was performed for 12 months, and different spectrophotometric parameters (phenols, anthocyanins, and total tannins) and HPLC-DAD (low molecular weight phenols) were evaluated. The wood inputs were donated by Toneleria Nacional and corresponded to products from the same production batch. The total phenols content increased significantly after 40 days, while the total tannin concentration decreased gradually during the study. The anthocyanin concentration increased after 120 days of the assay in all treatments. Comparatively, it was observed that the wine of T2 presented the lowest values of these polyphenols, while the T0 and T4 presented the highest total phenol contents. Also, T1 presented the highest values of total tannins in relation to the rest of the treatments in some samples. The low molecular weight phenolic compounds identified by HPLC-DAD were 7 flavonoids (epigallocatechin, catechin, procyanidin gallate, epicatechin, quercetin, rutin and myricetin) and 14 non-flavonoids (gallic, protocatechuic, hydroxybenzoic, trans-cutaric, vanillinic, caffeic, syringic, p-coumaric and ellagic acids; tyrosol, vanillin, syringaldehyde, trans-resveratrol and cis-resveratrol). Tyrosol was the most abundant compound, whereas ellagic acid was the lowest in the samples. Comparatively, it was observed that the wines of T2 showed the lowest concentrations of flavonoid and non-flavonoid phenols during the study. In contrast, wines of T1, T3, and T4 presented the highest contents of non-flavonoid polyphenols. In summary, the use of barrel renovators (zig zag and staves) is an interesting alternative which would emulate the contribution of polyphenols from the barrels to the wine.

Keywords: barrels, oak wood aging, polyphenols, red wine

Procedia PDF Downloads 200

Authors: Shantala Herlekar

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Introduction: Entrainment effect of music on cardiovascular parameters is well established. Music is being used in the background by medical students while studying. However, does it really help them relax faster and concentrate better? Objectives: This study was done to compare the effects of classical instrumental background music versus no music on blood pressure response over time and on successively performed divided attention test in Indian and Malaysian 1st-year medical students. Method: 60 Indian and 60 Malaysian first year medical students, with an equal number of girls and boys were randomized into two groups i.e music group and control group thus creating four subgroups. Three different forms of Symbol Digit Modality Test (to test concentration ability) were used as a pre-test, during music/control session and post-test. It was assessed using total, correct and error score. Simultaneously, multiple Blood Pressure recordings were taken as pre-test, during 1, 5, 15, 25 minutes during music/control (+SDMT) and post-test. The music group performed the test with classical instrumental background music while the control group performed it in silence. Results were analyzed using students paired t test. p value < 0.05 was taken as statistically significant. A drop in BP recording was indicative of relaxed state and a rise in BP with task performance was indicative of increased arousal. Results: In Symbol Digit Modality Test (SDMT) test, Music group showed significant better results for correct (p = 0.02) and total (p = 0.029) scores during post-test while errors reduced (p = 0.002). Indian music group showed decline in post-test error scores (p = 0.002). Malaysian music group performed significantly better in all categories. Blood pressure response was similar in music and control group with following variations, a drop in BP at 5minutes, being significant in music group (p < 0.001), a steep rise in values till 15minutes (corresponding to SDMT test) also being significant only in music group (p < 0.001) and the Systolic BP readings in controls during post-test were at lower levels compared to music group. On comparing the subgroups, not much difference was noticed in recordings of Indian student’s subgroups while all the paired-t test values in the Malaysian music group were significant. Conclusion: These recordings indicate an increased relaxed state with classical instrumental music and an increased arousal while performing a concentration task. Music used in our study was beneficial to students irrespective of their nationality and preference of music type. It can act as an “active coping” strategy and alleviate stress within a very short period of time, in our study within a span of 5minutes. When used in the background, during task performance, can increase arousal which helps the students perform better. Implications: Music can be used between lectures for a short time to relax the students and help them concentrate better for the subsequent classes, especially for late afternoon sessions.

Keywords: blood pressure, classical instrumental background music, ethnicity, symbol digit modality test

Procedia PDF Downloads 141

Authors: Adriana de Paula Lacerda Santos, Bruna Godke, Mauro Lacerda Santos Filho

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Several dams in the world have already collapsed, causing environmental, social and economic damage. The concern to avoid future disasters has stimulated the creation of a great number of laws and rules in many countries. In Brazil, Law 12.334/2010 was created, which establishes the National Policy on Dam Safety. Overall, this policy requires the dam owners to invest in the maintenance of their structures and to improve its monitoring systems in order to provide faster and straightforward responses in the case of an increase of risks. As monitoring tools, visual inspections has provides comprehensive assessment of the structures performance, while auscultation’s instrumentation has added specific information on operational or behavioral changes, providing an alarm when a performance indicator exceeds the acceptable limits. These limits can be set using statistical methods based on the relationship between instruments measures and other variables, such as reservoir level, time of the year or others instruments measuring. Besides the design parameters (uplift of the foundation, displacements, etc.) the dam instrumentation can also be used to monitor the behavior of defects and damage manifestations. Specifically in concrete gravity dams, one of the main causes for the appearance of cracks, are the concrete volumetric changes generated by the thermal origin phenomena, which are associated with the construction process of these structures. Based on this, the goal of this research is to propose a monitoring process of the thermal cracking behavior in concrete gravity dams, through the instrumentation data analysis and the establishment of control values. Therefore, as a case study was selected the Block B-11 of José Richa Governor Dam Power Plant, that presents a cracking process, which was identified even before filling the reservoir in August’ 1998, and where crack meters and surface thermometers were installed for its monitoring. Although these instruments were installed in May 2004, the research was restricted to study the last 4.5 years (June 2010 to November 2014), when all the instruments were calibrated and producing reliable data. The adopted method is based on simple linear correlations procedures to understand the interactions among the instruments time series, verifying the response times between them. The scatter plots were drafted from the best correlations, which supported the definition of the limit control values. Among the conclusions, it is shown that there is a strong or very strong correlation between ambient temperature and the crack meters and flowmeters measurements. Based on the results of the statistical analysis, it was possible to develop a tool for monitoring the behavior of the case study cracks. Thus it was fulfilled the goal of the research to develop a proposal for a monitoring process of the behavior of thermal cracking in concrete gravity dams.

