Search results for: seasonal dynamics

Authors: Kirandeep Kaur, Rohit Mehra, Pargin Bangotra

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Radon and thoron are pervasive radioactive gases and so are their progenies. The progenies of radon and thoron are present in the indoor atmosphere as attached/unattached fractions. In the present work, seasonal variation of concentration of attached and total (attached + unattached) nanosized decay products of indoor radon and thoron has been studied in the dwellings of Bathinda District of Punjab using Deposition based progeny sensors over long integrated times, which are independent of air turbulence. The preliminary results of these measurements are reported particularly regarding DTPS (Direct Thoron Progeny Sensor) and DRPS (Direct Radon Progeny Sensor) for the first time in Bathinda. It has been observed that there is a strong linear relationship in total EERC (Equilibrium Equivalent Radon Concentration) and EETC (Equilibrium Equivalent Thoron Concentration) in rainy season (R2 = 0.83). Further a strong linear relation between total indoor radon concentration and attached fraction has also been observed for the same rainy season (R2= 0.91). The concentration of attached progeny of radon (EERCatt) is 76.3 % of the total Equilibrium Equivalent Radon Concentration (EERC).

Keywords: radon, thoron, progeny, DTPS/DRPS, EERC, EETC, seasonal variation

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Authors: Myunggon Yoon, Jung-Ho Moon

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In this paper, we present a transfer function representation of a general one-dimensional combustor. The input of the transfer function is a heat rate perturbation of a burner and the output is a flow velocity perturbation at the burner. This paper considers a general combustor model composed of multiple cans with different cross sectional areas, along with a non-zero flow rate.

Keywords: combustor, dynamics, thermoacoustics, transfer function

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Authors: Alpana Tiwari, N. K. Gaur

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We have incorporated the translational rotational (TR) coupling effects in the framework of three body force shell model (TSM) to develop an extended TSM (ETSM). The dynamical matrix of ETSM has been applied to compute the phonon frequencies of orientationally disordered mixed crystal (ND4Br)x(KBr)1-x in (q00), (qq0) and (qqq) symmetry directions for compositions 0.10≤x≤0.50 at T=300K.These frequencies are plotted as a function of wave vector k. An unusual acoustic mode softening is found along symmetry directions (q00) and (qq0) as a result of translation-rotation coupling.

Keywords: orientational glass, phonons, TR-coupling, lattice dynamics

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Authors: M. Bučas, A. Skersonas, E. Ivanauskas, J. Lesutienė, N. Nika, G. Srėbalienė, E. Tiškus, J. Gintauskas, A.Šaškov, G. Martin

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Submerged vegetation enhances heterogeneity of sublittoral habitats; therefore, macrophyte stands are essential elements of aquatic ecosystems to maintain a diverse fish fauna. Fish-habitat relations have been extensively studied in streams and coastal waters, but in lakes and estuaries are still underestimated. The aim of this study is to assess temporal (diurnal and seasonal) patterns of fish juvenile assemblages associated with common submerged macrophyte habitats, which have significantly spread during the recent decade in the upper littoral part of the Curonian Lagoon. The assessment was performed by means of an upgraded pop-up net approach resulting in much precise sampling versus other techniques. The optimal number of samples (i.e., pop-up nets) required to cover>80% of the total number of fish species depended on the time of the day in both study sites: at least 7and 9 nets in the evening (18-24 pm) in the Southern and Northern study sites, respectively. In total, 14 fish species were recorded, where perch and roach dominated (respectively 48% and 24%). From multivariate analysis, water salinity and seasonality (temperature or sampling month) were primary factors determining fish assemblage composition. The southern littoral area, less affected by brackish water conditions, hosted a higher number of species (13) than in the Northern site (8). In the latter site, brackish water tolerant species (three-spined and nine-spined sticklebacks, spiny loach, roach, and round goby) were more abundant than in the Southern site. Perch and ruffe dominated in the Southern site. Spiny loach and nine-spined stickleback were more frequent in September, while ruffe, perch, and roach occurred more in July. The diel dynamics of the common species such as perch, roach, and ruffe followed the general pattern, but it was species specific and depended on the study site, habitat, and month. The species composition between macrophyte habitats did not significantly differ; however, it differed from the results obtained in 2005 at both study sites indicating the importance of expanded charophyte stands during the last decade in the littoral zone.

Keywords: diel dynamics, charophytes, pondweeds, herbivorous and benthivorous fishes, littoral, nursery habitat, shelter

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Authors: Majid Etaati, Hamid Majedi

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Relational planning approach proposed by Patsy Healey goes beyond the physical proximity and emphasizes social proximity. This approach stresses the importance of nodes and flows between nodes. Current plans in European cities have incrementally incorporated this approach, but urban plans in Iran have still stayed very detailed and rigid. In response to the weak evaluation results of the comprehensive planning approach in Qazvin, the local authorities applied the City Development Strategy (CDS) to cope with new urban challenges. The paper begins with an explanation of relational planning and suggests that Healey gives urban planners about spatial strategies and then it surveys relational factors in CDS of Qazvin. This study analyzes the extent which CDS of Qazvin have highlighted nodes, flows, and dynamics. In the end, the study concludes that there is a relational understanding of urban dynamics in the plan, but it is weak.

