Search results for: optimal irrigation

Authors: Alexander Aurell

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One of the latest trends in the modeling of human crowds is the mean-field game approach. In the mean-field game approach, the motion of a human crowd is described by a nonstandard stochastic optimal control problem. It is nonstandard since congestion is considered, introduced through a dependence in the performance functional on the distribution of the crowd. This study extends the class of mean-field pedestrian crowd models to allow for non-local congestion and arbitrary, but finitely, many interacting crowds. The new congestion feature grants pedestrians a 'personal space' where crowding is undesirable. The model is treated as a mean-field type game which is derived from a particle picture. This, in contrast to a mean-field game, better describes a situation where the crowd can be controlled by a central planner. The latter is suitable for decentralized situations. Solutions to the mean-field type game are characterized via a Pontryagin-type Maximum Principle.

Keywords: congestion, crowd dynamics, interacting populations, mean-field approximation, optimal control

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Authors: S. Adhirai, R. P. Mahapatra, Paramjit Singh

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Optimization is an important tool in making decisions and in analysing physical systems. In mathematical terms, an optimization problem is the problem of finding the best solution from among the set of all feasible solutions. The paper discusses the Whale Optimization Algorithm (WOA), and its applications in different fields. The algorithm is tested using MATLAB because of its unique and powerful features. The benchmark functions used in WOA algorithm are grouped as: unimodal (F1-F7), multimodal (F8-F13), and fixed-dimension multimodal (F14-F23). Out of these benchmark functions, we show the experimental results for F7, F11, and F19 for different number of iterations. The search space and objective space for the selected function are drawn, and finally, the best solution as well as the best optimal value of the objective function found by WOA is presented. The algorithmic results demonstrate that the WOA performs better than the state-of-the-art meta-heuristic and conventional algorithms.

Keywords: optimization, optimal value, objective function, optimization problems, meta-heuristic optimization algorithms, Whale Optimization Algorithm, implementation, MATLAB

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Authors: Seyedomid Fatemi

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The walls of the building, as the main intermediary between the outside and the inside of the building, play an important role in controlling the environmental conditions and ensuring the comfort of the residents, thus reducing the heating and cooling loads. Therefore, the use of suitable materials is considered one of the simplest and most effective ways to reduce the heating and cooling loads of the building, which will also save energy. Therefore, in order to achieve the goal of the research "Ranking of optimal materials for building walls," optimal materials for building walls in a temperate and humid climate (case example: Sari city) from the perspective of embodied energy, waste of electricity and gas energy, cost and reuse been investigated to achieve sustainable architecture. In this regard, using information obtained from Sari Municipality, design components have been presented by experts using the Delphi method. Considering the criteria of experts' opinions (cost and reuse), the amount of embodied energy of the materials, as well as the amount of waste of electricity and gas of different materials of the walls, with the help of the AHP weighting technique and finally with the TOPSIS technique, the best type of materials in the order of 1- 3-D Panel 2-ICF-, 3-Cement block with pumice, 4-Wallcrete block, 5-Clay block, 6-Autoclaved Aerated Concrete (AAC), 7-Foam cement block, 8-Aquapanel and 9-Reinforced concrete wall for use in The walls of the buildings were proposed in Sari city.

Keywords: optimum materials, building walls, moderate and humid climate, sustainable architecture, AHP-TOPSIS technique

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Authors: Mohamed Raouf Benmakrelouf, Wafa Karouche, Joseph Rynkiewicz

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In this paper, we propose an alternative method to construct a Bayesian Network (BN). This method relies on a convolutional neural network (CNN classifier), which determinates the edges of the network skeleton. We train a CNN on a normalized empirical probability density distribution (NEPDF) for predicting causal interactions and relationships. We have to find the optimal Bayesian network structure for causal inference. Indeed, we are undertaking a search for pair-wise causality, depending on considered causal assumptions. In order to avoid unreasonable causal structure, we consider a blacklist and a whitelist of causality senses. We tested the method on real data to assess the influence of education on the voting intention for the extreme right-wing party. We show that, with this method, we get a safer causal structure of variables (Bayesian Network) and make to identify a variable that satisfies the backdoor criterion.

Keywords: Bayesian network, structure learning, optimal search, convolutional neural network, causal inference

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Authors: Joshua Chima Chizoba, Wisdom Izuchukwu Uzoma, Elizabeth Ifeyiwa Okoyeh

