Buncher system parameter optimization
International Nuclear Information System (INIS)
Wadlinger, E.A.
1981-01-01
A least-squares algorithm is presented to calculate the RF amplitudes and cavity spacings for a series of buncher cavities each resonating at a frequency that is a multiple of a fundamental frequency of interest. The longitudinal phase-space distribution, obtained by particle tracing through the bunching system, is compared to a desired distribution function of energy and phase. The buncher cavity parameters are adjusted to minimize the difference between these two distributions. Examples are given for zero space charge. The manner in which the method can be extended to include space charge using the 3-D space-charge calculation procedure is indicated
Optimization of Parameters of Asymptotically Stable Systems
Directory of Open Access Journals (Sweden)
Anna Guerman
2011-01-01
Full Text Available This work deals with numerical methods of parameter optimization for asymptotically stable systems. We formulate a special mathematical programming problem that allows us to determine optimal parameters of a stabilizer. This problem involves solutions to a differential equation. We show how to chose the mesh in order to obtain discrete problem guaranteeing the necessary accuracy. The developed methodology is illustrated by an example concerning optimization of parameters for a satellite stabilization system.
Optimalization of selected RFID systems Parameters
Directory of Open Access Journals (Sweden)
Peter Vestenicky
2004-01-01
Full Text Available This paper describes procedure for maximization of RFID transponder read range. This is done by optimalization of magnetics field intensity at transponder place and by optimalization of antenna and transponder coils coupling factor. Results of this paper can be used for RFID with inductive loop, i.e. system working in near electromagnetic field.
Hybrid computer optimization of systems with random parameters
White, R. C., Jr.
1972-01-01
A hybrid computer Monte Carlo technique for the simulation and optimization of systems with random parameters is presented. The method is applied to the simultaneous optimization of the means and variances of two parameters in the radar-homing missile problem treated by McGhee and Levine.
Future xenon system operational parameter optimization
International Nuclear Information System (INIS)
Lowrey, J.D.; Eslinger, P.W.; Miley, H.S.
2016-01-01
Any atmospheric monitoring network will have practical limitations in the density of its sampling stations. The classical approach to network optimization has been to have 12 or 24-h integration of air samples at the highest station density possible to improve minimum detectable concentrations. The authors present here considerations on optimizing sampler integration time to make the best use of any network and maximize the likelihood of collecting quality samples at any given location. In particular, this work makes the case that shorter duration sample integration (i.e. <12 h) enhances critical isotopic information and improves the source location capability of a radionuclide network, or even just one station. (author)
Optimization Design of Multi-Parameters in Rail Launcher System
Yujiao Zhang; Weinan Qin; Junpeng Liao; Jiangjun Ruan
2014-01-01
Today the energy storage systems are still encumbering, therefore it is useful to think about the optimization of a railgun system in order to achieve the best performance with the lowest energy input. In this paper, an optimal design method considering 5 parameters is proposed to improve the energy conversion efficiency of a simple railgun. In order to avoid costly trials, the field- circuit method is employed to analyze the operations of different structural railguns with different paramete...
Optimal Parameter Selection of Power System Stabilizer using Genetic Algorithm
Energy Technology Data Exchange (ETDEWEB)
Chung, Hyeng Hwan; Chung, Dong Il; Chung, Mun Kyu [Dong-AUniversity (Korea); Wang, Yong Peel [Canterbury Univeristy (New Zealand)
1999-06-01
In this paper, it is suggested that the selection method of optimal parameter of power system stabilizer (PSS) with robustness in low frequency oscillation for power system using real variable elitism genetic algorithm (RVEGA). The optimal parameters were selected in the case of power system stabilizer with one lead compensator, and two lead compensator. Also, the frequency responses characteristics of PSS, the system eigenvalues criterion and the dynamic characteristics were considered in the normal load and the heavy load, which proved usefulness of RVEGA compare with Yu's compensator design theory. (author). 20 refs., 15 figs., 8 tabs.
Optimization Design of Multi-Parameters in Rail Launcher System
Directory of Open Access Journals (Sweden)
Yujiao Zhang
2014-05-01
Full Text Available Today the energy storage systems are still encumbering, therefore it is useful to think about the optimization of a railgun system in order to achieve the best performance with the lowest energy input. In this paper, an optimal design method considering 5 parameters is proposed to improve the energy conversion efficiency of a simple railgun. In order to avoid costly trials, the field- circuit method is employed to analyze the operations of different structural railguns with different parameters respectively. And the orthogonal test approach is used to guide the simulation for choosing the better parameter combinations, as well reduce the calculation cost. The research shows that the proposed method gives a better result in the energy efficiency of the system. To improve the energy conversion efficiency of electromagnetic rail launchers, the selection of more parameters must be considered in the design stage, such as the width, height and length of rail, the distance between rail pair, and pulse forming inductance. However, the relationship between these parameters and energy conversion efficiency cannot be directly described by one mathematical expression. So optimization methods must be applied to conduct design. In this paper, a rail launcher with five parameters was optimized by using orthogonal test method. According to the arrangement of orthogonal table, the better parameters’ combination can be obtained through less calculation. Under the condition of different parameters’ value, field and circuit simulation analysis were made. The results show that the energy conversion efficiency of the system is increased by 71.9 % after parameters optimization.
METAHEURISTIC OPTIMIZATION METHODS FOR PARAMETERS ESTIMATION OF DYNAMIC SYSTEMS
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V. Panteleev Andrei
2017-01-01
Full Text Available The article considers the usage of metaheuristic methods of constrained global optimization: “Big Bang - Big Crunch”, “Fireworks Algorithm”, “Grenade Explosion Method” in parameters of dynamic systems estimation, described with algebraic-differential equations. Parameters estimation is based upon the observation results from mathematical model behavior. Their values are derived after criterion minimization, which describes the total squared error of state vector coordinates from the deduced ones with precise values observation at different periods of time. Paral- lelepiped type restriction is imposed on the parameters values. Used for solving problems, metaheuristic methods of constrained global extremum don’t guarantee the result, but allow to get a solution of a rather good quality in accepta- ble amount of time. The algorithm of using metaheuristic methods is given. Alongside with the obvious methods for solving algebraic-differential equation systems, it is convenient to use implicit methods for solving ordinary differen- tial equation systems. Two ways of solving the problem of parameters evaluation are given, those parameters differ in their mathematical model. In the first example, a linear mathematical model describes the chemical action parameters change, and in the second one, a nonlinear mathematical model describes predator-prey dynamics, which characterize the changes in both kinds’ population. For each of the observed examples there are calculation results from all the three methods of optimization, there are also some recommendations for how to choose methods parameters. The obtained numerical results have demonstrated the efficiency of the proposed approach. The deduced parameters ap- proximate points slightly differ from the best known solutions, which were deduced differently. To refine the results one should apply hybrid schemes that combine classical methods of optimization of zero, first and second orders and
Identification of metabolic system parameters using global optimization methods
Directory of Open Access Journals (Sweden)
Gatzke Edward P
2006-01-01
Full Text Available Abstract Background The problem of estimating the parameters of dynamic models of complex biological systems from time series data is becoming increasingly important. Methods and results Particular consideration is given to metabolic systems that are formulated as Generalized Mass Action (GMA models. The estimation problem is posed as a global optimization task, for which novel techniques can be applied to determine the best set of parameter values given the measured responses of the biological system. The challenge is that this task is nonconvex. Nonetheless, deterministic optimization techniques can be used to find a global solution that best reconciles the model parameters and measurements. Specifically, the paper employs branch-and-bound principles to identify the best set of model parameters from observed time course data and illustrates this method with an existing model of the fermentation pathway in Saccharomyces cerevisiae. This is a relatively simple yet representative system with five dependent states and a total of 19 unknown parameters of which the values are to be determined. Conclusion The efficacy of the branch-and-reduce algorithm is illustrated by the S. cerevisiae example. The method described in this paper is likely to be widely applicable in the dynamic modeling of metabolic networks.
Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems
Patan, Maciej
2012-01-01
Sensor networks have recently come into prominence because they hold the potential to revolutionize a wide spectrum of both civilian and military applications. An ingenious characteristic of sensor networks is the distributed nature of data acquisition. Therefore they seem to be ideally prepared for the task of monitoring processes with spatio-temporal dynamics which constitute one of most general and important classes of systems in modelling of the real-world phenomena. It is clear that careful deployment and activation of sensor nodes are critical for collecting the most valuable information from the observed environment. Optimal Sensor Network Scheduling in Identification of Distributed Parameter Systems discusses the characteristic features of the sensor scheduling problem, analyzes classical and recent approaches, and proposes a wide range of original solutions, especially dedicated for networks with mobile and scanning nodes. Both researchers and practitioners will find the case studies, the proposed al...
Parameter Optimization of Multi-Element Synthetic Aperture Imaging Systems
Directory of Open Access Journals (Sweden)
Vera Behar
2007-03-01
Full Text Available In conventional ultrasound imaging systems with phased arrays, the further improvement of lateral resolution requires enlarging of the number of array elements that in turn increases both, the complexity and the cost, of imaging systems. Multi-element synthetic aperture focusing (MSAF systems are a very good alternative to conventional systems with phased arrays. The benefit of the synthetic aperture is in reduction of the system complexity, cost and acquisition time. In a MSAF system considered in the paper, a group of elements transmit and receive signals simultaneously, and the transmit beam is defocused to emulate a single element response. The echo received at each element of a receive sub-aperture is recorded in the computer memory. The process of transmission/reception is repeated for all positions of a transmit sub-aperture. All the data recordings associated with each corresponding pair "transmit-receive sub-aperture" are then focused synthetically producing a low-resolution image. The final high-resolution image is formed by summing of the all low-resolution images associated with transmit/receive sub-apertures. A problem of parameter optimization of a MSAF system is considered in this paper. The quality of imaging (lateral resolution and contrast is expressed in terms of the beam characteristics - beam width and side lobe level. The comparison between the MSAF system described in the paper and an equivalent conventional phased array system shows that the MSAF system acquires images of equivalent quality much faster using only a small part of the power per image.
Optimization of Experimental Model Parameter Identification for Energy Storage Systems
Directory of Open Access Journals (Sweden)
Rosario Morello
2013-09-01
Full Text Available The smart grid approach is envisioned to take advantage of all available modern technologies in transforming the current power system to provide benefits to all stakeholders in the fields of efficient energy utilisation and of wide integration of renewable sources. Energy storage systems could help to solve some issues that stem from renewable energy usage in terms of stabilizing the intermittent energy production, power quality and power peak mitigation. With the integration of energy storage systems into the smart grids, their accurate modeling becomes a necessity, in order to gain robust real-time control on the network, in terms of stability and energy supply forecasting. In this framework, this paper proposes a procedure to identify the values of the battery model parameters in order to best fit experimental data and integrate it, along with models of energy sources and electrical loads, in a complete framework which represents a real time smart grid management system. The proposed method is based on a hybrid optimisation technique, which makes combined use of a stochastic and a deterministic algorithm, with low computational burden and can therefore be repeated over time in order to account for parameter variations due to the battery’s age and usage.
Parameter estimation for chaotic systems with a Drift Particle Swarm Optimization method
International Nuclear Information System (INIS)
Sun Jun; Zhao Ji; Wu Xiaojun; Fang Wei; Cai Yujie; Xu Wenbo
2010-01-01
Inspired by the motion of electrons in metal conductors in an electric field, we propose a variant of Particle Swarm Optimization (PSO), called Drift Particle Swarm Optimization (DPSO) algorithm, and apply it in estimating the unknown parameters of chaotic dynamic systems. The principle and procedure of DPSO are presented, and the algorithm is used to identify Lorenz system and Chen system. The experiment results show that for the given parameter configurations, DPSO can identify the parameters of the systems accurately and effectively, and it may be a promising tool for chaotic system identification as well as other numerical optimization problems in physics.
Directory of Open Access Journals (Sweden)
Shaolong Chen
2016-01-01
Full Text Available Parameter estimation is an important problem in nonlinear system modeling and control. Through constructing an appropriate fitness function, parameter estimation of system could be converted to a multidimensional parameter optimization problem. As a novel swarm intelligence algorithm, chicken swarm optimization (CSO has attracted much attention owing to its good global convergence and robustness. In this paper, a method based on improved boundary chicken swarm optimization (IBCSO is proposed for parameter estimation of nonlinear systems, demonstrated and tested by Lorenz system and a coupling motor system. Furthermore, we have analyzed the influence of time series on the estimation accuracy. Computer simulation results show it is feasible and with desirable performance for parameter estimation of nonlinear systems.
Use of multilevel modeling for determining optimal parameters of heat supply systems
Stennikov, V. A.; Barakhtenko, E. A.; Sokolov, D. V.
2017-07-01
The problem of finding optimal parameters of a heat-supply system (HSS) is in ensuring the required throughput capacity of a heat network by determining pipeline diameters and characteristics and location of pumping stations. Effective methods for solving this problem, i.e., the method of stepwise optimization based on the concept of dynamic programming and the method of multicircuit optimization, were proposed in the context of the hydraulic circuit theory developed at Melentiev Energy Systems Institute (Siberian Branch, Russian Academy of Sciences). These methods enable us to determine optimal parameters of various types of piping systems due to flexible adaptability of the calculation procedure to intricate nonlinear mathematical models describing features of used equipment items and methods of their construction and operation. The new and most significant results achieved in developing methodological support and software for finding optimal parameters of complex heat supply systems are presented: a new procedure for solving the problem based on multilevel decomposition of a heat network model that makes it possible to proceed from the initial problem to a set of interrelated, less cumbersome subproblems with reduced dimensionality; a new algorithm implementing the method of multicircuit optimization and focused on the calculation of a hierarchical model of a heat supply system; the SOSNA software system for determining optimum parameters of intricate heat-supply systems and implementing the developed methodological foundation. The proposed procedure and algorithm enable us to solve engineering problems of finding the optimal parameters of multicircuit heat supply systems having large (real) dimensionality, and are applied in solving urgent problems related to the optimal development and reconstruction of these systems. The developed methodological foundation and software can be used for designing heat supply systems in the Central and the Admiralty regions in
Optimization of parameters for the inline-injection system at Brookhaven Accelerator Test Facility
International Nuclear Information System (INIS)
Parsa, Z.; Ko, S.K.
1995-01-01
We present some of our parameter optimization results utilizing code PARMLEA, for the ATF Inline-Injection System. The new solenoid-Gun-Solenoid -- Drift-Linac Scheme would improve the beam quality needed for FEL and other experiments at ATF as compared to the beam quality of the original design injection system. To optimize the gain in the beam quality we have considered various parameters including the accelerating field gradient on the photoathode, the Solenoid field strengths, separation between the gun and entrance to the linac as well as the (type size) initial charge distributions. The effect of the changes in the parameters on the beam emittance is also given
Infrared Drying Parameter Optimization
Jackson, Matthew R.
In recent years, much research has been done to explore direct printing methods, such as screen and inkjet printing, as alternatives to the traditional lithographic process. The primary motivation is reduction of the material costs associated with producing common electronic devices. Much of this research has focused on developing inkjet or screen paste formulations that can be printed on a variety of substrates, and which have similar conductivity performance to the materials currently used in the manufacturing of circuit boards and other electronic devices. Very little research has been done to develop a process that would use direct printing methods to manufacture electronic devices in high volumes. This study focuses on developing and optimizing a drying process for conductive copper ink in a high volume manufacturing setting. Using an infrared (IR) dryer, it was determined that conductive copper prints could be dried in seconds or minutes as opposed to tens of minutes or hours that it would take with other drying devices, such as a vacuum oven. In addition, this study also identifies significant parameters that can affect the conductivity of IR dried prints. Using designed experiments and statistical analysis; the dryer parameters were optimized to produce the best conductivity performance for a specific ink formulation and substrate combination. It was determined that for an ethylene glycol, butanol, 1-methoxy 2- propanol ink formulation printed on Kapton, the optimal drying parameters consisted of a dryer height of 4 inches, a temperature setting between 190 - 200°C, and a dry time of 50-65 seconds depending on the printed film thickness as determined by the number of print passes. It is important to note that these parameters are optimized specifically for the ink formulation and substrate used in this study. There is still much research that needs to be done into optimizing the IR dryer for different ink substrate combinations, as well as developing a
Directory of Open Access Journals (Sweden)
Yu Huang
Full Text Available Parameter estimation for fractional-order chaotic systems is an important issue in fractional-order chaotic control and synchronization and could be essentially formulated as a multidimensional optimization problem. A novel algorithm called quantum parallel particle swarm optimization (QPPSO is proposed to solve the parameter estimation for fractional-order chaotic systems. The parallel characteristic of quantum computing is used in QPPSO. This characteristic increases the calculation of each generation exponentially. The behavior of particles in quantum space is restrained by the quantum evolution equation, which consists of the current rotation angle, individual optimal quantum rotation angle, and global optimal quantum rotation angle. Numerical simulation based on several typical fractional-order systems and comparisons with some typical existing algorithms show the effectiveness and efficiency of the proposed algorithm.
International Nuclear Information System (INIS)
Ahmadi, Mohamadreza; Mojallali, Hamed
2012-01-01
Highlights: ► A new meta-heuristic optimization algorithm. ► Integration of invasive weed optimization and chaotic search methods. ► A novel parameter identification scheme for chaotic systems. - Abstract: This paper introduces a novel hybrid optimization algorithm by taking advantage of the stochastic properties of chaotic search and the invasive weed optimization (IWO) method. In order to deal with the weaknesses associated with the conventional method, the proposed chaotic invasive weed optimization (CIWO) algorithm is presented which incorporates the capabilities of chaotic search methods. The functionality of the proposed optimization algorithm is investigated through several benchmark multi-dimensional functions. Furthermore, an identification technique for chaotic systems based on the CIWO algorithm is outlined and validated by several examples. The results established upon the proposed scheme are also supplemented which demonstrate superior performance with respect to other conventional methods.
Development of a parameter optimization technique for the design of automatic control systems
Whitaker, P. H.
1977-01-01
Parameter optimization techniques for the design of linear automatic control systems that are applicable to both continuous and digital systems are described. The model performance index is used as the optimization criterion because of the physical insight that can be attached to it. The design emphasis is to start with the simplest system configuration that experience indicates would be practical. Design parameters are specified, and a digital computer program is used to select that set of parameter values which minimizes the performance index. The resulting design is examined, and complexity, through the use of more complex information processing or more feedback paths, is added only if performance fails to meet operational specifications. System performance specifications are assumed to be such that the desired step function time response of the system can be inferred.
Factorization and the synthesis of optimal feedback gains for distributed parameter systems
Milman, Mark H.; Scheid, Robert E.
1990-01-01
An approach based on Volterra factorization leads to a new methodology for the analysis and synthesis of the optimal feedback gain in the finite-time linear quadratic control problem for distributed parameter systems. The approach circumvents the need for solving and analyzing Riccati equations and provides a more transparent connection between the system dynamics and the optimal gain. The general results are further extended and specialized for the case where the underlying state is characterized by autonomous differential-delay dynamics. Numerical examples are given to illustrate the second-order convergence rate that is derived for an approximation scheme for the optimal feedback gain in the differential-delay problem.
Optimal selection of LQR parameter using AIS for LFC in a multi-area power system
Directory of Open Access Journals (Sweden)
Muhammad Abdillah
2016-12-01
Full Text Available This paper proposes a method to optimize the parameter of the linear quadratic regulator (LQR using artificial immune system (AIS via clonal selection. The parameters of LQR utilized in this paper are the weighting matrices Q and R. The optimal LQR control for load frequency control (LFC is installed on each area as a decentralized control scheme. The aim of this control design is to improve the dynamic performance of LFC automatically when unexpected load change occurred on power system network. The change of load demands 0.01 p.u used as a disturbance is applied to LFC in Area 1. The proposed method guarantees the stability of the overall closed-loop system. The simulation result shows that the proposed method can reduce the overshoot of the system and compress the time response to steady-state which is better compared to trial error method (TEM and without optimal LQR control.
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
The design of a measured program devoted to parameter identification of structural dynamic systems is considered, the design problem is formulated as an optimization problem due to minimize the total expected cost of the measurement program. All the calculations are based on a priori knowledge...... and engineering judgement. One of the contribution of the approach is that the optimal nmber of sensors can be estimated. This is sown in an numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement program for estimating the modal damping parameters...
Parameter optimization method for longitudinal vibration absorber of ship shaft system
Directory of Open Access Journals (Sweden)
LIU Jinlin
2017-05-01
Full Text Available The longitudinal vibration of the ship shaft system is the one of the most important factors of hull stern vibration, and it can be effectively minimized by installing a longitudinal vibration absorber. In this way, the vibration and noise of ships can be brought under control. However, the parameters of longitudinal vibration absorbers have a great influence on the vibration characteristics of the shaft system. As such, a certain shafting testing platform was studied as the object on which a finite model was built, and the relationship between longitudinal stiffness and longitudinal vibration in the shaft system was analyzed in a straight alignment state. Furthermore, a longitudinal damping model of the shaft system was built in which the parameters of the vibration absorber were non-dimensionalized, the weight of the vibration absorber was set as a constant, and an optimizing algorithm was used to calculate the optimized stiffness and damping coefficient of the vibration absorber. Finally, the longitudinal vibration frequency response of the shafting testing platform before and after optimizing the parameters of the longitudinal vibration absorber were compared, and the results indicated that the longitudinal vibration of the shafting testing platform was decreased effectively, which suggests that it could provide a theoretical foundation for the parameter optimization of longitudinal vibration absorbers.
Optimization of Temperature Schedule Parameters on Heat Supply in Power-and-Heat Supply Systems
Directory of Open Access Journals (Sweden)
V. A. Sednin
2009-01-01
Full Text Available The paper considers problems concerning optimization of a temperature schedule in the district heating systems with steam-turbine thermal power stations having average initial steam parameters. It has been shown in the paper that upkeeping of an optimum network water temperature permits to increase an energy efficiency of heat supply due to additional systematic saving of fuel.
Directory of Open Access Journals (Sweden)
Guozhen Hu
2017-12-01
Full Text Available A loosely coupled inductive power transfer (IPT system for industrial track applications has been researched in this paper. The IPT converter using primary Inductor-Capacitor-Inductor (LCL network and secondary parallel-compensations is analyzed combined coil design for optimal operating efficiency. Accurate mathematical analytical model and expressions of self-inductance and mutual inductance are proposed to achieve coil parameters. Furthermore, the optimization process is performed combined with the proposed resonant compensations and coil parameters. The results are evaluated and discussed using finite element analysis (FEA. Finally, an experimental prototype is constructed to verify the proposed approach and the experimental results show that the optimization can be better applied to industrial track distributed IPT system.
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Jing Li
2017-01-01
Full Text Available The goal of this study is to improve thermal comfort and indoor air quality with the adaptive network-based fuzzy inference system (ANFIS model and improved particle swarm optimization (PSO algorithm. A method to optimize air conditioning parameters and installation distance is proposed. The methodology is demonstrated through a prototype case, which corresponds to a typical laboratory in colleges and universities. A laboratory model is established, and simulated flow field information is obtained with the CFD software. Subsequently, the ANFIS model is employed instead of the CFD model to predict indoor flow parameters, and the CFD database is utilized to train ANN input-output “metamodels” for the subsequent optimization. With the improved PSO algorithm and the stratified sequence method, the objective functions are optimized. The functions comprise PMV, PPD, and mean age of air. The optimal installation distance is determined with the hemisphere model. Results show that most of the staff obtain a satisfactory degree of thermal comfort and that the proposed method can significantly reduce the cost of building an experimental device. The proposed methodology can be used to determine appropriate air supply parameters and air conditioner installation position for a pleasant and healthy indoor environment.
Directory of Open Access Journals (Sweden)
Li Junyi
2015-01-01
Full Text Available A fractional order PID (FOPID controller, which is suitable for control system designing for being insensitive to the variation in system parameter, is proposed for hydroturbine governing system in the paper. The simultaneous optimization for several parameters of controller, that is, Ki, Kd, Kp, λ, and μ, is done by a recently developed metaheuristic nature-inspired algorithm, namely, the firefly algorithm (FA, for the first time, where the selecting, moving, attractiveness behavior between fireflies and updating of brightness, and decision range are studied in detail to simulate the optimization process. Investigation clearly reveals the advantages of the FOPID controller over the integer controllers in terms of reduced oscillations and settling time. The present work also explores the superiority of FA based optimization technique in finding optimal parameters of the controller. Further, convergence characteristics of the FA are compared with optimum integer order PID (IOPID controller to justify its efficiency. What is more, analysis confirms the robustness of FOPID controller under isolated load operation conditions.
International Nuclear Information System (INIS)
Frolov, A.M.
1986-01-01
The problem of exact variational calculations of few-particle systems in the exponential basis of the relative coordinates using nonlinear parameters is studied. The techniques of stepwise optimization and global chaos of nonlinear parameters are used to calculate the S and P states of homonuclear muonic molecules with an error of no more than +0.001 eV. The global-chaos technique also has proved to be successful in the case of the nuclear systems 3 H and 3 He
Optimal allocation of sensors for state estimation of distributed parameter systems
International Nuclear Information System (INIS)
Sunahara, Yoshifumi; Ohsumi, Akira; Mogami, Yoshio.
1978-01-01
The purpose of this paper is to present a method for finding the optimal allocation of sensors for state estimation of linear distributed parameter systems. This method is based on the criterion that the error covariance associated with the state estimate becomes minimal with respect to the allocation of the sensors. A theorem is established, giving the sufficient condition for optimizing the allocation of sensors to make minimal the error covariance approximated by a modal expansion. The remainder of this paper is devoted to illustrate important phases of the general theory of the optimal measurement allocation problem. To do this, several examples are demonstrated, including extensive discussions on the mutual relation between the optimal allocation and the dynamics of sensors. (author)
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
The design of measurement programs devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost that is the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contribution of the approach is that the optimal number of sensors can be estimated. This is shown in a numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement program...
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
1993-01-01
The design of a measurement program devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost that is the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contribution of the approach is that the optimal number of sensory can be estimated. This is shown in an numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement...
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
1991-01-01
The design of a measurement program devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost, i.e. the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contributions of the approach is that the optimal number of sensors can be estimated. This is shown in a numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement...
Optimizing parameters of a technical system using quality function deployment method
Baczkowicz, M.; Gwiazda, A.
2015-11-01
The article shows the practical use of Quality Function Deployment (QFD) on the example of a mechanized mining support. Firstly it gives a short description of this method and shows how the designing process, from the constructor point of view, looks like. The proposed method allows optimizing construction parameters and comparing them as well as adapting to customer requirements. QFD helps to determine the full set of crucial construction parameters and then their importance and difficulty of their execution. Secondly it shows chosen technical system and presents its construction with figures of the existing and future optimized model. The construction parameters were selected from the designer point of view. The method helps to specify a complete set of construction parameters, from the point of view, of the designed technical system and customer requirements. The QFD matrix can be adjusted depending on designing needs and not every part of it has to be considered. Designers can choose which parts are the most important. Due to this QFD can be a very flexible tool. The most important is to define relationships occurring between parameters and that part cannot be eliminated from the analysis.
Selection of optimal multispectral imaging system parameters for small joint arthritis detection
Dolenec, Rok; Laistler, Elmar; Stergar, Jost; Milanic, Matija
2018-02-01
Early detection and treatment of arthritis is essential for a successful outcome of the treatment, but it has proven to be very challenging with existing diagnostic methods. Novel methods based on the optical imaging of the affected joints are becoming an attractive alternative. A non-contact multispectral imaging (MSI) system for imaging of small joints of human hands and feet is being developed. In this work, a numerical simulation of the MSI system is presented. The purpose of the simulation is to determine the optimal design parameters. Inflamed and unaffected human joint models were constructed with a realistic geometry and tissue distributions, based on a MRI scan of a human finger with a spatial resolution of 0.2 mm. The light transport simulation is based on a weighted-photon 3D Monte Carlo method utilizing CUDA GPU acceleration. An uniform illumination of the finger within the 400-1100 nm spectral range was simulated and the photons exiting the joint were recorded using different acceptance angles. From the obtained reflectance and transmittance images the spectral and spatial features most indicative of inflammation were identified. Optimal acceptance angle and spectral bands were determined. This study demonstrates that proper selection of MSI system parameters critically affects ability of a MSI system to discriminate the unaffected and inflamed joints. The presented system design optimization approach could be applied to other pathologies.
State and parameter estimation in nonlinear systems as an optimal tracking problem
International Nuclear Information System (INIS)
Creveling, Daniel R.; Gill, Philip E.; Abarbanel, Henry D.I.
2008-01-01
In verifying and validating models of nonlinear processes it is important to incorporate information from observations in an efficient manner. Using the idea of synchronization of nonlinear dynamical systems, we present a framework for connecting a data signal with a model in a way that minimizes the required coupling yet allows the estimation of unknown parameters in the model. The need to evaluate unknown parameters in models of nonlinear physical, biophysical, and engineering systems occurs throughout the development of phenomenological or reduced models of dynamics. Our approach builds on existing work that uses synchronization as a tool for parameter estimation. We address some of the critical issues in that work and provide a practical framework for finding an accurate solution. In particular, we show the equivalence of this problem to that of tracking within an optimal control framework. This equivalence allows the application of powerful numerical methods that provide robust practical tools for model development and validation
International Nuclear Information System (INIS)
Gao Fei; Tong Hengqing; Li Zhuoqiu
2008-01-01
This paper proposes a novel quantum-behaved particle swarm optimization (NQPSO) for the estimation of chaos' unknown parameters by transforming them into nonlinear functions' optimization. By means of the techniques in the following three aspects: contracting the searching space self-adaptively; boundaries restriction strategy; substituting the particles' convex combination for their centre of mass, this paper achieves a quite effective search mechanism with fine equilibrium between exploitation and exploration. Details of applying the proposed method and other methods into Lorenz systems are given, and experiments done show that NQPSO has better adaptability, dependability and robustness. It is a successful approach in unknown parameter estimation online especially in the cases with white noises
Cho, Ming-Yuan; Hoang, Thi Thom
2017-01-01
Fast and accurate fault classification is essential to power system operations. In this paper, in order to classify electrical faults in radial distribution systems, a particle swarm optimization (PSO) based support vector machine (SVM) classifier has been proposed. The proposed PSO based SVM classifier is able to select appropriate input features and optimize SVM parameters to increase classification accuracy. Further, a time-domain reflectometry (TDR) method with a pseudorandom binary sequence (PRBS) stimulus has been used to generate a dataset for purposes of classification. The proposed technique has been tested on a typical radial distribution network to identify ten different types of faults considering 12 given input features generated by using Simulink software and MATLAB Toolbox. The success rate of the SVM classifier is over 97%, which demonstrates the effectiveness and high efficiency of the developed method.
Directory of Open Access Journals (Sweden)
Ming-Yuan Cho
2017-01-01
Full Text Available Fast and accurate fault classification is essential to power system operations. In this paper, in order to classify electrical faults in radial distribution systems, a particle swarm optimization (PSO based support vector machine (SVM classifier has been proposed. The proposed PSO based SVM classifier is able to select appropriate input features and optimize SVM parameters to increase classification accuracy. Further, a time-domain reflectometry (TDR method with a pseudorandom binary sequence (PRBS stimulus has been used to generate a dataset for purposes of classification. The proposed technique has been tested on a typical radial distribution network to identify ten different types of faults considering 12 given input features generated by using Simulink software and MATLAB Toolbox. The success rate of the SVM classifier is over 97%, which demonstrates the effectiveness and high efficiency of the developed method.
Optimization of measure parameters for an X- and gamma-ray spectrometry portable system
International Nuclear Information System (INIS)
Fernandes, Jaquiel S.; Appoloni, Carlos R.
2008-01-01
In order to optimize the use of a system for in situ gamma (γ)- and X-ray spectrometry composed of a 3x3x1 mm 3 Cadmium Telluride (CdTe) detector with respect to the detection of low-activity radioactive sources, a two level factorial planning was accomplished, involving three factors that could modify the system response. This planning was made with a 137 Cs punctual source, analyzing the X-ray energy line of 32 keV from 137m Ba. It was concluded that, for the system optimization, the best configuration for the involved parameters was to work with the detector at temperature of -22 o C, shaping time of 3 μs and rise time discrimination (RTD) with value 3
Directory of Open Access Journals (Sweden)
Sheng Lu
2015-01-01
Full Text Available To solve the problem of parameter selection during the design of magnetically coupled resonant wireless power transmission system (MCR-WPT, this paper proposed an improved genetic simulated annealing algorithm. Firstly, the equivalent circuit of the system is analysis in this study and a nonlinear programming mathematical model is built. Secondly, in place of the penalty function method in the genetic algorithm, the selection strategy based on the distance between individuals is adopted to select individual. In this way, it reduces the excess empirical parameters. Meanwhile, it can improve the convergence rate and the searching ability by calculating crossover probability and mutation probability according to the variance of population’s fitness. At last, the simulated annealing operator is added to increase local search ability of the method. The simulation shows that the improved method can break the limit of the local optimum solution and get the global optimum solution faster. The optimized system can achieve the practical requirements.
International Nuclear Information System (INIS)
Harish, V.S.K.V.; Kumar, Arun
2016-01-01
Highlights: • A BES model based on 1st principles is developed and solved numerically. • Parameters of lumped capacitance model are fitted using the proposed optimization routine. • Validations are showed for different types of building construction elements. • Step response excitations for outdoor air temperature and relative humidity are analyzed. - Abstract: Different control techniques together with intelligent building technology (Building Automation Systems) are used to improve energy efficiency of buildings. In almost all control projects, it is crucial to have building energy models with high computational efficiency in order to design and tune the controllers and simulate their performance. In this paper, a set of partial differential equations are formulated accounting for energy flow within the building space. These equations are then solved as conventional finite difference equations using Crank–Nicholson scheme. Such a model of a higher order is regarded as a benchmark model. An optimization algorithm has been developed, depicted through a flowchart, which minimizes the sum squared error between the step responses of the numerical and the optimal model. Optimal model of the construction element is nothing but a RC-network model with the values of Rs and Cs estimated using the non-linear time invariant constrained optimization routine. The model is validated with comparing the step responses with other two RC-network models whose parameter values are selected based on a certain criteria. Validations are showed for different types of building construction elements viz., low, medium and heavy thermal capacity elements. Simulation results show that the optimal model closely follow the step responses of the numerical model as compared to the responses of other two models.
Helicopter TEM parameters analysis and system optimization based on time constant
Xiao, Pan; Wu, Xin; Shi, Zongyang; Li, Jutao; Liu, Lihua; Fang, Guangyou
2018-03-01
Helicopter transient electromagnetic (TEM) method is a kind of common geophysical prospecting method, widely used in mineral detection, underground water exploration and environment investigation. In order to develop an efficient helicopter TEM system, it is necessary to analyze and optimize the system parameters. In this paper, a simple and quantitative method is proposed to analyze the system parameters, such as waveform, power, base frequency, measured field and sampling time. A wire loop model is used to define a comprehensive 'time constant domain' that shows a range of time constant, analogous to a range of conductance, after which the characteristics of the system parameters in this domain is obtained. It is found that the distortion caused by the transmitting base frequency is less than 5% when the ratio of the transmitting period to the target time constant is greater than 6. When the sampling time window is less than the target time constant, the distortion caused by the sampling time window is less than 5%. According to this method, a helicopter TEM system, called CASHTEM, is designed, and flight test has been carried out in the known mining area. The test results show that the system has good detection performance, verifying the effectiveness of the method.
International Nuclear Information System (INIS)
Bisio, G.
1992-01-01
The aim of this paper is to study the thermodynamic optimization by the variation of the heat transfer rate in a finite number of points through insulation for the general case of one-dimensional heat transfer (flat plate, hollow cylinder and hollow sphere) in systems, consisting of different materials in series, whose thermal conductivity is a function of temperature and of the coordinate in the heat flux direction. Besides, some parameters or their first derivative are assumed stepwise continuous. For this purpose, the results of some researches by the author pertinent to the properties of entropy production rate in the one-dimensional heat transfer are utilized
Directory of Open Access Journals (Sweden)
Felix Ströer
2018-02-01
Full Text Available Stylus instruments are widely used in production metrology due to their robustness. Interchangeable cantilevers allow a wide range of measuring tasks to be covered with one measuring device. When approaching the sample, the positioning of the stylus instrument tip relative to the measurement object has to be accomplished in a controlled way in order to prevent damages to the specimen and the stylus cantilever. This is achieved by a closed-loop control. We present a method for the objective description of the stylus cantilever dynamics with system-theoretical techniques and show a simple iterative approach to optimize closed-loop control parameters with boundary conditions.
Beinarts, I; Ļevčenkovs, A; Kuņicina, N
2007-01-01
In article interest is concentrated on the climate parameters optimization in passengers’ salon of public electric transportation vehicles. The article presents mathematical problem for using intelligent agents in mechatronics problems for climate parameters optimal control. Idea is to use fuzzy logic and intelligent algorithms to create coordination mechanism for climate parameters control to save electrical energy, and it increases the level of comfort for passengers. A special interest for...
Sue-Ann, Goh; Ponnambalam, S. G.
This paper focuses on the operational issues of a Two-echelon Single-Vendor-Multiple-Buyers Supply chain (TSVMBSC) under vendor managed inventory (VMI) mode of operation. To determine the optimal sales quantity for each buyer in TSVMBC, a mathematical model is formulated. Based on the optimal sales quantity can be obtained and the optimal sales price that will determine the optimal channel profit and contract price between the vendor and buyer. All this parameters depends upon the understanding of the revenue sharing between the vendor and buyers. A Particle Swarm Optimization (PSO) is proposed for this problem. Solutions obtained from PSO is compared with the best known results reported in literature.
Directory of Open Access Journals (Sweden)
NAMMALVAR, P.
2018-02-01
Full Text Available This paper projects Parameter Improved Particle Swarm Optimization (PIPSO based direct current vector control technology for the integration of photovoltaic array in an AC micro-grid to enhance the system performance and stability. A photovoltaic system incorporated with AC micro-grid is taken as the pursuit of research study. The test system features two power converters namely, PV side converter which consists of DC-DC boost converter with Perturbation and Observe (P&O MPPT control to reap most extreme power from the PV array, and grid side converter which consists of Grid Side-Voltage Source Converter (GS-VSC with proposed direct current vector control strategy. The gain of the proposed controller is chosen from a set of three values obtained using apriori test and tuned through the PIPSO algorithm so that the Integral of Time multiplied Absolute Error (ITAE between the actual and the desired DC link capacitor voltage reaches a minimum and allows the system to extract maximum power from PV system, whereas the existing d-q control strategy is found to perform slowly to control the DC link voltage under varying solar insolation and load fluctuations. From simulation results, it is evident that the proposed optimal control technique provides robust control and improved efficiency.
International Nuclear Information System (INIS)
Berrazouane, S.; Mohammedi, K.
2014-01-01
Highlights: • Optimized fuzzy logic controller (FLC) for operating a standalone hybrid power system based on cuckoo search algorithm. • Comparison between optimized fuzzy logic controller based on cuckoo search and swarm intelligent. • Loss of power supply probability and levelized energy cost are introduced. - Abstract: This paper presents the development of an optimized fuzzy logic controller (FLC) for operating a standalone hybrid power system based on cuckoo search algorithm. The FLC inputs are batteries state of charge (SOC) and net power flow, FLC outputs are the power rate of batteries, photovoltaic and diesel generator. Data for weekly solar irradiation, ambient temperature and load profile are used to tune the proposed controller by using cuckoo search algorithm. The optimized FLC is able to minimize loss of power supply probability (LPSP), excess energy (EE) and levelized energy cost (LEC). Moreover, the results of CS optimization are better than of particle swarm optimization PSO for fuzzy system controller
Controller Parameter Optimization for Nonlinear Systems Using Enhanced Bacteria Foraging Algorithm
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V. Rajinikanth
2012-01-01
Full Text Available An enhanced bacteria foraging optimization (EBFO algorithm-based Proportional + integral + derivative (PID controller tuning is proposed for a class of nonlinear process models. The EBFO algorithm is a modified form of standard BFO algorithm. A multiobjective performance index is considered to guide the EBFO algorithm for discovering the best possible value of controller parameters. The efficiency of the proposed scheme has been validated through a comparative study with classical BFO, adaptive BFO, PSO, and GA based controller tuning methods proposed in the literature. The proposed algorithm is tested in real time on a nonlinear spherical tank system. The real-time results show that, EBFO tuned PID controller gives a smooth response for setpoint tracking performance.
Cahyadi, Christine; Heng, Paul Wan Sia; Chan, Lai Wah
2011-03-01
The aim of this study was to identify and optimize the critical process parameters of the newly developed Supercell quasi-continuous coater for optimal tablet coat quality. Design of experiments, aided by multivariate analysis techniques, was used to quantify the effects of various coating process conditions and their interactions on the quality of film-coated tablets. The process parameters varied included batch size, inlet temperature, atomizing pressure, plenum pressure, spray rate and coating level. An initial screening stage was carried out using a 2(6-1(IV)) fractional factorial design. Following these preliminary experiments, optimization study was carried out using the Box-Behnken design. Main response variables measured included drug-loading efficiency, coat thickness variation, and the extent of tablet damage. Apparent optimum conditions were determined by using response surface plots. The process parameters exerted various effects on the different response variables. Hence, trade-offs between individual optima were necessary to obtain the best compromised set of conditions. The adequacy of the optimized process conditions in meeting the combined goals for all responses was indicated by the composite desirability value. By using response surface methodology and optimization, coating conditions which produced coated tablets of high drug-loading efficiency, low incidences of tablet damage and low coat thickness variation were defined. Optimal conditions were found to vary over a large spectrum when different responses were considered. Changes in processing parameters across the design space did not result in drastic changes to coat quality, thereby demonstrating robustness in the Supercell coating process. © 2010 American Association of Pharmaceutical Scientists
Multivariate optimization of ILC parameters
International Nuclear Information System (INIS)
Bazarov, I.V.; Padamsee, H.S.
2005-01-01
We present results of multiobjective optimization of the International Linear Collider (ILC) which seeks to maximize luminosity at each given total cost of the linac (capital and operating costs of cryomodules, refrigeration and RF). Evolutionary algorithms allow quick exploration of optimal sets of parameters in a complicated system such as ILC in the presence of realistic constraints as well as investigation of various what-if scenarios in potential performance. Among the parameters we varied there were accelerating gradient and Q of the cavities (in a coupled manner following a realistic Q vs. E curve), the number of particles per bunch, the bunch length, number of bunches in the train, etc. We find an optimum which decreases (relative to TESLA TDR baseline) the total linac cost by 22%, capital cost by 25% at the same luminosity of 3 x 10 38 m -2 s -1 . For this optimum the gradient is 35 MV/m, the final spot size is 3.6 nm, and the beam power is 15.9 MV/m. Changing the luminosity by 10 38 m -2 s -1 results in 10% change in the total linac cost and 4% in the capital cost. We have also explored the optimal fronts of luminosity vs. cost for several other scenarios using the same approach. (orig.)
Multi-parameter optimization of a nanomagnetic system for spintronic applications
Energy Technology Data Exchange (ETDEWEB)
Morales Meza, Mishel [Centro de Investigación en Materiales Avanzados, S.C. (CIMAV), Chihuahua/Monterrey, 120 Avenida Miguel de Cervantes, 31109 Chihuahua (Mexico); Zubieta Rico, Pablo F. [Centro de Investigación en Materiales Avanzados, S.C. (CIMAV), Chihuahua/Monterrey, 120 Avenida Miguel de Cervantes, 31109 Chihuahua (Mexico); Centro de Investigación y de Estudios Avanzados del IPN (CINVESTAV) Querétaro, Libramiento Norponiente 2000, Fracc. Real de Juriquilla, 76230 Querétaro (Mexico); Horley, Paul P., E-mail: paul.horley@cimav.edu.mx [Centro de Investigación en Materiales Avanzados, S.C. (CIMAV), Chihuahua/Monterrey, 120 Avenida Miguel de Cervantes, 31109 Chihuahua (Mexico); Sukhov, Alexander [Institut für Physik, Martin-Luther Universität Halle-Wittenberg, 06120 Halle (Saale) (Germany); Vieira, Vítor R. [Centro de Física das Interacções Fundamentais (CFIF), Instituto Superior Técnico, Universidade Técnica de Lisboa, Avenida Rovisco Pais, 1049-001 Lisbon (Portugal)
2014-11-15
Magnetic properties of nano-particles feature many interesting physical phenomena that are essentially important for the creation of a new generation of spin-electronic devices. The magnetic stability of the nano-particles can be improved by formation of ordered particle arrays, which should be optimized over several parameters. Here we report successful optimization regarding inter-particle distance and applied field frequency allowing to obtain about three-times reduction of coercivity of a particle array compared to that of a single particle, which opens new perspectives for development of new spintronic devices.
Multi-parameter optimization of a nanomagnetic system for spintronic applications
International Nuclear Information System (INIS)
Morales Meza, Mishel; Zubieta Rico, Pablo F.; Horley, Paul P.; Sukhov, Alexander; Vieira, Vítor R.
2014-01-01
Magnetic properties of nano-particles feature many interesting physical phenomena that are essentially important for the creation of a new generation of spin-electronic devices. The magnetic stability of the nano-particles can be improved by formation of ordered particle arrays, which should be optimized over several parameters. Here we report successful optimization regarding inter-particle distance and applied field frequency allowing to obtain about three-times reduction of coercivity of a particle array compared to that of a single particle, which opens new perspectives for development of new spintronic devices
Slot Parameter Optimization for Multiband Antenna Performance Improvement Using Intelligent Systems
Directory of Open Access Journals (Sweden)
Erdem Demircioglu
2015-01-01
Full Text Available This paper discusses bandwidth enhancement for multiband microstrip patch antennas (MMPAs using symmetrical rectangular/square slots etched on the patch and the substrate properties. The slot parameters on MMPA are modeled using soft computing technique of artificial neural networks (ANN. To achieve the best ANN performance, Particle Swarm Optimization (PSO and Differential Evolution (DE are applied with ANN’s conventional training algorithm in optimization of the modeling performance. In this study, the slot parameters are assumed as slot distance to the radiating patch edge, slot width, and length. Bandwidth enhancement is applied to a formerly designed MMPA fed by a microstrip transmission line attached to the center pin of 50 ohm SMA connecter. The simulated antennas are fabricated and measured. Measurement results are utilized for training the artificial intelligence models. The ANN provides 98% model accuracy for rectangular slots and 97% for square slots; however, ANFIS offer 90% accuracy with lack of resonance frequency tracking.
Energy Technology Data Exchange (ETDEWEB)
Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2017-08-25
This work proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of the hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system.
Yin, Hui; Yu, Dejie; Yin, Shengwen; Xia, Baizhan
2018-03-01
The conventional engineering optimization problems considering uncertainties are based on the probabilistic model. However, the probabilistic model may be unavailable because of the lack of sufficient objective information to construct the precise probability distribution of uncertainties. This paper proposes a possibility-based robust design optimization (PBRDO) framework for the uncertain structural-acoustic system based on the fuzzy set model, which can be constructed by expert opinions. The objective of robust design is to optimize the expectation and variability of system performance with respect to uncertainties simultaneously. In the proposed PBRDO, the entropy of the fuzzy system response is used as the variability index; the weighted sum of the entropy and expectation of the fuzzy response is used as the objective function, and the constraints are established in the possibility context. The computations for the constraints and objective function of PBRDO are a triple-loop and a double-loop nested problem, respectively, whose computational costs are considerable. To improve the computational efficiency, the target performance approach is introduced to transform the calculation of the constraints into a double-loop nested problem. To further improve the computational efficiency, a Chebyshev fuzzy method (CFM) based on the Chebyshev polynomials is proposed to estimate the objective function, and the Chebyshev interval method (CIM) is introduced to estimate the constraints, thereby the optimization problem is transformed into a single-loop one. Numerical results on a shell structural-acoustic system verify the effectiveness and feasibility of the proposed methods.
International Nuclear Information System (INIS)
Kotarski, W.; Kowalewski, A.
1982-03-01
In this paper we consider an optimal control problem for a system described by a linear partial differential equation of the parabolic type with Dirichlet's boundary condition. We impose some constraints on the control. The performance functional has the integral form. The control time T is fixed. The initial condition is not given by a known function but belongs to a certain set (incomplete information about the initial state). The problem formulated in this paper describes the process of optimal heating, of which we do not have exact information about the initial temperature on the heated object. We present an example in which the set of admissible controls and one of initial conditions are given by means of the norm constraints too. The application of the well-known projective gradient method in the Hilbert space allows us to obtain the numerical solution for our optimization problem. (author)
Miró, Anton; Pozo, Carlos; Guillén-Gosálbez, Gonzalo; Egea, Jose A; Jiménez, Laureano
2012-05-10
The estimation of parameter values for mathematical models of biological systems is an optimization problem that is particularly challenging due to the nonlinearities involved. One major difficulty is the existence of multiple minima in which standard optimization methods may fall during the search. Deterministic global optimization methods overcome this limitation, ensuring convergence to the global optimum within a desired tolerance. Global optimization techniques are usually classified into stochastic and deterministic. The former typically lead to lower CPU times but offer no guarantee of convergence to the global minimum in a finite number of iterations. In contrast, deterministic methods provide solutions of a given quality (i.e., optimality gap), but tend to lead to large computational burdens. This work presents a deterministic outer approximation-based algorithm for the global optimization of dynamic problems arising in the parameter estimation of models of biological systems. Our approach, which offers a theoretical guarantee of convergence to global minimum, is based on reformulating the set of ordinary differential equations into an equivalent set of algebraic equations through the use of orthogonal collocation methods, giving rise to a nonconvex nonlinear programming (NLP) problem. This nonconvex NLP is decomposed into two hierarchical levels: a master mixed-integer linear programming problem (MILP) that provides a rigorous lower bound on the optimal solution, and a reduced-space slave NLP that yields an upper bound. The algorithm iterates between these two levels until a termination criterion is satisfied. The capabilities of our approach were tested in two benchmark problems, in which the performance of our algorithm was compared with that of the commercial global optimization package BARON. The proposed strategy produced near optimal solutions (i.e., within a desired tolerance) in a fraction of the CPU time required by BARON.
International Nuclear Information System (INIS)
Frolov, A.M.
1986-01-01
Exact variational calculations are treated for few-particle systems in the exponential basis of relative coordinates using nonlinear parameters. The methods of step-by-step optimization and global chaos of nonlinear parameters are applied to calculate the S and P states of ppμ, ddμ, ttμ homonuclear mesomolecules within the error ≤±0.001 eV. The global chaos method turned out to be well applicable to nuclear 3 H and 3 He systems
Energy Technology Data Exchange (ETDEWEB)
Frolov, A M
1986-09-01
Exact variational calculations are treated for few-particle systems in the exponential basis of relative coordinates using nonlinear parameters. The methods of step-by-step optimization and global chaos of nonlinear parameters are applied to calculate the S and P states of pp..mu.., dd..mu.., tt..mu.. homonuclear mesomolecules within the error less than or equal to+-0.001 eV. The global chaos method turned out to be well applicable to nuclear /sup 3/H and /sup 3/He systems.
Gowtham, K. N.; Vasudevan, M.; Maduraimuthu, V.; Jayakumar, T.
2011-04-01
Modified 9Cr-1Mo ferritic steel is used as a structural material for steam generator components of power plants. Generally, tungsten inert gas (TIG) welding is preferred for welding of these steels in which the depth of penetration achievable during autogenous welding is limited. Therefore, activated flux TIG (A-TIG) welding, a novel welding technique, has been developed in-house to increase the depth of penetration. In modified 9Cr-1Mo steel joints produced by the A-TIG welding process, weld bead width, depth of penetration, and heat-affected zone (HAZ) width play an important role in determining the mechanical properties as well as the performance of the weld joints during service. To obtain the desired weld bead geometry and HAZ width, it becomes important to set the welding process parameters. In this work, adaptative neuro fuzzy inference system is used to develop independent models correlating the welding process parameters like current, voltage, and torch speed with weld bead shape parameters like depth of penetration, bead width, and HAZ width. Then a genetic algorithm is employed to determine the optimum A-TIG welding process parameters to obtain the desired weld bead shape parameters and HAZ width.
Alghoul, M. A.; Ali, Amer; Kannanaikal, F. V.; Amin, N.; Sopian, K.
2017-11-01
PV power systems have been commercially available and widely used for decades. The performance of a reliable PV system that fulfils the expectations requires correct input data and careful design. Inaccurate input data of the techno-economic feasibility would affect the size, cost aspects, stability and performance of PV power system on the long run. The annual capacity shortage is one of the main input data that should be selected with careful attention. The aim of this study is to reveal the effect of different annual capacity shortages on the techno-economic feasibility parameters and determining the optimal value for Baghdad city location using HOMER simulation tool. Six values of annual capacity shortage percentages (0%, 1%, 2%, 3%, 4%, and 5%), and wide daily load profile range (10 kWh - 100 kWh) are implemented. The optimal annual capacity shortage is the value that always "wins" when each techno-economic feasibility parameter is at its optimal/ reasonable criteria. The results showed that the optimal annual capacity shortage that reduces significantly the cost of PV power system while keeping the PV system with reasonable technical feasibility is 3%. This capacity shortage value can be carried as a reference value in future works for Baghdad city location. Using this approach of analysis at other locations, annual capacity shortage can be always offered as a reference value for those locations.
Optimizing the Air Dissolution Parameters in an Unpacked Dissolved Air Flotation System
Directory of Open Access Journals (Sweden)
Adam Dassey
2011-12-01
Full Text Available Due to the various parameters that influence air solubility and microbubble production in dissolved air flotation (DAF, a multitude of values that cover a large range for these parameters are suggested for field systems. An unpacked saturator and an air quantification unit were designed to specify the effects of power, pressure, temperature, hydraulic retention time, and air flow on the DAF performance. It was determined that a pressure of 621 kPa, hydraulic retention time of 18.2 min, and air flow of 8.5 L/h would be the best controlled parameters for maximum efficiency in this unit. A temperature of 7 °C showed the greatest microbubble production, but temperature control would not be expected in actual application. The maximum microbubble flow from the designed system produced 30 mL of air (±1.5 per L of water under these conditions with immediate startup. The maximum theoretical dissolved air volume of 107 mL (±6 was achieved at a retention time of 2 h and a pressure of 621 kPa. To isolate and have better control over the various DAF operational parameters, the DAF unit was operated without the unsaturated flow stream. This mode of operation led to the formation of large bubbles at peak bubble production rates. In a real-world application, the large bubble formation will be avoided by mixing with raw unsaturated stream and by altering the location of dissolved air output flow.
Energy Technology Data Exchange (ETDEWEB)
Wilson, Jr., Joe D. [Christopher Newport Univ., Newport News, VA (United States)
2003-01-01
The technology of Jefferson Laboratory's (JLab) Continuous Electron Beam Accelerator Facility (CEBAF) and Free Electron Laser (FEL) requires cooling from one of the world's largest 2K helium refrigerators known as the Central Helium Liquefier (CHL). The key characteristic of CHL is the ability to maintain a constant low vapor pressure over the large liquid helium inventory using a series of five cold compressors. The cold compressor system operates with a constrained discharge pressure over a range of suction pressures and mass flows to meet the operational requirements of CEBAF and FEL. The research topic is the prediction of the most thermodynamically efficient conditions for the system over its operating range of mass flows and vapor pressures with minimum disruption to JLab operations. The research goal is to find the operating points for each cold compressor for optimizing the overall system at any given flow and vapor pressure.