Keywords: relational, dynamics, city development strategy, urban planning, Qazvin

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Authors: Bruno Tassin, Robin Treilles, Cleo Stratmann, Minh Trang Nguyen, Sam Azimi, Vincent Rocher, Rachid Dris, Johnny Gasperi

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Microplastics (<5mm) in the environment and in hydro systems is one of the major present environmental issues. Over the last five years a research programme was conducted in order to assess the behavior of microplastics in the Seine river catchment, in a Man-Land-Sea continuum approach. Results show that microplastic concentration varies at the seasonal scale, but also at much smaller scales, during flood events and with tides in the estuary for instance. Moreover, microplastic sampling and characterization issues emerged throughout this work. The Seine river is a 750km long river flowing in Northwestern France. It crosses the Paris megacity (12 millions inhabitants) and reaches the English Channel after a 170 km long estuary. This site is a very relevant one to assess the effect of anthropogenic pollution as the mean river flow is low (mean flow around 350m³/s) while the human presence and activities are very intense. Monthly monitoring of the microplastic concentration took place over a 19-month period and showed significant temporal variations at all sampling stations but no significant upstream-downstream increase, indicating a possible major sink to the sediment. At the scale of a major flood event (winter and spring 2018), microplastic concentration shows an evolution similar to the well-known suspended solids concentration, with an increase during the increase of the flow and a decrease during the decrease of the flow. Assessing the position of the concentration peak in relation to the flow peak was unfortunately impossible. In the estuary, concentrations vary with time in connection with tides movements and in the water column in relation to the salinity and the turbidity. Although major gains of knowledge on the microplastic dynamics in the Seine river have been obtained over the last years, major gaps remain to deal mostly with the interaction with the dynamics of the suspended solids, the selling processes in the water column and the resuspension by navigation or shear stress increase. Moreover, the development of efficient chemical characterization techniques during the 5 year period of this pluriannual research programme led to the improvement of the sampling techniques in order to access smaller microplastics (>10µm) as well as larger but rare ones (>500µm).

Keywords: microplastics, Paris megacity, seine river, suspended solids

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Authors: Nashalla Gwyn Nyinda

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The ancient system of Tibetan Medicine, known as Sowa Rigpa across the Himalayan regions, is a systematic system of healing encouraging balance primarily through diet and behavior modifications. With the rise of the popularity of Tibetan Medicine, compliance is critical to successful treatment outcomes. As patients learn more about who they are as individuals and how their elemental balances or imbalances affect disorders and mental-emotional balance, they develop faith and dedication to their healing process. Specifically, regarding diet and behavior and the basic principles of the medical system, patient compliance increases dramatically in all treatment areas when they understand why a treatment or dietary prescription guidance is effective. Successful responses to Tibetan treatment rely on a buy-in from the patient. Trust between the slower process of Traditional medicine treatments, the Tibetan physician and the patient is a cornerstone of treatment. The resulting decrease in the use of allopathic medicine and better health outcomes for acute and chronic disorders are well documented. This paper addresses essential points of the Tibetan Medicine system, dialogue between doctor and patient focused on appropriate and seasonal changing dietetics. Such fluctuating treatment approaches, based on external elemental factors, dramatically increase treatment outcomes. Specifically, this work addresses why allopathic medicine models may need more trust development between practitioner and patient.

Keywords: compliancy in treatment, diet and lifestyle medicine, nature and elements as medicine, seasonal diets, Sowa Rigpa, traditional Tibetan medicine, treatment outcomes

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Authors: Pooja Verma, Sumana Ghosh

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There is a growing need for alternative way of power generation worldwide. The reason can be attributed to limited resources of fossil fuels, environmental pollution, increasing cost of conventional fuels, and lower efficiency of conversion of energy in existing systems. In this context, one of the potential alternatives for power generation is wave energy. However, it is difficult to estimate the amount of electrical energy generation in an irregular sea condition by experiment and or analytical methods. Therefore in this work, a numerical wave tank is developed using the computational fluid dynamics software Open FOAM. In this software a specific utility known as waves2Foam utility is being used to carry out the simulation work. The computational domain is a tank of dimension: 5m*1.5m*1m with a floating object of dimension: 0.5m*0.2m*0.2m. Regular waves are generated at the inlet of the wave tank according to Stokes second order theory. The main objective of the present study is to validate the numerical model against existing experimental data. It shows a good matching with the existing experimental data of floater displacement. Later the model is exploited to estimate energy extraction due to the movement of such a point absorber in real sea conditions. Scale down the wave properties like wave height, wave length, etc. are used as input parameters. Seasonal variations are also considered.

