Search results for: optimal functioning

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: Noemia Bessa Vilela, Jose Caramelo Gomes

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All law student are familiarized, in the first years of their bachelor of laws with the concepts of “public goods” and “ private goods”; often, such legal concept does not exactly match such economic concept, and there are consequences are some sort of confusion being created. The list of goods that follow under each category is not exhaustive, nor are students given proper mechanisms to acknowledge that some legal fields can, on its own, be considered as a “public good”; this is the case of Competition. Legal authors consider that “competition law is used to promote public interest” and, as such, it is a “public good”; in economics theory, Competition is the first public good in a market economy, as the enabler of allocation efficiency. Competition law is the legal tool to support the proper functioning of the market economy and democracy itself. It is fact that Competition Law only applies to economic activities, still, competition is object of private litigation as an integral part of Public Law. Still, regardless of the importance of Competition Law in the economic activity and market regulation, most student complete their studies in law, join the Bar Associations and engage in their professional activities never having been given sufficient tools to deal with the increasing demands of a globalized world. The lack of knowledge of economics, market functioning and the mechanisms at their reach in order to ensure proper realization of their duties as lawyers/ attorneys-at-law would be tackled if Competition Law would be included as part of the curricula of Law Schools. Proper teaching of Competition Law would combine the foundations of Competition Law, doctrine, case solving and Case Law study. Students should to understand and apply the analytical model. Special emphasis should be given to EU Competition Law, namely the TFEU Articles 101 to 106. Damages Directive should also be part of the curriculum. Students must in the first place acquire and master the economic rationale as competition and the world of competition law are the cornerstone of sound and efficient market. The teaching of Competition Law in undergraduate programs in Law would contribute to fulfill the potential of the students who will deal with matters related to consumer protection, economic and commercial law issues both in private practice and as in-house lawyers for companies.

Keywords: higher education, competition law, legal education, law, market economy, industrial economics

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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: Alua Massalimova

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Situation analysis of Blood Service revealed that the strengths dominated over the weak 1.4 times. The possibilities dominate over the threats by 1.1 times. It follows that by using timely the possibility the Service, it is possible to strengthen its strengths and avoid threats. Priority directions of the resulting analysis are the use of subjective factors, such as personal management capacity managers of the Blood Center in the field of possibilities of legal activity of administrative decisions and the mobilization of stable staff in general market conditions. We have studied for the period 2011-2015 retrospectively indicators of Blood Service of Kazakhstan. Strengths of Blood Service of RK(Ps4,5): 1) indicators of donations for 1000 people is higher than in some countries of the CIS (in Russia 14, Kazakhstan - 17); 2) the functioning science centre of transfusiology; 3) the legal possibility of additional financing blood centers in the form of paid services; 4) the absence of competitors; 5) training on specialty Transfusiology; 6) the stable management staff of blood centers, a high level of competence; 7) increase in the incidence requiring transfusion therapy (oncohematology); 8) equipment upgrades; 9) the opening of a reference laboratory; 10) growth of the proportion of issued high-quality blood components; 11) governmental organization 'Drop of Life'; 12) the functioning bone marrow register; 13) equipped with modern equipment HLA-laboratory; 14) High categorization of average medical workers; 15) availability of own specialized scientific journal; 16) vivarium. The weaknesses (Ps = 3.5): 1) the incomplete equipping of blood centers and blood transfusion cabinets according to standards; 2) low specific weight of paid services of the CC; 3) low categorization of doctors; 4) high staff turnover; 5) the low scientific potential of industrial and clinical of transfusiology; 6) the low wages paid; 7) slight growth of harvested donor blood; 8) the weak continuity with offices blood transfusion; 9) lack of agitation work; 10) the formally functioning of Transfusion Association; 11) the absence of scientific laboratories; 12) high standard deviation from the average for donations in the republic. The possibilities (Ps = 2,7): 1): international grants; 2) organization of international seminars on clinical of transfusiology; 3) cross-sectoral cooperation; 4) to increase scientific research in the field of clinical of transfusiology; 5) reduce the share of donation unsuitable for transfusion and processing; 6) strengthening marketing management in the development of fee-based services; 7) advertising paid services; 8) strengthening the publishing of teaching aids; 9) team-building staff. The threats (Ps = 2.1): 1) an increase of staff turnover; 2) the risk of litigation; 3) reduction gemoprodukts based on evidence-based medicine; 4) regression of scientific capacity; 5) organization of marketing; 6) transfusiologist marketing; 7) reduction in the quality of the evidence base transfusions.