Keywords: concrete gravity dam, dams safety, instrumentation, simple linear correlation

Procedia PDF Downloads 292

Authors: Elham Koohi, Silvio Jose Gumiere, Hossein Bonakdari, Saeid Homayouni

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Water used in agricultural crops can be managed by irrigation scheduling based on soil moisture levels and plant water stress thresholds. Automated irrigation scheduling limits crop physiological damage and yield reduction. Knowledge of crop water stress monitoring approaches can be effective in optimizing the use of agricultural water. Understanding the physiological mechanisms of crop responding and adapting to water deficit ensures sustainable agricultural management and food supply. This aim could be achieved by analyzing and diagnosing crop characteristics and their interlinkage with the surrounding environment. Assessments of plant functional types (e.g., leaf area and structure, tree height, rate of evapotranspiration, rate of photosynthesis), controlling changes, and irrigated areas mapping. Calculating thresholds of soil water content parameters, crop water use efficiency, and Nitrogen status make irrigation scheduling decisions more accurate by preventing water limitations between irrigations. Combining Remote Sensing (RS), the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning Algorithms (MLAs) can improve measurement accuracies and automate irrigation scheduling. This paper is a review structured by surveying about 100 recent research studies to analyze varied approaches in terms of providing high spatial and temporal resolution mapping, sensor-based Variable Rate Application (VRA) mapping, the relation between spectral and thermal reflectance and different features of crop and soil. The other objective is to assess RS indices formed by choosing specific reflectance bands and identifying the correct spectral band to optimize classification techniques and analyze Proximal Optical Sensors (POSs) to control changes. The innovation of this paper can be defined as categorizing evaluation methodologies of precision irrigation (applying the right practice, at the right place, at the right time, with the right quantity) controlled by soil moisture levels and sensitiveness of crops to water stress, into pre-processing, processing (retrieval algorithms), and post-processing parts. Then, the main idea of this research is to analyze the error reasons and/or values in employing different approaches in three proposed parts reported by recent studies. Additionally, as an overview conclusion tried to decompose different approaches to optimizing indices, calibration methods for the sensors, thresholding and prediction models prone to errors, and improvements in classification accuracy for mapping changes.

Keywords: agricultural crops, crop water stress detection, irrigation scheduling, precision agriculture, remote sensing

Procedia PDF Downloads 71

Authors: Ekin Esen, Mohammad Alipour, Riza Kizilel

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Rechargeable lithium-ion batteries have been replacing lead-acid batteries for the last decade due to their outstanding properties such as high energy density, long shelf life, and almost no memory effect. Besides these, being very light compared to lead acid batteries has gained them their dominant place in the portable electronics market, and they are now the leading candidate for electric vehicles (EVs) and hybrid electric vehicles (HEVs). However, their performance strongly depends on temperature, and this causes some inconveniences for their utilization in extreme temperatures. Since weather conditions vary across the globe, this situation limits their utilization for EVs and HEVs and makes a thermal management system obligatory for the battery units. The objective of this study is to understand thermal characteristics of Li-ion battery modules for various operation conditions and design a thermal management system to enhance battery performance in EVs and HEVs. In the first part of our study, we investigated thermal behavior of commercially available pouch type 20Ah LiFePO₄ (LFP) cells under various conditions. Main parameters were chosen as ambient temperature and discharge current rate. Each cell was charged and discharged at temperatures of 0°C, 10°C, 20°C, 30°C, 40°C, and 50°C. The current rate of charging process was 1C while it was 1C, 2C, 3C, 4C, and 5C for discharge process. Temperatures of 7 different points on the cells were measured throughout charging and discharging with N-type thermocouples, and a detailed temperature profile was obtained. In the second part of our study, we connected 4 cells in series by clinching and prepared 4S1P battery modules similar to ones in EVs and HEVs. Three reference points were determined according to the findings of the first part of the study, and a thermocouple is placed on each reference point on the cells composing the 4S1P battery modules. In the end, temperatures of 6 points in the module and 3 points on the top surface were measured and changes in the surface temperatures were recorded for different discharge rates (0.2C, 0.5C, 0.7C, and 1C) at various ambient temperatures (0°C – 50°C). Afterwards, aluminum plates with channels were placed between the cells in the 4S1P battery modules, and temperatures were controlled with airflow. Airflow was provided with a regular compressor, and the effect of flow rate on cell temperature was analyzed. Diameters of the channels were in mm range, and shapes of the channels were determined in order to make the cell temperatures uniform. Results showed that the designed thermal management system could help keeping the cell temperatures in the modules uniform throughout charge and discharge processes. Other than temperature uniformity, the system was also beneficial to keep cell temperature close to the optimum working temperature of Li-ion batteries. It is known that keeping the temperature at an optimum degree and maintaining uniform temperature throughout utilization can help obtaining maximum power from the cells in battery modules for a longer time. Furthermore, it will increase safety by decreasing the risk of thermal runaways. Therefore, the current study is believed to be beneficial for wider use of Li batteries for battery modules of EVs and HEVs globally.

