WorldWideScience

Sample records for waste parameter optimization

  1. Optimization of extraction parameters for trehalose from beer waste ...

    African Journals Online (AJOL)

    ... be 103.15 μg/s; it was 15.96 times higher than microwave and 34.08 times higher than ultrasound. This demonstrated that the PEF could be regarded as a promising technique for bio-material extraction. Key words: High-intensity pulsed electric field (PEF), Beer waste brewing yeast (BWBY), Trehalose, Regression model.

  2. Vacuum pyrolysis characteristics and parameter optimization of recycling organic materials from waste tantalum capacitors.

    Science.gov (United States)

    Chen, Zhenyang; Niu, Bo; Zhang, Lingen; Xu, Zhenming

    2018-01-15

    Recycling rare metal tantalum from waste tantalum capacitors (WTCs) is significant to alleviate the shortage of tantalum resource. However, environmental problems will be caused if the organic materials from WTCs are improperly disposed. This study presented a promising vacuum pyrolysis technology to recycle the organic materials from WTCs. The organics removal rate could reach 94.32wt% according to TG results. The optimal parameters were determined as 425°C, 50Pa and 30min on the basis of response surface methodology (RSM). The oil yield and residual rate was 18.09wt% and 74.94wt%, respectively. All pyrolysis products can be recycled through a reasonable route. Besides, to deeply understand the pyrolysis process, the pyrolysis mechanism was also proposed based on the product and free radical theory. This paper provides an efficient process for recycling the organic material from WTCs, which can facilitate the following tantalum recovery. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Radioactive wastes Conditioning. Optimization of operating parameters by the experience plan method

    Directory of Open Access Journals (Sweden)

    bouchra El hilal

    2016-02-01

    Full Text Available The conditioning of exhausted Resins Exchanging Ions (REI (radioactive wastes generated by nuclear operations was optimized using a full factorial experiments plan 24. Sixteen experiments with a suitable choice of four interpretable variables led to a mathematical model in the form of a first degree polynomial. After analysing the effects, this model showed that the most influential factor on the response (compression strength is the water/cement ratio (W/C with a positive effect of (+2.17, the second factor in order is the mixing time with a positive effect of (+1.54. The interaction between the (W/C and the number of vibration and interaction between the (W/C and the mixing time also have effects on the response.

  4. Production of melanin by soil microbial isolate on fruit waste extract: two step optimization of key parameters

    Directory of Open Access Journals (Sweden)

    Korumilli Tarangini

    2014-12-01

    Full Text Available In this study, optimization of production parameters influencing melanin production in an economical fruit waste extract was attempted using a garden soil isolate (Bacillus safensis. Taguchi approach was adopted for screening of critical parameters and further optimization was done using a central composite design of response surface methodology (RSM. At optimum conditions (pH 6.84 and Temp 30.7 °C, a significant yield of ∼6.96 mg/mL was observed. Statistical analysis revealed that the experimental results fitted well to the statistical model with model R2 value 0.982. The optimization of process parameters using RSM reported a 15% increase in the pigment yield than average yield obtained from the studied model. The melanin produced was confirmed by UV–visible spectroscopy, FTIR and XRD analysis. Moreover melanin obtained has significant photoprotective, radical scavenging and metal chelating activity. Thus, B. safensis has the potential to be a new source for the production of melanin, which is of industrial interest.

  5. Production of melanin by soil microbial isolate on fruit waste extract: two step optimization of key parameters.

    Science.gov (United States)

    Tarangini, Korumilli; Mishra, Susmita

    2014-12-01

    In this study, optimization of production parameters influencing melanin production in an economical fruit waste extract was attempted using a garden soil isolate ( Bacillus safensis ). Taguchi approach was adopted for screening of critical parameters and further optimization was done using a central composite design of response surface methodology (RSM). At optimum conditions (pH 6.84 and Temp 30.7 °C), a significant yield of ∼6.96 mg/mL was observed. Statistical analysis revealed that the experimental results fitted well to the statistical model with model R 2 value 0.982. The optimization of process parameters using RSM reported a 15% increase in the pigment yield than average yield obtained from the studied model. The melanin produced was confirmed by UV-visible spectroscopy, FTIR and XRD analysis. Moreover melanin obtained has significant photoprotective, radical scavenging and metal chelating activity. Thus, B. safensis has the potential to be a new source for the production of melanin, which is of industrial interest.

  6. Criticality parameters for tank waste evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Rogers, C.A.; Harris, H.

    1996-08-21

    A summary is provided of basic parameters used to evaluate criticality safety of high-level tank waste at the Hanford Site.Critical sizes and plutonium concentrations are based on a conservative waste model with reduced neutron absorption and optimized water. Figures were provided of sphere and slab minimum critical dimensions and plutonium critical masses.Minimum subcritical limit absorber/plutonium mass ratios are provided for selected waste components. Component contributions to subcriticality can be combined by adding the individual actual-to-minimum subcritical mass fractions. A discussion is provided of the margin of safety inherent in tank waste.

  7. Conversion of solid organic wastes into oil via Boettcherisca peregrine (Diptera: Sarcophagidae larvae and optimization of parameters for biodiesel production.

    Directory of Open Access Journals (Sweden)

    Sen Yang

    Full Text Available The feedstocks for biodiesel production are predominantly from edible oils and the high cost of the feedstocks prevents its large scale application. In this study, we evaluated the oil extracted from Boettcherisca peregrine larvae (BPL grown on solid organic wastes for biodiesel production. The oil contents detected in the BPL converted from swine manure, fermentation residue and the degreased food waste, were 21.7%, 19.5% and 31.1%, respectively. The acid value of the oil is 19.02 mg KOH/g requiring a two-step transesterification process. The optimized process of 12∶1 methanol/oil (mol/mol with 1.5% H(2SO(4 reacted at 70°C for 120 min resulted in a 90.8% conversion rate of free fatty acid (FFA by esterification, and a 92.3% conversion rate of triglycerides into esters by alkaline transesterification. Properties of the BPL oil-based biodiesel are within the specifications of ASTM D6751, suggesting that the solid organic waste-grown BPL could be a feasible non-food feedstock for biodiesel production.

  8. Conversion of solid organic wastes into oil via Boettcherisca peregrine (Diptera: Sarcophagidae) larvae and optimization of parameters for biodiesel production.

    Science.gov (United States)

    Yang, Sen; Li, Qing; Zeng, Qinglan; Zhang, Jibin; Yu, Ziniu; Liu, Ziduo

    2012-01-01

    The feedstocks for biodiesel production are predominantly from edible oils and the high cost of the feedstocks prevents its large scale application. In this study, we evaluated the oil extracted from Boettcherisca peregrine larvae (BPL) grown on solid organic wastes for biodiesel production. The oil contents detected in the BPL converted from swine manure, fermentation residue and the degreased food waste, were 21.7%, 19.5% and 31.1%, respectively. The acid value of the oil is 19.02 mg KOH/g requiring a two-step transesterification process. The optimized process of 12∶1 methanol/oil (mol/mol) with 1.5% H(2)SO(4) reacted at 70°C for 120 min resulted in a 90.8% conversion rate of free fatty acid (FFA) by esterification, and a 92.3% conversion rate of triglycerides into esters by alkaline transesterification. Properties of the BPL oil-based biodiesel are within the specifications of ASTM D6751, suggesting that the solid organic waste-grown BPL could be a feasible non-food feedstock for biodiesel production.

  9. Conversion of Solid Organic Wastes into Oil via Boettcherisca peregrine (Diptera: Sarcophagidae) Larvae and Optimization of Parameters for Biodiesel Production

    Science.gov (United States)

    Yang, Sen; Li, Qing; Zeng, Qinglan; Zhang, Jibin; Yu, Ziniu; Liu, Ziduo

    2012-01-01

    The feedstocks for biodiesel production are predominantly from edible oils and the high cost of the feedstocks prevents its large scale application. In this study, we evaluated the oil extracted from Boettcherisca peregrine larvae (BPL) grown on solid organic wastes for biodiesel production. The oil contents detected in the BPL converted from swine manure, fermentation residue and the degreased food waste, were 21.7%, 19.5% and 31.1%, respectively. The acid value of the oil is 19.02 mg KOH/g requiring a two-step transesterification process. The optimized process of 12∶1 methanol/oil (mol/mol) with 1.5% H2SO4 reacted at 70°C for 120 min resulted in a 90.8% conversion rate of free fatty acid (FFA) by esterification, and a 92.3% conversion rate of triglycerides into esters by alkaline transesterification. Properties of the BPL oil-based biodiesel are within the specifications of ASTM D6751, suggesting that the solid organic waste-grown BPL could be a feasible non-food feedstock for biodiesel production. PMID:23029331

  10. Optimizing the operating parameters of corona electrostatic separation for recycling waste scraped printed circuit boards by computer simulation of electric field.

    Science.gov (United States)

    Li, Jia; Lu, Hongzhou; Liu, Shushu; Xu, Zhenming

    2008-05-01

    The printed circuit board (PCB) has a metal content of nearly 28% metal, including an abundance of nonferrous metals such as copper, lead, and tin. The purity of precious metals in PCBs is more than 10 times that of rich-content minerals. Therefore, the recycling of PCBs is an important subject, not only from the viewpoint of waste treatment, but also with respect to the recovery of valuable materials. Compared with traditional process the corona electrostatic separation (CES) had no waste water or gas during the process and it had high productivity with a low-energy cost. In this paper, the roll-type corona electrostatic separator was used to separate metals and nonmetals from scraped waste PCBs. The software MATLAB was used to simulate the distribution of electric field in separating space. It was found that, the variations of parameters of electrodes and applied voltages directly influenced the distribution of electric field. Through the correlation of simulated and experimental results, the good separation results were got under the optimized operating parameter: U=20-30 kV, L=L(1)=L(2)=0.21 m, R(1)=0.114, R(2)=0.019 m, theta(1)=20 degrees and theta(2)=60 degrees .

  11. Identification and optimization of parameters for the semi-continuous production of garbage enzyme from pre-consumer organic waste by green RP-HPLC method.

    Science.gov (United States)

    Arun, C; Sivashanmugam, P

    2015-10-01

    Reuse and management of organic solid waste, reduce the environmental impact on human health and increase the economic status by generating valuable products for current and novel applications. Garbage enzyme is one such product produced from fermentation of organic solid waste and it can be used as liquid fertilizer, antimicrobial agents, treatment of domestic wastewater, municipal and industrial sludge treatment, etc. The semi-continuous production of garbage enzyme in large quantity at minimal time period and at lesser cost is needed to cater for treatment of increasing quantities of industrial waste activated sludge. This necessitates a parameter for monitoring and control for the scaling up of current process on semi-continuous basis. In the present study a RP-HPLC (Reversed Phase-High Performance Liquid Chromatography) method is used for quantification of standard organic acid at optimized condition 30°C column oven temperature, pH 2.7, and 0.7 ml/min flow rate of the mobile phase (potassium dihydrogen phosphate in water) at 50mM concentration. The garbage enzyme solution collected in 15, 30, 45, 60, 75 and 90 days were used as sample to determine the concentration of organic acid. Among these, 90th day sample showed the maximum concentration of 78.14 g/l of acetic acid in garbage enzyme, whereas other organic acids concentration got decreased when compare to the 15th day sample. This result confirms that the matured garbage enzyme contains a higher concentration of acetic acid and thus it can be used as a monitoring parameter for semi-continuous production of garbage enzyme in large scale. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. 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

    2017-06-01

    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.

  13. Wet oxidation pre-treatment of woody yard waste: Parameter optimization and enzymatic digestibility for ethanol production

    DEFF Research Database (Denmark)

    Lissens, G.; Klinke, H.B.; Verstraete, W.

    2004-01-01

    Woody yard waste with high lignin content (22% of dry matter (DM)) was subjected to wet oxidation pre-treatment for subsequent enzymatic conversion and fermentation. The effects of temperature (185-200 degreesC), oxygen pressure (3-12 bar) and addition of sodium carbonate (0-3.3 g per 100 g DM bi...

  14. Production and Optimization of Physicochemical Parameters of Cellulase Using Untreated Orange Waste by Newly Isolated Emericella variecolor NS3.

    Science.gov (United States)

    Srivastava, Neha; Srivastava, Manish; Manikanta, Ambepu; Singh, Pardeep; Ramteke, P W; Mishra, P K; Malhotra, Bansi D

    2017-10-01

    Cellulase enzymes have versatile industrial applications. This study was directed towards the isolation, production, and characterization of cellulase enzyme system. Among the five isolated fungal cultures, Emericella variecolor NS3 showed maximum cellulase production using untreated orange peel waste as substrate using solid-state fermentation (SSF). Maximum enzyme production of 31 IU/gds (per gram of dry substrate) was noticed at 6.0 g concentration of orange peel. Further, 50 °C was recorded as the optimum temperature for cellulase activity and the thermal stability for 240 min was observed at this temperature. In addition, the crude enzyme was stable at pH 5.0 and held its complete relative activity in presence of Mn 2+ and Fe 3+ . This study explored the production of crude enzyme system using biological waste with future potential for research and industrial applications.

  15. Optimizing High Level Waste Disposal

    Energy Technology Data Exchange (ETDEWEB)

    Dirk Gombert

    2005-09-01

    If society is ever to reap the potential benefits of nuclear energy, technologists must close the fuel-cycle completely. A closed cycle equates to a continued supply of fuel and safe reactors, but also reliable and comprehensive closure of waste issues. High level waste (HLW) disposal in borosilicate glass (BSG) is based on 1970s era evaluations. This host matrix is very adaptable to sequestering a wide variety of radionuclides found in raffinates from spent fuel reprocessing. However, it is now known that the current system is far from optimal for disposal of the diverse HLW streams, and proven alternatives are available to reduce costs by billions of dollars. The basis for HLW disposal should be reassessed to consider extensive waste form and process technology research and development efforts, which have been conducted by the United States Department of Energy (USDOE), international agencies and the private sector. Matching the waste form to the waste chemistry and using currently available technology could increase the waste content in waste forms to 50% or more and double processing rates. Optimization of the HLW disposal system would accelerate HLW disposition and increase repository capacity. This does not necessarily require developing new waste forms, the emphasis should be on qualifying existing matrices to demonstrate protection equal to or better than the baseline glass performance. Also, this proposed effort does not necessarily require developing new technology concepts. The emphasis is on demonstrating existing technology that is clearly better (reliability, productivity, cost) than current technology, and justifying its use in future facilities or retrofitted facilities. Higher waste processing and disposal efficiency can be realized by performing the engineering analyses and trade-studies necessary to select the most efficient methods for processing the full spectrum of wastes across the nuclear complex. This paper will describe technologies being

  16. Study on optimization of process parameters for enhancing the multi-hydrolytic enzyme activity in garbage enzyme produced from preconsumer organic waste.

    Science.gov (United States)

    Arun, C; Sivashanmugam, P

    2017-02-01

    The garbage enzymes produced from preconsumer organic waste containing multi hydrolytic enzyme activity which helps to solubilize the waste activated sludge. The continuous production of garbage enzyme and its scaling up process need a globe optimized condition. In present study the effect of fruit peel composition and sonication time on enzyme activity were investigated. Garbage enzyme produced from 6g pineapple peels: 4g citrus peels pre-treated with ultrasound for 20min shows higher hydrolytic enzymes activity. Simultaneously statistical optimization tools were used to model garbage enzyme production with higher activity of amylase, lipase and protease. The maximum activity of amylase, lipase and protease were predicted to be 56.409, 44.039, 74.990U/ml respectively at optimal conditions (pH (6), temperature (37°C), agitation (218 RPM) and fermentation duration (3days)). These optimized conditions can be successfully used for large scale production of garbage enzyme with higher hydrolytic enzyme activity. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Challenges when performing economic optimization of waste treatment: A review

    Energy Technology Data Exchange (ETDEWEB)

    Juul, N., E-mail: njua@dtu.dk [DTU Management, Risø Campus, Technical University of Denmark (Denmark); Münster, M., E-mail: maem@dtu.dk [DTU Management, Risø Campus, Technical University of Denmark (Denmark); Ravn, H., E-mail: hans.ravn@aeblevangen.dk [RAM-løse edb, Æblevangen 55, 2765 Smørum (Denmark); Söderman, M. Ljunggren, E-mail: maria.ljunggren@chalmers.se [Energy and Environment, Chalmers University of Technology, Gothenburg (Sweden); IVL Swedish Environmental Research Institute, Gothenburg (Sweden)

    2013-09-15

    Highlights: • Review of main optimization tools in the field of waste management. • Different optimization methods are applied. • Different fractions are analyzed. • There is focus on different parameters in different geographical regions. • More research is needed which encompasses both recycling and energy solutions. - Abstract: Strategic and operational decisions in waste management, in particular with respect to investments in new treatment facilities, are needed due to a number of factors, including continuously increasing amounts of waste, political demands for efficient utilization of waste resources, and the decommissioning of existing waste treatment facilities. Optimization models can assist in ensuring that these investment strategies are economically feasible. Various economic optimization models for waste treatment have been developed which focus on different parameters. Models focusing on transport are one example, but models focusing on energy production have also been developed, as well as models which take into account a plant’s economies of scale, environmental impact, material recovery and social costs. Finally, models combining different criteria for the selection of waste treatment methods in multi-criteria analysis have been developed. A thorough updated review of the existing models is presented, and the main challenges and crucial parameters that need to be taken into account when assessing the economic performance of waste treatment alternatives are identified. The review article will assist both policy-makers and model-developers involved in assessing the economic performance of waste treatment alternatives.

  18. Optimization of phytase production from potato waste using Aspergillus ficuum

    OpenAIRE

    Tian, Mengmeng; Yuan, Qiuyan

    2016-01-01

    Solid-state fermentation (SSF) can divert food waste from landfills and produce high-value products. This study was aimed to investigate the feasibility of using SSF and optimize the conditions of production of phytase by Aspergillus ficuum from potato waste. Different parameters including pH of the potato waste, inoculum level, moisture content, incubation period, temperature, and supplementary nitrogen and carbon sources were evaluated. The results indicated that pH, inoculum level, and moi...

  19. Economic and environmental optimization of waste treatment

    DEFF Research Database (Denmark)

    Münster, Marie; Ravn, Hans; Hedegaard, Karsten

    2015-01-01

    with different assumptions regarding displaced electricity production. The article shows that it is feasible to combine LCA methodology with optimization. Furthermore, it highlights the need for including the integrated waste and energy system into the model. © 2014 Elsevier Ltd. All rights reserved.......This article presents the new systems engineering optimization model, OptiWaste, which incorporates a life cycle assessment (LCA) methodology and captures important characteristics of waste management systems. As part of the optimization, the model identifies the most attractive waste management...... options. The model renders it possible to apply different optimization objectives such as minimizing costs or greenhouse gas emissions or to prioritize several objectives given different weights. A simple illustrative case is analysed, covering alternative treatments of one tonne of residual household...

  20. Challenges when performing economic optimization of waste treatment: a review.

    Science.gov (United States)

    Juul, N; Münster, M; Ravn, H; Söderman, M Ljunggren

    2013-09-01

    Strategic and operational decisions in waste management, in particular with respect to investments in new treatment facilities, are needed due to a number of factors, including continuously increasing amounts of waste, political demands for efficient utilization of waste resources, and the decommissioning of existing waste treatment facilities. Optimization models can assist in ensuring that these investment strategies are economically feasible. Various economic optimization models for waste treatment have been developed which focus on different parameters. Models focusing on transport are one example, but models focusing on energy production have also been developed, as well as models which take into account a plant's economies of scale, environmental impact, material recovery and social costs. Finally, models combining different criteria for the selection of waste treatment methods in multi-criteria analysis have been developed. A thorough updated review of the existing models is presented, and the main challenges and crucial parameters that need to be taken into account when assessing the economic performance of waste treatment alternatives are identified. The review article will assist both policy-makers and model-developers involved in assessing the economic performance of waste treatment alternatives. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. Optimization of waste combinations during in-vessel composting of agricultural waste.

    Science.gov (United States)

    Varma, V Sudharsan; Kalamdhad, Ajay S; Kumar, Bimlesh

    2017-01-01

    In-vessel composting of agricultural waste is a well-described approach for stabilization of compost within a short time period. Although composting studies have shown the different combinations of waste materials for producing good quality compost, studies of the particular ratio of the waste materials in the mix are still limited. In the present study, composting was conducted with a combination of vegetable waste, cow dung, sawdust and dry leaves using a 550 L rotary drum composter. Application of a radial basis functional neural network was used to simulate the composting process. The model utilizes physico-chemical parameters with different waste materials as input variables and three output variables: volatile solids, soluble biochemical oxygen demand and carbon dioxide evolution. For the selected model, the coefficient of determination reached the high value of 0.997. The complicated interaction of agricultural waste components during composting makes it a nonlinear problem so it is difficult to find the optimal waste combinations for producing quality compost. Optimization of a trained radial basis functional model has yielded the optimal proportion as 62 kg, 17 kg and 9 kg for vegetable waste, cow dung and sawdust, respectively. The results showed that the predictive radial basis functional model described for drum composting of agricultural waste was well suited for organic matter degradation and can be successfully applied.

  2. 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.

  3. Optimization of submerged vane parameters

    Indian Academy of Sciences (India)

    H Sharma

    velocities simulated from CFD using standard k-x model were very much in accordance with what it was measured by Wang and Odgaard [4]. Thus, model can be used to study the turbulence characteristics around submerged vanes and to predict various parameters downstream of the submerged vanes. After the model ...

  4. Optimization of phytase production from potato waste using Aspergillus ficuum.

    Science.gov (United States)

    Tian, Mengmeng; Yuan, Qiuyan

    2016-12-01

    Solid-state fermentation (SSF) can divert food waste from landfills and produce high-value products. This study was aimed to investigate the feasibility of using SSF and optimize the conditions of production of phytase by Aspergillus ficuum from potato waste. Different parameters including pH of the potato waste, inoculum level, moisture content, incubation period, temperature, and supplementary nitrogen and carbon sources were evaluated. The results indicated that pH, inoculum level, and moisture content did not significantly vary phytase production. However, different incubation periods, incubation temperatures, nitrogen sources, and carbon sources changed the phytase production significantly. The ideal and economic conditions for phytase production consisted of a normal moisture content (79%) of potato waste, 1.0 ml inoculum size, and normal pH 6.1 at room temperature for 144 h incubation time. The highest phytase activity (5.17 ± 0.82 U/g ds) was obtained under the aforementioned optimized conditions. When (NH4)2SO4 was used as a nitrogen source in the substrate, the phytase activity increased to 12.93 ± 0.47 U/g ds, which was a 2.5-fold increase compared to the control treatment. This study proposed a novel and economical way to convert food processing waste to highly valuable products and investigated the optimal conditions of the production of phytase during SSF in potato waste.

  5. Optimal Formation Trajectory-Planning Using Parameter Optimization Technique

    Directory of Open Access Journals (Sweden)

    Hyung-Chul Lim

    2004-09-01

    Full Text Available Some methods have been presented to get optimal formation trajectories in the step of configuration or reconfiguration, which subject to constraints of collision avoidance and final configuration. In this study, a method for optimal formation trajectory-planning is introduced in view of fuel/time minimization using parameter optimization technique which has not been applied to optimal trajectory-planning for satellite formation flying. New constraints of nonlinear equality are derived for final configuration and constraints of nonlinear inequality are used for collision avoidance. The final configuration constraints are that three or more satellites should be placed in an equilateral polygon of the circular horizontal plane orbit. Several examples are given to get optimal trajectories based on the parameter optimization problem which subjects to constraints of collision avoidance and final configuration. They show that the introduced method for trajectory-planning is well suited to trajectory design problems of formation flying missions.

  6. 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.

  7. Optimization of municipal solid waste collection and transportation routes

    Energy Technology Data Exchange (ETDEWEB)

    Das, Swapan, E-mail: swapan2009sajal@gmail.com; Bhattacharyya, Bidyut Kr., E-mail: bidyut53@yahoo.co.in

    2015-09-15

    Graphical abstract: Display Omitted - Highlights: • Profitable integrated solid waste management system. • Optimal municipal waste collection scheme between the sources and waste collection centres. • Optimal path calculation between waste collection centres and transfer stations. • Optimal waste routing between the transfer stations and processing plants. - Abstract: Optimization of municipal solid waste (MSW) collection and transportation through source separation becomes one of the major concerns in the MSW management system design, due to the fact that the existing MSW management systems suffer by the high collection and transportation cost. Generally, in a city different waste sources scatter throughout the city in heterogeneous way that increase waste collection and transportation cost in the waste management system. Therefore, a shortest waste collection and transportation strategy can effectively reduce waste collection and transportation cost. In this paper, we propose an optimal MSW collection and transportation scheme that focus on the problem of minimizing the length of each waste collection and transportation route. We first formulize the MSW collection and transportation problem into a mixed integer program. Moreover, we propose a heuristic solution for the waste collection and transportation problem that can provide an optimal way for waste collection and transportation. Extensive simulations and real testbed results show that the proposed solution can significantly improve the MSW performance. Results show that the proposed scheme is able to reduce more than 30% of the total waste collection path length.

  8. Optimized Parameters for a Mercury Jet Target

    Energy Technology Data Exchange (ETDEWEB)

    Ding, X.; Kirk, H.

    2010-12-01

    A study of target parameters for a high-power, liquid mercury jet target system for a neutrino factory or muon collider is presented. Using the MARS code, we simulate particle production initiated by incoming protons with kinetic energies between 2 and 100 GeV. For each proton beam energy, we maximize production by varying the geometric parameters of the target: the mercury jet radius, the incoming proton beam angle, and the crossing angle between the mercury jet and the proton beam. The number of muons surviving through an ionization cooling channel is determined as a function of the proton beam energy. We optimize the mercury jet target parameters: the mercury jet radius, the incoming proton beam angle and the crossing angle between the mercury jet and the proton beam for each proton beam energy. The optimized target radius varies from about 0.4 cm to 0.6 cm as the proton beam energy increases. The optimized beam angle varies from 75 mrad to 120 mrad. The optimized crossing angle is near 20 mrad for energies above 5 GeV. These values differ from earlier choices of 67 mrad for the beam angle and 33 mrad for the crossing angle. These new choices for the beam parameters increase the meson production by about 20% compared to the earlier parameters. Our study demonstrates that the maximum meson production efficiency per unit proton beam power occurs when the proton kinetic energy is in the range of 5-15 GeV. Finally, the dependence on energy of the number of muons at the end of the cooling channel is nearly identical to the dependence on energy of the meson production 50 m from the target. This demonstrates that the target parameters can be optimized without the additional step of running the distribution through a code such as ICOOL that simulates the bunching, phase rotation, and cooling.

  9. Nanohydroxyapatite synthesis using optimized process parameters ...

    Indian Academy of Sciences (India)

    Home; Journals; Bulletin of Materials Science; Volume 39; Issue 1 ... parameters: temperature () (70, 80 and 90°C), ultrasonication time () (20, 25 and 30 min), and amplitude () (60, 65 and 70%) were studied and optimized using response surface methodology based on 3 factors and 5 level central composite design.

  10. 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.

  11. 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.

  12. Optimization of machining parameters for green manufacturing

    Directory of Open Access Journals (Sweden)

    Y. Anand

    2016-12-01

    Full Text Available Energy crisis is affecting the world badly. While the production in developed countries stabilizes, in the developing world it continues to expand. This results in higher energy use, thereby releasing higher CO2. Thus, a pilot experiment was conducted to check and subsequently take corrective measures to reduce the energy consumption of manufacturing industry. Here, the emphasis is laid particularly on the turning operation for the cutting parameters, and effort has been made to optimize them, using Design Expert, with regard to the energy consumed. Also the optimized values, from the, for the different parameters under study have been checked and compared by those being generally used. For experimental studies, the machining was first carried on mild steel and then after aluminum and brass were also considered for study. All the values show an appreciable reduction in the energy consumption, thus reducing the carbon emission, for all the materials.

  13. Optimization of machining parameters for green manufacturing

    OpenAIRE

    Y. Anand; A. Gupta; A. Abrol; Ayush Gupta; V. Kumar; S.K. Tyagi; S. Anand

    2016-01-01

    Energy crisis is affecting the world badly. While the production in developed countries stabilizes, in the developing world it continues to expand. This results in higher energy use, thereby releasing higher CO2. Thus, a pilot experiment was conducted to check and subsequently take corrective measures to reduce the energy consumption of manufacturing industry. Here, the emphasis is laid particularly on the turning operation for the cutting parameters, and effort has been made to optimize them...

  14. The model relationship of wastes for parameter design with green lean production of fresh water

    Directory of Open Access Journals (Sweden)

    Mastiadi Tamjidillah

    2017-12-01

    Full Text Available Lean manufacturing is about eliminating waste including the seven traditional, this writing suggested an observation on no value added of seven wastes influencing the process of fresh water production. The relationship value among waste was statistically verified to create an approach for continuous improvement action. Thus, the main goal of this research is to develop a methodology of relationship among wastes and eliminate them. In relationship among wastes, it could be known that the high value indicating how often it happened in the production process gave direct cause in the system of fresh water treatment. A recommendation to reduce the highest value of waste is by doing improvement on parameter setting to obtain an optimum mixing model between water supply, alum and stroke pump with Taguchi method. The interaction of relationship among these seven types of waste can be portrayed using fishbone diagram and a relationship model among wastes using PLS smart (partial least squares. The final relationship model with the highest value of waste was analyzed using off-line quality control to upgrade the quality of fresh water used as the basis to eliminate waste and find out the optimal parameter of mixing process in accordance with the health standard.

  15. Parameter optimization in S-system models

    Directory of Open Access Journals (Sweden)

    Vasconcelos Ana

    2008-04-01

    Full Text Available Abstract Background The inverse problem of identifying the topology of biological networks from their time series responses is a cornerstone challenge in systems biology. We tackle this challenge here through the parameterization of S-system models. It was previously shown that parameter identification can be performed as an optimization based on the decoupling of the differential S-system equations, which results in a set of algebraic equations. Results A novel parameterization solution is proposed for the identification of S-system models from time series when no information about the network topology is known. The method is based on eigenvector optimization of a matrix formed from multiple regression equations of the linearized decoupled S-system. Furthermore, the algorithm is extended to the optimization of network topologies with constraints on metabolites and fluxes. These constraints rejoin the system in cases where it had been fragmented by decoupling. We demonstrate with synthetic time series why the algorithm can be expected to converge in most cases. Conclusion A procedure was developed that facilitates automated reverse engineering tasks for biological networks using S-systems. The proposed method of eigenvector optimization constitutes an advancement over S-system parameter identification from time series using a recent method called Alternating Regression. The proposed method overcomes convergence issues encountered in alternate regression by identifying nonlinear constraints that restrict the search space to computationally feasible solutions. Because the parameter identification is still performed for each metabolite separately, the modularity and linear time characteristics of the alternating regression method are preserved. Simulation studies illustrate how the proposed algorithm identifies the correct network topology out of a collection of models which all fit the dynamical time series essentially equally well.

  16. Using environmental parameters to optimize process operation

    Energy Technology Data Exchange (ETDEWEB)

    Levasseur, J.F. [James MacLaren Industries Inc., Thurso, PQ (Canada); Savoie, M.C. [James MacLaren Industries Inc., Masson, PQ, (Canada)

    1999-12-01

    The debottlenecking of the recovery furnace leading to increased transformation of black liquor to green liquor and additional steam production, a $400,000 reduction in fuel oil costs, and a $25,000 reduction in make-up sulfur costs and avoidance of costly pollution control equipment is of interest in the cost-competitive pulp and paper sector. The key to these savings is effective monitoring and analysis of environmental parameters. A description is included of the approach and methodology that resulted in optimized performance of the recovery furnaces at Thurso, PQ, a kraft pulp mill being coincident with the close tracking of total reduced sulfur (TRS) emissions. Also, two other cases with similar characteristics are summarized in which process optimization accomplished by the analysis of air emissions data also produced substantial savings and improved performance. TRS emission levels as a measure in minutes of TRS emission above 20 ppm per month over the 35 months during which improvements were made are illustrated. After analysis and corrective action, such as complete operator and helper training on basic combustion principles in a recovery boiler, installing an automatic primary and secondary air-port rodding system installation, and modifying the tertiary air dampers, the aim was achieved. There was a reduction in TRS emission and improvement in furnace stability under similar conditions. Other examples of process improvements triggered by environmental requirements included: optimization of hog fuel with particulate matter opacity as the environmental parameter, and installation of a continuous high pressure washing system for the lime mud precoat filter with TRS emissions from the lime kiln as the environmental parameter. The direct financial benefits, as well as complementary benefits, are illustrated for those two examples of process improvements. Environmemtal parameters can be used for process improvement with a significant effect on operations

  17. Site suitability analysis and route optimization for solid waste ...

    African Journals Online (AJOL)

    Solid waste management system is a tedious task that is facing both developing and developed countries. Site Suitability analysis and route optimization for solid waste disposal can make waste management cheap and can be used for sustainable development. However, if the disposal site(s) is/are not sited and handle ...

  18. Emission control with route optimization in solid waste collection ...

    Indian Academy of Sciences (India)

    Solid waste collection processes are usually carried out by using trucks with diesel engine. In solid waste collection process, the trucks emit to environment different emissions from its exhausts. For this reason, in solid waste collection process, it is necessary that route optimization should be performed in order to decrease ...

  19. XTC MRI: sensitivity improvement through parameter optimization.

    Science.gov (United States)

    Ruppert, Kai; Mata, Jaime F; Wang, Hsuan-Tsung J; Tobias, William A; Cates, Gordon D; Brookeman, James R; Hagspiel, Klaus D; Mugler, John P

    2007-06-01

    Xenon polarization Transfer Contrast (XTC) MRI pulse sequences permit the gas exchange of hyperpolarized xenon-129 in the lung to be measured quantitatively. However, the pulse sequence parameter values employed in previously published work were determined empirically without considering the now-known gas exchange rates and the underlying lung physiology. By using a theoretical model for the consumption of magnetization during data acquisition, the noise intensity in the computed gas-phase depolarization maps was minimized as a function of the gas-phase depolarization rate. With such optimization the theoretical model predicted an up to threefold improvement in precision. Experiments in rabbits demonstrated that for typical imaging parameter values the optimized XTC pulse sequence yielded a median noise intensity of only about 3% in the depolarization maps. Consequently, the reliable detection of variations in the average alveolar wall thickness of as little as 300 nm can be expected. This improvement in the precision of the XTC MRI technique should lead to a substantial increase in its sensitivity for detecting pathological changes in lung function.

  20. Optimization of processes in waste management plant

    OpenAIRE

    Tomažin, Andrej

    2016-01-01

    This undergraduate thesis presents details of the RCERO Ljubljana project, the Regional Waste Management Centre with its most important part: the mechanical-biological treatment plant. The plant has been constructed for the reception and processing of household waste, bulky waste, biodegradable waste and waste from craft activities, manufacturing and service activities for the city of Ljubljana and the Central Slovenia region. The presentation covers a description of the facilities and instal...

  1. 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.

  2. Warpage minimization on wheel caster by optimizing process parameters using response surface methodology (RSM)

    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, it is important to keep the productivity increase constantly with least of waste produced such as warpage defect. Thus, this study is concerning on minimizing warpage defect on wheel caster part. Apart from eliminating product wastes, this project also giving out best optimization techniques using response surface methodology. This research studied on five parameters A-packing pressure, B-packing time, C-mold temperature, D-melting temperature and E-cooling time. The optimization showed that packing pressure is the most significant parameter. Warpage have been improved 42.64% from 0.6524 mm to 0.3742mm.

  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. Methodology for computer-assisted optimization of waste flow

    Directory of Open Access Journals (Sweden)

    Popa Cicerone Laurentiu

    2017-01-01

    Full Text Available The paper reports the development of a methodology based on computer simulations with the purpose to support decisions in designing the optimal architecture of different types of selective waste collection systems and recycling systems. The design of such systems is a complex task which involves both a very good knowledge of selective waste collection system equipment characteristics and of recycling processes, and the correct placing of the equipment along the flow so that to avoid underutilization of the structural elements and to avoid bottlenecks which generate low productivity or even blockages. The methodology is applied for three case studies in which different types of waste flow models are investigated: hybrid waste flows (windshields recycling, discrete waste flows (waste electric and electronic equipment collection and continuous flows (industrial and automotive used oil collection and recycling. The architectures of these systems are optimized using the developed methodology in order to increase usage degree and productivity.

  5. Optimal linear estimation of binary star parameters

    Science.gov (United States)

    Burke, Daniel; Devaney, Nicholas; Gladysz, Szymon; Barrett, Harrisson H.; Whitaker, Meredith K.; Caucci, Luca

    2008-07-01

    We propose a new post-processing technique for the detection of faint companions and the estimation of their parameters from adaptive optics (AO) observations. We apply the optimal linear detector, which is the Hotelling observer, to perform detection, astrometry and photometry on real and simulated data. The real data was obtained from the AO system on the 3m Lick telescope1. The Hotelling detector, which is a prewhitening matched filter, calculates the Hotelling test statistic which is then compared to a threshold. If the test statistic is greater than the threshold the algorithm decides that a companion is present. This decision is the main task performed by the Hotelling observer. After a detection is made the location and intensity of the companion which maximise this test statistic are taken as the estimated values. We compare the Hotelling approach with current detection algorithms widely used in astronomy. We discuss the use of the estimation receiver operating characteristic (EROC) curve in quantifying the performance of the algorithm with no prior estimate of the companion's location or intensity. The robustness of this technique to errors in point spread function (PSF) estimation is also investigated.

  6. Economic optimization of waste treatment and energy production in Denmark

    DEFF Research Database (Denmark)

    Münster, Marie; Ravn, Hans; Hedegaard, Karsten

    2013-01-01

    This article presents an optimization model that incorporates LCA methodology and captures important characteristics of waste management systems. The most attractive waste management options are in the model identified as part the optimization. The model renders it possible to apply different...... optimization objectives such as minimizing costs or greenhouse gas emissions or to prioritise several objectives given different weights. An illustrative case is analyzed, covering alternative treatments of 1 tonne residual household waste: incineration of the full amount or sorting out organic waste...... for biogas production for either CHP generation or as fuel in vehicles. The case study illustrates, that what is the optimal solution depends on the objective and assumptions regarding the background system – here illustrated with different assumptions regarding displaced electricity production. The article...

  7. Waste Ergonomics Optimization in Ilorin, Nigeria | Ajibade ...

    African Journals Online (AJOL)

    In order to ease and achieve best desired results in waste management procedures and operations in Ilorin metropolis, Kwara State of Nigeria, the government, through the Kwara State Waste Management Corporation (KWMC), has provided different equipment including vehicles and containers. The distribution and ...

  8. Energy and exergy optimization of food waste pretreatment and incineration.

    Science.gov (United States)

    Tang, Yuanjun; Dong, Jun; Chi, Yong; Zhou, Zhaozhi; Ni, Mingjiang

    2017-08-01

    With the aim of upgrading current food waste (FW) management strategy, a novel FW hydrothermal pretreatment and air-drying incineration system is proposed and optimized from an energy and exergy perspective. Parameters considered include the extracted steam quality, the final moisture content of dehydrated FW, and the reactor thermal efficiency. Results show that optimal working condition can be obtained when the temperature and pressure of extracted steam are 159 °C and 0.17 MPa, the final moisture content of dehydrated FW is 10%, and the reactor thermal efficiency is 90%. Under such circumstance, the optimal steam energy and exergy increments reach 194.92 and 324.50 kJ/kg-FW, respectively. The novel system is then applied under the local conditions of Hangzhou, China. Results show that approximately 2.7 or 11.6% (from energy or exergy analysis perspective) of electricity can be additionally generated from 1 ton of MSW if the proposed novel FW system is implemented. Besides, comparisons between energy and exergy analysis are also discussed.

  9. 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.

  10. 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.

  11. GA BASED GLOBAL OPTIMAL DESIGN PARAMETERS FOR ...

    African Journals Online (AJOL)

    This article uses Genetic Algorithm (GA) for the global design optimization of consecutive reactions taking place in continuous stirred tank reactors (CSTRs) connected in series. GA based optimal design determines the optimum number of CSTRs in series to achieve the maximum conversion, fractional yield and selectivity ...

  12. 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.

  13. Machining parameter optimization in turning process for sustainable manufacturing

    Directory of Open Access Journals (Sweden)

    S. G. Dambhare

    2015-09-01

    Full Text Available There is an increase in awareness about sustainable manufacturing process. Manufacturing industries are backbone of a country’s economy. Although it is important but there is a great concern about consumption of resources and waste creation. The primary aim of this study was to explore sustainability concern in turning process in an Indian machining industry. The effect of cutting parameters, Speed/Feed/Depth of Cut, the machining environment, Dry/MQL/Wet, and the type of cutting tool on sustainability factors under study were observed. Analysis of Variance (ANOVA was used to analyse the data obtained from experimentation in a small scale machining industry. The process is modelled mathematically using response surface methodology (RSM.The economic and environmental aspect like surface roughness, material removal rate and energy consumption were considered as sustainability factors. The model helps to understand the effect of the cutting parameters and conditions on surface finish, energy consumption, and material removal rate. The process was optimized for minimum power consumption considering environmental concern as prime importance. Studies suggest that the cutting environment and tool type influenced on the power consumption during turning process. Extended form of the proposed model could be useful to predict the environmental impact due to machining process, which would bring environmental concern into conventional machining.

  14. Optimal control of a waste water cleaning plant

    Directory of Open Access Journals (Sweden)

    Ellina V. Grigorieva

    2010-09-01

    Full Text Available In this work, a model of a waste water treatment plant is investigated. The model is described by a nonlinear system of two differential equations with one bounded control. An optimal control problem of minimizing concentration of the polluted water at the terminal time T is stated and solved analytically with the use of the Pontryagin Maximum Principle. Dependence of the optimal solution on the initial conditions is established. Computer simulations of a model of an industrial waste water treatment plant show the advantage of using our optimal strategy. Possible applications are discussed.

  15. 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...

  16. Optimization parameters system maintenance transport aircraft

    Directory of Open Access Journals (Sweden)

    І.І. Ліннік

    2006-01-01

    Full Text Available  The algorithm of unconditional and conditional optimization Markov models of maintenance systems of transport airplanes of their programs of technical operation used at improvement is considered.

  17. Optimization of Enzymatic Hydrolysis of Waste Bread before Fermentation

    Directory of Open Access Journals (Sweden)

    Helena Hudečková

    2017-01-01

    Full Text Available Finding of optimal hydrolysis conditions is important for increasing the yield of saccharides. The higher yield of saccharides is usable for increase of the following fermentation effectivity. In this study optimal conditions (pH and temperature for amylolytic enzymes were searched. As raw material was used waste bread. Two analytical methods for analysis were used. Efficiency and process of hydrolysis was analysed spectrophotometrically by Somogyi-Nelson method. Final yields of glucose were analysed by HPLC. As raw material was used waste bread from local cafe. Waste bread was pretreated by grinding into small particles. Hydrolysis was performed in 100 mL of 15 % (w/v waste bread particles in the form of water suspension. Waste bread was hydrolysed by two commercial enzymes. For the liquefaction was used α‑amylase (BAN 240 L. The saccharification was performed by glucoamylase (AMG 300 L. Optimal conditions for α‑amylase (pH 6; 80 °C were found. The yield of total sugars was 67.08 g∙L-1 (calculated to maltose. As optimal conditions for glucoamylase (pH 4.2; 60 °C were found. Amount of glucose was 70.28 g∙L1. The time of waste bread liquefaction was 180 minutes. The time of saccharification was 90 minutes. The results were presented at the conference CECE Junior 2014.

  18. Optimization of electrospinning parameters for chitosan nanofibres

    CSIR Research Space (South Africa)

    Jacobs, V

    2011-06-01

    Full Text Available uniform chitosan nanofibres. The parameters studied were electric field strength, ratio of solvents - trifluoroacetic acid (TFA)/ dichloromethane (DCM), concentration of chitosan in the spinning solution, their individual and interaction effects...

  19. Physical parameter optimization by Response Surface Methodology ...

    African Journals Online (AJOL)

    Response Surface Methodology (RSM) is an empirical technique involving the use of Design Expert software to derive a predictive model similar to regression analysis. This present study explains the significant application of RSM in optimization of lipase production by Aspergillus niger. The experimental validation of the ...

  20. Optimization of parameters for Agrobacterium mediated ...

    African Journals Online (AJOL)

    satyam

    2013-03-13

    Mar 13, 2013 ... Agrobacterium mediated transformation of black gram using cotyledon derived calli was optimized based on. GUS histochemical assay. Subculturing of the explants prior to infection caused mechanical injury facilitating bacterial penetration into the tissue as well as production of vir gene inducers and ...

  1. Adaptive Parameters for a Modified Comprehensive Learning Particle Swarm Optimizer

    Directory of Open Access Journals (Sweden)

    Yu-Jun Zheng

    2012-01-01

    Full Text Available Particle swarm optimization (PSO is a stochastic optimization method sensitive to parameter settings. The paper presents a modification on the comprehensive learning particle swarm optimizer (CLPSO, which is one of the best performing PSO algorithms. The proposed method introduces a self-adaptive mechanism that dynamically changes the values of key parameters including inertia weight and acceleration coefficient based on evolutionary information of individual particles and the swarm during the search. Numerical experiments demonstrate that our approach with adaptive parameters can provide comparable improvement in performance of solving global optimization problems.

  2. Optimizing the selection of organic waste for biomethanization.

    Science.gov (United States)

    Gil, A; Siles, J A; Márquez, P; Gutiérrez, M C; Martín, M A

    2017-11-15

    This study evaluates the feasibility of using simultaneous mass balances of different nutrients as a tool for optimizing feeding composition in anaerobic digestion. Different ratios, among them total chemical oxygen demand/total Kjeldahl nitrogen (TCOD/TKN) and soluble chemical oxygen demand/TCOD (SCOD/TCOD), were assessed. The TCOD/total volatile solids (TVS) ratio was 1.73 kg O2/kg TVS, while, with the exception of the sewage sludge, pig slurry and animal wastes, a linear relationship was established between phosphorus and nitrogen (0.06 kg P/kg TKN (R2 = 0.9045)). The study was applied to different mixtures of waste (cucumber, quince, tomato, strawberry waste, vinasse, glycerol, tomato plant, pig slurry, sewage sludge, fish waste, landfill leachate and viscera). The mass balance was performed for 50 mixtures chosen at random, containing three different wastes. After evaluating the theoretical optimal values determined by the mass balances, the most promising data were compared with the experimental results of the anaerobic co-digestion of one of the three waste mixtures. As predicted by the mass balances, the codigestion of glycerol, strawberry extrudate and fish waste (41:54:4 in VS) improved methane production to a maximum value of 0.308 m3 CH4/kg TVSadded for an organic loading rate of 0.62-4.26 kg TVS/m3·d.

  3. Optimization of Experimental Parameters in preparing ...

    African Journals Online (AJOL)

    The anodic oxidation method has been applied to the preparation of multinanoporous TiO2 thin films. The experimental parameters, including the electrolyte nature, oxidation voltage, and oxidation time have been carefully controlled. Their influence on the structure, morphology and photocatalytic activity of the prepared ...

  4. A contribution to theory and practice of nonlinear parameter optimization

    NARCIS (Netherlands)

    Stol, P.T.

    1975-01-01

    Nonlinear parameter optimization in least squares was studied from a point of view of differential geometry. Properties of curvilinear coordinates, scale factors and curvature were investigated. Parameters of the condition function were expressed as functions of algorithm parameters to

  5. Optimal planning for the sustainable utilization of municipal solid waste

    Energy Technology Data Exchange (ETDEWEB)

    Santibañez-Aguilar, José Ezequiel [Chemical Engineering Department, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán 58060 (Mexico); Ponce-Ortega, José María, E-mail: jmponce@umich.mx [Chemical Engineering Department, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán 58060 (Mexico); Betzabe González-Campos, J. [Institute of Chemical and Biological Researches, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán 58060 (Mexico); Serna-González, Medardo [Chemical Engineering Department, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán 58060 (Mexico); El-Halwagi, Mahmoud M. [Chemical Engineering Department, Texas A and M University, College Station, TX 77843 (United States); Adjunct Faculty at the Chemical and Materials Engineering Department, Faculty of Engineering, King Abdulaziz University, P.O. Box 80204, Jeddah 21589 (Saudi Arabia)

    2013-12-15

    Highlights: • An optimization approach for the sustainable management of municipal solid waste is proposed. • The proposed model optimizes the entire supply chain network of a distributed system. • A case study for the sustainable waste management in the central-west part of Mexico is presented. • Results shows different interesting solutions for the case study presented. - Abstract: The increasing generation of municipal solid waste (MSW) is a major problem particularly for large urban areas with insufficient landfill capacities and inefficient waste management systems. Several options associated to the supply chain for implementing a MSW management system are available, however to determine the optimal solution several technical, economic, environmental and social aspects must be considered. Therefore, this paper proposes a mathematical programming model for the optimal planning of the supply chain associated to the MSW management system to maximize the economic benefit while accounting for technical and environmental issues. The optimization model simultaneously selects the processing technologies and their location, the distribution of wastes from cities as well as the distribution of products to markets. The problem was formulated as a multi-objective mixed-integer linear programing problem to maximize the profit of the supply chain and the amount of recycled wastes, where the results are showed through Pareto curves that tradeoff economic and environmental aspects. The proposed approach is applied to a case study for the west-central part of Mexico to consider the integration of MSW from several cities to yield useful products. The results show that an integrated utilization of MSW can provide economic, environmental and social benefits.

  6. 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...

