Search results for: modeling and optimization

Authors: Lei Xue, Liye Zhao, Jundong Wang, Yu Xue

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A hybrid energy conversion system composed of a floating offshore wind turbine (FOWT) and wave energy converters (WECs) may possibly reduce the levelized cost of energy, improving the platform dynamics and increasing the capacity to harvest energy. This paper investigates the aerodynamic performance and dynamic responses of the combined semi-submersible FOWT and point-absorber WECs in frequency and time domains using synthetic optimizing control under turbulent wind and irregular wave conditions. Individual pitch control is applied to the FOWT part, while spring–damping control is used on the WECs part, as well as the synergistic control effect of both are studied. The effect of the above control optimization is analyzed under several typical working conditions, such as below-rated wind speed, rated wind speed, and above-rated wind speed by OpenFAST and WEC-Sim software. Particularly, the wind-wave misalignment is also comparatively investigated, which has demonstrated the importance of applying proper integrated optimal control in this hybrid energy system. More specifically, the combination of individual pitch control and spring–damping control is able to mitigate the platform pitch motion and improve output power. However, the increase in blade root load needs to be considered which needs further investigations in the future.

Keywords: floating offshore wind turbine, wave energy converters, control optimization, individual pitch control, dynamic response

Procedia PDF Downloads 53

Authors: Davood Barari Tari

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In order to investigate the correlation of rice traits in different nitrogen management methods by modeling programming, an experiment was laid out in rice paddy field in an experimental field at Caspian Coastal Sea region from 2013 to 2014. Variety used was Shiroudi as a high yielding variety. Nitrogen management was in two methods. Amount of nitrogen at four levels (30, 60, 90, and 120 Kg N ha-1 and control) and nitrogen-splitting at four levels (T1: 50% in base + 50% in maximum tillering stage, T2= 33.33% basal +33.33% in maximum tillering stage +33.33% in panicle initiation stage, T3=25% basal+37.5% in maximum tillering stage +37.5% in panicle initiation stage, T4: 25% in basal + 25% in maximum tillering stage + 50% in panicle initiation stage). Results showed that nitrogen traits, total grain number, filled spikelets, panicle number per m2 had a significant correlation with grain yield. Results related to calibrated and validation of rice model methods indicated that correlation between rice yield and yield components was accurate. The correlation between panicle length and grain yield was minimum. Physiological indices was simulated with low accuracy. According to results, investigation of the correlation between rice traits in physiological, morphological and phenological characters and yield by modeling and simulation methods are very useful.

Keywords: rice, physiology, modelling, simulation, yield traits

Procedia PDF Downloads 343

Authors: Shilpesh R. Rajpurohit, Harshit K. Dave

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Fused deposition modeling (FDM) gains popularity in recent times, due to its capability to create prototype as well as functional end use product directly from CAD file. Parts fabricated using FDM process have mechanical properties comparable with those of injection-molded parts. However, performance of the FDM part is severally affected by the poor mechanical properties of the part due to nature of layered structure of printed part. Mechanical properties of the part can be improved by proper selection of process variables. In the present study, a comparative study between unidirectional and bidirectional raster angle has been carried out at a combination of different layer height and raster width. Unidirectional raster angle varied at five different levels, and bidirectional raster angle has been varied at three different levels. Fabrication of tensile specimen and tensile testing of specimen has been conducted according to ASTM D638 standard. From the results, it can be observed that higher tensile strength has been obtained at 0° raster angle followed by 45°/45° raster angle, while lower tensile strength has been obtained at 90° raster angle. Analysis of fractured surface revealed that failure takes place along with raster deposition direction for unidirectional and zigzag failure can be observed for bidirectional raster angle.

Keywords: additive manufacturing, fused deposition modeling, unidirectional, bidirectional, raster angle, tensile strength

Procedia PDF Downloads 185

Authors: Zahid Ullah, Atlas Khan

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In today's data-driven world, the role of mathematics in bridging the gap between theory and applications is becoming increasingly vital. This abstract highlights the significance of mathematics as a powerful tool for analyzing, interpreting, and extracting meaningful insights from vast amounts of data. By integrating mathematical principles with real-world applications, researchers can unlock the full potential of data-driven decision-making processes. This abstract delves into the various ways mathematics acts as a bridge connecting theoretical frameworks to practical applications. It explores the utilization of mathematical models, algorithms, and statistical techniques to uncover hidden patterns, trends, and correlations within complex datasets. Furthermore, it investigates the role of mathematics in enhancing predictive modeling, optimization, and risk assessment methodologies for improved decision-making in diverse fields such as finance, healthcare, engineering, and social sciences. The abstract also emphasizes the need for interdisciplinary collaboration between mathematicians, statisticians, computer scientists, and domain experts to tackle the challenges posed by the data-driven landscape. By fostering synergies between these disciplines, novel approaches can be developed to address complex problems and make data-driven insights accessible and actionable. Moreover, this abstract underscores the importance of robust mathematical foundations for ensuring the reliability and validity of data analysis. Rigorous mathematical frameworks not only provide a solid basis for understanding and interpreting results but also contribute to the development of innovative methodologies and techniques. In summary, this abstract advocates for the pivotal role of mathematics in bridging theory and applications in a data-driven world. By harnessing mathematical principles, researchers can unlock the transformative potential of data analysis, paving the way for evidence-based decision-making, optimized processes, and innovative solutions to the challenges of our rapidly evolving society.