Keywords: OpenFOAM, numerical wave tank, regular waves, floating object, point absorber

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Authors: Dino Carpentras, Paul J. Maher, Caoimhe O'Reilly, Michael Quayle

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Opinion dynamics is a sub-field of agent-based modeling that focuses on people’s opinions and their evolutions over time. Despite the rapid increase in the number of publications in this field, it is still not clear how to apply these models to real-world scenarios. Indeed, there is no agreement on how people update their opinion while interacting. Furthermore, it is not clear if different topics will show the same dynamics (e.g., more polarized topics may behave differently). These problems are mostly due to the lack of experimental validation of the models. Some previous studies started bridging this gap in the literature by directly measuring people’s opinions before and after the interaction. However, these experiments force people to express their opinion as a number instead of using natural language (and then, eventually, encoding it as numbers). This is not the way people normally interact, and it may strongly alter the measured dynamics. Another limitation of these studies is that they usually average all the topics together, without checking if different topics may show different dynamics. In our work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions in natural language (“agree” or “disagree”). We also measured the certainty of their answer, expressed as a number between 1 and 10. However, this value was not shown to other participants to keep the interaction based on natural language. We then showed the opinion (and not the certainty) of another participant and, after a distraction task, we repeated the measurement. To make the data compatible with opinion dynamics models, we multiplied opinion and certainty to obtain a new parameter (here called “continuous opinion”) ranging from -10 to +10 (using agree=1 and disagree=-1). We firstly checked the 5 topics individually, finding that all of them behaved in a similar way despite having different initial opinions distributions. This suggested that the same model could be applied for different unpolarized topics. We also observed that people tend to maintain similar levels of certainty, even when they changed their opinion. This is a strong violation of what is suggested from common models, where people starting at, for example, +8, will first move towards 0 instead of directly jumping to -8. We also observed social influence, meaning that people exposed with “agree” were more likely to move to higher levels of continuous opinion, while people exposed with “disagree” were more likely to move to lower levels. However, we also observed that the effect of influence was smaller than the effect of random fluctuations. Also, this configuration is different from standard models, where noise, when present, is usually much smaller than the effect of social influence. Starting from this, we built an opinion dynamics model that explains more than 80% of data variance. This model was also able to show the natural conversion of polarization from unpolarized states. This experimental approach offers a new way to build models grounded on experimental data. Furthermore, the model offers new insight into the fundamental terms of opinion dynamics models.

Keywords: experimental validation, micro-dynamics rule, opinion dynamics, update rule

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Authors: R. Pilafkan, M. Kaffash Irzarahimi, S. F. Asbaghian Namin

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The biaxial buckling behavior of single-layered graphene sheets (SLGSs) is studied in the present work. To consider the size-effects in the analysis, Eringen’s nonlocal elasticity equations are incorporated into classical plate theory (CLPT). A Generalized Differential Quadrature Method (GDQM) approach is utilized and numerical solutions for the critical buckling loads are obtained. Then, molecular dynamics (MD) simulations are performed for a series of zigzag SLGSs with different side-lengths and with various boundary conditions, the results of which are matched with those obtained by the nonlocal plate model to numerical the appropriate values of nonlocal parameter relevant to each type of boundary conditions.

Keywords: biaxial buckling, single-layered graphene sheets, nonlocal elasticity, molecular dynamics simulation, classical plate theory

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Authors: Dino Carpentras, Alejandro Dinkelberg, Michael Quayle

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Within agent-based modeling, opinion dynamics is the field that focuses on modeling people's opinions. In this prolific field, most of the literature is dedicated to the exploration of the two 'degrees of freedom' and how they impact the model’s properties (e.g., the average final opinion, the number of final clusters, etc.). These degrees of freedom are (1) the interaction rule, which determines how agents update their own opinion, and (2) the network topology, which defines the possible interaction among agents. In this work, we show that the third degree of freedom exists. This can be used to change a model's output up to 100% of its initial value or to transform two models (both from the literature) into each other. Since opinion dynamics models are representations of the real world, it is fundamental to understand how people’s opinions can be measured. Even for abstract models (i.e., not intended for the fitting of real-world data), it is important to understand if the way of numerically representing opinions is unique; and, if this is not the case, how the model dynamics would change by using different representations. The process of measuring opinions is non-trivial as it requires transforming real-world opinion (e.g., supporting most of the liberal ideals) to a number. Such a process is usually not discussed in opinion dynamics literature, but it has been intensively studied in a subfield of psychology called psychometrics. In psychometrics, opinion scales can be converted into each other, similarly to how meters can be converted to feet. Indeed, psychometrics routinely uses both linear and non-linear transformations of opinion scales. Here, we analyze how this transformation affects opinion dynamics models. We analyze this effect by using mathematical modeling and then validating our analysis with agent-based simulations. Firstly, we study the case of perfect scales. In this way, we show that scale transformations affect the model’s dynamics up to a qualitative level. This means that if two researchers use the same opinion dynamics model and even the same dataset, they could make totally different predictions just because they followed different renormalization processes. A similar situation appears if two different scales are used to measure opinions even on the same population. This effect may be as strong as providing an uncertainty of 100% on the simulation’s output (i.e., all results are possible). Still, by using perfect scales, we show that scales transformations can be used to perfectly transform one model to another. We test this using two models from the standard literature. Finally, we test the effect of scale transformation in the case of finite precision using a 7-points Likert scale. In this way, we show how a relatively small-scale transformation introduces both changes at the qualitative level (i.e., the most shared opinion at the end of the simulation) and in the number of opinion clusters. Thus, scale transformation appears to be a third degree of freedom of opinion dynamics models. This result deeply impacts both theoretical research on models' properties and on the application of models on real-world data.