  7. Investigation of thermodynamic parameters in the thermal decomposition of plastic waste-waste lube oil compounds.

    Science.gov (United States)

    Kim, Yong Sang; Kim, Young Seok; Kim, Sung Hyun

    2010-07-01

    Thermal decomposition properties of plastic waste-waste lube oil compounds were investigated under nonisothermal conditions. Polyethylene (PE), polypropylene (PP), polystyrene (PS), and polyethylene terephthalate (PET) were selected as representative household plastic wastes. A plastic waste mixture (PWM) and waste lube oil (WLO) were mixed with mixing ratios of 33, 50, and 67 (w/w) % on a PWM weight basis, and thermogravimetric (TG) experiments were performed from 25 to 600 degrees C. The Flynn-Wall method and the Ozawa-Flynn-Wall method were used for analyses of thermodynamic parameters. In this study, activation energies of PWM/WLO compounds ranged from 73.4 to 229.6 kJ/mol between 0.2 and 0.8 of normalized mass conversions, and the 50% PWM/WLO compound had lower activation energies and enthalpies among the PWM/WLO samples at each mass conversion. At the point of maximum differential mass conversion, the analyzed activation energies, enthalpies, entropies, and Gibbs free energies indicated that mixing PWM and WLO has advantages in reducing energy to decrease the degree of disorder. However, no difference in overall energy that would require overcoming both thermal decomposition reactions and degree of disorder was observed among PWM/WLO compounds under these experimental conditions.

  8. Optimal Control of Diesel Engines with Waste Heat Recovery System

    NARCIS (Netherlands)

    Willems, F.P.T.; Donkers, M.C.F.; Kupper, F.

    2014-01-01

    This study presents an integrated energy and emission management strategy for a Euro-VI diesel engine with Waste Heat Recovery (WHR) system. This Integrated Powertrain Control (IPC) strategy optimizes the CO2-NOx trade-off by minimizing the operational costs associated with fuel and AdBlue

  9. Environmental Optimization Using the WAste Reduction Algorithm (WAR)

    Science.gov (United States)

    Traditionally chemical process designs were optimized using purely economic measures such as rate of return. EPA scientists developed the WAste Reduction algorithm (WAR) so that environmental impacts of designs could easily be evaluated. The goal of WAR is to reduce environme...

  10. Optimizing Resource and Energy Recovery for Municipal Solid Waste Management

    Science.gov (United States)

    Significant reductions of carbon emissions and air quality impacts can be achieved by optimizing municipal solid waste (MSW) as a resource. Materials and discards management were found to contribute ~40% of overall U.S. GHG emissions as a result of materials extraction, transpo...

  11. 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.

  12. 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 ...

  13. Optimization of Nanostructuring Burnishing Technological Parameters by Taguchi Method

    Science.gov (United States)

    Kuznetsov, V. P.; Dmitriev, A. I.; Anisimova, G. S.; Semenova, Yu V.

    2016-04-01

    On the basis of application of Taguchi optimization method, an approach for researching influence of nanostructuring burnishing technological parameters, considering the surface layer microhardness criterion, is developed. Optimal values of burnishing force, feed and number of tool passes for hardened steel AISI 420 hardening treatment are defined.

  14. Multimodel parameter optimization with adaptive population importance sampler (APIS)

    Science.gov (United States)

    Mäkelä, Jarmo; Susiluoto, Jouni; Knauer, Jürgen; Aurela, Mika; Mammarella, Ivan; Markkanen, Tiina; Thum, Tea; Zaehle, Sönke; Aalto, Tuula

    2017-04-01

    We are optimizing key parameters in soil hydrology and forest water and carbon exchange related formulations in ecosystem model JSBACH, which is the land surface component of the Earth System model of Max Planck Institute for Meteorology (MPI-ESM). The model has been modified to use multiple stomatal/canopy conductance formulations which will vary during the optimization process. Our previous results have shown that JSBACH is lacking in its response to drought, which is the motivation to test the different conductance formulations. The optimization is done with the adaptive population importance sampler (APIS) algorithm, that provides a global estimation of the selected JSBACH parameters, using all generated samples. Additionally APIS is able to estimate the model evidence (or partition function), which can be used to determine the optimal submodel (conductance formulation). APIS starts with a set of N randomly generated proposals (standard deviations for the parameters), with location parameters spread in the state space. We draw M samples and calculate the partial IS (importance sampler) estimators for each proposal, after which we update the location parameters and each proposal as well as the global estimator for each JSBACH parameter. This process is then repeated a number of times. The study focuses on boreal coniferous evergreen forests. The optimization is based on site level eddy covariance flux measurements on multiple sites across the Northern Hemisphere, where the parameters are estimated by minimizing the model-data mismatch in evapotranspiration and gross primary production.

  15. Optimal planning for the sustainable utilization of municipal solid waste.

    Science.gov (United States)

    Santibañez-Aguilar, José Ezequiel; Ponce-Ortega, José María; Betzabe González-Campos, J; Serna-González, Medardo; El-Halwagi, Mahmoud M

    2013-12-01

    The increasing generation of municipal solid waste (MSW) is a major problem particularly for large urban areas with insufficient landfill capacities and inefficient waste management systems. Several options associated to the supply chain for implementing a MSW management system are available, however to determine the optimal solution several technical, economic, environmental and social aspects must be considered. Therefore, this paper proposes a mathematical programming model for the optimal planning of the supply chain associated to the MSW management system to maximize the economic benefit while accounting for technical and environmental issues. The optimization model simultaneously selects the processing technologies and their location, the distribution of wastes from cities as well as the distribution of products to markets. The problem was formulated as a multi-objective mixed-integer linear programing problem to maximize the profit of the supply chain and the amount of recycled wastes, where the results are showed through Pareto curves that tradeoff economic and environmental aspects. The proposed approach is applied to a case study for the west-central part of Mexico to consider the integration of MSW from several cities to yield useful products. The results show that an integrated utilization of MSW can provide economic, environmental and social benefits. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. Statistical optimization of acid catalyzed steam pretreatment of citrus peel waste for bioethanol production

    OpenAIRE

    Indulekha John; Prasanthi Yaragarla; Perumalsamy Muthaiah; Kalaichelvi Ponnusamy; Arunagiri Appusamy

    2017-01-01

    Citrus waste is an attractive lignocellulosic biomass for the production of bioethanol due to the richness in carbohydrates and low lignin content. In this study, sweet lime peel was chosen as the lignocellulosic biomass. To increase the cellulose for enzymatic hydrolysis, the statistical optimization of process parameters namely, solid loading, time of exposure and sulphuric acid concentration for pretreatment of sweet lime peel were accomplished by Taguchi orthogonal array design. The sweet...

  17. 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.

  18. Expected optimal feedback with Time-Varying Parameters

    NARCIS (Netherlands)

    Tucci, M.P.; Kendrick, D.A.; Amman, H.M.|info:eu-repo/dai/nl/070970777

    2011-01-01

    In this paper we derive the closed loop form of the Expected Optimal Feedback rule, sometimes called passive learning stochastic control, with time varying parameters. As such this paper extends the work of Kendrick (1981,2002, Chapter 6) where parameters are assumed to vary randomly around a known

  19. Optimal Waste Load Allocation Using Multi-Objective Optimization and Multi-Criteria Decision Analysis

    Directory of Open Access Journals (Sweden)

    L. Saberi

    2016-10-01

    Full Text Available Introduction: Increasing demand for water, depletion of resources of acceptable quality, and excessive water pollution due to agricultural and industrial developments has caused intensive social and environmental problems all over the world. Given the environmental importance of rivers, complexity and extent of pollution factors and physical, chemical and biological processes in these systems, optimal waste-load allocation in river systems has been given considerable attention in the literature in the past decades. The overall objective of planning and quality management of river systems is to develop and implement a coordinated set of strategies and policies to reduce or allocate of pollution entering the rivers so that the water quality matches by proposing environmental standards with an acceptable reliability. In such matters, often there are several different decision makers with different utilities which lead to conflicts. Methods/Materials: In this research, a conflict resolution framework for optimal waste load allocation in river systems is proposed, considering the total treatment cost and the Biological Oxygen Demand (BOD violation characteristics. There are two decision-makers inclusive waste load discharges coalition and environmentalists who have conflicting objectives. This framework consists of an embedded river water quality simulator, which simulates the transport process including reaction kinetics. The trade-off curve between objectives is obtained using the Multi-objective Particle Swarm Optimization Algorithm which these objectives are minimization of the total cost of treatment and penalties that must be paid by discharges and a violation of water quality standards considering BOD parameter which is controlled by environmentalists. Thus, the basic policy of river’s water quality management is formulated in such a way that the decision-makers are ensured their benefits will be provided as far as possible. By using MOPSO

  20. 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.

  1. Stable structures in parameter space and optimal ratchet transport

    Science.gov (United States)

    Celestino, A.; Manchein, C.; Albuquerque, H. A.; Beims, M. W.

    2014-01-01

    Optimal ratchet currents are shown to be directly connected, for all parameters combinations of the ratchet model, to Isoperiodic Stable Structures (ISSs), which are believed to be generic in the parameter spaces of nonlinear dynamical systems. As the ratchet current is more efficient inside the ISSs, which usually are located in preferred direction in the parameter space, it allows us to make crucial statements about the relevant parameters combination to obtain an optimal transport. This is important from the theoretical point of view and for possible experimental realization of efficient currents. We provide an extensive numerical description of the ratchet current throughout the parameters and indicate a trio of ISSs (cusp, non-cusp and shrimp-like), which exist in all pairwise combinations of ratchet parameters. This suggests the general behavior of the ISSs in the context of ratchet transport.

  2. 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.

  3. A kinetic analysis of solid waste composting at optimal conditions.

    Science.gov (United States)

    Komilis, Dimitris P

    2006-01-01

    Six municipal solid waste (MSW) and yard waste components (food waste, mixed paper, yard waste, leaves, branches, grass clippings) were aerobically decomposed to measure the extent of decomposition under near optimal conditions. Decomposition was characterized by at least two principal stages, for most components, as was indicated by the carbon dioxide production rates. An aerobic biodegradation conceptual model is presented here based on the principle that solids hydrolysis is the rate-limiting step during solid waste composting. The mineralizable solid carbon of each solid waste component was assumed to comprise the readily, the moderately and the slowly (or refractory) hydrolysable carbons, each hydrolyzing at different rates to aqueous (water soluble) carbon. Aqueous carbon mineralizes to CO2 at rapid rates that are not rate-limiting to the process. Solids hydrolysis rate constants were calculated after fitting the experimentally determined carbon dioxide production rate data to model results. Hydrolysis rates for the readily hydrolysable carbon in all components ranged from approximately 0.06 to 0.1 d(-1); hydrolysis rates for the moderately hydrolysable carbon ranged from 0.005 to 0.06 d(-1). Leaves, branches and grass clippings did not have a readily hydrolysable carbon fraction, whilst the leaves and branches had the largest slowly hydrolysable carbon fractions (70%, 82%, respectively, of the total solid organic carbon). Grass and yard waste did not contain slowly hydrolysable carbon fractions. Food waste had the largest readily hydrolysable carbon fraction and produced the highest amount of CO2 among all substrates. Moderately hydrolysable solid carbon fractions ranged from 16% to 90% of the total solid organic carbon for all substrates used.

  4. The Optimal Confidence Region for a Random Parameter

    OpenAIRE

    Hajime Uno; Lu Tian; L.J. Wei

    2004-01-01

    Under a two-level hierarchical model, suppose that the distribution of the random parameter is known or can be estimated well. Data are generated via a fixed, but unobservable realization of this parameter. In this paper, we derive the smallest confidence region of the random parameter under a joint Bayesian/frequentist paradigm. On average this optimal region can be much smaller than the corresponding Bayesian highest posterior density region. The new estimation procedure is appealing when o...

  5. 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.

  6. Optimization of structures under material parameter uncertainty using evidence theory

    Science.gov (United States)

    Salehghaffari, S.; Rais-Rohani, M.; Marin, E. B.; Bammann, D. J.

    2013-09-01

    An evidence-based approach is developed for optimization of structural components under material parameter uncertainty. The approach is applied to evidence-based design optimization (EBDO) of externally stiffened circular tubes under axial impact load using an isotropic-elastic-plastic plasticity model to simulate dynamic material behaviour. Uncertainty modelling considers the changes in material parameters that are caused by variability in material properties as well as incertitude and errors in experimental data and procedure to determine the material parameters. Spatial variation of material parameters across the structural component is modelled using a field joint belief structure and propagated for the calculation of evidence-based objective function and design constraints. Surrogate models are used in both uncertainty propagation and solution of the optimization problem. The methodology and the solution to the EBDO example problem are presented and discussed.

  7. Machining Parameters Optimization using Hybrid Firefly Algorithm and Particle Swarm Optimization

    Science.gov (United States)

    Farahlina Johari, Nur; Zain, Azlan Mohd; Haszlinna Mustaffa, Noorfa; Udin, Amirmudin

    2017-09-01

    Firefly Algorithm (FA) is a metaheuristic algorithm that is inspired by the flashing behavior of fireflies and the phenomenon of bioluminescent communication and the algorithm is used to optimize the machining parameters (feed rate, depth of cut, and spindle speed) in this research. The algorithm is hybridized with Particle Swarm Optimization (PSO) to discover better solution in exploring the search space. Objective function of previous research is used to optimize the machining parameters in turning operation. The optimal machining cutting parameters estimated by FA that lead to a minimum surface roughness are validated using ANOVA test.

  8. Challenges when performing economic optimization of waste treatment: A review

    DEFF Research Database (Denmark)

    Juul, Nina; Münster, Marie; Ravn, H.

    2013-01-01

    example, but models focusing on energy production have also been developed, as well as models which take into account a plant’s economies of scale, environmental impact, material recovery and social costs. Finally, models combining different criteria for the selection of waste treatment methods in multi......-criteria analysis have been developed.A thorough updated review of the existing models is presented, and the main challenges and crucial parameters that need to be taken into account when assessing the economic performance of waste treatment alternatives are identified. The review article will assist both policy...

  9. Machining parameter optimization in turning process for sustainable manufacturing

    OpenAIRE

    S. G. Dambhare; S. J. Deshmukh; A. B. Borade

    2015-01-01

    There is an increase in awareness about sustainable manufacturing process. Manufacturing industries are backbone of a country’s economy. Although it is important but there is a great concern about consumption of resources and waste creation. The primary aim of this study was to explore sustainability concern in turning process in an Indian machining industry. The effect of cutting parameters, Speed/Feed/Depth of Cut, the machining environment, Dry/MQL/Wet, and the type of cutting tool on sust...

  10. 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.

  11. Optimization of Gas Metal Arc Welding Process Parameters

    Science.gov (United States)

    Kumar, Amit; Khurana, M. K.; Yadav, Pradeep K.

    2016-09-01

    This study presents the application of Taguchi method combined with grey relational analysis to optimize the process parameters of gas metal arc welding (GMAW) of AISI 1020 carbon steels for multiple quality characteristics (bead width, bead height, weld penetration and heat affected zone). An orthogonal array of L9 has been implemented to fabrication of joints. The experiments have been conducted according to the combination of voltage (V), current (A) and welding speed (Ws). The results revealed that the welding speed is most significant process parameter. By analyzing the grey relational grades, optimal parameters are obtained and significant factors are known using ANOVA analysis. The welding parameters such as speed, welding current and voltage have been optimized for material AISI 1020 using GMAW process. To fortify the robustness of experimental design, a confirmation test was performed at selected optimal process parameter setting. Observations from this method may be useful for automotive sub-assemblies, shipbuilding and vessel fabricators and operators to obtain optimal welding conditions.

  12. 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.

  13. 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....

  14. Likelihood transform: making optimization and parameter estimation easier

    CERN Document Server

    Wang, Yan

    2014-01-01

    Parameterized optimization and parameter estimation is of great importance in almost every branch of modern science, technology and engineering. A practical issue in the problem is that when the parameter space is large and the available data is noisy, the geometry of the likelihood surface in the parameter space will be complicated. This makes searching and optimization algorithms computationally expensive, sometimes even beyond reach. In this paper, we define a likelihood transform which can make the structure of the likelihood surface much simpler, hence reducing the intrinsic complexity and easing optimization significantly. We demonstrate the properties of likelihood transform by apply it to a simplified gravitational wave chirp signal search. For the signal with an signal-to-noise ratio 20, likelihood transform has made a deterministic template-based search possible for the first time, which turns out to be 1000 times more efficient than an exhaustive grid- based search. The method in principle can be a...

  15. 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.

  16. OPTIMAL DISCRETE FUZZY FILTER OF UAV’S FLIGHT PARAMETERS

    Directory of Open Access Journals (Sweden)

    Victor Bocharnikov

    2012-09-01

    Full Text Available  The robust optimal discrete filter for flight information parameters estimation of Unman Arial Vehicle in conditions of nonstationary and not additive disturbance influence, with unknown parameters, is synthesized. The filter based on the theory of fuzzy measure and fuzzy-integral calculus. An estimation of the signal is determined by fuzzy images of the signal estimated value at the previous step of the measured signal and by selection of filtration function. . The investigations of the optimality of synthesized fuzzy filter are performed.

  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. A DEPTH OPTIMIZATION STUDY FOR GEOLOGIC ISOLATION OF RADIOACTIVE WASTES

    Energy Technology Data Exchange (ETDEWEB)

    Thadani, M.

    1980-02-01

    Current Federal plans for the isolation of high-level radioactive wastes and spent fuel include the possible placement of these wastes in deep geologic repositories. It is generally assumed that increasing the emplacement depth increases safety because the wastes are farther removed from the phenomena that might compromise the integrity of their isolation. Also, the path length for the migration of radionuclides to the biosphere increases with depth, thus delaying their arrival. However, increasing the depth of emplacement adds cost and operatiunal penalties. Therefore, a trade-off between the safety and the cost of waste isolation exists. A simple algorithm has been developed to relate the repository construction and operation costs, the costs associated with construction and operational hazards, and the costs resulting from radiological exposures to future generations to the depth of emplacement: The application of the algorithm is illustrated by SdDlP 1 e ca leul at ions u t il i zing se 1 ec ted parameters. The cost-optimum emplacement depths are estimated by summing the cost elements and determining the depth at which the sum would be the least. The relationship between the repository construction costs and the depth of the depository was derived from simplified rock mechanics and stability considerations applied to repository design concepts selected from the current literature and the available data base on mining and excavation costs. In developing the relationship between the repository costs and the depth of the depository, a worldwide cost information data base was used. The relationships developed are suitable for application to bedded sa1t, shale, and basalt geologies. The incremental impacts of hazards as a function of repository depth resulting from drilling, construction of repositories and hoisting systems, and operation of repositories were developed from the reported data on accidents involving shafts and mine construction activities and shaft

  19. Steam generators lay-up optimization and derived wastes reduction

    Energy Technology Data Exchange (ETDEWEB)

    Rabeau, A.M.; Viricel, L. [Electricite de France, Group de Laboratoires (France); Foct, F. [Electricite de France, Dept. MMC (France); Lemaire, P. [Electricite de France, Groupe Maintenance Chaudiere (France); Moreaux, D. [Electricite de France, Groupe Environnement (France)

    2002-07-01

    Today, EDF plants face a new release permit after a steam generators (SGs) wet lay-up, so that the legal authorizations for wastes release to the environment, renewed or being renewed by the safety authorities, allow smallest quantities of wastes than earlier. In this context, EDF studies the optimization of SGs lay-up conditions, and especially of the hydrazine concentration, in order to reduce the liquid wastes releases to the environment, while keeping low corrosion conditions. At the same time, EDF examines a treatment for hydrazine elimination in liquid wastes before their releases. An experimental study has been conducted in order to evaluate the efficiency of hydrazine to control materials corrosion and of nitrogen gas phase to deaerate water. The consequences of lay-up conditions on carbon steel corrosion has also been studied. In the absence of an efficient alternative reagent, hydrazine remains necessary but implies a great care due to its carcinogenic risks and to its toxicity for aquatic organisms. This choice implies studying a method for hydrazine elimination before its release to the environment. The hydrazine elimination from SGs lay-up wastes could be achieved within about one day, by adding about 700 to 800 liters of 30% hydrogen peroxide solution to eliminate 100 kg hydrazine. Copper sulfate would have to be added if copper is not present in the wastes; the copper content in the wastes should be around 100 to 200 {mu}g/kg for the reaction to be fast enough, which is consistent with the legal authorization for copper release to the environment. The nuclear power plants would have to adjust the quantity of hydrogen peroxide to add to the wastes to be treated, based on the quantity of hydrazine to eliminate, in order to avoid any excess of hydrogen peroxide in the wastes at the end of the treatment, since this species is not allowed to be released to the environment. Moreover, the hydrogen peroxide treatment should not have any significant impact on

  20. Optimization of municipal solid waste management in Port Said - Egypt.

    Science.gov (United States)

    Badran, M F; El-Haggar, S M

    2006-01-01

    Optimization of solid waste management systems using operational research methodologies has not yet been applied in any Egyptian governorate. In this paper, a proposed model for a municipal solid waste management system in Port Said, Egypt is presented. It includes the use of the concept of collection stations, which have not yet been used in Egypt. Mixed integer programming is used to model the proposed system and its solution is performed using MPL software V4.2. The results show that the best model would include 27 collection stations of 15-ton daily capacity and 2 collection stations of 10 ton daily capacity. Any transfer of waste between the collection station and the landfill should not occur. Moreover, the flow of the district waste should not be confined to the district collection stations. The cost of the objective function for this solution is 10,122 LE/day (equivalent to 1716 US dollars). After further calculations, the profit generated by the proposed model is 49,655.8 LE/day (equivalent to 8418.23 US dollars).

  1. Optimization of turning process parameters by using grey-Taguchi

    African Journals Online (AJOL)

    DR OKE

    By applying Taguchi method the quality of manufactured goods, and engineering designs are developed by studying variations. In this work, an attempt has been made to solve the correlated multiple criteria optimization problem of turning process by considering three different process parameters viz. cutting-speed, feed ...

  2. Statistical optimization of process parameters for the production of ...

    African Journals Online (AJOL)

    ONOS

    2010-01-25

    Jan 25, 2010 ... 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.

  3. Optimization of physical and biological parameters for transient ...

    African Journals Online (AJOL)

    African Journal of Biotechnology ... The effects of different physical, biological and DNA parameters were evaluated by comparing the number of blue spots obtained from the histochemical GUS assay. Optimal ... The highest number of blue spots obtained in this protocol was 1500 blue spots per 1 cm2 of bombarded tissue.

  4. Optimization of process parameters for the production of alkali ...

    African Journals Online (AJOL)

    Optimization of process parameters for the production of alkali-tolerant carboxymethyl cellulase by newly isolated Streptomyces sp. strain NEAE-D. ... The optimum conditions for CMCase production were the use of pretreated rice straw as the best carbon source that supported better CMCase production than carboxymethyl ...

  5. Optimization of physical and biological parameters for transient ...

    African Journals Online (AJOL)

    STORAGESEVER

    2009-08-18

    Aug 18, 2009 ... Full Length Research Paper. Optimization of physical and biological parameters for transient .... removal of the liquid, the pellet was washed twice (without vortexing) with 140 µl of 70 and 100% ethanol, ..... et al., 1999), cassava (Schopk et al., 1997), coffee. (Gatica-Arias et al., 2008) and Alstromeria (Kim, ...

  6. The optimization of voltage parameter for tissue electroporation in ...

    African Journals Online (AJOL)

    USER

    2010-07-19

    Jul 19, 2010 ... Full Length Research Paper. The optimization of voltage parameter for tissue .... After incubation, 20 embryos were washed twice with sterile water and transferred to each ice-cold 0.4 cm ... were electroporated different somatic embryos of coffee, found the highest transient GUS gene expression at the.

  7. Optimization of processing parameters for making alumina–partially ...

    Indian Academy of Sciences (India)

    The aim of the work was to optimize the processing parameters for fabricating laminated ceramic composites of Al2O3–Y–PSZ. ... the co-sintering layers due to their different sintering kinetics,; thermal expansion mismatch, and; a tensile component of the residual stress in the layer under residual compressive stress.

  8. Optimization of process parameter for synthesis of silicon quantum ...

    Indian Academy of Sciences (India)

    Home; Journals; Bulletin of Materials Science; Volume 36; Issue 3. Optimization of process parameter for synthesis of silicon quantum dots using low pressure chemical vapour deposition. Dipika Barbadikar Rashmi Gautam Sanjay Sahare Rajendra Patrikar Jatin Bhatt. Volume 36 Issue 3 June 2013 pp 483-490 ...

  9. Optimization of machining parameters of hard porcelain on a CNC ...

    African Journals Online (AJOL)

    In order to build up a relationship between quality and productivity, the present work focuses an optimized approach to establishing the multi-objective machining parameters and mathematical models for Pressure and Voltage on CNC turning machine (SINUMERIK802D). The Pressure and Voltage seem to be known as ...

  10. Multi responses optimization of wire EDM process parameters using ...

    African Journals Online (AJOL)

    The wire EDM was known as for its better efficiency to machining hardest material and give precise and accurate result comparing to other machining process. The intent of this experimental paper is to optimize the machining parameters of Wire Electrical Discharge Machining (WEDM) on En45A Alloy Steel with the ...

  11. Optimization of processing parameters for making alumina–partially ...

    Indian Academy of Sciences (India)

    Unknown

    The aim of the work was to optimize the processing parameters for fabricating laminated ceramic .... 3.1 Residual stress. The residual strain developed in a ceramic laminate con- sisting of thin layers of two different materials, 1 and 2, due to their thermal expansion ..... and another irregular pore shaped pocket of alumina.

  12. The Determination of Optimal Parameters of Fuzzy PI Sugeno Controller

    Science.gov (United States)

    Kudinov, Y. I.; Kudinov, I. Yu; Volkova, A. A.; Durgarjan, I. S.; Pashchenko, F. F.

    2017-11-01

    Describe the procedure for determining by means of Matlab and Simulink optimal parameters of the fuzzy PI controller Sugeno, where some indicators of the quality of the transition process in a closed system control with this controller satisfies the specified conditions.

  13. 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 ...

  14. Combined Municipal Solid Waste and biomass system optimization for district energy applications.

    Science.gov (United States)

    Rentizelas, Athanasios A; Tolis, Athanasios I; Tatsiopoulos, Ilias P

    2014-01-01

    Municipal Solid Waste (MSW) disposal has been a controversial issue in many countries over the past years, due to disagreement among the various stakeholders on the waste management policies and technologies to be adopted. One of the ways of treating/disposing MSW is energy recovery, as waste is considered to contain a considerable amount of bio-waste and therefore can lead to renewable energy production. The overall efficiency can be very high in the cases of co-generation or tri-generation. In this paper a model is presented, aiming to support decision makers in issues relating to Municipal Solid Waste energy recovery. The idea of using more fuel sources, including MSW and agricultural residue biomass that may exist in a rural area, is explored. The model aims at optimizing the system specifications, such as the capacity of the base-load Waste-to-Energy facility, the capacity of the peak-load biomass boiler and the location of the facility. Furthermore, it defines the quantity of each potential fuel source that should be used annually, in order to maximize the financial yield of the investment. The results of an energy tri-generation case study application at a rural area of Greece, using mixed MSW and biomass, indicate positive financial yield of investment. In addition, a sensitivity analysis is performed on the effect of the most important parameters of the model on the optimum solution, pinpointing the parameters of interest rate, investment cost and heating oil price, as those requiring the attention of the decision makers. Finally, the sensitivity analysis is enhanced by a stochastic analysis to determine the effect of the volatility of parameters on the robustness of the model and the solution obtained. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Optimization of squalene produced from crude palm oil waste

    Science.gov (United States)

    Wandira, Irda; Legowo, Evita H.; Widiputri, Diah I.

    2017-01-01

    Squalene is a hydrocarbon originally and still mostly extracted from shark liver oil. Due to environmental issues over shark hunting, there have been efforts to extract squalene from alternative sources, such as Palm Fatty Acid Distillate (PFAD), one of crude palm oil (CPO) wastes. Previous researches have shown that squalene can be extracted from PFAD using saponification process followed with liquid-liquid extraction process although the method had yet to be optimized in order to optimize the amount of squalene extracted from PFAD. The optimization was done by optimizing both processes of squalene extraction method: saponification and liquid-liquid extraction. The factors utilized in the saponification process optimization were KOH concentration and saponification duration while during the liquid-liquid extraction (LLE) process optimization, the factors used were the volumes of distilled water and dichloromethane. The optimum percentage of squalene content in the extract (24.08%) was achieved by saponifying the PFAD with 50%w/v KOH for 60 minutes and subjecting the saponified PFAD to LLE, utilizing 100 ml of distilled water along with 3 times addition of fresh dichloromethane, 75 ml each; those factors would be utilized in the optimum squalene extraction method.

  16. 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

  17. A split-optimization approach for obtaining multiple solutions in single-objective process parameter optimization.

    Science.gov (United States)

    Rajora, Manik; Zou, Pan; Yang, Yao Guang; Fan, Zhi Wen; Chen, Hung Yi; Wu, Wen Chieh; Li, Beizhi; Liang, Steven Y

    2016-01-01

    It can be observed from the experimental data of different processes that different process parameter combinations can lead to the same performance indicators, but during the optimization of process parameters, using current techniques, only one of these combinations can be found when a given objective function is specified. The combination of process parameters obtained after optimization may not always be applicable in actual production or may lead to undesired experimental conditions. In this paper, a split-optimization approach is proposed for obtaining multiple solutions in a single-objective process parameter optimization problem. This is accomplished by splitting the original search space into smaller sub-search spaces and using GA in each sub-search space to optimize the process parameters. Two different methods, i.e., cluster centers and hill and valley splitting strategy, were used to split the original search space, and their efficiency was measured against a method in which the original search space is split into equal smaller sub-search spaces. The proposed approach was used to obtain multiple optimal process parameter combinations for electrochemical micro-machining. The result obtained from the case study showed that the cluster centers and hill and valley splitting strategies were more efficient in splitting the original search space than the method in which the original search space is divided into smaller equal sub-search spaces.

  18. Optimizing of regime parameters in the rock disintegration

    Directory of Open Access Journals (Sweden)

    Milan Labaš

    2008-03-01

    Full Text Available The contribution describes a concept of the evaluation of rock disintegration process using the energetic theory and an optimization of rock disintegration process depending on input parameters, i.e. the thrust force and the torque. The interaction of the tool and the rock causes deformations, mechanical oscillations, etc. The Department of destructional and constructional geotechnics of the Institute of Geotechnics SAS investigates the vibrations from both the quantitative and qualitative point of view. The evaluation of disintegration processes improves the energy distribution and the efficiency of the mechanical rock disintegration. The paper evaluates the initial measurements at the rock disintegration by drilling. The contribution is a form of a profile and joins the optimization of rock disintegration based on input parameters with the optimization of a width of the drilling tool segment. The vibration signal as a carrier of the information on the process enables to improve the optimization with further parameters of rock disintegration, such as the rock type, tool and the tool wear.

  19. Multiexposure imaging and parameter optimization for intensified star trackers.

    Science.gov (United States)

    Yu, Wenbo; Jiang, Jie; Zhang, Guangjun

    2016-12-20

    Due to the introduction of the intensified image detector, the dynamic performance of the intensified star tracker is effectively improved. However, its attitude update rate is still seriously restricted by the transmission and processing of pixel data. In order to break through the above limitation, a multiexposure imaging approach for intensified star trackers is proposed in this paper. One star image formed by this approach actually records N different groups of star positions, and then N corresponding groups of attitude information can be acquired. Compared with the existing exposure imaging approach, the proposed approach improves the attitude update rate by N times. Furthermore, for a dim star, the proposed approach can also accumulate the energy of its N positions and then effectively improve its signal-to-noise ratio. Subsequently, in order to obtain the optimal performance of the proposed approach, parameter optimization is carried out. First, the motion model of the star spot in the image plane is established, and then based on it, all the key parameters are optimized. Simulations and experiments demonstrate the feasibility and effectiveness of the proposed approach and parameter optimization.

  20. The solution of private problems for optimization heat exchangers parameters

    Science.gov (United States)

    Melekhin, A.

    2017-11-01

    The relevance of the topic due to the decision of problems of the economy of resources in heating systems of buildings. To solve this problem we have developed an integrated method of research which allows solving tasks on optimization of parameters of heat exchangers. 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 author 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.

  1. Parameter Optimization for Turbulent Reacting Flows Using Adjoints

    Science.gov (United States)

    Lapointe, Caelan; Hamlington, Peter E.

    2017-11-01

    The formulation of a new adjoint solver for topology optimization of turbulent reacting flows is presented. This solver provides novel configurations (e.g., geometries and operating conditions) based on desired system outcomes (i.e., objective functions) for complex reacting flow problems of practical interest. For many such problems, it would be desirable to know optimal values of design parameters (e.g., physical dimensions, fuel-oxidizer ratios, and inflow-outflow conditions) prior to real-world manufacture and testing, which can be expensive, time-consuming, and dangerous. However, computational optimization of these problems is made difficult by the complexity of most reacting flows, necessitating the use of gradient-based optimization techniques in order to explore a wide design space at manageable computational cost. The adjoint method is an attractive way to obtain the required gradients, because the cost of the method is determined by the dimension of the objective function rather than the size of the design space. Here, the formulation of a novel solver is outlined that enables gradient-based parameter optimization of turbulent reacting flows using the discrete adjoint method. Initial results and an outlook for future research directions are provided.

  2. Optimizing dictionary learning parameters for solving Audio Inpainting problem

    Directory of Open Access Journals (Sweden)

    Václav Mach

    2013-01-01

    Full Text Available Recovering missing or distorted audio signal sam-ples has been recently improved by solving an Audio Inpaintingproblem. This paper aims to connect this problem with K-SVD dictionary learning to improve reconstruction error formissing signal insertion problem. Our aim is to adapt an initialdictionary to the reliable signal to be more accurate in missingsamples estimation. This approach is based on sparse signalsreconstruction and optimization problem. In the paper two staplealgorithms, connection between them and emerging problemsare described. We tried to find optimal parameters for efficientdictionary learning.

  3. 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.

  4. Optimization of thermo-chemical hydrolysis of kitchen wastes.

    Science.gov (United States)

    Vavouraki, Aikaterini Ioannis; Angelis, Evangelos Michael; Kornaros, Michael

    2013-03-01

    Municipal Solid Wastes (MSWs) in Greece consist mainly of fermentable organic material such as food scraps (∼50%) and paper residuals (∼20%). The aim of this work was to study the thermo-chemical pretreatment of the kitchen waste (KW) fraction of MSW focusing on biotechnological exploitation of pretreated wastes for biofuel production. A representative sample of municipal food residues was derived by combining weighted amounts of each individual type of residue recognized in daily samples obtained from the University of Patras' students restaurant located at the Students Residence Hall (Greece). Chemical pretreatment experiments of the representative KW sample were performed using several types of chemical solutions (i.e. H2SO4, HCl, NaOH, H2SO3) of different solute concentration (0.7%, 1.5%, 3%) at three temperatures (50, 75, 120°C) and a range of residence times (30-120min). Optimized results proved that chemical pretreatment of KW, using either 1.12% HCl for 94min or 1.17% HCl for 86min (at 100°C), increased soluble sugars concentration by 120% compared to untreated KW. The increase of soluble sugars was mainly attributed to the mono-sugars glucose and fructose. Copyright © 2012 Elsevier Ltd. All rights reserved.

  5. Modeling and optimization of integrated exhaust gas recirculation and multi-stage waste heat recovery in marine engines

    DEFF Research Database (Denmark)

    Kyriakidis, Fotis; Sørensen, Kim; Singh, Shobhana

    2017-01-01

    is optimized to utilize the maximum waste heat recovery. The Genetic algorithm and fmincon active-set algorithm are used to optimize the design and operation parameters for the two steam cycles. The optimization aims to find the theoretically optimal combination of the pressure levels and pinch......Waste heat recovery combined with exhaust gas recirculation is a promising technology that can address both the issue of NOx (nitrogen oxides) reduction and fuel savings by including a pressurized boiler. In the present study, a theoretical optimization of the performance of two different...... configurations of steam Rankine cycles, with integrated exhaust gas recirculation for a marine diesel engine, is presented. The first configuration employs two pressure levels and the second is configured with three-pressure levels. The models are developed in MATLAB based on the typical data of a large two...

  6. 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.

  7. Optimizing Muscle Parameters in Musculoskeletal Modeling Using Monte Carlo Simulations

    Science.gov (United States)

    Hanson, Andrea; Reed, Erik; Cavanagh, Peter

    2011-01-01

    Astronauts assigned to long-duration missions experience bone and muscle atrophy in the lower limbs. The use of musculoskeletal simulation software has become a useful tool for modeling joint and muscle forces during human activity in reduced gravity as access to direct experimentation is limited. Knowledge of muscle and joint loads can better inform the design of exercise protocols and exercise countermeasure equipment. In this study, the LifeModeler(TM) (San Clemente, CA) biomechanics simulation software was used to model a squat exercise. The initial model using default parameters yielded physiologically reasonable hip-joint forces. However, no activation was predicted in some large muscles such as rectus femoris, which have been shown to be active in 1-g performance of the activity. Parametric testing was conducted using Monte Carlo methods and combinatorial reduction to find a muscle parameter set that more closely matched physiologically observed activation patterns during the squat exercise. Peak hip joint force using the default parameters was 2.96 times body weight (BW) and increased to 3.21 BW in an optimized, feature-selected test case. The rectus femoris was predicted to peak at 60.1% activation following muscle recruitment optimization, compared to 19.2% activation with default parameters. These results indicate the critical role that muscle parameters play in joint force estimation and the need for exploration of the solution space to achieve physiologically realistic muscle activation.

  8. Optimization of Neutrino Oscillation Parameters using Differential Evolution

    CERN Document Server

    Mustafa, Ghulam; Masud, Bilal

    2011-01-01

    We combine Differential Evolution, a new technique, with the traditional grid based method for optimization of solar neutrino oscillation parameters $\\Delta m^2$ and $\\tan^{2}\\theta$ for the case of two neutrinos. The Differential Evolution is a population based stochastic algorithm for optimization of real valued non-linear non-differentiable objective functions that has become very popular during the last decade. We calculate well known chi-square ($\\chi^2$) function for neutrino oscillations for a grid of the parameters using total event rates of chlorine (Homestake), Gallax+GNO, SAGE, Superkamiokande and SNO detectors and theoretically calculated event rates. We find minimum $\\chi^2$ values in different regions of the parameter space. We explore regions around these minima using Differential Evolution for the fine tuning of the parameters allowing even those values of the parameters which do not lie on any grid. We note as much as 4 times decrease in $\\chi^2$ value in the SMA region and even better goodne...

  9. Optimal excitation design for identifying inertia parameters of spacecraft

    Science.gov (United States)

    Zhai, Kun; Wang, Tianshu; Meng, Dongbo

    2017-11-01

    Excitation design is one of the important contents in the identification of inertia parameters and the form of excitation has a great influence on the identification result. This paper presents a new method to design and calculate the optimal excitation. Firstly for a spacecraft equipped with momentum wheels, the identification problem is established based on conversation of angular momentum and an inverse operating. A performance index which is similar to but not the condition number is first defined as the benchmark for designing the optimal excitation. Because the performance index only depends on performances of the actuator, such as the angular momentum of the wheel, a simple direct-search method is applied to calculate the optimal excitation for the case without terminal angular velocity constraints and a two-step direct-search method for the case with terminal angular velocity constraints. While the initial angular momentum of spacecraft system is considered, the optimal excitation is obtained based on the difference of two successive measurements. Finally, the optimal excitation for a spacecraft using thrusters is designed according to the same design process. Simulation results show that the calculated optimal excitation has the good performance index and can produce accurate identification results even when some perturbations are considered.

  10. Analysis and Optimization of Central Processing Unit Process Parameters

    Science.gov (United States)

    Kaja Bantha Navas, R.; Venkata Chaitana Vignan, Budi; Durganadh, Margani; Rama Krishna, Chunduri

    2017-05-01

    The rapid growth of computer has made processing more data capable, which increase the heat dissipation. Hence the system unit CPU must be cooled against operating temperature. This paper presents a novel approach for the optimization of operating parameters on Central Processing Unit with single response based on response graph method. These methods have a series of steps from of proposed approach which are capable of decreasing uncertainty caused by engineering judgment in the Taguchi method. Orthogonal Array value was taken from ANSYS report. The method shows a good convergence with the experimental and the optimum process parameters.

  11. Communication: Optimal parameters for basin-hopping global optimization based on Tsallis statistics

    Science.gov (United States)

    Shang, C.; Wales, D. J.

    2014-08-01

    A fundamental problem associated with global optimization is the large free energy barrier for the corresponding solid-solid phase transitions for systems with multi-funnel energy landscapes. To address this issue we consider the Tsallis weight instead of the Boltzmann weight to define the acceptance ratio for basin-hopping global optimization. Benchmarks for atomic clusters show that using the optimal Tsallis weight can improve the efficiency by roughly a factor of two. We present a theory that connects the optimal parameters for the Tsallis weighting, and demonstrate that the predictions are verified for each of the test cases.

  12. Multidimensional Optimization of Signal Space Distance Parameters in WLAN Positioning

    Directory of Open Access Journals (Sweden)

    Milenko Brković

    2014-01-01

    Full Text Available Accurate indoor localization of mobile users is one of the challenging problems of the last decade. Besides delivering high speed Internet, Wireless Local Area Network (WLAN can be used as an effective indoor positioning system, being competitive both in terms of accuracy and cost. Among the localization algorithms, nearest neighbor fingerprinting algorithms based on Received Signal Strength (RSS parameter have been extensively studied as an inexpensive solution for delivering indoor Location Based Services (LBS. In this paper, we propose the optimization of the signal space distance parameters in order to improve precision of WLAN indoor positioning, based on nearest neighbor fingerprinting algorithms. Experiments in a real WLAN environment indicate that proposed optimization leads to substantial improvements of the localization accuracy. Our approach is conceptually simple, is easy to implement, and does not require any additional hardware.

  13. Underfill Parameter Optimization Study for Mobile Products with Numerical Analysis

    Science.gov (United States)

    Nakanishi, Tohru; Shundoh, Yoshimune; Kuboyama, Toshifumi

    We reported on a numerical analysis of the material properties that directly control the quality of the analytic results in our previous paper. In this paper, we focus on parameter optimization for the underfill in high density products such as consumer electronics devices. We report on our methodology to optimize the underfill properties through some parameter studies with numerical analysis. It is difficult to select the best underfill to be used for the high density packaging. In this study, some currently available underfills and a newly developed one are used in wafer level chip-sized package technology to compare the reliability of the packages against the stress and strain caused at both solder and underfill under thermal stress.

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

    Science.gov (United States)

    2017-09-01

    SUBJECT TERMS Search Theory , Undersea Warfare, South China Sea, Anti-Submarine Warfare 15. NUMBER OF PAGES 253 16. PRICE CODE 17. SECURITY...to 09-22-2017 4. TITLE AND SUBTITLE SEARCH PARAMETER OPTIMIZATION FOR DISCRETE, BAYESIAN, AND CON- TINUOUS SEARCH ALGORITHMS 5. FUNDING NUMBERS 6...REPORT NUMBER 9. SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) N/A 10. SPONSORING / MONITORING AGENCY REPORT NUMBER 11. SUPPLEMENTARY NOTES The

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

    Indian Academy of Sciences (India)

    An Al-5 wt% TiC composite was processed in situ using K2TiF6 and graphite in Al melt and subjected to FSP. Processing parameters for FSP were optimized to get a defect free stir zone and homogenize the particle distribution. It was found that a rotation speed > 800 rpm is needed. A rotation speed of 1000 rpm and a ...

  16. 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.

  17. Standardless quantification by parameter optimization in electron probe microanalysis

    Science.gov (United States)

    Limandri, Silvina P.; Bonetto, Rita D.; Josa, Víctor Galván; Carreras, Alejo C.; Trincavelli, Jorge C.

    2012-11-01

    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.

  18. Optimal sensor placement for parameter estimation of bridges

    Science.gov (United States)

    Eskew, Edward; Jang, Shinae

    2017-04-01

    Gathering measurements from a structure can be extremely valuable for tasks such as verifying a numerical model, or structural health monitoring (SHM) to identify changes in the natural frequencies and mode shapes which can be attributed to changes in the system. In most monitoring applications, the number of potential degrees-of-freedom (DOF) for monitoring greatly outnumbers the available sensors. Optimal sensor placement (OSP) is a field of research into different methods for locating the available sensors to gather the optimal measurements. Three common methods of OSP are the effective independence (EI), effective independence driving point residue (EI-DPR), and modal kinetic energy (MKE) methods. However, comparisons of the different OSP methods for SHM applications are limited. In this paper, a comparison of the performance of the three described OSP methods for parameter estimation is performed. Parameter estimation is implemented using modified parameter localization with direct model updating, and added mass quantification utilizing a genetic algorithm (GA). The quantification of the mass addition, using simulated measurements from the sensor networks developed by each OSP method, is compared to provide an evaluation of each OSP methods capability for parameter estimation applications.

  19. 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.

  20. A Combined Method in Parameters Optimization of Hydrocyclone

    Directory of Open Access Journals (Sweden)

    Jing-an Feng

    2016-01-01

    Full Text Available To achieve efficient separation of calcium hydroxide and impurities in carbide slag by using hydrocyclone, the physical granularity property of carbide slag, hydrocyclone operation parameters for slurry concentration, and the slurry velocity inlet are designed to be optimized. The optimization methods are combined with the Design of Experiment (DOE method and the Computational Fluid Dynamics (CFD method. Based on Design Expert software, the central composite design (CCD with three factors and five levels amounting to five groups of 20 test responses was constructed, and the experiments were performed by numerical simulation software FLUENT. Through the analysis of variance deduced from numerical simulation experiment results, the regression equations of pressure drop, overflow concentration, purity, and separation efficiencies of two solid phases were, respectively, obtained. The influences of factors were analyzed by the responses, respectively. Finally, optimized results were obtained by the multiobjective optimization method through the Design Expert software. Based on the optimized conditions, the validation test by numerical simulation and separation experiment were separately proceeded. The results proved that the combined method could be efficiently used in studying the hydrocyclone and it has a good performance in application engineering.

  1. Optimization of food waste compost with the use of biochar.

    Science.gov (United States)

    Waqas, M; Nizami, A S; Aburiazaiza, A S; Barakat, M A; Ismail, I M I; Rashid, M I

    2017-06-18

    This paper aims to examine the influence of biochar produced from lawn waste in accelerating the degradation and mineralization rates of food waste compost. Biochar produced at two different temperatures (350 and 450 °C) was applied at the rates 10 and 15% (w/w) of the total waste to an in-vessel compost bioreactor for evaluating its effects on food waste compost. The quality of compost was assessed against stabilization indices such as moisture contents (MC), electrical conductivity (EC), organic matters (OM) degradation, change in total carbon (TC) and mineral nitrogen contents such as ammonium (NH4+) and nitrate (NO3-). The use of biochar significantly improved the composting process and physiochemical properties of the final compost. Results showed that in comparison to control trial, biochar amended compost mixtures rapidly achieved the thermophilic temperature, increased the OM degradation by 14.4-15.3%, concentration of NH4+ by 37.8-45.6% and NO3- by 50-62%. The most prominent effects in term of achieving rapid thermophilic temperature and a higher concentration of NH4+ and NO3- were observed at 15% (w/w) biochar. According to compost quality standard of United States (US), California, Germany, and Austria, the compost stability as a result of biochar addition was achieved in 50-60 days. Nonetheless, the biochar produced at 450 °C had similar effects as to biochar produced at 350 °C for most of the compost parameters. Therefore, it is recommended to produce biochar at 350 °C to reduce the energy requirements for resource recovery of biomass and should be added at a concentration of 15% (w/w) to the compost bioreactor for achieving a stable compost. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Growth parameter optimization for fast quantum dot SESAMs.

    Science.gov (United States)

    Maas, D J H C; Bellancourt, A-R; Hoffmann, M; Rudin, B; Barbarin, Y; Golling, M; Südmeyer, T; Keller, U

    2008-11-10

    Semiconductor saturable absorber mirrors (SESAMs) using quantum dot (QD) absorbers exhibit a larger design freedom than standard quantum well absorbers. The additional parameter of the dot density in combination with the field enhancement allows for an independent control of saturation fluence and modulation depth. We present the first detailed study of the effect of QD growth parameters and post growth annealing on the macroscopic optical SESAM parameters, measuring both nonlinear reflectivity and recombination dynamics. We studied a set of self-assembled InAs QD-SESAMs optimized for an operation wavelength around 960 nm with varying dot density and growth temperature. We confirm that the modulation depth is controlled by the dot density. We present design guidelines for QD-SESAMs with low saturation fluence and fast recovery, which are for example important for modelocking of vertical external cavity surface emitting lasers (VECSELs).

  3. Optimal Parameters of Adaptive Segmentation for Epileptic Graphoelements Recognition

    Directory of Open Access Journals (Sweden)

    D. Kala

    2017-04-01

    Full Text Available Manual review of EEG records, as it is per¬formed in common medical practice, is very time-consuming. There is an effort to make this analysis easier and faster for neurologists by using systems for automatic EEG graphoelements recognition. Such a system is composed of three steps: (1 segmentation, which is a subject of this article, (2 features extraction and (3 classification. Precision of classification, and thereby the whole recognition, is strongly affected by the quality of preceding segmentation procedure, which depends on the method of segmentation and its parameters. In this paper, Varri’s method for segmentation of real epileptic EEG signals is used. Effect of input parameters on segmentation outcome is discussed and parameters values are proposed to achieve optimal outcome suitable for the following classification and graphoelements recognition. Only the results of segmentation are presented in this paper.

  4. Dose-painting IMRT optimization using biological parameters.

    Science.gov (United States)

    Kim, Yusung; Tomé, Wolfgang A

    2010-11-01

    Our work on dose-painting based on the possible risk characteristics for local recurrence in tumor subvolumes and the optimization of treatment plans using biological objective functions that are region-specific are reviewed. A series of intensity modulated dose-painting techniques are compared to their corresponding intensity modulated plans in which the entire PTV is treated to a single dose level, delivering the same equivalent uniform dose (EUD) to the entire PTV. Iso-TCP and iso-NTCP maps are introduced as a tool to aid the planner in the evaluation of the resulting non-uniform dose distributions. Iso-TCP and iso-NTCP maps are akin to iso-dose maps in 3D conformal radiotherapy. The impact of the currently limited diagnostic accuracy of functional imaging on a series of dose-painting techniques is also discussed. Utilizing biological parameters (risk-adaptive optimization) in the generation of dose-painting plans results in an increase in the therapeutic ratio as compared to conventional dose-painting plans in which optimization techniques based on physical dose are employed. Dose-painting employing biological parameters appears to be a promising approach for individualized patient- and disease-specific radiotherapy.