International Nuclear Information System (INIS)
Banerjee, Amit; Abu-Mahfouz, Issam
2014-01-01
The use of evolutionary algorithms has been popular in recent years for solving the inverse problem of identifying system parameters given the chaotic response of a dynamical system. The inverse problem is reformulated as a minimization problem and population-based optimizers such as evolutionary algorithms have been shown to be efficient solvers of the minimization problem. However, to the best of our knowledge, there has been no published work that evaluates the efficacy of using the two most popular evolutionary techniques – particle swarm optimization and differential evolution algorithm, on a wide range of parameter estimation problems. In this paper, the two methods along with their variants (for a total of seven algorithms) are applied to fifteen different parameter estimation problems of varying degrees of complexity. Estimation results are analyzed using nonparametric statistical methods to identify if an algorithm is statistically superior to others over the class of problems analyzed. Results based on parameter estimation quality suggest that there are significant differences between the algorithms with the newer, more sophisticated algorithms performing better than their canonical versions. More importantly, significant differences were also found among variants of the particle swarm optimizer and the best performing differential evolution algorithm
Energy Technology Data Exchange (ETDEWEB)
Paul, D. [SSBB and Senior Member-ASQ, Kolkata (India); Mandal, S.N. [Kalyani Govt Engg College, Kalyani (India); Mukherjee, D.; Bhadra Chaudhuri, S.R. [Dept of E. and T. C. Engg, B.E.S.U., Shibpur (India)
2010-10-15
System efficiency and payback time are yet to attain a commercially viable level for solar photovoltaic energy projects. Despite huge development in prediction of solar radiation data, there is a gap in extraction of pertinent information from such data. Hence the available data cannot be effectively utilized for engineering application. This is acting as a barrier for the emerging technology. For making accurate engineering and financial calculations regarding any solar energy project, it is crucial to identify and optimize the most significant statistic(s) representing insolation availability by the Photovoltaic setup at the installation site. Quality Function Deployment (QFD) technique has been applied for identifying the statistic(s), which are of high significance from a project designer's point of view. A MATLAB trademark program has been used to build the annual frequency distribution of hourly insolation over any module plane at a given location. Descriptive statistical analysis of such distributions is done through MINITAB trademark. For Building Integrated Photo Voltaic (BIPV) installation, similar statistical analysis has been carried out for the composite frequency distribution, which is formed by weighted summation of insolation distributions for different module planes used in the installation. Vital most influential statistic(s) of the composite distribution have been optimized through Artificial Neural Network computation. This approach is expected to open up a new horizon in BIPV system design. (author)
Ship nuclear power plants: system approach designing and optimal parameter selection
International Nuclear Information System (INIS)
Dolgov, V.N.
1995-01-01
Dependence of basic indices of naval nuclear power installations on combination of thermotechnical parameters is considered. The necessity of new approach to designing naval nuclear power facilities, based on combined analysis of the above facilities and the ship, as a single complex system, is demonstrated. The conclusion is made that unjustified increase in the ship metal capacity, terms and costs of their production takes place in case of disregarding the role of mass and dimensions of nuclear power facilities and consequently their thermotechnical characteristics in formation of the ship displacement tonnage. 2 refs., 3 figs
Directory of Open Access Journals (Sweden)
A.О. Khorolskiy
2017-12-01
Full Text Available The article deals with solving the scientific problem of select mining equipment for selection longwall faces of mining venture. The main goal of the paper is to study technology of coal extraction of mining venture. The paper proposes a new approach to solve a problem of mining equipment selection for longwall faces of mining venture. The article describes new method for selection of mining equipment based on theory graph. Special attention is given to technological aspects; they are lenght of longwall faces, depth of coal stratum. Predictions obtained for daily production of mining equipment are compared with design outputs. Conclusions regarding the main reason of instability of longwall faces workings are made. It is found that to be able to use standard algorithms find the shortest path between vertices, you must perform matrix description of the constructed graphs that illustrate the structure of the interaction of different types of control equipment. Using classical optimization of method of discrete mathematics and algorithms for finding the shortest path between two vertices of network models obtained from the formalization of graphs with maximum results of specific types of equipment production chains, solved the problem of rational choice cleaning equipment for the new site with the cost parameters of the mining equipment and cost of mining coal. The authors developed effective and appropriate variants for the mine development for different coal deposits of mining venture.
Parameter Optimization and Operating Strategy of a TEG System for Railway Vehicles
Heghmanns, A.; Wilbrecht, S.; Beitelschmidt, M.; Geradts, K.
2016-03-01
A thermoelectric generator (TEG) system demonstrator for diesel electric locomotives with the objective of reducing the mechanical load on the thermoelectric modules (TEM) is developed and constructed to validate a one-dimensional thermo-fluid flow simulation model. The model is in good agreement with the measurements and basis for the optimization of the TEG's geometry by a genetic multi objective algorithm. The best solution has a maximum power output of approx. 2.7 kW and does not exceed the maximum back pressure of the diesel engine nor the maximum TEM hot side temperature. To maximize the reduction of the fuel consumption, an operating strategy regarding the system power output for the TEG system is developed. Finally, the potential consumption reduction in passenger and freight traffic operating modes is estimated under realistic driving conditions by means of a power train and lateral dynamics model. The fuel savings are between 0.5% and 0.7%, depending on the driving style.
Khavekar, Rajendra; Vasudevan, Hari, Dr.; Modi, Bhavik
2017-08-01
Two well-known Design of Experiments (DoE) methodologies, such as Taguchi Methods (TM) and Shainin Systems (SS) are compared and analyzed in this study through their implementation in a plastic injection molding unit. Experiments were performed at a perfume bottle cap manufacturing company (made by acrylic material) using TM and SS to find out the root cause of defects and to optimize the process parameters for minimum rejection. Experiments obtained the rejection rate to be 8.57% from 40% (appx.) during trial runs, which is quiet low, representing successful implementation of these DoE methods. The comparison showed that both methodologies gave same set of variables as critical for defect reduction, but with change in their significance order. Also, Taguchi methods require more number of experiments and consume more time compared to the Shainin System. Shainin system is less complicated and is easy to implement, whereas Taguchi methods is statistically more reliable for optimization of process parameters. Finally, experimentations implied that DoE methods are strong and reliable in implementation, as organizations attempt to improve the quality through optimization.
Katti, Dhirendra S; Robinson, Kyle W; Ko, Frank K; Laurencin, Cato T
2004-08-15
Wound healing is a complex process that often requires treatment with antibiotics. This article reports the initial development of a biodegradable polymeric nanofiber-based antibiotic delivery system. The functions of such a system would be (a) to serve as a biodegradable gauze, and (b) to serve as an antibiotic delivery system. The polymer used in this study was poly(lactide-co-glycolide) (PLAGA), and nanofibers of PLAGA were fabricated with the use of the electrospinning process. The objective of this study was to determine the effect of fabrication parameters: orifice diameter (needle gauge), polymer solution concentration, and voltage per unit length, on the morphology and diameter of electrospun nanofibers. The needle gauges studied were 16 (1.19 mm), 18 (0.84 mm), and 20 (0.58 mm), and the range of polymer solution concentration studied was from 0.10 g/mL to 0.30 g/mL. The effect of voltage was determined by varying the voltage per unit electrospinning distance, and the range studied was from 0.375 kV/cm to 1.5 kV/cm. In addition, the mass per unit area of the electrospun nanofibers as a function of time was determined and the feasibility of antibiotic (cefazolin) loading into the nanofibers was also studied. The results indicate that the diameter of nanofibers decreased with an increase in needle gauge (decrease in orifice diameter), and increased with an increase in the concentration of the polymer solution. The voltage study demonstrated that the average diameter of the nanofibers decreased with an increase in voltage. However, the effect of voltage on fiber diameter was less pronounced as compared to polymer solution concentration. The results of the areal density study indicated that the mass per unit area of the electrospun nanofibers increased linearly with time. Feasibility of drug incorporation into the nanofibers was demonstrated with the use of cefazolin, a broad-spectrum antibiotic. Overall, these studies demonstrated that PLAGA nanofibers can be
Chen, Zhuoqi; Chen, Jing M.; Zhang, Shupeng; Zheng, Xiaogu; Ju, Weiming; Mo, Gang; Lu, Xiaoliang
2017-12-01
The Global Carbon Assimilation System that assimilates ground-based atmospheric CO2 data is used to estimate several key parameters in a terrestrial ecosystem model for the purpose of improving carbon cycle simulation. The optimized parameters are the leaf maximum carboxylation rate at 25°C (Vmax25), the temperature sensitivity of ecosystem respiration (Q10), and the soil carbon pool size. The optimization is performed at the global scale at 1° resolution for the period from 2002 to 2008. The results indicate that vegetation from tropical zones has lower Vmax25 values than vegetation in temperate regions. Relatively high values of Q10 are derived over high/midlatitude regions. Both Vmax25 and Q10 exhibit pronounced seasonal variations at middle-high latitudes. The maxima in Vmax25 occur during growing seasons, while the minima appear during nongrowing seasons. Q10 values decrease with increasing temperature. The seasonal variabilities of Vmax25 and Q10 are larger at higher latitudes. Optimized Vmax25 and Q10 show little seasonal variabilities at tropical regions. The seasonal variabilities of Vmax25 are consistent with the variabilities of LAI for evergreen conifers and broadleaf evergreen forests. Variations in leaf nitrogen and leaf chlorophyll contents may partly explain the variations in Vmax25. The spatial distribution of the total soil carbon pool size after optimization is compared favorably with the gridded Global Soil Data Set for Earth System. The results also suggest that atmospheric CO2 data are a source of information that can be tapped to gain spatially and temporally meaningful information for key ecosystem parameters that are representative at the regional and global scales.
Zhang, Ridong; Tao, Jili; Lu, Renquan; Jin, Qibing
2018-02-01
Modeling of distributed parameter systems is difficult because of their nonlinearity and infinite-dimensional characteristics. Based on principal component analysis (PCA), a hybrid modeling strategy that consists of a decoupled linear autoregressive exogenous (ARX) model and a nonlinear radial basis function (RBF) neural network model are proposed. The spatial-temporal output is first divided into a few dominant spatial basis functions and finite-dimensional temporal series by PCA. Then, a decoupled ARX model is designed to model the linear dynamics of the dominant modes of the time series. The nonlinear residual part is subsequently parameterized by RBFs, where genetic algorithm is utilized to optimize their hidden layer structure and the parameters. Finally, the nonlinear spatial-temporal dynamic system is obtained after the time/space reconstruction. Simulation results of a catalytic rod and a heat conduction equation demonstrate the effectiveness of the proposed strategy compared to several other methods.
Optimization of AVR Parameters of a Multi-machine Power System ...
African Journals Online (AJOL)
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Keywords: multi-machine power system stability, AVR system, power system stabilizer, PID controller ... The proposed controller was a fuzzy-logic-based stabilizer that has the capability to ..... Computer methods in power system analysis.
International Nuclear Information System (INIS)
Ma, Guoyuan; Li, Xianguo
2007-01-01
The heat pump system with economizer coupled with scroll compressor can extend effectively its operating ranges and provide a technological method to enable the heat pump to run steadily and efficiently in severe weather conditions. The intermediate pressure, namely the working pressure of the refrigerant in the economizer, is an essential design parameter and affects crucially the performances of the heat pump system. According to the exergetic model setup for the heat pump system based on the second law of thermodynamics, the influences of the intermediate pressure on the performances are comprehensively analyzed using experimental data of the heat pump prototype. It is found that the optimal relative intermediate pressure (RIP) is between 1.1 and 1.3
Zhao, Hui; Li, Yingcai
2010-01-10
In two papers [Proc. SPIE 4471, 272-280 (2001) and Appl. Opt. 43, 2709-2721 (2004)], a logarithmic phase mask was proposed and proved to be effective in extending the depth of field; however, according to our research, this mask is not that perfect because the corresponding defocused modulation transfer function has large oscillations in the low-frequency region, even when the mask is optimized. So, in a previously published paper [Opt. Lett. 33, 1171-1173 (2008)], we proposed an improved logarithmic phase mask by making a small modification. The new mask can not only eliminate the drawbacks to a certain extent but can also be even less sensitive to focus errors according to Fisher information criteria. However, the performance comparison was carried out with the modified mask not being optimized, which was not reasonable. In this manuscript, we optimize the modified logarithmic phase mask first before analyzing its performance and more convincing results have been obtained based on the analysis of several frequently used metrics.
Directory of Open Access Journals (Sweden)
Luquan Ren
2017-03-01
Full Text Available Recently, with a broadening range of available materials and alteration of feeding processes, several extrusion-based 3D printing processes for metal materials have been developed. An emerging process is applicable for the fabrication of metal parts into electronics and composites. In this paper, some critical parameters of extrusion-based 3D printing processes were optimized by a series of experiments with a melting extrusion printer. The raw materials were copper powder and a thermoplastic organic binder system and the system included paraffin wax, low density polyethylene, and stearic acid (PW–LDPE–SA. The homogeneity and rheological behaviour of the raw materials, the strength of the green samples, and the hardness of the sintered samples were investigated. Moreover, the printing and sintering parameters were optimized with an orthogonal design method. The influence factors in regard to the ultimate tensile strength of the green samples can be described as follows: infill degree > raster angle > layer thickness. As for the sintering process, the major factor on hardness is sintering temperature, followed by holding time and heating rate. The highest hardness of the sintered samples was very close to the average hardness of commercially pure copper material. Generally, the extrusion-based printing process for producing metal materials is a promising strategy because it has some advantages over traditional approaches for cost, efficiency, and simplicity.
Ren, Luquan; Zhou, Xueli; Song, Zhengyi; Zhao, Che; Liu, Qingping; Xue, Jingze; Li, Xiujuan
2017-01-01
Recently, with a broadening range of available materials and alteration of feeding processes, several extrusion-based 3D printing processes for metal materials have been developed. An emerging process is applicable for the fabrication of metal parts into electronics and composites. In this paper, some critical parameters of extrusion-based 3D printing processes were optimized by a series of experiments with a melting extrusion printer. The raw materials were copper powder and a thermoplastic organic binder system and the system included paraffin wax, low density polyethylene, and stearic acid (PW–LDPE–SA). The homogeneity and rheological behaviour of the raw materials, the strength of the green samples, and the hardness of the sintered samples were investigated. Moreover, the printing and sintering parameters were optimized with an orthogonal design method. The influence factors in regard to the ultimate tensile strength of the green samples can be described as follows: infill degree > raster angle > layer thickness. As for the sintering process, the major factor on hardness is sintering temperature, followed by holding time and heating rate. The highest hardness of the sintered samples was very close to the average hardness of commercially pure copper material. Generally, the extrusion-based printing process for producing metal materials is a promising strategy because it has some advantages over traditional approaches for cost, efficiency, and simplicity. PMID:28772665
Ren, Luquan; Zhou, Xueli; Song, Zhengyi; Zhao, Che; Liu, Qingping; Xue, Jingze; Li, Xiujuan
2017-03-16
Recently, with a broadening range of available materials and alteration of feeding processes, several extrusion-based 3D printing processes for metal materials have been developed. An emerging process is applicable for the fabrication of metal parts into electronics and composites. In this paper, some critical parameters of extrusion-based 3D printing processes were optimized by a series of experiments with a melting extrusion printer. The raw materials were copper powder and a thermoplastic organic binder system and the system included paraffin wax, low density polyethylene, and stearic acid (PW-LDPE-SA). The homogeneity and rheological behaviour of the raw materials, the strength of the green samples, and the hardness of the sintered samples were investigated. Moreover, the printing and sintering parameters were optimized with an orthogonal design method. The influence factors in regard to the ultimate tensile strength of the green samples can be described as follows: infill degree > raster angle > layer thickness. As for the sintering process, the major factor on hardness is sintering temperature, followed by holding time and heating rate. The highest hardness of the sintered samples was very close to the average hardness of commercially pure copper material. Generally, the extrusion-based printing process for producing metal materials is a promising strategy because it has some advantages over traditional approaches for cost, efficiency, and simplicity.
Energy Technology Data Exchange (ETDEWEB)
Gruzdev, I.A.; Temirbulatov, R.A.; Ladvishchenko, B.G.; Zhenenko, G.N.
1980-09-01
The electric power system is considered as a system of matrices of transfer functions (frequency characteristics) describing non-controlled system and control devices of generator excitation and steam turbine torques. This mathematical model can be used for the study of static stability of complex electric power systems. 5 refs.
International Nuclear Information System (INIS)
Avenhaus, R.; Heil, J.
1979-01-01
In this paper analyses are made of the values of those parameters that characterize the present safeguards system that is applied to a national fuel cycle; those values have to be fixed quantitatively so that all actions of the safeguards authority are specified precisely. The analysis starts by introducing three categories of quantities: The design parameters (number of MBAs, inventory frequency, variance of MUF, verification effort and false-alarm probability) describe those quantities whose values have to be specified before the safeguards system can be implemented. The performance criteria (probability of detection, expected detection time, goal quantity) measure the effectiveness of a safeguards system; and the standards (threshold amount and critical time) characterize the magnitude of the proliferation problem. The means by which the values of the individual design parameters can be determined with the help of the performance criteria; which qualitative arguments can narrow down the arbitrariness of the choice of values of the remaining parameters; and which parameter values have to be fixed more or less arbitrarily, are investigated. As a result of these considerations, which include the optimal allocation of a given inspection effort, the problem of analysing the structure of the safeguards system is reduced to an evaluation of the interplay of only a few parameters, essentially the quality of the measurement system (variance of MUF), verification effort, false-alarm probability, goal quantity and probability of detection
Directory of Open Access Journals (Sweden)
Fukang Ma
2018-04-01
Full Text Available Based on the introduction of opposed-piston two-stroke (OP2S gasoline direct injection (GDI engines, the OP2S-GDI engine working principle and scavenging process were analyzed. GT-Power software was employed to model the working process based on the structural style and principle of OP2S-GDI engine. The tracer gas method and OP2S-GDI engine experiment were employed for model validation at full load of 6000 rpm. The OP2S-GDI engine scavenging system parameters were optimized, including intake port height stroke ratio, intake port circumference ratio, exhaust port height stroke ratio, exhaust port circumference ratio, and opposed-piston motion phase difference. At the same time, the effect of the port height stroke ratio and opposed-piston motion phase difference on effective compression ratio and expansion ratio were considered, and the indicated work was employed as the optimization objective. A three-level orthogonal experiment was applied in the calculation process to reduce the calculation work. The influence and correlation coefficient on the scavenging efficiency and delivery ratio were investigated by the orthogonal experiment analysis of intake and exhaust port height stroke ratio and circular utilization. The effect of the scavenging system parameters on delivery ratio, scavenging efficiency and indicated work were calculated to obtain the best parameters. The results show that intake port height stroke ratio is the main factor for the delivery ratio, while exhaust port height stroke ratio is the main factor to engine delivery ratio and scavenging efficiency.
Mixed integer evolution strategies for parameter optimization.
Li, Rui; Emmerich, Michael T M; Eggermont, Jeroen; Bäck, Thomas; Schütz, M; Dijkstra, J; Reiber, J H C
2013-01-01
Evolution strategies (ESs) are powerful probabilistic search and optimization algorithms gleaned from biological evolution theory. They have been successfully applied to a wide range of real world applications. The modern ESs are mainly designed for solving continuous parameter optimization problems. Their ability to adapt the parameters of the multivariate normal distribution used for mutation during the optimization run makes them well suited for this domain. In this article we describe and study mixed integer evolution strategies (MIES), which are natural extensions of ES for mixed integer optimization problems. MIES can deal with parameter vectors consisting not only of continuous variables but also with nominal discrete and integer variables. Following the design principles of the canonical evolution strategies, they use specialized mutation operators tailored for the aforementioned mixed parameter classes. For each type of variable, the choice of mutation operators is governed by a natural metric for this variable type, maximal entropy, and symmetry considerations. All distributions used for mutation can be controlled in their shape by means of scaling parameters, allowing self-adaptation to be implemented. After introducing and motivating the conceptual design of the MIES, we study the optimality of the self-adaptation of step sizes and mutation rates on a generalized (weighted) sphere model. Moreover, we prove global convergence of the MIES on a very general class of problems. The remainder of the article is devoted to performance studies on artificial landscapes (barrier functions and mixed integer NK landscapes), and a case study in the optimization of medical image analysis systems. In addition, we show that with proper constraint handling techniques, MIES can also be applied to classical mixed integer nonlinear programming problems.
International Nuclear Information System (INIS)
Joe Wilson; Venkatarao Ganni; Dana Arenius; Jonathan Creel
2004-01-01
Jefferson Lab's (JLab) Continuous Electron Beam Accelerator Facility (CEBAF) and Free Electron Laser (FEL) are supported by 2 K helium refrigerator known as the Central Helium Liquefier (CHL), which maintains a constant low vapor pressure over the accelerators' large liquid helium inventory with a five-stage centrifugal compressor train. The cold compressor train operates with constrained discharge pressure and can be varied over a range of suction pressures and mass flows to meet the operational requirements of the two accelerators. Using data from commissioning and routine operations of the cold compressor system, the presented procedure predicts an operating point for each cold compressor such that maximum efficiency is attained for the overall cold compressor system for a given combination of mass flow and vapor pressure. The procedure predicts expected efficiency of the system and relative compressors speeds for operating vapor pressures from 4 to 2.5 kPa (corresponds to overall pressure ratios of 29 to 56) and flow rates of 135 g/s to 250 g/s. The results of the predictions are verified by test for a few operating conditions of mass flows and vapor pressures
Nekrylov, Ivan; Korotaev, Valery; Blokhina, Anastasia; Kleshchenok, Maksim
2017-06-01
In the world is the widespread adoption of measuring equipment of new generation, which is characterized by small size, high automation level, a multi-channel, digital filtering, satellite synchronization, wireless communication, digital record in long-term memory with great resource, powered by long-lived sources, etc. However, modern equipment base of the Russian institutions and the level of development of technical facilities and measuring technologies lag far behind developed countries. For this reason, the vacated niches are actively developed by foreign companies. For example, more than 70% instrumentation performing works on the territory of Russia, equipped with imported equipment (products of Sweden and Germany companies); the amount of work performed with German equipment is more than 70% of the total volume of these works; more than 80% of industrial measurements are performed using HEXAGON equipment (Sweden). These trends show that the Russian sector of measuring technology gradually become import-dependent, which poses a threat to the economic security of the country and consistent with national priorities. The results of the research will allow to develop the theory of formation of control systems of the displacement with high accuracy and unattainable for the existing analogue ergonomic and weight characteristics combined with a comparable or lower cost. These advantages will allow you to be successful competition, and eventually to supplant the existing system, which had no fundamental changes in the last 20 years and, therefore, retained all the drawbacks: large size and weight, high power consumption, the dependence on magnetic fields
Directory of Open Access Journals (Sweden)
MARWAN M. SHAMEL
2006-12-01
Full Text Available This paper reports on the use of pilot scale membrane separation system coupled with another pilot scale plate heat exchanger to investigate the possibilities of sweetening seawater from Telok Kalong Beach, Terengganu, Malaysia. Reverse osmosis (RO membrane of a surface area of 0.5 m2 was used during the experimental runs. Experiments were conducted at different transmembrane pressures (TMP ranged from 40 to 55 bars, operation temperature ranged from 35 to 45oC, feed concentration (TDS ranged from 34900 to 52500 ppm and cross flow velocities ranged from 1.4 to 2.1 m/s. The result show that the flux values increased linearly with TMP as well as sodium ion rejection. Permeate flux values increased proportionally with the temperature and the later effect was more significant at high pressures. The temperature changing has also influenced the rejection of sodium ion. The minerals content especially NaCl and total dissolved solid (TDS in the drinking water produced in this research are conforming to the standards of World Health Organization (WHO.
International Nuclear Information System (INIS)
Kahi, A.K.; Thorpe, W.
1999-01-01
An individual animal model was fitted to data from crossbred herd in the lowland coastal tropics of Kenya to estimate breed cross means for a total of 25 genotypes having different proportions of Ayrshire (A), Brown swiss (B), Friesian (F) and Sahiwal (S) genes. These means were then regressed on gene proportion of breeds and on the coefficients of heterosis and recombination loss. Per lactation, the S contributed 1802 kg and 18.4 kg less milk and milk per unit of metabolic weight (MW), respectively, than the F. The performance of A and B were intermediate. The contribution of the F breed for most traits was superior to that of the other Bos taurus breeds. the heterosis effect between B and S was large for lactation milk yield (MY) (296 kg) and calving interval (CL) (-36 days). The heterosis between A and B for most traits was small, which is consistent with other studies in the literature. The estimates of recombination loss were negative in crosses A * B and B * S for MY,daily milk yield (DMY) and MY expressed per unit MW. Modelling of alternative crossbreeding strategy should be considered in relation to the ecological and socio-economic characteristics of the target production systems, which vary markedly. Therefore, the generalisation that the first cross (F 1 ) is best suited for dairying in the tropics could be misleading, and there is the need to evaluate the potential of synthetic breeds
Optimization of parameters of heat exchangers vehicles
Directory of Open Access Journals (Sweden)
Andrei MELEKHIN
2014-09-01
Full Text Available The relevance of the topic due to the decision of problems of the economy of resources in heating systems of vehicles. To solve this problem we have developed an integrated method of research, which allows to solve tasks on optimization of parameters of heat exchangers vehicles. This method decides multicriteria optimization problem with the program nonlinear optimization on the basis of software with the introduction of an array of temperatures obtained using thermography. The authors have developed a mathematical model of process of heat exchange in heat exchange surfaces of apparatuses with the solution of multicriteria optimization problem and check its adequacy to the experimental stand in the visualization of thermal fields, an optimal range of managed parameters influencing the process of heat exchange with minimal metal consumption and the maximum heat output fin heat exchanger, the regularities of heat exchange process with getting generalizing dependencies distribution of temperature on the heat-release surface of the heat exchanger vehicles, defined convergence of the results of research in the calculation on the basis of theoretical dependencies and solving mathematical model.
International Nuclear Information System (INIS)
Islam, A.; Biswas, S.K.
1995-12-01
A study of the optimization of excitation parameters in a tube excited X-ray fluorescence system (TEXRF) having Mo as the primary target has been carried out for biological matrix. Fe, Zn and Mo were used as the secondary fluorecers. For the present investigation a cellulose based synthetic standard containing K, Cr, Ni, Zn, Se and Y was excited with the TEXRF system. All experiments were carried out under the same experimental conditions except the tube potential. For each fluorescer the minimum detection limits (MDL) of excited elements were calculated for the corresponding tube voltage. The MDLs were found to be increasing with decreasing atomic number and it was also observed that the maximum sensitivity with Fe and Zn secondary fluorescers for elements analyzed occurred around 35 kV of the excitation potential. For Mo secondary fluorescer maximum sensitivity was found at higher excitation potential. In most cases MDLs were minimum at 40-45 kV of the excitation potential. 5 refs., 12 figs
Directory of Open Access Journals (Sweden)
Xiangyang Zhou
2015-08-01
Full Text Available This paper presents a method based on co-simulation of a mechatronic system to optimize the control parameters of a two-axis inertially stabilized platform system (ISP applied in an unmanned airship (UA, by which high control performance and reliability of the ISP system are achieved. First, a three-dimensional structural model of the ISP is built by using the three-dimensional parametric CAD software SOLIDWORKS®; then, to analyze the system’s kinematic and dynamic characteristics under operating conditions, dynamics modeling is conducted by using the multi-body dynamics software ADAMS™, thus the main dynamic parameters such as displacement, velocity, acceleration and reaction curve are obtained, respectively, through simulation analysis. Then, those dynamic parameters were input into the established MATLAB® SIMULINK® controller to simulate and test the performance of the control system. By these means, the ISP control parameters are optimized. To verify the methods, experiments were carried out by applying the optimized parameters to the control system of a two-axis ISP. The results show that the co-simulation by using virtual prototyping (VP is effective to obtain optimized ISP control parameters, eventually leading to high ISP control performance.
Evaluation of GCC optimization parameters
Directory of Open Access Journals (Sweden)
Rodrigo D. Escobar
2012-12-01
Full Text Available Compile-time optimization of code can result in significant performance gains. The amount of these gains varies widely depending upon the code being optimized, the hardware being compiled for, the specific performance increase attempted (e.g. speed, throughput, memory utilization, etc. and the used compiler. We used the latest version of the SPEC CPU 2006 benchmark suite to help gain an understanding of possible performance improvements using GCC (GNU Compiler Collection options focusing mainly on speed gains made possible by tuning the compiler with the standard compiler optimization levels as well as a specific compiler option for the hardware processor. We compared the best standardized tuning options obtained for a core i7 processor, to the same relative options used on a Pentium4 to determine whether the GNU project has improved its performance tuning capabilities for specific hardware over time.
International Nuclear Information System (INIS)
Qi, Ronghui; Lu, Lin; Huang, Yu
2015-01-01
Highlights: • Operation conditions significantly affect energy & economic performance of SLDCS. • Control parameters in three areas were optimized by Multi-Population Genetic Algorithm. • Solar collector area showed the greatest effect on system performance for humid areas. • Desiccant concentration showed greatest effect on system performance for dry areas. • Requirement of collector area, heating water and desiccant flow rates for humid areas is highest. - Abstract: Operation conditions significantly affect the energy and economic performance of solar-assisted liquid desiccant cooling systems. This study optimized the system control parameters for buildings in different climates, i.e., Singapore (hot and humid), Beijing (moderate) and Boulder (hot and dry), with a multi-parameter optimization based on the Multi-Population Genetic Algorithm to obtain optimal system performance in terms of relatively maximum electricity saving rate with a minimum cost payback period. The results indicated that the selection of operation parameters is significantly influenced by climatic conditions. The solar collector installation area exhibited the greatest effect on both energy and economic performance in humid areas, and the heating water flow rate was also important. For dry areas, a change in desiccant concentration had the largest effect on system performance. Although the effect of the desiccant flow rate was significant in humid cities, it appeared to have little influence over buildings in dry areas. Furthermore, the requirements of the solar collector installation area in humid areas were much higher. The optimized area was up to 70 m"2 in Singapore compared with 27.5 m"2 in Boulder. Similar results were found for the flow rates of heating water and the desiccant solution. Applying the optimization, humid cities could achieve an electricity saving of more than 40% with a six-year payback period. The optimal performance for hot and dry areas of a 38% electricity
Hybrid Disease Diagnosis Using Multiobjective Optimization with Evolutionary Parameter Optimization
Directory of Open Access Journals (Sweden)
MadhuSudana Rao Nalluri
2017-01-01
Full Text Available With the widespread adoption of e-Healthcare and telemedicine applications, accurate, intelligent disease diagnosis systems have been profoundly coveted. In recent years, numerous individual machine learning-based classifiers have been proposed and tested, and the fact that a single classifier cannot effectively classify and diagnose all diseases has been almost accorded with. This has seen a number of recent research attempts to arrive at a consensus using ensemble classification techniques. In this paper, a hybrid system is proposed to diagnose ailments using optimizing individual classifier parameters for two classifier techniques, namely, support vector machine (SVM and multilayer perceptron (MLP technique. We employ three recent evolutionary algorithms to optimize the parameters of the classifiers above, leading to six alternative hybrid disease diagnosis systems, also referred to as hybrid intelligent systems (HISs. Multiple objectives, namely, prediction accuracy, sensitivity, and specificity, have been considered to assess the efficacy of the proposed hybrid systems with existing ones. The proposed model is evaluated on 11 benchmark datasets, and the obtained results demonstrate that our proposed hybrid diagnosis systems perform better in terms of disease prediction accuracy, sensitivity, and specificity. Pertinent statistical tests were carried out to substantiate the efficacy of the obtained results.
Parameters control in GAs for dynamic optimization
Directory of Open Access Journals (Sweden)
Khalid Jebari
2013-02-01
Full Text Available The Control of Genetic Algorithms parameters allows to optimize the search process and improves the performance of the algorithm. Moreover it releases the user to dive into a game process of trial and failure to find the optimal parameters.
Eloot, Sunny; Peperstraete, Harlinde; De Somer, Filip; Hoste, Eric
2017-01-13
Lung protective ventilation is recommended in patients with acute respiratory distress syndrome (ARDS) needing mechanical ventilation. This can however be associated with hypercapnia and respiratory acidosis, such that extracorporeal CO2 removal (ECCO2R) can be applied. The aim of this study was to derive optimal operating parameters for the ECCO2R Abylcap® system (Bellco, Italy). We included 4 ARDS patients with a partial arterial oxygen tension over the fraction of inspired oxygen (PaO2/FiO2) lower than 150 mmHg, receiving lung-protective ventilation and treated with the Abylcap® via a double lumen 13.5-Fr dialysis catheter in the femoral vein. Every 24 hours during 5 consecutive days, blood was sampled at the Abylcap® inlet and outlet for different blood flows (QB:200-300-400 mL/min) with 100% O2 gas flow (QG) of 7 L/min, and for different QG (QG: 0.5-1-1.5-3-6-8 L/min) with QB400 mL/min. CO2 and O2 transfer remained constant over 5 days for a fixed QB. We found that, for a fixed QG of 7 L/min, CO2 transfer linearly and significantly increased with QB (i.e. from 58 ± 8 to 98 ± 16 mL/min for QB 200 to 400 mL/min). For a fixed QB of 400 mL/min, CO2 transfer non-linearly increased with QG (i.e. from 39 ± 9 to 98 ± 16 mL/min for QG 0.5 to 8 L/min) reaching a plateau at QG of 6 L/min. Hence, when using the Abylcap® ECCO2R in the treatment of ARDS patients the O2 flow should be at least 6 L/min while QB should be set at its maximum.
International Nuclear Information System (INIS)
Ahamed, J.U.; Madlool, N.A.; Saidur, R.; Shahinuddin, M.I.; Kamyar, A.; Masjuki, H.H.
2012-01-01
Grate coolers are widely used in cement industries to recover heat from hot clinker, coming out from the rotary kiln. This study focuses on improving the energy, exergy and recovery efficiencies of a grate cooling system through the optimization of its operational parameters such as masses of cooling air and clinker, cooling air temperature, and grate speed. It has been found that the energy and recovery energy efficiencies of a cooling system can be increased by 1.1% and 1.9%, respectively, with every 5% mass increases of cooling air. Similarly, it has been estimated that energy and recovery energy efficiencies can be increased by 2.0% and 0.4% with every 5% increase of cooling temperature. The exergy and its recovery efficiencies found to be increased by 3.6% and 2.2%, respectively, for the same condition. Energy efficiency and energy recovery efficiencies are increased by 3.5% and 1.4% with every 9.1% increase of grate speed. Using heat recovery from the exhaust air, energy and exergy recovery efficiencies of the cooling system found to be increased by 21.5% and 9.4%, respectively. It has been found that about 38.10% and 30.86% energy cost can be saved by changing mass flow rate of clinker and mass flow rate of cooling air, respectively. -- Highlights: ► The energy and exergy efficiencies of the base case clinker cooler are 81.2% and 53.7%, respectively. ► To increase 5% mass flow of cooling air, the energy and exergy efficiency increase 1.1% and 0.9%, respectively. ► Increase of grate speed and cooling air temperature cause to increase of all efficiencies. ► Heat recovery from the exhaust air experiences 21.5% and 9.4% in energy and exergy recovery efficiency, respectively. ► Reduction of clinker mass flow reduces the emission of NO x , CO, PM and CO 2 .
Guía-Tello, J. C.; Pech-Canul, M. A.; Trujillo-Vázquez, E.; Pech-Canul, M. I.
2017-08-01
Controlled atmosphere brazing has a widespread industrial use in the production of aluminum automotive heat exchangers. Good-quality joints between the components depend on the initial condition of materials as well as on the brazing process parameters. In this work, the Taguchi method was used to optimize the brazing parameters with respect to corrosion performance for tube-fin mini-assemblies of an automotive condenser. The experimental design consisted of five factors (micro-channel tube type, flux type, peak temperature, heating rate and dwell time), with two levels each. The corrosion behavior in acidified seawater solution pH 2.8 was evaluated through potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) measurements. Scanning electron microscope (SEM) and energy-dispersive x-ray spectroscopy (EDS) were used to analyze the microstructural features in the joint zone. The results showed that the parameters that most significantly affect the corrosion rate are the type of flux and the peak temperature. The optimal conditions were: micro-channel tube with 4.2 g/m2 of zinc coating, standard flux, 610 °C peak temperature, 5 °C/min heating rate and 4 min dwell time. The corrosion current density value of the confirmation experiment is in excellent agreement with the predicted value. The electrochemical characterization for selected samples gave indication that the brazing conditions had a more significant effect on the kinetics of the hydrogen evolution reaction than on the kinetics of the metal dissolution reaction.
Directory of Open Access Journals (Sweden)
Li Wang
2017-02-01
Full Text Available The ability to obtain appropriate parameters for an advanced pressurized water reactor (PWR unit model is of great significance for power system analysis. The attributes of that ability include the following: nonlinear relationships, long transition time, intercoupled parameters and difficult obtainment from practical test, posed complexity and difficult parameter identification. In this paper, a model and a parameter identification method for the PWR primary loop system were investigated. A parameter identification process was proposed, using a particle swarm optimization (PSO algorithm that is based on random perturbation (RP-PSO. The identification process included model variable initialization based on the differential equations of each sub-module and program setting method, parameter obtainment through sub-module identification in the Matlab/Simulink Software (Math Works Inc., Natick, MA, USA as well as adaptation analysis for an integrated model. A lot of parameter identification work was carried out, the results of which verified the effectiveness of the method. It was found that the change of some parameters, like the fuel temperature and coolant temperature feedback coefficients, changed the model gain, of which the trajectory sensitivities were not zero. Thus, obtaining their appropriate values had significant effects on the simulation results. The trajectory sensitivities of some parameters in the core neutron dynamic module were interrelated, causing the parameters to be difficult to identify. The model parameter sensitivity could be different, which would be influenced by the model input conditions, reflecting the parameter identifiability difficulty degree for various input conditions.
Sorzano, Carlos Oscars S; Pérez-De-La-Cruz Moreno, Maria Angeles; Burguet-Castell, Jordi; Montejo, Consuelo; Ros, Antonio Aguilar
2015-06-01
Pharmacokinetics (PK) applications can be seen as a special case of nonlinear, causal systems with memory. There are cases in which prior knowledge exists about the distribution of the system parameters in a population. However, for a specific patient in a clinical setting, we need to determine her system parameters so that the therapy can be personalized. This system identification is performed many times by measuring drug concentrations in plasma. The objective of this work is to provide an irregular sampling strategy that minimizes the uncertainty about the system parameters with a fixed amount of samples (cost constrained). We use Monte Carlo simulations to estimate the average Fisher's information matrix associated to the PK problem, and then estimate the sampling points that minimize the maximum uncertainty associated to system parameters (a minimax criterion). The minimization is performed employing a genetic algorithm. We show that such a sampling scheme can be designed in a way that is adapted to a particular patient and that it can accommodate any dosing regimen as well as it allows flexible therapeutic strategies. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.
Optimization of electrospinning parameters for chitosan nanofibres
CSIR Research Space (South Africa)
Jacobs, V
2011-06-01
Full Text Available Electrospinning of chitosan, a naturally occurring polysaccharide biopolymer, has been investigated. In this paper, the authors report the optimization of electrospinning process and solution parameters using factorial design approach to obtain...
Optimization of Agrobacterium -mediated transformation parameters ...
African Journals Online (AJOL)
Agrobacterium-mediated transformation factors for sweet potato embryogenic calli were optimized using -glucuronidase (GUS) as a reporter. The binary vector pTCK303 harboring the modified GUS gene driven by the CaMV 35S promoter was used. Transformation parameters were optimized including bacterial ...
Optimization of nonlinear wave function parameters
International Nuclear Information System (INIS)
Shepard, R.; Minkoff, M.; Chemistry
2006-01-01
An energy-based optimization method is presented for our recently developed nonlinear wave function expansion form for electronic wave functions. This expansion form is based on spin eigenfunctions, using the graphical unitary group approach (GUGA). The wave function is expanded in a basis of product functions, allowing application to closed-shell and open-shell systems and to ground and excited electronic states. Each product basis function is itself a multiconfigurational function that depends on a relatively small number of nonlinear parameters called arc factors. The energy-based optimization is formulated in terms of analytic arc factor gradients and orbital-level Hamiltonian matrices that correspond to a specific kind of uncontraction of each of the product basis functions. These orbital-level Hamiltonian matrices give an intuitive representation of the energy in terms of disjoint subsets of the arc factors, they provide for an efficient computation of gradients of the energy with respect to the arc factors, and they allow optimal arc factors to be determined in closed form for subspaces of the full variation problem. Timings for energy and arc factor gradient computations involving expansion spaces of > 10 24 configuration state functions are reported. Preliminary convergence studies and molecular dissociation curves are presented for some small molecules
Directory of Open Access Journals (Sweden)
Fu-Kang Ma
2017-03-01
Full Text Available In this paper, an opposed-piston two-stroke (OP2S gasoline direct injection (GDI engine is introduced and its working principles and scavenging process were analyzed. An optimization function was established to optimize the scavenging system parameters, include intake port height, exhaust port height, intake port circumference ratio, the exhaust port circumference ratio and opposed-piston motion phase difference. The effect of the port height on the effective compression ratio and effective expansion ratio were considered, and indicated mean effective pressure (IMEP was employed as the optimization objective instead of scavenging efficiency. Orthogonal experiments were employed to reduce the calculation work. The effect of the scavenging parameters on delivery ratio, trapping ratio, scavenging efficiency and indicated thermal efficiency were calculated, and the best parameters were also obtained by the optimization function. The results show that IMEP can be used as the optimization objective in the uniflow scavenging system; intake port height is the main factor to the delivery ratio, while exhaust port height is the main to engine trapping ratio, scavenging efficiency and indicated thermal efficiency; exhaust port height is the most important factor to effect the gas exchange process of OP2S-GDI engine.
CSIR Research Space (South Africa)
Bembe, MJ
2010-11-01
Full Text Available single device. In this study the focus is on the modification of the antenna designs for dual-band functionality which is limited on the ESPAR antenna’s structural parameter. This modification should result in an antenna system which operates in both 2...
Optimal Laser Phototherapy Parameters for Pain Relief.
Kate, Rohit J; Rubatt, Sarah; Enwemeka, Chukuka S; Huddleston, Wendy E
2018-03-27
Studies on laser phototherapy for pain relief have used parameters that vary widely and have reported varying outcomes. The purpose of this study was to determine the optimal parameter ranges of laser phototherapy for pain relief by analyzing data aggregated from existing primary literature. Original studies were gathered from available sources and were screened to meet the pre-established inclusion criteria. The included articles were then subjected to meta-analysis using Cohen's d statistic for determining treatment effect size. From these studies, ranges of the reported parameters that always resulted into large effect sizes were determined. These optimal ranges were evaluated for their accuracy using leave-one-article-out cross-validation procedure. A total of 96 articles met the inclusion criteria for meta-analysis and yielded 232 effect sizes. The average effect size was highly significant: d = +1.36 (confidence interval [95% CI] = 1.04-1.68). Among all the parameters, total energy was found to have the greatest effect on pain relief and had the most prominent optimal ranges of 120-162 and 15.36-20.16 J, which always resulted in large effect sizes. The cross-validation accuracy of the optimal ranges for total energy was 68.57% (95% CI = 53.19-83.97). Fewer and less-prominent optimal ranges were obtained for the energy density and duration parameters. None of the remaining parameters was found to be independently related to pain relief outcomes. The findings of meta-analysis indicate that laser phototherapy is highly effective for pain relief. Based on the analysis of parameters, total energy can be optimized to yield the largest effect on pain relief.
Optimal design criteria - prediction vs. parameter estimation
Waldl, Helmut
2014-05-01
G-optimality is a popular design criterion for optimal prediction, it tries to minimize the kriging variance over the whole design region. A G-optimal design minimizes the maximum variance of all predicted values. If we use kriging methods for prediction it is self-evident to use the kriging variance as a measure of uncertainty for the estimates. Though the computation of the kriging variance and even more the computation of the empirical kriging variance is computationally very costly and finding the maximum kriging variance in high-dimensional regions can be time demanding such that we cannot really find the G-optimal design with nowadays available computer equipment in practice. We cannot always avoid this problem by using space-filling designs because small designs that minimize the empirical kriging variance are often non-space-filling. D-optimality is the design criterion related to parameter estimation. A D-optimal design maximizes the determinant of the information matrix of the estimates. D-optimality in terms of trend parameter estimation and D-optimality in terms of covariance parameter estimation yield basically different designs. The Pareto frontier of these two competing determinant criteria corresponds with designs that perform well under both criteria. Under certain conditions searching the G-optimal design on the above Pareto frontier yields almost as good results as searching the G-optimal design in the whole design region. In doing so the maximum of the empirical kriging variance has to be computed only a few times though. The method is demonstrated by means of a computer simulation experiment based on data provided by the Belgian institute Management Unit of the North Sea Mathematical Models (MUMM) that describe the evolution of inorganic and organic carbon and nutrients, phytoplankton, bacteria and zooplankton in the Southern Bight of the North Sea.
Cosmological parameter estimation using Particle Swarm Optimization
Prasad, J.; Souradeep, T.
2014-03-01
Constraining parameters of a theoretical model from observational data is an important exercise in cosmology. There are many theoretically motivated models, which demand greater number of cosmological parameters than the standard model of cosmology uses, and make the problem of parameter estimation challenging. It is a common practice to employ Bayesian formalism for parameter estimation for which, in general, likelihood surface is probed. For the standard cosmological model with six parameters, likelihood surface is quite smooth and does not have local maxima, and sampling based methods like Markov Chain Monte Carlo (MCMC) method are quite successful. However, when there are a large number of parameters or the likelihood surface is not smooth, other methods may be more effective. In this paper, we have demonstrated application of another method inspired from artificial intelligence, called Particle Swarm Optimization (PSO) for estimating cosmological parameters from Cosmic Microwave Background (CMB) data taken from the WMAP satellite.
Cosmological parameter estimation using Particle Swarm Optimization
International Nuclear Information System (INIS)
Prasad, J; Souradeep, T
2014-01-01
Constraining parameters of a theoretical model from observational data is an important exercise in cosmology. There are many theoretically motivated models, which demand greater number of cosmological parameters than the standard model of cosmology uses, and make the problem of parameter estimation challenging. It is a common practice to employ Bayesian formalism for parameter estimation for which, in general, likelihood surface is probed. For the standard cosmological model with six parameters, likelihood surface is quite smooth and does not have local maxima, and sampling based methods like Markov Chain Monte Carlo (MCMC) method are quite successful. However, when there are a large number of parameters or the likelihood surface is not smooth, other methods may be more effective. In this paper, we have demonstrated application of another method inspired from artificial intelligence, called Particle Swarm Optimization (PSO) for estimating cosmological parameters from Cosmic Microwave Background (CMB) data taken from the WMAP satellite
Directory of Open Access Journals (Sweden)
Francisco Javier Fernández
2017-11-01
Full Text Available Water loop heat pump (WLHP air conditioning systems use heat pumps connected to a common water circuit to fulfill the energy demands of different thermal zones in a building. In this study, the energy consumption was analyzed for the air conditioning of an office building in the typical climate of four important cities of the Iberian Peninsula. The energy consumption of one water loop heat pump system was compared with a conventional water system. Two design parameters, the range in the control temperatures and the water loop thermal storage size, were tested. Energy redistribution is an important advantage of the WLHP system, but significant savings came from high efficiency parameters in the heat pumps and minor air flow rates in the cooling tower. The low thermal level in the water loop makes this technology appropriate to combine with renewable sources. Using natural gas as the thermal energy source, a mean decrease in CO2 emissions of 8.1% was reached. Simulations showed that the installation of big thermal storage tanks generated small energy savings. Besides, the total annual consumption in buildings with high internal loads can be reduced by keeping the water loop as cool as possible.
Huang, Zhujian; Zhang, Xianning; Cui, Lihua; Yu, Guangwei
2016-09-15
In this work, three hybrid vertical down-flow constructed wetland (HVDF-CW) systems with different compound substrates were fed with domestic sewage and their pollutants removal performance under different hydraulic loading and step-feeding ratio was investigated. The results showed that the hydraulic loading and step-feeding ratio were two crucial factors determining the removal efficiency of most pollutants, while substrate types only significantly affected the removal of COD and NH4(+)-N. Generally, the lower the hydraulic loading, the better removal efficiency of all contaminants, except for TN. By contrast, the increase of step-feeding ratio would slightly reduce the removal rate of ammonium and TP but obviously promoted the TN removal. Therefore, the optimal operation of this CWs could be achieved with low hydraulic loading combined with 50% of step-feeding ratio when TN removal is the priority, whereas medium or low hydraulic loading without step-feeding would be suitable when TN removal is not taken into consideration. The obtained results in this study can provide us with a guideline for design and optimization of hybrid vertical flow constructed wetland systems to improve the pollutants removal from domestic sewage. Copyright © 2016 Elsevier Ltd. All rights reserved.
Optimal parameters uncoupling vibration modes of oscillators
Le, K. C.; Pieper, A.
2017-07-01
This paper proposes a novel optimization concept for an oscillator with two degrees of freedom. By using specially defined motion ratios, we control the action of springs to each degree of freedom of the oscillator. We aim at showing that, if the potential action of the springs in one period of vibration, used as the payoff function for the conservative oscillator, is maximized among all admissible parameters and motions satisfying Lagrange's equations, then the optimal motion ratios uncouple vibration modes. A similar result holds true for the dissipative oscillator having dampers. The application to optimal design of vehicle suspension is discussed.
Multi-objective optimization in quantum parameter estimation
Gong, BeiLi; Cui, Wei
2018-04-01
We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of parameter estimation is improved, it usually introduces a significant deformation to the system state. Moreover, we propose a multi-objective model to optimize the two conflicting objectives: (1) maximizing the Fisher information, improving the parameter estimation precision, and (2) minimizing the deformation of the system state, which maintains its fidelity. Finally, simulations of a simplified ɛ-constrained model demonstrate the feasibility of the Hamiltonian control in improving the precision of the quantum parameter estimation.
International Nuclear Information System (INIS)
Jung, Bongki; Park, Min; Heo, Sung Ryul; Kim, Tae-Seong; Jeong, Seung Ho; Chang, Doo-Hee; Lee, Kwang Won; In, Sang-Ryul
2016-01-01
Highlights: • High power magnetic bucket-type arc plasma source for the VEST NBI system is developed with modifications based on the prototype plasma source for KSTAR. • Plasma parameters in pulse duration are measured to characterize the plasma source. • High plasma density and good uniformity is achieved at the low operating pressure below 1 Pa. • Required ion beam current density is confirmed by analysis of plasma parameters and results of a particle balance model. - Abstract: A large-scale hydrogen arc plasma source was developed at the Korea Atomic Energy Research Institute for a high power pulsed NBI system of VEST which is a compact spherical tokamak at Seoul national university. One of the research target of VEST is to study innovative tokamak operating scenarios. For this purpose, high current density and uniform large-scale pulse plasma source is required to satisfy the target ion beam power efficiently. Therefore, optimizing the plasma parameters of the ion source such as the electron density, temperature, and plasma uniformity is conducted by changing the operating conditions of the plasma source. Furthermore, ion species of the hydrogen plasma source are analyzed using a particle balance model to increase the monatomic fraction which is another essential parameter for increasing the ion beam current density. Conclusively, efficient operating conditions are presented from the results of the optimized plasma parameters and the extractable ion beam current is calculated.
International Nuclear Information System (INIS)
Fakehi, Amir Hossein; Ahmadi, Somayeh; Mirghaed, Mohammad Rezaie
2015-01-01
Highlights: • The exergy analysis of a hybrid system of a wind turbine and PEM electrolyzer/fuel-cell has been performed. • Effects of various operating parameters on the exergy efficiency have been investigated. • The exergy and energy efficiency in each of hybrid system’s components have been compared. - Abstract: In this study, hybrid renewable energy system based on wind/electrolyzer/PEM fuel cell are conceptually modeled, and also, exergy and energy analysis are performed. The energy and exergy flows are investigated by the proposed model for Khaf region-Iran with high average wind speed and monsoon. Exergy and energy analysis framework is made based on thermodynamic, electro-chemical and mechanical model of the different component of hybrid system. Also, the effects of various operating parameters in exergy efficiency are calculated. The results show an optimum wind speed where the exergy efficiency and power coefficient is at maximum level, and also, when the ambient temperature start to be increased in wind turbine, the efficiencies decrease by a great deal for constant wind speeds. Also, the optimum temperature is calculated by exergy analysis in electrolyzer and fuel cell as 353 and the exergy efficiency of electrolyzer decreases by increasing the membrane thickness. Furthermore, pressure changes affect exergy and energy efficiency in PEM fuel cell. Finally, the electrolyzer and fuel cell efficiencies are calculated as 68.5% and 47% respectively.
International Nuclear Information System (INIS)
Sivasakthivel, T.; Murugesan, K.; Thomas, H.R.
2014-01-01
Highlights: • Ground Source Heat Pump (GSHP) technology is suitable for both heating and cooling. • Important parameters that affect the GSHP performance has been listed. • Parameters of GSHP system has been optimized for heating and cooling mode. • Taguchi technique and utility concept are developed for GSHP optimization. - Abstract: Use of ground source energy for space heating applications through Ground Source Heat pump (GSHP) has been established as an efficient thermodynamic process. The electricity input to the GSHP can be reduced by increasing the COP of the system. However, the COP of a GSHP system will be different for heating and cooling mode operations. Hence in order to reduce the electricity input to the GSHP, an optimum value of COP has to be determined when GSHP is operated in both heating and cooling modes. In the present research, a methodology is proposed to optimize the operating parameters of a GSHP system which will operate on both heating and cooling modes. Condenser inlet temperature, condenser outlet temperature, dryness fraction at evaporator inlet and evaporator outlet temperature are considered as the influencing parameters of the heat pump. Optimization of these parameters for only heating or only cooling mode operation is achieved by employing Taguchi method for three level variations of the above parameters using an L 9 (3 4 ) orthogonal array. Higher the better concept has been used to get a higher COP. A computer program in FORTAN has been developed to carry out the computations and the results have been analyzed for the optimum conditions using Signal-to-Noise (SN) ratio and Analysis Of Variance (ANOVA) method. Based on this analysis, the maximum COP for only heating and only cooling operation are obtained as 4.25 and 3.32 respectively. By making use of the utility concept both the higher values of COP obtained for heating and cooling modes are optimized to get a single optimum COP for heating and cooling modes. A single
GA BASED GLOBAL OPTIMAL DESIGN PARAMETERS FOR ...
African Journals Online (AJOL)
Journal of Modeling, Design and Management of Engineering Systems ... DESIGN PARAMETERS FOR CONSECUTIVE REACTIONS IN SERIALLY CONNECTED ... for the process equipments such as chemical reactors used in industries.
Chickpea seeds germination rational parameters optimization
Safonova, Yu A.; Ivliev, M. N.; Lemeshkin, A. V.
2018-05-01
The paper presents the influence of chickpea seeds bioactivation parameters on their enzymatic activity experimental results. Optimal bioactivation process modes were obtained by regression-factor analysis: process temperature - 13.6 °C, process duration - 71.5 h. It was found that in the germination process, the proteolytic, amylolytic and lipolytic enzymes activity increased, and the urease enzyme activity is reduced. The dependences of enzyme activity on chickpea seeds germination conditions were obtained by mathematical processing of experimental data. The calculated data are in good agreement with the experimental ones. This confirms the optimization efficiency based on experiments mathematical planning in order to determine the enzymatic activity of chickpea seeds germination optimal parameters of bioactivated seeds.