Keywords: blood service, healthcare, Kazakhstan, quantative swot analysis

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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: Marie Fouet, Olivier Maire, Cécile Masse, Hugues Blanchet, Salomé Coignard, Nicolas Lavesque, Guillaume Bernard

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Exacerbated by global change, extreme climatic events such as atmospheric and marine heat waves may interact with the spread of non-indigenous species and their associated impacts on marine ecosystems. Since the 1970’s, the introduction of non-indigenous species due to oyster exchanges has been numerous. Among them, the Asian date mussel Arcuatula senhousia has colonized a large number of ecosystems worldwide (e.g., California, New Zealand, Italy). In these places, A.senhousia led to important habitat modifications in the benthic compartment through physical, biological, and biogeochemical effects associated with the development of dense mussel populations. In Arcachon Bay (France), a coastal lagoon of the French Atlantic and hotspot of oyster farming, abundances of A. senhousia recently increased, following a lag time of ca. 20 years since the first record of the species in 2002. Here, we addressed the potential effects of the interaction between A. senhousia invasion and heatwave intensity on ecosystem functioning within an intertidal mudflat. More precisely, two realistic intensities (“High” and “Severe”) of combined marine and atmospheric heatwaves have been simulated in an experimental tidal mesocosm system onto which naturally varying densities of A. senhousia and associated benthic communities were exposed in sediment cores collected in situ. Following a six-day exposure, community-scale responses were assessed by measuring benthic metabolism (oxygen and nutrient fluxes) in each core. Results show that besides significantly enhanced benthic metabolism with increasing heatwave intensity, mussel density clearly mediated the magnitude of the community-scale response, thereby highlighting the importance of understanding the interactive effects of environmental stressors co-occurring with non-indigenous species and their dependencies for a better assessment of their impacts.

Keywords: arcuatula senhousia, benthic habitat, ecosystem functioning, heatwaves, metabolism

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

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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

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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

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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: Mulligan T., Barker-Collo S., Gobson K., Jones K.

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There is a relatively scarce body of literature regarding adolescent experiences of traumatic brain injury (TBI). This qualitative study explored how sustaining a TBI at this unique stage of development might impact a young person as they navigate the challenges of adolescence and transition to adulthood, and what might support recovery. Thirteen young adults who sustained a mild-moderate TBI as an adolescent (aged 13 – 17 years), approximately 7.7 years (range = 6.7 – 8.0 years) prior, participated in the research. Semi-structured individual interviews were conducted to explore participants’ experiences surrounding and following their TBIs. Thematic analysis of interview data produced five key categories of findings: (1) Following their TBIs, many participants experienced problems with cognitive (e.g., forgetfulness, concentration difficulties), physical (e.g., migraines, fatigue) and emotional (e.g., depression, anxiety) functioning, which were often endured into adulthood. (2) TBI-related problems often adversely affected important areas of life for the participant, including school, work and friendships. (3) Changes following TBI commonly impacted identity formation. (4) Recovery processes evolved over time as the participants coped initially by just ‘getting on with it’, before learning to accept new limitations and, ultimately, growing from their TBI experiences. (5) While the presence of friends and family assisted recovery, struggles were often exacerbated by a lack of emotional support from others, in addition to the absence of any assistance or information-provision from professionals regarding what to expect following TBI. The findings suggest that even mild TBI sustained during adolescence can have consequences for an individual’s functioning, engagement in life and identity development, whilst also giving rise to post-traumatic growth. Recovery following adolescent TBI might be maximised by facilitating greater understanding of the injury and acknowledging its impacts on important areas of life, as well as the provision of emotional support and facilitating self-reflection and meaning-making.