  5. Optimization of plasma flow parameters of the magnetoplasma compressor

    Science.gov (United States)

    Dojcinovic, I. P.; Kuraica, M. M.; Obradovc, B. M.; Cvetanovic, N.; Puric, J.

    2007-02-01

    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.

  6. Estimation of Saxophone Control Parameters by Convex Optimization.

    Science.gov (United States)

    Wang, Cheng-I; Smyth, Tamara; Lipton, Zachary C

    2014-12-01

    In this work, an approach to jointly estimating the tone hole configuration (fingering) and reed model parameters of a saxophone is presented. The problem isn't one of merely estimating pitch as one applied fingering can be used to produce several different pitches by bugling or overblowing. Nor can a fingering be estimated solely by the spectral envelope of the produced sound (as it might for estimation of vocal tract shape in speech) since one fingering can produce markedly different spectral envelopes depending on the player's embouchure and control of the reed. The problem is therefore addressed by jointly estimating both the reed (source) parameters and the fingering (filter) of a saxophone model using convex optimization and 1) a bank of filter frequency responses derived from measurement of the saxophone configured with all possible fingerings and 2) sample recordings of notes produced using all possible fingerings, played with different overblowing, dynamics and timbre. The saxophone model couples one of several possible frequency response pairs (corresponding to the applied fingering), and a quasi-static reed model generating input pressure at the mouthpiece, with control parameters being blowing pressure and reed stiffness. Applied fingering and reed parameters are estimated for a given recording by formalizing a minimization problem, where the cost function is the error between the recording and the synthesized sound produced by the model having incremental parameter values for blowing pressure and reed stiffness. The minimization problem is nonlinear and not differentiable and is made solvable using convex optimization. The performance of the fingering identification is evaluated with better accuracy than previous reported value.

  7. 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.

  8. Statistical optimization of acid catalyzed steam pretreatment of citrus peel waste for bioethanol production

    Directory of Open Access Journals (Sweden)

    Indulekha John

    2017-12-01

    Full Text Available Citrus waste is an attractive lignocellulosic biomass for the production of bioethanol due to the richness in carbohydrates and low lignin content. In this study, sweet lime peel was chosen as the lignocellulosic biomass. To increase the cellulose for enzymatic hydrolysis, the statistical optimization of process parameters namely, solid loading, time of exposure and sulphuric acid concentration for pretreatment of sweet lime peel were accomplished by Taguchi orthogonal array design. The sweet lime peel was exposed to acid catalyzed steam pretreatment for solid loading [10%, 12%, 15% and 17% (w/v], time of exposure [15min, 30min, 45min and 60min] and sulphuric acid concentration [0.25%, 0.5%, 0.75% and 1% (v/v]. The cellulose content was found to be an optimum at 35% for 17% (w/v solid loading and 0.25% (v/v acid concentration and steam exposure for 60min. With these optimized process parameters, enzymatic hydrolysis of pretreated sweet lime peel was investigated at 50 °C for 48h using in vitro isolated enzymes, viz., cellulase and pectinase from Aspergillus Niger with an activity of 1.7FPU/ml and15IU/ml respectively. 7.09mg of reducing sugar/ml of hydrolysate was released in enzymatic hydrolysis which was estimated by DNS method. For the production of bioethanol, fermentation of hydrolysate was carried out at 30 °C for 72h using baker's yeast. The yield of ethanol was 18%. From this study, it is proved that citrus waste is a promising source for the production of bioethanol. Keywords: Bioethanol, Citrus peel waste, Optimization, Pretreatment, Hydrolysis, Fermentation

  9. Optimization of Eisenia fetida stocking density for the bioconversion of rock phosphate enriched cow dung–waste paper mixtures

    Energy Technology Data Exchange (ETDEWEB)

    Unuofin, F.O., E-mail: funmifrank2009@gmail.com; Mnkeni, P.N.S., E-mail: pmnkeni@ufh.ac.za

    2014-11-15

    Highlights: • Vermidegradation of RP-enriched waste mixtures is dependent on E. fetida stocking density. • A stocking density of 12.5 g-worms kg{sup -1} resulted in highly humified vermicomposts. • P release from RP-enriched waste vermicomposts increases with E. fetida stocking density. • RP-enriched waste vermicomposts had no inhibitory effect on seed germination. - Abstract: Vermitechnology is gaining recognition as an environmental friendly waste management strategy. Its successful implementation requires that the key operational parameters like earthworm stocking density be established for each target waste/waste mixture. One target waste mixture in South Africa is waste paper mixed with cow dung and rock phosphate (RP) for P enrichment. This study sought to establish optimal Eisenia fetida stocking density for maximum P release and rapid bioconversion of RP enriched cow dung–paper waste mixtures. E. fetida stocking densities of 0, 7.5, 12.5, 17.5 and 22.5 g-worms kg{sup −1} dry weight of cow dung–waste paper mixtures were evaluated. The stocking density of 12.5 g-worms kg{sup −1} resulted in the highest earthworm growth rate and humification of the RP enriched waste mixture as reflected by a C:N ratio of <12 and a humic acid/fulvic acid ratio of >1.9 in final vermicomposts. A germination test revealed that the resultant vermicompost had no inhibitory effect on the germination of tomato, carrot, and radish. Extractable P increased with stocking density up to 22.5 g-worm kg{sup −1} feedstock suggesting that for maximum P release from RP enriched wastes a high stocking density should be considered.

  10. variation of some waste stabilization pond parameters with shape

    African Journals Online (AJOL)

    Waste Stabilization Pond (WSP) are designed to provide control environment for wastewater treatment. The primary purpose of wastewater treatment is the reduction of pathogenic contamination, suspended solids, oxygen demand and nutrient environment. The geometry of the pond could be structured in order to give the ...

  11. Variation of some Waste Stabilization Pond Parameters with Shape ...

    African Journals Online (AJOL)

    Waste Stabilization Pond (WSP) are designed to provide control environment for wastewater treatment. The primary purpose of wastewater treatment is the reduction of pathogenic contamination, suspended solids, oxygen demand and nutrient environment. The geometry of the pond could be structured in order to give the ...

  12. Optimizing experimental parameters for tracking of diffusing particles

    DEFF Research Database (Denmark)

    Vestergaard, Christian L.

    2016-01-01

    We describe how a single-particle tracking experiment should be designed in order for its recorded trajectories to contain the most information about a tracked particle's diffusion coefficient. The precision of estimators for the diffusion coefficient is affected by motion blur, limited photon...... statistics, and the length of recorded time series. We demonstrate for a particle undergoing free diffusion that precision is negligibly affected by motion blur in typical experiments, while optimizing photon counts and the number of recorded frames is the key to precision. Building on these results, we...... describe for a wide range of experimental scenarios how to choose experimental parameters in order to optimize the precision. Generally, one should choose quantity over quality: experiments should be designed to maximize the number of frames recorded in a time series, even if this means lower information...

  13. Total energy control system autopilot design with constrained parameter optimization

    Science.gov (United States)

    Ly, Uy-Loi; Voth, Christopher

    1990-01-01

    A description is given of the application of a multivariable control design method (SANDY) based on constrained parameter optimization to the design of a multiloop aircraft flight control system. Specifically, the design method is applied to the direct synthesis of a multiloop AFCS inner-loop feedback control system based on total energy control system (TECS) principles. The design procedure offers a structured approach for the determination of a set of stabilizing controller design gains that meet design specifications in closed-loop stability, command tracking performance, disturbance rejection, and limits on control activities. The approach can be extended to a broader class of multiloop flight control systems. Direct tradeoffs between many real design goals are rendered systematic by proper formulation of the design objectives and constraints. Satisfactory designs are usually obtained in few iterations. Performance characteristics of the optimized TECS design have been improved, particularly in the areas of closed-loop damping and control activity in the presence of turbulence.

  14. 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.

  15. Tank waste remediation system optimized processing strategy with an altered treatment scheme

    Energy Technology Data Exchange (ETDEWEB)

    Slaathaug, E.J.

    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 with an altered treatment scheme 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.

  16. Optimization of process parameters in high-energy film radiography

    Science.gov (United States)

    Miller, Arthur C.; Cochran, Joseph L.

    2001-04-01

    Film radiography provides unequaled resolution for component and assembly inspection, certification, and quality evaluations. However, improvements can be made in our ability to identify defects and to obtain much more detail about fine features. A systematic approach to make incremental changes in current high-energy radiography may well provide the additional improvement needed. Consequently, the work described is concerned with optimizing important parameters affecting image quality. Modeling and simulation with advanced parallel computer systems provide a more detailed understanding of latent image formation at high x-ray energies and help explain image degradation mechanisms in enhancement screens.

  17. Parameter optimization in AQM controller design to support TCP traffic

    Science.gov (United States)

    Yang, Wei; Yang, Oliver W.

    2004-09-01

    TCP congestion control mechanism has been widely investigated and deployed on Internet in preventing congestion collapse. We would like to employ modern control theory to specify quantitatively the control performance of the TCP communication system. In this paper, we make use of a commonly used performance index called the Integral of the Square of the Error (ISE), which is a quantitative measure to gauge the performance of a control system. By applying the ISE performance index into the Proportional-plus-Integral controller based on Pole Placement (PI_PP controller) for active queue management (AQM) in IP routers, we can further tune the parameters for the controller to achieve an optimum control minimizing control errors. We have analyzed the dynamic model of the TCP congestion control under this ISE, and used OPNET simulation tool to verify the derived optimized parameters of the controllers.

  18. Parameter optimization in molecular dynamics simulations using a genetic algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Angibaud, L. [Department ' Science and Analysis of Materials' (SAM), Centre de Recherche Public - Gabriel Lippmann, 41 rue du Brill, L-4422 Belvaux (Luxembourg); Briquet, L., E-mail: briquet@lippmann.lu [Department ' Science and Analysis of Materials' (SAM), Centre de Recherche Public - Gabriel Lippmann, 41 rue du Brill, L-4422 Belvaux (Luxembourg); Philipp, P.; Wirtz, T. [Department ' Science and Analysis of Materials' (SAM), Centre de Recherche Public - Gabriel Lippmann, 41 rue du Brill, L-4422 Belvaux (Luxembourg); Kieffer, J. [Department of Materials Science and Engineering, University of Michigan, Ann Arbor, MI 48109-2136 (United States)

    2011-07-15

    In this work, we introduce a genetic algorithm for the parameterization of the reactive force field developed by Kieffer . This potential includes directional covalent bonds and dispersion terms. Important features of this force field for simulating systems that undergo significant structural reorganization are (i) the ability to account for the redistribution of electron density upon ionization, formation, or breaking of bonds, through a charge transfer term, and (ii) the fact that the angular constraints dynamically adjust when a change in the coordination number of an atom occurs. In this paper, we present the implementation of the genetic algorithm into the existing code as well as the algorithm efficiency and preliminary results on Si-Si force field optimization. The parameters obtained by this method will be compared to existing parameter sets obtained by a trial-and-error process.

  19. Dynamic composting optimization through C/N ratio variation as a startup parameter

    OpenAIRE

    AZIM, Khalid; OUYIHYA, Khalid; AMELLOUK, Aomar; PERISSOL, Claude; THAMI ALAMI, Imane; Soudi, Brahim

    2014-01-01

    Different organic wastes (waste of tomato leaves and stems, sheep manure, olive mill waste and melon waste) were mixed with different proportions for different C/N ratio to make better use of tomato waste as it constitutes the majority of horticultural waste in the Souss-Massa region (south-western of Morocco). The objective of this study was to evaluate the effect of C/N ratio on the physicochemical parameters during aerobic composting process (temperature, relative humidity, pH, EC...), and...

  20. Optimization of the extraction of polysaccharides from tobacco waste and their biological activities.

    Science.gov (United States)

    Jing, Yanqiu; Gao, Yuzhen; Wang, Weifeng; Cheng, Yuyuan; Lu, Ping; Ma, Cong; Zhang, Yuehua

    2016-10-01

    A response surface methodology was used to optimize the parameters for extracting the polysaccharides from tobacco waste (TWPs) using hot water. The extraction process, carried out under the following optimized parameters: an extraction temperature of 90°C, a ratio of water to raw material of 54, and an extraction time of 115min, allowed an experimental yield of 28.32±1.78%. The chemical composition analysis showed that TWPs were composed of mannose, rhamnose, glucuronic acid, galacturonic acid, glucose, galactose and arabinose with the following molecular ratio: 1.00:2.69:1.29:2.29:5.23:6.90:3.92. The molecular weights of its four major fractions were 0.558, 1.015, 16.286, and 151.194kDa. Bioactivity experiments showed that TWPs not only decreased the reactive oxygen species level in salt-stressed tomato seedlings, but also possessed significant antioxidant activities in vitro. Antioxidant activity in vivo further showed that TWPs could significantly increase the activities of antioxidant enzymes including superoxide dismutase (SOD), glutathione peroxidase (GSH-Px) and catalase (CAT), and decrease the level of malondialodehyde (MDA). In addition, according to the acute toxicity test, TWPs did not cause behavioral changes or any death of mice. This study provides an effective method to utilize tobacco waste resources. Copyright © 2016 Elsevier B.V. All rights reserved.

  1. Biohydrogen Production from Simple Carbohydrates with Optimization of Operating Parameters.

    Science.gov (United States)

    Muri, Petra; Osojnik-Črnivec, Ilja Gasan; Djinovič, Petar; Pintar, Albin

    2016-01-01

    Hydrogen could be alternative energy carrier in the future as well as source for chemical and fuel synthesis due to its high energy content, environmentally friendly technology and zero carbon emissions. In particular, conversion of organic substrates to hydrogen via dark fermentation process is of great interest. The aim of this study was fermentative hydrogen production using anaerobic mixed culture using different carbon sources (mono and disaccharides) and further optimization by varying a number of operating parameters (pH value, temperature, organic loading, mixing intensity). Among all tested mono- and disaccharides, glucose was shown as the preferred carbon source exhibiting hydrogen yield of 1.44 mol H(2)/mol glucose. Further evaluation of selected operating parameters showed that the highest hydrogen yield (1.55 mol H(2)/mol glucose) was obtained at the initial pH value of 6.4, T=37 °C and organic loading of 5 g/L. The obtained results demonstrate that lower hydrogen yield at all other conditions was associated with redirection of metabolic pathways from butyric and acetic (accompanied by H(2) production) to lactic (simultaneous H(2) production is not mandatory) acid production. These results therefore represent an important foundation for the optimization and industrial-scale production of hydrogen from organic substrates.

  2. Process parameter optimization for fly ash brick by Taguchi method

    Directory of Open Access Journals (Sweden)

    Prabir Kumar Chaulia

    2008-06-01

    Full Text Available This paper presents the results of an experimental investigation carried out to optimize the mix proportions of the fly ash brick by Taguchi method of parameter design. The experiments have been designed using an L9 orthogonal array with four factors and three levels each. Small quantity of cement has been mixed as binding materials. Both cement and the fly ash used are indicated as binding material and water binder ratio has been considered as one of the control factors. So the effects of water/binder ratio, fly ash, coarse sand, and stone dust on the performance characteristic are analyzed using signal-to-noise ratios and mean response data. According to the results, water/binder ratio and stone dust play the significant role on the compressive strength of the brick. Furthermore, the estimated optimum values of the process parameters are corresponding to water/binder ratio of 0.4, fly ash of 39%, coarse sand of 24%, and stone dust of 30%. The mean value of optimal strength is predicted as 166.22 kg.cm-2 with a tolerance of ± 10.97 kg.cm-2. Confirmatory experimental result obtained for the optimum conditions is 160.17 kg.cm-2.

  3. Changes of parameters during composting of bio-waste collected over four seasons.

    Science.gov (United States)

    Hanc, Ales; Ochecova, Pavla; Vasak, Filip

    2017-07-01

    This study investigated the evolution of several main parameters during the composting of separately collected household bio-waste originating from urban settlements (U-bio-waste) and family houses (F-bio-waste) from four climate seasons. When comparing both types of composts, U-bio-waste compost contained a higher amount of nutrients, however F-bio-waste compost was characterized by greater yield, greater availability of phosphorus and magnesium, and faster stability. In terms of seasons, compost from bio-waste collected in spring contained the highest amount of nutrients, reflecting the high content of nutrients in plant feedstock. Dissolved organic carbon and pH in U- and F-bio-waste compost, respectively, frequently showed close relationships with other parameters. The seasonal variations of most of the parameters in the composts were found to be lower compared to the variations observed in the feedstocks. The greatest seasonal variation was found in nitrate nitrogen, which is the reason for the more frequent analysis of this parameter.

  4. 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.

  5. Sub Optimal E-Waste Management and the Lost Opportunity

    OpenAIRE

    Tyagi, Rakesh; Kaushal, Priyanka

    2018-01-01

    Electronic waste or e-waste is the wastegenerated from discarded and end of life electronic items. In recent times withchange in lifestyle and improved purchasing capacity of people has acceleratedthe demand of new and improved electronic items, quick technology obsolescence,as a consequence the generation of e-waste has seen a huge rise. In year 2016,globally 93.5 tons of E-waste was generated, India, one of the leadingproducers of e-waste, produced 1.65 Million tones of E-waste. Apart fromd...

  6. Optimization of fuels from waste composition with application of genetic algorithm.

    Science.gov (United States)

    Małgorzata, Wzorek

    2014-05-01

    The objective of this article is to elaborate a method to optimize the composition of the fuels from sewage sludge (PBS fuel - fuel based on sewage sludge and coal slime, PBM fuel - fuel based on sewage sludge and meat and bone meal, PBT fuel - fuel based on sewage sludge and sawdust). As a tool for an optimization procedure, the use of a genetic algorithm is proposed. The optimization task involves the maximization of mass fraction of sewage sludge in a fuel developed on the basis of quality-based criteria for the use as an alternative fuel used by the cement industry. The selection criteria of fuels composition concerned such parameters as: calorific value, content of chlorine, sulphur and heavy metals. Mathematical descriptions of fuel compositions and general forms of the genetic algorithm, as well as the obtained optimization results are presented. The results of this study indicate that the proposed genetic algorithm offers an optimization tool, which could be useful in the determination of the composition of fuels that are produced from waste.

  7. Optimization of the Enzymatic Saccharification Process of Milled Orange Wastes

    Directory of Open Access Journals (Sweden)

    Daniel Velasco

    2017-08-01

    Full Text Available Orange juice production generates a very high quantity of residues (Orange Peel Waste or OPW-50–60% of total weight that can be used for cattle feed as well as feedstock for the extraction or production of essential oils, pectin and nutraceutics and several monosaccharides by saccharification, inversion and enzyme-aided extraction. As in all solid wastes, simple pretreatments can enhance these processes. In this study, hydrothermal pretreatments and knife milling have been analyzed with enzyme saccharification at different dry solid contents as the selection test: simple knife milling seemed more appropriate, as no added pretreatment resulted in better final glucose yields. A Taguchi optimization study on dry solid to liquid content and the composition of the enzymatic cocktail was undertaken. The amounts of enzymatic preparations were set to reduce their impact on the economy of the process; however, as expected, the highest amounts resulted in the best yields to glucose and other monomers. Interestingly, the highest content in solid to liquid (11.5% on dry basis rendered the best yields. Additionally, in search for process economy with high yields, operational conditions were set: medium amounts of hemicellulases, polygalacturonases and β-glucosidases. Finally, a fractal kinetic modelling of results for all products from the saccharification process indicated very high activities resulting in the liberation of glucose, fructose and xylose, and very low activities to arabinose and galactose. High activity on pectin was also observed, but, for all monomers liberated initially at a fast rate, high hindrances appeared during the saccharification process.

  8. Effect of Domestic Waste Leachates on Quality Parameters of Groundwater

    Directory of Open Access Journals (Sweden)

    John Jiya MUSA

    2014-02-01

    Full Text Available Water is an elixir of life. Percolating groundwater provides a medium through which wastes particularly organics can undergo degradation into simpler substances through biochemical reactions involving dissolution, hydrolysis, oxidation and reduction processes. Ground water samples in and around dumpsite and landfills located in Kubuwa were studied to assess the effect of wastewater leachates on groundwater resources in the particular area. Groundwater samples were collected from 5 different bore-wells in and around relative distances from dumpsites. EC values ranged between 30 and 138 µS/cm, TDS ranged between 95 mg/L and 120 mg/L, SS ranged between 10 and 23 mg/L while that of the evening ranged between 11 and 15 mg/L, nitrate values ranged between 0.18 to 0.80 mg/L for the early morning samples while the late evening samples which ranged between 0.25 and 0.43 mg/L, while concentration of Sulphate in the morning water sample ranged between 168 and 213 mg/L while that of the evening ranged between 20 and 45 mg/L. The government of the Federal Republic of Nigeria should create landfills and dumpsites far away from residential homes and better still recycling plants should be put in place to recycle the various forms of waste products from homes.

  9. 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...

  10. 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.

  11. Parameter optimization in differential geometry based solvation models.

    Science.gov (United States)

    Wang, Bao; Wei, G W

    2015-10-07

    Differential geometry (DG) based solvation models are a new class of variational implicit solvent approaches that are able to avoid unphysical solvent-solute boundary definitions and associated geometric singularities, and dynamically couple polar and non-polar interactions in a self-consistent framework. Our earlier study indicates that DG based non-polar solvation model outperforms other methods in non-polar solvation energy predictions. However, the DG based full solvation model has not shown its superiority in solvation analysis, due to its difficulty in parametrization, which must ensure the stability of the solution of strongly coupled nonlinear Laplace-Beltrami and Poisson-Boltzmann equations. In this work, we introduce new parameter learning algorithms based on perturbation and convex optimization theories to stabilize the numerical solution and thus achieve an optimal parametrization of the DG based solvation models. An interesting feature of the present DG based solvation model is that it provides accurate solvation free energy predictions for both polar and non-polar molecules in a unified formulation. Extensive numerical experiment demonstrates that the present DG based solvation model delivers some of the most accurate predictions of the solvation free energies for a large number of molecules.

  12. Robust integrated autopilot/autothrottle design using constrained parameter optimization

    Science.gov (United States)

    Ly, Uy-Loi; Voth, Christopher; Sanjay, Swamy

    1990-01-01

    A multivariable control design method based on constrained parameter optimization was applied to the design of a multiloop aircraft flight control system. Specifically, the design method is applied to the following: (1) direct synthesis of a multivariable 'inner-loop' feedback control system based on total energy control principles; (2) synthesis of speed/altitude-hold designs as 'outer-loop' feedback/feedforward control systems around the above inner loop; and (3) direct synthesis of a combined 'inner-loop' and 'outer-loop' multivariable control system. The design procedure offers a direct and structured approach for the determination of a set of controller gains that meet design specifications in closed-loop stability, command tracking performance, disturbance rejection, and limits on control activities. The presented approach may be applied to a broader class of multiloop flight control systems. Direct tradeoffs between many real design goals are rendered systematic by this method following careful problem formulation of the design objectives and constraints. Performance characteristics of the optimization design were improved over the current autopilot design on the B737-100 Transport Research Vehicle (TSRV) at the landing approach and cruise flight conditions; particularly in the areas of closed-loop damping, command responses, and control activity in the presence of turbulence.

  13. 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.

  14. Optimal z-axis scanning parameters for gynecologic cytology specimens.

    Science.gov (United States)

    Donnelly, Amber D; Mukherjee, Maheswari S; Lyden, Elizabeth R; Bridge, Julia A; Lele, Subodh M; Wright, Najia; McGaughey, Mary F; Culberson, Alicia M; Horn, Adam J; Wedel, Whitney R; Radio, Stanley J

    2013-01-01

    The use of virtual microscopy (VM) in clinical cytology has been limited due to the inability to focus through three dimensional (3D) cell clusters with a single focal plane (2D images). Limited information exists regarding the optimal scanning parameters for 3D scanning. The purpose of this study was to determine the optimal number of the focal plane levels and the optimal scanning interval to digitize gynecological (GYN) specimens prepared on SurePath™ glass slides while maintaining a manageable file size. The iScanCoreo Au scanner (Ventana, AZ, USA) was used to digitize 192 SurePath™ glass slides at three focal plane levels at 1 μ interval. The digitized virtual images (VI) were annotated using BioImagene's Image Viewer. Five participants interpreted the VI and recorded the focal plane level at which they felt confident and later interpreted the corresponding glass slide specimens using light microscopy (LM). The participants completed a survey about their experiences. Inter-rater agreement and concordance between the VI and the glass slide specimens were evaluated. This study determined an overall high intra-rater diagnostic concordance between glass and VI (89-97%), however, the inter-rater agreement for all cases was higher for LM (94%) compared with VM (82%). Survey results indicate participants found low grade dysplasia and koilocytes easy to diagnose using three focal plane levels, the image enhancement tool was useful and focusing through the cells helped with interpretation; however, the participants found VI with hyperchromatic crowded groups challenging to interpret. Participants reported they prefer using LM over VM. This study supports using three focal plane levels and 1 μ interval to expand the use of VM in GYN cytology. Future improvements in technology and appropriate training should make this format a more preferable and practical option in clinical cytology.

  15. Optimal z-axis scanning parameters for gynecologic cytology specimens

    Directory of Open Access Journals (Sweden)

    Amber D Donnelly

    2013-01-01

    Full Text Available Background: The use of virtual microscopy (VM in clinical cytology has been limited due to the inability to focus through three dimensional (3D cell clusters with a single focal plane (2D images. Limited information exists regarding the optimal scanning parameters for 3D scanning. Aims: The purpose of this study was to determine the optimal number of the focal plane levels and the optimal scanning interval to digitize gynecological (GYN specimens prepared on SurePath™ glass slides while maintaining a manageable file size. Subjects and Methods: The iScanCoreo Au scanner (Ventana, AZ, USA was used to digitize 192 SurePath™ glass slides at three focal plane levels at 1 μ interval. The digitized virtual images (VI were annotated using BioImagene′s Image Viewer. Five participants interpreted the VI and recorded the focal plane level at which they felt confident and later interpreted the corresponding glass slide specimens using light microscopy (LM. The participants completed a survey about their experiences. Inter-rater agreement and concordance between the VI and the glass slide specimens were evaluated. Results: This study determined an overall high intra-rater diagnostic concordance between glass and VI (89-97%, however, the inter-rater agreement for all cases was higher for LM (94% compared with VM (82%. Survey results indicate participants found low grade dysplasia and koilocytes easy to diagnose using three focal plane levels, the image enhancement tool was useful and focusing through the cells helped with interpretation; however, the participants found VI with hyperchromatic crowded groups challenging to interpret. Participants reported they prefer using LM over VM. This study supports using three focal plane levels and 1 μ interval to expand the use of VM in GYN cytology. Conclusion: Future improvements in technology and appropriate training should make this format a more preferable and practical option in clinical cytology.

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

    Science.gov (United States)

    Gao, Hao

    2016-04-07

    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.

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

    Science.gov (United States)

    Gao, Hao

    2016-04-01

    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.

  18. Optimal waste load allocation using graph model for conflict resolution.

    Science.gov (United States)

    Saberi, Leila; Niksokhan, Mohammad Hossein

    2017-03-01

    In this paper, a new methodology is proposed for waste load allocation in river systems using the decision support system (DSS) for the graph model for conflict resolution II (GMCRII), multi-criteria decision making (MCDM) analysis and the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm. Minimization of total treatment and penalty costs and minimization of biological oxygen demand violation of standards at the check point are considered as the main objectives of this study. At first, the water quality along the river was simulated using the Streeter-Phelps (S-P) equation coupled with the MOPSO model. Thereby a trade-off curve between the objectives is obtained and a set of non-dominated solutions is selected. In the next step, the best alternative is chosen using MCDM techniques and the GMCRII DSS package and non-cooperative stability definitions. The applicability and efficiency of the methodology are examined in a real-world case study of the Sefidrud River in the northern part of Iran.

  19. 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

    2017-11-01

    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.

  20. 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.

  1. Optimal Joint Target Detection and Parameter Estimation By MIMO Radar

    CERN Document Server

    Tajer, Ali; Wang, Xiaodong; Moustakides, George V

    2009-01-01

    We consider multiple-input multiple-output (MIMO) radar systems with widely-spaced antennas. Such antenna configuration facilitates capturing the inherent diversity gain due to independent signal dispersion by the target scatterers. We consider a new MIMO radar framework for detecting a target that lies in an unknown location. This is in contrast with conventional MIMO radars which break the space into small cells and aim at detecting the presence of a target in a specified cell. We treat this problem through offering a novel composite hypothesis testing framework for target detection when (i) one or more parameters of the target are unknown and we are interested in estimating them, and (ii) only a finite number of observations are available. The test offered optimizes a metric which accounts for both detection and estimation accuracies. In this paper as the parameter of interest we focus on the vector of time-delays that the waveforms undergo from being emitted by the transmit antennas until being observed b...

  2. 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.

  3. Optimized drying parameters of water hyacinths (Eichhornia crassipes. L

    Directory of Open Access Journals (Sweden)

    Edgardo V. Casas

    2012-12-01

    Full Text Available The study investigated the optimum drying conditions of water hyacinth to contribute in the improvement of present drying processes. The effects of independent parameters (drying temperature, airflow rate, and number of passes on the responses were determined using the Response Surface Methodology. The response parameters were composed of (1 final moisture content, (2 moisture ratio, (3 drying rate,(4 tensile strength, and (5 browning index. Box and Behnken experimental design represented the design of experiments that resulted in 15 drying runs. Statistical analysis evaluated the treatment effects. Drying temperature significantly affected the drying rate, moisture ratio, and browning index. Airflow rate had a significant effect only on the drying rate, while the number of passes significantly affected both the drying rate and browning index. The optimized conditions for drying the water hyacinth were at drying temperature of 90C, airflow rate of 0.044m3/s, and number of passes equivalent to five. The best modelthat characterizes the drying of water hyacinth is a rational function expressed as:

  4. Optimized interaction parameters for metal-doped endohedral fullerene

    Science.gov (United States)

    Dhiman, Shobhna; Kumar, Ranjan; Dharamvir, Keya

    2017-06-01

    Interaction between various atoms doped inside C60 can be modeled using interaction potentials and, thus, cohesive energy and other physical constants may be calculated. In case of metal-doped fullerene total energy may be written in terms of three different types of interactions, namely carbon-carbon interaction, metal-metal interaction and carbon-metal interaction. Brenner potential, Gupta potential, and Lennard-Jones potentials have been used to model these interactions respectively. Generally, parameters used in these model potentials are not readily available and need to be fine-tuned for different dopants. In this paper, we have deduced/optimized these interaction parameters for Cu, Ag, Al and Ga doped C60 comparing with our Density Functional Theory (DFT) results and hence predicting the stability of various metal-doped fullerenes. Total energy calculations reveal that a maximum of nine copper atoms can be doped inside the fullerene cage and form stable complex without distorting the cage significantly. As we add more number of Cu atoms in the fullerene molecule, cage structure breaks down. In the same way, we have done calculations for Ag, Al and Ga atoms doped inside the fullerene molecule and found that the maximum of eight, nine, nine atoms can form stable complexes.

  5. Investigation and Parameter Optimization of a Hydraulic Ram Pump Using Taguchi Method

    Science.gov (United States)

    Sarma, Dhrupad; Das, Monotosh; Brahma, Bipul; Pandwar, Deepak; Rongphar, Sermirlong; Rahman, Mafidur

    2016-10-01

    The main objective of this research work is to investigate the effect of Waste Valve height and Pressure Chamber height on the output flow rate of a Hydraulic ram pump. Also the second objective of this work is to optimize them for a hydraulic ram pump delivering water up to a height of 3.81 m (12.5 feet ) from the ground with a drive head (inlet head) of 1.86 m (6.11 feet). Two one-factor-at-a-time experiments have been conducted to decide the levels of the selected input parameters. After deciding the input parameters, an experiment has been designed using Taguchi's L9 Orthogonal Array with three repetitions. Analysis of Variance (ANOVA) is carried out to verify the significance of effect of the factors on the output flow rate of the pump. Results show that the height of the Waste Valve and height of the Pressure Chamber have significant effect on the outlet flow of the pump. For a pump of drive pipe diameter (inlet pipe) 31.75 mm (1.25 in.) and delivery pipe diameter of 12.7 mm (0.5 in.) the optimum setting was found out to be at a height of 114.3 mm (4.5 in.) of the Waste Valve and 406.4 mm (16 in.) of the Pressure vessel providing a delivery flow rate of 93.14 l per hour. For the same pump estimated range of output flow rate is, 90.65-94.97 l/h.

  6. 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

  7. Parameter Estimation for Simultaneous Saccharification and Fermentation of Food Waste Into Ethanol Using Matlab Simulink

    Science.gov (United States)

    Davis, Rebecca Anne

    The increase in waste disposal and energy costs has provided an incentive to convert carbohydrate-rich food waste streams into fuel. For example, dining halls and restaurants discard foods that require tipping fees for removal. An effective use of food waste may be the enzymatic hydrolysis of the waste to simple sugars and fermentation of the sugars to ethanol. As these wastes have complex compositions which may change day-to-day, experiments were carried out to test fermentability of two different types of food waste at 27° C using Saccharomyces cerevisiae yeast (ATCC4124) and Genencor's STARGEN™ enzyme in batch simultaneous saccharification and fermentation (SSF) experiments. A mathematical model of SSF based on experimentally matched rate equations for enzyme hydrolysis and yeast fermentation was developed in Matlab Simulink®. Using Simulink® parameter estimation 1.1.3, parameters for hydrolysis and fermentation were estimated through modified Michaelis-Menten and Monod-type equations with the aim of predicting changes in the levels of ethanol and glycerol from different initial concentrations of glucose, fructose, maltose, and starch. The model predictions and experimental observations agree reasonably well for the two food waste streams and a third validation dataset. The approach of using Simulink® as a dynamic visual model for SSF represents a simple method which can be applied to a variety of biological pathways and may be very useful for systems approaches in metabolic engineering in the future.

  8. Parameter estimation for simultaneous saccharification and fermentation of food waste into ethanol using Matlab Simulink.

    Science.gov (United States)

    Davis, Rebecca Anne

    2008-03-01

    The increase in waste disposal and energy costs has provided an incentive to convert carbohydrate-rich food waste streams into fuel. For example, dining halls and restaurants discard foods that require tipping fees for removal. An effective use of food waste may be the enzymatic hydrolysis of the waste to simple sugars and fermentation of the sugars to ethanol. As these wastes have complex compositions which may change day-to-day, experiments were carried out to test fermentability of two different types of food waste at 27 degrees C using Saccharomyces cerevisiae yeast (ATCC4124) and Genencor's STARGEN enzyme in batch simultaneous saccharification and fermentation (SSF) experiments. A mathematical model of SSF based on experimentally matched rate equations for enzyme hydrolysis and yeast fermentation was developed in Matlab Simulink. Using Simulink parameter estimation 1.1.3, parameters for hydrolysis and fermentation were estimated through modified Michaelis-Menten and Monod-type equations with the aim of predicting changes in the levels of ethanol and glycerol from different initial concentrations of glucose, fructose, maltose, and starch. The model predictions and experimental observations agree reasonably well for the two food waste streams and a third validation dataset. The approach of using Simulink as a dynamic visual model for SSF represents a simple method which can be applied to a variety of biological pathways and may be very useful for systems approaches in metabolic engineering in the future.

  9. Effect of Mix Parameters on the Strength Performance of Waste Plastics Incorporated Concrete Mixes

    Directory of Open Access Journals (Sweden)

    Santhosh M. Malkapur

    2014-01-01

    Full Text Available Disposal of solid wastes has been a major problem all over the world. Out of all the different types of solid wastes, the major challenge of disposal is posed by the ever increasing volumes of plastic wastes. While several methods are in practice, producing newer useful materials by recycling of such plastic wastes is, by far, the best method of their disposal. One such possible method is to use the waste plastics as an ingredient in the production of the concrete mixes in the construction industry. The present study aims to investigate the relative contributions of the various mix parameters to the mechanical properties of concrete mixes produced with waste plastics as partial replacement (10–30% by volume to coarse aggregates. Initially, strength test results of a set of trial mixes, selected based on Taguchi’s design of experiments (DOE method are obtained. A detailed analysis of the experimental results is carried out to study the effect of using waste plastics as a partial replacement to coarse aggregates on the strength parameters of these concrete mixes. It is found that all these trial mixes have performed satisfactorily in terms of workability in the fresh state and strength properties in their hardened state.

  10. Using GIS-Based Tools for the Optimization of Solid Waste Collection and Transport: Case Study of Sfax City, Tunisia

    Directory of Open Access Journals (Sweden)

    Amjad Kallel

    2016-01-01

    Full Text Available Expenditure for waste collection and transport in Tunisia constitutes 75–100% of the total solid waste management budget. In this study, optimized scenarios were developed using ArcGIS Network Analyst tool in order to improve the efficiency of waste collection and transportation in the district Cité El Habib of Sfax city, Tunisia. Geographic Information System (GIS was created based on data collection and GPS tracking (collection route/bins position. The actual state (Scenario S0 was evaluated, and by modifying its particular parameters, other scenarios were generated and analyzed to identify optimal routes: S1, route optimized with the same working resources (change of stops sequencing only; S2, route optimized with change of vehicles; and S3, route optimized with change of collection method (vehicles and reallocation of bins. The results showed that the three scenarios guarantee savings compared to S0 in terms of collection time (14%, 57%, and 57% for S1, S2, and S3, resp. and distance (13.5%, 13.5%, and 40.5% for S1, S2, and S3, resp.. Thus, a direct impact on fuel consumption can be expected with savings of 16%, 20%, and 48% for S1, S2, and S3, respectively, without mentioning the additional benefits related to CO2 emissions, hours of work, vehicles wear/maintenance, and so forth.

  11. Optimization of pozzolanic reaction of ground waste glass

    OpenAIRE

    Gomes, João Paulo de Castro; Santos, P.; Oliveira, Luiz António Pereira de

    2010-01-01

    This paper examines the possibility of using finely ground waste glass of the three most common coloured glass bottles used in Portugal as partial cement replacement in mortar and concrete. The pozzolanic activity of ground glass was optimised as function of different particle size. The reduction of waste glass particle size was accomplished in the laboratory by crushing and grinding the waste glass using a jar mill. The particle fineness, to obtain a required reactivity, was s...

  12. Research on the drying kinetics of household food waste for the development and optimization of domestic waste drying technique.

    Science.gov (United States)

    Sotiropoulos, A; Malamis, D; Michailidis, P; Krokida, M; Loizidou, M

    2016-01-01

    Domestic food waste drying foresees the significant reduction of household food waste mass through the hygienic removal of its moisture content at source. In this manuscript, a new approach for the development and optimization of an innovative household waste dryer for the effective dehydration of food waste at source is presented. Food waste samples were dehydrated with the use of the heated air-drying technique under different air-drying conditions, namely air temperature and air velocity, in order to investigate their drying kinetics. Different thin-layer drying models have been applied, in which the drying constant is a function of the process variables. The Midilli model demonstrated the best performance in fitting the experimental data in all tested samples, whereas it was found that food waste drying is greatly affected by temperature and to a smaller scale by air velocity. Due to the increased moisture content of food waste, an appropriate configuration of the drying process variables can lead to a total reduction of its mass by 87% w/w, thus achieving a sustainable residence time and energy consumption level. Thus, the development of a domestic waste dryer can be proved to be economically and environmentally viable in the future.

  13. 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.

  14. Optimal parameters of monolithic high-index contrast grating VCSELs

    Science.gov (United States)

    Marciniak, Magdalena; Gebski, Marcin; Dems, Maciej; Czyszanowski, Tomasz

    2016-04-01

    Monolithic High refractive index Contrast Grating (MHCG) allows several-fold size reduction of epitaxial structure of VCSEL and facilitates VCSEL fabrication in all photonic material systems. MHCGs can be fabricated of material which refractive index is higher than 1.75 without the need of the combination of low and high refractive index materials. MHCGs have a great application potential in optoelectronic devices, especially in phosphide- and nitride-based VCSELs, which suffer from the lack of efficient monolithically integrated DBR mirrors. MHCGs can simplify the construction of VCSELs, reducing their epitaxial design to monolithic wafer with carrier confinement and active region inside and etched stripes on both surfaces in post processing. In this paper we present results of numerical analysis of MHCGs as a high reflective mirrors for broad range of refractive indices that corresponds to plethora of materials typically used in optoelectronics. Our calculations base on a three-dimensional, fully vectorial optical model. We investigate the reflectance of the MHCG mirrors of different design as the function of the refractive index and we show the optimal geometrical parameters of MHCG enabling nearly 100% reflectance and broad reflection stop-band. We show that MHCG can be designed based on most of semiconductors materials and for any incident light wavelength from optical spectrum.

  15. Biogas production from livestock waste anaerobic digesters: evaluation and optimization

    Science.gov (United States)

    Livestock wastes can serve as the feedstock for biogas production (mainly methane) that could be used as alternative energy source. The green energy derived from animal wastes is considered to be carbon neutral and offsetting those generated from fossil fuels. However, feedstocks from livestock re...

  16. Optimization of use of waste in the future energy system

    DEFF Research Database (Denmark)

    Münster, Marie; Meibom, Peter

    2011-01-01

    of mixed waste, anaerobic digestion of organic waste, and gasification of part of the potential RDF (refuse derived fuel) for CHP (combined heat and power) production, while the remaining part is co-combusted with coal. Co-combustion mainly takes place in new coal-fired power plants, allowing investments...

  17. Optimization of solid content, carbon/nitrogen ratio and food/inoculum ratio for biogas production from food waste.

    Science.gov (United States)

    Dadaser-Celik, Filiz; Azgin, Sukru Taner; Yildiz, Yalcin Sevki

    2016-12-01

    Biogas production from food waste has been used as an efficient waste treatment option for years. The methane yields from decomposition of waste are, however, highly variable under different operating conditions. In this study, a statistical experimental design method (Taguchi OA9) was implemented to investigate the effects of simultaneous variations of three parameters on methane production. The parameters investigated were solid content (SC), carbon/nitrogen ratio (C/N) and food/inoculum ratio (F/I). Two sets of experiments were conducted with nine anaerobic reactors operating under different conditions. Optimum conditions were determined using statistical analysis, such as analysis of variance (ANOVA). A confirmation experiment was carried out at optimum conditions to investigate the validity of the results. Statistical analysis showed that SC was the most important parameter for methane production with a 45% contribution, followed by F/I ratio with a 35% contribution. The optimum methane yield of 151 l kg-1 volatile solids (VS) was achieved after 24 days of digestion when SC was 4%, C/N was 28 and F/I were 0.3. The confirmation experiment provided a methane yield of 167 l kg-1 VS after 24 days. The analysis showed biogas production from food waste may be increased by optimization of operating conditions. © The Author(s) 2016.

  18. Mini-review of the geotechnical parameters of municipal solid waste: Mechanical and biological pre-treated versus raw untreated waste.

    Science.gov (United States)

    Petrovic, Igor

    2016-09-01

    The most viable option for biostabilisation of old sanitary landfills, filled with raw municipal solid waste, is the so-called bioreactor landfill. Even today, bioreactor landfills are viable options in many economically developing countries. However, in order to reduce the biodegradable component of landfilled waste, mechanical and biological treatment has become a widely accepted waste treatment technology, especially in more prosperous countries. Given that mechanical and biological treatment alters the geotechnical properties of raw waste material, the design of sanitary landfills which accepts mechanically and biologically treated waste, should be carried out with a distinct set of geotechnical parameters. However, under the assumption that 'waste is waste', some design engineers might be tempted to use geotechnical parameters of untreated raw municipal solid waste and mechanical and biological pre-treated municipal solid waste interchangeably. Therefore, to provide guidelines for use and to provide an aggregated source of this information, this mini-review provides comparisons of geotechnical parameters of mechanical and biological pre-treated waste and raw untreated waste at various decomposition stages. This comparison reveals reasonable correlations between the hydraulic conductivity values of untreated and mechanical and biological pre-treated municipal solid waste. It is recognised that particle size might have a significant influence on the hydraulic conductivity of both municipal solid waste types. However, the compression ratios and shear strengths of untreated and pre-treated municipal solid waste do not show such strong correlations. Furthermore, another emerging topic that requires appropriate attention is the recovery of resources that are embedded in old landfills. Therefore, the presented results provide a valuable tool for engineers designing landfills for mechanical and biological pre-treated waste or bioreactor landfills for untreated raw

  19. Bakery waste in sheep diets: intake, digestibility, nitrogen balance and ruminal parameters

    Directory of Open Access Journals (Sweden)

    Almira Biazon França

    2012-01-01

    Full Text Available The objective of the study was to evaluate the effects of bakery waste inclusion (0; 25; 50; 75 and 100%, DM basis in proportion to corn meal in the energetic mixture of the concentrate on intake, digestibility, nitrogen balance and ruminal parameters in sheep. Five male lambs with body weight of 30 kg were used in a 5 × 5 Latin square design. Experimental diets were composed of concentrate and Tifton 85 (Cynodon spp. hay in a 60:40 forage:concentrate ratio. The concentrate rations were composed of corn meal, soybean meal and bakery waste. The bakery waste:corn meal ratio corresponded to the inclusion of, approximately, 0, 7, 14, 22 and 30% (DM basis of bakery waste in the diet. There was no effect of bakery waste inclusion on the intake and digestibility of nutrients, nor on nitrogen balance, pH values or concentrations of volatile fatty acids. However, the ammonia nitrogen concentration showed negative linear response in relation to the level of inclusion, in which each increase of 1% bakery waste promoted reduction of 0.11 mg/dL in the concentration of ammonia nitrogen. This fact may be related to the increase in ruminal availability of energy, which allows greater use of ammonia for microbial growth. Bakery waste can replace corn meal in concentrate rations for sheep.

  20. 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

  1. Egg shell waste as heterogeneous nanocatalyst for biodiesel production: Optimized by response surface methodology.

    Science.gov (United States)

    Pandit, Priti R; Fulekar, M H

    2017-08-01

    Worldwide consumption of hen eggs results in availability of large amount of discarded egg waste particularly egg shells. In the present study, the waste shells were utilized for the synthesis of highly active heterogeneous calcium oxide (CaO) nanocatalyst to transesterify dry biomass into methyl esters (biodiesel). The CaO nanocatalyst was synthesied by calcination-hydration-dehydration technique and fully characterized by infrared spectroscopy, X-ray powder diffraction (XRD), scanning electron microscope (SEM), transmission electron microscope (TEM), brunauer-emmett-teller (BET) elemental and thermogravimetric analysis. TEM image showed that the nano catalyst had spherical shape with average particle size of 75 nm. BET analysis indicated that the catalyst specific surface area was 16.4 m 2  g -1 with average pore diameter of 5.07 nm. The effect of nano CaO catalyst was investigated by direct transesterification of dry biomass into biodiesel along with other reaction parameters such as catalyst ratio, reaction time and stirring rate. The impact of the transesterification reaction parameters and microalgal biodiesel yield were analyzed by response surface methodology based on a full factorial, central composite design. The significance of the predicted mode was verified and 86.41% microalgal biodiesel yield was reported at optimal parameter conditions 1.7% (w/w), catalyst ratio, 3.6 h reaction time and stirring rate of 140.6 rpm. The biodiesel conversion was determined by 1 H nuclear magnetic resonance spectroscopy (NMR). The fuel properties of prepared biodiesel were found to be highly comply with the biodiesel standard ASTMD6751 and EN14214. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Effect of biochars produced from solid organic municipal waste on soil quality parameters.

    Science.gov (United States)

    Randolph, P; Bansode, R R; Hassan, O A; Rehrah, Dj; Ravella, R; Reddy, M R; Watts, D W; Novak, J M; Ahmedna, M

    2017-05-01

    New value-added uses for solid municipal waste are needed for environmental and economic sustainability. Fortunately, value-added biochars can be produced from mixed solid waste, thereby addressing solid waste management issues, and enabling long-term carbon sequestration. We hypothesize that soil deficiencies can be remedied by the application of municipal waste-based biochars. Select municipal organic wastes (newspaper, cardboard, woodchips and landscaping residues) individually or in a 25% blend of all four waste streams were used as feedstocks of biochars. Three sets of pyrolysis temperatures (350, 500, and 750 °C) and 3 sets of pyrolysis residence time (2, 4 and 6 h) were used for biochar preparation. The biochar yield was in the range of 21-62% across all feedstocks and pyrolysis conditions. We observed variations in key biochar properties such as pH, electrical conductivity, bulk density and surface area depending on the feedstocks and production conditions. Biochar increased soil pH and improved its electrical conductivity, aggregate stability, water retention and micronutrient contents. Similarly, leachate from the soil amended with biochar showed increased pH and electrical conductivity. Some elements such as Ca and Mg decreased while NO 3 -N increased in the leachates of soils incubated with biochars. Overall, solid waste-based biochar produced significant improvements to soil fertility parameters indicating that solid municipal wastes hold promising potential as feedstocks for manufacturing value-added biochars with varied physicochemical characteristics, allowing them to not only serve the needs for solid waste management and greenhouse gas mitigation, but also as a resource for improving the quality of depleted soils. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Key parameters for behaviour related to source separation of household organic waste: A case study in Hanoi, Vietnam.

    Science.gov (United States)

    Kawai, Kosuke; Huong, Luong Thi Mai

    2017-03-01

    Proper management of food waste, a major component of municipal solid waste (MSW), is needed, especially in developing Asian countries where most MSW is disposed of in landfill sites without any pretreatment. Source separation can contribute to solving problems derived from the disposal of food waste. An organic waste source separation and collection programme has been operated in model areas in Hanoi, Vietnam, since 2007. This study proposed three key parameters (participation rate, proper separation rate and proper discharge rate) for behaviour related to source separation of household organic waste, and monitored the progress of the programme based on the physical composition of household waste sampled from 558 households in model programme areas of Hanoi. The results showed that 13.8% of 558 households separated organic waste, and 33.0% discharged mixed (unseparated) waste improperly. About 41.5% (by weight) of the waste collected as organic waste was contaminated by inorganic waste, and one-third of the waste disposed of as organic waste by separators was inorganic waste. We proposed six hypothetical future household behaviour scenarios to help local officials identify a final or midterm goal for the programme. We also suggested that the city government take further actions to increase the number of people participating in separating organic waste, improve the accuracy of separation and prevent non-separators from discharging mixed waste improperly.

