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Sample records for process parameter optimization

  1. 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.

  2. 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, ...

  3. 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.

  4. 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...

  5. Laser Processing of Multilayered Thermal Spray Coatings: Optimal Processing Parameters

    Science.gov (United States)

    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.

  6. Parameter optimization of electrochemical machining process using black hole algorithm

    Science.gov (United States)

    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.

  7. 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 ...

  8. 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 ...

  9. 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 ...

  10. 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.

  11. Optimization of cutting parameters for machining time in turning process

    Science.gov (United States)

    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.

  12. Optimization of process parameters for friction stir processing (FSP ...

    Indian Academy of Sciences (India)

    Administrator

    al 2005; Yadav and Bauri 2011) as the thermo- mechanical aspect of the process provides enough driving force for occurrence of dynamic recovery (DRV) that precedes DRX leading to an equi-axed fine grain struc- ture. The microstructure evolution is further discussed below with the aid of transmission electron microscopy.

  13. Optimization of Robotic Spray Painting process Parameters using Taguchi Method

    Science.gov (United States)

    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.

  14. 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.

  15. 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.

  16. A Taguchi approach on optimal process control parameters for HDPE pipe extrusion process

    Science.gov (United States)

    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.

  17. 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)

  18. Laser dimpling process parameters selection and optimization using surrogate-driven process capability space

    Science.gov (United States)

    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

  19. 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 ...

  20. Biologic phosphorus elimination - influencing parameters, boundary conditions, process optimation

    International Nuclear Information System (INIS)

    Dai Xiaohu.

    1992-01-01

    This paper first presents a systematic study of the basic process of biologic phosphorus elimination as employed by the original 'Phoredox (Main Stream) Process'. The conditions governing the process and the factors influencing its performance were determined by trial operation. A stationary model was developed for the purpose of modelling biologic phosphorus elimination in such a main stream process and optimising the dimensioning. The validity of the model was confirmed by operational data given in the literature and by operational data from the authors' own semitechnical-scale experimental plant. The model permits simulation of the values to be expected for effluent phosphorus and phosphate concentrations for given influent data and boundary conditions. It is thus possible to dimension a plant for accomodation of the original Phoredox (Main Stream) Process or any similar phosphorus eliminating plant that is to work according to the principle of the main stream process. (orig./EF) [de

  1. 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

  2. Optimization of Injection Moulding Process Parameters in the ...

    African Journals Online (AJOL)

    ADOWIE PERE

    https://www.ajol.info/index.php/jasem ... Cooling time was found to be the factor with most significant effect on ... Keywords: High Density Polyethylene (HDPE), Injection Moulding, Process .... value of shrinkage behavior is expected to be.

  3. Multi-Response Parameter Interval Sensitivity and Optimization for the Composite Tape Winding Process

    Science.gov (United States)

    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

  4. 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.

  5. Optimization of process parameters in drilling of fibre hybrid composite using Taguchi and grey relational analysis

    Science.gov (United States)

    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.

  6. Optimization of TRPO process parameters for americium extraction from high level waste

    International Nuclear Information System (INIS)

    Chen Jing; Wang Jianchen; Song Chongli

    2001-01-01

    The numerical calculations for Am multistage fractional extraction by trialkyl phosphine oxide (TRPO) were verified by a hot test. 1750L/t-U high level waste (HLW) was used as the feed to the TRPO process. The analysis used the simple objective function to minimize the total waste content in the TRPO process streams. Some process parameters were optimized after other parameters were selected. The optimal process parameters for Am extraction by TRPO are: 10 stages for extraction and 2 stages for scrubbing; a flow rate ratio of 0.931 for extraction and 4.42 for scrubbing; nitric acid concentration of 1.35 mol/L for the feed and 0.5 mol/L for the scrubbing solution. Finally, the nitric acid and Am concentration profiles in the optimal TRPO extraction process are given

  7. Warpage improvement on wheel caster by optimizing the process parameters using genetic algorithm (GA)

    Science.gov (United States)

    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.

  8. Grinding Parameter Optimization of Ultrasound-Aided Electrolytic in Process Dressing for Finishing Nanocomposite Ceramics

    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.

  9. Optimization of submerged arc welding process parameters using quasi-oppositional based Jaya algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Rao, R. Venkata; Rai, Dhiraj P. [Sardar Vallabhbhai National Institute of Technology, Gujarat (India)

    2017-05-15

    Submerged arc welding (SAW) is characterized as a multi-input process. Selection of optimum combination of process parameters of SAW process is a vital task in order to achieve high quality of weld and productivity. The objective of this work is to optimize the SAW process parameters using a simple optimization algorithm, which is fast, robust and convenient. Therefore, in this work a very recently proposed optimization algorithm named Jaya algorithm is applied to solve the optimization problems in SAW process. In addition, a modified version of Jaya algorithm with oppositional based learning, named “Quasi-oppositional based Jaya algorithm” (QO-Jaya) is proposed in order to improve the performance of the Jaya algorithm. Three optimization case studies are considered and the results obtained by Jaya algorithm and QO-Jaya algorithm are compared with the results obtained by well-known optimization algorithms such as Genetic algorithm (GA), Particle swarm optimization (PSO), Imperialist competitive algorithm (ICA) and Teaching learning based optimization (TLBO).

  10. Optimization of submerged arc welding process parameters using quasi-oppositional based Jaya algorithm

    International Nuclear Information System (INIS)

    Rao, R. Venkata; Rai, Dhiraj P.

    2017-01-01

    Submerged arc welding (SAW) is characterized as a multi-input process. Selection of optimum combination of process parameters of SAW process is a vital task in order to achieve high quality of weld and productivity. The objective of this work is to optimize the SAW process parameters using a simple optimization algorithm, which is fast, robust and convenient. Therefore, in this work a very recently proposed optimization algorithm named Jaya algorithm is applied to solve the optimization problems in SAW process. In addition, a modified version of Jaya algorithm with oppositional based learning, named “Quasi-oppositional based Jaya algorithm” (QO-Jaya) is proposed in order to improve the performance of the Jaya algorithm. Three optimization case studies are considered and the results obtained by Jaya algorithm and QO-Jaya algorithm are compared with the results obtained by well-known optimization algorithms such as Genetic algorithm (GA), Particle swarm optimization (PSO), Imperialist competitive algorithm (ICA) and Teaching learning based optimization (TLBO).

  11. Parameter extraction using global particle swarm optimization approach and the influence of polymer processing temperature on the solar cell parameters

    Science.gov (United States)

    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.

  12. An analysis to optimize the process parameters of friction stir welded ...

    African Journals Online (AJOL)

    The friction stir welding (FSW) of steel is a challenging task. Experiments are conducted here, with a tool having a conical pin of 0.4mm clearance. The process parameters are optimized by using the Taguchi technique based on Taguchi's L9 orthogonal array. Experiments have been conducted based on three process ...

  13. Optimization of WEDM process parameters using deep cryo-treated Inconel 718 as work material

    Directory of Open Access Journals (Sweden)

    Bijaya Bijeta Nayak

    2016-03-01

    Full Text Available The present work proposes an experimental investigation and optimization of various process parameters during taper cutting of deep cryo-treated Inconel 718 in wire electrical discharge machining process. Taguchi's design of experiment is used to gather information regarding the process with less number of experimental runs considering six input parameters such as part thickness, taper angle, pulse duration, discharge current, wire speed and wire tension. Since traditional Taguchi method fails to optimize multiple performance characteristics, maximum deviation theory is applied to convert multiple performance characteristics into an equivalent single performance characteristic. Due to the complexity and non-linearity involved in this process, good functional relationship with reasonable accuracy between performance characteristics and process parameters is difficult to obtain. To address this issue, the present study proposes artificial neural network (ANN model to determine the relationship between input parameters and performance characteristics. Finally, the process model is optimized to obtain a best parametric combination by a new meta-heuristic approach known as bat algorithm. The results of the proposed algorithm show that the proposed method is an effective tool for simultaneous optimization of performance characteristics during taper cutting in WEDM process.

  14. Process parameter optimization based on principal components analysis during machining of hardened steel

    Directory of Open Access Journals (Sweden)

    Suryakant B. Chandgude

    2015-09-01

    Full Text Available The optimum selection of process parameters has played an important role for improving the surface finish, minimizing tool wear, increasing material removal rate and reducing machining time of any machining process. In this paper, optimum parameters while machining AISI D2 hardened steel using solid carbide TiAlN coated end mill has been investigated. For optimization of process parameters along with multiple quality characteristics, principal components analysis method has been adopted in this work. The confirmation experiments have revealed that to improve performance of cutting; principal components analysis method would be a useful tool.

  15. Optimization of injection molding process parameters for a plastic cell phone housing component

    Science.gov (United States)

    Rajalingam, Sokkalingam; Vasant, Pandian; Khe, Cheng Seong; Merican, Zulkifli; Oo, Zeya

    2016-11-01

    To produce thin-walled plastic items, injection molding process is one of the most widely used application tools. However, to set optimal process parameters is difficult as it may cause to produce faulty items on injected mold like shrinkage. This study aims at to determine such an optimum injection molding process parameters which can reduce the fault of shrinkage on a plastic cell phone cover items. Currently used setting of machines process produced shrinkage and mis-specified length and with dimensions below the limit. Thus, for identification of optimum process parameters, maintaining closer targeted length and width setting magnitudes with minimal variations, more experiments are needed. The mold temperature, injection pressure and screw rotation speed are used as process parameters in this research. For optimal molding process parameters the Response Surface Methods (RSM) is applied. The major contributing factors influencing the responses were identified from analysis of variance (ANOVA) technique. Through verification runs it was found that the shrinkage defect can be minimized with the optimal setting found by RSM.

  16. Optimization of cryogenic cooled EDM process parameters using grey relational analysis

    International Nuclear Information System (INIS)

    Kumar, S Vinoth; Kumar, M Pradeep

    2014-01-01

    This paper presents an experimental investigation on cryogenic cooling of liquid nitrogen (LN 2 ) copper electrode in the electrical discharge machining (EDM) process. The optimization of the EDM process parameters, such as the electrode environment (conventional electrode and cryogenically cooled electrode in EDM), discharge current, pulse on time, gap voltage on material removal rate, electrode wear, and surface roughness on machining of AlSiCp metal matrix composite using multiple performance characteristics on grey relational analysis was investigated. The L 18 orthogonal array was utilized to examine the process parameters, and the optimal levels of the process parameters were identified through grey relational analysis. Experimental data were analyzed through analysis of variance. Scanning electron microscopy analysis was conducted to study the characteristics of the machined surface.

  17. VISUALIZATION SOFTWARE DEVELOPMENT FOR PROCEDURE OF MULTI-DIMENSIONAL OPTIMIZATION OF TECHNOLOGICAL PROCESS FUNCTIONAL PARAMETERS

    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.

  18. Optimization of process parameters in welding of dissimilar steels using robot TIG welding

    Science.gov (United States)

    Navaneeswar Reddy, G.; VenkataRamana, M.

    2018-03-01

    Robot TIG welding is a modern technique used for joining two work pieces with high precision. Design of Experiments is used to conduct experiments by varying weld parameters like current, wire feed and travelling speed. The welding parameters play important role in joining of dissimilar stainless steel SS 304L and SS430. In this work, influences of welding parameter on Robot TIG Welded specimens are investigated using Response Surface Methodology. The Micro Vickers hardness tests of the weldments are measured. The process parameters are optimized to maximize the hardness of the weldments.

  19. Optimization of process parameters for a quasi-continuous tablet coating system using design of experiments.

    Science.gov (United States)

    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

  20. Optimization of the Process Parameters for Controlling Residual Stress and Distortion in Friction Stir Welding

    DEFF Research Database (Denmark)

    Tutum, Cem Celal; Schmidt, Henrik Nikolaj Blicher; Hattel, Jesper Henri

    2008-01-01

    In the present paper, numerical optimization of the process parameters, i.e. tool rotation speed and traverse speed, aiming minimization of the two conflicting objectives, i.e. the residual stresses and welding time, subjected to process-specific thermal constraints in friction stir welding......, is investigated. The welding process is simulated in 2-dimensions with a sequentially coupled transient thermo-mechanical model using ANSYS. The numerical optimization problem is implemented in modeFRONTIER and solved using the Multi-Objective Genetic Algorithm (MOGA-II). An engineering-wise evaluation or ranking...

  1. 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)

  2. Laser Welding Process Parameters Optimization Using Variable-Fidelity Metamodel and NSGA-II

    Directory of Open Access Journals (Sweden)

    Wang Chaochao

    2017-01-01

    Full Text Available An optimization methodology based on variable-fidelity (VF metamodels and nondominated sorting genetic algorithm II (NSGA-II for laser bead-on-plate welding of stainless steel 316L is presented. The relationships between input process parameters (laser power, welding speed and laser focal position and output responses (weld width and weld depth are constructed by VF metamodels. In VF metamodels, the information from two levels fidelity models are integrated, in which the low-fidelity model (LF is finite element simulation model that is used to capture the general trend of the metamodels, and high-fidelity (HF model which from physical experiments is used to ensure the accuracy of metamodels. The accuracy of the VF metamodel is verified by actual experiments. To slove the optimization problem, NSGA-II is used to search for multi-objective Pareto optimal solutions. The results of verification experiments show that the obtained optimal parameters are effective and reliable.

  3. Fault detection of feed water treatment process using PCA-WD with parameter optimization.

    Science.gov (United States)

    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.

  4. Optimization of process parameters in precipitation for consistent quality UO{sub 2} powder production

    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)

  5. 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)

  6. Model Optimization Identification Method Based on Closed-loop Operation Data and Process Characteristics Parameters

    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.

  7. Optimization of process parameter for graft copolymerization of glycidyl methacrylate onto delignified banana fibers

    International Nuclear Information System (INIS)

    Selambakkannu, S.; Nor Azillah Fatimah Othman; Siti Fatahiyah Mohamad

    2016-01-01

    This paper focused on pre-treated banana fibers as a trunk polymer for optimization of radiation-induced graft copolymerization process parameters. Pre-treated banana fiber was grafted with glycidyl methacrylate (GMA) via electron beam irradiation. Optimization of grafting parameters in term of grafting yield was analyzed at numerous radiation dose, monomer concentration and reaction time. Grafting yield had been calculated gravimetrically against all the process parameters. The grafting yield at 40 kGy had increases from 14 % to 22.5 % at 1 h and 24 h of reaction time respectively. Grafting yield at 1 % of GMA was about 58 % and it increases to 187 % at 3 % GMA. The grafting of GMA onto pre-treated banana fibers confirmed with the characterization using FTIR, SEM and TGA. Grafting of GMA onto pre-treated fibers was successfully carried out and it was confirmed by the results obtained via the characterization. (author)

  8. Optimization of a Cu CMP process modeling parameters of nanometer integrated circuits

    International Nuclear Information System (INIS)

    Ruan Wenbiao; Chen Lan; Ma Tianyu; Fang Jingjing; Zhang He; Ye Tianchun

    2012-01-01

    A copper chemical mechanical polishing (Cu CMP) process is reviewed and analyzed from the view of chemical physics. Three steps Cu CMP process modeling is set up based on the actual process of manufacturing and pattern-density-step-height (PDSH) modeling from MIT. To catch the pattern dependency, a 65 nm testing chip is designed and processed in the foundry. Following the model parameter extraction procedure, the model parameters are extracted and verified by testing data from the 65 nm testing chip. A comparison of results between the model predictions and test data show that the former has the same trend as the latter and the largest deviation is less than 5 nm. Third party testing data gives further evidence to support the great performance of model parameter optimization. Since precise CMP process modeling is used for the design of manufacturability (DFM) checks, critical hotspots are displayed and eliminated, which will assure good yield and production capacity of IC. (semiconductor technology)

  9. Optimization of process parameters of ECM by RSM on AISI 202 steel

    Directory of Open Access Journals (Sweden)

    P. Alex John Britto

    2015-12-01

    Full Text Available The machining of complex shaped designs was difficult earlier, but with the advent of the newer machining processes incorporating in it electrical, chemical & mechanical processes, manufacturing has redefined itself. Especially, the Electrochemical Machining (ECM process is used to machine the hard to cut materials without producing heat and friction. Hence, in this work, the ECM process has been chosen to machine SS AISI 202 steel. This study establishes the effect of process parameters such as voltage, current and concentration of electrolyte on the responses on material removal rate (MRR. In this work, second-order quadratic models were developed for MRR, considering the electrolyte concentration, voltage and current as the machining parameters, using central composite design. The developed models were used for Response Surface Methodology (RSM optimization by desirability function approach to determine the optimum machining parameters.

  10. Optimization of processing parameters of amaranth grits before grinding into flour

    Science.gov (United States)

    Zharkova, I. M.; Safonova, Yu A.; Slepokurova, Yu I.

    2018-05-01

    There are the results of experimental studies about the influence of infrared treatment (IR processing) parameters of the amaranth grits before their grinding into flour on the composition and properties of the received product. Using the method called as regressionfactor analysis, the optimal conditions of the thermal processing to the amaranth grits were obtained: the belt speed of the conveyor – 0.049 m/s; temperature of amaranth grits in the tempering silo – 65.4 °C the thickness of the layer of amaranth grits on the belt is 3 - 5 mm and the lamp power is 69.2 kW/m2. The conducted researches confirmed that thermal effect to the amaranth grains in the IR setting allows getting flour with a smaller size of starch grains, with the increased water-holding ability, and with a changed value of its glycemic index. Mathematical processing of experimental data allowed establishing the dependence of the structural and technological characteristics of the amaranth flour on the IR processing parameters of amaranth grits. The obtained results are quite consistent with the experimental ones that proves the effectiveness of optimization based on mathematical planning of the experiment to determine the influence of heat treatment optimal parameters of the amaranth grits on the functional and technological properties of the flour received from it.

  11. Experiments for practical education in process parameter optimization for selective laser sintering to increase workpiece quality

    Science.gov (United States)

    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.

  12. An intelligent approach to optimize the EDM process parameters using utility concept and QPSO algorithm

    Directory of Open Access Journals (Sweden)

    Chinmaya P. Mohanty

    2017-04-01

    Full Text Available Although significant research has gone into the field of electrical discharge machining (EDM, analysis related to the machining efficiency of the process with different electrodes has not been adequately made. Copper and brass are frequently used as electrode materials but graphite can be used as a potential electrode material due to its high melting point temperature and good electrical conductivity. In view of this, the present work attempts to compare the machinability of copper, graphite and brass electrodes while machining Inconel 718 super alloy. Taguchi’s L27 orthogonal array has been employed to collect data for the study and analyze effect of machining parameters on performance measures. The important performance measures selected for this study are material removal rate, tool wear rate, surface roughness and radial overcut. Machining parameters considered for analysis are open circuit voltage, discharge current, pulse-on-time, duty factor, flushing pressure and electrode material. From the experimental analysis, it is observed that electrode material, discharge current and pulse-on-time are the important parameters for all the performance measures. Utility concept has been implemented to transform a multiple performance characteristics into an equivalent performance characteristic. Non-linear regression analysis is carried out to develop a model relating process parameters and overall utility index. Finally, the quantum behaved particle swarm optimization (QPSO and particle swarm optimization (PSO algorithms have been used to compare the optimal level of cutting parameters. Results demonstrate the elegance of QPSO in terms of convergence and computational effort. The optimal parametric setting obtained through both the approaches is validated by conducting confirmation experiments.

  13. A novel membrane-based process to isolate peroxidase from horseradish roots: optimization of operating parameters.

    Science.gov (United States)

    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.

  14. Multi-objective Optimization of Process Parameters in Friction Stir Welding

    DEFF Research Database (Denmark)

    Tutum, Cem Celal; Hattel, Jesper Henri

    The objective of this paper is to investigate optimum process parameters in Friction Stir Welding (FSW) to minimize residual stresses in the work piece and maximize production efficiency meanwhile satisfying process specific constraints as well. More specifically, the choices of tool rotational...... speed and traverse welding speed have been sought in order to achieve the goals mentioned above using an evolutionary multi-objective optimization (MOO) algorithm, i.e. non-dominated sorting genetic algorithm (NSGA-II), integrated with a transient, 2- dimensional sequentially coupled thermo...

  15. Optimization of pulsed TIG welding process parameters on mechanical properties of AA 5456 Aluminum alloy weldments

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, A. [Department of Mechanical Engineering, National Institute of Technology, Warangal 506 004 (India)], E-mail: adepu_kumar7@yahoo.co.in; Sundarrajan, S. [Scientist ' G' , Defence Research and Development Laboratory, Hyderabad 500 028 (India)

    2009-04-15

    The present work pertains to the improvement of mechanical properties of AA 5456 Aluminum alloy welds through pulsed tungsten inert gas (TIG) welding process. Taguchi method was employed to optimize the pulsed TIG welding process parameters of AA 5456 Aluminum alloy welds for increasing the mechanical properties. Regression models were developed. Analysis of variance was employed to check the adequacy of the developed models. The effect of planishing on mechanical properties was also studied and observed that there was improvement in mechanical properties. Microstructures of all the welds were studied and correlated with the mechanical properties.

  16. Optimization of pulsed TIG welding process parameters on mechanical properties of AA 5456 Aluminum alloy weldments

    International Nuclear Information System (INIS)

    Kumar, A.; Sundarrajan, S.

    2009-01-01

    The present work pertains to the improvement of mechanical properties of AA 5456 Aluminum alloy welds through pulsed tungsten inert gas (TIG) welding process. Taguchi method was employed to optimize the pulsed TIG welding process parameters of AA 5456 Aluminum alloy welds for increasing the mechanical properties. Regression models were developed. Analysis of variance was employed to check the adequacy of the developed models. The effect of planishing on mechanical properties was also studied and observed that there was improvement in mechanical properties. Microstructures of all the welds were studied and correlated with the mechanical properties

  17. Process Parameters Optimization of 14nm MOSFET Using 2-D Analytical Modelling

    Directory of Open Access Journals (Sweden)

    Noor Faizah Z.A.

    2016-01-01

    Full Text Available This paper presents the modeling and optimization of 14nm gate length CMOS transistor which is down-scaled from previous 32nm gate length. High-k metal gate material was used in this research utilizing Hafnium Dioxide (HfO2 as dielectric and Tungsten Silicide (WSi2 and Titanium Silicide (TiSi2 as a metal gate for NMOS and PMOS respectively. The devices are fabricated virtually using ATHENA module and characterized its performance evaluation via ATLAS module; both in Virtual Wafer Fabrication (VWF of Silvaco TCAD Tools. The devices were then optimized through a process parameters variability using L9 Taguchi Method. There were four process parameter with two noise factor of different values were used to analyze the factor effect. The results show that the optimal value for both transistors are well within ITRS 2013 prediction where VTH and IOFF are 0.236737V and 6.995705nA/um for NMOS device and 0.248635 V and 5.26nA/um for PMOS device respectively.

  18. Infrared Drying Parameter Optimization

    Science.gov (United States)

    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

  19. Multi-Response Optimization of WEDM Process Parameters Using Taguchi Based Desirability Function Analysis

    Science.gov (United States)

    Majumder, Himadri; Maity, Kalipada

    2018-03-01

    Shape memory alloy has a unique capability to return to its original shape after physical deformation by applying heat or thermo-mechanical or magnetic load. In this experimental investigation, desirability function analysis (DFA), a multi-attribute decision making was utilized to find out the optimum input parameter setting during wire electrical discharge machining (WEDM) of Ni-Ti shape memory alloy. Four critical machining parameters, namely pulse on time (TON), pulse off time (TOFF), wire feed (WF) and wire tension (WT) were taken as machining inputs for the experiments to optimize three interconnected responses like cutting speed, kerf width, and surface roughness. Input parameter combination TON = 120 μs., TOFF = 55 μs., WF = 3 m/min. and WT = 8 kg-F were found to produce the optimum results. The optimum process parameters for each desired response were also attained using Taguchi’s signal-to-noise ratio. Confirmation test has been done to validate the optimum machining parameter combination which affirmed DFA was a competent approach to select optimum input parameters for the ideal response quality for WEDM of Ni-Ti shape memory alloy.

  20. Optimization of process parameters of pulsed TIG welded maraging steel C300

    Science.gov (United States)

    Deepak, P.; Jualeash, M. J.; Jishnu, J.; Srinivasan, P.; Arivarasu, M.; Padmanaban, R.; Thirumalini, S.

    2016-09-01

    Pulsed TIG welding technology provides excellent welding performance on thin sections which helps to increase productivity, enhance weld quality, minimize weld costs, and boost operator efficiency and this has drawn the attention of the welding society. Maraging C300 steel is extensively used in defence and aerospace industry and thus its welding becomes an area of paramount importance. In pulsed TIG welding, weld quality depends on the process parameters used. In this work, Pulsed TIG bead-on-plate welding is performed on a 5mm thick maraging C300 plate at different combinations of input parameters: peak current (Ip), base current (Ib) and pulsing frequency (HZ) as per box behnken design with three-levels for each factor. Response surface methodology is utilized for establishing a mathematical model for predicting the weld bead depth. The effect of Ip, Ib and HZ on the weld bead depth is investigated using the developed model. The weld bead depth is found to be affected by all the three parameters. Surface and contour plots developed from regression equation are used to optimize the processing parameters for maximizing the weld bead depth. Optimum values of Ip, Ib and HZ are obtained as 259 A, 120 A and 8 Hz respectively. Using this optimum condition, maximum bead depth of the weld is predicted to be 4.325 mm.

  1. Application study of evolutionary operation methods in optimization of process parameters for mosquito coils industry

    Science.gov (United States)

    Ginting, E.; Tambunanand, M. M.; Syahputri, K.

    2018-02-01

    Evolutionary Operation Methods (EVOP) is a method that is designed used in the process of running or operating routinely in the company to enables high productivity. Quality is one of the critical factors for a company to win the competition. Because of these conditions, the research for products quality has been done by gathering the production data of the company and make a direct observation to the factory floor especially the drying department to identify the problem which is the high water content in the mosquito incense coil. PT.X which is producing mosquito coils attempted to reduce product defects caused by the inaccuracy of operating conditions. One of the parameters of good quality insect repellent that is water content, that if the moisture content is too high then the product easy to mold and broken, and vice versa if it is too low the products are easily broken and burn shorter hours. Three factors that affect the value of the optimal water content, the stirring time, drying temperature and drying time. To obtain the required conditions Evolutionary Operation (EVOP) methods is used. Evolutionary Operation (EVOP) is used as an efficient technique for optimization of two or three variable experimental parameters using two-level factorial designs with center point. Optimal operating conditions in the experiment are stirring time performed for 20 minutes, drying temperature at 65°C, and drying time for 130 minutes. The results of the analysis based on the method of Evolutionary Operation (EVOP) value is the optimum water content of 6.90%, which indicates the value has approached the optimal in a production plant that is 7%.

  2. Optimal process parameters for phosphorus spin-on-doping of germanium

    Energy Technology Data Exchange (ETDEWEB)

    Boldrini, Virginia [Dipartimento di Fisica e Astronomia, Università degli Studi di Padova, Via Marzolo 8, I-35131 Padova (Italy); INFN-LNL, Viale dell’Università 2, I-35020 Legnaro, Padova (Italy); Carturan, Sara Maria, E-mail: sara.carturan@lnl.infn.it [Dipartimento di Fisica e Astronomia, Università degli Studi di Padova, Via Marzolo 8, I-35131 Padova (Italy); INFN-LNL, Viale dell’Università 2, I-35020 Legnaro, Padova (Italy); Maggioni, Gianluigi; Napolitani, Enrico [Dipartimento di Fisica e Astronomia, Università degli Studi di Padova, Via Marzolo 8, I-35131 Padova (Italy); INFN-LNL, Viale dell’Università 2, I-35020 Legnaro, Padova (Italy); Napoli, Daniel Ricardo [INFN-LNL, Viale dell’Università 2, I-35020 Legnaro, Padova (Italy); Camattari, Riccardo [INFN Sezione di Ferrara, Dipartimento di Fisica, Università di Ferrara, Via Saragat 1, 44122, Ferrara (Italy); De Salvador, Davide [Dipartimento di Fisica e Astronomia, Università degli Studi di Padova, Via Marzolo 8, I-35131 Padova (Italy); INFN-LNL, Viale dell’Università 2, I-35020 Legnaro, Padova (Italy)

    2017-01-15

    Highlights: • Optimized protocol for the application of phosphorus spin-on-doping to Ge surface. • Homogeneous n-type Ge layers, fully electrically active, are obtained. • Crucial parameters for SOD curing are relative humidity, time and temperature. • Characterization of Ge loss from the surface into the SOD film by diffusion. • Spike annealing in standard tube chamber furnace are performed. - Abstract: The fabrication of homogeneously doped germanium layers characterized by total electrical activation is currently a hot topic in many fields, such as microelectronics, photovoltaics, optics and radiation detectors. Phosphorus spin-on-doping technique has been implemented on Ge wafers, by developing a protocol for the curing process and subsequent diffusion annealing for optimal doping. Parameters such as relative humidity and curing time turned out to affect the surface morphology, the degree of reticulation reached by the dopant source and the amount of dopant available for diffusion. After spike annealing in a conventional furnace, diffusion profiles and electrical properties have been measured. Ge loss from the surface during high-temperature annealing, due to diffusion into the source film, has been observed and quantified.

  3. Multi-response optimization of process parameters in friction stir welded AM20 magnesium alloy by Taguchi grey relational analysis

    Directory of Open Access Journals (Sweden)

    Prakash Kumar Sahu

    2015-03-01

    Full Text Available The purpose of this paper is to optimize the process parameter to get the better mechanical properties of friction stir welded AM20 magnesium alloy using Taguchi Grey relational analysis (GRA. The considered process parameters are welding speed, tool rotation speed, shoulder diameter and plunging depth. The experiments were carried out by using Taguchi's L18 factorial design of experiment. The processes parameters were optimized and ranked the parameters based on the GRA. The percentage influence of each process parameter on the weld quality was also quantified. A validation experimental run was conducted using optimal process condition, which was obtained from the analysis, to show the improvement in mechanical properties of the joint. This study also shows the feasibility of the GRA with Taguchi technique for improvement in welding quality of magnesium alloy.

  4. Optimization of process parameters for spark plasma sintering of nano structured SAF 2205 composite

    Directory of Open Access Journals (Sweden)

    Samuel Ranti Oke

    2018-04-01

    Full Text Available This research optimized spark plasma sintering (SPS process parameters in terms of sintering temperature, holding time and heating rate for the development of a nano-structured duplex stainless steel (SAF 2205 grade reinforced with titanium nitride (TiN. The mixed powders were sintered using an automated spark plasma sintering machine (model HHPD-25, FCT GmbH, Germany. Characterization was performed using X-ray diffraction and scanning electron microscopy. Density and hardness of the composites were investigated. The XRD result showed the formation of FeN0.068. SEM/EDS revealed the presence of nano ranged particles of TiN segregated at the grain boundaries of the duplex matrix. A decrease in hardness and densification was observed when sintering temperature and heating rate were 1200 °C and 150 °C/min respectively. The optimum properties were obtained in composites sintered at 1150 °C for 15 min and 100 °C/min. The composite grades irrespective of the process parameters exhibited similar shrinkage behavior, which is characterized by three distinctive peaks, which is an indication of good densification phenomena. Keywords: Spark plasma sintering, Duplex stainless steel (SAF 2205, Titanium nitride (TiN, Microstructure, Density, Hardness

  5. Sensitivity study and parameter optimization of OCD tool for 14nm finFET process

    Science.gov (United States)

    Zhang, Zhensheng; Chen, Huiping; Cheng, Shiqiu; Zhan, Yunkun; Huang, Kun; Shi, Yaoming; Xu, Yiping

    2016-03-01

    Optical critical dimension (OCD) measurement has been widely demonstrated as an essential metrology method for monitoring advanced IC process in the technology node of 90 nm and beyond. However, the rapidly shrunk critical dimensions of the semiconductor devices and the increasing complexity of the manufacturing process bring more challenges to OCD. The measurement precision of OCD technology highly relies on the optical hardware configuration, spectral types, and inherently interactions between the incidence of light and various materials with various topological structures, therefore sensitivity analysis and parameter optimization are very critical in the OCD applications. This paper presents a method for seeking the optimum sensitive measurement configuration to enhance the metrology precision and reduce the noise impact to the greatest extent. In this work, the sensitivity of different types of spectra with a series of hardware configurations of incidence angles and azimuth angles were investigated. The optimum hardware measurement configuration and spectrum parameter can be identified. The FinFET structures in the technology node of 14 nm were constructed to validate the algorithm. This method provides guidance to estimate the measurement precision before measuring actual device features and will be beneficial for OCD hardware configuration.

  6. Optimization of Pre-Treatment Process Parameters to Generate Biodiesel from Microalga

    Directory of Open Access Journals (Sweden)

    Chukwuma Onumaegbu

    2018-03-01

    Full Text Available Cell disruption is an integral part of microalga production process, which improves the release of intracellular products that are essential for biofuel production. In this work, pre-treatment parameters that will enhance the efficiency of lipid production using high-pressure homogenizer on microalgae biomass will be investigated. The high-pressure homogenizer that is considered is a GYB40-10S/GY60-6S; with a pre-treatment pressure of 1000 psi, 2000 psi, and 3000 psi, the number of passes; 1, 2, and 3, a reaction time of 3, 3.5, and 4 h. Pressure and cavitation increase the efficiency of the pre-treatment process of the homogenizer. In addition, homogenization shear force and pressure are the basic significant factors that enhance the efficiency of microalgae cell rupture. Also, the use of modelling to simulate pre-treatment processes (Response Surface Methodology (RSM, Box-Behnken Designs (BBD, and design of experiment (DOE for process optimization will be adopted in this study. The results clearly demonstrate that high-pressure homogenization pre-treatment can effectively disrupt microalga cell walls to enhance lipid recovery efficiency, with a relatively short extraction time, both that are essential for maintaining a good quality of lipids for biofuel production. A maximum of 18% lipid yields were obtained after 3 h of HPH pre-treatment at 3000 psi.

  7. Meltlets(®) of soy isoflavones: process optimization and the effect of extrusion spheronization process parameters on antioxidant activity.

    Science.gov (United States)

    Deshmukh, Ketkee; Amin, Purnima

    2013-07-01

    In the current research work an attempt was made to develop "Melt in mouth pellets" (Meltlets(®)) containing 40% herbal extract of soy isoflavones that served to provide antioxidants activity in menopausal women. The process of extrusion-spheronization was optimized for extruder speed, extruder screen size, spheronization speed, and time. While doing so the herbal extract incorporated in the pellet matrix was subjected to various processing conditions such as the effect of the presence of other excipients, mixing or kneading to prepare wet mass, heat generated during the process of extrusion, spheronization, and drying. Thus, the work further investigates the effect of these processing parameters on the antioxidant activity of the soy isoflavone herbal extract incorporated in the formula. Thereby, the antioxidant activity of the soya bean herbal extract, Meltlets(®) and of the placebo pellets was evaluated using DPPH free radical scavenging assay and total reduction capacity.

  8. Parameter optimization of electrolytic process of obtaining sodium hypochlorite for disinfection of water

    Science.gov (United States)

    Bogoslovskii, S. Yu; Kuznetsov, N. N.; Boldyrev, V. S.

    2017-11-01

    Electrochlorination parameters were optimized in flowing and non-flowing modes for a cell with a volume of 1 l. At a current density of 0.1 A/cm2 in the range of flow rates from 0.8 to 6.0 l/h with a temperature of the initial solution below 20°C the outlet temperature is maintained close to the optimal 40°C. The pH of the solution during electrolysis increases to 8.8 ÷ 9.4. There was studied a process in which a solution with a temperature of 7-8°C and a concentration of sodium chloride of 25 and 35 g/l in non-flowing cell was used. The dependence of the concentration of active chlorine on the electrolysis time varies with the concentration of the initial solution of sodium chloride. In case of chloride concentration of 25 g/l virtually linear relationship makes it easy to choose the time of electrolysis with the aim of obtaining the needed concentration of the product.

  9. OPTIMIZATION OF PROCESS PARAMETERS FOR ENHANCED MECHANICAL PROPERTIES OF POLYPROPYLENE TERNARY NANOCOMPOSITES

    Directory of Open Access Journals (Sweden)

    Oladipupo Olaosebikan Ogunleye

    2015-02-01

    Full Text Available Preparation of Polypropylene ternary nanocomposites (PPTN was accomplished by blending multiwall carbon nanotube (MWCNT in polypropylene/clay binary system using a melt intercalation method. The effects of MWCNT loadings (A, melting temperature (B and mixing speed (C were investigated and optimized using central composite design. The analysis of the fitted cubic model clearly indicated that A and B were the main factors influencing the tensile properties at a fixed value of C. However, the analysis of variance showed that the interactions between the process parameters, such as; AB, AC, AB2, A2B and ABC, were highly significant on both tensile strength and Young’s modulus enhancement, while no interaction is significant in all models considered for elongation. The established optimal conditions gave 0.17%, 165 °C, and 120 rpm for A, B and C, respectively. These conditions yielded a percentage increase of 57 and 63% for tensile strength and Young’s modulus respectively compared to the virgin Polypropylene used.

  10. Grey fuzzy logic approach for the optimization of DLC thin film coating process parameters using PACVD technique

    Science.gov (United States)

    Ghadai, R. K.; Das, P. P.; Shivakoti, I.; Mondal, S. C.; Swain, B. P.

    2017-07-01

    Diamond-like carbon (DLC) coatings are widely used in medical, manufacturing and aerospace industries due to their excellent mechanical, biological, optical and tribological properties. The selection of optimal process parameters for efficient characteristics of DLC film is always a challenging issue for the materials science researchers. The optimal combination of the process parameters involved in the deposition of DLC films provide a better result, which subsequently help other researchers to choose the process parameters. In the present work Grey Relation Analysis (GRA) and Fuzzy-logic are being used for the optimization of process parameters in DLC film coating by using plasma assist chemical vapour deposition (PACVD) technique. The bias voltage, bias frequency, deposition pressure, gas composition are considered as input process parameters and hardness (GPa), Young's modulus (GPa), ratio between diamond to graphic fraction, (Id/Ig) ratio are considered as response parameters. The input parameters are optimized by grey fuzzy analysis. The contribution of individual input parameter is done by ANOVA. In this analysis found that bias voltage having the least influence and gas composition has highest influence in the PACVD deposited DLC films. The grey fuzzy analysis results indicated that optimum results for bias voltage, bias frequency, deposition pressure, gas composition for the DLC thin films are -50 V, 6 kHz, 4 μbar and 60:40 % respectively.

  11. Application of dragonfly algorithm for optimal performance analysis of process parameters in turn-mill operations- A case study

    Science.gov (United States)

    Vikram, K. Arun; Ratnam, Ch; Lakshmi, VVK; Kumar, A. Sunny; Ramakanth, RT

    2018-02-01

    Meta-heuristic multi-response optimization methods are widely in use to solve multi-objective problems to obtain Pareto optimal solutions during optimization. This work focuses on optimal multi-response evaluation of process parameters in generating responses like surface roughness (Ra), surface hardness (H) and tool vibration displacement amplitude (Vib) while performing operations like tangential and orthogonal turn-mill processes on A-axis Computer Numerical Control vertical milling center. Process parameters like tool speed, feed rate and depth of cut are considered as process parameters machined over brass material under dry condition with high speed steel end milling cutters using Taguchi design of experiments (DOE). Meta-heuristic like Dragonfly algorithm is used to optimize the multi-objectives like ‘Ra’, ‘H’ and ‘Vib’ to identify the optimal multi-response process parameters combination. Later, the results thus obtained from multi-objective dragonfly algorithm (MODA) are compared with another multi-response optimization technique Viz. Grey relational analysis (GRA).

  12. Optimization of the tape placement process parameters for carbon–PPS composites

    NARCIS (Netherlands)

    Grouve, Wouter Johannes Bernardus; Warnet, Laurent; Rietman, B.; Visser, Roy; Akkerman, Remko

    2013-01-01

    The interrelation between process parameters, material properties and interlaminar bond strength is investigated for the laser assisted tape placement process. Unidirectionally carbon reinforced poly(phenylene sulfide) (PPS) tapes were welded onto carbon woven fabric reinforced PPS laminates. The

  13. Statistical optimization of process parameters for the production of tannase by Aspergillus flavus under submerged fermentation.

    Science.gov (United States)

    Mohan, S K; Viruthagiri, T; Arunkumar, C

    2014-04-01

    Production of tannase by Aspergillus flavus (MTCC 3783) using tamarind seed powder as substrate was studied in submerged fermentation. Plackett-Burman design was applied for the screening of 12 medium nutrients. From the results, the significant nutrients were identified as tannic acid, magnesium sulfate, ferrous sulfate and ammonium sulfate. Further the optimization of process parameters was carried out using response surface methodology (RSM). RSM has been applied for designing of experiments to evaluate the interactive effects through a full 31 factorial design. The optimum conditions were tannic acid concentration, 3.22 %; fermentation period, 96 h; temperature, 35.1 °C; and pH 5.4. Higher value of the regression coefficient (R 2  = 0.9638) indicates excellent evaluation of experimental data by second-order polynomial regression model. The RSM revealed that a maximum tannase production of 139.3 U/ml was obtained at the optimum conditions.