Keywords: mathematics, bridging theory and applications, data-driven world, mathematical models

Procedia PDF Downloads 75

Authors: Dessalegn Abera Waktole, Boru Jia, Zhengxing Zuo, Wei Wang, Nianling Kuang

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A flexible thermoelectric generator is one method for recycling waste heat. This research provides the optimum performance of a flexible thermoelectric generator with optimal geometric parameters and a detailed structural design. In this research, a numerical simulation and experiment were carried out to develop an efficient, flexible thermoelectric generator for energy harvesting from human skin. Heteromorphic electrodes and a polyimide substrate with a copper-printed circuit board were introduced into the structural design of a flexible thermoelectric generator. The heteromorphic electrode was used as a heat sink and component of a flexible thermoelectric generator to enhance the temperature difference within the thermoelectric legs. Both N-type and P-type thermoelectric legs were made of bismuth selenium telluride (Bi1.7Te3.7Se0.3) and bismuth antimony telluride (Bi0.4Sb1.6Te3). The output power of the flexible thermoelectric generator was analyzed under different heat source temperatures and heat dissipation conditions. The COMSOL Multiphysics 5.6 software was used to conduct the simulation, which was validated by experiment. It is recorded that the maximum power output of 232.064μW was obtained by considering different wind speed conditions, the ambient temperature of 20℃, and the heat source temperature of 36℃ under various load resistance conditions, which range from 0.24Ω to 0. 91Ω. According to this finding, heteromorphic electrodes have a significant impact on the performance of the device.

Keywords: flexible thermoelectric generator, optimization, performance, temperature gradient, waste heat recovery

Procedia PDF Downloads 164

Authors: Jiahui Yang, John Quigley, Lesley Walls

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In this paper, the authors develop a stochastic model regarding the investment in supplier delivery performance development from a buyer’s perspective. The authors propose a multivariate model through a Multinomial-Dirichlet distribution within an Empirical Bayesian inference framework, representing both the epistemic and aleatory uncertainties in deliveries. A closed form solution is obtained and the lower and upper bound for both optimal investment level and expected profit under uncertainty are derived. The theoretical properties provide decision makers with useful insights regarding supplier delivery performance improvement problems where multiple delivery statuses are involved. The authors also extend the model from a single supplier investment into a supplier portfolio, using a Lagrangian method to obtain a theoretical expression for an optimal investment level and overall expected profit. The model enables a buyer to know how the marginal expected profit/investment level of each supplier changes with respect to the budget and which supplier should be invested in when additional budget is available. An application of this model is illustrated in a simulation study. Overall, the main contribution of this study is to provide an optimal investment decision making framework for supplier development, taking into account multiple delivery statuses as well as multiple projects.

Keywords: decision making, empirical bayesian, portfolio optimization, supplier development, supply chain management

Procedia PDF Downloads 288

Authors: Vasudha Hegde, Narendra Chaulagain, H. M. Ravikumar, Sonu Mishra, Siva Yellampalli

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Acoustic sensors are extensively used in recent days not only for sensing and condition monitoring applications but also for small scale energy harvesting applications to power wireless sensor networks (WSN) due to their inherent advantages. The natural frequency of the structure plays a major role in energy harvesting applications since the sensor key element has to operate at resonant frequency. In this paper, circular diaphragm based MEMS acoustic sensor is modelled by Lumped Element Model (LEM) and the natural frequency is compared with the simulated model using Finite Element Method (FEM) tool COMSOL Multiphysics. The sensor has the circular diaphragm of 3000 µm radius and thickness of 30 µm to withstand the high SPL (Sound Pressure Level) and also to withstand the various fabrication steps. A Piezoelectric ZnO layer of thickness of 1 µm sandwiched between two aluminium electrodes of thickness 0.5 µm and is coated on the diaphragm. Further, a channel with radius 3000 µm radius and length 270 µm is connected at the bottom of the diaphragm. The natural frequency of the structure by LEM method is approximately 16.6 kHz which is closely matching with that of simulated structure with suitable approximations.

Keywords: acoustic sensor, diaphragm based, lumped element modeling (LEM), natural frequency, piezoelectric

Procedia PDF Downloads 442

Authors: Jaimala Ghambir, Tilak Thakur, Puneet Chawla

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As per the statistical data, the Doubly-fed Induction Generator (DFIG) based wind turbine with variable speed and variable pitch control is the most common wind turbine in the growing wind market. This machine is usually used on the grid connected wind energy conversion system to satisfy grid code requirements such as grid stability, fault ride through (FRT), power quality improvement, grid synchronization and power control etc. Though the requirements are not fulfilled directly by the machine, the control strategy is used in both the stator as well as rotor side along with power electronic converters to fulfil the requirements stated above. To satisfy the grid code requirements of wind turbine, usually grid side converter is playing a major role. So in order to improve the operation capacity of wind turbine under critical situation, the intensive study of both machine side converter control and grid side converter control is necessary In this paper DFIG is modeled using power components as variables and the performance of the DFIG system is analysed under grid voltage fluctuations. The voltage fluctuations are made by lowering and raising the voltage values in the utility grid intentionally for the purpose of simulation keeping in view of different grid disturbances.

Keywords: DFIG, dynamic modeling, DPC, sag, swell, voltage fluctuations, FRT

Procedia PDF Downloads 462

Authors: Siri Marthe Arbo, Afaf Saai, Sture Sørli, Mette Nedreberg

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This work aims to establish a reliable approach for optimizing a Laser Metal Deposition (LMD) process for a critical maritime component, based on the material properties and structural performance required by the maritime industry. The component of interest is a water jet impeller, for which specific requirements for material properties are defined. The developed approach is based on the assessment of the effects of LMD process parameters on microstructure and material performance of standard AM 2205 duplex stainless steel powder. Duplex stainless steel offers attractive properties for maritime applications, combining high strength, enhanced ductility and excellent corrosion resistance due to the specific amounts of ferrite and austenite. These properties are strongly affected by the microstructural characteristics in addition to microstructural defects such as porosity and welding defects, all strongly influenced by the chosen LMD process parameters. In this study, the influence of deposition speed and heat input was evaluated. First, the influences of deposition speed and heat input on the microstructure characteristics, including ferrite/austenite fraction, amount of porosity and welding defects, were evaluated. Then, the achieved mechanical properties were evaluated by standard testing methods, measuring the hardness, tensile strength and elongation, bending force and impact energy. The measured properties were compared to the requirements of the water jet impeller. The results show that the required amounts of ferrite and austenite can be achieved directly by the LMD process without post-weld heat treatments. No intermetallic phases were observed in the material produced by the investigated process parameters. A high deposition speed was found to reduce the ductility due to the formation of welding defects. An increased heat input was associated with reduced strength due to the coarsening of the ferrite/austenite microstructure. The microstructure characterizations and measured mechanical performance demonstrate the great potential of the LMD process and generate a valuable database for the optimization of the LMD process for duplex stainless steels.