  4. Induction and optimization of cellulases using various agro-wastes ...

    African Journals Online (AJOL)

    SAM

    2014-08-13

    6500 IUL-1). ... thrust in bioconversion of agriculture waste to chemical .... cellulosic ethanol. In the present study, T. viride (S 34) produces a good amount of β-glucosidase enzyme on all type of lignocellulosics especially on ...

  5. Optimization of the Area 5 Radioactive Waste Management Site Closure Cover

    Energy Technology Data Exchange (ETDEWEB)

    Shott, Greg; Yucel, Vefa

    2009-04-01

    The U.S. Department of Energy Manual DOE M 435.1-1, “Radioactive Waste Management Manual,” requires that performance assessments demonstrate that releases of radionuclides to the environment are as low as reasonably achievable (ALARA). Quantitative cost benefit analysis of radiation protection options is one component of the ALARA process. This report summarizes a quantitative cost benefit analysis of closure cover thickness for the Area 5 Radioactive Waste Management Site (RWMS) on the Nevada Test Site. The optimum cover thickness that maintains doses ALARA is shown to be the thickness with the minimum total closure cost. Total closure cost is the sum of cover construction cost and the health detriment cost. Cover construction cost is estimated based on detailed cost estimates for closure of the 92-acre Low-Level Waste Management Unit (LLWMU). The health detriment cost is calculated as the product of collective dose and a constant monetary value of health detriment in units of dollars per unit collective dose. Collective dose is the sum of all individual doses in an exposed population and has units of person-sievert (Sv). Five discrete cover thickness options ranging from 2.5 to 4.5 meters (m) (8.2 to 15 feet [ft]) are evaluated. The optimization was subject to the constraints that (1) options must meet all applicable regulatory requirements and that (2) individual doses be a small fraction of background radiation dose. Total closure cost is found to be a monotonically increasing function of cover thickness for the 92-ac LLWMU, the Northern Expansion Area, and the entire Area 5 RWMS. The cover construction cost is orders of magnitude greater than the health detriment cost. Two-thousand Latin hypercube sampling realizations of the relationship between total closure cost and cover thickness are generated. In every realization, the optimum cover thickness is 2.5 m (8.2 ft) for the 92-ac Low-Level Waste Management Unit, the Northern Expansion Area, and the entire

  6. Optimization of Laser Beam Transformation Hardening by One Single Parameter

    NARCIS (Netherlands)

    Meijer, J.; van Sprang, I.

    1991-01-01

    The process of laser beam transformation hardening is principally controlled by two independent parameters, the absorbed laser power on a given area and the interaction time. These parameters can be transformed into two functional parameters: the maximum surface temperature and the hardening depth.

  7. Using multi-criteria decision making for selection of the optimal strategy for municipal solid waste management.

    Science.gov (United States)

    Jovanovic, Sasa; Savic, Slobodan; Jovicic, Nebojsa; Boskovic, Goran; Djordjevic, Zorica

    2016-09-01

    Multi-criteria decision making (MCDM) is a relatively new tool for decision makers who deal with numerous and often contradictory factors during their decision making process. This paper presents a procedure to choose the optimal municipal solid waste (MSW) management system for the area of the city of Kragujevac (Republic of Serbia) based on the MCDM method. Two methods of multiple attribute decision making, i.e. SAW (simple additive weighting method) and TOPSIS (technique for order preference by similarity to ideal solution), respectively, were used to compare the proposed waste management strategies (WMS). Each of the created strategies was simulated using the software package IWM2. Total values for eight chosen parameters were calculated for all the strategies. Contribution of each of the six waste treatment options was valorized. The SAW analysis was used to obtain the sum characteristics for all the waste management treatment strategies and they were ranked accordingly. The TOPSIS method was used to calculate the relative closeness factors to the ideal solution for all the alternatives. Then, the proposed strategies were ranked in form of tables and diagrams obtained based on both MCDM methods. As shown in this paper, the results were in good agreement, which additionally confirmed and facilitated the choice of the optimal MSW management strategy. © The Author(s) 2016.

  8. 83 Waste Ergonomics Optimization in Ilorin, Nigeria * Ajibade, L.T. ...

    African Journals Online (AJOL)

    Choice-Academy

    sake. Since wastes are materials that are of no use and has no economic values, it therefore means that appropriate equipments and optimal uses of these equipments are of great importance (Beyene, 1999). Mathematical optimization is the branch of computational science that seeks to answer the question 'what is best?

  9. Optimization of CNC end milling process parameters using PCA ...

    African Journals Online (AJOL)

    An attempt has been made to optimize aforesaid quality attributes in a manner that these multi-criterions could be fulfilled simultaneously up to the expected level. This invites a multi-objective optimization problem which has been solved by PCA based Taguchi method. To meet the basic assumption of Taguchi method; ...

  10. Optimization of non-linear mass damper parameters for transient response

    DEFF Research Database (Denmark)

    Jensen, Jakob Søndergaard; Lazarov, Boyan Stefanov

    2008-01-01

    We optimize the parameters of multiple non-linear mass dampers based on numerical simulation of transient wave propagation through a linear mass-spring carrier structure. Topology optimization is used to obtain optimized distributions of damper mass ratio, natural frequency, damping ratio...... and nonlinear stiffness coefficient. Large improvements in performance is obtained with optimized parameters and it is shown that nonlinearmass dampers can bemore effective for wave attenuation than linear mass dampers....

  11. Optimization-based design of waste heat recovery systems

    DEFF Research Database (Denmark)

    Cignitti, Stefano

    product and process system in terms of efficiency and sustainability. Today, some of the most important chemical product design problems are solvents and working fluids. Solvents are a vital part in the recovery of valuable resources in separation processes or waste water treatment. Working fluids....../or selected. This dissertation focuses on the chemical product and process systems used for waste heat recovery. Here, chemical products are working fluids, which are under continuous development and screening to fulfill regulatory environmental protection and safe operation requirements. Furthermore......, for the recovery of low-grade waste heat, new fluids and processes are needed to make the recovery technically and economically feasible. As the chemical product is influential in the design of the process system, the design of novel chemical products must be considered with the process system. Currently, state...

  12. Direct Multiple Shooting Optimization with Variable Problem Parameters

    Science.gov (United States)

    Whitley, Ryan J.; Ocampo, Cesar A.

    2009-01-01

    Taking advantage of a novel approach to the design of the orbital transfer optimization problem and advanced non-linear programming algorithms, several optimal transfer trajectories are found for problems with and without known analytic solutions. This method treats the fixed known gravitational constants as optimization variables in order to reduce the need for an advanced initial guess. Complex periodic orbits are targeted with very simple guesses and the ability to find optimal transfers in spite of these bad guesses is successfully demonstrated. Impulsive transfers are considered for orbits in both the 2-body frame as well as the circular restricted three-body problem (CRTBP). The results with this new approach demonstrate the potential for increasing robustness for all types of orbit transfer problems.

  13. Emission control with route optimization in solid waste collection ...

    Indian Academy of Sciences (India)

    paths. The software was also operated with GIS elements such as numerical pathways, demo- graphic data, container distribution data and solid waste production data. RouteView ProTM is a software, which provides comprehensive routing and catchment area analysis. Different analyses can be done with the software.

  14. Challenges when Performing Economic Optimization of Waste Treatment

    DEFF Research Database (Denmark)

    Juul, Nina; Münster, Marie; Ravn, Hans

    2011-01-01

    on transport are one example but models focusing on energy production have also been developed as well as models which take into account the plants economies of scale, environmental impact, material recovery and social costs. Finally, models combining different criteria for selection of waste treatment methods...

  15. Parameter optimization method for the water quality dynamic model based on data-driven theory.

    Science.gov (United States)

    Liang, Shuxiu; Han, Songlin; Sun, Zhaochen

    2015-09-15

    Parameter optimization is important for developing a water quality dynamic model. In this study, we applied data-driven method to select and optimize parameters for a complex three-dimensional water quality model. First, a data-driven model was developed to train the response relationship between phytoplankton and environmental factors based on the measured data. Second, an eight-variable water quality dynamic model was established and coupled to a physical model. Parameter sensitivity analysis was investigated by changing parameter values individually in an assigned range. The above results served as guidelines for the control parameter selection and the simulated result verification. Finally, using the data-driven model to approximate the computational water quality model, we employed the Particle Swarm Optimization (PSO) algorithm to optimize the control parameters. The optimization routines and results were analyzed and discussed based on the establishment of the water quality model in Xiangshan Bay (XSB). Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. 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)

  17. Parametric Investigation and Thermoeconomic Optimization of a Combined Cycle for Recovering the Waste Heat from Nuclear Closed Brayton Cycle

    Directory of Open Access Journals (Sweden)

    Lihuang Luo

    2016-01-01

    Full Text Available A combined cycle that combines AWM cycle with a nuclear closed Brayton cycle is proposed to recover the waste heat rejected from the precooler of a nuclear closed Brayton cycle in this paper. The detailed thermodynamic and economic analyses are carried out for the combined cycle. The effects of several important parameters, such as the absorber pressure, the turbine inlet pressure, the turbine inlet temperature, the ammonia mass fraction, and the ambient temperature, are investigated. The combined cycle performance is also optimized based on a multiobjective function. Compared with the closed Brayton cycle, the optimized power output and overall efficiency of the combined cycle are higher by 2.41% and 2.43%, respectively. The optimized LEC of the combined cycle is 0.73% lower than that of the closed Brayton cycle.

  18. 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.

  19. 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.

  20. Selective waste collection optimization in Romania and its impact to urban climate

    Science.gov (United States)

    Mihai, Šercǎianu; Iacoboaea, Cristina; Petrescu, Florian; Aldea, Mihaela; Luca, Oana; Gaman, Florian; Parlow, Eberhard

    2016-08-01

    According to European Directives, transposed in national legislation, the Member States should organize separate collection systems at least for paper, metal, plastic, and glass until 2015. In Romania, since 2011 only 12% of municipal collected waste was recovered, the rest being stored in landfills, although storage is considered the last option in the waste hierarchy. At the same time there was selectively collected only 4% of the municipal waste. Surveys have shown that the Romanian people do not have selective collection bins close to their residencies. The article aims to analyze the current situation in Romania in the field of waste collection and management and to make a proposal for selective collection containers layout, using geographic information systems tools, for a case study in Romania. Route optimization is used based on remote sensing technologies and network analyst protocols. Optimizing selective collection system the greenhouse gases, particles and dust emissions can be reduced.

  1. 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.

  2. A sensitivity analysis of hazardous waste disposal site climatic and soil design parameters using HELP3

    Energy Technology Data Exchange (ETDEWEB)

    Adelman, D.D. [Water Resources Engineer, Lincoln, NE (United States); Stansbury, J. [Univ. of Nebraska-Lincoln, Omaha, NE (United States)

    1997-12-31

    The Resource Conservation and Recovery Act (RCRA) Subtitle C, Comprehensive Environmental Response, Compensation, And Liability Act (CERCLA), and subsequent amendments have formed a comprehensive framework to deal with hazardous wastes on the national level. Key to this waste management is guidance on design (e.g., cover and bottom leachate control systems) of hazardous waste landfills. The objective of this research was to investigate the sensitivity of leachate volume at hazardous waste disposal sites to climatic, soil cover, and vegetative cover (Leaf Area Index) conditions. The computer model HELP3 which has the capability to simulate double bottom liner systems as called for in hazardous waste disposal sites was used in the analysis. HELP3 was used to model 54 combinations of climatic conditions, disposal site soil surface curve numbers, and leaf area index values to investigate how sensitive disposal site leachate volume was to these three variables. Results showed that leachate volume from the bottom double liner system was not sensitive to these parameters. However, the cover liner system leachate volume was quite sensitive to climatic conditions and less sensitive to Leaf Area Index and curve number values. Since humid locations had considerably more cover liner system leachate volume than and locations, different design standards may be appropriate for humid conditions than for and conditions.

  3. Parameters optimization of fabric finishing system of a textile industry using teaching–learning-based optimization algorithm

    Directory of Open Access Journals (Sweden)

    Rajiv Kumar

    2017-07-01

    Full Text Available In the present work, a recently developed advanced optimization algorithm named as teaching–learning-based optimization (TLBO is used for the parameters optimization of fabric finishing system of a textile industry. Fabric Finishing System has four main subsystems, arranged in hybrid configuration. For performance modeling and analysis of availability, a performance evaluating model of fabric finishing system has been developed with the help of mathematical formulation based on Markov-Birth-Death process using Probabilistic Approach. Then, the overall performance of the concerned system has first analyzed and then, optimized by using teaching–learning-based optimization (TLBO. The results of optimization using the proposed algorithm are validated by comparing with those obtained by using the genetic algorithm (GA on the same system. Improvement in the results is obtained by the proposed algorithm. The results of effect of variation of the algorithm parameters on fitness values of the objective function are reported.

  4. Fuel Cell Impedance Model Parameters Optimization using a Genetic Algorithm

    National Research Council Canada - National Science Library

    Mohamed Selmene Ben Yahia; Hatem Allagui; Arafet Bouaicha; Abdelkader Mami

    2017-01-01

    .... The method used for the identification is a sample genetic algorithm and the proposed impedance model is based on electric parameters, which will be found from a sweeping of well determined frequency bands...

  5. Key safety parameters in the optimization of fuel management

    Energy Technology Data Exchange (ETDEWEB)

    Kollmar, W.; Boehm, R.; Dernedde, I.; Haase, H.; Kiehlmann, H.D.; Neufert, A.

    1988-08-01

    Nuclear design related key safety parameters and admissible parameter ranges are defined for reload cycles which are so similar in safety terms as to allow these to be covered by generic reload safety analyses in advance. The conceptual frame of such safety analyses together with the resulting economic benefits are illustrated by four concrete applications demonstrating reduction of excessive safety margins, increase in discharge burnup, streamlining of steam break analysis, and increase in operational flexibility of first cores.

  6. Glass optimization for vitrification of Hanford Site low-level tank waste

    Energy Technology Data Exchange (ETDEWEB)

    Feng, X.; Hrma, P.R.; Westsik, J.H. Jr. [and others

    1996-03-01

    The radioactive defense wastes stored in 177 underground single-shell tanks (SST) and double-shell tanks (DST) at the Hanford Site will be separated into low-level and high-level fractions. One technology activity underway at PNNL is the development of glass formulations for the immobilization of the low-level tank wastes. A glass formulation strategy has been developed that describes development approaches to optimize glass compositions prior to the projected LLW vitrification facility start-up in 2005. Implementation of this strategy requires testing of glass formulations spanning a number of waste loadings, compositions, and additives over the range of expected waste compositions. The resulting glasses will then be characterized and compared to processing and performance specifications yet to be developed. This report documents the glass formulation work conducted at PNL in fiscal years 1994 and 1995 including glass formulation optimization, minor component impacts evaluation, Phase 1 and Phase 2 melter vendor glass development, liquidus temperature and crystallization kinetics determination. This report also summarizes relevant work at PNNL on high-iron glasses for Hanford tank wastes conducted through the Mixed Waste Integrated Program and work at Savannah River Technology Center to optimize glass formulations using a Plackett-Burnam experimental design.

  7. Statistical optimization of process parameters for the production of ...

    African Journals Online (AJOL)

    ONOS

    2010-01-25

    Jan 25, 2010 ... The regression equation for the optimization of medium constituents showed that citric acid production (Y, g/kg of dry EFB)) is a function of the moisture content (A, v/w) and the incubation temperature (B, °C). A second order quadratic model was developed with the effect of linear, quadratic and interactive ...

  8. Investigation and validation of optimal cutting parameters for least ...

    African Journals Online (AJOL)

    user

    A commercial statistical analysis software DESIGN-EXPERT was employed for design and analyze the experiment. In. DESIGN-EXPERT, RSM is used to find a combination of factors which gives the optimal response. The experimental results were analyzed with Analysis Of Variance (ANOVA), which is used for identifying ...

  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. Optimization of machining parameters of hard porcelain on a CNC ...

    African Journals Online (AJOL)

    Process modelliing as well as optimization are two major problems of manufacturing products. Processes in manufacturing have the general characteristics of exhibiting variables that are interfacing dynamically (Mahapatra et al, 2006). Recently, diverse substantial benefits have been recognized in the machine tool industry ...

  11. Optimizing pulsed current micro plasma arc welding parameters to ...

    African Journals Online (AJOL)

    user

    tensile strength of pulsed current micro plasma arc welded Inconel 625 sheets. Four factors, five level, central composite rotatable design matrix is used to optimize the number of experiments. The mathematical model has been developed by using. Response Surface Method. The adequacy of the developed model is ...

  12. Conceptual modeling to optimize the haul and transfer of municipal solid waste.

    Science.gov (United States)

    Komilis, D P

    2008-11-01

    Two conceptual mixed integer linear optimization models were developed to optimize the haul and transfer of municipal solid waste (MSW) prior to landfilling. One model is based on minimizing time (h/d), whilst the second model is based on minimizing total cost (euro/d). Both models aim to calculate the optimum pathway to haul MSW from source nodes (waste production nodes, such as urban centers or municipalities) to sink nodes (landfills) via intermediate nodes (waste transfer stations). The models are applicable provided that the locations of the source, intermediate and sink nodes are fixed. The basic input data are distances among nodes, average vehicle speeds, haul cost coefficients (in euro/ton km), equipment and facilities' operating and investment cost, labor cost and tipping fees. The time based optimization model is easier to develop, since it is based on readily available data (distances among nodes). It can be used in cases in which no transfer stations are included in the system. The cost optimization model is more reliable compared to the time model provided that accurate cost data are available. The cost optimization model can be a useful tool to optimally allocate waste transfer stations in a region and can aid a community to investigate the threshold distance to a landfill above which the construction of a transfer station becomes financially beneficial. A sensitivity analysis reveals that queue times at the landfill or at the waste transfer station are key input variables. In addition, the waste transfer station ownership and the initial cost data affect the optimum path. A case study at the Municipality of Athens is used to illustrate the presented models.

  13. 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...

  14. Optimization of Electrical Stimulation Parameters for Cardiac Tissue Engineering

    Science.gov (United States)

    Tandon, Nina; Marsano, Anna; Maidhof, Robert; Wan, Leo; Park, Hyoungshin; Vunjak-Novakovic, Gordana

    2010-01-01

    In vitro application of pulsatile electrical stimulation to neonatal rat cardiomyocytes cultured on polymer scaffolds has been shown to improve the functional assembly of cells into contractile cardiac tissue constrcuts. However, to date, the conditions of electrical stimulation have not been optimized. We have systematically varied the electrode material, amplitude and frequency of stimulation, to determine the conditions that are optimal for cardiac tissue engineering. Carbon electrodes, exhibiting the highest charge-injection capacity and producing cardiac tissues with the best structural and contractile properties, and were thus used in tissue engineering studies. Cardiac tissues stimulated at 3V/cm amplitude and 3Hz frequency had the highest tissue density, the highest concentrations of cardiac troponin-I and connexin-43, and the best developed contractile behavior. These findings contribute to defining bioreactor design specifications and electrical stimulation regime for cardiac tissue engineering. PMID:21604379

  15. Optimizing pulsed current micro plasma arc welding parameters to ...

    African Journals Online (AJOL)

    This paper reveals the influences of pulsed current parameters namely peak current, back current, pulse and pulse width on the ultimate tensile strength of Micro Plasma Arc Welded Inconel 625 sheets. Mathematical model is developed to predict ultimate tensile strength of pulsed current micro plasma arc welded Inconel ...

  16. Optimal Two Parameter Bounds for the Seiffert Mean

    Directory of Open Access Journals (Sweden)

    Hui Sun

    2013-01-01

    Full Text Available We obtain sharp bounds for the Seiffert mean in terms of a two parameter family of means. Our results generalize and extend the recent bounds presented in the Journal of Inequalities and Applications (2012 and Abstract and Applied Analysis (2012.

  17. Optimization of turning process parameters by using grey-Taguchi ...

    African Journals Online (AJOL)

    The main objective of this study is to improve toughness and hardness of engineering material by changing the machining parameters of turning process. By applying Taguchi method the quality of manufactured goods, and engineering designs are developed by studying variations. In this work, an attempt has been made to ...

  18. Optimization of burnishing parameters and determination of select ...

    Indian Academy of Sciences (India)

    Abstract. The present study is aimed at filling the gaps in scientific understand- ing of the burnishing process, and also to aid and arrive at technological solutions for the surface modifications based on burnishing of some of the commonly employed engineering materials. The effects of various burnishing parameters on the ...

  19. Screening for the optimal induction parameters for periplasmic ...

    African Journals Online (AJOL)

    Recombinant E. coli Rosetta-gami 2(DE3) harboring the plasmid pET26b containing IFN-α2b gene under the control of the T7lac promoter was used, where the induction was accomplished by isopropyl β-D-1- thiogalactopyranoside (IPTG). The induction parameters (inducer concentration, point of induction, induction ...

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

    Indian Academy of Sciences (India)

    Administrator

    Abstract. Segregation of in situ formed particles at the grain boundaries is a major drawback of in situ composites. In this study, it has been demonstrated that friction stir processing (FSP) can be used as an effec- tive tool to homogenize the particle distribution in Al based in situ composites and FSP processing parameters.

  1. Optimizing the processing parameters for modular production of ...

    African Journals Online (AJOL)

    ... ensure best quality at minimum cost. The evaluation involves the processing of several experimental boards under varying times and temperatures. The optimum values for the parameters are determined by employing a systems approach to analyze the observations from each process. Nigerian Journal of Physics Vol.

  2. 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.

  3. Modeling and verification of process parameters for the production of tannase by Aspergillus oryzae under submerged fermentation using agro-wastes.

    Science.gov (United States)

    Varadharajan, Venkatramanan; Vadivel, Sudhan Shanmuga; Ramaswamy, Arulvel; Sundharamurthy, Venkatesaprabhu; Chandrasekar, Priyadharshini

    2017-01-01

    Tannase production by Aspergillus oryzae using various agro-wastes as substrates by submerged fermentation was studied in this research. The microbe was isolated from degrading corn kernel obtained from the corn fields at Tiruchengode, India. The microbial identification was done using 18S rRNA gene analysis. The agro-wastes chosen for the study were pomegranate rind, Cassia auriculata flower, black gram husk, and tea dust. The process parameters chosen for optimization study were substrate concentration, pH, temperature, and incubation period. During one variable at a time optimization, the pomegranate rind extract produced maximum tannase activity of 138.12 IU/mL and it was chosen as the best substrate for further experiments. The quadratic model was found to be the effective model for prediction of tannase production by A. oryzae. The optimized conditions predicted by response surface methodology (RSM) with genetic algorithm (GA) were 1.996% substrate concentration, pH of 4.89, temperature of 34.91 °C, and an incubation time of 70.65 H with maximum tannase activity of 138.363 IU/mL. The confirmatory experiment under optimized conditions showed tannase activity of 139.22 IU/mL. Hence, RSM-GA pair was successfully used in this study to optimize the process parameters required for the production of tannase using pomegranate rind. © 2015 International Union of Biochemistry and Molecular Biology, Inc.

  4. Validating carbonation parameters of alkaline solid wastes via integrated thermal analyses: Principles and applications

    Energy Technology Data Exchange (ETDEWEB)

    Pan, Shu-Yuan [Graduate Institute of Environmental Engineering, National Taiwan University, Taipei 10673, Taiwan (China); Chang, E.-E. [Department of Biochemistry, Taipei Medical University, Taipei 110, Taiwan (China); Kim, Hyunook [Department of Environmental Engineering, University of Seoul, Seoul 130-743 (Korea, Republic of); Chen, Yi-Hung [Department of Chemical Engineering and Biotechnology, National Taipei University of Technology, Taipei 10608, Taiwan (China); Chiang, Pen-Chi, E-mail: pcchiang@ntu.edu.tw [Graduate Institute of Environmental Engineering, National Taiwan University, Taipei 10673, Taiwan (China)

    2016-04-15

    Highlights: • Key carbonation parameters of wastes are determined by integrated thermal analyses. • A modified TG-DTG interpretation is proposed, and validated by the DSC technique. • The modified TG-DTG interpretation is further verified by DTA, TG-MS and TG-FTIR. • Kinetics and thermodynamics of CaCO{sub 3} decomposition in solid wastes are determined. • Implication to maximum carbonation conversion of various solid wastes is described. - Abstract: Accelerated carbonation of alkaline solid wastes is an attractive method for CO{sub 2} capture and utilization. However, the evaluation criteria of CaCO{sub 3} content in solid wastes and the way to interpret thermal analysis profiles were found to be quite different among the literature. In this investigation, an integrated thermal analyses for determining carbonation parameters in basic oxygen furnace slag (BOFS) were proposed based on thermogravimetric (TG), derivative thermogravimetric (DTG), and differential scanning calorimetry (DSC) analyses. A modified method of TG-DTG interpretation was proposed by considering the consecutive weight loss of sample with 200–900 °C because the decomposition of various hydrated compounds caused variances in estimates by using conventional methods of TG interpretation. Different quantities of reference CaCO{sub 3} standards, carbonated BOFS samples and synthetic CaCO{sub 3}/BOFS mixtures were prepared for evaluating the data quality of the modified TG-DTG interpretation, in terms of precision and accuracy. The quantitative results of the modified TG-DTG method were also validated by DSC analysis. In addition, to confirm the TG-DTG results, the evolved gas analysis was performed by mass spectrometer and Fourier transform infrared spectroscopy for detection of the gaseous compounds released during heating. Furthermore, the decomposition kinetics and thermodynamics of CaCO{sub 3} in BOFS was evaluated using Arrhenius equation and Kissinger equation. The proposed

  5. Integrated geophysical surveys on waste dumps: evaluation of physical parameters to characterize an urban waste dump (four case studies in Italy).

    Science.gov (United States)

    Cardarelli, Ettore; Di Filippo, Gerardina

    2004-10-01

    Geophysical surveys were carried out on different waste dumps to evaluate key geometric and physical parameters. Depending on the dump dimensions and physical characteristics different geophysical techniques were used. Vertical electrical sounding, electrical resistivity tomography, induced polarization and seismic refraction techniques were integrated to eliminate the non-uniqueness of solutions and for a better understanding of the results. Physical parameters inside and outside the dumps were compared. The change of physical parameters such as resistivity, chargeability, and P-wave velocity allowed evaluation of waste dump geometry, leachate saturation levels, and thickness of waste. Furthermore, in illegal dumps, the size and waste type disposed could be evaluated. Calculated results were compared with plans and book-keeping from the dumps investigated.

  6. 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. From the total budget of $5,000, Tricia and I studied the problem domain for developing ail 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 the data for GA based multi-resolution optimal search. Wavelet processing is proposed to create a coarse resolution representation of data providing two advantages in GA based search: 1. We will have less data to begin with to make search sub-spaces. 2. It will have robustness against the noise because at every level of wavelet based decomposition, we will be decomposing the signal into low pass and high pass filters.

  7. Optimal estimation of parameters of an entangled quantum state

    Science.gov (United States)

    Virzì, S.; Avella, A.; Piacentini, F.; Gramegna, M.; Brida, G.; Degiovanni, I. P.; Genovese, M.

    2017-05-01

    Two-photon entangled quantum states are a fundamental tool for quantum information and quantum cryptography. A complete description of a generic quantum state is provided by its density matrix: the technique allowing experimental reconstruction of the density matrix is called quantum state tomography. Entangled states density matrix reconstruction requires a large number of measurements on many identical copies of the quantum state. An alternative way of certifying the amount of entanglement in two-photon states is represented by the estimation of specific parameters, e.g., negativity and concurrence. If we have a priori partial knowledge of our state, it’s possible to develop several estimators for these parameters that require lower amount of measurements with respect to full density matrix reconstruction. The aim of this work is to introduce and test different estimators for negativity and concurrence for a specific class of two-photon states.

  8. Optimization of biogas production from coffee production waste.

    Science.gov (United States)

    Battista, Federico; Fino, Debora; Mancini, Giuseppe

    2016-01-01

    This study was conducted to investigate the effects of chemical pretreatments on biogas production from coffee waste. After the preparation of a mixture of coffee waste with a TS concentration of 10%w/w, basic and acid pretreatments were conducted in batch mode and their performances were compared with the biogas produced from a mixture without any pretreatment stage. The basic pretreatment demonstrated a very good action on the hydrolysis of the lignin and cellulose, and permitted a biogas production of about 18NL/L with a methane content of almost 80%v/v. Thus, the basic pretreatment has been used to scale-up the process. The coffee refuse was has been carried out in a 45L anaerobic reactor working in continuous mode and in a mesophilic condition (35°C) with a Hydraulic Retention Time (HRT) of about 40days. A high biogas production of 1.14NL/Ld, with a methane percentage of 65%v/v was obtained, thus permitting a process yield of about 83% to be obtained. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Parameter optimization for 3D mass-spring-damper models.

    Science.gov (United States)

    Wang, Xiuzhong; Devarajan, Venkat

    2008-01-01

    In this paper, we investigate the physical accuracy of the 3D mass-spring-damper (MSD) model of an isotropic object. The isotropic object should have the same Poisson constant and Young's modulus in different directions, and so should its model. Based on these two properties, we derive a set of constraints on the parameters of the 3D MSD model. From these constraints, the parameters of the MSD model can be obtained by the constrained least square method. For the MSD model with tetrahedral meshes, we show that its tensile stiffness can be achieved very accurately, and the prone irregular Poisson effects can be suppressed below a tolerable level although its Poisson constant generally cannot be precisely achieved. For the MSD model with hexahedral meshes, we find that the parameters of the model can be obtained explicitly in terms of material properties and mesh geometry. In this case, we also demonstrate that both the tensile stiffness and the Poisson constant can be accurately achieved.

  10. 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

  11. Relationships among various parameters for decision tree optimization

    KAUST Repository

    Hussain, Shahid

    2014-01-14

    In this chapter, we study, in detail, the relationships between various pairs of cost functions and between uncertainty measure and cost functions, for decision tree optimization. We provide new tools (algorithms) to compute relationship functions, as well as provide experimental results on decision tables acquired from UCI ML Repository. The algorithms presented in this paper have already been implemented and are now a part of Dagger, which is a software system for construction/optimization of decision trees and decision rules. The main results presented in this chapter deal with two types of algorithms for computing relationships; first, we discuss the case where we construct approximate decision trees and are interested in relationships between certain cost function, such as depth or number of nodes of a decision trees, and an uncertainty measure, such as misclassification error (accuracy) of decision tree. Secondly, relationships between two different cost functions are discussed, for example, the number of misclassification of a decision tree versus number of nodes in a decision trees. The results of experiments, presented in the chapter, provide further insight. © 2014 Springer International Publishing Switzerland.

  12. Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithm.

    Science.gov (United States)

    Hannan, M A; Akhtar, Mahmuda; Begum, R A; Basri, H; Hussain, A; Scavino, Edgar

    2018-01-01

    Waste collection widely depends on the route optimization problem that involves a large amount of expenditure in terms of capital, labor, and variable operational costs. Thus, the more waste collection route is optimized, the more reduction in different costs and environmental effect will be. This study proposes a modified particle swarm optimization (PSO) algorithm in a capacitated vehicle-routing problem (CVRP) model to determine the best waste collection and route optimization solutions. In this study, threshold waste level (TWL) and scheduling concepts are applied in the PSO-based CVRP model under different datasets. The obtained results from different datasets show that the proposed algorithmic CVRP model provides the best waste collection and route optimization in terms of travel distance, total waste, waste collection efficiency, and tightness at 70-75% of TWL. The obtained results for 1 week scheduling show that 70% of TWL performs better than all node consideration in terms of collected waste, distance, tightness, efficiency, fuel consumption, and cost. The proposed optimized model can serve as a valuable tool for waste collection and route optimization toward reducing socioeconomic and environmental impacts. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. The Application of PSO-AFSA Method in Parameter Optimization for Underactuated Autonomous Underwater Vehicle Control

    Directory of Open Access Journals (Sweden)

    Chunmeng Jiang

    2017-01-01

    Full Text Available In consideration of the difficulty in determining the parameters of underactuated autonomous underwater vehicles in multi-degree-of-freedom motion control, a hybrid method that combines particle swarm optimization (PSO with artificial fish school algorithm (AFSA is proposed in this paper. The optimization process of the PSO-AFSA method is firstly introduced. With the control simulation models in the horizontal plane and vertical plane, the PSO-AFSA method is elaborated when applied in control parameter optimization for an underactuated autonomous underwater vehicle. Both simulation tests and field trials were carried out to prove the efficiency of the PSO-AFSA method in underactuated autonomous underwater vehicle control parameter optimization. The optimized control parameters showed admirable control quality by enabling the underactuated autonomous underwater vehicle to reach the desired states with fast convergence.

  14. 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.

  15. A web-based Decision Support System for the optimal management of construction and demolition waste.

    Science.gov (United States)

    Banias, G; Achillas, Ch; Vlachokostas, Ch; Moussiopoulos, N; Papaioannou, I

    2011-12-01

    Wastes from construction activities constitute nowadays the largest by quantity fraction of solid wastes in urban areas. In addition, it is widely accepted that the particular waste stream contains hazardous materials, such as insulating materials, plastic frames of doors, windows, etc. Their uncontrolled disposal result to long-term pollution costs, resource overuse and wasted energy. Within the framework of the DEWAM project, a web-based Decision Support System (DSS) application - namely DeconRCM - has been developed, aiming towards the identification of the optimal construction and demolition waste (CDW) management strategy that minimises end-of-life costs and maximises the recovery of salvaged building materials. This paper addresses both technical and functional structure of the developed web-based application. The web-based DSS provides an accurate estimation of the generated CDW quantities of twenty-one different waste streams (e.g. concrete, bricks, glass, etc.) for four different types of buildings (residential, office, commercial and industrial). With the use of mathematical programming, the DeconRCM provides also the user with the optimal end-of-life management alternative, taking into consideration both economic and environmental criteria. The DSS's capabilities are illustrated through a real world case study of a typical five floor apartment building in Thessaloniki, Greece. Copyright © 2011 Elsevier Ltd. All rights reserved.

  16. Teaching-learning-based Optimization Algorithm for Parameter Identification in the Design of IIR Filters

    Science.gov (United States)

    Singh, R.; Verma, H. K.

    2013-12-01

    This paper presents a teaching-learning-based optimization (TLBO) algorithm to solve parameter identification problems in the designing of digital infinite impulse response (IIR) filter. TLBO based filter modelling is applied to calculate the parameters of unknown plant in simulations. Unlike other heuristic search algorithms, TLBO algorithm is an algorithm-specific parameter-less algorithm. In this paper big bang-big crunch (BB-BC) optimization and PSO algorithms are also applied to filter design for comparison. Unknown filter parameters are considered as a vector to be optimized by these algorithms. MATLAB programming is used for implementation of proposed algorithms. Experimental results show that the TLBO is more accurate to estimate the filter parameters than the BB-BC optimization algorithm and has faster convergence rate when compared to PSO algorithm. TLBO is used where accuracy is more essential than the convergence speed.

  17. The Study of the Optimal Parameter Settings in a Hospital Supply Chain System in Taiwan

    Directory of Open Access Journals (Sweden)

    Hung-Chang Liao

    2014-01-01

    Full Text Available This study proposed the optimal parameter settings for the hospital supply chain system (HSCS when either the total system cost (TSC or patient safety level (PSL (or both simultaneously was considered as the measure of the HSCS’s performance. Four parameters were considered in the HSCS: safety stock, maximum inventory level, transportation capacity, and the reliability of the HSCS. A full-factor experimental design was used to simulate an HSCS for the purpose of collecting data. The response surface method (RSM was used to construct the regression model, and a genetic algorithm (GA was applied to obtain the optimal parameter settings for the HSCS. The results show that the best method of obtaining the optimal parameter settings for the HSCS is the simultaneous consideration of both the TSC and the PSL to measure performance. Also, the results of sensitivity analysis based on the optimal parameter settings were used to derive adjustable strategies for the decision-makers.

  18. Optimization of sampling parameters for standardized exhaled breath sampling.

    Science.gov (United States)

    Doran, Sophie; Romano, Andrea; Hanna, George B

    2017-09-05

    The lack of standardization of breath sampling is a major contributing factor to the poor repeatability of results and hence represents a barrier to the adoption of breath tests in clinical practice. On-line and bag breath sampling have advantages but do not suit multicentre clinical studies whereas storage and robust transport are essential for the conduct of wide-scale studies. Several devices have been developed to control sampling parameters and to concentrate volatile organic compounds (VOCs) onto thermal desorption (TD) tubes and subsequently transport those tubes for laboratory analysis. We conducted three experiments to investigate (i) the fraction of breath sampled (whole vs. lower expiratory exhaled breath); (ii) breath sample volume (125, 250, 500 and 1000ml) and (iii) breath sample flow rate (400, 200, 100 and 50 ml/min). The target VOCs were acetone and potential volatile biomarkers for oesophago-gastric cancer belonging to the aldehyde, fatty acids and phenol chemical classes. We also examined the collection execution time and the impact of environmental contamination. The experiments showed that the use of exhaled breath-sampling devices requires the selection of optimum sampling parameters. The increase in sample volume has improved the levels of VOCs detected. However, the influence of the fraction of exhaled breath and the flow rate depends on the target VOCs measured. The concentration of potential volatile biomarkers for oesophago-gastric cancer was not significantly different between the whole and lower airway exhaled breath. While the recovery of phenols and acetone from TD tubes was lower when breath sampling was performed at a higher flow rate, other VOCs were not affected. A dedicated 'clean air supply' overcomes the contamination from ambient air, but the breath collection device itself can be a source of contaminants. In clinical studies using VOCs to diagnose gastro-oesophageal cancer, the optimum parameters are 500mls sample volume

  19. 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.

  20. Optimization of waste water discharge and waste water cleaning on the basis of measurements of the organic pollutant load; Optimierung von Abwasserableitung und Abwasserreinigung durch Messung der organischen Abwasserbelastung

    Energy Technology Data Exchange (ETDEWEB)

    Haeck, M. [Dr. Bruno Lange GmbH Berlin, Duesseldorf (Germany)

    1999-07-01

    The spectral absorption coefficient (SAC) is a sum parameter for describing the organic pollutant load of waste water. It is based on a purely physical measuring technique and can be monitored continuously and directly in the medium by means of the described UV process probe. From this arise numerous opportunities for optimizing waste water discharge and cleaning. (orig.) [German] Der spektrale Absorptionskoeffizient (SAK) ist ein Summenparameter zur Beschreibung der organischen Abwasserbelastung. Er basiert auf einem rein physikalischen Messverfahren und kann mit der hier vorgestellten UV-Prozess-Sonde kontinuierlich und direkt im Medium erfasst werden. Daraus ergeben sich zahlreiche Moeglichkeiten zur Optimierung von Abwasserableitung und -reinigung. (orig.)

  1. Optimization of welding parameters for gas transportation steel pipes

    Directory of Open Access Journals (Sweden)

    S. Cvetkovski

    2010-10-01

    Full Text Available The aim of this paper is to define optimization of welding conditions for Submerged Arc Welding (SAW of steel pipes for gas transportation. Fine grain steel X-52 with thickness of 8 mm were used as a base material. Welding was performed from inner and outer side. Two wires, inclined under different angles, were feed separately. Eleven samples divided in three series were experimentally welded. Performed investigations indicated that the best properties showed weldments from series III, welded with the highest heat input. On the contrary of our expectations, welds from series II, using self made equipment, showed pretty bead properties and improper geometry. So, improving of this this equipment and obtaining welds with better properties is the target in future investigations.

  2. Optimization of design parameters of low-energy buildings

    Science.gov (United States)

    Vala, Jiří; Jarošová, Petra

    2017-07-01

    Evaluation of temperature development and related consumption of energy required for heating, air-conditioning, etc. in low-energy buildings requires the proper physical analysis, covering heat conduction, convection and radiation, including beam and diffusive components of solar radiation, on all building parts and interfaces. The system approach and the Fourier multiplicative decomposition together with the finite element technique offers the possibility of inexpensive and robust numerical and computational analysis of corresponding direct problems, as well as of the optimization ones with several design variables, using the Nelder-Mead simplex method. The practical example demonstrates the correlation between such numerical simulations and the time series of measurements of energy consumption on a small family house in Ostrov u Macochy (35 km northern from Brno).

  3. Recycling of plastic waste by density separation: prospects for optimization.

    Science.gov (United States)

    Gent, Malcolm Richard; Menendez, Mario; Toraño, Javier; Diego, Isidro

    2009-03-01

    A review of existing industrial processing and results of alternative processing investigations for separating solid mixtures and specifically recycling plastic waste by density separation is presented. Media density separation is shown to be fundamental for separation and/or pre-concentration in the recycling of plastics. The current use of static media processes limits the capacity and size of material that can be treated commercially. Investigations have shown that the hydroscopic properties of plastics can be reduced to improve such separations. This indicates that an alternative processing method is required to increase the commercial recovery of recyclable plastics. Cylindroconical and cylindrical cyclone-type media separators, such as those used for processing coal, are reviewed and suggested as a potential substitute. Both have superior production capacities and are able to process a larger range in particle sizes treated. A summary of results of investigations with cyclone media devices for recycling plastics is presented.

  4. Methods for genetic optimization of biocatalysts for biofuel production from dairy waste through synthetic biology.

    Science.gov (United States)

    Pasotti, Lorenzo; Zucca, Susanna; Casanova, Michela; Politi, Nicolo; Massaiu, Ilaria; Mazzini, Giuliano; Micoli, Giuseppina; Calvio, Cinzia; Cusella De Angelis, Maria Gabriella; Magni, Paolo

    2015-08-01

    Whey is an abundant by-product of cheese production process and it is considered a special waste due to its high nutritional load and hypertrophic potential. Technologies for whey valorization are available. They can convert such waste into high-value products, like whey proteins. However, the remaining liquid (called permeate) is still considered as a polluting waste due to its high lactose concentration. The alcoholic fermentation of lactose into ethanol will simultaneously achieve two important goals: safe disposal of a pollutant waste and green energy production. This methodology paper illustrates the workflow carried out to design and realize an optimized microorganism that can efficiently perform the lactose-to-ethanol conversion, engineered via synthetic biology experimental and computational approaches.

  5. Evaluation of Externality Costs in Life-Cycle Optimization of Municipal Solid Waste Management Systems

    DEFF Research Database (Denmark)

    Martinez Sanchez, Veronica; Levis, James W.; Damgaard, Anders

    2017-01-01

    development encourages the use of a mixed waste material recovery facility with residues going to incineration, and separated organics to anaerobic digestion. Results are sensitive to waste composition, energy mix and recycling rates. Most of the externality costs stem from SO2, NOx, PM2.5, CH4, fossil CO2......The development of sustainable solid waste management (SWM) systems requires consideration of both economic and environmental impacts. Societal life-cycle costing (S-LCC) provides a quantitative framework to estimate both economic and environmental impacts, by including "budget costs...... suburban U.S. county of 500 000 people generating 320 000 Mg of waste annually. Estimated externality costs are based on emissions of CO2, CH4, N2O, PM2.5, PM10, NOx, SO2, VOC, CO, NH3, Hg, Pb, Cd, Cr (VI), Ni, As, and dioxins. The results indicate that incorporating S-LCC into optimized SWM strategy...

  6. Determining an Efficient Solvent Extraction Parameters for Re-Refining of Waste Lubricating Oils

    Directory of Open Access Journals (Sweden)

    Hassan Ali Durrani

    2012-04-01

    Full Text Available Re-refining of vehicle waste lubricating oil by solvent extraction is one of the efficient and cheapest methods. Three extracting solvents MEK (Methyl-Ethyl-Ketone, 1-butanol, 2-propanol were determined experimentally for their performance based on the parameters i.e. solvent type, solvent oil ratio and extraction temperature. From the experimental results it was observed the MEK performance was highest based on the lowest oil percent losses and highest sludge removal. Further, when temperature of extraction increased the oil losses percent also decreased. This is due to the solvent ability that dissolves the base oil in waste lubricating oil and determines the best SOR (Solvent Oil Ratio and extraction temperatures.

  7. Optimization of Experimental Model Parameter Identification for Energy Storage Systems

    Directory of Open Access Journals (Sweden)

    Rosario Morello

    2013-09-01

    Full Text Available The smart grid approach is envisioned to take advantage of all available modern technologies in transforming the current power system to provide benefits to all stakeholders in the fields of efficient energy utilisation and of wide integration of renewable sources. Energy storage systems could help to solve some issues that stem from renewable energy usage in terms of stabilizing the intermittent energy production, power quality and power peak mitigation. With the integration of energy storage systems into the smart grids, their accurate modeling becomes a necessity, in order to gain robust real-time control on the network, in terms of stability and energy supply forecasting. In this framework, this paper proposes a procedure to identify the values of the battery model parameters in order to best fit experimental data and integrate it, along with models of energy sources and electrical loads, in a complete framework which represents a real time smart grid management system. The proposed method is based on a hybrid optimisation technique, which makes combined use of a stochastic and a deterministic algorithm, with low computational burden and can therefore be repeated over time in order to account for parameter variations due to the battery’s age and usage.

  8. Optimizing Nutrient Utilization and Reducing Waste Through Diet Composition and Feeding Strategies

    Science.gov (United States)

    This document summarizes the findings of the Southern Regional Aquaculture Center project Optimizing Nutrient Utilization and Reducing Waste through Diet Composition and Feeding Strategies. The primary objectives of the project were to determine the effects of diet composition on fish production, n...

  9. Optimal routes scheduling for municipal waste disposal garbage trucks using evolutionary algorithm and artificial immune system

    Directory of Open Access Journals (Sweden)

    Bogna MRÓWCZYŃSKA

    2011-01-01

    Full Text Available This paper describes an application of an evolutionary algorithm and an artificial immune systems to solve a problem of scheduling an optimal route for waste disposal garbage trucks in its daily operation. Problem of an optimisation is formulated and solved using both methods. The results are presented for an area in one of the Polish cities.

  10. Parameter Identification of Anaerobic Wastewater Treatment Bioprocesses Using Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Dorin Sendrescu

    2013-01-01

    Full Text Available This paper deals with the offline parameters identification for a class of wastewater treatment bioprocesses using particle swarm optimization (PSO techniques. Particle swarm optimization is a relatively new heuristic method that has produced promising results for solving complex optimization problems. In this paper one uses some variants of the PSO algorithm for parameter estimation of an anaerobic wastewater treatment process that is a complex biotechnological system. The identification scheme is based on a multimodal numerical optimization problem with high dimension. The performances of the method are analyzed by numerical simulations.

  11. 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.

  12. Steam condenser optimization using Real-parameter Genetic Algorithm for Prototype Fast Breeder Reactor

    Energy Technology Data Exchange (ETDEWEB)

    Jayalal, M.L., E-mail: jayalal@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Kumar, L. Satish, E-mail: satish@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Jehadeesan, R., E-mail: jeha@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Rajeswari, S., E-mail: raj@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Satya Murty, S.A.V., E-mail: satya@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Balasubramaniyan, V.; Chetal, S.C. [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India)

    2011-10-15

    Highlights: > We model design optimization of a vital reactor component using Genetic Algorithm. > Real-parameter Genetic Algorithm is used for steam condenser optimization study. > Comparison analysis done with various Genetic Algorithm related mechanisms. > The results obtained are validated with the reference study results. - Abstract: This work explores the use of Real-parameter Genetic Algorithm and analyses its performance in the steam condenser (or Circulating Water System) optimization study of a 500 MW fast breeder nuclear reactor. Choice of optimum design parameters for condenser for a power plant from among a large number of technically viable combination is a complex task. This is primarily due to the conflicting nature of the economic implications of the different system parameters for maximizing the capitalized profit. In order to find the optimum design parameters a Real-parameter Genetic Algorithm model is developed and applied. The results obtained are validated with the reference study results.

  13. Central Plant Optimization for Waste Energy Reduction (CPOWER)

    Science.gov (United States)

    2016-12-01

    demands reliably, not necessarily for fuel economy or energy efficiency. Central plants contain multiple chiller, boiler, power generation and...operational optimization. Central plants are currently operated to meet all demands reliably and not necessarily for fuel economy or energy efficiency...representatives of Fort Bragg were facilitated by Honeywell staff located on site at Fort Bragg. All digital communication networks used in this program

  14. Parameter and cost optimizations for a modular stellarator reactor

    Science.gov (United States)

    Hitchon, W. N. G.; Johnson, P. C.; Watson, C. J. H.

    1983-02-01

    The physical scaling and cost scaling of a modular stellarator reactor are described. It is shown that configurations based on l=2 are best able to support adequate beta, and physical relationships are derived which enable the geometry and parameters of an l=2 modular stellarator to be defined. A cost scaling for the components of the nuclear island is developed using Starfire (tokamak reactor study) engineering as a basis. It is shown that for minimum cost the stellarator should be of small aspect ratio. For a 4000 MWth plant, as Starfire, the optimum configuration is a 15 coil, 3 field period, l=2 device with a major radius of 16 m and a plasma minor radius of 2 m; and with a conservative wall loading of 2 MW/m2 and an average beta of 3.9%; the estimated cost per kilowatt (electrical) is marginally (7%) greater than Starfire.

  15. Measuring Digital PCR Quality: Performance Parameters and Their Optimization.

    Directory of Open Access Journals (Sweden)

    A Lievens

    Full Text Available Digital PCR is rapidly being adopted in the field of DNA-based food analysis. The direct, absolute quantification it offers makes it an attractive technology for routine analysis of food and feed samples for their composition, possible GMO content, and compliance with labelling requirements. However, assessing the performance of dPCR assays is not yet well established. This article introduces three straightforward parameters based on statistical principles that allow users to evaluate if their assays are robust. In addition, we present post-run evaluation criteria to check if quantification was accurate. Finally, we evaluate the usefulness of Poisson confidence intervals and present an alternative strategy to better capture the variability in the analytical chain.

