In the paper the squared voltage-current functionals are minimized, which represent the global power losses in the network. In that way it is possible to find the voltage-current distributions on the net without the use of immitance operators and basing only on the Kirchhoff laws. Farther the individual branch parameters are defined in the syntheses process. Many optimal power analysis examples are also shown to illustrate the thesis included in the paper.
The paper deals with linear circuits synthesis with periodic parameters. It was proved that the time-varying voltages and currents of inner branches of such circuits can be calculated using linear recursive equations with periodic coefficients if signals on port are given. The stability theorem of periodic solution was formulated. Hereby described the synthesis problems appear when compensation of power supply systems is considered.
The box wing system is an unconventional way to connect the lifting surfaces that the designers willingly to use in prototypes of new aircrafts. The article present a way to quickly optimize the wing structure of box wing airplane that can be useful during conceptual design. At the beginning, there is presented theory and methods used to code optimization program. Structure analysis is based on FEM beam model, which is sufficient in conceptual design. Optimization is performed using hybrid method, connection of simple iteration and gradient descent methods. Finally, the program is validated by case study.
An optimal sensor placement methodology is implemented and herein proposed for SHM model-assisted design and analysis purposes. The kernel of this approach analysis is a genetic-based algorithm providing the sensor network layout by optimizing the probability of detection (PoD) function while, in this preliminary phase, a classic strain energy approach is adopted as well established damage detection criteria. The layout of the sensor network is assessed with respect to its own capability of detection, parameterized through the PoD. A distributed fiber optic strain sensor is adopted in order to get dense information of the structural strain field. The overall methodology includes an original user-friendly graphical interface (GUI) that reduces the time-to-design costs needs. The proposed methodology is preliminarily validated for isotropic and anisotropic elements.
The presented paper concerns CFD optimization of the straight-through labyrinth seal with a smooth land. The aim of the process was to reduce the leakage flow through a labyrinth seal with two fins. Due to the complexity of the problem and for the sake of the computation time, a decision was made to modify the standard evolutionary optimization algorithm by adding an approach based on a metamodel. Five basic geometrical parameters of the labyrinth seal were taken into account: the angles of the seal’s two fins, and the fin width, height and pitch. Other parameters were constrained, including the clearance over the fins. The CFD calculations were carried out using the ANSYS-CFX commercial code. The in-house optimization algorithm was prepared in the Matlab environment. The presented metamodel was built using a Multi-Layer Perceptron Neural Network which was trained using the Levenberg-Marquardt algorithm. The Neural Network training and validation were carried out based on the data from the CFD analysis performed for different geometrical configurations of the labyrinth seal. The initial response surface was built based on the design of the experiment (DOE). The novelty of the proposed methodology is the steady improvement in the response surface goodness of fit. The accuracy of the response surface is increased by CFD calculations of the labyrinth seal additional geometrical configurations. These configurations are created based on the evolutionary algorithm operators such as selection, crossover and mutation. The created metamodel makes it possible to run a fast optimization process using a previously prepared response surface. The metamodel solution is validated against CFD calculations. It then complements the next generation of the evolutionary algorithm.
The near net shaped manufacturing ability of squeeze casting process requiresto set the process variable combinations at their optimal levels to obtain both aesthetic appearance and internal soundness of the cast parts. The aesthetic and internal soundness of cast parts deal with surface roughness and tensile strength those can readily put the part in service without the requirement of costly secondary manufacturing processes (like polishing, shot blasting, plating, hear treatment etc.). It is difficult to determine the levels of the process variable (that is, pressure duration, squeeze pressure, pouring temperature and die temperature) combinations for extreme values of the responses (that is, surface roughness, yield strength and ultimate tensile strength) due to conflicting requirements. In the present manuscript, three population based search and optimization methods, namely genetic algorithm (GA), particle swarm optimization (PSO) and multi-objective particle swarm optimization based on crowding distance (MOPSO-CD) methods have been used to optimize multiple outputs simultaneously. Further, validation test has been conducted for the optimal casting conditions suggested by GA, PSO and MOPSO-CD. The results showed that PSO outperformed GA with regard to computation time.
The paper presents the theory of constraints (TOC) as a method used to improve results in a complex, multiplants organization. In the article the assumptions of this method has been presented as well as iterative approach concerning how to launch it in practice. Main indicators for organizational effectiveness assessment have also been presented. The maximization of production assets utilization is a key issue for competitive organization in the changing market conditions. An appropriate usage of the theory of constraints enables efficient allocation of financial assets among particular plants within a capital group. An application of a method has been presented based on throughput analyses and its influence to improve financial results of one plant organization and synergy effect in multiplants organization. The theory of constraints can be used in almost every kind of business sectors, among them are metal and foundry industries. It allows to be implemented in production organizations as well as in any other company’s profiles. Everywhere the constraint has been defined there is a chance to achieve an improvement following the presented method. The examples have been taken from the casting plants which use continuous and mold casting technologies. The examples show that TOC approach can be successfully employed as the improvement tool of foundries’ performances.