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Water cannot be optimally used and sustained unless the quality is periodically assessed. The study area Umunneochi and environs are located in south eastern part of Nigeria. It stretches geographically from latitudes 50501N to 60000N and longitudes 70201E to 70301. The major geologic formations in the area include the Asu River group, Nkporo Shale, and Ajali Sandstone. The aim of this study is to evaluate the hydrochemical characteristics of surface and ground water sources in parts of Umunneochi and environs in order to establish portability of the water sources for drinking, domestic and irrigation purposes. A total of 15 samples were collected randomly from streams, springs and wells. The samples were analyzed for physicochemical parameters and heavy metals using handheld digital kits, photometer, titration method and Atomic Absorption Spectrophotometer (AAS) following acceptable standards. The obtained analytical data were interpreted, and results were compared with World Health Organization (WHO) standard. The concentration of pH, SO42-and Cl- range from 5.81 mg/l – 6.07 mg/l, 41.93 mg/l – 142.95 mg/l and 20.00 mg/l – 111 mg/l respectively, while Pb and Zn revealed a relative low mean concentration of 0.14 mg/l and 0.40 mg/l, which are all within (WHO) permissible limits except pH. About 27% of the samples are moderately hard. This is attributed to the mining activities in the areas. The abundance of cations and anions in the area are in the order of K+>Na+>Mg2+>Ca2+ and SO4->Cl->HCO3->NO3-, respectively. Chloride, bicarbonate, and nitrate are all within the permissible limits. 13.33% of the total samples contain Sulphate above the standard permissible limits. The values of calculated Water Quality Index (WQI) are less than 50 indicating excellent water. The predominant water-type in the study area is Na-Cl water type and mixed Ca-Mg-Cl water type based on the sample plots on the Piper diagram. The Sodium Absorption Ratio (SAR) calculations showed excellent water for consumption and also good water for irrigation purpose with low sodium and alkalinity ratio respectively. Government water projects are recommended in the area for sustainable domestic and agricultural water supply to ease the stress of water supply problems.

Keywords: groundwater, hydrochemical, physichochemical, water-type, sodium adsorption ratio

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Authors: Lazic Marina, Sugden Scott, Sharma Kanta Hem, Sauvageau Dominic, Stein Lisa

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Methane is a highly potent greenhouse gas mostly released through anthropogenic activities. Methane represents a low-cost and sustainable feedstock used for the biological production of value-added compounds by bacteria known as methanotrophs. In addition to methane, these organisms can utilize methanol, another cheap carbon source that is a common industrial by-product. Alphaproteobacteria methanotrophs can utilize both methane and methanol to produce the biopolymer polyhydroxybutyrate. The goal of this study was to examine the effect of methanol on polyhydroxybutyrate production in Methylocystis sp. Rockwell and to identify the optimal methane: methanol ratio that will improve PHB without reducing biomass production. Three methane: methanol ratios (4, 2.5., and 0.5) and three nitrogen source (ammonium or nitrate) concentrations (10 mM, 1 mM, and 0.1 mM) were combined to generate 18 growing conditions (9 per carbon source). The production of polyhydroxybutyrate and biomass was analyzed at the end of growth. Overall, the methane: methanol ratios that promoted polyhydroxybutyrate synthesis without reducing biomass were 4 and 2.5 and the optimal nitrogen concentration was 1 mM for both ammonium and nitrate. The physiological mechanism behind the beneficial effect of combining methane and methanol as carbon sources remain to be discovered. One possibility is that methanol has a dual role as a carbon source at lower concentrations and as a stringent response trigger at higher concentrations. Nevertheless, the beneficial effect of methanol and optimal nitrogen concentration for PHB production was confirmed, providing a basis for future physiological analysis and conditions for process scale-up.

Keywords: methane, methanol, methanotrophs, polyhydroxybutyrate, methylocystis sp. rockwell, single carbon bioconversions

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Authors: Halil Bas, Unal Demiray, Sukru Dursun

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Water and ground water pollution at the most of the countries is important problem. Investigation of water pollution source must be carried out to save fresh water. Because fresh water sources are very limited and recent sources are not enough for increasing population of world. In this study, investigation was carried out on pollution factors effecting the quality of the groundwater in Çorum Stream Basin in Turkey. Effect of geological structure of the region and the interaction between the stream and groundwater was researched. For the investigation, stream and groundwater sampling were performed at rainy and dry seasons to see if there is a change on quality parameters. The results were evaluated by the computer programs and then graphics, distribution maps were prepared. Thus, degree of the quality and pollution were tried to understand. According to analysis results, because the results of streams and the ground waters are not so close to each other we can say that there is no interaction between the stream and the groundwater. As the irrigation water, the stream waters are generally in the range between C3S1 region and the ground waters are generally in the range between C3S1 and C4S2 regions according to US Salinity Laboratory Diagram. According to Wilcox diagram stream waters are generally good-permissible and ground waters are generally good permissible, doubtful to unsuitable and unsuitable type. Especially ground waters are doubtful to unsuitable and unsuitable types in dry season. It may be assumed that as the result of relative increase in concentration of salt minerals. Especially samples from groundwater wells bored close to gypsium bearing units have high hardness, electrical conductivity and salinity values. Thus for drinking and irrigation these waters are determined as unsuitable. As a result of these studies, it is understood that the groundwater especially was effected by the lithological contamination rather than the anthropogenic or the other types of pollution. Because the alluvium is covered by the silt and clay lithology it is not affected by the anthropogenic and the other foreign factors. The results of solid waste disposal site leachate indicate that this site would have a risk potential for pollution in the future. Although the parameters did not exceed the maximum dangerous values it does not mean that they will not be dangerous in the future, and this case must be taken into account.