Keywords: duplex stainless steel, laser metal deposition, process optimization, microstructure, mechanical properties

Procedia PDF Downloads 218

Authors: Hassiba Benguergoura, Kamal Chanane, Sâad Moulay

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Pervaporation (PV), a membrane-based separation technology, has gained much attention because of its energy saving capability and low-cost, especially for separation of azeotropic or close-boiling liquid mixtures. There are two crucial issues for industrial application of pervaporation process. The first is developing membrane material and tailoring membrane structure to obtain high pervaporation performances. The second is modeling pervaporation transport to better understand of the above-mentioned structure–pervaporation relationship. Many models were proposed to predict the mass transfer process, among them, solution-diffusion model is most widely used in describing pervaporation transport including preferential sorption, diffusion and evaporation steps. For modeling pervaporation transport, the permeation flux, which depends on the solubility and diffusivity of components in the membrane, should be obtained first. Traditionally, the solubility was calculated according to the Flory–Huggins theory. Separation of the benzene (Bz)/cyclohexane (Cx) mixture is industrially significant. Numerous papers have been focused on the Bz/Cx system to assess the PV properties of membrane materials. Membranes with both high permeability and selectivity are desirable for practical application. Several new polymers have been prepared to get both high permeability and selectivity. Styrene-butadiene rubbers (SBR), dense membranes cross-linked by chloromethylation were used in the separation of benzene/cyclohexane mixtures. The impact of chloromethylation reaction as a new method of cross-linking SBR on the pervaporation performance have been reported. In contrast to the vulcanization with sulfur, the cross-linking takes places on styrene units of polymeric chains via a methylene bridge. The partial pervaporative (PV) fluxes of benzene/cyclohexane mixtures in styrene-butadiene rubber (SBR) were predicted using Fick's first law. The predicted partial fluxes and the PV separation factor agreed well with the experimental data by integrating Fick's law over the benzene concentration. The effects of feed concentration and operating temperature on the predicted permeation flux by this proposed model are investigated. The predicted permeation fluxes are in good agreement with experimental data at lower benzene concentration in feed, but at higher benzene concentration, the model overestimated permeation flux. The predicted and experimental permeation fluxes all increase with operating temperature increasing. Solvent sorption levels for benzene/ cyclohexane mixtures in a SBR membrane were determined experimentally. The results showed that the solvent sorption levels were strongly affected by the feed composition. The Flory- Huggins equation generates higher R-square coefficient for the sorption selectivity.

Keywords: benzene, cyclohexane, pervaporation, permeation, sorption modeling, SBR

Procedia PDF Downloads 326

Authors: L. Grinis

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Turbulent flow in complex geometries receives considerable attention due to its importance in many engineering applications. It has been the subject of interest for many researchers. Some of these interests include the design of storm water channels. The design of these channels requires testing through physical models. The main practical limitation of physical models is the so called “scale effect”, that is, the fact that in many cases only primary physical mechanisms can be correctly represented, while secondary mechanisms are often distorted. These observations form the basis of our study, which centered on problems associated with the design of storm water channels near the Dead Sea, in Israel. To help reach a final design decision we used different physical models. Our research showed good coincidence with the results of laboratory tests and theoretical calculations, and allowed us to study different effects of fluid flow in an open channel. We determined that problems of this nature cannot be solved only by means of theoretical calculation and computer simulation. This study demonstrates the use of physical models to help resolve very complicated problems of fluid flow through baffles and similar structures. The study applies these models and observations to different construction and multiphase water flows, among them, those that include sand and stone particles, a significant attempt to bring to the testing laboratory a closer association with reality.

Keywords: open channel, physical modeling, baffles, turbulent flow

Procedia PDF Downloads 284

Authors: Dena Alhaloul

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The Middle East and North Africa (MENA) region is characterized by diverse cultures, economies, and social structures. Fertility rates in MENA have seen significant changes over time, with variations among countries and subregions. Understanding fertility patterns in this region is essential due to its impact on demographic dynamics, healthcare, labor markets, and social policies. Rising or declining fertility rates have far-reaching consequences for the region's socioeconomic development. The main thrust of this study is to comprehensively examine fertility rates in the Middle East and North Africa (MENA) region. It aims to understand the distribution, determinants, and temporal trends of fertility rates in MENA countries. The study seeks to provide insights into the factors influencing fertility decisions, assess how fertility rates have evolved over time, and potentially develop statistical models to characterize these trends. As for the methodology of the study, the study uses descriptive statistics to summarize and visualize fertility rate data. It also uses regression analyses to identify determinants of fertility rates as well as statistical modeling to characterize temporal trends in fertility rates. The conclusion of this study The research will contribute to a deeper understanding of fertility dynamics in the MENA region, shedding light on the distribution of fertility rates, their determinants, and historical trends.

Keywords: fertility, distribution, modeling, regression

Procedia PDF Downloads 81

Authors: Yenny Paola Morales Cortés, Fabián Rico Rodríguez, Juan Carlos Serrato Bermúdez, Carlos Arturo Martínez Riascos

