Search results for: control optimization

Authors: Hakim T. Kadhim, Faris A. Jabbar, Aldo Rona, Audrius Bagdanaviciu

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Computer-based optimization techniques can be employed to improve the efficiency of energy conversions processes, including reducing the aerodynamic loss in a thermal power plant turbomachine. In this paper, towards mitigating secondary flow losses, a design optimization workflow is implemented for the casing geometry of a 1.5 stage axial flow turbine that improves the turbine isentropic efficiency. The improved turbine is used in an open thermodynamic gas cycle with regeneration and cogeneration. Performance estimates are obtained by the commercial software Cycle – Tempo. Design and off design conditions are considered as well as variations in inlet air temperature. Reductions in both the natural gas specific fuel consumption and in CO₂ emissions are predicted by using the gas turbine cycle fitted with the new casing design. These gains are attractive towards enhancing the competitiveness and reducing the environmental impact of thermal power plant.

Keywords: axial flow turbine, computational fluid dynamics, gas turbine power plant, optimization

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Authors: B. Moaveni, S. Morovati

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In recent years, increasing the usage of railway transportations especially in developing countries caused more attention to control systems railway vehicles. Consequently, designing and implementing the modern control systems to improve the operating performance of trains and locomotives become one of the main concerns of researches. Dynamic braking systems is an important safety system which controls the amount of braking torque generated by traction motors, to keep the adhesion coefficient between the wheel-sets and rail road in optimum bound. Adhesion force has an important role to control the braking distance and prevent the wheels from slipping during the braking process. Cascade control structure is one of the best control methods for the wide range of industrial plants in the presence of disturbances and errors. This paper presents cascade control structure based on two forward simple controllers with two feedback loops to control the slip ratio and braking torque. In this structure, the inner loop controls the angular velocity and the outer loop control the longitudinal velocity of the locomotive that its dynamic is slower than the dynamic of angular velocity. This control structure by controlling the torque of DC traction motors, tries to track the desired velocity profile to access the predefined braking distance and to control the slip ratio. Simulation results are employed to show the effectiveness of the introduced methodology in dynamic braking system.

Keywords: cascade control, dynamic braking system, DC traction motors, slip control

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Authors: Martin Doran, Roy Sterritt, George Wilkie

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NASA, ESA, and NSSC space agencies have plans to put planetary rovers on Mars in 2020. For these future planetary rovers to succeed, they will heavily depend on sensors to detect obstacles. This will also become of vital importance in the future, if rovers become less dependent on commands received from earth-based control and more dependent on self-configuration and self-decision making. These planetary rovers will face harsh environments and the possibility of hardware failure is high, as seen in missions from the past. In this paper, we focus on using Autonomic principles where self-healing, self-optimization, and self-adaption are explored using the MAPE-K model and expanding this model to encapsulate the attributes such as Awareness, Analysis, and Adjustment (AAA-3). In the experimentation, a Pioneer P3-DX research robot is used to simulate a planetary rover. The sonar sensors on the P3-DX robot are used to simulate the sensors on a planetary rover (even though in reality, sonar sensors cannot operate in a vacuum). Experiments using the P3-DX robot focus on how our software system can be adapted with the loss of sonar sensor functionality. The autonomic manager system is responsible for the decision making on how to make use of remaining ‘enabled’ sonars sensors to compensate for those sonar sensors that are ‘disabled’. The key to this research is that the robot can still detect objects even with reduced sonar sensor capability.

Keywords: autonomic, self-adaption, self-healing, self-optimization

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Authors: Young Min Kim, Jeong Lak Sohn, Eui Soo Yoon

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This study describes the optimization of supercritical carbon dioxide (S-CO2) power cycle for recovering waste heat from a gas turbine. An S-CO2 cycle that recovers heat from small industrial and aeroderivative gas turbines can outperform a steam-bottoming cycle despite its simplicity and compactness. In using S-CO2 power cycles for waste heat recovery, a split cycle was studied to maximize the net output power by incorporating the utilization efficiency of the waste heat (lowering the temperature of the exhaust gas through the heater) along with the thermal efficiency of the cycle (minimizing the temperature difference for the heat transfer, exergy loss). The cooling condition of the S-CO2 WHR system has a great impact on the performance and the optimum low pressure of the system. Furthermore, the optimum high pressure of the S-CO2 WHR systems for the maximum power from the given heat sources is dependent on the temperature of the waste heat source.