  14. Finite element analysis and optimization of process parameters during stamp forming of composite materials

    International Nuclear Information System (INIS)

    Venkatesan, S; Kalyanasundaram, S

    2010-01-01

    In the manufacture of parts for high performance structures using composite materials, the quality and robustness of the parts is of utmost importance. The quality of the produced parts depends largely on the process parameters and manufacturing methodologies. This study presents the use of a temperature dependant orthotropic material for a coupled structural-thermal analysis of the stamp forming process. The study investigated the effects of process parameters such as pre-heat temperature, blank holder force and process time on the formability of composite materials. Temperature was found to be the dominant factor governing the formability of the composite material while higher blank holder forces were deemed to be important for achieving high quality of the parts manufactured. Finally, an optimum set of parameters was used to compare the simulations with experimental results using an optical strain measurement system.

  15. Influence of emulsifiers on the optimization of processing parameters of refining milk chocolate in the ball mill

    Directory of Open Access Journals (Sweden)

    Pajin Biljana

    2011-01-01

    Full Text Available Chocolate manufacture is a complex process which includes a large number of technology operations. One of the obligatory phases is milling, called refining, which aims at obtaining the appropriate distribution of particle size, resulting in the chocolate with optimal physical and sensory characteristics. The aim of this work was to define and optimize the process parameters for the production of milk chocolate by a non-conventional procedure, using the ball mill. The quality of chocolate mass, produced on this way, is determined by measuring the following parameters: moisture, size of the largest cocoa particle, yield flow, and Casson plastic viscosity. A special consideration of this study is the optimization of the types and amounts of emulsifiers, which are responsible for achieving the appropriate rheological and physical characteristics of the chocolate mass. The obtained parameters are compared with those which are typical for the standard procedure.

  16. Optimization and Simulation of Machining Parameters in Radial-axial Ring Rolling Process

    Directory of Open Access Journals (Sweden)

    Shuiyuan Tang

    2011-05-01

    Full Text Available Ring rolling is a complicated process, in which rolling parameters influence directly the quality of ring. It is a process method with high productivity and few waste of material, widely used in transportation industry including automotive, shipbuilding, aerospace etc. During the rolling process of large-sized parts, crinkle and hollows often appear on surface, due to inconsistence of rolling motions with the deformation of ring part. Based on radial-axial ring rolling system configuration, motions and forces in rolling process are analyzed, and a dynamic model is formulated. Error of ring's end flatness and roundness are defined as the characteristic parameters of ring quality. The relationship between core roller feed speed, drive roller speed, the upper taper roller feed speed, and quality of ring part are analyzed. The stress and strain of the part are simulated in the Finite Element Method by DEFORM software. The simulation results provide a reference for the definition of ring rolling process parameters. It is able to make the deformation of the part be consistent with the process parameters, and improve product quality considerably.

  17. Intelligent Modeling Combining Adaptive Neuro Fuzzy Inference System and Genetic Algorithm for Optimizing Welding Process Parameters

    Science.gov (United States)

    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.

  18. Process parameter optimization during EDM of AISI 316 LN stainless steel by using fuzzy based multi-objective PSO

    Energy Technology Data Exchange (ETDEWEB)

    Majumder, Arindam [National Institute of Technology Agartala, Tripura (India)

    2013-07-15

    The present contribution describes an application of a hybrid approach using fuzzy logic and particle swarm optimization (PSO) for optimizing the process parameters in the electric discharge machining (EDM) of AISI 316LN Stainless Steel. In this study, each experimentation was performed under different machining conditions of pulse current, pulse on-time, and pulse off-time. Machining performances such as MRR and EWR were evaluated. A Taguchi L9 orthogonal array was produced to plan the experimentation and the regression method was applied to model the relationship between the input factors and responses. A fuzzy model was employed to provide a fitness function to PSO by unifying the multiple responses. Finally, PSO was used to predict the optimal process parametric settings for the multi-performance optimization of the EDM operation. The experimental results confirm the feasibility of the strategy and are in good agreement with the predicted results over a wide range of machining conditions employed in the process.

  19. Experimental design approach to the process parameter optimization for laser welding of martensitic stainless steels in a constrained overlap configuration

    Science.gov (United States)

    Khan, M. M. A.; Romoli, L.; Fiaschi, M.; Dini, G.; Sarri, F.

    2011-02-01

    This paper presents an experimental design approach to process parameter optimization for the laser welding of martensitic AISI 416 and AISI 440FSe stainless steels in a constrained overlap configuration in which outer shell was 0.55 mm thick. To determine the optimal laser-welding parameters, a set of mathematical models were developed relating welding parameters to each of the weld characteristics. These were validated both statistically and experimentally. The quality criteria set for the weld to determine optimal parameters were the minimization of weld width and the maximization of weld penetration depth, resistance length and shearing force. Laser power and welding speed in the range 855-930 W and 4.50-4.65 m/min, respectively, with a fiber diameter of 300 μm were identified as the optimal set of process parameters. However, the laser power and welding speed can be reduced to 800-840 W and increased to 4.75-5.37 m/min, respectively, to obtain stronger and better welds.

  20. The study of optimization on process parameters of high-accuracy computerized numerical control polishing

    Science.gov (United States)

    Huang, Wei-Ren; Huang, Shih-Pu; Tsai, Tsung-Yueh; Lin, Yi-Jyun; Yu, Zong-Ru; Kuo, Ching-Hsiang; Hsu, Wei-Yao; Young, Hong-Tsu

    2017-09-01

    Spherical lenses lead to forming spherical aberration and reduced optical performance. Consequently, in practice optical system shall apply a combination of spherical lenses for aberration correction. Thus, the volume of the optical system increased. In modern optical systems, aspherical lenses have been widely used because of their high optical performance with less optical components. However, aspherical surfaces cannot be fabricated by traditional full aperture polishing process due to their varying curvature. Sub-aperture computer numerical control (CNC) polishing is adopted for aspherical surface fabrication in recent years. By using CNC polishing process, mid-spatial frequency (MSF) error is normally accompanied during this process. And the MSF surface texture of optics decreases the optical performance for high precision optical system, especially for short-wavelength applications. Based on a bonnet polishing CNC machine, this study focuses on the relationship between MSF surface texture and CNC polishing parameters, which include feed rate, head speed, track spacing and path direction. The power spectral density (PSD) analysis is used to judge the MSF level caused by those polishing parameters. The test results show that controlling the removal depth of single polishing path, through the feed rate, and without same direction polishing path for higher total removal depth can efficiently reduce the MSF error. To verify the optical polishing parameters, we divided a correction polishing process to several polishing runs with different direction polishing paths. Compare to one shot polishing run, multi-direction path polishing plan could produce better surface quality on the optics.

  1. A bottom-up approach for optimization of friction stir processing parameters; a study on aluminium 2024-T3 alloy

    International Nuclear Information System (INIS)

    Nadammal, Naresh; Kailas, Satish V.; Suwas, Satyam

    2015-01-01

    Highlights: • An experimental bottom-up approach has been developed for optimizing the process parameters for friction stir processing. • Optimum parameter processed samples were tested and characterized in detail. • Ultimate tensile strength of 1.3 times the base metal strength was obtained. • Residual stresses on the processed surface were only 10% of the yield strength of base metal. • Microstructure observations revealed fine equi-axed grains with precipitate particles at the grain boundaries. - Abstract: Friction stir processing (FSP) is emerging as one of the most competent severe plastic deformation (SPD) method for producing bulk ultra-fine grained materials with improved properties. Optimizing the process parameters for a defect free process is one of the challenging aspects of FSP to mark its commercial use. For the commercial aluminium alloy 2024-T3 plate of 6 mm thickness, a bottom-up approach has been attempted to optimize major independent parameters of the process such as plunge depth, tool rotation speed and traverse speed. Tensile properties of the optimum friction stir processed sample were correlated with the microstructural characterization done using Scanning Electron Microscope (SEM) and Electron Back-Scattered Diffraction (EBSD). Optimum parameters from the bottom-up approach have led to a defect free FSP having a maximum strength of 93% the base material strength. Micro tensile testing of the samples taken from the center of processed zone has shown an increased strength of 1.3 times the base material. Measured maximum longitudinal residual stress on the processed surface was only 30 MPa which was attributed to the solid state nature of FSP. Microstructural observation reveals significant grain refinement with less variation in the grain size across the thickness and a large amount of grain boundary precipitation compared to the base metal. The proposed experimental bottom-up approach can be applied as an effective method for

  2. Process parameters optimization for synthesis of methyl ester from sunflower oil using Taguchi technique

    Directory of Open Access Journals (Sweden)

    G. Senthilkumar

    2014-09-01

    Full Text Available In this work, transesterification of sunflower oil for obtaining biodiesel was studied. Taguchi’s methodology (L9 orthogonal array was selected to optimize the most significant variables (methanol, catalyst concentration and stirrer speed in transesterification process. Experiments have conducted based on development of L9 orthogonal array by using Taguchi technique. Analysis of Variance (ANOVA and the regression equations were used to find the optimum yield of sunflower methyl ester under the influence of methanol, catalyst & stirrer speed. The study resulted in a maximum yield of sun flower methyl ester as 96% with the optimal conditions of methanol 110 ml with 0.5% by wt. of sodium hydroxide (NaOH stirred at 1200 rpm. The yield was analyzed on the basis of “larger is better”. Finally, confirmation tests were carried out to verify the experimental results.

  3. Optimizing supercritical antisolvent process parameters to minimize the particle size of paracetamol nanoencapsulated in L-polylactide

    Directory of Open Access Journals (Sweden)

    Kalani M

    2011-05-01

    Full Text Available Mahshid Kalani, Robiah Yunus, Norhafizah AbdullahChemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Selangor Darul Ehsan, MalaysiaBackground: The aim of this study was to optimize the different process parameters including pressure, temperature, and polymer concentration, to produce fine small spherical particles with a narrow particle size distribution using a supercritical antisolvent method for drug encapsulation. The interaction between different process parameters was also investigated.Methods and results: The optimized process parameters resulted in production of nanoencapsulated paracetamol in L-polylactide with a mean diameter of approximately 300 nm at 120 bar, 30°C, and a polymer concentration of 16 ppm. Thermogravimetric analysis illustrated the thermal characteristics of the nanoparticles. The high electrical charge on the surface of the nanoparticles caused the particles to repel each other, with the high negative zeta potential preventing flocculation.Conclusion: Our results illustrate the effect of different process parameters on particle size and morphology, and validate results obtained via RSM statistical software. Furthermore, the in vitro drug-release profile is consistent with a Korsmeyer–Peppas kinetic model.Keywords: supercritical, antisolvent, encapsulation, nanoparticles, biodegradable polymer, optimization, drug delivery

  4. Artificial Intelligence Based Selection of Optimal Cutting Tool and Process Parameters for Effective Turning and Milling Operations

    Science.gov (United States)

    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.

  5. Optimization of process parameters during carbonization for improved carbon fibre strength

    Science.gov (United States)

    Köhler, T.; Pursche, F.; Burscheidt, P.; Seide, G.; Gries, T.

    2017-10-01

    Based on their extraordinary properties, carbon fibres nowadays play a significant role in modern industries. In the last years carbon fibres are increasingly used for lightweight constructions in the energy or the transportation industry. However, a bigger market penetration of carbon fibres is still hindered by high prices (~ 22 /kg) [3]. One crucial step in carbon fibre production is the process of carbonization of stabilized fibres. However, the cause effect relationships of carbonization are nowadays not fully understood. Therefore, the main goal of this research work is the quantification of the cause-effect relationships of process parameters like temperature and residence time on carbon fibre strength.

  6. Optimization of process parameters for WEDM of Inconel 825 using grey relational analysis

    Directory of Open Access Journals (Sweden)

    Pawan Kuma

    2018-09-01

    Full Text Available Inconel 825 is high nickel-chromium-based superalloy which retains its mechanical properties and exhibits good corrosion and oxidation resistance at elevated temperature. Inconel 825 is extensively used for making aircraft engine parts like combustor casing and turbine blades in aero space industry. This research proposed the Response Surface Methodology with GRA to optimize multiple responses during Wire-cut EDM of Inconel 825. At optimum combination of input parameters i.e. A4B1C1D5E4F2, increase in MRR from 36.13 mm2/min to 41.822 mm2/min, decrease in SR from 2.842μm to 2.445μm and decrease in WWR from 0.01832 to 0.01758 was obtained. Experimental results showed that pulse-on time, wire feed, pulse-off time, and peak current significantly affected the MRR, and surface integrity of specimen and electrode with the formation of craters, pockmarks, debris, micro cracks, and recast layer. The optimal parametric combination obtained from the present study will be advantageous for working on high strength; high thermal conductivity and low melting point materials like nickel alloys.

  7. Castor Oil: Properties, Uses, and Optimization of Processing Parameters in Commercial Production.

    Science.gov (United States)

    Patel, Vinay R; Dumancas, Gerard G; Kasi Viswanath, Lakshmi C; Maples, Randall; Subong, Bryan John J

    2016-01-01

    Castor oil, produced from castor beans, has long been considered to be of important commercial value primarily for the manufacturing of soaps, lubricants, and coatings, among others. Global castor oil production is concentrated primarily in a small geographic region of Gujarat in Western India. This region is favorable due to its labor-intensive cultivation method and subtropical climate conditions. Entrepreneurs and castor processors in the United States and South America also cultivate castor beans but are faced with the challenge of achieving high castor oil production efficiency, as well as obtaining the desired oil quality. In this manuscript, we provide a detailed analysis of novel processing methods involved in castor oil production. We discuss novel processing methods by explaining specific processing parameters involved in castor oil production.

  8. Optimization of process parameters in flash pyrolysis of waste tyres to liquid and gaseous fuel in a fluidized bed reactor

    International Nuclear Information System (INIS)

    Edwin Raj, R.; Robert Kennedy, Z.; Pillai, B.C.

    2013-01-01

    Highlights: ► Non-recyclable, hazards, under-utilized waste tyre was converted to useful fuel. ► Design of experiment was used to optimize the process parameters. ► Fuel compatibility for IC engines was tested by standard fuel testing procedures. ► Optimized process parameters were tested and the empirical model validated. - Abstract: Pyrolysis process offers solution to utilize huge quantity of worn out automobile tyres to produce fuel for energy needs. Shredded tyre wastes were subjected to pyrolysis at atmospheric pressure under inert gas atmosphere in a fluidized bed combustion setup. The shredded tyre particle size, the feed rate of the feed stock, and the pyrolysis temperature were varied systematically as per the designed experiment to study their influence on product yield. Maximizing the oil yield and subduing the gas and char yield is the objective to optimize the process parameters. A low pyrolysis temperature of 440 °C with low feed rate increases the residence time in the combustion reactor yielding maximum oil. The physical properties of raw pyrolysis oil, distilled oil and the evolved gases were done to find its suitability to utilize them as alternatives to the conventional fuels

  9. Multi-Objective Optimization of Friction Stir Welding Process Parameters of AA6061-T6 and AA7075-T6 Using a Biogeography Based Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Mehran Tamjidy

    2017-05-01

    Full Text Available The development of Friction Stir Welding (FSW has provided an alternative approach for producing high-quality welds, in a fast and reliable manner. This study focuses on the mechanical properties of the dissimilar friction stir welding of AA6061-T6 and AA7075-T6 aluminum alloys. The FSW process parameters such as tool rotational speed, tool traverse speed, tilt angle, and tool offset influence the mechanical properties of the friction stir welded joints significantly. A mathematical regression model is developed to determine the empirical relationship between the FSW process parameters and mechanical properties, and the results are validated. In order to obtain the optimal values of process parameters that simultaneously optimize the ultimate tensile strength, elongation, and minimum hardness in the heat affected zone (HAZ, a metaheuristic, multi objective algorithm based on biogeography based optimization is proposed. The Pareto optimal frontiers for triple and dual objective functions are obtained and the best optimal solution is selected through using two different decision making techniques, technique for order of preference by similarity to ideal solution (TOPSIS and Shannon’s entropy.

  10. Multi-Objective Optimization of Friction Stir Welding Process Parameters of AA6061-T6 and AA7075-T6 Using a Biogeography Based Optimization Algorithm.

    Science.gov (United States)

    Tamjidy, Mehran; Baharudin, B T Hang Tuah; Paslar, Shahla; Matori, Khamirul Amin; Sulaiman, Shamsuddin; Fadaeifard, Firouz

    2017-05-15

    The development of Friction Stir Welding (FSW) has provided an alternative approach for producing high-quality welds, in a fast and reliable manner. This study focuses on the mechanical properties of the dissimilar friction stir welding of AA6061-T6 and AA7075-T6 aluminum alloys. The FSW process parameters such as tool rotational speed, tool traverse speed, tilt angle, and tool offset influence the mechanical properties of the friction stir welded joints significantly. A mathematical regression model is developed to determine the empirical relationship between the FSW process parameters and mechanical properties, and the results are validated. In order to obtain the optimal values of process parameters that simultaneously optimize the ultimate tensile strength, elongation, and minimum hardness in the heat affected zone (HAZ), a metaheuristic, multi objective algorithm based on biogeography based optimization is proposed. The Pareto optimal frontiers for triple and dual objective functions are obtained and the best optimal solution is selected through using two different decision making techniques, technique for order of preference by similarity to ideal solution (TOPSIS) and Shannon's entropy.

  11. Parameters Determination of Yoshida Uemori Model Through Optimization Process of Cyclic Tension-Compression Test and V-Bending Springback

    Directory of Open Access Journals (Sweden)

    Serkan Toros

    Full Text Available Abstract In recent years, the studies on the enhancement of the prediction capability of the sheet metal forming simulations have increased remarkably. Among the used models in the finite element simulations, the yield criteria and hardening models have a great importance for the prediction of the formability and springback. The required model parameters are determined by using the several test results, i.e. tensile, compression, biaxial stretching tests (bulge test and cyclic tests (tension-compression. In this study, the Yoshida-Uemori (combined isotropic and kinematic hardening model is used to determine the performance of the springback prediction. The model parameters are determined by the optimization processes of the cyclic test by finite element simulations. However, in the study besides the cyclic tests, the model parameters are also evaluated by the optimization process of both cyclic and V-die bending simulations. The springback angle predictions with the model parameters obtained by the optimization of both cyclic and V-die bending simulations are found to mimic the experimental results in a better way than those obtained from only cyclic tests. However, the cyclic simulation results are found to be close enough to the experimental results.

  12. Optimization of Process Parameters of Pulsed Electro Deposition Technique for Nanocrystalline Nickel Coating Using Gray Relational Analysis (GRA)

    Science.gov (United States)

    Venkatesh, C.; Sundara Moorthy, N.; Venkatesan, R.; Aswinprasad, V.

    The moving parts of any mechanism and machine parts are always subjected to a significant wear due to the development of friction. It is an utmost important aspect to address the wear problems in present environment. But the complexity goes on increasing to replace the worn out parts if they are very precise. Technology advancement in surface engineering ensures the minimum surface wear with the introduction of polycrystalline nano nickel coating. The enhanced tribological property of the nano nickel coating was achieved by the development of grain size and hardness of the surface. In this study, it has been decided to focus on the optimized parameters of the pulsed electro deposition to develop such a coating. Taguchi’s method coupled gray relational analysis was employed by considering the pulse frequency, average current density and duty cycle as the chief process parameters. The grain size and hardness were considered as responses. Totally, nine experiments were conducted as per L9 design of experiment. Additionally, response graph method has been applied to determine the most significant parameter to influence both the responses. In order to improve the degree of validation, confirmation test and predicted gray grade were carried out with the optimized parameters. It has been observed that there was significant improvement in gray grade for the optimal parameters.

  13. Multi response optimization of wire-EDM process parameters of ballistic grade aluminium alloy

    Directory of Open Access Journals (Sweden)

    Ravindranadh Bobbili

    2015-12-01

    Full Text Available In the current investigation, a multi response optimization technique based on Taguchi method coupled with Grey relational analysis is planned for wire-EDM operations on ballistic grade aluminium alloy for armour applications. Experiments have been performed with four machining variables: pulse-on time, pulse-off time, peak current and spark voltage. Experimentation has been planned as per Taguchi technique. Three performance characteristics namely material removal rate (MRR, surface roughness (SR and gap current (GC have been chosen for this study. Results showed that pulse-on time, peak current and spark voltage were significant variables to Grey relational grade. Variation of performance measures with process variables was modelled by using response surface method. The confirmation tests have also been performed to validate the results obtained by Grey relational analysis and found that great improvement with 6% error is achieved.

  14. Optimization of HTST process parameters for production of ready-to-eat potato-soy snack.

    Science.gov (United States)

    Nath, A; Chattopadhyay, P K; Majumdar, G C

    2012-08-01

    Ready-to-eat (RTE) potato-soy snacks were developed using high temperature short time (HTST) air puffing process and the process was found to be very useful for production of highly porous and light texture snack. The process parameters considered viz. puffing temperature (185-255 °C) and puffing time (20-60 s) with constant initial moisture content of 36.74% and air velocity of 3.99 m.s(-1) for potato-soy blend with varying soy flour content from 5% to 25% were investigated using response surface methodology following central composite rotatable design (CCRD). The optimum product in terms of minimum moisture content (11.03% db), maximum expansion ratio (3.71), minimum hardness (2,749.4 g), minimum ascorbic acid loss (9.24% db) and maximum overall acceptability (7.35) were obtained with 10.0% soy flour blend in potato flour at the process conditions of puffing temperature (231.0 °C) and puffing time (25.0 s).

  15. Modelling and multi objective optimization of LM13 aluminium alloy squeeze cast process parameters using taguchi and genetic algorithm

    Directory of Open Access Journals (Sweden)

    S. Vellingiri

    2018-01-01

    Full Text Available This present investigation deals with squeeze casting process in order to produce a component with good mechanical properties such as micro-hardness(VH, tensile strength(Rm, and density(ρ on LM13 by varying squeeze pressure(P, molten temperature(Tm and die temperature(Td. Taguchi experimental design L9 orthogonal array was used to determine the signal to noise ratio. The results specified that the squeeze pressure and die preheat temperature are the most influencing parameters for mechanical properties improvement. Genetic algorithm (GA has been applied to optimize the casting parameters that simultaneously maximize the responses.

  16. Optimization of Surface Roughness Parameters of Al-6351 Alloy in EDC Process: A Taguchi Coupled Fuzzy Logic Approach

    Science.gov (United States)

    Kar, Siddhartha; Chakraborty, Sujoy; Dey, Vidyut; Ghosh, Subrata Kumar

    2017-10-01

    This paper investigates the application of Taguchi method with fuzzy logic for multi objective optimization of roughness parameters in electro discharge coating process of Al-6351 alloy with powder metallurgical compacted SiC/Cu tool. A Taguchi L16 orthogonal array was employed to investigate the roughness parameters by varying tool parameters like composition and compaction load and electro discharge machining parameters like pulse-on time and peak current. Crucial roughness parameters like Centre line average roughness, Average maximum height of the profile and Mean spacing of local peaks of the profile were measured on the coated specimen. The signal to noise ratios were fuzzified to optimize the roughness parameters through a single comprehensive output measure (COM). Best COM obtained with lower values of compaction load, pulse-on time and current and 30:70 (SiC:Cu) composition of tool. Analysis of variance is carried out and a significant COM model is observed with peak current yielding highest contribution followed by pulse-on time, compaction load and composition. The deposited layer is characterised by X-Ray Diffraction analysis which confirmed the presence of tool materials on the work piece surface.

  17. Optimizing the equal channel angular pressing process (ECAP) operation parameters to produce bulk nanostructure materials

    International Nuclear Information System (INIS)

    Abushgair, K.

    2015-01-01

    In this work we were interested in doing simulation using finite elements analysis (FEA) to study the equal channel angular pressing process (ECAP), which is currently one of the most popular methods of severe plastic deformation Processes (SPD). for fabricating Ultra-Fine Grained (UFG) materials, because it allows very high strains to be imposed leading to extreme work hardening and microstructural refinement. The main object of this study is to establish the influence of main parameters which effect ECAP process which are magnitude of the die angle and the friction coefficient. The angle studied between (90-135°) degree, and magnitude of the friction coefficient μ between (0.12-0.6), and number of pass. The samples were made from aluminum alloy at room temperature with (15X 15) mm cross section and 150 mm length. The simulation result shows that normal elastic strain, shears elastic strain, and max. shear elastic strain increased, when changing the angle from 90° to 100°. and decrease between the angle 110° to 135°. Also the total deformation increased when we change die angle from 90° to 135°. By studding the friction effect on the die and sample we noted that increasing the friction coefficient from 0.12 to 0.6, normal elastic strain, and shear elastic strain increased and increasing the friction coefficient from 0.1 to 0.6 decrease the normal and shear stress

  18. Process Parameters Optimization for Friction Stir Welding of Pure Aluminium to Brass (CuZn30 using Taguchi Technique

    Directory of Open Access Journals (Sweden)

    Elfar O. M. R.

    2016-01-01

    Full Text Available In this research, the friction stir welding of dissimilar commercial pure aluminium and brass (CuZn30 plates was investigated and the process parameters were optimized using Taguchi L9 orthogonal array. The considered process parameters were the rotational speed, traverse speed and pin offset. The optimum setting was determined with reference to ultimate tensile strength of the joint. The predicted optimum value of ultimate tensile strength was confirmed by experimental run using optimum parameters. Analysis of variance revealed that traverse speed is the most significant factor in controlling the joint tensile strength and pin offset also plays a significant role. In this investigation, the optimum tensile strength is 50% of aluminium base metal. Metallographic examination revealed that intermetallic compounds were formed in the interface of the optimum joint where the tensile failure was observed to take place.

  19. Multi-response optimization of process parameters for TIG welding of Incoloy 800HT by Taguchi grey relational analysis

    Directory of Open Access Journals (Sweden)

    Arun Kumar Srirangan

    2016-06-01

    Full Text Available Incoloy 800HT which was selected as one of the prominent material for fourth generation power plant can exhibit appreciable strength, good resistance to corrosion and oxidation in high temperature environment. This study focuses on the multi-objective optimization using grey relational analysis for Incoloy 800HT welded with tungsten inert arc welding process with N82 filler wire of diameter 1.2 mm. The welding input parameters play a vital role in determining desired weld quality. The experiments were conducted according to L9 orthogonal array. The input parameter chosen were the welding current, Voltage and welding speed. The output response for quality targets chosen were the ultimate tensile strength and yield strength (at room temperature, 750 °C and impact toughness. Grey relational analysis was applied to optimize the input parameters simultaneously considering multiple output variables. The optimal parameters combination was determined as A2B1C2 i.e. welding current at 110 A, voltage at 10 V and welding speed at 1.5 mm/s. ANOVA method was used to assess the significance of factors on the overall quality of the weldment. The output of the mechanical properties for best and least grey relational grade was validated by the metallurgical characteristics:

  20. Tablet coating by injection molding technology - Optimization of coating formulation attributes and coating process parameters.

    Science.gov (United States)

    Desai, Parind M; Puri, Vibha; Brancazio, David; Halkude, Bhakti S; Hartman, Jeremy E; Wahane, Aniket V; Martinez, Alexander R; Jensen, Keith D; Harinath, Eranda; Braatz, Richard D; Chun, Jung-Hoon; Trout, Bernhardt L

    2018-01-01

    We developed and evaluated a solvent-free injection molding (IM) coating technology that could be suitable for continuous manufacturing via incorporation with IM tableting. Coating formulations (coating polymers and plasticizers) were prepared using hot-melt extrusion and screened via stress-strain analysis employing a universal testing machine. Selected coating formulations were studied for their melt flow characteristics. Tablets were coated using a vertical injection molding unit. Process parameters like softening temperature, injection pressure, and cooling temperature played a very important role in IM coating processing. IM coating employing polyethylene oxide (PEO) based formulations required sufficient room humidity (>30% RH) to avoid immediate cracks, whereas other formulations were insensitive to the room humidity. Tested formulations based on Eudrajit E PO and Kollicoat IR had unsuitable mechanical properties. Three coating formulations based on hydroxypropyl pea starch, PEO 1,000,000 and Opadry had favorable mechanical (35% elongation, >95×10 4 J/m 3 toughness) and melt flow (>0.4g/min) characteristics, that rendered acceptable IM coats. These three formulations increased the dissolution time by 10, 15 and 35min, respectively (75% drug release), compared to the uncoated tablets (15min). Coated tablets stored in several environmental conditions remained stable to cracking for the evaluated 8-week time period. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Process Parameter Optimization of Extrusion-Based 3D Metal Printing Utilizing PW–LDPE–SA Binder System

    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.

  2. Process Parameter Optimization of Extrusion-Based 3D Metal Printing Utilizing PW–LDPE–SA Binder System

    Science.gov (United States)

    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

  3. Process Parameter Optimization of Extrusion-Based 3D Metal Printing Utilizing PW-LDPE-SA Binder System.

    Science.gov (United States)

    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.

  4. Optimization of Process Parameters During End Milling and Prediction of Work Piece Temperature Rise

    Directory of Open Access Journals (Sweden)

    Bhirud N.L.

    2017-09-01

    Full Text Available During the machining processes, heat gets generated as a result of plastic deformation of metal and friction along the tool–chip and tool–work piece interface. In materials having high thermal conductivity, like aluminium alloys, large amount of this heat is absorbed by the work piece. This results in the rise in the temperature of the work piece, which may lead to dimensional inaccuracies, surface damage and deformation. So, it is needed to control rise in the temperature of the work piece. This paper focuses on the measurement, analysis and prediction of work piece temperature rise during the dry end milling operation of Al 6063. The control factors used for experimentation were number of flutes, spindle speed, depth of cut and feed rate. The Taguchi method was employed for the planning of experimentation and L18 orthogonal array was selected. The temperature rise of the work piece was measured with the help of K-type thermocouple embedded in the work piece. Signal to noise (S/N ratio analysis was carried out using the lower-the-better quality characteristics. Depth of cut was identified as the most significant factor affecting the work piece temperature rise, followed by spindle speed. Analysis of variance (ANOVA was employed to find out the significant parameters affecting the work piece temperature rise. ANOVA results were found to be in line with the S/N ratio analysis. Regression analysis was used for developing empirical equation of temperature rise. The temperature rise of the work piece was calculated using the regression equation and was found to be in good agreement with the measured values. Finally, confirmation tests were carried out to verify the results obtained. From the confirmation test it was found that the Taguchi method is an effective method to determine optimised parameters for minimization of work piece temperature.

  5. Multi-objective optimization of swash plate forging process parameters for the die wear/service life improvement

    Science.gov (United States)

    Hu, X. F.; Wang, L. G.; Wu, H.; Liu, S. S.

    2017-12-01

    For the forging process of the swash plate, the author designed a kind of multi-index orthogonal experiment. Based on the Archard wear model, the influences of billet temperature, die temperature, forming speed, top die hardness and friction coefficient on forming load and die wear were numerically simulated by DEFORM software. Through the analysis of experimental results, the best forging process parameters were optimized and determined, which could effectively reduce the die wear and prolong the die service life. It is significant to increase the practical production of enterprise, especially to reduce the production cost and to promote enterprise profit.

  6. 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.

  7. Estimation of fundamental kinetic parameters of polyhydroxybutyrate fermentation process of Azohydromonas australica using statistical approach of media optimization.

    Science.gov (United States)

    Gahlawat, Geeta; Srivastava, Ashok K

    2012-11-01

    Polyhydroxybutyrate or PHB is a biodegradable and biocompatible thermoplastic with many interesting applications in medicine, food packaging, and tissue engineering materials. The present study deals with the enhanced production of PHB by Azohydromonas australica using sucrose and the estimation of fundamental kinetic parameters of PHB fermentation process. The preliminary culture growth inhibition studies were followed by statistical optimization of medium recipe using response surface methodology to increase the PHB production. Later on batch cultivation in a 7-L bioreactor was attempted using optimum concentration of medium components (process variables) obtained from statistical design to identify the batch growth and product kinetics parameters of PHB fermentation. A. australica exhibited a maximum biomass and PHB concentration of 8.71 and 6.24 g/L, respectively in bioreactor with an overall PHB production rate of 0.75 g/h. Bioreactor cultivation studies demonstrated that the specific biomass and PHB yield on sucrose was 0.37 and 0.29 g/g, respectively. The kinetic parameters obtained in the present investigation would be used in the development of a batch kinetic mathematical model for PHB production which will serve as launching pad for further process optimization studies, e.g., design of several bioreactor cultivation strategies to further enhance the biopolymer production.

  8. Alanine-EPR dosimetry in 10 MeV electron beam to optimize process parameters for food irradiation

    International Nuclear Information System (INIS)

    Sanyal, B.; Kumar, S.; Kumar, M.; Mittal, K.C.; Sharma, A.

    2011-01-01

    Absorbed dose in a food product is determined and controlled by several components of the LINAC irradiation facility as well as the product. Standardization of the parameters characterizing the facility components, process load and the irradiation conditions collectively termed as 'process parameters' are of paramount importance for successful dose delivery to the food products. In the present study alanine-EPR dosimetry system was employed to optimize the process parameters of 10 MeV electron beam of a LINAC facility for commercial irradiation of food. Three sets of experiments were carried out with different food commodities namely, mango, potato and rawa with the available product conveying system of different irradiation geometry like one sided or both sided mode of irradiation. Three dimensional dose distributions into the process load for low dose requiring food commodities (0.25 to 1 kGy) were measured in each experiment. The actual depth dose profile in food product and useful scan width of the electron beam were found out to be satisfactory for commercial radiation processing of food. Finally a scaled up experiment with commercial food product (packets of Rawa) exhibited adequate dose uniformity ratio of 3 proving the feasibility of the facility for large scale radiation processing of food commodities. (author)

  9. A Comparative Analysis of Taguchi Methodology and Shainin System DoE in the Optimization of Injection Molding Process Parameters

    Science.gov (United States)

    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.

  10. Optimization of process parameters for microwave pyrolysis of oil palm fiber (OPF) for hydrogen and biochar production

    International Nuclear Information System (INIS)

    Arafat Hossain, Md; Ganesan, P.; Jewaratnam, J.; Chinna, K.

    2017-01-01

    Highlights: • Microwave pyrolysis process parameters are optimized by response surface methodology. • Experimental values are well in agreement with the predicted values from model. • Correction coefficients (R 2 ) which had been found near to the 1, satisfied the model. • Errors are less than 10% between the optimized conditions and experimental values. • Higher carbon (%) and porosity have been found in the biochar. - Abstract: Response surface methodology (RSM) based on central composite design (CCD) is used to investigate the optimized experimental conditions for maximum H 2 and biochar yields from microwave pyrolysis of OPF. Input parameters (temperature, microwave power and N 2 flow rate) have been coded which suggest a complete summary of experimental design with a set of experiment for the two responses of H 2 and biochar. Quadratic model has been found fit for the optimization. This method significantly reduces the number of the experiments (Full factorial experiments). Actual vs. predicted plots clearly imply that experimental values are well in agreement with the predicted values for both H 2 and biochar yield. The perturbation plots indicate that H 2 and biochar yields are more sensitive for N 2 flow rate and temperature respectively. The software suggested three optimized experimental conditions for maximum H 2 yield, maximum biochar yield and for both maximum H 2 and biochar yields together. The software results were further validated by conducting relevant experiments. The error was less than 10%, suggesting that the software predictions are quite reliable. Proximate and ultimate analysis of the optimized biochars have showed a big percentage of carbon contents (More than 60 wt.%) and high heating value. SEM and BET analysis show some pores in the biochars which are effective for soil improvements.

  11. Process parameters optimization of needle-punched nonwovens for sound absorption application

    CSIR Research Space (South Africa)

    Mvubu, M

    2015-12-01

    Full Text Available , and stroke frequency on sound absorption properties were studied. These parameters were varied at three levels during experimental trials. From multiple regression analysis, it was observed that the depth of needle penetration alone was the most dominant...

  12. Metal oxide nanostructures-containing organic polymer hybrid solarcells: Optimization of processing parameters on cell performance

    CSIR Research Space (South Africa)

    Motaung, DE

    2015-07-01

    Full Text Available We report the chemical synthesis of various ZnO nanostructures and TiO2 nanoparticles and their dispersion in a P3HT matrix. The photoluminescence studies revealed improved charge transport in the active layer of the optimized TiO2 nanoparticles...

  13. Optimization of Process Parameters During Drilling of Glass-Fiber Polyester Reinforced Composites Using DOE and ANOVA

    Directory of Open Access Journals (Sweden)

    N.S. Mohan

    2010-09-01

    Full Text Available Polymer-based composite material possesses superior properties such as high strength-to-weight ratio, stiffness-to-weight ratio and good corrosive resistance and therefore, is attractive for high performance applications such as in aerospace, defense and sport goods industries. Drilling is one of the indispensable methods for building products with composite panels. Surface quality and dimensional accuracy play an important role in the performance of a machined component. In machining processes, however, the quality of the component is greatly influenced by the cutting conditions, tool geometry, tool material, machining process, chip formation, work piece material, tool wear and vibration during cutting. Drilling tests were conducted on glass fiber reinforced plastic composite [GFRP] laminates using an instrumented CNC milling center. A series of experiments are conducted using TRIAC VMC CNC machining center to correlate the cutting parameters and material parameters on the cutting thrust, torque and surface roughness. The measured results were collected and analyzed with the help of the commercial software packages MINITAB14 and Taly Profile. The surface roughness of the drilled holes was measured using Rank Taylor Hobson Surtronic 3+ instrument. The method could be useful in predicting thrust, torque and surface roughness parameters as a function of process variables. The main objective is to optimize the process parameters to achieve low cutting thrust, torque and good surface roughness. From the analysis it is evident that among all the significant parameters, speed and drill size have significant influence cutting thrust and drill size and specimen thickness on the torque and surface roughness. It was also found that feed rate does not have significant influence on the characteristic output of the drilling process.

  14. Optimization of laser welding process parameters for super austenitic stainless steel using artificial neural networks and genetic algorithm

    International Nuclear Information System (INIS)

    Sathiya, P.; Panneerselvam, K.; Abdul Jaleel, M.Y.

    2012-01-01

    Highlights: ► Super austenitic stainless steel has successfully welded by laser welding with three different shielding gases. ► Among the three shielded joints, the helium shielded weld has more tensile strength. ► Neural network model was developed to predict the depth of penetration, bead width and tensile strength of the joints. ► The developed ANN model is suitably integrated with GA for optimization. -- Abstract: The laser welding input parameters play a very significant role in determining the quality of a weld joint. The quality of the joint can be defined in terms of properties such as weld bead geometry, mechanical properties and distortion. In particular mechanical properties should be controlled to obtain good welded joints. In this study, the weld bead geometry such as depth of penetration (DP), bead width (BW) and tensile strength (TS) of the laser welded butt joints made of AISI 904L super austenitic stainless steel are investigated. Full factorial design is used to carry out the experimental design. Artificial neural networks (ANNs) program was developed in MatLab software to establish the relationship between the laser welding input parameters like beam power, travel speed and focal position and the three responses DP, BW and TS in three different shielding gases (argon, helium and nitrogen). The established models are used for optimizing the process parameters using genetic algorithm (GA). Optimum solutions for the three different gases and their respective responses are obtained. Confirmation experiment has also been conducted to validate the optimized parameters obtained from GA.

  15. Optimization of Process Parameters for ε-Polylysine Production by Response Surface Methods

    Directory of Open Access Journals (Sweden)

    Maxiaoqi Zhu

    2016-01-01

    Full Text Available ε-Polylysine (ε-PL is a highly safe natural food preservative with a broad antimicrobial spectrum, excellent corrosion resistances, and great commercial potentials. In the present work, we evaluated the ε-PL adsorption performances of HZB-3B and D155 resins and optimized the adsorption and desorption conditions by single-factor test, response surface method, and orthogonal design. The complexes of resin and ε-PL were characterized by SEM and FITR. The results indicated that D155 resin had the best ε-PL adsorption performance and was selected for the separation and purification of ε-PL. The conditions for the static adsorption of ε-PL on D155 resin were optimized as follows: ε-PL solution 40 g/L, pH 8.5, resins 15 g/L, and absorption time 14 h. The adsorption efficiency of ε-PL under the optimal conditions was 96.84%. The ε-PL adsorbed on the D155 resin was easily desorbed with 0.4 mol/L HCl at 30°C in 10 h. The highest desorption efficiency was 97.57% and the overall recovery of ε-PL was 94.49% under the optimal conditions. The excellent ε-PL adsorption and desorption properties of D155 resin including high selectivity and adsorption capacity, easy desorption, and high stability make it a good candidate for the isolation of ε-PL from fermentation broths.

  16. Modeling and Parameter Optimization for Surface Roughness and Residual Stress in Dry Turning Process

    Directory of Open Access Journals (Sweden)

    M. H. El-Axir

    2017-10-01

    Full Text Available The influence of some turning variables and tool overhang on surface roughness parameters and residual stress induced due to machining 6061-T6 aluminum alloy is investigated in this paper. Four input parameters (cutting speed, feed rate, depth of cut and tool overhang are considered. Tests are carried out by precision turning operation on a lathe. Design of experiment techniques, i.e. response surface methodology (RSM and Taguchi's technique have been used to accomplish the objective of the experimental study. Surface roughness parameters are measured using a portable surface roughness device while residual stresses are measured employing deflection-etching technique using electrochemical analysis. The results obtained reveal that feed and rotational speed play significant role in determining the average surface roughness. Furthermore, the depth of cut and tool overhang are less significant parameters, whereas tool overhang interacts with feed rate. The best result of surface roughness was obtained using low or medium values of overhang with low speed and /or feed rate. Minimum maximum tensile residual stress can be obtained with a combination of tool overhang of 37 mm with very low depth of cut, low rotational speed and feed rate of 0.188 mm/rev.

