Search results for: optimal condition

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: Mosses E. Lufuke

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This paper attempted to investigate whether there is Granger-causality running from trade to environment as evidenced in the changing climatic condition and land degradation. Using Tanzania as the reference, VAR-Granger-causality test was employed to rationalize the conundrum of causal-effect relationship between trade and environment. The changing climatic condition, as the proxy of both nitrous oxide emissions (in thousand metric tons of CO₂ equivalent) and land degradation measured by the size of arable land were tested against trade using both exports and imports variables. The result indicated that neither of the trade variables Granger-cause the variability on gas emissions and arable land size. This suggests the possibility that all trade concerns in relation to environment to have been internalized in domestic policies to offset any likely negative consequence.

Keywords: environment, growth, impact, trade

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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: Benniche Omar

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We are concerned with abstract fully nonlinear differential equations having the form y’(t)=Ay(t)+f(t,y(t)) where A is an m—dissipative operator (possibly multi—valued) defined on a subset D(A) of a Banach space X with values in X and f is a given function defined on I×X with values in X. We consider a graph K in I×X. We recall that K is said to be viable with respect to the above abstract differential equation if for each initial data in K there exists at least one trajectory starting from that initial data and remaining in K at least for a short time. The viability problem has been studied by many authors by using various techniques and frames. If K is closed, it is shown that a tangency condition, which is mainly linked to the dynamic, is crucial for viability. In the case when X is infinite dimensional, compactness and convexity assumptions are needed. In this paper, we are concerned with the notion of near viability for a given graph K with respect to y’(t)=Ay(t)+f(t,y(t)). Roughly speaking, the graph K is said to be near viable with respect to y’(t)=Ay(t)+f(t,y(t)), if for each initial data in K there exists at least one trajectory remaining arbitrary close to K at least for short time. It is interesting to note that the near viability is equivalent to an appropriate tangency condition under mild assumptions on the dynamic. Adding natural convexity and compactness assumptions on the dynamic, we may recover the (exact) viability. Here we investigate near viability for a graph K in I×X with respect to y’(t)=Ay(t)+f(t,y(t)) where A and f are as above. We emphasis that the t—dependence on the perturbation f leads us to introduce a new tangency concept. In the base of a tangency conditions expressed in terms of that tangency concept, we formulate criteria for K to be near viable with respect to y’(t)=Ay(t)+f(t,y(t)). As application, an abstract null—controllability theorem is given.

Keywords: abstract differential equation, graph, tangency condition, viability

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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: K. Debkowska

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The aim of this article is presenting the possibilities of using Fuzzy Set Qualitative Comparative Analysis (fsQCA) in researches concerning business models of enterprises. FsQCA is a bridge between quantitative and qualitative researches. It's potential can be used in analysis and evaluation of business models. The article presents the results of a study conducted on the basis of enterprises belonging to different sectors: transport and logistics, industry, building construction, and trade. The enterprises have been researched taking into account the components of business models and the financial condition of companies. Business models are areas of complex and heterogeneous nature. The use of fsQCA has enabled to answer the following question: which components of a business model and in which configuration influence better financial condition of enterprises. The analysis has been performed separately for particular sectors. This enabled to compare the combinations of business models' components which actively influence the financial condition of enterprises in analyzed sectors. The following components of business models were analyzed for the purposes of the study: Key Partners, Key Activities, Key Resources, Value Proposition, Channels, Cost Structure, Revenue Streams, Customer Segment and Customer Relationships. These components of the study constituted the variables shaping the financial results of enterprises. The results of the study lead us to believe that fsQCA can help in analyzing and evaluating a business model, which is important in terms of making a business decision about the business model used or its change. In addition, results obtained by fsQCA can be applied by all stakeholders connected with the company.

Keywords: business models, components of business models, data analysis, fsQCA

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Authors: Lin Yunuo, Seow Xing Quan, Burra Venkata Durga Kumar

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In this modern era, the cloud operating system is the world trend applied in various industries such as business, healthy, etc. In order to deal with the large capacity of requirements in cloud computing, research come up with multi-tenant cloud computing to maximize the benefits of server providers and clients. However, there are still issues in multi-tenant cloud computing especially regarding resource allocation. Issues such as inefficient resource utilization, large latency, lack of scalability and elasticity and poor data isolation had caused inefficient resource allocation in multi-tenant cloud computing. Without a doubt, these issues prevent multitenancy reaches its best condition. In fact, there are multiple studies conducted to determine the optimal resource allocation to solve these problems these days. This article will briefly introduce the cloud operating system, Multi-tenant cloud computing and resource allocation in cloud computing. It then discusses resource allocation in multi-tenant cloud computing and the current challenges it faces. According to the issue ‘ineffective resource utilization’, we will discuss an efficient dynamic scheduling technique for multitenancy, namely Multi-tenant Dynamic Resource Scheduling Model (MTDRSM). Moreover, there also have some recommendations to improve the shortcoming of this model in this paper’s final section.