Keywords: Çorum, environment, groundwater, hydrogeology, geology, pollution, quality, stream

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Authors: Mehmet Halkaci, Ekrem Öztürk, Mevlüt Türköz, H. Selçuk Halkacı

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Hydromechanical deep drawing (HMD) process is an advanced manufacturing process used to form deep parts with only one forming step. In this process, sheet metal blank can be drawn deeper by means of fluid pressure acting on sheet surface in the opposite direction of punch movement. High limiting drawing ratio, good surface quality, less springback characteristic and high dimensional accuracy are some of the advantages of this process. The performance of the HMD process is affected by various process parameters such as fluid pressure, blank holder force, punch-die radius, pre-bulging pressure and height, punch diameter, friction between sheet-die and sheet-punch. The fluid pressure and bank older force are the main loading parameters and affect the formability of HMD process significantly. The punch diameter also influences the limiting drawing ratio (the ratio of initial sheet diameter to punch diameter) of the sheet metal blank. In this research, optimal loading (fluid pressure and blank holder force) profiles were determined for AA 5754-O sheet material through fuzzy control algorithm developed in previous study using LS-DYNA finite element analysis (FEA) software. In the preceding study, the fuzzy control algorithm was developed utilizing geometrical criteria such as thinning and wrinkling. In order to obtain the final desired part with the developed algorithm in terms of the punch diameter requested, the effect of punch diameter, which is the one of the process parameters, on loading profiles was investigated separately using blank thickness of 1 mm. Thus, the practicality of the previously developed fuzzy control algorithm with different punch diameters was clarified. Also, thickness distributions of the sheet metal blank along a curvilinear distance were compared for the FEA in which different punch diameters were used. Consequently, it was found that the use of different punch diameters did not affect the optimal loading profiles too much.

Keywords: Finite Element Analysis (FEA), fuzzy control, hydromechanical deep drawing, optimal loading profiles, punch diameter

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Authors: István Patkó, Hosam Bayoumi Hamuda, András Szeder

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In order to efficiently solve the problems created by the deepening energy crisis affecting Europe and the world, governments cannot neglect the opportunities of using the energy produced by sun collectors. In many of the EU countries there are sun collectors producing heat energy, e.g. in 2011 in the area of EU27 (countries which belong to European Union) + Switzerland altogether 37519126 m2 were operated, which are capable of producing 26.3 GWh heat energy. The energy produced by these sun collectors is utilized at the place of production. In the near future governments will have to focus more on spreading and using sun collectors. Among the complex problems of operating sun collectors, this article deals with determining the optimal tilt angle, directions of sun collectors. We evaluate the contamination of glass surface of sun collector to the produced energy. Our theoretically results are confirmed by laboratory measurements. The purpose of our work is to help users and engineers in determination of optimal operation parameters of sun collectors.

Keywords: heat energy, tilt angle, direction of sun collector, contamination of surface

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Authors: Edokpa Idemudia Waziri, Salisu S. Umar

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The Hotellng’s T^2 is a well-known statistic for detecting a shift in the mean vector of a multivariate normal distribution. Control charts based on T have been widely used in statistical process control for monitoring a multivariate process. Although it is a powerful tool, the T statistic is deficient when the shift to be detected in the mean vector of a multivariate process is small and consistent. The Multivariate Exponentially Weighted Moving Average (MEWMA) control chart is one of the control statistics used to overcome the drawback of the Hotellng’s T statistic. In this paper, the probability distribution of the Average Run Length (ARL) of the MEWMA control chart when the quality characteristics exhibit substantial cross correlation and when the process is in-control and out-of-control was derived using the Markov Chain algorithm. The derivation of the probability functions and the moments of the run length distribution were also obtained and they were consistent with some existing results for the in-control and out-of-control situation. By simulation process, the procedure identified a class of ARL for the MEWMA control when the process is in-control and out-of-control. From our study, it was observed that the MEWMA scheme is quite adequate for detecting a small shift and a good way to improve the quality of goods and services in a multivariate situation. It was also observed that as the in-control average run length ARL0¬ or the number of variables (p) increases, the optimum value of the ARL0pt increases asymptotically and as the magnitude of the shift σ increases, the optimal ARLopt decreases. Finally, we use the example from the literature to illustrate our method and demonstrate its efficiency.