  16. Optimization of process parameters for osmotic dehydration of papaya cubes.

    Science.gov (United States)

    Jain, S K; Verma, R C; Murdia, L K; Jain, H K; Sharma, G P

    2011-04-01

    Process temperature (30, 40 and 50 °C), syrup concentration (50, 60 and 70(o) Brix) and process time (4, 5 and 6 h) for osmotic dehydration of papaya (Carica papaya) cubes were optimized for the maximum water loss and optimum sugar gain by using response surface methodology. The peeled and pre-processed papaya cubes of 1 cm size were immersed in sugar syrup at constant temperature water bath having syrup to papaya cubes ratio of 4:1 (w/w). The cubes were removed from bath at pre-decided time, rinsed with water and weighed. Initial moisture content of papaya samples were 87.5-88.5% (wb), which was reduced to 67.6-81.1% after osmotic dehydration in various experiments showing mass reduction, water loss and sugar gain in the range of 20.6-36.4, 23.2-44.5 and 2.5-8.1%, respectively. The weight reduction, water loss and sugar gain data were statistically analyzed and regression equation of second order were found the best fit for all the experimental data. Maximum water loss of 28% with optimum sugar gain of 4% was predicted for the 60(o)Brix syrup concentration at 37 °C for syrup to fruit ratio as 4:1 in 4.25 h of osmotic dehydration.

  17. Optimizing supercritical carbon dioxide in the inactivation of bacteria in clinical solid waste by using response surface methodology

    Energy Technology Data Exchange (ETDEWEB)

    Hossain, Md. Sohrab [Department of Environmental Technology, School of Industrial Technology, Universiti Sains Malaysia, 11800 Penang (Malaysia); Nik Ab Rahman, Nik Norulaini [School of Distance Education, Universiti Sains Malaysia, 11800 Penang (Malaysia); Balakrishnan, Venugopal [Institute for Research in Molecular Medicine, Universiti Sains Malaysia, 11800 Penang (Malaysia); Alkarkhi, Abbas F.M. [Department of Environmental Technology, School of Industrial Technology, Universiti Sains Malaysia, 11800 Penang (Malaysia); Ahmad Rajion, Zainul [School of Dental Science, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan (Malaysia); Ab Kadir, Mohd Omar, E-mail: akmomar@usm.my [Department of Environmental Technology, School of Industrial Technology, Universiti Sains Malaysia, 11800 Penang (Malaysia)

    2015-04-15

    Highlights: • Supercritical carbon dioxide sterilization of clinical solid waste. • Inactivation of bacteria in clinical solid waste using supercritical carbon dioxide. • Reduction of the hazardous exposure of clinical solid waste. • Optimization of the supercritical carbon dioxide experimental conditions. - Abstract: Clinical solid waste (CSW) poses a challenge to health care facilities because of the presence of pathogenic microorganisms, leading to concerns in the effective sterilization of the CSW for safe handling and elimination of infectious disease transmission. In the present study, supercritical carbon dioxide (SC-CO{sub 2}) was applied to inactivate gram-positive Staphylococcus aureus, Enterococcus faecalis, Bacillus subtilis, and gram-negative Escherichia coli in CSW. The effects of SC-CO{sub 2} sterilization parameters such as pressure, temperature, and time were investigated and optimized by response surface methodology (RSM). Results showed that the data were adequately fitted into the second-order polynomial model. The linear quadratic terms and interaction between pressure and temperature had significant effects on the inactivation of S. aureus, E. coli, E. faecalis, and B. subtilis in CSW. Optimum conditions for the complete inactivation of bacteria within the experimental range of the studied variables were 20 MPa, 60 °C, and 60 min. The SC-CO{sub 2}-treated bacterial cells, observed under a scanning electron microscope, showed morphological changes, including cell breakage and dislodged cell walls, which could have caused the inactivation. This espouses the inference that SC-CO{sub 2} exerts strong inactivating effects on the bacteria present in CSW, and has the potential to be used in CSW management for the safe handling and recycling-reuse of CSW materials.

  18. Prioritizing and optimizing sustainable measures for food waste prevention and management.

    Science.gov (United States)

    Cristóbal, Jorge; Castellani, Valentina; Manfredi, Simone; Sala, Serenella

    2018-02-01

    Food waste has gained prominence in the European political debate thanks to the recent Circular Economy package. Currently the waste hierarchy, introduced by the Waste Framework Directive, has been the rule followed to prioritize food waste prevention and management measures according to the environmental criteria. But when considering other criteria along with the environmental one, such as the economic, other tools are needed for the prioritization and optimization. This paper addresses the situation in which a decision-maker has to design a food waste prevention programme considering the limited economic resources in order to achieve the highest environmental impact prevention along the whole food life cycle. A methodology using Life Cycle Assessment and mathematical programing is proposed and its capabilities are shown through a case study. Results show that the order established in the waste hierarchy is generally followed. The proposed methodology revealed to be especially helpful in identifying "quick wins" - measures that should be always prioritized since they avoid a high environmental impact at a low cost. Besides, in order to aggregate the environmental scores related to a variety of impact categories, different weighting sets were proposed. In general, results show that the relevance of the weighting set in the prioritization of the measures appears to be limited. Finally, the correlation between reducing food waste generation and reducing environmental impact along the Food Supply Chain has been studied. Results highlight that when planning food waste prevention strategies, it is important to set the targets at the level of environmental impact instead of setting the targets at the level of avoided food waste generation (in mass). Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  19. Methods of Parametric Optimization of Thin-Walled Structures and Parameters which Influence on it

    Directory of Open Access Journals (Sweden)

    Kibkalo Anton

    2016-01-01

    Full Text Available The question of efficiency of thin-walled structures contains a number of contradictions. You need to select the best from all the existing structures on the criteria of optimization options. The search is conducted by varying of the parameters at parametric optimization. As a rule the aim of building structure optimization is reducing of material consumption, the labor input and cost. The costs of a particular variant of construction most full describes the given cost. There are two types of optimization parameters - immutable and varying. The result of the optimization of thin-walled beams will be a combination of parameters for each design situation in which provides the required strength and the minimum of the objective function - factory cost of production

  20. SU-E-T-295: Simultaneous Beam Sampling and Aperture Shape Optimization for Station Parameter Optimized Radiation Therapy (SPORT)

    Energy Technology Data Exchange (ETDEWEB)

    Zarepisheh, M; Li, R; Xing, L [Stanford UniversitySchool of Medicine, Stanford, CA (United States); Ye, Y [Stanford Univ, Management Science and Engineering, Stanford, Ca (United States); Boyd, S [Stanford University, Electrical Engineering, Stanford, CA (United States)

    2014-06-01

    Purpose: Station Parameter Optimized Radiation Therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital LINACs, in which the station parameters of a delivery system, (such as aperture shape and weight, couch position/angle, gantry/collimator angle) are optimized altogether. SPORT promises to deliver unprecedented radiation dose distributions efficiently, yet there does not exist any optimization algorithm to implement it. The purpose of this work is to propose an optimization algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: We build a mathematical model whose variables are beam angles (including non-coplanar and/or even nonisocentric beams) and aperture shapes. To solve the resulting large scale optimization problem, we devise an exact, convergent and fast optimization algorithm by integrating three advanced optimization techniques named column generation, gradient method, and pattern search. Column generation is used to find a good set of aperture shapes as an initial solution by adding apertures sequentially. Then we apply the gradient method to iteratively improve the current solution by reshaping the aperture shapes and updating the beam angles toward the gradient. Algorithm continues by pattern search method to explore the part of the search space that cannot be reached by the gradient method. Results: The proposed technique is applied to a series of patient cases and significantly improves the plan quality. In a head-and-neck case, for example, the left parotid gland mean-dose, brainstem max-dose, spinal cord max-dose, and mandible mean-dose are reduced by 10%, 7%, 24% and 12% respectively, compared to the conventional VMAT plan while maintaining the same PTV coverage. Conclusion: Combined use of column generation, gradient search and pattern search algorithms provide an effective way to optimize simultaneously the large collection of station parameters and significantly improves

  1. Parameter optimization using GA in SVM to predict damage level of non-reshaped berm breakwater.

    Digital Repository Service at National Institute of Oceanography (India)

    Harish, N.; Lokesha.; Mandal, S.; Rao, S.; Patil, S.G.

    In the present study, Support Vector Machines (SVM) and hybrid of Genetic Algorithm (GA) with SVM models are developed to predict the damage level of non-reshaped berm breakwaters. Optimal kernel parameters of SVM are determined by using GA...

  2. NACP VPRM NEE Parameters Optimized to North American Flux Tower Sites, 2000-2006

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides Vegetation Photosynthesis Respiration Model (VPRM) net ecosystem exchange (NEE) parameter values optimized to 65 flux tower sites across North...

  3. THE PARAMETER OPTIMIZATION MODEL OF INVESTMENT AND CONSTRUCTION PROJECTS AND MANAGERIAL FEASIBILITY OF THEIR BEHAVIOR

    Directory of Open Access Journals (Sweden)

    P. Ye. Uvarov

    2009-09-01

    Full Text Available In the article the basic problem of substantiation of parameters of optimization model of organizationaltechnological solutions for investment-building projects in the system of project management is considered.

  4. Optimizing the Process Parameters for Electrochemical Reduction of Carbon Dioxide

    Science.gov (United States)

    Mudunur, Santosh shekar

    One the major problems of this modern industrialized world is its dependence on fossil fuels for its energy needs. Burning of fossils fuels generates green-house gases which have adverse effects on global climate contributing to global warming. According to Environmental Protection Agency (EPA), carbon dioxide makes up 80 percent of green-house gases emitted in USA. Electrochemical reduction of carbon dioxide is an approach which uses CO2 emissions to produce other useful hydrocarbons which can be used in many ways. In this study, primary focus was on optimizing the operating conditions, determining the better catalyst material, and analyzing the reaction products for the process of electrochemical reduction of carbon dioxide (ERC). Membrane electrode assemblies (MEA's) are developed by air bushing the metal particles with a spray gun on to Nafion-212 which is a solid polymer based electrolyte (SPE), to support the electrodes in the electrochemical reactor gas diffusion layers (GDL) are developed using porous carbon paper. Anode was always made using the same material which is platinum but cathode material was changed as it is the working electrode. The membrane electrode assembly (MEA) is then placed into the electrochemical reactor along with gas diffusion layer (GDL) to assess the performance of the catalyst material by techniques like linear sweep voltammetry and chronoamperometry. Performance of MEA was analyzed at 4 different potentials, 2 different temperatures and for 2 different cathode catalyst materials. The reaction products of the process are analyzed using gas chromatography (GC) which has thermal conductivity detector (TCD) used for detecting hydrogen (H2), carbon monoxide (CO) and flame ionization detector (FID) used for detecting hydrocarbons. The experiments performed at 40° C gave the better results when compared with the experiments performed at ambient temperature. Also results suggested that copper oxide cathode catalyst has better durability

  5. The determination of an optimal waste management scenario for Kampala, Uganda.

    Science.gov (United States)

    Oyoo, Richard; Leemans, Rik; Mol, Arthur P J

    2013-12-01

    The quality of the environment in the city of Kampala is deteriorating. The city needs a novel waste management approach to improve the environmental quality in its heterogeneous settlement patterns. Earlier, an integrated urban waste flow model (IUWFM) was applied to project the future waste flows and their impacts on the environment of Kampala using four waste management scenarios. These scenarios were 'business-as-usual', 'more enforcement', 'more collection' and 'proper management'. The robustness of the scenario results was determined by using a multi-criteria decision analysis. Twenty-four criteria were identified and grouped as environmental, economic, social, technological and general. Equal weights were assigned to these five sets of criteria. The four scenarios were evaluated against all criteria, and a sensitivity analysis was performed on the role of the equal weights on the choice of the scenarios. The results showed that 'proper management' scenario, which integrates diverse technologies and management programs matching with the local context, is the optimal approach to improve Kampala's environmental quality. Scenarios that emphasized more waste collection, but less resource recovery were ranked in the middle. The scenario of maintaining the status quo performed worst. Application of a mix of diverse technologies and management programs matching the local conditions is the most optimal solution to improve Kampala's environmental quality.

  6. Optimization of first order decay gas generation model parameters for landfills located in cold semi-arid climates.

    Science.gov (United States)

    Vu, Hoang Lan; Ng, Kelvin Tsun Wai; Richter, Amy

    2017-11-01

    Canada has one of the highest waste generation rates in the world. Because of high land availability, land disposal rates in the province of Saskatchewan are high compared to the rest of the country. In this study, landfill gas data was collected at semi-arid landfills in Regina and Saskatoon, Saskatchewan, and curve fitting was carried out to find optimal k and Lo or DOC values using LandGEM, Afvalzorg Simple, and IPCC first order decay models. Model parameters at each landfill were estimated and compared using default k and Lo or DOC values. Methane generation rates were substantially overestimated using default values (with percentage errors from 55 to 135%). The mean percentage errors for the optimized k and Lo or DOC values ranged from 11.60% to 19.93% at the Regina landfill, and 1.65% to 10.83% at the Saskatoon landfill. Finally, the effect of different iterative methods on the curve fitting process was examined. The residual sum of squares for each model and iterative approaches were similar, with the exception of iterative method 1 for the IPCC model. The default values in these models fail to represent landfills located in cold semi-arid climates. The use of site specific data, provided enough information is available regarding waste mass and composition, can greatly help to improve the accuracy of these first order decay models. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Optimization of Process Parameters by Statistical Experimental Designs for the Production of Naringinase Enzyme by Marine Fungi

    Directory of Open Access Journals (Sweden)

    Abeer Nasr Shehata

    2014-01-01

    Full Text Available Naringinase has attracted a great deal of attention in recent years due to its hydrolytic activities which include the production of rhamnose and prunin and debittering of citrus fruit juices. Screening of fifteen marine-derived fungi, locally isolated from Ismalia, Egypt, for naringinase enzyme production, indicated that Aspergillus niger was the most promising. In solid state fermentation (SSF of the agroindustrial waste, orange rind was used as a substrate containing naringin. Sequential optimization strategy, based on statistical experimental designs, was employed to enhance the production of the debittering naringinase enzyme. Effects of 19 variables were examined for their significance on naringinase production using Plackett-Burman factorial design. Significant parameters were further investigated using Taguchi’s (L16 45 orthogonal array design. Based on statistical analysis (ANOVA, the optimal combinations of the major constituents of media for maximal naringinase production were evaluated as follows: 15 g orange rind waste, 30 mL moisture content, 1% grape fruit, 1% NaNO3, 0.5% KH2PO4, 5 mM MgSO4, 5 mM FeSO4, and the initial pH 7.5. The activity obtained was more than 3.14-fold the basal production medium.

  8. Recent Strategy of Biodiesel Production from Waste Cooking Oil and Process Influencing Parameters: A Review

    Directory of Open Access Journals (Sweden)

    A. Gnanaprakasam

    2013-01-01

    Full Text Available Cost of biodiesel produced from virgin vegetable oil through transesterification is higher than that of fossil fuel, because of high raw material cost. To minimize the biofuel cost, in recent days waste cooking oil was used as feedstock. Catalysts used in this process are usually acids, base, and lipase. Since lipase catalysts are much expensive, the usage of lipase in biodiesel production is limited. In most cases, NaOH is used as alkaline catalyst, because of its low cost and higher reaction rate. In the case of waste cooking oil containing high percentage of free fatty acid, alkaline catalyst reacts with free fatty acid and forms soap by saponification reaction. Also, it reduces the biodiesel conversions. In order to reduce the level of fatty acid content, waste cooking oil is pretreated with acid catalyst to undergo esterification reaction, which also requires high operating conditions. In this review paper, various parameters influencing the process of biofuel production such as reaction rate, catalyst concentration, temperature, stirrer speed, catalyst type, alcohol used, alcohol to oil ratio, free fatty acid content, and water content have been summarized.

  9. Wing Geometry and Kinematic Parameters Optimization of Flapping Wing Hovering Flight

    Directory of Open Access Journals (Sweden)

    Xijun Ke

    2016-11-01

    Full Text Available How to efficiently mimic the wing shape and kinematics pattern of an able hovering living flier is always a concern of researchers from the flapping wing micro aerial vehicles community. In this work, the separate or combined optimizations of wing geometry or/and wing kinematic parameters are systematically performed to minimize the energy of hovering flight, firstly on the basis of analytically extended quasi-steady aerodynamic model by using hybrid genetic algorithm. Before the elaboration of the optimization problem, the parametrization description of dynamically scaled wing with non-dimensional conformal feature of insect-scale rigid wing is firstly proposed. The optimization results show that the combined optimization of wing geometry and kinematic parameters can obtain lower flapping frequency, larger wing geometry parameters and lower power density in comparison with those from other cases of optimization. Moreover, the flapping angle for the optimization involving wing kinematic parameters manifests harmonic shape profile and the pitch angle possesses round trapezoidal profile with certain faster time scale of pitch reversal. The combined optimization framework provides a novel method for the conceptual design of fundamental parameters of biomimetic flapping wing micro aerial vehicle.

  10. A Parameter Estimation Method for Nonlinear Systems Based on Improved Boundary Chicken Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Shaolong Chen

    2016-01-01

    Full Text Available Parameter estimation is an important problem in nonlinear system modeling and control. Through constructing an appropriate fitness function, parameter estimation of system could be converted to a multidimensional parameter optimization problem. As a novel swarm intelligence algorithm, chicken swarm optimization (CSO has attracted much attention owing to its good global convergence and robustness. In this paper, a method based on improved boundary chicken swarm optimization (IBCSO is proposed for parameter estimation of nonlinear systems, demonstrated and tested by Lorenz system and a coupling motor system. Furthermore, we have analyzed the influence of time series on the estimation accuracy. Computer simulation results show it is feasible and with desirable performance for parameter estimation of nonlinear systems.

  11. Theoretical aspects of selection of optimal design parameters of a new generation of AC transmission lines

    Directory of Open Access Journals (Sweden)

    Postolati V.M.

    2010-04-01

    Full Text Available The problems of compactness and of a choice of optimal parameters of alternating current transmission lines are considered. Analytical analysis of some constructive characteristics of three variants of lines of new generation (one-chain, two-chain and operated self-compensated, for the purpose of their optimization by criteria of the maximum compactness is performed.

  12. Adjoint Parameter Sensitivity Analysis for the Hydrodynamic Lattice Boltzmann Method with Applications to Design Optimization

    DEFF Research Database (Denmark)

    Pingen, Georg; Evgrafov, Anton; Maute, Kurt

    2009-01-01

    We present an adjoint parameter sensitivity analysis formulation and solution strategy for the lattice Boltzmann method (LBM). The focus is on design optimization applications, in particular topology optimization. The lattice Boltzmann method is briefly described with an in-depth discussion of so...

  13. Information method of optimization parameters in the diagnosis of gas turbine engines

    Directory of Open Access Journals (Sweden)

    G. S. Zontov

    2015-01-01

    Full Text Available This article describes an algorithm parameter optimization method for the diagnosis of GTD in order to devide zones of efficiency. The autor focuses on the retional combination of methods of mathematical analysis and statistics and de-veloping an algorithm that allows to optimize the use of mathematical methods by longitudinal data collection and ma-chine learning.

  14. 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

  15. Optimization of Indoor Thermal Comfort Parameters with the Adaptive Network-Based Fuzzy Inference System and Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Jing Li

    2017-01-01

    Full Text Available The goal of this study is to improve thermal comfort and indoor air quality with the adaptive network-based fuzzy inference system (ANFIS model and improved particle swarm optimization (PSO algorithm. A method to optimize air conditioning parameters and installation distance is proposed. The methodology is demonstrated through a prototype case, which corresponds to a typical laboratory in colleges and universities. A laboratory model is established, and simulated flow field information is obtained with the CFD software. Subsequently, the ANFIS model is employed instead of the CFD model to predict indoor flow parameters, and the CFD database is utilized to train ANN input-output “metamodels” for the subsequent optimization. With the improved PSO algorithm and the stratified sequence method, the objective functions are optimized. The functions comprise PMV, PPD, and mean age of air. The optimal installation distance is determined with the hemisphere model. Results show that most of the staff obtain a satisfactory degree of thermal comfort and that the proposed method can significantly reduce the cost of building an experimental device. The proposed methodology can be used to determine appropriate air supply parameters and air conditioner installation position for a pleasant and healthy indoor environment.

  16. Effects of operational parameters on dark fermentative hydrogen production from biodegradable complex waste biomass.

    Science.gov (United States)

    Ghimire, Anish; Sposito, Fabio; Frunzo, Luigi; Trably, Eric; Escudié, Renaud; Pirozzi, Francesco; Lens, Piet N L; Esposito, Giovanni

    2016-04-01

    This work aimed to investigate the effect of the initial pH, combination of food to microorganism ratio (F/M) and initial pH, substrate pre-treatment and different inoculum sources on the dark fermentative biohydrogen (H2) yields. Three model complex waste biomasses (food waste, olive mill wastewater (OMWW) and rice straw) were used to assess the effect of the aforementioned parameters. The effect of the initial pH between 4.5 and 7.0 was investigated in batch tests carried out with food waste. The highest H2 yields were shown at initial pH 4.5 (60.6 ± 9.0 mL H2/g VS) and pH 5.0 (50.7 ± 0.8 mL H2/g VS). Furthermore, tests carried out with F/M ratios of 0.5, 1.0 and 1.5 at initial pH 5.0 and 6.5 revealed that a lower F/M ratio (0.5 and 1.0) favored the H2 production at an initial pH 5.0 compared to pH 6.5. Alkaline pre-treatment of raw rice straw using 4% and 8% NaOH at 55°C for 24h, increased the H2 yield by 26 and 57-fold, respectively. In the dark fermentation of OMWW, the H2 yield was doubled when heat-shock pre-treated activated sludge was used as inoculum in comparison to anaerobic sludge. Overall, this study shows that the application of different operating parameters to maximize the H2 yields strongly depends on the biodegradability of the substrate. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Learning optimal spatially-dependent regularization parameters in total variation image denoising

    Science.gov (United States)

    Van Chung, Cao; De los Reyes, J. C.; Schönlieb, C. B.

    2017-07-01

    We consider a bilevel optimization approach in function space for the choice of spatially dependent regularization parameters in TV image denoising models. First- and second-order optimality conditions for the bilevel problem are studied when the spatially-dependent parameter belongs to the Sobolev space {{H}1}≤ft(Ω \\right) . A combined Schwarz domain decomposition-semismooth Newton method is proposed for the solution of the full optimality system and local superlinear convergence of the semismooth Newton method is verified. Exhaustive numerical computations are finally carried out to show the suitability of the approach.

  18. Optimization of the Separation Parameters and Indicators of Separation Efficiency of Buckwheat Seeds

    Directory of Open Access Journals (Sweden)

    Stanisław Konopka

    2017-11-01

    Full Text Available The separation parameters and the indicators of separation efficiency for buckwheat seeds and impurities that are difficult to separate were optimized with the use of self-designed software based on genetic algorithms. The results of the calculations differed significantly from the suboptimal values determined in previous studies. The optimal values of the indicator of separation efficiency were higher; whereas the values of the indicator of buckwheat seed loss were significantly lower. The optimal working parameters for a seed separator in order to promote separation efficiency were determined.

  19. Optimal Design of the Transverse Flux Machine Using a Fitted Genetic Algorithm with Real Parameters

    DEFF Research Database (Denmark)

    Argeseanu, Alin; Ritchie, Ewen; Leban, Krisztina Monika

    2012-01-01

    This paper applies a fitted genetic algorithm (GA) to the optimal design of transverse flux machine (TFM). The main goal is to provide a tool for the optimal design of TFM that is an easy to use. The GA optimizes the analytic basic design of two TFM topologies: the C-core and the U-core. First......, the GA was designed with real parameters. A further, objective of the fitted GA is minimization of the computation time, related to the number of individuals, the number of generations and the types of operators and their specific parameters....

  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. 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...

  2. 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.

  3. Combustion Model and Control Parameter Optimization Methods for Single Cylinder Diesel Engine

    Directory of Open Access Journals (Sweden)

    Bambang Wahono

    2014-01-01

    Full Text Available This research presents a method to construct a combustion model and a method to optimize some control parameters of diesel engine in order to develop a model-based control system. The construction purpose of the model is to appropriately manage some control parameters to obtain the values of fuel consumption and emission as the engine output objectives. Stepwise method considering multicollinearity was applied to construct combustion model with the polynomial model. Using the experimental data of a single cylinder diesel engine, the model of power, BSFC, NOx, and soot on multiple injection diesel engines was built. The proposed method succesfully developed the model that describes control parameters in relation to the engine outputs. Although many control devices can be mounted to diesel engine, optimization technique is required to utilize this method in finding optimal engine operating conditions efficiently beside the existing development of individual emission control methods. Particle swarm optimization (PSO was used to calculate control parameters to optimize fuel consumption and emission based on the model. The proposed method is able to calculate control parameters efficiently to optimize evaluation item based on the model. Finally, the model which added PSO then was compiled in a microcontroller.

  4. Prediction Model of Battery State of Charge and Control Parameter Optimization for Electric Vehicle

    Directory of Open Access Journals (Sweden)

    Bambang Wahono

    2015-07-01

    Full Text Available This paper presents the construction of a battery state of charge (SOC prediction model and the optimization method of the said model to appropriately control the number of parameters in compliance with the SOC as the battery output objectives. Research Centre for Electrical Power and Mechatronics, Indonesian Institute of Sciences has tested its electric vehicle research prototype on the road, monitoring its voltage, current, temperature, time, vehicle velocity, motor speed, and SOC during the operation. Using this experimental data, the prediction model of battery SOC was built. Stepwise method considering multicollinearity was able to efficiently develops the battery prediction model that describes the multiple control parameters in relation to the characteristic values such as SOC. It was demonstrated that particle swarm optimization (PSO succesfully and efficiently calculated optimal control parameters to optimize evaluation item such as SOC based on the model.

  5. Parameters-tuning of PID controller for automatic voltage regulators using the African buffalo optimization.

    Science.gov (United States)

    Odili, Julius Beneoluchi; Mohmad Kahar, Mohd Nizam; Noraziah, A

    2017-01-01

    In this paper, an attempt is made to apply the African Buffalo Optimization (ABO) to tune the parameters of a PID controller for an effective Automatic Voltage Regulator (AVR). Existing metaheuristic tuning methods have been proven to be quite successful but there were observable areas that need improvements especially in terms of the system's gain overshoot and steady steady state errors. Using the ABO algorithm where each buffalo location in the herd is a candidate solution to the Proportional-Integral-Derivative parameters was very helpful in addressing these two areas of concern. The encouraging results obtained from the simulation of the PID Controller parameters-tuning using the ABO when compared with the performance of Genetic Algorithm PID (GA-PID), Particle-Swarm Optimization PID (PSO-PID), Ant Colony Optimization PID (ACO-PID), PID, Bacteria-Foraging Optimization PID (BFO-PID) etc makes ABO-PID a good addition to solving PID Controller tuning problems using metaheuristics.

  6. 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.

  7. Optimizing the control process parameters for the induction soldering of aluminium alloy waveguide paths1

    Science.gov (United States)

    Tynchenko, V. S.; Murygin, A. V.; Petrenko, V. E.; Emilova, O. A.; Bocharov, A. N.

    2017-10-01

    The paper describes the problem of selecting the optimal initial values of algorithm parameters for the process of the induction soldering of aluminium alloy waveguide paths. The authors consider some factors influencing the quality of waveguide soldered joint elements. These factors depend on the correct choice of initial values for control parameters. The problem of optimizing such parameters for further analytical and numerical studies is researched by authors. For solving the stated task, the random search method is selected, allowing for an acceptable field study within the stated time to solve the problem of control optimization with the level of accuracy required by the technological process. Therefore, optimal initial values of the induction soldering technological process were found for three sizes of waveguide tubes and flanges.

  8. Solar collector parameter identification from unsteady data by a discrete-gradient optimization algorithm

    Science.gov (United States)

    Hotchkiss, G. B.; Burmeister, L. C.; Bishop, K. A.

    1980-01-01

    A discrete-gradient optimization algorithm is used to identify the parameters in a one-node and a two-node capacitance model of a flat-plate collector. Collector parameters are first obtained by a linear-least-squares fit to steady state data. These parameters, together with the collector heat capacitances, are then determined from unsteady data by use of the discrete-gradient optimization algorithm with less than 10 percent deviation from the steady state determination. All data were obtained in the indoor solar simulator at the NASA Lewis Research Center.

  9. LONGEVITY IMPROVEMENT OF DRIVE TOOTHED BELTS USING METHOD FOR OPTIMIZATION OF TECHNOLOGICAL MANUFACTURING PROCESS PARAMETERS

    Directory of Open Access Journals (Sweden)

    A. G. Bakhanovich

    2006-01-01

    Full Text Available Impact of technological process parameters (pressing pressure, duration and vulcanization temperature on drive toothed belt longevity has been investigated. Optimum parameters of the technological process that permit to improve a belt resource have been determined. Methodology for determination of a number of cycles intended for loading of belt teeth according to a test duration and transmission parameters has been developed. The paper presents results of industrial resource tests of drive toothed belts manufactured in accordance with an optimized technology

  10. Optimization of the Transesterification of Waste Cooking Oil with Mg-Al Hydrotalcite Using Response Surface Methodology

    Directory of Open Access Journals (Sweden)

    Laureano Costarrosa

    2018-01-01

    Full Text Available Nowadays, biodiesel has become a very promising alternative to fossil diesel fuel, regarding environmental concerns and fuel resource depletion. Biodiesel is usually produced through homogeneous or heterogeneous transesterification of different fatty raw materials. Although main research has been carried out with homogenous catalysts, heterogeneous catalysts may be of interest due to ease of recovery and recycling, as well as readiness for continuous processing. In this work, calcined Mg-Al hydrotalcite (HT was used for the heterogeneous transesterification of waste cooking oil. Three reaction parameters, namely, reaction time, amount of catalyst, and methanol-to-oil molar ratio, were optimized by means of Response Surface Methodology (RSM at constant temperature (65 °C, using a Box-Behnken design. Optimal fatty acid methyl ester (FAME content (86.23% w/w FAME/sample was predicted by the model with an R-squared value of 98.45%, using 3.39 g of HT (8.5% w/w oil and an 8:1 methanol-oil molar ratio, for a duration of 3.12 h. It was observed that calcination of HT, while avoiding the previous washing step, allowed the presence of chemical species that enhanced the effect of the catalyst. It can be concluded from this field trial that calcined and nonwashed Mg-Al hydrotalcite may be considered an effective basic catalyst for the production of biodiesel from waste cooking oil. Also, RSM proved to be a useful tool for predicting biodiesel yield.

  11. Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization

    Directory of Open Access Journals (Sweden)

    Huanqing Cui

    2017-03-01

    Full Text Available Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors’ memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.

  12. Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization.

    Science.gov (United States)

    Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

    2017-03-01

    Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors' memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.

  13. Building energy system optimizations with utilization of waste heat from cogenerations by means of genetic algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Kayo, Genku [Department of Architecture, Graduate School of Engineering, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Ooka, Ryozo [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan)

    2010-07-15

    Distributed energy systems based on cogeneration offer significant potential to save energy since they effectively utilize waste heat from power generators. However, unless there is an appropriate combination of machinery and operations, the planned performance cannot be achieved. Thus, it is quite difficult to determine the optimal combination of machinery and operations. For this, an optimal design approach is needed. In this study, a new optimal design method for building energy systems is proposed. There are an enormous variety of combinations with regard to energy supply and demand. This method designs the most efficient energy system by optimizing the operation of available systems with consideration for the optimal capacity of machinery in the systems. Optimization algorithms known as ''genetic algorithms'' (GAs) with the capacity to deal with non-linear optimization problems have been adopted in this optimization analysis. In this study, a single-building energy system is evaluated. The result shows that the proposed method is sufficiently capable of optimizing the design, and has the potential to be applied to very complex energy systems with appropriate improvements. (author)

  14. The Optimal Evaporation Temperature of Subcritical ORC Based on Second Law Efficiency for Waste Heat Recovery

    Directory of Open Access Journals (Sweden)

    Xiaoxiao Xu

    2012-03-01

    Full Text Available The subcritical Organic Rankine Cycle (ORC with 28 working fluids for waste heat recovery is discussed in this paper. The effects of the temperature of the waste heat, the critical temperature of working fluids and the pinch temperature difference in the evaporator on the optimal evaporation temperature (OET of the ORC have been investigated. The second law efficiency of the system is regarded as the objective function and the evaporation temperature is optimized by using the quadratic approximations method. The results show that the OET will appear for the temperature ranges investigated when the critical temperatures of working fluids are lower than the waste heat temperatures by 18 ± 5 K under the pinch temperature difference of 5 K in the evaporator. Additionally, the ORC always exhibits the OET when the pinch temperature difference in the evaporator is raised under the fixed waste heat temperature. The maximum second law efficiency will decrease with the increase of pinch temperature difference in the evaporator.

  15. Performance optimization of biological waste treatment by flotation clarification at a chemical manufacturing facility

    Energy Technology Data Exchange (ETDEWEB)

    Kerecz, B.J. [Air Products and Chemicals, Inc., Allentown, PA (United States); Miller, D.R. [Komline-Sanderson, Peapack, NJ (United States)

    1995-12-31

    Air Products and Chemicals, Inc., utilizes a deep-tank activated sludge wastewater treatment system with a dissolved air flotation clarifier (DAF) to effectively treat amine wastes containing residual organics, ammonia-nitrogen and organic nitrogen. The bio-system, a deep tank aeration system, produces a high quality final effluent low in biochemical oxygen demand (BOD), ammonia and organic nitrogen, turbidity and total suspended solids. Prior to installing the DAF, treatment performance was at risk with a gravity clarifier. Waste treatment performance was jeopardized by poor settling bio-flocs and uncontrollable solids-liquid separation problems within the gravity clarifier. The solids settleability problems resulted primarily from mixed liquor nitrogen supersaturation degassing in the clarifier. As a result of the degassing, biomass floated on the gravity clarifier or overflowed the effluent weir. As a result of biomass loss periodically organic carbon and total Kjeldahl nitrogen loadings had to be reduced in order to maintain optimal food-to-mass ratios. As biomass levels dropped within the aeration basin, waste treatment performance was at risk and waste loads had to be decreased causing waste inventories to increase in storage tanks.

  16. Assessing FPAR Source and Parameter Optimization Scheme in Application of a Diagnostic Carbon Flux Model

    Energy Technology Data Exchange (ETDEWEB)

    Turner, D P; Ritts, W D; Wharton, S; Thomas, C; Monson, R; Black, T A

    2009-02-26

    The combination of satellite remote sensing and carbon cycle models provides an opportunity for regional to global scale monitoring of terrestrial gross primary production, ecosystem respiration, and net ecosystem production. FPAR (the fraction of photosynthetically active radiation absorbed by the plant canopy) is a critical input to diagnostic models, however little is known about the relative effectiveness of FPAR products from different satellite sensors nor about the sensitivity of flux estimates to different parameterization approaches. In this study, we used multiyear observations of carbon flux at four eddy covariance flux tower sites within the conifer biome to evaluate these factors. FPAR products from the MODIS and SeaWiFS sensors, and the effects of single site vs. cross-site parameter optimization were tested with the CFLUX model. The SeaWiFs FPAR product showed greater dynamic range across sites and resulted in slightly reduced flux estimation errors relative to the MODIS product when using cross-site optimization. With site-specific parameter optimization, the flux model was effective in capturing seasonal and interannual variation in the carbon fluxes at these sites. The cross-site prediction errors were lower when using parameters from a cross-site optimization compared to parameter sets from optimization at single sites. These results support the practice of multisite optimization within a biome for parameterization of diagnostic carbon flux models.

  17. Use of multilevel modeling for determining optimal parameters of heat supply systems

    Science.gov (United States)

    Stennikov, V. A.; Barakhtenko, E. A.; Sokolov, D. V.

    2017-07-01

    The problem of finding optimal parameters of a heat-supply system (HSS) is in ensuring the required throughput capacity of a heat network by determining pipeline diameters and characteristics and location of pumping stations. Effective methods for solving this problem, i.e., the method of stepwise optimization based on the concept of dynamic programming and the method of multicircuit optimization, were proposed in the context of the hydraulic circuit theory developed at Melentiev Energy Systems Institute (Siberian Branch, Russian Academy of Sciences). These methods enable us to determine optimal parameters of various types of piping systems due to flexible adaptability of the calculation procedure to intricate nonlinear mathematical models describing features of used equipment items and methods of their construction and operation. The new and most significant results achieved in developing methodological support and software for finding optimal parameters of complex heat supply systems are presented: a new procedure for solving the problem based on multilevel decomposition of a heat network model that makes it possible to proceed from the initial problem to a set of interrelated, less cumbersome subproblems with reduced dimensionality; a new algorithm implementing the method of multicircuit optimization and focused on the calculation of a hierarchical model of a heat supply system; the SOSNA software system for determining optimum parameters of intricate heat-supply systems and implementing the developed methodological foundation. The proposed procedure and algorithm enable us to solve engineering problems of finding the optimal parameters of multicircuit heat supply systems having large (real) dimensionality, and are applied in solving urgent problems related to the optimal development and reconstruction of these systems. The developed methodological foundation and software can be used for designing heat supply systems in the Central and the Admiralty regions in

  18. Determination of conditions for search of optimal parameters of railway chassis suspensions

    Directory of Open Access Journals (Sweden)

    Leonas Povilas LINGAITIS

    2008-01-01

    Full Text Available The efficiency of resilient suspension is usually expressed through various combinations of resilient and viscous elements, defined by dynamic and viscosity coefficients and other parameters. The aim of this article is to identify the components of the objective function, establish their weighted values and parameter regimes, and todetermine fluctuation limits, initial values, and speeds of optimization parameters, which cannot be established a priori in advance. Calculations aimed at optimization of parameters show that the stability coefficient should be considered the main indicator ofthe objective function, as this is the first parameter to limit the running speed. Given the increasing speeds of trains, the presented method is very important in calculating suspensions.

  19. Selection of Near Optimal Laser Cutting Parameters in CO2 Laser Cutting by the Taguchi Method

    Directory of Open Access Journals (Sweden)

    Miloš MADIĆ

    2013-12-01

    Full Text Available Identification of laser cutting conditions that are insensitive to parameter variations and noise is of great importance. This paper demonstrates the application of Taguchi method for optimization of surface roughness in CO2 laser cutting of stainless steel. The laser cutting experiment was planned and conducted according to the Taguchi’s experimental design using the L27 orthogonal array. Four laser cutting parameters such as laser power, cutting speed, assist gas pressure, and focus position were considered in the experiment. Using the analysis of means and analysis of variance, the significant laser cutting parameters were identified, and subsequently the optimal combination of laser cutting parameter levels was determined. The results showed that the cutting speed is the most significant parameter affecting the surface roughness whereas the influence of the assist gas pressure can be neglected. It was observed, however, that interaction effects have predominant influence over the main effects on the surface roughness.

  20. Parameter optimization in milling of glass fiber reinforced plastic (GFRP) using DOE-Taguchi method.

    Science.gov (United States)

    Ghalme, Sachin; Mankar, Ankush; Bhalerao, Y J

    2016-01-01

    Optimization of machining parameters is essential for improving expected outcome of any machining operation. The aim of this work is to find out optimum values of machining parameters to achieve minimal surface roughness during milling operation of GFRP. In this machining operation speed, depth of cut and feed rate are considered as parameters affecting surface roughness and Design of Experiment (DOE)-Taguchi method tool is used to plan experiments and analyse results. Analysis of experimental results presents optimum values of these three parameters to achieve minimal surface roughness with speed as a major contributing factor. Speed-200 rpm, depth of cut-1.2 mm and feed-40 mm/min are an optimal combination of machining parameter to produce minimal surface roughness during milling of GFRP.

  1. Application of Differential Evolutionary Optimization Methodology for Parameter Structure Identification in Groundwater Modeling

    Science.gov (United States)

    Chiu, Y.; Nishikawa, T.

    2013-12-01

    With the increasing complexity of parameter-structure identification (PSI) in groundwater modeling, there is a need for robust, fast, and accurate optimizers in the groundwater-hydrology field. For this work, PSI is defined as identifying parameter dimension, structure, and value. In this study, Voronoi tessellation and differential evolution (DE) are used to solve the optimal PSI problem. Voronoi tessellation is used for automatic parameterization, whereby stepwise regression and the error covariance matrix are used to determine the optimal parameter dimension. DE is a novel global optimizer that can be used to solve nonlinear, nondifferentiable, and multimodal optimization problems. It can be viewed as an improved version of genetic algorithms and employs a simple cycle of mutation, crossover, and selection operations. DE is used to estimate the optimal parameter structure and its associated values. A synthetic numerical experiment of continuous hydraulic conductivity distribution was conducted to demonstrate the proposed methodology. The results indicate that DE can identify the global optimum effectively and efficiently. A sensitivity analysis of the control parameters (i.e., the population size, mutation scaling factor, crossover rate, and mutation schemes) was performed to examine their influence on the objective function. The proposed DE was then applied to solve a complex parameter-estimation problem for a small desert groundwater basin in Southern California. Hydraulic conductivity, specific yield, specific storage, fault conductance, and recharge components were estimated simultaneously. Comparison of DE and a traditional gradient-based approach (PEST) shows DE to be more robust and efficient. The results of this work not only provide an alternative for PSI in groundwater models, but also extend DE applications towards solving complex, regional-scale water management optimization problems.

  2. 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

    2017-12-01

    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.

  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. 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.

  5. Development and Application of a Tool for Optimizing Composite Matrix Viscoplastic Material Parameters

    Science.gov (United States)

    Murthy, Pappu L. N.; Naghipour Ghezeljeh, Paria; Bednarcyk, Brett A.

    2018-01-01

    This document describes a recently developed analysis tool that enhances the resident capabilities of the Micromechanics Analysis Code with the Generalized Method of Cells (MAC/GMC) and its application. MAC/GMC is a composite material and laminate analysis software package developed at NASA Glenn Research Center. The primary focus of the current effort is to provide a graphical user interface (GUI) capability that helps users optimize highly nonlinear viscoplastic constitutive law parameters by fitting experimentally observed/measured stress-strain responses under various thermo-mechanical conditions for braided composites. The tool has been developed utilizing the MATrix LABoratory (MATLAB) (The Mathworks, Inc., Natick, MA) programming language. Illustrative examples shown are for a specific braided composite system wherein the matrix viscoplastic behavior is represented by a constitutive law described by seven parameters. The tool is general enough to fit any number of experimentally observed stress-strain responses of the material. The number of parameters to be optimized, as well as the importance given to each stress-strain response, are user choice. Three different optimization algorithms are included: (1) Optimization based on gradient method, (2) Genetic algorithm (GA) based optimization and (3) Particle Swarm Optimization (PSO). The user can mix and match the three algorithms. For example, one can start optimization with either 2 or 3 and then use the optimized solution to further fine tune with approach 1. The secondary focus of this paper is to demonstrate the application of this tool to optimize/calibrate parameters for a nonlinear viscoplastic matrix to predict stress-strain curves (for constituent and composite levels) at different rates, temperatures and/or loading conditions utilizing the Generalized Method of Cells. After preliminary validation of the tool through comparison with experimental results, a detailed virtual parametric study is

  6. An automated analysis workflow for optimization of force-field parameters using neutron scattering data

    Energy Technology Data Exchange (ETDEWEB)

    Lynch, Vickie E.; Borreguero, Jose M. [Neutron Data Analysis & Visualization Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Bhowmik, Debsindhu [Computational Sciences & Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Ganesh, Panchapakesan; Sumpter, Bobby G. [Center for Nanophase Material Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Computational Sciences & Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Proffen, Thomas E. [Neutron Data Analysis & Visualization Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Goswami, Monojoy, E-mail: goswamim@ornl.gov [Center for Nanophase Material Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Computational Sciences & Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States)

    2017-07-01

    Graphical abstract: - Highlights: • An automated workflow to optimize force-field parameters. • Used the workflow to optimize force-field parameter for a system containing nanodiamond and tRNA. • The mechanism relies on molecular dynamics simulation and neutron scattering experimental data. • The workflow can be generalized to any other experimental and simulation techniques. - Abstract: Large-scale simulations and data analysis are often required to explain neutron scattering experiments to establish a connection between the fundamental physics at the nanoscale and data probed by neutrons. However, to perform simulations at experimental conditions it is critical to use correct force-field (FF) parameters which are unfortunately not available for most complex experimental systems. In this work, we have developed a workflow optimization technique to provide optimized FF parameters by comparing molecular dynamics (MD) to neutron scattering data. We describe the workflow in detail by using an example system consisting of tRNA and hydrophilic nanodiamonds in a deuterated water (D{sub 2}O) environment. Quasi-elastic neutron scattering (QENS) data show a faster motion of the tRNA in the presence of nanodiamond than without the ND. To compare the QENS and MD results quantitatively, a proper choice of FF parameters is necessary. We use an efficient workflow to optimize the FF parameters between the hydrophilic nanodiamond and water by comparing to the QENS data. Our results show that we can obtain accurate FF parameters by using this technique. The workflow can be generalized to other types of neutron data for FF optimization, such as vibrational spectroscopy and spin echo.

  7. Optimization of Allelic Combinations Controlling Parameters of a Peach Quality Model.

    Science.gov (United States)

    Quilot-Turion, Bénédicte; Génard, Michel; Valsesia, Pierre; Memmah, Mohamed-Mahmoud

    2016-01-01

    Process-based models are effective tools to predict the phenotype of an individual in different growing conditions. Combined with a quantitative trait locus (QTL) mapping approach, it is then possible to predict the behavior of individuals with any combinations of alleles. However the number of simulations to explore the realm of possibilities may become infinite. Therefore, the use of an efficient optimization algorithm to intelligently explore the search space becomes imperative. The optimization algorithm has to solve a multi-objective problem, since the phenotypes of interest are usually a complex of traits, to identify the individuals with best tradeoffs between those traits. In this study we proposed to unroll such a combined approach in the case of peach fruit quality described through three targeted traits, using a process-based model with seven parameters controlled by QTL. We compared a current approach based on the optimization of the values of the parameters with a more evolved way to proceed which consists in the direct optimization of the alleles controlling the parameters. The optimization algorithm has been adapted to deal with both continuous and combinatorial problems. We compared the spaces of parameters obtained with different tactics and the phenotype of the individuals resulting from random simulations and optimization in these spaces. The use of a genetic model enabled the restriction of the dimension of the parameter space toward more feasible combinations of parameter values, reproducing relationships between parameters as observed in a real progeny. The results of this study demonstrated the potential of such an approach to refine the solutions toward more realistic ideotypes. Perspectives of improvement are discussed.

  8. A local segmentation parameter optimization approach for mapping heterogeneous urban environments using VHR imagery

    Science.gov (United States)

    Grippa, Tais; Georganos, Stefanos; Lennert, Moritz; Vanhuysse, Sabine; Wolff, Eléonore

    2017-10-01

    Mapping large heterogeneous urban areas using object-based image analysis (OBIA) remains challenging, especially with respect to the segmentation process. This could be explained both by the complex arrangement of heterogeneous land-cover classes and by the high diversity of urban patterns which can be encountered throughout the scene. In this context, using a single segmentation parameter to obtain satisfying segmentation results for the whole scene can be impossible. Nonetheless, it is possible to subdivide the whole city into smaller local zones, rather homogeneous according to their urban pattern. These zones can then be used to optimize the segmentation parameter locally, instead of using the whole image or a single representative spatial subset. This paper assesses the contribution of a local approach for the optimization of segmentation parameter compared to a global approach. Ouagadougou, located in sub-Saharan Africa, is used as case studies. First, the whole scene is segmented using a single globally optimized segmentation parameter. Second, the city is subdivided into 283 local zones, homogeneous in terms of building size and building density. Each local zone is then segmented using a locally optimized segmentation parameter. Unsupervised segmentation parameter optimization (USPO), relying on an optimization function which tends to maximize both intra-object homogeneity and inter-object heterogeneity, is used to select the segmentation parameter automatically for both approaches. Finally, a land-use/land-cover classification is performed using the Random Forest (RF) classifier. The results reveal that the local approach outperforms the global one, especially by limiting confusions between buildings and their bare-soil neighbors.

  9. Evaluation and optimization of footwear comfort parameters using finite element analysis and a discrete optimization algorithm

    Science.gov (United States)

    Papagiannis, P.; Azariadis, P.; Papanikos, P.

    2017-10-01

    Footwear is subject to bending and torsion deformations that affect comfort perception. Following review of Finite Element Analysis studies of sole rigidity and comfort, a three-dimensional, linear multi-material finite element sole model for quasi-static bending and torsion simulation, overcoming boundary and optimisation limitations, is described. Common footwear materials properties and boundary conditions from gait biomechanics are used. The use of normalised strain energy for product benchmarking is demonstrated along with comfort level determination through strain energy density stratification. Sensitivity of strain energy against material thickness is greater for bending than for torsion, with results of both deformations showing positive correlation. Optimization for a targeted performance level and given layer thickness is demonstrated with bending simulations sufficing for overall comfort assessment. An algorithm for comfort optimization w.r.t. bending is presented, based on a discrete approach with thickness values set in line with practical manufacturing accuracy. This work illustrates the potential of the developed finite element analysis applications to offer viable and proven aids to modern footwear sole design assessment and optimization.

  10. 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.