  17. Honing process optimization algorithms

    Science.gov (United States)

    Kadyrov, Ramil R.; Charikov, Pavel N.; Pryanichnikova, Valeria V.

    2018-03-01

    This article considers the relevance of honing processes for creating high-quality mechanical engineering products. The features of the honing process are revealed and such important concepts as the task for optimization of honing operations, the optimal structure of the honing working cycles, stepped and stepless honing cycles, simulation of processing and its purpose are emphasized. It is noted that the reliability of the mathematical model determines the quality parameters of the honing process control. An algorithm for continuous control of the honing process is proposed. The process model reliably describes the machining of a workpiece in a sufficiently wide area and can be used to operate the CNC machine CC743.

  18. Experimental investigation and optimization of welding process parameters for various steel grades using NN tool and Taguchi method

    Science.gov (United States)

    Soni, Sourabh Kumar; Thomas, Benedict

    2018-04-01

    The term "weldability" has been used to describe a wide variety of characteristics when a material is subjected to welding. In our analysis we perform experimental investigation to estimate the tensile strength of welded joint strength and then optimization of welding process parameters by using taguchi method and Artificial Neural Network (ANN) tool in MINITAB and MATLAB software respectively. The study reveals the influence on weldability of steel by varying composition of steel by mechanical characterization. At first we prepare the samples of different grades of steel (EN8, EN 19, EN 24). The samples were welded together by metal inert gas welding process and then tensile testing on Universal testing machine (UTM) was conducted for the same to evaluate the tensile strength of the welded steel specimens. Further comparative study was performed to find the effects of welding parameter on quality of weld strength by employing Taguchi method and Neural Network tool. Finally we concluded that taguchi method and Neural Network Tool is much efficient technique for optimization.

  19. An Investigation of Sintering Parameters on Titanium Powder for Electron Beam Melting Processing Optimization

    Directory of Open Access Journals (Sweden)

    Philipp Drescher

    2016-12-01

    Full Text Available Selective electron beam melting (SEBM is a relatively new additive manufacturing technology for metallic materials. Specific to this technology is the sintering of the metal powder prior to the melting process. The sintering process has disadvantages for post-processing. The post-processing of parts produced by SEBM typically involves the removal of semi-sintered powder through the use of a powder blasting system. Furthermore, the sintering of large areas before melting decreases productivity. Current investigations are aimed at improving the sintering process in order to achieve better productivity, geometric accuracy, and resolution. In this study, the focus lies on the modification of the sintering process. In order to investigate and improve the sintering process, highly porous titanium test specimens with various scan speeds were built. The aim of this study was to decrease build time with comparable mechanical properties of the components and to remove the residual powder more easily after a build. By only sintering the area in which the melt pool for the components is created, an average productivity improvement of approx. 20% was achieved. Tensile tests were carried out, and the measured mechanical properties show comparatively or slightly improved values compared with the reference.

  20. An Investigation of Sintering Parameters on Titanium Powder for Electron Beam Melting Processing Optimization.

    Science.gov (United States)

    Drescher, Philipp; Sarhan, Mohamed; Seitz, Hermann

    2016-12-01

    Selective electron beam melting (SEBM) is a relatively new additive manufacturing technology for metallic materials. Specific to this technology is the sintering of the metal powder prior to the melting process. The sintering process has disadvantages for post-processing. The post-processing of parts produced by SEBM typically involves the removal of semi-sintered powder through the use of a powder blasting system. Furthermore, the sintering of large areas before melting decreases productivity. Current investigations are aimed at improving the sintering process in order to achieve better productivity, geometric accuracy, and resolution. In this study, the focus lies on the modification of the sintering process. In order to investigate and improve the sintering process, highly porous titanium test specimens with various scan speeds were built. The aim of this study was to decrease build time with comparable mechanical properties of the components and to remove the residual powder more easily after a build. By only sintering the area in which the melt pool for the components is created, an average productivity improvement of approx. 20% was achieved. Tensile tests were carried out, and the measured mechanical properties show comparatively or slightly improved values compared with the reference.

  1. Regulation and optimization of the biogas process: Propionate as a key parameter

    DEFF Research Database (Denmark)

    Bangsø Nielsen, Henrik; Uellendahl, Hinrich; Ahring, Birgitte Kiær

    2007-01-01

    .6 to 2.9 mM. A process disturbance caused by overloading with industrial waste was reflected by a significant increase in all VFA concentrations. During the recovery of the process, the return of propionate back to the steady-state level was 2-3 days slower than any other VFA and propionate could best......, a process breakdown caused by organic overloading with meat and bone meal and lipids was indicated by changes in propionate concentration 12-18 days before a decrease in methane production was observed. Furthermore, a more efficient and stable utilization of the substrate was observed when propionate...

  2. 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

  3. Investigation on the Effects of Process Parameters on Laser Percussion Drilling Using Finite Element Methodology; Statistical Modelling and Optimization

    Directory of Open Access Journals (Sweden)

    Mahmoud Moradi

    Full Text Available Abstract In the present research, the simulation of the Nickel-base superalloy Inconel 718 fiber-laser drilling process with the thickness of 1mm is investigated through the Finite Element Method. In order to specify the appropriate Gaussian distribution of laser beam, the results of an experimental research on glass laser drilling were simulated using three types of Gaussian distribution. The DFLUX subroutine was used to implement the laser heat sources of the models using the Fortran language. After the appropriate Gaussian distribution was chosen, the model was validated with the experimental results of the Nickel-base superalloy Inconel 718 laser drilling process. The negligible error percentage among the experimental and simulation results demonstrates the high accuracy of this model. The experiments were performed based on the Response Surface Methodology (RSM as a statistical design of experiment (DOE approach to investigate the influence of process parameters on the responses, obtaining the mathematical regressions and predicting the new results. Four parameters i.e. laser pulse frequency (150 to 550 Hz, laser power (200 to 500 watts, laser focal plane position (-0.5 to +0.5 mm and the duty cycle (30 to 70% were considered to be the input variables in 5 levels and four external parameters i.e. the hole's entrance and exit diameters, hole taper angle and the weight of mass removed from the hole, were observed to be the process output responses of this central composite design. By performing the statistical analysis, the input and output parameters were found to have a direct relation with each other. By an increase in each of the input variables, the entrance and exit hole diameters, the hole taper angel, and the weight of mass removed from the hole increase. Finally, the results of the conducted simulations and statistical analyses having been used, the laser drilling process was optimized by means of the desire ability approach. Good

  4. Application of quality by design approach to optimize process and formulation parameters of rizatriptan loaded chitosan nanoparticles

    Directory of Open Access Journals (Sweden)

    Ajinath Eknath Shirsat

    2015-01-01

    Full Text Available The purpose of present study was to optimize rizatriptan (RZT chitosan (CS nanoparticles using ionic gelation method by application of quality by design (QbD approach. Based on risk assessment, effect of three variables, that is CS %, tripolyphosphate % and stirring speed were studied on critical quality attributes (CQAs; particle size and entrapment efficiency. Central composite design (CCD was implemented for design of experimentation with 20 runs. RZT CS nanoparticles were characterized for particle size, polydispersity index, entrapment efficiency, in-vitro release study, differential scanning calorimetric, X-ray diffraction, scanning electron microscopy (SEM. Based on QbD approach, design space (DS was optimized with a combination of selected variables with entrapment efficiency > 50% w/w and a particle size between 400 and 600 nm. Validation of model was performed with 3 representative formulations from DS for which standard error of − 0.70-3.29 was observed between experimental and predicted values. In-vitro drug release followed initial burst release 20.26 ± 2.34% in 3-4 h with sustained drug release of 98.43 ± 2.45% in 60 h. Lower magnitude of standard error for CQAs confirms the validation of selected CCD model for optimization of RZT CS nanoparticles. In-vitro drug release followed dual mechanism via, diffusion and polymer erosion. RZT CS nanoparticles were prepared successfully using QbD approach with the understanding of the high risk process and formulation parameters involved and optimized DS with a multifactorial combination of critical parameters to obtain predetermined RZT loaded CS nanoparticle specifications.

  5. Regulation and optimization of the biogas process: Propionate as a key parameter

    International Nuclear Information System (INIS)

    Nielsen, Henrik Bangso; Uellendahl, Hinrich; Ahring, Birgitte Kiaer

    2007-01-01

    The use of volatile fatty acids (VFA) as process indicators in biogas reactors treating manure together with industrial waste was studied. At a full-scale biogas plant, an online VFA sensor was installed in order to study VFA dynamics during stable and unstable operation. During stable operation acetate increased significantly during the feeding periods from a level of 2-4 to 12-17 mM, but the concentration generally dropped to about the same level as before feeding. The fluctuations in the propionate were more moderate than for acetate but the average level rose during 1 week of operation from 0.6 to 2.9 mM. A process disturbance caused by overloading with industrial waste was reflected by a significant increase in all VFA concentrations. During the recovery of the process, the return of propionate back to the steady-state level was 2-3 days slower than any other VFA and propionate could best describe the normalizing of the process. In a lab-scale continuously stirred tank reactor experiment, with manure as main substrate, the prospective of using either propionate concentration or methane production as single process indicators was studied. Propionate was found to be the best indicator. Thus, a process breakdown caused by organic overloading with meat and bone meal and lipids was indicated by changes in propionate concentration 12-18 days before a decrease in methane production was observed. Furthermore, a more efficient and stable utilization of the substrate was observed when propionate was used as process indicator

  6. Process Parameter Evaluation and Optimization for Advanced Material Development Final Report CRADA No. TC-1234-96

    Energy Technology Data Exchange (ETDEWEB)

    Hrubesh, L. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); McGann, T. W. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-10-19

    This project was established as a three-year collaboration to produce and characterize · silica aerogels prepared by a Rapid Supercritical Extraction (RSCE) process to meet . BNA, Inc. application requirements. The objectives of this project were to study the parameters necessary to produce optimized aerogel parts with narrowly specified properties and establish the range and limits of the process for producing such aerogels. The project also included development of new aerogel materials useful for high temperature applications. The results of the project were expected to set the conditions necessary to produce quantities of aerogels having particular specifications such as size, shape, density, and mechanical strength. BNA, Inc. terminated the project on April 7, 1999, 10-months prior to the anticipated completion date, due to termination of corporate funding for the project. The technical accomplishments achieved are outlined in Paragraph C below.

  7. Optimization of Process Parameters of Edge Robotic Deburring with Force Control

    Directory of Open Access Journals (Sweden)

    Burghardt A.

    2016-12-01

    Full Text Available The issues addressed in the paper present a part of the scientific research conducted within the framework of the automation of the aircraft engine part manufacturing processes. The results of the research presented in the article provided information in which tolerances while using a robotic control station with the option of force control we can make edge deburring.

  8. Optimization of Process Parameters of Edge Robotic Deburring with Force Control

    Science.gov (United States)

    Burghardt, A.; Szybicki, D.; Kurc, K.; Muszyńska, M.

    2016-12-01

    The issues addressed in the paper present a part of the scientific research conducted within the framework of the automation of the aircraft engine part manufacturing processes. The results of the research presented in the article provided information in which tolerances while using a robotic control station with the option of force control we can make edge deburring.

  9. Cellular scanning strategy for selective laser melting: Generating reliable, optimized scanning paths and processing parameters

    DEFF Research Database (Denmark)

    Mohanty, Sankhya; Hattel, Jesper Henri

    2015-01-01

    method based uncertainty and reliability analysis. The reliability of the scanning paths are established using cumulative probability distribution functions for process output criteria such as sample density, thermal homogeneity, etc. A customized genetic algorithm is used along with the simulation model...

  10. The Optimization of Process Parameters and Microstructural Characterization of Fiber Laser Welded Dissimilar HSLA and MART Steel Joints

    Directory of Open Access Journals (Sweden)

    Celalettin Yuce

    2016-10-01

    Full Text Available Nowadays, environmental impact, safety and fuel efficiency are fundamental issues for the automotive industry. These objectives are met by using a combination of different types of steels in the auto bodies. Therefore, it is important to have an understanding of how dissimilar materials behave when they are welded. This paper presents the process parameters’ optimization procedure of fiber laser welded dissimilar high strength low alloy (HSLA and martensitic steel (MART steel using a Taguchi approach. The influence of laser power, welding speed and focal position on the mechanical and microstructural properties of the joints was determined. The optimum parameters for the maximum tensile load-minimum heat input were predicted, and the individual significance of parameters on the response was evaluated by ANOVA results. The optimum levels of the process parameters were defined. Furthermore, microstructural examination and microhardness measurements of the selected welds were conducted. The samples of the dissimilar joints showed a remarkable microstructural change from nearly fully martensitic in the weld bead to the unchanged microstructure in the base metals. The heat affected zone (HAZ region of joints was divided into five subzones. The fusion zone resulted in an important hardness increase, but the formation of a soft zone in the HAZ region.

  11. Optimization of processing parameters for extraction of essential oil from Foeniculum vulgare

    Directory of Open Access Journals (Sweden)

    2017-11-01

    Full Text Available Background and objectives: It is necessary to specify the best conditions of essential oils production to get more major compound(s and higher yield oil. The fennel oil is useful in pharmaceutical industry as flavor. The main component of fennel oil is anethole (55-75%. The objective of this work was to identify the effect of  particle size, pH of water, method of distillation and using ultrasound on extraction of fennel essential oil (and its major constituent, anethole. Methods: We used a statistical method called D-optimal Design that appointed pH, particle size and method for each assay. Fennel seeds were purchased, then milled and passed from different meshes. In the first series, the seeds powder was distilled directly. In the second series the seeds were placed in an ultrasonic apparatus for 30 min. The essential oils were subsequently isolated by two methods, hydro distillation and steam distillation, in different sizes (25, 30, 40, 50 and pH (5.5, 5.8, 7, 7.4, 8.5. Fifty g of dry seeds were used in each distillation (for 3 h. Analytical gas chromatography (GC was used to determine the essential oil composition. Results: In the steam distillation, the volume of essential oils and the concentration of anethole, whatever the plant became smaller, was less. However, in the water distillation, it was more and by comparing the two steps, without and with ultrasound, it increased 20% after the ultrasound. Conclusion: optimum conditions according to the statistical results were steam distillation, mesh size 50 and using ultrasounic device.

  12. DETERMINATION AND OPTIMIZATION OF CYLINDRICAL GRINDING PROCESS PARAMETERS USING TAGUCHI METHOD AND REGRESSION ANALYSIS

    OpenAIRE

    M.Janardhan; Dr.A.Gopala Krishna

    2011-01-01

    Cylindrical grinding is one of the important metal cutting processes used extensively in the finishing operations. Metal removal rate and surface finish are the important out put responses in the production with respect to quantity and quality respectively. The Experiments are conducted on CNC cylindrical grinding machine with L9 Orthogonal array with input machining variables as work speed, feed rate and depth of cut. Empirical models are developed using design of experiments and response su...

  13. Activated sludge treatment by electro-Fenton process: Parameter optimization and degradation mechanism

    Energy Technology Data Exchange (ETDEWEB)

    Rahmani, Ali Reza; Azarian, Ghasem; Berizi, Zohreh [Hamadan University of Medical Sciences, Hamadan (Iran, Islamic Republic of); Nematollahi, Davood [Bu-Ali-Sina University, Hamadan (Iran, Islamic Republic of); Godini, Kazem [Ilam University of Medical Sciences, Ilam (Iran, Islamic Republic of)

    2015-08-15

    This study was conducted to evaluate the mineralization of activated sludge (MAS) by a facile and environmentally friendly electro-Fenton process (EFP). The effects of initial H{sub 2}O{sub 2} concentration, pH value, applied current density and operating time on MAS through determining the removal rate of chemical oxygen demand (COD) and total coliform (TC) were studied. 72% of COD was removed by indirect oxidation double-mediated based on the electro- generation of hydroxyl radical and active chlorine, under the following optimum conditions: 127mmol L{sup -}1 of hydrogen peroxide, pH=3.0, 10 mA cm{sup -}2 of DC current, 120min of operating time, and 0.22mol L{sup -}1 of NaCl as the supporting electrolyte. Only in 10 min and pH 3.0 approximately 100% of TC was removed. The findings indicated that EFP can be applied efficiently for MAS by selecting appropriate operating conditions. The bottom line is that the process is entirely effective owing to the application of green oxidants (hydroxyl radical and active chlorine) and lack of being influenced by environmental situations, which can be introduced as an alternative to current conventional methods.

  14. Activated sludge treatment by electro-Fenton process: Parameter optimization and degradation mechanism

    International Nuclear Information System (INIS)

    Rahmani, Ali Reza; Azarian, Ghasem; Berizi, Zohreh; Nematollahi, Davood; Godini, Kazem

    2015-01-01

    This study was conducted to evaluate the mineralization of activated sludge (MAS) by a facile and environmentally friendly electro-Fenton process (EFP). The effects of initial H 2 O 2 concentration, pH value, applied current density and operating time on MAS through determining the removal rate of chemical oxygen demand (COD) and total coliform (TC) were studied. 72% of COD was removed by indirect oxidation double-mediated based on the electro- generation of hydroxyl radical and active chlorine, under the following optimum conditions: 127mmol L - 1 of hydrogen peroxide, pH=3.0, 10 mA cm - 2 of DC current, 120min of operating time, and 0.22mol L - 1 of NaCl as the supporting electrolyte. Only in 10 min and pH 3.0 approximately 100% of TC was removed. The findings indicated that EFP can be applied efficiently for MAS by selecting appropriate operating conditions. The bottom line is that the process is entirely effective owing to the application of green oxidants (hydroxyl radical and active chlorine) and lack of being influenced by environmental situations, which can be introduced as an alternative to current conventional methods.

  15. Stevia rebaudiana Bertoni as a natural antioxidant/antimicrobial for high pressure processed fruit extract: processing parameter optimization.

    Science.gov (United States)

    Barba, Francisco José; Criado, María Nieves; Belda-Galbis, Clara Miracle; Esteve, María José; Rodrigo, Dolores

    2014-04-01

    Response surface methodology was used to evaluate the optimal high pressure processing treatment (300-500 MPa, 5-15 min) combined with Stevia rebaudiana (Stevia) addition (0-2.5% (w/v)) to guarantee food safety while maintaining maximum retention of nutritional properties. A fruit extract matrix was selected and Listeria monocytogenes inactivation was followed from the food safety point of view while polyphenoloxidase (PPO) and peroxidase (POD) activities, total phenolic content (TPC) and antioxidant capacity (TEAC and ORAC) were studied from the food quality point of view. A combination of treatments achieved higher levels of inactivation of L. monocytogenes and of the oxidative enzymes, succeeding in completely inactivating POD and also increasing the levels of TPC, TEAC and ORAC. A treatment of 453 MPa for 5 min with a 2.5% (w/v) of Stevia succeeded in inactivating over 5 log cycles of L. monocytogenes and maximizing inactivation of PPO and POD, with the greatest retention of bioactive components. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. 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...

  17. Intensification of the Reverse Cationic Flotation of Hematite Ores with Optimization of Process and Hydrodynamic Parameters of Flotation Cell

    Science.gov (United States)

    Poperechnikova, O. Yu; Filippov, L. O.; Shumskaya, E. N.; Filippova, I. V.

    2017-07-01

    The demand of high grade iron ore concentrates is a major issue due to the depletion of rich iron-bearing ores and high competitiveness in the iron ore market. Iron ore production is forced out to upgrade flowsheets to decrease the silica content in the pelettes. Different types of ore have different mineral composition and texture-structural features which require different mineral processing methods and technologies. The paper presents a comparative study of the cationic and anionic flotation routes to process a fine-grain oxidized iron ore. The modified carboxymethyl cellulose was found as the most efficient depressant in reverse cationic flotation. The results of flotation optimization of hematite ores using matrix of second-order center rotatable uniform design allowed to define the collector concentration, impeller rotation speed and air flowrate as the main flotation parameters impacting on the iron ore concentrate quality and iron recovery in a laboratory flotation machine. These parameters have been selected as independent during the experiments.

  18. Optimization of process parameter variations on leakage current in in silicon-oninsulator vertical double gate mosfet device

    Directory of Open Access Journals (Sweden)

    K.E. Kaharudin

    2015-12-01

    Full Text Available This paper presents a study of optimizing input process parameters on leakage current (IOFF in silicon-on-insulator (SOI Vertical Double-Gate,Metal Oxide Field-Effect-Transistor (MOSFET by using L36 Taguchi method. The performance of SOI Vertical DG-MOSFET device is evaluated in terms of its lowest leakage current (IOFF value. An orthogonal array, main effects, signal-to-noise ratio (SNR and analysis of variance (ANOVA are utilized in order to analyze the effect of input process parameter variation on leakage current (IOFF. Based on the results, the minimum leakage current ((IOFF of SOI Vertical DG-MOSFET is observed to be 0.009 nA/µm or 9 ρA/µm while keeping the drive current (ION value at 434 µA/µm. Both the drive current (ION and leakage current (IOFF values yield a higher ION/IOFF ratio (48.22 x 106 for low power consumption application. Meanwhile, polysilicon doping tilt angle and polysilicon doping energy are recognized as the most dominant factors with each of the contributing factor effects percentage of 59% and 25%.

  19. Electrocoagulation treatment of raw landfill leachate using iron-based electrodes: Effects of process parameters and optimization.

    Science.gov (United States)

    Huda, N; Raman, A A A; Bello, M M; Ramesh, S

    2017-12-15

    The main problem of landfill leachate is its diverse composition comprising many persistent organic pollutants which must be removed before being discharge into the environment. This study investigated the treatment of raw landfill leachate using electrocoagulation process. An electrocoagulation system was designed with iron as both the anode and cathode. The effects of inter-electrode distance, initial pH and electrolyte concentration on colour and COD removals were investigated. All these factors were found to have significant effects on the colour removal. On the other hand, electrolyte concentration was the most significant parameter affecting the COD removal. Numerical optimization was also conducted to obtain the optimum process performance. Under optimum conditions (initial pH: 7.73, inter-electrode distance: 1.16 cm, and electrolyte concentration (NaCl): 2.00 g/L), the process could remove up to 82.7% colour and 45.1% COD. The process can be applied as a pre-treatment for raw leachates before applying other appropriate treatment technologies. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Evaluation and Optimization of Downstream Process Parameters for Extraction of Betulinic Acid from the Bark of Ziziphus jujubae L.

    Directory of Open Access Journals (Sweden)

    Kashyap Kumar Dubey

    2013-01-01

    Full Text Available Present work investigated an apposite and efficient method for extraction of betulinic acid (BA from the bark of Ziziphus jujubae. Various extraction methods like stirring extraction, soxhlet extraction, ultrasonic extraction, and microwave assisted extraction (MAE were evaluated for increasing recovery percentage of BA. From the raffinate so obtained, BA was isolated. Thin layer chromatography (TLC was used to analyze the extract and high performance liquid chromatography (HPLC for quantification. The results revealed that the percentage extraction of BA from Z. jujubae by MAE was more proficient. As recovery percentage of BA by MAE technique turned out to be maximum, by using response surface methodology (RSM, three process parameters (pH, temperature, and time were optimized by MAE and it was observed that the optimum parameters (pH 6.5, temp. 70.23°C, and time 3.5 min gave the maximum recovery of BA (0.44% w/w. To validate the RSM model, experiments were performed and the highest recovery of BA was found to be 0.4% w/w which is ±0.04% to the predicted value. Henceforth the extraction efficiency and the substantial saving of time by MAE was more capable than the other extraction techniques.

  1. Multi-response optimization of process parameters using Taguchi method and grey relational analysis during turning AA 7075/SiC composite in dry and spray cooling environments

    Directory of Open Access Journals (Sweden)

    P. C. Mishra

    2015-09-01

    Full Text Available Turning experiments were carried out on AA 7075/SiC composite workpiece in dry and spray cooling environments based on L16 Taguchi design of experiments. Multiple performance optimization of process parameters was performed using grey relational analysis. The performance characteristics considered were average surface roughness, cutting tool temperature and material removal rate. Uncoated carbide inserts were used for machining the workpiece in a high speed precision lathe. A grey relational grade obtained from grey relational analysis was used to optimize the process parameters. Optimal combination of process parameters was then determined by the Taguchi method using the grey relational grade as the performance index. Experimental results indicated that the turning in spray cooling environment was beneficial compared to that in dry environment for the quality response characteristics under consideration. Analysis of variance showed that feed was the most significant parameter for the multiple performance characteristics during turning in both the environments.

  2. Application of processing maps in the optimization of the parameters of a hot working process. Part 1. Theoretical review

    International Nuclear Information System (INIS)

    Al Omar, A.; Prado, J.M.

    1997-01-01

    The hot working processes constitute an important step in the manufacture of components for engineering applications. In the past, the mechanical processing have been used to impart a shape to the engineering materials. More recently, however, the hot working processes are used not only to achieve the required shape but also to impart desirable mechanical and microstructural characteristics by an adequate design of the thermomechanical process. The aim of the present paper is to summarize the general characteristics of the Dynamic Materials Model. In this model, the work piece material under hot working conditions is considered to be a dissipator of power. Also, the extreme principles of irreversible thermodynamics applied to large plastic flow are described to develop a continuum criterion capable to predict the metallurgical instabilities in a hot worked material. (Author) 22 refs

  3. Process Parameters Optimization of Potential SO42-/ZnO Acid Catalyst for Heterogeneous Transesterification of Vegetable Oil to Biodiesel

    Directory of Open Access Journals (Sweden)

    Istadi Istadi

    2012-12-01

    Full Text Available Among the possible renewable energy resources, diesel fuels derived from triglycerides of vegetable oils and animal fats have shown potential as substitutes for petroleum-based diesel fuels. The biodiesel could be produced from vegetable oils over homogeneous catalyst, heterogeneous catalyst, or enzymatic catalyst. In this study, the synthesized SO42-/ZnO catalyst was explored to be used in the heterogeneous biodiesel production by using the vegetable oils and methanol. The study began with the preparation of SO42-/ZnO catalyst followed by the transesterification reaction between vegetable oil with methanol. The independent variables (reaction time and the weight ratio of catalyst/oil were optimized to obtain the optimum biodiesel (fatty acid methyl ester yield. The results of this study showed that the acid catalyst SO42-/ZnO was potential to be used as catalyst for biodiesel production through heterogeneous transesterification of vegetable oils. Optimum operating condition for this catalytic reaction was the weight ratio of catalyst/oil of 8:1 and reaction time of 2.6 h with respect to 75.5% yield of methyl ester products. The biodiesel product was also characterized to identify the respected fatty acid methyl ester components. Copyright © 2012 by BCREC UNDIP. All rights reserved. (Selected Paper from International Conference on Chemical and Material Engineering (ICCME 2012Received: 23rd October 2012, Revised: 25th November 2012, Accepted: 25th November 2012[How to Cite: I. Istadi, Didi D. Anggoro, Luqman Buchori, Inshani Utami, Roikhatus Solikhah, (2012. Process Parameters Optimization of Potential SO42-/ZnO Acid Catalyst for Heterogeneous Transesterification of Vegetable Oil to Biodiesel. Bulletin of Chemical Reaction Engineering & Catalysis, 7(2: 150-157. (doi:10.9767/bcrec.7.2.4064.150-157][How to Link / DOI: http://dx.doi.org/10.9767/bcrec.7.2.4064.150-157 ] | View in 

  4. [Temporal and spatial heterogeneity analysis of optimal value of sensitive parameters in ecological process model: The BIOME-BGC model as an example.

    Science.gov (United States)

    Li, Yi Zhe; Zhang, Ting Long; Liu, Qiu Yu; Li, Ying

    2018-01-01

    The ecological process models are powerful tools for studying terrestrial ecosystem water and carbon cycle at present. However, there are many parameters for these models, and weather the reasonable values of these parameters were taken, have important impact on the models simulation results. In the past, the sensitivity and the optimization of model parameters were analyzed and discussed in many researches. But the temporal and spatial heterogeneity of the optimal parameters is less concerned. In this paper, the BIOME-BGC model was used as an example. In the evergreen broad-leaved forest, deciduous broad-leaved forest and C3 grassland, the sensitive parameters of the model were selected by constructing the sensitivity judgment index with two experimental sites selected under each vegetation type. The objective function was constructed by using the simulated annealing algorithm combined with the flux data to obtain the monthly optimal values of the sensitive parameters at each site. Then we constructed the temporal heterogeneity judgment index, the spatial heterogeneity judgment index and the temporal and spatial heterogeneity judgment index to quantitatively analyze the temporal and spatial heterogeneity of the optimal values of the model sensitive parameters. The results showed that the sensitivity of BIOME-BGC model parameters was different under different vegetation types, but the selected sensitive parameters were mostly consistent. The optimal values of the sensitive parameters of BIOME-BGC model mostly presented time-space heterogeneity to different degrees which varied with vegetation types. The sensitive parameters related to vegetation physiology and ecology had relatively little temporal and spatial heterogeneity while those related to environment and phenology had generally larger temporal and spatial heterogeneity. In addition, the temporal heterogeneity of the optimal values of the model sensitive parameters showed a significant linear correlation

  5. Analysis and optimization of process parameters for production of polyhydroxyalkanoates along with wastewater treatment by Serratia sp. ISTVKR1.

    Science.gov (United States)

    Gupta, Asmita; Kumar, Madan; Thakur, Indu Shekhar

    2017-10-01

    A previously reported biodegrading bacterial strain Serratia sp. ISTVKR1 was studied for polyhydroxyalkanoate (PHA) production along with wastewater contaminant removal. Nile red fluorescence, GC-MS, FT-IR, NMR and TEM confirmed the accumulation of homopolymer poly-3-hydroxyvalerate (PHV) within the bacterial cells. Analysis of culture after 72h of bacterial treatment showed maximum COD removal (8.4-fold), non-detection of organic contaminants such as 1H-Cyclopropa [a] naphthalene (R.T.=10.12) using GC-MS and increased proportion of elements like Cr, Mn, Fe, Ni, Cu, Cd and Pb in the bacterial cell pellets by SEM-EDX analysis. Optimization of process parameters for enhanced PHA production along with wastewater treatment done using Response Surface Methodology (RSM) showed 5% and 0.74% increase in the PHA production (0.3368±0.13gL -1 ) and % COD reduction (88.93±2.41) of wastewater, respectively. The study, thus established the production of PHA along with wastewater contaminant removal by Serratia sp. ISTVKR1. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Response surface methodology for evaluation and optimization of process parameter and antioxidant capacity of rice flour modified by enzymatic extrusion.

    Science.gov (United States)

    Xu, Enbo; Pan, Xiaowei; Wu, Zhengzong; Long, Jie; Li, Jingpeng; Xu, Xueming; Jin, Zhengyu; Jiao, Aiquan

    2016-12-01

    For the purpose of investigating the effect of enzyme concentration (EC), barrel temperature (BT), moisture content (MC), and screw speed (SS) on processing parameters (product temperature, die pressure and special mechanical energy (SME)) and product responses (extent of gelatinization (GE), retention rate of total phenolic content (TPC-RR)), rice flour extruded with thermostable α-amylase was analyzed by response surface methodology. Stepwise regression models were computed to generate response surface and contour plots, revealing that both TPC-RR and GE increased as increasing MC while expressed different sensitivities to BT during enzymatic extrusion. Phenolics preservation was benefited from low SME. According to multiple-factor optimization, the conditions required to obtain the target SME (10kJ/kg), GE (100%) and TPC-RR (85%) were: EC=1.37‰, BT=93.01°C, MC=44.30%, and SS=171.66rpm, with the actual values (9.49kJ/kg, 99.96% and 87.10%, respectively) showing a good fit to the predicted values. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

  7. Chickpea seeds germination rational parameters optimization

    Science.gov (United States)

    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.

  8. Optimization of processing parameters on the controlled growth of c-axis oriented ZnO nanorod arrays

    Energy Technology Data Exchange (ETDEWEB)

    Malek, M. F., E-mail: mfmalek07@gmail.com; Rusop, M., E-mail: rusop@salam.uitm.my [NANO-ElecTronic Centre (NET), Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM), 40450 Shah Alam, Selangor (Malaysia); NANO-SciTech Centre (NST), Institute of Science (IOS), Universiti Teknologi MARA - UiTM, 40450 Shah Alam, Selangor (Malaysia); Mamat, M. H., E-mail: hafiz-030@yahoo.com [NANO-ElecTronic Centre (NET), Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM), 40450 Shah Alam, Selangor (Malaysia); Musa, M. Z., E-mail: musa948@gmail.com [NANO-ElecTronic Centre (NET), Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM), 40450 Shah Alam, Selangor (Malaysia); Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM) Pulau Pinang, Jalan Permatang Pauh, 13500 Permatang Pauh, Pulau Pinang (Malaysia); Saurdi, I., E-mail: saurdy788@gmail.com; Ishak, A., E-mail: ishak@sarawak.uitm.edu.my [NANO-ElecTronic Centre (NET), Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM), 40450 Shah Alam, Selangor (Malaysia); Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM) Sarawak, Kampus Kota Samarahan, Jalan Meranek, 94300 Kota Samarahan, Sarawak (Malaysia); Alrokayan, Salman A. H., E-mail: dr.salman@alrokayan.com; Khan, Haseeb A., E-mail: khan-haseeb@yahoo.com [Chair of Targeting and Treatment of Cancer Using Nanoparticles, Deanship of Scientific Research, King Saud University (KSU), Riyadh 11451 (Saudi Arabia)

    2016-07-06

    Optimization of the growth time parameter was conducted to synthesize high-quality c-axis ZnO nanorod arrays. The effects of the parameter on the crystal growth and properties were systematically investigated. Our studies confirmed that the growth time influence the properties of ZnO nanorods where the crystallite size of the structures was increased at higher deposition time. Field emission scanning electron microsope analysis confirmed the morphologies structure of the ZnO nanorods. The ZnO nanostructures prepared under the optimized growth conditions showed an intense XRD peak which reveal a higher c-axis oriented ZnO nanorod arrays thus demonstrating the formation of defect free structure.

  9. Statistical optimization of process parameters for inulinase production from Tithonia weed by Arthrobacter mysorens strain no.1.

    Science.gov (United States)

    Kamble, Prajakta P; Kore, Maheshkumar V; Patil, Sushama A; Jadhav, Jyoti P; Attar, Yasmin C

    2018-06-01

    Tithonia rotundifolia is an easily available and abundant inulin rich weed reported to be competitive and allelopathic. This weed inulin is hydrolyzed by inulinase into fructose. Response surface methodology was employed to optimize culture conditions for the inulinase production from Arthrobacter mysorens strain no.1 isolated from rhizospheric area of Tithonia weed. Initially, Plackett- Burman design was used for screening 11 nutritional parameters for inulinase production including inulin containing weeds as cost effective substrate. The experiment shows that amongst the 11 parameters studied, K 2 HPO 4 , Inulin, Agave sisalana extract and Tithonia rotundifolia were the most significant variables for inulinase production. Quantitative effects of these 4 factors were further investigated using Box Behnken design. The medium having 0.27% K 2 HPO 4 , 2.54% Inulin, 6.57% Agave sisalana extract and 7.27% Tithonia rotundifolia extract were found to be optimum for maximum inulinase production. The optimization strategies used showed 2.12 fold increase in inulinase yield (1669.45 EU/ml) compared to non-optimized medium (787 EU/ml). Fructose produced by the action of inulinase was further confirmed by spectrophotometer, osazone, HPTLC and FTIR methods. Thus Tithonia rotundifolia can be used as an eco-friendly, economically feasible and promising alternative substrate for commercial inulinase production yielding fructose from Arthrobacter mysorens strain no.1. Copyright © 2018 Elsevier B.V. All rights reserved.

  10. Production of biodiesel from coastal macroalgae (Chara vulgaris) and optimization of process parameters using Box-Behnken design.

    Science.gov (United States)

    Siddiqua, Shaila; Mamun, Abdullah Al; Enayetul Babar, Sheikh Md

    2015-01-01

    Renewable biodiesels are needed as an alternative to petroleum-derived transport fuels, which contribute to global warming and are of limited availability. Algae biomass, are a potential source of renewable energy, and they can be converted into energy such as biofuels. This study introduces an integrated method for the production of biodiesel from Chara vulgaris algae collected from the coastal region of Bangladesh. The Box-Behnken design based on response surface methods (RSM) used as the statistical tool to optimize three variables for predicting the best performing conditions (calorific value and yield) of algae biodiesel. The three parameters for production condition were chloroform (X1), sodium chloride concentration (X2) and temperature (X3). Optimal conditions were estimated by the aid of statistical regression analysis and surface plot chart. The optimal condition of biodiesel production parameter for 12 g of dry algae biomass was observed to be 198 ml chloroform with 0.75 % sodium chloride at 65 °C temperature, where the calorific value of biodiesel is 9255.106 kcal/kg and yield 3.6 ml.

  11. 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.)

  12. Multi-response optimization of process parameters in biogas production from food waste using Taguchi – Grey relational analysis

    International Nuclear Information System (INIS)

    Deepanraj, B.; Sivasubramanian, V.; Jayaraj, S.

    2017-01-01

    Highlights: • Influence of process parameters on biogas production was experimentally investigated. • The optimum conditions were determined using Taguchi based Grey relational analysis. • Percentage contribution of chosen parameters were determined using ANOVA. • Empirical relationship between the input and output variables were derived. - Abstract: In the present study, the influence of process parameters and pretreatment on biogas production, volatile solid degradation and COD degradation during anaerobic digestion of food waste were experimentally investigated. Using Taguchi based Grey relational analysis, the optimum condition for anaerobic digestion was found. Taguchi technique was coupled with grey relational analysis to obtain a grey relational grade for evaluating multiple outputs. A L_1_6 orthogonal array was selected and designed for five parameters varied through four levels by applying Taguchi’s design of experiments. The optimum level values of parameters obtained for anaerobic digestion of food waste is solid concentration of 7.5% TS, pH of 7, temperature of 50 °C, C/N ratio of 20.19 and ultrasonication pretreatment. Percentage contribution of input parameters on output was determined using ANOVA. The results showed that pretreatment is the prominent parameter that contributes towards output responses followed by pH, solid concentration, temperature and C/N ratio.

  13. Optimization of process parameters for acrylonitrile removal by a low-cost adsorbent using Box-Behnken design

    International Nuclear Information System (INIS)

    Kumar, Arvind; Prasad, B.; Mishra, I.M.

    2008-01-01

    In the present work, acrylonitrile removal from wastewater was investigated using an agri-based adsorbent-sugarcane bagasse fly ash (BFA). The effect of such parameters as adsorbent dose (w), temperature (T) and time of contact (t) on the sorption of acrylonitrile by BFA was investigated using response surface methodology (RSM) based on Box-Behnken surface statistical design at an initial acrylonitrile concentration, C 0 = 100 mg/l as a fixed input parameter. The results of RSM indicate that the proposed models predict the responses adequately within the limits of input parameters being used. The isotherm shows a two-step adsorption, well represented by a two-step Langmuir isotherm equation. Thermodynamic parameters indicate the sorption process to be spontaneous and exothermic

  14. Application of the Taguchi analytical method for optimization of effective parameters of the chemical vapor deposition process controlling the production of nanotubes/nanobeads.

    Science.gov (United States)

    Sharon, Maheshwar; Apte, P R; Purandare, S C; Zacharia, Renju

    2005-02-01

    Seven variable parameters of the chemical vapor deposition system have been optimized with the help of the Taguchi analytical method for getting a desired product, e.g., carbon nanotubes or carbon nanobeads. It is observed that almost all selected parameters influence the growth of carbon nanotubes. However, among them, the nature of precursor (racemic, R or Technical grade camphor) and the carrier gas (hydrogen, argon and mixture of argon/hydrogen) seem to be more important parameters affecting the growth of carbon nanotubes. Whereas, for the growth of nanobeads, out of seven parameters, only two, i.e., catalyst (powder of iron, cobalt, and nickel) and temperature (1023 K, 1123 K, and 1273 K), are the most influential parameters. Systematic defects or islands on the substrate surface enhance nucleation of novel carbon materials. Quantitative contributions of process parameters as well as optimum factor levels are obtained by performing analysis of variance (ANOVA) and analysis of mean (ANOM), respectively.