Keywords: degrees of freedom, empirical validation, opinion scale, opinion dynamics

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Authors: Nurul Bin Ibrahim

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Advancements in neural networks have offered valuable insights into Fluid Dynamics, notably in addressing turbulence-related challenges. In this research, we introduce multiple applications of models of neural networks, namely Feed-Forward and Recurrent Neural Networks, to explore the relationship between jet formations and stratified turbulence within stochastically excited Boussinesq systems. Using machine learning tools like TensorFlow and PyTorch, the study has created models that effectively mimic and show the underlying features of the complex patterns of jet formation and stratified turbulence. These models do more than just help us understand these patterns; they also offer a faster way to solve problems in stochastic systems, improving upon traditional numerical techniques to solve stochastic differential equations such as the Euler-Maruyama method. In addition, the research includes a thorough comparison with the Statistical State Dynamics (SSD) approach, which is a well-established method for studying chaotic systems. This comparison helps evaluate how well neural networks can help us understand the complex relationship between jet formations and stratified turbulence. The results of this study underscore the potential of neural networks in computational physics and fluid dynamics, opening up new possibilities for more efficient and accurate simulations in these fields.

Keywords: neural networks, machine learning, computational fluid dynamics, stochastic systems, simulation, stratified turbulence

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Authors: Keiwoma Mark Yila, Mathew Lamrana Siaffa Gboku, Mohamed Sahr Lebbie, Lamin Ibrahim Kamara

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Rainfall and temperature are the important variables which are often used to trace climate variability and change. A perception study and analysis of climatic data were conducted to assess the changes in rainfall and temperature and their impact on crop production in Moyamba district, Sierra Leone. For the perception study, 400 farmers were randomly selected from farmer-based organizations (FBOs) in 4 chiefdoms, and 30 agricultural extension workers (AWEs) in the Moyamba district were purposely selected as respondents. Descriptive statistics and Kendall’s test of concordance was used to analyze the data collected from the farmers and AEWs. Data for the analysis of variability and trends of rainfall and temperature from 1991 to 2020 were obtained from the Sierra Leone Meteorological Agency and Njala University and grouped into monthly, seasonal and annual time series. Regression analysis was used to determine the statistical values and trend lines for the seasonal and annual time series data. The Mann-Kendall test and Sen’s Slope Estimator were used to analyze the trends' significance and magnitude, respectively. The results of both studies show evidence of climate change in the Moyamba district. A substantial number of farmers and AEWs perceived a decrease in the annual rainfall amount, length of the rainy season, a late start and end of the rainy season, an increase in the temperature during the day and night, and a shortened harmattan period over the last 30 years. Analysis of the meteorological data shows evidence of variability in the seasonal and annual distribution of rainfall and temperature, a decreasing and non-significant trend in the rainy season and annual rainfall, and an increasing and significant trend in seasonal and annual temperature from 1991 to 2020. However, the observed changes in rainfall and temperature by the farmers and AEWs partially agree with the results of the analyzed meteorological data. The majority of the farmers perceived that; adverse weather conditions have negatively affected crop production in the district. Droughts, high temperatures, and irregular rainfall are the three major adverse weather events that farmers perceived to have contributed to a substantial loss in the yields of the major crops cultivated in the district. In response to the negative effects of adverse weather events, a substantial number of farmers take no action due to their lack of knowledge and technical or financial capacity to implement climate-sensitive agricultural (CSA) practices. Even though few farmers are practising some CSA practices in their farms, there is an urgent need to build the capacity of farmers and AEWs to adapt to and mitigate the negative impacts of climate change. The most priority support needed by farmers is the provision of climate-resilient crop varieties, whilst the AEWs need training on CSA practices.

Keywords: climate change, crop productivity, farmer’s perception, rainfall, temperature, Sierra Leone

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Authors: Ling Dai

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Surface-sensing devices such as atomic force microscope have been widely used to characterize the surface structure and properties of nanoscale polymer films. However, using molecular dynamics simulations, we show that there is intrinsic and unavoidable inelastic deformation at polymer surfaces induced by the sensing tip. For linear chain polymers like perfluoropolyether, such tip-induced deformation derives from the differences in the atomic interactions which are atomic specie-based Van der Waals interactions, and resulting in atomic shuffling and causing inelastic alternation in both molecular structures and mechanical properties at the regions of the polymer surface. For those aromatic chain polymers like epoxy, the intrinsic deformation is depicted as the intra-chain rotation of aromatic rings and kinking of linear atomic connections. The present work highlights the need to reinterpret the data obtained from surface-sensing tests by considering this intrinsic inelastic deformation occurring at polymer surfaces.