Keywords: adolescent, brain Injury, qualitative, post-traumatic growth

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

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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: Takaharu Hirai, Yuta Mitobe, Hiromi Hirai

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Introduction: Eating disorders (ED) are serious psychiatric disorders that affect individuals, especially adolescents. It has been suggested that nonclinical ED-like characteristics are related to sleep problems. However, studies exploring the association between potential ED and sleep disorders have primarily been conducted in Europe and the United States. We conducted a survey of Japanese adolescents to investigate this claim. Method: In this cross-sectional study, 398 school-aged adolescents, aged 12–18 years old, matched for gender ratio, responded to a self-administered questionnaire survey. We used the Eating Attitudes Test-26 (EAT-26) and the Athens Insomnia Scale (AIS) to measure potential ED and sleep problems, respectively. In this study, participants with an EAT-26 total score of 0–19 points were classified as non-ED, while those with scores of 20 points or higher were classified as potential ED. Result: Of the 398 participants, 17 (4.3%) had an EAT-26 total score of 20 or higher. Among boys, the rate was 6 of 199 participants (3%), and among girls, the rate was 11 of 182 participants (6%). There were 89 participants (22.4%) with an AIS score of 6 points or higher, of which 36 (17.6%) were boys, and 53 (27.5%) were girls. Adolescents with potential ED had significantly higher rates of daytime sleep problems than those without ED. Further, while examining the types of sleep problems, adolescents with potential ED had greater problems with a sense of well-being and physical and mental functioning during the day. In contrast, no significant associations were found between potential ED and sleep initiation, awakenings during the night, early morning awakening, total sleep duration, or overall quality of sleep. Finally, nocturnal and daytime sleep scores were significantly associated with dieting, bulimia, and oral control EAT-26 sub-scores. Discussion: While Japanese adolescents with possible ED do not experience nighttime sleep problems, they do experience problems related to well-being and mental and physical functioning, which are indicators of daytime sleep problems. This may assist with early detection of disordered eating in adolescents. The study suggested that professionals working towards adolescent mental health issues need an approach that comprehensively integrates both sleep problems and potential ED.

Keywords: adolescents, potential eating disorders, sleep problems, eating attitudes test-26

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

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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

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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

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Authors: Yaseri Dahlia Apritasari

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Visual comfort is important for the building occupants to need. Visual comfort can be fulfilled through natural lighting (daylighting) and artificial lighting. One strategy to optimize natural lighting can be achieved through the facade second skin design. This strategy can reduce glare, and fulfill visual comfort need. However, the design strategy cannot achieve light intensity for visual comfort. Because the materials, design and opening percentage of the facade of second skin blocked sunlight. This paper discusses aluminum material for the facade second skin design that can fulfill the optimal visual comfort with the case studies Multi Media Tower building. The methodology of the research is combination quantitative and qualitative through field study observed, lighting measurement and visual comfort questionnaire. Then it used too simulation modeling (DIALUX 4.13, 2016) for three facades second skin design model. Through following steps; (1) Measuring visual comfort factor: light intensity indoor and outdoor; (2) Taking visual comfort data from building occupants; (3) Making models with different facade second skin design; (3) Simulating and analyzing the light intensity value for each models that meet occupants visual comfort standard: 350 lux (Indonesia National Standard, 2010). The result shows that optimization of aluminum material for the facade second skin design can meet optimal visual comfort for building occupants. The result can give recommendation aluminum opening percentage of the facade second skin can meet optimal visual comfort for building occupants.