Keywords: exergy loss, gas turbine, optimization, supercritical CO2 power cycle, split cycle, waste heat recovery

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Authors: Meetty Tomy, Arxhana G Thosar

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This paper provides the implementation of optimal control for an armature-controlled DC motor. The selection of error weighted Matrix and control weighted matrix in order to implement optimal control theory for improving the dynamic behavior of DC motor is presented. The closed loop performance of Armature controlled DC motor with derived linear optimal controller is then evaluated for the transient operating condition (starting). The result obtained from MATLAB is compared with that of PID controller and simple closed loop response of the motor.

Keywords: optimal control, DC motor, performance index, MATLAB

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Authors: Ritesh Joshi, Kishan Fuse, Gopal Zinzala, Nishit Nirmal

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Ti-6Al-4V is a titanium alloy having high strength, low weight and corrosion resistant which is a required characteristic for a material to be used in aerospace industry. Titanium, being a hard alloy is difficult to the machine via conventional methods, so it is a call to use non-conventional processes. In present work, the effects on Ti-6Al-4V by drilling a hole of Ø 6 mm using copper (99%) electrode in Electric Discharge Machining (EDM) process is analyzed. Effect of various input parameters like peak current, pulse-on time and pulse-off time on output parameters viz material removal rate (MRR) and electrode wear rate (EWR) is studied. Multi-objective optimization technique Grey relational analysis is used for process optimization. Experiments are designed using an L9 orthogonal array. ANOVA is used for finding most contributing parameter followed by confirmation tests for validating the results. Improvement of 7.45% in gray relational grade is observed.

Keywords: ANOVA, electric discharge machining, grey relational analysis, Ti-6Al-4V

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Authors: Youn-Sung Kim, Hye-Mi Kim, Sang-Hoon Seo, Jaden Cha

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This International standard IEC 61508 sets out a generic approach for all safety lifecycle activities for systems comprised of electrical/electronic/programmable electronic (E/E/PE) elements that are used to perform safety functions. The control unit in stage control system is safety related facilities to control state and speed for stage system running, and it performs safety-critical function by stage control system. The controller unit is part of safety loops corresponding to the IEC 61508 and classified as logic part in the safety loop. In this paper, we analyze using FMEDA (Failure Mode Effect and Diagnostic Analysis) to verification for fault tolerance methods and functional safety of control unit. Moreover, we determined SIL (Safety Integrity Level) for control unit according to the safety requirements defined in IEC 61508-2 based on an analyzed functional safety.

Keywords: safety function, failure mode effect, IEC 61508-2, diagnostic analysis, stage control system

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Authors: Zhoucheng Bao, Haiyan Zhu, Tingting Pang, Zuling Wang

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This paper proposes a multi-population DE with adaptive mutation and local search for global optimization, named AMMADE. In order to better coordinate the cooperation between the populations and the rational use of resources. In AMMADE, the population is divided based on the Euclidean distance sorting method at each generation to appropriately coordinate the cooperation between subpopulations and the usage of resources, such that the best-performed subpopulation will get more computing resources in the next generation. Further, an adaptive local search strategy is employed on the best-performed subpopulation to achieve a balanced search. The proposed algorithm has been tested by solving optimization problems taken from CEC2014 benchmark problems. Experimental results show that our algorithm can achieve a competitive or better than related methods. The results also confirm the significance of devised strategies in the proposed algorithm.

Keywords: differential evolution, multi-mutation strategies, memetic algorithm, adaptive local search

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Authors: Konstantinos Tolidis

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The mountains are amongst the most fragile environments in the world. The world’s mountain areas cover 24% of the Earth’s land surface and are home to 12% of the global population. A further 14% of the global population is estimated to live in the vicinity of their surrounding areas. As urbanization continues to increase in the world, the mountains are also key centers for recreation and tourism; their attraction is often heightened by their remarkably high levels of biodiversity. Due to the fact that the features in mountain areas vary spatially (development degree, human geography, socio-economic reality, relations of dependency and interaction with other areas-regions), the spatial planning on these areas consists of a crucial process for preserving the natural, cultural and human environment and consists of one of the major processes of an integrated spatial policy. This research has been focused on the spatial decision problem of land use allocation optimization which is an ordinary planning problem on the mountain areas. It is a matter of fact that such decisions must be made not only on what to do, how much to do, but also on where to do, adding a whole extra class of decision variables to the problem when combined with the consideration of spatial optimization. The utility of optimization as a normative tool for spatial problem is widely recognized. However, it is very difficult for planners to quantify the weights of the objectives especially when these are related to mountain areas. Furthermore, the land use allocation optimization problems at mountain areas must be addressed not only by taking into account the general development objectives but also the spatial objectives (e.g. compactness, compatibility and accessibility, etc). Therefore, the main research’s objective was to approach the land use allocation problem by utilizing a hybrid meta-heuristic optimization technique tailored to the mountain areas’ spatial characteristics. The results indicates that the proposed methodological approach is very promising and useful for both generating land use alternatives for further consideration in land use allocation decision-making and supporting spatial management plans at mountain areas.