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Numerous benefits of galactooligosaccharides (GOS) as prebiotics have motivated the study of enzymatic processes for their production. These processes have special complexities due to several factors that make difficult high productivity, such as enzyme type, reaction medium pH, substrate concentrations and presence of inhibitors, among others. In the present work the production of galactooligosaccharides (with different degrees of polymerization: two, three and four) from lactose was studied. The study considers the formulation of a mathematical model that predicts the production of GOS from lactose using the enzyme β-galactosidase. The effect of pH in the reaction was studied. For that, phosphate buffer was used and with this was evaluated three pH values (6.0.6.5 and 7.0). Thus it was observed that at pH 6.0 the enzymatic activity insignificant. On the other hand, at pH 7.0 the enzymatic activity was approximately 27 times greater than at 6.5. The last result differs from previously reported results. Therefore, pH 7.0 was chosen as working pH. Additionally, the enzyme concentration was analyzed, which allowed observing that the effect of the concentration depends on the pH and the concentration was set for the following studies in 0.272 mM. Afterwards, experiments were performed varying the lactose concentration to evaluate its effects on the process and to generate the data for the adjustment of the mathematical model parameters. The mathematical model considers the reactions of lactose hydrolysis and transgalactosylation for the production of disaccharides and trisaccharides, with their inverse reactions. The production of tetrasaccharides was negligible and, because of that, it was not included in the model. The reaction was monitored by HPLC and for the quantitative analysis of the experimental data the Matlab programming language was used, including solvers for differential equations systems integration (ode15s) and nonlinear problems optimization (fminunc). The results confirm that the transgalactosylation and hydrolysis reactions are reversible, additionally inhibition by glucose and galactose is observed on the production of GOS. In relation to the production process of galactooligosaccharides, the results show that it is necessary to have high initial concentrations of lactose considering that favors the transgalactosylation reaction, while low concentrations favor hydrolysis reactions.

Keywords: β-galactosidase, galactooligosaccharides, inhibition, lactose, Matlab, modeling

Procedia PDF Downloads 358

Authors: Siamak Eskandari, Neda Ebadi

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Among common electronic parts which have been invented and have made a great revolution in the lighting system through the world, certainly LEDs have no rival. These small parts with their very low power consumption, very dazzling and powerful light and small size and with their extremely high lifetime- compared to incandescent bulbs and compact fluorescent lamp (CFLs) have undoubtedly revolutionized the lighting industry of the world. Based on conducted studies and experiments, in addition to their acceptable light and low power consumption -compared to incandescent bulbs and CFLs-, they have very low and in some cases zero environmental pollution and negative effects on human beings. Because of their longevity, in the case of using high-quality circuits and proper and consistent use of LEDs in conventional and intelligent buildings, there will be no need to replace the burnout lamps, for a long time (10 years). In this study which was conducted on 10-watt power LEDs with suitable heatsink/cooling, considerable amount of heat was generated during lighting after 5 minutes and 45 seconds. The temperature rose to above 99 degrees Celsius and this amount of heat can raise the water temperature to 60 degrees Celsius and more. Based on conducted experiments, this can provide the heat required for bathing, washing, radiators (in cold seasons) easily and only by imposing very low cost and it will be a big step in the optimization of energy consumption in the future.

Keywords: energy, light, water, optimization of power LED

Procedia PDF Downloads 153

Authors: Jing Jiang, Wenhuan XU, Lei Zhang, Shiyi Zhang, Tongli Wang

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Climate data quality significantly affects the reliability of ecological modeling. In the Asia Pacific (AP) region, low-quality climate data hinders ecological modeling. ClimateAP, a software developed in 2017, generates high-quality climate data for the AP region, benefiting researchers in forestry and agriculture. However, its adoption remains limited. This study aims to confirm the validity of biologically relevant variable data generated by ClimateAP during the normal climate period through comparison with the currently available gridded data. Climate data from 2,366 weather stations were used to evaluate the prediction accuracy of ClimateAP in comparison with the commonly used gridded data from WorldClim1.4. Univariate regressions were applied to 48 monthly biologically relevant variables, and the relationship between the observational data and the predictions made by ClimateAP and WorldClim was evaluated using Adjusted R-Squared and Root Mean Squared Error (RMSE). Locations were categorized into mountainous and flat landforms, considering elevation, slope, ruggedness, and Topographic Position Index. Univariate regressions were then applied to all biologically relevant variables for each landform category. Random Forest (RF) models were implemented for the climatic niche modeling of Cunninghamia lanceolata. A comparative analysis of the prediction accuracies of RF models constructed with distinct climate data sources was conducted to evaluate their relative effectiveness. Biologically relevant variables were obtained from three unpublished Chinese meteorological datasets. ClimateAPv3.0 and WorldClim predictions were obtained from weather station coordinates and WorldClim1.4 rasters, respectively, for the normal climate period of 1961-1990. Occurrence data for Cunninghamia lanceolata came from integrated biodiversity databases with 3,745 unique points. ClimateAP explains a minimum of 94.74%, 97.77%, 96.89%, and 94.40% of monthly maximum, minimum, average temperature, and precipitation variances, respectively. It outperforms WorldClim in 37 biologically relevant variables with lower RMSE values. ClimateAP achieves higher R-squared values for the 12 monthly minimum temperature variables and consistently higher Adjusted R-squared values across all landforms for precipitation. ClimateAP's temperature data yields lower Adjusted R-squared values than gridded data in high-elevation, rugged, and mountainous areas but achieves higher values in mid-slope drainages, plains, open slopes, and upper slopes. Using ClimateAP improves the prediction accuracy of tree occurrence from 77.90% to 82.77%. The biologically relevant climate data produced by ClimateAP is validated based on evaluations using observations from weather stations. The use of ClimateAP leads to an improvement in data quality, especially in non-mountainous regions. The results also suggest that using biologically relevant variables generated by ClimateAP can slightly enhance climatic niche modeling for tree species, offering a better understanding of tree species adaptation and resilience compared to using gridded data.

Keywords: climate data validation, data quality, Asia pacific climate, climatic niche modeling, random forest models, tree species

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Authors: Rituparna Nath, Shawn J. Marshall

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Glaciers are one of the main sensitive climatic indicators, as they respond strongly to small climatic shifts. We develop a flow line model of glacier dynamics to simulate the past and future extent of glaciers in the Canadian Rocky Mountains, with the aim of coupling this model within larger scale regional climate models of glacier response to climate change. This paper will focus on glacier-climate modeling and reconstructions of glacier volume from the Little Ice Age (LIA) to present for Athabasca Glacier, Alberta, Canada. Glacier thickness, volume and mass change will be constructed using flow line modelling and examination of different climate scenarios that are able to give good reconstructions of LIA ice extent. With the availability of SPOT 5 imagery, Digital elevation models and GIS Arc Hydro tool, ice catchment properties-glacier width and LIA moraines have been extracted using automated procedures. Simulation of glacier mass change will inform estimates of meltwater run off over the historical period and model calibration from the LIA reconstruction will aid in future projections of the effects of climate change on glacier recession. Furthermore, the model developed will be effective for further future studies with ensembles of glaciers.