Keywords: aluminium material, Facade, second skin, visual comfort

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Authors: Rishikesh Dingari, Sai Kiran Dornala

Abstract:

In this paper, a simple method of achieving maximum power by mechanical energy transmission device (METD) with integration to induction generator is proposed. METD functioning is explained and dynamic response of system to step input is plotted. Induction generator is being operated at self-excited mode with excitation capacitor at stator. Voltage and current are observed when linked to METD.

Keywords: mechanical energy transmitting device(METD), self-excited induction generator, wind turbine, hydraulic actuators

Procedia PDF Downloads 343

Authors: Kornelius Ronald Demu, Dewi Retno Sari Saputro, Purnami Widyaningsih

Abstract:

Human Development Index (HDI) is a standard measurement for a country's human development. Several factors may have influenced it, such as life expectancy, gross domestic product (GDP) based on the province's annual expenditure, the number of poor people, and the percentage of an illiterate people. The scatter plot between HDI and the influenced factors show that the plot does not follow a specific pattern or form. Therefore, the HDI's data in Indonesia can be applied with a nonparametric regression model. The estimation of the regression curve in the nonparametric regression model is flexible because it follows the shape of the data pattern. One of the nonparametric regression's method is a truncated spline. Truncated spline regression is one of the nonparametric approach, which is a modification of the segmented polynomial functions. The estimator of a truncated spline regression model was affected by the selection of the optimal knots point. Knot points is a focus point of spline truncated functions. The optimal knots point was determined by the minimum value of generalized cross validation (GCV). In this article were applied the data of Human Development Index with a truncated spline nonparametric regression model. The results of this research were obtained the best-truncated spline regression model to the HDI's data in Indonesia with the combination of optimal knots point 5-5-5-4. Life expectancy and the percentage of an illiterate people were the significant factors depend to the HDI in Indonesia. The coefficient of determination is 94.54%. This means the regression model is good enough to applied on the data of HDI in Indonesia.

Keywords: generalized cross validation (GCV), Human Development Index (HDI), knots point, nonparametric regression, truncated spline

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Authors: Daud Mustafa Minhas, Raja Rehan Khalid, Georg Frey

Abstract:

The next generation power systems are equipped with abundantly available free renewable energy resources (RES). During their low-cost operations, the price of electricity significantly reduces to a lower value, and sometimes it becomes negative. Therefore, it is recommended not to operate the traditional power plants (e.g. coal power plants) and to reduce the losses. In fact, it is not a cost-effective solution, because these power plants exhibit some shutdown and startup costs. Moreover, they require certain time for shutdown and also need enough pause before starting up again, increasing inefficiency in the whole power network. Hence, there is always a trade-off between avoiding negative electricity prices, and the startup costs of power plants. To exploit this trade-off and to increase the profit of a power plant, two main contributions are made: 1) introducing retrofit technology for state of art coal power plant; 2) proposing optimal control strategy for a power plant by exploiting different flexibility features. These flexibility features include: improving ramp rate of power plant, reducing startup time and lowering minimum load. While, the control strategy is solved as mixed integer linear programming (MILP), ensuring optimal solution for the profit maximization problem. Extensive comparisons are made considering pre and post-retrofit coal power plant having the same efficiencies under different electricity price scenarios. It concludes that if the power plant must remain in the market (providing services), more flexibility reflects direct economic advantage to the plant operator.

Keywords: discrete optimization, power plant flexibility, profit maximization, unit commitment model

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Authors: R. Santos Alimi

Abstract:

Using time-series techniques, this study empirically tested the validity of existing theory which stipulates there is a nonlinear relationship between government size and economic growth; such that government spending is growth-enhancing at low levels but growth-retarding at high levels, with the optimal size occurring somewhere in between. This study employed three estimation equations. First, for the size of government, two measures are considered as follows: (i) share of total expenditures to gross domestic product, (ii) share of recurrent expenditures to gross domestic product. Second, the study adopted real GDP (without government expenditure component), as a variant measure of economic growth other than the real total GDP, in estimating the optimal level of government expenditure. The study is based on annual Nigeria country-level data for the period 1970 to 2012. Estimation results show that the inverted U-shaped curve exists for the two measures of government size and the estimated optimum shares are 19.81% and 10.98%, respectively. Finally, with the adoption of real GDP (without government expenditure component), the optimum government size was found to be 12.58% of GDP. Our analysis shows that the actual share of government spending on average (2000 - 2012) is about 13.4%.This study adds to the literature confirming that the optimal government size exists not only for developed economies but also for developing economy like Nigeria. Thus, a public intervention threshold level that fosters economic growth is a reality; beyond this point economic growth should be left in the hands of the private sector. This finding has a significant implication for the appraisal of government spending and budgetary policy design.

