Optimization of the radioactive waste storage

International Nuclear Information System (INIS)

Dellamano, Jose Claudio

2005-01-01

Radioactive waste storage is the practice adopted in countries where the production of small quantities of radioactive waste does not justify the immediate investment in the construction of a repository. Accordingly, at IPEN, treated radioactive wastes, mainly solid compacted, have been stored for more than 20 years, in 200 dm 3 drums. The storage facility is almost complete and must be extended. Taking into account that a fraction of these wastes has decayed to a very low level due to the short half - life of some radionuclides and considering that 'retrieval for disposal as very low level radioactive waste' is one of the actions suggested to radioactive waste managers, the Laboratory of Waste Management of IPEN started a project to apply the concepts of clearance levels and exemption limits to optimize the radioactive waste storage capacity . This study has been carried out by determining the doses and costs related to two main options: either to maintain the present situation or to open the packages and segregate the wastes that may be subject to clearance, using the national, two international clearance levels and the annual public limit. Doses and costs were evaluated as well as the collective dose and the detriment cost. The analytical solution among the evaluated options was determined by using the technique to aid decision making known as cost-benefit analysis. At last, it was carried out the sensitivity analysis considering all criteria and parameters in order to assess the robustness of the analytical solution. This study can be used as base to other institutions or other countries with similar nuclear programs. (author)

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.

Optimization of municipal solid waste collection and transportation routes

International Nuclear Information System (INIS)

Das, Swapan; Bhattacharyya, Bidyut Kr.

2015-01-01

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

Optimal waste heat recovery and reuse in industrial zones

International Nuclear Information System (INIS)

Stijepovic, Mirko Z.; Linke, Patrick

2011-01-01

Significant energy efficiency gains in zones with concentrated activity from energy intensive industries can often be achieved by recovering and reusing waste heat between processing plants. We present a systematic approach to target waste heat recovery potentials and design optimal reuse options across plants in industrial zones. The approach first establishes available waste heat qualities and reuse feasibilities considering distances between individual plants. A targeting optimization problem is solved to establish the maximum possible waste heat recovery for the industrial zone. Then, a design optimization problem is solved to identify concrete waste heat recovery options considering economic objectives. The paper describes the approach and illustrates its application with a case study. -- Highlights: → Developed a systematic approach to target waste heat recovery potentials and to design optimal recovery and reuse options across plants in industrial zones. → Five stage approach involving data acquisition, analysis, assessment, targeting and design. → Targeting optimization problem establishes the maximum possible waste heat recovery and reuse limit for the industrial zone. → Design optimization problem provides concrete waste heat recovery and reuse network design options considering economic objectives.

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

Science.gov (United States)

Gupta, Ankur; Balomajumder, Chandrajit

2017-12-01

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

Optimizing High Level Waste Disposal

International Nuclear Information System (INIS)

Dirk Gombert

2005-01-01

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

Optimization of extraction parameters on the antioxidant properties of banana waste.

Science.gov (United States)

Toh, Pui Yee; Leong, Fei Shan; Chang, Sui Kiat; Khoo, Hock Eng; Yim, Hip Seng

2016-01-01

Banana is grown worldwide and consumed as ripe fruit or used for culinary purposes. Peels form about 18-33% of the whole fruit and are discarded as a waste product. With a view to exploiting banana peel as a source of valuable compounds, this study was undertaken to evaluate the effect of different extraction parameters on the antioxidant activities of the industrial by-product of banana waste (peel). Influence of different extraction parameters such as types of solvent, percentages of solvent, and extraction times on total phenolic content (TPC) and antioxidant activity of mature and green peels of Pisang Abu (PA), Pisang Berangan (PB), and Pisang Mas (PM) were investigated. The best extraction parameters were initially selected based on different percentages of ethanol (0-100% v/v), extraction time (1-5 hr), and extraction temperature (25-60°C) for extraction of antioxidants in the banana peels. Total phenolic content (TPC) was evaluated using Folin-Ciocalteu reagent assay while antioxidant activities (AA) of banana peel were accessed by DPPH, ABTS, and β-carotene bleaching (BCB) assays at optimum extraction conditions. Based on different extraction solvents and percentages of solvents used, 70% and 90% of acetone had yielded the highest TPC for the mature and green PA peels, respectively; 90% of ethanol and methanol has yielded the highest TPC for the mature and green PB peels, respectively; while 90% ethanol for the mature and green PM peels. Similar extraction conditions were found for the antioxidant activities for the banana peel assessed using DPPH assay except for green PB peel, which 70% methanol had contributed to the highest AA. Highest TPC and AA were obtained by applying 4, 1, and 2 hrs extraction for the peels of PA, PB and PM, respectively. The best extraction conditions were also used for determination of AAs using ABTS and β-carotene bleaching assays. Therefore, the best extraction conditions used have given the highest TPC and AAs. By

Characterization optimization for the National TRU waste system

International Nuclear Information System (INIS)

Basabilvazo, George T.; Countiss, S.; Moody, D.C.; Jennings, S.G.; Lott, S.A.

2002-01-01

On March 26, 1999, the Waste Isolation Pilot Plant (WIPP) received its first shipment of transuranic (TRU) waste. On November 26, 1999, the Hazardous Waste Facility Permit (HWFP) to receive mixed TRU waste at WIPP became effective. Having achieved these two milestones, facilitating and supporting the characterization, transportation, and disposal of TRU waste became the major challenges for the National TRU Waste Program. Significant challenges still remain in the scientific, engineering, regulatory, and political areas that need to be addressed. The National TRU Waste System Optimization Project has been established to identify, develop, and implement cost-effective system optimization strategies that address those significant challenges. Fundamental to these challenges is the balancing and prioritization of potential regulatory changes with potential technological solutions. This paper describes some of the efforts to optimize (to make as functional as possible) characterization activities for TRU waste.

Tank Waste Remediation System optimized processing strategy

International Nuclear Information System (INIS)

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

1996-03-01

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

Analytical methodology for optimization of waste management scenarios in nuclear installation decommissioning process - 16148

International Nuclear Information System (INIS)

Zachar, Matej; Necas, Vladimir; Daniska, Vladimir; Rehak, Ivan; Vasko, Marek

2009-01-01

The nuclear installation decommissioning process is characterized by production of large amount of various radioactive and non-radioactive waste that has to be managed, taking into account its physical, chemical, toxic and radiological properties. Waste management is considered to be one of the key issues within the frame of the decommissioning process. During the decommissioning planning period, the scenarios covering possible routes of materials release into the environment and radioactive waste disposal, should be discussed and evaluated. Unconditional and conditional release to the environment, long-term storage at the nuclear site, near surface or deep geological disposal and relevant material management techniques for achieving the final status should be taken into account in the analysed scenarios. At the level of the final decommissioning plan, it is desirable to have the waste management scenario optimized for local specific facility conditions taking into account a national decommissioning background. The analytical methodology for the evaluation of decommissioning waste management scenarios, presented in the paper, is based on the materials and radioactivity flow modelling, which starts from waste generation activities like pre-dismantling decontamination, selected methods of dismantling, waste treatment and conditioning, up to materials release or conditioned radioactive waste disposal. The necessary input data for scenarios, e.g. nuclear installation inventory database (physical and radiological data), waste processing technologies parameters or material release and waste disposal limits, have to be considered. The analytical methodology principles are implemented into the standardised decommissioning parameters calculation code OMEGA, developed in the DECOM company. In the paper the examples of the methodology implementation for the scenarios optimization are presented and discussed. (authors)

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.

Synthesizing optimal waste blends

International Nuclear Information System (INIS)

Narayan, V.; Diwekar, W.M.; Hoza, M.

1996-01-01

Vitrification of tank wastes to form glass is a technique that will be used for the disposal of high-level waste at Hanford. Process and storage economics show that minimizing the total number of glass logs produced is the key to keeping cost as low as possible. The amount of glass produced can be reduced by blending of the wastes. The optimal way to combine the tanks to minimize the vole of glass can be determined from a discrete blend calculation. However, this problem results in a combinatorial explosion as the number of tanks increases. Moreover, the property constraints make this problem highly nonconvex where many algorithms get trapped in local minima. In this paper the authors examine the use of different combinatorial optimization approaches to solve this problem. A two-stage approach using a combination of simulated annealing and nonlinear programming (NLP) is developed. The results of different methods such as the heuristics approach based on human knowledge and judgment, the mixed integer nonlinear programming (MINLP) approach with GAMS, and branch and bound with lower bound derived from the structure of the given blending problem are compared with this coupled simulated annealing and NLP approach

Optimization on Pretreatment Conditions of Seaweed Liquid Waste for Bio ethanol Production

International Nuclear Information System (INIS)

Nur Zatul-Iffah Zakaria; Dachyar Arbain; Mohd Noor Ahmad; Mohd Irfan Hatim Mohamed Dzahir

2015-01-01

Seaweed liquid waste (SLW) from a non-conventional seaweed (Gracilaria sp.) drying process where the seaweed is ruptured and filter-squeezed has been investigated. The liquid contains proteins and minerals which potentially pollute the environment if it is not been properly treated. For that reason, this paper deals with study on the feasibility of SLW utilization as a feedstock for bio ethanol production. The fermentation of bio ethanol production was carried out by Saccharomyces cerevisiae in which ethanol produced was measured by gas chromatography. In order to increase its fermentable sugar content, the SLW was treated with dilute acid. Center composite design of response surface methodology (RSM) had been used to optimize the sugar content by varying the parameters involved in the dilute acid pretreatment conditions. These are sulphuric acid concentration (M), temperature (degree Celsius) and seaweed waste concentration (g/ ml). It was obtained that the R 2 value reached 0.97 indicating that the model is acceptable. The three parameters showed p-value less than 0.05 suggesting their significance interactions. The optimization resulted 25 times improvement of reducing sugar concentration. The reducing sugar resulting from the optimized pretreatment was later used as fermentation medium to produce ethanol up to 123.197 mg/ l. (author)

The Optimization of Radioactive Waste Management in the Nuclear Installation Decommissioning Process

International Nuclear Information System (INIS)

Zachar, Matej; Necas, Vladimir

2008-01-01

The paper presents a basic characterization of nuclear installation decommissioning process especially in the term of radioactive materials management. A large amount of solid materials and secondary waste created after implementation of decommissioning activities have to be managed considering their physical, chemical, toxic and radiological characteristics. Radioactive materials should be, after fulfilling all the conditions defined by the authorities, released to the environment for the further use. Non-releasable materials are considered to be a radioactive waste. Their management includes various procedures starting with pre-treatment activities, continuing with storage, treatment and conditioning procedures. Finally, they are disposed in the near surface or deep geological repositories. Considering the advantages and disadvantages of all possible ways of releasing the material from nuclear installation area, optimization of the material management process should be done. Emphasis is placed on the radiological parameters of materials, availability of waste management technologies, waste repositories and on the radiological limits and conditions for materials release or waste disposal. Appropriate optimization of material flow should lead to the significant savings of money, disposal capacities or raw material resources. Using a suitable calculation code e.g. OMEGA, the evaluation of the various material management scenarios and selection of the best one, based on the multi-criterion analysis, should be done. (authors)

Optimization of a packed bed reactor for liquid waste treatment

International Nuclear Information System (INIS)

Schmidt, C.A.; Brower, M.J.; Coogan, J.J.; Tennant, R.A.

1993-01-01

The authors describe an optimization study of a packed bed reactor (PBR), developed for the treatment of hazardous liquid wastes. The focus is on the destruction of trichloroethylene (TCE). The PBR technology offers many distinct advantages over other processes: simple design, high destruction rates (99.99%), low costs, ambient pressure operation, easy maintenance and scaleability. The cost effectiveness, optimal operating parameters and scaleability were determined. As a second stage of treatment, a silent discharge plasma (SDP) reactor was installed to further treat offgases from the PBR. A primary advantage of this system is closed loop operation, where exhaust gases are continuously recycled and not released into the atmosphere

Optimization of concrete composition in radioactive waste management

International Nuclear Information System (INIS)

Plecas, I.; Peric, A.

1995-01-01

Low and intermediate level waste represents 95% of the total wastes that is conditioned into special concrete containers. Since these containers are to protect radioactive waste safely for about 300 years, the selection and precise control of physical and mechanical characteristics of materials is very important. After volume reduction and valuable components recovery, waste materials have to be conditioned for transport, storage and disposal. Conditioning is the waste management step in which radioactive wastes are immobilized and packed. The immobilization processes involve conversation of the wastes to solid forms that reduce the potential for migration or dispersion of radionuclides from the wastes by natural processes during storage, transport and disposal. The immobilization processes involve the use of various matrices of nonradioactive materials, such as concrete, to fix the wastes as monoliths, usually directly in the waste containers used for subsequent handling. In this paper an optimization of concrete container composition, used for storing radioactive waste from nuclear power plants, is presented. Optimization was performed on the composition of the concrete that is used in the container production. In experiments, the authors tried to obtain the best mechanical characteristics of the concrete, varying the weight percentage of the granulate due to its diameter, water-to-cement ratios and type of the cements that were used in preparing the concrete container formulation. Concrete containers, that were optimized in the manner described in this paper, will be in used for the radioactive waste materials final disposal, using the concept of the engineer trench system facilities

Optimization of municipal solid waste collection and transportation routes.

Science.gov (United States)

Das, Swapan; Bhattacharyya, Bidyut Kr

2015-09-01

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. Copyright © 2015 Elsevier Ltd. All rights reserved.

Impact of thermal constraints on the optimal design of high-level waste repositories in geologic media

Energy Technology Data Exchange (ETDEWEB)

Malbrain, C; Lester, R K [Massachusetts Inst. of Tech., Cambridge (USA). Dept. of Nuclear Engineering

1982-12-01

An approximate, semi-analytical heat conduction model for predicting the time-dependent temperature distribution in the region of a high-level waste repository has been developed. The model provides the basis for a systematic, inexpensive examination of the impact of several independent thermal design constraints on key repository design parameters and for determining the optimal set of design parameters which satisfy these constraints. Illustrative calculations have been carried out for conceptual repository designs for spent pressurized water reactor (PWR) fuel and reprocessed PWR high-level waste in salt and granite media.

Control parameter optimization for AP1000 reactor using Particle Swarm Optimization

International Nuclear Information System (INIS)

Wang, Pengfei; Wan, Jiashuang; Luo, Run; Zhao, Fuyu; Wei, Xinyu

2016-01-01

Highlights: • The PSO algorithm is applied for control parameter optimization of AP1000 reactor. • Key parameters of the MSHIM control system are optimized. • Optimization results are evaluated though simulations and quantitative analysis. - Abstract: The advanced mechanical shim (MSHIM) core control strategy is implemented in the AP1000 reactor for core reactivity and axial power distribution control simultaneously. The MSHIM core control system can provide superior reactor control capabilities via automatic rod control only. This enables the AP1000 to perform power change operations automatically without the soluble boron concentration adjustments. In this paper, the Particle Swarm Optimization (PSO) algorithm has been applied for the parameter optimization of the MSHIM control system to acquire better reactor control performance for AP1000. System requirements such as power control performance, control bank movement and AO control constraints are reflected in the objective function. Dynamic simulations are performed based on an AP1000 reactor simulation platform in each iteration of the optimization process to calculate the fitness values of particles in the swarm. The simulation platform is developed in Matlab/Simulink environment with implementation of a nodal core model and the MSHIM control strategy. Based on the simulation platform, the typical 10% step load decrease transient from 100% to 90% full power is simulated and the objective function used for control parameter tuning is directly incorporated in the simulation results. With successful implementation of the PSO algorithm in the control parameter optimization of AP1000 reactor, four key parameters of the MSHIM control system are optimized. It has been demonstrated by the calculation results that the optimized MSHIM control system parameters can improve the reactor power control capability and reduce the control rod movement without compromising AO control. Therefore, the PSO based optimization

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

International Nuclear Information System (INIS)

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

2017-01-01

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

A new model for simulating microbial cyanide production and optimizing the medium parameters for recovering precious metals from waste printed circuit boards.

Science.gov (United States)

Yuan, Zhihui; Ruan, Jujun; Li, Yaying; Qiu, Rongliang

2018-04-10

Bioleaching is a green recycling technology for recovering precious metals from waste printed circuit boards (WPCBs). However, this technology requires increasing cyanide production to obtain desirable recovery efficiency. Luria-Bertani medium (LB medium, containing tryptone 10 g/L, yeast extract 5 g/L, NaCl 10 g/L) was commonly used in bioleaching of precious metal. In this study, results showed that LB medium did not produce highest yield of cyanide. Under optimal culture conditions (25 °C, pH 7.5), the maximum cyanide yield of the optimized medium (containing tryptone 6 g/L and yeast extract 5 g/L) was 1.5 times as high as that of LB medium. In addition, kinetics and relationship of cell growth and cyanide production was studied. Data of cell growth fitted logistics model well. Allometric model was demonstrated effective in describing relationship between cell growth and cyanide production. By inserting logistics equation into allometric equation, we got a novel hybrid equation containing five parameters. Kinetic data for cyanide production were well fitted to the new model. Model parameters reflected both cell growth and cyanide production process. Copyright © 2018 Elsevier B.V. All rights reserved.

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...

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.

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.