Keywords: lithium ion batteries, thermal management system, electric vehicles, hybrid electric vehicles

Procedia PDF Downloads 163

Authors: Aboulkacem El Mehdi

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We develop a theoretical model at the crossroads of labour and urban economics, used for explaining the mechanism through which the duration of home-workplace trips and their monetary costs impact the labour demand and supply in a spatially scattered labour market and how they are impacted by a change in passenger transport infrastructures and services. The spatial disconnection between home and job opportunities is referred to as the spatial mismatch hypothesis (SMH). Its harmful impact on employment has been subject to numerous theoretical propositions. However, all the theoretical models proposed so far are patterned around the American context, which is particular as it is marked by racial discrimination against blacks in the housing and the labour markets. Therefore, it is only natural that most of these models are developed in order to reproduce a steady state characterized by agents carrying out their economic activities in a mono-centric city in which most unskilled jobs being created in the suburbs, far from the Blacks who dwell in the city-centre, generating a high unemployment rates for blacks, while the White population resides in the suburbs and has a low unemployment rate. Our model doesn't rely on any racial discrimination and doesn't aim at reproducing a steady state in which these stylized facts are replicated; it takes the main principle of the SMH -the spatial disconnection between homes and workplaces- as a starting point. One of the innovative aspects of the model consists in dealing with a SMH related issue at an aggregate level. We link the parameters of the passengers transport system to employment in the whole area of a city. We consider here a city that consists of four areas: two of them are residential areas with unemployed workers, the other two host firms looking for labour force. The workers compare the indirect utility of working in each area with the utility of unemployment and choose between submitting an application for the job that generate the highest indirect utility or not submitting. This arbitration takes account of the monetary and the time expenditures generated by the trips between the residency areas and the working areas. Each of these expenditures is clearly and explicitly formulated so that the impact of each of them can be studied separately than the impact of the other. The first findings show that the unemployed workers living in an area benefiting from good transport infrastructures and services have a better chance to prefer activity to unemployment and are more likely to supply a higher 'quantity' of labour than those who live in an area where the transport infrastructures and services are poorer. We also show that the firms located in the most accessible area receive much more applications and are more likely to hire the workers who provide the highest quantity of labour than the firms located in the less accessible area. Currently, we are working on the matching process between firms and job seekers and on how the equilibrium between the labour demand and supply occurs.

Keywords: labour market, passenger transport infrastructure, spatial mismatch hypothesis, urban economics

Procedia PDF Downloads 292

Authors: Quentin C.P. Bourgogne, Vanessa Bouchart, Pierre Chevrier, Emmanuel Dattoli

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This study presents an experimental and theoretical work conducted on a PolyPhenylene Sulfide reinforced with 40%wt of short glass fibers (PPS GF40) and its matrix. Thermoplastics are widely used in the automotive industry to lightweight automotive parts. The replacement of metallic parts by thermoplastics is reaching under-the-hood parts, near the engine. In this area, the parts are subjected to high temperatures and are immersed in cooling liquid. This liquid is composed of water and glycol and can affect the mechanical properties of the composite. The aim of this work was thus to quantify the evolution of mechanical properties of the thermoplastic composite, as a function of temperature and liquid aging effects, in order to develop a reliable design of parts. An experimental campaign in the tensile mode was carried out at different temperatures and for various glycol proportions in the cooling liquid, for monotonic and cyclic loadings on a neat and a reinforced PPS. The results of these tests allowed to highlight some of the main physical phenomena occurring during these solicitations under tough hydro-thermal conditions. Indeed, the performed tests showed that temperature and liquid cooling aging can affect the mechanical behavior of the material in several ways. The more the cooling liquid contains water, the more the mechanical behavior is affected. It was observed that PPS showed a higher sensitivity to absorption than to chemical aggressiveness of the cooling liquid, explaining this dominant sensitivity. Two kinds of behaviors were noted: an elasto-plastic type under the glass transition temperature and a visco-pseudo-plastic one above it. It was also shown that viscosity is the leading phenomenon above the glass transition temperature for the PPS and could also be important under this temperature, mostly under cyclic conditions and when the stress rate is low. Finally, it was observed that soliciting this composite at high temperatures is decreasing the advantages of the presence of fibers. A new phenomenological model was then built to take into account these experimental observations. This new model allowed the prediction of the evolution of mechanical properties as a function of the loading environment, with a reduced number of parameters compared to precedent studies. It was also shown that the presented approach enables the description and the prediction of the mechanical response with very good accuracy (2% of average error at worst), over a wide range of hydrothermal conditions. A temperature-humidity equivalence principle was underlined for the PPS, allowing the consideration of aging effects within the proposed model. Then, a limit of improvement of the reachable accuracy was determinate for all models using this set of data by the application of an artificial intelligence-based model allowing a comparison between artificial intelligence-based models and phenomenological based ones.