  15. Multi-objective Optimization of Friction Welding Process Parameters using Grey Relational Analysis for Joining Aluminium Metal Matrix Composite

    Directory of Open Access Journals (Sweden)

    Sreenivasan KONGANAPURAM SUNDARARAJAN

    2018-05-01

    Full Text Available Aluminium metal matrix composites has gained importance in recent time because of its improved mechanical and metallurgical properties. The welding of aluminium metal matrix composites using conventional welding process has got many demerits so in order to overcome them a solid state welding process is to be employed. To achieve a good strength weld in the aluminium metal matrix composite bars an efficient and most preferred technique is friction welding. In this work the aluminium metal matrix composite AA7075 + 10 % vol SiC-T6 is selected and friction welded. The combination of friction welding process parameters such as spindle speed, friction pressure, upset pressure and burn-off- length for joining the AA7075 + 10 % vol SiCP-T6 metal matrix composite bars are selected by Taguchi’s design of experiment. The optimum friction welding parameters were determined for achieving improved ultimate tensile strength and the hardness using grey relational analysis. A combined grey relational grade is found from the determined grey relational coefficient of the output responses and the optimum friction welding process parameters were obtained as spindle speed – 1200 rpm, friction pressure – 100 MPa, upset pressure – 250 MPa, Burn-off-Length – 2 mm. Analysis of variance (ANOVA performed shows that the friction pressure is the most significant friction welding parameter that influences the both the ultimate tensile strength and hardness of friction welded AA7075 + 10 % volSiCP-T6 joints. The fractured surface under microstructure study also revealed good compliance with the grey relational grade result. DOI: http://dx.doi.org/10.5755/j01.ms.24.2.17725

  16. Optimization of the Hot Forging Processing Parameters for Powder Metallurgy Fe-Cu-C Connecting Rods Based on Finite Element Simulation

    Science.gov (United States)

    Li, Fengxian; Yi, Jianhong; Eckert, Jürgen

    2017-12-01

    Powder forged connecting rods have the problem of non-uniform density distributions because of their complex geometric shape. The densification behaviors of powder metallurgy (PM) connecting rod preforms during hot forging processes play a significant role in optimizing the connecting rod quality. The deformation behaviors of a connecting rod preform, a Fe-3Cu-0.5C (wt pct) alloy compacted and sintered by the powder metallurgy route (PM Fe-Cu-C), were investigated using the finite element method, while damage and friction behaviors of the material were considered in the complicated forging process. The calculated results agree well with the experimental results. The relationship between the processing parameters of hot forging and the relative density of the connecting rod was revealed. The results showed that the relative density of the hot forged connecting rod at the central shank changed significantly compared with the relative density at the big end and at the small end. Moreover, the relative density of the connecting rod was sensitive to the processing parameters such as the forging velocity and the initial density of the preform. The optimum forging processing parameters were determined and presented by using an orthogonal design method. This work suggests that the processing parameters can be optimized to prepare a connecting rod with uniform density distribution and can help to better meet the requirements of the connecting rod industry.

  17. 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.

  18. Optimization of Processing Parameters in 3D-Printing of Poly(lactic acid by Fused Deposition Modeling Method

    Directory of Open Access Journals (Sweden)

    Maryam Ezoji

    2017-05-01

    Full Text Available Nowadays, making use of additive manufacturing (AM processes such as fused deposition modeling (FDM, in different areas, such as car manufacturing, biomedical and aerospace industries is gaining popularity worldwide because of their capacities in producing functional parts with complex geometries. Therefore, it is very important to identify the significance of FDM processing parameters which would have an impact on the quality of articles produced by the processing system. In this work, poly(lactic acid was used to study the effects of processing parameters such as layer thickness, raster angle and printing plane on the tensile properties and surface roughness of the printed specimens. The results showed that the tensile strength of a specimen increased by reducing its layer thickness. However, the elastic modulus values increased with decreasing the layer thickness to some extent. Moreover, when the layer thickness was kept constant at 0.05 mm and 3D-printing was carried out in XYZ plane, the maximum modulus and tensile strength were obtained for the raster angle of 0˚. Microscopic studies showed that in low layer thickness, the polymeric layers diffused properly into each other and no voids were formed between the layers. However, with a thickness above its critical value, a few voids were formed between the layers which played as a stress concentrator and decreased the tensile strength of the specimens. The results also showed that the surface roughness increased with increasing the layer thickness.

  19. Multi response optimization of internal grinding process parameters for outer ring using Taguchi method and PCR-TOPSIS

    Science.gov (United States)

    Wisnuadi, Alief Regyan; Damayanti, Retno Wulan; Pujiyanto, Eko

    2018-02-01

    Bearing is one of the most widely used parts in automotive industry. One of the leading bearing manufacturing companies in the world is SKF Indonesia. This company must produce bearing with international standard. SKF Indonesia must do continuous improvement in order to face competition. During this time, SKF Indonesia is only performing quality control at its Quality Assurance department. In other words, quality improvement at SKF Indonesia has not been done thoroughly. The purpose of this research is to improve quality of outer ring product at SKF Indonesia by conducting an internal grinding process experiment about setting speed ratio, fine position, and spark out grinding time. The specific purpose of this experiment is to optimize some quality responses such as roughness, roundness, and cycle time. All of the response in this experiment were smaller the better. Taguchi method and PCR-TOPSIS are used for the optimization process. The result of this research shows that by using Taguchi method and PCR-TOPSIS, the optimum condition occurs on speed ratio 36, fine position 18 µm/s and spark out 0.5 s. The optimum conditions result were roughness 0.398 µm, roundness 1.78 µm and cycle time 8.1 s. This results have been better than the previous results and meet the standards. The roughness of 0.523 µm decrease to 0.398 µm and the average cycle time of 8.5 s decrease to 8.1 s.

  20. Data on the optimized sulphate electrolyte zinc rich coating produced through in-situ variation of process parameters.

    Science.gov (United States)

    Fayomi, Ojo Sunday Isaac

    2018-02-01

    In this study, a comprehensive effect of particle loading and optimised process parameter on the developed zinc electrolyte was presented. The depositions were performed between 10-30 min at a stirring rate of 200 rpm at room temperature of 30 °C. The effect of coating difference on the properties and interfacial surface was acquired, at a voltage interval between 0.6 and 1.0 V for the coating duration. The framework of bath condition as it influences the coating thickness was put into consideration. Hence, the electrodeposition data for coating thickness, and coating per unit area at constant distance between the anode and cathode with depth of immersion were acquired. The weight gained under varying coating parameter were acquired and could be used for designing and given typical direction to multifunctional performance of developed multifacetal coatings in surface engineering application.

  1. Process Damping Parameters

    International Nuclear Information System (INIS)

    Turner, Sam

    2011-01-01

    The phenomenon of process damping as a stabilising effect in milling has been encountered by machinists since milling and turning began. It is of great importance when milling aerospace alloys where maximum surface speed is limited by excessive tool wear and high speed stability lobes cannot be attained. Much of the established research into regenerative chatter and chatter avoidance has focussed on stability lobe theory with different analytical and time domain models developed to expand on the theory first developed by Trusty and Tobias. Process damping is a stabilising effect that occurs when the surface speed is low relative to the dominant natural frequency of the system and has been less successfully modelled and understood. Process damping is believed to be influenced by the interference of the relief face of the cutting tool with the waveform traced on the cut surface, with material properties and the relief geometry of the tool believed to be key factors governing performance. This study combines experimental trials with Finite Element (FE) simulation in an attempt to identify and understand the key factors influencing process damping performance in titanium milling. Rake angle, relief angle and chip thickness are the variables considered experimentally with the FE study looking at average radial and tangential forces and surface compressive stress. For the experimental study a technique is developed to identify the critical process damping wavelength as a means of measuring process damping performance. For the range of parameters studied, chip thickness is found to be the dominant factor with maximum stable parameters increased by a factor of 17 in the best case. Within the range studied, relief angle was found to have a lesser effect than expected whilst rake angle had an influence.

  2. Optimization of process parameters for the inactivation of Lactobacillus sporogenes in tomato paste with ultrasound and {sup 60}Co-{gamma} irradiation using response surface methodology

    Energy Technology Data Exchange (ETDEWEB)

    Ye Shengying [College of Food Science, South China Agricultural University, Wushan, Guangzhou, GD 510640 (China)], E-mail: yesy@scau.edu.cn; Qiu Yuanxin; Song Xianliang; Luo Shucan [College of Food Science, South China Agricultural University, Wushan, Guangzhou, GD 510640 (China)

    2009-03-15

    The processing parameters for ultrasound and {sup 60}Co-{gamma} irradiation were optimized for their ability to inactivate Lactobacillus sporogenes in tomato paste using a systematic experimental design based on response surface methodology. Ultrasonic power, ultrasonic processing time and irradiation dose were explored and a central composite rotation design was adopted as the experimental plan, and a least-squares regression model was obtained. The significant influential factors for the inactivation rate of L. sporogenes were obtained from the quadratic model and the t-test analyses for each process parameter. Confirmation of the experimental results indicated that the proposed model was reasonably accurate and could be used to describe the efficacy of the treatments for inactivating L. sporogenes within the limits of the factors studied. The optimized processing parameters were found to be an ultrasonic power of 120 W with a processing time of 25 min and an irradiation dose of 6.5 kGy. These were measured under the constraints of parameter limitation, based on the Monte Carlo searching method and the quadratic model of the response surface methodology, including the a/b value of the Hunter color scale of tomato paste. Nevertheless, the ultrasound treatment prior to irradiation for the inactivation of L. sporogenes in tomato paste was unsuitable for reducing the irradiation dose.

  3. Optimization of process parameter and reformer configuration for hydrogen production from steam reforming of heavy hydrocarbons. Paper no. IGEC-1-079

    International Nuclear Information System (INIS)

    Chen, Z.; Elnashaie, S.E.H.

    2005-01-01

    The present optimization investigation is classified into reforming configuration optimization in one hand and parameter optimization of each configuration on the other hand. Heptane is used as a model component for heavy hydrocarbons. The proposed novel reforming process is basically a Circulating Fluidized-Bed Membrane Reformer (CFBMR) with continuous catalyst regeneration and gas-solid separation. Composite hydrogen selective membranes are used for removing the product hydrogen from the reacting gas mixture and therefore driving the reversible reactions beyond their thermodynamic equilibriums. Dense perovskite oxygen selective membranes are also used to introduce oxygen for the exothermic oxidation of hydrocarbons and carbon. Four configurations are investigated, two of them are with the catalyst regeneration before the gas-solid separation and the other two are with the catalyst regeneration after the gas-solid separation. The optimization of the performance of each configuration is carried out for a number of design and operating parameters as optimization parameters and under both non-autothermal and autothermal reforming conditions. Results show that the autothermal operation with direct contact between cold feeds (water and heptane) and hot circulating catalyst can be the best configuration for efficient hydrogen production with minimum energy consumption. The maximum net hydrogen yield is 16.732 moles of hydrogen per mole of heptane fed, which is 76.05% of the maximum theoretical hydrogen yield of 22. (author)

  4. Development of mathematical models and optimization of the process parameters of laser surface hardened EN25 steel using elitist non-dominated sorting genetic algorithm

    Science.gov (United States)

    Vignesh, S.; Dinesh Babu, P.; Surya, G.; Dinesh, S.; Marimuthu, P.

    2018-02-01

    The ultimate goal of all production entities is to select the process parameters that would be of maximum strength, minimum wear and friction. The friction and wear are serious problems in most of the industries which are influenced by the working set of parameters, oxidation characteristics and mechanism involved in formation of wear. The experimental input parameters such as sliding distance, applied load, and temperature are utilized in finding out the optimized solution for achieving the desired output responses such as coefficient of friction, wear rate, and volume loss. The optimization is performed with the help of a novel method, Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) based on an evolutionary algorithm. The regression equations obtained using Response Surface Methodology (RSM) are used in determining the optimum process parameters. Further, the results achieved through desirability approach in RSM are compared with that of the optimized solution obtained through NSGA-II. The results conclude that proposed evolutionary technique is much effective and faster than the desirability approach.

  5. Optimization of process parameters of the activated tungsten inert gas welding for aspect ratio of UNS S32205 duplex stainless steel welds

    Directory of Open Access Journals (Sweden)

    G. Magudeeswaran

    2014-09-01

    Full Text Available The activated TIG (ATIG welding process mainly focuses on increasing the depth of penetration and the reduction in the width of weld bead has not been paid much attention. The shape of a weld in terms of its width-to-depth ratio known as aspect ratio has a marked influence on its solidification cracking tendency. The major influencing ATIG welding parameters, such as electrode gap, travel speed, current and voltage, that aid in controlling the aspect ratio of DSS joints, must be optimized to obtain desirable aspect ratio for DSS joints. Hence in this study, the above parameters of ATIG welding for aspect ratio of ASTM/UNS S32205 DSS welds are optimized by using Taguchi orthogonal array (OA experimental design and other statistical tools such as Analysis of Variance (ANOVA and Pooled ANOVA techniques. The optimum process parameters are found to be 1 mm electrode gap, 130 mm/min travel speed, 140 A current and 12 V voltage. The aspect ratio and the ferrite content for the DSS joints fabricated using the optimized ATIG parameters are found to be well within the acceptable range and there is no macroscopically evident solidification cracking.

  6. Optimization of the reaction parameters of heavy naphtha reforming process using Pt-Re/Al2O3 catalyst system

    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.

  7. In vitro⿿in vivo performance of bare and drug loaded silica gel synthesized via optimized process parameters

    Science.gov (United States)

    Chakraborty, Suparna; Biswas, Supratim

    2016-01-01

    Silica xerogel as a potential drug carrier system for the in vivo as well as in vitro delivery of andrographolide was tested. The present study aims to optimize the effective experimental parameters; volume of ethanol, volume of water and drying temperature by applying response surface methodology coupled with Box⿿Behnken experimental design. The in vitro drug release in simulated body fluid at 37 οC from the selected formulation was significantly highest (44.83 ± 0.9%) among rest of the formulations. Results indicate that sol⿿gel method is useful for entrapping andrographolide in the silica gel and for releasing the same via diffusion through the porous matrix under the in vitro/in vivo conditions. Silica gel exhibited slow matrix degradation as well as sustained release of andrographolide within the experimental time frame of 168 h. In vivo study was performed with three increasing doses [2 mg (S1), 8 mg (S2), and 16 mg (S3)] of silica. Histological fates of different organs were executed with those doses.

  8. Parameter optimization for surface flux transport models

    Science.gov (United States)

    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.

  9. Genetic algorithm based optimization of the process parameters for gas metal arc welding of AISI 904 L stainless steel

    International Nuclear Information System (INIS)

    Sathiya, P.; Ajith, P. M.; Soundararajan, R.

    2013-01-01

    The present study is focused on welding of super austenitic stainless steel sheet using gas metal arc welding process with AISI 904 L super austenitic stainless steel with solid wire of 1.2 mm diameter. Based on the Box - Behnken design technique, the experiments are carried out. The input parameters (gas flow rate, voltage, travel speed and wire feed rate) ranges are selected based on the filler wire thickness and base material thickness and the corresponding output variables such as bead width (BW), bead height (BH) and depth of penetration (DP) are measured using optical microscopy. Based on the experimental data, the mathematical models are developed as per regression analysis using Design Expert 7.1 software. An attempt is made to minimize the bead width and bead height and maximize the depth of penetration using genetic algorithm.

  10. Genetic algorithm based optimization of the process parameters for gas metal arc welding of AISI 904 L stainless steel

    Energy Technology Data Exchange (ETDEWEB)

    Sathiya, P. [National Institute of Technology Tiruchirappalli (India); Ajith, P. M. [Department of Mechanical Engineering Rajiv Gandhi Institute of Technology, Kottayam (India); Soundararajan, R. [Sri Krishna College of Engineering and Technology, Coimbatore (India)

    2013-08-15

    The present study is focused on welding of super austenitic stainless steel sheet using gas metal arc welding process with AISI 904 L super austenitic stainless steel with solid wire of 1.2 mm diameter. Based on the Box - Behnken design technique, the experiments are carried out. The input parameters (gas flow rate, voltage, travel speed and wire feed rate) ranges are selected based on the filler wire thickness and base material thickness and the corresponding output variables such as bead width (BW), bead height (BH) and depth of penetration (DP) are measured using optical microscopy. Based on the experimental data, the mathematical models are developed as per regression analysis using Design Expert 7.1 software. An attempt is made to minimize the bead width and bead height and maximize the depth of penetration using genetic algorithm.

  11. Towards automatic parameter tuning of stream processing systems

    KAUST Repository

    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

  12. Multi-Response Optimization and Regression Analysis of Process Parameters for Wire-EDMed HCHCr Steel Using Taguchi’s Technique

    Directory of Open Access Journals (Sweden)

    K. Srujay Varma

    2017-04-01

    Full Text Available In this study, effect of machining process parameters viz. pulse-on time, pulse-off time, current and servo-voltage for machining High Carbon High Chromium Steel (HCHCr using copper electrode in wire EDM was investigated. High Carbon High Chromium Steel is a difficult to machine alloy, which has many applications in low temperature manufacturing, and copper is chosen as electrode as it has good electrical conductivity and most frequently used electrode all over the world. Tool making culture of copper has made many shops in Europe and Japan to used copper electrode. Experiments were conducted according to Taguchi’s technique by varying the machining process parameters at three levels. Taguchi’s method based on L9 orthogonal array was followed and number of experiments was limited to 9. Experimental cost and time consumption was reduced by following this statistical technique. Targeted output parameters are Material Removal Rate (MRR, Vickers Hardness (HV and Surface Roughness (SR. Analysis of Variance (ANOVA and Regression Analysis was performed using Minitab 17 software to optimize the parameters and draw relationship between input and output process parameters. Regression models were developed relating input and output parameters. It was observed that most influential factor for MRR, Hardness and SR are Ton, Toff and SV.

  13. Taguchi design optimization of machining parameters on the CNC end milling process of halloysite nanotube with aluminium reinforced epoxy matrix (HNT/Al/Ep hybrid composite

    Directory of Open Access Journals (Sweden)

    J.S. Pang

    2014-08-01

    Full Text Available This paper introduces the application of Taguchi optimization methodology in optimizing the cutting parameters of end-milling process for machining the halloysite nanotubes (HNTs with aluminium reinforced epoxy hybrid composite material under dry condition. The machining parameters which are chosen to be evaluated in this study are the depth of cut (d, cutting speed (S and feed rate (f. While, the response factors to be measured are the surface roughness of the machined composite surface and the cutting force. An orthogonal array of the Taguchi method was set-up and used to analyse the effect of the milling parameters on the surface roughness and cutting force. The result from this study shows that the application of the Taguchi method can determine the best combination of machining parameters that can provide the optimal machining response conditions which are the lowest surface roughness and lowest cutting force value. For the best surface finish, A1–B3–C3 (d = 0.4 mm, S = 1500 rpm, f = 60 mmpm is found to be the optimized combination of levels for all the three control factors from the analysis. Meanwhile, the optimized combination of levels for all the three control factors from the analysis which provides the lowest cutting force was found to be A2–B2–C2 (d = 0.6 mm, S = 1000 rpm, f = 40 mmpm.

  14. Optimization the machining parameters by using VIKOR and Entropy Weight method during EDM process of Al–18% SiCp Metal matrix composit

    Directory of Open Access Journals (Sweden)

    Rajesh Kumar Bhuyan

    2016-06-01

    Full Text Available The objective of this paper is to optimize the process parameters by combined approach of VIKOR and Entropy weight measurement method during Electrical discharge machining (EDM process of Al-18wt.%SiCp metal matrix composite (MMC. The central composite design (CCD method is considered to evaluate the effect of three process parameters; namely pulse on time (Ton, peak current (Ip and flushing pressure (Fp on the responses like material removal rate (MRR, tool wear rate (TWR, Radial over cut (ROC and surface roughness (Ra. The Entropy weight measurement method evaluates the individual weights of each response and, using VIKOR method, the multi-objective responses are optimized to get a single numerical index known as VIKOR Index. Then the Analysis of Variance (ANOVA technique is used to determine the significance of the process parameters on the VIKOR Index. Finally, the result of the VIKOR Indexed is validated by conformation test using the liner mathematical model equation develop by responses surface methodology to identify the effectiveness of the proposed method.

  15. Machinability study of Carbon Fiber Reinforced Polymer in the longitudinal and transverse direction and optimization of process parameters using PSO–GSA

    Directory of Open Access Journals (Sweden)

    K. Shunmugesh

    2016-09-01

    Full Text Available Carbon Fiber Reinforced Polymer (CFRP composites are widely used in aerospace industry in lieu of its high strength to weight ratio. This study is an attempt to evaluate the machinability of Bi-Directional Carbon Fiber–Epoxy composite and optimize the process parameters of cutting speed, feed rate and drill tool material. Machining trials were carried using drill bits made of high speed steel, TiN and TiAlN at different cutting speeds and feed rates. Output parameters of thrust force and torque were monitored using Kistler multicomponent dynamometer 9257B and vibrations occurring during machining normal to the work surface were measured by a vibration sensor (Dytran 3055B. Linear regression analysis was carried out by using Response Surface Methodology (RSM, to correlate the input and output parameters in drilling of the composite in the longitudinal and transverse directions. The optimization of process parameters were attempted using Genetic Algorithm (GA and Particle Swarm Optimization–Gravitational Search Algorithm (PSO–GSA techniques.

  16. Solar degradation of diclofenac using Eosin-Y-activated TiO2: cost estimation, process optimization and parameter interaction study.

    Science.gov (United States)

    Hashim, Noshin; Thakur, Shaila; Patang, Mouska; Crapulli, Ferdinando; Ray, Ajay K

    2017-04-01

    Diclofenac (DCF), a widely used non-steroidal anti-inflammatory drug, is a commonly detected substance that readily accumulates in tissues of aquatic fish and poses a threat to wildlife and freshwater quality. Advanced Oxidation Processes have been employed as an alternative due to the inadequacy of conventional treatment methods of trace contaminants. This study utilized an innovative method of solar-activation of TiO 2 using Eosin-Y dye for the degradation of DCF. Furthermore, the study incorporated a central composite design (CCD) to optimize the dye concentration and estimated the cost for the present process. Optimized parameters for light intensity (750 mW/cm 2 ), Eosin-Y dye concentration (2 mg/L), TiO 2 loading (37.5 mg/cm 2 ) and DCF concentration (25 mg/L) were determined through a CCD. The optimized parameters convey a DCF degradation rate of 40% and 49% for 2 ppm (low range) and 4 ppm (high range) dye concentrations, respectively, for a 5-minute reaction time. Cost estimation for the materials used was for the current process was also performed. It was determined that the additional cost of using 4 ppm instead of 2 ppm to achieve only 10% more DCF degradation is not warranted and would require additional treatment to remove subsequently formed halogenated compounds.

  17. 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.

  18. Optimal design for laser beam butt welding process parameter using artificial neural networks and genetic algorithm for super austenitic stainless steel

    Science.gov (United States)

    Sathiya, P.; Panneerselvam, K.; Soundararajan, R.

    2012-09-01

    Laser welding input parameters play a very significant role in determining the quality of a weld joint. The joint quality can be defined in terms of properties such as weld bead geometry, mechanical properties and distortion. Therefore, mechanical properties should be controlled to obtain good welded joints. In this study, the weld bead geometry such as depth of penetration (DP), bead width (BW) and tensile strength (TS) of the laser welded butt joints made of AISI 904L super austenitic stainless steel were investigated. Full factorial design was used to carry out the experimental design. Artificial Neural networks (ANN) program was developed in MatLab software to establish the relationships between the laser welding input parameters like beam power, travel speed and focal position and the three responses DP, BW and TS in three different shielding gases (Argon, Helium and Nitrogen). The established models were used for optimizing the process parameters using Genetic Algorithm (GA). Optimum solutions for the three different gases and their respective responses were obtained. Confirmation experiment has also been conducted to validate the optimized parameters obtained from GA.

  19. 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.

  20. Influence of Optimization of Process Parameters on Threshold Voltage for Development of HfO2/TiSi2 18 nm PMOS

    Directory of Open Access Journals (Sweden)

    Atan N.

    2016-01-01

    Full Text Available Manufacturing a 18-nm transistor requires a variety of parameters, materials, temperatures, and methods. In this research, HfO2 was used as the gate dielectric ad TiO2 was used as the gate material. The transistor HfO2/TiSi2 18-nm PMOS was invented using SILVACO TCAD. Ion implantation was adopted in the fabrication process for the method’s practicality and ability to be used to suppress short channel effects. The study involved ion implantation methods: compensation implantation, halo implantation energy, halo tilt, and source–drain implantation. Taguchi method is the best optimization process for a threshold voltage of HfO2/TiSi2 18-nm PMOS. In this case, the method adopted was Taguchi orthogonal array L9. The process parameters (ion implantations and noise factors were evaluated by examining the Taguchi’s signal-to-noise ratio (SNR and nominal-the-best for the threshold voltage (VTH. After optimization, the result showed that the VTH value of the 18-nm PMOS device was -0.291339.

  1. Optimization of friction stir welding process parameters to maximize tensile strength of stir cast AA6061-T6/AlNp composite

    International Nuclear Information System (INIS)

    Ashok Kumar, B.; Murugan, N.

    2014-01-01

    Highlights: • AA6061/AlN p cast composite was welded by FSW process. • Regression models were developed to predict UTS and elongation of the FS welded joint. • FS welded joint using the optimized parameters exhibited maximum UTS and joint efficiency. • Defect free weld joint was obtained with optimized parameters value. - Abstract: Aluminium Matrix Composites (AMCs) reinforced with particulate form of reinforcement has replaced monolithic alloys in many engineering industries due to its superior mechanical properties and tailorable thermal and electrical properties. As aluminium nitride (AlN) has high specific strength, high thermal conductivity, high electrical resistivity, low dielectric constant, low coefficient of thermal expansion and good compatibility with aluminium alloy, Al/AlN composite is extensively used in electronic packaging industries. Joining of AMCs is unavoidable in many engineering applications. Friction Stir Welding (FSW) is one of the most suitable welding process to weld the AMCs reinforced with particulate form of ceramics without deteriorating its superior mechanical properties. An attempt has been made to develop regression models to predict the Ultimate Tensile Strength (UTS) and Percent Elongation (PE) of the friction stir welded AA6061 matrix composite reinforced with aluminium nitride particles (AlN p ) by correlating the significant parameters such as tool rotational speed, welding speed, axial force and percentage of AlN p reinforcement in the AA6061 matrix. Statistical software SYSTAT 12 and statistical tools such as analysis of variance (ANOVA) and student’s t test, have been used to validate the developed models. It was observed from the investigation that these factors independently influenced the UTS and PE of the friction stir welded composite joints. The developed regression models were optimized to maximize UTS of friction stir welded AA6061/AlN p composite joints

  2. Application of processing maps in the optimization of the parameters of a hot working process. Part 2. Processing maps of a microalloyed medium carbon steel

    International Nuclear Information System (INIS)

    Al Omar, A.; Cabrera, J.M.; Prado, J.M.

    1997-01-01

    Part 1 of this work presents a revision of the general characteristics of the so called dynamic materials model on which processing maps are developed. In this part following the methodology described in part 1, processing maps of a microalloyed medium carbon steel are developed over a temperature range varying from 900 to 1.150 degree centigree at different true strain rates ranging from 10''-4 to 10s''-1. The analysis of these maps revealed a domain of dynamic recrystallization centred at about 1.1.50 degree centigree and strain rate 10 s''-1 and a domain of dynamic recovery centred at 900 degree centigree and 0,1 s''-1. (Author) 20 refs

  3. Optimization of Tape Winding Process Parameters to Enhance the Performance of Solid Rocket Nozzle Throat Back Up Liners using Taguchi's Robust Design Methodology

    Science.gov (United States)

    Nath, Nayani Kishore

    2017-08-01

    The throat back up liners is used to protect the nozzle structural members from the severe thermal environment in solid rocket nozzles. The throat back up liners is made with E-glass phenolic prepregs by tape winding process. The objective of this work is to demonstrate the optimization of process parameters of tape winding process to achieve better insulative resistance using Taguchi's robust design methodology. In this method four control factors machine speed, roller pressure, tape tension, tape temperature that were investigated for the tape winding process. The presented work was to study the cogency and acceptability of Taguchi's methodology in manufacturing of throat back up liners. The quality characteristic identified was Back wall temperature. Experiments carried out using L 9 ' (34) orthogonal array with three levels of four different control factors. The test results were analyzed using smaller the better criteria for Signal to Noise ratio in order to optimize the process. The experimental results were analyzed conformed and successfully used to achieve the minimum back wall temperature of the throat back up liners. The enhancement in performance of the throat back up liners was observed by carrying out the oxy-acetylene tests. The influence of back wall temperature on the performance of throat back up liners was verified by ground firing test.

  4. Optimization of process parameters for ethanol production from sugar cane molasses by Zymomonas mobilis using response surface methodology and genetic algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Maiti, Bodhisatta; Shekhawat, Mitali; Srivastava, Pradeep [Banaras Hindu Univ., Varanasi (India). School of Biochemical Engineering; Rathore, Ankita [Nizam College, Hyderabad (India). Dept. of Biotechnology; Srivastava, Saurav [National Institute of Technology, Durgapur (India). Dept. of Biotechnology

    2011-04-15

    Ethanol is a potential energy source and its production from renewable biomass has gained lot of popularity. There has been worldwide research to produce ethanol from regional inexpensive substrates. The present study deals with the optimization of process parameters (viz. temperature, pH, initial total reducing sugar (TRS) concentration in sugar cane molasses and fermentation time) for ethanol production from sugar cane molasses by Zymomonas mobilis using Box-Behnken experimental design and genetic algorithm (GA). An empirical model was developed through response surface methodology to analyze the effects of the process parameters on ethanol production. The data obtained after performing the experiments based on statistical design was utilized for regression analysis and analysis of variance studies. The regression equation obtained after regression analysis was used as a fitness function for the genetic algorithm. The GA optimization technique predicted a maximum ethanol yield of 59.59 g/L at temperature 31 C, pH 5.13, initial TRS concentration 216 g/L and fermentation time 44 h. The maximum experimental ethanol yield obtained after applying GA was 58.4 g/L, which was in close agreement with the predicted value. (orig.)

  5. Optimization of Laser Transmission Joining Process Parameters on Joint Strength of PET and 316 L Stainless Steel Joint Using Response Surface Methodology

    Directory of Open Access Journals (Sweden)

    Shashi Prakash Dwivedi

    2014-01-01

    Full Text Available The objective of the present work is to study the effects of laser power, joining speed, and stand-off distance on the joint strength of PET and 316 L stainless steel joint. The process parameters were optimized using response methodology for achieving good joint strength. The central composite design (CCD has been utilized to plan the experiments and response surface methodology (RSM is employed to develop mathematical model between laser transmission joining parameters and desired response (joint strength. From the ANOVA (analysis of variance, it was concluded that laser power is contributing more and it is followed by joining speed and stand-off distance. In the range of process parameters, the result shows that laser power increases and joint strength increases. Whereas joining speed increases, joint strength increases. The joint strength increases with the increase of the stand-off distance until it reaches the center value; the joint strength then starts to decrease with the increase of stand-off distance beyond the center limit. Optimum values of laser power, joining speed, and stand-off distance were found to be 18 watt, 100 mm/min, and 2 mm to get the maximum joint strength (predicted: 88.48 MPa. There was approximately 3.37% error in the experimental and modeled results of joint strength.

  6. Development of an in-situ multi-component reinforced Al-based metal matrix composite by direct metal laser sintering technique — Optimization of process parameters

    Energy Technology Data Exchange (ETDEWEB)

    Ghosh, Subrata Kumar, E-mail: subratagh82@gmail.com [Department of Mechanical Engineering, National Institute of Technology Agartala, Tripura 799055 (India); Bandyopadhyay, Kaushik; Saha, Partha [Department of Mechanical Engineering, Indian Institute of Technology Kharagpur, Kharagpur 721302 (India)

    2014-07-01

    In the present investigation, an in-situ multi-component reinforced aluminum based metal matrix composite was fabricated by the combination of self-propagating high-temperature synthesis and direct metal laser sintering process. The different mixtures of Al, TiO{sub 2} and B{sub 4}C powders were used to initiate and maintain the self-propagating high-temperature synthesis by laser during the sintering process. It was found from the X-ray diffraction analysis and scanning electron microscopy that the reinforcements like Al{sub 2}O{sub 3}, TiC, and TiB{sub 2} were formed in the composite. The scanning electron microscopy revealed the distribution of the reinforcement phases in the composite and phase identities. The variable parameters such as powder layer thickness, laser power, scanning speed, hatching distance and composition of the powder mixture were optimized for higher density, lower porosity and higher microhardness using Taguchi method. Experimental investigation shows that the density of the specimen mainly depends upon the hatching distance, composition and layer thickness. On the other hand, hatching distance, layer thickness and laser power are the significant parameters which influence the porosity. The composition, laser power and layer thickness are the key influencing parameters for microhardness. - Highlights: • The reinforcements such as Al{sub 2}O{sub 3}, TiC, and TiB{sub 2} were produced in Al-MMC through SHS. • The density is mainly influenced by the material composition and hatching distance. • Hatching distance is the major influencing parameter on porosity. • The material composition is the significant parameter to enhance the microhardness. • The SEM micrographs reveal the distribution of TiC, TiB{sub 2} and Al{sub 2}O{sub 3} in the composite.

  7. Development of an in-situ multi-component reinforced Al-based metal matrix composite by direct metal laser sintering technique — Optimization of process parameters

    International Nuclear Information System (INIS)

    Ghosh, Subrata Kumar; Bandyopadhyay, Kaushik; Saha, Partha

    2014-01-01

    In the present investigation, an in-situ multi-component reinforced aluminum based metal matrix composite was fabricated by the combination of self-propagating high-temperature synthesis and direct metal laser sintering process. The different mixtures of Al, TiO 2 and B 4 C powders were used to initiate and maintain the self-propagating high-temperature synthesis by laser during the sintering process. It was found from the X-ray diffraction analysis and scanning electron microscopy that the reinforcements like Al 2 O 3 , TiC, and TiB 2 were formed in the composite. The scanning electron microscopy revealed the distribution of the reinforcement phases in the composite and phase identities. The variable parameters such as powder layer thickness, laser power, scanning speed, hatching distance and composition of the powder mixture were optimized for higher density, lower porosity and higher microhardness using Taguchi method. Experimental investigation shows that the density of the specimen mainly depends upon the hatching distance, composition and layer thickness. On the other hand, hatching distance, layer thickness and laser power are the significant parameters which influence the porosity. The composition, laser power and layer thickness are the key influencing parameters for microhardness. - Highlights: • The reinforcements such as Al 2 O 3 , TiC, and TiB 2 were produced in Al-MMC through SHS. • The density is mainly influenced by the material composition and hatching distance. • Hatching distance is the major influencing parameter on porosity. • The material composition is the significant parameter to enhance the microhardness. • The SEM micrographs reveal the distribution of TiC, TiB 2 and Al 2 O 3 in the composite

  8. Microstructure and tensile properties of Ti-6Al-4V alloys manufactured by selective laser melting with optimized processing parameters

    Science.gov (United States)

    Wang, L.; Ma, C.; Huang, J.; Ding, H. Y.; Chu, M. Q.

    2017-11-01

    Selective laser melting (SLM) is a precise additive manufacturing process that the metallic powders without binder are melted layer by layer to complex components using a high bright fiber laser. In the paper, Ti-6Al-4V alloy was fabricated by SLM and its microstructure and mechanical properties were investigated in order to evaluate the SLM process. The results show that the microstructure exists anisotropy between the horizontal and vertical section due to the occurrence of epitaxial growth, and the former microstructure seems equal-axis and the latter is column. Moreover, there is little difference in tensile test between the horizontal and vertical sections. Furthermore, the tensile properties of fabricated Ti-6Al-4V alloy by SLM are higher than the forged standard ones. However, the fatigue results show that there are some scatters, which need further investigation to define the fatigue initiation.

  9. 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 ...

  10. Improved Detection and Mapping of Deepwater Hydrocarbon Seeps: Optimizing Acquisition and Processing Parameters for Marine Seep Hunting

    Science.gov (United States)

    Mitchell, G. A.; Orange, D.; Gharib, J. J.; Saade, E. J.; Joye, S. B.

    2016-12-01

    Mexico and Caribbean Sea. Our study shows that a comprehensive multibeam calibration involving bathymetric difference grids, a seafloor backscatter intensity normalization, a 2X acquisition survey technique, and processing with multiple processing packages can improve resolvability of seep features and interpretation.

  11. Statistical optimization of process parameters for the simultaneous adsorption of Cr(VI) and phenol onto Fe-treated tea waste biomass

    Science.gov (United States)

    Gupta, Ankur; Balomajumder, Chandrajit

    2017-12-01

    In this study, simultaneous removal of Cr(VI) and phenol from binary solution was carried out using Fe-treated tea waste biomass. The effect of process parameters such as adsorbent dose, pH, initial concentration of Cr(VI) (mg/L), and initial concentration of phenol (mg/L) was optimized. The analysis of variance of the quadratic model demonstrates that the experimental results are in good agreement with the predicted values. Based on experimental design at an initial concentration of 55 mg/L of Cr(VI), 27.50 mg/L of phenol, pH 2.0, 15 g/L adsorbent dose, 99.99% removal of Cr(VI), and phenol was achieved.

  12. Critical tuning of magnetron sputtering process parameters for optimized solar selective absorption of NiCrO{sub x} cermet coatings on aluminium substrate

    Energy Technology Data Exchange (ETDEWEB)

    Gaouyat, Lucie, E-mail: lucie.gaouyat@fundp.ac.be [Solid State Physics Laboratory, Research Center in Physics of Matter and Radiation (PMR), Facultés Universitaires Notre-Dame de la Paix (FUNDP), 61 rue de Bruxelles, B-5000 Namur (Belgium); Mirabella, Frédéric [CRM Group – AC and CS, 57b boulevard de Colonster, B-4000 Liège (Belgium); Deparis, Olivier [Solid State Physics Laboratory, Research Center in Physics of Matter and Radiation (PMR), Facultés Universitaires Notre-Dame de la Paix (FUNDP), 61 rue de Bruxelles, B-5000 Namur (Belgium)

    2013-04-15

    NiCrO{sub x} ceramic–metal composites (i.e. cermets) exhibit not only oxidation and moisture resistances, which are very important for industrial applications, but also remarkable solar selective absorption properties. In order to reach the best optical performances with only one coating layer, tuning of the magnetron sputtering process parameters (O{sub 2} flow rate, pressure and deposition time) was performed systematically. The process window turned out to be very narrow implying a critical tuning of the parameters. The optimal operating point was determined for a single layer coating of NiCrO{sub x} on an aluminium substrate, leading to a spectrally integrated solar absorption as high as 78%. Among various material properties, the focus was put on the optical reflectance of the coating/substrate system, which was measured by UV–vis–NIR spectrophotometry. Using complex refractive index data from the literature, the theoretical reflectance spectra were calculated and found to be in good agreement with the measurements. Chemical analysis combined with scanning electronic and atomic force microscopies suggested a cermet structure consisting of metallic Ni particles and a compound matrix made of a mixture of chromium oxide, nickel oxide and nickel hydroxide.

  13. Evaluation of 2,4-D removal via activated carbon from pomegranate husk/polymer composite hydrogel: Optimization of process parameters through face centered composite design

    International Nuclear Information System (INIS)

    Taktak, Fulya; Ilbay, Zeynep; Sahin, Selin

    2015-01-01

    A new type of polymer composite hydrogel was prepared by introducing activated carbons from pomegranate husk into poly ((2-dimethylamino) ethyl methacrylate) network. The removal of 2,4-dichlorophenoxyacetic acid (2,4-D) from aqueous solution was studied with respect to pH of the media, initial 2,4-D concentration and activated carbon content into the polymeric network. Face centered composite design (FCCD) through response surface methodology (RSM) was used for designing the experiments as well as for studying the effects of the process parameters. A quadratic model and a two factor interaction design model were developed for the removal of 2,4-D and adsorption capacity, respectively. The optimum pH of the pesticide solution, activated carbon content into the polymeric network and initial concentration of 2,4-D were found as 3, 2.5 wt% and 100mg/L. 63.245% and 68.805 (mg/g) for the removal of 2,4-D and adsorption capacity were obtained by using Simplex optimization method. Furthermore, the surface characteristics of the adsorbent prepared under optimized conditions were examined by scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FT-IR).

  14. Evaluation of 2,4-D removal via activated carbon from pomegranate husk/polymer composite hydrogel: Optimization of process parameters through face centered composite design

    Energy Technology Data Exchange (ETDEWEB)

    Taktak, Fulya; Ilbay, Zeynep [Usak Univ, Usak (Turkmenistan); Sahin, Selin [Istanbul University, Istanbul (Turkmenistan)

    2015-09-15

    A new type of polymer composite hydrogel was prepared by introducing activated carbons from pomegranate husk into poly ((2-dimethylamino) ethyl methacrylate) network. The removal of 2,4-dichlorophenoxyacetic acid (2,4-D) from aqueous solution was studied with respect to pH of the media, initial 2,4-D concentration and activated carbon content into the polymeric network. Face centered composite design (FCCD) through response surface methodology (RSM) was used for designing the experiments as well as for studying the effects of the process parameters. A quadratic model and a two factor interaction design model were developed for the removal of 2,4-D and adsorption capacity, respectively. The optimum pH of the pesticide solution, activated carbon content into the polymeric network and initial concentration of 2,4-D were found as 3, 2.5 wt% and 100mg/L. 63.245% and 68.805 (mg/g) for the removal of 2,4-D and adsorption capacity were obtained by using Simplex optimization method. Furthermore, the surface characteristics of the adsorbent prepared under optimized conditions were examined by scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FT-IR).

  15. Optimal Laser Phototherapy Parameters for Pain Relief.

    Science.gov (United States)

    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.

  16. Optimization of surface roughness parameters in dry turning

    OpenAIRE

    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...