Control parameter optimization for AP1000 reactor using Particle Swarm Optimization
International Nuclear Information System (INIS)
Wang, Pengfei; Wan, Jiashuang; Luo, Run; Zhao, Fuyu; Wei, Xinyu
2016-01-01
Highlights: • The PSO algorithm is applied for control parameter optimization of AP1000 reactor. • Key parameters of the MSHIM control system are optimized. • Optimization results are evaluated though simulations and quantitative analysis. - Abstract: The advanced mechanical shim (MSHIM) core control strategy is implemented in the AP1000 reactor for core reactivity and axial power distribution control simultaneously. The MSHIM core control system can provide superior reactor control capabilities via automatic rod control only. This enables the AP1000 to perform power change operations automatically without the soluble boron concentration adjustments. In this paper, the Particle Swarm Optimization (PSO) algorithm has been applied for the parameter optimization of the MSHIM control system to acquire better reactor control performance for AP1000. System requirements such as power control performance, control bank movement and AO control constraints are reflected in the objective function. Dynamic simulations are performed based on an AP1000 reactor simulation platform in each iteration of the optimization process to calculate the fitness values of particles in the swarm. The simulation platform is developed in Matlab/Simulink environment with implementation of a nodal core model and the MSHIM control strategy. Based on the simulation platform, the typical 10% step load decrease transient from 100% to 90% full power is simulated and the objective function used for control parameter tuning is directly incorporated in the simulation results. With successful implementation of the PSO algorithm in the control parameter optimization of AP1000 reactor, four key parameters of the MSHIM control system are optimized. It has been demonstrated by the calculation results that the optimized MSHIM control system parameters can improve the reactor power control capability and reduce the control rod movement without compromising AO control. Therefore, the PSO based optimization
Directory of Open Access Journals (Sweden)
Chien-Lin Huang
2015-01-01
Full Text Available This study aims to construct a typhoon precipitation forecast model providing forecasts one to six hours in advance using optimal model parameters and structures retrieved from a combination of the adaptive network-based fuzzy inference system (ANFIS and artificial intelligence. To enhance the accuracy of the precipitation forecast, two structures were then used to establish the precipitation forecast model for a specific lead-time: a single-model structure and a dual-model hybrid structure where the forecast models of higher and lower precipitation were integrated. In order to rapidly, automatically, and accurately retrieve the optimal parameters and structures of the ANFIS-based precipitation forecast model, a tabu search was applied to identify the adjacent radius in subtractive clustering when constructing the ANFIS structure. The coupled structure was also employed to establish a precipitation forecast model across short and long lead-times in order to improve the accuracy of long-term precipitation forecasts. The study area is the Shimen Reservoir, and the analyzed period is from 2001 to 2009. Results showed that the optimal initial ANFIS parameters selected by the tabu search, combined with the dual-model hybrid method and the coupled structure, provided the favors in computation efficiency and high-reliability predictions in typhoon precipitation forecasts regarding short to long lead-time forecasting horizons.
Parameter optimization for surface flux transport models
Whitbread, T.; Yeates, A. R.; Muñoz-Jaramillo, A.; Petrie, G. J. D.
2017-11-01
Accurate prediction of solar activity calls for precise calibration of solar cycle models. Consequently we aim to find optimal parameters for models which describe the physical processes on the solar surface, which in turn act as proxies for what occurs in the interior and provide source terms for coronal models. We use a genetic algorithm to optimize surface flux transport models using National Solar Observatory (NSO) magnetogram data for Solar Cycle 23. This is applied to both a 1D model that inserts new magnetic flux in the form of idealized bipolar magnetic regions, and also to a 2D model that assimilates specific shapes of real active regions. The genetic algorithm searches for parameter sets (meridional flow speed and profile, supergranular diffusivity, initial magnetic field, and radial decay time) that produce the best fit between observed and simulated butterfly diagrams, weighted by a latitude-dependent error structure which reflects uncertainty in observations. Due to the easily adaptable nature of the 2D model, the optimization process is repeated for Cycles 21, 22, and 24 in order to analyse cycle-to-cycle variation of the optimal solution. We find that the ranges and optimal solutions for the various regimes are in reasonable agreement with results from the literature, both theoretical and observational. The optimal meridional flow profiles for each regime are almost entirely within observational bounds determined by magnetic feature tracking, with the 2D model being able to accommodate the mean observed profile more successfully. Differences between models appear to be important in deciding values for the diffusive and decay terms. In like fashion, differences in the behaviours of different solar cycles lead to contrasts in parameters defining the meridional flow and initial field strength.
Towards automatic parameter tuning of stream processing systems
Bilal, Muhammad; Canini, Marco
2017-01-01
for automating parameter tuning for stream-processing systems. Our framework supports standard black-box optimization algorithms as well as a novel gray-box optimization algorithm. We demonstrate the multiple benefits of automated parameter tuning in optimizing
Optimization of hydraulic turbine governor parameters based on WPA
Gao, Chunyang; Yu, Xiangyang; Zhu, Yong; Feng, Baohao
2018-01-01
The parameters of hydraulic turbine governor directly affect the dynamic characteristics of the hydraulic unit, thus affecting the regulation capacity and the power quality of power grid. The governor of conventional hydropower unit is mainly PID governor with three adjustable parameters, which are difficult to set up. In order to optimize the hydraulic turbine governor, this paper proposes wolf pack algorithm (WPA) for intelligent tuning since the good global optimization capability of WPA. Compared with the traditional optimization method and PSO algorithm, the results show that the PID controller designed by WPA achieves a dynamic quality of hydraulic system and inhibits overshoot.
Integral Optimization of Systematic Parameters of Flip-Flow Screens
Institute of Scientific and Technical Information of China (English)
翟宏新
2004-01-01
The synthetic index Ks for evaluating flip-flow screens is proposed and systematically optimized in view of the whole system. A series of optimized values of relevant parameters are found and then compared with those of the current industrial specifications. The results show that the optimized value Ks approaches the one of those famous flip-flow screens in the world. Some new findings on geometric and kinematics parameters are useful for improving the flip-flow screens with a low Ks value, which is helpful in developing clean coal technology.
Cosmological parameter estimation using particle swarm optimization
Prasad, Jayanti; Souradeep, Tarun
2012-06-01
Constraining theoretical models, which are represented by a set of parameters, using observational data is an important exercise in cosmology. In Bayesian framework this is done by finding the probability distribution of parameters which best fits to the observational data using sampling based methods like Markov chain Monte Carlo (MCMC). It has been argued that MCMC may not be the best option in certain problems in which the target function (likelihood) poses local maxima or have very high dimensionality. Apart from this, there may be examples in which we are mainly interested to find the point in the parameter space at which the probability distribution has the largest value. In this situation the problem of parameter estimation becomes an optimization problem. In the present work we show that particle swarm optimization (PSO), which is an artificial intelligence inspired population based search procedure, can also be used for cosmological parameter estimation. Using PSO we were able to recover the best-fit Λ cold dark matter (LCDM) model parameters from the WMAP seven year data without using any prior guess value or any other property of the probability distribution of parameters like standard deviation, as is common in MCMC. We also report the results of an exercise in which we consider a binned primordial power spectrum (to increase the dimensionality of problem) and find that a power spectrum with features gives lower chi square than the standard power law. Since PSO does not sample the likelihood surface in a fair way, we follow a fitting procedure to find the spread of likelihood function around the best-fit point.
Directory of Open Access Journals (Sweden)
Xiang-ming Gao
2017-01-01
Full Text Available Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD and support vector machine (SVM optimized with an artificial bee colony (ABC algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.
Gao, Xiang-Ming; Yang, Shi-Feng; Pan, San-Bo
2017-01-01
Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.
Genetic Algorithm Optimizes Q-LAW Control Parameters
Lee, Seungwon; von Allmen, Paul; Petropoulos, Anastassios; Terrile, Richard
2008-01-01
A document discusses a multi-objective, genetic algorithm designed to optimize Lyapunov feedback control law (Q-law) parameters in order to efficiently find Pareto-optimal solutions for low-thrust trajectories for electronic propulsion systems. These would be propellant-optimal solutions for a given flight time, or flight time optimal solutions for a given propellant requirement. The approximate solutions are used as good initial solutions for high-fidelity optimization tools. When the good initial solutions are used, the high-fidelity optimization tools quickly converge to a locally optimal solution near the initial solution. Q-law control parameters are represented as real-valued genes in the genetic algorithm. The performances of the Q-law control parameters are evaluated in the multi-objective space (flight time vs. propellant mass) and sorted by the non-dominated sorting method that assigns a better fitness value to the solutions that are dominated by a fewer number of other solutions. With the ranking result, the genetic algorithm encourages the solutions with higher fitness values to participate in the reproduction process, improving the solutions in the evolution process. The population of solutions converges to the Pareto front that is permitted within the Q-law control parameter space.
Parameter optimization in the regularized kernel minimum noise fraction transformation
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack
2012-01-01
Based on the original, linear minimum noise fraction (MNF) transformation and kernel principal component analysis, a kernel version of the MNF transformation was recently introduced. Inspired by we here give a simple method for finding optimal parameters in a regularized version of kernel MNF...... analysis. We consider the model signal-to-noise ratio (SNR) as a function of the kernel parameters and the regularization parameter. In 2-4 steps of increasingly refined grid searches we find the parameters that maximize the model SNR. An example based on data from the DLR 3K camera system is given....
Directory of Open Access Journals (Sweden)
Hussien A. Elsayed
2017-12-01
Full Text Available One of the most significant procedures in oil refineries is naphtha catalytic reforming unit in which high octane gasoline is gained. Normally, in oil refineries, flow instability in the composition of feedstock can affect the product quality. The aim of the present work was focused on modifications of the final product flow rate and product’s octane number with respect to the modifications of the feedstock composition. The main three reforming reactions investigated, namely; dehydrogenation, dehydrocyclization, and hydrocracking were conducted employing silica supported bimetallic (Pt-Re patented catalyst. Optimization of the catalytic process reaction conditions, i.e.; temperature, hydrogen pressure and liquid hourly space velocity (LHSV was carried out with regard to conversion and selectivity. The optimization results indicated that heavy naphtha component conversion (paraffin’s and naphthenes increases with an increasing in reaction temperature and pressure while decreases with an increase in LHSV. The kinetic study of catalytic reforming reactions reported helped establishing the reaction model explicitly.
Fine-Tuning ADAS Algorithm Parameters for Optimizing Traffic ...
With the development of the Connected Vehicle technology that facilitates wirelessly communication among vehicles and road-side infrastructure, the Advanced Driver Assistance Systems (ADAS) can be adopted as an effective tool for accelerating traffic safety and mobility optimization at various highway facilities. To this end, the traffic management centers identify the optimal ADAS algorithm parameter set that enables the maximum improvement of the traffic safety and mobility performance, and broadcast the optimal parameter set wirelessly to individual ADAS-equipped vehicles. After adopting the optimal parameter set, the ADAS-equipped drivers become active agents in the traffic stream that work collectively and consistently to prevent traffic conflicts, lower the intensity of traffic disturbances, and suppress the development of traffic oscillations into heavy traffic jams. Successful implementation of this objective requires the analysis capability of capturing the impact of the ADAS on driving behaviors, and measuring traffic safety and mobility performance under the influence of the ADAS. To address this challenge, this research proposes a synthetic methodology that incorporates the ADAS-affected driving behavior modeling and state-of-the-art microscopic traffic flow modeling into a virtually simulated environment. Building on such an environment, the optimal ADAS algorithm parameter set is identified through an optimization programming framework to enable th
International Nuclear Information System (INIS)
Vasseur, D.; Eid, M.
1996-01-01
One of EDF's current priorities is the optimisation of the preventive maintenance in all French nuclear power stations. This optimisation involves a rationalization of the choice of equipments to be maintained and maintenance tasks to be carried out, as well as a judicious choice of intervals between these tasks. This work is being carried out in cooperation between EDF and the CEA (Atomic Energy Commission), and suggests a procedure to provide assistance in optimising intervals between maintenance tasks respecting a global unavailability target. This work is based on the differential model for equivalent parameters (DMEP). (authors)
AI-guided parameter optimization in inverse treatment planning
International Nuclear Information System (INIS)
Yan Hui; Yin Fangfang; Guan Huaiqun; Kim, Jae Ho
2003-01-01
An artificial intelligence (AI)-guided inverse planning system was developed to optimize the combination of parameters in the objective function for intensity-modulated radiation therapy (IMRT). In this system, the empirical knowledge of inverse planning was formulated with fuzzy if-then rules, which then guide the parameter modification based on the on-line calculated dose. Three kinds of parameters (weighting factor, dose specification, and dose prescription) were automatically modified using the fuzzy inference system (FIS). The performance of the AI-guided inverse planning system (AIGIPS) was examined using the simulated and clinical examples. Preliminary results indicate that the expected dose distribution was automatically achieved using the AI-guided inverse planning system, with the complicated compromising between different parameters accomplished by the fuzzy inference technique. The AIGIPS provides a highly promising method to replace the current trial-and-error approach
National Aeronautics and Space Administration — An optimal alarm system is simply an optimal level-crossing predictor that can be designed to elicit the fewest false alarms for a fixed detection probability. It...
Jung, Kyung-Won; Park, Dae-Seon; Hwang, Min-Jin; Ahn, Kyu-Hong
2015-09-01
In this study, the decolorization of Acid Orange 7 (AO-7) with intensified performance was obtained using hydrodynamic cavitation (HC) combined with an electric field (graphite electrodes). As a preliminary step, various HC systems were compared in terms of decolorization, and, among them, the electric field-assisted modified orifice plate HC (EFM-HC) system exhibited perfect decolorization performance within 40 min of reaction time. Interestingly, when H2O2 was injected into the EFM-HC system as an additional oxidant, the reactor performance gradually decreased as the dosing ratio increased; thus, the remaining experiments were performed without H2O2. Subsequently, an optimization process was conducted using response surface methodology with a Box-Behnken design. The inlet pressure, initial pH, applied voltage, and reaction time were chosen as operational key factors, while decolorization was selected as the response variable. The overall performance revealed that the selected parameters were either slightly interdependent, or had significant interactive effects on the decolorization. In the verification test, complete decolorization was observed under statistically optimized conditions. This study suggests that EFM-HC is a useful method for pretreatment of dye wastewater with positive economic and commercial benefits. Copyright © 2015 Elsevier B.V. All rights reserved.
Parameters optimization for magnetic resonance coupling wireless power transmission.
Li, Changsheng; Zhang, He; Jiang, Xiaohua
2014-01-01
Taking maximum power transmission and power stable transmission as research objectives, optimal design for the wireless power transmission system based on magnetic resonance coupling is carried out in this paper. Firstly, based on the mutual coupling model, mathematical expressions of optimal coupling coefficients for the maximum power transmission target are deduced. Whereafter, methods of enhancing power transmission stability based on parameters optimal design are investigated. It is found that the sensitivity of the load power to the transmission parameters can be reduced and the power transmission stability can be enhanced by improving the system resonance frequency or coupling coefficient between the driving/pick-up coil and the transmission/receiving coil. Experiment results are well conformed to the theoretical analysis conclusions.
System performance optimization
International Nuclear Information System (INIS)
Bednarz, R.J.
1978-01-01
The System Performance Optimization has become an important and difficult field for large scientific computer centres. Important because the centres must satisfy increasing user demands at the lowest possible cost. Difficult because the System Performance Optimization requires a deep understanding of hardware, software and workload. The optimization is a dynamic process depending on the changes in hardware configuration, current level of the operating system and user generated workload. With the increasing complication of the computer system and software, the field for the optimization manoeuvres broadens. The hardware of two manufacturers IBM and CDC is discussed. Four IBM and two CDC operating systems are described. The description concentrates on the organization of the operating systems, the job scheduling and I/O handling. The performance definitions, workload specification and tools for the system stimulation are given. The measurement tools for the System Performance Optimization are described. The results of the measurement and various methods used for the operating system tuning are discussed. (Auth.)
Concurrently adjusting interrelated control parameters to achieve optimal engine performance
Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna
2015-12-01
Methods and systems for real-time engine control optimization are provided. A value of an engine performance variable is determined, a value of a first operating condition and a value of a second operating condition of a vehicle engine are detected, and initial values for a first engine control parameter and a second engine control parameter are determined based on the detected first operating condition and the detected second operating condition. The initial values for the first engine control parameter and the second engine control parameter are adjusted based on the determined value of the engine performance variable to cause the engine performance variable to approach a target engine performance variable. In order to cause the engine performance variable to approach the target engine performance variable, adjusting the initial value for the first engine control parameter necessitates a corresponding adjustment of the initial value for the second engine control parameter.
GA based CNC turning center exploitation process parameters optimization
Directory of Open Access Journals (Sweden)
Z. Car
2009-01-01
Full Text Available This paper presents machining parameters (turning process optimization based on the use of artificial intelligence. To obtain greater efficiency and productivity of the machine tool, optimal cutting parameters have to be obtained. In order to find optimal cutting parameters, the genetic algorithm (GA has been used as an optimal solution finder. Optimization has to yield minimum machining time and minimum production cost, while considering technological and material constrains.
Directory of Open Access Journals (Sweden)
Davison JA
2015-08-01
Full Text Available James A DavisonWolfe Eye Clinic, Marshalltown, IA, USA Purpose: To present a cause of posterior capsule aspiration and a technique using optimized parameters to prevent it from happening when operating soft cataracts.Patients and methods: A prospective list of posterior capsule aspiration cases was kept over 4,062 consecutive cases operated with the Alcon CENTURION machine and Balanced Tip. Video analysis of one case of posterior capsule aspiration was accomplished. A surgical technique was developed using empirically derived machine parameters and customized setting-selection procedure step toolbar to reduce the pace of aspiration of soft nuclear quadrants in order to prevent capsule aspiration.Results: Two cases out of 3,238 experienced posterior capsule aspiration before use of the soft quadrant technique. Video analysis showed an attractive vortex effect with capsule aspiration occurring in 1/5 of a second. A soft quadrant removal setting was empirically derived which had a slower pace and seemed more controlled with no capsule aspiration occurring in the subsequent 824 cases. The setting featured simultaneous linear control from zero to preset maximums for: aspiration flow, 20 mL/min; and vacuum, 400 mmHg, with the addition of torsional tip amplitude up to 20% after the fluidic maximums were achieved. A new setting selection procedure step toolbar was created to increase intraoperative flexibility by providing instantaneous shifting between the soft and normal settings.Conclusion: A technique incorporating a reduced pace for soft quadrant acquisition and aspiration can be accomplished through the use of a dedicated setting of integrated machine parameters. Toolbar placement of the procedure button next to the normal setting procedure button provides the opportunity to instantaneously alternate between the two settings. Simultaneous surgeon control over vacuum, aspiration flow, and torsional tip motion may make removal of soft nuclear
Optimization of rotational arc station parameter optimized radiation therapy
Energy Technology Data Exchange (ETDEWEB)
Dong, P.; Ungun, B. [Department of Radiation Oncology, Stanford University, Stanford, California 94305 (United States); Boyd, S. [Department of Electrical Engineering, Stanford University, Stanford, California 94305 (United States); Xing, L., E-mail: lei@stanford.edu [Department of Radiation Oncology, Stanford University, Stanford, California 94305 and Department of Electrical Engineering, Stanford University, Stanford, California 94305 (United States)
2016-09-15
Purpose: To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of matching VMAT in both plan quality and delivery efficiency by using three clinical cases of different disease sites. Methods: The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state-of-the-art GPU based proximal operator graph solver. To avoid being trapped in a local minimum in beamlet-based aperture selection using the gradient descent algorithm, a stochastic gradient descent was employed here. Apertures with zero or low weight were thrown out. To find out whether there was room to further improve the plan by adding more apertures or SPs, the authors repeated the above procedure with consideration of the existing dose distribution from the last iteration. At the end of the second iteration, the weights of all the apertures were reoptimized, including those of the first iteration. The above procedure was repeated until the plan could not be improved any further. The optimization technique was assessed by using three clinical cases (prostate, head and neck, and brain) with the results compared to that obtained using conventional VMAT in terms of dosimetric properties, treatment time, and total MU. Results: Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. For the prostate case, the volume of the 50% prescription dose was decreased by 22% for the rectum and 6% for the bladder. For the head and neck case, SPORT improved the mean dose for the left and right parotids by 15% each. The maximum dose was lowered from 72.7 to 71.7 Gy for the mandible, and from 30.7 to 27.3 Gy for the spinal cord. The mean dose for the pharynx and larynx was
Optimization of rotational arc station parameter optimized radiation therapy
International Nuclear Information System (INIS)
Dong, P.; Ungun, B.; Boyd, S.; Xing, L.
2016-01-01
Purpose: To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of matching VMAT in both plan quality and delivery efficiency by using three clinical cases of different disease sites. Methods: The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state-of-the-art GPU based proximal operator graph solver. To avoid being trapped in a local minimum in beamlet-based aperture selection using the gradient descent algorithm, a stochastic gradient descent was employed here. Apertures with zero or low weight were thrown out. To find out whether there was room to further improve the plan by adding more apertures or SPs, the authors repeated the above procedure with consideration of the existing dose distribution from the last iteration. At the end of the second iteration, the weights of all the apertures were reoptimized, including those of the first iteration. The above procedure was repeated until the plan could not be improved any further. The optimization technique was assessed by using three clinical cases (prostate, head and neck, and brain) with the results compared to that obtained using conventional VMAT in terms of dosimetric properties, treatment time, and total MU. Results: Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. For the prostate case, the volume of the 50% prescription dose was decreased by 22% for the rectum and 6% for the bladder. For the head and neck case, SPORT improved the mean dose for the left and right parotids by 15% each. The maximum dose was lowered from 72.7 to 71.7 Gy for the mandible, and from 30.7 to 27.3 Gy for the spinal cord. The mean dose for the pharynx and larynx was
A choice of the parameters of NPP steam generators on the basis of vector optimization
International Nuclear Information System (INIS)
Lemeshev, V.U.; Metreveli, D.G.
1981-01-01
The optimization problem of the parameters of the designed systems is considered as the problem of multicriterion optimization. It is proposed to choose non-dominant, optimal according to Pareto, parameters. An algorithm is built on the basis of the required and sufficient non-dominant conditions to find non-dominant solutions. This algorithm has been employed to solve the problem on a choice of optimal parameters for the counterflow shell-tube steam generator of NPP of BRGD type [ru
Optimal parameters for laser tissue soldering
McNally-Heintzelman, Karen M.; Sorg, Brian S.; Chan, Eric K.; Welch, Ashley J.; Dawes, Judith M.; Owen, Earl R.
1998-07-01
Variations in laser irradiance, exposure time, solder composition, chromophore type and concentration have led to inconsistencies in published results of laser-solder repair of tissue. To determine optimal parameters for laser tissue soldering, an in vitro study was performed using an 808-nm diode laser in conjunction with an indocyanine green (ICG)- doped albumin protein solder to weld bovine aorta specimens. Liquid and solid protein solders prepared from 25% and 60% bovine serum albumin (BSA), respectively, were compared. The effects of laser irradiance and exposure time on tensile strength of the weld and temperature rise as well as the effect of hydration on bond stability were investigated. Optimum irradiance and exposure times were identified for each solder type. Increasing the BSA concentration from 25% to 60% greatly increased the tensile strength of the weld. A reduction in dye concentration from 2.5 mg/ml to 0.25 mg/ml was also found to result in an increase in tensile strength. The strongest welds were produced with an irradiance of 6.4 W/cm2 for 50 s using a solid protein solder composed of 60% BSA and 0.25 mg/ml ICG. Steady-state solder surface temperatures were observed to reach 85 plus or minus 5 degrees Celsius with a temperature gradient across the solid protein solder strips of between 15 and 20 degrees Celsius. Finally, tensile strength was observed to decrease significantly (20 to 25%) after the first hour of hydration in phosphate-buffered saline. No appreciable change was observed in the strength of the tissue bonds with further hydration.
Energy Technology Data Exchange (ETDEWEB)
Costa, Geraldo R.M. da [Sao Paulo Univ., Sao Carlos, SP (Brazil). Escola de Engenharia
1994-12-31
This paper discusses, partially, the advantages and the disadvantages of the optimal power flow. It shows some of the difficulties of implementation and proposes solutions. An analysis is made comparing the power flow, BIGPOWER/CESP, and the optimal power flow, FPO/SEL, developed by the author, when applied to the CEPEL-ELETRONORTE and CESP systems. (author) 8 refs., 5 tabs.
PARAMETER COORDINATION AND ROBUST OPTIMIZATION FOR MULTIDISCIPLINARY DESIGN
Institute of Scientific and Technical Information of China (English)
HU Jie; PENG Yinghong; XIONG Guangleng
2006-01-01
A new parameter coordination and robust optimization approach for multidisciplinary design is presented. Firstly, the constraints network model is established to support engineering change, coordination and optimization. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. Secondly, the parameter coordination method is presented to solve the constraints network model, monitor the potential conflicts due to engineering changes, and obtain the consistency solution space corresponding to the given product specifications. Finally, the robust parameter optimization model is established, and genetic arithmetic is used to obtain the robust optimization parameter. An example of bogie design is analyzed to show the scheme to be effective.
Density-based penalty parameter optimization on C-SVM.
Liu, Yun; Lian, Jie; Bartolacci, Michael R; Zeng, Qing-An
2014-01-01
The support vector machine (SVM) is one of the most widely used approaches for data classification and regression. SVM achieves the largest distance between the positive and negative support vectors, which neglects the remote instances away from the SVM interface. In order to avoid a position change of the SVM interface as the result of an error system outlier, C-SVM was implemented to decrease the influences of the system's outliers. Traditional C-SVM holds a uniform parameter C for both positive and negative instances; however, according to the different number proportions and the data distribution, positive and negative instances should be set with different weights for the penalty parameter of the error terms. Therefore, in this paper, we propose density-based penalty parameter optimization of C-SVM. The experiential results indicated that our proposed algorithm has outstanding performance with respect to both precision and recall.
Parameter Optimization of MIMO Fuzzy Optimal Model Predictive Control By APSO
Directory of Open Access Journals (Sweden)
Adel Taieb
2017-01-01
Full Text Available This paper introduces a new development for designing a Multi-Input Multi-Output (MIMO Fuzzy Optimal Model Predictive Control (FOMPC using the Adaptive Particle Swarm Optimization (APSO algorithm. The aim of this proposed control, called FOMPC-APSO, is to develop an efficient algorithm that is able to have good performance by guaranteeing a minimal control. This is done by determining the optimal weights of the objective function. Our method is considered an optimization problem based on the APSO algorithm. The MIMO system to be controlled is modeled by a Takagi-Sugeno (TS fuzzy system whose parameters are identified using weighted recursive least squares method. The utility of the proposed controller is demonstrated by applying it to two nonlinear processes, Continuous Stirred Tank Reactor (CSTR and Tank system, where the proposed approach provides better performances compared with other methods.
Structural parameter optimization design for Halbach permanent maglev rail
International Nuclear Information System (INIS)
Guo, F.; Tang, Y.; Ren, L.; Li, J.
2010-01-01
Maglev rail is an important part of the magnetic levitation launch system. Reducing the manufacturing cost of magnetic levitation rail is the key problem for the development of magnetic levitation launch system. The Halbach permanent array has an advantage that the fundamental spatial field is cancelled on one side of the array while the field on the other side is enhanced. So this array used in the design of high temperature superconducting permanent maglev rail could improve the surface magnetic field and the levitation force. In order to make the best use of Nd-Fe-B (NdFeB) material and reduce the cost of maglev rail, the effect of the rail's structural parameters on levitation force and the utilization rate of NdFeB material are analyzed. The optimal ranges of these structural parameters are obtained. The mutual impact of these parameters is also discussed. The optimization method of these structure parameters is proposed at the end of this paper.
Structural parameter optimization design for Halbach permanent maglev rail
Energy Technology Data Exchange (ETDEWEB)
Guo, F., E-mail: guofang19830119@163.co [R and D Center of Applied Superconductivity, Huazhong University of Science and Technology, Wuhan 430074 (China); Tang, Y.; Ren, L.; Li, J. [R and D Center of Applied Superconductivity, Huazhong University of Science and Technology, Wuhan 430074 (China)
2010-11-01
Maglev rail is an important part of the magnetic levitation launch system. Reducing the manufacturing cost of magnetic levitation rail is the key problem for the development of magnetic levitation launch system. The Halbach permanent array has an advantage that the fundamental spatial field is cancelled on one side of the array while the field on the other side is enhanced. So this array used in the design of high temperature superconducting permanent maglev rail could improve the surface magnetic field and the levitation force. In order to make the best use of Nd-Fe-B (NdFeB) material and reduce the cost of maglev rail, the effect of the rail's structural parameters on levitation force and the utilization rate of NdFeB material are analyzed. The optimal ranges of these structural parameters are obtained. The mutual impact of these parameters is also discussed. The optimization method of these structure parameters is proposed at the end of this paper.
Analysis Balance Parameter of Optimal Ramp metering
Li, Y.; Duan, N.; Yang, X.
2018-05-01
Ramp metering is a motorway control method to avoid onset congestion through limiting the access of ramp inflows into the main road of the motorway. The optimization model of ramp metering is developed based upon cell transmission model (CTM). With the piecewise linear structure of CTM, the corresponding motorway traffic optimization problem can be formulated as a linear programming (LP) problem. It is known that LP problem can be solved by established solution algorithms such as SIMPLEX or interior-point methods for the global optimal solution. The commercial software (CPLEX) is adopted in this study to solve the LP problem within reasonable computational time. The concept is illustrated through a case study of the United Kingdom M25 Motorway. The optimal solution provides useful insights and guidances on how to manage motorway traffic in order to maximize the corresponding efficiency.
Optimization of regeneration and transformation parameters in ...
African Journals Online (AJOL)
PRECIOUS
transformation and regeneration therefore optimization of these two factors is .... An analysis of variance was conducted using explants types x construct ... and significant differences between means were assessed by the. Tukey's test at 1 and ...
Optimal Design of Shock Tube Experiments for Parameter Inference
Bisetti, Fabrizio; Knio, Omar
2014-01-01
We develop a Bayesian framework for the optimal experimental design of the shock tube experiments which are being carried out at the KAUST Clean Combustion Research Center. The unknown parameters are the pre-exponential parameters and the activation
Optimization of process and solution parameters in electrospinning polyethylene oxide
CSIR Research Space (South Africa)
Jacobs, V
2011-11-01
Full Text Available This paper reports the optimization of electrospinning process and solution parameters using factorial design approach to obtain uniform polyethylene oxide (PEO) nanofibers. The parameters studied were distance between nozzle and collector screen...
Parameters in pure type systems
Bloo, C.J.; Kamareddine, F.; Laan, T.D.L.; Nederpelt, R.P.; Rajsbaum, S.
2002-01-01
In this paper we study the addition of parameters to typed ¿-calculus with definitions. We show that the resulting systems have nice properties and illustrate that parameters allow for a better fine-tuning of the strength of type systems as well as staying closer to type systems used in practice in
Nanohydroxyapatite synthesis using optimized process parameters ...
Indian Academy of Sciences (India)
3Energy Research Group, School of Engineering, Taylor's University, 47500 ... influence of different ultrasonication parameters on the prop- ... to evaluate multiple process parameters and their interaction. ..... dent and dependent variables by a 3-D representation of .... The intensities of O–H functional groups are seen to.
Distributed Optimization System
Hurtado, John E.; Dohrmann, Clark R.; Robinett, III, Rush D.
2004-11-30
A search system and method for controlling multiple agents to optimize an objective using distributed sensing and cooperative control. The search agent can be one or more physical agents, such as a robot, and can be software agents for searching cyberspace. The objective can be: chemical sources, temperature sources, radiation sources, light sources, evaders, trespassers, explosive sources, time dependent sources, time independent sources, function surfaces, maximization points, minimization points, and optimal control of a system such as a communication system, an economy, a crane, and a multi-processor computer.
System floorplanning optimization
Browning, David W.
2012-12-01
Notebook and Laptop Original Equipment Manufacturers (OEMs) place great emphasis on creating unique system designs to differentiate themselves in the mobile market. These systems are developed from the \\'outside in\\' with the focus on how the system is perceived by the end-user. As a consequence, very little consideration is given to the interconnections or power of the devices within the system with a mentality of \\'just make it fit\\'. In this paper we discuss the challenges of Notebook system design and the steps by which system floor-planning tools and algorithms can be used to provide an automated method to optimize this process to ensure all required components most optimally fit inside the Notebook system. © 2012 IEEE.
System floorplanning optimization
Browning, David W.
2013-01-10
Notebook and Laptop Original Equipment Manufacturers (OEMs) place great emphasis on creating unique system designs to differentiate themselves in the mobile market. These systems are developed from the \\'outside in\\' with the focus on how the system is perceived by the end-user. As a consequence, very little consideration is given to the interconnections or power of the devices within the system with a mentality of \\'just make it fit\\'. In this paper we discuss the challenges of Notebook system design and the steps by which system floor-planning tools and algorithms can be used to provide an automated method to optimize this process to ensure all required components most optimally fit inside the Notebook system.
Nanohydroxyapatite synthesis using optimized process parameters
Indian Academy of Sciences (India)
Nanohydroxyapatite; ultrasonication; response surface methodology; calcination; ... Three independent process parameters: temperature () (70, 80 and 90°C), ... Bangi, Selangor, Malaysia; Energy Research Group, School of Engineering, ...
Hammonds, J; Price, R; Donnelly, E; Pickens, D
2012-06-01
A laboratory-based phase-contrast radiography/tomosynthesis imaging system previously (Med. Phys. Vol. 38, 2353 May 2011) for improved detection of low-contrast soft-tissue masses was used to evaluate the sensitivity for detecting the presence of thin layers of corrosion on aluminum aircraft structures. The evaluation utilized a test object of aluminum (2.5 inch × 2.5 inch × 1/8 inch) on which different geometric patterns of 0.0038 inch thick anodized aluminum oxide was deposited. A circular area of radius 1 inch centered on the phantom's midpoint was milled to an approximate thickness of 0.022 inches. The x-ray source used for this investigation was a dual focal spot, tungsten anode x-ray tube. The focal used during the investigation has a nominal size of 0.010 mm. The active area of the imager is 17.1 cm × 23.9 cm (2016 × 2816 pixels) with a pixel pitch of 0.085 mm. X-ray tube voltages ranged from 20-40 kVp and source- to-object and object-to-image distances were varied from 20-100 cm. Performance of the phase-contrast mode was compared to conventional absorption-based radiography using contrast ratio and contrast-to-noise ratios (C/N). Phase-contrast performance was based on edge-enhancement index (EEI) and the edge-enhancement-to-noise (EE/N) ratio. for absorption-based radiography, the best C/N ratio was observed at the lowest kVp value (20 kVp). The optimum sampling angle for tomosynthesis was +/- 8 degrees. Comparing C/N to EE/N demonstrated the phase-contrast techniques improve the conspicuity of the oxide layer edges. This work provides the optimal parameters that a radiographic imaging system would need to differentiate the two different compounds of aluminum. Subcontractee from Positron Systems Inc. (Boise, Idaho) through United States Air Force grant (AF083-225). © 2012 American Association of Physicists in Medicine.
Optimization of Milling Parameters Employing Desirability Functions
Ribeiro, J. L. S.; Rubio, J. C. Campos; Abrão, A. M.
2011-01-01
The principal aim of this paper is to investigate the influence of tool material (one cermet and two coated carbide grades), cutting speed and feed rate on the machinability of hardened AISI H13 hot work steel, in order to identify the cutting conditions which lead to optimal performance. A multiple response optimization procedure based on tool life, surface roughness, milling forces and the machining time (required to produce a sample cavity) was employed. The results indicated that the TiCN-TiN coated carbide and cermet presented similar results concerning the global optimum values for cutting speed and feed rate per tooth, outperforming the TiN-TiCN-Al2O3 coated carbide tool.
Parameters Optimization and Application to Glutamate Fermentation Model Using SVM
Zhang, Xiangsheng; Pan, Feng
2015-01-01
Aimed at the parameters optimization in support vector machine (SVM) for glutamate fermentation modelling, a new method is developed. It optimizes the SVM parameters via an improved particle swarm optimization (IPSO) algorithm which has better global searching ability. The algorithm includes detecting and handling the local convergence and exhibits strong ability to avoid being trapped in local minima. The material step of the method was shown. Simulation experiments demonstrate the effective...
Parameters Optimization and Application to Glutamate Fermentation Model Using SVM
Directory of Open Access Journals (Sweden)
Xiangsheng Zhang
2015-01-01
Full Text Available Aimed at the parameters optimization in support vector machine (SVM for glutamate fermentation modelling, a new method is developed. It optimizes the SVM parameters via an improved particle swarm optimization (IPSO algorithm which has better global searching ability. The algorithm includes detecting and handling the local convergence and exhibits strong ability to avoid being trapped in local minima. The material step of the method was shown. Simulation experiments demonstrate the effectiveness of the proposed algorithm.
Optimization of plasma flow parameters of the magnetoplasma compressor
International Nuclear Information System (INIS)
Dojcinovic, I P; Kuraica, M M; Obradovc, B M; Cvetanovic, N; Puric, J
2007-01-01
Optimization of the working conditions of the magnetoplasma compressor (MPC) has been performed through analysing discharge and compression plasma flow parameters in hydrogen, nitrogen and argon at different pressures. Energy conversion rate, volt-ampere curve exponent and plasma flow velocities have been studied to optimize the efficiency of energy transfer from the supply source to the plasma. It has been found that the most effective energy transfer from the supply to the plasma is in hydrogen as a working gas at 1000 Pa pressure. It was found that the accelerating regime exists for hydrogen up to 3000 Pa pressures, in nitrogen up to 2000 Pa and in argon up to 1000 Pa pressure. At higher pressures MPC in all the gases works in the decelerating regime. At pressures lower than 200 Pa, high cathode erosion is observed. MPC plasma flow parameter optimization is very important because this plasma accelerating system may be of special interest for solid surface modification and other technology applications
International Nuclear Information System (INIS)
Yamada, T; Fujii, Y; Miyamoto, N; Matsuura, T; Takao, S; Matsuzaki, Y; Koyano, H; Shirato, H; Nihongi, H; Umezawa, M; Matsuda, K; Umegaki, K
2015-01-01
Purpose: We have developed a gated spot scanning proton beam therapy system with real-time tumor-tracking. This system has the ability of multiple-gated irradiation in a single synchrotron operation cycle controlling the wait-time for consecutive gate signals during a flat-top phase so that the decrease in irradiation efficiency induced by irregular variation of gate signal is reduced. Our previous studies have shown that a 200 ms wait-time is appropriate to increase the average irradiation efficiency, but the optimal wait-time can vary patient by patient and day by day. In this research, we have developed an evaluation system of the optimal wait-time in each irradiation based on the log data of the real-time-image gated proton beam therapy (RGPT) system. Methods: The developed system consists of logger for operation of RGPT system and software for evaluation of optimal wait-time. The logger records timing of gate on/off, timing and the dose of delivered beam spots, beam energy and timing of X-ray irradiation. The evaluation software calculates irradiation time in the case of different wait-time by simulating the multiple-gated irradiation operation using several timing information. Actual data preserved in the log data are used for gate on and off time, spot irradiation time, and time moving to the next spot. Design values are used for the acceleration and deceleration times. We applied this system to a patient treated with the RGPT system. Results: The evaluation system found the optimal wait-time of 390 ms that reduced the irradiation time by about 10 %. The irradiation time with actual wait-time used in treatment was reproduced with accuracy of 0.2 ms. Conclusion: For spot scanning proton therapy system with multiple-gated irradiation in one synchrotron operation cycle, an evaluation system of the optimal wait-time in each irradiation based on log data has been developed. Funding Support: Japan Society for the Promotion of Science (JSPS) through the FIRST
Telemetry System of Biological Parameters
Directory of Open Access Journals (Sweden)
Jan Spisak
2005-01-01
Full Text Available The mobile telemetry system of biological parameters serves for reading and wireless data transfer of measured values of selected biological parameters to an outlying computer. It concerns basically long time monitoring of vital function of car pilot.The goal of this projects is to propose mobile telemetry system for reading, wireless transfer and processing of biological parameters of car pilot during physical and psychical stress. It has to be made with respect to minimal consumption, weight and maximal device mobility. This system has to eliminate signal noise, which is created by biological artifacts and disturbances during the data transfer.
System for optimizing activation measurements
International Nuclear Information System (INIS)
Antonov, V.A.
1993-01-01
Optimization procedures make it possible to perform committed activation investigations, reduce the number of experiments, make them less laborious, and increase their productivity. Separate mathematical functions were investigated for given optimization conditions, and these enable numerical optimal parameter values to be established only in the particular cases of specific techniques and mathematical computer programs. In the known mathematical models insufficient account is taken of the variety and complexity of real nuclide mixtures, the influence of background radiation, and the wide diversity of activation measurement conditions, while numerical methods for solving the optimization problem fail to reveal the laws governing the variations of the activation parameters and their functional interdependences. An optimization method was proposed in which was mainly used to estimate the time intervals for activation measurements of a mononuclide, binary or ternary nuclide mixture. However, by forming a mathematical model of activation processes it becomes possible to extend the number of nuclides in the mixture and to take account of the influence of background radiation and the diversity of the measurement alternatives. The analytical expressions and nomograms obtained can be used to determine the number of measurements, their minimum errors, their sensitivities when estimating the quantity of the tracer nuclide, the permissible quantity of interfering nuclides, the permissible background radiation intensity, and the flux of activating radiation. In the worker described herein these investigations are generalized to include spectrally resolved detection of the activation effect in the presence of the tracer and the interfering nuclides. The analytical expressions are combined into a system from which the optimal activation parameters can be found under different given conditions
Optimizing incomplete sample designs for item response model parameters
van der Linden, Willem J.
Several models for optimizing incomplete sample designs with respect to information on the item parameters are presented. The following cases are considered: (1) known ability parameters; (2) unknown ability parameters; (3) item sets with multiple ability scales; and (4) response models with
Robust Optimization for Household Load Scheduling with Uncertain Parameters
Directory of Open Access Journals (Sweden)
Jidong Wang
2018-04-01
Full Text Available Home energy management systems (HEMS face many challenges of uncertainty, which have a great impact on the scheduling of home appliances. To handle the uncertain parameters in the household load scheduling problem, this paper uses a robust optimization method to rebuild the household load scheduling model for home energy management. The model proposed in this paper can provide the complete robust schedules for customers while considering the disturbance of uncertain parameters. The complete robust schedules can not only guarantee the customers’ comfort constraints but also cooperatively schedule the electric devices for cost minimization and load shifting. Moreover, it is available for customers to obtain multiple schedules through setting different robust levels while considering the trade-off between the comfort and economy.
Optimized Evaluation System to Athletic Food Safety
Shanshan Li
2015-01-01
This study presented a new method of optimizing evaluation function in athletic food safety information programming by particle swarm optimization. The process of food information evaluation function is to automatically adjust these parameters in the evaluation function by self-optimizing method accomplished through competition, which is a food information system plays against itself with different evaluation functions. The results show that the particle swarm optimization is successfully app...
Optimizing a Water Simulation based on Wavefront Parameter Optimization
Lundgren, Martin
2017-01-01
DICE, a Swedish game company, wanted a more realistic water simulation. Currently, most large scale water simulations used in games are based upon ocean simulation technology. These techniques falter when used in other scenarios, such as coastlines. In order to produce a more realistic simulation, a new one was created based upon the water simulation technique "Wavefront Parameter Interpolation". This technique involves a rather extensive preprocess that enables ocean simulations to have inte...
Office lighting systems: Optimization
Energy Technology Data Exchange (ETDEWEB)
Dagnino, U. (ENEL, Milan (Italy))
1990-09-01
Relative to office lighting systems, in particular, those making use of tubular fluorescent lamps, currently available on the international market, this paper tries to develop lighting system, design optimization criteria. The comparative assessment of the various design possibilities considers operating cost, energy consumption, and occupational comfort/safety aspects such as lighting level uniformity and equilibrium, reduction of glare and reflection, natural/artificial lighting balance, programmed switching, computerized control systems for multi-use requirements in large areas, programmed maintenance for greater efficiency and reliability.
Optimal Selection of the Sampling Interval for Estimation of Modal Parameters by an ARMA- Model
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning
1993-01-01
Optimal selection of the sampling interval for estimation of the modal parameters by an ARMA-model for a white noise loaded structure modelled as a single degree of- freedom linear mechanical system is considered. An analytical solution for an optimal uniform sampling interval, which is optimal...
Azmi, Nur Iffah Mohamed; Arifin Mat Piah, Kamal; Yusoff, Wan Azhar Wan; Romlay, Fadhlur Rahman Mohd
2018-03-01
Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. Tuning PID control method is divided into two namely the classical methods and the methods of artificial intelligence. Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey- Taguchi Design of Experiment (DOE) method. This is done by conducting the DOE on the two PSO optimizing parameters: the particle velocity limit and the weight distribution factor. Computer simulations and physical experiments were conducted by using the proposed PSO- PID with the Variable Weight Grey-Taguchi DOE and the classical Ziegler-Nichols methods. They are implemented on the hydraulic positioning system. Simulation results show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE has reduced the rise time by 48.13% and settling time by 48.57% compared to the Ziegler-Nichols method. Furthermore, the physical experiment results also show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE tuning method responds better than Ziegler-Nichols tuning. In conclusion, this research has improved the PSO-PID parameter by applying the PSO-PID algorithm together with the Variable Weight Grey-Taguchi DOE method as a tuning method in the hydraulic positioning system.
Optimization of surface roughness parameters in dry turning
R.A. Mahdavinejad; H. Sharifi Bidgoli
2009-01-01
Purpose: The precision of machine tools on one hand and the input setup parameters on the other hand, are strongly influenced in main output machining parameters such as stock removal, toll wear ratio and surface roughnes.Design/methodology/approach: There are a lot of input parameters which are effective in the variations of these output parameters. In CNC machines, the optimization of machining process in order to predict surface roughness is very important.Findings: From this point of view...
Fučík, Ivan
2015-01-01
This thesis is focused on CRM solutions in small and medium-sized organizations with respect to the quality of their customer relationship. The main goal of this work is to design an optimal CRM solution in the environment of real organization. To achieve this goal it is necessary to understand the theoretical basis of several topics, such as organizations and their relationship with customers, CRM systems, their features and trends. On the basis of these theoretical topics it is possible to ...
International Nuclear Information System (INIS)
Bogdan, Zeljko; Cehil, Mislav
2007-01-01
Long-term gas purchase contracts usually determine delivery and payment for gas on the regular hourly basis, independently of demand side consumption. In order to use fuel gas in an economically viable way, optimization of gas distribution for covering consumption must be introduced. In this paper, a mathematical model of the electric utility system which is used for optimization of gas distribution over electric generators is presented. The utility system comprises installed capacity of 1500 MW of thermal power plants, 400 MW of combined heat and power plants, 330 MW of a nuclear power plant and 1600 MW of hydro power plants. Based on known demand curve the optimization model selects plants according to the prescribed criteria. Firstly it engages run-of-river hydro plants, then the public cogeneration plants, the nuclear plant and thermal power plants. Storage hydro plants are used for covering peak load consumption. In case of shortage of installed capacity, the cross-border purchase is allowed. Usage of dual fuel equipment (gas-oil), which is available in some thermal plants, is also controlled by the optimization procedure. It is shown that by using such a model it is possible to properly plan the amount of fuel gas which will be contracted. The contracted amount can easily be distributed over generators efficiently and without losses (no breaks in delivery). The model helps in optimizing of fuel gas-oil ratio for plants with combined burners and enables planning of power plants overhauls over a year in a viable and efficient way. (author)
Optimal parameters of the SVM for temperature prediction
Directory of Open Access Journals (Sweden)
X. Shi
2015-05-01
Full Text Available This paper established three different optimization models in order to predict the Foping station temperature value. The dimension was reduced to change multivariate climate factors into a few variables by principal component analysis (PCA. And the parameters of support vector machine (SVM were optimized with genetic algorithm (GA, particle swarm optimization (PSO and developed genetic algorithm. The most suitable method was applied for parameter optimization by comparing the results of three different models. The results are as follows: The developed genetic algorithm optimization parameters of the predicted values were closest to the measured value after the analog trend, and it is the most fitting measured value trends, and its homing speed is relatively fast.
The optimal extraction parameters and anti-diabetic activity of ...
African Journals Online (AJOL)
diabetic activity of FIBL on alloxan induced diabetic mice were studied. The optimal extraction parameters of FIBL were obtained by single factor test and orthogonal test, as follows: ethanol concentration 60 %, ratio of solvent to raw material 30 ...
Optimization of process parameters for synthesis of silica–Ni ...
Indian Academy of Sciences (India)
Optimization of process parameters for synthesis of silica–Ni nanocomposite by design of experiment ... Sol–gel; Ni; design of experiments; nanocomposites. ... Kolkata 700 032, India; Rustech Products Pvt. Ltd., Kolkata 700 045, India ...
Setting of the Optimal Parameters of Melted Glass
Czech Academy of Sciences Publication Activity Database
Luptáková, Natália; Matejíčka, L.; Krečmer, N.
2015-01-01
Roč. 10, č. 1 (2015), s. 73-79 ISSN 1802-2308 Institutional support: RVO:68081723 Keywords : Striae * Glass * Glass melting * Regression * Optimal parameters Subject RIV: JH - Ceramics, Fire-Resistant Materials and Glass
Search Parameter Optimization for Discrete, Bayesian, and Continuous Search Algorithms
2017-09-01
NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS SEARCH PARAMETER OPTIMIZATION FOR DISCRETE , BAYESIAN, AND CONTINUOUS SEARCH ALGORITHMS by...to 09-22-2017 4. TITLE AND SUBTITLE SEARCH PARAMETER OPTIMIZATION FOR DISCRETE , BAYESIAN, AND CON- TINUOUS SEARCH ALGORITHMS 5. FUNDING NUMBERS 6...simple search and rescue acts to prosecuting aerial/surface/submersible targets on mission. This research looks at varying the known discrete and
Acoustical characterization and parameter optimization of polymeric noise control materials
Homsi, Emile N.
2003-10-01
The sound transmission loss (STL) characteristics of polymer-based materials are considered. Analytical models that predict, characterize and optimize the STL of polymeric materials, with respect to physical parameters that affect performance, are developed for single layer panel configuration and adapted for layered panel construction with homogenous core. An optimum set of material parameters is selected and translated into practical applications for validation. Sound attenuating thermoplastic materials designed to be used as barrier systems in the automotive and consumer industries have certain acoustical characteristics that vary in function of the stiffness and density of the selected material. The validity and applicability of existing theory is explored, and since STL is influenced by factors such as the surface mass density of the panel's material, a method is modified to improve STL performance and optimize load-bearing attributes. An experimentally derived function is applied to the model for better correlation. In-phase and out-of-phase motion of top and bottom layers are considered. It was found that the layered construction of the co-injection type would exhibit fused planes at the interface and move in-phase. The model for the single layer case is adapted to the layered case where it would behave as a single panel. Primary physical parameters that affect STL are identified and manipulated. Theoretical analysis is linked to the resin's matrix attribute. High STL material with representative characteristics is evaluated versus standard resins. It was found that high STL could be achieved by altering materials' matrix and by integrating design solution in the low frequency range. A suggested numerical approach is described for STL evaluation of simple and complex geometries. In practice, validation on actual vehicle systems proved the adequacy of the acoustical characterization process.
On the role of modeling parameters in IMRT plan optimization
International Nuclear Information System (INIS)
Krause, Michael; Scherrer, Alexander; Thieke, Christian
2008-01-01
The formulation of optimization problems in intensity-modulated radiotherapy (IMRT) planning comprises the choice of various values such as function-specific parameters or constraint bounds. In current inverse planning programs that yield a single treatment plan for each optimization, it is often unclear how strongly these modeling parameters affect the resulting plan. This work investigates the mathematical concepts of elasticity and sensitivity to deal with this problem. An artificial planning case with a horse-shoe formed target with different opening angles surrounding a circular risk structure is studied. As evaluation functions the generalized equivalent uniform dose (EUD) and the average underdosage below and average overdosage beyond certain dose thresholds are used. A single IMRT plan is calculated for an exemplary parameter configuration. The elasticity and sensitivity of each parameter are then calculated without re-optimization, and the results are numerically verified. The results show the following. (1) elasticity can quantify the influence of a modeling parameter on the optimization result in terms of how strongly the objective function value varies under modifications of the parameter value. It also can describe how strongly the geometry of the involved planning structures affects the optimization result. (2) Based on the current parameter settings and corresponding treatment plan, sensitivity analysis can predict the optimization result for modified parameter values without re-optimization, and it can estimate the value intervals in which such predictions are valid. In conclusion, elasticity and sensitivity can provide helpful tools in inverse IMRT planning to identify the most critical parameters of an individual planning problem and to modify their values in an appropriate way
An optimization method for parameters in reactor nuclear physics
International Nuclear Information System (INIS)
Jachic, J.
1982-01-01
An optimization method for two basic problems of Reactor Physics was developed. The first is the optimization of a plutonium critical mass and the bruding ratio for fast reactors in function of the radial enrichment distribution of the fuel used as control parameter. The second is the maximization of the generation and the plutonium burnup by an optimization of power temporal distribution. (E.G.) [pt
Parameter optimization toward optimal microneedle-based dermal vaccination.
van der Maaden, Koen; Varypataki, Eleni Maria; Yu, Huixin; Romeijn, Stefan; Jiskoot, Wim; Bouwstra, Joke
2014-11-20
Microneedle-based vaccination has several advantages over vaccination by using conventional hypodermic needles. Microneedles are used to deliver a drug into the skin in a minimally-invasive and potentially pain free manner. Besides, the skin is a potent immune organ that is highly suitable for vaccination. However, there are several factors that influence the penetration ability of the skin by microneedles and the immune responses upon microneedle-based immunization. In this study we assessed several different microneedle arrays for their ability to penetrate ex vivo human skin by using trypan blue and (fluorescently or radioactively labeled) ovalbumin. Next, these different microneedles and several factors, including the dose of ovalbumin, the effect of using an impact-insertion applicator, skin location of microneedle application, and the area of microneedle application, were tested in vivo in mice. The penetration ability and the dose of ovalbumin that is delivered into the skin were shown to be dependent on the use of an applicator and on the microneedle geometry and size of the array. Besides microneedle penetration, the above described factors influenced the immune responses upon microneedle-based vaccination in vivo. It was shown that the ovalbumin-specific antibody responses upon microneedle-based vaccination could be increased up to 12-fold when an impact-insertion applicator was used, up to 8-fold when microneedles were applied over a larger surface area, and up to 36-fold dependent on the location of microneedle application. Therefore, these influencing factors should be considered to optimize microneedle-based dermal immunization technologies. Copyright © 2014 Elsevier B.V. All rights reserved.
Davison, James A
2015-01-01
To present a cause of posterior capsule aspiration and a technique using optimized parameters to prevent it from happening when operating soft cataracts. A prospective list of posterior capsule aspiration cases was kept over 4,062 consecutive cases operated with the Alcon CENTURION machine and Balanced Tip. Video analysis of one case of posterior capsule aspiration was accomplished. A surgical technique was developed using empirically derived machine parameters and customized setting-selection procedure step toolbar to reduce the pace of aspiration of soft nuclear quadrants in order to prevent capsule aspiration. Two cases out of 3,238 experienced posterior capsule aspiration before use of the soft quadrant technique. Video analysis showed an attractive vortex effect with capsule aspiration occurring in 1/5 of a second. A soft quadrant removal setting was empirically derived which had a slower pace and seemed more controlled with no capsule aspiration occurring in the subsequent 824 cases. The setting featured simultaneous linear control from zero to preset maximums for: aspiration flow, 20 mL/min; and vacuum, 400 mmHg, with the addition of torsional tip amplitude up to 20% after the fluidic maximums were achieved. A new setting selection procedure step toolbar was created to increase intraoperative flexibility by providing instantaneous shifting between the soft and normal settings. A technique incorporating a reduced pace for soft quadrant acquisition and aspiration can be accomplished through the use of a dedicated setting of integrated machine parameters. Toolbar placement of the procedure button next to the normal setting procedure button provides the opportunity to instantaneously alternate between the two settings. Simultaneous surgeon control over vacuum, aspiration flow, and torsional tip motion may make removal of soft nuclear quadrants more efficient and safer.
Optimization and optimal control in automotive systems
Kolmanovsky, Ilya; Steinbuch, Maarten; Re, Luigi
2014-01-01
This book demonstrates the use of the optimization techniques that are becoming essential to meet the increasing stringency and variety of requirements for automotive systems. It shows the reader how to move away from earlier approaches, based on some degree of heuristics, to the use of more and more common systematic methods. Even systematic methods can be developed and applied in a large number of forms so the text collects contributions from across the theory, methods and real-world automotive applications of optimization. Greater fuel economy, significant reductions in permissible emissions, new drivability requirements and the generally increasing complexity of automotive systems are among the criteria that the contributing authors set themselves to meet. In many cases multiple and often conflicting requirements give rise to multi-objective constrained optimization problems which are also considered. Some of these problems fall into the domain of the traditional multi-disciplinary optimization applie...