Keywords: aging, analytical modeling, mechanical testing, polymer matrix composites, sequential model, thermomechanical

Procedia PDF Downloads 116

Authors: Chusit Apirumanekul, Chayanis Krittasudthacheewa, Ratchapat Ratanavaraha, Yanyong Inmuong

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Rapid economic development in the Lower Mekong region is leading to changes in water quantity and quality. Changes in land- and forest-use, infrastructure development, increasing urbanization, migration patterns and climate risks are increasing demands for water, within various sectors, placing pressure on scarce water resources. Appropriate policies, strategies, and planning are urgently needed for improved water resource management. Over the last decade, Thailand has experienced more frequent and intense drought situations, affecting the level of water storage in reservoirs along with insufficient water allocation for agriculture during the dry season. The Huay Saibat River Basin, one of the well-known water-scarce areas in the northeastern region of Thailand, is experiencing ongoing water scarcity that affects both farming livelihoods and household consumption. Drought management in Thailand mainly focuses on emergency responses, rather than advance preparation and mitigation for long-term solutions. Despite many efforts from local authorities to mitigate the drought situation, there is yet no long-term comprehensive water management strategy, that integrates climate risks alongside other uncertainties. This paper assesses the application in the Huay Saibat River Basin, of the Robust Decision Support framework, to explore the feasibility of multiple drought management policies; including a shift in cropping season, in crop changes, in infrastructural operations and in the use of groundwater, under a wide range of uncertainties, including climate and land-use change. A series of consultative meetings were organized with relevant agencies and experts at the local level, to understand and explore plausible water resources strategies and identify thresholds to evaluate the performance of those strategies. Three different climate conditions were identified (dry, normal and wet). Other non-climatic factors influencing water allocation were further identified, including changes from sugarcane to rubber, delaying rice planting, increasing natural retention storage and using groundwater to supply demands for household consumption and small-scale gardening. Water allocation and water use in various sectors, such as in agriculture, domestic, industry and the environment, were estimated by utilising the Water Evaluation And Planning (WEAP) system, under various scenarios developed from the combination of climatic and non-climatic factors mentioned earlier. Water coverage (i.e. percentage of water demand being successfully supplied) was defined as a threshold for water resource strategy assessment. Thresholds for different sectors (agriculture, domestic, industry, and environment) were specified during multi-stakeholder engagements. Plausible water strategies (e.g. increasing natural retention storage, change of crop type and use of groundwater as an alternative source) were evaluated based on specified thresholds in 4 sectors (agriculture, domestic, industry, and environment) under 3 climate conditions. 'Business as usual' was evaluated for comparison. The strategies considered robust, emerge when performance is assessed as successful, under a wide range of uncertainties across the river basin. Without adopting any strategy, the water scarcity situation is likely to escalate in the future. Among the strategies identified, the use of groundwater as an alternative source was considered a potential option in combating water scarcity for the basin. Further studies are needed to explore the feasibility for groundwater use as a potential sustainable source.

Keywords: climate change, robust decision support, scenarios, water resources management

Procedia PDF Downloads 170

Authors: Habib Muhammetoglu, I. Ethem Karadirek, Selami Kara, Ayse Muhammetoglu

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The problem of non-revenue water (NRW) from municipal water distribution networks is common in many countries such as Turkey, where the average yearly water losses are around 50% . Water losses can be divided into two major types namely: 1) Real or physical water losses, and 2) Apparent or commercial water losses. Total water losses in Antalya city, Turkey is around 45%. Methods: A research study was conducted to develop appropriate methodologies to reduce NRW. A pilot study area of about 60 thousands inhabitants was chosen to apply the study. The pilot study area has a supervisory control and data acquisition (SCADA) system for the monitoring and control of many water quantity and quality parameters at the groundwater drinking wells, pumping stations, distribution reservoirs, and along the water mains. The pilot study area was divided into 18 District Metered Areas (DMAs) with different number of service connections that ranged between a few connections to less than 3000 connections. The flow rate and water pressure to each DMA were on-line continuously measured by an accurate flow meter and water pressure meter that were connected to the SCADA system. Customer water meters were installed to all billed and unbilled water users. The monthly water consumption as given by the water meters were recorded regularly. Water balance was carried out for each DMA using the well-know standard IWA approach. There were considerable variations in the water losses percentages and the components of the water losses among the DMAs of the pilot study area. Old Class B customer water meters at one DMA were replaced by more accurate new Class C water meters. Hydraulic modelling using the US-EPA EPANET model was carried out in the pilot study area for the prediction of water pressure variations at each DMA. The data sets required to calibrate and verify the hydraulic model were supplied by the SCADA system. It was noticed that a number of the DMAs exhibited high water pressure values. Therefore, pressure reducing valves (PRV) with constant head were installed to reduce the pressure up to a suitable level that was determined by the hydraulic model. On the other hand, the hydraulic model revealed that the water pressure at the other DMAs cannot be reduced when complying with the minimum pressure requirement (3 bars) as stated by the related standards. Results: Physical water losses were reduced considerably as a result of just reducing water pressure. Further physical water losses reduction was achieved by applying acoustic methods. The results of the water balances helped in identifying the DMAs that have considerable physical losses. Many bursts were detected especially in the DMAs that have high physical water losses. The SCADA system was very useful to assess the efficiency level of this method and to check the quality of repairs. Regarding apparent water losses reduction, changing the customer water meters resulted in increasing water revenue by more than 20%. Conclusions: DMA, SCADA, modelling, pressure management, leakage detection and accurate customer water meters are efficient for NRW.