The optimization of cut-off grades is a fundamental issue for metallic ore deposits. The cut-off grade is used to classify the material as ore or waste. Due to the time value of money, in order to achieve the maximum net present value, an optimum schedules of cut-off grades must be used. The depletion rate is the rate of depletion of a mineral deposit. Variable mining costs are to be applied to the really excavated material, as some of the depletion can be left in-situ. Due to access constraints, some of the blocks that have an average grade less than the determined cut-off grade are left in-situ, some of them are excavated and dumped as waste material. Naturally, variable mining costs should be applied to the blocks of a mineral deposit that are actually excavated. The probability density function of an exponential distribution is used to find the portion of the depletion rate over the production rate that is to be left in-situ. As a result, inverse probability density function is to be applied as the portion of the depletion rate over the production rate that is to be excavated and dumped. The parts of a mineral deposit that are excavated but will be dumped as waste material incur some additional cost of rehabilitation that is to be included in the algorithm of the cut-off grades optimization. This paper describes the general problem of cut-off grades optimization and outlines the further extension of the method including various depletion rates and variable rehabilitation cost. The author introduces the general background of the use of grid search in cut-off grades optimization by using various depletion rates and variable rehabilitation cost. The software developed in this subject is checked by means of a case study.
The article discusses the weldment to casting conversion process of rocker arm designed for operation in a special purpose vehicle to obtain a consistency of objective functions, which assume the reduced weight of component, the reduced maximum effort of material under the impact of service loads achieved through topology modification for optimum strength distribution in the sensitive areas, and the development of rocker arm manufacturing technology. As a result of conducted studies, the unit weight of the item was reduced by 25%, and the stress limit values were reduced to a level guaranteeing safe application.
Five models and methodology are discussed in this paper for constructing classifiers capable of recognizing in real time the type of fuel injected into a diesel engine cylinder to accuracy acceptable in practical technical applications. Experimental research was carried out on the dynamic engine test facility. The signal of in-cylinder and in-injection line pressure in an internal combustion engine powered by mineral fuel, biodiesel or blends of these two fuel types was evaluated using the vibro-acoustic method. Computational intelligence methods such as classification trees, particle swarm optimization and random forest were applied.
The paper presents results of a research on simulation of magnetic tip-surface interaction as a function of the lift height in the magnetic force microscopy. As expected, magnetic signal monotonically decays with increasing lift height, but the question arises, whether or not optimal lift height eventually exists. To estimate such a lift height simple procedure is proposed in the paper based on the minimization of the fractal dimension of the averaged profile of the MFM signal. In this case, the fractal dimension serves as a measure of distortion of a pure tip-surface magnetic coupling by various side effects, e.g. thermal noise and contribution of topographic features. Obtained simulation results apparently agree with experimental data.
The article describes the optimization of the melting brass. Brasses, as one of the most popular alloys of copper, deserve special attention in the context of the processes of melting, which in turn would provide not only products of better quality, but also reduce the cost of their production or refining. For this purpose, several studies carried out deriatographic (DTA) and thermogravimetric (TG) using derivatograph. The results were confronted with the program SLAG - PROP used to evaluate the physicochemical properties of the coatings extraction. Based on the survey and analysis of the program can identify the most favorable physico - chemical properties, which should be carried out treatments. This allows for slag mixtures referred configurations oxide matrix containing specific stimulators of the reaction. Conducted empirical studies indicate a convergence of the areas proposed by the application. It should also be noted that the program also indicates additional areas in which to carry out these processes would get even better, to optimize the melting process, the results.
Energy and spectral efficiency are the main challenges in 5th generation of mobile cellular networks. In this paper, we propose an optimization algorithm to optimize the energy efficiency by maximizing the spectral efficiency. Our simulation results show a significant increase in terms of spectral efficiency as well as energy efficiency whenever the mobile user is connected to a low power indoor base station. By applying the proposed algorithm, we show the network performance improvements up to 9 bit/s/Hz in spectral efficiency and 20 Gbit/Joule increase in energy efficiency for the mobile user served by the indoor base station rather than by the outdoor base station.
The paper is an exploration of the optimal design parameters of a space-constrained electromagnetic vibration-based generator. An electromagnetic energy harvester is composed of a coiled polyoxymethylen circular shell, a cylindrical NdFeB magnet, and a pair of helical springs. The magnet is vertically confined between the helical springs that serve as a vibrator. The electrical power connected to the coil is actuated when the energy harvester is vibrated by an external force causing the vibrator to periodically move through the coil. The primary factors of the electrical power generated from the energy harvester include a magnet, a spring, a coil, an excited frequency, an excited amplitude, and a design space. In order to obtain maximal electrical power during the excitation period, it is necessary to set the system’s natural frequency equal to the external forcing frequency. There are ten design factors of the energy harvester including the magnet diameter (Dm), the magnet height (Hm), the system damping ratio (ζsys), the spring diameter (Ds), the diameter of the spring wire (ds), the spring length (ℓs), the pitch of the spring (ps), the spring’s number of revolutions (Ns), the coil diameter (Dc), the diameter of the coil wire (dc), and the coil’s number of revolutions (Nc). Because of the mutual effects of the above factors, searching for the appropriate design parameters within a constrained space is complicated. Concerning their geometric allocation, the above ten design parameters are reduced to four (Dm, Hm, ζsys, and Nc). In order to search for optimal electrical power, the objective function of the electrical power is maximized by adjusting the four design parameters (Dm, Hm, ζsys, and Nc) via the simulated annealing method. Consequently, the optimal design parameters of Dm, Hm, ζsys, and Nc that produce maximum electrical power for an electromagnetic energy harvester are found.