Keywords: average run length, markov chain, multivariate exponentially weighted moving average, optimal smoothing parameter

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Authors: Xiao-Dong Wang, Wei-Mon Yan

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The flow field design in the bipolar plates affects the performance of the proton exchange membrane (PEM) fuel cell. This work adopted a combined optimization procedure, including a simplified conjugate-gradient method and a completely three-dimensional, two-phase, non-isothermal fuel cell model, to look for optimal flow field design for a single serpentine fuel cell of size 9×9 mm with five channels. For the direct solution, the two-fluid method was adopted to incorporate the heat effects using energy equations for entire cells. The model assumes that the system is steady; the inlet reactants are ideal gases; the flow is laminar; and the porous layers such as the diffusion layer, catalyst layer and PEM are isotropic. The model includes continuity, momentum and species equations for gaseous species, liquid water transport equations in the channels, gas diffusion layers, and catalyst layers, water transport equation in the membrane, electron and proton transport equations. The Bulter-Volumer equation was used to describe electrochemical reactions in the catalyst layers. The cell output power density Pcell is maximized subjected to an optimal set of channel heights, H1-H5, and channel widths, W2-W5. The basic case with all channel heights and widths set at 1 mm yields a Pcell=7260 Wm-2. The optimal design displays a tapered characteristic for channels 1, 3 and 4, and a diverging characteristic in height for channels 2 and 5, producing a Pcell=8894 Wm-2, about 22.5% increment. The reduced channel heights of channels 2-4 significantly increase the sub-rib convection and widths for effectively removing liquid water and oxygen transport in gas diffusion layer. The final diverging channel minimizes the leakage of fuel to outlet via sub-rib convection from channel 4 to channel 5. Near-optimal design without huge loss in cell performance but is easily manufactured is tested. The use of a straight, final channel of 0.1 mm height has led to 7.37% power loss, while the design with all channel widths to be 1 mm with optimal channel heights obtained above yields only 1.68% loss of current density. The presence of a final, diverging channel has greater impact on cell performance than the fine adjustment of channel width at the simulation conditions set herein studied.

Keywords: optimization, flow field design, simplified conjugate-gradient method, serpentine flow field, sub-rib convection

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Authors: Hyun-Woo Jun, In-Gun Kim, Hyun Seok Hong, Dong-Woo Kang, Ju Lee

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In high-speed SPMSM design, the rotor-retaining sleeve is inserted into rotor to prevent permanent magnet’s damage. It is quite efficient way considering manufacturability, but the sleeve becomes major source of ohm loss in high-speed operation. In this paper, the high-speed motor for turbo-blower at the rating of 100kW was introduced. To improve its efficiency, the retaining sleeve’s optimal design was needed. Within the range of satisfies the mechanical safety, sleeve’s some design variables have been changed. The effect of changing design variables of the sleeve was studied. This paper presents the optimized sleeve’s advantages in electrical efficiency from the result of electromagnetic FEA (finite element analysis) software. Finally, it suggests the optimal sleeve design to reduce eddy current loss, which is related to motor shape.

Keywords: SPMSM, sleeve, eddy current, high efficiency

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Authors: Oqba Basal, András Szabó

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Legume crops are able to fix atmospheric nitrogen by the symbiotic relation with specific bacteria, which allows the use of the mineral nitrogen-fertilizer to be reduced, or even excluded, resulting in more profit for the farmers and less pollution for the environment. Soybean (Glycine max (L.) Merrill) is one of the most important legumes with its high content of both protein and oil. However, it is recommended to combine the two nitrogen sources under stress conditions in order to overcome its negative effects. Drought stress is one of the most important abiotic stresses that increasingly limits soybean yields. A precise rate of mineral nitrogen under drought conditions is not confirmed, as it depends on many factors; soybean yield-potential and soil-nitrogen content to name a few. An experiment was conducted during 2017 growing season in Debrecen, Hungary to investigate the effects of nitrogen source on the physiology and the yield of the soybean cultivar 'Boglár'. Three N-fertilizer rates including no N-fertilizer (0 N), 35 kg ha^-1 of N-fertilizer (35 N) and 105 kg ha^-1 of N-fertilizer (105 N) were applied under three different irrigation regimes; severe drought stress (SD), moderate drought stress (MD) and control with no drought stress (ND). Half of the seeds in each treatment were pre-inoculated with Bradyrhizobium japonicum inoculant. The overall results showed significant differences associated with fertilization and irrigation, but not with inoculation. Increasing N rate was mostly accompanied with increased chlorophyll content and leaf area index, whereas it positively affected the plant height only when the drought was waived off. Plant height was the lowest under severe drought, regardless of inoculation and N-fertilizer application and rate. Inoculation increased the yield when there was no drought, and a low rate of N-fertilizer increased the yield furthermore; however, the high rate of N-fertilizer decreased the yield to a level even less than the inoculated control. On the other hand, the yield of non-inoculated plants increased as the N-fertilizer rate increased. Under drought conditions, adding N-fertilizer increased the yield of the non-inoculated plants compared to their inoculated counterparts; moreover, the high rate of N-fertilizer resulted in the best yield. Regardless of inoculation, the mean yield of the three fertilization rates was better when the water amount increased. It was concluded that applying N-fertilizer to provide the nitrogen needed by soybean plants, with the absence of N₂-fixation process, is very important. Moreover, adding relatively high rate of N-fertilizer is very important under severe drought stress to alleviate the drought negative effects. Further research to recommend the best N-fertilizer rate to inoculated soybean under drought stress conditions should be executed.