Keywords: NRW, water losses, pressure management, SCADA, apparent water losses, urban water distribution networks

Procedia PDF Downloads 405

Authors: Olga Sukhoveeva

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Carbon dioxide (CO2) is the main component of carbon biogeochemical cycle and one of the most important greenhouse gases (GHG). Agriculture, particularly arable soils, are one the largest sources of GHG emission for the atmosphere including CO2.Models may be used for estimation of GHG emission from agriculture if they can be adapted for different countries conditions. The only model used in officially at national level in United Kingdom and China for this purpose is DNDC (DeNitrification-DeComposition). In our research, the model DNDC is offered for estimation of GHG emission from arable soils in Russia. The aim of our research was to create the method of DNDC using for evaluation of CO2 emission in Russia based on official statistical information. The target territory was European part of Russia where many field experiments are located. At the first step of research the database on climate, soil and cropping characteristics for the target region from governmental, statistical, and literature sources were created. All-Russia Research Institute of Hydrometeorological Information – World Data Centre provides open daily data about average meteorological and climatic conditions. It must be calculated spatial average values of maximum and minimum air temperature and precipitation over the region. Spatial average values of soil characteristics (soil texture, bulk density, pH, soil organic carbon content) can be determined on the base of Union state register of soil recourses of Russia. Cropping technologies are published by agricultural research institutes and departments. We offer to define cropping system parameters (annual information about crop yields, amount and types of fertilizers and manure) on the base of the Federal State Statistics Service data. Content of carbon in plant biomass may be calculated via formulas developed and published by Ministry of Natural Resources and Environment of the Russian Federation. At the second step CO2 emission from soil in this region were calculated by DNDC. Modelling data were compared with empirical and literature data and good results were obtained, modelled values were equivalent to the measured ones. It was revealed that the DNDC model may be used to evaluate and forecast the CO2 emission from arable soils in Russia based on the official statistical information. Also, it can be used for creation of the program for decreasing GHG emission from arable soils to the atmosphere. Financial Support: fundamental scientific researching theme 0148-2014-0005 No 01201352499 ‘Solution of fundamental problems of analysis and forecast of Earth climatic system condition’ for 2014-2020; fundamental research program of Presidium of RAS No 51 ‘Climate change: causes, risks, consequences, problems of adaptation and regulation’ for 2018-2020.

Keywords: arable soils, carbon dioxide emission, DNDC model, European Russia

Procedia PDF Downloads 191

Authors: Qaisar Ali, Waqar A. Khan, Shafiq R. Qureshi

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Heat transfer in Power Law Fluids across cylindrical surfaces has copious engineering applications. These applications comprises of areas such as underwater pollution, bio medical engineering, filtration systems, chemical, petroleum, polymer, food processing, recovery of geothermal energy, crude oil extraction, pharmaceutical and thermal energy storage. The quantum of research work with diversified conditions to study the effects of combined heat transfer and fluid flow across porous media has increased considerably over last few decades. The most non-Newtonian fluids of practical interest are highly viscous and therefore are often processed in the laminar flow regime. Several studies have been performed to investigate the effects of free and mixed convection in Newtonian fluids along vertical and horizontal cylinder embedded in a saturated porous medium, whereas very few analysis have been performed on Power law fluids along wedge. In this study, boundary layer analysis under the effects of radiation-mixed convection in power law fluids along vertical wedge in porous medium have been investigated using an implicit finite difference method (Keller box method). Steady, 2-D laminar flow has been considered under prescribed surface heat flux condition. Darcy, Boussinesq and Roseland approximations are assumed to be valid. Neglecting viscous dissipation effects and the radiate heat flux in the flow direction, the boundary layer equations governing mixed convection flow over a vertical wedge are transformed into dimensionless form. The single mathematical model represents the case for vertical wedge, cone and plate by introducing the geometry parameter. Both similar and Non- similar solutions have been obtained and results for Non similar case have been presented/ plotted. Effects of radiation parameter, variable heat flux parameter, wedge angle parameter ‘m’ and mixed convection parameter have been studied for both Newtonian and Non-Newtonian fluids. The results are also compared with the available data for the analysis of heat transfer in the prescribed range of parameters and found in good agreement. Results for the details of dimensionless local Nusselt number, temperature and velocity fields have also been presented for both Newtonian and Non-Newtonian fluids. Analysis of data revealed that as the radiation parameter or wedge angle is increased, the Nusselt number decreases whereas it increases with increase in the value of heat flux parameter at a given value of mixed convection parameter. Also, it is observed that as viscosity increases, the skin friction co-efficient increases which tends to reduce the velocity. Moreover, pseudo plastic fluids are more heat conductive than Newtonian and dilatant fluids respectively. All fluids behave identically in pure forced convection domain.