Keywords: polymer, surface, nano, molecular dynamics

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Authors: Sanghoon Bae, Hanju Cha

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Failed fuel detector (FFD) in research reactor is a very crucial instrument to detect the anomaly from failed fuels in the early stage around primary cooling system (PCS) outlet prior to the decay tank. FFD is considered as a mandatory sensor to ensure the integrity of fuel assemblies and mitigate the consequence from a failed fuel accident. For the effective function of FFD, the location of them should be determined by contemplating the effect from coolant flow around two outlets. For this, the analysis on computational flow dynamics (CFD) should be first performed how the coolant outlet flow including radioactive materials from failed fuels are mixed and discharged through the outlet plenum within certain seconds. The analysis result shows that the outlet flow is well mixed regardless of the position of failed fuel and ultimately illustrates the effect of detector location.

Keywords: computational flow dynamics (CFD), failed fuel detector (FFD), fresh fuel assembly (FFA), spent fuel assembly (SFA)

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Authors: Michel Wakim, Rodrigo Rivera Tinoco

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Supersonic ejector is an economical device that use high pressure vapor to compress a low pressure vapor without any rotating parts or external power sources. Entrainment ratio is a major characteristic of the ejector performance, so the ejector performance is highly dependent on its geometry. The aim of this paper is to design ejector geometry, based on pre-specified operating conditions, and to study the flow behavior inside the ejector by using computational fluid dynamics ‘CFD’ by using ‘ANSYS FLUENT 15.0’ software. In the first section; 1-D mathematical model is carried out to predict the ejector geometry. The second part describes the flow behavior inside the designed model. CFD is the most reliable tool to reveal the mixing process at different parts of the supersonic turbulent flow and to study the effect of the geometry on the effective ejector area. Finally, the results show the effect of the geometry on the entrainment ratio.

Keywords: computational fluids dynamics, ejector, entrainment ratio, geometry optimization, performance

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Authors: Isha Sharawat, R. P. Dahiya, T. R. Sreekrishnan

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One of the environmental challenges in India is urban wastewater management as regulations and infrastructural development has not kept pace with the urbanization and growing population. The quality of life of people is also improving with the rapid growth of the gross domestic product. This has contributed to the enhancement in the per capita water requirement and consumption. More domestic water consumption generates more wastewater. The scarcity of potable water is making the situation quite serious, and water supply has to be regulated in most parts of the country during summer. This requires elaborate and concerted efforts to efficiently manage the water resources and supply systems. In this article, a system dynamics modelling approach is used for estimating the water demand and wastewater generation in a district headquarter city of North India. Projections are made till the year 2035. System dynamics is a software tool used for formulation of policies. On the basis of the estimates, policy scenarios are developed for sustainable development of water resources in conformity with the growing population. Mitigation option curtailing the water demand and wastewater generation include population stabilization, water reuse and recycle and water pricing. The model is validated quantitatively, and sensitivity analysis tests are carried out to examine the robustness of the model.

Keywords: system dynamics, wastewater, water pricing, water recycle

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Authors: S. Mamoucha, N. Tsafantakis, Α. Ioannidis, S. Chatzipanagiotou, C. Nikolaou, L. Skaltsounis, N. Fokialakis, N. Christodoulakis

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Introduction: Plant secondary metabolites (SM) can be grouped into three chemically distinct groups: terpenes, phenolics, and nitrogen-containing compounds. For many years the adaptive significance of SM was unknown. They were thought to be functionless end-products. Currently it is accepted that many secondary metabolites (also known as natural products) have important ecological roles in plants. For instance, they serve as attractants (odor, color, taste) for pollinators and seed-dispersing animals. Moreover, they protect plants from herbivores, microbial pathogens and from environmental stress (high and low temperatures, drought, alkalinity, salinity, radiation etc). It is well known that both biotic and abiotic stress often increase the accumulation of SM. The local climatic conditions, seasonal changes, external factors such as light, temperature, humidity affect the biosynthesis and composition of secondary metabolites. A well known dioecious evergreen plant, Pistacia lentiscus L. (mastic tree), was selected in order to study the metabolic variations occur in response to the different climate conditions, due to the seasonal variation and its effect on the biosynthesis of bioactive compounds. Materials-methods: Young and mature leaves were collected in January and July 2014, dried and extracted by accelerated solvent extraction (Dionex ASE™ 350) using solvents of increased polarity (DCM, MeOH, and H2O). GC-MS and UHPLC-HRMS analysis were carried out in order to define the nature and the relative abundance of SM. The antibacterial activity was evaluated by using the Agar Disc Diffusion Assay against ATCC and clinical isolates strains: Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, Candida albicans, Streptococcus mutans and Klebsiella pneumoniae. All tests were carried out in duplicate and the average radii of the inhibition zones were calculated for each extract. Results: According to the phytochemical profile obtained from each extract, the biosynthesis of SM varied both qualitatively and quantitatively under the two different types of seasonal stress. With exception of the biologically inactive nonpolar DCM extract of July, all extracts inhibited the growth of most of the investigated microorganisms. A clear positive correlation has been observed between the relative abundance of SM and the bioactivity of the DCM extracts of January and July. Observed changes during phytochemical analysis were mainly focused on the triterpenoid content. On the other hand, the bioactivity of the polar extracts (MeOH and H2O) of January and July resulted practically invariable against most of the microorganisms, besides the significant variation of the SM content due to the seasonal variation. Conclusion: Our results clearly confirmed the hypothesis of abiotic stress as an important regulating factor that significantly affects the biosynthesis of secondary metabolites and thus the presence of bioactive compounds. Acknowledgment: This work was supported by IKY - State Scholarship Foundation, Athens, Greece.