Investigation and validation of optimal cutting parameters for least ...
African Journals Online (AJOL)
The cutting parameters were analyzed and optimized using Box Behnken procedure in the DESIGN EXPERT environment. The effect of process parameters with the output variable were predicted which indicates that the highest cutting speed has significant role in producing least surface roughness followed by feed and ...
de Roo, Arjan; Sözer, Hasan; Aksit, Mehmet
Customers of today's complex embedded systems demand the optimization of multiple system qualities under varying operational conditions. To be able to influence the system qualities, the system must have parameters that can be adapted. Constraints may be defined on the value of these parameters.
Parameter optimization of electrochemical machining process using black hole algorithm
Singh, Dinesh; Shukla, Rajkamal
2017-12-01
Advanced machining processes are significant as higher accuracy in machined component is required in the manufacturing industries. Parameter optimization of machining processes gives optimum control to achieve the desired goals. In this paper, electrochemical machining (ECM) process is considered to evaluate the performance of the considered process using black hole algorithm (BHA). BHA considers the fundamental idea of a black hole theory and it has less operating parameters to tune. The two performance parameters, material removal rate (MRR) and overcut (OC) are considered separately to get optimum machining parameter settings using BHA. The variations of process parameters with respect to the performance parameters are reported for better and effective understanding of the considered process using single objective at a time. The results obtained using BHA are found better while compared with results of other metaheuristic algorithms, such as, genetic algorithm (GA), artificial bee colony (ABC) and bio-geography based optimization (BBO) attempted by previous researchers.
Multi-parameter optimization design of parabolic trough solar receiver
International Nuclear Information System (INIS)
Guo, Jiangfeng; Huai, Xiulan
2016-01-01
Highlights: • The optimal condition can be obtained by multi-parameter optimization. • Exergy and thermal efficiencies are employed as objective function. • Exergy efficiency increases at the expense of heat losses. • The heat obtained by working fluid increases as thermal efficiency grows. - Abstract: The design parameters of parabolic trough solar receiver are interrelated and interact with one another, so the optimal performance of solar receiver cannot be obtained by the convectional single-parameter optimization. To overcome the shortcoming of single-parameter optimization, a multi-parameter optimization of parabolic trough solar receiver is employed based on genetic algorithm in the present work. When the thermal efficiency is taken as the objective function, the heat obtained by working fluid increases while the average temperature of working fluid and wall temperatures of solar receiver decrease. The average temperature of working fluid and the wall temperatures of solar receiver increase while the heat obtained by working fluid decreases generally by taking the exergy efficiency as an objective function. Assuming that the solar radiation intensity remains constant, the exergy obtained by working fluid increases by taking exergy efficiency as the objective function, which comes at the expense of heat losses of solar receiver.
Nonlinearity Analysis and Parameters Optimization for an Inductive Angle Sensor
Directory of Open Access Journals (Sweden)
Lin Ye
2014-02-01
Full Text Available Using the finite element method (FEM and particle swarm optimization (PSO, a nonlinearity analysis based on parameter optimization is proposed to design an inductive angle sensor. Due to the structure complexity of the sensor, understanding the influences of structure parameters on the nonlinearity errors is a critical step in designing an effective sensor. Key parameters are selected for the design based on the parameters’ effects on the nonlinearity errors. The finite element method and particle swarm optimization are combined for the sensor design to get the minimal nonlinearity error. In the simulation, the nonlinearity error of the optimized sensor is 0.053% in the angle range from −60° to 60°. A prototype sensor is manufactured and measured experimentally, and the experimental nonlinearity error is 0.081% in the angle range from −60° to 60°.
Optimizing chirped laser pulse parameters for electron acceleration in vacuum
Energy Technology Data Exchange (ETDEWEB)
Akhyani, Mina; Jahangiri, Fazel; Niknam, Ali Reza; Massudi, Reza, E-mail: r-massudi@sbu.ac.ir [Laser and Plasma Research Institute, Shahid Beheshti University, Tehran 1983969411 (Iran, Islamic Republic of)
2015-11-14
Electron dynamics in the field of a chirped linearly polarized laser pulse is investigated. Variations of electron energy gain versus chirp parameter, time duration, and initial phase of laser pulse are studied. Based on maximizing laser pulse asymmetry, a numerical optimization procedure is presented, which leads to the elimination of rapid fluctuations of gain versus the chirp parameter. Instead, a smooth variation is observed that considerably reduces the accuracy required for experimentally adjusting the chirp parameter.
Bhattacharjya, Rajib Kumar
2018-05-01
The unit hydrograph and the infiltration parameters of a watershed can be obtained from observed rainfall-runoff data by using inverse optimization technique. This is a two-stage optimization problem. In the first stage, the infiltration parameters are obtained and the unit hydrograph ordinates are estimated in the second stage. In order to combine this two-stage method into a single stage one, a modified penalty parameter approach is proposed for converting the constrained optimization problem to an unconstrained one. The proposed approach is designed in such a way that the model initially obtains the infiltration parameters and then searches the optimal unit hydrograph ordinates. The optimization model is solved using Genetic Algorithms. A reduction factor is used in the penalty parameter approach so that the obtained optimal infiltration parameters are not destroyed during subsequent generation of genetic algorithms, required for searching optimal unit hydrograph ordinates. The performance of the proposed methodology is evaluated by using two example problems. The evaluation shows that the model is superior, simple in concept and also has the potential for field application.
Optimization of exposure parameters in full field digital mammography
International Nuclear Information System (INIS)
Williams, Mark B.; Raghunathan, Priya; More, Mitali J.; Seibert, J. Anthony; Kwan, Alexander; Lo, Joseph Y.; Samei, Ehsan; Ranger, Nicole T.; Fajardo, Laurie L.; McGruder, Allen; McGruder, Sandra M.; Maidment, Andrew D. A.; Yaffe, Martin J.; Bloomquist, Aili; Mawdsley, Gordon E.
2008-01-01
Optimization of exposure parameters (target, filter, and kVp) in digital mammography necessitates maximization of the image signal-to-noise ratio (SNR), while simultaneously minimizing patient dose. The goal of this study is to compare, for each of the major commercially available full field digital mammography (FFDM) systems, the impact of the selection of technique factors on image SNR and radiation dose for a range of breast thickness and tissue types. This phantom study is an update of a previous investigation and includes measurements on recent versions of two of the FFDM systems discussed in that article, as well as on three FFDM systems not available at that time. The five commercial FFDM systems tested, the Senographe 2000D from GE Healthcare, the Mammomat Novation DR from Siemens, the Selenia from Hologic, the Fischer Senoscan, and Fuji's 5000MA used with a Lorad M-IV mammography unit, are located at five different university test sites. Performance was assessed using all available x-ray target and filter combinations and nine different phantom types (three compressed thicknesses and three tissue composition types). Each phantom type was also imaged using the automatic exposure control (AEC) of each system to identify the exposure parameters used under automated image acquisition. The figure of merit (FOM) used to compare technique factors is the ratio of the square of the image SNR to the mean glandular dose. The results show that, for a given target/filter combination, in general FOM is a slowly changing function of kVp, with stronger dependence on the choice of target/filter combination. In all cases the FOM was a decreasing function of kVp at the top of the available range of kVp settings, indicating that higher tube voltages would produce no further performance improvement. For a given phantom type, the exposure parameter set resulting in the highest FOM value was system specific, depending on both the set of available target/filter combinations, and
Optimization-based particle filter for state and parameter estimation
Institute of Scientific and Technical Information of China (English)
Li Fu; Qi Fei; Shi Guangming; Zhang Li
2009-01-01
In recent years, the theory of particle filter has been developed and widely used for state and parameter estimation in nonlinear/non-Gaussian systems. Choosing good importance density is a critical issue in particle filter design. In order to improve the approximation of posterior distribution, this paper provides an optimization-based algorithm (the steepest descent method) to generate the proposal distribution and then sample particles from the distribution. This algorithm is applied in 1-D case, and the simulation results show that the proposed particle filter performs better than the extended Kalman filter (EKF), the standard particle filter (PF), the extended Kalman particle filter (PF-EKF) and the unscented particle filter (UPF) both in efficiency and in estimation precision.
Directory of Open Access Journals (Sweden)
P. Ye. Uvarov
2009-09-01
Full Text Available In the article the basic problem of substantiation of parameters of optimization model of organizationaltechnological solutions for investment-building projects in the system of project management is considered.
International Nuclear Information System (INIS)
Xu, Anlin; Wei, Kajia; Zhang, Yonghao; Han, Weiqing; Li, Jiansheng; Sun, Xiuyun; Shen, Jinyou; Wang, Lianjun
2017-01-01
Highlights: •A novel tubular cathode coated by carbon black and Fe 2 O 3 -NPs was fabricated and tested. •Effective flutriafol degradation of in dual tubular EF reactor was optimized by RSM. •Ti/RuO 2 and Ti/SnO 2 -Sb anode as oxygen provider can reach high oxygen utilization (78.8%). •The best flutriafol removal (76.5%) without circulation was gained if Ti/RuO 2 was selected as anode. •The simplest operation by the EOC process without aeration, pH and iron adjustment was obtained in the system. -- Abstract: An effective tubular membrane cathode coated by heterogeneous Fe 2 O 3 nanoparticles with carbon black (CB), combined with oxygen evolution reaction (OER), was fabricated to simplify the operation of electro-Fenton system. It was demonstrated that the cathode had a favorable suitability for this system owing to the excellent performance presented on Field emission scanning electron microscopy (FE-SEM), Transmission electron microscope (TEM), X-ray photoelectron spectroscopy (XPS) and Cyclic voltammetry (CV). An optimal condition was obtained by response surface methodology (RSM) including pH of 6.7, current density of 13.0 A m −2 , membrane flux of 82.9 L m −2 h −1 , and CB/Fe of 6.2:1. Meanwhile, we achieved an estimated degradation efficiency of flutriafol (79.6%) in optimal condition without circulation of the influent. Effects of OER on the degradation of flutriafol via Ti/RuO 2 and Ti/SnO 2 -Sb tubular anodes were further interpreted by the gas production rate and the H 2 /O 2 value. High oxygen utilization of 78.8% was acquired when Ti/RuO 2 anode served as a sufficient oxygen provider. The electrocatalytic oxygen cycle, a key loop process, was firstly interpreted in this system, which achieved a great comprehensive electrocatalytic effect with the simplest operation and had a 74.5% removal of flutriafol in the verified experiment.
APPLICATION OF GENETIC ALGORITHMS FOR ROBUST PARAMETER OPTIMIZATION
Directory of Open Access Journals (Sweden)
N. Belavendram
2010-12-01
Full Text Available Parameter optimization can be achieved by many methods such as Monte-Carlo, full, and fractional factorial designs. Genetic algorithms (GA are fairly recent in this respect but afford a novel method of parameter optimization. In GA, there is an initial pool of individuals each with its own specific phenotypic trait expressed as a ‘genetic chromosome’. Different genes enable individuals with different fitness levels to reproduce according to natural reproductive gene theory. This reproduction is established in terms of selection, crossover and mutation of reproducing genes. The resulting child generation of individuals has a better fitness level akin to natural selection, namely evolution. Populations evolve towards the fittest individuals. Such a mechanism has a parallel application in parameter optimization. Factors in a parameter design can be expressed as a genetic analogue in a pool of sub-optimal random solutions. Allowing this pool of sub-optimal solutions to evolve over several generations produces fitter generations converging to a pre-defined engineering optimum. In this paper, a genetic algorithm is used to study a seven factor non-linear equation for a Wheatstone bridge as the equation to be optimized. A comparison of the full factorial design against a GA method shows that the GA method is about 1200 times faster in finding a comparable solution.
Directory of Open Access Journals (Sweden)
Akatsuki eKimura
2015-03-01
Full Text Available Construction of quantitative models is a primary goal of quantitative biology, which aims to understand cellular and organismal phenomena in a quantitative manner. In this article, we introduce optimization procedures to search for parameters in a quantitative model that can reproduce experimental data. The aim of optimization is to minimize the sum of squared errors (SSE in a prediction or to maximize likelihood. A (local maximum of likelihood or (local minimum of the SSE can efficiently be identified using gradient approaches. Addition of a stochastic process enables us to identify the global maximum/minimum without becoming trapped in local maxima/minima. Sampling approaches take advantage of increasing computational power to test numerous sets of parameters in order to determine the optimum set. By combining Bayesian inference with gradient or sampling approaches, we can estimate both the optimum parameters and the form of the likelihood function related to the parameters. Finally, we introduce four examples of research that utilize parameter optimization to obtain biological insights from quantified data: transcriptional regulation, bacterial chemotaxis, morphogenesis, and cell cycle regulation. With practical knowledge of parameter optimization, cell and developmental biologists can develop realistic models that reproduce their observations and thus, obtain mechanistic insights into phenomena of interest.
Halyo, Nesim
1987-01-01
Some measures of eigenvalue and eigenvector sensitivity applicable to both continuous and discrete linear systems are developed and investigated. An infinite series representation is developed for the eigenvalues and eigenvectors of a system. The coefficients of the series are coupled, but can be obtained recursively using a nonlinear coupled vector difference equation. A new sensitivity measure is developed by considering the effects of unmodeled dynamics. It is shown that the sensitivity is high when any unmodeled eigenvalue is near a modeled eigenvalue. Using a simple example where the sensor dynamics have been neglected, it is shown that high feedback gains produce high eigenvalue/eigenvector sensitivity. The smallest singular value of the return difference is shown not to reflect eigenvalue sensitivity since it increases with the feedback gains. Using an upper bound obtained from the infinite series, a procedure to evaluate whether the sensitivity to parameter variations is within given acceptable bounds is developed and demonstrated by an example.
Utama, D. N.; Ani, N.; Iqbal, M. M.
2018-03-01
Optimization is a process for finding parameter (parameters) that is (are) able to deliver an optimal value for an objective function. Seeking an optimal generic model for optimizing is a computer science study that has been being practically conducted by numerous researchers. Generic model is a model that can be technically operated to solve any varieties of optimization problem. By using an object-oriented method, the generic model for optimizing was constructed. Moreover, two types of optimization method, simulated-annealing and hill-climbing, were functioned in constructing the model and compared to find the most optimal one then. The result said that both methods gave the same result for a value of objective function and the hill-climbing based model consumed the shortest running time.
Optimization and Optimal Control in Automotive Systems
Waschl, H.; Kolmanovsky, I.V.; Steinbuch, M.; Re, del L.
2014-01-01
This book demonstrates the use of the optimization techniques that are becoming essential to meet the increasing stringency and variety of requirements for automotive systems. It shows the reader how to move away from earlier approaches, based on some degree of heuristics, to the use of more and
International Nuclear Information System (INIS)
Jayalal, M.L.; Kumar, L. Satish; Jehadeesan, R.; Rajeswari, S.; Satya Murty, S.A.V.; Balasubramaniyan, V.; Chetal, S.C.
2011-01-01
Highlights: → We model design optimization of a vital reactor component using Genetic Algorithm. → Real-parameter Genetic Algorithm is used for steam condenser optimization study. → Comparison analysis done with various Genetic Algorithm related mechanisms. → The results obtained are validated with the reference study results. - Abstract: This work explores the use of Real-parameter Genetic Algorithm and analyses its performance in the steam condenser (or Circulating Water System) optimization study of a 500 MW fast breeder nuclear reactor. Choice of optimum design parameters for condenser for a power plant from among a large number of technically viable combination is a complex task. This is primarily due to the conflicting nature of the economic implications of the different system parameters for maximizing the capitalized profit. In order to find the optimum design parameters a Real-parameter Genetic Algorithm model is developed and applied. The results obtained are validated with the reference study results.
Energy Technology Data Exchange (ETDEWEB)
Jayalal, M.L., E-mail: jayalal@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Kumar, L. Satish, E-mail: satish@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Jehadeesan, R., E-mail: jeha@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Rajeswari, S., E-mail: raj@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Satya Murty, S.A.V., E-mail: satya@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Balasubramaniyan, V.; Chetal, S.C. [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India)
2011-10-15
Highlights: > We model design optimization of a vital reactor component using Genetic Algorithm. > Real-parameter Genetic Algorithm is used for steam condenser optimization study. > Comparison analysis done with various Genetic Algorithm related mechanisms. > The results obtained are validated with the reference study results. - Abstract: This work explores the use of Real-parameter Genetic Algorithm and analyses its performance in the steam condenser (or Circulating Water System) optimization study of a 500 MW fast breeder nuclear reactor. Choice of optimum design parameters for condenser for a power plant from among a large number of technically viable combination is a complex task. This is primarily due to the conflicting nature of the economic implications of the different system parameters for maximizing the capitalized profit. In order to find the optimum design parameters a Real-parameter Genetic Algorithm model is developed and applied. The results obtained are validated with the reference study results.
Parameter Optimization and Electrode Improvement of Rotary Stepper Micromotor
Sone, Junji; Mizuma, Toshinari; Mochizuki, Shunsuke; Sarajlic, Edin; Yamahata, Christophe; Fujita, Hiroyuki
We developed a three-phase electrostatic stepper micromotor and performed a numerical simulation to improve its performance for practical use and to optimize its design. We conducted its circuit simulation by simplifying its structure, and the effect of springback force generated by supported mechanism using flexures was considered. And we considered new improvement method for electrodes. This improvement and other parameter optimizations achieved the low voltage drive of micromotor.
Complicated problem solution techniques in optimal parameter searching
International Nuclear Information System (INIS)
Gergel', V.P.; Grishagin, V.A.; Rogatneva, E.A.; Strongin, R.G.; Vysotskaya, I.N.; Kukhtin, V.V.
1992-01-01
An algorithm is presented of a global search for numerical solution of multidimentional multiextremal multicriteria optimization problems with complicated constraints. A boundedness of object characteristic changes is assumed at restricted changes of its parameters (Lipschitz condition). The algorithm was realized as a computer code. The algorithm was realized as a computer code. The programme was used to solve in practice the different applied optimization problems. 10 refs.; 3 figs
National Research Council Canada - National Science Library
Best, Brad; Lovett, Marsha
2005-01-01
.... Using an optimal model of task performance subject to human constraints may be a more efficient way to develop models of skilled human performance for use in training, especially since optimal models...
Optimal Design of Shock Tube Experiments for Parameter Inference
Bisetti, Fabrizio
2014-01-06
We develop a Bayesian framework for the optimal experimental design of the shock tube experiments which are being carried out at the KAUST Clean Combustion Research Center. The unknown parameters are the pre-exponential parameters and the activation energies in the reaction rate expressions. The control parameters are the initial mixture composition and the temperature. The approach is based on first building a polynomial based surrogate model for the observables relevant to the shock tube experiments. Based on these surrogates, a novel MAP based approach is used to estimate the expected information gain in the proposed experiments, and to select the best experimental set-ups yielding the optimal expected information gains. The validity of the approach is tested using synthetic data generated by sampling the PC surrogate. We finally outline a methodology for validation using actual laboratory experiments, and extending experimental design methodology to the cases where the control parameters are noisy.
Optimization of parameters of special asynchronous electric drives
Karandey, V. Yu; Popov, B. K.; Popova, O. B.; Afanasyev, V. L.
2018-03-01
The article considers the solution of the problem of parameters optimization of special asynchronous electric drives. The solution of the problem will allow one to project and create special asynchronous electric drives for various industries. The created types of electric drives will have optimum mass-dimensional and power parameters. It will allow one to realize and fulfill the set characteristics of management of technological processes with optimum level of expenses of electric energy, time of completing the process or other set parameters. The received decision allows one not only to solve a certain optimizing problem, but also to construct dependences between the optimized parameters of special asynchronous electric drives, for example, with the change of power, current in a winding of the stator or rotor, induction in a gap or steel of magnetic conductors and other parameters. On the constructed dependences, it is possible to choose necessary optimum values of parameters of special asynchronous electric drives and their components without carrying out repeated calculations.
OPTIMIZATION OF HEMISPHERICAL RESONATOR GYROSCOPE STANDING WAVE PARAMETERS
Directory of Open Access Journals (Sweden)
Olga Sergeevna Khalyutina
2017-01-01
Full Text Available Traditionally, the problem of autonomous navigation is solved by dead reckoning navigation flight parameters (NFP of the aircraft (AC. With increasing requirements to accuracy of definition NFP improved the sensors of the prima- ry navigation information: gyroscopes and accelerometers. the gyroscopes of a new type, the so-called solid-state wave gyroscopes (SSVG are currently developed and put into practice. The work deals with the problem of increasing the accu- racy of measurements of angular velocity of the hemispherical resonator gyroscope (HRG. The reduction in the accuracy characteristics of HRG is caused by the presence of defects in the distribution of mass in the volume of its design. The syn- thesis of control system for optimal damping of the distortion parameters of the standing wave due to the influence of the mass defect resonator is adapted. The research challenge was: to examine and analytically offset the impact of the standing wave (amplitude and frequency parameters defect. Research was performed by mathematical modeling in the environment of SolidWorks Simulation for the case when the characteristics of the sensitive element of the HRG met the technological drawings of a particular type of resonator. The method of the inverse dynamics was chosen for synthesis. The research re- sults are presented in graphs the amplitude-frequency characteristics (AFC of the resonator output signal. Simulation was performed for the cases: the perfect distribution of weight; the presence of the mass defect; the presence of the mass defects are shown using the synthesized control action. Evaluating the effectiveness of the proposed control algorithm is deter- mined by the results of the resonator output signal simulation provided the perfect constructive and its performance in the presence of a mass defect in it. It is assumed that the excitation signals are standing waves in the two cases are identical in both amplitude and frequency. In this
Optimization of Nano-Process Deposition Parameters Based on Gravitational Search Algorithm
Directory of Open Access Journals (Sweden)
Norlina Mohd Sabri
2016-06-01
Full Text Available This research is focusing on the radio frequency (RF magnetron sputtering process, a physical vapor deposition technique which is widely used in thin film production. This process requires the optimized combination of deposition parameters in order to obtain the desirable thin film. The conventional method in the optimization of the deposition parameters had been reported to be costly and time consuming due to its trial and error nature. Thus, gravitational search algorithm (GSA technique had been proposed to solve this nano-process parameters optimization problem. In this research, the optimized parameter combination was expected to produce the desirable electrical and optical properties of the thin film. The performance of GSA in this research was compared with that of Particle Swarm Optimization (PSO, Genetic Algorithm (GA, Artificial Immune System (AIS and Ant Colony Optimization (ACO. Based on the overall results, the GSA optimized parameter combination had generated the best electrical and an acceptable optical properties of thin film compared to the others. This computational experiment is expected to overcome the problem of having to conduct repetitive laboratory experiments in obtaining the most optimized parameter combination. Based on this initial experiment, the adaptation of GSA into this problem could offer a more efficient and productive way of depositing quality thin film in the fabrication process.
Comparisons of criteria in the assessment model parameter optimizations
International Nuclear Information System (INIS)
Liu Xinhe; Zhang Yongxing
1993-01-01
Three criteria (chi square, relative chi square and correlation coefficient) used in model parameter optimization (MPO) process that aims at significant reduction of prediction uncertainties were discussed and compared to each other with the aid of a well-controlled tracer experiment
Statistical optimization of process parameters for the production of ...
African Journals Online (AJOL)
In this study, optimization of process parameters such as moisture content, incubation temperature and initial pH (fixed) for the improvement of citric acid production from oil palm empty fruit bunches through solid state bioconversion was carried out using traditional one-factor-at-a-time (OFAT) method and response surface ...
Optimization of physico-chemical and nutritional parameters for ...
African Journals Online (AJOL)
Optimization of physico-chemical and nutritional parameters for pullulan production by a mutant of thermotolerant Aureobasidium pullulans, in fed batch ... minutes, having killing rate of 70% level, produced 6 g l-1 higher pullulan as compared to the wild type without loosing thermotolerant and non-melanin producing ability.
Optimization of machining parameters of hard porcelain on a CNC ...
African Journals Online (AJOL)
Optimization of machining parameters of hard porcelain on a CNC machine by Taguchi-and RSM method. ... Journal Home > Vol 10, No 1 (2018) > ... The conduct of experiments was made by employing the Taguchi's L27 Orthogonal array to ...
Optimization of CNC end milling process parameters using PCA ...
African Journals Online (AJOL)
Optimization of CNC end milling process parameters using PCA-based Taguchi method. ... International Journal of Engineering, Science and Technology ... To meet the basic assumption of Taguchi method; in the present work, individual response correlations have been eliminated first by means of Principal Component ...
Brodusch, Nicolas; Demers, Hendrix; Trudeau, Michel; Gauvin, Raynald
2013-01-01
Transmission electron forward scatter diffraction (t-EFSD) is a new technique providing crystallographic information with high resolution on thin specimens by using a conventional electron backscatter diffraction (EBSD) system in a scanning electron microscope. In this study, the impact of tilt angle, working distance, and detector distance on the Kikuchi pattern quality were investigated in a cold-field emission scanning electron microscope (CFE-SEM). We demonstrated that t-EFSD is applicable for tilt angles ranging from -20° to -40°. Working distance (WD) should be optimized for each material by choosing the WD for which the EBSD camera screen illumination is the highest, as the number of detected electrons on the screen is directly dependent on the scattering angle. To take advantage of the best performances of the CFE-SEM, the EBSD camera should be close to the sample and oriented towards the bottom to increase forward scattered electron collection efficiency. However, specimen chamber cluttering and beam/mechanical drift are important limitations in the CFE-SEM used in this work. Finally, the importance of t-EFSD in materials science characterization was illustrated through three examples of phase identification and orientation mapping. © Wiley Periodicals, Inc.
Parameter assessment for virtual Stackelberg game in aerodynamic shape optimization
Wang, Jing; Xie, Fangfang; Zheng, Yao; Zhang, Jifa
2018-05-01
In this paper, parametric studies of virtual Stackelberg game (VSG) are conducted to assess the impact of critical parameters on aerodynamic shape optimization, including design cycle, split of design variables and role assignment. Typical numerical cases, including the inverse design and drag reduction design of airfoil, have been carried out. The numerical results confirm the effectiveness and efficiency of VSG. Furthermore, the most significant parameters are identified, e.g. the increase of design cycle can improve the optimization results but it will also add computational burden. These studies will maximize the productivity of the effort in aerodynamic optimization for more complicated engineering problems, such as the multi-element airfoil and wing-body configurations.
Network optimization including gas lift and network parameters under subsurface uncertainty
Energy Technology Data Exchange (ETDEWEB)
Schulze-Riegert, R.; Baffoe, J.; Pajonk, O. [SPT Group GmbH, Hamburg (Germany); Badalov, H.; Huseynov, S. [Technische Univ. Clausthal, Clausthal-Zellerfeld (Germany). ITE; Trick, M. [SPT Group, Calgary, AB (Canada)
2013-08-01
Optimization of oil and gas field production systems poses a great challenge to field development due to complex and multiple interactions between various operational design parameters and subsurface uncertainties. Conventional analytical methods are capable of finding local optima based on single deterministic models. They are less applicable for efficiently generating alternative design scenarios in a multi-objective context. Practical implementations of robust optimization workflows integrate the evaluation of alternative design scenarios and multiple realizations of subsurface uncertainty descriptions. Production or economic performance indicators such as NPV (Net Present Value) are linked to a risk-weighted objective function definition to guide the optimization processes. This work focuses on an integrated workflow using a reservoir-network simulator coupled to an optimization framework. The work will investigate the impact of design parameters while considering the physics of the reservoir, wells, and surface facilities. Subsurface uncertainties are described by well parameters such as inflow performance. Experimental design methods are used to investigate parameter sensitivities and interactions. Optimization methods are used to find optimal design parameter combinations which improve key performance indicators of the production network system. The proposed workflow will be applied to a representative oil reservoir coupled to a network which is modelled by an integrated reservoir-network simulator. Gas-lift will be included as an explicit measure to improve production. An objective function will be formulated for the net present value of the integrated system including production revenue and facility costs. Facility and gas lift design parameters are tuned to maximize NPV. Well inflow performance uncertainties are introduced with an impact on gas lift performance. Resulting variances on NPV are identified as a risk measure for the optimized system design. A
On the effect of response transformations in sequential parameter optimization.
Wagner, Tobias; Wessing, Simon
2012-01-01
Parameter tuning of evolutionary algorithms (EAs) is attracting more and more interest. In particular, the sequential parameter optimization (SPO) framework for the model-assisted tuning of stochastic optimizers has resulted in established parameter tuning algorithms. In this paper, we enhance the SPO framework by introducing transformation steps before the response aggregation and before the actual modeling. Based on design-of-experiments techniques, we empirically analyze the effect of integrating different transformations. We show that in particular, a rank transformation of the responses provides significant improvements. A deeper analysis of the resulting models and additional experiments with adaptive procedures indicates that the rank and the Box-Cox transformation are able to improve the properties of the resultant distributions with respect to symmetry and normality of the residuals. Moreover, model-based effect plots document a higher discriminatory power obtained by the rank transformation.
Topology optimized permanent magnet systems
Bjørk, R.; Bahl, C. R. H.; Insinga, A. R.
2017-09-01
Topology optimization of permanent magnet systems consisting of permanent magnets, high permeability iron and air is presented. An implementation of topology optimization for magnetostatics is discussed and three examples are considered. The Halbach cylinder is topology optimized with iron and an increase of 15% in magnetic efficiency is shown. A topology optimized structure to concentrate a homogeneous field is shown to increase the magnitude of the field by 111%. Finally, a permanent magnet with alternating high and low field regions is topology optimized and a Λcool figure of merit of 0.472 is reached, which is an increase of 100% compared to a previous optimized design.
International Nuclear Information System (INIS)
Shishov, S.
1990-01-01
The model proposed helps to ground the quantitative evaluation of the maintenance parameters of the electrical equipment of the coal mine. In the process of simulation an assumption is made that no additional capital investments are needed - only the existing situation of the electric supply system is considered and the effect of the measures taken to increase its reliability. The model takes into account the annual operating expenses, the downtime costs, the power not supplied to the user due to breakdowns, the average total outage duration; the breakdowns intensity, the average time for serviceability restoration. The model is based on the statistical data from the equipment operation for a period of 3 years, as well as on the economical standards acting in this mine. The outage expenses calculations of two units of the Bobov Dol mine are presented as an illustrative example of the model testing. The model is realized as a software product written on PL-1. It can also simulate the effect of the personnel number as well as the annual reserves of spare parts of various equipment's makes. 2 tabs, 6 refs
International Nuclear Information System (INIS)
McQuaid, Sarah J; Southekal, Sudeepti; Kijewski, Marie Foley; Moore, Stephen C
2011-01-01
Obtaining the best possible task performance using reconstructed SPECT images requires optimization of both the collimator and reconstruction parameters. The goal of this study is to determine how to perform this optimization, namely whether the collimator parameters can be optimized solely from projection data, or whether reconstruction parameters should also be considered. In order to answer this question, and to determine the optimal collimation, a digital phantom representing a human torso with 16 mm diameter hot lesions (activity ratio 8:1) was generated and used to simulate clinical SPECT studies with parallel-hole collimation. Two approaches to optimizing the SPECT system were then compared in a lesion quantification task: sequential optimization, where collimation was optimized on projection data using the Cramer–Rao bound, and joint optimization, which simultaneously optimized collimator and reconstruction parameters. For every condition, quantification performance in reconstructed images was evaluated using the root-mean-squared-error of 400 estimates of lesion activity. Compared to the joint-optimization approach, the sequential-optimization approach favoured a poorer resolution collimator, which, under some conditions, resulted in sub-optimal estimation performance. This implies that inclusion of the reconstruction parameters in the optimization procedure is important in obtaining the best possible task performance; in this study, this was achieved with a collimator resolution similar to that of a general-purpose (LEGP) collimator. This collimator was found to outperform the more commonly used high-resolution (LEHR) collimator, in agreement with other task-based studies, using both quantification and detection tasks.
Optimal Control of Mechanical Systems
Directory of Open Access Journals (Sweden)
Vadim Azhmyakov
2007-01-01
Full Text Available In the present work, we consider a class of nonlinear optimal control problems, which can be called “optimal control problems in mechanics.” We deal with control systems whose dynamics can be described by a system of Euler-Lagrange or Hamilton equations. Using the variational structure of the solution of the corresponding boundary-value problems, we reduce the initial optimal control problem to an auxiliary problem of multiobjective programming. This technique makes it possible to apply some consistent numerical approximations of a multiobjective optimization problem to the initial optimal control problem. For solving the auxiliary problem, we propose an implementable numerical algorithm.
Optimization of virtual source parameters in neutron scattering instrumentation
International Nuclear Information System (INIS)
Habicht, K; Skoulatos, M
2012-01-01
We report on phase-space optimizations for neutron scattering instruments employing horizontal focussing crystal optics. Defining a figure of merit for a generic virtual source configuration we identify a set of optimum instrumental parameters. In order to assess the quality of the instrumental configuration we combine an evolutionary optimization algorithm with the analytical Popovici description using multidimensional Gaussian distributions. The optimum phase-space element which needs to be delivered to the virtual source by preceding neutron optics may be obtained using the same algorithm which is of general interest in instrument design.
Network synthesis and parameter optimization for vehicle suspension with inerter
Directory of Open Access Journals (Sweden)
Long Chen
2016-12-01
Full Text Available In order to design a comfortable-oriented vehicle suspension structure, the network synthesis method was utilized to transfer the problem into solving a timing robust control problem and determine the structure of “inerter–spring–damper” suspension. Bilinear Matrix Inequality was utilized to obtain the timing transfer function. Then, the transfer function of suspension system can be physically implemented by passive elements such as spring, damper, and inerter. By analyzing the sensitivity and quantum genetic algorithm, the optimized parameters of inerter–spring–damper suspension were determined. A quarter-car model was established. The performance of the inerter–spring–damper suspension was verified under random input. The simulation results manifested that the dynamic performance of the proposed suspension was enhanced in contrast with traditional suspension. The root mean square of vehicle body acceleration decreases by 18.9%. The inerter–spring–damper suspension can inhibit the vertical vibration within the frequency of 1–3 Hz effectively and enhance the performance of ride comfort significantly.
Beyond bixels: Generalizing the optimization parameters for intensity modulated radiation therapy
International Nuclear Information System (INIS)
Markman, Jerry; Low, Daniel A.; Beavis, Andrew W.; Deasy, Joseph O.
2002-01-01
Intensity modulated radiation therapy (IMRT) treatment planning systems optimize fluence distributions by subdividing the fluence distribution into rectangular bixels. The algorithms typically optimize the fluence intensity directly, often leading to fluence distributions with sharp discontinuities. These discontinuities may yield difficulties in delivery of the fluence distribution, leading to inaccurate dose delivery. We have developed a method for decoupling the bixel intensities from the optimization parameters; either by introducing optimization control points from which the bixel intensities are interpolated or by parametrizing the fluence distribution using basis functions. In either case, the number of optimization search parameters is reduced from the direct bixel optimization method. To illustrate the concept, the technique is applied to two-dimensional idealized head and neck treatment plans. The interpolation algorithms investigated were nearest-neighbor, linear and cubic spline, and radial basis functions serve as the basis function test. The interpolation and basis function optimization techniques were compared against the direct bixel calculation. The number of optimization parameters were significantly reduced relative to the bixel optimization, and this was evident in the reduction of computation time of as much as 58% from the full bixel optimization. The dose distributions obtained using the reduced optimization parameter sets were very similar to the full bixel optimization when examined by dose distributions, statistics, and dose-volume histograms. To evaluate the sensitivity of the fluence calculations to spatial misalignment caused either by delivery errors or patient motion, the doses were recomputed with a 1 mm shift in each beam and compared to the unshifted distributions. Except for the nearest-neighbor algorithm, the reduced optimization parameter dose distributions were generally less sensitive to spatial shifts than the bixel
Energy Technology Data Exchange (ETDEWEB)
Man, Jun [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Zhang, Jiangjiang [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Li, Weixuan [Pacific Northwest National Laboratory, Richland Washington USA; Zeng, Lingzao [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Wu, Laosheng [Department of Environmental Sciences, University of California, Riverside California USA
2016-10-01
The ensemble Kalman filter (EnKF) has been widely used in parameter estimation for hydrological models. The focus of most previous studies was to develop more efficient analysis (estimation) algorithms. On the other hand, it is intuitively understandable that a well-designed sampling (data-collection) strategy should provide more informative measurements and subsequently improve the parameter estimation. In this work, a Sequential Ensemble-based Optimal Design (SEOD) method, coupled with EnKF, information theory and sequential optimal design, is proposed to improve the performance of parameter estimation. Based on the first-order and second-order statistics, different information metrics including the Shannon entropy difference (SD), degrees of freedom for signal (DFS) and relative entropy (RE) are used to design the optimal sampling strategy, respectively. The effectiveness of the proposed method is illustrated by synthetic one-dimensional and two-dimensional unsaturated flow case studies. It is shown that the designed sampling strategies can provide more accurate parameter estimation and state prediction compared with conventional sampling strategies. Optimal sampling designs based on various information metrics perform similarly in our cases. The effect of ensemble size on the optimal design is also investigated. Overall, larger ensemble size improves the parameter estimation and convergence of optimal sampling strategy. Although the proposed method is applied to unsaturated flow problems in this study, it can be equally applied in any other hydrological problems.
Optimization of reserve lithium thionyl chloride battery electrochemical design parameters
Energy Technology Data Exchange (ETDEWEB)
Doddapaneni, N.; Godshall, N.A.
1987-01-01
The performance of Reserve Lithium Thionyl Chloride (RLTC) batteries was optimized by conducting a parametric study of seven electrochemical parameters: electrode compression, carbon thickness, presence of catalyst, temperature, electrode limitation, discharge rate, and electrolyte acidity. Increasing electrode compression (from 0 to 15%) improved battery performance significantly (10% greater carbon capacity density). Although thinner carbon cathodes yielded less absolute capacity than did thicker cathodes, they did so with considerably higher volume efficiencies. The effect of these parameters, and their synergistic interactions, on electrochemical cell peformance is illustrated. 5 refs., 9 figs., 3 tabs.
Optimization of reserve lithium thionyl chloride battery electrochemical design parameters
Doddapaneni, N.; Godshall, N. A.
The performance of Reserve Lithium Thionyl Chloride (RLTC) batteries was optimized by conducting a parametric study of seven electrochemical parameters: electrode compression, carbon thickness, presence of catalyst, temperature, electrode limitation, discharge rate, and electrolyte acidity. Increasing electrode compression (from 0 to 15 percent) improved battery performance significantly (10 percent greater carbon capacity density). Although thinner carbon cathodes yielded less absolute capacity than did thicker cathodes, they did so with considerably higher volume efficiencies. The effect of these parameters, and their synergistic interactions, on electrochemical cell performance is illustrated.
Directory of Open Access Journals (Sweden)
Bin He
2014-01-01
Full Text Available In city traffic, it is important to improve transportation efficiency and the spacing of platoon should be shortened when crossing the street. The best method to deal with this problem is automatic control of vehicles. In this paper, a mathematical model is established for the platoon’s longitudinal movement. A systematic analysis of longitudinal control law is presented for the platoon of vehicles. However, the parameter calibration for the platoon model is relatively difficult because the platoon model is complex and the parameters are coupled with each other. In this paper, the particle swarm optimization method is introduced to effectively optimize the parameters of platoon. The proposed method effectively finds the optimal parameters based on simulations and makes the spacing of platoon shorter.
Topology optimized permanent magnet systems
DEFF Research Database (Denmark)
Bjørk, Rasmus; Bahl, Christian; Insinga, Andrea Roberto
2017-01-01
Topology optimization of permanent magnet systems consisting of permanent magnets, high permeability iron and air is presented. An implementation of topology optimization for magnetostatics is discussed and three examples are considered. The Halbach cylinder is topology optimized with iron...... and an increase of 15% in magnetic efficiency is shown. A topology optimized structure to concentrate a homogeneous field is shown to increase the magnitude of the field by 111%. Finally, a permanent magnet with alternating high and low field regions is topology optimized and a ΛcoolΛcool figure of merit of 0...
Optimization of power system operation
Zhu, Jizhong
2015-01-01
This book applies the latest applications of new technologies topower system operation and analysis, including new and importantareas that are not covered in the previous edition. Optimization of Power System Operation covers both traditional andmodern technologies, including power flow analysis, steady-statesecurity region analysis, security constrained economic dispatch,multi-area system economic dispatch, unit commitment, optimal powerflow, smart grid operation, optimal load shed, optimalreconfiguration of distribution network, power system uncertaintyanalysis, power system sensitivity analysis, analytic hierarchicalprocess, neural network, fuzzy theory, genetic algorithm,evolutionary programming, and particle swarm optimization, amongothers. New topics such as the wheeling model, multi-areawheeling, the total transfer capability computation in multipleareas, are also addressed. The new edition of this book continues to provide engineers andac demics with a complete picture of the optimization of techn...
PARAMETER ESTIMATION OF VALVE STICTION USING ANT COLONY OPTIMIZATION
Directory of Open Access Journals (Sweden)
S. Kalaivani
2012-07-01
Full Text Available In this paper, a procedure for quantifying valve stiction in control loops based on ant colony optimization has been proposed. Pneumatic control valves are widely used in the process industry. The control valve contains non-linearities such as stiction, backlash, and deadband that in turn cause oscillations in the process output. Stiction is one of the long-standing problems and it is the most severe problem in the control valves. Thus the measurement data from an oscillating control loop can be used as a possible diagnostic signal to provide an estimate of the stiction magnitude. Quantification of control valve stiction is still a challenging issue. Prior to doing stiction detection and quantification, it is necessary to choose a suitable model structure to describe control-valve stiction. To understand the stiction phenomenon, the Stenman model is used. Ant Colony Optimization (ACO, an intelligent swarm algorithm, proves effective in various fields. The ACO algorithm is inspired from the natural trail following behaviour of ants. The parameters of the Stenman model are estimated using ant colony optimization, from the input-output data by minimizing the error between the actual stiction model output and the simulated stiction model output. Using ant colony optimization, Stenman model with known nonlinear structure and unknown parameters can be estimated.
Standardless quantification by parameter optimization in electron probe microanalysis
International Nuclear Information System (INIS)
Limandri, Silvina P.; Bonetto, Rita D.; Josa, Víctor Galván; Carreras, Alejo C.; Trincavelli, Jorge C.
2012-01-01
A method for standardless quantification by parameter optimization in electron probe microanalysis is presented. The method consists in minimizing the quadratic differences between an experimental spectrum and an analytical function proposed to describe it, by optimizing the parameters involved in the analytical prediction. This algorithm, implemented in the software POEMA (Parameter Optimization in Electron Probe Microanalysis), allows the determination of the elemental concentrations, along with their uncertainties. The method was tested in a set of 159 elemental constituents corresponding to 36 spectra of standards (mostly minerals) that include trace elements. The results were compared with those obtained with the commercial software GENESIS Spectrum® for standardless quantification. The quantifications performed with the method proposed here are better in the 74% of the cases studied. In addition, the performance of the method proposed is compared with the first principles standardless analysis procedure DTSA for a different data set, which excludes trace elements. The relative deviations with respect to the nominal concentrations are lower than 0.04, 0.08 and 0.35 for the 66% of the cases for POEMA, GENESIS and DTSA, respectively. - Highlights: ► A method for standardless quantification in EPMA is presented. ► It gives better results than the commercial software GENESIS Spectrum. ► It gives better results than the software DTSA. ► It allows the determination of the conductive coating thickness. ► It gives an estimation for the concentration uncertainties.
Optimal construction parameters of electrosprayed trilayer organic photovoltaic devices
International Nuclear Information System (INIS)
Shah, S K; Ali, M; Gunnella, R; Abbas, M; Hirsch, L
2014-01-01
A detailed investigation of the optimal set of parameters employed in multilayer device fabrication obtained through successive electrospray deposited layers is reported. In this scheme, the donor/acceptor (D/A) bulk heterojunction layer is sandwiched between two thin stacked layers of individual donor and acceptor materials. The stacked layers geometry with optimal thicknesses plays a decisive role in improving operation characteristics. Among the parameters of the multilayer organic photovoltaics device, the D/A concentration ratio, blend thickness and stacking layers thicknesses are optimized. Other parameters, such as thermal annealing and the role of top metal contacts, are also discussed. Internal photon to current efficiency is found to attain a strong response in the 500 nm optical region for the most efficient device architectures. Such an observation indicates a clear interplay between photon harvesting of active layers and transport by ancillary stacking layers, opening up the possibility to engineer both the material fine structure and the device architecture to obtain the best photovoltaic response from a complex organic heterostructure. (paper)
Optimizing queries in distributed systems
Directory of Open Access Journals (Sweden)
Ion LUNGU
2006-01-01
Full Text Available This research presents the main elements of query optimizations in distributed systems. First, data architecture according with system level architecture in a distributed environment is presented. Then the architecture of a distributed database management system (DDBMS is described on conceptual level followed by the presentation of the distributed query execution steps on these information systems. The research ends with presentation of some aspects of distributed database query optimization and strategies used for that.
Real-time parameter optimization based on neural network for smart injection molding
Lee, H.; Liau, Y.; Ryu, K.
2018-03-01
The manufacturing industry has been facing several challenges, including sustainability, performance and quality of production. Manufacturers attempt to enhance the competitiveness of companies by implementing CPS (Cyber-Physical Systems) through the convergence of IoT(Internet of Things) and ICT(Information & Communication Technology) in the manufacturing process level. Injection molding process has a short cycle time and high productivity. This features have been making it suitable for mass production. In addition, this process is used to produce precise parts in various industry fields such as automobiles, optics and medical devices. Injection molding process has a mixture of discrete and continuous variables. In order to optimized the quality, variables that is generated in the injection molding process must be considered. Furthermore, Optimal parameter setting is time-consuming work to predict the optimum quality of the product. Since the process parameter cannot be easily corrected during the process execution. In this research, we propose a neural network based real-time process parameter optimization methodology that sets optimal process parameters by using mold data, molding machine data, and response data. This paper is expected to have academic contribution as a novel study of parameter optimization during production compare with pre - production parameter optimization in typical studies.
Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology
Directory of Open Access Journals (Sweden)
Rupert Faltermeier
2015-01-01
Full Text Available Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP and intracranial pressure (ICP. Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP, with the outcome of the patients represented by the Glasgow Outcome Scale (GOS. For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.
Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology.
Faltermeier, Rupert; Proescholdt, Martin A; Bele, Sylvia; Brawanski, Alexander
2015-01-01
Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.
Robustness of dynamic systems with parameter uncertainties
Balemi, S; Truöl, W
1992-01-01
Robust Control is one of the fastest growing and promising areas of research today. In many practical systems there exist uncertainties which have to be considered in the analysis and design of control systems. In the last decade methods were developed for dealing with dynamic systems with unstructured uncertainties such as HOO_ and £I-optimal control. For systems with parameter uncertainties, the seminal paper of V. L. Kharitonov has triggered a large amount of very promising research. An international workshop dealing with all aspects of robust control was successfully organized by S. P. Bhattacharyya and L. H. Keel in San Antonio, Texas, USA in March 1991. We organized the second international workshop in this area in Ascona, Switzer land in April 1992. However, this second workshop was restricted to robust control of dynamic systems with parameter uncertainties with the objective to concentrate on some aspects of robust control. This book contains a collection of papers presented at the International W...
System floorplanning optimization
Browning, David W.; Elansary, Ayman; Shalaby, Mohamed
2012-01-01
Notebook and Laptop Original Equipment Manufacturers (OEMs) place great emphasis on creating unique system designs to differentiate themselves in the mobile market. These systems are developed from the 'outside in' with the focus on how the system
System floorplanning optimization
Browning, David W.; Ansary, Ayman M. El; Shalaby, Mohamed
2013-01-01
Notebook and Laptop Original Equipment Manufacturers (OEMs) place great emphasis on creating unique system designs to differentiate themselves in the mobile market. These systems are developed from the 'outside in' with the focus on how the system
An Optimal Lower Eigenvalue System
Directory of Open Access Journals (Sweden)
Yingfan Liu
2011-01-01
Full Text Available An optimal lower eigenvalue system is studied, and main theorems including a series of necessary and suffcient conditions concerning existence and a Lipschitz continuity result concerning stability are obtained. As applications, solvability results to some von-Neumann-type input-output inequalities, growth, and optimal growth factors, as well as Leontief-type balanced and optimal balanced growth paths, are also gotten.
Oyster Creek cycle 10 nodal model parameter optimization study using PSMS
International Nuclear Information System (INIS)
Dougher, J.D.
1987-01-01
The power shape monitoring system (PSMS) is an on-line core monitoring system that uses a three-dimensional nodal code (NODE-B) to perform nodal power calculations and compute thermal margins. The PSMS contains a parameter optimization function that improves the ability of NODE-B to accurately monitor core power distributions. This functions iterates on the model normalization parameters (albedos and mixing factors) to obtain the best agreement between predicted and measured traversing in-core probe (TIP) reading on a statepoint-by-statepoint basis. Following several statepoint optimization runs, an average set of optimized normalization parameters can be determined and can be implemented into the current or subsequent cycle core model for on-line core monitoring. A statistical analysis of 19 high-power steady-state state-points throughout Oyster Creek cycle 10 operation has shown a consistently poor virgin model performance. The normalization parameters used in the cycle 10 NODE-B model were based on a cycle 8 study, which evaluated only Exxon fuel types. The introduction of General Electric (GE) fuel into cycle 10 (172 assemblies) was a significant fuel/core design change that could have altered the optimum set of normalization parameters. Based on the need to evaluate a potential change in the model normalization parameters for cycle 11 and in an attempt to account for the poor cycle 10 model performance, a parameter optimization study was performed
Xu, Quan-Li; Cao, Yu-Wei; Yang, Kun
2018-03-01
Ant Colony Optimization (ACO) is the most widely used artificial intelligence algorithm at present. This study introduced the principle and mathematical model of ACO algorithm in solving Vehicle Routing Problem (VRP), and designed a vehicle routing optimization model based on ACO, then the vehicle routing optimization simulation system was developed by using c ++ programming language, and the sensitivity analyses, estimations and improvements of the three key parameters of ACO were carried out. The results indicated that the ACO algorithm designed in this paper can efficiently solve rational planning and optimization of VRP, and the different values of the key parameters have significant influence on the performance and optimization effects of the algorithm, and the improved algorithm is not easy to locally converge prematurely and has good robustness.
Directory of Open Access Journals (Sweden)
Damilola Isaac Adebiyi
2016-06-01
Full Text Available The cold spray coating process involves many process parameters which make the process very complex, and highly dependent and sensitive to small changes in these parameters. This results in a small operational window of the parameters. Consequently, mathematical optimization of the process parameters is key, not only to achieving deposition but also improving the coating quality. This study focuses on the mathematical identification and experimental justification of the optimum process parameters for cold spray coating of titanium alloy with silicon carbide (SiC. The continuity, momentum and the energy equations governing the flow through the low-pressure cold spray nozzle were solved by introducing a constitutive equation to close the system. This was used to calculate the critical velocity for the deposition of SiC. In order to determine the input temperature that yields the calculated velocity, the distribution of velocity, temperature, and pressure in the cold spray nozzle were analyzed, and the exit values were predicted using the meshing tool of Solidworks. Coatings fabricated using the optimized parameters and some non-optimized parameters are compared. The coating of the CFD-optimized parameters yielded lower porosity and higher hardness.
Optimal correction and design parameter search by modern methods of rigorous global optimization
International Nuclear Information System (INIS)
Makino, K.; Berz, M.
2011-01-01
Frequently the design of schemes for correction of aberrations or the determination of possible operating ranges for beamlines and cells in synchrotrons exhibit multitudes of possibilities for their correction, usually appearing in disconnected regions of parameter space which cannot be directly qualified by analytical means. In such cases, frequently an abundance of optimization runs are carried out, each of which determines a local minimum depending on the specific chosen initial conditions. Practical solutions are then obtained through an often extended interplay of experienced manual adjustment of certain suitable parameters and local searches by varying other parameters. However, in a formal sense this problem can be viewed as a global optimization problem, i.e. the determination of all solutions within a certain range of parameters that lead to a specific optimum. For example, it may be of interest to find all possible settings of multiple quadrupoles that can achieve imaging; or to find ahead of time all possible settings that achieve a particular tune; or to find all possible manners to adjust nonlinear parameters to achieve correction of high order aberrations. These tasks can easily be phrased in terms of such an optimization problem; but while mathematically this formulation is often straightforward, it has been common belief that it is of limited practical value since the resulting optimization problem cannot usually be solved. However, recent significant advances in modern methods of rigorous global optimization make these methods feasible for optics design for the first time. The key ideas of the method lie in an interplay of rigorous local underestimators of the objective functions, and by using the underestimators to rigorously iteratively eliminate regions that lie above already known upper bounds of the minima, in what is commonly known as a branch-and-bound approach. Recent enhancements of the Differential Algebraic methods used in particle
Combustion Model and Control Parameter Optimization Methods for Single Cylinder Diesel Engine
Directory of Open Access Journals (Sweden)
Bambang Wahono
2014-01-01
Full Text Available This research presents a method to construct a combustion model and a method to optimize some control parameters of diesel engine in order to develop a model-based control system. The construction purpose of the model is to appropriately manage some control parameters to obtain the values of fuel consumption and emission as the engine output objectives. Stepwise method considering multicollinearity was applied to construct combustion model with the polynomial model. Using the experimental data of a single cylinder diesel engine, the model of power, BSFC, NOx, and soot on multiple injection diesel engines was built. The proposed method succesfully developed the model that describes control parameters in relation to the engine outputs. Although many control devices can be mounted to diesel engine, optimization technique is required to utilize this method in finding optimal engine operating conditions efficiently beside the existing development of individual emission control methods. Particle swarm optimization (PSO was used to calculate control parameters to optimize fuel consumption and emission based on the model. The proposed method is able to calculate control parameters efficiently to optimize evaluation item based on the model. Finally, the model which added PSO then was compiled in a microcontroller.
Optimization of geometric parameters of heat exchange pipes pin finning
Akulov, K. A.; Golik, V. V.; Voronin, K. S.; Zakirzakov, A. G.
2018-05-01
The work is devoted to optimization of geometric parameters of the pin finning of heat-exchanging pipes. Pin fins were considered from the point of view of mechanics of a deformed solid body as overhang beams with a uniformly distributed load. It was found out under what geometric parameters of the nib (diameter and length); the stresses in it from the influence of the washer fluid will not exceed the yield strength of the material (aluminum). Optimal values of the geometric parameters of nibs were obtained for different velocities of the medium washed by them. As a flow medium, water and air were chosen, and the cross section of the nibs was round and square. Pin finning turned out to be more than 3 times more compact than circumferential finning, so its use makes it possible to increase the number of fins per meter of the heat-exchanging pipe. And it is well-known that this is the main method for increasing the heat transfer of a convective surface, giving them an indisputable advantage.
Optimization of vibratory welding process parameters using response surface methodology
Energy Technology Data Exchange (ETDEWEB)
Singh, Pravin Kumar; Kumar, S. Deepak; Patel, D.; Prasad, S. B. [National Institute of Technology Jamshedpur, Jharkhand (India)
2017-05-15
The current investigation was carried out to study the effect of vibratory welding technique on mechanical properties of 6 mm thick butt welded mild steel plates. A new concept of vibratory welding technique has been designed and developed which is capable to transfer vibrations, having resonance frequency of 300 Hz, into the molten weld pool before it solidifies during the Shielded metal arc welding (SMAW) process. The important process parameters of vibratory welding technique namely welding current, welding speed and frequency of the vibrations induced in molten weld pool were optimized using Taguchi’s analysis and Response surface methodology (RSM). The effect of process parameters on tensile strength and hardness were evaluated using optimization techniques. Applying RSM, the effect of vibratory welding parameters on tensile strength and hardness were obtained through two separate regression equations. Results showed that, the most influencing factor for the desired tensile strength and hardness is frequency at its resonance value, i.e. 300 Hz. The micro-hardness and microstructures of the vibratory welded joints were studied in detail and compared with those of conventional SMAW joints. Comparatively, uniform and fine grain structure has been found in vibratory welded joints.