Keywords: multiobjective land use allocation, mountain areas, spatial planning, spatial decision making, meta-heuristic methods

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Authors: Hao Li, Guy Y. Cornejo Maceda, Yiqing Li, Jianguo Tan, Marek Morzynski, Bernd R. Noack

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We propose an automated analysis of the flow control behaviour from an ensemble of control laws and associated time-resolved flow snapshots. The input may be the rich database of machine learning control (MLC) optimizing a feedback law for a cost function in the plant. The proposed methodology provides (1) insights into the control landscape, which maps control laws to performance, including extrema and ridge-lines, (2) a catalogue of representative flow states and their contribution to cost function for investigated control laws and (3) visualization of the dynamics. Key enablers are classification and feature extraction methods of machine learning. The analysis is successfully applied to the stabilization of a mixing layer with sensor-based feedback driving an upstream actuator. The fluctuation energy is reduced by 26%. The control replaces unforced Kelvin-Helmholtz vortices with subsequent vortex pairing by higher-frequency Kelvin-Helmholtz structures of lower energy. These efforts target a human interpretable, fully automated analysis of MLC identifying qualitatively different actuation regimes, distilling corresponding coherent structures, and developing a digital twin of the plant.

Keywords: machine learning control, mixing layer, feedback control, model-free control

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Authors: Dimitrios Ntardas, Alexandros Tzanetos, Georgios Dounias

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High Voltage Substations (HVS) are the intermediate step between production of power and successfully transmitting it to clients, making them one of the most important checkpoints in power grids. Nowadays - renewable resources and consequently distributed generation are growing fast, the construction of HVS is of high importance both in terms of quality and time completion so that new energy producers can quickly and safely intergrade in power grids. The resources needed, such as machines and workers, should be carefully allocated so that the construction of a HVS is completed on time, with the lowest possible cost (e.g. not spending additional cost that were not taken into consideration, because of project delays), but in the highest quality. In addition, there are milestones and several checkpoints to be precisely achieved during construction to ensure the cost and timeline control and to ensure that the percentage of governmental funding will be granted. The management of such a demanding project is a NP-hard problem that consists of prerequisite constraints and resource limits for each task of the project. In this work, a hybrid meta-heuristic method is implemented to solve this problem. Meta-heuristics have been proven to be quite useful when dealing with high-dimensional constraint optimization problems. Hybridization of them results in boost of their performance.

Keywords: hybrid meta-heuristic methods, substation construction, resource allocation, time-cost efficiency

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Authors: Efrain Rodriguez, Sergio Pertuz, Cristhian Riano

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Tool-path generation is an essential step in the FFF (Fused Filament Fabrication)-based Additive Manufacturing (AM) process planning. In the manufacture of a mechanical part by using additive processes, high resource consumption and prolonged production times are inherent drawbacks of these processes mainly due to non-optimized tool-path generation. In this work, we propose a heuristic-search intelligent algorithm-based approach for optimized tool-path generation for FFF-based AM. The main benefit of this approach is a significant reduction of travels without material deposition when the AM machine performs moves without any extrusion. The optimization method used reduces the number of travels without extrusion in comparison with commercial software as Slic3r or Cura Engine, which means a reduction of production time.

Keywords: additive manufacturing, tool-path optimization, fused filament fabrication, process planning

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Authors: Lahoucine Zaama, Sanae Douama

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In this work, we present the results of a dosimetry study in a Moroccan radiology department . The results are compared with those of a similar study in France. Furthermore, it determines the coefficient of transmission of the lead sheets of different thicknesses depending on the voltage (KV) in a direct exposure. The objective of this study is to choose the thickness of the radiation means to determine the leaf sample sealed with the smallest percentage value radiation transmission, and that in the context of optimization. Thus the comparison among the studies is essential to consider conduct studies and research in this framework to achieve the goal of optimization.