In the paper the new constructions of robots, modern technologies of painting and newest methods of paint robots programming were presented. Fanuc P-250iA robot using to painting was characterized. The general characteristic of robot with controller R-30iA was demonstrated. The technology and the paint equipment applied to paint frames and load-carrying boxes was shown. The possibilities of simulation software Roboguide were presented exactly, which is a tool for robot environment simulation on a computer PC. Roboguide system application can reduce the programming time of robots and necessary programs optimization conducted before implementation to production.
Removal of mercury(II) (Hg(II)) from aqueous media by a new biosorbent was carried out. Natural Polyporus squamosus fungus, which according to the literature has not been used for the purpose of Hg(II) biosorption before, was utilized as a low-cost biosorbent, and the biosorption conditions were analyzed by response surface methodology (RSM). Medium parameters which were expected to affect the biosorption of Hg(II) were determined to be initial pH, initial Hg(II) concentration (Co), temperature (T (°C)), and contact time (min). All experiments were carried out in a batch system using 250 mL fl asks containing 100 mL solution with a magnetic stirrer. The Hg(II) concentrations remaining in fi ltration solutions after biosorption were analyzed using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES). Based on the RSM results, the optimal conditions were found to be 5.30, 47.39 mg/L, 20°C and 254.9 min for pH, Co, T (°C), and contact time, respectively. Under these optimal conditions, the maximum biosorbed amount and the biosorption yield were calculated to be 3.54 mg/g and 35.37%, respectively. This result was confi rmed by experiments. This result shows that Polyporus squamosus has a specifi c affi nity for Hg ions. Under optimal conditions, by increasing the amount of Polyporus squamosus used, it can be concluded that all Hg ions will be removed
One of the most critical aspects of mine design is to determine the optimum cut-off grade. Despite Lane’s theory, which aims to optimize the cut-off grade by maximizing the net present value (NPV), which is now an accepted principle used in open pit planning studies, it is less developed and applied in optimizing the cut-off grade for underground polymetallic mines than open pit mines, as optimization in underground polymetallic mines is more difficult. Since there is a similar potential for optimization between open pit mines and underground mines, this paper extends the utilization of Lane’s theory and proposes an optimization model of the cut-off grade applied to combined mining-mineral processing in underground mines with multi-metals. With the help of 3D visualization model of deposits and using the equivalent factors, the objective function is expressed as one variable function of the cut-off grade. Then, the curves of increment in present value versus the cut-off grade concerning different constraints of production capacities are constructed respectively, and the reasonable cut-off grade corresponding to each constraint is calculated by using the golden section search method. The defined criterion for the global optimization of the cut-off grade is determined by maximizing the overall marginal economics. An underground polymetallic copper deposit in Tibet is taken as an example to validate the proposed model in the case study. The results show that the overall optimum equivalent cut-off grade, 0.28%, improves NPV by RMB 170.2 million in comparison with the cut-off grade policy currently used. Thus, the application of the optimization model is conducive to achieving more satisfactory economic benefits under the premise of the rational utilization of mineral resources.
Optimization of encoding process in video compression is an important research problem, especially in the case of modern, sophisticated compression technologies. In this paper, we consider HEVC, for which a novel method for selection of the encoding modes is proposed. By the encoding modes we mean e.g. coding block structure, prediction types and motion vectors. The proposed selection is done basing on noise-reduced version of the input sequence, while the information about the video itself, e.g. transform coefficients, is coded basing on the unaltered input. The proposed method involves encoding of two versions of the input sequence. Further, we show realization proving that the complexity is only negligibly higher than complexity of a single encoding. The proposal has been implemented in HEVC reference software from MPEG and tested experimentally. The results show that the proposal provides up to 1.5% bitrate reduction while preserving the same quality of a decoded video.
Screw axis measurement methods obtain a precise identification of the physical reality of the industrial robots’ geometry. However, these methods are in a clear disadvantage compared to mathematical optimisation processes for kinematical parameters. That’s because mathematical processes obtain kinematical parameters which best reduce the robot errors, despite not necessarily representing the real geometry of the robot. This paper takes the next step at the identification of a robot’s movement from the identification of its real kinematical parameters for the later study of every articulation’s rotation. We then obtain a combination of real kinematic and dynamic parameters which describe the robot’s movement, improving its precision with a physical understanding of the errors.