Energy Technology Data Exchange (ETDEWEB)
Zarepisheh, M; Li, R; Xing, L [Stanford UniversitySchool of Medicine, Stanford, CA (United States); Ye, Y [Stanford Univ, Management Science and Engineering, Stanford, Ca (United States); Boyd, S [Stanford University, Electrical Engineering, Stanford, CA (United States)
2014-06-01
Purpose: Station Parameter Optimized Radiation Therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital LINACs, in which the station parameters of a delivery system, (such as aperture shape and weight, couch position/angle, gantry/collimator angle) are optimized altogether. SPORT promises to deliver unprecedented radiation dose distributions efficiently, yet there does not exist any optimization algorithm to implement it. The purpose of this work is to propose an optimization algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: We build a mathematical model whose variables are beam angles (including non-coplanar and/or even nonisocentric beams) and aperture shapes. To solve the resulting large scale optimization problem, we devise an exact, convergent and fast optimization algorithm by integrating three advanced optimization techniques named column generation, gradient method, and pattern search. Column generation is used to find a good set of aperture shapes as an initial solution by adding apertures sequentially. Then we apply the gradient method to iteratively improve the current solution by reshaping the aperture shapes and updating the beam angles toward the gradient. Algorithm continues by pattern search method to explore the part of the search space that cannot be reached by the gradient method. Results: The proposed technique is applied to a series of patient cases and significantly improves the plan quality. In a head-and-neck case, for example, the left parotid gland mean-dose, brainstem max-dose, spinal cord max-dose, and mandible mean-dose are reduced by 10%, 7%, 24% and 12% respectively, compared to the conventional VMAT plan while maintaining the same PTV coverage. Conclusion: Combined use of column generation, gradient search and pattern search algorithms provide an effective way to optimize simultaneously the large collection of station parameters and significantly improves
International Nuclear Information System (INIS)
Zarepisheh, M; Li, R; Xing, L; Ye, Y; Boyd, S
2014-01-01
Purpose: Station Parameter Optimized Radiation Therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital LINACs, in which the station parameters of a delivery system, (such as aperture shape and weight, couch position/angle, gantry/collimator angle) are optimized altogether. SPORT promises to deliver unprecedented radiation dose distributions efficiently, yet there does not exist any optimization algorithm to implement it. The purpose of this work is to propose an optimization algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: We build a mathematical model whose variables are beam angles (including non-coplanar and/or even nonisocentric beams) and aperture shapes. To solve the resulting large scale optimization problem, we devise an exact, convergent and fast optimization algorithm by integrating three advanced optimization techniques named column generation, gradient method, and pattern search. Column generation is used to find a good set of aperture shapes as an initial solution by adding apertures sequentially. Then we apply the gradient method to iteratively improve the current solution by reshaping the aperture shapes and updating the beam angles toward the gradient. Algorithm continues by pattern search method to explore the part of the search space that cannot be reached by the gradient method. Results: The proposed technique is applied to a series of patient cases and significantly improves the plan quality. In a head-and-neck case, for example, the left parotid gland mean-dose, brainstem max-dose, spinal cord max-dose, and mandible mean-dose are reduced by 10%, 7%, 24% and 12% respectively, compared to the conventional VMAT plan while maintaining the same PTV coverage. Conclusion: Combined use of column generation, gradient search and pattern search algorithms provide an effective way to optimize simultaneously the large collection of station parameters and significantly improves
Energy Technology Data Exchange (ETDEWEB)
Lynch, Vickie E.; Borreguero, Jose M. [Neutron Data Analysis & Visualization Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Bhowmik, Debsindhu [Computational Sciences & Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Ganesh, Panchapakesan; Sumpter, Bobby G. [Center for Nanophase Material Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Computational Sciences & Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Proffen, Thomas E. [Neutron Data Analysis & Visualization Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Goswami, Monojoy, E-mail: goswamim@ornl.gov [Center for Nanophase Material Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Computational Sciences & Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States)
2017-07-01
Graphical abstract: - Highlights: • An automated workflow to optimize force-field parameters. • Used the workflow to optimize force-field parameter for a system containing nanodiamond and tRNA. • The mechanism relies on molecular dynamics simulation and neutron scattering experimental data. • The workflow can be generalized to any other experimental and simulation techniques. - Abstract: Large-scale simulations and data analysis are often required to explain neutron scattering experiments to establish a connection between the fundamental physics at the nanoscale and data probed by neutrons. However, to perform simulations at experimental conditions it is critical to use correct force-field (FF) parameters which are unfortunately not available for most complex experimental systems. In this work, we have developed a workflow optimization technique to provide optimized FF parameters by comparing molecular dynamics (MD) to neutron scattering data. We describe the workflow in detail by using an example system consisting of tRNA and hydrophilic nanodiamonds in a deuterated water (D{sub 2}O) environment. Quasi-elastic neutron scattering (QENS) data show a faster motion of the tRNA in the presence of nanodiamond than without the ND. To compare the QENS and MD results quantitatively, a proper choice of FF parameters is necessary. We use an efficient workflow to optimize the FF parameters between the hydrophilic nanodiamond and water by comparing to the QENS data. Our results show that we can obtain accurate FF parameters by using this technique. The workflow can be generalized to other types of neutron data for FF optimization, such as vibrational spectroscopy and spin echo.
Optimization of cutting parameters for machining time in turning process
Mavliutov, A. R.; Zlotnikov, E. G.
2018-03-01
This paper describes the most effective methods for nonlinear constraint optimization of cutting parameters in the turning process. Among them are Linearization Programming Method with Dual-Simplex algorithm, Interior Point method, and Augmented Lagrangian Genetic Algorithm (ALGA). Every each of them is tested on an actual example – the minimization of production rate in turning process. The computation was conducted in the MATLAB environment. The comparative results obtained from the application of these methods show: The optimal value of the linearized objective and the original function are the same. ALGA gives sufficiently accurate values, however, when the algorithm uses the Hybrid function with Interior Point algorithm, the resulted values have the maximal accuracy.
Optimizing electrical distribution systems
International Nuclear Information System (INIS)
Scott, W.G.
1990-01-01
Electrical utility distribution systems are in the middle of an unprecedented technological revolution in planning, design, maintenance and operation. The prime movers of the revolution are the major economic shifts that affect decision making. The major economic influence on the revolution is the cost of losses (technical and nontechnical). The vehicle of the revolution is the computer, which enables decision makers to examine alternatives in greater depth and detail than their predecessors could. The more important elements of the technological revolution are: system planning, computers, load forecasting, analytical systems (primary systems, transformers and secondary systems), system losses and coming technology. The paper is directed towards the rather unique problems encountered by engineers of utilities in developing countries - problems that are being solved through high technology, such as the recent World Bank-financed engineering computer system for Sri Lanka. This system includes a DEC computer, digitizer, plotter and engineering software to model the distribution system via a digitizer, analyse the system and plot single-line diagrams. (author). 1 ref., 4 tabs., 6 figs
Optimal CT scanning parameters for commonly used tumor ablation applicators
International Nuclear Information System (INIS)
Eltorai, Adam E.M.; Baird, Grayson L.; Monu, Nicholas; Wolf, Farrah; Seidler, Michael; Collins, Scott; Kim, Jeomsoon; Dupuy, Damian E.
2017-01-01
Highlights: • This study aimed to determine optimal scanning parameters for commonly-used tumor ablation applicators. • The findings illustrate the overall interaction of the effects of kVp, ASiR, and reconstruction algorithm within and between probes, so that radiologists may easily reference optimal imaging performance. • Optimum combinations for each probe are provided. - Abstract: Purpose: CT-beam hardening artifact can make tumor margin visualization and its relationship to the ablation applicator tip challenging. To determine optimal scanning parameters for commonly-used applicators. Materials and methods: Applicators were placed in ex-vivo cow livers with implanted mock tumors, surrounded by bolus gel. Various CT scans were performed at 440 mA with 5 mm thickness changing kVp, scan time, ASiR, scan type, pitch, and reconstruction algorithm. Four radiologists blindly scored the images for image quality and artifact quantitatively. Results: A significant relationship between probe, kVp level, ASiR level, and reconstruction algorithm was observed concerning both image artifact and image quality (both p = <0.0001). Specifically, there are certain combinations of kVp, ASiR, and reconstruction algorithm that yield better images than other combinations. In particular, one probe performed equivalently or better than any competing probe considered here, regardless of kVp, ASiR, and reconstruction algorithm combination. Conclusion: The findings illustrate the overall interaction of the effects of kVp, ASiR, and reconstruction algorithm within and between probes, so that radiologists may easily reference optimal imaging performance for a certain combinations of kVp, ASiR, reconstruction algorithm and probes at their disposal. Optimum combinations for each probe are provided.
Optimal CT scanning parameters for commonly used tumor ablation applicators
Energy Technology Data Exchange (ETDEWEB)
Eltorai, Adam E.M. [Warren Alpert Medical School of Brown University (United States); Baird, Grayson L. [Department of Diagnostic Imaging (United States); Warren Alpert Medical School of Brown University (United States); Lifespan Biostatistics Core (United States); Rhode Island Hospital (United States); Monu, Nicholas; Wolf, Farrah; Seidler, Michael [Department of Diagnostic Imaging (United States); Warren Alpert Medical School of Brown University (United States); Rhode Island Hospital (United States); Collins, Scott [Department of Diagnostic Imaging (United States); Rhode Island Hospital (United States); Kim, Jeomsoon [Department of Medical Physics (United States); Rhode Island Hospital (United States); Dupuy, Damian E., E-mail: ddupuy@comcast.net [Department of Diagnostic Imaging (United States); Warren Alpert Medical School of Brown University (United States); Rhode Island Hospital (United States)
2017-04-15
Highlights: • This study aimed to determine optimal scanning parameters for commonly-used tumor ablation applicators. • The findings illustrate the overall interaction of the effects of kVp, ASiR, and reconstruction algorithm within and between probes, so that radiologists may easily reference optimal imaging performance. • Optimum combinations for each probe are provided. - Abstract: Purpose: CT-beam hardening artifact can make tumor margin visualization and its relationship to the ablation applicator tip challenging. To determine optimal scanning parameters for commonly-used applicators. Materials and methods: Applicators were placed in ex-vivo cow livers with implanted mock tumors, surrounded by bolus gel. Various CT scans were performed at 440 mA with 5 mm thickness changing kVp, scan time, ASiR, scan type, pitch, and reconstruction algorithm. Four radiologists blindly scored the images for image quality and artifact quantitatively. Results: A significant relationship between probe, kVp level, ASiR level, and reconstruction algorithm was observed concerning both image artifact and image quality (both p = <0.0001). Specifically, there are certain combinations of kVp, ASiR, and reconstruction algorithm that yield better images than other combinations. In particular, one probe performed equivalently or better than any competing probe considered here, regardless of kVp, ASiR, and reconstruction algorithm combination. Conclusion: The findings illustrate the overall interaction of the effects of kVp, ASiR, and reconstruction algorithm within and between probes, so that radiologists may easily reference optimal imaging performance for a certain combinations of kVp, ASiR, reconstruction algorithm and probes at their disposal. Optimum combinations for each probe are provided.
Standardless quantification by parameter optimization in electron probe microanalysis
Energy Technology Data Exchange (ETDEWEB)
Limandri, Silvina P. [Instituto de Fisica Enrique Gaviola (IFEG), CONICET (Argentina); Facultad de Matematica, Astronomia y Fisica, Universidad Nacional de Cordoba, Medina Allende s/n, (5016) Cordoba (Argentina); Bonetto, Rita D. [Centro de Investigacion y Desarrollo en Ciencias Aplicadas Dr. Jorge Ronco (CINDECA), CONICET, 47 Street 257, (1900) La Plata (Argentina); Facultad de Ciencias Exactas, Universidad Nacional de La Plata, 1 and 47 Streets (1900) La Plata (Argentina); Josa, Victor Galvan; Carreras, Alejo C. [Instituto de Fisica Enrique Gaviola (IFEG), CONICET (Argentina); Facultad de Matematica, Astronomia y Fisica, Universidad Nacional de Cordoba, Medina Allende s/n, (5016) Cordoba (Argentina); Trincavelli, Jorge C., E-mail: trincavelli@famaf.unc.edu.ar [Instituto de Fisica Enrique Gaviola (IFEG), CONICET (Argentina); Facultad de Matematica, Astronomia y Fisica, Universidad Nacional de Cordoba, Medina Allende s/n, (5016) Cordoba (Argentina)
2012-11-15
A method for standardless quantification by parameter optimization in electron probe microanalysis is presented. The method consists in minimizing the quadratic differences between an experimental spectrum and an analytical function proposed to describe it, by optimizing the parameters involved in the analytical prediction. This algorithm, implemented in the software POEMA (Parameter Optimization in Electron Probe Microanalysis), allows the determination of the elemental concentrations, along with their uncertainties. The method was tested in a set of 159 elemental constituents corresponding to 36 spectra of standards (mostly minerals) that include trace elements. The results were compared with those obtained with the commercial software GENESIS Spectrum Registered-Sign for standardless quantification. The quantifications performed with the method proposed here are better in the 74% of the cases studied. In addition, the performance of the method proposed is compared with the first principles standardless analysis procedure DTSA for a different data set, which excludes trace elements. The relative deviations with respect to the nominal concentrations are lower than 0.04, 0.08 and 0.35 for the 66% of the cases for POEMA, GENESIS and DTSA, respectively. - Highlights: Black-Right-Pointing-Pointer A method for standardless quantification in EPMA is presented. Black-Right-Pointing-Pointer It gives better results than the commercial software GENESIS Spectrum. Black-Right-Pointing-Pointer It gives better results than the software DTSA. Black-Right-Pointing-Pointer It allows the determination of the conductive coating thickness. Black-Right-Pointing-Pointer It gives an estimation for the concentration uncertainties.
PI Stabilization for Congestion Control of AQM Routers with Tuning Parameter Optimization
Directory of Open Access Journals (Sweden)
S. Chebli
2016-09-01
Full Text Available In this paper, we consider the problem of stabilizing network using a new proportional- integral (PI based congestion controller in active queue management (AQM router; with appropriate model approximation in the first order delay systems, we seek a stability region of the controller by using the Hermite- Biehler theorem, which isapplicable to quasipolynomials. A Genetic Algorithm technique is employed to derive optimal or near optimal PI controller parameters.
Optimization of some electrochemical etching parameters for cellulose derivatives
International Nuclear Information System (INIS)
Chowdhury, Annis; Gammage, R.B.
1978-01-01
Electrochemical etching of fast neutron induced recoil particle tracks in cellulose derivatives and other polymers provides an inexpensive and sensitive means of fast neutron personnel dosimetry. A study of the shape, clarity, and size of the tracks in Transilwrap polycarbonate indicated that the optimum normality of the potassium hydroxide etching solution is 9 N. Optimizations have also been attempted for cellulose nitrate, triacetate, and acetobutyrate with respect to such electrochemical etching parameters as frequency, voltage gradient, and concentration of the etching solution. The measurement of differential leakage currents between the undamaged and the neutron damaged foils aided in the selection of optimum frequencies. (author)
The Structural Optimization System CAOS
DEFF Research Database (Denmark)
Rasmussen, John
1990-01-01
CAOS is a system for structural shape optimization. It is closely integrated in a Computer Aided Design environment and controlled entirely from the CAD-system AutoCAD. The mathematical foundation of the system is briefly presented and a description of the CAD-integration strategy is given together...
Optimization of a wearable power system
Energy Technology Data Exchange (ETDEWEB)
Kovacevic, I.; Round, S. D.; Kolar, J. W.; Boulouchos, K.
2008-07-01
In this paper the optimization of wearable power system comprising of an internal combustion engine, motor/generator, inverter/rectifier, Li-battery pack, DC/DC converters, and controller is performed. The Wearable Power System must have the capability to supply an average 20 W for 4 days with peak power of 200 W and have a system weight less then 4 kg. The main objectives are to select the engine, fuel and battery type, to match the weight of fuel and the number of battery cells, to find the optimal working point of engine and minimizing the system weight. The minimization problem is defined in Matlab as a nonlinear constrained optimization task. The optimization procedure returns the optimal system design parameters: the Li-polymer battery with eight cells connected in series for a 28 V DC output voltage, the selection of gasoline/oil fuel mixture and the optimal engine working point of 12 krpm for a 4.5 cm{sup 3} 4-stroke engine. (author)
Optimization of multilayer neural network parameters for speaker recognition
Tovarek, Jaromir; Partila, Pavol; Rozhon, Jan; Voznak, Miroslav; Skapa, Jan; Uhrin, Dominik; Chmelikova, Zdenka
2016-05-01
This article discusses the impact of multilayer neural network parameters for speaker identification. The main task of speaker identification is to find a specific person in the known set of speakers. It means that the voice of an unknown speaker (wanted person) belongs to a group of reference speakers from the voice database. One of the requests was to develop the text-independent system, which means to classify wanted person regardless of content and language. Multilayer neural network has been used for speaker identification in this research. Artificial neural network (ANN) needs to set parameters like activation function of neurons, steepness of activation functions, learning rate, the maximum number of iterations and a number of neurons in the hidden and output layers. ANN accuracy and validation time are directly influenced by the parameter settings. Different roles require different settings. Identification accuracy and ANN validation time were evaluated with the same input data but different parameter settings. The goal was to find parameters for the neural network with the highest precision and shortest validation time. Input data of neural networks are a Mel-frequency cepstral coefficients (MFCC). These parameters describe the properties of the vocal tract. Audio samples were recorded for all speakers in a laboratory environment. Training, testing and validation data set were split into 70, 15 and 15 %. The result of the research described in this article is different parameter setting for the multilayer neural network for four speakers.
METHODS OF INTEGRATED OPTIMIZATION MAGLEV TRANSPORT SYSTEMS
Directory of Open Access Journals (Sweden)
A. Lasher
2013-09-01
Full Text Available Purpose. To demonstrate feasibility of the proposed integrated optimization of various MTS parameters to reduce capital investments as well as decrease any operational and maintenance expense. This will make use of MTS reasonable. At present, the Maglev Transport Systems (MTS for High-Speed Ground Transportation (HSGT almost do not apply. Significant capital investments, high operational and maintenance costs are the main reasons why Maglev Transport Systems (MTS are hardly currently used for the High-Speed Ground Transportation (HSGT. Therefore, this article justifies use of Theory of Complex Optimization of Transport (TCOT, developed by one of the co-authors, to reduce MTS costs. Methodology. According to TCOT, authors developed an abstract model of the generalized transport system (AMSTG. This model mathematically determines the optimal balance between all components of the system and thus provides the ultimate adaptation of any transport systems to the conditions of its application. To identify areas for effective use of MTS, by TCOT, the authors developed a dynamic model of distribution and expansion of spheres of effective use of transport systems (DMRRSEPTS. Based on this model, the most efficient transport system was selected for each individual track. The main estimated criterion at determination of efficiency of application of MTS is the size of the specific transportation tariff received from calculation of payback of total given expenses to a standard payback period or term of granting the credit. Findings. The completed multiple calculations of four types of MTS: TRANSRAPID, MLX01, TRANSMAG and TRANSPROGRESS demonstrated efficiency of the integrated optimization of the parameters of such systems. This research made possible expending the scope of effective usage of MTS in about 2 times. The achieved results were presented at many international conferences in Germany, Switzerland, United States, China, Ukraine, etc. Using MTS as an
Study of dose calculation and beam parameters optimization with genetic algorithm in IMRT
International Nuclear Information System (INIS)
Chen Chaomin; Tang Mutao; Zhou Linghong; Lv Qingwen; Wang Zhuoyu; Chen Guangjie
2006-01-01
Objective: To study the construction of dose calculation model and the method of automatic beam parameters selection in IMRT. Methods: The three-dimension convolution dose calculation model of photon was constructed with the methods of Fast Fourier Transform. The objective function based on dose constrain was used to evaluate the fitness of individuals. The beam weights were optimized with genetic algorithm. Results: After 100 iterative analyses, the treatment planning system produced highly conformal and homogeneous dose distributions. Conclusion: the throe-dimension convolution dose calculation model of photon gave more accurate results than the conventional models; genetic algorithm is valid and efficient in IMRT beam parameters optimization. (authors)
Diagnostics and tolerance optimization of nuclear facilities parameters
International Nuclear Information System (INIS)
Novak, M.; Otcenasek, P.
1988-01-01
The possibilities are discussed of applying the theory of tolerances for assessing the service life of systems in nuclear power. The approach proceeds from the postulate that the nuclear power plant is on the one hand an extremely sophisticated technical system and on the other a system with well defined demands on the state and properties of components and of the whole system, with rationally defined limits, conditions of permissible states and limit values. It is stated that the basic ideas of the theory of the hot channel may be extended and generalized. The theory was initially limited to the study of relations between deviations in nucleaer and non-nuclear parameters in the fuel assembly, and the temperature field; it can be generalized to the analysis of permissible parameter tolerances of the whole system. The foundations are outlined of the theory of tolerances of general technical system parameters. Brief attention is also paid to the general possibilities of the use of life curves for designing the system such as would extend its service life. (Z.M.). 10 figs., 5 refs
International Nuclear Information System (INIS)
Parkhomchuk, V.V.; Shiltsev, V.D.
1993-06-01
The paper considers the Superconducting Super Collider (SSC) site ground motion measurements as well as data from accelerators worldwide about noises that worsen beam performance. Unacceptably fast emittance growth due to these noises is predicted for the SSC. A transverse feedback system was found to be the only satisfactory alternative to prevent emittance decay. Optimization of the primary feedback parameters was done
Optimal control systems in hydro power plants
International Nuclear Information System (INIS)
Babunski, Darko L.
2012-01-01
The aim of the research done in this work is focused on obtaining the optimal models of hydro turbine including auxiliary equipment, analysis of governors for hydro power plants and analysis and design of optimal control laws that can be easily applicable in real hydro power plants. The methodology of the research and realization of the set goals consist of the following steps: scope of the models of hydro turbine, and their modification using experimental data; verification of analyzed models and comparison of advantages and disadvantages of analyzed models, with proposal of turbine model for design of control low; analysis of proportional-integral-derivative control with fixed parameters and gain scheduling and nonlinear control; analysis of dynamic characteristics of turbine model including control and comparison of parameters of simulated system with experimental data; design of optimal control of hydro power plant considering proposed cost function and verification of optimal control law with load rejection measured data. The hydro power plant models, including model of power grid are simulated in case of island ing and restoration after breakup and load rejection with consideration of real loading and unloading of hydro power plant. Finally, simulations provide optimal values of control parameters, stability boundaries and results easily applicable to real hydro power plants. (author)
Truss systems and shape optimization
Pricop, Mihai Victor; Bunea, Marian; Nedelcu, Roxana
2017-07-01
Structure optimization is an important topic because of its benefits and wide applicability range, from civil engineering to aerospace and automotive industries, contributing to a more green industry and life. Truss finite elements are still in use in many research/industrial codesfor their simple stiffness matrixand are naturally matching the requirements for cellular materials especially considering various 3D printing technologies. Optimality Criteria combined with Solid Isotropic Material with Penalization is the optimization method of choice, particularized for truss systems. Global locked structures areobtainedusinglocally locked lattice local organization, corresponding to structured or unstructured meshes. Post processing is important for downstream application of the method, to make a faster link to the CAD systems. To export the optimal structure in CATIA, a CATScript file is automatically generated. Results, findings and conclusions are given for two and three-dimensional cases.
Murthy, Pappu L. N.; Naghipour Ghezeljeh, Paria; Bednarcyk, Brett A.
2018-01-01
This document describes a recently developed analysis tool that enhances the resident capabilities of the Micromechanics Analysis Code with the Generalized Method of Cells (MAC/GMC) and its application. MAC/GMC is a composite material and laminate analysis software package developed at NASA Glenn Research Center. The primary focus of the current effort is to provide a graphical user interface (GUI) capability that helps users optimize highly nonlinear viscoplastic constitutive law parameters by fitting experimentally observed/measured stress-strain responses under various thermo-mechanical conditions for braided composites. The tool has been developed utilizing the MATrix LABoratory (MATLAB) (The Mathworks, Inc., Natick, MA) programming language. Illustrative examples shown are for a specific braided composite system wherein the matrix viscoplastic behavior is represented by a constitutive law described by seven parameters. The tool is general enough to fit any number of experimentally observed stress-strain responses of the material. The number of parameters to be optimized, as well as the importance given to each stress-strain response, are user choice. Three different optimization algorithms are included: (1) Optimization based on gradient method, (2) Genetic algorithm (GA) based optimization and (3) Particle Swarm Optimization (PSO). The user can mix and match the three algorithms. For example, one can start optimization with either 2 or 3 and then use the optimized solution to further fine tune with approach 1. The secondary focus of this paper is to demonstrate the application of this tool to optimize/calibrate parameters for a nonlinear viscoplastic matrix to predict stress-strain curves (for constituent and composite levels) at different rates, temperatures and/or loading conditions utilizing the Generalized Method of Cells. After preliminary validation of the tool through comparison with experimental results, a detailed virtual parametric study is
Optimization theory for large systems
Lasdon, Leon S
2002-01-01
Important text examines most significant algorithms for optimizing large systems and clarifying relations between optimization procedures. Much data appear as charts and graphs and will be highly valuable to readers in selecting a method and estimating computer time and cost in problem-solving. Initial chapter on linear and nonlinear programming presents all necessary background for subjects covered in rest of book. Second chapter illustrates how large-scale mathematical programs arise from real-world problems. Appendixes. List of Symbols.
Worst-case tolerance optimization of antenna systems
DEFF Research Database (Denmark)
Schjær-Jacobsen, Hans
1980-01-01
The application of recently developed algorithms to antenna systems design is demonstrated by the worst-case tolerance optimization of linear broadside arrays, using both spacings and excitation coefficients as design parameters. The resulting arrays are optimally immunized against deviations...... of the design parameters from their nominal values....
Distributed optimization system and method
Hurtado, John E.; Dohrmann, Clark R.; Robinett, III, Rush D.
2003-06-10
A search system and method for controlling multiple agents to optimize an objective using distributed sensing and cooperative control. The search agent can be one or more physical agents, such as a robot, and can be software agents for searching cyberspace. The objective can be: chemical sources, temperature sources, radiation sources, light sources, evaders, trespassers, explosive sources, time dependent sources, time independent sources, function surfaces, maximization points, minimization points, and optimal control of a system such as a communication system, an economy, a crane, and a multi-processor computer.
LIFE CYCLE ASSESSMENT IN HEALTHCARE SYSTEM OPTIMIZATION. INTRODUCTION
Directory of Open Access Journals (Sweden)
V. Sarancha
2015-03-01
Full Text Available Article describes the life cycle assessment method and introduces opportunities for method performance in healthcare system settings. LSA draws attention to careful use of resources, environmental, human and social responsibility. Modelling of environmental and technological inputs allows optimizing performance of the system. Various factors and parameters that may influence effectiveness of different sectors in healthcare system are detected. Performance optimization of detected parameters could lead to better system functioning, higher patient safety, economic sustainability and reduce resources consumption.
Towards automatic parameter tuning of stream processing systems
Bilal, Muhammad
2017-09-27
Optimizing the performance of big-data streaming applications has become a daunting and time-consuming task: parameters may be tuned from a space of hundreds or even thousands of possible configurations. In this paper, we present a framework for automating parameter tuning for stream-processing systems. Our framework supports standard black-box optimization algorithms as well as a novel gray-box optimization algorithm. We demonstrate the multiple benefits of automated parameter tuning in optimizing three benchmark applications in Apache Storm. Our results show that a hill-climbing algorithm that uses a new heuristic sampling approach based on Latin Hypercube provides the best results. Our gray-box algorithm provides comparable results while being two to five times faster.
Air conditioning with methane: Efficiency and economics optimization parameters
International Nuclear Information System (INIS)
Mastrullo, R.; Sasso, M.; Sibilio, S.; Vanoli, R.
1992-01-01
This paper presents an efficiency and economics evaluation method for methane fired cooling systems. Focus is on direct flame two staged absorption systems and alternative engine driven compressor sets. Comparisons are made with conventional vapour compression plants powered by electricity supplied by the national grid. A first and second law based thermodynamics analysis is made in which fuel use coefficients and exergy yields are determined. The economics analysis establishes annual energy savings, unit cooling energy production costs, payback periods and economics/efficiency optimization curves useful for preliminary feasibility studies
Data Mining and Optimization Tools for Developing Engine Parameters Tools
Dhawan, Atam P.
1998-01-01
This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. Tricia Erhardt and I studied the problem domain for developing an Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy, datasets. From the study and discussion with NASA LeRC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of tile data for GA based multi-resolution optimal search.
Multivariate optimization of production systems
International Nuclear Information System (INIS)
Carroll, J.A.; Horne, R.N.
1992-01-01
This paper reports that mathematically, optimization involves finding the extreme values of a function. Given a function of several variables, Z = ∫(rvec x 1 , rvec x 2 ,rvec x 3 ,→x n ), an optimization scheme will find the combination of these variables that produces an extreme value in the function, whether it is a minimum or a maximum value. Many examples of optimization exist. For instance, if a function gives and investor's expected return on the basis of different investments, numerical optimization of the function will determine the mix of investments that will yield the maximum expected return. This is the basis of modern portfolio theory. If a function gives the difference between a set of data and a model of the data, numerical optimization of the function will produce the best fit of the model to the data. This is the basis for nonlinear parameter estimation. Similar examples can be given for network analysis, queuing theory, decision analysis, etc
Time Optimal Control Laws for Bilinear Systems
Directory of Open Access Journals (Sweden)
Salim Bichiou
2018-01-01
Full Text Available The aim of this paper is to determine the feedforward and state feedback suboptimal time control for a subset of bilinear systems, namely, the control sequence and reaching time. This paper proposes a method that uses Block pulse functions as an orthogonal base. The bilinear system is projected along that base. The mathematical integration is transformed into a product of matrices. An algebraic system of equations is obtained. This system together with specified constraints is treated as an optimization problem. The parameters to determine are the final time, the control sequence, and the states trajectories. The obtained results via the newly proposed method are compared to known analytical solutions.
A parameter estimation for DC servo motor by using optimization process
International Nuclear Information System (INIS)
Arjoni Amir
2010-01-01
Modeling and simulation parameters of DC servo motor using Matlab Simulink software have been done. The objective to define the DC servo motor parameter estimation is to get DC servo motor parameter values (B, La, Ra, Km, J) which are significant value that can be used for actuation process of control systems. In the analysis of control systems DC the servo motor expressed by transfer function equation to make faster to be analyzed as a component of the actuator. To obtain the data model parameters and initial conditions of the DC servo motors is then carried out the processor modeling and simulation in which the DC servo motor combined with other components. To obtain preliminary data of the DC servo motor parameters as estimated venue, it is obtained from the data factory of the DC servo motor. The initial data parameters of the DC servo motor are applied for the optimization process by using nonlinear least square algorithm and minimize the cost function value so that the DC servo motors parameter values are obtained significantly. The result of the optimization process of the DC servo motor parameter values are B = 0.039881, J= 1.2608e-007, Km = 0.069648, La = 2.3242e-006 and Ra = 1.8837. (author)
Optimizing design parameter for light isotopes separation by distillation method
International Nuclear Information System (INIS)
Ahmadi, M.
1999-01-01
More than methods are suggested in the world for producing heavy water, where between them chemical isotopic methods, distillation and electro lys are used widely in industrial scale. To select suitable method for heavy water production in Iran, taking into consideration, domestic technology an facilities, combination of hydrogen sulphide-water dual temperature process (Gs) and distillation (D W) may be proposed. Natural water, is firstly enriched up to 15 a% by G S process and then by distillation unit is enriched up to the grade necessary for Candu type reactors (99.8 a%). The aim of present thesis, is to achieve know-how, optimization of design parameters, and executing basic design for water isotopes separation using distillation process in a plant having minimum scale possible. In distillation, vapour phase resulted from liquid phase heating, is evidently composed of the same constituents as liquid phase. In isotopic distillation, the difference in composition of constituents is not considerable. In fact alteration of constituents composition is so small that makes the separation process impossible, however, direct separation and production of pure products without further processing which becomes possible by distillation, makes this process as one of the most important separation processes. Profiting distillation process to produce heavy water is based on difference existing between boiling point of heavy and light water. The trends of boiling points differences (heavy and light water) is adversely dependant with pressure. As the whole system pressure decreases, difference in boiling points increases. On the other hand according to the definition, separation factor is equal to the ratio of pure light water vapour pressure to that of heavy water, or we can say that the trend of whole system pressure decrease results in separation factor increase, which accordingly separation factor equation to pressure variable should be computed firstly. According to the
Microbial alkaline proteases: Optimization of production parameters and their properties
Directory of Open Access Journals (Sweden)
Kanupriya Miglani Sharma
2017-06-01
Full Text Available Proteases are hydrolytic enzymes capable of degrading proteins into small peptides and amino acids. They account for nearly 60% of the total industrial enzyme market. Proteases are extensively exploited commercially, in food, pharmaceutical, leather and detergent industry. Given their potential use, there has been renewed interest in the discovery of proteases with novel properties and a constant thrust to optimize the enzyme production. This review summarizes a fraction of the enormous reports available on various aspects of alkaline proteases. Diverse sources for isolation of alkaline protease producing microorganisms are reported. The various nutritional and environmental parameters affecting the production of alkaline proteases in submerged and solid state fermentation are described. The enzymatic and physicochemical properties of alkaline proteases from several microorganisms are discussed which can help to identify enzymes with high activity and stability over extreme pH and temperature, so that they can be developed for industrial applications.
OPTIMIZATION OF OPERATION PARAMETERS OF 80-KEV ELECTRON GUN
Directory of Open Access Journals (Sweden)
JEONG DONG KIM
2014-06-01
As a first step, the electron generator of an 80-keV electron gun was manufactured. In order to produce the high beam power from electron linear accelerator, a proper beam current is required form the electron generator. In this study, the beam current was measured by evaluating the performance of the electron generator. The beam current was determined by five parameters: high voltage at the electron gun, cathode voltage, pulse width, pulse amplitude, and bias voltage at the grid. From the experimental results under optimal conditions, the high voltage was determined to be 80 kV, the pulse width was 500 ns, and the cathode voltage was from 4.2 V to 4.6 V. The beam current was measured as 1.9 A at maximum. These results satisfy the beam current required for the operation of an electron linear accelerator.
High Temperature Epoxy Foam: Optimization of Process Parameters
Directory of Open Access Journals (Sweden)
Samira El Gazzani
2016-06-01
Full Text Available For many years, reduction of fuel consumption has been a major aim in terms of both costs and environmental concerns. One option is to reduce the weight of fuel consumers. For this purpose, the use of a lightweight material based on rigid foams is a relevant choice. This paper deals with a new high temperature epoxy expanded material as substitution of phenolic resin, classified as potentially mutagenic by European directive Reach. The optimization of thermoset foam depends on two major parameters, the reticulation process and the expansion of the foaming agent. Controlling these two phenomena can lead to a fully expanded and cured material. The rheological behavior of epoxy resin is studied and gel time is determined at various temperatures. The expansion of foaming agent is investigated by thermomechanical analysis. Results are correlated and compared with samples foamed in the same temperature conditions. The ideal foaming/gelation temperature is then determined. The second part of this research concerns the optimization of curing cycle of a high temperature trifunctional epoxy resin. A two-step curing cycle was defined by considering the influence of different curing schedules on the glass transition temperature of the material. The final foamed material has a glass transition temperature of 270 °C.
Directory of Open Access Journals (Sweden)
E. N. Ishakova
2016-05-01
Full Text Available A method for multi-criteria optimization of the design parameters for technological object is described. The existing optimization methods are overviewed, and works in the field of basic research and applied problems are analyzed. The problem is formulated, based on the process requirements, making it possible to choose the geometrical dimensions of machine tips and the flow rate of the process, so that the resulting technical and economical parameters were optimal. In the problem formulation application of the performance method adapted to a particular domain is described. Task implementation is shown; the method of characteristics creation for the studied object in view of some restrictions for parameters in both analytical and graphical representation. On the basis of theoretical research the software system is developed that gives the possibility to automate the discovery of optimal solutions for specific problems. Using available information sources, that characterize the object of study, it is possible to establish identifiers, add restrictions from the one side, and in the interval as well. Obtained result is a visual depiction of dependence of the main study parameters on the others, which may have an impact on both the flow of the process, and the quality of products. The resulting optimal area shows the use of different design options for technological object in an acceptable kinematic range that makes it possible for the researcher to choose the best design solution.
Optimization of control parameters of a hot cold controller by means of Simplex type methods
Porte, C.; Caron-Poussin, M.; Carot, S.; Couriol, C.; Moreno, M. Martin; Delacroix, A.
1997-01-01
This paper describes a hot/cold controller for regulating crystallization operations. The system was identified with a common method (the Broida method) and the parameters were obtained by the Ziegler-Nichols method. The paper shows that this empirical method will only allow a qualitative approach to regulation and that, in some instances, the parameters obtained are unreliable and therefore cannot be used to cancel variations between the set point and the actual values. Optimization methods were used to determine the regulation parameters and solve this identcation problem. It was found that the weighted centroid method was the best one. PMID:18924791
Acquisition system of tandem injector parameters
International Nuclear Information System (INIS)
Decourt, M.
1986-01-01
The system centralizes all the parameters belonging to the accelerator injector. The acquisition center system reinforces an original device made of cameras and video receivers. Besides giving access to all the parameters of the ion source, the new system allows, in the ''OSCILLO'' mode, to visualize in real time any channel on the oscilloscope [fr
Parameter selection for the SSC trade-offs and optimization
International Nuclear Information System (INIS)
Edwards, D.A.; Syphers, M.J.
1991-01-01
In November of 1988, a site was selected in the state of Texas for the SSC. In January of 1989, the SSC Laboratory was established in Texas to adapt the design of the collider to the site and to manage the construction of the project. This paper describes the evolution of the SSC design since site selection, notes the increased concentration on the injector system, and addresses the rationale for choice of parameters
Laser Processing of Multilayered Thermal Spray Coatings: Optimal Processing Parameters
Tewolde, Mahder; Zhang, Tao; Lee, Hwasoo; Sampath, Sanjay; Hwang, David; Longtin, Jon
2017-12-01
Laser processing offers an innovative approach for the fabrication and transformation of a wide range of materials. As a rapid, non-contact, and precision material removal technology, lasers are natural tools to process thermal spray coatings. Recently, a thermoelectric generator (TEG) was fabricated using thermal spray and laser processing. The TEG device represents a multilayer, multimaterial functional thermal spray structure, with laser processing serving an essential role in its fabrication. Several unique challenges are presented when processing such multilayer coatings, and the focus of this work is on the selection of laser processing parameters for optimal feature quality and device performance. A parametric study is carried out using three short-pulse lasers, where laser power, repetition rate and processing speed are varied to determine the laser parameters that result in high-quality features. The resulting laser patterns are characterized using optical and scanning electron microscopy, energy-dispersive x-ray spectroscopy, and electrical isolation tests between patterned regions. The underlying laser interaction and material removal mechanisms that affect the feature quality are discussed. Feature quality was found to improve both by using a multiscanning approach and an optional assist gas of air or nitrogen. Electrically isolated regions were also patterned in a cylindrical test specimen.
Optimization of Robotic Spray Painting process Parameters using Taguchi Method
Chidhambara, K. V.; Latha Shankar, B.; Vijaykumar
2018-02-01
Automated spray painting process is gaining interest in industry and research recently due to extensive application of spray painting in automobile industries. Automating spray painting process has advantages of improved quality, productivity, reduced labor, clean environment and particularly cost effectiveness. This study investigates the performance characteristics of an industrial robot Fanuc 250ib for an automated painting process using statistical tool Taguchi’s Design of Experiment technique. The experiment is designed using Taguchi’s L25 orthogonal array by considering three factors and five levels for each factor. The objective of this work is to explore the major control parameters and to optimize the same for the improved quality of the paint coating measured in terms of Dry Film thickness(DFT), which also results in reduced rejection. Further Analysis of Variance (ANOVA) is performed to know the influence of individual factors on DFT. It is observed that shaping air and paint flow are the most influencing parameters. Multiple regression model is formulated for estimating predicted values of DFT. Confirmation test is then conducted and comparison results show that error is within acceptable level.
Real parameter optimization by an effective differential evolution algorithm
Directory of Open Access Journals (Sweden)
Ali Wagdy Mohamed
2013-03-01
Full Text Available This paper introduces an Effective Differential Evolution (EDE algorithm for solving real parameter optimization problems over continuous domain. The proposed algorithm proposes a new mutation rule based on the best and the worst individuals among the entire population of a particular generation. The mutation rule is combined with the basic mutation strategy through a linear decreasing probability rule. The proposed mutation rule is shown to promote local search capability of the basic DE and to make it faster. Furthermore, a random mutation scheme and a modified Breeder Genetic Algorithm (BGA mutation scheme are merged to avoid stagnation and/or premature convergence. Additionally, the scaling factor and crossover of DE are introduced as uniform random numbers to enrich the search behavior and to enhance the diversity of the population. The effectiveness and benefits of the proposed modifications used in EDE has been experimentally investigated. Numerical experiments on a set of bound-constrained problems have shown that the new approach is efficient, effective and robust. The comparison results between the EDE and several classical differential evolution methods and state-of-the-art parameter adaptive differential evolution variants indicate that the proposed EDE algorithm is competitive with , and in some cases superior to, other algorithms in terms of final solution quality, efficiency, convergence rate, and robustness.
OPTIMIZATION OF DYEING PARAMETERS TO DYE COTTON WITH CARROT EXTRACTION
Directory of Open Access Journals (Sweden)
MIRALLES Verónica
2017-05-01
Full Text Available Natural dyes derived from flora and fauna are believed to be safe because of non-toxic, non-carcinogenic and biodegradable nature. Furthermore, natural dyes do not cause pollution and waste water problems. Natural dyes as well as synthetic dyes need the optimum parameters to get a good dyeing. On some occasions, It is necessary the use of mordants to increase the affinity between cellulose fiber and natural dye, but there are other conditions to optimize in the dyeing process, like time, temperature, auxiliary porducts, etc. In addition, the optimum conditions are different depends on the type of dye and the fiber nature. The aim of this work is the use of carrot extract to dye cotton fabric by exhaustion at diverse dyeing conditions. Diffferent dyeing processes were carried out to study the effect of pH condition and the temperature, using 7, 6 and 4 pH values and 95 ºC and 130ºC for an hour. As a result some images of dyed samples are shown. Moreover, to evaluate the colour of each sample CIELAB parameters are analysed obtained by reflexion spectrophotometre. The results showed that the temperature used has an important influence on the colour of the dyed sample.
International Nuclear Information System (INIS)
Gao, Hao
2016-01-01
For the treatment planning during intensity modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT), beam fluence maps can be first optimized via fluence map optimization (FMO) under the given dose prescriptions and constraints to conformally deliver the radiation dose to the targets while sparing the organs-at-risk, and then segmented into deliverable MLC apertures via leaf or arc sequencing algorithms. This work is to develop an efficient algorithm for FMO based on alternating direction method of multipliers (ADMM). Here we consider FMO with the least-square cost function and non-negative fluence constraints, and its solution algorithm is based on ADMM, which is efficient and simple-to-implement. In addition, an empirical method for optimizing the ADMM parameter is developed to improve the robustness of the ADMM algorithm. The ADMM based FMO solver was benchmarked with the quadratic programming method based on the interior-point (IP) method using the CORT dataset. The comparison results suggested the ADMM solver had a similar plan quality with slightly smaller total objective function value than IP. A simple-to-implement ADMM based FMO solver with empirical parameter optimization is proposed for IMRT or VMAT. (paper)
GPU based Monte Carlo for PET image reconstruction: parameter optimization
International Nuclear Information System (INIS)
Cserkaszky, Á; Légrády, D.; Wirth, A.; Bükki, T.; Patay, G.
2011-01-01
This paper presents the optimization of a fully Monte Carlo (MC) based iterative image reconstruction of Positron Emission Tomography (PET) measurements. With our MC re- construction method all the physical effects in a PET system are taken into account thus superior image quality is achieved in exchange for increased computational effort. The method is feasible because we utilize the enormous processing power of Graphical Processing Units (GPUs) to solve the inherently parallel problem of photon transport. The MC approach regards the simulated positron decays as samples in mathematical sums required in the iterative reconstruction algorithm, so to complement the fast architecture, our work of optimization focuses on the number of simulated positron decays required to obtain sufficient image quality. We have achieved significant results in determining the optimal number of samples for arbitrary measurement data, this allows to achieve the best image quality with the least possible computational effort. Based on this research recommendations can be given for effective partitioning of computational effort into the iterations in limited time reconstructions. (author)
Choice of optimal parameters for the superconductive quantum magnetometer
Energy Technology Data Exchange (ETDEWEB)
Vasiliev, B V; Ivanenko, A I; Trofimov, V N
1974-12-31
The problem of choosing the optimal coupling coefficient and optimal working frequency for superconductive quantum magnetometer is considered. The present experimental signalnoise dependence confirms the drawn conclusions. (auth)
He, L; Huang, G H; Lu, H W
2010-04-15
Solving groundwater remediation optimization problems based on proxy simulators can usually yield optimal solutions differing from the "true" ones of the problem. This study presents a new stochastic optimization model under modeling uncertainty and parameter certainty (SOMUM) and the associated solution method for simultaneously addressing modeling uncertainty associated with simulator residuals and optimizing groundwater remediation processes. This is a new attempt different from the previous modeling efforts. The previous ones focused on addressing uncertainty in physical parameters (i.e. soil porosity) while this one aims to deal with uncertainty in mathematical simulator (arising from model residuals). Compared to the existing modeling approaches (i.e. only parameter uncertainty is considered), the model has the advantages of providing mean-variance analysis for contaminant concentrations, mitigating the effects of modeling uncertainties on optimal remediation strategies, offering confidence level of optimal remediation strategies to system designers, and reducing computational cost in optimization processes. 2009 Elsevier B.V. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
He, L., E-mail: li.he@ryerson.ca [Department of Civil Engineering, Faculty of Engineering, Architecture and Science, Ryerson University, 350 Victoria Street, Toronto, Ontario, M5B 2K3 (Canada); Huang, G.H. [Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Saskatchewan, S4S 0A2 (Canada); College of Urban Environmental Sciences, Peking University, Beijing 100871 (China); Lu, H.W. [Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Saskatchewan, S4S 0A2 (Canada)
2010-04-15
Solving groundwater remediation optimization problems based on proxy simulators can usually yield optimal solutions differing from the 'true' ones of the problem. This study presents a new stochastic optimization model under modeling uncertainty and parameter certainty (SOMUM) and the associated solution method for simultaneously addressing modeling uncertainty associated with simulator residuals and optimizing groundwater remediation processes. This is a new attempt different from the previous modeling efforts. The previous ones focused on addressing uncertainty in physical parameters (i.e. soil porosity) while this one aims to deal with uncertainty in mathematical simulator (arising from model residuals). Compared to the existing modeling approaches (i.e. only parameter uncertainty is considered), the model has the advantages of providing mean-variance analysis for contaminant concentrations, mitigating the effects of modeling uncertainties on optimal remediation strategies, offering confidence level of optimal remediation strategies to system designers, and reducing computational cost in optimization processes.
Directory of Open Access Journals (Sweden)
Tashkova Katerina
2011-10-01
Full Text Available Abstract Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA, particle-swarm optimization (PSO, and differential evolution (DE, as well as a local-search derivative-based algorithm 717 (A717 to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE clearly and significantly outperform the local derivative-based method (A717. Among the three meta-heuristics, differential evolution (DE performs best in terms of the objective function, i.e., reconstructing the output, and in terms of
Tashkova, Katerina; Korošec, Peter; Silc, Jurij; Todorovski, Ljupčo; Džeroski, Sašo
2011-10-11
We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These results hold for both real and
Parameter identification of chaos system based on unknown parameter observer
International Nuclear Information System (INIS)
Wang Shaoming; Luo Haigeng; Yue Chaoyuan; Liao Xiaoxin
2008-01-01
Parameter identification of chaos system based on unknown parameter observer is discussed generally. Based on the work of Guan et al. [X.P. Guan, H.P. Peng, L.X. Li, et al., Acta Phys. Sinica 50 (2001) 26], the design of unknown parameter observer is improved. The application of the improved approach is extended greatly. The works in some literatures [X.P. Guan, H.P. Peng, L.X. Li, et al., Acta Phys. Sinica 50 (2001) 26; J.H. Lue, S.C. Zhang, Phys. Lett. A 286 (2001) 148; X.Q. Wu, J.A. Lu, Chaos Solitons Fractals 18 (2003) 721; J. Liu, S.H. Chen, J. Xie, Chaos Solitons Fractals 19 (2004) 533] are only the special cases of our Corollaries 1 and 2. Some observers for Lue system and a new chaos system are designed to test our improved method, and simulations results demonstrate the effectiveness and feasibility of the improved approach
Optimizing Technology-Oriented Constructional Paramour's of complex dynamic systems
International Nuclear Information System (INIS)
Novak, S.M.
1998-01-01
Creating optimal vibro systems requires sequential solving of a few problems: selecting the basic pattern of dynamic actions, synthesizing the dynamic active systems, optimizing technological, technical, economic and design parameters. This approach is illustrated by an example of a high-efficiency vibro system synthesized for forming building structure components. When using only one single source to excite oscillations, resonance oscillations are imparted to the product to be formed in the horizontal and vertical planes. In order to obtain versatile and dynamically optimized parameters, a factor is introduced into the differential equations of the motion, accounting for the relationship between the parameters, which determine the frequency characteristics of the system and the parameter variation range. This results in obtaining non-sophisticated mathematical models of the system under investigation, convenient for optimization and for engineering design and calculations as well
Q-Learning Multi-Objective Sequential Optimal Sensor Parameter Weights
Directory of Open Access Journals (Sweden)
Raquel Cohen
2016-04-01
Full Text Available The goal of our solution is to deliver trustworthy decision making analysis tools which evaluate situations and potential impacts of such decisions through acquired information and add efficiency for continuing mission operations and analyst information.We discuss the use of cooperation in modeling and simulation and show quantitative results for design choices to resource allocation. The key contribution of our paper is to combine remote sensing decision making with Nash Equilibrium for sensor parameter weighting optimization. By calculating all Nash Equilibrium possibilities per period, optimization of sensor allocation is achieved for overall higher system efficiency. Our tool provides insight into what are the most important or optimal weights for sensor parameters and can be used to efficiently tune those weights.
Importance theory for lumped-parameter systems
International Nuclear Information System (INIS)
Cady, K.B.; Kenton, M.A.; Ward, J.C.; Piepho, M.G.
1981-01-01
A general sensitivity theory has been developed for nonlinear lumped parameter system simulations. The point of departure is general perturbation theory for nonlinear systems. Importance theory as developed here allows the calculation of the sensitivity of a response function to any physical or design parameter; importance of any equation or term or physical effect in the system model on the response function; variance of the response function caused by the variances and covariances of all physical parameters; and approximate effect on the response function of missing physical phenomena or incorrect parameters
Integrated solar energy system optimization
Young, S. K.
1982-11-01
The computer program SYSOPT, intended as a tool for optimizing the subsystem sizing, performance, and economics of integrated wind and solar energy systems, is presented. The modular structure of the methodology additionally allows simulations when the solar subsystems are combined with conventional technologies, e.g., a utility grid. Hourly energy/mass flow balances are computed for interconnection points, yielding optimized sizing and time-dependent operation of various subsystems. The program requires meteorological data, such as insolation, diurnal and seasonal variations, and wind speed at the hub height of a wind turbine, all of which can be taken from simulations like the TRNSYS program. Examples are provided for optimization of a solar-powered (wind turbine and parabolic trough-Rankine generator) desalinization plant, and a design analysis for a solar powered greenhouse.
Efficiency Optimization Control of IPM Synchronous Motor Drives with Online Parameter Estimation
Directory of Open Access Journals (Sweden)
Sadegh Vaez-Zadeh
2011-04-01
Full Text Available This paper describes an efficiency optimization control method for high performance interior permanent magnet synchronous motor drives with online estimation of motor parameters. The control system is based on an input-output feedback linearization method which provides high performance control and simultaneously ensures the minimization of the motor losses. The controllable electrical loss can be minimized by the optimal control of the armature current vector. It is shown that parameter variations except at near the nominal conditions have undesirable effect on the controller performance. Therefore, a parameter estimation method based on the second method of Lyapunov is presented which guarantees the stability and convergence of the estimation. The extensive simulation results show the feasibility of the proposed controller and observer and their desirable performances.
High-resolution MRI of the labyrinth. Optimization of scan parameters with 3D-FSE
International Nuclear Information System (INIS)
Sakata, Motomichi; Harada, Kuniaki; Shirase, Ryuji; Kumagai, Akiko; Ogasawara, Masashi
2005-01-01
The aim of our study was to optimize the parameters of high-resolution MRI of the labyrinth with a 3D fast spin-echo (3D-FSE) sequence. We investigated repetition time (TR), echo time (TE), Matrix, field of view (FOV), and coil selection in terms of CNR (contrast-to-noise ratio) and SNR (signal-to-noise ratio) by comparing axial images and/or three-dimensional images. The optimal 3D-FSE sequence parameters were as follows: 1.5 Tesla MR unit (Signa LX, GE Medical Systems), 3D-FSE sequence, dual 3-inch surface coil, acquisition time=12.08 min, TR=5000 msec, TE=300 msec, 3 number of excitations (NEX), FOV=12 cm, matrix=256 x 256, slice thickness=0.5 mm/0.0 sp, echo train=64, bandwidth=±31.5 kHz. High-resolution MRI of the labyrinth using the optimized 3D-FSE sequence parameters permits visualization of important anatomic details (such as scala tympani and scala vestibuli), making it possible to determine inner ear anomalies and the patency of cochlear turns. To obtain excellent heavily T2-weighted axial and three-dimensional images in the labyrinth, high CNR, SNR, and spatial resolution are significant factors at the present time. Furthermore, it is important not only to optimize the scan parameters of 3D-FSE but also to select an appropriate coil for high-resolution MRI of the labyrinth. (author)
Optimizing gelling parameters of gellan gum for fibrocartilage tissue engineering.
Lee, Haeyeon; Fisher, Stephanie; Kallos, Michael S; Hunter, Christopher J
2011-08-01
Gellan gum is an attractive biomaterial for fibrocartilage tissue engineering applications because it is cell compatible, can be injected into a defect, and gels at body temperature. However, the gelling parameters of gellan gum have not yet been fully optimized. The aim of this study was to investigate the mechanics, degradation, gelling temperature, and viscosity of low acyl and low/high acyl gellan gum blends. Dynamic mechanical analysis showed that increased concentrations of low acyl gellan gum resulted in increased stiffness and the addition of high acyl gellan gum resulted in greatly decreased stiffness. Degradation studies showed that low acyl gellan gum was more stable than low/high acyl gellan gum blends. Gelling temperature studies showed that increased concentrations of low acyl gellan gum and CaCl₂ increased gelling temperature and low acyl gellan gum concentrations below 2% (w/v) would be most suitable for cell encapsulation. Gellan gum blends were generally found to have a higher gelling temperature than low acyl gellan gum. Viscosity studies showed that increased concentrations of low acyl gellan gum increased viscosity. Our results suggest that 2% (w/v) low acyl gellan gum would have the most appropriate mechanics, degradation, and gelling temperature for use in fibrocartilage tissue engineering applications. Copyright © 2011 Wiley Periodicals, Inc.