Keywords: radiology, dosimetry, radiation, dose, transmission

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Authors: Mustahsan Mir, Ahmed Hassanin, Mohammed A. Al-Saleh

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The layout optimization of building blocks of unequal areas has applications in many disciplines including VLSI floorplanning, macrocell placement, unequal-area facilities layout optimization, and plant or machine layout design. A number of heuristics and some analytical and hybrid techniques have been published to solve this problem. This paper presents an efficient high-quality building-block layout design technique especially suited for solving large-size problems. The higher efficiency and improved quality of optimized solutions are made possible by introducing the concept of Promising Infant Clusters in a constructive placement procedure. The results presented in the paper demonstrate the improved performance of the presented technique for benchmark problems in comparison with published heuristic, analytic, and hybrid techniques.

Keywords: block layout problem, building-block layout design, CAD, optimization, search techniques

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Authors: Arkadiusz Mezyk, Wojciech Klein, Mariusz Pawlak, Jacek Gnilka

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The aortic heart valve stents should fulfill many criterions. These criteria have a strong impact on the geometrical shape of the stent. Usually, the final construction of stent is a result of many year experience and knowledge. Depending on patents claims, different stent shapes are produced by different companies. This causes difficulties for biomechanics engineers narrowing the domain of feasible solutions. The paper present optimization method for stent geometry defining by a specific analytical equation based on various mathematical functions. This formula was implemented as APDL script language in ANSYS finite element environment. For the purpose of simulation tests, a few parameters were separated from developed equation. The application of the genetic algorithms allows finding the best solution due to selected objective function. Obtained solution takes into account parameters such as radial force, compression ratio and coefficient of expansion on the transverse axial.

Keywords: aortic stent, optimization process, geometry, finite element method

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Authors: Mrinmoy Majumder, Apu Kumar Saha

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The ever-increasing human population and its demand for energy is placing stress upon conventional energy sources; and as demand for power continues to outstrip supply, the need to optimize energy distribution and utilization is emerging as an important focus for various stakeholders. The distribution of available energy must be achieved in such a way that the needs of the consumer are satisfied. However, if the availability of resources is not sufficient to satisfy consumer demand, it is necessary to find a method to select consumers based on factors such as their socio-economic or environmental impacts. Weighting consumer types in this way can help separate them based on their relative importance, and cognitive optimization of the allocation process can then be carried out so that, even on days of particularly scarce supply, the socio-economic impacts of not satisfying the needs of consumers can be minimized. In this context, the present study utilized fuzzy logic to assign weightage to different types of consumers based at an educational campus in India, and then established optimal allocation by applying the non-linear mapping capability of neuro-genetic algorithms. The outputs of the algorithms were compared with similar outputs from particle swarm optimization and differential evolution algorithms. The results of the study demonstrate an option for the optimal utilization of available energy based on the socio-economic importance of consumers.

Keywords: power allocation, optimization problem, neural networks, environmental and ecological engineering

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Authors: Pingping Zhang, Yanpeng Cai, Jianlong Wang

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Stormwater storage tank (SST) is a popular low impact development technology for reducing stormwater runoff in the construction of sponge city. At present, it is difficult to perform the automatic control of SST for reducing peak flow. In this paper, fuzzy control was introduced into the peak control of SST to improve the efficiency of reducing stormwater runoff. Firstly, the design of SST was investigated. A catchment area and a return period were assumed, a SST model was manufactured, and then the storage capacity of the SST was verified. Secondly, the control parameters of the SST based on reducing stormwater runoff were analyzed, and a schematic diagram of real-time control (RTC) system based on peak control SST was established. Finally, fuzzy control system of a double input (flow and water level) and double output (inlet and outlet valve) was designed. The results showed that 1) under the different return periods (one year, three years, five years), the SST had the effect of delayed peak control and storage by increasing the detention time, 2) rainfall, pipeline flow, the influent time and the water level in the SST could be used as RTC parameters, and 3) the response curves of flow velocity and water level fluctuated very little and reached equilibrium in a short time. The combination of online monitoring and fuzzy control was feasible to control the SST automatically. This paper provides a theoretical reference for reducing stormwater runoff and improving the operation efficiency of SST.