Keywords: cloud computing, cloud operation system, multitenancy, resource allocation, utilization of cloud resources

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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: Pongchanun Luangpaiboon, Wanwisa Sarasang

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In this paper, a performance of shuffled frog leaping algorithm was investigated on the stealth laser dicing process. Effect of problem on the performance of the algorithm was based on the tolerance of meandering data. From the customer specification it could be less than five microns with the target of zero microns. Currently, the meandering levels are unsatisfactory when compared to the customer specification. Firstly, the two-level factorial design was applied to preliminary study the statistically significant effects of five process variables. In this study one influential process variable is integer. From the experimental results, the new operating condition from the algorithm was superior when compared to the current manufacturing condition.

Keywords: stealth laser dicing process, meandering, meta-heuristics, shuffled frog leaping algorithm

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Authors: N. Seemuang, T. McLeay, T. Slatter

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Worn tools have a direct effect on the surface finish and part accuracy. Tool condition monitoring systems have been developed over a long period and used to avoid a loss of productivity resulting from using a worn tool. However, the majority of tool monitoring research has applied expensive sensing systems not suitable for production. In this work, the cutting sound in turning machine was studied using microphone. Machining trials using seven cutting conditions were conducted until the observable flank wear width (FWW) on the main cutting edge exceeded 0.4 mm. The cutting inserts were removed from the tool holder and the flank wear width was measured optically. A microphone with built-in preamplifier was used to record the machining sound of EN24 steel being face turned by a CNC lathe in a wet cutting condition using constant surface speed control. The sound was sampled at 50 kS/s and all sound signals recorded from microphone were transformed into the frequency domain by FFT in order to establish the frequency content in the audio signature that could be then used for tool condition monitoring. The extracted feature from audio signal was compared to the flank wear progression on the cutting inserts. The spectrogram reveals a promising feature, named as ‘spindle noise’, which emits from the main spindle motor of turning machine. The spindle noise frequency was detected at 5.86 kHz of regardless of cutting conditions used on this particular CNC lathe. Varying cutting speed and feed rate have an influence on the magnitude of power spectrum of spindle noise. The magnitude of spindle noise frequency alters in conjunction with the tool wear progression. The magnitude increases significantly in the transition state between steady-state wear and severe wear. This could be used as a warning signal to prepare for tool replacement or adapt cutting parameters to extend tool life.

Keywords: tool wear, flank wear, condition monitoring, spindle noise

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Authors: J. Singh, Swati Dubey, R. P. Singh

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Microalgal strains can accumulate greatly enhanced levels of lipids under nitrogen-deficient condition, making these as one of the most promising sustainable sources for biofuel production. High-grade biofuel production from microalgal biomass could be facilitated by analysing the lipid content of the microalgae and enumerating its dynamics under varying nutrient conditions. In the present study, a detailed investigation of changes in lipid composition in Chlorella species and Scenedesmus abundans in response to nitrogen limited condition was performed to provide novel mechanistic insights into the lipidome during stress conditions. The mass spectroscopic approaches mainly LC-MS and GC-MS were employed for lipidomic profiling in both the microalgal strains. The analyses of lipid profiling using LC-MS revealed distinct forms of lipids mainly phospho- and glycolipids, including betaine lipids, and various other forms of lipids in both the microalgal strains. As detected, an overall decrease in polar lipids was observed. However, GC-MS analyses had revealed that the synthesis of the storage lipid i.e. triacylglycerol (TAG) was substantially stimulated in both the strains under nitrogen limited conditions. The changes observed in the overall fatty acid profile were primarily due to the decrease in proportion of polar lipids to TAGs. This study had enabled in analysing a detailed and orchestrated form of lipidomes in two different microalgal strains having potential for biodiesel production.

Keywords: biofuel, GC-MS, LC-MS, lipid, microalgae

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Authors: Xuan Sun, Mingbo Tong

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In order to study the effect of hydrothermal environment on the fatigue properties of carbon fiber fabric composites, the experiments on fatigue and residual compressive strength with the center-hole laminates were carried out. For the experiments on fatigue in hydrothermal environment, an environmental chamber used for hydrothermal environment was designed, and the FLUENT was used to simulate the field of temperature in the environmental chamber, it proved that the design met the test requirements. In accordance with ASTM standard, the fatigue test fixture and compression test fixture were designed and produced. Then the tension-compression fatigue tests were carried out in conditions of standard environment (temperature of 23+2℃, relative humidity of 50+/-5%RH) and hydrothermal environment (temperature of 70 +2℃, relative humidity of 85+/-5%RH). After that, the residual compressive strength tests were carried out, respectively. The residual compressive strength after fatigue in condition of standard environment was set as a reference value, compared with the value in condition of hydrothermal environment, calculating the difference between them. According to the result of residual compressive strength tests, it shows that the residual compressive strength after fatigue in condition of hydrothermal environment was decreased by 13.5%,so the hydrothermal environment has little effect on the residual compressive strength of carbon fiber fabric composites laminates after fatigue under load spectrum in this research.