Keywords: flow line modeling, Athabasca Glacier, glacier mass balance, Remote Sensing, Arc hydro tool, little ice age

Procedia PDF Downloads 268

Authors: Marcela Karmazínová, Michal Štrba, Miln Pilgr

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The paper deals with the problems of the actual behavior, failure mechanism and load-carrying capacity of the special bolt connection developed and intended for the assembly connections of truss main girders of perspective railway temporary steel bridges. Within the framework of this problem solution, several types of structural details of assembly joints have been considered as the conceptual structural design. Based on the preliminary evaluation of advantages or disadvantages of these ones, in principle two basic structural configurations so-called “tooth” and “splice-plate” connections have been selected for the subsequent detailed investigation. This investigation is mainly based on the experimental verification of the actual behavior, strain and failure mechanism and corresponding strength of the connection, and on its numerical modeling using FEM. This paper is focused only on the cyclic loading (fatigue) tests results of “splice-plate” connections and their evaluation, which have already been finished. Simultaneously with the fatigue tests, the static loading tests have been realized too, but these ones, as well as FEM numerical modeling, are not the subject of this paper.

Keywords: Bolt assembly connection, cyclic loading, failure mechanisms, fatigue strength, steel structure, structural detail category, temporary railway bridge

Procedia PDF Downloads 444

Authors: Haileyesus Tessema Alemneh, Abiyu Enyew Molla, Oluwole Daniel Makinde

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Introduction: Faba bean is one of the most important grown plants worldwide for humans and animals. Several biotic and abiotic elements have limited the output of faba beans, irrespective of their diverse significance. Many faba bean pathogens have been reported so far, of which the most important yield-limiting disease is chocolate spot disease (Botrytis fabae). The dynamics of disease transmission and decision-making processes for intervention programs for disease control are now better understood through the use of mathematical modeling. Currently, a lot of mathematical modeling researchers are interested in plant disease modeling. Objective: In this paper, a deterministic mathematical model for chocolate spot disease (CSD) on faba bean plant with an optimal control model was developed and analyzed to examine the best strategy for controlling CSD. Methodology: Three control interventions, quarantine (u2), chemical control (u3), and prevention (u1), are employed that would establish the optimal control model. The optimality system, characterization of controls, the adjoint variables, and the Hamiltonian are all generated employing Pontryagin’s maximum principle. A cost-effective approach is chosen from a set of possible integrated strategies using the incremental cost-effectiveness ratio (ICER). The forward-backward sweep iterative approach is used to run numerical simulations. Results: The Hamiltonian, the optimality system, the characterization of the controls, and the adjoint variables were established. The numerical results demonstrate that each integrated strategy can reduce the diseases within the specified period. However, due to limited resources, an integrated strategy of prevention and uprooting was found to be the best cost-effective strategy to combat CSD. Conclusion: Therefore, attention should be given to the integrated cost-effective and environmentally eco-friendly strategy by stakeholders and policymakers to control CSD and disseminate the integrated intervention to the farmers in order to fight the spread of CSD in the Faba bean population and produce the expected yield from the field.

Keywords: CSD, optimal control theory, Pontryagin’s maximum principle, numerical simulation, cost-effectiveness analysis

Procedia PDF Downloads 87

Authors: Kamran Siddique, Hiroyuki Asada, Yoshifumi Ogami

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The use of Micro Gas Turbine (MGT) as the engine in Unmanned Aerobic Vehicles (UAVs) and power source in Robotics is widespread these days. Research has been conducted in the past decade or so to improve the performance of different components of MGT. This type of engine has interrelated components which have non-linear characteristics. Therefore, the overall engine performance depends on the individual engine element’s performance. Computational Fluid Dynamics (CFD) is one of the simulation method tools used to analyze or even optimize MGT system performance. In this study, the compressor of the MGT is designed, and performance optimization is being done using CFD. Performance of the micro compressor is improved in order to increase the overall performance of MGT. A high value of pressure ratio is to be achieved by studying the effect of change of different operating parameters like mass flow rate and revolutions per minute (RPM) and aerodynamical and geometrical parameters on the pressure ratio of the compressor. Two types of compressor designs are considered in this study; 3D centrifugal and ‘planar’ designs. For a 10 mm impeller, the planar model is the simplest compressor model with the ease in manufacturability. On the other hand, 3D centrifugal model, although more efficient, is very difficult to manufacture using current microfabrication resources. Therefore, the planar model is the best-suited model for a micro compressor. So. a planar micro compressor has been designed that has a good pressure ratio, and it is easy to manufacture using current microfabrication technologies. Future work is to fabricate the compressor to get experimental results and validate the theoretical model.

Keywords: computational fluid dynamics, microfabrication, MEMS, unmanned aerobic vehicles

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Authors: H. K. Esfahani, B. Datta