Keywords: drought stress, inoculation, N-fertilizer, soybean physiology, yield

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Authors: K. K. Saijaand, K. Prabhakaran Nair

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This study aims to determine change in optimal lo-cations of dual trailing-edge flaps for various thrust coefficient to solidity (Ct /σ) ratios of helicopter to achieve minimum hub vibration levels, with low penalty in terms of required trailing-edge flap control power. Polynomial response functions are used to approximate hub vibration and flap power objective functions. Single objective and multi-objective optimization is carried with the objective of minimizing hub vibration and flap power. The optimization results shows that the inboard flap location at low Ct/σ ratio move farther from the baseline value and at high Ct/σ ratio move towards the root of the blade for minimizing hub vibration.

Keywords: helicopter rotor, trailing-edge flap, thrust coefficient to solidity (Ct /σ) ratio, optimization

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Authors: Bita Payami-Shabestari, Dariush Eslami

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The purpose of this paper is to develop a multi-product economic production quantity model under vendor management inventory policy and restrictions including limited warehouse space, budget, and number of orders, average shortage time and maximum permissible shortage. Since the “costs” cannot be predicted with certainty, it is assumed that data behave under uncertain environment. The problem is first formulated into the framework of a bi-objective of multi-product economic production quantity model. Then, the problem is solved with three multi-objective decision-making (MODM) methods. Then following this, three methods had been compared on information on the optimal value of the two objective functions and the central processing unit (CPU) time with the statistical analysis method and the multi-attribute decision-making (MADM). The results are compared with statistical analysis method and the MADM. The results of the study demonstrate that augmented-constraint in terms of optimal value of the two objective functions and the CPU time perform better than global criteria, and goal programming. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The contribution of this research is the use of random costs data in developing a multi-product economic production quantity model under vendor management inventory policy with several constraints.

Keywords: economic production quantity, random cost, supply chain management, vendor-managed inventory

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Authors: Pin-Wei Chiang, Wen-Liang Chang, Ruey-Huei Yeh

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This paper investigates optimal replacement and preventative maintenance policies of secondhand products under a Finite Planning Horizon (FPH). Any consumer wishing to replace their product under FPH would have it undergo minimal repairs. The replacement provided would be required to undergo periodical preventive maintenance done to avoid product failure. Then, a mathematical formula for disbursement cost for products under FPH can be derived. Optimal policies are then obtained to minimize cost. In the first of two segments of the paper, a model for initial product purchase of either new or secondhand products is used. This model is built by analyzing product purchasing price, surplus value of product, as well as the minimal repair cost. The second segment uses a model for replacement products, which are also secondhand products with no limit on usage. This model analyzes the same components as the first as well as expected preventative maintenance cost. Using these two models, a formula for the expected final total cost can be developed. The formula requires four variables (optimal preventive maintenance level, preventive maintenance frequency, replacement timing, age of replacement product) to find minimal cost requirement. Based on analysis of the variables using the expected total final cost model, it was found that the purchasing price and length of ownership were directly related. Also, consumers should choose the secondhand product with the higher usage for replacement. Products with higher initial usage upon acquisition require an earlier replacement schedule. In this case, replacements should be made with a secondhand product with less usage. In addition, preventative maintenance also significantly reduces cost. Consumers that plan to use products for longer periods of time replace their products later. Hence these consumers should choose the secondhand product with lesser initial usage for replacement. Preventative maintenance also creates significant total cost savings in this case. This study provides consumers with a method of calculating both the ideal amount of usage of the products they should purchase as well as the frequency and level of preventative maintenance that should be conducted in order to minimize cost and maintain product function.

Keywords: finite planning horizon, second hand product, replacement, preventive maintenance, minimal repair

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Authors: Meet Patel, Darshan Patel, Nilay Shah

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Excess growth of wind-based renewable energy sources is required to identify the optimal location and damping capacity of doubly fed induction-generator-based (DFIG) wind farms while it penetrates into the transmission network. In this analysis, various ratings of DFIG wind farms are penetrated into the Single Machine Infinite Bus (SMIB ) at a different distance of the transmission line. On the basis of detailed examinations, a prime position is evaluated to maximize the stability of overall systems. A damping controller is designed at an optimum location to mitigate the small oscillations. The proposed model was validated using eigenvalue analysis, calculation of the participation factor, and time-domain simulation.