Keywords: public expenditure, economic growth, optimum level, fully modified OLS

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Authors: Wanatchapong Kongkaew

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This paper proposes an application of probabilistic technique, namely Gaussian process regression, for estimating an optimal sequence of the single machine with total weighted tardiness (SMTWT) scheduling problem. In this work, the Gaussian process regression (GPR) model is utilized to predict an optimal sequence of the SMTWT problem, and its solution is improved by using an iterated local search based on simulated annealing scheme, called GPRISA algorithm. The results show that the proposed GPRISA method achieves a very good performance and a reasonable trade-off between solution quality and time consumption. Moreover, in the comparison of deviation from the best-known solution, the proposed mechanism noticeably outperforms the recently existing approaches.

Keywords: Gaussian process regression, iterated local search, simulated annealing, single machine total weighted tardiness

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Authors: Medani Khaled Ben Oualid

Abstract:

Most of researchers solved and analyzed the ORPD problem in the normal conditions. However, network collapses appear in contingency conditions. In this paper, ORPD under several contingencies is presented using the proposed method WOA. To ensure viability of the power system in contingency conditions, several critical cases are simulated in order to prevent and prepare the power system to face such situations. The results obtained are carried out in IEEE 30 bus test system for the solution of ORPD problem in which control of bus voltages, tap position of transformers and reactive power sources are involved. Moreover, another method, namely, Particle Swarm Optimization with Time Varying Acceleration Coefficient (PSO-TVAC) has been compared with the proposed technique. Simulation results indicate that the proposed WOA gives remarkable solution in terms of effectiveness in case of outages.

Keywords: optimal reactive power dispatch, metaheuristic techniques, whale optimization algorithm, real power loss minimization, contingency conditions

Procedia PDF Downloads 90

Authors: Imen Amari, Kaouther Gasmi, Asma Rebaya, Salem Hasnaoui

Abstract:

The problem of scheduling and mapping data flow applications on multi-core architectures is notoriously difficult. This difficulty is related to the rapid evaluation of Telecommunication and multimedia systems accompanied by a rapid increase of user requirements in terms of latency, execution time, consumption, energy, etc. Having an optimal scheduling on multi-cores DSP (Digital signal Processors) platforms is a challenging task. In this context, we present a novel technic and algorithm in order to find a valid schedule that optimizes the key performance metrics particularly the Latency. Our contribution is based on Satisfiability Modulo Theories (SMT) solving technologies which is strongly driven by the industrial applications and needs. This paper, describe a scheduling module integrated in our proposed Workflow which is advised to be a successful approach for programming the applications based on NoC-DSP platforms. This workflow transform automatically a Simulink model to a synchronous dataflow (SDF) model. The automatic transformation followed by SMT solver scheduling aim to minimize the final latency and other software/hardware metrics in terms of an optimal schedule. Also, finding the optimal numbers of cores to be used. In fact, our proposed workflow taking as entry point a Simulink file (.mdl or .slx) derived from embedded Matlab functions. We use an approach which is based on the synchronous and hierarchical behavior of both Simulink and SDF. Whence, results of running the scheduler which exist in the Workflow mentioned above using our proposed SMT solver algorithm refinements produce the best possible scheduling in terms of latency and numbers of cores.

Keywords: multi-cores DSP, scheduling, SMT solver, workflow

Procedia PDF Downloads 286