  11. Optimal parameters for the Green-Ampt infiltration model under rainfall conditions

    Directory of Open Access Journals (Sweden)

    Chen Li

    2015-06-01

    Full Text Available The Green-Ampt (GA model is widely used in hydrologic studies as a simple, physically-based method to estimate infiltration processes. The accuracy of the model for applications under rainfall conditions (as opposed to initially ponded situations has not been studied extensively. We compared calculated rainfall infiltration results for various soils obtained using existing GA parameterizations with those obtained by solving the Richards equation for variably saturated flow. Results provided an overview of GA model performance evaluated by means of a root-meansquare- error-based objective function across a large region in GA parameter space as compared to the Richards equation, which showed a need for seeking optimal GA parameters. Subsequent analysis enabled the identification of optimal GA parameters that provided a close fit with the Richards equation. The optimal parameters were found to substantially outperform the standard theoretical parameters, thus improving the utility and accuracy of the GA model for infiltration simulations under rainfall conditions. A sensitivity analyses indicated that the optimal parameters may change for some rainfall scenarios, but are relatively stable for high-intensity rainfall events.

  12. 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).

  13. Economic Analysis about the Solid Waste Quantities and Optimal Hauling Distance to Install Transfer Stations in Colombia

    National Research Council Canada - National Science Library

    Perdomo, Jorge; Ramírez, Juan

    2011-01-01

    The main objective of this study is to develop an economic analysis estimating the solid waste quantities and optimal hauling distance to install transfer stations in Colombia, according to landfill location...

  14. 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.

  15. Parameter estimation of fractional-order chaotic systems by using quantum parallel particle swarm optimization algorithm.

    Directory of Open Access Journals (Sweden)

    Yu Huang

    Full Text Available Parameter estimation for fractional-order chaotic systems is an important issue in fractional-order chaotic control and synchronization and could be essentially formulated as a multidimensional optimization problem. A novel algorithm called quantum parallel particle swarm optimization (QPPSO is proposed to solve the parameter estimation for fractional-order chaotic systems. The parallel characteristic of quantum computing is used in QPPSO. This characteristic increases the calculation of each generation exponentially. The behavior of particles in quantum space is restrained by the quantum evolution equation, which consists of the current rotation angle, individual optimal quantum rotation angle, and global optimal quantum rotation angle. Numerical simulation based on several typical fractional-order systems and comparisons with some typical existing algorithms show the effectiveness and efficiency of the proposed algorithm.

  16. Parameter estimation of fractional-order chaotic systems by using quantum parallel particle swarm optimization algorithm.

    Science.gov (United States)

    Huang, Yu; Guo, Feng; Li, Yongling; Liu, Yufeng

    2015-01-01

    Parameter estimation for fractional-order chaotic systems is an important issue in fractional-order chaotic control and synchronization and could be essentially formulated as a multidimensional optimization problem. A novel algorithm called quantum parallel particle swarm optimization (QPPSO) is proposed to solve the parameter estimation for fractional-order chaotic systems. The parallel characteristic of quantum computing is used in QPPSO. This characteristic increases the calculation of each generation exponentially. The behavior of particles in quantum space is restrained by the quantum evolution equation, which consists of the current rotation angle, individual optimal quantum rotation angle, and global optimal quantum rotation angle. Numerical simulation based on several typical fractional-order systems and comparisons with some typical existing algorithms show the effectiveness and efficiency of the proposed algorithm.

  17. Optimization of Processing Parameters for Lettuce Vacuum Osmotic Dehydration Using Response Surface Methodology

    Directory of Open Access Journals (Sweden)

    Yuan Yuejin

    2018-03-01

    Full Text Available In order to obtain the optimal technological parameters of lettuce vacuum osmotic dehydration, the effects of osmotic temperature, slice thickness, sucrose concentration, and vacuum degree on the vacuum osmotic dehydration were explored. The lettuce water loss rate and solid gain rate decreased with the increase of slice thickness and vacuum degree, and increased with the increase of sucrose concentration and osmotic temperature. Response surface methodology was applied to analyze the influence of the four influential factors on the evaluated parameters and the optimization of lettuce vacuum osmotic dehydration was studied. The results indicated that, within the experimental scope, the optimized technological parameters of lettuce vacuum osmotic dehydration are the temperature of 28°C, the slice thickness of 2 mm, sucrose concentration of 47%, the vacuum degree of 22 kPa, and the water loss rate and solid gain rate are 72.16% and 11.82%, respectively.

  18. Case study: Optimizing fault model input parameters using bio-inspired algorithms

    Science.gov (United States)

    Plucar, Jan; Grunt, Onřej; Zelinka, Ivan

    2017-07-01

    We present a case study that demonstrates a bio-inspired approach in the process of finding optimal parameters for GSM fault model. This model is constructed using Petri Nets approach it represents dynamic model of GSM network environment in the suburban areas of Ostrava city (Czech Republic). We have been faced with a task of finding optimal parameters for an application that requires high amount of data transfers between the application itself and secure servers located in datacenter. In order to find the optimal set of parameters we employ bio-inspired algorithms such as Differential Evolution (DE) or Self Organizing Migrating Algorithm (SOMA). In this paper we present use of these algorithms, compare results and judge their performance in fault probability mitigation.

  19. Numerical Parameter Optimization of the Ignition and Growth Model for HMX Based Plastic Bonded Explosives

    Science.gov (United States)

    Gambino, James; Tarver, Craig; Springer, H. Keo; White, Bradley; Fried, Laurence

    2017-06-01

    We present a novel method for optimizing parameters of the Ignition and Growth reactive flow (I&G) model for high explosives. The I&G model can yield accurate predictions of experimental observations. However, calibrating the model is a time-consuming task especially with multiple experiments. In this study, we couple the differential evolution global optimization algorithm to simulations of shock initiation experiments in the multi-physics code ALE3D. We develop parameter sets for HMX based explosives LX-07 and LX-10. The optimization finds the I&G model parameters that globally minimize the difference between calculated and experimental shock time of arrival at embedded pressure gauges. This work was performed under the auspices of the U.S. DOE by LLNL under contract DE-AC52-07NA27344. LLNS, LLC LLNL-ABS- 724898.

  20. Development of Hybrid Model for Estimating Construction Waste for Multifamily Residential Buildings Using Artificial Neural Networks and Ant Colony Optimization

    Directory of Open Access Journals (Sweden)

    Dongoun Lee

    2016-09-01

    Full Text Available Due to the increasing costs of construction waste disposal, an accurate estimation of the amount of construction waste is a key factor in a project’s success. Korea has been burdened by increasing construction waste as a consequence of the growing number of construction projects and a lack of construction waste management (CWM strategies. One of the problems associated with predicting the amount of waste is that there are no suitable estimation strategies currently available. Therefore, we developed a hybrid estimation model to predict the quantity and cost of waste in the early stage of construction. The proposed approach can be used to address cost overruns and improve CWM in the subsequent stages of construction. The proposed hybrid model uses artificial neural networks (ANNs and ant colony optimization (ACO. It is expected to provide an accurate waste estimate by applying historical data from multifamily residential buildings.

  1. Optimization of the Municipal Waste Collection Route Based on the Method of the Minimum Pairing

    Directory of Open Access Journals (Sweden)

    Michal Petřík

    2016-01-01

    Full Text Available In the present article is shown the use of Maple program for processing of data describing the position of municipal waste sources and topology of collecting area. The data are further processed through the use of graph theory algorithms, which enable creation of collection round proposal. In this case study is described method of waste pick-up solution in a certain village of approx. 1,600 inhabitants and built-up area of approx. 30 hectares. Village has approx. 11.5 kilometers of ride able routes, with approx. 1 kilometer without waste source. The first part shows topology of the village in light of location of waste sources and capacity of the routes. In the second part are topological data converted into data that can be processed by use of the Graph Theory and the correspondent graph is shown. Optimizing collection route in a certain graph means to find the Euler circle. However, this circle can be constructed only on condition that all the vertices of the graph are of an even degree. Practically this means that is necessary to introduce auxiliary edges – paths that will be passed twice. These paths will connect vertices with odd values. The optimal solution then requires that the total length of the inserted edges was minimal possible, which corresponds to the minimum pairing method. As it is a problem of exponential complexity, it is necessary to make some simplifications. These simplifications are depicted graphically and the results are displayed in the conclusion. The resulting graph with embedded auxiliary edges can be used as a basic decision making material for creation of real collection round that respects local limitations such as one way streets or streets where is the waste collection is not possible from both sides at the same time.

  2. Parameter optimization and sensitivity analysis for large kinetic models using a real-coded genetic algorithm.

    Science.gov (United States)

    Tohsato, Yukako; Ikuta, Kunihiko; Shionoya, Akitaka; Mazaki, Yusaku; Ito, Masahiro

    2013-04-10

    Dynamic modeling is a powerful tool for predicting changes in metabolic regulation. However, a large number of input parameters, including kinetic constants and initial metabolite concentrations, are required to construct a kinetic model. Therefore, it is important not only to optimize the kinetic parameters, but also to investigate the effects of their perturbations on the overall system. We investigated the efficiency of the use of a real-coded genetic algorithm (RCGA) for parameter optimization and sensitivity analysis in the case of a large kinetic model involving glycolysis and the pentose phosphate pathway in Escherichia coli K-12. Sensitivity analysis of the kinetic model using an RCGA demonstrated that the input parameter values had different effects on model outputs. The results showed highly influential parameters in the model and their allowable ranges for maintaining metabolite-level stability. Furthermore, it was revealed that changes in these influential parameters may complement one another. This study presents an efficient approach based on the use of an RCGA for optimizing and analyzing parameters in large kinetic models. Copyright © 2012 Elsevier B.V. All rights reserved.

  3. PI Stabilization for Congestion Control of AQM Routers with Tuning Parameter Optimization

    Directory of Open Access Journals (Sweden)

    S. Chebli

    2016-09-01

    Full Text Available In this paper, we consider the problem of stabilizing network using a new proportional- integral (PI based congestion controller in active queue management (AQM router; with appropriate model approximation in the first order delay systems, we seek a stability region of the controller by using the Hermite- Biehler theorem, which isapplicable to quasipolynomials. A Genetic Algorithm technique is employed to derive optimal or near optimal PI controller parameters.

  4. Optimization Of Parameters Of Heating Elements For Floor Panel Of Piglets Resting Places

    OpenAIRE

    Zagorska, V.; Iljins, U.

    2015-01-01

    The article deals with problem solving of mathematical physics using the method of separation of variables optimizing heating element – optimizing water tube parameters (tube material, radius, insulation thickness, choosing appropriate surrounding environment). For ensuring piglets comfort, concrete floor panels heated by electric current or hot water are used. If an electro-heated cable in the panels body is placed, than amount of heat conducted from the cable is the same along all the lengt...

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

    Science.gov (United States)

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

    2014-04-01

    To establish a new mathematical framework for radiotherapy treatment optimization with voxel-dependent optimization parameters. 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. 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 allowing for the

  6. 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.

  7. Geographic information system-based healthcare waste management planning for treatment site location and optimal transportation routeing.

    Science.gov (United States)

    Shanmugasundaram, Jothiganesh; Soulalay, Vongdeuane; Chettiyappan, Visvanathan

    2012-06-01

    In Lao People's Democratic Republic (Lao PDR), a growth of healthcare centres, and the environmental hazards and public health risks typically accompanying them, increased the need for healthcare waste (HCW) management planning. An effective planning of an HCW management system including components such as the treatment plant siting and an optimized routeing system for collection and transportation of waste is deemed important. National government offices at developing countries often lack the proper tools and methodologies because of the high costs usually associated with them. However, this study attempts to demonstrate the use of an inexpensive GIS modelling tool for healthcare waste management in the country. Two areas were designed for this study on HCW management, including: (a) locating centralized treatment plants and designing optimum travel routes for waste collection from nearby healthcare facilities; and (b) utilizing existing hospital incinerators and designing optimum routes for collecting waste from nearby healthcare facilities. Spatial analysis paved the way to understand the spatial distribution of healthcare wastes and to identify hotspots of higher waste generating locations. Optimal route models were designed for collecting and transporting HCW to treatment plants, which also highlights constraints in collecting and transporting waste for treatment and disposal. The proposed model can be used as a decision support tool for the efficient management of hospital wastes by government healthcare waste management authorities and hospitals.

  8. 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.

  9. 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

    2017-05-01

    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

  10. Determination of Optimized Parameters for the Flexible Operation of a Biomass-Fueled, Microscale Externally Fired Gas Turbine (EFGT

    Directory of Open Access Journals (Sweden)

    Mathhar Bdour

    2016-10-01

    Full Text Available Biomass as a source of renewable energy is a promising solution for current problems in energy supply. Olive waste is considered as an interesting option, especially for Mediterranean countries. Within this paper, a microscale externally fired gas turbine (EFGT technology is presented as a decentralized power plant, within the range of 15 kWth, based on olive residues. It was modeled by Aspen Plus 8.6 software to provide a sufficient technical study for such a plant. Optimized parameters for pressure ratio and turbine air-mass flow have been mapped for several loads to provide information for process control. For all cases, mechanical output, efficiency curves, and back-work ratio have been calculated. Using this information, typical plant sizes and an example of power production are discussed. Additionally, achievable energy production from olive waste is estimated on the basis of this data. The results of this study show that such a plant has an electrical efficiency of 5%–17%. This variation is due to the examination being performed under several combustion temperatures, actual load, heat exchanger temperatures, and heat transfer efficiency. A cost estimation of the discussed system showed an estimated capital cost of 33,800 to 65,300 € for a 15 kWth system.

  11. Iterative optimization algorithm with parameter estimation for the ambulance location problem.

    Science.gov (United States)

    Kim, Sun Hoon; Lee, Young Hoon

    2016-12-01

    The emergency vehicle location problem to determine the number of ambulance vehicles and their locations satisfying a required reliability level is investigated in this study. This is a complex nonlinear issue involving critical decision making that has inherent stochastic characteristics. This paper studies an iterative optimization algorithm with parameter estimation to solve the emergency vehicle location problem. In the suggested algorithm, a linear model determines the locations of ambulances, while a hypercube simulation is used to estimate and provide parameters regarding ambulance locations. First, we suggest an iterative hypercube optimization algorithm in which interaction parameters and rules for the hypercube and optimization are identified. The interaction rules employed in this study enable our algorithm to always find the locations of ambulances satisfying the reliability requirement. We also propose an iterative simulation optimization algorithm in which the hypercube method is replaced by a simulation, to achieve computational efficiency. The computational experiments show that the iterative simulation optimization algorithm performs equivalently to the iterative hypercube optimization. The suggested algorithms are found to outperform existing algorithms suggested in the literature.

  12. An approach to design controllers for MIMO fractional-order plants based on parameter optimization algorithm.

    Science.gov (United States)

    Xue, Dingyü; Li, Tingxue

    2017-04-27

    The parameter optimization method for multivariable systems is extended to the controller design problems for multiple input multiple output (MIMO) square fractional-order plants. The algorithm can be applied to search for the optimal parameters of integer-order controllers for fractional-order plants with or without time delays. Two examples are given to present the controller design procedures for MIMO fractional-order systems. Simulation studies show that the integer-order controllers designed are robust to plant gain variations. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  13. Parameter Optimization of Single-Diode Model of Photovoltaic Cell Using Memetic Algorithm

    Directory of Open Access Journals (Sweden)

    Yourim Yoon

    2015-01-01

    Full Text Available This study proposes a memetic approach for optimally determining the parameter values of single-diode-equivalent solar cell model. The memetic algorithm, which combines metaheuristic and gradient-based techniques, has the merit of good performance in both global and local searches. First, 10 single algorithms were considered including genetic algorithm, simulated annealing, particle swarm optimization, harmony search, differential evolution, cuckoo search, least squares method, and pattern search; then their final solutions were used as initial vectors for generalized reduced gradient technique. From this memetic approach, we could further improve the accuracy of the estimated solar cell parameters when compared with single algorithm approaches.

  14. An automated analysis workflow for optimization of force-field parameters using neutron scattering data

    Science.gov (United States)

    Lynch, Vickie E.; Borreguero, Jose M.; Bhowmik, Debsindhu; Ganesh, Panchapakesan; Sumpter, Bobby G.; Proffen, Thomas E.; Goswami, Monojoy

    2017-07-01

    Large-scale simulations and data analysis are often required to explain neutron scattering experiments to establish a connection between the fundamental physics at the nanoscale and data probed by neutrons. However, to perform simulations at experimental conditions it is critical to use correct force-field (FF) parameters which are unfortunately not available for most complex experimental systems. In this work, we have developed a workflow optimization technique to provide optimized FF parameters by comparing molecular dynamics (MD) to neutron scattering data. We describe the workflow in detail by using an example system consisting of tRNA and hydrophilic nanodiamonds in a deuterated water (D2O) environment. Quasi-elastic neutron scattering (QENS) data show a faster motion of the tRNA in the presence of nanodiamond than without the ND. To compare the QENS and MD results quantitatively, a proper choice of FF parameters is necessary. We use an efficient workflow to optimize the FF parameters between the hydrophilic nanodiamond and water by comparing to the QENS data. Our results show that we can obtain accurate FF parameters by using this technique. The workflow can be generalized to other types of neutron data for FF optimization, such as vibrational spectroscopy and spin echo.

  15. A Particle Swarm Optimization of Natural Ventilation Parameters in a Greenhouse with Continuous Roof Vents

    Directory of Open Access Journals (Sweden)

    Abdelhafid HASNI

    2009-03-01

    Full Text Available Although natural ventilation plays an important role in the affecting greenhouse climate, as defined by temperature, humidity and CO2 concentration, particularly in Mediterranean countries, little information and data are presently available on full-scale greenhouse ventilation mechanisms. In this paper, we present a new method for selecting the parameters based on a particle swarm optimization (PSO algorithm which optimize the choice of parameters by minimizing a cost function. The simulator was based on a published model with some minor modifications as we were interested in the parameter of ventilation. The function is defined by a reduced model that could be used to simulate and predict the greenhouse environment, as well as the tuning methods to compute their parameters. This study focuses on the dynamic behavior of the inside air temperature and humidity during ventilation. Our approach is validated by comparison with some experimental results. Various experimental techniques were used to make full-scale measurements of the air exchange rate in a 400 m2 plastic greenhouse. The model which we propose based on natural ventilation parameters optimized by a particle swarm optimization was compared with the measurements results.

  16. A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors

    Science.gov (United States)

    Zhang, Jilin; Tu, Hangdi; Ren, Yongjian; Wan, Jian; Zhou, Li; Li, Mingwei; Wang, Jue; Yu, Lifeng; Zhao, Chang; Zhang, Lei

    2017-01-01

    In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors. PMID:28934163

  17. A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors

    Directory of Open Access Journals (Sweden)

    Jilin Zhang

    2017-09-01

    Full Text Available In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT. Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP, which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS. This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors.

  18. A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors.

    Science.gov (United States)

    Zhang, Jilin; Tu, Hangdi; Ren, Yongjian; Wan, Jian; Zhou, Li; Li, Mingwei; Wang, Jue; Yu, Lifeng; Zhao, Chang; Zhang, Lei

    2017-09-21

    In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors.

  19. Determining Optimal Parameters for Brown Dwarf Spectral Extraction using the aXe Pipeline

    Science.gov (United States)

    Davis, Jonathan D.; Radigan, Jacqueline

    2017-06-01

    This research seeks to find optimal extraction parameters for brown dwarf slitless spectra obtained using the Wide Field Camera 3 (WFC3), with the G141 grism on the Hubble Space Telescope. We have used the STScI aXe pipeline to extract spectral time series for three brown dwarf targets from HST program GO-13299 (PI: Radigan). These targets include two L/T transition dwarfs 2MASS-J16291840+033537 and SDSS-J075840.33+324723.4, and one L-dwarf 2MASS-J11263991-5003550. The parameters explored in this study include the spectral extraction width, the type of background subtraction, and the pixel weighting of the extraction. We also explore how target brightness effects the optimal reduction parameters. Scatter within the spectral time series are used to draw conclusions regarding the relative goodness of different sets of reduction parameters.

  20. Parameter estimation of a pulp digester model with derivative-free optimization strategies

    Science.gov (United States)

    Seiça, João C.; Romanenko, Andrey; Fernandes, Florbela P.; Santos, Lino O.; Fernandes, Natércia C. P.

    2017-07-01

    The work concerns the parameter estimation in the context of the mechanistic modelling of a pulp digester. The problem is cast as a box bounded nonlinear global optimization problem in order to minimize the mismatch between the model outputs with the experimental data observed at a real pulp and paper plant. MCSFilter and Simulated Annealing global optimization methods were used to solve the optimization problem. While the former took longer to converge to the global minimum, the latter terminated faster at a significantly higher value of the objective function and, thus, failed to find the global solution.

  1. A summary of the sources of input parameter values for the Waste Isolation Pilot Plant final porosity surface calculations

    Energy Technology Data Exchange (ETDEWEB)

    Butcher, B.M.

    1997-08-01

    A summary of the input parameter values used in final predictions of closure and waste densification in the Waste Isolation Pilot Plant disposal room is presented, along with supporting references. These predictions are referred to as the final porosity surface data and will be used for WIPP performance calculations supporting the Compliance Certification Application to be submitted to the U.S. Environmental Protection Agency. The report includes tables and list all of the input parameter values, references citing their source, and in some cases references to more complete descriptions of considerations leading to the selection of values.

  2. DOUBLE SHELL TANK (DST) INTEGRITY PROJECT HIGH LEVEL WASTE CHEMISTRY OPTIMIZATION

    Energy Technology Data Exchange (ETDEWEB)

    WASHENFELDER DJ

    2008-01-22

    The U.S. Department of Energy's Office (DOE) of River Protection (ORP) has a continuing program for chemical optimization to better characterize corrosion behavior of High-Level Waste (HLW). The DOE controls the chemistry in its HLW to minimize the propensity of localized corrosion, such as pitting, and stress corrosion cracking (SCC) in nitrate-containing solutions. By improving the control of localized corrosion and SCC, the ORP can increase the life of the Double-Shell Tank (DST) carbon steel structural components and reduce overall mission costs. The carbon steel tanks at the Hanford Site are critical to the mission of safely managing stored HLW until it can be treated for disposal. The DOE has historically used additions of sodium hydroxide to retard corrosion processes in HLW tanks. This also increases the amount of waste to be treated. The reactions with carbon dioxide from the air and solid chemical species in the tank continually deplete the hydroxide ion concentration, which then requires continued additions. The DOE can reduce overall costs for caustic addition and treatment of waste, and more effectively utilize waste storage capacity by minimizing these chemical additions. Hydroxide addition is a means to control localized and stress corrosion cracking in carbon steel by providing a passive environment. The exact mechanism that causes nitrate to drive the corrosion process is not yet clear. The SCC is less of a concern in the newer stress relieved double shell tanks due to reduced residual stress. The optimization of waste chemistry will further reduce the propensity for SCC. The corrosion testing performed to optimize waste chemistry included cyclic potentiodynamic volarization studies. slow strain rate tests. and stress intensity factor/crack growth rate determinations. Laboratory experimental evidence suggests that nitrite is a highly effective:inhibitor for pitting and SCC in alkaline nitrate environments. Revision of the corrosion control

  3. Strain selection and medium optimization for glucoamylase production from industrial potato waste by Aspergillus niger.

    Science.gov (United States)

    Izmirlioglu, Gulten; Demirci, Ali

    2016-06-01

    Glucoamylase is one of the most common enzymes used in the food industry to break down starch into its monomers. Glucoamylase production and its activity are highly dependent on medium composition. Starch is well known as a glucoamylase inducer, and utilization of industrial starchy potato waste is an inexpensive way of improving glucoamylase production. Since glucoamylase production is highly dependent on medium composition, in this study medium optimization for glucoamylase production was considered to enhance glucoamylase activity. Among the evaluated microbial species, Aspergillus niger van Tieghem was found to be the best glucoamylase-producing fungus. The Plackett-Burman design was used to screen various medium ingredients, and malt extract, FeSO4 .7H2 O and CaCl2 ·2H2 O were found to have significant effects on glucoamylase production. Finally, malt extract, FeSO4 .7H2 O and CaCl2 .2H2 O were optimized by using a central composite design of response surface methodology. The results showed that the optimal medium composition for A. niger van Tieghem was 50 g L(-1) industrial waste potato mash supplemented with 51.82 g L(-1) malt extract, 9.27 g L(-1) CaCl2 ·2H2 O and 0.50 g L(-1) FeSO4 .7H2 O. At the end of optimization, glucoamylase activity and glucose production were improved 126% and 98% compared to only industrial waste potato mash basal medium; 274.4 U mL(-1) glucoamylase activity and 41.7 g L(-1) glucose levels were achieved, respectively. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

  4. Effects of AV-delay optimization on hemodynamic parameters in patients with VDD pacemakers.

    Science.gov (United States)

    Krychtiuk, Konstantin A; Nürnberg, Michael; Volker, Romana; Pachinger, Linda; Jarai, Rudolf; Freynhofer, Matthias K; Wojta, Johann; Huber, Kurt; Weiss, Thomas W

    2014-05-01

    Atrioventricular (AV) delay optimization improves hemodynamics and clinical parameters in patients treated with cardiac resynchronization therapy and dual-chamber-pacemakers (PM). However, data on optimizing AV delay in patients treated with VDD-PMs are scarce. We, therefore, investigated the acute and chronic effects of AV delay optimization on hemodynamics in patients treated with VDD-PMs due to AV-conduction disturbances. In this prospective, single-center interventional trial, we included 64 patients (38 men, 26 women, median age: 77 (70-82) years) with implanted VDD-PM. AV-delay optimization was performed using a formula based on the surface electrocardiogram (ECG). Hemodynamic parameters (stroke volume (SV), cardiac output (CO), heart rate (HR), and blood pressure (BP)) were measured at baseline and follow-up after 3 months using impedance cardiography. Using an ECG formula for AV-delay optimization, the AV interval was decreased from 180 (180-180) to 75 (75-100) ms. At baseline, AV-delay optimization led to a significant increase of both SV (71.3 ± 15.8 vs. 55.3 ± 12.7 ml, p < 0.001, for optimized AV delay vs. nominal AV interval, respectively) and CO (5.1 ± 1.4 vs. 3.9 ± 1.0 l/min, p < 0.001), while HR and BP remained unchanged. At follow-up, the improvement in CO remained stable (4.9 ± 1.3 l/min, p = 0.09), while SV slightly, but significantly, decreased (to 65.1 ± 17.6, p < 0.01). AV-delay optimization in patients treated with VDD-PMs exhibits immediate beneficial effects on hemodynamic parameters that are sustained for 3 months.

  5. Technoeconomic Optimization of Waste Heat Driven Forward Osmosis for Flue Gas Desulfurization Wastewater Treatment

    Energy Technology Data Exchange (ETDEWEB)

    Gingerich, Daniel B [Carnegie Mellon Univ., Pittsburgh, PA (United States); Bartholomew, Timothy V [Carnegie Mellon Univ., Pittsburgh, PA (United States); Mauter, Meagan S [Carnegie Mellon Univ., Pittsburgh, PA (United States)

    2017-06-26

    With the Environmental Protection Agency’s recent Effluent Limitation Guidelines for Steam Electric Generators, power plants are having to install and operate new wastewater technologies. Many plants are evaluating desalination technologies as possible compliance options. However, the desalination technologies under review that can reduce wastewater volume or treat to a zero-liquid discharges standard have a significant energy penalty to the plant. Waste heat, available from the exhaust gas or cooling water from coal-fired power plants, offers an opportunity to drive wastewater treatment using thermal desalination technologies. One such technology is forward osmosis (FO). Forward osmosis utilizes an osmotic pressure gradient to passively pull water from a saline or wastewater stream across a semi-permeable membrane and into a more concentrated draw solution. This diluted draw solution is then fed into a distillation column, where the addition of low temperature waste heat can drive the separation to produce a reconcentrated draw solution and treated water for internal plant reuse. The use of low-temperature waste heat decouples water treatment from electricity production and eliminates the link between reducing water pollution and increasing air emissions from auxiliary electricity generation. In order to evaluate the feasibility of waste heat driven FO, we first build a model of an FO system for flue gas desulfurization (FGD) wastewater treatment at coal-fired power plants. This model includes the FO membrane module, the distillation column for draw solution recovery, and waste heat recovery from the exhaust gas. We then add a costing model to account for capital and operating costs of the forward osmosis system. We use this techno-economic model to optimize waste heat driven FO for the treatment of FGD wastewater. We apply this model to three case studies: the National Energy Technology Laboratory (NETL) 550 MW model coal fired power plant without carbon

  6. Parameters Optimization for Operational Storm Surge/Tide Forecast Model using a Genetic Algorithm

    Science.gov (United States)

    Lee, W.; You, S.; Ryoo, S.; Global Environment System Research Laboratory

    2010-12-01

    Typhoons generated in northwestern Pacific Ocean annually affect the Korean Peninsula and storm surges generated by strong low pressure and sea winds often cause serious damage to property in the coastal region. To predict storm surges, a lot of researches have been conducted by using numerical models for many years. Various parameters used for calculation of physics process are used in numerical models based on laws of physics, but they are not accurate values. Because those parameters affect to the model performance, these uncertain values can sensitively operate results of the model. Therefore, optimization of these parameters used in numerical model is essential for accurate storm surge predictions. A genetic algorithm (GA) is recently used to estimate optimized values of these parameters. The GA is a stochastic exploration modeling natural phenomenon named genetic heritance and competition for survival. To realize breeding of species and selection, the groups which may be harmed are kept and use genetic operators such as inheritance, mutation, selection and crossover. In this study, we have improved operational storm surge/tide forecast model(STORM) of NIMR/KMA (National Institute of Meteorological Research/Korea Meteorological Administration) that covers 115E - 150E, 20N - 52N based on POM (Princeton Ocean Model) with 8km horizontal resolutions using the GA. Optimized values have been estimated about main 4 parameters which are bottom drag coefficient, background horizontal diffusivity coefficient, Smagoranski’s horizontal viscosity coefficient and sea level pressure scaling coefficient within STORM. These optimized parameters were estimated on typhoon MAEMI in 2003 and 9 typhoons which have affected to Korea peninsula from 2005 to 2007. The 4 estimated parameters were also used to compare one-month predictions in February and August 2008. During the 48h forecast time, the mean and median model accuracies improved by 25 and 51%, respectively.

  7. Parameter Estimation in Rainfall-Runoff Modelling Using Distributed Versions of Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Michala Jakubcová

    2015-01-01

    Full Text Available The presented paper provides the analysis of selected versions of the particle swarm optimization (PSO algorithm. The tested versions of the PSO were combined with the shuffling mechanism, which splits the model population into complexes and performs distributed PSO optimization. One of them is a new proposed PSO modification, APartW, which enhances the global exploration and local exploitation in the parametric space during the optimization process through the new updating mechanism applied on the PSO inertia weight. The performances of four selected PSO methods were tested on 11 benchmark optimization problems, which were prepared for the special session on single-objective real-parameter optimization CEC 2005. The results confirm that the tested new APartW PSO variant is comparable with other existing distributed PSO versions, AdaptW and LinTimeVarW. The distributed PSO versions were developed for finding the solution of inverse problems related to the estimation of parameters of hydrological model Bilan. The results of the case study, made on the selected set of 30 catchments obtained from MOPEX database, show that tested distributed PSO versions provide suitable estimates of Bilan model parameters and thus can be used for solving related inverse problems during the calibration process of studied water balance hydrological model.

  8. Effects of biochars produced from solid organic municipal waste on soil quality parameters

    Science.gov (United States)

    New, value-added uses for solid organic waste are needed for environmental and economic sustainability. Fortunately, value-added biochars can be produced from mixed organic solid waste, thereby addressing solid waste management issues, and enabling long-term carbon sequestration. We hypothesize that...

  9. 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.

  10. Cellular Neural Networks: A genetic algorithm for parameters optimization in artificial vision applications

    Energy Technology Data Exchange (ETDEWEB)

    Taraglio, S. [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dipt. Innovazione; Zanela, A. [Rome Univ. `La Sapienza` (Italy). Dipt. di Fisica

    1997-03-01

    An optimization method for some of the CNN`s (Cellular Neural Network) parameters, based on evolutionary strategies, is proposed. The new class of feedback template found is more effective in extracting features from the images that an autonomous vehicle acquires, than in the previous CNN`s literature.

  11. Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune

    The design of a measured program devoted to parameter identification of structural dynamic systems is considered, the design problem is formulated as an optimization problem due to minimize the total expected cost of the measurement program. All the calculations are based on a priori knowledge...

  12. Optimization of parameters on material removal rate in micro-WEDG ...

    African Journals Online (AJOL)

    In this work, an orthogonal array, signal to noise (S/N) ratio and Pareto analysis of variance (ANOVA) are employed to analyze the effect of the micro-WEDG parameters such as feed rate, capacitance and voltage on MRR. This paper focuses on the Taguchi technique for the optimization in micro-WEDG process to achieve ...

  13. APPLICATION OF EXCEL INFORMATION TECHNOLOGIES FOR SOLVING PROBLEMS ON OPTIMIZATION OF WIRE BRUSHING PARAMETERS

    Directory of Open Access Journals (Sweden)

    S. I. Romanchuk

    2010-01-01

    Full Text Available The paper considers an application of  Excel  information technologies for optimization of parameters concerning of wire brushing process  depending on the requirements to quality of parts’ surface and that ensures their required operational characteristics.

  14. Exploration of Genetic Programming Optimal Parameters for Feature Extraction from Remote Sensed Imagery

    Science.gov (United States)

    Gao, P.; Shetty, S.; Momm, H. G.

    2014-11-01

    Evolutionary computation is used for improved information extraction from high-resolution satellite imagery. The utilization of evolutionary computation is based on stochastic selection of input parameters often defined in a trial-and-error approach. However, exploration of optimal input parameters can yield improved candidate solutions while requiring reduced computation resources. In this study, the design and implementation of a system that investigates the optimal input parameters was researched in the problem of feature extraction from remotely sensed imagery. The two primary assessment criteria were the highest fitness value and the overall computational time. The parameters explored include the population size and the percentage and order of mutation and crossover. The proposed system has two major subsystems; (i) data preparation: the generation of random candidate solutions; and (ii) data processing: evolutionary process based on genetic programming, which is used to spectrally distinguish the features of interest from the remaining image background of remote sensed imagery. The results demonstrate that the optimal generation number is around 1500, the optimal percentage of mutation and crossover ranges from 35% to 40% and 5% to 0%, respectively. Based on our findings the sequence that yielded better results was mutation over crossover. These findings are conducive to improving the efficacy of utilizing genetic programming for feature extraction from remotely sensed imagery.

  15. Performance Evaluation and Parameter Optimization of Wavelength Division Multiplexing Networks with Importance Sampling Techniques

    NARCIS (Netherlands)

    Remondo Bueno, D.; Srinivasan, R.; Nicola, V.F.; van Etten, Wim; Tattje, H.E.P.

    1998-01-01

    In this paper new adaptive importance sampling techniques are applied to the performance evaluation and parameter optimization of wavelength division multiplexing (WDM) network impaired by crosstalk in an optical cross-connect. Worst-case analysis is carried out including all the beat noise terms

  16. Optimization of AVR Parameters of a Multi-machine Power System ...

    African Journals Online (AJOL)

    In this paper, a method for optimizing the parameters of Automatic Voltage Regulation (AVR) system installed on the generators of a multi-machine power system using Artificial Intelligence (AI) techniques is presented. Each AVR system is equipped with a PID (Proportional, Integral and Derivative) controller and a Power ...

  17. Optimization of Temperature Schedule Parameters on Heat Supply in Power-and-Heat Supply Systems

    Directory of Open Access Journals (Sweden)

    V. A. Sednin

    2009-01-01

    Full Text Available The paper considers problems concerning optimization of a temperature schedule in the district heating systems with steam-turbine thermal power stations having average initial steam parameters. It has been shown in the paper that upkeeping of an optimum network water temperature permits to increase an energy efficiency of heat supply due to additional systematic saving of fuel. 

  18. Optimal parameters of dental ultrasonic instrument diamond coating for enamel removal

    Directory of Open Access Journals (Sweden)

    Yunn-Shiuan Liao

    2015-06-01

    Conclusion: Protrusion, shape, and density of diamonds of an ultrasonic dental tip are significantly related to the MRR of enamel, and the optimal combination of these parameters is obtained. Knowledge of the importance of these variables will help in more effective use of the ultrasonic technology in dentistry.

  19. Optimal experiment design: Link between the concentration and the accuracy of estimation of aggregation parameters

    Science.gov (United States)

    Evstigneev, Vladislav P.; Pashkova, Irina S.; Kostjukov, Viktor V.; Hernandez Santiago, Adrian A.; Evstigneev, Maxim P.

    2016-11-01

    The principal condition for optimal experiment design, required for getting reasonable error for equilibrium aggregation constant, K, determination is obtained. This condition states that the selected concentration range for performing titration experiment should be inversely proportional to the expected value of K. As a consequence, the choice of physico-chemical methods for determination of aggregation parameters must obey this condition.

  20. Selecting Optimal Parameters of Random Linear Network Coding for Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Heide, Janus; Zhang, Qi; Fitzek, Frank

    2013-01-01

    This work studies how to select optimal code parameters of Random Linear Network Coding (RLNC) in Wireless Sensor Networks (WSNs). With Rateless Deluge [1] the authors proposed to apply Network Coding (NC) for Over-the-Air Programming (OAP) in WSNs, and demonstrated that with NC a significant...

  1. 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.

  2. Optimization of AVR Parameters of a Multi-machine Power System ...

    African Journals Online (AJOL)

    user1

    In this paper, a method for optimizing the parameters of Automatic Voltage Regulation (AVR) system installed on the generators of a multi-machine power system using Artificial Intelligence. (AI) techniques is presented. Each AVR system is equipped with a PID (Proportional, Integral and Derivative) controller and a Power ...

  3. A study on the machining parameters optimization of micro-end ...

    African Journals Online (AJOL)

    user

    piece and it is an important factor that greatly influences production rate and cost. MRR greatly vary with the change of cutting process parameters. This paper focuses the taguchi technique for the optimization in micro-end milling operation to achieve maximum metal removal rate (MRR) considering the spindle speed, feed ...

  4. Modified temporal approach to meta-optimizing an extended Kalman filter's parameters

    CSIR Research Space (South Africa)

    Salmon, BP

    2014-07-01

    Full Text Available meta-optimization approach has been proposed in the literature for setting the parameters of the non-linear Extended Kalman Filter (EKF) to rapidly and efficiently estimate the features for these triply modulated cosine functions using spatial...

  5. Optimization of municipal solid waste transportation by integrating GIS analysis, equation-based, and agent-based model.

    Science.gov (United States)

    Nguyen-Trong, Khanh; Nguyen-Thi-Ngoc, Anh; Nguyen-Ngoc, Doanh; Dinh-Thi-Hai, Van

    2017-01-01

    The amount of municipal solid waste (MSW) has been increasing steadily over the last decade by reason of population rising and waste generation rate. In most of the urban areas, disposal sites are usually located outside of the urban areas due to the scarcity of land. There is no fixed route map for transportation. The current waste collection and transportation are already overloaded arising from the lack of facilities and insufficient resources. In this paper, a model for optimizing municipal solid waste collection will be proposed. Firstly, the optimized plan is developed in a static context, and then it is integrated into a dynamic context using multi-agent based modelling and simulation. A case study related to Hagiang City, Vietnam, is presented to show the efficiency of the proposed model. From the optimized results, it has been found that the cost of the MSW collection is reduced by 11.3%. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. Q-Learning Multi-Objective Sequential Optimal Sensor Parameter Weights

    Directory of Open Access Journals (Sweden)

    Raquel Cohen

    2016-04-01

    Full Text Available The goal of our solution is to deliver trustworthy decision making analysis tools which evaluate situations and potential impacts of such decisions through acquired information and add efficiency for continuing mission operations and analyst information.We discuss the use of cooperation in modeling and simulation and show quantitative results for design choices to resource allocation. The key contribution of our paper is to combine remote sensing decision making with Nash Equilibrium for sensor parameter weighting optimization. By calculating all Nash Equilibrium possibilities per period, optimization of sensor allocation is achieved for overall higher system efficiency. Our tool provides insight into what are the most important or optimal weights for sensor parameters and can be used to efficiently tune those weights.

  7. On the optimal experimental design for heat and moisture parameter estimation

    CERN Document Server

    Berger, Julien; Mendes, Nathan

    2016-01-01

    In the context of estimating material properties of porous walls based on in-site measurements and identification method, this paper presents the concept of Optimal Experiment Design (OED). It aims at searching the best experimental conditions in terms of quantity and position of sensors and boundary conditions imposed to the material. These optimal conditions ensure to provide the maximum accuracy of the identification method and thus the estimated parameters. The search of the OED is done by using the Fisher information matrix and a priori knowledge of the parameters. The methodology is applied for two case studies. The first one deals with purely conductive heat transfer. The concept of optimal experiment design is detailed and verified with 100 inverse problems for different experiment designs. The second case study combines a strong coupling between heat and moisture transfer through a porous building material. The methodology presented is based on a scientific formalism for efficient planning of experim...

  8. Parameter optimization of differential evolution algorithm for automatic playlist generation problem

    Science.gov (United States)

    Alamag, Kaye Melina Natividad B.; Addawe, Joel M.

    2017-11-01

    With the digitalization of music, the number of collection of music increased largely and there is a need to create lists of music that filter the collection according to user preferences, thus giving rise to the Automatic Playlist Generation Problem (APGP). Previous attempts to solve this problem include the use of search and optimization algorithms. If a music database is very large, the algorithm to be used must be able to search the lists thoroughly taking into account the quality of the playlist given a set of user constraints. In this paper we perform an evolutionary meta-heuristic optimization algorithm, Differential Evolution (DE) using different combination of parameter values and select the best performing set when used to solve four standard test functions. Performance of the proposed algorithm is then compared with normal Genetic Algorithm (GA) and a hybrid GA with Tabu Search. Numerical simulations are carried out to show better results from Differential Evolution approach with the optimized parameter values.

  9. Optimization of process parameters for production of volatile fatty acid, biohydrogen and methane from anaerobic digestion.

    Science.gov (United States)

    Khan, M A; Ngo, H H; Guo, W S; Liu, Y; Nghiem, L D; Hai, F I; Deng, L J; Wang, J; Wu, Y

    2016-11-01

    The anaerobic digestion process has been primarily utilized for methane containing biogas production over the past few years. However, the digestion process could also be optimized for producing volatile fatty acids (VFAs) and biohydrogen. This is the first review article that combines the optimization approaches for all three possible products from the anaerobic digestion. In this review study, the types and configurations of the bioreactor are discussed for each type of product. This is followed by a review on optimization of common process parameters (e.g. temperature, pH, retention time and organic loading rate) separately for the production of VFA, biohydrogen and methane. This review also includes additional parameters, treatment methods or special additives that wield a significant and positive effect on production rate and these products' yield. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Enhancing anaerobic digestion of high-pressure extruded food waste by inoculum optimization.

    Science.gov (United States)

    Kong, Xin; Xu, Shuang; Liu, Jianguo; Li, Huan; Zhao, Ke; He, Liang

    2016-01-15

    The inoculation for extruded food waste anaerobic digestion (AD) was optimized to improve methane (CH4) yield. The inoculum of acclimated anaerobic sludge resulted in high biodegradability, producing CH4 yields from 580 mLCH4 g(-1)·VSadded to 605 mLCH4 g(-1)·VSadded, with corresponding BDCH4 ranging from 90% to 94%. We also investigated inoculum to substrate ratios (ISRs). With regards to digested slurry as inoculum, we found that a decrease in ISR improved CH4 yield, while a lower ISR prolonged the lag time of the initial AD stage due to lipid inhibition caused by excessive food waste. These results demonstrate that minimal inocula are required to start the AD system for high-pressure extruded food waste because it is easily biodegraded. High ammonia concentration had a negative effect on CH4 production (i.e., when free ammonia nitrogen [FAN] increased from 20 to 30 mg L(-1) to 120-140 mg L(-1), the CH4 yield decreased by 25%), suggesting that FAN was a significant inhibitor in CH4 yield reduction. In terms of CH4 yield and lag time of the AD process, the optimal inoculation of digested slurry for the extruded food waste had an ISR of 0.33 with CH4 yield of 505 mLCH4 g(-1)VSadded, which was 20% higher than what was found for higher ISR controls of 2, 1 and 0.5. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. Parameter uncertainties in the design and optimization of cantilever piezoelectric energy harvesters

    Science.gov (United States)

    Franco, V. R.; Varoto, P. S.

    2017-09-01

    A crucial issue in piezoelectric energy harvesting is the efficiency of the mechanical to electrical conversion process. Several techniques have been investigated in order to obtain a set of optimum design parameters that will lead to the best performance of the harvester in terms of electrical power generation. Once an optimum design is reached it is also important to consider uncertainties in the selected parameters that in turn can lead to loss of performance in the energy conversion process. The main goal of this paper is to perform a comprehensive discussion of the effects of multi-parameter aleatory uncertainties on the performance and design optimization of a given energy harvesting system. For that, a typical energy harvester consisting of a cantilever beam carrying a tip mass and partially covered by piezoelectric layers on top and bottom surfaces is considered. A distributed parameter electromechanical modal of the harvesting system is formulated and validated through experimental tests. First, the SQP (Sequential Quadratic Planning) optimization is employed to obtain an optimum set of parameters that will lead to best performance of the harvester. Second, once the optimum harvester configuration is found random perturbations are introduced in the key parameters and Monte Carlo simulations are performed to investigate how these uncertainties propagate and affect the performance of the device studied. Numerically simulated results indicate that small variations in some design parameters can cause a significant variation in the output electrical power, what strongly suggests that uncertainties must be accounted for in the design of beam energy harvesting systems.

  12. Study on Parameter Optimization for Support Vector Regression in Solving the Inverse ECG Problem

    Directory of Open Access Journals (Sweden)

    Mingfeng Jiang

    2013-01-01

    Full Text Available The typical inverse ECG problem is to noninvasively reconstruct the transmembrane potentials (TMPs from body surface potentials (BSPs. In the study, the inverse ECG problem can be treated as a regression problem with multi-inputs (body surface potentials and multi-outputs (transmembrane potentials, which can be solved by the support vector regression (SVR method. In order to obtain an effective SVR model with optimal regression accuracy and generalization performance, the hyperparameters of SVR must be set carefully. Three different optimization methods, that is, genetic algorithm (GA, differential evolution (DE algorithm, and particle swarm optimization (PSO, are proposed to determine optimal hyperparameters of the SVR model. In this paper, we attempt to investigate which one is the most effective way in reconstructing the cardiac TMPs from BSPs, and a full comparison of their performances is also provided. The experimental results show that these three optimization methods are well performed in finding the proper parameters of SVR and can yield good generalization performance in solving the inverse ECG problem. Moreover, compared with DE and GA, PSO algorithm is more efficient in parameters optimization and performs better in solving the inverse ECG problem, leading to a more accurate reconstruction of the TMPs.

  13. Human-in-the-loop Bayesian optimization of wearable device parameters

    Science.gov (United States)

    Malcolm, Philippe; Speeckaert, Jozefien; Siviy, Christoper J.; Walsh, Conor J.; Kuindersma, Scott

    2017-01-01

    The increasing capabilities of exoskeletons and powered prosthetics for walking assistance have paved the way for more sophisticated and individualized control strategies. In response to this opportunity, recent work on human-in-the-loop optimization has considered the problem of automatically tuning control parameters based on realtime physiological measurements. However, the common use of metabolic cost as a performance metric creates significant experimental challenges due to its long measurement times and low signal-to-noise ratio. We evaluate the use of Bayesian optimization—a family of sample-efficient, noise-tolerant, and global optimization methods—for quickly identifying near-optimal control parameters. To manage experimental complexity and provide comparisons against related work, we consider the task of minimizing metabolic cost by optimizing walking step frequencies in unaided human subjects. Compared to an existing approach based on gradient descent, Bayesian optimization identified a near-optimal step frequency with a faster time to convergence (12 minutes, p < 0.01), smaller inter-subject variability in convergence time (± 2 minutes, p < 0.01), and lower overall energy expenditure (p < 0.01). PMID:28926613

  14. Optimal Estimation of Phenological Crop Model Parameters for Rice (Oryza sativa)

    Science.gov (United States)

    Sharifi, H.; Hijmans, R. J.; Espe, M.; Hill, J. E.; Linquist, B.

    2015-12-01

    Crop phenology models are important components of crop growth models. In the case of phenology models, generally only a few parameters are calibrated and default cardinal temperatures are used which can lead to a temperature-dependent systematic phenology prediction error. Our objective was to evaluate different optimization approaches in the Oryza2000 and CERES-Rice phenology sub-models to assess the importance of optimizing cardinal temperatures on model performance and systematic error. We used two optimization approaches: the typical single-stage (planting to heading) and three-stage model optimization (for planting to panicle initiation (PI), PI to heading (HD), and HD to physiological maturity (MT)) to simultaneously optimize all model parameters. Data for this study was collected over three years and six locations on seven California rice cultivars. A temperature-dependent systematic error was found for all cultivars and stages, however it was generally small (systematic error Oryza2000 and from 6.6 to 3.8 in CERES-Rice. With regards to systematic error, we found a trade-off between RMSE and systematic error when optimization objective set to minimize RMSE or systematic error. Therefore, it is important to find the limits within which the trade-offs between RMSE and systematic error are acceptable, especially in climate change studies where this can prevent erroneous conclusions.

  15. Study on parameter optimization for support vector regression in solving the inverse ECG problem.

    Science.gov (United States)

    Jiang, Mingfeng; Jiang, Shanshan; Zhu, Lingyan; Wang, Yaming; Huang, Wenqing; Zhang, Heng

    2013-01-01

    The typical inverse ECG problem is to noninvasively reconstruct the transmembrane potentials (TMPs) from body surface potentials (BSPs). In the study, the inverse ECG problem can be treated as a regression problem with multi-inputs (body surface potentials) and multi-outputs (transmembrane potentials), which can be solved by the support vector regression (SVR) method. In order to obtain an effective SVR model with optimal regression accuracy and generalization performance, the hyperparameters of SVR must be set carefully. Three different optimization methods, that is, genetic algorithm (GA), differential evolution (DE) algorithm, and particle swarm optimization (PSO), are proposed to determine optimal hyperparameters of the SVR model. In this paper, we attempt to investigate which one is the most effective way in reconstructing the cardiac TMPs from BSPs, and a full comparison of their performances is also provided. The experimental results show that these three optimization methods are well performed in finding the proper parameters of SVR and can yield good generalization performance in solving the inverse ECG problem. Moreover, compared with DE and GA, PSO algorithm is more efficient in parameters optimization and performs better in solving the inverse ECG problem, leading to a more accurate reconstruction of the TMPs.