  17. Optimal design criteria - prediction vs. parameter estimation

    Science.gov (United States)

    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.

  18. Cosmological parameter estimation using Particle Swarm Optimization

    Science.gov (United States)

    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.

  19. 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

  20. Same-vessel enzymatic saccharification and fermentation of organosolv/H2O2 pretreated oil palm (Elaeis guineensis Jacq.) fronds for bioethanol production: Optimization of process parameters

    International Nuclear Information System (INIS)

    Ofori-Boateng, Cynthia; Lee, Keat Teong

    2014-01-01

    Highlights: • Same vessel enzymatic saccharification and fermentation (SVSF) of pretreated OPFs. • Optimum conditions:37 °C, 8.0% solid loading, 14.0 g/l yeast concentration, pH 5.3. • Optimum bioethanol concentration and yield of 21.96 g/l and 84.65% respectively. • Organosolv/H 2 O 2 pretreatment of OPFs improved SVSF yield at high solid loading. - Abstract: Based on optimized pretreatment process, oil palm fronds (OPFs) were sequentially pretreated with 1.4% (w/v) aq. NaOH in 80% ethanol with ultrasound assistance (at 75 °C for 30 min) and 3% (v/v) aq. H 2 O 2 . Using the Box–Behnken design (BBD) of response surface methodology (RSM), bioethanol production from the sono-assisted organosolv/H 2 O 2 OPFs were optimized using same-vessel enzymatic saccharification and fermentation (SVSF) where both the hydrolysis and fermentation processes were carried out in one vessel simultaneously. Throughout the SVSF process, the incubation time and enzyme loading were kept at 72 h and 15 filter paper unit (FPU)/g substrate respectively. The other SVSF parameters which affect bioethanol yield such as temperature (X 1 : 30–50 °C), solid loading (X 2 : 5.0–10.0% w/v), yeast concentration (X 3 : 5.0–20 g/l) and pH (X 4 : 4.0–7.0) were optimized. Well fitted regression equations (R 2 > 0.97) obtained were able to predict reliable optimum bioethanol concentration and yield. The predicted optimum bioethanol concentration (i.e., 20.61 g/l) and yield (i.e., 84.60%) were attained at 36.94 °C (∼37 °C), 7.57% w/v solid loading (∼8.0% w/v), 13.97 g/l yeast concentration (∼14.0 g/l) and pH of 5.29 (∼5.30). Validated results indicated a maximum ethanol concentration and yield of 21.96 g/l and 84.65% respectively, which were closer to the predicted optimum responses. Using the optimum conditions, the highest bioethanol productivity of 0.76 g/l/h was observed at 12 h of SVSF process

  1. 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.

  2. Optimization of process parameters and catalyst compositions in carbon dioxide oxidative coupling of methane over CaO-MnO/CeO{sub 2} catalyst using response surface methodology

    Energy Technology Data Exchange (ETDEWEB)

    Istadi,; Amin, Nor Aishah Saidina [Chemical Reaction Engineering Group (CREG), Faculty of Chemical and Natural Resources Engineering, Universiti Teknologi Malaysia, UTM Skudai, Johor Bahru (81310 Malaysia)

    2006-05-15

    The optimization of process parameters and catalyst compositions for the CO{sub 2} oxidative coupling of methane (CO{sub 2}-OCM) reaction over CaO-MnO/CeO{sub 2} catalyst was developed using Response Surface Methodology (RSM). The relationship between the responses, i.e. CH{sub 4} conversion, C{sub 2} hydrocarbons selectivity or yield, with four independent variables, i.e. CO{sub 2}/CH{sub 4} ratio, reactor temperature, wt.% CaO and wt.% MnO in the catalyst, were presented as empirical mathematical models. The maximum C{sub 2} hydrocarbons selectivity and yields of 82.62% and 3.93%, respectively, were achieved by the individual-response optimization at the corresponding optimal process parameters and catalyst compositions. However, the CH{sub 4} conversion was a saddle function and did not show a unique optimum as revealed by the canonical analysis. Moreover pertaining to simultaneous multi-responses optimization, the maximum C{sub 2} selectivity and yield of 76.56% and 3.74%, respectively, were obtained at a unique optimal process parameters and catalyst compositions. It may be deduced that both individual- and multi-responses optimizations are useful for the recommendation of optimal process parameters and catalyst compositions for the CO{sub 2}-OCM process. (author)

  3. Optimal parameters uncoupling vibration modes of oscillators

    Science.gov (United States)

    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.

  4. 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 ...

  5. Mixed integer evolution strategies for parameter optimization.

    Science.gov (United States)

    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.

  6. Short-Term Wind Speed Forecasting Using the Data Processing Approach and the Support Vector Machine Model Optimized by the Improved Cuckoo Search Parameter Estimation Algorithm

    Directory of Open Access Journals (Sweden)

    Chen Wang

    2016-01-01

    Full Text Available Power systems could be at risk when the power-grid collapse accident occurs. As a clean and renewable resource, wind energy plays an increasingly vital role in reducing air pollution and wind power generation becomes an important way to produce electrical power. Therefore, accurate wind power and wind speed forecasting are in need. In this research, a novel short-term wind speed forecasting portfolio has been proposed using the following three procedures: (I data preprocessing: apart from the regular normalization preprocessing, the data are preprocessed through empirical model decomposition (EMD, which reduces the effect of noise on the wind speed data; (II artificially intelligent parameter optimization introduction: the unknown parameters in the support vector machine (SVM model are optimized by the cuckoo search (CS algorithm; (III parameter optimization approach modification: an improved parameter optimization approach, called the SDCS model, based on the CS algorithm and the steepest descent (SD method is proposed. The comparison results show that the simple and effective portfolio EMD-SDCS-SVM produces promising predictions and has better performance than the individual forecasting components, with very small root mean squared errors and mean absolute percentage errors.

  7. Optimization of process parameters for the production of collagen peptides from fish skin (Epinephelus malabaricus) using response surface methodology and its characterization.

    Science.gov (United States)

    Hema, G S; Joshy, C G; Shyni, K; Chatterjee, Niladri S; Ninan, George; Mathew, Suseela

    2017-02-01

    The study optimized the hydrolysis conditions for the production of fish collagen peptides from skin of Malabar grouper ( Epinephelus malabaricus ) using response surface methodology. The hydrolysis was done with enzymes pepsin, papain and protease from bovine pancreas. Effects of process parameters viz: pH, temperature, enzyme substrate ratio and hydrolysis time of the three different enzymes on degree of hydrolysis were investigated. The optimum response of degree of hydrolysis was estimated to be 10, 20 and 28% respectively for pepsin, papain and protease. The functional properties of the product developed were analysed which showed changes in the properties from proteins to peptides. SDS-PAGE combined with MALDI TOF method was successfully applied to determine the molecular weight distribution of the hydrolysate. The electrophoretic pattern indicated that the molecular weights of peptides formed due to hydrolysis were nearly 2 kDa. MALDI TOF spectral analysis showed the developed hydrolysate contains peptides having molecular weight in the range below 2 kDa.

  8. Genetic Algorithm Optimizes Q-LAW Control Parameters

    Science.gov (United States)

    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.

  9. An optimal generic model for multi-parameters and big data optimizing: a laboratory experimental study

    Science.gov (United States)

    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.

  10. Cosmological parameter estimation using particle swarm optimization

    Science.gov (United States)

    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.

  11. Hydrothermal Conversion of Giant Reed to Furfural and Levulinic Acid: Optimization of the Process under Microwave Irradiation and Investigation of Distinctive Agronomic Parameters

    Directory of Open Access Journals (Sweden)

    Claudia Antonetti

    2015-11-01

    Full Text Available The hydrothermal conversion of giant reed (Arundo donax L. to furfural (FA and levulinic acid (LA was investigated in the presence of dilute hydrochloric acid. FA and LA yields were improved by univariate optimization of the main reaction parameters: concentration of the acid catalyst, solid/liquid ratio of the reaction mixture, hydrolysis temperature, and reaction time. The catalytic performances were investigated adopting the efficient microwave (MW irradiation, allowing significant energy and time savings. The best FA and LA yields were further confirmed using a traditionally heated autoclave reactor, giving very high results, when compared with the literature. Hydrolysis temperature and time were the main reaction variables to be carefully optimized: FA formation needed milder reaction conditions, while LA more severe ones. The effect of the crop management (e.g., harvest time on FA/LA production was discussed, revealing that harvest time was not a discriminating parameter for the further optimization of both FA and LA production, due to the very high productivity of the giant reed throughout the year. The promising results demonstrate that giant reed represents a very interesting candidate for a very high contemporary production of FA and LA of up to about 70% and 90% of the theoretical yields, respectively.

  12. 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

  13. 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

  14. Optimization of bead milling parameters for the cell disruption of microalgae: process modeling and application to Porphyridium cruentum and Nannochloropsis oculata.

    Science.gov (United States)

    Montalescot, V; Rinaldi, T; Touchard, R; Jubeau, S; Frappart, M; Jaouen, P; Bourseau, P; Marchal, L

    2015-11-01

    A study of cell disruption by bead milling for two microalgae, Nannochloropsis oculata and Porphyridium cruentum, was performed. Strains robustness was quantified by high-pressure disruption assays. The hydrodynamics in the bead mill grinding chamber was studied by Residence Time Distribution modeling. Operating parameters effects were analyzed and modeled in terms of stress intensities and stress number. RTD corresponded to a 2 CSTR in series model. First order kinetics cell disruption was modeled in consequence. Continuous bead milling was efficient for both strains disruption. SI-SN modeling was successfully adapted to microalgae. As predicted by high pressure assays, N. oculata was more resistant than P. cruentum. The critical stress intensity was twice more important for N. oculata than for P. cruentum. SI-SN modeling allows the determination of operating parameters minimizing energy consumption and gives a scalable approach to develop and optimize microalgal disruption by bead milling. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. Optimization of the parameter calculation the process of production historic by using Parallel Virtual Machine-PVM; Otimizacao do calculo de parametros no processo de ajuste de historicos de producao usando PVM

    Energy Technology Data Exchange (ETDEWEB)

    Vargas Cuervo, Carlos Hernan

    1997-03-01

    The main objective of this work is to develop a methodology to optimize the simultaneous computation of two parameters in the process of production history matching. This work describes a procedure to minimize an objective function established to find the values of the parameters which are modified in the process. The parameters are chosen after a sensibility analysis. Two optimization methods are tested: a Region Search Method (MBR) and Polytope Method. Both are based in direct search methods which do not require the function derivative. The software PVM (Parallel Virtual Machine) is used to parallelize the simulation runs, allowing the acceleration of the process and the search of multiple solutions. The validation of the methodology is applied to two reservoir models: one homogeneous and other heterogeneous. The advantages of each method and of the parallelization are also present. (author)

  16. Optimization of pulsed laser welding process parameters in order to attain minimum underfill and undercut defects in thin 316L stainless steel foils

    Science.gov (United States)

    Pakmanesh, M. R.; Shamanian, M.

    2018-02-01

    In this study, the optimization of pulsed Nd:YAG laser welding parameters was done on the lap-joint of a 316L stainless steel foil with the aim of reducing weld defects through response surface methodology. For this purpose, the effects of peak power, pulse-duration, and frequency were investigated. The most important weld defects seen in this method include underfill and undercut. By presenting a second-order polynomial, the above-mentioned statistical method was managed to be well employed to balance the welding parameters. The results showed that underfill increased with the increased power and reduced frequency, it first increased and then decreased with the increased pulse-duration; and the most important parameter affecting it was the power, whose effect was 65%. The undercut increased with the increased power, pulse-duration, and frequency; and the most important parameter affecting it was the power, whose effect was 64%. Finally, by superimposing different responses, improved conditions were presented to attain a weld with no defects.

  17. Estimating cellular parameters through optimization procedures: elementary principles and applications

    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.

  18. 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

  19. Optimization of pulsed current GTAW process parameters for sintered hot forged AISI 4135 P/M steel welds by simulated annealing and genetic algorithm

    International Nuclear Information System (INIS)

    Joseph, Joby; Muthukumaran, S.

    2016-01-01

    Abundant improvements have occurred in materials handling, especially in metal joining. Pulsed current gas tungsten arc welding (PCGTAW) is one of the consequential fusion techniques. In this work, PCGTAW of AISI 4135 steel engendered through powder metallurgy (P/M) has been executed, and the process parameters have been highlighted applying Taguchi's L9 orthogonal array. The results show that the peak current (Ip), gas flow rate (GFR), welding speed (WS) and base current (Ib) are the critical constraints in strong determinant of the Tensile strength (TS) as well as percentage of elongation (% Elong) of the joint. The practical impact of applying Genetic algorithm (GA) and Simulated annealing (SA) to PCGTAW process has been authenticated by means of calculating the deviation between predicted and experimental welding process parameters

  20. Optimization of pulsed current GTAW process parameters for sintered hot forged AISI 4135 P/M steel welds by simulated annealing and genetic algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Joseph, Joby; Muthukumaran, S. [National Institute of Technology, Tamil Nadu (India)

    2016-01-15

    Abundant improvements have occurred in materials handling, especially in metal joining. Pulsed current gas tungsten arc welding (PCGTAW) is one of the consequential fusion techniques. In this work, PCGTAW of AISI 4135 steel engendered through powder metallurgy (P/M) has been executed, and the process parameters have been highlighted applying Taguchi's L9 orthogonal array. The results show that the peak current (Ip), gas flow rate (GFR), welding speed (WS) and base current (Ib) are the critical constraints in strong determinant of the Tensile strength (TS) as well as percentage of elongation (% Elong) of the joint. The practical impact of applying Genetic algorithm (GA) and Simulated annealing (SA) to PCGTAW process has been authenticated by means of calculating the deviation between predicted and experimental welding process parameters.

  1. Optimization of input parameters of supra-threshold stochastic resonance image processing algorithm for the detection of abdomino-pelvic tumors on PET/CT scan

    International Nuclear Information System (INIS)

    Pandey, Anil Kumar; Saroha, Kartik; Patel, C.D.; Bal, C.S.; Kumar, Rakesh

    2016-01-01

    Administration of diuretics increases the urine output to clear radioactive urine from kidneys and bladder. Hence post-diuretic pelvic PET/CT scan enhances the probability of detection of abdomino-pelvic tumor. However, it causes discomfort in patients and has some side effects also. Application of supra threshold stochastic resonance (SSR) image processing algorithm on Pre-diuretic PET/CT scan may also increase the probability of detection of these tumors. Amount of noise and threshold are two variable parameters that effect the final image quality. This study was conducted to investigate the effect of these two variable parameters on the detection of abdomen-pelvic tumor

  2. Optimization of parameters of special asynchronous electric drives

    Science.gov (United States)

    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.

  3. A process insight repository supporting process optimization

    OpenAIRE

    Vetlugin, Andrey

    2012-01-01

    Existing solutions for analysis and optimization of manufacturing processes, such as online analysis processing or statistical calculations, have shortcomings that limit continuous process improvements. In particular, they lack means of storing and integrating the results of analysis. This makes the valuable information that can be used for process optimizations used only once and then disposed. The goal of the Advanced Manufacturing Analytics (AdMA) research project is to design an integrate...

  4. Computation of interactive effects and optimization of process parameters for alkaline lipase production by mutant strain of Pseudomonas aeruginosa using response surface methodology

    Directory of Open Access Journals (Sweden)

    Deepali Bisht

    2013-01-01

    Full Text Available Alkaline lipase production by mutant strain of Pseudomonas aeruginosa MTCC 10,055 was optimized in shake flask batch fermentation using response surface methodology. An empirical model was developed through Box-Behnken experimental design to describe the relationship among tested variables (pH, temperature, castor oil, starch and triton-X-100. The second-order quadratic model determined the optimum conditions as castor oil, 1.77 mL.L-1; starch, 15.0 g.L-1; triton-X-100, 0.93 mL.L-1; incubation temperature, 34.12 ºC and pH 8.1 resulting into maximum alkaline lipase production (3142.57 U.mL-1. The quadratic model was in satisfactory adjustment with the experimental data as evidenced by a high coefficient of determination (R² value (0.9987. The RSM facilitated the analysis and interpretation of experimental data to ascertain the optimum conditions of the variables for the process and recognized the contribution of individual variables to assess the response under optimal conditions. Hence Box-Behnken approach could fruitfully be applied for process optimization.

  5. Computation of interactive effects and optimization of process parameters for alkaline lipase production by mutant strain of Pseudomonas aeruginosa using response surface methodology

    Science.gov (United States)

    Bisht, Deepali; Yadav, Santosh Kumar; Darmwal, Nandan Singh

    2013-01-01

    Alkaline lipase production by mutant strain of Pseudomonas aeruginosa MTCC 10,055 was optimized in shake flask batch fermentation using response surface methodology. An empirical model was developed through Box-Behnken experimental design to describe the relationship among tested variables (pH, temperature, castor oil, starch and triton-X-100). The second-order quadratic model determined the optimum conditions as castor oil, 1.77 mL.L−1; starch, 15.0 g.L−1; triton-X-100, 0.93 mL.L−1; incubation temperature, 34.12 °C and pH 8.1 resulting into maximum alkaline lipase production (3142.57 U.mL−1). The quadratic model was in satisfactory adjustment with the experimental data as evidenced by a high coefficient of determination (R2) value (0.9987). The RSM facilitated the analysis and interpretation of experimental data to ascertain the optimum conditions of the variables for the process and recognized the contribution of individual variables to assess the response under optimal conditions. Hence Box-Behnken approach could fruitfully be applied for process optimization. PMID:24159311

  6. 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.

  7. Optimizing towing processes at airports

    OpenAIRE

    Du, Jia Yan

    2015-01-01

    This work addresses the optimization of push-back and towing processes at airports, as an important part of the turnaround process. A vehicle routing based scheduling model is introduced to find a cost optimal assignment of jobs to towing tractors in daily operations. A second model derives an investment strategy to optimize tractor fleet size and mix in the long-run. Column generation heuristics are proposed as solution procedures. The thesis concludes with a case study of a major European ...

  8. optimization of process parameters for lovastatin production under solid-state fermentation from ground corn cobs by gamma irradiated aspergillus tamarri isolate

    International Nuclear Information System (INIS)

    Mattar, Z.A.; Khalaf, M.A.; Meleigy, S.A.

    2010-01-01

    rapid screening method is demonstrated for isolating lovastatin overproducing strains of gamma irradiated aspergillus tamarri. the screening methodology, based on the activity of lovastatin against the yeast candida albicans. among 24 gamma irradiated isolates of a. tamarri, the isolate G-8 was selected as best producer for lovastatin. solid state fermentation (SSF)was evaluated to produce lovastatin by a. tamarri G-8 isolate using ground corn cobs as substrate. monofactorial experiments were adopted to optimize the fermentation conditions. various crucial parameters such as particle size, moisture content, ph, temperature, inoculum size and incubation time were derived. corn cobs of particle size 0.4 mm having moisture level of 60 % and ph 5 gave the highest yield of lovastatin (12.4 mg/gram dry substrate) when inoculated with a. tamarri G-8 at inoculum size 10 % and 28 degree C for 8 days.

  9. Optimization of Process Parameters of Extraction of Amentoflavone, Quercetin and Ginkgetin from Taxus chinensis Using Supercritical CO2 Plus Co-Solvent

    Directory of Open Access Journals (Sweden)

    Xiao Ruan

    2014-10-01

    Full Text Available The effects of extraction time, temperature, pressure and different concentration of ethanol and their interactions on the yields of amentoflavone, quercetin and ginkgetin extracted from Taxus chinensis by supercritical CO2 were investigated by using a central composite design (CCD. An CCD experimental design with four factors and five levels was used to optimize the extraction parameters. Ultra performance liquid chromatography (UPLC was used to analyze the content of the tree components in the extracts. Experimental results show that the main effects of factors and their interactions are significant on the yields (p < 0.05. The optimal extraction conditions were established for the three compounds: yield of 4.47 mg/g for amentoflavone at 48 °C, 25 MPa, 2.02 h and 78.5% ethanol, 3.73 mg/g for quercetin at 46 °C, 24 MPa, 2.3 h, 82% ethanol and 3.47 mg/g for ginkgetin at 48 °C, 20 MPa, 2.38 h, 82% ethanol, respectively.

  10. Optimum combination of process parameters to optimize Surface Roughness and Chip Thickness during End Milling of Aluminium 6351-T6 Alloy Using Taguchi Grey Relational Analysis

    Directory of Open Access Journals (Sweden)

    Reddy Sreenivasulu

    2017-06-01

    Full Text Available In any machining operations, quality is the important conflicting objective. In order to give assurance for high productivity, some extent of quality has to be compromised. Similarly productivity will be decreased while the efforts are channelized to enhance quality. In this study,  the experiments were carried out on a CNC vertical machining center (KENT and INDIA Co. Ltd, Taiwan make to perform 10mm slots on Al 6351-T6 alloy work piece by K10 carbide, four flute end milling cutter as per taguchi design of experiments plan by L9 orthogonal array was choosen to determine experimental trials. Furthermore the spindle speed (rpm, the feed rate (mm/min and depth of cut (mm are regulated in these experiments. Surface roughness and chip thickness was measured by a surface analyser of Surf Test-211 series (Mitutoyo and Digital Micrometer (Mitutoyo with least count 0.001 mm respectively. Grey relational analysis was employed to minimize surface roughness and chip thickness by setting of optimum combination of machining parameters. Minimum surface roughness and chip thickness obtained with 1000 rpm of spindle speed, 50 mm/min feed rate and 0.7 mm depth of cut respectively. Confirmation experiments showed that Gray relational analysis precisely optimized the drilling parameters in drilling of Al 6351-T6 alloy.

  11. Freeze drying optimization of polymeric nanoparticles for ocular flurbiprofen delivery: effect of protectant agents and critical process parameters on long-term stability.

    Science.gov (United States)

    Ramos Yacasi, Gladys Rosario; Calpena Campmany, Ana Cristina; Egea Gras, María Antonia; Espina García, Marta; García López, María Luisa

    2017-04-01

    The stabilization of flurbiprofen loaded poly-ɛ-caprolactone nanoparticles (FB-PɛCL-NPs) for ocular delivery under accurate freeze-drying (FD) process provides the basis for a large-scale production and its commercial development. Optimization of the FD to improve long-term stability of ocular administration's FB-PɛCL-NPs. FB-PɛCL-NPs were prepared by solvent displacement method with poloxamer 188 (P188) as stabilizer. Freezing and primary drying (PD) were studied and optimized through freeze-thawing test and FD microscopy. Design of experiments was used to accurate secondary drying (SD) conditions and components concentration. Formulations were selected according to desired physicochemical properties. Furthermore, differential scanning calorimetry (DSC) and X-ray diffraction (XRD) were used to study interactions components. Optimized FB-PɛCL-NPs, stabilized with 3.5% (w/w) P188 and protected with 8% (w/w) poly(ethylene glycol), was submitted to precooling at +10 °C for 1 h, freezing at -50 °C for 4 h, PD at +5 °C and 0.140 mbar for 24 h and a SD at +45 °C during 10 h. These conditions showed 188.4 ± 1.3 nm, 0.087 ± 0.014, 85.5 ± 1.4%, 0.61 ± 0.12%, -16.4 ± 0.1 mV and 325 ± 7 mOsm/kg of average size, polydispersity index, entrapment efficiency, residual moisture, surface charge and osmolality, respectively. It performed a long-term stability >12 months. DSC and XRD spectra confirmed adequate chemical interaction between formulation components and showed a semi-crystalline state after FD. An optimal freeze dried ocular formulation was achieved. Evidently, the successful design of this promising colloidal system resulted from rational cooperation between a good formulation and the right conditions in the FD process.

  12. 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

  13. 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

  14. Combination of Machining Parameters to Optimize Surface Roughness and Chip Thickness during End Milling Process on Aluminium 6351-T6 Alloy Using Taguchi Design Method

    Directory of Open Access Journals (Sweden)

    Reddy Sreenivasulu

    2016-12-01

    Full Text Available In any machining operations, quality is the important conflicting objective. In order to give assurance for high productivity, some extent of quality has to be compromised. Similarly productivity will be decreased while the efforts are channelized to enhance quality. In this study,  the experiments were carried out on a CNC vertical machining center  to perform 10mm slots on Al 6351-T6 alloy work piece by K10 carbide, four flute end milling cutter. Furthermore the cutting speed, the feed rate and depth of cut are regulated in this experiment. Each experiment was conducted three times and the surface roughness and chip thickness was measured by a surface analyser of Surf Test-211 series (Mitutoyo and Digital Micrometer (Mitutoyo with least count 0.001 mm respectively. The selection of orthogonal array is concerned with the total degree of freedom of process parameters. Total degree of freedom (DOF associated with three parameters is equal to 6 (3X2.The degree of freedom for the orthogonal array should be greater than or at least equal to that of the process parameters. There by, a L9 orthogonal array having degree of freedom equal to (9-1= 8 8 has been considered .But in present case each experiment is conducted three times, therefore total degree of freedom (9X3-1=26 26 has been considered. Finally, confirmation test (ANOVA was conducted to compare the predicted values with the experimental values confirm its effectiveness in the analysis of surface roughness and chip thickness. Surface Roughness (Ra is greatly reduced from 0.145 µm to 0.1326 µm and the chip thickness (Ct is slightly reduced from 0.1 mm to 0.085 mm, because of in the measurement collected the chips after machining of every experiment, from that randomly selected a few chips for measuring of their thickness using digital micrometer.

  15. Application of the Taguchi Method for Optimizing the Process Parameters of Producing Lightweight Aggregates by Incorporating Tile Grinding Sludge with Reservoir Sediments.

    Science.gov (United States)

    Chen, How-Ji; Chang, Sheng-Nan; Tang, Chao-Wei

    2017-11-10

    This study aimed to apply the Taguchi optimization technique to determine the process conditions for producing synthetic lightweight aggregate (LWA) by incorporating tile grinding sludge powder with reservoir sediments. An orthogonal array L 16 (4⁵) was adopted, which consisted of five controllable four-level factors (i.e., sludge content, preheat temperature, preheat time, sintering temperature, and sintering time). Moreover, the analysis of variance method was used to explore the effects of the experimental factors on the particle density, water absorption, bloating ratio, and loss on ignition of the produced LWA. Overall, the produced aggregates had particle densities ranging from 0.43 to 2.1 g/cm³ and water absorption ranging from 0.6% to 13.4%. These values are comparable to the requirements for ordinary and high-performance LWAs. The results indicated that it is considerably feasible to produce high-performance LWA by incorporating tile grinding sludge with reservoir sediments.

  16. Co-modified MCM-41 as an effective adsorbent for levofloxacin removal from aqueous solution: optimization of process parameters, isotherm, and thermodynamic studies.

    Science.gov (United States)

    Jin, Ting; Yuan, Wenhua; Xue, Yujie; Wei, Hong; Zhang, Chaoying; Li, Kebin

    2017-02-01

    Antibiotics are emerging contaminants due to their potential risks to human health and ecosystems. Poor biodegradability makes it necessary to develop effective physical-chemical methods to eliminate these contaminants from water. The cobalt-modified MCM-41 was prepared by a one-pot hydrothermal method and characterized by SAXRD, N 2 adsorption-desorption, SEM, UV-Vis DR, and FTIR spectroscopy. The results revealed that the prepared 3% Co-MCM-41 possessed mesoporous structure with BET surface areas at around 898.5 m 2 g -1 . The adsorption performance of 3% Co-MCM-41 toward levofloxacin (LVF) was investigated by batch experiments. The adsorption of LVF on 3% Co-MCM-41 was very fast and reached equilibrium within 2 h. The adsorption kinetics followed the pseudo-second-order kinetic model with the second-order rate constants in the range of 0.00198-0.00391 g mg -1  min -1 . The adsorption isotherms could be well represented by the Langmuir, Freundlich, and Dubinin-Radushkevich (D-R) isotherm equations. Nevertheless, D-R isotherm provided the best fit based on the coefficient of determination and average relative error values. The mean free energy of adsorption (E) calculated from D-R model was about 11 kJ mol -1 , indicating that the adsorption was mainly governed by a chemisorption process. Moreover, the adsorption capacity was investigated as a function of pH, adsorbent dosage, LVF concentration, and temperature with help of respond surface methodology (RSM). A quadratic model was established, and an optimal condition was obtained as follows: pH 8.5, adsorbent dosage of 1 g L -1 , initial LVF concentration of 119.8 mg L -1 , and temperature of 31.6 °C. Under the optimal condition, the adsorption capacity of 3% Co-MCM-41 to LVF could reach about 108.1 mg g -1 . The solution pH, adsorbent dosage, LVF concentration, and a combination of adsorbent dose and LVF concentration were significant factors affecting the adsorption process. The adsorption

  17. Optimal parameters for laser tissue soldering

    Science.gov (United States)

    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.

  18. 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.

  19. 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.

  20. Ring rolling process simulation for geometry optimization

    Science.gov (United States)

    Franchi, Rodolfo; Del Prete, Antonio; Donatiello, Iolanda; Calabrese, Maurizio

    2017-10-01

    Ring Rolling is a complex hot forming process where different rolls are involved in the production of seamless rings. Since each roll must be independently controlled, different speed laws must be set; usually, in the industrial environment, a milling curve is introduced to monitor the shape of the workpiece during the deformation in order to ensure the correct ring production. In the present paper a ring rolling process has been studied and optimized in order to obtain anular components to be used in aerospace applications. In particular, the influence of process input parameters (feed rate of the mandrel and angular speed of main roll) on geometrical features of the final ring has been evaluated. For this purpose, a three-dimensional finite element model for HRR (Hot Ring Rolling) has been implemented in SFTC DEFORM V11. The FEM model has been used to formulate a proper optimization problem. The optimization procedure has been implemented in the commercial software DS ISight in order to find the combination of process parameters which allows to minimize the percentage error of each obtained dimension with respect to its nominal value. The software allows to find the relationship between input and output parameters applying Response Surface Methodology (RSM), by using the exact values of output parameters in the control points of the design space explored through FEM simulation. Once this relationship is known, the values of the output parameters can be calculated for each combination of the input parameters. After the calculation of the response surfaces for the selected output parameters, an optimization procedure based on Genetic Algorithms has been applied. At the end, the error between each obtained dimension and its nominal value has been minimized. The constraints imposed were the maximum values of standard deviations of the dimensions obtained for the final ring.

  1. Effects of process parameters on supercritical CO2 extraction of total phenols from strawberry (Arbutus unedo L.) fruits: An optimization study.

    Science.gov (United States)

    Akay, Seref; Alpak, Ilknur; Yesil-Celiktas, Ozlem

    2011-08-01

    The aim of this work was to optimize total phenolic yield of Arbutus unedo fruits using supercritical fluid extraction. A Box-Behnken statistical design was used to evaluate the effect of various values of pressure (50-300 bar), temperature (30-80°C) and concentration of ethanol as co-solvent (0-20%) by CO2 flow rate of 15 g/min for 60 min. The most effective variable was co-solvent ratio (p<0.005). Evaluative criteria for both dependent variables (total phenols and radical scavenging activity) in the model were assigned maximum. Optimum extraction conditions were elicited as 60 bar, 48°C and 19.7% yielding 25.72 mg gallic acid equivalent (GAE) total phenols/g extract and 99.9% radical scavenging capacity, which were higher than the values obtained by conventional water (24.89 mg/g; 83.8%) and ethanol (15.12 mg/g; 95.8%) extractions demonstrating challenges as a green separation process with improved product properties for industrial applications. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. 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.

  3. Optimization of the p-xylene oxidation process by a multi-objective differential evolution algorithm with adaptive parameters co-derived with the population-based incremental learning algorithm

    Science.gov (United States)

    Guo, Zhan; Yan, Xuefeng

    2018-04-01

    Different operating conditions of p-xylene oxidation have different influences on the product, purified terephthalic acid. It is necessary to obtain the optimal combination of reaction conditions to ensure the quality of the products, cut down on consumption and increase revenues. A multi-objective differential evolution (MODE) algorithm co-evolved with the population-based incremental learning (PBIL) algorithm, called PBMODE, is proposed. The PBMODE algorithm was designed as a co-evolutionary system. Each individual has its own parameter individual, which is co-evolved by PBIL. PBIL uses statistical analysis to build a model based on the corresponding symbiotic individuals of the superior original individuals during the main evolutionary process. The results of simulations and statistical analysis indicate that the overall performance of the PBMODE algorithm is better than that of the compared algorithms and it can be used to optimize the operating conditions of the p-xylene oxidation process effectively and efficiently.

  4. Analysis Balance Parameter of Optimal Ramp metering

    Science.gov (United States)

    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.

  5. 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 ...

  6. Optimal Design of Shock Tube Experiments for Parameter Inference

    KAUST Repository

    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

  7. Multivariate optimization of process parameters in the synthesis of calcined Ca‒Al (NO3) LDH for defluoridation using 3(3) factorial, central composite and Box-Behnken design.

    Science.gov (United States)

    Ghosal, Partha S; Gupta, Ashok K; Sulaiman, Ayoob

    2016-01-01

    Response surface methodology was applied for the first time in the optimization of the preparation of layered double hydroxide (LDH) for defluoridation. The influence of three vital process parameters (viz. pH, molar ratio and calcination temperature) in the synthesis of the adsorbent 'Calcined Ca‒Al (NO3) LDH' was thoroughly examined to maximize its fluoride scavenging potential. The process parameters were optimized using the 3(3) factorial, face centered central composite and Box-Behnken designs and a comparative assessment of the methods was conducted. The maximum fluoride removal efficiency was achieved at a calcination temperature of approximately 500ºC; however, the efficiency decreased with increasing pH and molar ratio. The outcome of the comparative assessment clearly delineates the case specific nature of the models. A better predictability over the entire experimental domain was obtained with the 3(3) factorial method, whereas the Box-Behnken design was found to be the most efficient model with lesser number of experimental runs. The desirability function technique was performed for optimizing the response, wherein face centered central composite design exhibited a maximum desirability. The calcined Ca‒Al (NO3) LDH, synthesized under the optimum conditions, demonstrated the removal efficiencies of 95% and 99% for the doses of 3 g L(-1) and 5 g L(-1), respectively.

  8. 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)

  9. 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.

  10. Hybrid computer optimization of systems with random parameters

    Science.gov (United States)

    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.

  11. Optimization of Milling Parameters Employing Desirability Functions

    Science.gov (United States)

    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.

  12. Parameters Optimization and Application to Glutamate Fermentation Model Using SVM

    OpenAIRE

    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...

  13. 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.

  14. Optimization of lime treatment processes

    International Nuclear Information System (INIS)

    Zinck, J. M.; Aube, B. C.

    2000-01-01

    Lime neutralization technology used in the treatment of acid mine drainage and other acidic effluents is discussed. Theoretical studies and laboratory experiments designed to optimize the technology of lime neutralization processes and to improve the cost efficiency of the treatment process are described. Effluent quality, slaking temperature, aeration, solid-liquid separation, sludge production and geochemical stability have been studied experimentally and on site. Results show that through minor modification of the treatment process, costs, sludge volume generated, and metal released to the environment can be significantly reduced. 17 refs., 4 figs

  15. Optimizing incomplete sample designs for item response model parameters

    NARCIS (Netherlands)

    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

  16. Optimization of process parameters for extrusion cooking of low amylose rice flour blended with seeded banana and carambola pomace for development of minerals and fiber rich breakfast cereal.

    Science.gov (United States)

    Borah, Anjan; Lata Mahanta, Charu; Kalita, Dipankar

    2016-01-01

    The low-amylose rice flour, seeded banana (Musa balbisiana, ABB) and carambola (Averrhoa carambola L.) pomace blends were extruded to prepare ready to eat breakfast cereal in a single-screw extruder. Response surface methodology using a central composite design was used to evaluate effect of independent variables, namely blend ratio (80:10:10 - 60:30:10 of low-amylose rice flour, seeded banana and carambola pomace), screw speed (200 - 400 rpm), barrel temperature (90 - 130 (°)C) and feed moisture content (9 - 21 g/100 g, wet basis) on product responses. Quadratic polynomial equations were also obtained by multiple regression analysis. The predicted models were adequate based on lack-of-fit test and coefficient of determination obtained. The feed moisture content had critical effect on all response variables. The compromised optimal conditions obtained by numerical integration for development of extrudates were: screw speed of 350 rpm, barrel temperature of 120 (°)C, feed moisture content of 12 g/100 g and 65:25:10 of blend ratio of feed. In the optimized condition low-amylose rice blend is found to have better physicochemical properties (water absorption index of 481.79 g/100 g; water solubility index of 44.13 g/100 g) and dietary fiber content of 21.35 g/100 g respectively. The developed breakfast cereal showed considerable amount of minerals (Mg and K) and overall acceptability was found to be 7.8.

  17. Optimization of airport security process

    Science.gov (United States)

    Wei, Jianan

    2017-05-01

    In order to facilitate passenger travel, on the basis of ensuring public safety, the airport security process and scheduling to optimize. The stochastic Petri net is used to simulate the single channel security process, draw the reachable graph, construct the homogeneous Markov chain to realize the performance analysis of the security process network, and find the bottleneck to limit the passenger throughput. Curve changes in the flow of passengers to open a security channel for the initial state. When the passenger arrives at a rate that exceeds the processing capacity of the security channel, it is queued. The passenger reaches the acceptable threshold of the queuing time as the time to open or close the next channel, simulate the number of dynamic security channel scheduling to reduce the passenger queuing time.

  18. Optimizing a Water Simulation based on Wavefront Parameter Optimization

    OpenAIRE

    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...

  19. Towards automatic parameter tuning of stream processing systems

    KAUST Repository

    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.

  20. Real-time parameter optimization based on neural network for smart injection molding

    Science.gov (United States)

    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.

  1. Improved Artificial Fish Algorithm for Parameters Optimization of PID Neural Network

    OpenAIRE

    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...

  2. Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization

    Science.gov (United States)

    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.

  3. Optimal control of a CSTR process

    Directory of Open Access Journals (Sweden)

    A. Soukkou

    2008-12-01

    Full Text Available Designing an effective criterion and learning algorithm for find the best structure is a major problem in the control design process. In this paper, the fuzzy optimal control methodology is applied to the design of the feedback loops of an Exothermic Continuous Stirred Tank Reactor system. The objective of design process is to find an optimal structure/gains of the Robust and Optimal Takagi Sugeno Fuzzy Controller (ROFLC. The control signal thus obtained will minimize a performance index, which is a function of the tracking/regulating errors, the quantity of the energy of the control signal applied to the system, and the number of fuzzy rules. The genetic learning is proposed for constructing the ROFLC. The chromosome genes are arranged into two parts, the binary-coded part contains the control genes and the real-coded part contains the genes parameters representing the fuzzy knowledge base. The effectiveness of this chromosome formulation enables the fuzzy sets and rules to be optimally reduced. The performances of the ROFLC are compared to these found by the traditional PD controller with Genetic Optimization (PD_GO. Simulations demonstrate that the proposed ROFLC and PD_GO has successfully met the design specifications.

  4. 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.

  5. 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 ...

  6. 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

  7. Improving processes through evolutionary optimization.

    Science.gov (United States)

    Clancy, Thomas R

    2011-09-01

    As systems evolve over time, their natural tendency is to become increasingly more complex. Studies on complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 18th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, I discuss methods to optimize complex healthcare processes through learning, adaptation, and evolutionary planning.

  8. Search Parameter Optimization for Discrete, Bayesian, and Continuous Search Algorithms

    Science.gov (United States)

    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

  9. Optimization Design of Multi-Parameters in Rail Launcher System

    OpenAIRE

    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...

  10. 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

  11. 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

  12. Parameter optimization toward optimal microneedle-based dermal vaccination.

    Science.gov (United States)

    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.

  13. Development of an in-situ synthesized multi-component reinforced Al–4.5%Cu–TiC metal matrix composite by FAS technique – Optimization of process parameters

    Directory of Open Access Journals (Sweden)

    Biswajit Das

    2016-03-01

    Full Text Available In the present investigation, an in-situ multi-component reinforced aluminium copper alloy based metal matrix composite was fabricated by the flux assisted synthesis (FAS technique. It was found from the optical microscopy analysis that TiC particles are formed in the composite. Further the present research investigates the feasibility and dry machining characteristics of Al–4.5%Cu/5TiC metal matrix composite in CNC milling machine using uncoated solid carbide end mill cutter. The effect of the machining parameters such as feed, cutting speed, depth of cut on the response parameters such as cutting force and COM is determined by using analysis of variance (ANOVA. From the analysis it was found that cutting speed and depth of cut played a major role in affecting cutting force. Multi output optimization of the process was carried out by the application of the Taguchi method with fuzzy logic, and the confirmatory test has revealed the accuracy of the developed model. For predicting the response parameters, regression equations were developed and verified with a number of test cases and it was observed that the percentage error for both responses is less than ±3%, which indicates there is a close agreement between the predicted and the measured results.

  14. Acoustical characterization and parameter optimization of polymeric noise control materials

    Science.gov (United States)

    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.

  15. Optimization of hydraulic turbine governor parameters based on WPA

    Science.gov (United States)

    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.

  16. 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.

  17. Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems

    CERN Document Server

    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...

  18. 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.

  19. 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.

  20. 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°.

  1. Multi-objective optimization in quantum parameter estimation

    Science.gov (United States)

    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.

  2. 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.