Thermodynamic analysis and performance optimization of an Organic Rankine Cycle (ORC) waste heat recovery system for marine diesel engines

International Nuclear Information System (INIS)

Song, Jian; Song, Yin; Gu, Chun-wei

2015-01-01

Escalating fuel prices and imposition of carbon dioxide emission limits are creating renewed interest in methods to increase the thermal efficiency of marine diesel engines. One viable means to achieve such improved thermal efficiency is the conversion of engine waste heat to a more useful form of energy, either mechanical or electrical. Organic Rankine Cycle (ORC) has been demonstrated to be a promising technology to recover waste heat. This paper examines waste heat recovery of a marine diesel engine using ORC technology. Two separated ORC apparatuses for the waste heat from both the jacket cooling water and the engine exhaust gas are designed as the traditional recovery system. The maximum net power output is chosen as the evaluation criterion to select the suitable working fluid and define the optimal system parameters. To simplify the waste heat recovery, an optimized system using the jacket cooling water as the preheating medium and the engine exhaust gas for evaporation is presented. The influence of preheating temperature on the system performance is evaluated to define the optimal operating condition. Economic and off-design analysis of the optimized system is conducted. The simulation results reveal that the optimized system is technically feasible and economically attractive. - Highlights: • ORC is used to recover waste heat from both exhaust gas and jacket cooling water. • Comparative study is conducted for different ORC systems. • Thermal performance, system structure and economic feasibility are considered. • Optimal preheating temperature of the system is selected

Optimal waste-to-energy strategy assisted by GIS For sustainable solid waste management

International Nuclear Information System (INIS)

Tan, S T; Hashim, H; Lee, C T; Lim, J S; Kanniah, K D

2014-01-01

Municipal solid waste (MSW) management has become more complex and costly with the rapid socio-economic development and increased volume of waste. Planning a sustainable regional waste management strategy is a critical step for the decision maker. There is a great potential for MSW to be used for the generation of renewable energy through waste incineration or landfilling with gas capture system. However, due to high processing cost and cost of resource transportation and distribution throughout the waste collection station and power plant, MSW is mostly disposed in the landfill. This paper presents an optimization model incorporated with GIS data inputs for MSW management. The model can design the multi-period waste-to-energy (WTE) strategy to illustrate the economic potential and tradeoffs for MSW management under different scenarios. The model is capable of predicting the optimal generation, capacity, type of WTE conversion technology and location for the operation and construction of new WTE power plants to satisfy the increased energy demand by 2025 in the most profitable way. Iskandar Malaysia region was chosen as the model city for this study

Optimal waste-to-energy strategy assisted by GIS For sustainable solid waste management

Science.gov (United States)

Tan, S. T.; Hashim, H.

2014-02-01

Municipal solid waste (MSW) management has become more complex and costly with the rapid socio-economic development and increased volume of waste. Planning a sustainable regional waste management strategy is a critical step for the decision maker. There is a great potential for MSW to be used for the generation of renewable energy through waste incineration or landfilling with gas capture system. However, due to high processing cost and cost of resource transportation and distribution throughout the waste collection station and power plant, MSW is mostly disposed in the landfill. This paper presents an optimization model incorporated with GIS data inputs for MSW management. The model can design the multi-period waste-to-energy (WTE) strategy to illustrate the economic potential and tradeoffs for MSW management under different scenarios. The model is capable of predicting the optimal generation, capacity, type of WTE conversion technology and location for the operation and construction of new WTE power plants to satisfy the increased energy demand by 2025 in the most profitable way. Iskandar Malaysia region was chosen as the model city for this study.

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.

An Optimization Waste Load Allocation Model in River Systems

Science.gov (United States)

Amirpoor Daylami, A.; jarihani, A. A.; Aminisola, K.

2012-04-01

In many river systems, increasing of the waste discharge leads to increasing pollution of these water bodies. While the capacity of the river flow for pollution acceptance is limited and the ability of river to clean itself is restricted, the dischargers have to release their waste into the river after a primary pollution treatment process. Waste Load Allocation as a well-known water quality control strategy is used to determine the optimal pollutant removal at a number of point sources along the river. This paper aim at developing a new approach for treatment and management of wastewater inputs into the river systems, such that water quality standards in these receiving waters are met. In this study, inspired by the fact that cooperation among some single point source waste dischargers can lead to a more waste acceptance capacity and/or more optimum quality control in a river, an efficient approach was implemented to determine both primary waste water treatment levels and/or the best releasing points of the waste into the river. In this methodology, a genetic algorithm is used as an optimization tool to calculate optimal fraction removal levels of each one of single or shared discharger. Besides, a sub-model embedded to optimization model was used to simulate water quality of the river in each one of discharging scenarios based on the modified Streeter and Phelps quality equations. The practical application of the model is illustrated with a case study of the Gharesoo river system in west of Iran.

Applying waste heat recovery system in a sewage sludge dryer – A technical and economic optimization

International Nuclear Information System (INIS)

Tańczuk, Mariusz; Kostowski, Wojciech; Karaś, Marcin

2016-01-01

Highlights: • A modernization of waste heat recovery system in a sludge drying plant is proposed. • Energy performance analysis rejected the downsize case of modernization. • Optimal system sizes regarding Net Present Value and Net Present Value Ratio do not coincide. • Up to 683 MW h/y of chemical energy savings for optimal heat exchanger size. • Higher profitability for the larger heat exchanger cases: paybacks below 3.65 years. - Abstract: Drying of digested sewage sludge, as an important alternative to sludge disposal at dumping sites, should comply with the requirements of high energy efficiency as well as economic feasibility. The technical and economic optimization analysis of installing a waste process heat recovery unit in a medium-temperature belt dryer operated in a municipal waste water treatment plant was carried out. Inlet capacity of the plant is 1.83 Mg of wet sludge per hour. The post-process air was indicated as a source of waste heat and the configuration of a heat recovery system was proposed. The main objective of the research was to find the optimal size of a chosen type of waste heat recovery heat exchanger for preheating ambient air to the process. The maximization of Net Present Value, and, alternatively, also Net Present Value Ratio were selected for the objective function of the optimization procedure. Simulation of yearly operation of waste heat exchanger was made for a range of different heat exchanging areas (101–270 m"2) regarding given parameters of a post-process air and different temperatures of ambient air. Energy performance of the modernization was evaluated and economic indices were calculated for each of the analyzed cases. The location of the maximum of optimization function was found and the calculations show higher profitability of the cases with larger waste heat exchanger. It can be concluded that the location of optimum of the objective function is very sensitive to the price of natural gas supplied to the

Optimization of Concrete Composition in Radioactive Waste Management

International Nuclear Information System (INIS)

IIija, P.

1999-01-01

Low and Intermediate level radioactive waste re presents 95% of the total wastes that is conditioned into special concrete containers. Since these containers are to protect radioactive waste safely for about 300 years, the selection and precise control of physical and mechanical characteristics of materials is very important. After volume reduction and valuable components recovery, waste materials have to be conditioned for transport, storage and disposal. Conditioning is the waste management step in which radioactive wastes are immobilized and packed . In this paper methods and optimization of concrete container composition, used for storing radioactive waste, is presented

Optimization of Parameters of Asymptotically Stable Systems

Directory of Open Access Journals (Sweden)

Anna Guerman

2011-01-01

Full Text Available This work deals with numerical methods of parameter optimization for asymptotically stable systems. We formulate a special mathematical programming problem that allows us to determine optimal parameters of a stabilizer. This problem involves solutions to a differential equation. We show how to chose the mesh in order to obtain discrete problem guaranteeing the necessary accuracy. The developed methodology is illustrated by an example concerning optimization of parameters for a satellite stabilization system.

Parametric optimization and comparative study of organic Rankine cycle (ORC) for low grade waste heat recovery

International Nuclear Information System (INIS)

Dai Yiping; Wang Jiangfeng; Gao Lin

2009-01-01

Organic Rankine cycles for low grade waste heat recovery are described with different working fluids. The effects of the thermodynamic parameters on the ORC performance are examined, and the thermodynamic parameters of the ORC for each working fluid are optimized with exergy efficiency as an objective function by means of the genetic algorithm. The optimum performance of cycles with different working fluids was compared and analyzed under the same waste heat condition. The results show that the cycles with organic working fluids are much better than the cycle with water in converting low grade waste heat to useful work. The cycle with R236EA has the highest exergy efficiency, and adding an internal heat exchanger into the ORC system could not improve the performance under the given waste heat condition. In addition, for the working fluids with non-positive saturation vapor curve slope, the cycle has the best performance property with saturated vapor at the turbine inlet

Towards optimization of nuclear waste glass: Constraints, property models, and waste loading

International Nuclear Information System (INIS)

Hrma, P.

1994-04-01

Vitrification of both low- and high-level wastes from 177 tanks at Hanford poses a great challenge to glass makers, whose task is to formulate a system of glasses that are acceptable to the federal repository for disposal. The enormous quantity of the waste requires a glass product of the lowest possible volume. The incomplete knowledge of waste composition, its variability, and lack of an appropriate vitrification technology further complicates this difficult task. A simple relationship between the waste loading and the waste glass volume is presented and applied to the predominantly refractory (usually high-activity) and predominantly alkaline (usually low-activity) waste types. Three factors that limit waste loading are discussed, namely product acceptability, melter processing, and model validity. Glass formulation and optimization problems are identified and a broader approach to uncertainties is suggested

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.

Major Components of the National TRU Waste System Optimization Project

International Nuclear Information System (INIS)

Moody, D.C.; Bennington, B.; Sharif, F.

2002-01-01

The National Transuranic (TRU) Program (NTP) is being optimized to allow for disposing of the legacy TRU waste at least 10 years earlier than originally planned. This acceleration will save the nation an estimated $713. The Department of Energy's (DOE'S) Carlsbad Field Office (CBFO) has initiated the National TRU Waste System Optimization Project to propose, and upon approvaI, implement activities that produce significant cost saving by improving efficiency, thereby accelerating the rate of TRU waste disposal without compromising safety. In its role as NTP agent of change, the National TRU Waste System Optimization Project (the Project) (1) interacts closely with all NTP activities. Three of the major components of the Project are the Central Characterization Project (CCP), the Central Confirmation Facility (CCF), and the MobiIe/Modular Deployment Program.

Infrared Drying Parameter Optimization

Science.gov (United States)

Jackson, Matthew R.

In recent years, much research has been done to explore direct printing methods, such as screen and inkjet printing, as alternatives to the traditional lithographic process. The primary motivation is reduction of the material costs associated with producing common electronic devices. Much of this research has focused on developing inkjet or screen paste formulations that can be printed on a variety of substrates, and which have similar conductivity performance to the materials currently used in the manufacturing of circuit boards and other electronic devices. Very little research has been done to develop a process that would use direct printing methods to manufacture electronic devices in high volumes. This study focuses on developing and optimizing a drying process for conductive copper ink in a high volume manufacturing setting. Using an infrared (IR) dryer, it was determined that conductive copper prints could be dried in seconds or minutes as opposed to tens of minutes or hours that it would take with other drying devices, such as a vacuum oven. In addition, this study also identifies significant parameters that can affect the conductivity of IR dried prints. Using designed experiments and statistical analysis; the dryer parameters were optimized to produce the best conductivity performance for a specific ink formulation and substrate combination. It was determined that for an ethylene glycol, butanol, 1-methoxy 2- propanol ink formulation printed on Kapton, the optimal drying parameters consisted of a dryer height of 4 inches, a temperature setting between 190 - 200°C, and a dry time of 50-65 seconds depending on the printed film thickness as determined by the number of print passes. It is important to note that these parameters are optimized specifically for the ink formulation and substrate used in this study. There is still much research that needs to be done into optimizing the IR dryer for different ink substrate combinations, as well as developing a

PARAMETER COORDINATION AND ROBUST OPTIMIZATION FOR MULTIDISCIPLINARY DESIGN

Institute of Scientific and Technical Information of China (English)

HU Jie; PENG Yinghong; XIONG Guangleng

2006-01-01

A new parameter coordination and robust optimization approach for multidisciplinary design is presented. Firstly, the constraints network model is established to support engineering change, coordination and optimization. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. Secondly, the parameter coordination method is presented to solve the constraints network model, monitor the potential conflicts due to engineering changes, and obtain the consistency solution space corresponding to the given product specifications. Finally, the robust parameter optimization model is established, and genetic arithmetic is used to obtain the robust optimization parameter. An example of bogie design is analyzed to show the scheme to be effective.

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.

Optimal planning for the sustainable utilization of municipal solid waste

International Nuclear Information System (INIS)

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

2013-01-01

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

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 ...

Optimal Laser Phototherapy Parameters for Pain Relief.

Science.gov (United States)

Kate, Rohit J; Rubatt, Sarah; Enwemeka, Chukuka S; Huddleston, Wendy E

2018-03-27

Studies on laser phototherapy for pain relief have used parameters that vary widely and have reported varying outcomes. The purpose of this study was to determine the optimal parameter ranges of laser phototherapy for pain relief by analyzing data aggregated from existing primary literature. Original studies were gathered from available sources and were screened to meet the pre-established inclusion criteria. The included articles were then subjected to meta-analysis using Cohen's d statistic for determining treatment effect size. From these studies, ranges of the reported parameters that always resulted into large effect sizes were determined. These optimal ranges were evaluated for their accuracy using leave-one-article-out cross-validation procedure. A total of 96 articles met the inclusion criteria for meta-analysis and yielded 232 effect sizes. The average effect size was highly significant: d = +1.36 (confidence interval [95% CI] = 1.04-1.68). Among all the parameters, total energy was found to have the greatest effect on pain relief and had the most prominent optimal ranges of 120-162 and 15.36-20.16 J, which always resulted in large effect sizes. The cross-validation accuracy of the optimal ranges for total energy was 68.57% (95% CI = 53.19-83.97). Fewer and less-prominent optimal ranges were obtained for the energy density and duration parameters. None of the remaining parameters was found to be independently related to pain relief outcomes. The findings of meta-analysis indicate that laser phototherapy is highly effective for pain relief. Based on the analysis of parameters, total energy can be optimized to yield the largest effect on pain relief.

Multi-objective optimization of an organic Rankine cycle (ORC) for low grade waste heat recovery using evolutionary algorithm

International Nuclear Information System (INIS)

Wang, Jiangfeng; Yan, Zhequan; Wang, Man; Li, Maoqing; Dai, Yiping

2013-01-01

Highlights: • Multi-objective optimization of an ORC is conducted to obtain optimum performance. • NSGA-II is employed to solve this multi-objective optimization problem. • The effects of parameters on the exergy efficiency and capital cost are examined. - Abstract: Organic Rankine cycle (ORC) can effectively recover low grade waste heat due to its excellent thermodynamic performance. Based on the examinations of the effects of key thermodynamic parameters on the exergy efficiency and overall capital cost, multi-objective optimization of the ORC with R134a as working fluid is conducted to achieve the system optimization design from both thermodynamic and economic aspects using Non-dominated sorting genetic algorithm-II (NSGA-II). The exergy efficiency and overall capital cost are selected as two objective functions to maximize the exergy efficiency and minimize the overall capital cost under the given waste heat conditions. Turbine inlet pressure, turbine inlet temperature, pinch temperature difference, approach temperature difference and condenser temperature difference are selected as the decision variables owing to their significant effects on the exergy efficiency and overall capital cost. A Pareto frontier obtained shows that an increase in the exergy efficiency can increase the overall capital cost of the ORC system. The optimum design solution with their corresponding decision variables is selected from the Pareto frontier. The optimum exergy efficiency and overall capital cost are 13.98% and 129.28 × 10 4 USD, respectively, under the given waste heat conditions

Parameters control in GAs for dynamic optimization

Directory of Open Access Journals (Sweden)

Khalid Jebari

2013-02-01

Full Text Available The Control of Genetic Algorithms parameters allows to optimize the search process and improves the performance of the algorithm. Moreover it releases the user to dive into a game process of trial and failure to find the optimal parameters.

DEVELOPMENT OF A KINETIC MODEL OF BOEHMITE DISSOLUTION IN CAUSTIC SOLUTIONS APPLIED TO OPTIMIZE HANFORD WASTE PROCESSING

International Nuclear Information System (INIS)

Disselkamp, R.S.

2011-01-01

Boehmite (e.g., aluminum oxyhydroxide) is a major non-radioactive component in Hanford and Savannah River nuclear tank waste sludge. Boehmite dissolution from sludge using caustic at elevated temperatures is being planned at Hanford to minimize the mass of material disposed of as high-level waste (HLW) during operation of the Waste Treatment Plant (WTP). To more thoroughly understand the chemistry of this dissolution process, we have developed an empirical kinetic model for aluminate production due to boehmite dissolution. Application of this model to Hanford tank wastes would allow predictability and optimization of the caustic leaching of aluminum solids, potentially yielding significant improvements to overall processing time, disposal cost, and schedule. This report presents an empirical kinetic model that can be used to estimate the aluminate production from the leaching of boehmite in Hanford waste as a function of the following parameters: (1) hydroxide concentration; (2) temperature; (3) specific surface area of boehmite; (4) initial soluble aluminate plus gibbsite present in waste; (5) concentration of boehmite in the waste; and (6) (pre-fit) Arrhenius kinetic parameters. The model was fit to laboratory, non-radioactive (e.g. 'simulant boehmite') leaching results, providing best-fit values of the Arrhenius A-factor, A, and apparent activation energy, E A , of A = 5.0 x 10 12 hour -1 and E A = 90 kJ/mole. These parameters were then used to predict boehmite leaching behavior observed in previously reported actual waste leaching studies. Acceptable aluminate versus leaching time profiles were predicted for waste leaching data from both Hanford and Savannah River site studies.

Repository Waste Package Transporter Shielding Weight Optimization

International Nuclear Information System (INIS)

C.E. Sanders; Shiaw-Der Su

2005-01-01

The Yucca Mountain repository requires the use of a waste package (WP) transporter to transport a WP from a process facility on the surface to the subsurface for underground emplacement. The transporter is a part of the waste emplacement transport systems, which includes a primary locomotive at the front end and a secondary locomotive at the rear end. The overall system with a WP on board weights over 350 metric tons (MT). With the shielding mass constituting approximately one-third of the total system weight, shielding optimization for minimal weight will benefit the overall transport system with reduced axle requirements and improved maneuverability. With a high contact dose rate on the WP external surface and minimal personnel shielding afforded by the WP, the transporter provides radiation shielding to workers during waste emplacement and retrieval operations. This paper presents the design approach and optimization method used in achieving a shielding configuration with minimal weight

Economic and ecological optimal strategies of management of the system of regional solid waste disposal

Directory of Open Access Journals (Sweden)

Samoylik Marina S.