Keywords: stormwater runoff, stormwater storage tank, real-time control, fuzzy control

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Authors: Shraddha Digole, Swarali Hingse, Uday Annapure

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Mycophenolic acid (MPA) is an immunosuppressant; produced by Penicillium Sp. Box-Behnken statistical experimental design was employed to optimize the condition of Penicillium brevicompactum NRRL 2011 for mycophenolic acid (MPA) production. Initially optimization of various physicochemical parameters and media components was carried out using one factor at a time approach and significant factors were screened by Taguchi L-16 orthogonal array design. Taguchi design indicated that glucose, KH2PO4 and MgSO4 had significant effect on MPA production. These variables were selected for further optimization studies using Box-Behnken design. Optimised fermentation condition, glucose (60 g/L), glycine (28 g/L), L-leucine (1.5g/L), KH2PO4 (3g/L), MgSO4.7H2O (1.5g/L), increased the production of MPA from 170 mg/L to 1032.54 mg/L. Analysis of variance (ANOVA) showed a high value of coefficient of determination R2 (0.9965), indicating a good agreement between experimental and predicted values and proves validity of the statistical model.

Keywords: Box-Behnken design, fermentation, mycophenolic acid, Penicillium brevicompactum

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Authors: Mamidi Ramakrishna Rao

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Doubly-fed induction generators (DFIG) due to their advantages like speed variation and four-quadrant operation, find its application in wind turbines. DFIG besides supplying power to the grid has to support reactive power (kvar) under grid voltage variations, should contribute minimum fault current during faults, have high efficiency, minimum weight, adequate rotor protection during crow-bar-operation from +20% to -20% of rated speed.  To achieve the optimum performance, a good electromagnetic design of DFIG is required. In this paper, a simple and heuristic global optimization – Differential Evolution has been used. Variables considered are lamination details such as slot dimensions, stack diameters, air gap length, and generator stator and rotor stack length. Two operating conditions have been considered - voltage and speed variations. Constraints included were reactive power supplied to the grid and limiting fault current and torque. The optimization has been executed separately for three objective functions - maximum efficiency, weight reduction, and grid fault stator currents. Subsequent calculations led to the conclusion that designs determined through differential evolution help in determining an optimum electrical design for each objective function.

Keywords: design optimization, performance, DFIG, differential evolution

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Authors: Torsten Schwan, Rene Unger

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Simulation of thermal and electrical building performance more and more becomes part of an integrative planning process. Increasing requirements on energy efficiency, the integration of volatile renewable energy, smart control and storage management often cause tremendous challenges for building engineers and architects. This mainly affects commercial or non-residential buildings. Their energy consumption characteristics significantly distinguish from residential ones. This work focuses on the many-objective optimization problem indoor air quality and comfort, especially in non-residential buildings. Based on a brief description of intermediate dependencies between different requirements on indoor air treatment it extends existing Modelica-based building physics models with additional system states to adequately represent indoor air conditions. Interfaces to corresponding HVAC (heating, ventilation, and air conditioning) system and control models enable closed-loop analyzes of occupants' requirements and energy efficiency as well as profitableness aspects. A complex application scenario of a nearly-zero-energy school building shows advantages of presented evaluation process for engineers and architects. This way, clear identification of air quality requirements in individual rooms together with realistic model-based description of occupants' behavior helps to optimize HVAC system already in early design stages. Building planning processes can be highly improved and accelerated by increasing integration of advanced simulation methods. Those methods mainly provide suitable answers on engineers' and architects' questions regarding more exuberant and complex variety of suitable energy supply solutions.

Keywords: indoor air quality, dynamic simulation, energy efficient control, non-residential buildings

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Authors: Chatchaval Pornpatkul, Wipawan Suksathid

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This paper is to study and control the pressure of the water inside the open tank using a cascade control with the communication in the process by fieldbus system for the pressure calibration. The plant model is to be used in experiments to control the level and flow process of the water by using Syscon program to create functions. We used to control by Intouch runtime program to create the graphic display on the screen. In this case we used PI control the level and the flow process of water in the open tank in the range of 0 – 10 L/m. The output signal of the level and the flow transmitter are the digital standard signal by fieldbus system. And all information displayed on the computer with the communication between the computer and plant model can be communication to each other through just one cable pair. And in this paper, the PI tuning, we used calculate by Ziegler-Nichols reaction curve method to control the plant model by PI controller.