  3. A Modified Penalty Parameter Approach for Optimal Estimation of UH with Simultaneous Estimation of Infiltration Parameters

    Science.gov (United States)

    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.

  4. Dynamic Optimization of UV Flash Processes

    DEFF Research Database (Denmark)

    Ritschel, Tobias Kasper Skovborg; Capolei, Andrea; Jørgensen, John Bagterp

    2017-01-01

    UV ash processes, also referred to as isoenergetic-isochoric ash processes, occur for dynamic simulation and optimization of vapor-liquid equilibrium processes. Dynamic optimization and nonlinear model predictive control of distillation columns, certain two-phase ow problems, as well as oil reser...... that the optimization solver, the compiler, and high-performance linear algebra software are all important for e_cient dynamic optimization of UV ash processes....

  5. Fine-Tuning ADAS Algorithm Parameters for Optimizing Traffic ...

    Science.gov (United States)

    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

  6. 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.

  7. Optimization of a centrifugal compressor impeller using CFD: the choice of simulation model parameters

    Science.gov (United States)

    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.

  8. 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.

  9. 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....

  10. THE OPTIMIZATION OF PLUSH YARNS BULKING PROCESS

    Directory of Open Access Journals (Sweden)

    VINEREANU Adam

    2014-05-01

    Full Text Available This paper presents the experiments that were conducted on the installation of continuous bulking and thermofixing “SUPERBA” type TVP-2S for optimization of the plush yarns bulking process. There were considered plush yarns Nm 6.5/2, made of the fibrous blend of 50% indigenous wool sort 41 and 50% PES. In the first stage, it performs a thermal treatment with a turboprevaporizer at a temperature lower than thermofixing temperature, at atmospheric pressure, such that the plush yarns - deposed in a freely state on a belt conveyor - are uniformly bulking and contracting. It was followed the mathematical modeling procedure, working with a factorial program, rotatable central composite type, and two independent variables. After analyzing the parameters that have a direct influence on the bulking degree, there were selected the pre-vaporization temperature (coded x1,oC and the velocity of belt inside pre-vaporizer (coded x 2, m/min. As for the dependent variable, it was chosen the plush yarn diameter (coded y, mm. There were found the coordinates of the optimal point, and then this pair of values was verified in practice. These coordinates are: x1optim= 90oC and x 2optim= 6.5 m/min. The conclusion is that the goal was accomplished: it was obtained a good cover degree f or double-plush carpets by reducing the number of tufts per unit surface.

  11. Experimental Verification of Statistically Optimized Parameters for Low-Pressure Cold Spray Coating of Titanium

    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.

  12. Parameter Optimization and Electrode Improvement of Rotary Stepper Micromotor

    Science.gov (United States)

    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.

  13. 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

  14. Optimisation of shock absorber process parameters using failure mode and effect analysis and genetic algorithm

    Science.gov (United States)

    Mariajayaprakash, Arokiasamy; Senthilvelan, Thiyagarajan; Vivekananthan, Krishnapillai Ponnambal

    2013-07-01

    The various process parameters affecting the quality characteristics of the shock absorber during the process were identified using the Ishikawa diagram and by failure mode and effect analysis. The identified process parameters are welding process parameters (squeeze, heat control, wheel speed, and air pressure), damper sealing process parameters (load, hydraulic pressure, air pressure, and fixture height), washing process parameters (total alkalinity, temperature, pH value of rinsing water, and timing), and painting process parameters (flowability, coating thickness, pointage, and temperature). In this paper, the process parameters, namely, painting and washing process parameters, are optimized by Taguchi method. Though the defects are reasonably minimized by Taguchi method, in order to achieve zero defects during the processes, genetic algorithm technique is applied on the optimized parameters obtained by Taguchi method.

  15. 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.

  16. 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.

  17. Optimal Design of Shock Tube Experiments for Parameter Inference

    KAUST Repository

    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.

  18. 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.

  19. Concurrently adjusting interrelated control parameters to achieve optimal engine performance

    Science.gov (United States)

    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.

  20. Study on feed forward neural network convex optimization for LiFePO4 battery parameters

    Science.gov (United States)

    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.

  1. Stellar atmospheric parameter estimation using Gaussian process regression

    Science.gov (United States)

    Bu, Yude; Pan, Jingchang

    2015-02-01

    As is well known, it is necessary to derive stellar parameters from massive amounts of spectral data automatically and efficiently. However, in traditional automatic methods such as artificial neural networks (ANNs) and kernel regression (KR), it is often difficult to optimize the algorithm structure and determine the optimal algorithm parameters. Gaussian process regression (GPR) is a recently developed method that has been proven to be capable of overcoming these difficulties. Here we apply GPR to derive stellar atmospheric parameters from spectra. Through evaluating the performance of GPR on Sloan Digital Sky Survey (SDSS) spectra, Medium resolution Isaac Newton Telescope Library of Empirical Spectra (MILES) spectra, ELODIE spectra and the spectra of member stars of galactic globular clusters, we conclude that GPR can derive stellar parameters accurately and precisely, especially when we use data preprocessed with principal component analysis (PCA). We then compare the performance of GPR with that of several widely used regression methods (ANNs, support-vector regression and KR) and find that with GPR it is easier to optimize structures and parameters and more efficient and accurate to extract atmospheric parameters.

  2. Evaluation of Injection Molding Process Parameters for Manufacturing Polyethylene Terephthalate

    Directory of Open Access Journals (Sweden)

    Marwah O.M.F.

    2017-01-01

    Full Text Available Quality control is an important aspect in manufacturing process. The quality of product in injection moulding is influenced by injection moulding process parameter. In this study, the effect of injection moulding parameter on defects quantity of PET preform was investigated. Optimizing the parameter of injection moulding process is critical to enhance productivity where parameters must operate at an optimum level for an acceptable performance. Design of Experiment (DOE by factorial design approach was used to find an optimum parameter setting and reduce the defects. In this case study, Minitab 17 software was used to analyses the data. The selected input parameters were mould hot runner temperature, water cooling chiller temperature 1 and water cooling chiller temperature 2. Meanwhile, the output for the process was defects quantity of the preform. The relationship between input and output of the process was analyzed using regression method and Analysis of Variance (ANOVA. In order to interpolate the experiment data, mathematical modeling was used which consists of different types of regression equation. Next, from the model, 95% confidence level (p-value was considered and the significant parameter was figured out. This study involved a collaboration with a preform injection moulding company which was Nilai Legasi Plastik Sdn Bhd. The collaboration enabled the researchers to collect the data and also help the company to improve the quality of its production. The results of the study showed that the optimum parameter setting that could reduce the defect quantity of preform was MHR= 88°C, CT1= 24°C and CT2= 27°C. The comparison defect quantity analysis between current companies setting with the optimum setting showed improvement by 21% reduction of defect quantity at the optimum setting. Finally, from the optimization plot, the validation error between the prediction value and experiment was 1.72%. The result proved that quality of products

  3. Optimization of Process Parameters for Palm Oil and Rapeseed Oil Hot Pot Soup Stock%棕榈油与菜籽油复合火锅底料关键工艺参数优化

    Institute of Scientific and Technical Information of China (English)

    张丽珠; 唐洁; 车振明; 肖文艳; 黄清吉

    2014-01-01

    采用响应曲面分析法对棕榈油与菜籽油复合火锅底料关键工艺参数进行了优化。在单因素试验的基础上,以火锅底料的感观综合评分为响应值,进行了棕榈油与菜籽油用油量、油配比、熬制时间3个因素的显著性和交互作用分析,优化得到其最佳工艺参数条件:用油量为52%(m/m),棕榈油与菜籽油配比为3∶2∶3(5℃棕榈油∶8℃棕榈油∶菜籽油),熬制时间为26 min。在此条件下对棕榈油与菜籽油复合火锅底料进行感官综合评分,其中组织形态89.16分、浑汤度88.83分、色泽89.02分、香味92.87分、滋味87.29分,感官综合评分为89.65分。%The critical processing parameters of palm oil and rapesee d oil blend hot pot soup stock are optimized by response surface methodology (RSM).Use sensory scores to evaluate the response value,and the significance and interactions of three factors,including content of palm oil and rapeseed oil,oils ra-tio and stewing time.The optimal process parameters are obtained as follows:oil content is 5 2%(m/m),ratio of palm oil and rapeseed oil is 3∶2∶3 (palm oil with melting point of 5 ℃∶palm oil with melting point of 8 ℃∶rapeseed oil),the optimum stewing time established is 26 min.Under such conditions,the sensory evaluation score for palm oil and rapeseed oil hot pot soup stock is 89.16 for appearance,88.83 for turbidity,89.02 for color,92.87 for smell,87.29 for taste,and the overall sensory evaluation score is excellent at 89.65.

  4. Parameter identification in multinomial processing tree models

    NARCIS (Netherlands)

    Schmittmann, V.D.; Dolan, C.V.; Raijmakers, M.E.J.; Batchelder, W.H.

    2010-01-01

    Multinomial processing tree models form a popular class of statistical models for categorical data that have applications in various areas of psychological research. As in all statistical models, establishing which parameters are identified is necessary for model inference and selection on the basis

  5. 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.

  6. 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 ...

  7. Parameters optimization for magnetic resonance coupling wireless power transmission.

    Science.gov (United States)

    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.

  8. Parameter assessment for virtual Stackelberg game in aerodynamic shape optimization

    Science.gov (United States)

    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.

  9. METAHEURISTIC OPTIMIZATION METHODS FOR PARAMETERS ESTIMATION OF DYNAMIC SYSTEMS

    Directory of Open Access Journals (Sweden)

    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

  10. On the effect of response transformations in sequential parameter optimization.

    Science.gov (United States)

    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.

  11. Optimal operation of batch membrane processes

    CERN Document Server

    Paulen, Radoslav

    2016-01-01

    This study concentrates on a general optimization of a particular class of membrane separation processes: those involving batch diafiltration. Existing practices are explained and operational improvements based on optimal control theory are suggested. The first part of the book introduces the theory of membrane processes, optimal control and dynamic optimization. Separation problems are defined and mathematical models of batch membrane processes derived. The control theory focuses on problems of dynamic optimization from a chemical-engineering point of view. Analytical and numerical methods that can be exploited to treat problems of optimal control for membrane processes are described. The second part of the text builds on this theoretical basis to establish solutions for membrane models of increasing complexity. Each chapter starts with a derivation of optimal operation and continues with case studies exemplifying various aspects of the control problems under consideration. The authors work their way from th...

  12. Optimization and control of metal forming processes

    NARCIS (Netherlands)

    Havinga, Gosse Tjipke

    2016-01-01

    Inevitable variations in process and material properties limit the accuracy of metal forming processes. Robust optimization methods or control systems can be used to improve the production accuracy. Robust optimization methods are used to design production processes with low sensitivity to the

  13. 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

    optimization. These results indicate that significant reductions in optimization parameter sets can be accomplished with a negligible reduction in dose distribution quality. The decreased parameters can result in a reduced optimization time, or can be used to allow an improved and consequently more computation-intensive dose calculation for more accurate dose calculations during the optimization process. The basis functions may be generalized to model the accelerator motion for direct computation of the accelerator motion sequence, removing the need for developing an independent leaf sequence step

  14. Selection of parameters for advanced machining processes using firefly algorithm

    Directory of Open Access Journals (Sweden)

    Rajkamal Shukla

    2017-02-01

    Full Text Available Advanced machining processes (AMPs are widely utilized in industries for machining complex geometries and intricate profiles. In this paper, two significant processes such as electric discharge machining (EDM and abrasive water jet machining (AWJM are considered to get the optimum values of responses for the given range of process parameters. The firefly algorithm (FA is attempted to the considered processes to obtain optimized parameters and the results obtained are compared with the results given by previous researchers. The variation of process parameters with respect to the responses are plotted to confirm the optimum results obtained using FA. In EDM process, the performance parameter “MRR” is increased from 159.70 gm/min to 181.6723 gm/min, while “Ra” and “REWR” are decreased from 6.21 μm to 3.6767 μm and 6.21% to 6.324 × 10−5% respectively. In AWJM process, the value of the “kerf” and “Ra” are decreased from 0.858 mm to 0.3704 mm and 5.41 mm to 4.443 mm respectively. In both the processes, the obtained results show a significant improvement in the responses.

  15. 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.

  16. 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.

  17. 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

  18. Sequential ensemble-based optimal design for parameter estimation: SEQUENTIAL ENSEMBLE-BASED OPTIMAL DESIGN

    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.

  19. 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.

  20. Energy optimization of bread baking process undergoing quality constraints

    International Nuclear Information System (INIS)

    Papasidero, Davide; Pierucci, Sauro; Manenti, Flavio

    2016-01-01

    International home energy rating regulations are forcing to use efficient cooking equipment and processes towards energy saving and sustainability. For this reason gas ovens are replaced by the electric ones, to get the highest energy rating. Due to this fact, the study of the technologies related to the energy efficiency in cooking is increasingly developing. Indeed, big industries are working to the energy optimization of their processes since decades, while there is still a lot of room in energy optimization of single household appliances. The achievement of a higher efficiency can have a big impact on the society only if the use of modern equipment gets widespread. The combination of several energy sources (e.g. forced convection, irradiation, microwave, etc.) and their optimization is an emerging target for oven manufacturers towards optimal oven design. In this work, an energy consumption analysis and optimization is applied to the case of bread baking. Each source of energy gets the due importance and the process conditions are compared. A basic quality standard is guaranteed by taking into account some quality markers, which are relevant based on a consumer viewpoint. - Highlights: • Energy optimization is based on a validated finite-element model for bread baking. • Quality parameters for the product acceptability are introduced as constraints. • Dynamic optimization leads to 20% energy saving compared to non-optimized case. • The approach is applicable to many products, quality parameters, thermal processes. • Other heating processes can be easily integrated in the presented model.

  1. Assessing the applicability of WRF optimal parameters under the different precipitation simulations in the Greater Beijing Area

    Science.gov (United States)

    Di, Zhenhua; Duan, Qingyun; Wang, Chen; Ye, Aizhong; Miao, Chiyuan; Gong, Wei

    2018-03-01

    Forecasting skills of the complex weather and climate models have been improved by tuning the sensitive parameters that exert the greatest impact on simulated results based on more effective optimization methods. However, whether the optimal parameter values are still work when the model simulation conditions vary, which is a scientific problem deserving of study. In this study, a highly-effective optimization method, adaptive surrogate model-based optimization (ASMO), was firstly used to tune nine sensitive parameters from four physical parameterization schemes of the Weather Research and Forecasting (WRF) model to obtain better summer precipitation forecasting over the Greater Beijing Area in China. Then, to assess the applicability of the optimal parameter values, simulation results from the WRF model with default and optimal parameter values were compared across precipitation events, boundary conditions, spatial scales, and physical processes in the Greater Beijing Area. The summer precipitation events from 6 years were used to calibrate and evaluate the optimal parameter values of WRF model. Three boundary data and two spatial resolutions were adopted to evaluate the superiority of the calibrated optimal parameters to default parameters under the WRF simulations with different boundary conditions and spatial resolutions, respectively. Physical interpretations of the optimal parameters indicating how to improve precipitation simulation results were also examined. All the results showed that the optimal parameters obtained by ASMO are superior to the default parameters for WRF simulations for predicting summer precipitation in the Greater Beijing Area because the optimal parameters are not constrained by specific precipitation events, boundary conditions, and spatial resolutions. The optimal values of the nine parameters were determined from 127 parameter samples using the ASMO method, which showed that the ASMO method is very highly-efficient for optimizing WRF

  2. 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.

  3. Optimization of reserve lithium thionyl chloride battery electrochemical design parameters

    Science.gov (United States)

    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.

  4. Trafficability Analysis at Traffic Crossing and Parameters Optimization Based on Particle Swarm Optimization Method

    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.

  5. 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...

  6. Affect of different ICT processing parameters to the quality of tomograms

    International Nuclear Information System (INIS)

    Zhou Jiang; Sun Lingxia; Ye Yunchang

    2009-01-01

    The quality of ICT tomograms is affected by detecting processing parameters and image processing methods besides the performances of ICT systems. Optimal processing parameters and image processing methods can promote not only the quality of tomogram but also the resolution. Some research work was carried out about processing parameters and image processing methods including choice of collimator, filter, false color composite image. And some examples were given in this paper, which can provide the ICT analyst with reference. (authors)

  7. Food processing optimization using evolutionary algorithms | Enitan ...

    African Journals Online (AJOL)

    Evolutionary algorithms are widely used in single and multi-objective optimization. They are easy to use and provide solution(s) in one simulation run. They are used in food processing industries for decision making. Food processing presents constrained and unconstrained optimization problems. This paper reviews the ...

  8. 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.

  9. 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)

  10. Effects of process parameters on hydrothermal carbonization

    Science.gov (United States)

    Uddin, Md. Helal

    In recent years there has been increased research activity in renewable energy, especially upgrading widely available lignicellulosic biomass, in a bid to counter the increasing environmental concerns related with the use of fossil fuels. Hydrothermal carbonization (HTC), also known as wet torrefaction or hot water pretreatment, is a process for pretreatment of diverse lignocellulosic biomass feedstocks, where biomass is treated under subcritical water conditions in short contact time to produce high-value products. The products of this process are: a solid mass characterized as biochar/biocoal/biocarbon, which is homogeneous, energy dense, and hydrophobic; a liquid stream composed of five and six carbon sugars, various organic acids, and 5-HMF; and a gaseous stream, mainly CO2. A number of process parameters are considered important for the extensive application of the HTC process. Primarily, reaction temperature determines the characteristics of the products. In the solid product, the oxygen carbon ratio decreases with increasing reaction temperature and as a result, HTC biochar has the similar characteristics to low rank coal. However, liquid and gaseous stream compositions are largely correlated with the residence time. Biomass particle size can also limit the reaction kinetics due to the mass transfer effect. Recycling of process water can help to minimize the utility consumption and reduce the waste treatment cost as a result of less environmental impact. Loblolly pine was treated in hot compressed water at 200 °C, 230 °C, and 260 °C with 5:1 water:biomass mass ratio to investigate the effects of process parameters on HTC. The solid product were characterized by their mass yields, higher heating values (HHV), and equilibrium moisture content (EMC), while the liquid were characterized by their total organic carbon content and pH value.

  11. 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.

  12. 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.

  13. 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.

  14. Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology.

    Science.gov (United States)

    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.

  15. Zener Diode Compact Model Parameter Extraction Using Xyce-Dakota Optimization.

    Energy Technology Data Exchange (ETDEWEB)

    Buchheit, Thomas E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wilcox, Ian Zachary [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sandoval, Andrew J [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Reza, Shahed [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-12-01

    This report presents a detailed process for compact model parameter extraction for DC circuit Zener diodes. Following the traditional approach of Zener diode parameter extraction, circuit model representation is defined and then used to capture the different operational regions of a real diode's electrical behavior. The circuit model contains 9 parameters represented by resistors and characteristic diodes as circuit model elements. The process of initial parameter extraction, the identification of parameter values for the circuit model elements, is presented in a way that isolates the dependencies between certain electrical parameters and highlights both the empirical nature of the extraction and portions of the real diode physical behavior which of the parameters are intended to represent. Optimization of the parameters, a necessary part of a robost parameter extraction process, is demonstrated using a 'Xyce-Dakota' workflow, discussed in more detail in the report. Among other realizations during this systematic approach of electrical model parameter extraction, non-physical solutions are possible and can be difficult to avoid because of the interdependencies between the different parameters. The process steps described are fairly general and can be leveraged for other types of semiconductor device model extractions. Also included in the report are recommendations for experiment setups for generating optimum dataset for model extraction and the Parameter Identification and Ranking Table (PIRT) for Zener diodes.

  16. 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

  17. Density-based penalty parameter optimization on C-SVM.

    Science.gov (United States)

    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.

  18. Optimization Of Process Parameters For The Production Of Bio diesel From Waste Cooking Oil In The Presence Of Bifunctional γ-Al2O3-CeO2 Supported Catalysts

    International Nuclear Information System (INIS)

    Anita Ramli; Muhammad Farooq

    2015-01-01

    Huge quantities of waste cooking oils are produced all over the world every day, especially in the developed countries with 0.5 million ton per year waste cooking oil are being generated in Malaysia alone. Such large amount of waste cooking oil production can create disposal problems and contamination to water and land resources if not disposed properly. The use of waste cooking oil as feedstock for bio diesel production will not only avoid the competition of the same oil resources for food and fuel but will also overcome the waste cooking oil disposal problems. However, waste cooking oil has high acid value, thus would require the oil to undergo esterification with an acid catalyst prior to transesterification with a base catalyst. Therefore, in this study, bifunctional catalyst supports were developed for one-step esterification-transesterification of waste cooking oil by varying the CeO 2 loading on γ-Al 2 O 3 . The bifunctional supports were then impregnated with 5 wt % Mo and characterized using N 2 adsorption-desorption isotherm to determine the surface area of the catalysts while temperature programmed desorption with NH 3 and CO 2 as adsorbents were used to determine the acidity and basicity of the catalysts. Results show that the γ-Al 2 O 3 -CeO 2 supported Mo catalysts are active for the one-step esterification-transesterification of waste cooking oil to produce bio diesel with the Mo/ γ-Al 2 O 3 -20 wt% CeO 2 as the most active catalyst. Optimization of process parameters for the production of bio diesel from waste cooking oil in the presence of this catalyst show that 81.1 % bio diesel yield was produced at 110 degree Celsius with catalyst loading of 7 wt %, agitation speed of 600 rpm, methanol to oil ratio of 30:1 and reaction period of 270 minutes. (author)

  19. Experimental design and process optimization

    CERN Document Server

    Rodrigues, Maria Isabel; Dos Santos, Elian Luiz

    2014-01-01

    Initial ConsiderationsTopics of Elementary StatisticsIntroductory NotionsGeneral IdeasVariablesPopulations and Samples Importance of the Form of the PopulationFirst Ideas of Interference on a Normal PopulationParameters and EstimatesNotions on Testing HypothesesInference of the Mean of a Normal PopulationInference of the Variance of a Normal PopulationInference of the Means of Two Normal PopulationsIndependent SamplesPaired Samples L

  20. 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.

  1. 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

  2. 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

  3. 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

  4. Comparative study for different statistical models to optimize cutting parameters of CNC end milling machines

    International Nuclear Information System (INIS)

    El-Berry, A.; El-Berry, A.; Al-Bossly, A.

    2010-01-01

    In machining operation, the quality of surface finish is an important requirement for many work pieces. Thus, that is very important to optimize cutting parameters for controlling the required manufacturing quality. Surface roughness parameter (Ra) in mechanical parts depends on turning parameters during the turning process. In the development of predictive models, cutting parameters of feed, cutting speed, depth of cut, are considered as model variables. For this purpose, this study focuses on comparing various machining experiments which using CNC vertical machining center, work pieces was aluminum 6061. Multiple regression models are used to predict the surface roughness at different experiments.

  5. Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters

    Science.gov (United States)

    Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

    2016-01-01

    Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme. PMID:27362762

  6. Application of an Evolutionary Algorithm for Parameter Optimization in a Gully Erosion Model

    Energy Technology Data Exchange (ETDEWEB)

    Rengers, Francis; Lunacek, Monte; Tucker, Gregory

    2016-06-01

    Herein we demonstrate how to use model optimization to determine a set of best-fit parameters for a landform model simulating gully incision and headcut retreat. To achieve this result we employed the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), an iterative process in which samples are created based on a distribution of parameter values that evolve over time to better fit an objective function. CMA-ES efficiently finds optimal parameters, even with high-dimensional objective functions that are non-convex, multimodal, and non-separable. We ran model instances in parallel on a high-performance cluster, and from hundreds of model runs we obtained the best parameter choices. This method is far superior to brute-force search algorithms, and has great potential for many applications in earth science modeling. We found that parameters representing boundary conditions tended to converge toward an optimal single value, whereas parameters controlling geomorphic processes are defined by a range of optimal values.

  7. Optimization of geometric parameters of heat exchange pipes pin finning

    Science.gov (United States)

    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.

  8. Optimal processing of reversible quantum channels

    Energy Technology Data Exchange (ETDEWEB)

    Bisio, Alessandro, E-mail: alessandro.bisio@unipv.it [QUIT Group, Dipartimento di Fisica, INFN Sezione di Pavia, via Bassi 6, 27100 Pavia (Italy); D' Ariano, Giacomo Mauro; Perinotti, Paolo [QUIT Group, Dipartimento di Fisica, INFN Sezione di Pavia, via Bassi 6, 27100 Pavia (Italy); Sedlák, Michal [Department of Optics, Palacký University, 17. Listopadu 1192/12, CZ-771 46 Olomouc (Czech Republic); Institute of Physics, Slovak Academy of Sciences, Dúbravská Cesta 9, 845 11 Bratislava (Slovakia)

    2014-05-01

    We consider the general problem of the optimal transformation of N uses of (possibly different) unitary channels to a single use of another unitary channel in any finite dimension. We show how the optimal transformation can be fully parallelized, consisting in a preprocessing channel followed by a parallel action of all the N unitaries and a final postprocessing channel. Our techniques allow to achieve an exponential reduction in the number of the free parameters of the optimization problem making it amenable to an efficient numerical treatment. Finally, we apply our general results to find the analytical solution for special cases of interest like the cloning of qubit phase gates.

  9. 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.

  10. 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.

  11. Optimization of basic parameters of cyclic operation of underground gas storages

    Directory of Open Access Journals (Sweden)

    Віктор Олександрович Заєць

    2015-04-01

    Full Text Available The problem of optimization of process parameters of cyclic operation of underground gas storages in gas mode is determined in the article. The target function is defined, expressing necessary capacity of compressor station for gas injection in the storage. Its minimization will find the necessary technological parameters, such as flow and reservoir pressure change over time. Limitations and target function are reduced to a linear form. Solution of problems is made by the simplex method

  12. 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.

  13. Advanced Process Control Application and Optimization in Industrial Facilities

    Directory of Open Access Journals (Sweden)

    Howes S.

    2015-01-01

    Full Text Available This paper describes application of the new method and tool for system identification and PID tuning/advanced process control (APC optimization using the new 3G (geometric, gradient, gravity optimization method. It helps to design and implement control schemes directly inside the distributed control system (DCS or programmable logic controller (PLC. Also, the algorithm helps to identify process dynamics in closed-loop mode, optimizes controller parameters, and helps to develop adaptive control and model-based control (MBC. Application of the new 3G algorithm for designing and implementing APC schemes is presented. Optimization of primary and advanced control schemes stabilizes the process and allows the plant to run closer to process, equipment and economic constraints. This increases production rates, minimizes operating costs and improves product quality.

  14. 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)

  15. Optimizing Processes to Minimize Risk

    Science.gov (United States)

    Loyd, David

    2017-01-01

    NASA, like the other hazardous industries, has suffered very catastrophic losses. Human error will likely never be completely eliminated as a factor in our failures. When you can't eliminate risk, focus on mitigating the worst consequences and recovering operations. Bolstering processes to emphasize the role of integration and problem solving is key to success. Building an effective Safety Culture bolsters skill-based performance that minimizes risk and encourages successful engagement.

  16. 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.

  17. Optimization of Cutting Parameters of the Haynes 718 Nickel Alloy With Gas CO2 Laser

    Directory of Open Access Journals (Sweden)

    Jana PETRŮ

    2011-06-01

    Full Text Available This article deals with the application of laser technology and the optimization of parameters in the area of nickel alloy laser cutting intended for application in the aircraft industry. The main goal is to outline possibilities of use of the laser technology, primarily its application in the area of 3D material cutting. This experiment is focused on the optimization of cutting parameters of the Haynes 718 alloy with a gas CO2 laser. Originating cuts are evaluated primarily from the point of view of cut quality and accompanying undesirable phenomena occurring in the process of cutting. In conclusion the results achieved in the metallographic laboratory are described and analyzed.

  18. STATISTICAL OPTIMIZATION OF PROCESS VARIABLES FOR ...

    African Journals Online (AJOL)

    2012-11-03

    Nov 3, 2012 ... The osmotic dehydration process was optimized for water loss and solutes gain. ... basis) with safe moisture content for storage (10% wet basis) [3]. Due to ... sucrose, glucose, fructose, corn syrup and sodium chlo- ride have ...

  19. Optimization and standardization of pavement management processes.

    Science.gov (United States)

    2004-08-01

    This report addresses issues related to optimization and standardization of current pavement management processes in Kentucky. Historical pavement management records were analyzed, which indicates that standardization is necessary in future pavement ...

  20. Design and optimization of food processing conditions

    OpenAIRE

    Silva, C. L. M.

    1996-01-01

    The main research objectives of the group are the design and optimization of food processing conditions. Most of the work already developed is on the use of mathematical modeling of transport phenomena and quantification of degradation kinetics as two tools to optimize the final quality of thermally processed food products. Recently, we initiated a project with the main goal of studying the effects of freezing and frozen storage on orange and melon juice pectinesterase activity and q...

  1. 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.

  2. Thermo-mechanical simulation and parameters optimization for beam blank continuous casting

    International Nuclear Information System (INIS)

    Chen, W.; Zhang, Y.Z.; Zhang, C.J.; Zhu, L.G.; Lu, W.G.; Wang, B.X.; Ma, J.H.

    2009-01-01

    The objective of this work is to optimize the process parameters of beam blank continuous casting in order to ensure high quality and productivity. A transient thermo-mechanical finite element model is developed to compute the temperature and stress profile in beam blank continuous casting. By comparing the calculated data with the metallurgical constraints, the key factors causing defects of beam blank can be found out. Then based on the subproblem approximation method, an optimization program is developed to search out the optimum cooling parameters. Those optimum parameters can make it possible to run the caster at its maximum productivity, minimum cost and to reduce the defects. Now, online verifying of this optimization project has been put in practice, which can prove that it is very useful to control the actual production

  3. Error propagation of partial least squares for parameters optimization in NIR modeling.

    Science.gov (United States)

    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.

  4. Error propagation of partial least squares for parameters optimization in NIR modeling

    Science.gov (United States)

    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.

  5. A stochastic optimization model under modeling uncertainty and parameter certainty for groundwater remediation design--part I. Model development.

    Science.gov (United States)

    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.

  6. A stochastic optimization model under modeling uncertainty and parameter certainty for groundwater remediation design-Part I. Model development

    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.

  7. Manufacturing of anode supported SOFCs: Processing parameters and their influence

    DEFF Research Database (Denmark)

    Ramousse, Severine; Menon, Mohan; Brodersen, Karen

    2007-01-01

    The establishment of low cost, highly reliable and reproducible manufacturing processes has been focused for commercialization of SOFC technology. A major challenge in the production chain is the manufacture of anode-supported planar SOFC's single cells in which each layer in a layered structure...... contains a complex microstructure. In order to improve the cell performance as well as reducing the processing costs, it has been found necessary to consider the process chain holistically, because successful manufacture of such a cell and the achievement of optimal final properties depend on each...... of the processing steps and their interdependence. A large database for several thousand anode-supported SOFCs manufactured annually at the Risoe National Laboratory in collaboration with Topsoe Fuel Cell A/S has been constructed. This enables a statistical analysis of the various controlling parameters. Some...

  8. Optimization of Squeeze Casting Parameters for 2017 A Wrought Al Alloy Using Taguchi Method

    Directory of Open Access Journals (Sweden)

    Najib Souissi

    2014-04-01

    Full Text Available This study applies the Taguchi method to investigate the relationship between the ultimate tensile strength, hardness and process variables in a squeeze casting 2017 A wrought aluminium alloy. The effects of various casting parameters including squeeze pressure, melt temperature and die temperature were studied. Therefore, the objectives of the Taguchi method for the squeeze casting process are to establish the optimal combination of process parameters and to reduce the variation in quality between only a few experiments. The experimental results show that the squeeze pressure significantly affects the microstructure and the mechanical properties of 2017 A Al alloy.

  9. Unraveling the Processing Parameters in Friction Stir Welding

    Science.gov (United States)

    Schneider, Judy; Nunes, Arthur C., Jr.

    2005-01-01

    In friction stir welding (FSW), a rotating threaded pin tool is translated along a weld seam, literally stirring the edges of the seam together. To determine optimal processing parameters for producing a defect free weld, a better understanding of the resulting metal deformation flow path or paths is required. In this study, various markers are used to trace the flow paths of the metal. X-ray radiographs record the segmentation and position of the wire. Several variations in the trajectories can be differentiated within the weld zone.

  10. Hydrothermal carbonization. Investigation of process parameters

    Energy Technology Data Exchange (ETDEWEB)

    Steinbrueck, J.; Rossbach, M.; Reichert, D.; Bockhorn, H. [Karlsruher Institut fuer Technologie (KIT), Karlsruhe (Germany). Inst. of Technical Chemistry and Polymerchemistry; Walz, L. [Energie Baden-Wuerttemberg AG, Karlsruhe (Germany); Eyler, D. [European Institute for Energy Research, Karlsruhe (Germany)

    2010-07-01

    For energetic use and as a raw material lignocellulosic biomass becomes more and more important. Among pyrolytic refining, the hydrothermal treatment can be an alternative way to deoxygenerate biomass. The objective of this study is to gain deeper insights into the Hydrothermal Carbonization (HTC) process and also to define basic parameters for the construction of a small pilot plant. The biomass is converted in an autoclave at temperatures between 180 C and 240 C establishing the respective vapour pressure. Reaction times between 1 and 12 hours are applied and various catalysts in different concentrations are tested. Elemental analysis of the product, a brown coal-like solid, shows a composition of ca. C{sub 4}H{sub 3}O{sub 1}, corresponding to a carbon recovery of 60% of initial carbon mass. The elemental composition of the product is independent of the process temperature and the applied biomass, if a minimal reaction time is adhered, which however heavily depends on the reaction temperature. The remaining carbon species in intermediate reaction products in the liquid and gas phase are characterised by use of GC/MS, HPLC and FTIR. From the experimental data a two-way mechanism is deduced that includes a rapid formation of an initial solid and dehydration and decomposition reactions which lead to smaller organic molecules, e.g. furfural and aromatic species, and can be promoted by acid catalysis, e.g. H{sub 2}SO{sub 4}. (orig.)

  11. Power Consumption Optimization in Tooth Gears Processing

    Science.gov (United States)

    Kanatnikov, N.; Harlamov, G.; Kanatnikova, P.; Pashmentova, A.

    2018-01-01

    The paper reviews the issue of optimization of technological process of tooth gears production of the power consumption criteria. The authors dwell on the indices used for cutting process estimation by the consumed energy criteria and their applicability in the analysis of the toothed wheel production process. The inventors proposed a method for optimization of power consumptions based on the spatial modeling of cutting pattern. The article is aimed at solving the problem of effective source management in order to achieve economical and ecological effect during the mechanical processing of toothed gears. The research was supported by Russian Science Foundation (project No. 17-79-10316).

  12. Optimization of the dressing parameters in cylindrical grinding based on a generalized utility function

    Science.gov (United States)

    Aleksandrova, Irina

    2016-01-01

    The existing studies, concerning the dressing process, focus on the major influence of the dressing conditions on the grinding response variables. However, the choice of the dressing conditions is often made, based on the experience of the qualified staff or using data from reference books. The optimal dressing parameters, which are only valid for the particular methods and dressing and grinding conditions, are also used. The paper presents a methodology for optimization of the dressing parameters in cylindrical grinding. The generalized utility function has been chosen as an optimization parameter. It is a complex indicator determining the economic, dynamic and manufacturing characteristics of the grinding process. The developed methodology is implemented for the dressing of aluminium oxide grinding wheels by using experimental diamond roller dressers with different grit sizes made of medium- and high-strength synthetic diamonds type ??32 and ??80. To solve the optimization problem, a model of the generalized utility function is created which reflects the complex impact of dressing parameters. The model is built based on the results from the conducted complex study and modeling of the grinding wheel lifetime, cutting ability, production rate and cutting forces during grinding. They are closely related to the dressing conditions (dressing speed ratio, radial in-feed of the diamond roller dresser and dress-out time), the diamond roller dresser grit size/grinding wheel grit size ratio, the type of synthetic diamonds and the direction of dressing. Some dressing parameters are determined for which the generalized utility function has a maximum and which guarantee an optimum combination of the following: the lifetime and cutting ability of the abrasive wheels, the tangential cutting force magnitude and the production rate of the grinding process. The results obtained prove the possibility of control and optimization of grinding by selecting particular dressing

  13. Prediction and optimization of friction welding parameters for super duplex stainless steel (UNS S32760) joints

    International Nuclear Information System (INIS)

    Udayakumar, T.; Raja, K.; Afsal Husain, T.M.; Sathiya, P.

    2014-01-01

    Highlights: • Corrosion resistance and impact strength – predicted by response surface methodology. • Burn off length has highest significance on corrosion resistance. • Friction force is a strong determinant in changing impact strength. • Pareto front points generated by genetic algorithm aid to fix input control variable. • Pareto front will be a trade-off between corrosion resistance and impact strength. - Abstract: Friction welding finds widespread industrial use as a mass production process for joining materials. Friction welding process allows welding of several materials that are extremely difficult to fusion weld. Friction welding process parameters play a significant role in making good quality joints. To produce a good quality joint it is important to set up proper welding process parameters. This can be done by employing optimization techniques. This paper presents a multi objective optimization method for optimizing the process parameters during friction welding process. The proposed method combines the response surface methodology (RSM) with an intelligent optimization algorithm, i.e. genetic algorithm (GA). Corrosion resistance and impact strength of friction welded super duplex stainless steel (SDSS) (UNS S32760) joints were investigated considering three process parameters: friction force (F), upset force (U) and burn off length (B). Mathematical models were developed and the responses were adequately predicted. Direct and interaction effects of process parameters on responses were studied by plotting graphs. Burn off length has high significance on corrosion current followed by upset force and friction force. In the case of impact strength, friction force has high significance followed by upset force and burn off length. Multi objective optimization for maximizing the impact strength and minimizing the corrosion current (maximizing corrosion resistance) was carried out using GA with the RSM model. The optimization procedure resulted in

  14. 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)

  15. Optimization of turning process through the analytic flank wear modelling

    Science.gov (United States)

    Del Prete, A.; Franchi, R.; De Lorenzis, D.

    2018-05-01

    In the present work, the approach used for the optimization of the process capabilities for Oil&Gas components machining will be described. These components are machined by turning of stainless steel castings workpieces. For this purpose, a proper Design Of Experiments (DOE) plan has been designed and executed: as output of the experimentation, data about tool wear have been collected. The DOE has been designed starting from the cutting speed and feed values recommended by the tools manufacturer; the depth of cut parameter has been maintained as a constant. Wear data has been obtained by means the observation of the tool flank wear under an optical microscope: the data acquisition has been carried out at regular intervals of working times. Through a statistical data and regression analysis, analytical models of the flank wear and the tool life have been obtained. The optimization approach used is a multi-objective optimization, which minimizes the production time and the number of cutting tools used, under the constraint on a defined flank wear level. The technique used to solve the optimization problem is a Multi Objective Particle Swarm Optimization (MOPS). The optimization results, validated by the execution of a further experimental campaign, highlighted the reliability of the work and confirmed the usability of the optimized process parameters and the potential benefit for the company.

  16. Gaussian process regression for geometry optimization

    Science.gov (United States)

    Denzel, Alexander; Kästner, Johannes

    2018-03-01

    We implemented a geometry optimizer based on Gaussian process regression (GPR) to find minimum structures on potential energy surfaces. We tested both a two times differentiable form of the Matérn kernel and the squared exponential kernel. The Matérn kernel performs much better. We give a detailed description of the optimization procedures. These include overshooting the step resulting from GPR in order to obtain a higher degree of interpolation vs. extrapolation. In a benchmark against the Limited-memory Broyden-Fletcher-Goldfarb-Shanno optimizer of the DL-FIND library on 26 test systems, we found the new optimizer to generally reduce the number of required optimization steps.

  17. Tank Waste Remediation System optimized processing strategy

    International Nuclear Information System (INIS)

    Slaathaug, E.J.; Boldt, A.L.; Boomer, K.D.; Galbraith, J.D.; Leach, C.E.; Waldo, T.L.

    1996-03-01

    This report provides an alternative strategy evolved from the current Hanford Site Tank Waste Remediation System (TWRS) programmatic baseline for accomplishing the treatment and disposal of the Hanford Site tank wastes. This optimized processing strategy performs the major elements of the TWRS Program, but modifies the deployment of selected treatment technologies to reduce the program cost. The present program for development of waste retrieval, pretreatment, and vitrification technologies continues, but the optimized processing strategy reuses a single facility to accomplish the separations/low-activity waste (LAW) vitrification and the high-level waste (HLW) vitrification processes sequentially, thereby eliminating the need for a separate HLW vitrification facility

  18. On the theory of optimal processes

    International Nuclear Information System (INIS)

    Goldenberg, P.; Provenzano, V.