2014-01-01

Full Text Available The article develops an economic and ecological model of optimal management of the system of solid waste disposal at the regional level, identifies its target functions and forms optimisation scenarios of management of this sphere with theoretically optimal parameters’ values. Based on the model of management of the sphere of solid waste disposal the article forms an algorithm of identification of optimal managerial strategies and mechanisms of their realisation, which allows solution of the set tasks of optimisation of development of the sphere of solid waste disposal at a given set of values and parameters of the state of the system for a specific type of life cycle of solid waste and different subjects of this sphere. The developed model has a number of feasible solutions and, consequently, offers selection of the best of them with consideration of target functions. The article conducts a SWOT analysis of the current state of solid waste disposal in the Poltava region and identifies a necessity of development of a relevant strategy on the basis of the developed economic and ecological model with consideration of optimisation of mutually opposite criteria: ecological risk for the population from the sphere of solid waste disposal and total expenditures for this sphere functioning. The article conducts modelling of this situation by basic (current situation and alternative scenarios and finds out that, at this stage, it is most expedient to build in the region four sorting lines and five regional solid waste grounds, while expenditures on this sphere are UAH 62.0 million per year, income from secondary raw material sales – UAH 71.2 per year and reduction of the ecological risk – UAH 13 million per year.

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.

Simultaneous heat integration and techno-economic optimization of Organic Rankine Cycle (ORC) for multiple waste heat stream recovery

International Nuclear Information System (INIS)

Yu, Haoshui; Eason, John; Biegler, Lorenz T.; Feng, Xiao

2017-01-01

In the past decades, the Organic Rankine Cycle (ORC) has become a promising technology for low and medium temperature energy utilization. In refineries, there are usually multiple waste heat streams to be recovered. From a safety and controllability perspective, using an intermedium (hot water) to recover waste heat before releasing heat to the ORC system is more favorable than direct integration. The mass flowrate of the intermediate hot water stream determines the amount of waste heat recovered and the final hot water temperature affects the thermal efficiency of ORC. Both, in turn, exert great influence on the power output. Therefore, the hot water mass flowrate is a critical decision variable for the optimal design of the system. This study develops a model for techno-economic optimization of an ORC with simultaneous heat recovery and capital cost optimization. The ORC is modeled using rigorous thermodynamics with the concept of state points. The task of waste heat recovery using the hot water intermedium is modeled using the Duran-Grossmann model for simultaneous heat integration and process optimization. The combined model determines the optimal design of an ORC that recovers multiple waste heat streams in a large scale background process using an intermediate heat transfer stream. In particular, the model determines the optimal heat recovery approach temperature (HRAT), the utility load of the background process, and the optimal operating conditions of the ORC simultaneously. The effectiveness of this method is demonstrated with a case study that uses a refinery as the background process. Sensitivity of the optimal solution to the parameters (electricity price, utility cost) is quantified in this paper. - Highlights: • A new model for Organic Rankine cycle design optimization is presented. • Process heat integration and ORC are considered simultaneously. • Rigorous equation oriented models of the ORC are used for accurate results. • Impact of working

Backtracking search algorithm in CVRP models for efficient solid waste collection and route optimization.

Science.gov (United States)

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

2017-03-01

Waste collection is an important part of waste management that involves different issues, including environmental, economic, and social, among others. Waste collection optimization can reduce the waste collection budget and environmental emissions by reducing the collection route distance. This paper presents a modified Backtracking Search Algorithm (BSA) in capacitated vehicle routing problem (CVRP) models with the smart bin concept to find the best optimized waste collection route solutions. The objective function minimizes the sum of the waste collection route distances. The study introduces the concept of the threshold waste level (TWL) of waste bins to reduce the number of bins to be emptied by finding an optimal range, thus minimizing the distance. A scheduling model is also introduced to compare the feasibility of the proposed model with that of the conventional collection system in terms of travel distance, collected waste, fuel consumption, fuel cost, efficiency and CO 2 emission. The optimal TWL was found to be between 70% and 75% of the fill level of waste collection nodes and had the maximum tightness value for different problem cases. The obtained results for four days show a 36.80% distance reduction for 91.40% of the total waste collection, which eventually increases the average waste collection efficiency by 36.78% and reduces the fuel consumption, fuel cost and CO 2 emission by 50%, 47.77% and 44.68%, respectively. Thus, the proposed optimization model can be considered a viable tool for optimizing waste collection routes to reduce economic costs and environmental impacts. Copyright © 2017 Elsevier Ltd. All rights reserved.

Thermoeconomic multi-objective optimization of an organic Rankine cycle for exhaust waste heat recovery of a diesel engine

International Nuclear Information System (INIS)

Yang, Fubin; Zhang, Hongguang; Song, Songsong; Bei, Chen; Wang, Hongjin; Wang, Enhua

2015-01-01

In this paper, the ORC (Organic Rankine cycle) technology is adopted to recover the exhaust waste heat of diesel engine. The thermodynamic, economic and optimization models of the ORC system are established, respectively. Firstly, the effects of four key parameters, including evaporation pressure, superheat degree, condensation temperature and exhaust temperature at the outlet of the evaporator on the thermodynamic performances and economic indicators of the ORC system are investigated. Subsequently, based on the established optimization model, GA (genetic algorithm) is employed to solve the Pareto solution of the thermodynamic performances and economic indicators for maximizing net power output and minimizing total investment cost under diesel engine various operating conditions using R600, R600a, R601a, R245fa, R1234yf and R1234ze as working fluids. The most suitable working fluid used in the ORC system for diesel engine waste heat recovery is screened out, and then the corresponding optimal parameter regions are analyzed. The results show that thermodynamic performance of the ORC system is improved at the expense of economic performance. Among these working fluids, R245fa is considered as the most suitable working fluid for the ORC waste heat application of the diesel engine with comprehensive consideration of thermoeconomic performances, environmental impacts and safety levels. Under the various operating conditions of the diesel engine, the optimal evaporation pressure is in the range of 1.1 MPa–2.1 MPa. In addition, the optimal superheat degree and the exhaust temperature at the outlet of the evaporator are mainly influenced by the operating conditions of the diesel engine. The optimal condensation temperature keeps a nearly constant value of 298.15 K. - Highlights: • Thermoeconomic multi-objective optimization of an ORC (Organic Rankine cycle) system is conducted. • Sensitivity analysis of the decision variables is performed. • Genetic algorithm

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.

Thermo-economic analysis and optimization of a combined cooling and power (CCP) system for engine waste heat recovery

International Nuclear Information System (INIS)

Xia, Jiaxi; Wang, Jiangfeng; Lou, Juwei; Zhao, Pan; Dai, Yiping

2016-01-01

Highlights: • A combined cooling and power system was proposed for engine waste heat recovery. • Effects of key parameters on thermodynamic performance of the system were studied. • Exergoeconomic parameter analysis was performed for the system. • A single-objective optimization by means of genetic algorithm was carried out. - Abstract: A combined cooling and power (CCP) system is developed, which comprises a CO 2 Brayton cycle (BC), an organic Rankine cycle (ORC) and an ejector refrigeration cycle for the cascade utilization of waste heat from an internal combustion engine. By establishing mathematical model to simulate the overall system, thermodynamic analysis and exergoeconomic analysis are conducted to examine the effects of five key parameters including the compressor pressure ratio, the compressor inlet temperature, the BC turbine inlet temperature, the ORC turbine inlet pressure and the ejector primary flow pressure on system performance. What’s more, a single-objective optimization by means of genetic algorithm (GA) is carried out to search the optimal system performance from viewpoint of exergoeconomic. Results show that the increases of the BC turbine inlet temperature, the ORC turbine inlet pressure and the ejector primary flow pressure are benefit to both thermodynamic and exergoeconimic performances of the CCP system. However, the rises in compressor pressure ratio and compressor inlet temperature will lead to worse system performances. By the single-objective optimization, the lowest average cost per unit of exergy product for the overall system is obtained.

Optimization of use of waste in the future energy system

International Nuclear Information System (INIS)

Muenster, Marie; Meibom, Peter

2011-01-01

Alternative uses of waste for energy production become increasingly interesting when considered from two perspectives, that of waste management and the energy system perspective. This paper presents the results of an enquiry into the use of waste in a future energy system. The analysis was performed using the energy system analysis model, Balmorel. The study is focused on Germany and the Nordic countries and demonstrates the optimization of both investments and production within the energy systems. The results present cost optimization excluding taxation concerning the use of waste for energy production in Denmark in a 2025 scenario with 48% renewable energy. Investments in a range of waste conversion technologies are facilitated, including waste incineration, co-combustion with coal, anaerobic digestion, and gasification. The most economically feasible solutions are found to be incineration 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 to increase in comparison with a situation where only investments in waste incineration are allowed. -- Highlights: → The analysis is based on hourly chronological time steps, thereby taking dynamic properties of the energy system into account. → The system analyzed includes both the heat and the electricity market, which is important when analyzing e.g. CHP technologies. → The surrounding countries, which form part of the same electricity market, are included in the analysis. → New innovative Waste-to-Energy production plants have been modeled to allow for a more efficient and flexible use of waste. → The analysis includes economical optimization of operation and of investments in production and transmission of both electricity and heat.

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.

Optimized application of systems engineering to nuclear waste repository projects

International Nuclear Information System (INIS)

Miskimin, P.A.; Shepard, M.

1986-01-01

The purpose of this presentation is to describe a fully optimized application of systems engineering methods and philosophy to the management of a large nuclear waste repository project. Knowledge gained from actual experience with the use of the systems approach on two repository projects is incorporated in the material presented. The projects are currently evaluating the isolation performance of different geologic settings and are in different phases of maturity. Systems engineering methods were applied by the principal author at the Waste Isolation Pilot Plant (WIPP) in the form of a functional analysis. At the Basalt Waste Isolation Project (BWIP), the authors assisted the intergrating contractor with the development and application of systems engineering methods. Based on this experience and that acquired from other waste management projects, an optimized plan for applying systems engineering techniques was developed. The plan encompasses the following aspects: project organization, developing and defining requirements, assigning work responsibilities, evaluating system performance, quality assurance, controlling changes, enhancing licensability, optimizing project performance, and addressing regulatory issues. This information is presented in the form of a roadmap for the practical application of system engineering principles to a nuclear waste repository project

Chickpea seeds germination rational parameters optimization

Science.gov (United States)

Safonova, Yu A.; Ivliev, M. N.; Lemeshkin, A. V.

2018-05-01

The paper presents the influence of chickpea seeds bioactivation parameters on their enzymatic activity experimental results. Optimal bioactivation process modes were obtained by regression-factor analysis: process temperature - 13.6 °C, process duration - 71.5 h. It was found that in the germination process, the proteolytic, amylolytic and lipolytic enzymes activity increased, and the urease enzyme activity is reduced. The dependences of enzyme activity on chickpea seeds germination conditions were obtained by mathematical processing of experimental data. The calculated data are in good agreement with the experimental ones. This confirms the optimization efficiency based on experiments mathematical planning in order to determine the enzymatic activity of chickpea seeds germination optimal parameters of bioactivated seeds.

Charging for waste motivates generators to optimize waste control at the source

International Nuclear Information System (INIS)

Berry, J.B.; Homan, F.J.

1988-01-01

The Department of Energy (DOE) has recognized the need for waste management that incorporates improved waste-handling techniques and more stringent regulatory requirements to prevent future liabilities such as Superfund sites. DOE-Oak Ridge Operations (DOE-ORO) has recognized that an effective waste management program focuses on control at the source and that the burden for responsible waste management can be placed on generators by charging for waste management costs. The principle of including the waste management costs in the total cost of the product, even when the product is research and development, is being implemented at Oak Ridge National Laboratory (ORNL). Charging waste management costs to generators creates an incentive to optimize processes so that less waste is produced, and it provides a basis for determining the cost effectiveness of capital improvements so that the mature phase of waste management can be attained. Improving waste management practices requires a long-range commitment and consistent administration. Making this commitment and providing adequate funding for proper waste disposal are most cost-effective measures than the alternative of paying for remedial actions after improper disposal. This paper summarizes a plan to charge waste generators, the administrative structure of the plan, a comparison between the rate structure and changes in waste disposal operations, and issues that have surfaced as the plan is implemented

Mixed integer evolution strategies for parameter optimization.

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Li, Rui; Emmerich, Michael T M; Eggermont, Jeroen; Bäck, Thomas; Schütz, M; Dijkstra, J; Reiber, J H C

2013-01-01

Evolution strategies (ESs) are powerful probabilistic search and optimization algorithms gleaned from biological evolution theory. They have been successfully applied to a wide range of real world applications. The modern ESs are mainly designed for solving continuous parameter optimization problems. Their ability to adapt the parameters of the multivariate normal distribution used for mutation during the optimization run makes them well suited for this domain. In this article we describe and study mixed integer evolution strategies (MIES), which are natural extensions of ES for mixed integer optimization problems. MIES can deal with parameter vectors consisting not only of continuous variables but also with nominal discrete and integer variables. Following the design principles of the canonical evolution strategies, they use specialized mutation operators tailored for the aforementioned mixed parameter classes. For each type of variable, the choice of mutation operators is governed by a natural metric for this variable type, maximal entropy, and symmetry considerations. All distributions used for mutation can be controlled in their shape by means of scaling parameters, allowing self-adaptation to be implemented. After introducing and motivating the conceptual design of the MIES, we study the optimality of the self-adaptation of step sizes and mutation rates on a generalized (weighted) sphere model. Moreover, we prove global convergence of the MIES on a very general class of problems. The remainder of the article is devoted to performance studies on artificial landscapes (barrier functions and mixed integer NK landscapes), and a case study in the optimization of medical image analysis systems. In addition, we show that with proper constraint handling techniques, MIES can also be applied to classical mixed integer nonlinear programming problems.

Optimization of Agrobacterium -mediated transformation parameters ...

African Journals Online (AJOL)

Agrobacterium-mediated transformation factors for sweet potato embryogenic calli were optimized using -glucuronidase (GUS) as a reporter. The binary vector pTCK303 harboring the modified GUS gene driven by the CaMV 35S promoter was used. Transformation parameters were optimized including bacterial ...

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.

Determination of service standard time for liquid waste parameter in certification institution

Science.gov (United States)

Sembiring, M. T.; Kusumawaty, D.

2018-02-01

Baristand Industry Medan is a technical implementation unit under the Industrial and Research and Development Agency, the Ministry of Industry. One of the services often used in Baristand Industry Medan is liquid waste testing service. The company set the standard of service 9 working days for testing services. At 2015, 89.66% on testing services liquid waste does not meet the specified standard of services company. The purpose of this research is to specify the standard time of each parameter in testing services liquid waste. The method used is the stopwatch time study. There are 45 test parameters in liquid waste laboratory. The measurement of the time done 4 samples per test parameters using the stopwatch. From the measurement results obtained standard time that the standard Minimum Service test of liquid waste is 13 working days if there is testing E. coli.

Thermodynamic analysis and performance optimization of an ORC (Organic Rankine Cycle) system for multi-strand waste heat sources in petroleum refining industry

International Nuclear Information System (INIS)

Song, Jian; Li, Yan; Gu, Chun-wei; Zhang, Li

2014-01-01

Low-grade waste heat source accounts for a large part of the total industrial waste heat, which cannot be efficiently recovered. The ORC (Organic Rankine Cycle) system has been proved to be a promising solution for the utilization of low-grade heat sources. It is evident that there might be several waste heat sources distributing in different temperature levels in one industry unit, and the entire recovery system will be extremely large and complex if the different heat sources are utilized one by one through several independent ORC subsystems. This paper aims to design and optimize a comprehensive ORC system to recover multi-strand waste heat sources in Shijiazhuang Refining and Chemical Company in China, involving defining suitable working fluids and operating parameters. Thermal performance is a first priority criterion for the system, and system simplicity, technological feasibility and economic factors are considered during optimization. Four schemes of the recovery system are presented in continuous optimization progress. By comparison, the scheme of dual integrated subsystems with R141B as a working fluid is optimal. Further analysis is implemented from the view of economic factors and off-design conditions. The analytical method and optimization progress presented can be widely applied in similar multi-strand waste heat sources recovery. - Highlights: • This paper focuses on the recovery of multi-strand waste heat sources. • ORC technology is used as a promising solution for the recovery. • Thermal performance, system simplicity and economic factors are considered

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

Science.gov (United States)

Bhattacharjya, Rajib Kumar

2018-05-01

The unit hydrograph and the infiltration parameters of a watershed can be obtained from observed rainfall-runoff data by using inverse optimization technique. This is a two-stage optimization problem. In the first stage, the infiltration parameters are obtained and the unit hydrograph ordinates are estimated in the second stage. In order to combine this two-stage method into a single stage one, a modified penalty parameter approach is proposed for converting the constrained optimization problem to an unconstrained one. The proposed approach is designed in such a way that the model initially obtains the infiltration parameters and then searches the optimal unit hydrograph ordinates. The optimization model is solved using Genetic Algorithms. A reduction factor is used in the penalty parameter approach so that the obtained optimal infiltration parameters are not destroyed during subsequent generation of genetic algorithms, required for searching optimal unit hydrograph ordinates. The performance of the proposed methodology is evaluated by using two example problems. The evaluation shows that the model is superior, simple in concept and also has the potential for field application.

Economic optimization of nuclear waste management

International Nuclear Information System (INIS)

DeWames, R.E.; Grantham, L.F.; Guon, J.; McKisson, R.L.

1984-01-01

The paper presented here addresses the impact of waste management system operating parameters on overall system economics. The conclusion reached by this study is that currently available technology and proposed operating conditions do not lead to optimum economics. The decision to utilize the current reference waste package and non-optimum operating conditions will cause added expenditures of 7 billion dollars over the next several decades. Further, this paper points out that optimum economics is not necessarily incompatible with improved system safety

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

International Nuclear Information System (INIS)

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

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.

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

Optimized waste management: Less volume and less radiotoxicity

International Nuclear Information System (INIS)

Fournier, Ph.; Nigon, J.L.