Keywords: antibacterial screening, phytochemical profile, Pistacia lentiscus, abiotic stress

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Authors: Nini Johana Marín Rodríguez, William Fernando Oquendo Patino

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In this work, we model a coupled system where we explore the effects of steady and random behavior on a linear system like an extension of the classic Strogatz model. This is exemplified by modeling a couple love dynamics as a linear system of two coupled differential equations and studying its stability for four types of lovers chosen as CC='Cautious- Cautious', OO='Only other feelings', OP='Opposites' and RR='Romeo the Robot'. We explore the effects of, first, introducing saturation, and second, adding a random variation to one of the CC-type lover, which will shape his character by trying to model how its variability influences the dynamics between love and hate in couple in a long run relationship. This work could also be useful to model other kind of systems where interactions can be modeled as linear systems with external or internal random influence. We found the final results are not easy to predict and a strong dependence on initial conditions appear, which a signature of chaos.

Keywords: differential equations, dynamical systems, linear system, love dynamics

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Authors: Jagdish Prasad Maurya, Sanjay Kumar Pandey

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Inadequate understanding of the complex nature of flow features in tornado vortex is a major problem in modelling tornadoes. Tornadoes are violent atmospheric phenomenon that appear all over the world. Modelling tornadoes aim to reduce the loss of the human lives and material damage caused by the tornadoes. Dynamics of tornado is investigated by a numerical technique, the improved version of the projection method. In this paper, authors solve the problem for axisymmetric tornado vortex by the said method that uses a finite difference approach for getting an accurate and stable solution. The conclusions drawn are that large radial inflow velocity occurs near the ground that leads to increase the tangential velocity. The increased velocity phenomenon occurs close to the boundary and absolute maximum wind is obtained near the vortex core. The results validate previous numerical and theoretical models.

Keywords: computational fluid dynamics, mathematical model, Navier-Stokes equations, tornado

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Authors: Samah Laalej, Abdelfattah Bouatem

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In the field of wind turbine blades, it is complicated to evaluate the aerodynamic performances through experimental measurements as it requires a lot of computing time and resources. Therefore, in this paper, a hybrid BEM-CFD numerical technique is developed to predict power and aerodynamic forces acting on the blades. Computational fluid dynamics (CFD) simulation was conducted to calculate the drag and lift forces through Ansys software using the K-w model. Then an enhanced BEM code was created to predict the power outputs generated by the wind turbine using the aerodynamic properties extracted from the CFD approach. The numerical approach was compared and validated with experimental data. The power curves calculated from this hybrid method were in good agreement with experimental measurements for all velocity ranges.

Keywords: blade element momentum, aerodynamic forces, wind turbine blades, computational fluid dynamics approach

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Authors: Kassahun Birhanu Tadesse, Megersa Olumana Dinka

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Reliable future river flow information is basic for planning and management of any river systems. For data scarce river system having only a river flow records like the Waterval River, a univariate time series models are appropriate for river flow forecasting. In this study, a univariate Seasonal Autoregressive Integrated Moving Average (SARIMA) model was applied for forecasting Waterval River flow using GRETL statistical software. Mean monthly river flows from 1960 to 2016 were used for modeling. Different unit root tests and Mann-Kendall trend analysis were performed to test the stationarity of the observed flow time series. The time series was differenced to remove the seasonality. Using the correlogram of seasonally differenced time series, different SARIMA models were identified, their parameters were estimated, and diagnostic check-up of model forecasts was performed using white noise and heteroscedasticity tests. Finally, based on minimum Akaike Information (AIc) and Hannan-Quinn (HQc) criteria, SARIMA (3, 0, 2) x (3, 1, 3)12 was selected as the best model for Waterval River flow forecasting. Therefore, this model can be used to generate future river information for water resources development and management in Waterval River system. SARIMA model can also be used for forecasting other similar univariate time series with seasonality characteristics.