Keywords: carbon fiber, hydrothermal environment, fatigue, residual compressive strength

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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: Y. Alrubyli

Abstract:

Unmanned Arial Vehicles (UAVs), and more specifically, quadcopters need to be stable during their flights. Altitude stability is usually achieved by using a PID controller that is built into the flight controller software. Furthermore, the PID controller has gains that need to be tuned to reach optimal altitude stabilization during the quadcopter’s flight. For that, control system engineers need to tune those gains by using extensive modeling of the environment, which might change from one environment and condition to another. As quadcopters penetrate more sectors, from the military to the consumer sectors, they have been put into complex and challenging environments more than ever before. Hence, intelligent self-stabilizing quadcopters are needed to maneuver through those complex environments and situations. Here we show that by using online reinforcement learning with minimal background knowledge, the altitude stability of the quadcopter can be achieved using a model-free approach. We found that by using background knowledge instead of letting the online reinforcement learning algorithm wander for a while to tune the PID gains, altitude stabilization can be achieved faster. In addition, using this approach will accelerate development by avoiding extensive simulations before applying the PID gains to the real-world quadcopter. Our results demonstrate the possibility of using the trial and error approach of reinforcement learning combined with background knowledge to achieve faster quadcopter altitude stabilization in different environments and conditions.

Keywords: reinforcement learning, Q-leanring, online learning, PID tuning, unmanned aerial vehicle, quadcopter

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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 518

Authors: Gbenga F. Akomolafe, Joseph Omojola, Ezekiel S. Joshua, Seyi C. Adediwura, Elijah T. Adesuji, Michael O. Odey, Oyinade A. Dedeke, Ayo H. Labulo

Abstract:

Microgravity is known to be a major abiotic stress in space which affects plants depending on the duration of exposure. In this work, tomatoes seeds were exposed to long hours of simulated microgravity condition using a one-axis clinostat. The seeds were sown on a 1.5% combination of plant nutrient and agar-agar solidified medium in three Petri dishes. One of the Petri dishes was mounted on the clinostat and allowed to rotate at the speed of 20 rpm for 72 hours, while the others were subjected to the normal gravity vector. The anatomical sections of both clinorotated and normal gravity plants were made after 72 hours and observed using a Phase-contrast digital microscope. The percentage germination, as well as the growth rate of the normal gravity seeds, was higher than the clinorotated ones. The germinated clinorotated roots followed different directions unlike the normal gravity ones which grew towards the direction of gravity vector. The clinostat was able to switch off gravistimulation. Distinct cellular arrangement was observed for tomatoes under normal gravity condition, unlike those of clinorotated ones. The root epidermis and cortex of normal gravity are thicker than the clinorotated ones. This implied that under long-term microgravity influence, plants do alter their anatomical features as a way of adapting to the stress condition.

Keywords: anatomy, clinostat, germination, lycopersicon esculentum, microgravity

Procedia PDF Downloads 322

Authors: Lazlo Fauth, Andreas Ligocki

Abstract:

For cost-effective use of harvesters, expensive repairs and unplanned downtimes must be reduced as far as possible. The predictive detection of failing systems and the calculation of intelligent service intervals, necessary to avoid these factors, require in-depth knowledge of the machines' behavior. Such know-how needs permanent monitoring of the machine state from different technical perspectives. In this paper, three approaches will be presented as they are currently pursued in the publicly funded project PreForst at Ostfalia University of Applied Sciences. These include the intelligent linking of workshop and service data, sensors on the harvester, and a special online hydraulic oil condition monitoring system. Furthermore the paper shows potentials as well as challenges for the use of these data in the conception of a predictive maintenance system.

Keywords: predictive maintenance, condition monitoring, forest harvesting, forest engineering, oil data, hydraulic data

Procedia PDF Downloads 145

Authors: Rachael Collins, George Lafford

Abstract:

We report a case of a generally fit and a well 54-year-old gentleman who presented with a two-day history of worsening left-sided otorrhea, headache, neck stiffness, vomiting and pyrexia on the background of a seven-week history of OE. His condition progressed dramatically as he developed symptoms consistent with acute complete cervical cord syndrome with radiological evidence of skull base osteomyelitis, parapharyngeal, retropharyngeal and paravertebral abscesses and sigmoid sinus thrombus. Ultimately he made a significant, although not complete, recovery. This case is unique in demonstrating how OE can develop into a potentially life-threatening condition. It emphasizes the importance of early diagnosis and treatment of OE, the recognition of ‘red flag’ symptoms and highlights the importance of a multi-disciplinary team (MDT) approach when managing complex complications of OE.

Keywords: ENT, neurology, otology, MDT

Procedia PDF Downloads 149

Authors: Yaseri Dahlia Apritasari

Abstract:

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

Procedia PDF Downloads 352