  16. Preliminary performance assessment for the Waste Isolation Pilot Plant, December 1992. Volume 3, Model parameters: Sandia WIPP Project

    Energy Technology Data Exchange (ETDEWEB)

    1992-12-29

    This volume documents model parameters chosen as of July 1992 that were used by the Performance Assessment Department of Sandia National Laboratories in its 1992 preliminary performance assessment of the Waste Isolation Pilot Plant (WIPP). Ranges and distributions for about 300 modeling parameters in the current secondary data base are presented in tables for the geologic and engineered barriers, global materials (e.g., fluid properties), and agents that act upon the WIPP disposal system such as climate variability and human-intrusion boreholes. The 49 parameters sampled in the 1992 Preliminary Performance Assessment are given special emphasis with tables and graphics that provide insight and sources of data for each parameter.

  17. Material stream management of biomass wastes for the optimization of organic wastes utilization; Stoffstrommanagement von Biomasseabfaellen mit dem Ziel der Optimierung der Verwertung organischer Abfaelle

    Energy Technology Data Exchange (ETDEWEB)

    Knappe, Florian; Boess, Andreas; Fehrenbach, Horst; Giegrich, Juergen; Vogt, Regine [ifeu-Institut fuer Energie- und Umweltforschung GmbH, Heidelberg (Germany); Dehoust, Guenter; Schueler, Doris; Wiegmann, Kirsten; Fritsche, Uwe [Oeko-Institut, Inst. fuer Angewandte Oekologie, Darmstadt (Germany)

    2007-02-15

    The effective use of the valuable substances found in waste materials can make an important contribution to climate protection and the conservation of fossil and mineral resources. In order to harness the potential contribution of biomass waste streams, it is necessary to consider the potential of the waste in connection with that of the total biomass. In this project, relevant biogenous material streams in the forestry, the agriculture as well as in several industries are studied, and their optimization potentials are illustrated. Scenarios are then developed, while taking various other environmental impacts into considerations, to explore possible optimized utilization of biomass streams and biomass waste substances for the future. Straw that is not needed for humus production and currently left on the field can be used for its energy content. The realisation of this potential would be significant contribution towards climate protection. The energetic use of liquid manure without negatively influencing its application as commercial fertilizer can also be similarly successful because of its large volume. The results of our study also support an increased energetic use of saw residues as fuel (in form of pellets) in small furnaces. For household organic wastes, the report suggests the fermentation with optimized energy use and intensified marketing of the aerobically treated compost as peat substitution. While for waste cooking fat that is currently disposed in the residual waste, a separate collection and direct use in motors that are used as combined heat and power generation are recommended. For meat and bone meal and communal sludge that are not being used substantial currently or in the future, phosphorus can be recovered with promising success from the ash produced when the waste is burnt in mono incinerators. These technical options should however be tested against disposal standard. (orig.)

  18. Optimized Production of Biodiesel from Waste Cooking Oil by Lipase Immobilized on Magnetic Nanoparticles

    Directory of Open Access Journals (Sweden)

    Chi-Yang Yu

    2013-12-01

    Full Text Available Biodiesel, a non-toxic and biodegradable fuel, has recently become a major source of renewable alternative fuels. Utilization of lipase as a biocatalyst to produce biodiesel has advantages over common alkaline catalysts such as mild reaction conditions, easy product separation, and use of waste cooking oil as raw material. In this study, Pseudomonas cepacia lipase immobilized onto magnetic nanoparticles (MNP was used for biodiesel production from waste cooking oil. The optimal dosage of lipase-bound MNP was 40% (w/w of oil and there was little difference between stepwise addition of methanol at 12 h- and 24 h-intervals. Reaction temperature, substrate molar ratio (methanol/oil, and water content (w/w of oil were optimized using response surface methodology (RSM. The optimal reaction conditions were 44.2 °C, substrate molar ratio of 5.2, and water content of 12.5%. The predicted and experimental molar conversions of fatty acid methyl esters (FAME were 80% and 79%, respectively.

  19. Improving flash flood forecasting with distributed hydrological model by parameter optimization

    Science.gov (United States)

    Chen, Yangbo

    2016-04-01

    In China, flash food is usually regarded as flood occured in small and medium sized watersheds with drainage area less than 200 km2, and is mainly induced by heavy rains, and occurs in where hydrological observation is lacked. Flash flood is widely observed in China, and is the flood causing the most casualties nowadays in China. Due to hydrological data scarcity, lumped hydrological model is difficult to be employed for flash flood forecasting which requires lots of observed hydrological data to calibrate model parameters. Physically based distributed hydrological model discrete the terrain of the whole watershed into a number of grid cells at fine resolution, assimilate different terrain data and precipitation to different cells, and derive model parameteris from the terrain properties, thus having the potential to be used in flash flood forecasting and improving flash flood prediction capability. In this study, the Liuxihe Model, a physically based distributed hydrological model mainly proposed for watershed flood forecasting is employed to simulate flash floods in the Ganzhou area in southeast China, and models have been set up in 5 watersheds. Model parameters have been derived from the terrain properties including the DEM, the soil type and land use type, but the result shows that the flood simulation uncertainty is high, which may be caused by parameter uncertainty, and some kind of uncertainty control is needed before the model could be used in real-time flash flood forecastin. Considering currently many Chinese small and medium sized watersheds has set up hydrological observation network, and a few flood events could be collected, it may be used for model parameter optimization. For this reason, an automatic model parameter optimization algorithm using Particle Swam Optimization(PSO) is developed to optimize the model parameters, and it has been found that model parameters optimized even only with one observed flood events could largely reduce the flood

  20. 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.

  1. Optimizing Support Vector Machine Parameters with Genetic Algorithm for Credit Risk Assessment

    Science.gov (United States)

    Manurung, Jonson; Mawengkang, Herman; Zamzami, Elviawaty

    2017-12-01

    Support vector machine (SVM) is a popular classification method known to have strong generalization capabilities. SVM can solve the problem of classification and linear regression or nonlinear kernel which can be a learning algorithm for the ability of classification and regression. However, SVM also has a weakness that is difficult to determine the optimal parameter value. SVM calculates the best linear separator on the input feature space according to the training data. To classify data which are non-linearly separable, SVM uses kernel tricks to transform the data into a linearly separable data on a higher dimension feature space. The kernel trick using various kinds of kernel functions, such as : linear kernel, polynomial, radial base function (RBF) and sigmoid. Each function has parameters which affect the accuracy of SVM classification. To solve the problem genetic algorithms are proposed to be applied as the optimal parameter value search algorithm thus increasing the best classification accuracy on SVM. Data taken from UCI repository of machine learning database: Australian Credit Approval. The results show that the combination of SVM and genetic algorithms is effective in improving classification accuracy. Genetic algorithms has been shown to be effective in systematically finding optimal kernel parameters for SVM, instead of randomly selected kernel parameters. The best accuracy for data has been upgraded from kernel Linear: 85.12%, polynomial: 81.76%, RBF: 77.22% Sigmoid: 78.70%. However, for bigger data sizes, this method is not practical because it takes a lot of time.

  2. 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.

  3. Definitive screening design enables optimization of LC-ESI-MS/MS parameters in proteomics.

    Science.gov (United States)

    Aburaya, Shunsuke; Aoki, Wataru; Minakuchi, Hiroyoshi; Ueda, Mitsuyoshi

    2017-12-01

    In proteomics, more than 100,000 peptides are generated from the digestion of human cell lysates. Proteome samples have a broad dynamic range in protein abundance; therefore, it is critical to optimize various parameters of LC-ESI-MS/MS to comprehensively identify these peptides. However, there are many parameters for LC-ESI-MS/MS analysis. In this study, we applied definitive screening design to simultaneously optimize 14 parameters in the operation of monolithic capillary LC-ESI-MS/MS to increase the number of identified proteins and/or the average peak area of MS1. The simultaneous optimization enabled the determination of two-factor interactions between LC and MS. Finally, we found two parameter sets of monolithic capillary LC-ESI-MS/MS that increased the number of identified proteins by 8.1% or the average peak area of MS1 by 67%. The definitive screening design would be highly useful for high-throughput analysis of the best parameter set in LC-ESI-MS/MS systems.

  4. Parameter optimization for the visco-hyperelastic constitutive model of tendon using FEM.

    Science.gov (United States)

    Tang, C Y; Ng, G Y F; Wang, Z W; Tsui, C P; Zhang, G

    2011-01-01

    Numerous constitutive models describing the mechanical properties of tendons have been proposed during the past few decades. However, few were widely used owing to the lack of implementation in the general finite element (FE) software, and very few systematic studies have been done on selecting the most appropriate parameters for these constitutive laws. In this work, the visco-hyperelastic constitutive model of the tendon implemented through the use of three-parameter Mooney-Rivlin form and sixty-four-parameter Prony series were firstly analyzed using ANSYS FE software. Afterwards, an integrated optimization scheme was developed by coupling two optimization toolboxes (OPTs) of ANSYS and MATLAB for estimating these unknown constitutive parameters of the tendon. Finally, a group of Sprague-Dawley rat tendons was used to execute experimental and numerical simulation investigation. The simulated results showed good agreement with the experimental data. An important finding revealed that too many Maxwell elements was not necessary for assuring accuracy of the model, which is often neglected in most open literatures. Thus, all these proved that the constitutive parameter optimization scheme was reliable and highly efficient. Furthermore, the approach can be extended to study other tendons or ligaments, as well as any visco-hyperelastic solid materials.

  5. Sequencing biological acidification of waste-activated sludge aiming to optimize phosphorus dissolution and recovery.

    Science.gov (United States)

    Guilayn, Felipe; Braak, Etienne; Piveteau, Simon; Daumer, Marie-Line

    2017-06-01

    Phosphorus (P) recovery in wastewater treatment plants (WWTP) as pure crystals such as struvite (MgNH4PO4.6H2O), potassium struvite (KMgPO4.6H2O) and calcium phosphates (e.g. Ca3(PO4)2) is an already feasible technique that permits the production of green and marketable fertilizers and the reduction of operational costs. Commercial crystallizers can recovery more than 90% of soluble P. However, most of the P in WWTP sludge is unavailable for the processes (not dissolved). P solubilization and separation are thus the limiting steps in P-crystallization. With an innovative two-step sequencing acidification strategy, the current study has aimed to improve biological P solubilization on waste-activated sludge (WAS) from a full-scale plant. In the first step (P-release), low charges of organic waste were used as co-substrates of WAS pre-fermentation, seeking to produce volatile fatty acids to feed the P-release by Polyphosphate-accumulating organisms, while keeping its optimal metabolic pH (6-7). In this phase, milk serum, WWTP grease, urban organic waste and collective restaurant waste were individually applied as co-substrates. In the second step (P-dissolution), pH 4 was aimed at as it allows the dissolution of the most common precipitated species of P. Biological acidification was performed by white sugar addition, as a carbohydrate-rich organic waste model, which was compared to chemical acidification by HCl (12M) addition. With short retention times (48-96 h) and without inoculum application, all experiences succeeded on P solubilization (37-55% of soluble P), principally when carbohydrate-rich co-substrates were applied. Concentrations from 270 to 450 mg [Formula: see text] were achieved. [Formula: see text].

  6. Optimal Parameter Estimation for Muskingum Model Using a CSS-PSO Method

    Directory of Open Access Journals (Sweden)

    S. Talatahari

    2013-01-01

    Full Text Available Limited availability of hydrologic data is a major hurdle for implementation of detailed hydrologic models. In cases where available data is limited, simple hydrologic models such as linear Muskingum model consisting of a minimum number (one or two of model parameters are more desirable. As an alternative to the conventional mathematical approaches, this paper applies a new hybrid metaheuristic algorithm based on charged system search and particle swarm optimization for identifying the parameters of the linear Muskingum model. In order to evaluate the new algorithm, a numerical example is utilized and the results are compared to those of other algorithms. The results reveal the performance of the algorithm to optimize parameter estimation of the Muskingum model.

  7. Polishing parameter optimization for end-surface of chalcogenide glass fiber connector

    Science.gov (United States)

    Guo, Fangxia; Dai, Shixun; Tang, Junzhou; Wang, Xunsi; Li, Xing; Xu, Yinsheng; Wu, Yuehao; Liu, Zijun

    2017-11-01

    We have investigated the optimization parameters for polishing end-surface of chalcogenide glass fiber connector in the paper. Six SiC abrasive particles of different sizes were used to polish the fiber in order of size from large to small. We analyzed the effects of polishing parameters such as particle sizes, grinding speeds and polishing durations on the quality of the fiber end surface and determined the optimized polishing parameters. We found that, high-quality fiber end surface can be achieved using only three different SiC abrasives. The surface roughness of the final ChG fiber end surface is about 48 nm without any scratches, spots and cracks. Such polishing processes could reduce the average insertion loss of the connector to about 3.4 dB.

  8. An Improved Cuckoo Search Optimization Algorithm for the Problem of Chaotic Systems Parameter Estimation.

    Science.gov (United States)

    Wang, Jun; Zhou, Bihua; Zhou, Shudao

    2016-01-01

    This paper proposes an improved cuckoo search (ICS) algorithm to establish the parameters of chaotic systems. In order to improve the optimization capability of the basic cuckoo search (CS) algorithm, the orthogonal design and simulated annealing operation are incorporated in the CS algorithm to enhance the exploitation search ability. Then the proposed algorithm is used to establish parameters of the Lorenz chaotic system and Chen chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the algorithm can estimate parameters with high accuracy and reliability. Finally, the results are compared with the CS algorithm, genetic algorithm, and particle swarm optimization algorithm, and the compared results demonstrate the method is energy-efficient and superior.

  9. Optimization of operating parameters for gas-phase photocatalytic splitting of H2S by novel vermiculate packed tubular reactor.

    Science.gov (United States)

    Preethi, V; Kanmani, S

    2016-10-01

    Hydrogen production by gas-phase photocatalytic splitting of Hydrogen Sulphide (H2S) was investigated on four semiconductor photocatalysts including CuGa1.6Fe0.4O2, ZnFe2O3, (CdS + ZnS)/Fe2O3 and Ce/TiO2. The CdS and ZnS coated core shell particles (CdS + ZnS)/Fe2O3 shows the highest rate of hydrogen (H2) production under optimized conditions. Packed bed tubular reactor was used to study the performance of prepared photocatalysts. Selection of the best packing material is a key for maximum removal efficiency. Cheap, lightweight and easily adsorbing vermiculate materials were used as a novel packing material and were found to be effective in splitting H2S. Effect of various operating parameters like flow rate, sulphide concentration, catalyst dosage, light irradiation were tested and optimized for maximum H2 conversion of 92% from industrial waste H2S. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. A Method for Optimizing Lightweight-Gypsum Design Based on Sequential Measurements of Physical Parameters

    Directory of Open Access Journals (Sweden)

    Vimmrová Alena

    2016-06-01

    Full Text Available A method for lightweight-gypsum material design using waste stone dust as the foaming agent is described. The main objective is to reach several physical properties which are inversely related in a certain way. Therefore, a linear optimization method is applied to handle this task systematically. The optimization process is based on sequential measurement of physical properties. The results are subsequently point-awarded according to a complex point criterion and new composition is proposed. After 17 trials the final mixture is obtained, having the bulk density equal to (586 ± 19 kg/m3 and compressive strength (1.10 ± 0.07 MPa. According to a detailed comparative analysis with reference gypsum, the newly developed material can be used as excellent thermally insulating interior plaster with the thermal conductivity of (0.082 ± 0.005 W/(m·K. In addition, its practical application can bring substantial economic and environmental benefits as the material contains 25 % of waste stone dust.

  11. Influence of waste managemental and technical planning parameters on plant costs; Einfluss abfallwirtschaftlicher und technischer Plannungsgroessen auf die Anlagenkosten

    Energy Technology Data Exchange (ETDEWEB)

    Beckmann, R. [Inst. fuer Umwelt, Sicherheits- und Energietechnik e.V., Oberhausen (Germany)

    1998-09-01

    The probable future costs of thermal waste treatment depend on a great number of influencing factors. One of the essential aims of the present contribution is to elaborate and present the sensitivity of costs to various parameters. [Deutsch] Die zukuenftig zu erwartenden Kosten der thermischen Abfallbehandlung haengen von einer Vielzahl von Einflussgroessen ab. Im Rahmen des Beitrags besteht daher ein wesentliches Ziel darin, die Sensitivitaet der Kosten hinsichtlich verschiedenster Parameter herauszuarbeiten und darzustellen. (orig./SR)

  12. An improved swarm optimization for parameter estimation and biological model selection.

    Directory of Open Access Journals (Sweden)

    Afnizanfaizal Abdullah

    Full Text Available One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete

  13. An improved swarm optimization for parameter estimation and biological model selection.

    Science.gov (United States)

    Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail

    2013-01-01

    One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This

  14. Dermatology Disease Prediction Based on Two Step Cascade Genetic Algorithm Optimization of ANFIS Parameters.

    Science.gov (United States)

    Avdagic, Aja; Begic Fazlic, Lejla

    2017-01-01

    The aim of this study is to present novel algorithms for prediction of dermatological disease using only dermatological clinical features and diagnoses collected in real conditions. A combination of the Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Genetic algorithm (GA) for ANFIS subtractive clustering parameter optimization has been suggested for the first level of fuzzy model optimization. After that, a genetic optimized ANFIS fuzzy structure is used as input in GA for the second level of fuzzy model optimization. We used double 2-fold Cross validation for generating different validation sets for model improvements. Our approach is performed in the MATLAB environment. We compared results with the other studies. The results confirm that the proposed model achieves accuracy rates which are higher than the one with the previous model.

  15. Feature Selection and Parameters Optimization of SVM Using Particle Swarm Optimization for Fault Classification in Power Distribution Systems

    Directory of Open Access Journals (Sweden)

    Ming-Yuan Cho

    2017-01-01

    Full Text Available Fast and accurate fault classification is essential to power system operations. In this paper, in order to classify electrical faults in radial distribution systems, a particle swarm optimization (PSO based support vector machine (SVM classifier has been proposed. The proposed PSO based SVM classifier is able to select appropriate input features and optimize SVM parameters to increase classification accuracy. Further, a time-domain reflectometry (TDR method with a pseudorandom binary sequence (PRBS stimulus has been used to generate a dataset for purposes of classification. The proposed technique has been tested on a typical radial distribution network to identify ten different types of faults considering 12 given input features generated by using Simulink software and MATLAB Toolbox. The success rate of the SVM classifier is over 97%, which demonstrates the effectiveness and high efficiency of the developed method.

  16. Microbiological parameters and maturity degree during composting of Posidonia oceanica residues mixed with vegetable wastes in semi-arid pedo-climatic condition.

    Science.gov (United States)

    Saidi, Neyla; Kouki, Soulwene; M'hiri, Fadhel; Jedidi, Naceur; Mahrouk, Meriam; Hassen, Abdennaceur; Ouzari, Hadda

    2009-01-01

    The aim of this study was to characterize the biological stability and maturity degree of compost during a controlled pile-composting trial of mixed vegetable residues (VR) collected from markets of Tunis City with residues of Posidonia oceanica (PoR), collected from Tunis beaches. The accumulation in beaches (as well as their removal) constitutes a serious environmental problem in all Mediterranean countries particularly in Tunisia. Aerobic-thermophilic composting is the most reasonable way to profit highly-valuable content of organic matter in these wastes for agricultural purposes. The physical, chemical, and biological parameters were monitored during composting over 150 d. The most appropriate parameters were selected to establish the maturity degree. The main result of this research was the deduction of the following maturity criterion: (a) C/N ratio 80%. These five parameters, considered jointly are indicative of a high maturity degree and thus of a high-quality organic amendment which employed in a rational way, may improve soil fertility and soil quality. The mature compost was relatively rich in N (13.0 g/kg), P (4.74 g/kg) and MgO (15.80 g/kg). Thus composting definitively constitutes the most optimal option to exploit these wastes.

  17. Modelling of slaughterhouse solid waste anaerobic digestion: determination of parameters and continuous reactor simulation.

    Science.gov (United States)

    López, Iván; Borzacconi, Liliana

    2010-10-01

    A model based on the work of Angelidaki et al. (1993) was applied to simulate the anaerobic biodegradation of ruminal contents. In this study, two fractions of solids with different biodegradation rates were considered. A first-order kinetic was used for the easily biodegradable fraction and a kinetic expression that is function of the extracellular enzyme concentration was used for the slowly biodegradable fraction. Batch experiments were performed to obtain an accumulated methane curve that was then used to obtain the model parameters. For this determination, a methodology derived from the "multiple-shooting" method was successfully used. Monte Carlo simulations allowed a confidence range to be obtained for each parameter. Simulations of a continuous reactor were performed using the optimal set of model parameters. The final steady-states were determined as functions of the operational conditions (solids load and residence time). The simulations showed that methane flow peaked at a flow rate of 0.5-0.8 Nm(3)/d/m(reactor)(3) at a residence time of 10-20 days. Simulations allow the adequate selection of operating conditions of a continuous reactor. (c) 2010 Elsevier Ltd. All rights reserved.

  18. Inventory model optimization for supplier-manufacturer-retailer system with rework and waste disposal

    Science.gov (United States)

    Dwicahyani, A. R.; Kholisoh, E.; Jauhari, W. A.; Rosyidi, C. N.; Laksono, P. W.

    2017-11-01

    This study developed a model for a CLSC inventory system which consisted of a supplier, a manufacturer and a retailer. We applied single remanufacturing cycle and multiple manufacturing cycle, (1,P), policy and performed a comparison to the previous study. We conducted an investigation of an imperfect manufacturing process whose defective items were being reworked. Other considerations were quality dependent return rate and waste disposal activity, for any returned items that did not exceed the acceptable quality level. Some parameters including demand, proportion of defect, waste and refurbished item were assumed deterministic and constant. We proposed a solution procedure and presented a numerical example to illustrate the application of the model. The results showed that (1,P) policy allowed higher profit for the system than (R,1) policy presented in the previous study.

  19. Estimation of optimal dispersion model source parameters using satellite detections of volcanic ash

    Science.gov (United States)

    Zidikheri, Meelis J.; Lucas, Christopher; Potts, Rodney J.

    2017-08-01

    In this paper we demonstrate how parameters describing the geometry of the volcanic ash source for a particular volcanic ash dispersion model (Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT)) may be inferred by the use of satellite data and multiple trial simulations. The areas of space likely to be contaminated by ash are identified with the aid of various remote sensing techniques, and polygons are drawn around these areas as they would be in an operational setting. Dispersion model simulations are initialized by either a cylindrical source or a specified ash distribution depending on the context. Parameters of interest such as the base and top height, diameter, and optimal release time of the cylindrical source or the height of the specified ash distribution are inferred by forming a parameter grid and running multiple simulations for each parameter grid point value. Optimal values of the parameter values are identified by calculating spatial correlations between the model simulations and observations. We demonstrate that the methodology can be used to correctly infer various model parameters and improve volcanic ash forecasts in various eruption case studies.

  20. Dynamic optimization of a biped model: Energetic walking gaits with different mechanical and gait parameters

    Directory of Open Access Journals (Sweden)

    Kang An

    2015-05-01

    Full Text Available Energy consumption is one of the problems for bipedal robots walking. For the purpose of studying the parameter effects on the design of energetic walking bipeds with strong adaptability, we use a dynamic optimization method on our new walking model to first investigate the effects of the mechanical parameters, including mass and length distribution, on the walking efficiency. Then, we study the energetic walking gait features with the combinations of walking speed and step length. Our walking model is designed upon Srinivasan’s model. Dynamic optimization is used for a free search with minimal constraints. The results show that the cost of transport of a certain gait increases with the increase in the mass and length distribution parameters, except for that the cost of transport decreases with big length distribution parameter and long step length. We can also find a corresponding range of walking speed and step length, in which the variation in one of the two parameters has no obvious effect on the cost of transport. With fixed mechanical parameters, the cost of transport increases with the increase in the walking speed. There is a speed–step length relationship for walking with minimal cost of transport. The hip torque output strategy is adjusted in two situations to meet the walking requirements.

  1. Process parameters influencing tannase production by Aspergillus ...

    African Journals Online (AJOL)

    Rhizophora apiculata bark is a tannin-rich waste material obtained from charcoal industry. This industrial waste was used as solid substrate in the study for the production of tannase and at the same time, help in minimizing the country's industrial wastes. This study was carried out to optimize the physical parameters for the ...

  2. Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis

    Directory of Open Access Journals (Sweden)

    Tashkova Katerina

    2011-10-01

    Full Text Available Abstract Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA, particle-swarm optimization (PSO, and differential evolution (DE, as well as a local-search derivative-based algorithm 717 (A717 to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE clearly and significantly outperform the local derivative-based method (A717. Among the three meta-heuristics, differential evolution (DE performs best in terms of the objective function, i.e., reconstructing the output, and in terms of

  3. Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis

    Science.gov (United States)

    2011-01-01

    Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These

  4. Parameters-tuning of PID controller for automatic voltage regulators using the African buffalo optimization.

    Directory of Open Access Journals (Sweden)

    Julius Beneoluchi Odili

    Full Text Available In this paper, an attempt is made to apply the African Buffalo Optimization (ABO to tune the parameters of a PID controller for an effective Automatic Voltage Regulator (AVR. Existing metaheuristic tuning methods have been proven to be quite successful but there were observable areas that need improvements especially in terms of the system's gain overshoot and steady steady state errors. Using the ABO algorithm where each buffalo location in the herd is a candidate solution to the Proportional-Integral-Derivative parameters was very helpful in addressing these two areas of concern. The encouraging results obtained from the simulation of the PID Controller parameters-tuning using the ABO when compared with the performance of Genetic Algorithm PID (GA-PID, Particle-Swarm Optimization PID (PSO-PID, Ant Colony Optimization PID (ACO-PID, PID, Bacteria-Foraging Optimization PID (BFO-PID etc makes ABO-PID a good addition to solving PID Controller tuning problems using metaheuristics.

  5. A Parallel Genetic Algorithm Based Feature Selection and Parameter Optimization for Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Zhi Chen

    2016-01-01

    Full Text Available The extensive applications of support vector machines (SVMs require efficient method of constructing a SVM classifier with high classification ability. The performance of SVM crucially depends on whether optimal feature subset and parameter of SVM can be efficiently obtained. In this paper, a coarse-grained parallel genetic algorithm (CGPGA is used to simultaneously optimize the feature subset and parameters for SVM. The distributed topology and migration policy of CGPGA can help find optimal feature subset and parameters for SVM in significantly shorter time, so as to increase the quality of solution found. In addition, a new fitness function, which combines the classification accuracy obtained from bootstrap method, the number of chosen features, and the number of support vectors, is proposed to lead the search of CGPGA to the direction of optimal generalization error. Experiment results on 12 benchmark datasets show that our proposed approach outperforms genetic algorithm (GA based method and grid search method in terms of classification accuracy, number of chosen features, number of support vectors, and running time.

  6. 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.

  7. Parameters-tuning of PID controller for automatic voltage regulators using the African buffalo optimization

    Science.gov (United States)

    Mohmad Kahar, Mohd Nizam; Noraziah, A.

    2017-01-01

    In this paper, an attempt is made to apply the African Buffalo Optimization (ABO) to tune the parameters of a PID controller for an effective Automatic Voltage Regulator (AVR). Existing metaheuristic tuning methods have been proven to be quite successful but there were observable areas that need improvements especially in terms of the system’s gain overshoot and steady steady state errors. Using the ABO algorithm where each buffalo location in the herd is a candidate solution to the Proportional-Integral-Derivative parameters was very helpful in addressing these two areas of concern. The encouraging results obtained from the simulation of the PID Controller parameters-tuning using the ABO when compared with the performance of Genetic Algorithm PID (GA-PID), Particle-Swarm Optimization PID (PSO-PID), Ant Colony Optimization PID (ACO-PID), PID, Bacteria-Foraging Optimization PID (BFO-PID) etc makes ABO-PID a good addition to solving PID Controller tuning problems using metaheuristics. PMID:28441390

  8. Optimization of digital breast tomosynthesis (DBT) acquisition parameters for human observers: effect of reconstruction algorithms

    Science.gov (United States)

    Zeng, Rongping; Badano, Aldo; Myers, Kyle J.

    2017-04-01

    We showed in our earlier work that the choice of reconstruction methods does not affect the optimization of DBT acquisition parameters (angular span and number of views) using simulated breast phantom images in detecting lesions with a channelized Hotelling observer (CHO). In this work we investigate whether the model-observer based conclusion is valid when using humans to interpret images. We used previously generated DBT breast phantom images and recruited human readers to find the optimal geometry settings associated with two reconstruction algorithms, filtered back projection (FBP) and simultaneous algebraic reconstruction technique (SART). The human reader results show that image quality trends as a function of the acquisition parameters are consistent between FBP and SART reconstructions. The consistent trends confirm that the optimization of DBT system geometry is insensitive to the choice of reconstruction algorithm. The results also show that humans perform better in SART reconstructed images than in FBP reconstructed images. In addition, we applied CHOs with three commonly used channel models, Laguerre-Gauss (LG) channels, square (SQR) channels and sparse difference-of-Gaussian (sDOG) channels. We found that LG channels predict human performance trends better than SQR and sDOG channel models for the task of detecting lesions in tomosynthesis backgrounds. Overall, this work confirms that the choice of reconstruction algorithm is not critical for optimizing DBT system acquisition parameters.

  9. Quantum-behaved particle swarm optimization: analysis of individual particle behavior and parameter selection.

    Science.gov (United States)

    Sun, Jun; Fang, Wei; Wu, Xiaojun; Palade, Vasile; Xu, Wenbo

    2012-01-01

    Quantum-behaved particle swarm optimization (QPSO), motivated by concepts from quantum mechanics and particle swarm optimization (PSO), is a probabilistic optimization algorithm belonging to the bare-bones PSO family. Although it has been shown to perform well in finding the optimal solutions for many optimization problems, there has so far been little analysis on how it works in detail. This paper presents a comprehensive analysis of the QPSO algorithm. In the theoretical analysis, we analyze the behavior of a single particle in QPSO in terms of probability measure. Since the particle's behavior is influenced by the contraction-expansion (CE) coefficient, which is the most important parameter of the algorithm, the goal of the theoretical analysis is to find out the upper bound of the CE coefficient, within which the value of the CE coefficient selected can guarantee the convergence or boundedness of the particle's position. In the experimental analysis, the theoretical results are first validated by stochastic simulations for the particle's behavior. Then, based on the derived upper bound of the CE coefficient, we perform empirical studies on a suite of well-known benchmark functions to show how to control and select the value of the CE coefficient, in order to obtain generally good algorithmic performance in real world applications. Finally, a further performance comparison between QPSO and other variants of PSO on the benchmarks is made to show the efficiency of the QPSO algorithm with the proposed parameter control and selection methods.

  10. Optimization of pretreatments and process parameters for sorghum popping in microwave oven using response surface methodology.

    Science.gov (United States)

    Mishra, Gayatri; Joshi, Dinesh C; Mohapatra, Debabandya

    2015-12-01

    Sorghum is a popular healthy snack food. Popped sorghum was prepared in a domestic microwave oven. A 3 factor 3 level Box and Behneken design was used to optimize the pretreatment conditions. Grains were preconditioned to 12-20 % moisture content by the addition of 0-2 % salt solutions. Oil was applied (0-10 % w/w) to the preconditioned grains. Optimization of the pretreatments was based on popping yield, volume expansion ratio, and sensory score. The optimized condition was found at 16.62 % (wb), 0.55 % salt and 10 % oil with popping yield of 82.228 %, volume expansion ratio of 14.564 and overall acceptability of 8.495. Further, the microwave process parameters were optimized using a 2 factor 3 level design having microwave power density ranging from 9 to 18 W/g and residence time ranging from 100 to 180 s. For the production of superior quality pop sorghum, the optimized microwave process parameters were microwave power density of 18 Wg(-1) and residence time of 140 s.

  11. Determination of full piezoelectric complex parameters using gradient-based optimization algorithm

    Science.gov (United States)

    Kiyono, C. Y.; Pérez, N.; Silva, E. C. N.

    2016-02-01

    At present, numerical techniques allow the precise simulation of mechanical structures, but the results are limited by the knowledge of the material properties. In the case of piezoelectric ceramics, the full model determination in the linear range involves five elastic, three piezoelectric, and two dielectric complex parameters. A successful solution to obtaining piezoceramic properties consists of comparing the experimental measurement of the impedance curve and the results of a numerical model by using the finite element method (FEM). In the present work, a new systematic optimization method is proposed to adjust the full piezoelectric complex parameters in the FEM model. Once implemented, the method only requires the experimental data (impedance modulus and phase data acquired by an impedometer), material density, geometry, and initial values for the properties. This method combines a FEM routine implemented using an 8-noded axisymmetric element with a gradient-based optimization routine based on the method of moving asymptotes (MMA). The main objective of the optimization procedure is minimizing the quadratic difference between the experimental and numerical electrical conductance and resistance curves (to consider resonance and antiresonance frequencies). To assure the convergence of the optimization procedure, this work proposes restarting the optimization loop whenever the procedure ends in an undesired or an unfeasible solution. Two experimental examples using PZ27 and APC850 samples are presented to test the precision of the method and to check the dependency of the frequency range used, respectively.

  12. Nitrogen losses and chemical parameters during co-composting of solid wastes and liquid pig manure.

    Science.gov (United States)

    Vázquez, M A; de la Varga, D; Plana, R; Soto, M

    2017-07-04

    The aim of this research was to study nitrogen losses during the treatment of the liquid fraction (LF) of pig manure by co-composting and to establish the best conditions for compost production with higher nitrogen and low heavy metal contents. Windrows were constituted with the solid fraction (SF) of pig manure, different organic waste (SF of pig manure, sawdust and grape bagasse) as co-substrate and Populus spp. wood chips as bulking material and watered intensely with the LF. Results show that nitrogen losses ranged from 30% to 66% of initial nitrogen and were mainly governed by substrate to bulking mass ratio and liquid fraction to substrate (LF/S) ratio, and only secondarily by operational parameters. Nitrogen losses decreased from 55-65% at low LF/S ratios (1.7-1.9 m3/t total solids (TS)) to 30-39% at high LF/S ratios (4.4-4.7 m3/t TS). Therefore, integrating the LF in the composting process at high LF/S ratios favoured nitrogen recovery and conservation. Nitrogen in the fine fraction (ranging from 27% to 48% of initial nitrogen) was governed by operational parameters, namely pH and temperature. Final compost showed low content in most heavy metals, but Zn was higher than the limits for compost use in agriculture. Zn content in the obtained compost varied from 1863 to 3269 mg/kg dm, depending on several factors. The options for obtaining better quality composts from the LF of pig manure are selecting co-substrates with low heavy metal content and using them instead of the SF of pig manure.

  13. Computation of physiological human vocal fold parameters by mathematical optimization of a biomechanical model

    Science.gov (United States)

    Yang, Anxiong; Stingl, Michael; Berry, David A.; Lohscheller, Jörg; Voigt, Daniel; Eysholdt, Ulrich; Döllinger, Michael

    2011-01-01

    With the use of an endoscopic, high-speed camera, vocal fold dynamics may be observed clinically during phonation. However, observation and subjective judgment alone may be insufficient for clinical diagnosis and documentation of improved vocal function, especially when the laryngeal disease lacks any clear morphological presentation. In this study, biomechanical parameters of the vocal folds are computed by adjusting the corresponding parameters of a three-dimensional model until the dynamics of both systems are similar. First, a mathematical optimization method is presented. Next, model parameters (such as pressure, tension and masses) are adjusted to reproduce vocal fold dynamics, and the deduced parameters are physiologically interpreted. Various combinations of global and local optimization techniques are attempted. Evaluation of the optimization procedure is performed using 50 synthetically generated data sets. The results show sufficient reliability, including 0.07 normalized error, 96% correlation, and 91% accuracy. The technique is also demonstrated on data from human hemilarynx experiments, in which a low normalized error (0.16) and high correlation (84%) values were achieved. In the future, this technique may be applied to clinical high-speed images, yielding objective measures with which to document improved vocal function of patients with voice disorders. PMID:21877808

  14. Intelligent design of waste heat recovery systems using thermoelectric generators and optimization tools

    DEFF Research Database (Denmark)

    Goudarzi, A. M.; Mozaffari, Ahmad; Samadian, Pendar

    2014-01-01

    design to maximize the electricity demand of Damavand power plant as the biggest thermal system in Middle East sited in Iran. The idea of designing is laid behind applying a number of thermoelectric modules within the condenser in order to recover the waste heat of the thermal systems. Besides......, the authors have developed some intelligent tools to elaborate on the performance of their proposed model. Firstly, an artificial neural network has been utilized to estimate the potential power generation of the thermoelectric modules. At the second step, computational fluid dynamic solver, FLUENT is used...... to determine the variation of the temperature through the length of the thermoelectric module assembly. Based on the gained results, an intelligent multi-objective optimization algorithm called Pareto based mutable smart bee is developed to optimize the properties of the thermoelectric component....

  15. 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.

  16. Optimization-Based Inverse Identification of the Parameters of a Concrete Cap Material Model

    Science.gov (United States)

    Král, Petr; Hokeš, Filip; Hušek, Martin; Kala, Jiří; Hradil, Petr

    2017-10-01

    Issues concerning the advanced numerical analysis of concrete building structures in sophisticated computing systems currently require the involvement of nonlinear mechanics tools. The efforts to design safer, more durable and mainly more economically efficient concrete structures are supported via the use of advanced nonlinear concrete material models and the geometrically nonlinear approach. The application of nonlinear mechanics tools undoubtedly presents another step towards the approximation of the real behaviour of concrete building structures within the framework of computer numerical simulations. However, the success rate of this application depends on having a perfect understanding of the behaviour of the concrete material models used and having a perfect understanding of the used material model parameters meaning. The effective application of nonlinear concrete material models within computer simulations often becomes very problematic because these material models very often contain parameters (material constants) whose values are difficult to obtain. However, getting of the correct values of material parameters is very important to ensure proper function of a concrete material model used. Today, one possibility, which permits successful solution of the mentioned problem, is the use of optimization algorithms for the purpose of the optimization-based inverse material parameter identification. Parameter identification goes hand in hand with experimental investigation while it trying to find parameter values of the used material model so that the resulting data obtained from the computer simulation will best approximate the experimental data. This paper is focused on the optimization-based inverse identification of the parameters of a concrete cap material model which is known under the name the Continuous Surface Cap Model. Within this paper, material parameters of the model are identified on the basis of interaction between nonlinear computer simulations

  17. Optimal design of the aerodynamic parameters for a supersonic two-dimensional guided artillery projectile

    Directory of Open Access Journals (Sweden)

    Ke Liang

    2017-06-01

    Full Text Available An optimization method is introduced to design the aerodynamic parameters of a dual-spin two-dimensional guided projectile with the canards for trajectory correction. The nose guidance component contains two pairs of canards which can provide lift and despin with the projectile for stability. The optimal design algorithm is developed to decide the profiles both of the steering and spinning canards, and their deflection angles are also simulated to meet the needs of trajectory correction capabilities. Finally, the aerodynamic efficiency of the specific canards is discussed according to the CFD simulations. Results that obtained here can be further applied to the exterior ballistics design.

  18. Multi-parameter optimization of a nanomagnetic system for spintronic applications

    Energy Technology Data Exchange (ETDEWEB)

    Morales Meza, Mishel [Centro de Investigación en Materiales Avanzados, S.C. (CIMAV), Chihuahua/Monterrey, 120 Avenida Miguel de Cervantes, 31109 Chihuahua (Mexico); Zubieta Rico, Pablo F. [Centro de Investigación en Materiales Avanzados, S.C. (CIMAV), Chihuahua/Monterrey, 120 Avenida Miguel de Cervantes, 31109 Chihuahua (Mexico); Centro de Investigación y de Estudios Avanzados del IPN (CINVESTAV) Querétaro, Libramiento Norponiente 2000, Fracc. Real de Juriquilla, 76230 Querétaro (Mexico); Horley, Paul P., E-mail: paul.horley@cimav.edu.mx [Centro de Investigación en Materiales Avanzados, S.C. (CIMAV), Chihuahua/Monterrey, 120 Avenida Miguel de Cervantes, 31109 Chihuahua (Mexico); Sukhov, Alexander [Institut für Physik, Martin-Luther Universität Halle-Wittenberg, 06120 Halle (Saale) (Germany); Vieira, Vítor R. [Centro de Física das Interacções Fundamentais (CFIF), Instituto Superior Técnico, Universidade Técnica de Lisboa, Avenida Rovisco Pais, 1049-001 Lisbon (Portugal)

    2014-11-15

    Magnetic properties of nano-particles feature many interesting physical phenomena that are essentially important for the creation of a new generation of spin-electronic devices. The magnetic stability of the nano-particles can be improved by formation of ordered particle arrays, which should be optimized over several parameters. Here we report successful optimization regarding inter-particle distance and applied field frequency allowing to obtain about three-times reduction of coercivity of a particle array compared to that of a single particle, which opens new perspectives for development of new spintronic devices.

  19. 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

    , 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......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...

  20. The same number of optimized parameters scheme for determining intermolecular interaction energies

    DEFF Research Database (Denmark)

    Kristensen, Kasper; Ettenhuber, Patrick; Eriksen, Janus Juul

    2015-01-01

    We propose the Same Number Of Optimized Parameters (SNOOP) scheme as an alternative to the counterpoise method for treating basis set superposition errors in calculations of intermolecular interaction energies. The key point of the SNOOP scheme is to enforce that the number of optimized wave...... as numerically. Numerical results for second-order Møller-Plesset perturbation theory (MP2) and coupled-cluster with single, double, and approximate triple excitations (CCSD(T)) show that the SNOOP scheme in general outperforms the uncorrected and counterpoise approaches. Furthermore, we show that SNOOP...

  1. APPROXIMATION TO OPTIMAL STOPPING RULES FOR GUMBEL RANDOM VARIABLES WITH UNKNOWN LOCATION AND SCALE PARAMETERS

    OpenAIRE

    Yeh, Tzu-Sheng; Lee, Shen-Ming

    2006-01-01

    An optimal stopping rule is a rule that stops the sampling process at a sample size n that maximizes the expected reward. In this paper we will study the approximation to optimal stopping rule for Gumbel random variables, because the Gumbel-type distribution is the most commonly referred to in discussions of extreme values. Let $X_1, X_2,\\cdots X_n,\\cdots$ be independent, identically distributed Gumbel random variables with unknown location and scale parameters,$\\alpha$ and $\\beta$. If we def...

  2. Robust optimization on sustainable biodiesel supply chain produced from waste cooking oil under price uncertainty.

    Science.gov (United States)

    Zhang, Yong; Jiang, Yunjian

    2017-02-01

    Waste cooking oil (WCO)-for-biodiesel conversion is regarded as the "waste-to-wealthy" industry. This paper addresses the design of a WCO-for-biodiesel supply chain at both strategic and tactical levels. The supply chain of this problem is studied, which is based on a typical mode of the waste collection (from restaurants' kitchen) and conversion in the cities. The supply chain comprises three stakeholders: WCO supplier, integrated bio-refinery and demand zone. Three key problems should be addressed for the optimal design of the supply chain: (1) the number, sizes and locations of bio-refinery; (2) the sites and amount of WCO collected; (3) the transportation plans of WCO and biodiesel. A robust mixed integer linear model with muti-objective (economic, environmental and social objectives) is proposed for these problems. Finally, a large-scale practical case study is adopted based on Suzhou, a city in the east of China, to verify the proposed models. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Geotechnical aspects for the optimization of dump design at Chinh Bac Mine waste dump in Vietnam

    Energy Technology Data Exchange (ETDEWEB)

    Fuchsschwanz, M.; Ziegler, M. [Aachen Univ., Aachen (Germany). Dept. of Geotechnical Engineering; Ahmad, S.; Fernandez, J.B.P.; Martens, P.N. [Aachen Univ., Aachen (Germany). Inst. of Mining Engineering; Deissmann, G. [Brenk Systemplanung GmbH, Aachen (Germany)

    2009-07-01

    Vietnam's Quang Ninh province is one of the country's most important coal producing regions. Several open pit mines are being operated in the area by Nui Beo Coal Company (NBCC). The construction of large waste dumps for overburden removed by blasting have led to environmental problems at the mining sites, including dust emissions from mining and dumping operations; ground and surface water contamination by acid mine drainage; and slope stability problems caused by heavy rainfall and dump movements. This paper discussed investigations regarding the influence of the dump layout on slope stability and erosion. The paper described the project site and ongoing activities for the development of optimized stabilization and rehabilitation concepts with a particular focus on geotechnical aspects. The site was described in terms of coal and waste rock production; Chinh Bac waste rock dump; crack mapping; material properties of dumped material; density; and settlements. Ongoing activities focus on the effect of benches on slope stability; influence of benches on erosion; and layered dumping. 7 refs., 4 figs.

  4. Evaluation and Parameter Analysis of Burn up Calculations for the Assessment of Radioactive Waste

    OpenAIRE

    Fast, Ivan; Tietze-Jaensch, Holger; Aksyutina, Yuliya

    2013-01-01

    The purpose of this work is to define and verify the range of validity and limitations of correlations used for nuclear waste characterization and to scrutinize the dependencies and propagation of uncertainties that affect the waste inventory declarations and their independent verification. This is accomplished by numerical assessment and simulation of waste production using well accepted codes SCALE 6.0 and 6.1 to simulate the cooling time and burn up of a spent fuel element. The simulations...

  5. Parameter optimization of flux-aided backing-submerged arc welding by using Taguchi method

    Science.gov (United States)

    Pu, Juan; Yu, Shengfu; Li, Yuanyuan

    2017-07-01

    Flux-aided backing-submerged arc welding has been conducted on D36 steel with thickness of 20 mm. The effects of processing parameters such as welding current, voltage, welding speed and groove angle on welding quality were investigated by Taguchi method. The optimal welding parameters were predicted and the individual importance of each parameter on welding quality was evaluated by examining the signal-to-noise ratio and analysis of variance (ANOVA) results. The importance order of the welding parameters for the welding quality of weld bead was: welding current > welding speed > groove angle > welding voltage. The welding quality of weld bead increased gradually with increasing welding current and welding speed and decreasing groove angle. The optimum values of the welding current, welding speed, groove angle and welding voltage were found to be 1050 A, 27 cm/min, 40∘ and 34 V, respectively.

  6. IDENTIFICATION OF OPTIMAL PARAMETERS OF REINFORCED CONCRETE STRUCTURES WITH ACCOUNT FOR THE PROBABILITY OF FAILURE

    Directory of Open Access Journals (Sweden)

    Filimonova Ekaterina Aleksandrovna

    2012-10-01

    The author suggests splitting the aforementioned parameters into the two groups, namely, natural parameters and value-related parameters that are introduced to assess the costs of development, transportation, construction and operation of a structure, as well as the costs of its potential failure. The author proposes a new improved methodology for the identification of the above parameters that ensures optimal solutions to non-linear objective functions accompanied by non-linear restrictions that are critical to the design of reinforced concrete structures. Any structural failure may be interpreted as the bounce of a random process associated with the surplus bearing capacity into the negative domain. Monte Carlo numerical methods make it possible to assess these bounces into the unacc eptable domain.

  7. Application of Powell's optimization method to surge arrester circuit models' parameters

    Energy Technology Data Exchange (ETDEWEB)

    Christodoulou, C.A.; Stathopulos, I.A. [National Technical University of Athens, School of Electrical and Computer Engineering, 9 Iroon Politechniou St., Zografou Campus, 157 80 Athens (Greece); Vita, V.; Ekonomou, L.; Chatzarakis, G.E. [A.S.PE.T.E. - School of Pedagogical and Technological Education, Department of Electrical Engineering Educators, N. Heraklion, 141 21 Athens (Greece)

    2010-08-15

    Powell's optimization method has been used for the evaluation of the surge arrester models parameters. The proper modelling of metal-oxide surge arresters and the right selection of equivalent circuit parameters are very significant issues, since quality and reliability of lightning performance studies can be improved with the more efficient representation of the arresters' dynamic behavior. The proposed approach selects optimum arrester model equivalent circuit parameter values, minimizing the error between the simulated peak residual voltage value and this given by the manufacturer. Application of the method in performed on a 120 kV metal oxide arrester. The use of the obtained optimum parameter values reduces significantly the relative error between the simulated and manufacturer's peak residual voltage value, presenting the effectiveness of the method. (author)

  8. 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.

  9. Optimal injection process parameter analysis for front panel housing using response surface methodology

    Science.gov (United States)

    Zakaria, N. A.; Azlan, M. Z.; Shayfull, Z.; Roselina, S.; Nasir, S. M.

    2017-09-01

    The quality of plastic products depends on how its looks, whether it follows the intended design or not. Shrinkage and warpage are some of the main defects on the moulded parts produced in the injection moulding process due to the difficulty in adjusting the optimum set of parameter. This study was conducted to determine the optimal injection moulding parameters for minimizing shrinkage and warpage value on front panel housing part. The parameters selected for this study are melt temperature, mould temperature, packing pressure and cooling time. Response Surface Methodology (RSM) of analysis was applied to determine the best set of parameters and the significant factor(s) of the shrinkage and warpage were determined from analysis of variance (ANOVA). The input for this study was obtained through simulation.