Keywords: heteroscedasticity, stationarity test, trend analysis, validation, white noise

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Authors: Karla Sanchez-Ortiz, Yunuen Tapia-Torres, John Larsen, Felipe Garcia-Oliva

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Due to food demand production, the use of synthetic nitrogenous fertilizer has increased in agricultural soils to replace the N losses. Nevertheless, the intensive use of synthetic nitrogenous fertilizer in conventional agriculture negatively affects the soil and therefore the environment, so alternatives such as organic agriculture have been proposed for being more environmentally friendly. However, further research in soil is needed to see how agricultural management affects the dynamics of C and N. The objective of this research was to evaluate the C and N dynamics in the soil with three different agricultural management: an agricultural plot with intensive inorganic fertilization, a plot with semi-organic management and an agricultural plot with recent abandonment (2 years). For each plot, the soil C and N dynamics and the enzymatic activity of NAG and β-Glucosidase were characterized. Total C and N concentration of the plant biomass of each site was measured as well. Dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) was higher in abandoned plot, as well as this plot had higher total carbon (TC) and total nitrogen (TN), besides microbial N and microbial C. While the enzymatic activity of NAG and β-Glucosidase was greater in the agricultural plot with inorganic fertilization, as well as nitrate (NO₃) was higher in fertilized plot, in comparison with the other two plots. The aboveground biomass (AB) of maize in the plot with inorganic fertilization presented higher TC and TN concentrations than the maize AB growing in the semiorganic plot, but the C:N ratio was highest in the grass AB in the abandoned plot. The C:N ration in the maize grain was greater in the semi-organic agricultural plot. These results show that the plot under intensive agricultural management favors the loss of soil organic matter and N, degrading the dynamics of soil organic compounds, promoting its fertility depletion.

Keywords: mineralization, nitrogen cycle, soil degradation, soil nutrients

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Authors: Abdelhafid Zenati, Mohamed Tadjine

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The mathematical formulation of biomedical problems is an important phase to understand and predict the dynamic of the controlled population. In this paper we perform a stability analysis of a coupled model for healthy and cancerous cells dynamics in Acute Myeloid Leukemia, this represents our first aim. Second, we illustrate the effect of the interconnection between healthy and cancer cells. The PDE-based model is transformed to a nonlinear distributed state space model (delay system). For an equilibrium point of interest, necessary and sufficient conditions of global asymptotic stability are given. Thus, we came up to give necessary and sufficient conditions of global asymptotic stability of the origin and the healthy situation and control of the dynamics of normal hematopoietic stem cells and cancerous during myelode Acute leukemia. Simulation studies are given to illustrate the developed results.

Keywords: distributed delay, global stability, modelling, nonlinear models, PDE, state space

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Authors: Sandeep Mohan Ahuja, Gulshan Kumar Jawa

Abstract:

Cyclone separators are crucial components in various industries tasked with efficiently separating particulate matter from gas streams. Achieving optimal performance hinges on a deep understanding of flow dynamics and particle behaviour within these separators. In this investigation, Computational Fluid Dynamics (CFD) simulations are conducted utilizing the Discrete Phase Model (DPM) to dissect the intricate flow patterns, particle trajectories, and separation efficiency within cyclone separators. The study delves into the influence of pivotal parameters like inlet velocity, particle size distribution, and cyclone geometry on separation efficiency. Through numerical simulations, a comprehensive comprehension of fluid-particle interaction phenomena within cyclone separators is attained, allowing for the assessment of separation efficiency across diverse operational conditions and geometrical setups. The insights gleaned from this study promise to advance our understanding of the complex interplay between fluid and particle within cyclone separators, thereby enabling optimization across a wide array of industrial applications. By harnessing the power of CFD simulations and the DPM, this research endeavours to furnish valuable insights for designing, operating, and evaluating the performance of cyclone separators, ultimately fostering greater efficiency and environmental sustainability within industrial processes.

Keywords: cyclone separator, computational fluid dynamics, enhancing efficiency, discrete phase model

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Authors: A. Jéglot, F. Plauborg, M. K. Schnorr, R. S. Sørensen, L. Elsgaard

Abstract:

Artificial wetlands such as woodchip bioreactors are efficient tools to remove nitrate from agricultural wastewater with a minimized environmental impact. However, the temperature dependence of the microbiological nitrate removal prevents the woodchip bioreactors from being an efficient system when the water temperature drops below 8℃. To quantify and describe the temperature effects on nitrate removal efficiency, we studied nitrate-reducing enrichments from a woodchip bioreactor in Denmark based on samples collected in Spring and Fall. Growth was quantified as optical density, and nitrate and nitrous oxide concentrations were measured in time-course experiments to compare the growth of the microbial population and the nitrate conversion efficiencies at different temperatures. Ammonia was measured to indicate the importance of dissimilatory nitrate reduction to ammonia (DNRA) in nitrate conversion for the given denitrifying community. The temperature responses observed followed the increasing trend proposed by the Arrhenius equation, indicating higher nitrate removal efficiencies at higher temperatures. However, the growth and the nitrous oxide production observed at low temperature provided evidence of the psychrotolerance of the microbial community under study. The assays conducted showed higher nitrate removal from the microbial community extracted from the woodchip bioreactor at the cold season compared to the ones extracted during the warmer season. This indicated the ability of the bacterial populations in the bioreactor to evolve and adapt to different seasonal temperatures.