Relationships among various parameters for decision tree optimization
Hussain, Shahid
2014-01-14
In this chapter, we study, in detail, the relationships between various pairs of cost functions and between uncertainty measure and cost functions, for decision tree optimization. We provide new tools (algorithms) to compute relationship functions, as well as provide experimental results on decision tables acquired from UCI ML Repository. The algorithms presented in this paper have already been implemented and are now a part of Dagger, which is a software system for construction/optimization of decision trees and decision rules. The main results presented in this chapter deal with two types of algorithms for computing relationships; first, we discuss the case where we construct approximate decision trees and are interested in relationships between certain cost function, such as depth or number of nodes of a decision trees, and an uncertainty measure, such as misclassification error (accuracy) of decision tree. Secondly, relationships between two different cost functions are discussed, for example, the number of misclassification of a decision tree versus number of nodes in a decision trees. The results of experiments, presented in the chapter, provide further insight. © 2014 Springer International Publishing Switzerland.
Relationships among various parameters for decision tree optimization
Hussain, Shahid
2014-01-01
In this chapter, we study, in detail, the relationships between various pairs of cost functions and between uncertainty measure and cost functions, for decision tree optimization. We provide new tools (algorithms) to compute relationship functions, as well as provide experimental results on decision tables acquired from UCI ML Repository. The algorithms presented in this paper have already been implemented and are now a part of Dagger, which is a software system for construction/optimization of decision trees and decision rules. The main results presented in this chapter deal with two types of algorithms for computing relationships; first, we discuss the case where we construct approximate decision trees and are interested in relationships between certain cost function, such as depth or number of nodes of a decision trees, and an uncertainty measure, such as misclassification error (accuracy) of decision tree. Secondly, relationships between two different cost functions are discussed, for example, the number of misclassification of a decision tree versus number of nodes in a decision trees. The results of experiments, presented in the chapter, provide further insight. © 2014 Springer International Publishing Switzerland.
Directory of Open Access Journals (Sweden)
Zhiqiang GENG
2014-01-01
Full Text Available Output noise is strongly related to input in closed-loop control system, which makes model identification of closed-loop difficult, even unidentified in practice. The forward channel model is chosen to isolate disturbance from the output noise to input, and identified by optimization the dynamic characteristics of the process based on closed-loop operation data. The characteristics parameters of the process, such as dead time and time constant, are calculated and estimated based on the PI/PID controller parameters and closed-loop process input/output data. And those characteristics parameters are adopted to define the search space of the optimization identification algorithm. PSO-SQP optimization algorithm is applied to integrate the global search ability of PSO with the local search ability of SQP to identify the model parameters of forward channel. The validity of proposed method has been verified by the simulation. The practicability is checked with the PI/PID controller parameter turning based on identified forward channel model.
Optimization of dissolution process parameters for uranium ore concentrate powders
Energy Technology Data Exchange (ETDEWEB)
Misra, M.; Reddy, D.M.; Reddy, A.L.V.; Tiwari, S.K.; Venkataswamy, J.; Setty, D.S.; Sheela, S.; Saibaba, N. [Nuclear Fuel Complex, Hyderabad (India)
2013-07-01
Nuclear fuel complex processes Uranium Ore Concentrate (UOC) for producing uranium dioxide powder required for the fabrication of fuel assemblies for Pressurized Heavy Water Reactor (PHWR)s in India. UOC is dissolved in nitric acid and further purified by solvent extraction process for producing nuclear grade UO{sub 2} powder. Dissolution of UOC in nitric acid involves complex nitric oxide based reactions, since it is in the form of Uranium octa oxide (U{sub 3}O{sub 8}) or Uranium Dioxide (UO{sub 2}). The process kinetics of UOC dissolution is largely influenced by parameters like concentration and flow rate of nitric acid, temperature and air flow rate and found to have effect on recovery of nitric oxide as nitric acid. The plant scale dissolution of 2 MT batch in a single reactor is studied and observed excellent recovery of oxides of nitrogen (NO{sub x}) as nitric acid. The dissolution process is automated by PLC based Supervisory Control and Data Acquisition (SCADA) system for accurate control of process parameters and successfully dissolved around 200 Metric Tons of UOC. The paper covers complex chemistry involved in UOC dissolution process and also SCADA system. The solid and liquid reactions were studied along with multiple stoichiometry of nitrous oxide generated. (author)
Fiedler, Anna; Raeth, Sebastian; Theis, Fabian J; Hausser, Angelika; Hasenauer, Jan
2016-08-22
Ordinary differential equation (ODE) models are widely used to describe (bio-)chemical and biological processes. To enhance the predictive power of these models, their unknown parameters are estimated from experimental data. These experimental data are mostly collected in perturbation experiments, in which the processes are pushed out of steady state by applying a stimulus. The information that the initial condition is a steady state of the unperturbed process provides valuable information, as it restricts the dynamics of the process and thereby the parameters. However, implementing steady-state constraints in the optimization often results in convergence problems. In this manuscript, we propose two new methods for solving optimization problems with steady-state constraints. The first method exploits ideas from optimization algorithms on manifolds and introduces a retraction operator, essentially reducing the dimension of the optimization problem. The second method is based on the continuous analogue of the optimization problem. This continuous analogue is an ODE whose equilibrium points are the optima of the constrained optimization problem. This equivalence enables the use of adaptive numerical methods for solving optimization problems with steady-state constraints. Both methods are tailored to the problem structure and exploit the local geometry of the steady-state manifold and its stability properties. A parameterization of the steady-state manifold is not required. The efficiency and reliability of the proposed methods is evaluated using one toy example and two applications. The first application example uses published data while the second uses a novel dataset for Raf/MEK/ERK signaling. The proposed methods demonstrated better convergence properties than state-of-the-art methods employed in systems and computational biology. Furthermore, the average computation time per converged start is significantly lower. In addition to the theoretical results, the
Adaptive hybrid optimal quantum control for imprecisely characterized systems.
Egger, D J; Wilhelm, F K
2014-06-20
Optimal quantum control theory carries a huge promise for quantum technology. Its experimental application, however, is often hindered by imprecise knowledge of the input variables, the quantum system's parameters. We show how to overcome this by adaptive hybrid optimal control, using a protocol named Ad-HOC. This protocol combines open- and closed-loop optimal control by first performing a gradient search towards a near-optimal control pulse and then an experimental fidelity estimation with a gradient-free method. For typical settings in solid-state quantum information processing, adaptive hybrid optimal control enhances gate fidelities by an order of magnitude, making optimal control theory applicable and useful.
Parameter optimization for reproducible cardiac 1 H-MR spectroscopy at 3 Tesla.
de Heer, Paul; Bizino, Maurice B; Lamb, Hildo J; Webb, Andrew G
2016-11-01
frequency selective excitation water suppression (7.0%). Using the optimized parameters an intrasession limits of agreement of the myocardial triglyceride content of -0.11% to +0.04%, and an intersession of -0.15% to +0.9%, were achieved. The coefficient of variation was 5% for the intrasession reproducibility and 6.5% for the intersession reproducibility. Using approaches designed to optimize SNR and minimize the variation in inter-average signal intensities and frequencies/phases, a protocol was developed to perform cardiac MR spectroscopy on a clinical 3T system with high reproducibility. J. Magn. Reson. Imaging 2016;44:1151-1158. © 2016 International Society for Magnetic Resonance in Medicine.
Optimal sizing method for stand-alone photovoltaic power systems
Energy Technology Data Exchange (ETDEWEB)
Groumpos, P P; Papageorgiou, G
1987-01-01
The total life-cycle cost of stand-alone photovoltaic (SAPV) power systems is mathematically formulated. A new optimal sizing algorithm for the solar array and battery capacity is developed. The optimum value of a balancing parameter, M, for the optimal sizing of SAPV system components is derived. The proposed optimal sizing algorithm is used in an illustrative example, where a more economical life-cycle cost has bene obtained. The question of cost versus reliability is briefly discussed.
Lobato, Fran Sérgio
2017-01-01
This book is aimed at undergraduate and graduate students in applied mathematics or computer science, as a tool for solving real-world design problems. The present work covers fundamentals in multi-objective optimization and applications in mathematical and engineering system design using a new optimization strategy, namely the Self-Adaptive Multi-objective Optimization Differential Evolution (SA-MODE) algorithm. This strategy is proposed in order to reduce the number of evaluations of the objective function through dynamic update of canonical Differential Evolution parameters (population size, crossover probability and perturbation rate). The methodology is applied to solve mathematical functions considering test cases from the literature and various engineering systems design, such as cantilevered beam design, biochemical reactor, crystallization process, machine tool spindle design, rotary dryer design, among others.
Application of HGSO to security based optimal placement and parameter setting of UPFC
International Nuclear Information System (INIS)
Tarafdar Hagh, Mehrdad; Alipour, Manijeh; Teimourzadeh, Saeed
2014-01-01
Highlights: • A new method for solving the security based UPFC placement and parameter setting problem is proposed. • The proposed method is a global method for all mixed-integer problems. • The proposed method has the ability of the parallel search in binary and continues space. • By using the proposed method, most of the problems due to line contingencies are solved. • Comparison studies are done to compare the performance of the proposed method. - Abstract: This paper presents a novel method to solve security based optimal placement and parameter setting of unified power flow controller (UPFC) problem based on hybrid group search optimization (HGSO) technique. Firstly, HGSO is introduced in order to solve mix-integer type problems. Afterwards, the proposed method is applied to the security based optimal placement and parameter setting of UPFC problem. The focus of the paper is to enhance the power system security through eliminating or minimizing the over loaded lines and the bus voltage limit violations under single line contingencies. Simulation studies are carried out on the IEEE 6-bus, IEEE 14-bus and IEEE 30-bus systems in order to verify the accuracy and robustness of the proposed method. The results indicate that by using the proposed method, the power system remains secure under single line contingencies
Saturne II synchroton injector parameters operation and control: computerization and optimization
International Nuclear Information System (INIS)
Lagniel, J.M.
1983-01-01
The injector control system has been studied, aiming at the beam quality improvement, the increasing of the versatility, and a better machine availability. It has been choosen to realize the three following functions: - acquisition of the principal parameters of the process, so as to control them quickly and to be warned if one of them is wrong (monitoring); - the control of those parameters, one by one or by families (starting, operating point); - the research of an optimal control (on a model or on the process itself) [fr
Li, Rui
2009-01-01
The target of this work is to extend the canonical Evolution Strategies (ES) from traditional real-valued parameter optimization domain to mixed-integer parameter optimization domain. This is necessary because there exist numerous practical optimization problems from industry in which the set of
Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control
Vavrina, Matthew A.; Englander, Jacob Aldo; Ghosh, Alexander R.
2015-01-01
The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.
Cogeneration system simulation/optimization
International Nuclear Information System (INIS)
Puppa, B.A.; Chandrashekar, M.
1992-01-01
Companies are increasingly turning to computer software programs to improve and streamline the analysis o cogeneration systems. This paper introduces a computer program which originated with research at the University of Waterloo. The program can simulate and optimize any type of layout of cogeneration plant. An application of the program to a cogeneration feasibility study for a university campus is described. The Steam and Power Plant Optimization System (SAPPOS) is a PC software package which allows users to model any type of steam/power plant on a component-by-component basis. Individual energy/steam balances can be done quickly to model any scenario. A typical days per month cogeneration simulation can also be carried out to provide a detailed monthly cash flow and energy forecast. This paper reports that SAPPOS can be used for scoping, feasibility, and preliminary design work, along with financial studies, gas contract studies, and optimizing the operation of completed plants. In the feasibility study presented, SAPPOS is used to evaluate both diesel engine and gas turbine combined cycle options
Analysis and optimization of machining parameters of laser cutting for polypropylene composite
Deepa, A.; Padmanabhan, K.; Kuppan, P.
2017-11-01
Present works explains about machining of self-reinforced Polypropylene composite fabricated using hot compaction method. The objective of the experiment is to find optimum machining parameters for Polypropylene (PP). Laser power and Machining speed were the parameters considered in response to tensile test and Flexure test. Taguchi method is used for experimentation. Grey Relational Analysis (GRA) is used for multiple process parameter optimization. ANOVA (Analysis of Variance) is used to find impact for process parameter. Polypropylene has got the great application in various fields like, it is used in the form of foam in model aircraft and other radio-controlled vehicles, thin sheets (∼2-20μm) used as a dielectric, PP is also used in piping system, it is also been used in hernia and pelvic organ repair or protect new herrnis in the same location.
Janardhanan, S.; Datta, B.
2011-12-01
saltwater intrusion are considered. The salinity levels resulting at strategic locations due to these pumping are predicted using the ensemble surrogates and are constrained to be within pre-specified levels. Different realizations of the concentration values are obtained from the ensemble predictions corresponding to each candidate solution of pumping. Reliability concept is incorporated as the percent of the total number of surrogate models which satisfy the imposed constraints. The methodology was applied to a realistic coastal aquifer system in Burdekin delta area in Australia. It was found that all optimal solutions corresponding to a reliability level of 0.99 satisfy all the constraints and as reducing reliability level decreases the constraint violation increases. Thus ensemble surrogate model based simulation-optimization was found to be useful in deriving multi-objective optimal pumping strategies for coastal aquifers under parameter uncertainty.
WE-AB-209-09: Optimization of Rotational Arc Station Parameter Optimized Radiation Therapy
Energy Technology Data Exchange (ETDEWEB)
Dong, P; Xing, L [Stanford University School of Medicine, Stanford, CA (United States); Ungun, B [Stanford University School of Medicine, Stanford, CA (United States); Stanford University School of Engineering, Stanford, CA (United States); Boyd, S [Stanford University School of Engineering, Stanford, CA (United States)
2016-06-15
Purpose: To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of improving VMAT in both plan quality and delivery efficiency. Methods: The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state-of-the-art GPU based Proximal Operator Graph Solver (POGS) within seconds. Apertures with zero or low weight were thrown out. To avoid being trapped in a local minimum, a stochastic gradient descent method was employed which also greatly increased the convergence rate of the objective function. The above procedure repeated until the plan could not be improved any further. A weighting factor associated with the total plan MU also indirectly controlled the complexities of aperture shapes. The number of apertures for VMAT and SPORT was confined to 180. The SPORT allowed the coexistence of multiple apertures in a single SP. The optimization technique was assessed by using three clinical cases (prostate, H&N and brain). Results: Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. Prostate case: the volume of the 50% prescription dose was decreased by 22% for the rectum. H&N case: SPORT improved the mean dose for the left and right parotids by 15% each. Brain case: the doses to the eyes, chiasm and inner ears were all improved. SPORT shortened the treatment time by ∼1 min for the prostate case, ∼0.5 min for brain case, and ∼0.2 min for the H&N case. Conclusion: The superior dosimetric quality and delivery efficiency presented here indicates that SPORT is an intriguing alternative treatment modality.
WE-AB-209-09: Optimization of Rotational Arc Station Parameter Optimized Radiation Therapy
International Nuclear Information System (INIS)
Dong, P; Xing, L; Ungun, B; Boyd, S
2016-01-01
Purpose: To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of improving VMAT in both plan quality and delivery efficiency. Methods: The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state-of-the-art GPU based Proximal Operator Graph Solver (POGS) within seconds. Apertures with zero or low weight were thrown out. To avoid being trapped in a local minimum, a stochastic gradient descent method was employed which also greatly increased the convergence rate of the objective function. The above procedure repeated until the plan could not be improved any further. A weighting factor associated with the total plan MU also indirectly controlled the complexities of aperture shapes. The number of apertures for VMAT and SPORT was confined to 180. The SPORT allowed the coexistence of multiple apertures in a single SP. The optimization technique was assessed by using three clinical cases (prostate, H&N and brain). Results: Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. Prostate case: the volume of the 50% prescription dose was decreased by 22% for the rectum. H&N case: SPORT improved the mean dose for the left and right parotids by 15% each. Brain case: the doses to the eyes, chiasm and inner ears were all improved. SPORT shortened the treatment time by ∼1 min for the prostate case, ∼0.5 min for brain case, and ∼0.2 min for the H&N case. Conclusion: The superior dosimetric quality and delivery efficiency presented here indicates that SPORT is an intriguing alternative treatment modality.
Energy Technology Data Exchange (ETDEWEB)
Portnoy, David, E-mail: david.portnoy@jhuapl.edu [Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Road, Laurel, MD 20723 (United States); Feuerbach, Robert; Heimberg, Jennifer [Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Road, Laurel, MD 20723 (United States)
2011-10-01
Today there is a tremendous amount of interest in systems that can detect radiological or nuclear threats. Many of these systems operate in extremely high throughput situations where delays caused by false alarms can have a significant negative impact. Thus, calculating the tradeoff between detection rates and false alarm rates is critical for their successful operation. Receiver operating characteristic (ROC) curves have long been used to depict this tradeoff. The methodology was first developed in the field of signal detection. In recent years it has been used increasingly in machine learning and data mining applications. It follows that this methodology could be applied to radiological/nuclear threat detection systems. However many of these systems do not fit into the classic principles of statistical detection theory because they tend to lack tractable likelihood functions and have many parameters, which, in general, do not have a one-to-one correspondence with the detection classes. This work proposes a strategy to overcome these problems by empirically finding parameter values that maximize the probability of detection for a selected number of probabilities of false alarm. To find these parameter values a statistical global optimization technique that seeks to estimate portions of a ROC curve is proposed. The optimization combines elements of simulated annealing with elements of genetic algorithms. Genetic algorithms were chosen because they can reduce the risk of getting stuck in local minima. However classic genetic algorithms operate on arrays of Booleans values or bit strings, so simulated annealing is employed to perform mutation in the genetic algorithm. The presented initial results were generated using an isotope identification algorithm developed at Johns Hopkins University Applied Physics Laboratory. The algorithm has 12 parameters: 4 real-valued and 8 Boolean. A simulated dataset was used for the optimization study; the 'threat' set of
International Nuclear Information System (INIS)
Portnoy, David; Feuerbach, Robert; Heimberg, Jennifer
2011-01-01
Today there is a tremendous amount of interest in systems that can detect radiological or nuclear threats. Many of these systems operate in extremely high throughput situations where delays caused by false alarms can have a significant negative impact. Thus, calculating the tradeoff between detection rates and false alarm rates is critical for their successful operation. Receiver operating characteristic (ROC) curves have long been used to depict this tradeoff. The methodology was first developed in the field of signal detection. In recent years it has been used increasingly in machine learning and data mining applications. It follows that this methodology could be applied to radiological/nuclear threat detection systems. However many of these systems do not fit into the classic principles of statistical detection theory because they tend to lack tractable likelihood functions and have many parameters, which, in general, do not have a one-to-one correspondence with the detection classes. This work proposes a strategy to overcome these problems by empirically finding parameter values that maximize the probability of detection for a selected number of probabilities of false alarm. To find these parameter values a statistical global optimization technique that seeks to estimate portions of a ROC curve is proposed. The optimization combines elements of simulated annealing with elements of genetic algorithms. Genetic algorithms were chosen because they can reduce the risk of getting stuck in local minima. However classic genetic algorithms operate on arrays of Booleans values or bit strings, so simulated annealing is employed to perform mutation in the genetic algorithm. The presented initial results were generated using an isotope identification algorithm developed at Johns Hopkins University Applied Physics Laboratory. The algorithm has 12 parameters: 4 real-valued and 8 Boolean. A simulated dataset was used for the optimization study; the 'threat' set of spectra
Portnoy, David; Feuerbach, Robert; Heimberg, Jennifer
2011-10-01
Today there is a tremendous amount of interest in systems that can detect radiological or nuclear threats. Many of these systems operate in extremely high throughput situations where delays caused by false alarms can have a significant negative impact. Thus, calculating the tradeoff between detection rates and false alarm rates is critical for their successful operation. Receiver operating characteristic (ROC) curves have long been used to depict this tradeoff. The methodology was first developed in the field of signal detection. In recent years it has been used increasingly in machine learning and data mining applications. It follows that this methodology could be applied to radiological/nuclear threat detection systems. However many of these systems do not fit into the classic principles of statistical detection theory because they tend to lack tractable likelihood functions and have many parameters, which, in general, do not have a one-to-one correspondence with the detection classes. This work proposes a strategy to overcome these problems by empirically finding parameter values that maximize the probability of detection for a selected number of probabilities of false alarm. To find these parameter values a statistical global optimization technique that seeks to estimate portions of a ROC curve is proposed. The optimization combines elements of simulated annealing with elements of genetic algorithms. Genetic algorithms were chosen because they can reduce the risk of getting stuck in local minima. However classic genetic algorithms operate on arrays of Booleans values or bit strings, so simulated annealing is employed to perform mutation in the genetic algorithm. The presented initial results were generated using an isotope identification algorithm developed at Johns Hopkins University Applied Physics Laboratory. The algorithm has 12 parameters: 4 real-valued and 8 Boolean. A simulated dataset was used for the optimization study; the "threat" set of spectra
Liu, Jianguo; Yang, Bo; Chen, Changzhen
2013-02-01
The optimization of operating parameters for the isolation of peroxidase from horseradish (Armoracia rusticana) roots with ultrafiltration (UF) technology was systemically studied. The effects of UF operating conditions on the transmission of proteins were quantified using the parameter scanning UF. These conditions included solution pH, ionic strength, stirring speed and permeate flux. Under optimized conditions, the purity of horseradish peroxidase (HRP) obtained was greater than 84 % after a two-stage UF process and the recovery of HRP from the feedstock was close to 90 %. The resulting peroxidase product was then analysed by isoelectric focusing, SDS-PAGE and circular dichroism, to confirm its isoelectric point, molecular weight and molecular secondary structure. The effects of calcium ion on HRP specific activities were also experimentally determined.
Performance Evaluation and Parameter Optimization of SoftCast Wireless Video Broadcast
Directory of Open Access Journals (Sweden)
Dongxue Yang
2015-08-01
Full Text Available Wireless video broadcast plays an imp ortant role in multimedia communication with the emergence of mobile video applications. However, conventional video broadcast designs suffer from a cliff effect due to separated source and channel encoding. The newly prop osed SoftCast scheme employs a cross-layer design, whose reconstructed video quality is prop ortional to the channel condition. In this pap er, we provide the p erformance evaluation and the parameter optimization of the SoftCast system. Optimization principles on parameter selection are suggested to obtain a b etter video quality, o ccupy less bandwidth and/or utilize lower complexity. In addition, we compare SoftCast with H.264 in the LTE EPA scenario. The simulation results show that SoftCast provides a b etter p erformance in the scalability to channel conditions and the robustness to packet losses.
Parameter identifiability of linear dynamical systems
Glover, K.; Willems, J. C.
1974-01-01
It is assumed that the system matrices of a stationary linear dynamical system were parametrized by a set of unknown parameters. The question considered here is, when can such a set of unknown parameters be identified from the observed data? Conditions for the local identifiability of a parametrization are derived in three situations: (1) when input/output observations are made, (2) when there exists an unknown feedback matrix in the system and (3) when the system is assumed to be driven by white noise and only output observations are made. Also a sufficient condition for global identifiability is derived.
A procedure for multi-objective optimization of tire design parameters
Nikola Korunović; Miloš Madić; Miroslav Trajanović; Miroslav Radovanović
2015-01-01
The identification of optimal tire design parameters for satisfying different requirements, i.e. tire performance characteristics, plays an essential role in tire design. In order to improve tire performance characteristics, formulation and solving of multi-objective optimization problem must be performed. This paper presents a multi-objective optimization procedure for determination of optimal tire design parameters for simultaneous minimization of strain energy density at two distinctive zo...
Optimization of Loudspeaker Part Design Parameters by Air Viscosity Damping Effect
Yue Hu; Xilu Zhao; Takao Yamaguchi; Manabu Sasajima; Yoshio Koike; Akira Hara
2016-01-01
This study optimized the design parameters of a cone loudspeaker as an example of high flexibility of the product design. We developed an acoustic analysis software program that considers the impact of damping caused by air viscosity. In sound reproduction, it is difficult to optimize each parameter of the loudspeaker design. To overcome the limitation of the design problem in practice, this study presents an acoustic analysis algorithm to optimize the design parameters of the loudspeaker. Th...
Optimal concentrations in transport systems
Jensen, Kaare H.; Kim, Wonjung; Holbrook, N. Michele; Bush, John W. M.
2013-01-01
Many biological and man-made systems rely on transport systems for the distribution of material, for example matter and energy. Material transfer in these systems is determined by the flow rate and the concentration of material. While the most concentrated solutions offer the greatest potential in terms of material transfer, impedance typically increases with concentration, thus making them the most difficult to transport. We develop a general framework for describing systems for which impedance increases with concentration, and consider material flow in four different natural systems: blood flow in vertebrates, sugar transport in vascular plants and two modes of nectar drinking in birds and insects. The model provides a simple method for determining the optimum concentration copt in these systems. The model further suggests that the impedance at the optimum concentration μopt may be expressed in terms of the impedance of the pure (c = 0) carrier medium μ0 as μopt∼2αμ0, where the power α is prescribed by the specific flow constraints, for example constant pressure for blood flow (α = 1) or constant work rate for certain nectar-drinking insects (α = 6). Comparing the model predictions with experimental data from more than 100 animal and plant species, we find that the simple model rationalizes the observed concentrations and impedances. The model provides a universal framework for studying flows impeded by concentration, and yields insight into optimization in engineered systems, such as traffic flow. PMID:23594815
Energy Technology Data Exchange (ETDEWEB)
Tiwari, S.K.; Reddy, A.L.V.; Venkataswamy, J.; Misra, M.; Setty, D.S.; Sheela, S.; Saibaba, N., E-mail: misra@nfc.gov.in [Nuclear Fuel Complex, Hyderabad (India)
2013-07-01
Nuclear reactor grade natural uranium dioxide powder is being produced through precipitation route, which is further processed before converting into sintered pellets used in the fabrication of PHWR fuel assemblies of 220 and 540 MWe type reactors. The process of precipitating Uranyl Nitrate Pure Solution (UNPS) is an important step in the UO{sub 2} powder production line, where in soluble uranium is transformed into solid form of Ammonium Uranate (AU), which in turn reflects and decides the powder characteristics. Precipitation of UNPS with vapour ammonia is being carried out in semi batch process and process parameters like ammonia flow rate, temperature, concentration of UNPS and free acidity of UNPS are very critical and decides the UO{sub 2} powder quality. Variation in these critical parameters influences powder characteristics, which in turn influences the sinterability of UO{sub 2} powder. In order to get consistent powder quality and sinterability the critical parameter like ammonia flow rate during precipitation is studied, optimized and validated. The critical process parameters are controlled through PLC based automated on-line data acquisition systems for achieving consistent powder quality with increased recovery and production. The present paper covers optimization of process parameters and powder characteristics. (author)
Optimization of process parameters in precipitation for consistent quality UO2 powder production
International Nuclear Information System (INIS)
Tiwari, S.K.; Reddy, A.L.V.; Venkataswamy, J.; Misra, M.; Setty, D.S.; Sheela, S.; Saibaba, N.
2013-01-01
Nuclear reactor grade natural uranium dioxide powder is being produced through precipitation route, which is further processed before converting into sintered pellets used in the fabrication of PHWR fuel assemblies of 220 and 540 MWe type reactors. The process of precipitating Uranyl Nitrate Pure Solution (UNPS) is an important step in the UO 2 powder production line, where in soluble uranium is transformed into solid form of Ammonium Uranate (AU), which in turn reflects and decides the powder characteristics. Precipitation of UNPS with vapour ammonia is being carried out in semi batch process and process parameters like ammonia flow rate, temperature, concentration of UNPS and free acidity of UNPS are very critical and decides the UO 2 powder quality. Variation in these critical parameters influences powder characteristics, which in turn influences the sinterability of UO 2 powder. In order to get consistent powder quality and sinterability the critical parameter like ammonia flow rate during precipitation is studied, optimized and validated. The critical process parameters are controlled through PLC based automated on-line data acquisition systems for achieving consistent powder quality with increased recovery and production. The present paper covers optimization of process parameters and powder characteristics. (author)
An, Li-sha; Liu, Chun-jiao; Liu, Ying-wen
2018-05-01
In the polysilicon chemical vapor deposition reactor, the operating parameters are complex to affect the polysilicon's output. Therefore, it is very important to address the coupling problem of multiple parameters and solve the optimization in a computationally efficient manner. Here, we adopted Response Surface Methodology (RSM) to analyze the complex coupling effects of different operating parameters on silicon deposition rate (R) and further achieve effective optimization of the silicon CVD system. Based on finite numerical experiments, an accurate RSM regression model is obtained and applied to predict the R with different operating parameters, including temperature (T), pressure (P), inlet velocity (V), and inlet mole fraction of H2 (M). The analysis of variance is conducted to describe the rationality of regression model and examine the statistical significance of each factor. Consequently, the optimum combination of operating parameters for the silicon CVD reactor is: T = 1400 K, P = 3.82 atm, V = 3.41 m/s, M = 0.91. The validation tests and optimum solution show that the results are in good agreement with those from CFD model and the deviations of the predicted values are less than 4.19%. This work provides a theoretical guidance to operate the polysilicon CVD process.
TLM modeling and system identification of optimized antenna structures
Directory of Open Access Journals (Sweden)
N. Fichtner
2008-05-01
Full Text Available The transmission line matrix (TLM method in conjunction with the genetic algorithm (GA is presented for the bandwidth optimization of a low profile patch antenna. The optimization routine is supplemented by a system identification (SI procedure. By the SI the model parameters of the structure are estimated which is used for a reduction of the total TLM simulation time. The SI utilizes a new stability criterion of the physical poles for the parameter extraction.
Chen, Z.; Chen, J.; Zheng, X.; Jiang, F.; Zhang, S.; Ju, W.; Yuan, W.; Mo, G.
2014-12-01
In this study, we explore the feasibility of optimizing ecosystem photosynthetic and respiratory parameters from the seasonal variation pattern of the net carbon flux. An optimization scheme is proposed to estimate two key parameters (Vcmax and Q10) by exploiting the seasonal variation in the net ecosystem carbon flux retrieved by an atmospheric inversion system. This scheme is implemented to estimate Vcmax and Q10 of the Boreal Ecosystem Productivity Simulator (BEPS) to improve its NEP simulation in the Boreal North America (BNA) region. Simultaneously, in-situ NEE observations at six eddy covariance sites are used to evaluate the NEE simulations. The results show that the performance of the optimized BEPS is superior to that of the BEPS with the default parameter values. These results have the implication on using atmospheric CO2 data for optimizing ecosystem parameters through atmospheric inversion or data assimilation techniques.
System parameter identification information criteria and algorithms
Chen, Badong; Hu, Jinchun; Principe, Jose C
2013-01-01
Recently, criterion functions based on information theoretic measures (entropy, mutual information, information divergence) have attracted attention and become an emerging area of study in signal processing and system identification domain. This book presents a systematic framework for system identification and information processing, investigating system identification from an information theory point of view. The book is divided into six chapters, which cover the information needed to understand the theory and application of system parameter identification. The authors' research pr
Optimization-Based Inverse Identification of the Parameters of a Concrete Cap Material Model
Král, Petr; Hokeš, Filip; Hušek, Martin; Kala, Jiří; Hradil, Petr
2017-10-01
Issues concerning the advanced numerical analysis of concrete building structures in sophisticated computing systems currently require the involvement of nonlinear mechanics tools. The efforts to design safer, more durable and mainly more economically efficient concrete structures are supported via the use of advanced nonlinear concrete material models and the geometrically nonlinear approach. The application of nonlinear mechanics tools undoubtedly presents another step towards the approximation of the real behaviour of concrete building structures within the framework of computer numerical simulations. However, the success rate of this application depends on having a perfect understanding of the behaviour of the concrete material models used and having a perfect understanding of the used material model parameters meaning. The effective application of nonlinear concrete material models within computer simulations often becomes very problematic because these material models very often contain parameters (material constants) whose values are difficult to obtain. However, getting of the correct values of material parameters is very important to ensure proper function of a concrete material model used. Today, one possibility, which permits successful solution of the mentioned problem, is the use of optimization algorithms for the purpose of the optimization-based inverse material parameter identification. Parameter identification goes hand in hand with experimental investigation while it trying to find parameter values of the used material model so that the resulting data obtained from the computer simulation will best approximate the experimental data. This paper is focused on the optimization-based inverse identification of the parameters of a concrete cap material model which is known under the name the Continuous Surface Cap Model. Within this paper, material parameters of the model are identified on the basis of interaction between nonlinear computer simulations
Design and Simulation of PID parameters self-tuning based on DC speed regulating system
Directory of Open Access Journals (Sweden)
Feng Wei Jie
2016-01-01
Full Text Available The DC speed regulating system has many difficult issues such as system parameters and PID control parameters are difficult to determine. On the basis of model for a single closed-loop DC speed regulating system, this paper puts forward a method of PID parameters self-tuning based on the step response detection and reduced order equivalent. First, detect system step response and get response parameters. Then equal it to a second order system model, and achieve optimal PID control parameters based on optimal second order system to realize of PID parameters self-tuning. The PID parameters self-tuning process of DC speed regulating system is simulated with the help of MATLAB/Simulink. The simulation results show that the method is simple and effective. The system can obtain good dynamic and static performance when the PID parameters are applied to DC speed regulating system.
Optimization of machining parameters of hard porcelain on a CNC ...
African Journals Online (AJOL)
s (2010) focus was to calculate drilled composite's surface roughness with the application of ... instance, objective function as well as restrictions on rotor enactment. ..... to aerodynamic optimization design of helicopter rotor blade, International.
Characterization of PV panel and global optimization of its model parameters using genetic algorithm
International Nuclear Information System (INIS)
Ismail, M.S.; Moghavvemi, M.; Mahlia, T.M.I.
2013-01-01
Highlights: • Genetic Algorithm optimization ability had been utilized to extract parameters of PV panel model. • Effect of solar radiation and temperature variations was taken into account in fitness function evaluation. • We used Matlab-Simulink to simulate operation of the PV-panel to validate results. • Different cases were analyzed to ascertain which of them gives more accurate results. • Accuracy and applicability of this approach to be used as a valuable tool for PV modeling were clearly validated. - Abstract: This paper details an improved modeling technique for a photovoltaic (PV) module; utilizing the optimization ability of a genetic algorithm, with different parameters of the PV module being computed via this approach. The accurate modeling of any PV module is incumbent upon the values of these parameters, as it is imperative in the context of any further studies concerning different PV applications. Simulation, optimization and the design of the hybrid systems that include PV are examples of these applications. The global optimization of the parameters and the applicability for the entire range of the solar radiation and a wide range of temperatures are achievable via this approach. The Manufacturer’s Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. The results of single-diode and two-diode models are evaluated in order to ascertain which of them are more accurate. Other cases are also analyzed in this paper for the purpose of comparison. The Matlab–Simulink environment is used to simulate the operation of the PV module, depending on the extracted parameters. The results of the simulation are compared with the Data Sheet information, which is obtained via experimentation in order to validate the reliability of the approach. Three types of PV modules
Distributed Robust Optimization in Networked System.
Wang, Shengnan; Li, Chunguang
2016-10-11
In this paper, we consider a distributed robust optimization (DRO) problem, where multiple agents in a networked system cooperatively minimize a global convex objective function with respect to a global variable under the global constraints. The objective function can be represented by a sum of local objective functions. The global constraints contain some uncertain parameters which are partially known, and can be characterized by some inequality constraints. After problem transformation, we adopt the Lagrangian primal-dual method to solve this problem. We prove that the primal and dual optimal solutions of the problem are restricted in some specific sets, and we give a method to construct these sets. Then, we propose a DRO algorithm to find the primal-dual optimal solutions of the Lagrangian function, which consists of a subgradient step, a projection step, and a diffusion step, and in the projection step of the algorithm, the optimized variables are projected onto the specific sets to guarantee the boundedness of the subgradients. Convergence analysis and numerical simulations verifying the performance of the proposed algorithm are then provided. Further, for nonconvex DRO problem, the corresponding approach and algorithm framework are also provided.
An automatic and effective parameter optimization method for model tuning
Directory of Open Access Journals (Sweden)
T. Zhang
2015-11-01
simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.
Optimal parameters for the FFA-Beddoes dynamic stall model
Energy Technology Data Exchange (ETDEWEB)
Bjoerck, A; Mert, M [FFA, The Aeronautical Research Institute of Sweden, Bromma (Sweden); Madsen, H A [Risoe National Lab., Roskilde (Denmark)
1999-03-01
Unsteady aerodynamic effects, like dynamic stall, must be considered in calculation of dynamic forces for wind turbines. Models incorporated in aero-elastic programs are of semi-empirical nature. Resulting aerodynamic forces therefore depend on values used for the semi-empiricial parameters. In this paper a study of finding appropriate parameters to use with the Beddoes-Leishman model is discussed. Minimisation of the `tracking error` between results from 2D wind tunnel tests and simulation with the model is used to find optimum values for the parameters. The resulting optimum parameters show a large variation from case to case. Using these different sets of optimum parameters in the calculation of blade vibrations, give rise to quite different predictions of aerodynamic damping which is discussed. (au)
Kalabukhov, D. S.; Radko, V. M.; Grigoriev, V. A.
2018-01-01
Ultra-low power turbine drives are used as energy sources in auxiliary power systems, energy units, terrestrial, marine, air and space transport within the confines of shaft power N td = 0.01…10 kW. In this paper we propose a new approach to the development of surrogate models for evaluating the integrated efficiency of multistage ultra-low power impulse turbine with pressure stages. This method is based on the use of existing mathematical models of ultra-low power turbine stage efficiency and mass. It has been used in a method for selecting the rational parameters of two-stage axial ultra-low power turbine. The article describes the basic features of an algorithm for two-stage turbine parameters optimization and for efficiency criteria evaluating. Pledged mathematical models are intended for use at the preliminary design of turbine drive. The optimization method was tested at preliminary design of an air starter turbine. Validation was carried out by comparing the results of optimization calculations and numerical gas-dynamic simulation in the Ansys CFX package. The results indicate a sufficient accuracy of used surrogate models for axial two-stage turbine parameters selection
Alzraiee, Ayman H.; Bau, Domenico A.; Garcia, Luis A.
2013-06-01
Effective sampling of hydrogeological systems is essential in guiding groundwater management practices. Optimal sampling of groundwater systems has previously been formulated based on the assumption that heterogeneous subsurface properties can be modeled using a geostatistical approach. Therefore, the monitoring schemes have been developed to concurrently minimize the uncertainty in the spatial distribution of systems' states and parameters, such as the hydraulic conductivity K and the hydraulic head H, and the uncertainty in the geostatistical model of system parameters using a single objective function that aggregates all objectives. However, it has been shown that the aggregation of possibly conflicting objective functions is sensitive to the adopted aggregation scheme and may lead to distorted results. In addition, the uncertainties in geostatistical parameters affect the uncertainty in the spatial prediction of K and H according to a complex nonlinear relationship, which has often been ineffectively evaluated using a first-order approximation. In this study, we propose a multiobjective optimization framework to assist the design of monitoring networks of K and H with the goal of optimizing their spatial predictions and estimating the geostatistical parameters of the K field. The framework stems from the combination of a data assimilation (DA) algorithm and a multiobjective evolutionary algorithm (MOEA). The DA algorithm is based on the ensemble Kalman filter, a Monte-Carlo-based Bayesian update scheme for nonlinear systems, which is employed to approximate the posterior uncertainty in K, H, and the geostatistical parameters of K obtained by collecting new measurements. Multiple MOEA experiments are used to investigate the trade-off among design objectives and identify the corresponding monitoring schemes. The methodology is applied to design a sampling network for a shallow unconfined groundwater system located in Rocky Ford, Colorado. Results indicate that
International Nuclear Information System (INIS)
Avrigeanu, M.; Avrigeanu, V.
1994-09-01
A proposal for an optical potential parameter compilation format like-EXFOR system is presented, in total agreement with the structure of EXFOR. With respect to the primary RIPL objectives, an extended subroutine SYSPOT of the widely-used optical model code SCAT2, which is actually a library of global and regional optical potential parameter sets, could be well-suited. A version which allows the use of a great part of published potentials is also given. (Author) 1 Tab., 21 Refs
Directory of Open Access Journals (Sweden)
Jingxian Hao
2016-11-01
Full Text Available The rule-based logic threshold control strategy has been frequently used in energy management strategies for hybrid electric vehicles (HEVs owing to its convenience in adjusting parameters, real-time performance, stability, and robustness. However, the logic threshold control parameters cannot usually ensure the best vehicle performance at different driving cycles and conditions. For this reason, the optimization of key parameters is important to improve the fuel economy, dynamic performance, and drivability. In principle, this is a multiparameter nonlinear optimization problem. The logic threshold energy management strategy for an all-wheel-drive HEV is comprehensively analyzed and developed in this study. Seven key parameters to be optimized are extracted. The optimization model of key parameters is proposed from the perspective of fuel economy. The global optimization method, DIRECT algorithm, which has good real-time performance, low computational burden, rapid convergence, is selected to optimize the extracted key parameters globally. The results show that with the optimized parameters, the engine operates more at the high efficiency range resulting into a fuel savings of 7% compared with non-optimized parameters. The proposed method can provide guidance for calibrating the parameters of the vehicle energy management strategy from the perspective of fuel economy.
Yudin, V I; Taichenachev, A V; Basalaev, M Yu; Kovalenko, D V
2017-02-06
We theoretically investigate the dynamic regime of coherent population trapping (CPT) in the presence of frequency modulation (FM). We have formulated the criteria for quasi-stationary (adiabatic) and dynamic (non-adiabatic) responses of atomic system driven by this FM. Using the density matrix formalism for Λ system, the error signal is exactly calculated and optimized. It is shown that the optimal FM parameters correspond to the dynamic regime of atomic-field interaction, which significantly differs from conventional description of CPT resonances in the frame of quasi-stationary approach (under small modulation frequency). Obtained theoretical results are in good qualitative agreement with different experiments. Also we have found CPT-analogue of Pound-Driver-Hall regime of frequency stabilization.
Accuracy Analysis and Parameters Optimization in Urban Flood Simulation by PEST Model
Keum, H.; Han, K.; Kim, H.; Ha, C.
2017-12-01
The risk of urban flooding has been increasing due to heavy rainfall, flash flooding and rapid urbanization. Rainwater pumping stations, underground reservoirs are used to actively take measures against flooding, however, flood damage from lowlands continues to occur. Inundation in urban areas has resulted in overflow of sewer. Therefore, it is important to implement a network system that is intricately entangled within a city, similar to the actual physical situation and accurate terrain due to the effects on buildings and roads for accurate two-dimensional flood analysis. The purpose of this study is to propose an optimal scenario construction procedure watershed partitioning and parameterization for urban runoff analysis and pipe network analysis, and to increase the accuracy of flooded area prediction through coupled model. The establishment of optimal scenario procedure was verified by applying it to actual drainage in Seoul. In this study, optimization was performed by using four parameters such as Manning's roughness coefficient for conduits, watershed width, Manning's roughness coefficient for impervious area, Manning's roughness coefficient for pervious area. The calibration range of the parameters was determined using the SWMM manual and the ranges used in the previous studies, and the parameters were estimated using the automatic calibration method PEST. The correlation coefficient showed a high correlation coefficient for the scenarios using PEST. The RPE and RMSE also showed high accuracy for the scenarios using PEST. In the case of RPE, error was in the range of 13.9-28.9% in the no-parameter estimation scenarios, but in the scenario using the PEST, the error range was reduced to 6.8-25.7%. Based on the results of this study, it can be concluded that more accurate flood analysis is possible when the optimum scenario is selected by determining the appropriate reference conduit for future urban flooding analysis and if the results is applied to various
Overall Optimization for Offshore Wind Farm Electrical System
DEFF Research Database (Denmark)
Hou, Peng; Hu, Weihao; Chen, Cong
2017-01-01
Based on particle swarm optimization (PSO), an optimization platform for offshore wind farm electrical system (OWFES) is proposed in this paper, where the main components of an offshore wind farm and key technical constraints are considered as input parameters. The offshore wind farm electrical...... system is optimized in accordance with initial investment by considering three aspects: the number and siting of offshore substations (OS), the cable connection layout of both collection system (CS) and transmission system (TS) as well as the selection of electrical components in terms of voltage level...... that save 3.01% total cost compared with the industrial layout, and can be a useful tool for OWFES design and evaluation....
Optimization of turning process parameters by using grey-Taguchi
African Journals Online (AJOL)
DR OKE
... India continue to choose the operating conditions solely on the basis of handbook values .... Surface Roughness Measuring instrument ... process control parameters like spindle speed, feed and depth of cut. ..... and Industrial Engineering.
Sensitive parameters' optimization of the permanent magnet supporting mechanism
Energy Technology Data Exchange (ETDEWEB)
Liu, Yongguang; Gao, Xiaohui; Wang, Yixuan; Yang, Xiaowei [Beihang University, Beijing (China)
2014-07-15
The fast development of the ultra-high speed vertical rotor promotes the study and exploration for the supporting mechanism. It has become the focus of research that how to improve the speed and overcome the vibration when the rotors pass through the low-order critical frequencies. This paper introduces a kind of permanent magnet (PM) supporting mechanism and describes an optimization method of its sensitive parameters, which can make the vertical rotor system reach 80000 r/min smoothly. Firstly we find the sensitive parameters through analyzing the rotor's features in the process of achieving high-speed, then, study these sensitive parameters and summarize the regularities with the method of combining the experiment and the finite element method (FEM), at last, achieve the optimization method of these parameters. That will not only get a stable effect of raising speed and shorten the debugging time greatly, but also promote the extensive application of the PM supporting mechanism in the ultra-high speed vertical rotors.
Optimization of injection moulding process parameters in the ...
African Journals Online (AJOL)
In this study, optimal injection moulding conditions for minimum shrinkage during moulding of High Density Polyethylene (HDPE) were obtained by Taguchi method. The result showed that melting temperature of 190OC, injection pressure of 55 MPa, refilling pressure of 85 MPa and cooling time of 11 seconds gave ...
Air Compressor Driving with Synchronous Motors at Optimal Parameters
Directory of Open Access Journals (Sweden)
Iuliu Petrica
2010-10-01
Full Text Available In this paper a method of optimal compensation of the reactive load by the synchronous motors, driving the air compressors, used in mining enterprises is presented, taking into account that in this case, the great majority of the equipment (compressors, pumps are generally working a constant load.
Optimizing Acquisition Parameters for MASW in Shallow Water
Diaferia, G.; Kruiver, P.P.; Drijkoningen, G.G.
2013-01-01
Analogous to the use of Rayleigh waves in MASW on land, Scholte waves can be used to derive shear wave velocity profiles for the subsurface under water. These profiles are useful for dredging operations, offshore wind farms, oil rigs and pipelines. We have determined the optimal acquisition set up
Identifying optimal models to represent biochemical systems.
Directory of Open Access Journals (Sweden)
Mochamad Apri
Full Text Available Biochemical systems involving a high number of components with intricate interactions often lead to complex models containing a large number of parameters. Although a large model could describe in detail the mechanisms that underlie the system, its very large size may hinder us in understanding the key elements of the system. Also in terms of parameter identification, large models are often problematic. Therefore, a reduced model may be preferred to represent the system. Yet, in order to efficaciously replace the large model, the reduced model should have the same ability as the large model to produce reliable predictions for a broad set of testable experimental conditions. We present a novel method to extract an "optimal" reduced model from a large model to represent biochemical systems by combining a reduction method and a model discrimination method. The former assures that the reduced model contains only those components that are important to produce the dynamics observed in given experiments, whereas the latter ensures that the reduced model gives a good prediction for any feasible experimental conditions that are relevant to answer questions at hand. These two techniques are applied iteratively. The method reveals the biological core of a model mathematically, indicating the processes that are likely to be responsible for certain behavior. We demonstrate the algorithm on two realistic model examples. We show that in both cases the core is substantially smaller than the full model.
Wang, Qianqian; Zhao, Jing; Gong, Yong; Hao, Qun; Peng, Zhong
2017-11-20
A hybrid artificial bee colony (ABC) algorithm inspired by the best-so-far solution and bacterial chemotaxis was introduced to optimize the parameters of the five-parameter bidirectional reflectance distribution function (BRDF) model. To verify the performance of the hybrid ABC algorithm, we measured BRDF of three kinds of samples and simulated the undetermined parameters of the five-parameter BRDF model using the hybrid ABC algorithm and the genetic algorithm, respectively. The experimental results demonstrate that the hybrid ABC algorithm outperforms the genetic algorithm in convergence speed, accuracy, and time efficiency under the same conditions.
Optimizing the IAEA safeguards system
International Nuclear Information System (INIS)
Drobysz, Sonia; Sitt, Bernard
2011-09-01
During the 2010 Non-Proliferation Treaty Review Conference, States parties recognized that the Additional Protocol (AP) provides increased confidence about the absence of undeclared nuclear material and activities in a State as a whole. They agreed in action 28 of the final document to encourage 'all States parties that have not yet done so to conclude and bring into force an AP as soon as possible and to implement them provisionally pending their entry into force'. Today, 109 out of 189 States parties to the NPT have brought an AP in force. The remaining outliers have not yet done so for three types of reasons: they do not clearly understand what the AP entails; when they do, they refuse to accept new non-proliferation obligations either on the ground of lack of progress in the realm of disarmament, or simply because they are not ready to bear the burden of additional safeguards measures. Strong incentives are thus needed in order to facilitate universalization of the AP. While external incentives would help make the AP a de facto norm and encourage its conclusion by reducing the deplored imbalanced implementation of non-proliferation and disarmament obligations, internal incentives developed by the Agency and its member States can also play an important role. In this respect, NPT States parties recommended in action 32 of the Review Conference final document 'that IAEA safeguards should be assessed and evaluated regularly. Decisions adopted by the IAEA policy bodies aimed at further strengthening the effectiveness and improving the efficiency of IAEA safeguards should be supported and implemented'. The safeguards system should therefore be optimized: the most effective use of safeguards measures as well as safeguards human, financial and technical resources would indeed help enhance the acceptability and even attractiveness of the AP. Optimization can be attractive for States committed to a stronger verification regime independently from other claims, but still
Optimized controllers for enhancing dynamic performance of PV interface system
Directory of Open Access Journals (Sweden)
Mahmoud A. Attia
2018-05-01
Full Text Available The dynamic performance of PV interface system can be improved by optimizing the gains of the Proportional–Integral (PI controller. In this work, gravitational search algorithm and harmony search algorithm are utilized to optimal tuning of PI controller gains. Performance comparison between the PV system with optimized PI gains utilizing different techniques are carried out. Finally, the dynamic behavior of the system is studied under hypothetical sudden variations in irradiance. The examination of the proposed techniques for optimal tuning of PI gains is conducted using MATLAB/SIMULINK software package. The main contribution of this work is investigating the dynamic performance of PV interfacing system with application of gravitational search algorithm and harmony search algorithm for optimal PI parameters tuning. Keywords: Photovoltaic power systems, Gravitational search algorithm, Harmony search algorithm, Genetic algorithm, Artificial intelligence
Reliability and optimization of structural systems
International Nuclear Information System (INIS)
Thoft-Christensen, P.
1987-01-01
The proceedings contain 28 papers presented at the 1st working conference. The working conference was organized by the IFIP Working Group 7.5. The proceedings also include 4 papers which were submitted, but for various reasons not presented at the working conference. The working conference was attended by 50 participants from 18 countries. The conference was the first scientific meeting of the new IFIP Working Group 7.5 on 'Reliability and Optimization of Structural Systems'. The purpose of the Working Group 7.5 is to promote modern structural system optimization and reliability theory, to advance international cooperation in the field of structural system optimization and reliability theory, to stimulate research, development and application of structural system optimization and reliability theory, to further the dissemination and exchange of information on reliability and optimization of structural system optimization and reliability theory, and to encourage education in structural system optimization and reliability theory. (orig./HP)
Boundary feedback stabilization of distributed parameter systems
DEFF Research Database (Denmark)
Pedersen, Michael
1988-01-01
The author introduces the method of pseudo-differential stabilization. He notes that the theory of pseudo-differential boundary operators is a fruitful approach to problems arising in control and stabilization theory of distributed-parameter systems. The basic pseudo-differential calculus can...
Optimization of control parameters for petroleum waste composting
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Composting is being widely employed in the treatment of petroleum waste. The purpose of this study was to find the optimum control parameters for petroleum waste in-vessel composting. Various physical and chemical parameters were monitored to evaluate their influence on the microbial communities present in composting. The CO2 evolution and the number of microorganisms were measured as theactivity of composting. The results demonstrated that the optimum temperature, pH and moisture content were 56.5-59.5, 7.0-8.5 and 55%-60%, respectively. Under the optimum conditions, the removal efficiency of petroleum hydrocarbon reached 83.29% after 30 days composting.
International Nuclear Information System (INIS)
Isaev, P.S.; Osipov, A.A.
1984-01-01
The slope parameters of the ππ-system are calculated in the framework of the superconductor-tupe quark model. The analogous calculations are made for πK-system. The amplitudes are obtained by using the box quark diagrams and tree diagrams with the intermediate scalar epsilon(700), Ssup(x)(975), K tilde (1350) mesons and vector rho(770), K* (892) mesons
Stewart, James J P
2013-01-01
Modern semiempirical methods are of sufficient accuracy when used in the modeling of molecules of the same type as used as reference data in the parameterization. Outside that subset, however, there is an abundance of evidence that these methods are of very limited utility. In an attempt to expand the range of applicability, a new method called PM7 has been developed. PM7 was parameterized using experimental and high-level ab initio reference data, augmented by a new type of reference data intended to better define the structure of parameter space. The resulting method was tested by modeling crystal structures and heats of formation of solids. Two changes were made to the set of approximations: a modification was made to improve the description of noncovalent interactions, and two minor errors in the NDDO formalism were rectified. Average unsigned errors (AUEs) in geometry and ΔHf for PM7 were reduced relative to PM6; for simple gas-phase organic systems, the AUE in bond lengths decreased by about 5% and the AUE in ΔHf decreased by about 10%; for organic solids, the AUE in ΔHf dropped by 60% and the reduction was 33.3% for geometries. A two-step process (PM7-TS) for calculating the heights of activation barriers has been developed. Using PM7-TS, the AUE in the barrier heights for simple organic reactions was decreased from values of 12.6 kcal/mol(-1) in PM6 and 10.8 kcal/mol(-1) in PM7 to 3.8 kcal/mol(-1). The origins of the errors in NDDO methods have been examined, and were found to be attributable to inadequate and inaccurate reference data. This conclusion provides insight into how these methods can be improved.
Improved Artificial Fish Algorithm for Parameters Optimization of PID Neural Network
Jing Wang; Yourui Huang
2013-01-01
In order to solve problems such as initial weights are difficult to be determined, training results are easy to trap in local minima in optimization process of PID neural network parameters by traditional BP algorithm, this paper proposed a new method based on improved artificial fish algorithm for parameters optimization of PID neural network. This improved artificial fish algorithm uses a composite adaptive artificial fish algorithm based on optimal artificial fish and nearest artificial fi...
Optimization of MIS/IL solar cells parameters using genetic algorithm
Energy Technology Data Exchange (ETDEWEB)
Ahmed, K.A.; Mohamed, E.A.; Alaa, S.H. [Faculty of Engineering, Alexandria Univ. (Egypt); Motaz, M.S. [Institute of Graduate Studies and Research, Alexandria Univ. (Egypt)
2004-07-01
This paper presents a genetic algorithm optimization for MIS/IL solar cell parameters including doping concentration NA, metal work function {phi}m, oxide thickness d{sub ox}, mobile charge density N{sub m}, fixed oxide charge density N{sub ox} and the external back bias applied to the inversion grid V. The optimization results are compared with theoretical optimization and shows that the genetic algorithm can be used for determining the optimum parameters of the cell. (orig.)
The Pealization of the Most Economical and optimized Control System
Institute of Scientific and Technical Information of China (English)
WUBin
2002-01-01
In order to plow an access to low cost automation,the method to set up the most economical and optimized control system is studied.Such a system is achieved by adopting the field bus technologies based on net connection to form the hierarchical architecture and employing genetic algorithm to intelliently optimize the parameters of the topology structure at the field execution level and the parameters of a local controller,Praxios has proved that this realization can shorten the system development cycle,improve the systtem's reliability,and achieve conspicuous social economic benefits.