2001-01-01

This paper describes efforts to optimize fuel cycle back end solid wastes, in order to reduce both volume and radioactivity of final residues. An integrated strategy of standardized conditioning of all residues from reprocessing, called the Universal Canister Strategy, has been adopted. The application of feedback from over 30 years of operating experience and research and development to minimization of waste volume and radioactivity is presented. (author)

Optimization of waste management by actions taken at source

International Nuclear Information System (INIS)

Strachan, N.R.; Wakerley, M.W.

1988-01-01

The purpose of this document is to collate and review information on those measures and practices adopted within nuclear facilities to optimize the management of radioactive waste at the point at which it arises. The information on which it has been based has been obtained by a review of the literature and by visits to a number of different types of facilities within the European Community. The search revealed mainly references to waste-management optimization at US LWRs, whereas the visits have tried to cover as wide a range of European facilities as practicable. There are a number of different respects in which radioactive waste can be minimized: - minimizing the amount of activity appearing in the wastes. This is best achieved by the design of process equipment; - minimizing the volume of waste with which radioactivity is associated. This is best achieved by a combination of administrative controls and equipment design; - minimizing the amount of material which for administrative or measurement reasons is considered to be radioactive. Many examples of minimization at source by means of developments in equipment and administrative controls that were encountered during our visits, or identified in the literature search, are described

Optimization of waste management by actions taken at source

International Nuclear Information System (INIS)

Strachan, N.R.; Wakerley, M.W.

1988-01-01

The purpose of this document is to collate and review information on those measures and practices adopted within nuclear facilities to optimize the management of radioactive waste at the point of arising. The information on which it has been based has been obtained by literature review and by visits to a number of different types of facilities within the European Community. The search revealed mainly references to waste management optimization at US LWRs, whereas the visits have tried to cover as wide a range of European facilities as practicable. There are a number of different respects in which radioactive waste can be minimized: minimizing the amount of activity appearing in the wastes. This is best achieved by the design of process equipment; minimizing the volume of waste with which radioactivity is associated. This is best achieved by a combination of administrative controls and equipment design; minimizing the amount of material which for administrative or measurement reasons is considered to be radioactive. Many examples of minimization at source by means of equipment developments and administrative controls that were encountered during our visits or identified in the literature search are described. (author)

Optimizing Waste Heat Utilization in Vehicle Bio-Methane Plants

Directory of Open Access Journals (Sweden)

Feng Zhen

2018-06-01

Full Text Available Current vehicle bio-methane plants have drawbacks associated with high energy consumption and low recovery levels of waste heat produced during the gasification process. In this paper, we have optimized the performance of heat exchange networks using pinch analysis and through the introduction of heat pump integration technology. Optimal results for the heat exchange network of a bio-gas system producing 10,000 cubic meters have been calculated using a pinch point temperature of 50 °C, a minimum heating utility load of 234.02 kW and a minimum cooling utility load of 201.25 kW. These optimal parameters are predicted to result in energy savings of 116.08 kW (19.75%, whilst the introduction of new heat pump integration technology would afford further energy savings of 95.55 kW (16.25%. The combined energy saving value of 211.63 kW corresponds to a total energy saving of 36%, with economic analysis revealing that these reforms would give annual savings of 103,300 USD. The installation costs required to introduce these process modifications are predicted to require an initial investment of 423,200 USD, which would take 4.1 years to reach payout time based on predicted annual energy savings.

Hybrid computer optimization of systems with random parameters

Science.gov (United States)

White, R. C., Jr.

1972-01-01

A hybrid computer Monte Carlo technique for the simulation and optimization of systems with random parameters is presented. The method is applied to the simultaneous optimization of the means and variances of two parameters in the radar-homing missile problem treated by McGhee and Levine.

Molten salt treatment to minimize and optimize waste

International Nuclear Information System (INIS)

Gat, U.; Crosley, S.M.; Gay, R.L.

1993-01-01

A combination molten salt oxidizer (MSO) and molten salt reactor (MSR) is described for treatment of waste. The MSO is proposed for contained oxidization of organic hazardous waste, for reduction of mass and volume of dilute waste by evaporation of the water. The NTSO residue is to be treated to optimize the waste in terms of its composition, chemical form, mixture, concentration, encapsulation, shape, size, and configuration. Accumulations and storage are minimized, shipments are sized for low risk. Actinides, fissile material, and long-lived isotopes are separated and completely burned or transmuted in an MSR. The MSR requires no fuel element fabrication, accepts the materials as salts in arbitrarily small quantities enhancing safety, security, and overall acceptability

Optimization of parameters of special asynchronous electric drives

Science.gov (United States)

Karandey, V. Yu; Popov, B. K.; Popova, O. B.; Afanasyev, V. L.

2018-03-01

The article considers the solution of the problem of parameters optimization of special asynchronous electric drives. The solution of the problem will allow one to project and create special asynchronous electric drives for various industries. The created types of electric drives will have optimum mass-dimensional and power parameters. It will allow one to realize and fulfill the set characteristics of management of technological processes with optimum level of expenses of electric energy, time of completing the process or other set parameters. The received decision allows one not only to solve a certain optimizing problem, but also to construct dependences between the optimized parameters of special asynchronous electric drives, for example, with the change of power, current in a winding of the stator or rotor, induction in a gap or steel of magnetic conductors and other parameters. On the constructed dependences, it is possible to choose necessary optimum values of parameters of special asynchronous electric drives and their components without carrying out repeated calculations.

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

Science.gov (United States)

With the development of the Connected Vehicle technology that facilitates wirelessly communication among vehicles and road-side infrastructure, the Advanced Driver Assistance Systems (ADAS) can be adopted as an effective tool for accelerating traffic safety and mobility optimization at various highway facilities. To this end, the traffic management centers identify the optimal ADAS algorithm parameter set that enables the maximum improvement of the traffic safety and mobility performance, and broadcast the optimal parameter set wirelessly to individual ADAS-equipped vehicles. After adopting the optimal parameter set, the ADAS-equipped drivers become active agents in the traffic stream that work collectively and consistently to prevent traffic conflicts, lower the intensity of traffic disturbances, and suppress the development of traffic oscillations into heavy traffic jams. Successful implementation of this objective requires the analysis capability of capturing the impact of the ADAS on driving behaviors, and measuring traffic safety and mobility performance under the influence of the ADAS. To address this challenge, this research proposes a synthetic methodology that incorporates the ADAS-affected driving behavior modeling and state-of-the-art microscopic traffic flow modeling into a virtually simulated environment. Building on such an environment, the optimal ADAS algorithm parameter set is identified through an optimization programming framework to enable th

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

International Nuclear Information System (INIS)

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

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

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

International Nuclear Information System (INIS)

Anita Ramli; Muhammad Farooq

2015-01-01

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

Optimal design criteria - prediction vs. parameter estimation

Science.gov (United States)

Waldl, Helmut

2014-05-01

G-optimality is a popular design criterion for optimal prediction, it tries to minimize the kriging variance over the whole design region. A G-optimal design minimizes the maximum variance of all predicted values. If we use kriging methods for prediction it is self-evident to use the kriging variance as a measure of uncertainty for the estimates. Though the computation of the kriging variance and even more the computation of the empirical kriging variance is computationally very costly and finding the maximum kriging variance in high-dimensional regions can be time demanding such that we cannot really find the G-optimal design with nowadays available computer equipment in practice. We cannot always avoid this problem by using space-filling designs because small designs that minimize the empirical kriging variance are often non-space-filling. D-optimality is the design criterion related to parameter estimation. A D-optimal design maximizes the determinant of the information matrix of the estimates. D-optimality in terms of trend parameter estimation and D-optimality in terms of covariance parameter estimation yield basically different designs. The Pareto frontier of these two competing determinant criteria corresponds with designs that perform well under both criteria. Under certain conditions searching the G-optimal design on the above Pareto frontier yields almost as good results as searching the G-optimal design in the whole design region. In doing so the maximum of the empirical kriging variance has to be computed only a few times though. The method is demonstrated by means of a computer simulation experiment based on data provided by the Belgian institute Management Unit of the North Sea Mathematical Models (MUMM) that describe the evolution of inorganic and organic carbon and nutrients, phytoplankton, bacteria and zooplankton in the Southern Bight of the North Sea.

Preparation Parameter Analysis and Optimization of Sustainable Asphalt Binder Modified by Waste Rubber and Diatomite

Directory of Open Access Journals (Sweden)

Hanbing Liu

2018-01-01

Full Text Available In this study, crumb rubber and diatomite were used to modify asphalt binder. Wet process was adopted as a preparation method, and the corresponding preparation process was determined firstly. The effects of six preparation parameters (crumb rubber concentration, diatomite concentration, shear time, shear speed, shear temperature, and storing time on properties of modified asphalt binder (penetration at 25°C, softening point, ductility, viscosity at 135°C, elastic recovery, and penetration index were investigated, and multiresponse optimization was conducted using the response surface method. The results revealed that softening points, viscosity, elastic recovery, and penetration index increase, while penetration and ductility decrease with the increase of crumb rubber concentration. Softening points, viscosity, and penetration index increase, while penetration and ductility decrease with the increase of diatomite concentration, which presents little influence on elastic recovery of binder. Shear temperature presented significant effects on penetration, softening point, viscosity, and ductility. Shear speed, shear time, and storing time have similar effects on binder properties because of their similar mechanism of action. Based on the model obtained from the response surface method, optimized preparation parameters corresponding to specific criteria can be determined, which possess favorable accuracy compared with experimental results.

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 OA 9 ) 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.

Industrial waste recycling strategies optimization problem: mixed integer programming model and heuristics

Science.gov (United States)

Tang, Jiafu; Liu, Yang; Fung, Richard; Luo, Xinggang

2008-12-01

Manufacturers have a legal accountability to deal with industrial waste generated from their production processes in order to avoid pollution. Along with advances in waste recovery techniques, manufacturers may adopt various recycling strategies in dealing with industrial waste. With reuse strategies and technologies, byproducts or wastes will be returned to production processes in the iron and steel industry, and some waste can be recycled back to base material for reuse in other industries. This article focuses on a recovery strategies optimization problem for a typical class of industrial waste recycling process in order to maximize profit. There are multiple strategies for waste recycling available to generate multiple byproducts; these byproducts are then further transformed into several types of chemical products via different production patterns. A mixed integer programming model is developed to determine which recycling strategy and which production pattern should be selected with what quantity of chemical products corresponding to this strategy and pattern in order to yield maximum marginal profits. The sales profits of chemical products and the set-up costs of these strategies, patterns and operation costs of production are considered. A simulated annealing (SA) based heuristic algorithm is developed to solve the problem. Finally, an experiment is designed to verify the effectiveness and feasibility of the proposed method. By comparing a single strategy to multiple strategies in an example, it is shown that the total sales profit of chemical products can be increased by around 25% through the simultaneous use of multiple strategies. This illustrates the superiority of combinatorial multiple strategies. Furthermore, the effects of the model parameters on profit are discussed to help manufacturers organize their waste recycling network.

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.

Multi-parameter optimization design of parabolic trough solar receiver

International Nuclear Information System (INIS)

Guo, Jiangfeng; Huai, Xiulan

2016-01-01

Highlights: • The optimal condition can be obtained by multi-parameter optimization. • Exergy and thermal efficiencies are employed as objective function. • Exergy efficiency increases at the expense of heat losses. • The heat obtained by working fluid increases as thermal efficiency grows. - Abstract: The design parameters of parabolic trough solar receiver are interrelated and interact with one another, so the optimal performance of solar receiver cannot be obtained by the convectional single-parameter optimization. To overcome the shortcoming of single-parameter optimization, a multi-parameter optimization of parabolic trough solar receiver is employed based on genetic algorithm in the present work. When the thermal efficiency is taken as the objective function, the heat obtained by working fluid increases while the average temperature of working fluid and wall temperatures of solar receiver decrease. The average temperature of working fluid and the wall temperatures of solar receiver increase while the heat obtained by working fluid decreases generally by taking the exergy efficiency as an objective function. Assuming that the solar radiation intensity remains constant, the exergy obtained by working fluid increases by taking exergy efficiency as the objective function, which comes at the expense of heat losses of solar receiver.

Optimization of waste loading in high-level glass in the presence of uncertainty

International Nuclear Information System (INIS)

Hoza, M.; Fann, G.I.; Hopkins, D.F.

1995-02-01

Hanford high-level liquid waste will be converted into a glass form for long-term storage. The glass must meet certain constraints on its composition and properties in order to have desired properties for processing (e.g., electrical conductivity, viscosity, and liquidus temperature) and acceptable durability for long-term storage. The Optimal Waste Loading (OWL) models, based on rigorous mathematical optimization techniques, have been developed to minimize the number of glass logs required and determine glass-former compositions that will produce a glass meeting all relevant constraints. There is considerable uncertainty in many of the models and data relevant to the formulation of high-level glass. In this paper, we discuss how we handle uncertainty in the glass property models and in the high-level waste composition to the vitrification process. Glass property constraints used in optimization are inequalities that relate glass property models obtained by regression analysis of experimental data to numerical limits on property values. Therefore, these constraints are subject to uncertainty. The sampling distributions of the regression models are used to describe the uncertainties associated with the constraints. The optimization then accounts for these uncertainties by requiring the constraints to be satisfied within specified confidence limits. The uncertainty in waste composition is handled using stochastic optimization. Given means and standard deviations of component masses in the high-level waste stream, distributions of possible values for each component are generated. A series of optimization runs is performed; the distribution of each waste component is sampled for each run. The resultant distribution of solutions is then statistically summarized. The ability of OWL models to handle these forms of uncertainty make them very useful tools in designing and evaluating high-level waste glasses formulations

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.

Analyzing the optimization of an organic Rankine cycle system for recovering waste heat from a large marine engine containing a cooling water system

International Nuclear Information System (INIS)

Yang, Min-Hsiung; Yeh, Rong-Hua

2014-01-01

Highlights: • Employing the thermodynamic analysis and a heat-transfer method, an ORC optimization is presented. • An optimal objective parameter evaluation of six working fluids is presented. • Refrigerants with superior thermodynamic properties do not necessary have excellent performance. • Cylinder jacket water temperature strongly affects optimal evaporation temperature. - Abstract: In this study, six working fluids with zero ozone depletion potential and low global warming potential are used in an organic Rankine cycle (ORC) system to recover waste heat from cylinder jacket water of large marine diesel engines. Thermodynamic analysis and a finite-temperature-difference heat-transfer method are developed to evaluate the thermal efficiency, total heat-exchanger area, objective parameter, and exergy destruction of the ORC system. The optimal evaporation and condensation temperatures for achieving the maximal objective parameter, the ratio of net power output to the total heat-transfer area of heat exchangers, of an ORC system are investigated. The results show that, among the working fluids, R600a performs the best in the optimal objective parameter evaluation followed by R1234ze, R1234yf, R245fa, R245ca, and R1233zd at evaporation temperatures ranging from 58 °C to 68 °C and condensation temperatures ranging from 35 °C to 45 °C. The optimal operating temperatures and corresponding thermal efficiency and exergy destruction are proposed. Furthermore, the influences of inlet temperatures on cylinder jacket water and cooling water in the ORC are presented for recovering waste heat. The results of this work were verified with theoretical solutions and experimental results in the literature and it was revealed that they were consistent with them

Optimization method for dimensioning a geological HLW waste repository

International Nuclear Information System (INIS)

Ouvrier, N.; Chaudon, L.; Malherbe, L.

1990-01-01

This method was developed by the CEA to optimize the dimensions of a geological repository by taking account of technical and economic parameters. It involves optimizing radioactive waste storage conditions on the basis of economic criteria with allowance for specified thermal constraints. The results are intended to identify trends and guide the choice from among available options: simple and highly flexible models were therefore used in this study, and only nearfield thermal constraints were taken into consideration. Because of the present uncertainty on the physicochemical properties of the repository environment and on the unit cost figures, this study focused on developing a suitable method rather than on obtaining definitive results. The optimum values found for the two media investigated (granite and salt) show that it is advisable to minimize the interim storage time, implying the containers must be separated by buffer material, whereas vertical spacing may not be required after a 30-year interim storage period. Moreover, the boreholes should be as deep as possible, on a close pitch in widely spaced handling drifts. These results depend to a considerable extent on the assumption of high interim storage costs

On the role of modeling parameters in IMRT plan optimization

International Nuclear Information System (INIS)

Krause, Michael; Scherrer, Alexander; Thieke, Christian

2008-01-01

The formulation of optimization problems in intensity-modulated radiotherapy (IMRT) planning comprises the choice of various values such as function-specific parameters or constraint bounds. In current inverse planning programs that yield a single treatment plan for each optimization, it is often unclear how strongly these modeling parameters affect the resulting plan. This work investigates the mathematical concepts of elasticity and sensitivity to deal with this problem. An artificial planning case with a horse-shoe formed target with different opening angles surrounding a circular risk structure is studied. As evaluation functions the generalized equivalent uniform dose (EUD) and the average underdosage below and average overdosage beyond certain dose thresholds are used. A single IMRT plan is calculated for an exemplary parameter configuration. The elasticity and sensitivity of each parameter are then calculated without re-optimization, and the results are numerically verified. The results show the following. (1) elasticity can quantify the influence of a modeling parameter on the optimization result in terms of how strongly the objective function value varies under modifications of the parameter value. It also can describe how strongly the geometry of the involved planning structures affects the optimization result. (2) Based on the current parameter settings and corresponding treatment plan, sensitivity analysis can predict the optimization result for modified parameter values without re-optimization, and it can estimate the value intervals in which such predictions are valid. In conclusion, elasticity and sensitivity can provide helpful tools in inverse IMRT planning to identify the most critical parameters of an individual planning problem and to modify their values in an appropriate way

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.

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.

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.