Keywords: agricultural waste water treatment, artificial wetland, denitrification, psychrophilic conditions

Procedia PDF Downloads 96

Authors: T. N. Girish, B. E. Pradeep, Ravi Parkash

Abstract:

Insects from tropical wet or dry seasons are likely to cope starvation stress through seasonal phenotypic plasticity in energy metabolites. Accordingly, we analyzed such plastic changes in Zaprionus indianus flies reared under wet or dry season-specific conditions; and also after adult acclimation at 32℃ for 1 to 6 days; and to low (40% RH) or high (70% RH) humidity. Both thermal or humidity acclimation revealed significant accumulation of body lipids for wet season flies but low humidity acclimation did not change the level of body lipids in dry season flies. Developmental and adult acclimation showed sex specific differences i.e., starvation resistance and body lipids were higher in the males of dry season but in females of wet season. We found seasonal and sex specific differences in the relative level for body lipids at death; and in the rates of accumulation or utilization of energy metabolites (body lipids, carbohydrates and proteins). Body lipids constitute the preferred energy source under starvation for flies of both the seasons. However, utilization of carbohydrates (~20% to 30%) and proteins (~20% to 25%) was evident only in dry season flies. Higher starvation resistance after thermal or humidity acclimation is achieved by increased accumulation of lipids. Adult acclimation of wet or dry season flies revealed plastic changes in mean daily fecundity despite reduction in fecundity under starvation. Thus, thermal or humidity induced plastic responses in body lipids support starvation resistance under wet or dry seasons.

Keywords: heat or humidity acclimation, plastic changes in body lipids and starvation resistance, tropical drosophilid, Wet- or Dry seasons, Zaprionus indianus

Procedia PDF Downloads 123

Authors: Carlos A. Acosta, Amar Bhalla, Ruyan Guo

Abstract:

Scraped surface heat exchangers (SSHE) use a rotor shaft assembly with scraping blades to homogenize viscous fluids during the heat transfer process. Obtaining in-situ measurements is difficult because the rotor and scraping blades spin continuously inside the mixing chamber, obstructing the instrumentation pathway. Computational fluid dynamics simulations provide useful insight into the flow behavior around the scraper blades for a variety of fluids and blade geometries. However, numerical solutions often focus on the fluid dynamics and heat transfer phenomena of rotating flow, ignoring the glass-transition temperature and freezing point depression. This research studies the multi-phase fluid dynamics and freezing point depression inside the SSHE with non-isothermal conditions in a time dependent process using an aqueous solution that contains 13.5 wt.% high fructose corn syrup and CO₂. The computational results were validated with in-situ pressure, temperature, and optical spectroscopy measurements. Results from the numerical model show good quantitatively agreement with experimental values.

Keywords: computational fluid dynamics, freezing point depression, phase-transition temperature, multi-phase flow

Procedia PDF Downloads 114

Authors: Carlos Gonzalez

Abstract:

When communicating using private and secure keys, there is always the doubt as to the identity of the message creator. We introduce an algorithm that uses the personal typing rhythm (keystroke dynamics) of the message originator to increase the trust of the authenticity of the message originator by the message recipient. The methodology proposes the use of a Rhythm Certificate Authority (RCA) to validate rhythm information. An illustrative example of the communication between Bob and Alice and the RCA is included. An algorithm of how to communicate with the RCA is presented. This RCA can be an independent authority or an enhanced Certificate Authority like the one used in public key infrastructure (PKI).

Keywords: authentication, digital signature, keystroke dynamics, personal rhythm, public-key encryption

Procedia PDF Downloads 266

Authors: Radha Krishan, Deepak Khare, Bhaskar R. Nikam, Ayush Chandrakar

Abstract:

Every irrigation project is planned considering long-term historical climatic conditions; however, the prompt climatic shift and change has come out with such circumstances which were inconceivable in the past. Considering this fact, scrutiny of rainfall and temperature trend has been carried out over the command area of Eastern Ganga Canal project for pre-climate shift period and post-climate shift periods in the present study. Non-parametric Mann-Kendall and Sen’s methods have been applied to study the trends in annual rainfall, seasonal rainfall, annual rainy day, monsoonal rainy days, average annual temperature and seasonal temperature. The results showed decreasing trend of 48.11 to 42.17 mm/decade in annual rainfall and 79.78 tSo 49.67 mm/decade in monsoon rainfall in pre-climate to post-climate shift periods, respectively. The decreasing trend of 1 to 4 days/decade has been observed in annual rainy days from pre-climate to post-climate shift period. Trends in temperature revealed that there were significant decreasing trends in annual (-0.03 ºC/yr), Kharif (-0.02 ºC/yr), Rabi (-0.04 ºC/yr) and summer (-0.02 ºC/yr) season temperature during pre-climate shift period, whereas the significant increasing trend (0.02 ºC/yr) has been observed in all the four parameters during post climate shift period. These results will help project managers in understanding the climate shift and lead them to develop alternative water management strategies.

Keywords: climate shift, rainfall trend, temperature trend, Mann-Kendall test, sen slope estimator, eastern Ganga canal command

Procedia PDF Downloads 108