Reutterer, Bernd; Traxler, Lukas; Bayer, Natascha; Drauschke, Andreas
2016-04-01
Selective Laser Sintering (SLS) is considered as one of the most important additive manufacturing processes due to component stability and its broad range of usable materials. However the influence of the different process parameters on mechanical workpiece properties is still poorly studied, leading to the fact that further optimization is necessary to increase workpiece quality. In order to investigate the impact of various process parameters, laboratory experiments are implemented to improve the understanding of the SLS limitations and advantages on an educational level. Experiments are based on two different workstations, used to teach students the fundamentals of SLS. First of all a 50 W CO2 laser workstation is used to investigate the interaction of the laser beam with the used material in accordance with varied process parameters to analyze a single-layered test piece. Second of all the FORMIGA P110 laser sintering system from EOS is used to print different 3D test pieces in dependence on various process parameters. Finally quality attributes are tested including warpage, dimension accuracy or tensile strength. For dimension measurements and evaluation of the surface structure a telecentric lens in combination with a camera is used. A tensile test machine allows testing of the tensile strength and the interpreting of stress-strain curves. The developed laboratory experiments are suitable to teach students the influence of processing parameters. In this context they will be able to optimize the input parameters depending on the component which has to be manufactured and to increase the overall quality of the final workpiece.
Linear quadratic optimization for positive LTI system
Muhafzan, Yenti, Syafrida Wirma; Zulakmal
2017-05-01
Nowaday the linear quadratic optimization subject to positive linear time invariant (LTI) system constitute an interesting study considering it can become a mathematical model of variety of real problem whose variables have to nonnegative and trajectories generated by these variables must be nonnegative. In this paper we propose a method to generate an optimal control of linear quadratic optimization subject to positive linear time invariant (LTI) system. A sufficient condition that guarantee the existence of such optimal control is discussed.
Optimization of wireless Bluetooth sensor systems.
Lonnblad, J; Castano, J; Ekstrom, M; Linden, M; Backlund, Y
2004-01-01
Within this study, three different Bluetooth sensor systems, replacing cables for transmission of biomedical sensor data, have been designed and evaluated. The three sensor architectures are built on 1-, 2- and 3-chip solutions and depending on the monitoring situation and signal character, different solutions are optimal. Essential parameters for all systems have been low physical weight and small size, resistance to interference and interoperability with other technologies as global- or local networks, PC's and mobile phones. Two different biomedical input signals, ECG and PPG (photoplethysmography), have been used to evaluate the three solutions. The study shows that it is possibly to continuously transmit an analogue signal. At low sampling rates and slowly varying parameters, as monitoring the heart rate with PPG, the 1-chip solution is the most suitable, offering low power consumption and thus a longer battery lifetime or a smaller battery, minimizing the weight of the sensor system. On the other hand, when a higher sampling rate is required, as an ECG, the 3-chip architecture, with a FPGA or micro-controller, offers the best solution and performance. Our conclusion is that Bluetooth might be useful in replacing cables of medical monitoring systems.
Optimization of Storage Parameters of Selected Fruits in Passive ...
African Journals Online (AJOL)
This study was carried out to determine the optimum storage parameters of selected fruit using three sets of four types of passive evaporative cooling structures made of two different materials clay and aluminium. One set consisted of four separate cooling chambers. Two cooling chambers were made with aluminium ...
Optimal Two Parameter Bounds for the Seiffert Mean
Directory of Open Access Journals (Sweden)
Hui Sun
2013-01-01
Full Text Available We obtain sharp bounds for the Seiffert mean in terms of a two parameter family of means. Our results generalize and extend the recent bounds presented in the Journal of Inequalities and Applications (2012 and Abstract and Applied Analysis (2012.
Investigation and validation of optimal cutting parameters for least ...
African Journals Online (AJOL)
user
Turning is carried on lathe that provides the power to turn the work piece at a given rotational speed and ... The cutting parameters influencing the surface finish in EN24 is to be studied ...... Design from Anna University, Chennai, India in 2004.
Optimization of physico-chemical and nutritional parameters for ...
African Journals Online (AJOL)
hope&shola
2010-10-25
Oct 25, 2010 ... industrial production in order to reduce the cost of production. ... is of great economic importance with increased appli- ... industries (Seviour et al., 1992; Leathers, 2003). .... The various process parameters influencing pullulan production ..... formation by Aureobasidium pullulans in stirred tanks. Enzyme.
Optimization and Analysis of Cutting Tool Geometrical Parameters ...
African Journals Online (AJOL)
ADOWIE PERE
Bassett et al.,(2012);. Kountanya et al., (2016) studied the effect of tool edge geometry and cutting conditions on the chip morphology in orthogonal hard turning of 100Cr6 steel. Their study shows that the edge radius does not influence the geometrical parameters of the chip. Moreover cutting forces decreases as the cutting.
Wang, Xu; Bi, Fengrong; Du, Haiping
2018-05-01
This paper aims to develop an 5-degree-of-freedom driver and seating system model for optimal vibration control. A new method for identification of the driver seating system parameters from experimental vibration measurement has been developed. The parameter sensitivity analysis has been conducted considering the random excitation frequency and system parameter uncertainty. The most and least sensitive system parameters for the transmissibility ratio have been identified. The optimised PID controllers have been developed to reduce the driver's body vibration.
Strategies for Optimal Design of Structural Systems
DEFF Research Database (Denmark)
Enevoldsen, I.; Sørensen, John Dalsgaard
1992-01-01
Reliability-based design of structural systems is considered. Especially systems where the reliability model is a series system of parallel systems are analysed. A sensitivity analysis for this class of problems is presented. Direct and sequential optimization procedures to solve the optimization...
Neverov, V. V.; Kozhukhov, Y. V.; Yablokov, A. M.; Lebedev, A. A.
2017-08-01
Nowadays the optimization using computational fluid dynamics (CFD) plays an important role in the design process of turbomachines. However, for the successful and productive optimization it is necessary to define a simulation model correctly and rationally. The article deals with the choice of a grid and computational domain parameters for optimization of centrifugal compressor impellers using computational fluid dynamics. Searching and applying optimal parameters of the grid model, the computational domain and solver settings allows engineers to carry out a high-accuracy modelling and to use computational capability effectively. The presented research was conducted using Numeca Fine/Turbo package with Spalart-Allmaras and Shear Stress Transport turbulence models. Two radial impellers was investigated: the high-pressure at ψT=0.71 and the low-pressure at ψT=0.43. The following parameters of the computational model were considered: the location of inlet and outlet boundaries, type of mesh topology, size of mesh and mesh parameter y+. Results of the investigation demonstrate that the choice of optimal parameters leads to the significant reduction of the computational time. Optimal parameters in comparison with non-optimal but visually similar parameters can reduce the calculation time up to 4 times. Besides, it is established that some parameters have a major impact on the result of modelling.
Sensitivity analysis in multi-parameter probabilistic systems
International Nuclear Information System (INIS)
Walker, J.R.
1987-01-01
Probabilistic methods involving the use of multi-parameter Monte Carlo analysis can be applied to a wide range of engineering systems. The output from the Monte Carlo analysis is a probabilistic estimate of the system consequence, which can vary spatially and temporally. Sensitivity analysis aims to examine how the output consequence is influenced by the input parameter values. Sensitivity analysis provides the necessary information so that the engineering properties of the system can be optimized. This report details a package of sensitivity analysis techniques that together form an integrated methodology for the sensitivity analysis of probabilistic systems. The techniques have known confidence limits and can be applied to a wide range of engineering problems. The sensitivity analysis methodology is illustrated by performing the sensitivity analysis of the MCROC rock microcracking model
PC based 8-parameter data acquisition system
International Nuclear Information System (INIS)
Gupta, J.D.; Naik, K.V.; Jain, S.K.; Pathak, R.V.; Suman, B.
1989-01-01
Multiparameter data acquisition (MPA) systems which analyse nuclear events with respect to more than one property of the event are essential tools for the study of some complex nuclear phenomena requiring analysis of time coincident spectra. For better throughput and accuracy each parameter is digitized by its own ADC. A stand alone low cost IBM PC based 8-parameter data acquisition system developed by the authors makes use of Address Recording technique for acquiring data from eight 12 bit ADC's in the PC Memory. Two memory buffers in the PC memory are used in ping-pong fashion so that data acquisition in one bank and dumping of data onto PC disk from the other bank can proceed simultaneously. Data is acquired in the PC memory through DMA mode for realising high throughput and hardware interrupt is used for switching banks for data acquisition. A comprehensive software package developed in Turbo-Pascal offers a set of menu-driven interactive commands to the user for setting-up system parameters and control of the system. The system is to be used with pelletron accelerator. (author). 5 figs
Directory of Open Access Journals (Sweden)
Yu Wang
2017-10-01
Full Text Available Seepage failure in the form of piping can strongly influence the stability of block-in-matrix-soils (bimsoils, as well as weaken and affect the performance of bimsoil structures. The multiple-factor evaluation and optimization play a crucial role in controlling the seepage failure in bimsoil. The aim of this study is to improve the ability to control the piping seepage failure in bimsoil. In this work, the response surface method (RSM was employed to evaluate and optimize the multiple piping parameters to maximize the critical hydraulic gradient (CHG, in combination with experimental modeling based on a self-developed servo-controlled flow-erosion-stress coupled testing system. All of the studied specimens with rock block percentage (RBP of 30%, 50%, and 70% were produced as a cylindrical shape (50 mm diameter and 100 mm height by compaction tests. Four uncertain parameters, such as RBP, soil matrix density, confining pressure, and block morphology were used to fit an optimal response of the CHG. The sensitivity analysis reveals the influential order of the studied factors to CHG. It is found that RBP is the most sensitive factor, the CHG decreases with the increase of RBP, and CHG increases with the increase of confining pressure, soil matrix density, and block angularity.
Flores, Jorge L.; García-Torales, G.; Ponce Ávila, Cristina
2006-08-01
This paper describes an in situ image recognition system designed to inspect the quality standards of the chocolate pops during their production. The essence of the recognition system is the localization of the events (i.e., defects) in the input images that affect the quality standards of pops. To this end, processing modules, based on correlation filter, and segmentation of images are employed with the objective of measuring the quality standards. Therefore, we designed the correlation filter and defined a set of features from the correlation plane. The desired values for these parameters are obtained by exploiting information about objects to be rejected in order to find the optimal discrimination capability of the system. Regarding this set of features, the pop can be correctly classified. The efficacy of the system has been tested thoroughly under laboratory conditions using at least 50 images, containing 3 different types of possible defects.
OPTIMIZATION OF ADVANCED FILTER SYSTEMS
Energy Technology Data Exchange (ETDEWEB)
R.A. Newby; G.J. Bruck; M.A. Alvin; T.E. Lippert
1998-04-30
Reliable, maintainable and cost effective hot gas particulate filter technology is critical to the successful commercialization of advanced, coal-fired power generation technologies, such as IGCC and PFBC. In pilot plant testing, the operating reliability of hot gas particulate filters have been periodically compromised by process issues, such as process upsets and difficult ash cake behavior (ash bridging and sintering), and by design issues, such as cantilevered filter elements damaged by ash bridging, or excessively close packing of filtering surfaces resulting in unacceptable pressure drop or filtering surface plugging. This test experience has focused the issues and has helped to define advanced hot gas filter design concepts that offer higher reliability. Westinghouse has identified two advanced ceramic barrier filter concepts that are configured to minimize the possibility of ash bridge formation and to be robust against ash bridges should they occur. The ''inverted candle filter system'' uses arrays of thin-walled, ceramic candle-type filter elements with inside-surface filtering, and contains the filter elements in metal enclosures for complete separation from ash bridges. The ''sheet filter system'' uses ceramic, flat plate filter elements supported from vertical pipe-header arrays that provide geometry that avoids the buildup of ash bridges and allows free fall of the back-pulse released filter cake. The Optimization of Advanced Filter Systems program is being conducted to evaluate these two advanced designs and to ultimately demonstrate one of the concepts in pilot scale. In the Base Contract program, the subject of this report, Westinghouse has developed conceptual designs of the two advanced ceramic barrier filter systems to assess their performance, availability and cost potential, and to identify technical issues that may hinder the commercialization of the technologies. A plan for the Option I, bench
Optimization of process parameters through GRA, TOPSIS and RSA models
Directory of Open Access Journals (Sweden)
Suresh Nipanikar
2018-01-01
Full Text Available This article investigates the effect of cutting parameters on the surface roughness and flank wear during machining of titanium alloy Ti-6Al-4V ELI( Extra Low Interstitial in minimum quantity lubrication environment by using PVD TiAlN insert. Full factorial design of experiment was used for the machining 2 factors 3 levels and 2 factors 2 levels. Turning parameters studied were cutting speed (50, 65, 80 m/min, feed (0.08, 0.15, 0.2 mm/rev and depth of cut 0.5 mm constant. The results show that 44.61 % contribution of feed and 43.57 % contribution of cutting speed on surface roughness also 53.16 % contribution of cutting tool and 26.47 % contribution of cutting speed on tool flank wear. Grey relational analysis and TOPSIS method suggest the optimum combinations of machining parameters as cutting speed: 50 m/min, feed: 0.8 mm/rev., cutting tool: PVD TiAlN, cutting fluid: Palm oi
Optimal Trajectories Generation in Robotic Fiber Placement Systems
Gao, Jiuchun; Pashkevich, Anatol; Caro, Stéphane
2017-06-01
The paper proposes a methodology for optimal trajectories generation in robotic fiber placement systems. A strategy to tune the parameters of the optimization algorithm at hand is also introduced. The presented technique transforms the original continuous problem into a discrete one where the time-optimal motions are generated by using dynamic programming. The developed strategy for the optimization algorithm tuning allows essentially reducing the computing time and obtaining trajectories satisfying industrial constraints. Feasibilities and advantages of the proposed methodology are confirmed by an application example.
Optimal Control and Optimization of Stochastic Supply Chain Systems
Song, Dong-Ping
2013-01-01
Optimal Control and Optimization of Stochastic Supply Chain Systems examines its subject in the context of the presence of a variety of uncertainties. Numerous examples with intuitive illustrations and tables are provided, to demonstrate the structural characteristics of the optimal control policies in various stochastic supply chains and to show how to make use of these characteristics to construct easy-to-operate sub-optimal policies. In Part I, a general introduction to stochastic supply chain systems is provided. Analytical models for various stochastic supply chain systems are formulated and analysed in Part II. In Part III the structural knowledge of the optimal control policies obtained in Part II is utilized to construct easy-to-operate sub-optimal control policies for various stochastic supply chain systems accordingly. Finally, Part IV discusses the optimisation of threshold-type control policies and their robustness. A key feature of the book is its tying together of ...
Directory of Open Access Journals (Sweden)
Yun-ah Han
2013-03-01
Full Text Available The effects of structural design parameters on the performance of nano-replicated photonic crystal (PC label-free biosensors were examined by the analysis of simulated reflection spectra of PC structures. The grating pitch, duty, scaled grating height and scaled TiO2 layer thickness were selected as the design factors to optimize the PC structure. The peak wavelength value (PWV, full width at half maximum of the peak, figure of merit for the bulk and surface sensitivities, and surface/bulk sensitivity ratio were also selected as the responses to optimize the PC label-free biosensor performance. A parametric study showed that the grating pitch was the dominant factor for PWV, and that it had low interaction effects with other scaled design factors. Therefore, we can isolate the effect of grating pitch using scaled design factors. For the design of PC-label free biosensor, one should consider that: (1 the PWV can be measured by the reflection peak measurement instruments, (2 the grating pitch and duty can be manufactured using conventional lithography systems, and (3 the optimum design is less sensitive to the grating height and TiO2 layer thickness variations in the fabrication process. In this paper, we suggested a design guide for highly sensitive PC biosensor in which one select the grating pitch and duty based on the limitations of the lithography and measurement system, and conduct a multi objective optimization of the grating height and TiO2 layer thickness for maximizing performance and minimizing the influence of parameter variation. Through multi-objective optimization of a PC structure with a fixed grating height of 550 nm and a duty of 50%, we obtained a surface FOM of 66.18 RIU−1 and an S/B ratio of 34.8%, with a grating height of 117 nm and TiO2 height of 210 nm.
Ju, Jonghyun; Han, Yun-ah; Kim, Seok-min
2013-03-07
The effects of structural design parameters on the performance of nano-replicated photonic crystal (PC) label-free biosensors were examined by the analysis of simulated reflection spectra of PC structures. The grating pitch, duty, scaled grating height and scaled TiO2 layer thickness were selected as the design factors to optimize the PC structure. The peak wavelength value (PWV), full width at half maximum of the peak, figure of merit for the bulk and surface sensitivities, and surface/bulk sensitivity ratio were also selected as the responses to optimize the PC label-free biosensor performance. A parametric study showed that the grating pitch was the dominant factor for PWV, and that it had low interaction effects with other scaled design factors. Therefore, we can isolate the effect of grating pitch using scaled design factors. For the design of PC-label free biosensor, one should consider that: (1) the PWV can be measured by the reflection peak measurement instruments, (2) the grating pitch and duty can be manufactured using conventional lithography systems, and (3) the optimum design is less sensitive to the grating height and TiO2 layer thickness variations in the fabrication process. In this paper, we suggested a design guide for highly sensitive PC biosensor in which one select the grating pitch and duty based on the limitations of the lithography and measurement system, and conduct a multi objective optimization of the grating height and TiO2 layer thickness for maximizing performance and minimizing the influence of parameter variation. Through multi-objective optimization of a PC structure with a fixed grating height of 550 nm and a duty of 50%, we obtained a surface FOM of 66.18 RIU-1 and an S/B ratio of 34.8%, with a grating height of 117 nm and TiO2 height of 210 nm.
Hybrid Metaheuristic Approach for Nonlocal Optimization of Molecular Systems.
Dresselhaus, Thomas; Yang, Jack; Kumbhar, Sadhana; Waller, Mark P
2013-04-09
Accurate modeling of molecular systems requires a good knowledge of the structure; therefore, conformation searching/optimization is a routine necessity in computational chemistry. Here we present a hybrid metaheuristic optimization (HMO) algorithm, which combines ant colony optimization (ACO) and particle swarm optimization (PSO) for the optimization of molecular systems. The HMO implementation meta-optimizes the parameters of the ACO algorithm on-the-fly by the coupled PSO algorithm. The ACO parameters were optimized on a set of small difluorinated polyenes where the parameters exhibited small variance as the size of the molecule increased. The HMO algorithm was validated by searching for the closed form of around 100 molecular balances. Compared to the gradient-based optimized molecular balance structures, the HMO algorithm was able to find low-energy conformations with a 87% success rate. Finally, the computational effort for generating low-energy conformation(s) for the phenylalanyl-glycyl-glycine tripeptide was approximately 60 CPU hours with the ACO algorithm, in comparison to 4 CPU years required for an exhaustive brute-force calculation.
Dose responses in a normoxic polymethacrylic acid gel dosimeter using optimal CT scanning parameters
Energy Technology Data Exchange (ETDEWEB)
Cho, K.H. [Department of Radiation Oncology, College of Medicine, Soonchunhyang University, Bucheon 420-767 (Korea, Republic of); Department of Medical Physics, Kyonggi University, Suwon 443-760 (Korea, Republic of); Cho, S.J. [Department of Radiation Oncology, College of Medicine, Eulji University, Seongnam 461-713 (Korea, Republic of); Lee, S. [Department of Radiation Oncology, College of Medicine, Korea University, Seoul 130-701 (Korea, Republic of); Lee, S.H. [Cheil General Hospital and Women' s Healthcare Center, Kwandong University College of Medicine, Seoul 100-380 (Korea, Republic of); Min, C.K.; Kim, Y.H.; Moon, S.K.; Kim, E.S.; Chang, A.R. [Department of Radiation Oncology, College of Medicine, Soonchunhyang University, Bucheon 420-767 (Korea, Republic of); Kwon, S.I., E-mail: sikwon@kyonggi.ac.kr [Department of Medical Physics, Kyonggi University, Suwon 443-760 (Korea, Republic of)
2012-05-21
The dosimetric characteristics of normoxic polymethacrylic acid gels are investigated using optimal CT scanning parameters and the possibility of their clinical application is also considered. The effects of CT scanning parameters (tube voltage, tube current, scan time, slick thickness, field of view, and reconstruction algorithm) are experimentally investigated to determine the optimal parameters for minimizing the amount of noise in images obtained using normoxic polymethacrylic acid gel. In addition, the dose sensitivity, dose response, accuracy, and reproducibility of the normoxic polymethacrylic acid gel are evaluated. CT images are obtained using a head phantom that is fabricated for clinical applications. In addition, IMRT treatment planning is performed using a Tomotherapy radiation treatment planning system. A program for analyzing the results is produced using Visual C. A comparison between the treatment planning and the CT images of irradiated gels is performed. The dose sensitivity is found to be 2.41{+-}0.04 HGy{sup -1}. The accuracies of dose evaluation at doses of 2 Gy and 4 Gy are 3.0% and 2.6%, respectively, and their reproducibilities are 2.0% and 2.1%, respectively. In the comparison of gel and Tomotherpay planning, the pass rate of the {gamma}-index, based on the reference values of a dose error of 3% and a DTA of 3 mm, is 93.7%.
Dose responses in a normoxic polymethacrylic acid gel dosimeter using optimal CT scanning parameters
Cho, K. H.; Cho, S. J.; Lee, S.; Lee, S. H.; Min, C. K.; Kim, Y. H.; Moon, S. K.; Kim, E. S.; Chang, A. R.; Kwon, S. I.
2012-05-01
The dosimetric characteristics of normoxic polymethacrylic acid gels are investigated using optimal CT scanning parameters and the possibility of their clinical application is also considered. The effects of CT scanning parameters (tube voltage, tube current, scan time, slick thickness, field of view, and reconstruction algorithm) are experimentally investigated to determine the optimal parameters for minimizing the amount of noise in images obtained using normoxic polymethacrylic acid gel. In addition, the dose sensitivity, dose response, accuracy, and reproducibility of the normoxic polymethacrylic acid gel are evaluated. CT images are obtained using a head phantom that is fabricated for clinical applications. In addition, IMRT treatment planning is performed using a Tomotherapy radiation treatment planning system. A program for analyzing the results is produced using Visual C. A comparison between the treatment planning and the CT images of irradiated gels is performed. The dose sensitivity is found to be 2.41±0.04 HGy-1. The accuracies of dose evaluation at doses of 2 Gy and 4 Gy are 3.0% and 2.6%, respectively, and their reproducibilities are 2.0% and 2.1%, respectively. In the comparison of gel and Tomotherpay planning, the pass rate of the γ-index, based on the reference values of a dose error of 3% and a DTA of 3 mm, is 93.7%.
A Novel adaptative Discrete Cuckoo Search Algorithm for parameter optimization in computer vision
Directory of Open Access Journals (Sweden)
loubna benchikhi
2017-10-01
Full Text Available Computer vision applications require choosing operators and their parameters, in order to provide the best outcomes. Often, the users quarry on expert knowledge and must experiment many combinations to find manually the best one. As performance, time and accuracy are important, it is necessary to automate parameter optimization at least for crucial operators. In this paper, a novel approach based on an adaptive discrete cuckoo search algorithm (ADCS is proposed. It automates the process of algorithms’ setting and provides optimal parameters for vision applications. This work reconsiders a discretization problem to adapt the cuckoo search algorithm and presents the procedure of parameter optimization. Some experiments on real examples and comparisons to other metaheuristic-based approaches: particle swarm optimization (PSO, reinforcement learning (RL and ant colony optimization (ACO show the efficiency of this novel method.
Dependability of self-optimizing mechatronic systems
Rammig, Franz; Schäfer, Wilhelm; Sextro, Walter
2014-01-01
Intelligent technical systems, which combine mechanical, electrical and software engineering with control engineering and advanced mathematics, go far beyond the state of the art in mechatronics and open up fascinating perspectives. Among these systems are so-called self-optimizing systems, which are able to adapt their behavior autonomously and flexibly to changing operating conditions. Self-optimizing systems create high value for example in terms of energy and resource efficiency as well as reliability. The Collaborative Research Center 614 "Self-optimizing Concepts and Structures in Mechanical Engineering" pursued the long-term aim to open up the active paradigm of self-optimization for mechanical engineering and to enable others to develop self-optimizing systems. This book is directed to researchers and practitioners alike. It provides a design methodology for the development of self-optimizing systems consisting of a reference process, methods, and tools. The reference process is divided into two phase...
Optimization of sampling parameters for standardized exhaled breath sampling.
Doran, Sophie; Romano, Andrea; Hanna, George B
2017-09-05
The lack of standardization of breath sampling is a major contributing factor to the poor repeatability of results and hence represents a barrier to the adoption of breath tests in clinical practice. On-line and bag breath sampling have advantages but do not suit multicentre clinical studies whereas storage and robust transport are essential for the conduct of wide-scale studies. Several devices have been developed to control sampling parameters and to concentrate volatile organic compounds (VOCs) onto thermal desorption (TD) tubes and subsequently transport those tubes for laboratory analysis. We conducted three experiments to investigate (i) the fraction of breath sampled (whole vs. lower expiratory exhaled breath); (ii) breath sample volume (125, 250, 500 and 1000ml) and (iii) breath sample flow rate (400, 200, 100 and 50 ml/min). The target VOCs were acetone and potential volatile biomarkers for oesophago-gastric cancer belonging to the aldehyde, fatty acids and phenol chemical classes. We also examined the collection execution time and the impact of environmental contamination. The experiments showed that the use of exhaled breath-sampling devices requires the selection of optimum sampling parameters. The increase in sample volume has improved the levels of VOCs detected. However, the influence of the fraction of exhaled breath and the flow rate depends on the target VOCs measured. The concentration of potential volatile biomarkers for oesophago-gastric cancer was not significantly different between the whole and lower airway exhaled breath. While the recovery of phenols and acetone from TD tubes was lower when breath sampling was performed at a higher flow rate, other VOCs were not affected. A dedicated 'clean air supply' overcomes the contamination from ambient air, but the breath collection device itself can be a source of contaminants. In clinical studies using VOCs to diagnose gastro-oesophageal cancer, the optimum parameters are 500mls sample volume
Reliability-Based Optimization of Series Systems of Parallel Systems
DEFF Research Database (Denmark)
Enevoldsen, I.; Sørensen, John Dalsgaard
1993-01-01
Reliability-based design of structural systems is considered. In particular, systems where the reliability model is a series system of parallel systems are treated. A sensitivity analysis for this class of problems is presented. Optimization problems with series systems of parallel systems...... optimization of series systems of parallel systems, but it is also efficient in reliability-based optimization of series systems in general....
Kumar, S.; Singh, A.; Dhar, A.
2017-08-01
The accurate estimation of the photovoltaic parameters is fundamental to gain an insight of the physical processes occurring inside a photovoltaic device and thereby to optimize its design, fabrication processes, and quality. A simulative approach of accurately determining the device parameters is crucial for cell array and module simulation when applied in practical on-field applications. In this work, we have developed a global particle swarm optimization (GPSO) approach to estimate the different solar cell parameters viz., ideality factor (η), short circuit current (Isc), open circuit voltage (Voc), shunt resistant (Rsh), and series resistance (Rs) with wide a search range of over ±100 % for each model parameter. After validating the accurateness and global search power of the proposed approach with synthetic and noisy data, we applied the technique to the extract the PV parameters of ZnO/PCDTBT based hybrid solar cells (HSCs) prepared under different annealing conditions. Further, we examine the variation of extracted model parameters to unveil the physical processes occurring when different annealing temperatures are employed during the device fabrication and establish the role of improved charge transport in polymer films from independent FET measurements. The evolution of surface morphology, optical absorption, and chemical compositional behaviour of PCDTBT co-polymer films as a function of processing temperature has also been captured in the study and correlated with the findings from the PV parameters extracted using GPSO approach.
Parameters and design optimization of the ring piezoelectric ceramic transformer
Directory of Open Access Journals (Sweden)
Jiří Erhart
2015-09-01
Full Text Available Main aim of the presented paper is the theoretical analysis and experimental verification of the transformation parameters for the new type of nonhomogeneously poled ring transformer. The input part is poled in the thickness direction and output part in the radial direction. Two transformer geometries are studied — the input part is at inner ring segment, or it is at the outer ring segment. The optimum electrode size aspect ratios have been found experimentally as d1∕D≈0.60−0.65 for the ring with aspect ratio d∕D=0.2. The fundamental as well as higher overtone resonances were studied for the transformation ratio, the optimum resistive load, efficiency and no-load transformation ratio. Higher overtones have better transformation parameters compared to the fundamental resonance. The new type ring transformer exhibits very high transformation ratios up to 200 under no-load and up to 13.4 under a high efficiency of 97% at the optimum load conditions of 10 kΩ. Strong electric field gradient at the output circuit is applicable for the electrical discharge generation.
Multi-objective optimization of GENIE Earth system models.
Price, Andrew R; Myerscough, Richard J; Voutchkov, Ivan I; Marsh, Robert; Cox, Simon J
2009-07-13
The tuning of parameters in climate models is essential to provide reliable long-term forecasts of Earth system behaviour. We apply a multi-objective optimization algorithm to the problem of parameter estimation in climate models. This optimization process involves the iterative evaluation of response surface models (RSMs), followed by the execution of multiple Earth system simulations. These computations require an infrastructure that provides high-performance computing for building and searching the RSMs and high-throughput computing for the concurrent evaluation of a large number of models. Grid computing technology is therefore essential to make this algorithm practical for members of the GENIE project.
Fuzzy logic control and optimization system
Lou, Xinsheng [West Hartford, CT
2012-04-17
A control system (300) for optimizing a power plant includes a chemical loop having an input for receiving an input signal (369) and an output for outputting an output signal (367), and a hierarchical fuzzy control system (400) operably connected to the chemical loop. The hierarchical fuzzy control system (400) includes a plurality of fuzzy controllers (330). The hierarchical fuzzy control system (400) receives the output signal (367), optimizes the input signal (369) based on the received output signal (367), and outputs an optimized input signal (369) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.
Kinetic parameters for source driven systems
International Nuclear Information System (INIS)
Dulla, S.; Ravetto, P.; Carta, M.; D'Angelo, A.
2006-01-01
The definition of the characteristic kinetic parameters of a subcritical source-driven system constitutes an interesting problem in reactor physics with important consequences for practical applications. Consistent and physically meaningful values of the parameters allow to obtain accurate results from kinetic simulation tools and to correctly interpret kinetic experiments. For subcritical systems a preliminary problem arises for the adoption of a suitable weighting function to be used in the projection procedure to derive a point model. The present work illustrates a consistent factorization-projection procedure which leads to the definition of the kinetic parameters in a straightforward manner. The reactivity term is introduced coherently with the generalized perturbation theory applied to the source multiplication factor ks, which is thus given a physical role in the kinetic model. The effective prompt lifetime is introduced on the assumption that a neutron generation can be initiated by both the fission process and the source emission. Results are presented for simplified configurations to fully comprehend the physical features and for a more complicated highly decoupled system treated in transport theory. (authors)
Yu, Tao; Kang, Chao; Zhao, Pan
2018-01-01
The composite tape winding process, which utilizes a tape winding machine and prepreg tapes, provides a promising way to improve the quality of composite products. Nevertheless, the process parameters of composite tape winding have crucial effects on the tensile strength and void content, which are closely related to the performances of the winding products. In this article, two different object values of winding products, including mechanical performance (tensile strength) and a physical property (void content), were respectively calculated. Thereafter, the paper presents an integrated methodology by combining multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis to obtain the optimal intervals of the composite tape winding process. First, the global multi-parameter sensitivity analysis method was applied to investigate the sensitivity of each parameter in the tape winding processing. Then, the local single-parameter sensitivity analysis method was employed to calculate the sensitivity of a single parameter within the corresponding range. Finally, the stability and instability ranges of each parameter were distinguished. Meanwhile, the authors optimized the process parameter ranges and provided comprehensive optimized intervals of the winding parameters. The verification test validated that the optimized intervals of the process parameters were reliable and stable for winding products manufacturing. PMID:29385048
Research on Intelligent Control System of DC SQUID Magnetometer Parameters for Multi-channel System
Chen, Hua; Yang, Kang; Lu, Li; Kong, Xiangyan; Wang, Hai; Wu, Jun; Wang, Yongliang
2018-03-01
In a multi-channel SQUID measurement system, adjusting device parameters to optimal condition for all channels is time-consuming. In this paper, an intelligent control system is presented to determine the optimal working point of devices which is automatic and more efficient comparing to the manual one. An optimal working point searching algorithm is introduced as the core component of the control system. In this algorithm, the bias voltage V_bias is step scanned to obtain the maximal value of the peak-to-peak current value I_pp of the SQUID magnetometer modulation curve. We choose this point as the optimal one. Using the above control system, more than 30 weakly damped SQUID magnetometers with area of 5 × 5 mm^2 or 10 × 10 mm^2 are adjusted and a 36-channel magnetocardiography system perfectly worked in a magnetically shielded room. The average white flux noise is 15 μΦ_0/Hz^{1/2}.
Identification of systems with distributed parameters
International Nuclear Information System (INIS)
Moret, J.M.
1990-10-01
The problem of finding a model for the dynamical response of a system with distributed parameters based on measured data is addressed. First a mathematical formalism is developed in order to obtain the specific properties of such a system. Then a linear iterative identification algorithm is proposed that includes these properties, and that produces better results than usual non linear minimisation techniques. This algorithm is further improved by an original data decimation that allow to artificially increase the sampling period without losing between sample information. These algorithms are tested with real laboratory data
Metallic Fuel Casting Development and Parameter Optimization Simulations
International Nuclear Information System (INIS)
Fielding, Randall S.; Kennedy, J.R.; Crapps, J.; Unal, C.
2013-01-01
Conclusions: • Gravity casting is a feasible process for casting of metallic fuels: – May not be as robust as CGIC, more parameter dependent to find right “sweet spot” for high quality castings; – Fluid flow is very important and is affected by mold design, vent size, super heat, etc.; – Pressure differential assist was found to be detrimental. • Simulation found that vent location was important to allow adequate filling of mold; • Surface tension plays an important role in determining casting quality; • Casting and simulations high light the need for better characterized fluid physical and thermal properties; • Results from simulations will be incorporated in GACS design such as vent location and physical property characterization
Energy Technology Data Exchange (ETDEWEB)
Ohashi, M.; Imaizumi, H.; Ono, T. [Ono Sokki Co. Ltd., Tokyo (Japan)
1998-05-01
Human auditory sensation has both extremely excellent performance and general versatility as sound analyzer. At present, it is impossible to make equipment with the same functions as human being, and describe an auditory sensation function as acoustic sensor even by any physical analysis techniques. However, extraction of auditory sensation parameters is becoming possible by using psychoacoustics and binaural signal processing. This paper mainly explains the calculation method of sound quality evaluation parameters derived from psychoacoustic results based on a sound quality evaluation system under development by the authors. This system is based on binaural measurement by dummy head, and calculates psychoacoustic parameters such as loudness, sharpness, roughness, fluctuation strength and tonality through frequency analysis of the measured stereo signals. The system also calculates 2-D parameters such as sensory pleasantness and unbiased annoyance based on the above parameters. 12 refs., 4 figs.
Optimized multi area AGC simulation in restructured power systems
International Nuclear Information System (INIS)
Bhatt, Praghnesh; Roy, Ranjit; Ghoshal, S.P.
2010-01-01
In this paper, the traditional automatic generation control loop with modifications is incorporated for simulating automatic generation control (AGC) in restructured power system. Federal energy regulatory commission (FERC) encourages an open market system for price based operation. FERC has issued a notice for proposed rulemaking of various ancillary services. One of these ancillary services is load following with frequency control which comes broadly under Automatic Generation Control in deregulated regime. The concept of DISCO participation matrix is used to simulate the bilateral contracts in the three areas and four area diagrams. Hybrid particle swarm optimization is used to obtain optimal gain parameters for optimal transient performance. (author)
Air data system optimization using a genetic algorithm
Deshpande, Samir M.; Kumar, Renjith R.; Seywald, Hans; Siemers, Paul M., III
1992-01-01
An optimization method for flush-orifice air data system design has been developed using the Genetic Algorithm approach. The optimization of the orifice array minimizes the effect of normally distributed random noise in the pressure readings on the calculation of air data parameters, namely, angle of attack, sideslip angle and freestream dynamic pressure. The optimization method is applied to the design of Pressure Distribution/Air Data System experiment (PD/ADS) proposed for inclusion in the Aeroassist Flight Experiment (AFE). Results obtained by the Genetic Algorithm method are compared to the results obtained by conventional gradient search method.
Gomez-Cardona, Daniel; Hayes, John W; Zhang, Ran; Li, Ke; Cruz-Bastida, Juan Pablo; Chen, Guang-Hong
2018-05-01
and an anterior ROI, located further from the noise streaks region. Optimal results derived from the task-based detectability index metric were compared to other operating points in the parameter space with different noise and spatial resolution trade-offs. The optimal operating points determined through the d' metric depended on the interplay between the major spatial frequency components of each imaging task and the highly shift-variant and anisotropic noise and spatial resolution properties associated with each operating point in the LSC parameter space. This interplay influenced imaging performance the most when the major spatial frequency component of a given imaging task coincided with the direction of spatial resolution loss or with the dominant noise spatial frequency component; this was the case of imaging task II. The performance of imaging tasks I and III was influenced by this interplay in a smaller scale than imaging task II, since the major frequency component of task I was perpendicular to imaging task II, and because imaging task III did not have strong directional dependence. For both LSC methods, there was a strong dependence of the overall d' magnitude and shape of the contours on the spatial location within the phantom, particularly for imaging tasks II and III. The d' value obtained at the optimal operating point for each spatial location and imaging task was similar when comparing the LSC methods studied in this work. A local task-based detectability framework to optimize the selection of parameters for LSC methods was developed. The framework takes into account the potential shift-variant and anisotropic spatial resolution and noise properties to maximize the imaging performance of the CT system. Optimal parameters for a given LSC method depend strongly on the spatial location within the image object. © 2018 American Association of Physicists in Medicine.
PARAMETERS OPTIMIZATION OF METAL-DIELECTRIC NANOSTRUCTURES FOR SENSOR APPLICATIONS
Directory of Open Access Journals (Sweden)
V. I. Egorov
2014-07-01
Full Text Available We present calculation results of optical properties of silver nanoparticles with dielectric shell in relation to their applications in chemical and biosensors. Absorption cross-section calculation for spherical silver nanoparticles was performed by quasi static dipole approximation. It is shown that dielectric shell thickness equal to 2-3 nm and its refraction index equal to 1,5-1,75 are optimal. Calculation results were compared to experimental data. Experimental investigation of metal-dielectric nanostructures sensitivity to external refraction index was performed. Synthesis of silver nanoparticles with dielectric shell on glass surface was performed by nanosecond laser ablation method in near-surface glass layer at 1,06 μm wavelength (Solar LQ129. Synthesis of silver nanoparticles without a shell on the glass surface with silver ions was performed using thermal treatment in wet atmosphere. Spectrophotometer Cary 500 (Varyan was used for spectral measurements. In case of laser ablation method application, external refraction index changes from 1 (the air to 1,33 (water and plasmon resonance band shift for 6 nm occurs. In case of another method application at the same conditions the registered shift was equal to 13 nm. However, in the latter case the particles can be easily removed from the substrate surface. Obtained results will be useful for developing chemical and biological sensors based on plasmon resonance band shift.
Vijaya Ramnath, B.; Sharavanan, S.; Jeykrishnan, J.
2017-03-01
Nowadays quality plays a vital role in all the products. Hence, the development in manufacturing process focuses on the fabrication of composite with high dimensional accuracy and also incurring low manufacturing cost. In this work, an investigation on machining parameters has been performed on jute-flax hybrid composite. Here, the two important responses characteristics like surface roughness and material removal rate are optimized by employing 3 machining input parameters. The input variables considered are drill bit diameter, spindle speed and feed rate. Machining is done on CNC vertical drilling machine at different levels of drilling parameters. Taguchi’s L16 orthogonal array is used for optimizing individual tool parameters. Analysis Of Variance is used to find the significance of individual parameters. The simultaneous optimization of the process parameters is done by grey relational analysis. The results of this investigation shows that, spindle speed and drill bit diameter have most effect on material removal rate and surface roughness followed by feed rate.
Robust Design Optimization of an Aerospace Vehicle Prolusion System
Directory of Open Access Journals (Sweden)
Muhammad Aamir Raza
2011-01-01
Full Text Available This paper proposes a robust design optimization methodology under design uncertainties of an aerospace vehicle propulsion system. The approach consists of 3D geometric design coupled with complex internal ballistics, hybrid optimization, worst-case deviation, and efficient statistical approach. The uncertainties are propagated through worst-case deviation using first-order orthogonal design matrices. The robustness assessment is measured using the framework of mean-variance and percentile difference approach. A parametric sensitivity analysis is carried out to analyze the effects of design variables variation on performance parameters. A hybrid simulated annealing and pattern search approach is used as an optimizer. The results show the objective function of optimizing the mean performance and minimizing the variation of performance parameters in terms of thrust ratio and total impulse could be achieved while adhering to the system constraints.
METHODOLOGY FOR DETERMINING OPTIMAL EXPOSURE PARAMETERS OF A HYPERSPECTRAL SCANNING SENSOR
Directory of Open Access Journals (Sweden)
P. Walczykowski
2016-06-01
Full Text Available The purpose of the presented research was to establish a methodology that would allow the registration of hyperspectral images with a defined spatial resolution on a horizontal plane. The results obtained within this research could then be used to establish the optimum sensor and flight parameters for collecting aerial imagery data using an UAV or other aerial system. The methodology is based on an user-selected optimal camera exposure parameters (i.e. time, gain value and flight parameters (i.e. altitude, velocity. A push-broom hyperspectral imager- the Headwall MicroHyperspec A-series VNIR was used to conduct this research. The measurement station consisted of the following equipment: a hyperspectral camera MicroHyperspec A-series VNIR, a personal computer with HyperSpec III software, a slider system which guaranteed the stable motion of the sensor system, a white reference panel and a Siemens star, which was used to evaluate the spatial resolution. Hyperspectral images were recorded at different distances between the sensor and the target- from 5m to 100m. During the registration process of each acquired image, many exposure parameters were changed, such as: the aperture value, exposure time and speed of the camera’s movement on the slider. Based on all of the registered hyperspectral images, some dependencies between chosen parameters had been developed: - the Ground Sampling Distance – GSD and the distance between the sensor and the target, - the speed of the camera and the distance between the sensor and the target, - the exposure time and the gain value, - the Density Number and the gain value. The developed methodology allowed us to determine the speed and the altitude of an unmanned aerial vehicle on which the sensor would be mounted, ensuring that the registered hyperspectral images have the required spatial resolution.
Optimizing cooling systems in Egyptian arid urbans
International Nuclear Information System (INIS)
Medhat, Ahmed A.; Khalil, Essam E.
2006-01-01
Present study is devoted to climatic and site oriented investigations that were carried out in a new rural development in the Upper-Egypt. Bioclimatic classifications considered Upper Egypt region, near Sudan border, as a Hot and Dry climatic region. [1]. that is affected by solar heat intensities that can reach 900 W/m2 for a period ranged from 5-to-7 hours per day with the presence of study storms. Cooling season extends up to eight months per year having Upper-day-bulb temperature ranged from 400 degree centigrade - to - 470 degree centigrade while Lower-dry-bulb-temperature ranged from 280 degree centigrade - to - 320 degree centigrade with the relative humidity ranged from 10%-to-37% RH. [2]. Site surveys and field experimental and analyses of the commonly used cooling systems were investigated, evaluated and optimized for optimum indoor comfort conditions at efficient energy efficiency. [3]. Extensive analyses were performed based on Psychrometric formulae to evaluate the impact of energy consumptions related to different cooling systems such as direct expansion, chilled water, and evaporative systems. the present study enables the critical investigations of the influence of arid outdoor conditions and the required indoor thermal parameters on the energy efficiencies of HVAC-system. This work; focuses on the suggestion of suitable system that should be implemented by local energy codes in these arid urban.(Author)
System Topology Optimization - An Approach to System Design of Electro-Hydraulic-Mechanical Systems
DEFF Research Database (Denmark)
Andersen, T. O.; Hansen, M. R.; Conrad, Finn
2003-01-01
The current paper presents an approach to system design of combined electro-hydraulic-mechanical systems. The approach is based on the concurrent handling of the topology as well as the design parameters of the mechanical, hydraulic and controller sub- systems, respectively. Based on an initial...... design the procedure attempts to find the optimal topology and the related parameters. The topology considerations comprise the type of hydraulic pump, the employment of knee linkages or not as well as the type of hydraulic actuators. The design variables also include the signals to the proportional...... valve in a number of predefined load cases as well as the hydraulic and mechanical parameters....
GLOBAL OPTIMIZATION METHODS FOR GRAVITATIONAL LENS SYSTEMS WITH REGULARIZED SOURCES
International Nuclear Information System (INIS)
Rogers, Adam; Fiege, Jason D.
2012-01-01
Several approaches exist to model gravitational lens systems. In this study, we apply global optimization methods to find the optimal set of lens parameters using a genetic algorithm. We treat the full optimization procedure as a two-step process: an analytical description of the source plane intensity distribution is used to find an initial approximation to the optimal lens parameters; the second stage of the optimization uses a pixelated source plane with the semilinear method to determine an optimal source. Regularization is handled by means of an iterative method and the generalized cross validation (GCV) and unbiased predictive risk estimator (UPRE) functions that are commonly used in standard image deconvolution problems. This approach simultaneously estimates the optimal regularization parameter and the number of degrees of freedom in the source. Using the GCV and UPRE functions, we are able to justify an estimation of the number of source degrees of freedom found in previous work. We test our approach by applying our code to a subset of the lens systems included in the SLACS survey.
Optimization of Performance Parameters for Large Area Silicon Photomultipliers
Janzen, Kathryn
2008-10-01
The goal of the GlueX experiment is to search for exotic hybrid mesons as evidence of gluonic excitations in an effort to better understand confinement. A key component of the GlueX detector is the electromagnetic barrel calorimeter (BCAL) located immediately inside a superconducting solenoid of approximately 2.5T. Because of this arrangement, traditional vacuum photomultiplier tubes (PMTs) which are affected significantly by magnetic fields cannot be used on the BCAL. The use of Silicon photomultipliers (SiPMs) as front-end detectors has been proposed. While the largest SiPMs that have been previously employed by other experiments are 1x1 mm^2, GlueX proposes to use large area SiPMs each composed of 16 - 3x3 mm^2 cells in a 4x4 array. This puts the GlueX collaboration in the unique position of driving the technology for larger area sensors. In this talk I will discuss tests done in Regina regarding performance parameters of prototype SiPM arrays delivered by SensL, a photonics research and development company based in Ireland, as well as sample 1x1 mm^2 and 3x3 mm^2 SiPMs.
Simulation-based optimization of thermal systems
International Nuclear Information System (INIS)
Jaluria, Yogesh
2009-01-01
This paper considers the design and optimization of thermal systems on the basis of the mathematical and numerical modeling of the system. Many complexities are often encountered in practical thermal processes and systems, making the modeling challenging and involved. These include property variations, complicated regions, combined transport mechanisms, chemical reactions, and intricate boundary conditions. The paper briefly presents approaches that may be used to accurately simulate these systems. Validation of the numerical model is a particularly critical aspect and is discussed. It is important to couple the modeling with the system performance, design, control and optimization. This aspect, which has often been ignored in the literature, is considered in this paper. Design of thermal systems based on concurrent simulation and experimentation is also discussed in terms of dynamic data-driven optimization methods. Optimization of the system and of the operating conditions is needed to minimize costs and improve product quality and system performance. Different optimization strategies that are currently used for thermal systems are outlined, focusing on new and emerging strategies. Of particular interest is multi-objective optimization, since most thermal systems involve several important objective functions, such as heat transfer rate and pressure in electronic cooling systems. A few practical thermal systems are considered in greater detail to illustrate these approaches and to present typical simulation, design and optimization results
Complex optimization of radiometric control and measurement systems
International Nuclear Information System (INIS)
Onishchenko, A.M.
1995-01-01
Fundamentals of a new approach to increase in the accuracy of radiometric systems of control and measurements are presented in succession. Block diagram of the new concept of radiometric system optimization is provided. The approach involving radical increase in accuracy and envisages ascertaining of controlled parameter by the totality of two intelligence signals closely correlated with each other. The new concept makes use of system analysis as a unified one-piece object, permitting euristic synthesis of the system. 4 refs., 3 figs
Control and Estimation of Distributed Parameter Systems
Kappel, F; Kunisch, K
1998-01-01
Consisting of 23 refereed contributions, this volume offers a broad and diverse view of current research in control and estimation of partial differential equations. Topics addressed include, but are not limited to - control and stability of hyperbolic systems related to elasticity, linear and nonlinear; - control and identification of nonlinear parabolic systems; - exact and approximate controllability, and observability; - Pontryagin's maximum principle and dynamic programming in PDE; and - numerics pertinent to optimal and suboptimal control problems. This volume is primarily geared toward control theorists seeking information on the latest developments in their area of expertise. It may also serve as a stimulating reader to any researcher who wants to gain an impression of activities at the forefront of a vigorously expanding area in applied mathematics.
Characterization and optimized control by means of multi-parameter controllers
Energy Technology Data Exchange (ETDEWEB)
Nielsen, Carsten; Hoeg, S.; Thoegersen, A. (Dan-Ejendomme, Hellerup (Denmark)) (and others)
2009-07-01
Poorly functioning HVAC systems (Heating, Ventilation and Air Conditioning), but also separate heating, ventilation and air conditioning systems are costing the Danish society billions of kroner every year: partly because of increased energy consumption and high operational and maintenance costs, but mainly due to reduced productivity and absence due to illness because of a poor indoor climate. Typically, the operation of buildings and installations takes place today with traditional build-ing automation, which is characterised by 1) being based on static considerations 2) the individual sensor being coupled with one actuator/valve, i.e. the sensor's signal is only used in one place in the system 3) subsystems often being controlled independently of each other 4) the dynamics in building constructions and systems which is very important to the system and comfort regulation is not being considered. This, coupled with the widespread tendency to use large glass areas in the facades without sufficient sun shading, means that it is difficult to optimise comfort and energy consumption. Therefore, the last 10-20 years have seen a steady increase in the complaints of the indoor climate in Danish buildings and, at the same time, new buildings often turn out to be considerably higher energy consuming than expected. The purpose of the present project is to investigate the type of multi parameter sensors which may be generated for buildings and further to carry out a preliminary evaluation on how such multi parameter controllers may be utilized for optimal control of buildings. The aim of the project isn't to develop multi parameter controllers - this requires much more effort than possible in the present project. The aim is to show the potential of using multi parameter sensors when controlling buildings. For this purpose a larger office building has been chosen - an office building with at high energy demand and complaints regarding the indoor climate. In order to
Trajectory Optimization for Differential Flat Systems
Kahina Louadj; Benjamas Panomruttanarug; Alexandre Carlos Brandao Ramos; Felix Mora-Camino
2016-01-01
International audience; The purpose of this communication is to investigate the applicability of Variational Calculus to the optimization of the operation of differentially flat systems. After introducingcharacteristic properties of differentially flat systems, the applicability of variational calculus to the optimization of flat output trajectories is displayed. Two illustrative examples are also presented.
Parameter identification of a BWR nuclear power plant model for use in optimal control
International Nuclear Information System (INIS)
Volf, K.
1976-02-01
The problem being considered is the modeling of a nuclear power plant for the development of an optimal control system of the plant. Current system identification concepts, combining input/output information with a-priori structural information are employed. Two of the known parameter identification methods i.e., a least squares method and a maximum likelihood technique, are studied as ways of parameter identification from measurement data. A low order state variable stochastic model of a BWR nuclear power plant is presented as an application of this approach. The model consists of a deterministic and a noise part. The deterministic part is formed by simplified modeling of the major plant dynamic phenomena. The moise part models the effects of input random disturbances to the deterministic part and additive measurement noise. Most of the model parameters are assumed to be initially unknown. They are identified using measurement data records. A detailed high order digital computer simulation is used to simulate plant dynamic behaviour since it is not conceivable for experimentation of this kind to be performed on the real nuclear power plant. The identification task consists in adapting the performance of the simple model to the data acquired from this plant simulation ensuring the applicability of the techniques to measurement data acquired directly from the plant. (orig.) [de
Dynamical System Approaches to Combinatorial Optimization
DEFF Research Database (Denmark)
Starke, Jens
2013-01-01
of large times as an asymptotically stable point of the dynamics. The obtained solutions are often not globally optimal but good approximations of it. Dynamical system and neural network approaches are appropriate methods for distributed and parallel processing. Because of the parallelization......Several dynamical system approaches to combinatorial optimization problems are described and compared. These include dynamical systems derived from penalty methods; the approach of Hopfield and Tank; self-organizing maps, that is, Kohonen networks; coupled selection equations; and hybrid methods...... thereof can be used as models for many industrial problems like manufacturing planning and optimization of flexible manufacturing systems. This is illustrated for an example in distributed robotic systems....
Electric power system applications of optimization
Momoh, James A
2008-01-01
Introduction Structure of a Generic Electric Power System Power System Models Power System Control Power System Security Assessment Power System Optimization as a Function of Time Review of Optimization Techniques Applicable to Power Systems Electric Power System Models Complex Power Concepts Three-Phase Systems Per Unit Representation Synchronous Machine Modeling Reactive Capability Limits Prime Movers and Governing Systems Automatic Gain Control Transmission Subsystems Y-Bus Incorporating the Transformer Effect Load Models Available Transfer Capability Illustrative Examples Power
Optimizing Unmanned Aircraft System Scheduling
2008-06-01
ASC-U uses a deterministic algorithm to optimize over a given finite time horizon to obtain near-optimal UAS mission area assignments. ASC-U...the details of the algorithm . We set an upper bound on the total number of schedules that can be generated, so as not to create unsolvable ILPs. We...COL_MISSION_NAME)) If Trim( CStr (rMissions(iRow, COL_MISSION_REQUIRED))) <> "" Then If CLng(rMissions(iRow, COL_MISSION_REQUIRED)) > CLng
Directory of Open Access Journals (Sweden)
Jeevanandham Arumugam
2009-01-01
Full Text Available In this paper a classical lead-lag power system stabilizer is used for demonstration. The stabilizer parameters are selected in such a manner to damp the rotor oscillations. The problem of selecting the stabilizer parameters is converted to a simple optimization problem with an eigen value based objective function and it is proposed to employ simulated annealing and particle swarm optimization for solving the optimization problem. The objective function allows the selection of the stabilizer parameters to optimally place the closed-loop eigen values in the left hand side of the complex s-plane. The single machine connected to infinite bus system and 10-machine 39-bus system are considered for this study. The effectiveness of the stabilizer tuned using the best technique, in enhancing the stability of power system. Stability is confirmed through eigen value analysis and simulation results and suitable heuristic technique will be selected for the best performance of the system.
Safety parameter display system for Kalinin NPP
International Nuclear Information System (INIS)
Andreev, V.I.; Videneev, E.N.; Tissot, J.C.; Joonekindt, D.; Davidenko, N.N.; Shaftan, G.I.; Dounaev, V.G.; Neboyan, V.T.
1995-01-01
The paper discusses the safety parameter display system (SPDS), which is being designed for Kalinin NPP. The assessment of the safety status of the plant is done by the continuous monitoring of six critical safety functions and the corresponding status trees. Besides, a number of additional functions are realized within the scope of KlnNPP, aimed at providing the operator and the safety engineer in the main control room with more detailed information in accidental situation as well as during the normal operation. In particular, these functions are: archiving, data logs and alarm handling, safety actions monitoring, mnemonic diagrams indicating the state of main technological equipment and basic plant parameters, reference data, etc. As compared with the traditional scope of functions of this kind of systems, the functionality of KlnNPP SPDS is significantly expanded due to the inclusion in it the operator support function ''computerized procedures''. The basic SPDS implementation platform is ADACS of SEMA GROUP design. The system architecture includes two workstations in the main control room: one is for reactor operator and the other one for safety engineer. Every station has two CRT screens which ensures computerized procedures implementation and provides for extra services for the operator. Also, the information from the SPDS is transmitted to the local crisis center and to the crisis center of the State utility organization concern ''Rosenergoatom''. (author). 3 refs, 6 figs, 1 tab
Parameter estimation of Lorenz chaotic system using a hybrid swarm intelligence algorithm
International Nuclear Information System (INIS)
Lazzús, Juan A.; Rivera, Marco; López-Caraballo, Carlos H.