    1975-01-01

    The theory of optimal processes is a recent mathematical formalism that is used to solve an important class of problems in science and in technology, that cannot be solved by classical variational techniques. An example of such processes would be the control of a nuclear reactor. Certain features of the theory of optimal processes are discussed, emphasizing the central contribution of Pontryagin with his formulation of the maximum principle. An application of the theory of optimum control is presented. The example is a time optimum problem applied to a simplified model of a nuclear reactor. It deals with the question of changing the equilibrium power level of the reactor in an optimum time

  19. Heterogeneous architecture to process swarm optimization algorithms

    Directory of Open Access Journals (Sweden)

    Maria A. Dávila-Guzmán

    2014-01-01

    Full Text Available Since few years ago, the parallel processing has been embedded in personal computers by including co-processing units as the graphics processing units resulting in a heterogeneous platform. This paper presents the implementation of swarm algorithms on this platform to solve several functions from optimization problems, where they highlight their inherent parallel processing and distributed control features. In the swarm algorithms, each individual and dimension problem are parallelized by the granularity of the processing system which also offer low communication latency between individuals through the embedded processing. To evaluate the potential of swarm algorithms on graphics processing units we have implemented two of them: the particle swarm optimization algorithm and the bacterial foraging optimization algorithm. The algorithms’ performance is measured using the acceleration where they are contrasted between a typical sequential processing platform and the NVIDIA GeForce GTX480 heterogeneous platform; the results show that the particle swarm algorithm obtained up to 36.82x and the bacterial foraging swarm algorithm obtained up to 9.26x. Finally, the effect to increase the size of the population is evaluated where we show both the dispersion and the quality of the solutions are decreased despite of high acceleration performance since the initial distribution of the individuals can converge to local optimal solution.

  20. An optimization framework for process discovery algorithms

    NARCIS (Netherlands)

    Weijters, A.J.M.M.; Stahlbock, R.

    2011-01-01

    Today there are many process mining techniques that, based on an event log, allow for the automatic induction of a process model. The process mining algorithms that are able to deal with incomplete event logs, exceptions, and noise typically have many parameters to tune the algorithm. Therefore, the

  1. Multi Objective Optimization of Weld Parameters of Boiler Steel Using Fuzzy Based Desirability Function

    Directory of Open Access Journals (Sweden)

    M. Satheesh

    2014-01-01

    Full Text Available The high pressure differential across the wall of pressure vessels is potentially dangerous and has caused many fatal accidents in the history of their development and operation. For this reason the structural integrity of weldments is critical to the performance of pressure vessels. In recent years much research has been conducted to the study of variations in welding parameters and consumables on the mechanical properties of pressure vessel steel weldments to optimize weld integrity and ensure pressure vessels are safe. The quality of weld is a very important working aspect for the manufacturing and construction industries. Because of high quality and reliability, Submerged Arc Welding (SAW is one of the chief metal joining processes employed in industry. This paper addresses the application of desirability function approach combined with fuzzy logic analysis to optimize the multiple quality characteristics (bead reinforcement, bead width, bead penetration and dilution of submerged arc welding process parameters of SA 516 Grade 70 steels(boiler steel. Experiments were conducted using Taguchi’s L27 orthogonal array with varying the weld parameters of welding current, arc voltage, welding speed and electrode stickout. By analyzing the response table and response graph of the fuzzy reasoning grade, optimal parameters were obtained. Solutions from this method can be useful for pressure vessel manufacturers and operators to search an optimal solution of welding condition.

  2. 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.

  3. 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.

  4. 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.

  5. On the design of experimental separation processes for maximum accuracy in the estimation of their parameters

    International Nuclear Information System (INIS)

    Volkman, Y.

    1980-07-01

    The optimal design of experimental separation processes for maximum accuracy in the estimation of process parameters is discussed. The sensitivity factor correlates the inaccuracy of the analytical methods with the inaccuracy of the estimation of the enrichment ratio. It is minimized according to the design parameters of the experiment and the characteristics of the analytical method

  6. Method of optimization of the natural gas refining process

    Energy Technology Data Exchange (ETDEWEB)

    Sadykh-Zade, E.S.; Bagirov, A.A.; Mardakhayev, I.M.; Razamat, M.S.; Tagiyev, V.G.

    1980-01-01

    The SATUM (automatic control system of technical operations) system introduced at the Shatlyk field should assure good quality of gas refining. In order to optimize the natural gas refining processes and experimental-analytical method is used in compiling the mathematical descriptions. The program, compiled in Fortran language, in addition to parameters of optimal conditions gives information on the yield of concentrate and water, concentration and consumption of DEG, composition and characteristics of the gas and condensate. The algorithm for calculating optimum engineering conditions of gas refining is proposed to be used in ''advice'' mode, and also for monitoring progress of the gas refining process.

  7. 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

  8. Data Mining and Optimization Tools for Developing Engine Parameters Tools

    Science.gov (United States)

    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.

  9. Physical bases for diffusion welding processes optimization

    International Nuclear Information System (INIS)

    Bulygina, S.M.; Berber, N.N.; Mukhambetov, D.G.

    1999-01-01

    One of wide-spread method of different materials joint is diffusion welding. It has being brought off at the expense of mutual diffusion of atoms of contacting surfaces under long-duration curing at its heating and compression. Welding regime in dependence from properties of welding details is defining of three parameters: temperature, pressure, time. Problem of diffusion welding optimization concludes in determination less values of these parameters, complying with requirements for quality of welded joint. In the work experiments on diffusion welding for calculated temperature and for given surface's roughness were carried out. Tests conduct on samples of iron and iron-nickel alloy with size 1·1·1 cm 3 . Optimal regime of diffusion welding of examined samples in vacuum is defined. It includes compression of welding samples, heating, isothermal holding at temperature 650 deg C during 0.5 h and affords the required homogeneity of joint

  10. Influence of processing parameters on PZT thick films

    International Nuclear Information System (INIS)

    Huang, Oliver; Bandyopadhyay, Amit; Bose, Susmita

    2005-01-01

    We have studied influence of processing parameters on the microstructure and ferroelectric properties of lead zirconate titanate (PZT)-based thick films in the range of 5-25 μm. PZT and 2% La-doped PZT thick films were processed using a modified sol-gel process. In this process, PZT- and La-doped PZT powders were first prepared via sol-gel. These powders were calcined and then used with respective sols to form a slurry. Slurry composition was optimized to spin-coat thick films on platinized Si substrate (Si/SiO 2 /Ti/Pt). Spinning rate, acceleration and slurry deposition techniques were optimized to form thick films with uniform thickness and without any cracking. Increasing solids loading was found to enhance the surface smoothness of the film and decrease porosity. Films were tested for their electrical properties and ferroelectric fatigue response. The maximum polarization obtained was 40 μC/cm 2 at 250 kV/cm for PZT thick film and 30 μC/cm 2 at 450 kV/cm for La-doped PZT thick film. After 10 9 cycles of fatiguing at 35 kHz, La-doped PZT showed better resistance for ferroelectric fatigue compared with un-doped PZT films

  11. A multicriteria framework with voxel-dependent parameters for radiotherapy treatment plan optimization

    International Nuclear Information System (INIS)

    Zarepisheh, Masoud; Uribe-Sanchez, Andres F.; Li, Nan; Jia, Xun; Jiang, Steve B.

    2014-01-01

    Purpose: To establish a new mathematical framework for radiotherapy treatment optimization with voxel-dependent optimization parameters. Methods: In the treatment plan optimization problem for radiotherapy, a clinically acceptable plan is usually generated by an optimization process with weighting factors or reference doses adjusted for a set of the objective functions associated to the organs. Recent discoveries indicate that adjusting parameters associated with each voxel may lead to better plan quality. However, it is still unclear regarding the mathematical reasons behind it. Furthermore, questions about the objective function selection and parameter adjustment to assure Pareto optimality as well as the relationship between the optimal solutions obtained from the organ-based and voxel-based models remain unanswered. To answer these questions, the authors establish in this work a new mathematical framework equipped with two theorems. Results: The new framework clarifies the different consequences of adjusting organ-dependent and voxel-dependent parameters for the treatment plan optimization of radiation therapy, as well as the impact of using different objective functions on plan qualities and Pareto surfaces. The main discoveries are threefold: (1) While in the organ-based model the selection of the objective function has an impact on the quality of the optimized plans, this is no longer an issue for the voxel-based model since the Pareto surface is independent of the objective function selection and the entire Pareto surface could be generated as long as the objective function satisfies certain mathematical conditions; (2) All Pareto solutions generated by the organ-based model with different objective functions are parts of a unique Pareto surface generated by the voxel-based model with any appropriate objective function; (3) A much larger Pareto surface is explored by adjusting voxel-dependent parameters than by adjusting organ-dependent parameters, possibly

  12. Optimizing Governed Blockchains for Financial Process Authentications

    OpenAIRE

    Lundbaek, Leif-Nissen; D'Iddio, Andrea Callia; Huth, Michael

    2016-01-01

    We propose the formal study of governed blockchains that are owned and controlled by organizations and that neither create cryptocurrencies nor provide any incentives to solvers of cryptographic puzzles. We view such approaches as frameworks in which system parts, such as the cryptographic puzzle, may be instantiated with different technology. Owners of such a blockchain procure puzzle solvers as resources they control, and use a mathematical model to compute optimal parameters for the crypto...

  13. 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.

  14. Robust fluence map optimization via alternating direction method of multipliers with empirical parameter optimization

    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)

  15. Combination of Compensations and Multi-Parameter Coil for Efficiency Optimization of Inductive Power Transfer System

    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.

  16. 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

  17. 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)

  18. Optimization of thermal processing of canned mussels.

    Science.gov (United States)

    Ansorena, M R; Salvadori, V O

    2011-10-01

    The design and optimization of thermal processing of solid-liquid food mixtures, such as canned mussels, requires the knowledge of the thermal history at the slowest heating point. In general, this point does not coincide with the geometrical center of the can, and the results show that it is located along the axial axis at a height that depends on the brine content. In this study, a mathematical model for the prediction of the temperature at this point was developed using the discrete transfer function approach. Transfer function coefficients were experimentally obtained, and prediction equations fitted to consider other can dimensions and sampling interval. This model was coupled with an optimization routine in order to search for different retort temperature profiles to maximize a quality index. Both constant retort temperature (CRT) and variable retort temperature (VRT; discrete step-wise and exponential) were considered. In the CRT process, the optimal retort temperature was always between 134 °C and 137 °C, and high values of thiamine retention were achieved. A significant improvement in surface quality index was obtained for optimal VRT profiles compared to optimal CRT. The optimization procedure shown in this study produces results that justify its utilization in the industry.

  19. Parameters in selective laser melting for processing metallic powders

    Science.gov (United States)

    Kurzynowski, Tomasz; Chlebus, Edward; Kuźnicka, Bogumiła; Reiner, Jacek

    2012-03-01

    The paper presents results of studies on Selective Laser Melting. SLM is an additive manufacturing technology which may be used to process almost all metallic materials in the form of powder. Types of energy emission sources, mainly fiber lasers and/or Nd:YAG laser with similar characteristics and the wavelength of 1,06 - 1,08 microns, are provided primarily for processing metallic powder materials with high absorption of laser radiation. The paper presents results of selected variable parameters (laser power, scanning time, scanning strategy) and fixed parameters such as the protective atmosphere (argon, nitrogen, helium), temperature, type and shape of the powder material. The thematic scope is very broad, so the work was focused on optimizing the process of selective laser micrometallurgy for producing fully dense parts. The density is closely linked with other two conditions: discontinuity of the microstructure (microcracks) and stability (repeatability) of the process. Materials used for the research were stainless steel 316L (AISI), tool steel H13 (AISI), and titanium alloy Ti6Al7Nb (ISO 5832-11). Studies were performed with a scanning electron microscope, a light microscopes, a confocal microscope and a μCT scanner.

  20. Analysis and optimization of machining parameters of laser cutting for polypropylene composite

    Science.gov (United States)

    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.

  1. [Imaging center - optimization of the imaging process].

    Science.gov (United States)

    Busch, H-P

    2013-04-01

    Hospitals around the world are under increasing pressure to optimize the economic efficiency of treatment processes. Imaging is responsible for a great part of the success but also of the costs of treatment. In routine work an excessive supply of imaging methods leads to an "as well as" strategy up to the limit of the capacity without critical reflection. Exams that have no predictable influence on the clinical outcome are an unjustified burden for the patient. They are useless and threaten the financial situation and existence of the hospital. In recent years the focus of process optimization was exclusively on the quality and efficiency of performed single examinations. In the future critical discussion of the effectiveness of single exams in relation to the clinical outcome will be more important. Unnecessary exams can be avoided, only if in addition to the optimization of single exams (efficiency) there is an optimization strategy for the total imaging process (efficiency and effectiveness). This requires a new definition of processes (Imaging Pathway), new structures for organization (Imaging Center) and a new kind of thinking on the part of the medical staff. Motivation has to be changed from gratification of performed exams to gratification of process quality (medical quality, service quality, economics), including the avoidance of additional (unnecessary) exams. © Georg Thieme Verlag KG Stuttgart · New York.

  2. Bidirectional optimization of the melting spinning process.

    Science.gov (United States)

    Liang, Xiao; Ding, Yongsheng; Wang, Zidong; Hao, Kuangrong; Hone, Kate; Wang, Huaping

    2014-02-01

    A bidirectional optimizing approach for the melting spinning process based on an immune-enhanced neural network is proposed. The proposed bidirectional model can not only reveal the internal nonlinear relationship between the process configuration and the quality indices of the fibers as final product, but also provide a tool for engineers to develop new fiber products with expected quality specifications. A neural network is taken as the basis for the bidirectional model, and an immune component is introduced to enlarge the searching scope of the solution field so that the neural network has a larger possibility to find the appropriate and reasonable solution, and the error of prediction can therefore be eliminated. The proposed intelligent model can also help to determine what kind of process configuration should be made in order to produce satisfactory fiber products. To make the proposed model practical to the manufacturing, a software platform is developed. Simulation results show that the proposed model can eliminate the approximation error raised by the neural network-based optimizing model, which is due to the extension of focusing scope by the artificial immune mechanism. Meanwhile, the proposed model with the corresponding software can conduct optimization in two directions, namely, the process optimization and category development, and the corresponding results outperform those with an ordinary neural network-based intelligent model. It is also proved that the proposed model has the potential to act as a valuable tool from which the engineers and decision makers of the spinning process could benefit.

  3. Tailored parameter optimization methods for ordinary differential equation models with steady-state constraints.

    Science.gov (United States)

    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

  4. Development of a parameter optimization technique for the design of automatic control systems

    Science.gov (United States)

    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.

  5. Relationship between process parameters and properties of multifunctional needlepunched geotextiles

    CSIR Research Space (South Africa)

    Rawal, A

    2006-04-01

    Full Text Available , and filtration. In this study, the effect of process parameters, namely, feed rate, stroke frequency, and depth of needle penetration has been investigated on various properties of needlepunched geotextiles. These process parameters are then empirically related...

  6. A New Method for Determining Optimal Regularization Parameter in Near-Field Acoustic Holography

    Directory of Open Access Journals (Sweden)

    Yue Xiao

    2018-01-01

    Full Text Available Tikhonov regularization method is effective in stabilizing reconstruction process of the near-field acoustic holography (NAH based on the equivalent source method (ESM, and the selection of the optimal regularization parameter is a key problem that determines the regularization effect. In this work, a new method for determining the optimal regularization parameter is proposed. The transfer matrix relating the source strengths of the equivalent sources to the measured pressures on the hologram surface is augmented by adding a fictitious point source with zero strength. The minimization of the norm of this fictitious point source strength is as the criterion for choosing the optimal regularization parameter since the reconstructed value should tend to zero. The original inverse problem in calculating the source strengths is converted into a univariate optimization problem which is solved by a one-dimensional search technique. Two numerical simulations with a point driven simply supported plate and a pulsating sphere are investigated to validate the performance of the proposed method by comparison with the L-curve method. The results demonstrate that the proposed method can determine the regularization parameter correctly and effectively for the reconstruction in NAH.

  7. 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

  8. Simulation and Optimization of Foam EOR Processes

    NARCIS (Netherlands)

    Namdar Zanganeh, M.

    2011-01-01

    Chemical enhanced oil recovery (EOR) is relatively expensive due to the high cost of the injected chemicals such as surfactants. Excessive use of these chemicals leads to processes that are not economically feasible. Therefore, optimizing the volume of these injected chemicals is of extreme

  9. Synthesis and Optimization of a Methanol Process

    DEFF Research Database (Denmark)

    Grue, J.; Bendtsen, Jan Dimon

    2003-01-01

    of reaction. The resulting model consists of a system of DAEs. The model is compared with rigorous simulation results from Pro/II and good agreement is found. The process is optimized followed by heat integration and large differences in the operating economy of the plant can be observed as a result hereof...

  10. On the optimization of endoreversible processes

    Science.gov (United States)

    Pescetti, D.

    2014-03-01

    This paper is intended for undergraduates and specialists in thermodynamics and related areas. We consider and discuss the optimization of endoreversible thermodynamic processes under the condition of maximum work production. Explicit thermodynamic analyses of the solutions are carried out for the Novikov and Agrawal processes. It is shown that the efficiencies at maximum work production and maximum power output are not necessarily equal. They are for the Novikov process but not for the Agrawal process. The role of the constraints is put into evidence. The physical aspects are enhanced by the simplicity of the involved mathematics.

  11. OPTIMIZATION OF FLOCCULATION PROCESS BY MICROBIAL COAGULANT IN RIVER WATER

    Directory of Open Access Journals (Sweden)

    Fatin Nabilah Murad

    2017-12-01

    Full Text Available The existing process of coagulation and flocculation are using chemicals that known as cationic coagulant such as alum, ferric sulfate, calcium oxide, and organic polymers.  Thus, this study concentrates on optimizing of flocculation process by microbial coagulant in river water. Turbidity and suspended solids are the main constraints of river water quality in Malaysia. Hence, a study is proposed to produce microbial coagulants isolated locally for river water treatment. The chosen microbe used as the bioflocculant producer is Aspergillus niger. The parameters to optimization in the flocculation process were pH, bioflocculant dosage and effluent concentration. The research was done in the jar test process and the process parameters for maximum turbidity removal was validated. The highest flocculating activity was obtained on day seven of cultivation in the supernatant. The optimum pH and bioflocculant dosage for an optimize sedimentation process were between 4-5 and 2-3 mL for 0.3 g/L of effluent concentration respectively. The model was validated by using a river water sample from Sg. Pusu and the result showed that the model was acceptable to evaluate the bioflocculation process.

  12. Sensitivity of Calibrated Parameters and Water Resource Estimates on Different Objective Functions and Optimization Algorithms

    Directory of Open Access Journals (Sweden)

    Delaram Houshmand Kouchi

    2017-05-01

    Full Text Available The successful application of hydrological models relies on careful calibration and uncertainty analysis. However, there are many different calibration/uncertainty analysis algorithms, and each could be run with different objective functions. In this paper, we highlight the fact that each combination of optimization algorithm-objective functions may lead to a different set of optimum parameters, while having the same performance; this makes the interpretation of dominant hydrological processes in a watershed highly uncertain. We used three different optimization algorithms (SUFI-2, GLUE, and PSO, and eight different objective functions (R2, bR2, NSE, MNS, RSR, SSQR, KGE, and PBIAS in a SWAT model to calibrate the monthly discharges in two watersheds in Iran. The results show that all three algorithms, using the same objective function, produced acceptable calibration results; however, with significantly different parameter ranges. Similarly, an algorithm using different objective functions also produced acceptable calibration results, but with different parameter ranges. The different calibrated parameter ranges consequently resulted in significantly different water resource estimates. Hence, the parameters and the outputs that they produce in a calibrated model are “conditioned” on the choices of the optimization algorithm and objective function. This adds another level of non-negligible uncertainty to watershed models, calling for more attention and investigation in this area.

  13. Forecasting optimal duration of a beer main fermentation process using the Kalman filter

    OpenAIRE

    Niyonsaba T.; Pavlov V.A.

    2016-01-01

    One of the most important processes of beer production is the main process of fermentation. In this process, the wort transforms into beer. The quality of beer depends on the dynamics of wort parameters. The main fermentation process continues for 10 days and requires high costs. Therefore, the main purpose of this article is to forecast the optimal duration of the beer main fermentation process and provide its optimal control. The Kalman filter can provide optimal control of the main ferment...

  14. Optimization of welding parameters using a genetic algorithm: A robotic arm–assisted implementation for recovery of Pelton turbine blades

    Directory of Open Access Journals (Sweden)

    Luis Pérez Pozo

    2015-11-01

    Full Text Available This work presents the operational optimization of a welding operation involving using genetic algorithms. The welding curves correspond to the profile of a blade-shaped Pelton turbine. The procedure involved the development of a series of tests and observation of the parameters that will be controlled during the welding process. After the tests were performed, the samples were prepared for chemical attack, which allowed observation of the penetration, weld area, and dilution. After that, mathematical models were developed that correlate the controllable welding parameters with the aforementioned bead parameters. In those mathematical models, the optimization of the process parameters was performed using genetic algorithms. Specially programmed functions for mutation, reproduction, and initialization processes were written and used in the implemented model. After the optimization process was completed, the results were evaluated through new tests to verify whether the obtained objective functions properly describe the characteristics of the weld. The comparisons showed errors of less than 6%.

  15. Investigation of material removal rate (MRR) and wire wear ratio (WWR) for alloy Ti6Al4 V exposed to heat treatment processing in WEDM and optimization of parameters using Grey relational analysis

    Energy Technology Data Exchange (ETDEWEB)

    Altug, Mehmet [Inonu Univ., Malatya (Turkey). Dept. of Machine and Metal Technologies

    2016-11-01

    The study examines the changes of the microstructural, mechanical and conductivity characteristics of the titanium alloy Ti6Al4 V as a result of heat treatment using wire electrical discharge machining, and their effect on machinability. By means of optical microscopy and scanning electron microscopy (SEM), analyses have been performed to determine various characteristics and additionally, microhardness and conductivity measurements have been conducted. Material removal rate (MRR) and wire wear ratio (WWR) values have been determined by using L18 Taguchi test design. The microstructures of the samples have been changed by thermal procedures. Results have been obtained by using the Grey relational analysis (GRA) optimization technique to solve the maximum MRR and minimum WWR values. The best (highest) MRR value is obtained from sample E which was water quenched in dual phase processing. The microstructure of this sample is composed of primary α and α' phases. The best (lowest) WWR value is obtained from sample A.

  16. Investigation of material removal rate (MRR) and wire wear ratio (WWR) for alloy Ti6Al4 V exposed to heat treatment processing in WEDM and optimization of parameters using Grey relational analysis

    International Nuclear Information System (INIS)

    Altug, Mehmet

    2016-01-01

    The study examines the changes of the microstructural, mechanical and conductivity characteristics of the titanium alloy Ti6Al4 V as a result of heat treatment using wire electrical discharge machining, and their effect on machinability. By means of optical microscopy and scanning electron microscopy (SEM), analyses have been performed to determine various characteristics and additionally, microhardness and conductivity measurements have been conducted. Material removal rate (MRR) and wire wear ratio (WWR) values have been determined by using L18 Taguchi test design. The microstructures of the samples have been changed by thermal procedures. Results have been obtained by using the Grey relational analysis (GRA) optimization technique to solve the maximum MRR and minimum WWR values. The best (highest) MRR value is obtained from sample E which was water quenched in dual phase processing. The microstructure of this sample is composed of primary α and α' phases. The best (lowest) WWR value is obtained from sample A.

  17. 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.

  18. Optimizing gelling parameters of gellan gum for fibrocartilage tissue engineering.

    Science.gov (United States)

    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.

  19. Computer performance optimization systems, applications, processes

    CERN Document Server

    Osterhage, Wolfgang W

    2013-01-01

    Computing power performance was important at times when hardware was still expensive, because hardware had to be put to the best use. Later on this criterion was no longer critical, since hardware had become inexpensive. Meanwhile, however, people have realized that performance again plays a significant role, because of the major drain on system resources involved in developing complex applications. This book distinguishes between three levels of performance optimization: the system level, application level and business processes level. On each, optimizations can be achieved and cost-cutting p

  20. PROPOSAL OF SPATIAL OPTIMIZATION OF PRODUCTION PROCESS IN PROCESS DESIGNER

    Directory of Open Access Journals (Sweden)

    Peter Malega

    2015-03-01

    Full Text Available This contribution is focused on optimizing the use of space in the production process using software Process Designer. The aim of this contribution is to suggest possible improvements to the existing layout of the selected production process. Production process was analysed in terms of inputs, outputs and course of actions. Nowadays there are many software solutions aimed at optimizing the use of space. One of these software products is the Process Designer, which belongs to the product line Tecnomatix. This software is primarily aimed at production planning. With Process Designer is possible to design the layout of production and subsequently to analyse the production or to change according to the current needs of the company.

  1. Variation of physicochemical parameters during a composting process

    International Nuclear Information System (INIS)

    Faria C, D.M.; Ballesteros, M.I.; Bendeck, M.

    1999-01-01

    Two composting processes were carried out; they lasted for about 165 days. In one of the processes the decomposition of the material was performed only by microorganisms only (direct composting) and in the other one, by microorganisms and earthworms -Eisenla foetida- (indirect composting). The first one was carried out in a composting system called c amas a nd the indirect one was carried out in its initial phase in a system of p anelas , then the wastes were transferred to a c ama . The materials were treated in both processes with lime, ammonium nitrate and microorganisms. Periodical samples were taken from different places of the pile and a temperature control was made weekly. The following physicochemical parameters were analyzed in each sample: Humidity, color, pH soil : water in ratios of 1:5 and 1:10, ash, organic matter, CIC, contents of carbon and nitrogen and C/N ratio. In the aqueous extract, C/N ratio and percentage of hydro solubles were analyzed. It was also made a germination assay taking measurements of the percentage of garden cress seeds (Lepidium sativum) that germinated in the aqueous extract. The parameters variation in each process let us to establish that the greatest changes in the material happened in the initial phases of the process (thermophilic and mesophilic phases); the presence of microorganisms was the limiting factor in the dynamic of the process; on the other hand, the earthworm addition did not accelerate the mineralization of organic matter. The results let us to establish that the color determination is not an effective parameter in order to evaluate the degree of maturity of the compost. Other parameters such as temperature and germination percentage can be made as routine test to determine the process rate. Determination of CIC, ash and hydro solubles content are recommended to evaluate the optimal maturity degree in the material. It is proposed changes such as to reduce the composting time to a maximum of 100 days and to

  2. 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

  3. Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm

    International Nuclear Information System (INIS)

    Oliva, Diego; Abd El Aziz, Mohamed; Ella Hassanien, Aboul

    2017-01-01

    Highlights: •We modify the whale algorithm using chaotic maps. •We apply a chaotic algorithm to estimate parameter of photovoltaic cells. •We perform a study of chaos in whale algorithm. •Several comparisons and metrics support the experimental results. •We test the method with data from real solar cells. -- Abstract: The using of solar energy has been increased since it is a clean source of energy. In this way, the design of photovoltaic cells has attracted the attention of researchers over the world. There are two main problems in this field: having a useful model to characterize the solar cells and the absence of data about photovoltaic cells. This situation even affects the performance of the photovoltaic modules (panels). The characteristics of the current vs. voltage are used to describe the behavior of solar cells. Considering such values, the design problem involves the solution of the complex non-linear and multi-modal objective functions. Different algorithms have been proposed to identify the parameters of the photovoltaic cells and panels. Most of them commonly fail in finding the optimal solutions. This paper proposes the Chaotic Whale Optimization Algorithm (CWOA) for the parameters estimation of solar cells. The main advantage of the proposed approach is using the chaotic maps to compute and automatically adapt the internal parameters of the optimization algorithm. This situation is beneficial in complex problems, because along the iterative process, the proposed algorithm improves their capabilities to search for the best solution. The modified method is able to optimize complex and multimodal objective functions. For example, the function for the estimation of parameters of solar cells. To illustrate the capabilities of the proposed algorithm in the solar cell design, it is compared with other optimization methods over different datasets. Moreover, the experimental results support the improved performance of the proposed approach

  4. Parameters modelling of amaranth grain processing technology

    Science.gov (United States)

    Derkanosova, N. M.; Shelamova, S. A.; Ponomareva, I. N.; Shurshikova, G. V.; Vasilenko, O. A.

    2018-03-01

    The article presents a technique that allows calculating the structure of a multicomponent bakery mixture for the production of enriched products, taking into account the instability of nutrient content, and ensuring the fulfilment of technological requirements and, at the same time considering consumer preferences. The results of modelling and analysis of optimal solutions are given by the example of calculating the structure of a three-component mixture of wheat and rye flour with an enriching component, that is, whole-hulled amaranth flour applied to the technology of bread from a mixture of rye and wheat flour on a liquid leaven.

  5. Importance of design optimization of gamma processing plants

    International Nuclear Information System (INIS)

    George, Jain Reji

    2014-01-01

    Radiation processing of food commodities using ionizing radiations is well established world wide. In India too, novel designs are coming up for food irradiation as well as for multiproduct irradiation. It has been observed that though the designs of the product movement systems are excelling, the actual purpose for which the designs are made are failing in some. In such situations it is difficult to achieve an effective dose delivery by controlling the process parameters or even by modifying the source activity distribution without compromising some other aspects like throughput. It is very essential to arrive at an optimization in all components such as radiation source geometry, source product geometry and protective barriers of an irradiator system. Optimization of the various parameters can be done by modeling and analysis of the design

  6. Optimization of Cutting Parameters on Delamination of Drilling Glass-Polyester Composites

    Directory of Open Access Journals (Sweden)

    Majid Habeeb Faidh-Allah

    2018-02-01

    Full Text Available This paper attempted to study the effect of cutting parameters (spindle speed and feed rate on delamination phenomena during the drilling glass-polyester composites. Drilling process was done by CNC machine with 10 mm diameter of high-speed steel (HSS drill bit. Taguchi technique with L16 orthogonal layout was used to analyze the effective parameters on delamination factor. The optimal experiment was no. 13 with spindle speed 1273 rpm and feed 0.05 mm/rev with minimum delamination factor 1.28.

  7. Optimization of Minimum Quantity Lubricant Conditions and Cutting Parameters in Hard Milling of AISI H13 Steel

    OpenAIRE

    The-Vinh Do; Quang-Cherng Hsu

    2016-01-01

    As a successful solution applied to hard machining, the minimum quantity lubricant (MQL) has already been established as an alternative to flood coolant processing. The optimization of MQL parameters and cutting parameters under MQL condition are essential and pressing. The study was divided into two parts. In the first part of this study, the Taguchi method was applied to find the optimal values of MQL condition in the hard milling of AISI H13 with consideration of reduced surface roughness....

  8. Simulation and optimization of fractional crystallization processes

    DEFF Research Database (Denmark)

    Thomsen, Kaj; Rasmussen, Peter; Gani, Rafiqul

    1998-01-01

    A general method for the calculation of various types of phase diagrams for aqueous electrolyte mixtures is outlined. It is shown how the thermodynamic equilibrium precipitation process can be used to satisfy the operational needs of industrial crystallizer/centrifuge units. Examples of simulation...... and optimization of fractional crystallization processes are shown. In one of these examples, a process with multiple steady states is analyzed. The thermodynamic model applied for describing the highly non-ideal aqueous electrolyte systems is the Extended UNIQUAC model. (C) 1998 Published by Elsevier Science Ltd...

  9. The Process of Optimizing Mechanical Sound Quality in Product Design

    DEFF Research Database (Denmark)

    Eriksen, Kaare; Holst, Thomas

    2011-01-01

    The research field concerning optimizing product sound quality is a relatively unexplored area, and may become difficult for designers to operate in. To some degree, sound is a highly subjective parameter, which is normally targeted sound specialists. This paper describes the theoretical...... and practical background for managing a process of optimizing the mechanical sound quality in a product design by using simple tools and workshops systematically. The procedure is illustrated by a case study of a computer navigation tool (computer mouse or mouse). The process is divided into 4 phases, which...... clarify the importance of product sound, defining perceptive demands identified by users, and, finally, how to suggest mechanical principles for modification of an existing sound design. The optimized mechanical sound design is followed by tests on users of the product in its use context. The result...

  10. An Iterative Optimization Algorithm for Lens Distortion Correction Using Two-Parameter Models

    Directory of Open Access Journals (Sweden)

    Daniel Santana-Cedrés

    2016-12-01

    Full Text Available We present a method for the automatic estimation of two-parameter radial distortion models, considering polynomial as well as division models. The method first detects the longest distorted lines within the image by applying the Hough transform enriched with a radial distortion parameter. From these lines, the first distortion parameter is estimated, then we initialize the second distortion parameter to zero and the two-parameter model is embedded into an iterative nonlinear optimization process to improve the estimation. This optimization aims at reducing the distance from the edge points to the lines, adjusting two distortion parameters as well as the coordinates of the center of distortion. Furthermore, this allows detecting more points belonging to the distorted lines, so that the Hough transform is iteratively repeated to extract a better set of lines until no improvement is achieved. We present some experiments on real images with significant distortion to show the ability of the proposed approach to automatically correct this type of distortion as well as a comparison between the polynomial and division models.

  11. Electroreflectance of CuInS{sub 2}-solar cells for the optimization of the process parameters during the absorbers production process; Elektroreflexion an CuInS{sub 2}-Solarzellen im Hinblick auf die Optimierung der Prozessparameter bei der Absorber-Herstellung

    Energy Technology Data Exchange (ETDEWEB)

    Henninger, R.

    2002-07-01

    CuInS{sub 2} thin film solar cells were prepared by a new sequential process. The quality of these layers and the conversion efficiency of the solar cells depends on the process parameters of the sequential process. Electroreflectance measurements are used to characterize these solar cells. This method is suitable to measure optical properties like band gap energy and to detect secondary phases in the vicinity of the heterojunction and defects in the semiconductor. Electroreflectance measurements of the thin film solar cells shows clearly a dependence of film growth from the process parameters copper to indium ratio and sulfurization temperature. From the correlation of electroreflectance results with photoluminescence, X-ray-diffraction and external quantum efficiency measurements a model of film growth was derived. Solar cells made from optimized CuInS{sub 2} films reach an active area efficiency of 12,5%. This is the best efficiency reported so far for this type of solar cell. (orig.) [German] Mit einem neuen sequentiellen Verfahren wurden CuInS{sub 2}-Duennfilme fuer die Solarzellen-Anwendung hergestellt. Die Qualitaet dieser Schichten und damit der Solarzellenwirkungsgrad haengen von den Prozessparametern des sequentiellen Prozesses ab. Elektroreflexion wurde als Messverfahren zur Charakterisierung der fertigen Solarzellen eingesetzt. Dieses Verfahren ist geeignet um optische Eigenschaften, wie die Bandlueckenenergie, zu bestimmen und Fremdphasen in der Naehe des pn-Ueberganges sowie Defekte im Halbleiter nachzuweisen. In Elektroreflexionsmessungen an den hergestellten Duennfilmsolarzellen zeigte sich deutlich eine Abhaengigkeit des Schichtwachstums von den Prozessparametern Kupfer-Indium-Verhaeltnis und Sulfurisierungstemperatur. Aus der Korrelation der Elektroreflexionsergebnisse mit Photolumineszenz-, Roentgenbeugungs- und Quantenausbeutemessungen wurde ein Modell zur Schichtbildung von CuInS{sub 2} abgeleitet. Solarzellen aus optimierten CuInS{sub 2

  12. Fractional Order Controller Designing with Firefly Algorithm and Parameter Optimization for Hydroturbine Governing System

    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.

  13. Optimizing a Laser Process for Making Carbon Nanotubes

    Science.gov (United States)

    Arepalli, Sivaram; Nikolaev, Pavel; Holmes, William

    2010-01-01

    A systematic experimental study has been performed to determine the effects of each of the operating conditions in a double-pulse laser ablation process that is used to produce single-wall carbon nanotubes (SWCNTs). The comprehensive data compiled in this study have been analyzed to recommend conditions for optimizing the process and scaling up the process for mass production. The double-pulse laser ablation process for making SWCNTs was developed by Rice University researchers. Of all currently known nanotube-synthesizing processes (arc and chemical vapor deposition), this process yields the greatest proportion of SWCNTs in the product material. The aforementioned process conditions are important for optimizing the production of SWCNTs and scaling up production. Reports of previous research (mostly at Rice University) toward optimization of process conditions mention effects of oven temperature and briefly mention effects of flow conditions, but no systematic, comprehensive study of the effects of process conditions was done prior to the study described here. This was a parametric study, in which several production runs were carried out, changing one operating condition for each run. The study involved variation of a total of nine parameters: the sequence of the laser pulses, pulse-separation time, laser pulse energy density, buffer gas (helium or nitrogen instead of argon), oven temperature, pressure, flow speed, inner diameter of the flow tube, and flow-tube material.

  14. 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

  15. Optimal Machining Parameters for Achieving the Desired Surface Roughness in Turning of Steel

    Directory of Open Access Journals (Sweden)

    LB Abhang

    2012-06-01

    Full Text Available Due to the widespread use of highly automated machine tools in the metal cutting industry, manufacturing requires highly reliable models and methods for the prediction of output performance in the machining process. The prediction of optimal manufacturing conditions for good surface finish and dimensional accuracy plays a very important role in process planning. In the steel turning process the tool geometry and cutting conditions determine the time and cost of production which ultimately affect the quality of the final product. In the present work, experimental investigations have been conducted to determine the effect of the tool geometry (effective tool nose radius and metal cutting conditions (cutting speed, feed rate and depth of cut on surface finish during the turning of EN-31 steel. First and second order mathematical models are developed in terms of machining parameters by using the response surface methodology on the basis of the experimental results. The surface roughness prediction model has been optimized to obtain the surface roughness values by using LINGO solver programs. LINGO is a mathematical modeling language which is used in linear and nonlinear optimization to formulate large problems concisely, solve them, and analyze the solution in engineering sciences, operation research etc. The LINGO solver program is global optimization software. It gives minimum values of surface roughness and their respective optimal conditions.

  16. Optimization of cladding parameters for resisting corrosion on low carbon steels using simulated annealing algorithm

    Science.gov (United States)

    Balan, A. V.; Shivasankaran, N.; Magibalan, S.

    2018-04-01

    Low carbon steels used in chemical industries are frequently affected by corrosion. Cladding is a surfacing process used for depositing a thick layer of filler metal in a highly corrosive materials to achieve corrosion resistance. Flux cored arc welding (FCAW) is preferred in cladding process due to its augmented efficiency and higher deposition rate. In this cladding process, the effect of corrosion can be minimized by controlling the output responses such as minimizing dilution, penetration and maximizing bead width, reinforcement and ferrite number. This paper deals with the multi-objective optimization of flux cored arc welding responses by controlling the process parameters such as wire feed rate, welding speed, Nozzle to plate distance, welding gun angle for super duplex stainless steel material using simulated annealing technique. Regression equation has been developed and validated using ANOVA technique. The multi-objective optimization of weld bead parameters was carried out using simulated annealing to obtain optimum bead geometry for reducing corrosion. The potentiodynamic polarization test reveals the balanced formation of fine particles of ferrite and autenite content with desensitized nature of the microstructure in the optimized clad bead.

  17. Multi-objective optimization model of CNC machining to minimize processing time and environmental impact

    Science.gov (United States)

    Hamada, Aulia; Rosyidi, Cucuk Nur; Jauhari, Wakhid Ahmad

    2017-11-01

    Minimizing processing time in a production system can increase the efficiency of a manufacturing company. Processing time are influenced by application of modern technology and machining parameter. Application of modern technology can be apply by use of CNC machining, one of the machining process can be done with a CNC machining is turning. However, the machining parameters not only affect the processing time but also affect the environmental impact. Hence, optimization model is needed to optimize the machining parameters to minimize the processing time and environmental impact. This research developed a multi-objective optimization to minimize the processing time and environmental impact in CNC turning process which will result in optimal decision variables of cutting speed and feed rate. Environmental impact is converted from environmental burden through the use of eco-indicator 99. The model were solved by using OptQuest optimization software from Oracle Crystal Ball.

  18. Mixed-integer evolution strategies for parameter optimization and their applications to medical image analysis

    NARCIS (Netherlands)

    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

  19. Optimization Of A Mass Spectrometry Process

    International Nuclear Information System (INIS)

    Lopes, Jose; Alegria, F. Correa; Redondo, Luis; Barradas, N. P.; Alves, E.; Rocha, Jorge

    2011-01-01

    In this paper we present and discuss a system developed in order to optimize the mass spectrometry process of an ion implanter. The system uses a PC to control and display the mass spectrum. The operator interacts with the I/O board, that interfaces with the computer and the ion implanter by a LabVIEW code. Experimental results are shown and the capabilities of the system are discussed.

  20. Numerical simulation of distributed parameter processes

    CERN Document Server

    Colosi, Tiberiu; Unguresan, Mihaela-Ligia; Muresan, Vlad

    2013-01-01

    The present monograph defines, interprets and uses the matrix of partial derivatives of the state vector with applications for the study of some common categories of engineering. The book covers broad categories of processes that are formed by systems of partial derivative equations (PDEs), including systems of ordinary differential equations (ODEs). The work includes numerous applications specific to Systems Theory based on Mpdx, such as parallel, serial as well as feed-back connections for the processes defined by PDEs. For similar, more complex processes based on Mpdx with PDEs and ODEs as components, we have developed control schemes with PID effects for the propagation phenomena, in continuous media (spaces) or discontinuous ones (chemistry, power system, thermo-energetic) or in electro-mechanics (railway – traction) and so on. The monograph has a purely engineering focus and is intended for a target audience working in extremely diverse fields of application (propagation phenomena, diffusion, hydrodyn...