Keywords: porous medium, power law fluids, surface heat flux, vertical wedge

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Authors: Abida Mariam, Anwaar Ahmed, Asif Ahmad, Muhammad Sheeraz Ahmad, Muhammad Akram Khan, Muhammad Mazahir

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The plant olive (Olea europaea L.) is known for its commercial significance due to nutritional and health benefits. Pakistan is ranked 4th among countries who import olive oil whereas, 70% of edible oil is imported to fulfil the needs of the country. There exists great potential for Olea europaea cultivation in Pakistan. The popularity and cultivation of olive fruit has increased in recent past due to its high socio-economic and health significance. There exist almost negligible data on the chemical composition of extra virgin olive oil extracted from cultivars grown in Pothwar, an area with arid climate conducive for growth of olive trees. Keeping in view these factors a study has been conducted to characterize the olive oil extracted from olive cultivars collected from Pothwar regions of Pakistan for their nutritional potential and value addition. Ten olive cultivars (Gemlik, Coratina, Sevillano, Manzanilla, Leccino, Koroneiki, Frantoio, Arbiquina, Earlik and Ottobratica) were collected from Barani Agriculture Research Institute, Chakwal. Extra Virgin Olive Oil (EVOO) was extracted by cold pressing and centrifuging of olive fruits. The highest amount of oil was yielded in Coratina (23.9%) followed by Frantoio (23.7%), Koroneiki (22.8%), Sevillano (22%), Ottobratica (22%), Leccino (20.5%), Arbiquina (19.2%), Manzanilla (17.2%), Earlik (14.4%) and Gemllik (13.1%). The extracted virgin olive oil was studied for various physico- chemical properties and fatty acid profile. The Physical and chemical properties i.e., characteristic odor and taste, light yellow color with no foreign matter, insoluble impurities (≤0.08), fee fatty acid (0.1 to 0.8), acidity (0.5 to 1.6 mg/g acid), peroxide value (1.5 to 5.2 meqO2/kg), Iodine value (82 to 90), saponification value (186 to 192 mg/g) and unsaponifiable matter (4 to 8g/kg), ultraviolet spectrophotometric analysis (k232 and k270), showed values in the acceptable range, established by PSQCA and IOOC set for extra virgin olive oil. Olive oil was analyzed by Near Infra-Red spectrophotometry (NIR) for fatty acids sin olive oils which were found as: palmitic, palmitoleic, stearic, oleic, linoleic and alpha-linolenic. Major fatty acid was Oleic acid in the highest percentage ranging from (55 to 66.1%), followed by linoleic (10.4 to 20.4%), palmitic (13.8 to 19.5%), stearic (3.9 to 4.4%), palmitoleic (0.3 to 1.7%) and alpha-linolenic (0.9 to 1.7%). The results were significant with differences in parameters analyzed for all ten cultivars which confirm that genetic factors are important contributors in the physico-chemical characteristics of oil. The olive oil showed superior physical and chemical properties and recommended as one of the healthiest forms of edible oil. This study will help consumers to be more aware of and make better choices of healthy oils available locally thus contributing towards their better health.

Keywords: characterization, extra virgin olive oil, oil yield, fatty acids

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Authors: Sonia Bautista Carrascosa, Carlos Renedo Sanchez

Abstract:

The effect of a rapid drawdown is a classical scenario to be considered in slope stability under submerged conditions. This situation arises when totally or partially submerged slopes experience a descent of the external water level and is a typical verification to be done in a dam engineering discipline, as reservoir water levels commonly fluctuate noticeably during seasons and due to operational reasons. Although the scenario is well known and predictable in general, site conditions can increase the complexity of its assessment and external factors are not always expected, can cause a reduction in the stability or even a failure in a slope under a rapid drawdown situation. The present paper describes and discusses the interaction between two different infrastructures, a dam and a highway, and the impact on the stability of a natural rock slope overlaid by the north abutment of a viaduct of the A-44 Highway due to the rapid drawdown of the Rules Dam, in the province of Granada (south of Spain). In the year 2011, with both infrastructures, the A-44 Highway and the Rules Dam already constructed, delivered and under operation, some movements start to be recorded in the approximation embankment and north abutment of the Guadalfeo Viaduct, included in the highway and developed to solve the crossing above the tail of the reservoir. The embankment and abutment were founded in a low-angle natural rock slope formed by grey graphic phyllites, distinctly weathered and intensely fractured, with pre-existing fault and weak planes. After the first filling of the reservoir, to a relative level of 243m, three consecutive drawdowns were recorded in the autumns 2010, 2011 and 2012, to relative levels of 234m, 232m and 225m. To understand the effect of these drawdowns in the weak rock mass strength and in its stability, a new geological model was developed, after reviewing all the available ground investigations, updating the geological mapping of the area and supplemented with an additional geotechnical and geophysical investigations survey. Together with all this information, rainfall and reservoir level evolution data have been reviewed in detail to incorporate into the monitoring interpretation. The analysis of the monitoring data and the new geological and geotechnical interpretation, supported by the use of limit equilibrium software Slide2, concludes that the movement follows the same direction as the schistosity of the phyllitic rock mass, coincident as well with the direction of the natural slope, indicating a deep-seated movement of the whole slope towards the reservoir. As part of these conclusions, the solutions considered to reinstate the highway infrastructure to the required FoS will be described, and the geomechanical characterization of these weak rocks discussed, together with the influence of water level variations, not only in the water pressure regime but in its geotechnical behavior, by the modification of the strength parameters and deformability.