2016-01-01
A novel hybrid swarm intelligence algorithm for chaotic system parameter estimation is present. For this purpose, the parameters estimation on Lorenz systems is formulated as a multidimensional problem, and a hybrid approach based on particle swarm optimization with ant colony optimization (PSO–ACO) is implemented to solve this problem. Firstly, the performance of the proposed PSO–ACO algorithm is tested on a set of three representative benchmark functions, and the impact of the parameter settings on PSO–ACO efficiency is studied. Secondly, the parameter estimation is converted into an optimization problem on a three-dimensional Lorenz system. Numerical simulations on Lorenz model and comparisons with results obtained by other algorithms showed that PSO–ACO is a very powerful tool for parameter estimation with high accuracy and low deviations. - Highlights: • PSO–ACO combined particle swarm optimization with ant colony optimization. • This study is the first research of PSO–ACO to estimate parameters of chaotic systems. • PSO–ACO algorithm can identify the parameters of the three-dimensional Lorenz system with low deviations. • PSO–ACO is a very powerful tool for the parameter estimation on other chaotic system.
Parameter estimation of Lorenz chaotic system using a hybrid swarm intelligence algorithm
Energy Technology Data Exchange (ETDEWEB)
Lazzús, Juan A., E-mail: jlazzus@dfuls.cl; Rivera, Marco; López-Caraballo, Carlos H.
2016-03-11
A novel hybrid swarm intelligence algorithm for chaotic system parameter estimation is present. For this purpose, the parameters estimation on Lorenz systems is formulated as a multidimensional problem, and a hybrid approach based on particle swarm optimization with ant colony optimization (PSO–ACO) is implemented to solve this problem. Firstly, the performance of the proposed PSO–ACO algorithm is tested on a set of three representative benchmark functions, and the impact of the parameter settings on PSO–ACO efficiency is studied. Secondly, the parameter estimation is converted into an optimization problem on a three-dimensional Lorenz system. Numerical simulations on Lorenz model and comparisons with results obtained by other algorithms showed that PSO–ACO is a very powerful tool for parameter estimation with high accuracy and low deviations. - Highlights: • PSO–ACO combined particle swarm optimization with ant colony optimization. • This study is the first research of PSO–ACO to estimate parameters of chaotic systems. • PSO–ACO algorithm can identify the parameters of the three-dimensional Lorenz system with low deviations. • PSO–ACO is a very powerful tool for the parameter estimation on other chaotic system.
Optimization of a particle optical system in a mutilprocessor environment
International Nuclear Information System (INIS)
Wei Lei; Yin Hanchun; Wang Baoping; Tong Linsu
2002-01-01
In the design of a charged particle optical system, many geometrical and electric parameters have to be optimized to improve the performance characteristics. In every optimization cycle, the electromagnetic field and particle trajectories have to be calculated. Therefore, the optimization of a charged particle optical system is limited by the computer resources seriously. Apart from this, numerical errors of calculation may also influence the convergence of merit function. This article studies how to improve the optimization of charged particle optical systems. A new method is used to determine the gradient matrix. With this method, the accuracy of the Jacobian matrix can be improved. In this paper, the charged particle optical system is optimized with a Message Passing Interface (MPI). The electromagnetic field, particle trajectories and gradients of optimization variables are calculated on networks of workstations. Therefore, the speed of optimization has been increased largely. It is possible to design a complicated charged particle optical system with optimum quality on a MPI environment. Finally, an electron gun for a cathode ray tube has been optimized on a MPI environment to verify the method proposed in this paper
Ozkat, Erkan Caner; Franciosa, Pasquale; Ceglarek, Dariusz
2017-08-01
Remote laser welding technology offers opportunities for high production throughput at a competitive cost. However, the remote laser welding process of zinc-coated sheet metal parts in lap joint configuration poses a challenge due to the difference between the melting temperature of the steel (∼1500 °C) and the vapourizing temperature of the zinc (∼907 °C). In fact, the zinc layer at the faying surface is vapourized and the vapour might be trapped within the melting pool leading to weld defects. Various solutions have been proposed to overcome this problem over the years. Among them, laser dimpling has been adopted by manufacturers because of its flexibility and effectiveness along with its cost advantages. In essence, the dimple works as a spacer between the two sheets in lap joint and allows the zinc vapour escape during welding process, thereby preventing weld defects. However, there is a lack of comprehensive characterization of dimpling process for effective implementation in real manufacturing system taking into consideration inherent changes in variability of process parameters. This paper introduces a methodology to develop (i) surrogate model for dimpling process characterization considering multiple-inputs (i.e. key control characteristics) and multiple-outputs (i.e. key performance indicators) system by conducting physical experimentation and using multivariate adaptive regression splines; (ii) process capability space (Cp-Space) based on the developed surrogate model that allows the estimation of a desired process fallout rate in the case of violation of process requirements in the presence of stochastic variation; and, (iii) selection and optimization of the process parameters based on the process capability space. The proposed methodology provides a unique capability to: (i) simulate the effect of process variation as generated by manufacturing process; (ii) model quality requirements with multiple and coupled quality requirements; and (iii
Reliability Based Optimization of Structural Systems
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard
1987-01-01
The optimization problem to design structural systems such that the reliability is satisfactory during the whole lifetime of the structure is considered in this paper. Some of the quantities modelling the loads and the strength of the structure are modelled as random variables. The reliability...... is estimated using first. order reliability methods ( FORM ). The design problem is formulated as the optimization problem to minimize a given cost function such that the reliability of the single elements satisfies given requirements or such that the systems reliability satisfies a given requirement....... For these optimization problems it is described how a sensitivity analysis can be performed. Next, new optimization procedures to solve the optimization problems are presented. Two of these procedures solve the system reliability based optimization problem sequentially using quasi-analytical derivatives. Finally...
Kumar, Rishi; Mevada, N. Ramesh; Rathore, Santosh; Agarwal, Nitin; Rajput, Vinod; Sinh Barad, AjayPal
2017-08-01
To improve Welding quality of aluminum (Al) plate, the TIG Welding system has been prepared, by which Welding current, Shielding gas flow rate and Current polarity can be controlled during Welding process. In the present work, an attempt has been made to study the effect of Welding current, current polarity, and shielding gas flow rate on the tensile strength of the weld joint. Based on the number of parameters and their levels, the Response Surface Methodology technique has been selected as the Design of Experiment. For understanding the influence of input parameters on Ultimate tensile strength of weldment, ANOVA analysis has been carried out. Also to describe and optimize TIG Welding using a new metaheuristic Nature - inspired algorithm which is called as Firefly algorithm which was developed by Dr. Xin-She Yang at Cambridge University in 2007. A general formulation of firefly algorithm is presented together with an analytical, mathematical modeling to optimize the TIG Welding process by a single equivalent objective function.
Very-low speed control of PMSM based on EKF estimation with closed loop optimized parameters.
Xu, Dong; Zhang, Shaoguang; Liu, Jingmeng
2013-11-01
When calculating the speed from the position of permanent magnet synchronous motor (PMSM), the accuracy and real-time are limited by the precision of the sensor. This problem causes crawling and jitter at very-low speed. Using the angle from the position sensor, an extended Kalman filter (EKF) designed in dq-coordinate is presented to solve this problem. The usage of position sensor simplifies the model and improves the accuracy of speed estimation. Specially, a closed loop optimal (CLO) method is devised to overcome the difficulty to adjust the parameters of the EKF. The EKF is the feedback link of speed control, CLO method is derived from the perspective of the speed step response to optimize the measurement covariance matrix and the system covariance matrix of EKF. Simulation and experimental results, comparing the low-speed performance of the EKF and sensor feedback methods, prove the effectiveness of the method to adjust the parameters of EKF and the advantages in eliminating the low speed jitter. © 2013 ISA. Published by ISA. All rights reserved.
International Nuclear Information System (INIS)
Stieler, Florian; Yan, Hui; Lohr, Frank; Wenz, Frederik; Yin, Fang-Fang
2009-01-01
Parameter optimization in the process of inverse treatment planning for intensity modulated radiation therapy (IMRT) is mainly conducted by human planners in order to create a plan with the desired dose distribution. To automate this tedious process, an artificial intelligence (AI) guided system was developed and examined. The AI system can automatically accomplish the optimization process based on prior knowledge operated by several fuzzy inference systems (FIS). Prior knowledge, which was collected from human planners during their routine trial-and-error process of inverse planning, has first to be 'translated' to a set of 'if-then rules' for driving the FISs. To minimize subjective error which could be costly during this knowledge acquisition process, it is necessary to find a quantitative method to automatically accomplish this task. A well-developed machine learning technique, based on an adaptive neuro fuzzy inference system (ANFIS), was introduced in this study. Based on this approach, prior knowledge of a fuzzy inference system can be quickly collected from observation data (clinically used constraints). The learning capability and the accuracy of such a system were analyzed by generating multiple FIS from data collected from an AI system with known settings and rules. Multiple analyses showed good agreements of FIS and ANFIS according to rules (error of the output values of ANFIS based on the training data from FIS of 7.77 ± 0.02%) and membership functions (3.9%), thus suggesting that the 'behavior' of an FIS can be propagated to another, based on this process. The initial experimental results on a clinical case showed that ANFIS is an effective way to build FIS from practical data, and analysis of ANFIS and FIS with clinical cases showed good planning results provided by ANFIS. OAR volumes encompassed by characteristic percentages of isodoses were reduced by a mean of between 0 and 28%. The study demonstrated a feasible way
Directory of Open Access Journals (Sweden)
Wenz Frederik
2009-09-01
Full Text Available Abstract Background Parameter optimization in the process of inverse treatment planning for intensity modulated radiation therapy (IMRT is mainly conducted by human planners in order to create a plan with the desired dose distribution. To automate this tedious process, an artificial intelligence (AI guided system was developed and examined. Methods The AI system can automatically accomplish the optimization process based on prior knowledge operated by several fuzzy inference systems (FIS. Prior knowledge, which was collected from human planners during their routine trial-and-error process of inverse planning, has first to be "translated" to a set of "if-then rules" for driving the FISs. To minimize subjective error which could be costly during this knowledge acquisition process, it is necessary to find a quantitative method to automatically accomplish this task. A well-developed machine learning technique, based on an adaptive neuro fuzzy inference system (ANFIS, was introduced in this study. Based on this approach, prior knowledge of a fuzzy inference system can be quickly collected from observation data (clinically used constraints. The learning capability and the accuracy of such a system were analyzed by generating multiple FIS from data collected from an AI system with known settings and rules. Results Multiple analyses showed good agreements of FIS and ANFIS according to rules (error of the output values of ANFIS based on the training data from FIS of 7.77 ± 0.02% and membership functions (3.9%, thus suggesting that the "behavior" of an FIS can be propagated to another, based on this process. The initial experimental results on a clinical case showed that ANFIS is an effective way to build FIS from practical data, and analysis of ANFIS and FIS with clinical cases showed good planning results provided by ANFIS. OAR volumes encompassed by characteristic percentages of isodoses were reduced by a mean of between 0 and 28%. Conclusion The
Parameters of the Seismic system in Armenia
Energy Technology Data Exchange (ETDEWEB)
Karapetyan, N.K.
1976-01-01
An examination is made of the seismic system parameters in Armenia and the adjoining regions of Azerbaidzhan, Georgia, Iran, and Turkey. Data are given on correlations between the energy class, magnitude and intensity scale of earthquakes, and values for the level of activity and angular coefficients as a function of the region under examination, the time of observation, and method of determination; and diagrams are presented which illustrate the pattern of earthquake recurrence for the period 1679 to 1968, and observation times essential for determining earthquake recurrence with a given accuracy of 10% for the Armenian Highlands. 3 references, 2 figures, 2 tables.
DEFF Research Database (Denmark)
Pingen, Georg; Evgrafov, Anton; Maute, Kurt
2009-01-01
We present an adjoint parameter sensitivity analysis formulation and solution strategy for the lattice Boltzmann method (LBM). The focus is on design optimization applications, in particular topology optimization. The lattice Boltzmann method is briefly described with an in-depth discussion...
Logistics systems optimization under competition
DEFF Research Database (Denmark)
Choi, Tsan Ming; Govindan, Kannan; Ma, Lijun
2015-01-01
environment, decision making for all these critical areas requires more sophisticated mathematical modeling and analysis. Since finding the optimal solution of MCVRP is computationally expensive, they design a few guiding rules, which employ the searching history, to enhance the searching. They conduct...
Optimization strategies in complex systems
Bussolari, L.; Contucci, P.; Giardinà, C.; Giberti, C.; Unguendoli, F.; Vernia, C.
2003-01-01
We consider a class of combinatorial optimization problems that emerge in a variety of domains among which: condensed matter physics, theory of financial risks, error correcting codes in information transmissions, molecular and protein conformation, image restoration. We show the performances of two
Optimization of large-scale industrial systems : an emerging method
Energy Technology Data Exchange (ETDEWEB)
Hammache, A.; Aube, F.; Benali, M.; Cantave, R. [Natural Resources Canada, Varennes, PQ (Canada). CANMET Energy Technology Centre
2006-07-01
This paper reviewed optimization methods of large-scale industrial production systems and presented a novel systematic multi-objective and multi-scale optimization methodology. The methodology was based on a combined local optimality search with global optimality determination, and advanced system decomposition and constraint handling. The proposed method focused on the simultaneous optimization of the energy, economy and ecology aspects of industrial systems (E{sup 3}-ISO). The aim of the methodology was to provide guidelines for decision-making strategies. The approach was based on evolutionary algorithms (EA) with specifications including hybridization of global optimality determination with a local optimality search; a self-adaptive algorithm to account for the dynamic changes of operating parameters and design variables occurring during the optimization process; interactive optimization; advanced constraint handling and decomposition strategy; and object-oriented programming and parallelization techniques. Flowcharts of the working principles of the basic EA were presented. It was concluded that the EA uses a novel decomposition and constraint handling technique to enhance the Pareto solution search procedure for multi-objective problems. 6 refs., 9 figs.
Parameter estimation techniques for LTP system identification
Nofrarias Serra, Miquel
LISA Pathfinder (LPF) is the precursor mission of LISA (Laser Interferometer Space Antenna) and the first step towards gravitational waves detection in space. The main instrument onboard the mission is the LTP (LISA Technology Package) whose scientific goal is to test LISA's drag-free control loop by reaching a differential acceleration noise level between two masses in √ geodesic motion of 3 × 10-14 ms-2 / Hz in the milliHertz band. The mission is not only challenging in terms of technology readiness but also in terms of data analysis. As with any gravitational wave detector, attaining the instrument performance goals will require an extensive noise hunting campaign to measure all contributions with high accuracy. But, opposite to on-ground experiments, LTP characterisation will be only possible by setting parameters via telecommands and getting a selected amount of information through the available telemetry downlink. These two conditions, high accuracy and high reliability, are the main restrictions that the LTP data analysis must overcome. A dedicated object oriented Matlab Toolbox (LTPDA) has been set up by the LTP analysis team for this purpose. Among the different toolbox methods, an essential part for the mission are the parameter estimation tools that will be used for system identification during operations: Linear Least Squares, Non-linear Least Squares and Monte Carlo Markov Chain methods have been implemented as LTPDA methods. The data analysis team has been testing those methods with a series of mock data exercises with the following objectives: to cross-check parameter estimation methods and compare the achievable accuracy for each of them, and to develop the best strategies to describe the physics underlying a complex controlled experiment as the LTP. In this contribution we describe how these methods were tested with simulated LTP-like data to recover the parameters of the model and we report on the latest results of these mock data exercises.
Waste system optimization - can diameter selection
International Nuclear Information System (INIS)
Ashline, R.C.
1983-08-01
The purpose of the waste system optimization study is to define in terms of cost incentives the preferred waste package for HLW which has been converted to glass at a commercial reprocessing plant. The Waste Management Economic Model (WMEM) was employed to analyze the effect of varying important design parameters on the overall net present cost of waste handling. The parameters found to have the greatest effect on the calculated overall net present cost were can diameter, repository type (salt, basalt/bentonite, or welded tuff), allowable areal heat loading, and the repository availability date. The overall net present of a waste handling option is calculated over a 20-year operating period. It includes the total capital and operating costs associated with high-level and intermediate-level liquid waste storage, liquid waste solidification, hulls storage and compaction, and general process trash handling. It also includes the cask leasing and transportation costs associated with each waste type and the waste repository disposal costs. The waste repository disposal costs used in WMEM for this analysis were obtained from Battelle Pacific Northwest Laboratories and thir RECON model. 2 figures, 2 tables
Artificial intelligence in power system optimization
Ongsakul, Weerakorn
2013-01-01
With the considerable increase of AI applications, AI is being increasingly used to solve optimization problems in engineering. In the past two decades, the applications of artificial intelligence in power systems have attracted much research. This book covers the current level of applications of artificial intelligence to the optimization problems in power systems. This book serves as a textbook for graduate students in electric power system management and is also be useful for those who are interested in using artificial intelligence in power system optimization.
Optimization of some eco-energetic systems
International Nuclear Information System (INIS)
Purica, I.; Pavelescu, M.; Stoica, M.
1976-01-01
An optimization problem of two eco-energetic systems is described. The first one is close to the actual eco-energetic system in Romania, while the second is a new one, based on nuclear energy as primary source and hydrogen energy as secondary source. The optimization problem solved is to find the optimal structure of the systems so that the objective functions adopted, namely unitary energy cost C and total pollution P, to be minimum at the same time. The problem can be modelated with a bimatrix cooperative mathematical game without side payments. We demonstrate the superiority of the new eco-energetic system. (author)
A Pseudodifferential Approach to Distributed Parameter Systems and Stabilization
DEFF Research Database (Denmark)
Pedersen, Michael
1993-01-01
The recent developments in microlocal analysis and pdeudodifferential boundary calculus are well suited tools in the investigation of a large number of problems occurring in control theory for partial differential equations. We explain some of the basic ideas of a pseudodifferential model....... Differential Equations47 (1983); Appl. Math. Optim.10 (1983)). So far, this work seems to have simplified or unified many of the previous works cited above. We hope that in the future it will even provide stronger and newer results in the boundary control of distributed parameter systems....... (SIAM J. Control Optim.29 (1991)). The pseudo-differential techniques apply easily in the proof of existence of a feedback semigroup for the parabolic and hyperbolic evolution problems, and we reprove in this new setting some of the stabilization results of Lasiecka and Triggiani (see, e.g., J...
Sensitivity of the optimal parameter settings for a LTE packet scheduler
Fernandez-Diaz, I.; Litjens, R.; van den Berg, C.A.; Dimitrova, D.C.; Spaey, K.
Advanced packet scheduling schemes in 3G/3G+ mobile networks provide one or more parameters to optimise the trade-off between QoS and resource efficiency. In this paper we study the sensitivity of the optimal parameter setting for packet scheduling in LTE radio networks with respect to various
The primary ion source for construction and optimization of operation parameters
International Nuclear Information System (INIS)
Synowiecki, A.; Gazda, E.
1986-01-01
The construction of primary ion source for SIMS has been presented. The influence of individual operation parameters on the properties of ion source has been investigated. Optimization of these parameters has allowed to appreciate usefulness of the ion source for SIMS study. 14 refs., 8 figs., 2 tabs. (author)
Study on feed forward neural network convex optimization for LiFePO4 battery parameters
Liu, Xuepeng; Zhao, Dongmei
2017-08-01
Based on the modern facility agriculture automatic walking equipment LiFePO4 Battery, the parameter identification of LiFePO4 Battery is analyzed. An improved method for the process model of li battery is proposed, and the on-line estimation algorithm is presented. The parameters of the battery are identified using feed forward network neural convex optimization algorithm.
Optimization of accelerator parameters using normal form methods on high-order transfer maps
Energy Technology Data Exchange (ETDEWEB)
Snopok, Pavel [Michigan State Univ., East Lansing, MI (United States)
2007-05-01
in a way that is easy to understand, such important characteristics as the strengths of the resonances and the tune shifts with amplitude and various parameters of the system are calculated. Each major section is supplied with the results of applying various numerical optimization methods to the problems stated. The emphasis is made on the efficiency comparison of various approaches and methods. The main simulation tool is the arbitrary order code COSY INFINITY written by M. Berz, K. Makino, et al. at Michigan State University. Also, the code MAD is utilized to design the 750 x 750 GeV Muon Collider storage ring baseline lattice.
Maintenance resources optimization applied to a manufacturing system
International Nuclear Information System (INIS)
Fiori de Castro, Helio; Lucchesi Cavalca, Katia
2006-01-01
This paper presents an availability optimization of an engineering system assembled in a series configuration, with redundancy of units and corrective maintenance resources as optimization parameters. The aim is to reach maximum availability, considering as constraints installation and corrective maintenance costs, weight and volume. The optimization method uses a Genetic Algorithm based on biological concepts of species evolution. It is a robust method, as it does not converge to a local optimum. It does not require the use of differential calculus, thus facilitating computational implementation. Results indicate that the methodology is suitable to solve a wide range of engineering design problems involving allocation of redundancies and maintenance resources
Manjunath, S V; Kumar, S Mathava; Ngo, Huu Hao; Guo, Wenshan
2017-12-06
Metronidazole (MNZ) removal by two adsorbents, i.e., concrete-containing graphene (CG) and powder-activated carbon (PAC), was investigated via batch-mode experiments and the outcomes were used to analyze the kinetics, equilibrium and thermodynamics of MNZ adsorption. MNZ sorption on CG and PAC has followed the pseudo-second-order kinetic model, and the thermodynamic parameters revealed that MNZ adsorption was spontaneous on PAC and non-spontaneous on CG. Subsequently, two-parameter isotherm models, i.e., Langmuir, Freundlich, Temkin, Dubinin-Radushkevich and Elovich models, were applied to evaluate the MNZ adsorption capacity. The maximum MNZ adsorption capacities ([Formula: see text]) of PAC and CG were found to be between 25.5-32.8 mg/g and 0.41-0.002 mg/g, respectively. Subsequently, the effects of pH, temperature and adsorbent dosage on MNZ adsorption were evaluated by a central composite design (CCD) approach. The CCD experiments have pointed out the complete removal of MNZ at a much lower PAC dosage by increasing the system temperature (i.e., from 20°C to 40°C). On the other hand, a desorption experiment has shown 3.5% and 1.7% MNZ removal from the surface of PAC and CG, respectively, which was insignificant compared to the sorbed MNZ on the surface by adsorption. The overall findings indicate that PAC and CG with higher graphene content could be useful in MNZ removal from aqueous systems.
Toulabi, Mohammadreza; Bahrami, Shahab; Ranjbar, Ali Mohammad
2018-03-01
In most of the existing studies, the frequency response in the variable speed wind turbines (VSWTs) is simply realized by changing the torque set-point via appropriate inputs such as frequency deviations signal. However, effective dynamics and systematic process design have not been comprehensively discussed yet. Accordingly, this paper proposes a proportional-derivative frequency controller and investigates its performance in a wind farm consisting of several VSWTs. A band-pass filter is deployed before the proposed controller to avoid responding to either steady state frequency deviations or high rate of change of frequency. To design the controller, the frequency model of the wind farm is first characterized. The proposed controller is then designed based on the obtained open loop system. The stability region associated with the controller parameters is analytically determined by decomposing the closed-loop system's characteristic polynomial into the odd and even parts. The performance of the proposed controller is evaluated through extensive simulations in MATLAB/Simulink environment in a power system comprising a high penetration of VSWTs equipped with the proposed controller. Finally, based on the obtained feasible area and appropriate objective function, the optimal values associated with the controller parameters are determined using the genetic algorithm (GA). Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Accelerator optimization using a network control and acquisition system
International Nuclear Information System (INIS)
Geddes, Cameron G.R.; Catravas, P.E.; Faure, Jerome; Toth, Csaba; Tilborg, J. van; Leemans, Wim P.
2002-01-01
Accelerator optimization requires detailed study of many parameters, indicating the need for remote control and automated data acquisition systems. A control and data acquisition system based on a network of commodity PCs and applications with standards based inter-application communication is being built for the l'OASIS accelerator facility. This system allows synchronous acquisition of data at high (> 1 Hz) rates and remote control of the accelerator at low cost, allowing detailed study of the acceleration process
Intermolecular Force Field Parameters Optimization for Computer Simulations of CH4 in ZIF-8
Directory of Open Access Journals (Sweden)
Phannika Kanthima
2016-01-01
Full Text Available The differential evolution (DE algorithm is applied for obtaining the optimized intermolecular interaction parameters between CH4 and 2-methylimidazolate ([C4N2H5]− using quantum binding energies of CH4-[C4N2H5]− complexes. The initial parameters and their upper/lower bounds are obtained from the general AMBER force field. The DE optimized and the AMBER parameters are then used in the molecular dynamics (MD simulations of CH4 molecules in the frameworks of ZIF-8. The results show that the DE parameters are better for representing the quantum interaction energies than the AMBER parameters. The dynamical and structural behaviors obtained from MD simulations with both sets of parameters are also of notable differences.
Optimization of machining parameters of turning operations based on multi performance criteria
Directory of Open Access Journals (Sweden)
N.K.Mandal
2013-01-01
Full Text Available The selection of optimum machining parameters plays a significant role to ensure quality of product, to reduce the manufacturing cost and to increase productivity in computer controlled manufacturing process. For many years, multi-objective optimization of turning based on inherent complexity of process is a competitive engineering issue. This study investigates multi-response optimization of turning process for an optimal parametric combination to yield the minimum power consumption, surface roughness and frequency of tool vibration using a combination of a Grey relational analysis (GRA. Confirmation test is conducted for the optimal machining parameters to validate the test result. Various turning parameters, such as spindle speed, feed and depth of cut are considered. Experiments are designed and conducted based on full factorial design of experiment.
Prediction Model of Battery State of Charge and Control Parameter Optimization for Electric Vehicle
Directory of Open Access Journals (Sweden)
Bambang Wahono
2015-07-01
Full Text Available This paper presents the construction of a battery state of charge (SOC prediction model and the optimization method of the said model to appropriately control the number of parameters in compliance with the SOC as the battery output objectives. Research Centre for Electrical Power and Mechatronics, Indonesian Institute of Sciences has tested its electric vehicle research prototype on the road, monitoring its voltage, current, temperature, time, vehicle velocity, motor speed, and SOC during the operation. Using this experimental data, the prediction model of battery SOC was built. Stepwise method considering multicollinearity was able to efficiently develops the battery prediction model that describes the multiple control parameters in relation to the characteristic values such as SOC. It was demonstrated that particle swarm optimization (PSO succesfully and efficiently calculated optimal control parameters to optimize evaluation item such as SOC based on the model.
Parameters identification of photovoltaic models using an improved JAYA optimization algorithm
International Nuclear Information System (INIS)
Yu, Kunjie; Liang, J.J.; Qu, B.Y.; Chen, Xu; Wang, Heshan
2017-01-01
Highlights: • IJAYA algorithm is proposed to identify the PV model parameters efficiently. • A self-adaptive weight is introduced to purposefully adjust the search process. • Experience-based learning strategy is developed to enhance the population diversity. • Chaotic learning method is proposed to refine the quality of the best solution. • IJAYA features the superior performance in identifying parameters of PV models. - Abstract: Parameters identification of photovoltaic (PV) models based on measured current-voltage characteristic curves is significant for the simulation, evaluation, and control of PV systems. To accurately and reliably identify the parameters of different PV models, an improved JAYA (IJAYA) optimization algorithm is proposed in the paper. In IJAYA, a self-adaptive weight is introduced to adjust the tendency of approaching the best solution and avoiding the worst solution at different search stages, which enables the algorithm to approach the promising area at the early stage and implement the local search at the later stage. Furthermore, an experience-based learning strategy is developed and employed randomly to maintain the population diversity and enhance the exploration ability. A chaotic elite learning method is proposed to refine the quality of the best solution in each generation. The proposed IJAYA is used to solve the parameters identification problems of different PV models, i.e., single diode, double diode, and PV module. Comprehensive experiment results and analyses indicate that IJAYA can obtain a highly competitive performance compared with other state-of-the-state algorithms, especially in terms of accuracy and reliability.
International Nuclear Information System (INIS)
Yu, Kunjie; Chen, Xu; Wang, Xin; Wang, Zhenlei
2017-01-01
Highlights: • SATLBO is proposed to identify the PV model parameters efficiently. • In SATLBO, the learners self-adaptively select different learning phases. • An elite learning is developed in teacher phase to perform local searching. • A diversity learning is proposed in learner phase to maintain population diversity. • SATLBO achieves the first in ranking on overall performance among nine algorithms. - Abstract: Parameters identification of photovoltaic (PV) model based on measured current-voltage characteristic curves plays an important role in the simulation and evaluation of PV systems. To accurately and reliably identify the PV model parameters, a self-adaptive teaching-learning-based optimization (SATLBO) is proposed in this paper. In SATLBO, the learners can self-adaptively select different learning phases based on their knowledge level. The better learners are more likely to choose the learner phase for improving the population diversity, while the worse learners tend to choose the teacher phase to enhance the convergence rate. Thus, learners at different levels focus on different searching abilities to efficiently enhance the performance of algorithm. In addition, to improve the searching ability of different learning phases, an elite learning strategy and a diversity learning method are introduced into the teacher phase and learner phase, respectively. The performance of SATLBO is firstly evaluated on 34 benchmark functions, and experimental results show that SATLBO achieves the first in ranking on the overall performance among nine algorithms. Then, SATLBO is employed to identify parameters of different PV models, i.e., single diode, double diode, and PV module. Experimental results indicate that SATLBO exhibits high accuracy and reliability compared with other parameter extraction methods.
Poscharny, K.; Fabry, D.C.; Heddrich, S.; Sugiono, E.; Liauw, M.A.; Rueping, Magnus
2018-01-01
A methodology for the synthesis of oxetanes from benzophenone and furan derivatives is presented. UV-light irradiation in batch and flow systems allowed the [2 + 2] cycloaddition reaction to proceed and a broad range of oxetanes could be synthesized in manual and automated fashion. The identification of high-yielding reaction parameters was achieved through a new self-optimizing photoreactor system.
Poscharny, K.
2018-04-07
A methodology for the synthesis of oxetanes from benzophenone and furan derivatives is presented. UV-light irradiation in batch and flow systems allowed the [2 + 2] cycloaddition reaction to proceed and a broad range of oxetanes could be synthesized in manual and automated fashion. The identification of high-yielding reaction parameters was achieved through a new self-optimizing photoreactor system.
Optimizing sonication parameters for dispersion of single-walled carbon nanotubes
Energy Technology Data Exchange (ETDEWEB)
Yu, Haibo [Fraunhofer Institute for Electronic Nano Systems (Fraunhofer ENAS), 09126 Chemnitz (Germany); Graduate University of the Chinese Academy of Sciences, Beijing (China); State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, 110016 Shenyang (China); Hermann, Sascha, E-mail: sascha.hermann@zfm.tu-chemnitz.de [Center for Microtechnologies (ZfM), Chemnitz University of Technology, 09126 Chemnitz (Germany); Schulz, Stefan E.; Gessner, Thomas [Fraunhofer Institute for Electronic Nano Systems (Fraunhofer ENAS), 09126 Chemnitz (Germany); Center for Microtechnologies (ZfM), Chemnitz University of Technology, 09126 Chemnitz (Germany); Dong, Zaili [State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, 110016 Shenyang (China); Li, Wen J., E-mail: wenjungli@gmail.com [State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, 110016 Shenyang (China); Department of Mechanical and Biomedical Engineering, City University of Hong Kong, Hong Kong SAR (China)
2012-10-26
Graphical abstract: We study the dispersing behavior of SWCNTs based on the surfactant and the optimization of sonication parameters including the sonication power and running time. Highlights: Black-Right-Pointing-Pointer We study the optimization of sonication for the surfactant-based dispersion of SWCNTs. Black-Right-Pointing-Pointer The absorption spectrum of SWCNT solution strongly depend on the sonication conditions. Black-Right-Pointing-Pointer The sonication process has an important influence on the average length and diameters of SWCNTs in solution. Black-Right-Pointing-Pointer Centrifugation mainly contributes to the decrease of nonresonant absorption background. Black-Right-Pointing-Pointer Under the same sonication parameters, the large-diameter tip performs dispersion of SWCNTs better than the small-diameter tip. -- Abstract: Non-covalent functionalization based on surfactants has become one of the most common methods for dispersing of single-walled carbon nanotubes (SWCNTs). Previously, efforts have mainly been focused on experimenting with different surfactant systems, varying their concentrations and solvents. However sonication plays a very important role during the surfactant-based dispersion process for SWCNTs. The sonication treatment enables the surfactant molecules to adsorb onto the surface of SWCNTs by overcoming the interactions induced by the hydrophobic, electrostatic and van der Waals forces. This work describes a systematic study of the influence of the sonication power and time on the dispersion of SWCNTs. UV-vis-NIR absorption spectra is used to analyze and to evaluate the dispersion of SWCNTs in an aqueous solution of 1 w/v% sodium deoxycholate (DOC) showing that the resonant and nonresonant background absorption strongly depends on the sonication conditions. Furthermore, the diameter and length of SWCNTs under different sonication parameters are investigated using atomic force microscopy (AFM).
Embedded Systems Design: Optimization Challenges
DEFF Research Database (Denmark)
Pop, Paul
2005-01-01
Summary form only given. Embedded systems are everywhere: from alarm clocks to PDAs, from mobile phones to cars, almost all the devices we use are controlled by embedded systems. Over 99% of the microprocessors produced today are used in embedded systems, and recently the number of embedded systems...
Safuan, N. S.; Fathullah, M.; Shayfull, Z.; Nasir, S. M.; Hazwan, M. H. M.
2017-09-01
In injection moulding process, the defects will always encountered and affected the final product shape and functionality. This study is concerning on minimizing warpage and optimizing the process parameter of injection moulding part. Apart from eliminating product wastes, this project also giving out best recommended parameters setting. This research studied on five parameters. The optimization showed that warpage have been improved 42.64% from 0.6524 mm to 0.30879 mm in Autodesk Moldflow Insight (AMI) simulation result and Genetic Algorithm (GA) respectively.
International Nuclear Information System (INIS)
Liu Jian; Zhai Qi-Qing; Wang You-Guo; Liu Jin
2016-01-01
In this paper, we propose a parameter allocation scheme in a parallel array bistable stochastic resonance-based communication system (P-BSR-CS) to improve the performance of weak binary pulse amplitude modulated (BPAM) signal transmissions. The optimal parameter allocation policy of the P-BSR-CS is provided to minimize the bit error rate (BER) and maximize the channel capacity (CC) under the adiabatic approximation condition. On this basis, we further derive the best parameter selection theorem in realistic communication scenarios via variable transformation. Specifically, the P-BSR structure design not only brings the robustness of parameter selection optimization, where the optimal parameter pair is not fixed but variable in quite a wide range, but also produces outstanding system performance. Theoretical analysis and simulation results indicate that in the P-BSR-CS the proposed parameter allocation scheme yields considerable performance improvement, particularly in very low signal-to-noise ratio (SNR) environments. (paper)
Parameter Optimization Of Natural Hydroxyapatite/SS316l Via Metal Injection Molding (MIM)
Mustafa, N.; Ibrahim1, M. H. I.; Amin, A. M.; Asmawi, R.
2017-01-01
Metal injection molding (MIM) are well known as a worldwide application of powder injection molding (PIM) where as applied the shaping concept and the beneficial of plastic injection molding but develops the applications to various high performance metals and alloys, plus metal matrix composites and ceramics. This study investigates the strength of green part by using stainless steel 316L/ Natural hydroxyapatite composite as a feedstock. Stainless steel 316L (SS316L) was mixed with Natural hydroxyapatite (NHAP) by adding 40 wt. % Low Density Polyethylene and 60 %wt. Palm Stearin as a binder system at 63 wt. % powder loading consist of 90 % wt. of SS316 L and 10 wt. % NHAP prepared thru critical powder volume percentage (CPVC). Taguchi method was functional as a tool in determining the optimum green strength for Metal Injection Molding (MIM) parameters. The green strength was optimized with 4 significant injection parameter such as Injection temperature (A), Mold temperature (B), Pressure (C) and Speed (D) were selected throughout screening process. An orthogonal array of L9 (3)4 was conducted. The optimum injection parameters for highest green strength were established at A1, B2, C0 and D1 and where as calculated based on Signal to Noise Ratio.
Saranya, Kunaparaju; John Rozario Jegaraj, J.; Ramesh Kumar, Katta; Venkateshwara Rao, Ghanta
2016-06-01
With the increased trend in automation of modern manufacturing industry, the human intervention in routine, repetitive and data specific activities of manufacturing is greatly reduced. In this paper, an attempt has been made to reduce the human intervention in selection of optimal cutting tool and process parameters for metal cutting applications, using Artificial Intelligence techniques. Generally, the selection of appropriate cutting tool and parameters in metal cutting is carried out by experienced technician/cutting tool expert based on his knowledge base or extensive search from huge cutting tool database. The present proposed approach replaces the existing practice of physical search for tools from the databooks/tool catalogues with intelligent knowledge-based selection system. This system employs artificial intelligence based techniques such as artificial neural networks, fuzzy logic and genetic algorithm for decision making and optimization. This intelligence based optimal tool selection strategy is developed using Mathworks Matlab Version 7.11.0 and implemented. The cutting tool database was obtained from the tool catalogues of different tool manufacturers. This paper discusses in detail, the methodology and strategies employed for selection of appropriate cutting tool and optimization of process parameters based on multi-objective optimization criteria considering material removal rate, tool life and tool cost.
International Nuclear Information System (INIS)
Xu Ruirui; Chen Tianlun; Gao Chengfeng
2006-01-01
Nonlinear time series prediction is studied by using an improved least squares support vector machine (LS-SVM) regression based on chaotic mutation evolutionary programming (CMEP) approach for parameter optimization. We analyze how the prediction error varies with different parameters (σ, γ) in LS-SVM. In order to select appropriate parameters for the prediction model, we employ CMEP algorithm. Finally, Nasdaq stock data are predicted by using this LS-SVM regression based on CMEP, and satisfactory results are obtained.
A procedure for multi-objective optimization of tire design parameters
Directory of Open Access Journals (Sweden)
Nikola Korunović
2015-04-01
Full Text Available The identification of optimal tire design parameters for satisfying different requirements, i.e. tire performance characteristics, plays an essential role in tire design. In order to improve tire performance characteristics, formulation and solving of multi-objective optimization problem must be performed. This paper presents a multi-objective optimization procedure for determination of optimal tire design parameters for simultaneous minimization of strain energy density at two distinctive zones inside the tire. It consists of four main stages: pre-analysis, design of experiment, mathematical modeling and multi-objective optimization. Advantage of the proposed procedure is reflected in the fact that multi-objective optimization is based on the Pareto concept, which enables design engineers to obtain a complete set of optimization solutions and choose a suitable tire design. Furthermore, modeling of the relationships between tire design parameters and objective functions based on multiple regression analysis minimizes computational and modeling effort. The adequacy of the proposed tire design multi-objective optimization procedure has been validated by performing experimental trials based on finite element method.
Directory of Open Access Journals (Sweden)
Huanqing Cui
2017-03-01
Full Text Available Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors’ memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.
Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong
2017-03-01
Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors' memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.
Energy Technology Data Exchange (ETDEWEB)
Eldred, Michael Scott; Vigil, Dena M.; Dalbey, Keith R.; Bohnhoff, William J.; Adams, Brian M.; Swiler, Laura Painton; Lefantzi, Sophia (Sandia National Laboratories, Livermore, CA); Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Eddy, John P.
2011-12-01
The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the DAKOTA software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of DAKOTA-related research publications in the areas of surrogate-based optimization, uncertainty quantification, and optimization under uncertainty that provide the foundation for many of DAKOTA's iterative analysis capabilities.
Optimizing the Gating System for Steel Castings
Directory of Open Access Journals (Sweden)
Jan Jezierski
2018-04-01
Full Text Available The article presents the attempt to optimize a gating system to produce cast steel castings. It is based on John Campbell’s theory and presents the original results of computer modelling of typical and optimized gating systems for cast steel castings. The current state-of-the-art in cast steel casting foundry was compared with several proposals of optimization. The aim was to find a compromise between the best, theoretically proven gating system version, and a version that would be affordable in industrial conditions. The results show that it is possible to achieve a uniform and slow pouring process even for heavy castings to preserve their internal quality.
Dynamic Parameter-Control Chaotic System.
Hua, Zhongyun; Zhou, Yicong
2016-12-01
This paper proposes a general framework of 1-D chaotic maps called the dynamic parameter-control chaotic system (DPCCS). It has a simple but effective structure that uses the outputs of a chaotic map (control map) to dynamically control the parameter of another chaotic map (seed map). Using any existing 1-D chaotic map as the control/seed map (or both), DPCCS is able to produce a huge number of new chaotic maps. Evaluations and comparisons show that chaotic maps generated by DPCCS are very sensitive to their initial states, and have wider chaotic ranges, better unpredictability and more complex chaotic behaviors than their seed maps. Using a chaotic map of DPCCS as an example, we provide a field-programmable gate array design of this chaotic map to show the simplicity of DPCCS in hardware implementation, and introduce a new pseudo-random number generator (PRNG) to investigate the applications of DPCCS. Analysis and testing results demonstrate the excellent randomness of the proposed PRNG.
Samavati, Vahid; D-jomeh, Zahra Emam
2013-11-06
Optimization for retention and partition coefficient of ethyl acetate in emulsion model systems was investigated using response surface methodology in this paper. The effects of emulsion model ingredients, tragacanth gum (TG) (0.5-1 wt%), whey protein isolate (WPI) (2-4 wt%) and oleic acid (5-10%, v/v) on retention and partition coefficient of ethyl acetate were studied using a five-level three-factor central composite rotatable design (CCRD). Results showed that the regression models generated adequately explained the data variation and significantly represented the actual relationships between the independent and response parameters. The results showed that the highest retention (97.20±0.51%) and lowest partition coefficient (4.51±0.13%) of ethyl acetate were reached at the TG concentration 1 wt%, WPI concentration 4 wt% and oleic acid volume fraction 10% (v/v). Copyright © 2013 Elsevier Ltd. All rights reserved.
Parameter and state estimation in nonlinear dynamical systems
Creveling, Daniel R.
and driven by the synchronization error to increase coupling when needed. This method, along with a suitable cost function, allows for the determination of model parameters without the complexity of calculating Lyapunov exponents. Lastly, a method is developed allowing the coupling to vary in time without the constraint of following a differential equation. This approach shows the equivalence of the parameter and state estimation problem to that of tracking within an optimal control framework. This equivalence allows the application of powerful numerical methods that provide robust practical tools for model development and validation. Examples of each of these methods are presented with both simulated data and data measured from electrical circuit implementations of several dynamical systems.
N-Springs pump and treat system optimization study
International Nuclear Information System (INIS)
1997-03-01
This letter report describes and presents the results of a system optimization study conducted to evaluate the N-Springs pump and treat system. The N-Springs pump and treat is designed to remove strontium-90 (90Sr) found in the groundwater in the 100-NR-2 Operable Unit near the Columbia River. The goal of the system optimization study was to assess and quantify what conditions and operating parameters could be employed to enhance the operating and cost effectiveness of the recently upgraded pump and treat system.This report provides the results of the system optimization study, reports the cost effectiveness of operating the pump and treat at various operating modes and 90Sr removal goals, and provides recommendations for operating the pump and treat
Optimization of Steering System of Forklift Vehicle for Idle Performance
Directory of Open Access Journals (Sweden)
Yuan Shen
2015-01-01
Full Text Available This paper presents an optimal design process for the steering system of a forklift vehicle. An efficient procedure for minimizing the engine-induced idle vibration is developed in this study. Reciprocating unbalance and gas pressure torque as two major sources of engine excitation are studied. Using the field vibration tests and FEM analysis, the cause and characteristics of steering system’s idle vibration are recognized. So as to distribute the characteristic modes based on the optimization strategy, global sensitivity analysis of the main parameters is also carried out to achieve the optimal combination of the optimization factors. Based on all analysis above, some structure modifications for optimization are presented to control the idle vibration. The effectiveness and rationality of the improvements are also verified through experimental prototyping testing. This study also makes it possible to provide a design guideline using CAE (computer aided engineering analysis for some other objects.
Periodic orbits of hybrid systems and parameter estimation via AD
International Nuclear Information System (INIS)
Guckenheimer, John; Phipps, Eric Todd; Casey, Richard
2004-01-01
Rhythmic, periodic processes are ubiquitous in biological systems; for example, the heart beat, walking, circadian rhythms and the menstrual cycle. Modeling these processes with high fidelity as periodic orbits of dynamical systems is challenging because: (1) (most) nonlinear differential equations can only be solved numerically; (2) accurate computation requires solving boundary value problems; (3) many problems and solutions are only piecewise smooth; (4) many problems require solving differential-algebraic equations; (5) sensitivity information for parameter dependence of solutions requires solving variational equations; and (6) truncation errors in numerical integration degrade performance of optimization methods for parameter estimation. In addition, mathematical models of biological processes frequently contain many poorly-known parameters, and the problems associated with this impedes the construction of detailed, high-fidelity models. Modelers are often faced with the difficult problem of using simulations of a nonlinear model, with complex dynamics and many parameters, to match experimental data. Improved computational tools for exploring parameter space and fitting models to data are clearly needed. This paper describes techniques for computing periodic orbits in systems of hybrid differential-algebraic equations and parameter estimation methods for fitting these orbits to data. These techniques make extensive use of automatic differentiation to accurately and efficiently evaluate derivatives for time integration, parameter sensitivities, root finding and optimization. The boundary value problem representing a periodic orbit in a hybrid system of differential algebraic equations is discretized via multiple-shooting using a high-degree Taylor series integration method (GM00, Phi03). Numerical solutions to the shooting equations are then estimated by a Newton process yielding an approximate periodic orbit. A metric is defined for computing the distance
Reliability-Based Optimization of Series Systems of Parallel Systems
DEFF Research Database (Denmark)
Enevoldsen, I.; Sørensen, John Dalsgaard
Reliability-based design of structural systems is considered. Especially systems where the reliability model is a series system of parallel systems are analysed. A sensitivity analysis for this class of problems is presented. Direct and sequential optimization procedures to solve the optimization...
Energy Technology Data Exchange (ETDEWEB)
Turner, D P; Ritts, W D; Wharton, S; Thomas, C; Monson, R; Black, T A
2009-02-26
The combination of satellite remote sensing and carbon cycle models provides an opportunity for regional to global scale monitoring of terrestrial gross primary production, ecosystem respiration, and net ecosystem production. FPAR (the fraction of photosynthetically active radiation absorbed by the plant canopy) is a critical input to diagnostic models, however little is known about the relative effectiveness of FPAR products from different satellite sensors nor about the sensitivity of flux estimates to different parameterization approaches. In this study, we used multiyear observations of carbon flux at four eddy covariance flux tower sites within the conifer biome to evaluate these factors. FPAR products from the MODIS and SeaWiFS sensors, and the effects of single site vs. cross-site parameter optimization were tested with the CFLUX model. The SeaWiFs FPAR product showed greater dynamic range across sites and resulted in slightly reduced flux estimation errors relative to the MODIS product when using cross-site optimization. With site-specific parameter optimization, the flux model was effective in capturing seasonal and interannual variation in the carbon fluxes at these sites. The cross-site prediction errors were lower when using parameters from a cross-site optimization compared to parameter sets from optimization at single sites. These results support the practice of multisite optimization within a biome for parameterization of diagnostic carbon flux models.
International Nuclear Information System (INIS)
Carver, M.B.; Austin, C.F.; Ross, N.E.
1980-02-01
This report discusses the mechanics of automated parameter identification in simulation packages, and reviews available integration and optimization algorithms and their interaction within the recently developed optimization options in the FORSIM and MACKSIM simulation packages. In the MACKSIM mass-action chemical kinetics simulation package, the form and structure of the ordinary differential equations involved is known, so the implementation of an optimizing option is relatively straightforward. FORSIM, however, is designed to integrate ordinary and partial differential equations of abritrary definition. As the form of the equations is not known in advance, the design of the optimizing option is more intricate, but the philosophy could be applied to most simulation packages. In either case, however, the invocation of the optimizing interface is simple and user-oriented. Full details for the use of the optimizing mode for each program are given; specific applications are used as examples. (O.T.)
A Taguchi approach on optimal process control parameters for HDPE pipe extrusion process
Sharma, G. V. S. S.; Rao, R. Umamaheswara; Rao, P. Srinivasa
2017-06-01
High-density polyethylene (HDPE) pipes find versatile applicability for transportation of water, sewage and slurry from one place to another. Hence, these pipes undergo tremendous pressure by the fluid carried. The present work entails the optimization of the withstanding pressure of the HDPE pipes using Taguchi technique. The traditional heuristic methodology stresses on a trial and error approach and relies heavily upon the accumulated experience of the process engineers for determining the optimal process control parameters. This results in setting up of less-than-optimal values. Hence, there arouse a necessity to determine optimal process control parameters for the pipe extrusion process, which can ensure robust pipe quality and process reliability. In the proposed optimization strategy, the design of experiments (DoE) are conducted wherein different control parameter combinations are analyzed by considering multiple setting levels of each control parameter. The concept of signal-to-noise ratio ( S/ N ratio) is applied and ultimately optimum values of process control parameters are obtained as: pushing zone temperature of 166 °C, Dimmer speed at 08 rpm, and Die head temperature to be 192 °C. Confirmation experimental run is also conducted to verify the analysis and research result and values proved to be in synchronization with the main experimental findings and the withstanding pressure showed a significant improvement from 0.60 to 1.004 Mpa.
Selection of Near Optimal Laser Cutting Parameters in CO2 Laser Cutting by the Taguchi Method
Directory of Open Access Journals (Sweden)
Miloš MADIĆ
2013-12-01
Full Text Available Identification of laser cutting conditions that are insensitive to parameter variations and noise is of great importance. This paper demonstrates the application of Taguchi method for optimization of surface roughness in CO2 laser cutting of stainless steel. The laser cutting experiment was planned and conducted according to the Taguchi’s experimental design using the L27 orthogonal array. Four laser cutting parameters such as laser power, cutting speed, assist gas pressure, and focus position were considered in the experiment. Using the analysis of means and analysis of variance, the significant laser cutting parameters were identified, and subsequently the optimal combination of laser cutting parameter levels was determined. The results showed that the cutting speed is the most significant parameter affecting the surface roughness whereas the influence of the assist gas pressure can be neglected. It was observed, however, that interaction effects have predominant influence over the main effects on the surface roughness.
Application of Factorial Design for Gas Parameter Optimization in CO2 Laser Welding
DEFF Research Database (Denmark)
Gong, Hui; Dragsted, Birgitte; Olsen, Flemming Ove
1997-01-01
The effect of different gas process parameters involved in CO2 laser welding has been studied by applying two-set of three-level complete factorial designs. In this work 5 gas parameters, gas type, gas flow rate, gas blowing angle, gas nozzle diameter, gas blowing point-offset, are optimized...... to be a very useful tool for parameter optimi-zation in laser welding process. Keywords: CO2 laser welding, gas parameters, factorial design, Analysis of Variance........ The bead-on-plate welding specimens are evaluated by a number of quality char-acteristics, such as the penetration depth and the seam width. The significance of the gas pa-rameters and their interactions are based on the data found by the Analysis of Variance-ANOVA. This statistic methodology is proven...
Error propagation of partial least squares for parameters optimization in NIR modeling.
Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng
2018-03-05
A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models. Copyright © 2017. Published by Elsevier B.V.
Error propagation of partial least squares for parameters optimization in NIR modeling
Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng
2018-03-01
A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models.
Directory of Open Access Journals (Sweden)
Fan Chen
2016-01-01
Full Text Available In order to achieve the precision and efficient processing of nanocomposite ceramics, the ultrasound-aided electrolytic in process dressing method was proposed. But how to realize grinding parameter optimization, that is, the maximum processing efficiency, on the premise of the assurance of best workpiece quality is a problem that needs to be solved urgently. Firstly, this research investigated the influence of grinding parameters on material removal rate and critical ductile depth, and their mathematic models based on the existing models were developed to simulate the material removal process. Then, on the basis of parameter sensitivity analysis based on partial derivative, the sensitivity models of material removal rates on grinding parameter were established and computed quantitatively by MATLAB, and the key grinding parameter for optimal grinding process was found. Finally, the theoretical analyses were verified by experiments: the material removal rate increases with the increase of grinding parameters, including grinding depth (ap, axial feeding speed (fa, workpiece speed (Vw, and wheel speed (Vs; the parameter sensitivity of material removal rate was in a descending order as ap>fa>Vw>Vs; the most sensitive parameter (ap was optimized and it was found that the better machining result has been obtained when ap was about 3.73 μm.
Fault detection of feed water treatment process using PCA-WD with parameter optimization.
Zhang, Shirong; Tang, Qian; Lin, Yu; Tang, Yuling
2017-05-01
Feed water treatment process (FWTP) is an essential part of utility boilers; and fault detection is expected for its reliability improvement. Classical principal component analysis (PCA) has been applied to FWTPs in our previous work; however, the noises of T 2 and SPE statistics result in false detections and missed detections. In this paper, Wavelet denoise (WD) is combined with PCA to form a new algorithm, (PCA-WD), where WD is intentionally employed to deal with the noises. The parameter selection of PCA-WD is further formulated as an optimization problem; and PSO is employed for optimization solution. A FWTP, sustaining two 1000MW generation units in a coal-fired power plant, is taken as a study case. Its operation data is collected for following verification study. The results show that the optimized WD is effective to restrain the noises of T 2 and SPE statistics, so as to improve the performance of PCA-WD algorithm. And, the parameter optimization enables PCA-WD to get its optimal parameters in an automatic way rather than on individual experience. The optimized PCA-WD is further compared with classical PCA and sliding window PCA (SWPCA), in terms of four cases as bias fault, drift fault, broken line fault and normal condition, respectively. The advantages of the optimized PCA-WD, against classical PCA and SWPCA, is finally convinced with the results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Papagiannis, P.; Azariadis, P.; Papanikos, P.
2017-10-01
Footwear is subject to bending and torsion deformations that affect comfort perception. Following review of Finite Element Analysis studies of sole rigidity and comfort, a three-dimensional, linear multi-material finite element sole model for quasi-static bending and torsion simulation, overcoming boundary and optimisation limitations, is described. Common footwear materials properties and boundary conditions from gait biomechanics are used. The use of normalised strain energy for product benchmarking is demonstrated along with comfort level determination through strain energy density stratification. Sensitivity of strain energy against material thickness is greater for bending than for torsion, with results of both deformations showing positive correlation. Optimization for a targeted performance level and given layer thickness is demonstrated with bending simulations sufficing for overall comfort assessment. An algorithm for comfort optimization w.r.t. bending is presented, based on a discrete approach with thickness values set in line with practical manufacturing accuracy. This work illustrates the potential of the developed finite element analysis applications to offer viable and proven aids to modern footwear sole design assessment and optimization.
Optimal beamforming in MIMO systems with HPA nonlinearity
Qi, Jian
2010-09-01
In this paper, multiple-input multiple-output (MIMO) transmit beamforming (TB) systems under the consideration of nonlinear high-power amplifiers (HPAs) are investigated. The optimal beamforming scheme, with the optimal beamforming weight vector and combining vector, is proposed for MIMO systems with HPA nonlinearity. The performance of the proposed MIMO beamforming scheme in the presence of HPA nonlinearity is evaluated in terms of average symbol error probability (SEP), outage probability and system capacity, considering transmission over uncorrelated quasi-static frequency-flat Rayleigh fading channels. Numerical results are provided and show the effects of several system parameters, namely, parameters of nonlinear HPA, numbers of transmit and receive antennas, and modulation order of phase-shift keying (PSK), on performance. ©2010 IEEE.