Keywords: DFIG, small signal stability, eigenvalues, time domain simulation

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Authors: Hyeonkyeong Yang, Minseok Son, Taekbeom Yoo, Woojin Park

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Human error is the most salient contributing factor to railway accidents. To reduce the frequency of human errors, many researchers and train designers have adopted ergonomic design principles for designing display-control layout in rail cab. There exist a number of approaches for designing the display control layout based on optimization methods. However, the ergonomically optimized layout design may not be the best design for train drivers, since the drivers have their own mental models based on their experiences. Consequently, the drivers may prefer the existing display-control layout design over the optimal design, and even show better driving performance using the existing design compared to that using the optimal design. Thus, in addition to ergonomic design principles, train drivers’ mental models also need to be considered for designing display-control layout in rail cab. This paper developed an ergonomic assessment system of display-control layout design, and an interactive layout design system that can generate design alternatives and calculate ergonomic assessment score in real-time. The design alternatives generated from the interactive layout design system may not include the optimal design from the ergonomics point of view. However, the system’s strength is that it considers train drivers’ mental models, which can help generate alternatives that are more friendly and easier to use for train drivers. Also, with the developed system, non-experts in ergonomics, such as train drivers, can refine the design alternatives and improve ergonomic assessment score in real-time.

Keywords: display-control layout design, interactive layout design system, mental model, train drivers

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Authors: Theresa K., Shanmugasundaram R., Kennedy J. S.

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Nutrient supplements are indispensable for raising crops and to reap determining productivity. The nutrient imbalance between replenishment and crop uptake is attempted through the input of inorganic fertilizers. Excessive dumping of inorganic nutrients in soil cause stagnant and decline in yield. Imbalanced N-P-K ratio in the soil exacerbates and agitates the soil ecosystems. The study evaluated the fertilization practices of conventional (CFs), organic and Integrated Nutrient Management system (INM) on soil quality using key indicators and soil quality indices. Twelve rice farming fields of which, ten fields were having conventional cultivation practices, one field each was organic farming based and INM based cultivated under monocropping sequence in the Thondamuthur block of Coimbatore district were fixed and properties viz., physical, chemical and biological were studied for four cropping seasons to determine soil quality index (SQI). SQI was computed for conventional, organic and INM fields. Comparing conventional farming (CF) with organic and INM, CF was recorded with a lower soil quality index. While in organic and INM fields, the higher SQI value of 0.99 and 0.88 respectively were registered. CF₄ received with a super-optimal dose of N (250%) showed a lesser SQI value (0.573) as well as the yield (3.20 t ha⁻¹) and the CF6 which received 125 % N recorded the highest SQI (0.715) and yield (6.20 t ha⁻¹). Likewise, most of the CFs received higher N beyond the level of 125 % except CF₃ and CF₉, which recorded lower yields. CFs which received super-optimal P in the order of CF₆&CF₇>CF₁&CF₁₀ recorded lesser yields except for CF₆. Super-optimal K application also recorded lesser yield in CF₄, CF₇ and CF₉.

Keywords: rice cropping system, soil quality indicators, imbalanced fertilization, yield

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Authors: Rahmoune Abdelhaq

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Systemic risk is a key concern for central banks charged with safeguarding overall financial stability. In this work, we investigate how systemic risk is affected by the structure of the financial system. We construct banking systems that are composed of a number of banks that are connected by interbank linkages. We then vary the key parameters that define the structure of the financial system — including its level of capitalization, the degree to which banks are connected, the size of interbank exposures and the degree of concentration of the system — and analyses the influence of these parameters on the likelihood of contagious (knock-on) defaults. First, we find that the better-capitalized banks are, the more resilient is the banking system against contagious defaults and this effect is non-linear. Second, the effect of the degree of connectivity is non-monotonic, that is, initially a small increase in connectivity increases the contagion effect; but after a certain threshold value, connectivity improves the ability of a banking system to absorb shocks. Third, the size of interbank liabilities tends to increase the risk of knock-on default, even if banks hold capital against such exposures. Fourth, more concentrated banking systems are shown to be prone to larger systemic risk, all else equal. In an extension to the main analysis, we study how liquidity effects interact with banking structure to produce a greater chance of systemic breakdown. We finally consider how the risk of contagion might depend on the degree of asymmetry (tier) inherent in the structure of the banking system. A number of our results have important implications for public policy, which this paper also draws out. This paper also discusses why bank risk management is needed to get the optimal one.

Keywords: financial stability, contagion, liquidity risk, optimal risk

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Authors: P. Priyanka, S. Shruthi, N. Guruprasad

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Health is a common theme in most cultures. In fact all communities have their concepts of health, as part of their culture. Health continues to be a neglected entity. Planning of Human diet should be done very careful by selecting the food items or groups of food items also the composition involved. Low price and good taste of foods are regarded as two major factors for optimal human nutrition. Linear programming techniques have been extensively used for human diet formulation for quiet good number of years. Through the process, we mainly apply “The Simplex Method” which is a very useful statistical tool based on the theorem of Elementary Row Operation from Linear Algebra and also incorporate some other necessary rules set by the Simplex Method to help solve the problem. The study done by us is an attempt to develop a programming model for optimal planning and best use of nutrient ingredients.