Keywords: monitoring, rock slope stability, water drawdown, weak rock

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Authors: Hamadi Cherif, Christophe Coquelet, Paolo Stringari, Denis Clodic, Laura Pellegrini, Stefania Moioli, Stefano Langè

Abstract:

Biogas is a promising technology which can be used as a vehicle fuel, for heat and electricity production, or injected in the national gas grid. It is storable, transportable, not intermittent and substitutable for fossil fuels. This gas produced from the wastewater treatment by degradation of organic matter under anaerobic conditions is mainly composed of methane and carbon dioxide. To be used as a renewable fuel, biogas, whose energy comes only from methane, must be purified from carbon dioxide and other impurities such as water vapor, siloxanes and hydrogen sulfide. Purification of biogas for this application particularly requires the removal of hydrogen sulfide, which negatively affects the operation and viability of equipment especially pumps, heat exchangers and pipes, causing their corrosion. Several methods are available to eliminate hydrogen sulfide from biogas. Herein, reactive absorption in structured packed column by means of chemical absorption in aqueous sodium hydroxide solutions is considered. This study is based on simulations using Aspen Plus™ V8.0, and comparisons are done with data from an industrial pilot plant treating 85 Nm3/h of biogas which contains about 30 ppm of hydrogen sulfide. The rate-based model approach has been used for simulations in order to determine the efficiencies of separation for different operating conditions. To describe vapor-liquid equilibrium, a γ/ϕ approach has been considered: the Electrolyte NRTL model has been adopted to represent non-idealities in the liquid phase, while the Redlich-Kwong equation of state has been used for the vapor phase. In order to validate the thermodynamic model, Henry’s law constants of each compound in water have been verified against experimental data. Default values available in Aspen Plus™ V8.0 for the properties of pure components properties as heat capacity, density, viscosity and surface tension have also been verified. The obtained results for physical and chemical properties are in a good agreement with experimental data. Reactions involved in the process have been studied rigorously. Equilibrium constants for equilibrium reactions and the reaction rate constant for the kinetically controlled reaction between carbon dioxide and the hydroxide ion have been checked. Results of simulations of the pilot plant purification section show the influence of low temperatures, concentration of sodium hydroxide and hydrodynamic parameters on the selective absorption of hydrogen sulfide. These results show an acceptable degree of accuracy when compared with the experimental data obtained from the pilot plant. Results show also the great efficiency of sodium hydroxide for the removal of hydrogen sulfide. The content of this compound in the gas leaving the column is under 1 ppm.

Keywords: biogas, hydrogen sulfide, reactive absorption, sodium hydroxide, structured packed column

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Authors: Priyanka Verma, Vijaya Dixit, Rishabh Bajpai

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This research paper is aimed at selecting appropriate material handling equipment among the given choices so that the automation level in material handling can be enhanced. This work is a practical case scenario of material handling systems in consumer electronic appliances manufacturing organization. The choices of material handling equipment among which the decision has to be made are Automated Guided Vehicle’s (AGV), Autonomous Mobile Robots (AMR), Overhead Conveyer’s (OC) and Battery Operated Trucks/Vehicle’s (BOT). There is a need of attaining a certain level of automation in order to reduce human interventions in the organization. This requirement of achieving certain degree of automation can be attained by material handling equipment’s mentioned above. The main motive for selecting above equipment’s for study was solely based on corporate financial strategy of investment and return obtained through that investment made in stipulated time framework. Since the low cost automation with respect to material handling devices has to be achieved hence these equipment’s were selected. Investment to be done on each unit of this equipment is less than 20 lakh rupees (INR) and the recovery period is less than that of five years. Fuzzy analytic hierarchic process (FAHP) is applied here for selecting equipment where the four choices are evaluated on basis of four major criteria’s and 13 sub criteria’s, and are prioritized on the basis of weight obtained. The FAHP used here make use of triangular fuzzy numbers (TFN). The inability of the traditional AHP in order to deal with the subjectiveness and impreciseness in the pair-wise comparison process has been improved in the FAHP. The range of values for general rating purposes for all decision making parameters is kept between 0 and 1 on the basis of expert opinions captured on shop floor. These experts were familiar with operating environment and shop floor activity control. Instead of generating exact value the FAHP generates the ranges of values to accommodate the uncertainty in decision-making process. The four major criteria’s selected for the evaluation of choices of material handling equipment’s available are materials, technical capabilities, cost and other features. The thirteen sub criteria’s listed under these following four major criteria’s are weighing capacity, load per hour, material compatibility, capital cost, operating cost and maintenance cost, speed, distance moved, space required, frequency of trips, control required, safety and reliability issues. The key finding shows that among the four major criteria selected, cost is emerged as the most important criteria and is one of the key decision making aspect on the basis of which material equipment selection is based on. While further evaluating the choices of equipment available for each sub criteria it is found that AGV scores the highest weight in most of the sub-criteria’s. On carrying out complete analysis the research shows that AGV is the best material handling equipment suiting all decision criteria’s selected in FAHP and therefore it is beneficial for the organization to carry out automated material handling in the facility using AGV’s.