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Groundwater is one of the most important natural resources in many parts of the world; however it is widely polluted due to human activities. Currently, effective and reliable groundwater management and remediation strategies are obtained using characterization of groundwater pollution sources, where the measured data in monitoring locations are utilized to estimate the unknown pollutant source location and magnitude. However, accurately identifying characteristics of contaminant sources is a challenging task due to uncertainties in terms of predicting source flux injection, hydro-geological and geo-chemical parameters, and the concentration field measurement. Reactive transport of chemical species in contaminated groundwater systems, especially with multiple species, is a complex and highly non-linear geochemical process. Although sufficient concentration measurement data is essential to accurately identify sources characteristics, available data are often sparse and limited in quantity. Therefore, this inverse problem-solving method for characterizing unknown groundwater pollution sources is often considered ill-posed, complex and non- unique. Different methods have been utilized to identify pollution sources; however, the linked simulation-optimization approach is one effective method to obtain acceptable results under uncertainties in complex real life scenarios. With this approach, the numerical flow and contaminant transport simulation models are externally linked to an optimization algorithm, with the objective of minimizing the difference between measured concentration and estimated pollutant concentration at observation locations. Concentration measurement data are very important to accurately estimate pollution source properties; therefore, optimal design of the monitoring network is essential to gather adequate measured data at desired times and locations. Due to budget and physical restrictions, an efficient and effective approach for groundwater pollutant source characterization is to design an optimal monitoring network, especially when only inadequate and arbitrary concentration measurement data are initially available. In this approach, preliminary concentration observation data are utilized for preliminary source location, magnitude and duration of source activity identification, and these results are utilized for monitoring network design. Further, feedback information from the monitoring network is used as inputs for sequential monitoring network design, to improve the identification of unknown source characteristics. To design an effective monitoring network of observation wells, optimization and interpolation techniques are used. A simulation model should be utilized to accurately describe the aquifer properties in terms of hydro-geochemical parameters and boundary conditions. However, the simulation of the transport processes becomes complex when the pollutants are chemically reactive. Three dimensional transient flow and reactive contaminant transport process is considered. The proposed methodology uses HYDROGEOCHEM 5.0 (HGCH) as the simulation model for flow and transport processes with chemically multiple reactive species. Adaptive Simulated Annealing (ASA) is used as optimization algorithm in linked simulation-optimization methodology to identify the unknown source characteristics. Therefore, the aim of the present study is to develop a methodology to optimally design an effective monitoring network for pollution source characterization with reactive species in polluted aquifers. The performance of the developed methodology will be evaluated for an illustrative polluted aquifer sites, for example an abandoned mine site in Queensland, Australia.

Keywords: monitoring network design, source characterization, chemical reactive transport process, contaminated mine site

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Authors: Nicolae Daniel Stoica, Ion Mierlus Mazilu

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This work is one of numerical research and aims to address the issue of the design of new buildings in a 3D location of existing buildings. In today's continuous development and congestion of urban centers is a big question about the influence of the new buildings on an already existent vicinity site. Thus, in this study, we tried to focus on how existent buildings may be affected by any newly constructed buildings and in how far this influence is really decreased. The problem of modeling the influence of interaction between buildings is not simple in any area in the world, and neither in Romania. Unfortunately, most often the designers not done calculations that can determine how close to reality these 3D influences nor the simplified method and the more superior methods. In the most literature making a "shield" (the pilots or molded walls) is absolutely sufficient to stop the influence between the buildings, and so often the soil under the structure is ignored in the calculation models. The main causes for which the soil is neglected in the analysis are related to the complexity modeling of interaction between soil and structure. In this paper, based on a new simple but efficient methodology we tried to determine for a lot of study cases the influence, in terms of assessing the interaction land structure on the behavior of structures that influence a new building on an existing one. The study covers additional subsidence that may occur during the execution of new works and after its completion. It also highlighted the efforts diagrams and deflections in the soil for both the original case and the final stage. This is necessary to see to what extent the expected impact of the new building on existing areas.

Keywords: soil, structure, interaction, piles, earthquakes

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Authors: Younis Elhaddad, Alfonso Ortega

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Oil production by means of gas lift is a standard technique in oil production industry. To optimize the total amount of oil production in terms of the amount of gas injected is a key question in this domain. Different methods have been tested to propose a general methodology. Many of them apply well-known numerical methods. Some of them have taken into account the power of evolutionary approaches. Our goal is to provide the experts of the domain with a powerful automatic searching engine into which they can introduce their knowledge in a format close to the one used in their domain, and get solutions comprehensible in the same terms, as well. These proposals introduced in the genetic engine the most expressive formal models to represent the solutions to the problem. These algorithms have proven to be as effective as other genetic systems but more flexible and comfortable for the researcher although they usually require huge search spaces to justify their use due to the computational resources involved in the formal models. The first step to evaluate the viability of applying our approaches to this realm is to fully understand the domain and to select an instance of the problem (gas lift optimization) in which applying genetic approaches could seem promising. After analyzing the state of the art of this topic, we have decided to choose a previous work from the literature that faces the problem by means of numerical methods. This contribution includes details enough to be reproduced and complete data to be carefully analyzed. We have designed a classical, simple genetic algorithm just to try to get the same results and to understand the problem in depth. We could easily incorporate the well mathematical model, and the well data used by the authors and easily translate their mathematical model, to be numerically optimized, into a proper fitness function. We have analyzed the 100 curves they use in their experiment, similar results were observed, in addition, our system has automatically inferred an optimum total amount of injected gas for the field compatible with the addition of the optimum gas injected in each well by them. We have identified several constraints that could be interesting to incorporate to the optimization process but that could be difficult to numerically express. It could be interesting to automatically propose other mathematical models to fit both, individual well curves and also the behaviour of the complete field. All these facts and conclusions justify continuing exploring the viability of applying the approaches more sophisticated previously proposed by our research group.

Keywords: evolutionary automatic programming, gas lift, genetic algorithms, oil production

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Authors: Egemen Sert, Leila Hedayatifar, Rachel A. Rigg, Amir Akhavan, Olha Buchel, Dominic Elias Saadi, Aabir Abubaker Kar, Alfredo J. Morales, Yaneer Bar-Yam