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

Directory of Open Access Journals (Sweden)

Bin He

2014-01-01

Full Text Available In city traffic, it is important to improve transportation efficiency and the spacing of platoon should be shortened when crossing the street. The best method to deal with this problem is automatic control of vehicles. In this paper, a mathematical model is established for the platoon’s longitudinal movement. A systematic analysis of longitudinal control law is presented for the platoon of vehicles. However, the parameter calibration for the platoon model is relatively difficult because the platoon model is complex and the parameters are coupled with each other. In this paper, the particle swarm optimization method is introduced to effectively optimize the parameters of platoon. The proposed method effectively finds the optimal parameters based on simulations and makes the spacing of platoon shorter.

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.

Multivariate optimization of ILC parameters

International Nuclear Information System (INIS)

Bazarov, I.V.; Padamsee, H.S.

2005-01-01

We present results of multiobjective optimization of the International Linear Collider (ILC) which seeks to maximize luminosity at each given total cost of the linac (capital and operating costs of cryomodules, refrigeration and RF). Evolutionary algorithms allow quick exploration of optimal sets of parameters in a complicated system such as ILC in the presence of realistic constraints as well as investigation of various what-if scenarios in potential performance. Among the parameters we varied there were accelerating gradient and Q of the cavities (in a coupled manner following a realistic Q vs. E curve), the number of particles per bunch, the bunch length, number of bunches in the train, etc. We find an optimum which decreases (relative to TESLA TDR baseline) the total linac cost by 22%, capital cost by 25% at the same luminosity of 3 x 10 38 m -2 s -1 . For this optimum the gradient is 35 MV/m, the final spot size is 3.6 nm, and the beam power is 15.9 MV/m. Changing the luminosity by 10 38 m -2 s -1 results in 10% change in the total linac cost and 4% in the capital cost. We have also explored the optimal fronts of luminosity vs. cost for several other scenarios using the same approach. (orig.)

Optimization of quantitative waste volume determination technique for hanford waste tank closure

International Nuclear Information System (INIS)

Monts, David L.; Jang, Ping-Rey; Long, Zhiling; Okhuysen, Walter P.; Norton, Olin P.; Gresham, Lawrence L.; Su, Yi; Lindner, Jeffrey S.

2011-01-01

The Hanford Site is currently in the process of an extensive effort to empty and close its radioactive single-shell and double-shell waste storage tanks. Before this can be accomplished, it is necessary to know how much residual material is left in a given waste tank and the uncertainty with which that volume is known. The Institute for Clean Energy Technology (ICET) at Mississippi State University is currently developing a quantitative in-tank imaging system based on Fourier Transform Profilometry, FTP. FTP is a non-contact, 3-D shape measurement technique. By projecting a fringe pattern onto a target surface and observing its deformation due to surface irregularities from a different view angle, FTP is capable of determining the height (depth) distribution (and hence volume distribution) of the target surface, thus reproducing the profile of the target accurately under a wide variety of conditions. Hence FTP has the potential to be utilized for quantitative determination of residual wastes within Hanford waste tanks. In this paper, efforts to characterize the accuracy and precision of quantitative volume determination using FTP and the use of these results to optimize the FTP system for deployment within Hanford waste tanks are described. (author)

Optimization Design of Multi-Parameters in Rail Launcher System

Directory of Open Access Journals (Sweden)

Yujiao Zhang

2014-05-01

Full Text Available Today the energy storage systems are still encumbering, therefore it is useful to think about the optimization of a railgun system in order to achieve the best performance with the lowest energy input. In this paper, an optimal design method considering 5 parameters is proposed to improve the energy conversion efficiency of a simple railgun. In order to avoid costly trials, the field- circuit method is employed to analyze the operations of different structural railguns with different parameters respectively. And the orthogonal test approach is used to guide the simulation for choosing the better parameter combinations, as well reduce the calculation cost. The research shows that the proposed method gives a better result in the energy efficiency of the system. To improve the energy conversion efficiency of electromagnetic rail launchers, the selection of more parameters must be considered in the design stage, such as the width, height and length of rail, the distance between rail pair, and pulse forming inductance. However, the relationship between these parameters and energy conversion efficiency cannot be directly described by one mathematical expression. So optimization methods must be applied to conduct design. In this paper, a rail launcher with five parameters was optimized by using orthogonal test method. According to the arrangement of orthogonal table, the better parameters’ combination can be obtained through less calculation. Under the condition of different parameters’ value, field and circuit simulation analysis were made. The results show that the energy conversion efficiency of the system is increased by 71.9 % after parameters optimization.

A procedure for multi-objective optimization of tire design parameters

OpenAIRE

Nikola Korunović; Miloš Madić; Miroslav Trajanović; Miroslav Radovanović

2015-01-01

The identification of optimal tire design parameters for satisfying different requirements, i.e. tire performance characteristics, plays an essential role in tire design. In order to improve tire performance characteristics, formulation and solving of multi-objective optimization problem must be performed. This paper presents a multi-objective optimization procedure for determination of optimal tire design parameters for simultaneous minimization of strain energy density at two distinctive zo...

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...

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

Science.gov (United States)

Utama, D. N.; Ani, N.; Iqbal, M. M.

2018-03-01

Optimization is a process for finding parameter (parameters) that is (are) able to deliver an optimal value for an objective function. Seeking an optimal generic model for optimizing is a computer science study that has been being practically conducted by numerous researchers. Generic model is a model that can be technically operated to solve any varieties of optimization problem. By using an object-oriented method, the generic model for optimizing was constructed. Moreover, two types of optimization method, simulated-annealing and hill-climbing, were functioned in constructing the model and compared to find the most optimal one then. The result said that both methods gave the same result for a value of objective function and the hill-climbing based model consumed the shortest running time.

Relating structural parameters to leachability in a glass-bonded ceramic waste form

International Nuclear Information System (INIS)

Frank, S. M.; Johnson, S. G.; Moschetti, T. L.

1998-01-01

Lattice parameters for a crystalline material can be obtained by several methods, notably by analyzing x-ray powder diffraction patterns. By utilizing a computer program to fit a pattern, one can follow the evolution or subtle changes in a structure of a crystalline species in different environments. This work involves such a study for an essential component of the ceramic waste form that is under development at Argonne National Laboratory. Zeolite 4A and zeolite 5A are used to produce two different types of waste forms: a glass-bonded sodalite and a glass-bonded zeolite, respectively. Changes in structure during production of the waste forms are discussed. Specific salt-loadings in the sodalite waste form are related to relative peak intensities of certain reflections in the XRD patterns. Structural parameters for the final waste forms will also be given and related to leachability under standard conditions

Optimal correction and design parameter search by modern methods of rigorous global optimization

International Nuclear Information System (INIS)

Makino, K.; Berz, M.

2011-01-01

Frequently the design of schemes for correction of aberrations or the determination of possible operating ranges for beamlines and cells in synchrotrons exhibit multitudes of possibilities for their correction, usually appearing in disconnected regions of parameter space which cannot be directly qualified by analytical means. In such cases, frequently an abundance of optimization runs are carried out, each of which determines a local minimum depending on the specific chosen initial conditions. Practical solutions are then obtained through an often extended interplay of experienced manual adjustment of certain suitable parameters and local searches by varying other parameters. However, in a formal sense this problem can be viewed as a global optimization problem, i.e. the determination of all solutions within a certain range of parameters that lead to a specific optimum. For example, it may be of interest to find all possible settings of multiple quadrupoles that can achieve imaging; or to find ahead of time all possible settings that achieve a particular tune; or to find all possible manners to adjust nonlinear parameters to achieve correction of high order aberrations. These tasks can easily be phrased in terms of such an optimization problem; but while mathematically this formulation is often straightforward, it has been common belief that it is of limited practical value since the resulting optimization problem cannot usually be solved. However, recent significant advances in modern methods of rigorous global optimization make these methods feasible for optics design for the first time. The key ideas of the method lie in an interplay of rigorous local underestimators of the objective functions, and by using the underestimators to rigorously iteratively eliminate regions that lie above already known upper bounds of the minima, in what is commonly known as a branch-and-bound approach. Recent enhancements of the Differential Algebraic methods used in particle

Optimization of waste to energy routes through biochemical and thermochemical treatment options of municipal solid waste in Hyderabad, Pakistan

International Nuclear Information System (INIS)

Korai, Muhammad Safar; Mahar, Rasool Bux; Uqaili, Muhammad Aslam

2016-01-01

Highlights: • Existing practice of municipal solid waste management of Hyderabad city, Pakistan have been analyzed. • Development of scenarios on basis of nature of waste components for optimizing waste to energy route. • Analyzing the biochemical and thermochemical potential of MSW through various scenarios. • Evaluation of various treatment technologies under scenarios to optimize waste to energy route. - Abstract: Improper disposal of municipal solid waste (MSW) has created many environmental problems in Pakistan and the country is facing energy shortages as well. The present study evaluates the biochemical and thermochemical treatment options of MSW in order to address both the endemic environmental challenges and in part the energy shortage. According to the nature of waste components, a number of scenarios were developed to optimize the waste to energy (WTE) routes. The evaluation of treatment options has been performed by mathematical equations using the special characteristics of MSW. The power generation potential (PGP) of biochemical (anaerobic digestion) has been observed in the range of 5.9–11.3 kW/ton day under various scenarios. The PGP of Refuse Derived Fuel (RDF), Mass Burn Incinerator (MBI), Gasification/Pyrolysis (Gasi./Pyro.) and Plasma Arc Gasification (PAG) have been found to be in the range of 2.7–118.6 kW/ton day, 3.8–164.7 kW/ton day, 4.2–184.5 kW/ton day and 5.2–224 kW/ton day, respectively. The highest values of biochemical and all thermochemical technologies have been obtained through the use of scenarios including the putrescible components (PCs) of MSW such as food and yard wastes, and the non-biodegradable components (NBCs) of MSW such as plastic, rubber, leather, textile and wood respectively. Therefore, routes which include these components are the optimized WTE routes for maximum PGP by biochemical and thermochemical treatments of MSW. The findings of study lead to recommend that socio-economic and environmental

Optimized assessment and usage of biological waste; Optimierte Erfassung und Verwertung von Bioabfall

Energy Technology Data Exchange (ETDEWEB)

Kern, Michael; Raussen, Thomas (eds.)

2013-07-01

The booklet on the optimized assessment and usage of biological waste includes contributions on the following issues: implementation of the bio-waste assessment in the federal states; economy and ecology of bio-waste fermentation; practice forum biogas: new bio-waste fermentation plants in Germany; effects of legal reforms on the usage and processing of bio-waste; flexible electricity input and power-to-gas.

Beyond bixels: Generalizing the optimization parameters for intensity modulated radiation therapy

International Nuclear Information System (INIS)

Markman, Jerry; Low, Daniel A.; Beavis, Andrew W.; Deasy, Joseph O.

2002-01-01

Intensity modulated radiation therapy (IMRT) treatment planning systems optimize fluence distributions by subdividing the fluence distribution into rectangular bixels. The algorithms typically optimize the fluence intensity directly, often leading to fluence distributions with sharp discontinuities. These discontinuities may yield difficulties in delivery of the fluence distribution, leading to inaccurate dose delivery. We have developed a method for decoupling the bixel intensities from the optimization parameters; either by introducing optimization control points from which the bixel intensities are interpolated or by parametrizing the fluence distribution using basis functions. In either case, the number of optimization search parameters is reduced from the direct bixel optimization method. To illustrate the concept, the technique is applied to two-dimensional idealized head and neck treatment plans. The interpolation algorithms investigated were nearest-neighbor, linear and cubic spline, and radial basis functions serve as the basis function test. The interpolation and basis function optimization techniques were compared against the direct bixel calculation. The number of optimization parameters were significantly reduced relative to the bixel optimization, and this was evident in the reduction of computation time of as much as 58% from the full bixel optimization. The dose distributions obtained using the reduced optimization parameter sets were very similar to the full bixel optimization when examined by dose distributions, statistics, and dose-volume histograms. To evaluate the sensitivity of the fluence calculations to spatial misalignment caused either by delivery errors or patient motion, the doses were recomputed with a 1 mm shift in each beam and compared to the unshifted distributions. Except for the nearest-neighbor algorithm, the reduced optimization parameter dose distributions were generally less sensitive to spatial shifts than the bixel

Optimization of protection as a decision-making tool for radioactive waste disposal

International Nuclear Information System (INIS)

Bragg, K.

1988-03-01

This paper discusses whether optimization of radiation protection is a workable or helpful concept or tool with respect to decisions in the field of long-term radioactive waste management. Examples of three waste types (high-level, low-level and uranium mine tailings) are used to illustrate that actual decisions are made taking account of more complex factors and that optimization of protection plays a relatively minor role. It is thus concluded that it is not a useful general tool for waste management decision-making. Discussion of the nature of the differences between technical and non-technical factors is also presented along with suggestions to help facilitate future decision-making

Optimization of volatile fatty acid production with co-substrate of food wastes and dewatered excess sludge using response surface methodology.

Science.gov (United States)

Hong, Chen; Haiyun, Wu

2010-07-01

Central-composite design (CCD) and response surface methodology (RSM) were used to optimize the parameters of volatile fatty acid (VFA) production from food wastes and dewatered excess sludge in a semi-continuous process. The effects of four variables (food wastes composition in the co-substrate of food wastes and excess sludge, hydraulic retention time (HRT), organic loading rate (OLR), and pH) on acidogenesis were evaluated individually and interactively. The optimum condition derived via RSM was food wastes composition, 88.03%; HRT, 8.92 days; OLR, 8.31 g VSS/ld; and pH 6.99. The experimental VFA concentration was 29,099 mg/l under this optimum condition, which was well in agreement with the predicted value of 28,000 mg/l. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

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.

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.

Regional integrated solid waste management: an optimization model for northern Lebanon

International Nuclear Information System (INIS)

Abou Najm, M.; El Fadel, M.; El-Taha, M.; Ayoub, G.; Al-Awar

2000-01-01

Full text.Increased environmental concerns and the emphasis on material and energy recovery are gradually changing the orientation of municipal solid waste (MSW) management and planning. In this context, the application of optimization techniques have been introduced to design the least cost solid waste management systems, considering the variety of management processes (recycling, composting, anaerobic digestion, incineration and land filling) and the existence of uncertainties associated with the number of system components and their interrelations. This study presents a model that was developed and applied to serve as a solid socio-economic and environmental considerations. The model accounts for solid waste generation rates, composition, collection, treatment, disposal as well as potential environmental impacts of various MSW management techniques. The model follows a linear programming formulation with the framework of dynamic optimization. The model can serve as a tool to evaluate various MSW management alternatives and obtain the optimal combination of technologies for the handling, treatment and disposal of MSW in an economic and environmentally sustainable way. The sensitivity of various waste management policies is also addressed. Finally, the region of Northern Lebanon was considered as a case study with data collected for the year 2000, to demonstrate the applicability of the model

A procedure for multi-objective optimization of tire design parameters

Directory of Open Access Journals (Sweden)

Nikola Korunović

2015-04-01

Full Text Available The identification of optimal tire design parameters for satisfying different requirements, i.e. tire performance characteristics, plays an essential role in tire design. In order to improve tire performance characteristics, formulation and solving of multi-objective optimization problem must be performed. This paper presents a multi-objective optimization procedure for determination of optimal tire design parameters for simultaneous minimization of strain energy density at two distinctive zones inside the tire. It consists of four main stages: pre-analysis, design of experiment, mathematical modeling and multi-objective optimization. Advantage of the proposed procedure is reflected in the fact that multi-objective optimization is based on the Pareto concept, which enables design engineers to obtain a complete set of optimization solutions and choose a suitable tire design. Furthermore, modeling of the relationships between tire design parameters and objective functions based on multiple regression analysis minimizes computational and modeling effort. The adequacy of the proposed tire design multi-objective optimization procedure has been validated by performing experimental trials based on finite element method.

Parametric optimization and heat transfer analysis of a dual loop ORC (organic Rankine cycle) system for CNG engine waste heat recovery

International Nuclear Information System (INIS)

Yang, Fubin; Zhang, Hongguang; Yu, Zhibin; Wang, Enhua; Meng, Fanxiao; Liu, Hongda; Wang, Jingfu

2017-01-01

In this study, a dual loop ORC (organic Rankine cycle) system is adopted to recover exhaust energy, waste heat from the coolant system, and intercooler heat rejection of a six-cylinder CNG (compressed natural gas) engine. The thermodynamic, heat transfer, and optimization models for the dual loop ORC system are established. On the basis of the waste heat characteristics of the CNG engine over the whole operating range, a GA (genetic algorithm) is used to solve the Pareto solution for the thermodynamic and heat transfer performances to maximize net power output and minimize heat transfer area. Combined with optimization results, the optimal parameter regions of the dual loop ORC system are determined under various operating conditions. Then, the variation in the heat transfer area with the operating conditions of the CNG engine is analyzed. The results show that the optimal evaporation pressure and superheat degree of the HT (high temperature) cycle are mainly influenced by the operating conditions of the CNG engine. The optimal evaporation pressure and superheat degree of the HT cycle over the whole operating range are within 2.5–2.9 MPa and 0.43–12.35 K, respectively. The optimal condensation temperature of the HT cycle, evaporation and condensation temperatures of the LT (low temperature) cycle, and exhaust temperature at the outlet of evaporator 1 are kept nearly constant under various operating conditions of the CNG engine. The thermal efficiency of the dual loop ORC system is within the range of 8.79%–10.17%. The dual loop ORC system achieves the maximum net power output of 23.62 kW under the engine rated condition. In addition, the operating conditions of the CNG engine and the operating parameters of the dual loop ORC system significantly influence the heat transfer areas for each heat exchanger. - Highlights: • A dual loop ORC system is adopted to recover the waste heat of a CNG engine. • Parametric optimization and heat transfer analysis are

Enhanced Bio-Ethanol Production from Industrial Potato Waste by Statistical Medium Optimization

OpenAIRE

Izmirlioglu, Gulten; Demirci, Ali

2015-01-01

Industrial wastes are of great interest as a substrate in production of value-added products to reduce cost, while managing the waste economically and environmentally. Bio-ethanol production from industrial wastes has gained attention because of its abundance, availability, and rich carbon and nitrogen content. In this study, industrial potato waste was used as a carbon source and a medium was optimized for ethanol production by using statistical designs. The effect of various medium componen...