  1. SKOCh modified parameters and data processing method

    International Nuclear Information System (INIS)

    Abramov, V.V.; Baldin, B.Yu.; Vasil'chenko, V.G.

    1986-01-01

    Characteristics of a modified Cherenkov radiation ring spectrometer variant (SKOCH) are presented. Methods of experimental data processing are described. Different SKOCH optics variants are investigated. Multi-particle registering electronic equipment for data read-out from SKOCH providing for the improvement of multiparticle occurance registration conditions is applied in the course of measurements using proton beams. A system of SKOCH spectrometer data processing programms is developed and experimentally tested. Effective algorithm for calibrating Cherenkov radiation ring spectrometers with quite a large angular and radial aperture is developed. The on-line- and off-line-processing program complex provides for the complete control of SKOCH operation during statistics collection and for particle (π, K, P) identification within 5.5-30 GeV/c range

  2. On process optimization considering LCA methodology.

    Science.gov (United States)

    Pieragostini, Carla; Mussati, Miguel C; Aguirre, Pío

    2012-04-15

    The goal of this work is to research the state-of-the-art in process optimization techniques and tools based on LCA, focused in the process engineering field. A collection of methods, approaches, applications, specific software packages, and insights regarding experiences and progress made in applying the LCA methodology coupled to optimization frameworks is provided, and general trends are identified. The "cradle-to-gate" concept to define the system boundaries is the most used approach in practice, instead of the "cradle-to-grave" approach. Normally, the relationship between inventory data and impact category indicators is linearly expressed by the characterization factors; then, synergic effects of the contaminants are neglected. Among the LCIA methods, the eco-indicator 99, which is based on the endpoint category and the panel method, is the most used in practice. A single environmental impact function, resulting from the aggregation of environmental impacts, is formulated as the environmental objective in most analyzed cases. SimaPro is the most used software for LCA applications in literature analyzed. The multi-objective optimization is the most used approach for dealing with this kind of problems, where the ε-constraint method for generating the Pareto set is the most applied technique. However, a renewed interest in formulating a single economic objective function in optimization frameworks can be observed, favored by the development of life cycle cost software and progress made in assessing costs of environmental externalities. Finally, a trend to deal with multi-period scenarios into integrated LCA-optimization frameworks can be distinguished providing more accurate results upon data availability. Copyright © 2011 Elsevier Ltd. All rights reserved.

  3. Including Organizational Cultural Parameters in Work Processes

    National Research Council Canada - National Science Library

    Handley, Holly A; Heacox, Nancy J

    2004-01-01

    ... between decision-makers of different nationalities. In addition to nationality, a decision-maker is also a member of an organization and brings this organizational culture to his role in the work process, where it may also affect his task performance...

  4. Evaluation of Control Parameters for the Activated Sludge Process

    Science.gov (United States)

    Stall, T. Ray; Sherrard, Josephy H.

    1978-01-01

    An evaluation of the use of the parameters currently being used to design and operate the activated sludge process is presented. The advantages and disadvantages for the use of each parameter are discussed. (MR)

  5. Multi-objective optimization problems concepts and self-adaptive parameters with mathematical and engineering applications

    CERN Document Server

    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.

  6. Determining the optimum process parameter for grinding operations using robust process

    Energy Technology Data Exchange (ETDEWEB)

    Neseli, Suley Man; Asilturk, Ilhan; Celik, Levent [Univ. of Selcuk, Konya (Turkmenistan)

    2012-11-15

    We applied combined response surface methodology (RSM) and Taguchi methodology (TM) to determine optimum parameters for minimum surface roughness (Ra) and vibration (Vb) in external cylindrical grinding. First, an experiment was conducted in a CNC cylindrical grinding machine. The TM using L{sup 27} orthogonal array was applied to the design of the experiment. The three input parameters were workpiece revolution, feed rate and depth of cut; the outputs were vibrations and surface roughness. Second, to minimize wheel vibration and surface roughness, two optimized models were developed using computer aided single objective optimization. The experimental and statistical results revealed that the most significant grinding parameter for surface roughness and vibration is workpiece revolution followed by the depth of cut. The predicted values and measured values were fairly close, which indicates 2 ( 94.99 R{sup 2Ra}=and 2 92.73) R{sup 2Vb}=that the developed models can be effectively used to predict surface roughness and vibration in the grinding. The established model for determination of optimal operating conditions shows that a hybrid approach can lead to success of a robust process.

  7. Determining the optimum process parameter for grinding operations using robust process

    International Nuclear Information System (INIS)

    Neseli, Suley Man; Asilturk, Ilhan; Celik, Levent

    2012-01-01

    We applied combined response surface methodology (RSM) and Taguchi methodology (TM) to determine optimum parameters for minimum surface roughness (Ra) and vibration (Vb) in external cylindrical grinding. First, an experiment was conducted in a CNC cylindrical grinding machine. The TM using L 27 orthogonal array was applied to the design of the experiment. The three input parameters were workpiece revolution, feed rate and depth of cut; the outputs were vibrations and surface roughness. Second, to minimize wheel vibration and surface roughness, two optimized models were developed using computer aided single objective optimization. The experimental and statistical results revealed that the most significant grinding parameter for surface roughness and vibration is workpiece revolution followed by the depth of cut. The predicted values and measured values were fairly close, which indicates 2 ( 94.99 R 2Ra =and 2 92.73) R 2Vb =that the developed models can be effectively used to predict surface roughness and vibration in the grinding. The established model for determination of optimal operating conditions shows that a hybrid approach can lead to success of a robust process

  8. Genetic Algorithm-Based Optimization for Surface Roughness in Cylindrically Grinding Process Using Helically Grooved Wheels

    Science.gov (United States)

    Çaydaş, Ulaş; Çelik, Mahmut

    The present work is focused on the optimization of process parameters in cylindrical surface grinding of AISI 1050 steel with grooved wheels. Response surface methodology (RSM) and genetic algorithm (GA) techniques were merged to optimize the input variable parameters of grinding. The revolution speed of workpiece, depth of cut and number of grooves on the wheel were changed to explore their experimental effects on the surface roughness of machined bars. The mathematical models were established between the input parameters and response by using RSM. Then, the developed RSM model was used as objective functions on GA to optimize the process parameters.

  9. Characteristic parameters of the coal briquetting process

    International Nuclear Information System (INIS)

    Davkova, Katica

    1998-01-01

    The complete knowledge about the energetic sources in our country - Republic of Macedonia, point to the fact that coals are the most attractive and highly productive, still keeping the leadership position. However, the process of lignite exploitation causes their degradation and formation of large amount of fine fractions. The industrial valorization of these fractions is the most actual problem that could be solved only through production of made-up enriched fuels of wide spectrum of application. Thus, briquetting formation, with or without use of binds, is a process of mechanical or combined modification of coal fine fractions. At the same time, this is a possible procedure of solid fuels enrichment. Lignite from the Macedonian coal deposits 'Suvodol', 'Priskupshtina' and 'Brik-Berovo' is analyzed, in order to examine the possibilities of its briquetting. The results show that the 'Suvodol' lignite satisfy the quality requirements given with the MKS B H1.031 standard as well as the 'Brik-Berovo' lignite

  10. 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.

  11. 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.

  12. PROCESS TIME OPTIMIZATION IN DEPOSITOR AND FILLER

    Directory of Open Access Journals (Sweden)

    Jesús Iván Ruíz-Ibarra

    2017-07-01

    Full Text Available As in any industry, in soft drink manufacturing demand, customer service and production is of great importance that forces this production to have their equipment and production machines in optimal conditions for the product to be in the hands of the consumer without delays, therefore it is important to have the established times of each process, since the syrup is elaborated, packaged, distributed, until it is purchased by the consumer. After a chronometer analysis, the most common faults were detected in each analyzed process. In the filler machine the most frequent faults are: accumulation of bottles in the subsequent and previous processes to filling process, which in general the cause of the collection of bottles is due to failures in the other equipment of the production line. In the process of unloading the most common faults are: boxes jammed in bump and pusher (pushing boxes; boxes fallen in rollers and platforms transporter. According to observations in each machine, the actions to be followed are presented to solve the problems that arise. Also described the methodology to obtain results, to data analyze and decisions. Firstly an analysis of operations is done to know each machine, supported by the manuals of the machines and the operators themselves a study of times is done by chronometer to determine the standard time of the process where also they present the most common faults, then observations are made on the machines according to the determined sample size, thus obtaining the information necessary to take measurements and to make the study of optimization of the production processes. An analysis of the predetermined process times is also performed by the MTM methods and the MOST time analysis. The results of operators with MTM: Fault Filler = 0.846 minutes, Faultless Filler = 0.61 minutes, Fault Breaker = 0.74 minutes and Fault Flasher = 0.45 minutes. The results of MOST operators are: Fault Filler = 2.58 minutes, Filler Fails

  13. A novel optimization approach to estimating kinetic parameters of the enzymatic hydrolysis of corn stover

    Directory of Open Access Journals (Sweden)

    Fenglei Qi

    2016-01-01

    Full Text Available Enzymatic hydrolysis is an integral step in the conversion of lignocellulosic biomass to ethanol. The conversion of cellulose to fermentable sugars in the presence of inhibitors is a complex kinetic problem. In this study, we describe a novel approach to estimating the kinetic parameters underlying this process. This study employs experimental data measuring substrate and enzyme loadings, sugar and acid inhibitions for the production of glucose. Multiple objectives to minimize the difference between model predictions and experimental observations are developed and optimized by adopting multi-objective particle swarm optimization method. Model reliability is assessed by exploring likelihood profile in each parameter space. Compared to previous studies, this approach improved the prediction of sugar yields by reducing the mean squared errors by 34% for glucose and 2.7% for cellobiose, suggesting improved agreement between model predictions and the experimental data. Furthermore, kinetic parameters such as K2IG2, K1IG, K2IG, K1IA, and K3IA are identified as contributors to the model non-identifiability and wide parameter confidence intervals. Model reliability analysis indicates possible ways to reduce model non-identifiability and tighten parameter confidence intervals. These results could help improve the design of lignocellulosic biorefineries by providing higher fidelity predictions of fermentable sugars under inhibitory conditions.

  14. Optimization of operating parameters in polysilicon chemical vapor deposition reactor with response surface methodology

    Science.gov (United States)

    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.

  15. Optimizing parameters of a technical system using quality function deployment method

    Science.gov (United States)

    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.

  16. Intelligent methods for the process parameter determination of plastic injection molding

    Science.gov (United States)

    Gao, Huang; Zhang, Yun; Zhou, Xundao; Li, Dequn

    2018-03-01

    Injection molding is one of the most widely used material processing methods in producing plastic products with complex geometries and high precision. The determination of process parameters is important in obtaining qualified products and maintaining product quality. This article reviews the recent studies and developments of the intelligent methods applied in the process parameter determination of injection molding. These intelligent methods are classified into three categories: Case-based reasoning methods, expert system- based methods, and data fitting and optimization methods. A framework of process parameter determination is proposed after comprehensive discussions. Finally, the conclusions and future research topics are discussed.

  17. Optimal Information Processing in Biochemical Networks

    Science.gov (United States)

    Wiggins, Chris

    2012-02-01

    A variety of experimental results over the past decades provide examples of near-optimal information processing in biological networks, including in biochemical and transcriptional regulatory networks. Computing information-theoretic quantities requires first choosing or computing the joint probability distribution describing multiple nodes in such a network --- for example, representing the probability distribution of finding an integer copy number of each of two interacting reactants or gene products while respecting the `intrinsic' small copy number noise constraining information transmission at the scale of the cell. I'll given an overview of some recent analytic and numerical work facilitating calculation of such joint distributions and the associated information, which in turn makes possible numerical optimization of information flow in models of noisy regulatory and biochemical networks. Illustrating cases include quantification of form-function relations, ideal design of regulatory cascades, and response to oscillatory driving.

  18. Plasma spray technology process parameters and applications

    International Nuclear Information System (INIS)

    Sreekumar, K.P.; Karthikeyan, J.; Ananthapadmanabhan, P.V.; Venkatramani, N.; Chatterjee, U.K.

    1991-01-01

    The current trend in the structural design philosophy is based on the use of substrate with the necessary mechanical properties and a thin coating to exhibit surface properties. Plasma spray process is a versatile surface coating technique which finds extensive application in meeting advance technologies. This report describes the plasma spray technique and its use in developing coatings for various applications. The spray system is desribed in detail including the different variables such as power input to the torch, gas flow rate, powder properties, powder injection, etc. and their interrelation in deciding the quality of the coating. A brief write-up on the various plasma spray coatings developed for different applications is also included. (author). 15 refs., 15 figs., 2 tabs

  19. Benchmarking of radiological departments. Starting point for successful process optimization

    International Nuclear Information System (INIS)

    Busch, Hans-Peter

    2010-01-01

    Continuous optimization of the process of organization and medical treatment is part of the successful management of radiological departments. The focus of this optimization can be cost units such as CT and MRI or the radiological parts of total patient treatment. Key performance indicators for process optimization are cost- effectiveness, service quality and quality of medical treatment. The potential for improvements can be seen by comparison (benchmark) with other hospitals and radiological departments. Clear definitions of key data and criteria are absolutely necessary for comparability. There is currently little information in the literature regarding the methodology and application of benchmarks especially from the perspective of radiological departments and case-based lump sums, even though benchmarking has frequently been applied to radiological departments by hospital management. The aim of this article is to describe and discuss systematic benchmarking as an effective starting point for successful process optimization. This includes the description of the methodology, recommendation of key parameters and discussion of the potential for cost-effectiveness analysis. The main focus of this article is cost-effectiveness (efficiency and effectiveness) with respect to cost units and treatment processes. (orig.)

  20. A procedure for multi-objective optimization of tire design parameters

    OpenAIRE

    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...

  1. Optimization of Loudspeaker Part Design Parameters by Air Viscosity Damping Effect

    OpenAIRE

    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...

  2. Data Mining Process Optimization in Computational Multi-agent Systems

    OpenAIRE

    Kazík, O.; Neruda, R. (Roman)

    2015-01-01

    In this paper, we present an agent-based solution of metalearning problem which focuses on optimization of data mining processes. We exploit the framework of computational multi-agent systems in which various meta-learning problems have been already studied, e.g. parameter-space search or simple method recommendation. In this paper, we examine the effect of data preprocessing for machine learning problems. We perform the set of experiments in the search-space of data mining processes which is...

  3. 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

  4. Optimization of the fiber laser parameters for local high-temperature impact on metal

    Science.gov (United States)

    Yatsko, Dmitrii S.; Polonik, Marina V.; Dudko, Olga V.

    2016-11-01

    This paper presents the local laser heating process of surface layer of the metal sample. The aim is to create the molten pool with the required depth by laser thermal treatment. During the heating the metal temperature at any point of the molten zone should not reach the boiling point of the main material. The laser power, exposure time and the spot size of a laser beam are selected as the variable parameters. The mathematical model for heat transfer in a semi-infinite body, applicable to finite slab, is used for preliminary theoretical estimation of acceptable parameters values of the laser thermal treatment. The optimization problem is solved by using an algorithm based on the scanning method of the search space (the zero-order method of conditional optimization). The calculated values of the parameters (the optimal set of "laser radiation power - exposure time - spot radius") are used to conduct a series of natural experiments to obtain a molten pool with the required depth. A two-stage experiment consists of: a local laser treatment of metal plate (steel) and then the examination of the microsection of the laser irradiated region. According to the experimental results, we can judge the adequacy of the ongoing calculations within the selected models.

  5. 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.

  6. Optimization and Simulation of SLM Process for High Density H13 Tool Steel Parts

    Science.gov (United States)

    Laakso, Petri; Riipinen, Tuomas; Laukkanen, Anssi; Andersson, Tom; Jokinen, Antero; Revuelta, Alejandro; Ruusuvuori, Kimmo

    This paper demonstrates the successful printing and optimization of processing parameters of high-strength H13 tool steel by Selective Laser Melting (SLM). D-Optimal Design of Experiments (DOE) approach is used for parameter optimization of laser power, scanning speed and hatch width. With 50 test samples (1×1×1cm) we establish parameter windows for these three parameters in relation to part density. The calculated numerical model is found to be in good agreement with the density data obtained from the samples using image analysis. A thermomechanical finite element simulation model is constructed of the SLM process and validated by comparing the calculated densities retrieved from the model with the experimentally determined densities. With the simulation tool one can explore the effect of different parameters on density before making any printed samples. Establishing a parameter window provides the user with freedom for parameter selection such as choosing parameters that result in fastest print speed.

  7. Influence analysis of sewage sludge methane fermentation parameters on process efficiency

    Directory of Open Access Journals (Sweden)

    Катерина Борисівна Сорокіна

    2016-12-01

    Full Text Available The efficiency dependence of sewage sludge organic matter decomposition from organization and conditions of the process is analyzed. Support of the optimal values of several parameters ensures to provide completeness of the sludge fermentation process and obtain biogas in calculated amount. Biogas utilization reduces costs for reactor heating and provides additional obtaining of other types of energy

  8. Influence analysis of sewage sludge methane fermentation parameters on process efficiency

    OpenAIRE

    Катерина Борисівна Сорокіна

    2016-01-01

    The efficiency dependence of sewage sludge organic matter decomposition from organization and conditions of the process is analyzed. Support of the optimal values of several parameters ensures to provide completeness of the sludge fermentation process and obtain biogas in calculated amount. Biogas utilization reduces costs for reactor heating and provides additional obtaining of other types of energy

  9. Maximising municipal solid waste--legume trimming residue mixture degradation in composting by control parameters optimization.

    Science.gov (United States)

    Cabeza, I O; López, R; Ruiz-Montoya, M; Díaz, M J

    2013-10-15

    Composting is one of the most successful biological processes for the treatment of the residues enriched in putrescible materials. The optimization of parameters which have an influence on the stability of the products is necessary in order to maximize recycling and recovery of waste components. The influence of the composting process parameters (aeration, moisture, C/N ratio, and time) on the stability parameters (organic matter, N-losses, chemical oxygen demand, nitrate, biodegradability coefficient) of the compost was studied. The composting experiment was carried out using Municipal Solid Waste (MSW) and Legume Trimming Residues (LTR) in 200 L isolated acrylic barrels following a Box-Behnken central composite experimental design. Second-order polynomial models were found for each of the studied compost stability parameter, which accurately described the relationship between the parameters. The differences among the experimental values and those estimated by using the equations never exceeded 10% of the former. Results of the modelling showed that excluding the time, the C/N ratio is the strongest variable influencing almost all the stability parameters studied in this case, with the exception of N-losses which is strongly dependent on moisture. Moreover, an optimized ratio MSW/LTR of 1/1 (w/w), moisture content in the range of 40-55% and moderate to low aeration rate (0.05-0.175 Lair kg(-)(1) min(-1)) is recommended to maximise degradation and to obtain a stable product during co-composting of MSW and LTR. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. Design and optimization of sustainable process technologies

    DEFF Research Database (Denmark)

    Mussatto, Solange I.; Qin, Fen; Yamakawa, Celina Kiyomi

    has been then considered a keypoint to achieve such purposes, being also able to result in potential environmental, economic, and social benefits. In this sense, the Biomass Conversion and Bioprocess TechnologyGroup (BCBT) has been working on the development of newstrategies for the use of biomass......, minimizing the costs and maximizing the efficiencyand productivity.Once the optimal conditions are identified, the process scale-up can be then evaluated. This could be translated in a faster time to market for newprocess technologies....

  11. Discrete stochastic processes and optimal filtering

    CERN Document Server

    Bertein, Jean-Claude

    2012-01-01

    Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. This book provides a comprehensive overview of this area, discussing random and Gaussian vectors, outlining the results necessary for the creation of Wiener and adaptive filters used for stationary signals, as well as examining Kalman filters which ar

  12. 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)

  13. Optimization of IBF parameters based on adaptive tool-path algorithm

    Science.gov (United States)

    Deng, Wen Hui; Chen, Xian Hua; Jin, Hui Liang; Zhong, Bo; Hou, Jin; Li, An Qi

    2018-03-01

    As a kind of Computer Controlled Optical Surfacing(CCOS) technology. Ion Beam Figuring(IBF) has obvious advantages in the control of surface accuracy, surface roughness and subsurface damage. The superiority and characteristics of IBF in optical component processing are analyzed from the point of view of removal mechanism. For getting more effective and automatic tool path with the information of dwell time, a novel algorithm is proposed in this thesis. Based on the removal functions made through our IBF equipment and the adaptive tool-path, optimized parameters are obtained through analysis the residual error that would be created in the polishing process. A Φ600 mm plane reflector element was used to be a simulation instance. The simulation result shows that after four combinations of processing, the surface accuracy of PV (Peak Valley) value and the RMS (Root Mean Square) value was reduced to 4.81 nm and 0.495 nm from 110.22 nm and 13.998 nm respectively in the 98% aperture. The result shows that the algorithm and optimized parameters provide a good theoretical for high precision processing of IBF.

  14. 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.

  15. Hydrologic Process-oriented Optimization of Electrical Resistivity Tomography

    Science.gov (United States)

    Hinnell, A.; Bechtold, M.; Ferre, T. A.; van der Kruk, J.

    2010-12-01

    Electrical resistivity tomography (ERT) is commonly used in hydrologic investigations. Advances in joint and coupled hydrogeophysical inversion have enhanced the quantitative use of ERT to construct and condition hydrologic models (i.e. identify hydrologic structure and estimate hydrologic parameters). However the selection of which electrical resistivity data to collect and use is often determined by a combination of data requirements for geophysical analysis, intuition on the part of the hydrogeophysicist and logistical constraints of the laboratory or field site. One of the advantages of coupled hydrogeophysical inversion is the direct link between the hydrologic model and the individual geophysical data used to condition the model. That is, there is no requirement to collect geophysical data suitable for independent geophysical inversion. The geophysical measurements collected can be optimized for estimation of hydrologic model parameters rather than to develop a geophysical model. Using a synthetic model of drip irrigation we evaluate the value of individual resistivity measurements to describe the soil hydraulic properties and then use this information to build a data set optimized for characterizing hydrologic processes. We then compare the information content in the optimized data set with the information content in a data set optimized using a Jacobian sensitivity analysis.

  16. Optimization of multilayer neural network parameters for speaker recognition

    Science.gov (United States)

    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.

  17. Optimization of Key Parameters of Energy Management Strategy for Hybrid Electric Vehicle Using DIRECT Algorithm

    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.

  18. Optimization of control parameters for SR in EDM injection flushing type on stainless steel 304 workpiece

    International Nuclear Information System (INIS)

    Reza, M S; Yusoff, A R; Shaharun, M A

    2012-01-01

    The operating control parameters of injection flushing type of electrical discharge machining process on stainless steel 304 workpiece with copper tools are being optimized according to its individual machining characteristic i.e. surface roughness (SR). Higher SR during EDM machining process results for poor surface integrity of the workpiece. Hence, the quality characteristic for SR is set to lower-the-better to achieve the optimum surface integrity. Taguchi method has been used for the construction, layout and analysis of the experiment for each of the machining characteristic for the SR. The use of Taguchi method in the experiment saves a lot of time and cost of machining the experiment samples. Therefore, an L18 Orthogonal array which was the fundamental component in the statistical design of experiments has been used to plan the experiments and Analysis of Variance (ANOVA) is used to determine the optimum machining parameters for this machining characteristic. The control parameters selected for this optimization experiments are polarity, pulse on duration, discharge current, discharge voltage, machining depth, machining diameter and dielectric liquid pressure. The result had shown that the lower the machining diameter, the lower will be the SR.

  19. An experimental study on effect of process parameters in deep ...

    African Journals Online (AJOL)

    The effects of various deep drawing process parameters were determined by experimental study with the use of Taguchi fractional factorial design and analysis of variance for AA6111 Aluminum alloy. The optimum process parameters were determined based on their influence on the thickness variation at different regions ...

  20. Big Data Components for Business Process Optimization

    Directory of Open Access Journals (Sweden)

    Mircea Raducu TRIFU

    2016-01-01

    Full Text Available In these days, more and more people talk about Big Data, Hadoop, noSQL and so on, but very few technical people have the necessary expertise and knowledge to work with those concepts and technologies. The present issue explains one of the concept that stand behind two of those keywords, and this is the map reduce concept. MapReduce model is the one that makes the Big Data and Hadoop so powerful, fast, and diverse for business process optimization. MapReduce is a programming model with an implementation built to process and generate large data sets. In addition, it is presented the benefits of integrating Hadoop in the context of Business Intelligence and Data Warehousing applications. The concepts and technologies behind big data let organizations to reach a variety of objectives. Like other new information technologies, the main important objective of big data technology is to bring dramatic cost reduction.

  1. The Brewing Process: Optimizing the Fermentation

    Directory of Open Access Journals (Sweden)

    Teodora Coldea

    2014-11-01

    Full Text Available Beer is a carbonated alcoholic beverage obtained by alcoholic fermentation of malt wort boiled with hops. Brown beer obtained at Beer Pilot Station of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca was the result of a recipe based on blond, caramel and black malt in different proportions, water, hops and yeast. This study aimed to monitorize the evolution of wort in primary and secondary alcoholic fermentation in order to optimize the process. Two wort batches were assambled in order to increase the brewing yeast fermentation performance. The primary fermentation was 14 days, followed by another 14 days of secondary fermentation (maturation. The must fermentation monitoring was done by the automatic FermentoStar analyzer. The whole fermentation process was monitorized (temperature, pH, alcohol concentration, apparent and total wort extract.

  2. A Particle Swarm Optimization Algorithm for Optimal Operating Parameters of VMI Systems in a Two-Echelon Supply Chain

    Science.gov (United States)

    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.

  3. Biosorption of Cd(II), Ni(II) and Pb(II) from aqueous solution by dried biomass of aspergillus niger: application of response surface methodology to the optimization of process parameters

    Energy Technology Data Exchange (ETDEWEB)

    Amini, Malihe; Younesi, Habibollah [Department of Environmental Science, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Noor (Iran)

    2009-10-15

    In this study, the biosorption of Cd(II), Ni(II) and Pb(II) on Aspergillus niger in a batch system was investigated, and optimal condition determined by means of central composite design (CCD) under response surface methodology (RSM). Biomass inactivated by heat and pretreated by alkali solution was used in the determination of optimal conditions. The effect of initial solution pH, biomass dose and initial ion concentration on the removal efficiency of metal ions by A. niger was optimized using a design of experiment (DOE) method. Experimental results indicated that the optimal conditions for biosorption were 5.22 g/L, 89.93 mg/L and 6.01 for biomass dose, initial ion concentration and solution pH, respectively. Enhancement of metal biosorption capacity of the dried biomass by pretreatment with sodium hydroxide was observed. Maximal removal efficiencies for Cd(II), Ni(III) and Pb(II) ions of 98, 80 and 99% were achieved, respectively. The biosorption capacity of A. niger biomass obtained for Cd(II), Ni(II) and Pb(II) ions was 2.2, 1.6 and 4.7 mg/g, respectively. According to these observations the fungal biomass of A. niger is a suitable biosorbent for the removal of heavy metals from aqueous solutions. Multiple response optimization was applied to the experimental data to discover the optimal conditions for a set of responses, simultaneously, by using a desirability function. (Abstract Copyright [2009], Wiley Periodicals, Inc.)

  4. Simulative design and process optimization of the two-stage stretch-blow molding process

    Energy Technology Data Exchange (ETDEWEB)

    Hopmann, Ch.; Rasche, S.; Windeck, C. [Institute of Plastics Processing at RWTH Aachen University (IKV) Pontstraße 49, 52062 Aachen (Germany)

    2015-05-22

    The total production costs of PET bottles are significantly affected by the costs of raw material. Approximately 70 % of the total costs are spent for the raw material. Therefore, stretch-blow molding industry intends to reduce the total production costs by an optimized material efficiency. However, there is often a trade-off between an optimized material efficiency and required product properties. Due to a multitude of complex boundary conditions, the design process of new stretch-blow molded products is still a challenging task and is often based on empirical knowledge. Application of current CAE-tools supports the design process by reducing development time and costs. This paper describes an approach to determine optimized preform geometry and corresponding process parameters iteratively. The wall thickness distribution and the local stretch ratios of the blown bottle are calculated in a three-dimensional process simulation. Thereby, the wall thickness distribution is correlated with an objective function and preform geometry as well as process parameters are varied by an optimization algorithm. Taking into account the correlation between material usage, process history and resulting product properties, integrative coupled simulation steps, e.g. structural analyses or barrier simulations, are performed. The approach is applied on a 0.5 liter PET bottle of Krones AG, Neutraubling, Germany. The investigations point out that the design process can be supported by applying this simulative optimization approach. In an optimization study the total bottle weight is reduced from 18.5 g to 15.5 g. The validation of the computed results is in progress.

  5. Simulative design and process optimization of the two-stage stretch-blow molding process

    International Nuclear Information System (INIS)

    Hopmann, Ch.; Rasche, S.; Windeck, C.

    2015-01-01

    The total production costs of PET bottles are significantly affected by the costs of raw material. Approximately 70 % of the total costs are spent for the raw material. Therefore, stretch-blow molding industry intends to reduce the total production costs by an optimized material efficiency. However, there is often a trade-off between an optimized material efficiency and required product properties. Due to a multitude of complex boundary conditions, the design process of new stretch-blow molded products is still a challenging task and is often based on empirical knowledge. Application of current CAE-tools supports the design process by reducing development time and costs. This paper describes an approach to determine optimized preform geometry and corresponding process parameters iteratively. The wall thickness distribution and the local stretch ratios of the blown bottle are calculated in a three-dimensional process simulation. Thereby, the wall thickness distribution is correlated with an objective function and preform geometry as well as process parameters are varied by an optimization algorithm. Taking into account the correlation between material usage, process history and resulting product properties, integrative coupled simulation steps, e.g. structural analyses or barrier simulations, are performed. The approach is applied on a 0.5 liter PET bottle of Krones AG, Neutraubling, Germany. The investigations point out that the design process can be supported by applying this simulative optimization approach. In an optimization study the total bottle weight is reduced from 18.5 g to 15.5 g. The validation of the computed results is in progress

  6. Elements of an algorithm for optimizing a parameter-structural neural network

    Science.gov (United States)

    Mrówczyńska, Maria

    2016-06-01

    The field of processing information provided by measurement results is one of the most important components of geodetic technologies. The dynamic development of this field improves classic algorithms for numerical calculations in the aspect of analytical solutions that are difficult to achieve. Algorithms based on artificial intelligence in the form of artificial neural networks, including the topology of connections between neurons have become an important instrument connected to the problem of processing and modelling processes. This concept results from the integration of neural networks and parameter optimization methods and makes it possible to avoid the necessity to arbitrarily define the structure of a network. This kind of extension of the training process is exemplified by the algorithm called the Group Method of Data Handling (GMDH), which belongs to the class of evolutionary algorithms. The article presents a GMDH type network, used for modelling deformations of the geometrical axis of a steel chimney during its operation.

  7. Geometry-Driven-Diffusion filtering of MR Brain Images using dissimilarities and optimal relaxation parameter

    Energy Technology Data Exchange (ETDEWEB)

    Bajla, Ivan [Austrian Research Centres Sibersdorf, Department of High Performance Image Processing and Video-Technology, A-2444 Seibersdorf (Austria); Hollander, Igor [Institute of information Processing, Austrian Academy of Sciences, Sonnenfelsgasse 19/2, 1010 Wien (Austria)

    1999-12-31

    A novel method of local adapting of the conductance using a pixel dissimilarity measure is developed. An alternative processing methodology is proposed, which is based on intensity gradient histogram calculated for region interiors and boundaries of a phantom which models real MR brain scans. It involves a specific cost function suitable for the calculation of the optimum relaxation parameter Kopt and for the selection of the optimal exponential conductance. Computer experiments for locally adaptive geometry-driven-diffusion filtering of an MR brain phantom have been performed and evaluated. (authors) 6 refs., 3 figs.2 tabs.

  8. Geometry-Driven-Diffusion filtering of MR Brain Images using dissimilarities and optimal relaxation parameter

    International Nuclear Information System (INIS)

    Bajla, Ivan; Hollander, Igor

    1998-01-01

    A novel method of local adapting of the conductance using a pixel dissimilarity measure is developed. An alternative processing methodology is proposed, which is based on intensity gradient histogram calculated for region interiors and boundaries of a phantom which models real MR brain scans. It involves a specific cost function suitable for the calculation of the optimum relaxation parameter Kopt and for the selection of the optimal exponential conductance. Computer experiments for locally adaptive geometry-driven-diffusion filtering of an MR brain phantom have been performed and evaluated. (authors)

  9. 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.

  10. Optimizing Acquisition Parameters for MASW in Shallow Water

    NARCIS (Netherlands)

    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

  11. Hybrid artificial bee colony algorithm for parameter optimization of five-parameter bidirectional reflectance distribution function model.

    Science.gov (United States)

    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.

  12. STATISTICAL APPROACH FOR MULTI CRITERIA OPTIMIZATION OF CUTTING PARAMETERS OF TURNING ON HEAT TREATED BERYLLIUM COPPER ALLOY

    Directory of Open Access Journals (Sweden)

    K. DEVAKI DEVI

    2017-08-01

    Full Text Available In machining operations, achieving desired performance features of the machined product, is really a challenging job. Because, these quality features are highly correlated and are expected to be influenced directly or indirectly by the direct effect of process parameters or their interactive effects. This paper presents effective method and to determine optimal machining parameters in a turning operation on heat treated Beryllium copper alloy to minimize the surface roughness, cutting forces and work tool interface temperature along with the maximization of metal removal rate. The scope of this work is extended to Multi Objective Optimization. Response Surface Methodology is opted for preparing the design matrix, generating ANOVA, and optimization. A powerful model would be obtained with high accuracy to analyse the effect of each parameter on the output. The input parameters considered in this work are cutting speed, feed, depth of cut, work material (Annealed and Hardened and tool material (CBN and HSS.

  13. Optimization of ohmic heating parameters for polyphenoloxidase inactivation in not-from-concentrate elstar apple juice using RSM

    DEFF Research Database (Denmark)

    Abedelmaksoud, Tarek; Mohsen, Sobhy Mohamed; Duedahl-Olesen, Lene

    2018-01-01

    In this study, optimization of ohmic heating (OH) process parameters (temperature and voltage gradient) to inactivate polyphenoloxidase (PPO) of not-from-concentrate (NFC) apple juice was conducted. Response surface methodology was used for optimization of OH parameters, where the voltage gradient...... and temperature on the PPO activity in the NFC apple juice was evaluated. Then the optimized condition was used to produce the NFC apple juice and the quality parameters were evaluated and compared to NFC apple juice prepared by conventional heating (CH). The studied parameters were: PPO activity, total phenolic......, total carotenoids, ascorbic acid, cloud value, color as well as physical properties (i.e., TSS, acidity, electric conductivity and viscosity). The reduction of PPO activities was 97 and 91% for OH (at 40 V/cm and 80 °C) and CH (at 90 °C and 60 s), respectively. The reduction of the ascorbic acid...

  14. Anode baking process optimization through computer modelling

    Energy Technology Data Exchange (ETDEWEB)

    Wilburn, D.; Lancaster, D.; Crowell, B. [Noranda Aluminum, New Madrid, MO (United States); Ouellet, R.; Jiao, Q. [Noranda Technology Centre, Pointe Claire, PQ (Canada)

    1998-12-31

    Carbon anodes used in aluminum electrolysis are produced in vertical or horizontal type anode baking furnaces. The carbon blocks are formed from petroleum coke aggregate mixed with a coal tar pitch binder. Before the carbon block can be used in a reduction cell it must be heated to pyrolysis. The baking process represents a large portion of the aluminum production cost, and also has a significant effect on anode quality. To ensure that the baking of the anode is complete, it must be heated to about 1100 degrees C. To improve the understanding of the anode baking process and to improve its efficiency, a menu-driven heat, mass and fluid flow simulation tool, called NABSIM (Noranda Anode Baking SIMulation), was developed and calibrated in 1993 and 1994. It has been used since then to evaluate and screen firing practices, and to determine which firing procedure will produce the optimum heat-up rate, final temperature, and soak time, without allowing unburned tar to escape. NABSIM is used as a furnace simulation tool on a daily basis by Noranda plant process engineers and much effort is expended in improving its utility by creating new versions, and the addition of new modules. In the immediate future, efforts will be directed towards optimizing the anode baking process to improve temperature uniformity from pit to pit. 3 refs., 4 figs.

  15. Information theoretic methods for image processing algorithm optimization

    Science.gov (United States)

    Prokushkin, Sergey F.; Galil, Erez

    2015-01-01

    Modern image processing pipelines (e.g., those used in digital cameras) are full of advanced, highly adaptive filters that often have a large number of tunable parameters (sometimes > 100). This makes the calibration procedure for these filters very complex, and the optimal results barely achievable in the manual calibration; thus an automated approach is a must. We will discuss an information theory based metric for evaluation of algorithm adaptive characteristics ("adaptivity criterion") using noise reduction algorithms as an example. The method allows finding an "orthogonal decomposition" of the filter parameter space into the "filter adaptivity" and "filter strength" directions. This metric can be used as a cost function in automatic filter optimization. Since it is a measure of a physical "information restoration" rather than perceived image quality, it helps to reduce the set of the filter parameters to a smaller subset that is easier for a human operator to tune and achieve a better subjective image quality. With appropriate adjustments, the criterion can be used for assessment of the whole imaging system (sensor plus post-processing).

  16. Optimization of parameters for semiempirical methods VI: more modifications to the NDDO approximations and re-optimization of parameters.

    Science.gov (United States)

    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.

  17. Selecting and optimizing eco-physiological parameters of Biome-BGC to reproduce observed woody and leaf biomass growth of Eucommia ulmoides plantation in China using Dakota optimizer

    Science.gov (United States)

    Miyauchi, T.; Machimura, T.

    2013-12-01

    In the simulation using an ecosystem process model, the adjustment of parameters is indispensable for improving the accuracy of prediction. This procedure, however, requires much time and effort for approaching the simulation results to the measurements on models consisting of various ecosystem processes. In this study, we tried to apply a general purpose optimization tool in the parameter optimization of an ecosystem model, and examined its validity by comparing the simulated and measured biomass growth of a woody plantation. A biometric survey of tree biomass growth was performed in 2009 in an 11-year old Eucommia ulmoides plantation in Henan Province, China. Climate of the site was dry temperate. Leaf, above- and below-ground woody biomass were measured from three cut trees and converted into carbon mass per area by measured carbon contents and stem density. Yearly woody biomass growth of the plantation was calculated according to allometric relationships determined by tree ring analysis of seven cut trees. We used Biome-BGC (Thornton, 2002) to reproduce biomass growth of the plantation. Air temperature and humidity from 1981 to 2010 was used as input climate condition. The plant functional type was deciduous broadleaf, and non-optimizing parameters were left default. 11-year long normal simulations were performed following a spin-up run. In order to select optimizing parameters, we analyzed the sensitivity of leaf, above- and below-ground woody biomass to eco-physiological parameters. Following the selection, optimization of parameters was performed by using the Dakota optimizer. Dakota is an optimizer developed by Sandia National Laboratories for providing a systematic and rapid means to obtain optimal designs using simulation based models. As the object function, we calculated the sum of relative errors between simulated and measured leaf, above- and below-ground woody carbon at each of eleven years. In an alternative run, errors at the last year (at the

  18. Temporal and spatial heterogeneity analysis of optimal value of sensitive parameters in ecological process model: The BIOME-BGC model as an example%生态过程模型敏感参数最优取值的时空异质性分析——以BIOME-BGC模型为例

    Institute of Scientific and Technical Information of China (English)

    李一哲; 张廷龙; 刘秋雨; 李英

    2018-01-01

    The ecological process models are powerful tools for studying terrestrial ecosystem water and carbon cycle at present.However,there are many parameters for these models,and weather the reasonable values of these parameters were taken,have important impact on the models simulation results.In the past,the sensitivity and the optimization of model parameters were analyzed and discussed in many researches.But the temporal and spatial heterogeneity of the optimal parameters is less concerned.In this paper,the BIOME-BGC model was used as an example.In the evergreen broad-leaved forest,deciduous broad-leaved forest and C3 grassland,the sensitive parameters of the model were selected by constructing the sensitivity judgment index with two experimental sites selected under each vegetation type.The objective function was constructed by using the simulated annealing algorithm combined with the flux data to obtain the monthly optimal values of the sensitive parameters at each site.Then we constructed the temporal heterogeneity judgment index,the spatial heterogeneity judgment index and the temporal and spatial heterogeneity judgment index to quantitatively analyze the temporal and spatial heterogeneity of the optimal values of the model sensitive parameters.The results showed that the sensitivity of BIOME-BGC model parameters was different under different vegetation types,but the selected sensitive parameters were mostly consistent.The optimal values of the sensitive parameters of BIOME-BGC model mostly presented time-space heterogeneity to different degrees which varied with vegetation types.The sensitive parameters related to vegetation physiology and ecology had relatively little temporal and spatial heterogeneity while those related to environment and phenology had generally larger temporal and spatial heterogeneity.In addition,the temporal heterogeneity of the optimal values of the model sensitive parameters showed a significant linear correlation with the spatial

  19. 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...

  20. Optimization of control parameters for petroleum waste composting

    Institute of Scientific and Technical Information of China (English)

    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.