Keywords: diet formulation, linear programming, nutrient ingredients, optimization, simplex method

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Authors: A. Gopala Krishna, M. Lakshmi Chaitanya, V. Kalyana Manohar

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In the existent analysis, laser micro machining (LMM) of Silicon carbide (SiCp) reinforced Aluminum 7075 Metal Matrix Composite (Al7075/SiCp MMC) was studied. While machining, Because of the intense heat generated, A layer gets formed on the work piece surface which is called recast layer and this layer is detrimental to the surface quality of the component. The recast layer needs to be as small as possible for precise applications. Therefore, The height of recast layer and the depth of groove which are conflicting in nature were considered as the significant manufacturing criteria, Which determines the pursuit of a machining process obtained in LMM of Al7075/10%SiCp composite. The present work formulates the depth of groove and height of recast layer in relation to the machining parameters using the Response Surface Methodology (RSM) and correspondingly, The formulated mathematical models were put to use for optimization. Since the effect of machining parameters on the depth of groove and height of recast layer was contradictory, The problem was explicated as a multi objective optimization problem. Moreover, An evolutionary Non-dominated sorting genetic algorithm (NSGA-II) was employed to optimize the model established by RSM. Subsequently this algorithm was also adapted to achieve the Pareto optimal set of solutions that provide a detailed illustration for making the optimal solutions. Eventually experiments were conducted to affirm the results obtained from RSM and NSGA-II.

Keywords: Laser Micro Machining (LMM), depth of groove, Height of recast layer, Response Surface Methodology (RSM), non-dominated sorting genetic algorithm

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Authors: Ishita Singh

Abstract:

Social-dimension of Climate Change is no longer peripheral to Science, Technology and Innovation (STI). Indeed, STI is being mobilized to address small farmers’ vulnerability and adaptation to Climate Change. The experiences from the cold desert of Leh (Ladakh) in North-West Himalaya illustrate the potential of STI to address the challenges of Climate Change and the needs of small farmers through the use of Artificial Glacier Techniques. Small farmers have a unique technique of water harvesting to augment irrigation, called “Artificial Glaciers” - an intricate network of water channels and dams along the upper slope of a valley that are located closer to villages and at lower altitudes than natural glaciers. It starts to melt much earlier and supplements additional irrigation to small farmers’ improving their livelihoods. Therefore, the issue of vulnerability, adaptive capacity and adaptation strategy needs to be analyzed in a local context and the communities as well as regions where people live. Leh (Ladakh) in North-West Himalaya provides a Case Study for exploring the ways in which adaptation to Climate Change is taking place at a community scale using Artificial Glacier Technology. With the above backdrop, an attempt has been made to analyze the rural poor households' vulnerability and adaptation practices to Climate Change using this technology, thereby drawing lessons on vulnerability-livelihood interactions in the cold desert of Leh (Ladakh) in North-West Himalaya, India. The study is based on primary data and information collected from 675 households confined to 27 villages of Leh (Ladakh) in North-West Himalaya, India. It reveals that 61.18% of the population is driving livelihoods from agriculture and allied activities. With increased irrigation potential due to the use of Artificial Glaciers, food security has been assured to 77.56% of households and health vulnerability has been reduced in 31% of households. Seasonal migration as a livelihood diversification mechanism has declined in nearly two-thirds of households, thereby improving livelihood strategies. Use of tactical adaptations by small farmers in response to persistent droughts, such as selling livestock, expanding agriculture lands, and use of relief cash and foods, have declined to 20.44%, 24.74% and 63% of households. However, these measures are unsustainable on a long-term basis. The role of policymakers and societal stakeholders becomes important in this context. To address livelihood challenges, the role of technology is critical in a multidisciplinary approach involving multilateral collaboration among different stakeholders. The presence of social entrepreneurs and new actors on the adaptation scene is necessary to bring forth adaptation measures. Better linkage between Science and Technology policies, together with other policies, should be encouraged. Better health care, access to safe drinking water, better sanitary conditions, and improved standards of education and infrastructure are effective measures to enhance a community’s adaptive capacity. However, social transfers for supporting climate adaptive capacity require significant amounts of additional investment. Developing institutional mechanisms for specific adaptation interventions can be one of the most effective ways of implementing a plan to enhance adaptation and build resilience.

Keywords: climate change, adaptation, livelihood, stakeholders

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Authors: N. Tahouni, M. Gholami, M. H. Panjeshahi

Abstract:

Gas flaring is one of the most GHG emitting sources in the oil and gas industries. It is also a major way for wasting such an energy that could be better utilized and even generates revenue. Minimize flaring is an effective approach for reducing GHG emissions and also conserving energy in flaring systems. Integrating waste and flared gases into the fuel gas networks (FGN) of refineries is an efficient tool. A fuel gas network collects fuel gases from various source streams and mixes them in an optimal manner, and supplies them to different fuel sinks such as furnaces, boilers, turbines, etc. In this article we use fuel gas network model proposed by Hasan et al. as a base model and modify some of its features and add constraints on emission pollution by gas flaring to reduce GHG emissions as possible. Results for a refinery case study showed that integration of flare gas stream with waste and natural gas streams to construct an optimal FGN can significantly reduce total annualized cost and flaring emissions.