Keywords: cascade control, fieldbus system, pressure calibration, microelectronics systems

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Authors: Zheming Cao

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Control loops are the most important components in the wind turbine system. Product quality, operation safety, and the economic performance are directly or indirectly connected to the performance of control systems. This paper proposed a performance evaluation method based on minimum-variance for wind turbine control system. This method can be applied on PID controller for pitch control system in the wind turbine. The good performance result demonstrated in the paper was achieved by retuning and optimizing the controller settings based on the evaluation result. The concepts presented in this paper are illustrated with the actual data of the industrial wind farm.

Keywords: control performance, evaluation, minimum-variance, wind turbine

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Authors: Seyedvahid Najafi, Viliam Makis

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In recent years, maintenance optimization has attracted special attention due to the growth of industrial systems complexity. Maintenance costs are high for many systems, and preventive maintenance is effective when it increases operations' reliability and safety at a reduced cost. The novelty of this research is to consider general repair in the modeling of multi-unit series systems and solve the maintenance problem for such systems using the semi-Markov decision process (SMDP) framework. We propose an opportunistic maintenance policy for a series system composed of two main units. Unit 1, which is more expensive than unit 2, is subjected to condition monitoring, and its deterioration is modeled using a gamma process. Unit 1 hazard rate is estimated by the proportional hazards model (PHM), and two hazard rate control limits are considered as the thresholds of maintenance interventions for unit 1. Maintenance is performed on unit 2, considering an age control limit. The objective is to find the optimal control limits and minimize the long-run expected average cost per unit time. The proposed algorithm is applied to a numerical example to compare the effectiveness of the proposed policy (policy Ⅰ) with policy Ⅱ, which is similar to policy Ⅰ, but instead of general repair, replacement is performed. Results show that policy Ⅰ leads to lower average cost compared with policy Ⅱ. 

Keywords: condition-based maintenance, proportional hazards model, semi-Markov decision process, two-unit series systems

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Authors: Joseph C. Chen, Venkata Karthik Jakka

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The main objective of this research is to optimize tensile strength and dimensional accuracy in injection molding processes using Taguchi Parameter Design. An L16 orthogonal array (OA) is used in Taguchi experimental design with five control factors at four levels each and with non-controllable factor vibration. A total of 32 experiments were designed to obtain the optimal parameter setting for the process. The optimal parameters identified for the shrinkage are shot volume, 1.7 cubic inch (A4); mold term temperature, 130 ºF (B1); hold pressure, 3200 Psi (C4); injection speed, 0.61 inch3/sec (D2); and hold time of 14 seconds (E2). The optimal parameters identified for the tensile strength are shot volume, 1.7 cubic inch (A4); mold temperature, 160 ºF (B4); hold pressure, 3100 Psi (C3); injection speed, 0.69 inch3/sec (D4); and hold time of 14 seconds (E2). The Taguchi-based optimization framework was systematically and successfully implemented to obtain an adjusted optimal setting in this research. The mean shrinkage of the confirmation runs is 0.0031%, and the tensile strength value was found to be 3148.1 psi. Both outcomes are far better results from the baseline, and defects have been further reduced in injection molding processes.

Keywords: injection molding processes, taguchi parameter design, tensile strength, high-density polyethylene(HDPE)

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Authors: Hassan Hajabdollahi

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Economic optimization of shell and tube heat exchanger (STHE) is presented in this paper. To increase the rate of heat transfer, copper oxide (CuO) nanoparticle is added into the tube side fluid and their optimum results are compared with the case of without additive nanoparticle. Total annual cost (TAC) is selected as fitness function and nine decision variables related to the heat exchanger parameters as well as concentration of nanoparticle are considered. Optimization results reveal the noticeable improvement in the TAC and in the case of heat exchanger working with nanofluid compared with the case of base fluid (8.9%). Comparison of the results between two studied cases also reveal that the lower tube diameter, tube number, and baffle spacing are needed in the case of heat exchanger working with nanofluid compared with the case of base fluid.