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The complexity of providing timely and cost-effective distribution of finished goods from industrial facilities to customers makes effective operational coordination difficult, yet effectiveness is crucial for maintaining customer service levels and sustaining a business. Logistics planning becomes increasingly complex with growing numbers of customers, varied geographical locations, the uncertainty of future orders, and sometimes extreme competitive pressure to reduce inventory costs. Linear optimization methods become cumbersome or intractable due to a large number of variables and nonlinear dependencies involved. Here we develop a complex systems approach to optimizing logistics networks based upon dimensional reduction methods and apply our approach to a case study of a manufacturing company. In order to characterize the complexity in customer behavior, we define a “customer space” in which individual customer behavior is described by only the two most relevant dimensions: the distance to production facilities over current transportation routes and the customer's demand frequency. These dimensions provide essential insight into the domain of effective strategies for customers; direct and indirect strategies. In the direct strategy, goods are sent to the customer directly from a production facility using box or bulk trucks. In the indirect strategy, in advance of an order by the customer, goods are shipped to an external warehouse near a customer using trains and then "last-mile" shipped by trucks when orders are placed. Each strategy applies to an area of the customer space with an indeterminate boundary between them. Specific company policies determine the location of the boundary generally. We then identify the optimal delivery strategy for each customer by constructing a detailed model of costs of transportation and temporary storage in a set of specified external warehouses. Customer spaces help give an aggregate view of customer behaviors and characteristics. They allow policymakers to compare customers and develop strategies based on the aggregate behavior of the system as a whole. In addition to optimization over existing facilities, using customer logistics and the k-means algorithm, we propose additional warehouse locations. We apply these methods to a medium-sized American manufacturing company with a particular logistics network, consisting of multiple production facilities, external warehouses, and customers along with three types of shipment methods (box truck, bulk truck and train). For the case study, our method forecasts 10.5% savings on yearly transportation costs and an additional 4.6% savings with three new warehouses.

Keywords: logistics network optimization, direct and indirect strategies, K-means algorithm, dimensional reduction

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Authors: Fredrick Ishengoma, Leonard Mselle, Hector Mongi

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The growing number of mobile phone subscribers in Tanzania offers the government a new channel for the delivery of information and government services to citizens, thus mobile Government (m-Government). In Tanzania, m-Government services usage is in the early stages, and factors that influence its adoption are yet to be known. This study seeks to identify and understand the critical success factors (CSFs) that influence citizens’ behavioural intention (BI) to adopt m-Government services in Tanzania. The study employed the mobile services acceptance model (MSAM) and extends it with external factors relevant in the Tanzanian context. A survey questionnaire was used to collect primary data from users of m-Government services in Dar es salaam and Dodoma cities, and 253 responses were received. Data were analyzed by IBM-SPSS AMOS 23.0 software using structural equation modeling (SEM). The findings of the study indicate that perceived usefulness, trust, perceived mobility, power distance, quality of service, awareness, perceived cost, personal initiatives, and characteristics significantly influence the BI to adopt m-Government services. However, perceived ease of use was found statistically insignificant to predict BI. Furthermore, the interplay between CSFs, discussion on theoretical and practical implications that follow from the results are presented.

Keywords: adoption, critical success factors, structural equation modeling, m-Government, MSAM, Tanzania

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Authors: M. Bevilacqua, F. E. Ciarapica, G. Marcucci

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Supply Chain Resilience has been broadly studied during the last decade, focusing the research on many aspects of Supply Chain performance. Consequently, different definitions of Supply Chain Resilience have been developed by the research community, drawing inspiration also from other fields of study such as ecology, sociology, psychology, economy et al. This way, the definitions so far developed in the extant literature are therefore very heterogeneous, and many authors have pointed out a lack of consensus in this field of analysis. The aim of this research is to find common points between these definitions, through the development of a framework of study: the Resilience Triangle. The Resilience Triangle is a tool developed in the field of civil engineering, with the objective of modeling the loss of resilience of a given structure during and after the occurrence of a disruption such as an earthquake. The Resilience Triangle is a simple yet powerful tool: in our opinion, it can summarize all the features that authors have captured in the Supply Chain Resilience definitions over the years. This research intends to recapitulate within this framework all these heterogeneities in Supply Chain Resilience research. After collecting a various number of Supply Chain Resilience definitions present in the extant literature, the methodology approach provides a taxonomy step with the scope of collecting and analyzing all the data gathered. The next step provides the comparison of the data obtained with the plotting of a disruption profile, in order to contextualize the Resilience Triangle in the Supply Chain context. The tool and the results developed in this research will allow to lay the foundation for future Supply Chain Resilience modeling and measurement work.

Keywords: supply chain resilience, resilience definition, supply chain resilience triangle

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Authors: P. Kazymbet, G. Abildinova, K.Makhambetov, M. Bakhtin, D. Rybalkina, K. Zhumadilov

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Conducted cytogenetic research in workers Stepnogorsk Mining-Chemical Combine (Akmola region) with the study of 26341 chromosomal metaphase. Using a regression analysis with program DataFit, version 5.0, dependence between exposure dose and the following cytogenetic exponents has been studied: frequency of aberrant cells, frequency of chromosomal aberrations, frequency of the amounts of dicentric chromosomes, and centric rings. Experimental data on calibration curves "dose-effect" enabled the development of a mathematical model, allowing on data of the frequency of aberrant cells, chromosome aberrations, the amounts of dicentric chromosomes and centric rings calculate the absorbed dose at the time of the study. In the dose range of 0.1 Gy to 5.0 Gy dependence cytogenetic parameters on the dose had the following equation: Y = 0,0067е^0,3307х (R2 = 0,8206) – for frequency of chromosomal aberrations; Y = 0,0057е^0,3161х (R2 = 0,8832) –for frequency of cells with chromosomal aberrations; Y =5 Е-0,5е^0,6383 (R2 = 0,6321) – or frequency of the amounts of dicentric chromosomes and centric rings on cells. On the basis of cytogenetic parameters and regression equations calculated absorbed dose in workers of uranium production at the time of the study did not exceed 0.3 Gy.