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.

Integral Optimization of Systematic Parameters of Flip-Flow Screens

Institute of Scientific and Technical Information of China (English)

翟宏新

2004-01-01

The synthetic index Ks for evaluating flip-flow screens is proposed and systematically optimized in view of the whole system. A series of optimized values of relevant parameters are found and then compared with those of the current industrial specifications. The results show that the optimized value Ks approaches the one of those famous flip-flow screens in the world. Some new findings on geometric and kinematics parameters are useful for improving the flip-flow screens with a low Ks value, which is helpful in developing clean coal technology.

An Optimization Approach for Hazardous Waste Management Problem under Stochastic Programming

International Nuclear Information System (INIS)

Abass, S.A.; Abdallah, A.S.; Gomaa, M.A.

2008-01-01

Hazardous waste is the waste which, due to their nature and quantity, is potentially hazardous to human health and/or the environment. This kind of waste requires special disposal techniques to eliminate or reduce thc hazardous. Hazardous waste management (HWM) problem is concerned in the basic with the disposal method. hi this paper we focus on incineration as an effective to dispose the waste. For this type of disposal, there arc air pollution standards imposed by the government. We will propose an optimization model satisfied the air pollution standards and based on the model of Emek and Kara with using random variable coefficients in the constraint

Development of engineering parameters for the design of metal biosorption waste treatment systems

Energy Technology Data Exchange (ETDEWEB)

Graham, W.S.

1991-12-03

Untreated landfill leachates and wastes from metal plating and mining operations are sources of environmental contamination by heavy metals. Because of their toxicity and potential for accumulation, the discharge of heavy metals must be controlled. Standard physical and chemical treatments used to remove metals from wastes such as concentration by electro-precipitation, ion exchange, solvent extraction, evaporative recovery, and conventional precipitation, are usually expensive and produce high quantities of sludge. Biosorption is the removal of metals from aqueous solutions by microorganisms. It is called biosorption rather than bioadsorption or bioaccumulation because the mechanisms of removal are not restricted to adsorption or metabolic uptake and so the more general term is preferable and has come to be accepted. In this thesis the focus is one two microorganisms and two metals. However, the possible combinations of conditions such as pH, relative metal molarities, time of contact, and organism are numerous. These experiments are designed to provide optimized parameters to facilitate the design of a functioning biosorption system. The two metals chosen for study are copper and lead in aqueous solution. The two types of microorganisms chosen for testing include an actinomycete and a fungus. The purpose of this research is to identify the significant engineering parameters to be evaluated include reaction rates, equilibrium partitioning of metal ions between those in solution and those removed to the cells, optimum pH for achieving the removal or recovery goal, and biosorption selectivity for one metal over another.

DOUBLE SHELL TANK INTEGRITY PROJECT HIGH LEVEL WASTE CHEMISTRY OPTIMIZATION

International Nuclear Information System (INIS)

WASHENFELDER DJ

2008-01-01

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

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.)

Parameters Optimization and Application to Glutamate Fermentation Model Using SVM

OpenAIRE

Zhang, Xiangsheng; Pan, Feng

2015-01-01

Aimed at the parameters optimization in support vector machine (SVM) for glutamate fermentation modelling, a new method is developed. It optimizes the SVM parameters via an improved particle swarm optimization (IPSO) algorithm which has better global searching ability. The algorithm includes detecting and handling the local convergence and exhibits strong ability to avoid being trapped in local minima. The material step of the method was shown. Simulation experiments demonstrate the effective...

Optimization criteria for low temperature waste heat utilization

International Nuclear Information System (INIS)

Kranebitter, F.

1977-01-01

A special case in this field is the utilization of very low temperature waste heat. The temperature level under consideration in this paper is in the range between the body temperature of human beings and their environment. The waste heat from power generation and industrial processes is also considered. Thermal energy conversion will be mainly accomplished by heat cycles where discharged waste heat is reverse proportional to the upper cycle temperature. Limiting this upper cycle temperature by technological reasons the optimization of the heat cycle will depend on the nature of the cycle itself and specially on the temperature selected for the heat discharge. The waste heat discharge is typical for the different kinds of heat cycles and the paper presents the four most important of them. Feasible heat transfer methods and their economic evaluations are discussed and the distillation processes will be the basis for further considerations. The waste heat utilization for distillation purposes could be realized by three different cycles, the open cycle, the closed cycle and the multy cycle. Resulting problems as deaeration of large water streams and removal of the dissolved gases and their solutions are also discussed. (M.S.)

Research on Layout Optimization of Urban Circle Solid Waste Transfer and Disposal Stations

OpenAIRE

Xuhui Li; Gangyan Li; Guowen Sun; Huiping Shi; Bao’an Yang

2013-01-01

Based on the Systematic Layout Planning theory and the analysis of transfer stations’ technological processes, a layout optimization model for solid waste transfer and disposal stations was made. The operating units’ layout of the solid waste transfer and disposal stations was simulated and optimized using the genetic algorithm, which could achieve reasonable technological processes, the smallest floor space and the lowest construction cost. The simulation result can also direct t...

Structural optimization of reinforced concrete container for radioactive wastes

International Nuclear Information System (INIS)

Tamura, M.

1984-01-01

A structural optimization study of reinforced concrete container for transportation and disposal of the low level radioactive waste generated in Brazilian nuclear power plants. The code requires the structural integrity of these containers when subjected to fall from specified height, avoiding environmental contamination. The structural optimization allows material and transportation cost reduction by container wall thickness reduction. The structural analysis is performed by tridimensional mathematical model using finite element method. (Author) [pt

Optimization of Enzymatic Hydrolysis of Waste Bread before Fermentation

OpenAIRE

Hudečková, Helena; Šupinová, Petra; Ing. Mgr. Libor Babák, Ph.D., MBA

2017-01-01

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...

Multi-objective optimization in quantum parameter estimation

Science.gov (United States)

Gong, BeiLi; Cui, Wei

2018-04-01

We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of parameter estimation is improved, it usually introduces a significant deformation to the system state. Moreover, we propose a multi-objective model to optimize the two conflicting objectives: (1) maximizing the Fisher information, improving the parameter estimation precision, and (2) minimizing the deformation of the system state, which maintains its fidelity. Finally, simulations of a simplified ɛ-constrained model demonstrate the feasibility of the Hamiltonian control in improving the precision of the quantum parameter estimation.

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.

Optimization of Loudspeaker Part Design Parameters by Air Viscosity Damping Effect

OpenAIRE

Yue Hu; Xilu Zhao; Takao Yamaguchi; Manabu Sasajima; Yoshio Koike; Akira Hara

2016-01-01

This study optimized the design parameters of a cone loudspeaker as an example of high flexibility of the product design. We developed an acoustic analysis software program that considers the impact of damping caused by air viscosity. In sound reproduction, it is difficult to optimize each parameter of the loudspeaker design. To overcome the limitation of the design problem in practice, this study presents an acoustic analysis algorithm to optimize the design parameters of the loudspeaker. Th...

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

Indian Academy of Sciences (India)

system is used, route distance and route time will be decreased by 24·6% and. 44·3% as ... Keywords. Exhaust emission; route optimization; solid waste collection; GIS, .... Catchment areas for a sales campaign can be analysed. Customers ...

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.

Statistical optimization for lipase production from solid waste of vegetable oil industry.

Science.gov (United States)

Sahoo, Rajesh Kumar; Kumar, Mohit; Mohanty, Swati; Sawyer, Matthew; Rahman, Pattanathu K S M; Sukla, Lala Behari; Subudhi, Enketeswara

2018-04-21

The production of biofuel using thermostable bacterial lipase from hot spring bacteria out of low-cost agricultural residue olive oil cake is reported in the present paper. Using a lipase enzyme from Bacillus licheniformis, a 66.5% yield of methyl esters was obtained. Optimum parameters were determined, with maximum production of lipase at a pH of 8.2, temperature 50.8°C, moisture content of 55.7%, and biosurfactant content of 1.693 mg. The contour plots and 3D surface responses depict the significant interaction of pH and moisture content with biosurfactant during lipase production. Chromatographic analysis of the lipase transesterification product was methyl esters, from kitchen waste oil under optimized conditions, generated methyl palmitate, methyl stearate, methyl oleate, and methyl linoleate.

Low-dose cone-beam CT via raw counts domain low-signal correction schemes: Performance assessment and task-based parameter optimization (Part II. Task-based parameter optimization).

Science.gov (United States)

Gomez-Cardona, Daniel; Hayes, John W; Zhang, Ran; Li, Ke; Cruz-Bastida, Juan Pablo; Chen, Guang-Hong

2018-05-01

Different low-signal correction (LSC) methods have been shown to efficiently reduce noise streaks and noise level in CT to provide acceptable images at low-radiation dose levels. These methods usually result in CT images with highly shift-variant and anisotropic spatial resolution and noise, which makes the parameter optimization process highly nontrivial. The purpose of this work was to develop a local task-based parameter optimization framework for LSC methods. Two well-known LSC methods, the adaptive trimmed mean (ATM) filter and the anisotropic diffusion (AD) filter, were used as examples to demonstrate how to use the task-based framework to optimize filter parameter selection. Two parameters, denoted by the set P, for each LSC method were included in the optimization problem. For the ATM filter, these parameters are the low- and high-signal threshold levels p l and p h ; for the AD filter, the parameters are the exponents δ and γ in the brightness gradient function. The detectability index d' under the non-prewhitening (NPW) mathematical observer model was selected as the metric for parameter optimization. The optimization problem was formulated as an unconstrained optimization problem that consisted of maximizing an objective function d'(P), where i and j correspond to the i-th imaging task and j-th spatial location, respectively. Since there is no explicit mathematical function to describe the dependence of d' on the set of parameters P for each LSC method, the optimization problem was solved via an experimentally measured d' map over a densely sampled parameter space. In this work, three high-contrast-high-frequency discrimination imaging tasks were defined to explore the parameter space of each of the LSC methods: a vertical bar pattern (task I), a horizontal bar pattern (task II), and a multidirectional feature (task III). Two spatial locations were considered for the analysis, a posterior region-of-interest (ROI) located within the noise streaks region

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

Parameters Optimization and Application to Glutamate Fermentation Model Using SVM

Directory of Open Access Journals (Sweden)

Xiangsheng Zhang

2015-01-01

Full Text Available Aimed at the parameters optimization in support vector machine (SVM for glutamate fermentation modelling, a new method is developed. It optimizes the SVM parameters via an improved particle swarm optimization (IPSO algorithm which has better global searching ability. The algorithm includes detecting and handling the local convergence and exhibits strong ability to avoid being trapped in local minima. The material step of the method was shown. Simulation experiments demonstrate the effectiveness of the proposed algorithm.

Optimization of MIS/IL solar cells parameters using genetic algorithm

Energy Technology Data Exchange (ETDEWEB)

Ahmed, K.A.; Mohamed, E.A.; Alaa, S.H. [Faculty of Engineering, Alexandria Univ. (Egypt); Motaz, M.S. [Institute of Graduate Studies and Research, Alexandria Univ. (Egypt)

2004-07-01

This paper presents a genetic algorithm optimization for MIS/IL solar cell parameters including doping concentration NA, metal work function {phi}m, oxide thickness d{sub ox}, mobile charge density N{sub m}, fixed oxide charge density N{sub ox} and the external back bias applied to the inversion grid V. The optimization results are compared with theoretical optimization and shows that the genetic algorithm can be used for determining the optimum parameters of the cell. (orig.)

Optimizing incomplete sample designs for item response model parameters

NARCIS (Netherlands)

van der Linden, Willem J.

Several models for optimizing incomplete sample designs with respect to information on the item parameters are presented. The following cases are considered: (1) known ability parameters; (2) unknown ability parameters; (3) item sets with multiple ability scales; and (4) response models with

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.

Optimization of glass composition for the vitrification of nuclear waste at the Savannah River Plant

International Nuclear Information System (INIS)

Soper, P.D.; Roberts, G.J.; Lightner, L.F.; Walker, D.D.; Plodinec, M.J.

1982-01-01

Waste glasses of different compositions were compared in terms of leachability, viscosity, liquidus temperature, and coefficient of expansion. The compositions of the glasses were determined by statistical optimization. Waste glass of the optimized composition is more durable than the current reference composition but can still be processed at low temperature

Multi-objective optimization of two alkali catalyzed processes for biodiesel from waste cooking oil

International Nuclear Information System (INIS)

Patle, Dipesh S.; Sharma, Shivom; Ahmad, Z.; Rangaiah, G.P.

2014-01-01

Highlights: • Biodiesel processes use waste cooking oil and are close to industrial practice. • Detailed constituents of waste cooking oil and detailed kinetics are used. • Two complete processes are optimized for economic and environmental objectives. • Obtained trade-offs provide deeper understanding and alternative optimal solutions. - Abstract: In view of the finite availability and environmental concerns of fossil fuels, biodiesel is one of the promising fuel alternatives. This study considers waste cooking palm oil with 6% free fatty acids (FFA) as feed-stock, which facilitates its better utilization and promotes sustainability. Two biodiesel production processes (both involving esterification catalyzed by sulfuric acid and trans-esterification catalyzed by sodium hydroxide) are compared for economic and environmental objectives. Firstly, these processes are simulated, considering detailed constituents of palm oil and also detailed kinetics for both esterification and trans-esterification, in Aspen Plus simulator. Subsequently, both the processes are optimized considering profit, heat duty and organic waste as objectives, and using an Excel-based multi-objective optimization (EMOO) program for the elitist non-dominated sorting genetic algorithm-II (NSGA-II). The results show that the profit improves with the increase in heat duty, and that the profit increase is accompanied by larger amount of organic waste. Process 1 having three trans-esterification reactors produces significantly lower organic waste (by 32%), requires lower heat duty (by 39%) and slightly more profitable (by 1.6%) compared to Process 2 having a single trans-esterification reactor and also a different separation sequence. Overall, the obtained quantitative trade-offs between objectives enable better decision making about the process design for biodiesel production from waste cooking oil

Nonlinearity Analysis and Parameters Optimization for an Inductive Angle Sensor

Directory of Open Access Journals (Sweden)

Lin Ye

2014-02-01

Full Text Available Using the finite element method (FEM and particle swarm optimization (PSO, a nonlinearity analysis based on parameter optimization is proposed to design an inductive angle sensor. Due to the structure complexity of the sensor, understanding the influences of structure parameters on the nonlinearity errors is a critical step in designing an effective sensor. Key parameters are selected for the design based on the parameters’ effects on the nonlinearity errors. The finite element method and particle swarm optimization are combined for the sensor design to get the minimal nonlinearity error. In the simulation, the nonlinearity error of the optimized sensor is 0.053% in the angle range from −60° to 60°. A prototype sensor is manufactured and measured experimentally, and the experimental nonlinearity error is 0.081% in the angle range from −60° to 60°.

Optimal parameters uncoupling vibration modes of oscillators

Science.gov (United States)

Le, K. C.; Pieper, A.

2017-07-01

This paper proposes a novel optimization concept for an oscillator with two degrees of freedom. By using specially defined motion ratios, we control the action of springs to each degree of freedom of the oscillator. We aim at showing that, if the potential action of the springs in one period of vibration, used as the payoff function for the conservative oscillator, is maximized among all admissible parameters and motions satisfying Lagrange's equations, then the optimal motion ratios uncouple vibration modes. A similar result holds true for the dissipative oscillator having dampers. The application to optimal design of vehicle suspension is discussed.

Optimization of surface roughness parameters in dry turning

OpenAIRE

R.A. Mahdavinejad; H. Sharifi Bidgoli

2009-01-01

Purpose: The precision of machine tools on one hand and the input setup parameters on the other hand, are strongly influenced in main output machining parameters such as stock removal, toll wear ratio and surface roughnes.Design/methodology/approach: There are a lot of input parameters which are effective in the variations of these output parameters. In CNC machines, the optimization of machining process in order to predict surface roughness is very important.Findings: From this point of view...

Optimization Design of Multi-Parameters in Rail Launcher System

OpenAIRE

Yujiao Zhang; Weinan Qin; Junpeng Liao; Jiangjun Ruan

2014-01-01

Today the energy storage systems are still encumbering, therefore it is useful to think about the optimization of a railgun system in order to achieve the best performance with the lowest energy input. In this paper, an optimal design method considering 5 parameters is proposed to improve the energy conversion efficiency of a simple railgun. In order to avoid costly trials, the field- circuit method is employed to analyze the operations of different structural railguns with different paramete...

Optimization of electrospinning parameters for chitosan nanofibres

CSIR Research Space (South Africa)

Jacobs, V

2011-06-01

Full Text Available Electrospinning of chitosan, a naturally occurring polysaccharide biopolymer, has been investigated. In this paper, the authors report the optimization of electrospinning process and solution parameters using factorial design approach to obtain...

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

Science.gov (United States)

2017-09-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS SEARCH PARAMETER OPTIMIZATION FOR DISCRETE , BAYESIAN, AND CONTINUOUS SEARCH ALGORITHMS by...to 09-22-2017 4. TITLE AND SUBTITLE SEARCH PARAMETER OPTIMIZATION FOR DISCRETE , BAYESIAN, AND CON- TINUOUS SEARCH ALGORITHMS 5. FUNDING NUMBERS 6...simple search and rescue acts to prosecuting aerial/surface/submersible targets on mission. This research looks at varying the known discrete and

Cosmological parameter estimation using particle swarm optimization

Science.gov (United States)

Prasad, Jayanti; Souradeep, Tarun

2012-06-01

Constraining theoretical models, which are represented by a set of parameters, using observational data is an important exercise in cosmology. In Bayesian framework this is done by finding the probability distribution of parameters which best fits to the observational data using sampling based methods like Markov chain Monte Carlo (MCMC). It has been argued that MCMC may not be the best option in certain problems in which the target function (likelihood) poses local maxima or have very high dimensionality. Apart from this, there may be examples in which we are mainly interested to find the point in the parameter space at which the probability distribution has the largest value. In this situation the problem of parameter estimation becomes an optimization problem. In the present work we show that particle swarm optimization (PSO), which is an artificial intelligence inspired population based search procedure, can also be used for cosmological parameter estimation. Using PSO we were able to recover the best-fit Λ cold dark matter (LCDM) model parameters from the WMAP seven year data without using any prior guess value or any other property of the probability distribution of parameters like standard deviation, as is common in MCMC. We also report the results of an exercise in which we consider a binned primordial power spectrum (to increase the dimensionality of problem) and find that a power spectrum with features gives lower chi square than the standard power law. Since PSO does not sample the likelihood surface in a fair way, we follow a fitting procedure to find the spread of likelihood function around the best-fit point.