Keywords: shell and tube heat exchanger, nanoparticles additive, total annual cost, particle volumetric concentration

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Authors: A. Benbouali, H. Saidi, A. Derrouazin, T. Bessaad

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Aerial robotics is a very exciting research field dealing with a variety of subjects, including the attitude control. This paper deals with the control of a four rotor vertical take-off and landing (VTOL) Unmanned Aerial Vehicle. The paper presents a mathematical model based on the approach of Lagrange for the flight control of an autonomous quad-rotor. It also describes the controller architecture which is based on PID regulators. The control method has been simulated in closed loop in different situations. All the calculation stages and the simulation results have been detailed.

Keywords: quad-rotor, lagrange approach, proportional integral derivate (PID) controller, Matlab/Simulink

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Authors: L. A. Toro, N. Prieto, J. J. Vargas

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There are many control charts for monitoring mean and variance. Among these, the X y R, X y S, S2 Hotteling and Shewhart control charts, for mentioning some, are widely used for monitoring mean a variance in industrial processes. In particular, the Shewhart charts are based on the information about the process contained in the current observation only and ignore any information given by the entire sequence of points. Moreover, that the Shewhart chart is a control chart without memory. Consequently, Shewhart control charts are found to be less sensitive in detecting smaller shifts, particularly smaller than 1.5 times of the standard deviation. These kind of small shifts are important in many industrial applications. In this study and effective alternative to Shewhart control chart was implemented. In case of univariate process an Exponentially Moving Average (EWMA) control chart was developed and Multivariate Exponentially Moving Average (MEWMA) control chart in case of multivariate process. Both of these charts were based on memory and perform better that Shewhart chart while detecting smaller shifts. In these charts, information the past sample is cumulated up the current sample and then the decision about the process control is taken. The mentioned characteristic of EWMA and MEWMA charts, are of the paramount importance when it is necessary to control industrial process, because it is possible to correct or predict problems in the processes before they come to a dangerous limit.

Keywords: control charts, multivariate exponentially moving average (MEWMA), exponentially moving average (EWMA), industrial control process

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Authors: Lenka Dujčíková, Laurent Buiron, Ján Haščík

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The study is dedicated to safety management of SFR CAPRA core with CFV design improvements. In the case of CAPRA core, demands for reactivity control are higher than for reference core. There are two possible ways how to ensure the certain amount of negative reactivity. One option is to boost control rods worth. The Greater part of the study is aimed at the proposal of appropriate control rod design. At first, the European Fast Reactor (EFR) control rod design with high-enriched boron carbide B4C as absorber material was tested. Considering costly and difficult enrichment process, usage of natural boron carbide absorbator is desired. Obviously, the use of natural boron leads to CR worth reduction. In order to increase it to required value, moderator material was inserted inside the control rod. Various materials and geometric configurations were examined to find optimal solution corresponding with EFR based CR worth value.

Keywords: boron carbide, CAPRA core, control rod design, low void effect design, melting temperature, moderator material

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Authors: H. Hentati, R. Abdelmoula, Li Jia, A. Maalej

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In this work, we present numerical simulations of the quasi-static crack propagation based on the variation approach. We perform numerical simulations of a piece of brittle material without initial crack. An alternate minimization algorithm is used. Based on these numerical results, we determine the influence of numerical parameters on the location of crack. We show the importance of trying to optimize the time of numerical computation and we present the first attempt to develop a simple numerical method to optimize this time.

Keywords: fracture mechanics, optimization, variation approach, mechanic

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Authors: Imen Boudali, Marwa Ragmoun

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The Vehicle Routing Problem with Hard Time Windows (VRPHTW) is a basic distribution management problem that models many real-world problems. The objective of the problem is to deliver a set of customers with known demands on minimum-cost vehicle routes while satisfying vehicle capacity and hard time windows for customers. In this paper, we propose to deal with our optimization problem by using a new hybrid stochastic algorithm based on two metaheuristics: Chemical Reaction Optimization (CRO) and Greedy Randomized Adaptive Search Procedure (GRASP). The first method is inspired by the natural process of chemical reactions enabling the transformation of unstable substances with excessive energy to stable ones. During this process, the molecules interact with each other through a series of elementary reactions to reach minimum energy for their existence. This property is embedded in CRO to solve the VRPHTW. In order to enhance the population diversity throughout the search process, we integrated the GRASP in our method. Simulation results on the base of Solomon’s benchmark instances show the very satisfactory performances of the proposed approach.

Keywords: Benchmark Problems, Combinatorial Optimization, Vehicle Routing Problem with Hard Time Windows, Meta-heuristics, Hybridization, GRASP, CRO

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