  10. Optimal routing for efficient municipal solid waste transportation by using ArcGIS application in Chennai, India.

    Science.gov (United States)

    Sanjeevi, V; Shahabudeen, P

    2016-01-01

    Worldwide, about US$410 billion is spent every year to manage four billion tonnes of municipal solid wastes (MSW). Transport cost alone constitutes more than 50% of the total expenditure on solid waste management (SWM) in major cities of the developed world and the collection and transport cost is about 85% in the developing world. There is a need to improve the ability of the city administrators to manage the municipal solid wastes with least cost. Since 2000, new technologies such as geographical information system (GIS) and related optimization software have been used to optimize the haul route distances. The city limits of Chennai were extended from 175 to 426 km(2) in 2011, leading to sub-optimum levels in solid waste transportation of 4840 tonnes per day. After developing a spatial database for the whole of Chennai with 200 wards, the route optimization procedures have been run for the transport of solid wastes from 13 wards (generating nodes) to one transfer station (intermediary before landfill), using ArcGIS. The optimization process reduced the distances travelled by 9.93%. The annual total cost incurred for this segment alone is Indian Rupees (INR) 226.1 million. Savings in terms of time taken for both the current and shortest paths have also been computed, considering traffic conditions. The overall savings are thus very meaningful and call for optimization of the haul routes for the entire Chennai. © The Author(s) 2015.

  11. Optimization of extraction of high purity all-trans-lycopene from tomato pulp waste.

    Science.gov (United States)

    Poojary, Mahesha M; Passamonti, Paolo

    2015-12-01

    The aim of this work was to optimize the extraction of pure all-trans-lycopene from the pulp fractions of tomato processing waste. A full factorial design (FFD) consisting of four independent variables including extraction temperature (30-50 °C), time (1-60 min), percentage of acetone in n-hexane (25-75%, v/v) and solvent volume (10-30 ml) was used to investigate the effects of process variables on the extraction. The absolute amount of lycopene present in the pulp waste was found to be 0.038 mg/g. The optimal conditions for extraction were as follows: extraction temperature 20 °C, time 40 min, a solvent composition of 25% acetone in n-hexane (v/v) and solvent volume 40 ml. Under these conditions, the maximal recovery of lycopene was 94.7%. The HPLC-DAD analysis demonstrated that, lycopene was obtained in the all-trans-configuration at a very high purity grade of 98.3% while the amount of cis-isomers and other carotenoids were limited. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Optimization of Laccase Production using White Rot Fungi and Agriculture Wastes in Solid State Fermentation

    Directory of Open Access Journals (Sweden)

    Hendro Risdianto

    2012-07-01

    Full Text Available Laccase has been produced in a solid state fermentation (SSF using white rot fungi and various lignocellulosic based substrates. White rot fungi used were Marasmius sp, Trametes hirsuta, Trametes versicolor and Phanerochaete crysosporium. The solid substrates employed in this research were collected from agriculture waste which were empty fruit bunches (EFB, rice straw, corn cob, and rice husk. The objective of this research was to determine the most promising fungus, the best solid substrate and the optimal conditions for the production of laccase. The results showed that Marasmius sp. on all solid substrates displayed higher laccase activity than that of any other strain of white rot fungi. Marasmius sp. and solid substrate of rice straw demonstrated the highest laccase activity of 1116.11 U/L on day 10. Three significant factors, i.e. pH, temperature and yeast extract concentration were studied by response surface method on laccase production using Marasmius sp and rice straw. The optimized conditions were pH, temperature and yeast extract concentration of 4.9, 31ºC and 0.36 g/L respectively. The fermentation of Marasmius sp. in SSF on agricultural waste shows a great potential for the production of laccase.

  13. Optimization of parameters for bonnet polishing based on the minimum residual error method

    Science.gov (United States)

    Wang, Chunjin; Yang, Wei; Ye, Shiwei; Wang, Zhenzhong; Zhong, Bo; Guo, Yinbiao; Xu, Qiao

    2014-07-01

    For extremely high accuracy optical elements, the residual error induced by the superposition of the tool influence function cannot be ignored and leads to medium-high frequency errors. Even though the continuous computer-controlled optical surfacing process is better than the discrete one, which can decrease this error to a certain degree, the error still exists in scanning directions when adopting the raster path. The purpose of this paper is to optimize the parameters used in bonnet polishing to restrain this error. The formation of this error was theoretically demonstrated and will also be further experimentally presented using our newly designed prototype. Orthogonal simulation experiments were designed for the following five major operating parameters (some of them are normalized) at four levels: inner pressure, z offset, raster distance, H-axis speed, and precession angle. The minimum residual error method was used to evaluate the simulations. The results showed the impact of the evaluated parameters on the residual error. The parameters in descending order of impact are as follows: raster distance, z offset, inner pressure, H-axis speed, and precession angle. An optimal combination of these five parameters among the four levels considered, based on the minimum residual error method, was determined.

  14. Estimating parameters of the variable infiltration capacity model using ant colony optimization.

    Science.gov (United States)

    Yue, JiaJia; Pang, Bo; Xu, ZongXue

    Because hydrological models are so important for addressing environmental problems, parameter calibration is a fundamental task for applying them. A broadly used method for obtaining model parameters for the past 20 years is the evolutionary algorithm. This approach can estimate a set of unknown model parameters by simulating the evolution process. The ant colony optimization (ACO) algorithm is a type of evolutionary algorithm that has shown a strong ability in tackling combinatorial problems and is suitable for hydrological model calibration. In this study, an ACO based on the grid partitioning strategy was applied to the parameter calibration of the variable infiltration capacity (VIC) model for the Upper Heihe River basin and Xitiaoxi River basin, China. The shuffled complex evolution (SCE-UA) algorithm was used to test the applicability of the ACO. The results show that ACO is capable of model calibration of the VIC model; the Nash-Sutcliffe coefficient of efficiency is 0.62 and 0.81 in calibration and 0.65 and 0.86 in validation for the Upper Heihe River basin and Xitiaoxi River basin respectively, which are similar to the SCE-UA results. Despite the encouraging results obtained thus far, further studies could still be performed on the parameter optimization of an ACO to enlarge its applicability to more distributed hydrological models.

  15. Multiobjective Optimization of Injection Molding Process Parameters for the Precision Manufacturing of Plastic Optical Lens

    Directory of Open Access Journals (Sweden)

    Junhui Liu

    2017-01-01

    Full Text Available Injection molding process parameters (IMPP have a significant effect on the optical performance and surface waviness of precision plastic optical lens. This paper presents a set of procedures for the optimization of IMPP, with haze ratio (HR reflecting the optical performance and peak-to-valley 20 (PV20 reflecting the surface waviness as the optimization objectives. First, the orthogonal experiment was carried out with the Taguchi method, and the results were analyzed by ANOVA to screen out the IMPP having a significant effect on the objectives. Then, the 34 full-factor experiment was conducted on the key IMPP, and the experimental results were used as the training and testing samples. The BPNN algorithm and the M-SVR algorithm were applied to establish the mapping relationships between the IMPP and objectives. Finally, the multiple-objective optimization was performed by applying the nondominated sorting genetic algorithm (NSGA-II, with the built M-SVR models as the fitness function of the objectives, to obtain a Pareto-optimal set, which improved the quality of plastic optical lens comprehensively. Through the experimental verification on the optimization results, the mean prediction error (MPE of HR and PV20 is 7.16% and 9.78%, respectively, indicating that the optimization method has high accuracy.

  16. Machining parameters optimization during machining of Al/5 wt% alumina metal matrix composite by fiber laser

    Science.gov (United States)

    Ghosal, Arindam; Patil, Pravin

    2017-06-01

    This experimental work presents the study of machining parameters of Ytterbium fiber laser during machining of 5 mm thick Aluminium/5wt%Alumina-MMC (Metal Matrix Composite). Response surface methodology (RSM) is used to achieve the optimization i.e. minimize hole tapering and maximize Material Removal Rate (MRR). A mathematical model has been developed and ANOVA has been done for correlating the interactive and higher-order influences of Ytterbium fiber laser machining parameters (laser power, modulation frequency, gas pressure, wait time, pulse width) on Material Removal Rate (MRR) and hole tapering during machining process.

  17. 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.

  18. Vehicle-Routing Optimization for Municipal Solid Waste Collection Using Genetic Algorithm: The Case of Southern Nablus City

    Directory of Open Access Journals (Sweden)

    Assaf Ramiz

    2017-09-01

    Full Text Available Municipalities are responsible for solid waste collectiont for environmental, social and economic purposes. Practices of municipalities should be effective and efficient, with the objectives of reducing the total incurred costs in the solid waste collection network concurrently achieving the highest service level. This study aims at finding the best routes of solid waste collection network in Nablus city-Palestine. More specifically, the study seeks the optimal route that minimizes the total travelled distance by the trucks and hence the resulted costs. The current situation is evaluated and the problem is modelled as a Vehicle Routing Problem (VRP. The VRP is then optimized via a genetic algorithm. Specifically, compared to the current situation, the trucks total travelled distance was reduced by 66%, whereas the collection time was reduced from 7 hours per truck-trip to 2.3 hours. The findings of this study is useful for all municipality policy makers that are responsible for solid waste collection.

  19. Vehicle-Routing Optimization for Municipal Solid Waste Collection Using Genetic Algorithm: The Case of Southern Nablus City

    Science.gov (United States)

    Assaf, Ramiz; Saleh, Yahya

    2017-09-01

    Municipalities are responsible for solid waste collectiont for environmental, social and economic purposes. Practices of municipalities should be effective and efficient, with the objectives of reducing the total incurred costs in the solid waste collection network concurrently achieving the highest service level. This study aims at finding the best routes of solid waste collection network in Nablus city-Palestine. More specifically, the study seeks the optimal route that minimizes the total travelled distance by the trucks and hence the resulted costs. The current situation is evaluated and the problem is modelled as a Vehicle Routing Problem (VRP). The VRP is then optimized via a genetic algorithm. Specifically, compared to the current situation, the trucks total travelled distance was reduced by 66%, whereas the collection time was reduced from 7 hours per truck-trip to 2.3 hours. The findings of this study is useful for all municipality policy makers that are responsible for solid waste collection.

  20. Parameter optimization for transitions between memory states in small arrays of Josephson junctions

    Science.gov (United States)

    Rezac, J. D.; Imam, N.; Braiman, Y.

    2017-05-01

    Coupled arrays of Josephson junctions possess multiple stable zero voltage states. Such states can store information and consequently can be utilized for cryogenic memory applications. Basic memory operations can be implemented by sending a pulse to one of the junctions and studying transitions between the states. In order to be suitable for memory operations, such transitions between the states have to be fast and energy efficient. In this paper we employed simulated annealing, a stochastic optimization algorithm, to study parameter optimization of array parameters which minimizes times and energies of transitions between specifically chosen states that can be utilized for memory operations (Read, Write, and Reset). Simulation results show that such transitions occur with access times on the order of 10-100 ps and access energies on the order of 10-19-5×10-18 J. Numerical simulations are validated with approximate analytical results.

  1. The effect of key parameters on the design of an optimized caes power plant

    Directory of Open Access Journals (Sweden)

    Assadi M. Khalaji

    2016-01-01

    Full Text Available Due to the significant variations in electricity generation and its demand, the power plant owners are encountered with challenges of economic operation. Among all, Compressed air energy storage (CAES technology has proposed itself as a reliable and efficient solution to match the two sides. This paper deals with a modeled compressed air energy storage power plant which has been optimized thermodynamically through an efficient genetic algorithm code. The results of this optimized model, considered as the base case, show that the power plant is technically and financially justifiable. In order to obtain a more tangible realization, it is necessary to verify the results against the variation of key parameters. In this study, the sensitivity analysis is performed based on main parameters including plant loading and ambient condition and the resultant trends of each case are presented. This approach will help the designers to analyze the quality of their designs in different situations.

  2. Physiochemical parameters optimization for enhanced nisin production by Lactococcus lactis (MTCC 440

    Directory of Open Access Journals (Sweden)

    Puspadhwaja Mall

    2010-02-01

    Full Text Available The influence of various physiochemical parameters on the growth of Lactococcus lactis sub sp. lactis MTCC 440 was studied at shake flask level for 20 h. Media optimization (MRS broth was studied to achieve enhanced growth of the organism and also nisin production. Bioassay of nisin was done with agar diffusion method using Streptococcus agalactae NCIM 2401 as indicator strain. MRS broth (6%, w/v with 0.15μg/ml of nisin supplemented with 0.5% (v/v skimmed milk was found to be the best for nisin production as well as for growth of L lactis. The production of nisin was strongly influenced by the presence of skimmed milk and nisin in MRS broth. The production of nisin was affected by the physical parameters and maximum nisin production was at 30(0C while the optimal temperature for biomass production was 37(0C.

  3. The analysis of ground penetrating radar signal based on generalized S transform with parameters optimization

    Science.gov (United States)

    Xue, Wei; Zhu, Jichao; Rong, Xia; Huang, Yujin; Yang, Yue; Yu, Yunyun

    2017-05-01

    Ground penetrating radar (GPR) is widely used for subsurface detection due to the nondestructive characteristics. GPR signal is non-stationary because of complex medium environment, and time-frequency analysis is the powerful tool for the research of GPR signal. In this paper, a new generalized S transform with parameters optimization is proposed to analyze the GPR signal. In the proposed scheme, first a flexible window function replaces the fixed window function of S transform, then the criterion of time-frequency concentration is used to optimize the parameters of the window function, the aim is to improve the time-frequency resolution and applicability of S transform. The experimental results for synthetic data and practical GPR data show the proposed scheme can enhance the energy concentration in time-frequency domain effectively and provide better layer recognition and target detection performance.

  4. A Class of Parameter Estimation Methods for Nonlinear Muskingum Model Using Hybrid Invasive Weed Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Aijia Ouyang

    2015-01-01

    Full Text Available Nonlinear Muskingum models are important tools in hydrological forecasting. In this paper, we have come up with a class of new discretization schemes including a parameter θ to approximate the nonlinear Muskingum model based on general trapezoid formulas. The accuracy of these schemes is second order, if θ≠1/3, but interestingly when θ=1/3, the accuracy of the presented scheme gets improved to third order. Then, the present schemes are transformed into an unconstrained optimization problem which can be solved by a hybrid invasive weed optimization (HIWO algorithm. Finally, a numerical example is provided to illustrate the effectiveness of the present methods. The numerical results substantiate the fact that the presented methods have better precision in estimating the parameters of nonlinear Muskingum models.

  5. 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

    Selective laser melting is yet to become a standardized industrial manufacturing technique. The process continues to suffer from defects such as distortions, residual stresses, localized deformations and warpage caused primarily due to the localized heating, rapid cooling and high temperature...... gradients that occur during the process. While process monitoring and control of selective laser melting is an active area of research, establishing the reliability and robustness of the process still remains a challenge.In this paper, a methodology for generating reliable, optimized scanning paths...... and process parameters for selective laser melting of a standard sample is introduced. The processing of the sample is simulated by sequentially coupling a calibrated 3D pseudo-analytical thermal model with a 3D finite element mechanical model.The optimized processing parameters are subjected to a Monte Carlo...

  6. Improvement of properties of aluminosilicate pastes based on optimization of curing parameters

    Science.gov (United States)

    Kočí, Václav; Rovnaníková, Pavla; Černý, Robert

    2017-07-01

    Alkali-activated binders represent a low-energy alternative to traditional binders based on lime or cement. In this paper, a new binder of this type is designed and the influence of curing parameters on its mechanical properties, namely 7-days compressive strength, is investigated. The curing parameters include the curing temperature and the period of exposure. To maximize the compressive strength of the binder, simplex optimization procedure is applied in order to demonstrate its applicability for this research. The preliminary results indicate that the procedure is able to reach positive results as the compressive strength is found to increase by ˜11 %. As this improvement is achieved already after the first optimization step, it can be concluded that this approach has a potential to be more effective than traditional empirical design which is common in building materials engineering.

  7. Performance Evaluation and Parameter Optimization of SoftCast Wireless Video Broadcast

    Directory of Open Access Journals (Sweden)

    Dongxue Yang

    2015-08-01

    Full Text Available Wireless video broadcast plays an imp ortant role in multimedia communication with the emergence of mobile video applications. However, conventional video broadcast designs suffer from a cliff effect due to separated source and channel encoding. The newly prop osed SoftCast scheme employs a cross-layer design, whose reconstructed video quality is prop ortional to the channel condition. In this pap er, we provide the p erformance evaluation and the parameter optimization of the SoftCast system. Optimization principles on parameter selection are suggested to obtain a b etter video quality, o ccupy less bandwidth and/or utilize lower complexity. In addition, we compare SoftCast with H.264 in the LTE EPA scenario. The simulation results show that SoftCast provides a b etter p erformance in the scalability to channel conditions and the robustness to packet losses.

  8. Slot Parameter Optimization for Multiband Antenna Performance Improvement Using Intelligent Systems

    Directory of Open Access Journals (Sweden)

    Erdem Demircioglu

    2015-01-01

    Full Text Available This paper discusses bandwidth enhancement for multiband microstrip patch antennas (MMPAs using symmetrical rectangular/square slots etched on the patch and the substrate properties. The slot parameters on MMPA are modeled using soft computing technique of artificial neural networks (ANN. To achieve the best ANN performance, Particle Swarm Optimization (PSO and Differential Evolution (DE are applied with ANN’s conventional training algorithm in optimization of the modeling performance. In this study, the slot parameters are assumed as slot distance to the radiating patch edge, slot width, and length. Bandwidth enhancement is applied to a formerly designed MMPA fed by a microstrip transmission line attached to the center pin of 50 ohm SMA connecter. The simulated antennas are fabricated and measured. Measurement results are utilized for training the artificial intelligence models. The ANN provides 98% model accuracy for rectangular slots and 97% for square slots; however, ANFIS offer 90% accuracy with lack of resonance frequency tracking.

  9. LABORATORY OPTIMIZATION TESTS OF TECHNETIUM DECONTAMINATION OF HANFORD WASTE TREATMENT PLANT LOW ACTIVITY WASTE OFF-GAS CONDENSATE SIMULANT

    Energy Technology Data Exchange (ETDEWEB)

    Taylor-Pashow, K.; Nash, C.; McCabe, D.

    2014-09-29

    compatible with longterm tank storage and immobilization methods. For this new application, testing is needed to demonstrate acceptable treatment sorbents and precipitating agents and measure decontamination factors for additional radionuclides in this unique waste stream. The origin of this LAW Off-Gas Condensate stream will be the liquids from the Submerged Bed Scrubber (SBS) and the Wet Electrostatic Precipitator (WESP) from the LAW melter off-gas system. The stream is expected to be a dilute salt solution with near neutral pH, and will likely contain some insoluble solids from melter carryover. The soluble components are expected to be mostly sodium and ammonium salts of nitrate, chloride, and fluoride. This stream has not been generated yet and will not be available until the WTP begins operation, but a simulant has been produced based on models, calculations, and comparison with pilot-scale tests. One of the radionuclides that is volatile and expected to be in greatest abundance in this LAW Off-Gas Condensate stream is Technetium-99 ({sup 99}Tc). Technetium will not be removed from the aqueous waste in the Hanford WTP, and will primarily end up immobilized in the LAW glass by repeated recycle of the off-gas condensate into the LAW melter. Other radionuclides that are low but are also expected to be in measurable concentration in the LAW Off-Gas Condensate are {sup 129}I, {sup 90}Sr, {sup 137}Cs, {sup 241}Pu, and {sup 241}Am. These are present due to their partial volatility and some entrainment in the off-gas system. This report discusses results of optimized {sup 99}Tc decontamination testing of the simulant. Testing examined use of inorganic reducing agents for {sup 99}Tc. Testing focused on minimizing the quantity of sorbents/reactants added, and minimizing mixing time to reach the decontamination targets in this simulant formulation. Stannous chloride and ferrous sulfate were tested as reducing agents to determine the minimum needed to convert soluble pertechnetate

  10. Effect of data assimilation parameters on the optimized surface CO2 flux in Asia

    Science.gov (United States)

    Kim, Hyunjung; Kim, Hyun Mee; Kim, Jinwoong; Cho, Chun-Ho

    2017-09-01

    In this study, CarbonTracker, an inverse modeling system based on the ensemble Kalman filter, was used to evaluate the effects of data assimilation parameters (assimilation window length and ensemble size) on the estimation of surface CO2 fluxes in Asia. Several experiments with different parameters were conducted, and the results were verified using CO2 concentration observations. The assimilation window lengths tested were 3, 5, 7, and 10 weeks, and the ensemble sizes were 100, 150, and 300. Therefore, a total of 12 experiments using combinations of these parameters were conducted. The experimental period was from January 2006 to December 2009. Differences between the optimized surface CO2 fluxes of the experiments were largest in the Eurasian Boreal (EB) area, followed by Eurasian Temperate (ET) and Tropical Asia (TA), and were larger in boreal summer than in boreal winter. The effect of ensemble size on the optimized biosphere flux is larger than the effect of the assimilation window length in Asia, but the importance of them varies in specific regions in Asia. The optimized biosphere flux was more sensitive to the assimilation window length in EB, whereas it was sensitive to the ensemble size as well as the assimilation window length in ET. The larger the ensemble size and the shorter the assimilation window length, the larger the uncertainty (i.e., spread of ensemble) of optimized surface CO2 fluxes. The 10-week assimilation window and 300 ensemble size were the optimal configuration for CarbonTracker in the Asian region based on several verifications using CO2 concentration measurements.

  11. A LECCS model parameter optimization algorithm for EMC designs of IC/LSI systems

    OpenAIRE

    Funabiki, Nobuo; Nomura, Yohei; Kawashima, Jun; Minamisawa, Yuichiro; Wada, Osami

    2006-01-01

    In this paper, we propose a parameter optimization algorithm for EMC macro-modeling of IC/LSI power currents called the LECCS (linear equivalent circuit and current source) model. The unnecessary electro-magnetic wave from a digital electronics device may cause the electromagnetic interference (EMI) to other apparatus. Thus, its reduction has been regarded as one of the highest priority issues in digital electronics device designs. In order to accurately simulate high-frequency currents from ...

  12. Optimization of Processing Parameters for Lettuce Vacuum Osmotic Dehydration Using Response Surface Methodology

    OpenAIRE

    Yuan Yuejin; Tan Libin; Xu Yingying; Dong Jixian; Zhao Yu; Yuan Yueding

    2018-01-01

    In order to obtain the optimal technological parameters of lettuce vacuum osmotic dehydration, the effects of osmotic temperature, slice thickness, sucrose concentration, and vacuum degree on the vacuum osmotic dehydration were explored. The lettuce water loss rate and solid gain rate decreased with the increase of slice thickness and vacuum degree, and increased with the increase of sucrose concentration and osmotic temperature. Response surface methodology was applied to analyze the influen...

  13. Single- and multi-objective genetic algorithm optimization for identifying soil parameters

    OpenAIRE

    Papon, Aurélie; Riou, Yvon; Dano, Christophe; Hicher, Pierre Yves

    2012-01-01

    International audience; This paper discusses the quality of the procedure employed in identifying soil parameters by inverse analysis. This procedure includes a FEM-simulation for which two constitutive modelsa linear elastic perfectly plastic MohrCoulomb model and a strain-hardening elasto-plastic modelare successively considered. Two kinds of optimization algorithms have been used: a deterministic simplex method and a stochastic genetic method. The soil data come from the results of two pre...

  14. Seismic imaging of glaciomarine sediments of Antarctica: Optimizing the acquisition parameters

    Digital Repository Service at National Institute of Oceanography (India)

    Pandey, D.; Chaubey, A.K.; Rajan, S.

    of Marine Sciences Vol. 37(4), December 2008, pp. 412-418 Seismic imaging of glaciomarine sediments of Antarctica: Optimizing the acquisition parameters Dhananjai Pandey1*, Anil Chaubey2, S Rajan1 1National Centre for Antarctic and Ocean... discussions on the reflection signature of the glaciomarine sediments of the continental slope and rise off Prydz Bay in east Antarctica in terms of depositional processes. The present study is based on synthetic seismogram modeling using finite...

  15. Optimal parameters of dental ultrasonic instrument diamond coating for enamel removal

    OpenAIRE

    Liao, Yunn-Shiuan; Lin, Ting-Chang; Lee, Ming-Shu; Su, Po-Yuan; Chen, Yen-Liang; Chang, Hao-Hueng; Lin, Chun-Pin

    2015-01-01

    Background/purpose: Ultrasonic instruments are commonly used in dentistry because of their safety, acceptance by patients, ease of viewing the surgical area, and highly precise cutting. However, they do not efficiently remove enamel. The aim of this study is to optimize the surface coating parameters of an ultrasonic diamond grinding tip for enamel removal. Materials and methods: The experiments were conducted using a triple-axle precision moving platform. The ultrasonic handpiece was moun...

  16. Transduction dependent optimization of electromechanical parameters for electrostatically actuated MEMS/NEMS resonators.

    Science.gov (United States)

    Yan, Jize; Lee, Joshua E-Y; Seshia, Ashwin A

    2010-11-01

    This paper demonstrates an accurate model to predict the overall effective mass in micro- and nanomechanical resonators with non-uniform deformation along the transduction area. The model is verified experimentally through parameter extraction on various types of resonators with an error less than 3% well within the bounds dictated by manufacturing tolerances. Based on the model, an optimization of transduction electrode designs is proposed for micro- and nanomechanical resonators vibrating in the fabrication plane.

  17. 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.

  18. Modelling and Optimization of Process Parameters for Strawberry Osmotic Dehydration Using Central Composite Rotatable Design

    Directory of Open Access Journals (Sweden)

    Bei Liu

    2017-01-01

    Full Text Available Osmotic dehydration conditions for strawberry were optimized using central composite rotatable design. The optimal conditions included osmotic dehydration temperature of 59.5°C, osmotic dehydration time of 245.6 min, and sorbitol concentration of 66.8%. Water loss (WL exhibited a response value of 52.5% and was mainly influenced by sorbitol concentration (p≤0.01, followed by osmotic dehydration temperature (p≤0.01 and time (p≤0.01. The optimal condition was validated and found to be fitted well with the experimental data. The osmotic dehydration of strawberry was significantly influenced by osmotic dehydration temperature and time and sorbitol concentration. Based on the parameters of ANOVA, the predicted model for WL rate established by response surface quadratic regression provided an adequate mathematical description of the osmotic dehydration of strawberry.

  19. SVM classification model in depression recognition based on mutation PSO parameter optimization

    Directory of Open Access Journals (Sweden)

    Zhang Ming

    2017-01-01

    Full Text Available At present, the clinical diagnosis of depression is mainly through structured interviews by psychiatrists, which is lack of objective diagnostic methods, so it causes the higher rate of misdiagnosis. In this paper, a method of depression recognition based on SVM and particle swarm optimization algorithm mutation is proposed. To address on the problem that particle swarm optimization (PSO algorithm easily trap in local optima, we propose a feedback mutation PSO algorithm (FBPSO to balance the local search and global exploration ability, so that the parameters of the classification model is optimal. We compared different PSO mutation algorithms about classification accuracy for depression, and found the classification accuracy of support vector machine (SVM classifier based on feedback mutation PSO algorithm is the highest. Our study promotes important reference value for establishing auxiliary diagnostic used in depression recognition of clinical diagnosis.

  20. Numerical simulation and parameter optimization of automobile reinforced inner plate forming process

    Science.gov (United States)

    Su, Yanhong; Ma, Yaxin; Men, Zhengxing; Tang, Yue; Wang, Menghan

    2017-08-01

    Automotive reinforced inner plate is a typical sheet metal stamping parts, which is characterized by complex shape, the need for multi-channel process to complete. If the parts can be based on the needs and possibilities of a reasonable combination of some processes, not only can improve the quality of the workpiece, but also can save mold costs and improve production efficiency. The finite element analysis software Dy naform is used to develop the finite element model, and the forming process of the automotive reinforced inner plate was simulated and analyzed. The process parameters influencing the forming quality were optimized, and the shape and size of the blank were optimized to obtain the ideal billet state. In the wrinkled surface on the local optimization, a good control of the product forming quality. Finally, the simulation results are compared with those of the actual production. The correctness of the numerical simulation is verified.

  1. Simultaneous parameter and tolerance optimization of structures via probability-interval mixed reliability model

    DEFF Research Database (Denmark)

    Luo, Yangjun; Wu, Xiaoxiang; Zhou, Mingdong

    2015-01-01

    Both structural sizes and dimensional tolerances strongly influence the manufacturing cost and the functional performance of a practical product. This paper presents an optimization method to simultaneously find the optimal combination of structural sizes and dimensional tolerances. Based...... points (TPPs) and the worst case points (WCPs), which shows better performance than traditional approaches for highly nonlinear problems. Numerical results reveal that reasonable dimensions and tolerances can be suggested for the minimum manufacturing cost and a desirable structural safety....... on a probability-interval mixed reliability model, the imprecision of design parameters is modeled as interval uncertainties fluctuating within allowable tolerance bounds. The optimization model is defined as to minimize the total manufacturing cost under mixed reliability index constraints, which are further...

  2. The effect of system parameters on the biogas production from anaerobic digestion of livestock wastes

    Science.gov (United States)

    Animal wastes can serve as the feedstock for biogas production (mainly methane) that could be used as alternative energy source. The green energy derived from animal wastes is considered to be carbon neutral and offsetting those generated from fossil fuels. In this study, an evaluation of system p...

  3. Optimization of glycerol fed-batch fermentation in different reactor states: a variable kinetic parameter approach.

    Science.gov (United States)

    Xie, Dongming; Liu, Dehua; Zhu, Haoli; Zhang, Jianan

    2002-05-01

    To optimize the fed-batch processes of glycerol fermentation in different reactor states, typical bioreactors including 500-mL shaking flask, 600-mL and 15-L airlift loop reactor, and 5-L stirred vessel were investigated. It was found that by reestimating the values of only two variable kinetic parameters associated with physical transport phenomena in a reactor, the macrokinetic model of glycerol fermentation proposed in previous work could describe well the batch processes in different reactor states. This variable kinetic parameter (VKP) approach was further applied to model-based optimization of discrete-pulse feed (DPF) strategies of both glucose and corn steep slurry for glycerol fed-batch fermentation. The experimental results showed that, compared with the feed strategies determined just by limited experimental optimization in previous work, the DPF strategies with VKPs adjusted could improve glycerol productivity at least by 27% in the scale-down and scale-up reactor states. The approach proposed appeared promising for further modeling and optimization of glycerol fermentation or the similar bioprocesses in larger scales.

  4. Optimization of Silicon MZM Fabrication Parameters for High Speed Short Reach Interconnects at 1310 nm

    Directory of Open Access Journals (Sweden)

    Alexis Abraham

    2016-11-01

    Full Text Available Optical modulators are key components to realize photonic circuits, and Mach-Zehnder modulators (MZM are often used for high speed short reach interconnects. In order to maximize the tolerable path loss of a transmission link at a given bitrate, the MZM needs to be optimized. However, the optimization can be complex since the overall link performance depends on various parameters, and, for the MZM in particular, implies several trade-offs between efficiency, losses, and bandwidth. In this work, we propose a general and rigorous method to optimize silicon MZM. We first describe the optical link, and the numerical method used for this study. Then we present the results associated to the active region for 1310 nm applications. An analytical model is generated, and allows us to quickly optimize the p-n junction depending of the targeted performances for the MZM. Taking into account the required optical link parameters, the maximum tolerable path losses for different length of MZM is determined. By applying this method, simulations show that the optimum MZM length for 25 Gbps applications is 4 mm with an efficiency of 1.87 V·cm, 0.52 dB/mm of losses. A tolerable path loss of more than 25 dB is obtained.

  5. Optimization of pump parameters for gain flattened Raman fiber amplifiers based on artificial fish school algorithm

    Science.gov (United States)

    Jiang, Hai Ming; Xie, Kang; Wang, Ya Fei

    2011-11-01

    In this work, a novel metaheuristic named artificial fish school algorithm is introduced into the optimization of pump parameters for the design of gain flattened Raman fiber amplifiers for the first time. Artificial fish school algorithm emulates three simple social behaviors of a fish in a school, namely, preying, swarming and following, to optimize a target function. In this algorithm the pump wavelengths and power levels are mapped respectively to the state of a fish in a school, and the gain of a Raman fiber amplifier is mapped to the concentration of a food source for the fish school to search. Application of this algorithm to the design of a C-band gain flattened Raman fiber amplifier leads to an optimized amplifier that produces a flat gain spectrum with 0.63 dB in band ripple for given conditions. This result demonstrates that the artificial fish school algorithm is efficient for the optimization of pump parameters of gain flattened Raman fiber amplifiers.

  6. Optimizing Key Parameters of Ground Delay Program with Uncertain Airport Capacity

    Directory of Open Access Journals (Sweden)

    Jixin Liu

    2017-01-01

    Full Text Available The Ground Delay Program (GDP relies heavily on the capacity of the subject airport, which, due to its uncertainty, adds to the difficulty and suboptimality of GDP operation. This paper proposes a framework for the joint optimization of GDP key parameters including file time, end time, and distance. These parameters are articulated and incorporated in a GDP model, based on which an optimization problem is proposed and solved under uncertain airport capacity. Unlike existing literature, this paper explicitly calculates the optimal GDP file time, which could significantly reduce the delay times as shown in our numerical study. We also propose a joint GDP end-time-and-distance model solved with genetic algorithm. The optimization problem takes into account the GDP operational efficiency, airline and flight equity, and Air Traffic Control (ATC risks. A simulation study with real-world data is undertaken to demonstrate the advantage of the proposed framework. It is shown that, in comparison with the current GDP in operation, the proposed solution reduces the total delay time, unnecessary ground delay, and unnecessary ground delay flights by 14.7%, 50.8%, and 48.3%, respectively. The proposed GDP strategy has the potential to effectively reduce the overall delay while maintaining the ATC safety risk within an acceptable level.

  7. Optimization of some parameters on agglomeration performance of Zonguldak bituminous coal by oil agglomeration

    Energy Technology Data Exchange (ETDEWEB)

    N. Aslan; I. Unal [Cumhuriyet University, Sivas (Turkey). Mining Engineering Department

    2009-03-15

    In this study, the optimization of some parameters on agglomeration performance of Zonguldak bituminous coal by oil agglomeration was discussed. A three-level Box-Behnken design combining with a response surface methodology (RSM) and quadratic programming (QP) were employed for modeling and optimization some operations parameters on oil agglomeration performance. The relationship between the responses, i.e., grade and recovery, and four process parameters, i.e., amount of oil, agitation time, agitation rate and solid content were presented as empirical model equations for both grade and recovery on oil agglomeration. The model equations were then optimized individually using the quadratic programming method to maximize both for grade and recovery within the experimental range studied. The optimum conditions were found to be 14.61% for amount of oil, 8.94 min for agitation time, 1554 rpm for agitation rate and 5% for solid content to achieve the maximum grade. The maximum model prediction of 0.650 grade at these optimum conditions is higher than any value obtained in the initial tests conducted. Similarly, the conditions for maximum recovery were found to be 20.60% for amount of oil, 5 min for agitation time, 1800 rpm for agitation rate and 19.48% for solid content with a prediction of 96.90% recovery, which is also higher than any other recovery obtained in the initial tests conducted. 34 refs., 5 figs., 7 tabs.

  8. Parameter Estimation of Viscoelastic Materials: A Test Case with Different Optimization Strategies

    Science.gov (United States)

    Fernanda, M.; Costa, P.; Ribeiro, C.

    2011-09-01

    In this work, and based on numerical optimization techniques, constitutive parameters for viscoelastic materials are determined using a inverse problem formulation. The optimization methodology is based on experimental results obtained in the frequency domain, for a CFRP-Carbon Fibre Reinforced Polymer, through DMA-Dynamic Mechanical Analysis. The relaxation modulus of viscoelastic materials is given by a summation of decaying exponentiating functions, known as Prony series. Prony series, in time domain, are normally used to determine constitutive parameters for viscoelastic materials. In this paper, using the Fourier transform of the time domain Prony series, a nonlinear constrained least square problem based on Prony series representations of storage and loss modulus, for the considered material, is analyzed. A case study considering the estimation of 2N viscoelastic parameters, N = 1,2,⋯11, is taken as a benchmark. The nonlinear constrained least square problems are solved using global and local optimization solvers. The computational results as well as the main conclusion are shown.

  9. Biological optimization of simultaneous boost on intra-prostatic lesions (DILs): sensitivity to TCP parameters.

    Science.gov (United States)

    Azzeroni, R; Maggio, A; Fiorino, C; Mangili, P; Cozzarini, C; De Cobelli, F; Di Muzio, N G; Calandrino, R

    2013-11-01

    The aim of this investigation was to explore the potential of biological optimization in the case of simultaneous integrated boost on intra-prostatic dominant lesions (DIL) and evaluating the impact of TCP parameters uncertainty. Different combination of TCP parameters (TD50 and γ50 in the Poisson-like model), were considered for DILs and the prostate outside DILs (CTV) for 7 intermediate/high-risk prostate patients. The aim was to maximize TCP while constraining NTCPs below 5% for all organs at risk. TCP values were highly depending on the parameters used and ranged between 38.4% and 99.9%; the optimized median physical doses were in the range 94-116 Gy and 69-77 Gy for DIL and CTV respectively. TCP values were correlated with the overlap PTV-rectum and the minimum distance between rectum and DIL. In conclusion, biological optimization for selective dose escalation is feasible and suggests prescribed dose around 90-120 Gy to the DILs. The obtained result is critically depending on the assumptions concerning the higher radioresistence in the DILs. In case of very resistant clonogens into the DIL, it may be difficult to maximize TCP to acceptable levels without violating NTCP constraints. Copyright © 2012 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  10. Parameter estimation in biogeochimical surface model using nonlinear inversion: optimization with measurements over a pine forest.

    Science.gov (United States)

    Santaren, D.; Peylin, P.; Viovy, N.; Ciais, P.

    2003-04-01

    Global model of Carbone, water, and energy exchanges between the biosphere and the atmosphere are usually validated and calibrated with intensive measurement made over specific ecosystem like those of the fluxnet networks.However the nonlinear dependance between fluxes and model parameters generally complicate the optimization of the major parameters.In this study, we estimate few key parameters of the ORCHIDEE french model,using diurnal variation measurements of latent heat,sensible heat and net CO2 fluxes for 3 weeks over pine forest (Landes, France).The model is forced with the observed climatic forcing: Temperature, income solar radiations,wind velocity norm, air humidity, pressure and precipitations. We will first present the inverse methodology and the problem linkedto the non linearity. The result of the optimization shows correlations within the initial ensemble of parameters which allow us to choose only five parameters determined independently from the observations. Directly related to the net CO2 flux, the maximum rate of carboxylation,Vcmax,and the stomatal conductance, gs, are significantly changed from their apriori estimate for that period. The aerodynamic resistance, the albedo and a parameter linked to maintenance respiration were also modified within their physical range.Overall the model fit to the data was largely improved. Note however that some discrepancies remain for sensible heat flux which would probably require some model improvements for the stocking of energy in the soil. Such work is currently extended in time to account for parameter variations between the season. The application to other ecosystems and with the supplementary data of the Leaf Area Index will be also discussed.

  11. Reduction of MRI signal distortion from titanium intracavitary brachytherapy applicator by optimizing pulse sequence parameters.

    Science.gov (United States)

    Sullivan, Thomas P; Harkenrider, Matthew M; Surucu, Murat; Wood, Abbie M; Yacoub, Joseph H; Shea, Steven M

    2017-11-22

    To demonstrate that optimized pulse sequence parameters for a T2-weighted (T2w) fast spin echo acquisition reduced artifacts from a titanium brachytherapy applicator compared to conventional sequence parameters. Following Institutional Review Board approval and informed consent, seven patients were successfully imaged with both standard sagittal T2w fast spin echo parameters (voxel size of 0.98 × 0.78 × 4.0 mm 3 ; readout bandwidth of 200 Hz/px; repetition time of 2800 ms; echo time of 91 ms; echo train length of 15; 36 slices; and imaging time of 3:16 min) and an additional optimized T2w sequence (voxel size of 0.98 × 0.98 × 4.0 mm 3 ; readout bandwidth of 500 Hz/px; repetition time of 3610 ms; echo time of 91 ms; echo train length of 25; 18-36 slices; and imaging time of 1:15-2:30 min), which had demonstrated artifact reduction in prior phantom work. Visualized intracavitary tandem was hand-segmented by two of the authors. Three body imaging radiologists assessed image quality and intraobserver agreement scores were analyzed. The average segmented volume of the intracavitary applicator significantly (p parameters as compared to the standard pulse sequence. Comparison of experimental and standard T2w sequence qualitative scores for each reviewer showed no significant differences between the two techniques. This study demonstrated that pulse sequence parameter optimization can significantly reduce distortion artifact from titanium applicators while maintaining image quality and reasonable imaging times. Copyright © 2017 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

  12. Parameters Identification of Fluxgate Magnetic Core Adopting the Biogeography-Based Optimization Algorithm.

    Science.gov (United States)

    Jiang, Wenjuan; Shi, Yunbo; Zhao, Wenjie; Wang, Xiangxin

    2016-06-25

    The main part of the magnetic fluxgate sensor is the magnetic core, the hysteresis characteristic of which affects the performance of the sensor. When the fluxgate sensors are modelled for design purposes, an accurate model of hysteresis characteristic of the cores is necessary to achieve good agreement between modelled and experimental data. The Jiles-Atherton model is simple and can reflect the hysteresis properties of the magnetic material precisely, which makes it widely used in hysteresis modelling and simulation of ferromagnetic materials. However, in practice, it is difficult to determine the parameters accurately owing to the sensitivity of the parameters. In this paper, the Biogeography-Based Optimization (BBO) algorithm is applied to identify the Jiles-Atherton model parameters. To enhance the performances of the BBO algorithm such as global search capability, search accuracy and convergence rate, an improved Biogeography-Based Optimization (IBBO) algorithm is put forward by using Arnold map and mutation strategy of Differential Evolution (DE) algorithm. Simulation results show that IBBO algorithm is superior to Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Differential Evolution algorithm and BBO algorithm in identification accuracy and convergence rate. The IBBO algorithm is applied to identify Jiles-Atherton model parameters of selected permalloy. The simulation hysteresis loop is in high agreement with experimental data. Using permalloy as core of fluxgate probe, the simulation output is consistent with experimental output. The IBBO algorithm can identify the parameters of Jiles-Atherton model accurately, which provides a basis for the precise analysis and design of instruments and equipment with magnetic core.

  13. Multiobjective Optimization of Turning Cutting Parameters for J-Steel Material

    Directory of Open Access Journals (Sweden)

    Adel T. Abbas

    2016-01-01

    Full Text Available This paper presents a multiobjective optimization study of cutting parameters in turning operation for a heat-treated alloy steel material (J-Steel with Vickers hardness in the range of HV 365–395 using uncoated, unlubricated Tungsten-Carbide tools. The primary aim is to identify proper settings of the cutting parameters (cutting speed, feed rate, and depth of cut that lead to reasonable compromises between good surface quality and high material removal rate. Thorough exploration of the range of cutting parameters was conducted via a five-level full-factorial experimental matrix of samples and the Pareto trade-off frontier is identified. The trade-off among the objectives was observed to have a “knee” shape, in which certain settings for the cutting parameters can achieve both good surface quality and high material removal rate within certain limits. However, improving one of the objectives beyond these limits can only happen at the expense of a large compromise in the other objective. An alternative approach for identifying the trade-off frontier was also tested via multiobjective implementation of the Efficient Global Optimization (m-EGO algorithm. The m-EGO algorithm was successful in identifying two points within the good range of the trade-off frontier with 36% fewer experimental samples.

  14. Process Parameters Optimization for Producing AA6061/TiB2 Composites by Friction Stir Processing

    Directory of Open Access Journals (Sweden)

    Rao Santha Dakarapu

    2017-04-01

    Full Text Available Friction stir processing (FSP is solid state novel technique developed to refine microstructure and to improve the mechanical properties and be used to fabricate the aluminium alloy matrix composites. An attempt is made to fabricate AA6061/TiB2 aluminium alloy composite (AMCs and the influence of process parameters like rotational speed, transverse feed, axial load and percentage reinforcement on microstructure and mechanical properties were studied. The microstructural observations are carried out and revealed that the reinforcement particles (TiB2 were uniformly dispersed in the nugget zone. The Tensile strength and Hardness of composites were evaluated. It was observed that tensile strength, and hardness were increased with increased the rotational speed and percentage reinforcement of particles. The process parameters were optimized using Taguchi analysis (Single Variable and Grey analysis (Multi Variable. The most influential parameter was rotational speed in single variable method and multi variable optimization method. The ANOVA also done to know the percentage contribution of each parameter.

  15. Han's model parameters for microalgae grown under intermittent illumination: Determined using particle swarm optimization.

    Science.gov (United States)

    Pozzobon, Victor; Perre, Patrick

    2017-10-16

    This work provides a model and the associated set of parameters allowing for microalgae population growth computation under intermittent lightning. Han's model is coupled with a simple microalgae growth model to yield a relationship between illumination and population growth. The model parameters were obtained by fitting a dataset available in literature using Particle Swarm Optimization method. In their work, authors grew microalgae in excess of nutrients under flashing conditions. Light/dark cycles used for these experimentations are quite close to those found in photobioreactor, i.e. ranging from several seconds to one minute. In this work, in addition to producing the set of parameters, Particle Swarm Optimization robustness was assessed. To do so, two different swarm initialization techniques were used, i.e. uniform and random distribution throughout the search-space. Both yielded the same results. In addition, swarm distribution analysis reveals that the swarm converges to a unique minimum. Thus, the produced set of parameters can be trustfully used to link light intensity to population growth rate. Furthermore, the set is capable to describe photodamages effects on population growth. Hence, accounting for light overexposure effect on algal growth. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Anaerobic co-digestion of recalcitrant agricultural wastes: Characterizing of biochemical parameters of digestate and its impacts on soil ecosystem.

    Science.gov (United States)

    Muscolo, Adele; Settineri, Giovanna; Papalia, Teresa; Attinà, Emilio; Basile, Carmelo; Panuccio, Maria Rosaria

    2017-05-15

    Anaerobic digestion (AD) of organic wastes is a promising alternative to landfilling for reducing Greenhouse Gas Emission (GHG) and it is encouraged by current regulation in Europe. Biogas-AD produced, represents a useful source of green energy, while its by-product (digestate) is a waste, that needs to be safely disposal. The sustainability of anaerobic digestion plants partly depends on the management of their digestion residues. This study has been focused on the environmental and economic benefits of co-digest recalcitrant agricultural wastes such olive wastes and citrus pulp, in combination with livestock wastes, straw and cheese whey for biogas production. The aim of this work was to investigate the effects of two different bioenergy by-products on soil carbon stock, enzymes involved in nutrient cycling and microbial content. The two digestates were obtained from two plants differently fed: the first plant (Uliva) was powered with 60% of recalcitrant agricultural wastes, and 40% of livestock manure milk serum and maize silage. The second one (Fattoria) was fed with 40% of recalcitrant agricultural wastes and 60% of livestock manure, milk serum and maize silage. Each digestate, separated in liquid and solid fractions, was added to the soil at different concentrations. Our results evidenced that mixing and type of input feedstock affected the composition of digestates. Three months after treatments, our results showed that changes in soil chemical and biochemical characteristics depended on the source of digestate, the type of fraction and the concentration used. The mainly affected soil parameters were: Soil Organic Matter (SOM), Microbial Biomass Carbon (MBC), Fluorescein Diacetate Hydrolysis (FDA), Water Soluble Phenol (WSP) and Catalase (CAT) that can be used to assess the digestate agronomical feasibility. These results show that the agronomic quality of a digestate is strictly dependent on percentage and type of feedstocks that will be used to power the

  17. Particle Swarm Optimization with Power-Law Parameter Based on the Cross-Border Reset Mechanism

    Directory of Open Access Journals (Sweden)

    WANG, H.

    2017-11-01

    Full Text Available In order to improve the performance of traditional particle swarm optimization, this paper introduces the principle of Levy flight and cross-border reset mechanism. In the proposed particle swarm optimization, the dynamic variation of parameters meets the power-law distribution and the pattern of particles transition conforms to the Levy flight in the process of algorithm optimization. It means the particles make long distance movements in the search space with a small probability and make short distance movements with a large probability. Therefore, the particles can jump out of local optimum more easily and coordinate the global search and local search of particle swarm optimization. This paper also designs the cross-border reset mechanism to make particles regain optimization ability when stranding on the border of search space after a long distance movement. The simulation results demonstrate the proposed algorithms are easier to jump out of local optimum and have higher accuracy when compared with the existing similar algorithms based on benchmark test functions and handwriting character recognition system.

  18. A parameter optimization method to determine ski stiffness properties from ski deformation data.

    Science.gov (United States)

    Heinrich, Dieter; Mössner, Martin; Kaps, Peter; Nachbauer, Werner

    2011-02-01

    The deformation of skis and the contact pressure between skis and snow are crucial factors for carved turns in alpine skiing. The purpose of the current study was to develop and to evaluate an optimization method to determine the bending and torsional stiffness that lead to a given bending and torsional deflection of the ski. Euler-Bernoulli beam theory and classical torsion theory were applied to model the deformation of the ski. Bending and torsional stiffness were approximated as linear combinations of B-splines. To compute the unknown coefficients, a parameter optimization problem was formulated and successfully solved by multiple shooting and least squares data fitting. The proposed optimization method was evaluated based on ski stiffness data and ski deformation data taken from a recently published simulation study. The ski deformation data were used as input data to the optimization method. The optimization method was capable of successfully reproducing the shape of the original bending and torsional stiffness data of the ski with a root mean square error below 1 N m2. In conclusion, the proposed computational method offers the possibility to calculate ski stiffness properties with respect to a given ski deformation.

  19. 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.

  20. Effects of upper body parameters on biped walking efficiency studied by dynamic optimization

    Directory of Open Access Journals (Sweden)

    Kang An

    2016-12-01

    Full Text Available Walking efficiency is one of the considerations for designing biped robots. This article uses the dynamic optimization method to study the effects of upper body parameters, including upper body length and mass, on walking efficiency. Two minimal actuations, hip joint torque and push-off impulse, are used in the walking model, and minimal constraints are set in a free search using the dynamic optimization. Results show that there is an optimal solution of upper body length for the efficient walking within a range of walking speed and step length. For short step length, walking with a lighter upper body mass is found to be more efficient and vice versa. It is also found that for higher speed locomotion, the increase of the upper body length and mass can make the walking gait optimal rather than other kind of gaits. In addition, the typical strategy of an optimal walking gait is that just actuating the swing leg at the beginning of the step.