Keywords: fuzzy analytic hierarchy process (FAHP), material handling equipment, subjectiveness, triangular fuzzy number (TFN)

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Authors: Abheyjit Singh, Kulwant Singh

Abstract:

There is a gradual depletion of the water table in the earth's crust, and it is required to converse and reduce the scarcity of water. This is only done by rainwater harvesting, recycling of water and by judicially consumption/utilization of water and adopting unique treatment measures. Domestic waste is generated in residential areas, commercial settings, and institutions. Waste, in general, is unwanted, undesirable, and nevertheless an inevitable and inherent product of social, economic, and cultural life. In a cluster, a need-based system is formed where the project is designed for systematic analysis, collection of sewage from the cluster, treating it and then recycling it for multifarious work. The liquid waste may consist of Sanitary sewage/ Domestic waste, Industrial waste, Storm waste, or Mixed Waste. The sewage contains both suspended and dissolved particles, and the total amount of organic material is related to the strength of the sewage. The untreated domestic sanitary sewage has a BOD (Biochemical Oxygen Demand) of 200 mg/l. TSS (Total Suspended Solids) about 240 mg/l. Industrial Waste may have BOD and TSS values much higher than those of sanitary sewage. Another type of impurities of wastewater is plant nutrients, especially when there are compounds of nitrogen N phosphorus P in the sewage; raw sanitary contains approx. 35 mg/l Nitrogen and 10 mg/l of Phosphorus. Finally, the pathogen in the waste is expected to be proportional to the concentration of facial coliform bacteria. The coliform concentration in raw sanitary sewage is roughly 1 billion per liter. The system of sewage disposal technique has been universally applied to all conditions, which are the nature of soil formation, Availability of land, Quantity of Sewage to be disposed of, The degree of treatment and the relative cost of disposal technique. The adopted Thappar Model (India) has the following designed parameters consisting of a Screen Chamber, a Digestion Tank, a Skimming Tank, a Stabilization Tank, an Oxidation Pond and a Water Storage Pond. The screening Chamber is used to remove plastic and other solids, The Digestion Tank is designed as an anaerobic tank having a retention period of 8 hours, The Skimming Tank has an outlet that is kept 1 meter below the surface anaerobic condition at the bottom and also help in organic solid remover, Stabilization Tank is designed as primary settling tank, Oxidation Pond is a facultative pond having a depth of 1.5 meter, Storage Pond is designed as per the requirement. The cost of the Thappar model is Rs. 185 Lakh per 3,000 to 4,000 population, and the Area required is 1.5 Acre. The complete structure will linning as per the requirement. The annual maintenance will be Rs. 5 lakh per year. The project is useful for water conservation, silage water for irrigation, decrease of BOD and there will be no longer damage to community assets and economic loss to the farmer community by inundation. There will be a healthy and clean environment in the community.

Keywords: collection, treatment, utilization, economic

Procedia PDF Downloads 76

Authors: Elham Koohikerade, Silvio Jose Gumiere

Abstract:

In this research, irrigation is highlighted as crucial for improving both the yield and quality of ‎potatoes due to their high sensitivity to soil moisture changes. The study presents a hybrid Long ‎Short-Term Memory (LSTM) model aimed at optimizing irrigation scheduling in potato fields in ‎Quebec City, Canada. This model integrates model-based and satellite-derived datasets to simulate ‎soil moisture content, addressing the limitations of field data. Developed under the guidance of the ‎Food and Agriculture Organization (FAO), the simulation approach compensates for the lack of direct ‎soil sensor data, enhancing the LSTM model's predictions. The model was calibrated using indices ‎like Surface Soil Moisture (SSM), Normalized Vegetation Difference Index (NDVI), Enhanced ‎Vegetation Index (EVI), and Normalized Multi-band Drought Index (NMDI) to effectively forecast ‎soil moisture reductions. Understanding soil moisture and plant development is crucial for assessing ‎drought conditions and determining irrigation needs. This study validated the spectral characteristics ‎of vegetation and soil using ECMWF Reanalysis v5 (ERA5) and Moderate Resolution Imaging ‎Spectrometer (MODIS) data from 2019 to 2023, collected from agricultural areas in Dolbeau and ‎Peribonka, Quebec. Parameters such as surface volumetric soil moisture (0-7 cm), NDVI, EVI, and ‎NMDI were extracted from these images. A regional four-year dataset of soil and vegetation moisture ‎was developed using a machine learning approach combining model-based and satellite-based ‎datasets. The LSTM model predicts soil moisture dynamics hourly across different locations and ‎times, with its accuracy verified through cross-validation and comparison with existing soil moisture ‎datasets. The model effectively captures temporal dynamics, making it valuable for applications ‎requiring soil moisture monitoring over time, such as anomaly detection and memory analysis. By ‎identifying typical peak soil moisture values and observing distribution shapes, irrigation can be ‎scheduled to maintain soil moisture within Volumetric Soil Moisture (VSM) values of 0.25 to 0.30 ‎m²/m², avoiding under and over-watering. The strong correlations between parcels suggest that a ‎uniform irrigation strategy might be effective across multiple parcels, with adjustments based on ‎specific parcel characteristics and historical data trends. The application of the LSTM model to ‎predict soil moisture and vegetation indices yielded mixed results. While the model effectively ‎captures the central tendency and temporal dynamics of soil moisture, it struggles with accurately ‎predicting EVI, NDVI, and NMDI.‎

Keywords: irrigation scheduling, LSTM neural network, remotely sensed indices, soil and vegetation ‎monitoring

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