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.

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

Science.gov (United States)

Lee, H.; Liau, Y.; Ryu, K.

2018-03-01

The manufacturing industry has been facing several challenges, including sustainability, performance and quality of production. Manufacturers attempt to enhance the competitiveness of companies by implementing CPS (Cyber-Physical Systems) through the convergence of IoT(Internet of Things) and ICT(Information & Communication Technology) in the manufacturing process level. Injection molding process has a short cycle time and high productivity. This features have been making it suitable for mass production. In addition, this process is used to produce precise parts in various industry fields such as automobiles, optics and medical devices. Injection molding process has a mixture of discrete and continuous variables. In order to optimized the quality, variables that is generated in the injection molding process must be considered. Furthermore, Optimal parameter setting is time-consuming work to predict the optimum quality of the product. Since the process parameter cannot be easily corrected during the process execution. In this research, we propose a neural network based real-time process parameter optimization methodology that sets optimal process parameters by using mold data, molding machine data, and response data. This paper is expected to have academic contribution as a novel study of parameter optimization during production compare with pre - production parameter optimization in typical studies.

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

African Journals Online (AJOL)

This study presents optimization of various lignocellulosics and alkali pretreatment for maximum cellulase production by Trichoderma virdii sp. Maximum endoglucanase (642 IU/L) and exoglucanase (187IU/L) activity was achieved with maize straw at 5% concentration. Oat hay was the most suitable agro-waste for β ...

Test Summary Report Vitrification Demonstration of an Optimized Hanford C-106/AY-102 Waste-Glass Formulation

International Nuclear Information System (INIS)

Goles, Ronald W.; Buchmiller, William C.; Hymas, Charles R.; MacIsaac, Brett D.

2002-01-01

In order to further the goal of optimizing Hanford?s HLW borosilicate flowsheet, a glass formulation effort was launched to develop an advanced high-capacity waste form exhibiting acceptable leach and crystal formation characteristics. A simulated C-106/AY-102 waste envelop inclusive of LAW pretreatment products was chosen as the subject of these nonradioactive optimization efforts. To evaluate this optimized borosilicate waste formulation under continuous dynamic vitrification conditions, a research-scale Joule-heated ceramic melter was used to demonstrate the advanced waste form?s flowsheet. The main objectives of this melter test was to evaluate (1) the processing characteristics of the newly formulated C-106/AY-102 surrogate melter-feed stream, (2) the effectiveness of sucrose as a glass-oxidation-state modifier, and (3) the impact of this reductant upon processing rates

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

Optimization of the Area 5 Radioactive Waste Management Site Closure Cover

International Nuclear Information System (INIS)

Shott, Greg; Yucel, Vefa

2009-01-01

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 Area

Theoretical approach in optimization of stability of the multicomponent solid waste form

International Nuclear Information System (INIS)

Raicevic, S.; Plecas, I.; Mandic, M.

1998-01-01

Chemical precipitation of radionuclides and their immobilization into the solid matrix represents an important approach in the radioactive wastewater treatment. Unfortunately, because of the complexity of the system, optimization of this process in terms of its efficacy and safety represents a serious practical problem, even in treatment of the monocomponent nuclear waste. This situation is additionally complicated in the case of the polycomponent nuclear waste because of the synergic effects of interactions between the radioactive components and the solid matrix. Recently, we have proposed a general theoretical approach for optimization of the process of precipitation and immobilization of metal impurities by the solid matrix. One of the main advantages of this approach represents the possibility of treatment of the multicomponent liquid waste, immobilized by the solid matrix. This approach was used here for investigation of the stability of the system hydroxyapatite (HAP) - Pb/Cd, which was selected as a model multicomponent waste system. In this analysis, we have used a structurally dependent term of the cohesive energy as a stability criterion. (author)

Optimal Design of Shock Tube Experiments for Parameter Inference

KAUST Repository

Bisetti, Fabrizio; Knio, Omar

2014-01-01

We develop a Bayesian framework for the optimal experimental design of the shock tube experiments which are being carried out at the KAUST Clean Combustion Research Center. The unknown parameters are the pre-exponential parameters and the activation

Joint optimization of collimator and reconstruction parameters in SPECT imaging for lesion quantification

International Nuclear Information System (INIS)

McQuaid, Sarah J; Southekal, Sudeepti; Kijewski, Marie Foley; Moore, Stephen C

2011-01-01

Obtaining the best possible task performance using reconstructed SPECT images requires optimization of both the collimator and reconstruction parameters. The goal of this study is to determine how to perform this optimization, namely whether the collimator parameters can be optimized solely from projection data, or whether reconstruction parameters should also be considered. In order to answer this question, and to determine the optimal collimation, a digital phantom representing a human torso with 16 mm diameter hot lesions (activity ratio 8:1) was generated and used to simulate clinical SPECT studies with parallel-hole collimation. Two approaches to optimizing the SPECT system were then compared in a lesion quantification task: sequential optimization, where collimation was optimized on projection data using the Cramer–Rao bound, and joint optimization, which simultaneously optimized collimator and reconstruction parameters. For every condition, quantification performance in reconstructed images was evaluated using the root-mean-squared-error of 400 estimates of lesion activity. Compared to the joint-optimization approach, the sequential-optimization approach favoured a poorer resolution collimator, which, under some conditions, resulted in sub-optimal estimation performance. This implies that inclusion of the reconstruction parameters in the optimization procedure is important in obtaining the best possible task performance; in this study, this was achieved with a collimator resolution similar to that of a general-purpose (LEGP) collimator. This collimator was found to outperform the more commonly used high-resolution (LEHR) collimator, in agreement with other task-based studies, using both quantification and detection tasks.

Parameters optimization for magnetic resonance coupling wireless power transmission.

Science.gov (United States)

Li, Changsheng; Zhang, He; Jiang, Xiaohua

2014-01-01

Taking maximum power transmission and power stable transmission as research objectives, optimal design for the wireless power transmission system based on magnetic resonance coupling is carried out in this paper. Firstly, based on the mutual coupling model, mathematical expressions of optimal coupling coefficients for the maximum power transmission target are deduced. Whereafter, methods of enhancing power transmission stability based on parameters optimal design are investigated. It is found that the sensitivity of the load power to the transmission parameters can be reduced and the power transmission stability can be enhanced by improving the system resonance frequency or coupling coefficient between the driving/pick-up coil and the transmission/receiving coil. Experiment results are well conformed to the theoretical analysis conclusions.

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.

Improved Artificial Fish Algorithm for Parameters Optimization of PID Neural Network

OpenAIRE

Jing Wang; Yourui Huang

2013-01-01

In order to solve problems such as initial weights are difficult to be determined, training results are easy to trap in local minima in optimization process of PID neural network parameters by traditional BP algorithm, this paper proposed a new method based on improved artificial fish algorithm for parameters optimization of PID neural network. This improved artificial fish algorithm uses a composite adaptive artificial fish algorithm based on optimal artificial fish and nearest artificial fi...

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.

Cosmological parameter estimation using Particle Swarm Optimization

International Nuclear Information System (INIS)

Prasad, J; Souradeep, T

2014-01-01

Constraining parameters of a theoretical model from observational data is an important exercise in cosmology. There are many theoretically motivated models, which demand greater number of cosmological parameters than the standard model of cosmology uses, and make the problem of parameter estimation challenging. It is a common practice to employ Bayesian formalism for parameter estimation for which, in general, likelihood surface is probed. For the standard cosmological model with six parameters, likelihood surface is quite smooth and does not have local maxima, and sampling based methods like Markov Chain Monte Carlo (MCMC) method are quite successful. However, when there are a large number of parameters or the likelihood surface is not smooth, other methods may be more effective. In this paper, we have demonstrated application of another method inspired from artificial intelligence, called Particle Swarm Optimization (PSO) for estimating cosmological parameters from Cosmic Microwave Background (CMB) data taken from the WMAP satellite

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.

Optimization of protection as a decision-making tool, for radioactive waste disposal

International Nuclear Information System (INIS)

Bragg, K.

1988-01-01

Politically-based considerations and processes including public perception and confidence appear to be the basis for real decisions affecting waste management activities such as siting, construction, operation and monitoring. Optimization of radiation protection is not a useful general tool for waste disposal decision making. Optimization of radiation protection is essentially a technical tool which can, under appropriate circumstances, provide a clear preference among major management options. The level of discrimination will be case-specific but, in general, only fairly coarse differences can be discriminated. The preferences determined by optimization of protection tend not to be related to the final choices made for disposal of radioactive wastes. Tools such as multi-attribute analysis are very useful as they provide a convenient means to rationalize the real decisions and give them some air of technical respectability. They do not, however, provide the primary basis for the decisions. Technical experts must develop an awareness of the non-technical approach to decision making an attempt to adjust their method of analyses and their presentation of information to encourage dialogue rather than confrontation. Simple expressions of technical information will be needed and the use of analogues should prove helpful

An optimization method for parameters in reactor nuclear physics

International Nuclear Information System (INIS)

Jachic, J.

1982-01-01

An optimization method for two basic problems of Reactor Physics was developed. The first is the optimization of a plutonium critical mass and the bruding ratio for fast reactors in function of the radial enrichment distribution of the fuel used as control parameter. The second is the maximization of the generation and the plutonium burnup by an optimization of power temporal distribution. (E.G.) [pt

Oyster Creek cycle 10 nodal model parameter optimization study using PSMS

International Nuclear Information System (INIS)

Dougher, J.D.

1987-01-01

The power shape monitoring system (PSMS) is an on-line core monitoring system that uses a three-dimensional nodal code (NODE-B) to perform nodal power calculations and compute thermal margins. The PSMS contains a parameter optimization function that improves the ability of NODE-B to accurately monitor core power distributions. This functions iterates on the model normalization parameters (albedos and mixing factors) to obtain the best agreement between predicted and measured traversing in-core probe (TIP) reading on a statepoint-by-statepoint basis. Following several statepoint optimization runs, an average set of optimized normalization parameters can be determined and can be implemented into the current or subsequent cycle core model for on-line core monitoring. A statistical analysis of 19 high-power steady-state state-points throughout Oyster Creek cycle 10 operation has shown a consistently poor virgin model performance. The normalization parameters used in the cycle 10 NODE-B model were based on a cycle 8 study, which evaluated only Exxon fuel types. The introduction of General Electric (GE) fuel into cycle 10 (172 assemblies) was a significant fuel/core design change that could have altered the optimum set of normalization parameters. Based on the need to evaluate a potential change in the model normalization parameters for cycle 11 and in an attempt to account for the poor cycle 10 model performance, a parameter optimization study was performed

GEMSFITS: Code package for optimization of geochemical model parameters and inverse modeling

International Nuclear Information System (INIS)

Miron, George D.; Kulik, Dmitrii A.; Dmytrieva, Svitlana V.; Wagner, Thomas

2015-01-01

Highlights: • Tool for generating consistent parameters against various types of experiments. • Handles a large number of experimental data and parameters (is parallelized). • Has a graphical interface and can perform statistical analysis on the parameters. • Tested on fitting the standard state Gibbs free energies of aqueous Al species. • Example on fitting interaction parameters of mixing models and thermobarometry. - Abstract: GEMSFITS is a new code package for fitting internally consistent input parameters of GEM (Gibbs Energy Minimization) geochemical–thermodynamic models against various types of experimental or geochemical data, and for performing inverse modeling tasks. It consists of the gemsfit2 (parameter optimizer) and gfshell2 (graphical user interface) programs both accessing a NoSQL database, all developed with flexibility, generality, efficiency, and user friendliness in mind. The parameter optimizer gemsfit2 includes the GEMS3K chemical speciation solver ( (http://gems.web.psi.ch/GEMS3K)), which features a comprehensive suite of non-ideal activity- and equation-of-state models of solution phases (aqueous electrolyte, gas and fluid mixtures, solid solutions, (ad)sorption. The gemsfit2 code uses the robust open-source NLopt library for parameter fitting, which provides a selection between several nonlinear optimization algorithms (global, local, gradient-based), and supports large-scale parallelization. The gemsfit2 code can also perform comprehensive statistical analysis of the fitted parameters (basic statistics, sensitivity, Monte Carlo confidence intervals), thus supporting the user with powerful tools for evaluating the quality of the fits and the physical significance of the model parameters. The gfshell2 code provides menu-driven setup of optimization options (data selection, properties to fit and their constraints, measured properties to compare with computed counterparts, and statistics). The practical utility, efficiency, and

Centralized management for LA and MA waste selection and optimization of processes

International Nuclear Information System (INIS)

Medal, G.

1985-01-01

The procedure currently used for removal of process waste produced by EDF Nuclear Power Plants consists in the local embedding of the waste on each EDF site, the embedded waste is then shipped to a National Final Storage Center. The method used is a financial limitation of opportunities for amendment of containement and volume reduction techniques. The work made by the Commissariat a l'Energie Atomique and its subsidiary TECHNICATOME on behalf of the French Electricite Board (EDF) aim at the removal of waste ''in bulk'' with minimum possible pretreatment in compliance with transport regulation, treatment and conditioning taking place in a centralized waste treatment station so as to allow final storage. This method enables: optimization of the management of waste, selection of safe treatment-processes, storage volume reduction, lower investment and operating costs [fr

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.

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.

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

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...

Optimal construction parameters of electrosprayed trilayer organic photovoltaic devices

International Nuclear Information System (INIS)

Shah, S K; Ali, M; Gunnella, R; Abbas, M; Hirsch, L

2014-01-01

A detailed investigation of the optimal set of parameters employed in multilayer device fabrication obtained through successive electrospray deposited layers is reported. In this scheme, the donor/acceptor (D/A) bulk heterojunction layer is sandwiched between two thin stacked layers of individual donor and acceptor materials. The stacked layers geometry with optimal thicknesses plays a decisive role in improving operation characteristics. Among the parameters of the multilayer organic photovoltaics device, the D/A concentration ratio, blend thickness and stacking layers thicknesses are optimized. Other parameters, such as thermal annealing and the role of top metal contacts, are also discussed. Internal photon to current efficiency is found to attain a strong response in the 500 nm optical region for the most efficient device architectures. Such an observation indicates a clear interplay between photon harvesting of active layers and transport by ancillary stacking layers, opening up the possibility to engineer both the material fine structure and the device architecture to obtain the best photovoltaic response from a complex organic heterostructure. (paper)

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

International Nuclear Information System (INIS)

Unuofin, F.O.; Mnkeni, P.N.S.

2014-01-01

Highlights: • Vermidegradation of RP-enriched waste mixtures is dependent on E. fetida stocking density. • A stocking density of 12.5 g-worms kg -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 −1 dry weight of cow dung–waste paper mixtures were evaluated. The stocking density of 12.5 g-worms kg −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 −1 feedstock suggesting that for maximum P release from RP enriched wastes a high stocking density should be considered

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.

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.

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.

Complicated problem solution techniques in optimal parameter searching

International Nuclear Information System (INIS)

Gergel', V.P.; Grishagin, V.A.; Rogatneva, E.A.; Strongin, R.G.; Vysotskaya, I.N.; Kukhtin, V.V.

1992-01-01

An algorithm is presented of a global search for numerical solution of multidimentional multiextremal multicriteria optimization problems with complicated constraints. A boundedness of object characteristic changes is assumed at restricted changes of its parameters (Lipschitz condition). The algorithm was realized as a computer code. The algorithm was realized as a computer code. The programme was used to solve in practice the different applied optimization problems. 10 refs.; 3 figs

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.

Groundwater pathway sensitivity analysis and hydrogeologic parameters identification for waste disposal in porous media

International Nuclear Information System (INIS)

Yu, C.

1986-01-01

The migration of radionuclides in a geologic medium is controlled by the hydrogeologic parameters of the medium such as dispersion coefficient, pore water velocity, retardation factor, degradation rate, mass transfer coefficient, water content, and fraction of dead-end pores. These hydrogeologic parameters are often used to predict the migration of buried wastes in nuclide transport models such as the conventional advection-dispersion model, the mobile-immobile pores model, the nonequilibrium adsorption-desorption model, and the general group transfer concentration model. One of the most important factors determining the accuracy of predicting waste migration is the accuracy of the parameter values used in the model. More sensitive parameters have a greater influence on the results and hence should determined (measured or estimated) more accurately than less sensitive parameters. A formal parameter sensitivity analysis is carried out in this paper. Parameter identification techniques to determine the hydrogeologic parameters of the flow system are discussed. The dependence of the accuracy of the estimated parameters upon the parameter sensitivity is also discussed

Optimization of oil extraction from waste “Date pits” for biodiesel production

International Nuclear Information System (INIS)

Jamil, Farrukh; Al-Muhtaseb, Ala’a H.; Al-Haj, Lamya; Al-Hinai, Mohab A.; Hellier, Paul; Rashid, Umer

2016-01-01

Highlights: • Oil extraction from “Date pits” has been optimized first time by using RSM. • Optimized conditions for oil extraction gave oil yield of 16.5%. • “Date pits” oil as non-edible feedstock was transformed to biodiesel. • Biodiesel from “Date pits” oil posses potential fuel properties. - Abstract: Biodiesel produced from non-edible feedstocks is increasingly attractive alternative to both fossil diesels and renewable fuels derived from food crops. Date pits are one such lipid containing feedstock, and are widely available in Oman as a waste stream. This study analyses the effects of soxhlet process parameters (temperature, solvent to seed ratio and time) on the extraction of oils from waste Date pits and the subsequent production of biodiesel from it. The highest yield of oil extracted from the Date pits was 16.5 wt% obtained at a temperature of 70 °C, solvent to seed ratio of 4:1 and extraction duration of 7 h. Gas Chromatography analysis showed that Date pits oil consisted of 54.85% unsaturated fatty acids (UFA). Transesterification of the oil extracted was undertaken at 65 °C, a methanol to oil ratio of 6:1 and a reaction time of 1 h for biodiesel production. Biodiesel produced from the Date pits oil was found to have a cetane number of 58.23, density 870 of kg m"−"3, cloud point of 4 °C, pour point of −1 °C, CFPP of −0.5 °C and kinematic viscosity of 3.97 mm"2 s"−"1 (40 °C). In general, Date pit oil appears to be a potential alternative feedstock for biodiesel production.