Keywords: Stepnogorsk, mathematical modeling, cytogenetic, dicentric chromosomes

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Authors: Prabha Rohatgi

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To obtain an efficient control over a huge amount of inventory of drugs in pharmacy department of any hospital, generally, the medicines are categorized on the basis of their cost ‘ABC’ (Always Better Control), first and then categorize on the basis of their criticality ‘VED’ (Vital, Essential, desirable) for prioritization. About one-third of the annual expenditure of a hospital is spent on medicines. To minimize the inventory investment, the hospital management may like to keep the medicines inventory low, as medicines are perishable items. The main aim of each and every hospital is to provide better services to the patients under certain limited resources. To achieve the satisfactory level of health care services to outdoor patients, a hospital has to keep eye on the wastage of medicines because expiry date of medicines causes a great loss of money though it was limited and allocated for a particular period of time. The objectives of this study are to identify the categories of medicines requiring incentive managerial control. In this paper, to minimize the total inventory cost and the cost associated with the wastage of money due to expiry of medicines, an inventory control model is used as an estimation tool and then nonlinear programming technique is used under limited budget and fixed number of orders to be placed in a limited time period. Numerical computations have been given and shown that by using scientific methods in hospital services, we can give more effective way of inventory management under limited resources and can provide better health care services. The secondary data has been collected from a hospital to give empirical evidence.

Keywords: ABC-VED inventory classification, multi item inventory problem, nonlinear programming technique, optimization of EOQ

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Authors: Ying-Pin Chang

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This paper presents a method for combining a particle swarm optimization with nonlinear time-varying evolution and orthogonal arrays (PSO-NTVEOA) in the planning of harmonic filters for the high speed railway traction system with specially connected transformers in unbalanced three-phase power systems. The objective is to minimize the cost of the filter, the filters loss, the total harmonic distortion of currents and voltages at each bus simultaneously. An orthogonal array is first conducted to obtain the initial solution set. The set is then treated as the initial training sample. Next, the PSO-NTVEOA method parameters are determined by using matrix experiments with an orthogonal array, in which a minimal number of experiments would have an effect that approximates the full factorial experiments. This PSO-NTVEOA method is then applied to design optimal harmonic filters in Taiwan High Speed Rail (THSR) traction system, where both rectifiers and inverters with IGBT are used. From the results of the illustrative examples, the feasibility of the PSO-NTVEOA to design an optimal passive harmonic filter of THSR system is verified and the design approach can greatly reduce the harmonic distortion. Three design schemes are compared that V-V connection suppressing the 3rd order harmonic, and Scott and Le Blanc connection for the harmonic improvement is better than the V-V connection.

Keywords: harmonic filters, particle swarm optimization, nonlinear time-varying evolution, orthogonal arrays, specially connected transformers

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Authors: Sanja Podunavac-Kuzmanović, Denis Kučević, Strahinja Kovačević, Milica Karadžić, Lidija Jevrić

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The present study describes the application of chemometric methods in analysis of milk samples which were collected in a conventional dairy farm and an organic dairy farm in AP Vojvodina, Republic of Serbia. The chemometric analysis included the application of univariate regression modeling and Analysis of Variance (ANOVA) method. The ANOVA was used in order to determine the differences in fatty acids content in the milk samples from conventional and organic farm. The results of the ANOVA testing indicate that there is a highly statistically significant difference between the content of fatty acid (saturated fatty acid vs. unsaturated fatty acids) in different dairy farming. Besides, the linear univariate models have been obtained as a result of modeling the linear relationships between the milk fat content and saturated fatty acids content, and the linear relationships between the milk fat content and unsaturated fatty acids content. The models obtained on the basis of the milk samples which originate from the organic farming are statistically better than the models based on the milk samples from conventional farming.

Keywords: hemometrics, milk, organic farming, quality control

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Authors: E Tolufase

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The demand, high costs and health implications of using energy derived from hydrocarbon compound have necessitated the continuous search for alternative source of energy. The World energy market is facing some challenges viz: depletion of fossil fuel reserves, population explosion, lack of energy security, economic and urbanization growth and also, in Nigeria some rural areas still depend largely on wood, charcoal, kerosene, petrol among others, as the sources of their energy. To overcome these short falls in energy supply and demand, as well as taking into consideration the risks from global climate change due to effect of greenhouse gas emissions and other pollutants from fossil fuels’ combustion, brought a lot of attention on efficiently harnessing the renewable energy sources. A very promising among the renewable energy resources for a clean energy technology for power production, vehicle and domestic usage is biogas. Therefore, optimization of biogas yield and quality is imperative. Hence, this study investigated yield and quality of biogas using low cost bio-digester and combination of various feed stocks referred to as co-digestion. Batch/Discontinuous Bio-digester type was used because it was cheap, easy, plausible and appropriate for different substrates used to get the desired results. Three substrates were used; cow dung, chicken droppings and lemon grass digested in five separate 21 litre digesters, A, B, C, D, and E and the gas collection system was designed using locally available materials. For single digestion we had; cow dung, chicken droppings, lemon grass, in Bio-digesters A, B, and C respectively, the co-digested three substrates in different mixed ratio 7:1:2 in digester D and E in ratio 5:3:2. The respective feed-stocks materials were collected locally, digested and analyzed in accordance with standard procedures. They were pre-fermented for a period of 10 days before being introduced into the digesters. They were digested for a retention period of 28 days, the physiochemical parameters namely; pressure, temperature, pH, volume of the gas collector system and volume of biogas produced were all closely monitored and recorded daily. The values of pH and temperature ranged 6.0 - 8.0, and 220C- 350C respectively. For the single substrate, bio-digester A(Cow dung only) produced biogas of total volume 0.1607m3(average volume of 0.0054m3 daily),while B (Chicken droppings ) produced 0.1722m3 (average of 0.0057m3 daily) and C (lemon grass) produced 0.1035m3 (average of 0.0035m3 daily). For the co-digested substrates in bio-digester D the total biogas produced was 0.2007m³ (average volume of 0.0067m³ daily) and bio-digester E produced 0.1991m³ (average volume of 0.0066m³ daily) It’s obvious from the results, that combining different substrates gave higher yields than when a singular feed stock was used and also mixing ratio played some roles in the yield improvement. Bio-digesters D and E contained the same substrates but mixed with different ratios, but higher yield was noticed in D with mixing ratio of 7:1:2 than in E with ratio 5:3:2.Therefore, co-digestion of substrates and mixing proportions are important factors for biogas production optimization.

Keywords: anaerobic, batch, biogas, biodigester, digestion, fermentation, optimization

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