Keywords: flaring, fuel gas network, GHG emissions, stream

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Authors: Dibakar Chakrabarty, Mebada Suiting

Abstract:

Rapid urbanization coupled with changes in land use pattern results in increasing peak discharge and shortening of catchment time of concentration. The consequence is floods, which often inundate roads and inhabited areas of cities and towns. Management of storm water resulting from rainfall has, therefore, become an important issue for the municipal bodies. Proper management of storm water obviously includes adequate design of storm water drainage networks. The design of storm water network is a costly exercise. Least cost design of storm water networks assumes significance, particularly when the fund available is limited. Optimal design of a storm water system is a difficult task as it involves the design of various components, like, open or closed conduits, storage units, pumps etc. In this paper, a methodology for least cost design of storm water drainage systems is proposed. The methodology proposed in this study consists of coupling a storm water simulator with an optimization method. The simulator used in this study is EPA’s storm water management model (SWMM), which is linked with Genetic Algorithm (GA) optimization method. The model proposed here is a mixed integer nonlinear optimization formulation, which takes care of minimizing the sectional areas of the open conduits of storm water networks, while satisfactorily conveying the runoff resulting from rainfall to the network outlet. Performance evaluations of the developed model show that the proposed method can be used for cost effective design of open conduit based storm water networks.

Keywords: genetic algorithm (GA), optimal design, simulation-optimization, storm water network, SWMM

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Authors: Laidi Maamar, Hanini Salah

Abstract:

The present work investigates the potential of artificial neural network (ANN) model to predict the horizontal global solar radiation (HGSR). The ANN is developed and optimized using three years meteorological database from 2011 to 2013 available at the meteorological station of Blida (Blida 1 university, Algeria, Latitude 36.5°, Longitude 2.81° and 163 m above mean sea level). Optimal configuration of the ANN model has been determined by minimizing the Root Means Square Error (RMSE) and maximizing the correlation coefficient (R2) between observed and predicted data with the ANN model. To select the best ANN architecture, we have conducted several tests by using different combinations of parameters. A two-layer ANN model with six hidden neurons has been found as an optimal topology with (RMSE=4.036 W/m²) and (R²=0.999). A graphical user interface (GUI), was designed based on the best network structure and training algorithm, to enhance the users’ friendliness application of the model.

Keywords: artificial neural network, global solar radiation, solar energy, prediction, Algeria

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Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

Abstract:

Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

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Authors: T. Tahri, H. Zahloul, K. E. Meddah, H. Lazergue

Abstract:

This paper presents a theoretical study that leads to the design of a photovoltaic pumping system to irrigate six hectares of oranges in the valley of Chlef using the software "PVSYST". It was shown that the site of Chlef presents a favorable climate to this type of energy with an irradiation of over 5 kWh/m2/day, and significant resources underground water. Another very important coincidence still promotes the use of this type of energy for pumping water in Chlef is that the demand for water, especially in agriculture, peaked in hot and dry where it is precisely when one has access to the maximum of solar energy.

Keywords: solar energy, irradiation, water pumping, design, Valley of Chlef

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Authors: Yul Y. Nazaruddin, Anas Y. Widiaribowo, Satriyo Nugroho

Abstract:

Boiler is one of the critical unit in a petrochemical plant. Steam produced by the boiler is used for various processes in the plant such as urea and ammonia plant. An alternative method to optimize the boiler combustion system is presented in this paper. Adaptive Neuro-Fuzzy Inference System (ANFIS) approach is applied to model the boiler using real-time operational data collected from a boiler unit of the petrochemical plant. Nonlinear equation obtained is then used to optimize the air to fuel ratio using Genetic Algorithm, resulting an optimal ratio of 15.85. This optimal ratio is then maintained constant by ratio controller designed using inverse dynamics based on ANFIS. As a result, constant value of oxygen content in the flue gas is obtained which indicates more efficient combustion process.

Keywords: ANFIS, boiler, combustion process, genetic algorithm, optimization.

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Authors: E. Shahsavari, R. Ghasemi, A. Akramizadeh

Abstract:

This paper presents a new method to design nonlinear feedback linearization controller for polymer electrolyte membrane fuel cells (PEMFCs). A nonlinear controller is designed based on nonlinear model to prolong the stack life of PEM fuel cells. Since it is known that large deviations between hydrogen and oxygen partial pressures can cause severe membrane damage in the fuel cell, feedback linearization is applied to the PEM fuel cell system so that the deviation can be kept as small as possible during disturbances or load variations. To obtain an accurate feedback linearization controller, tuning the linear parameters are always important. So in proposed study NSGA_II method was used to tune the designed controller in aim to decrease the controller tracking error. The simulation result showed that the proposed method tuned the controller efficiently.

Keywords: nonlinear dynamic model, polymer electrolyte membrane fuel cells, feedback linearization, optimal control, NSGA_II

Procedia PDF Downloads 511