A systematic review on the composting of green waste: Feedstock quality and optimization strategies.

Science.gov (United States)

Reyes-Torres, M; Oviedo-Ocaña, E R; Dominguez, I; Komilis, D; Sánchez, A

2018-04-27

Green waste (GW) is an important fraction of municipal solid waste (MSW). The composting of lignocellulosic GW is challenging due to its low decomposition rate. Recently, an increasing number of studies that include strategies to optimize GW composting appeared in the literature. This literature review focuses on the physicochemical quality of GW and on the effect of strategies used to improve the process and product quality. A systematic search was carried out, using keywords, and 447 papers published between 2002 and 2018 were identified. After a screening process, 41 papers addressing feedstock quality and 32 papers on optimization strategies were selected to be reviewed and analyzed in detail. The GW composition is highly variable due to the diversity of the source materials, the type of vegetation, and climatic conditions. This variability limits a strict categorization of the GW physicochemical characteristics. However, this research established that the predominant features of GW are a C/N ratio higher than 25, a deficit in important nutrients, namely nitrogen (0.5-1.5% db), phosphorous (0.1-0.2% db) and potassium (0.4-0.8% db) and a high content of recalcitrant organic compounds (e.g. lignin). The promising strategies to improve composting of GW were: i) GW particle size reduction (e.g. shredding and separation of GW fractions); ii) addition of energy amendments (e.g. non-refined sugar, phosphate rock, food waste, volatile ashes), bulking materials (e.g. biocarbon, wood chips), or microbial inoculum (e.g. fungal consortia); and iii) variations in operating parameters (aeration, temperature, and two-phase composting). These alternatives have successfully led to the reduction of process length and have managed to transform recalcitrant substances to a high-quality end-product. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

African Journals Online (AJOL)

The cutting parameters were analyzed and optimized using Box Behnken procedure in the DESIGN EXPERT environment. The effect of process parameters with the output variable were predicted which indicates that the highest cutting speed has significant role in producing least surface roughness followed by feed and ...

Structural parameter optimization design for Halbach permanent maglev rail

International Nuclear Information System (INIS)

Guo, F.; Tang, Y.; Ren, L.; Li, J.

2010-01-01

Maglev rail is an important part of the magnetic levitation launch system. Reducing the manufacturing cost of magnetic levitation rail is the key problem for the development of magnetic levitation launch system. The Halbach permanent array has an advantage that the fundamental spatial field is cancelled on one side of the array while the field on the other side is enhanced. So this array used in the design of high temperature superconducting permanent maglev rail could improve the surface magnetic field and the levitation force. In order to make the best use of Nd-Fe-B (NdFeB) material and reduce the cost of maglev rail, the effect of the rail's structural parameters on levitation force and the utilization rate of NdFeB material are analyzed. The optimal ranges of these structural parameters are obtained. The mutual impact of these parameters is also discussed. The optimization method of these structure parameters is proposed at the end of this paper.

Structural parameter optimization design for Halbach permanent maglev rail

Energy Technology Data Exchange (ETDEWEB)

Guo, F., E-mail: guofang19830119@163.co [R and D Center of Applied Superconductivity, Huazhong University of Science and Technology, Wuhan 430074 (China); Tang, Y.; Ren, L.; Li, J. [R and D Center of Applied Superconductivity, Huazhong University of Science and Technology, Wuhan 430074 (China)

2010-11-01

Maglev rail is an important part of the magnetic levitation launch system. Reducing the manufacturing cost of magnetic levitation rail is the key problem for the development of magnetic levitation launch system. The Halbach permanent array has an advantage that the fundamental spatial field is cancelled on one side of the array while the field on the other side is enhanced. So this array used in the design of high temperature superconducting permanent maglev rail could improve the surface magnetic field and the levitation force. In order to make the best use of Nd-Fe-B (NdFeB) material and reduce the cost of maglev rail, the effect of the rail's structural parameters on levitation force and the utilization rate of NdFeB material are analyzed. The optimal ranges of these structural parameters are obtained. The mutual impact of these parameters is also discussed. The optimization method of these structure parameters is proposed at the end of this paper.

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.

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.

Sensitivity Analysis of Multi-objective Optimization for Solid Waste Management: A Case Study of Dar es Salaam, Tanzania

Directory of Open Access Journals (Sweden)

Halidi Lyeme

2017-11-01

Full Text Available In this study, a sensitivity analysis of a multi-objective optimization model for solid waste management (SWM for Dar es Salaam city in Tanzania is considered. Our objectives were to identify the most sensitive parameters and effect of other input data to the model output. Five scenarios were considered by varying their associated parameter values. The results showed that the decrease of total cost for the SWM system in all scenarios was observed compared to the baseline solution when the single landfill was considered. Furthermore, the analysis shows that the variable cost parameter for the processing facilities is very sensitivity in such a way that if you increase the variable cost then, there is a rapid increase of total cost for the SWM system and the vice versa is true. The relevant suggestions to the decision makers were also discussed.

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.

Setting of the Optimal Parameters of Melted Glass

Czech Academy of Sciences Publication Activity Database

Luptáková, Natália; Matejíčka, L.; Krečmer, N.

2015-01-01

Roč. 10, č. 1 (2015), s. 73-79 ISSN 1802-2308 Institutional support: RVO:68081723 Keywords : Striae * Glass * Glass melting * Regression * Optimal parameters Subject RIV: JH - Ceramics, Fire-Resistant Materials and Glass

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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

Optimal control of diesel engines with waste heat recovery systems

NARCIS (Netherlands)

Willems, F.P.T.; Donkers, M.C.F.; Kupper, F.; Waschl, H.; Kolmanovsky, I.; Steinbuch, M.; Del Re, L.

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 CO 2 - NO x trade-off by minimizing the operational costs associated with fuel and AdBlue

A Novel adaptative Discrete Cuckoo Search Algorithm for parameter optimization in computer vision

Directory of Open Access Journals (Sweden)

loubna benchikhi

2017-10-01

Full Text Available Computer vision applications require choosing operators and their parameters, in order to provide the best outcomes. Often, the users quarry on expert knowledge and must experiment many combinations to find manually the best one. As performance, time and accuracy are important, it is necessary to automate parameter optimization at least for crucial operators. In this paper, a novel approach based on an adaptive discrete cuckoo search algorithm (ADCS is proposed. It automates the process of algorithms’ setting and provides optimal parameters for vision applications. This work reconsiders a discretization problem to adapt the cuckoo search algorithm and presents the procedure of parameter optimization. Some experiments on real examples and comparisons to other metaheuristic-based approaches: particle swarm optimization (PSO, reinforcement learning (RL and ant colony optimization (ACO show the efficiency of this novel method.

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

Science.gov (United States)

Yu, Tao; Kang, Chao; Zhao, Pan

2018-01-01

The composite tape winding process, which utilizes a tape winding machine and prepreg tapes, provides a promising way to improve the quality of composite products. Nevertheless, the process parameters of composite tape winding have crucial effects on the tensile strength and void content, which are closely related to the performances of the winding products. In this article, two different object values of winding products, including mechanical performance (tensile strength) and a physical property (void content), were respectively calculated. Thereafter, the paper presents an integrated methodology by combining multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis to obtain the optimal intervals of the composite tape winding process. First, the global multi-parameter sensitivity analysis method was applied to investigate the sensitivity of each parameter in the tape winding processing. Then, the local single-parameter sensitivity analysis method was employed to calculate the sensitivity of a single parameter within the corresponding range. Finally, the stability and instability ranges of each parameter were distinguished. Meanwhile, the authors optimized the process parameter ranges and provided comprehensive optimized intervals of the winding parameters. The verification test validated that the optimized intervals of the process parameters were reliable and stable for winding products manufacturing. PMID:29385048

Numerical optimization for separation power of gas centrifuge

International Nuclear Information System (INIS)

Jiang Dongjun; Zeng Shi; Liu Bing

2012-01-01

In order to obtain higher separation power of the gas centrifuge, the code was developed to solve the flow-field of the counter-current to acquire the separation power, which was integrated with the iSight software, so a numerical optimization model for separation power was presented, in which the driver conditions and the geometry parameters of the waste baffle were optimized to get the maximum separation power using the sequential quadratic programming arithmetic, and the 12% higher results was acquired, which shows the feasibility of this method. The results also note that the separation power of gas centrifuge is sensitive to the driver conditions and the structure parameters of the waste baffle, so it is necessary to perform the optimization calculation for the certain gas centrifuge model. (authors)

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.

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

Energy Technology Data Exchange (ETDEWEB)

Rengers, Francis; Lunacek, Monte; Tucker, Gregory

2016-06-01

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

Parameter assessment for virtual Stackelberg game in aerodynamic shape optimization

Science.gov (United States)

Wang, Jing; Xie, Fangfang; Zheng, Yao; Zhang, Jifa

2018-05-01

In this paper, parametric studies of virtual Stackelberg game (VSG) are conducted to assess the impact of critical parameters on aerodynamic shape optimization, including design cycle, split of design variables and role assignment. Typical numerical cases, including the inverse design and drag reduction design of airfoil, have been carried out. The numerical results confirm the effectiveness and efficiency of VSG. Furthermore, the most significant parameters are identified, e.g. the increase of design cycle can improve the optimization results but it will also add computational burden. These studies will maximize the productivity of the effort in aerodynamic optimization for more complicated engineering problems, such as the multi-element airfoil and wing-body configurations.

Parameter estimation for chaotic systems with a Drift Particle Swarm Optimization method

International Nuclear Information System (INIS)

Sun Jun; Zhao Ji; Wu Xiaojun; Fang Wei; Cai Yujie; Xu Wenbo

2010-01-01

Inspired by the motion of electrons in metal conductors in an electric field, we propose a variant of Particle Swarm Optimization (PSO), called Drift Particle Swarm Optimization (DPSO) algorithm, and apply it in estimating the unknown parameters of chaotic dynamic systems. The principle and procedure of DPSO are presented, and the algorithm is used to identify Lorenz system and Chen system. The experiment results show that for the given parameter configurations, DPSO can identify the parameters of the systems accurately and effectively, and it may be a promising tool for chaotic system identification as well as other numerical optimization problems in physics.

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...

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.

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.

Intelligent Mechatronics Systems for Transport Climate Parameters Optimization Using Fuzzy Logic Control

OpenAIRE

Beinarts, I; Ļevčenkovs, A; Kuņicina, N

2007-01-01

In article interest is concentrated on the climate parameters optimization in passengers’ salon of public electric transportation vehicles. The article presents mathematical problem for using intelligent agents in mechatronics problems for climate parameters optimal control. Idea is to use fuzzy logic and intelligent algorithms to create coordination mechanism for climate parameters control to save electrical energy, and it increases the level of comfort for passengers. A special interest for...

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

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

International Nuclear Information System (INIS)

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

2009-01-01

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

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

International Nuclear Information System (INIS)

Gao, Hao

2016-01-01

For the treatment planning during intensity modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT), beam fluence maps can be first optimized via fluence map optimization (FMO) under the given dose prescriptions and constraints to conformally deliver the radiation dose to the targets while sparing the organs-at-risk, and then segmented into deliverable MLC apertures via leaf or arc sequencing algorithms. This work is to develop an efficient algorithm for FMO based on alternating direction method of multipliers (ADMM). Here we consider FMO with the least-square cost function and non-negative fluence constraints, and its solution algorithm is based on ADMM, which is efficient and simple-to-implement. In addition, an empirical method for optimizing the ADMM parameter is developed to improve the robustness of the ADMM algorithm. The ADMM based FMO solver was benchmarked with the quadratic programming method based on the interior-point (IP) method using the CORT dataset. The comparison results suggested the ADMM solver had a similar plan quality with slightly smaller total objective function value than IP. A simple-to-implement ADMM based FMO solver with empirical parameter optimization is proposed for IMRT or VMAT. (paper)

Fuel optimization in a multi chamber incinerator by the moisture control of oily sludge and medical wastes

International Nuclear Information System (INIS)

Haider, I.; Hussain, S.; Khan, S.; Mehran, T.

2011-01-01

Experiments have been performed to study the effects of %age moisture content on fuel optimization during the waste feed combustion of oily sludge, medical waste and mix blend waste in a 50 kg/hr multi chamber incinerator installed at NCPC- ARL RWP. Intention is to find out the optimum and in compliance with NEQs incinerator performance at various moisture contents in the different waste feeds. Optimum performances of the incinerator, so that optimum operating moisture conditions, which has been used for multi purpose waste, feeds, may be defined. Three waste feeds of 10 kg batch size were used for the experimentation namely; Oily Sludge, Medical waste and Mix blend waste (oily sludge and medical), with the primary chamber preheating temperature 655 deg. C for 15 mins. interval monitoring. The secondary chamber temperature was set to 850 deg. C. By the data obtained it is apparent that rising the waste moisture content tend to increase fuel consumption specifically in case of medical waste and hence lowering the overall combustion efficiency. In the emissions the CO/sub 2/ concentration is showing the incineration efficiency. Higher efficiency of the system could have been achieved by increasing the CO/sub 2/ in the gases leaving the incinerator, lower fuel usage per kg waste feed and maintain proper operating conditions. Fuel consumption for the oily sludge with 10% moisture content, was found to be least as compared with the same %age of medical waste and mix blend waste. However environmental compliance of the operation is shown by the flue gas analysis. The results shows that using mix blend(oily sludge and medical) waste having 12-13% moisture content would be suitable for incineration in multi-chamber incinerator .Other makes it possible to determine the optimum incinerator temperature control settings and operating conditions, as well as to assure continuous, efficient, environmentally satisfactory operation. The optimum fuel consumption for 10 kg each waste

Optimal operation planning of radioactive waste processing system by fuzzy theory

International Nuclear Information System (INIS)

Yang, Jin Yeong; Lee, Kun Jai

2000-01-01

This study is concerned with the applications of linear goal programming and fuzzy theory to the analysis of management and operational problems in the radioactive processing system (RWPS). The developed model is validated and verified using actual data obtained from the RWPS at Kyoto University in Japan. The solution by goal programming and fuzzy theory would show the optimal operation point which is to maximize the total treatable radioactive waste volume and minimize the released radioactivity of liquid waste even under the restricted resources. (orig.)

Parameter values for the long-term nuclear waste management food chain model LIMCAL

International Nuclear Information System (INIS)

Zach, Reto.

1982-09-01

Eighteen parameters of LIMCAL, a comprehensive food chain model for predicting ICRP 26 50-year committed effective dose equivalents to man due to long-term nuclear waste management are reviewed. The parameters are: soil bulk density, plowlayer depth, soil surface layer depth, resusupension factor, atmospheric dust load, deposition velocity, plant interception fraction, plant environmental half-time, translocation factor, time of above-ground exposure, plant yield, holdup time, animals' feed consumption rate, animals' water consumption rate, man's water consumption rate, food type calorie conversion factors, man's total caloric intake rate and food type calorie fractions. LIMCAL has both traditional and unique parameters. The former occur in most of the currently used assessment models for nuclear installations, whereas the latter do not. For each of the parameters of LIMCAL, a suitable generic value for long-term nuclear waste management was determined. Thus, the general literature and the values currently used or recommended by various agencies were reviewed

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

International Nuclear Information System (INIS)

Hossain, Md. Sohrab; Nik Ab Rahman, Nik Norulaini; Balakrishnan, Venugopal; Alkarkhi, Abbas F.M.; Ahmad Rajion, Zainul; Ab Kadir, Mohd Omar

2015-01-01

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 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 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 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 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

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.

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

Science.gov (United States)

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

2018-03-01

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

Optimization of plasma flow parameters of the magnetoplasma compressor

International Nuclear Information System (INIS)

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

2007-01-01

Optimization of the working conditions of the magnetoplasma compressor (MPC) has been performed through analysing discharge and compression plasma flow parameters in hydrogen, nitrogen and argon at different pressures. Energy conversion rate, volt-ampere curve exponent and plasma flow velocities have been studied to optimize the efficiency of energy transfer from the supply source to the plasma. It has been found that the most effective energy transfer from the supply to the plasma is in hydrogen as a working gas at 1000 Pa pressure. It was found that the accelerating regime exists for hydrogen up to 3000 Pa pressures, in nitrogen up to 2000 Pa and in argon up to 1000 Pa pressure. At higher pressures MPC in all the gases works in the decelerating regime. At pressures lower than 200 Pa, high cathode erosion is observed. MPC plasma flow parameter optimization is very important because this plasma accelerating system may be of special interest for solid surface modification and other technology applications

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

Parameter optimization method for longitudinal vibration absorber of ship shaft system

Directory of Open Access Journals (Sweden)

LIU Jinlin

2017-05-01

Full Text Available The longitudinal vibration of the ship shaft system is the one of the most important factors of hull stern vibration, and it can be effectively minimized by installing a longitudinal vibration absorber. In this way, the vibration and noise of ships can be brought under control. However, the parameters of longitudinal vibration absorbers have a great influence on the vibration characteristics of the shaft system. As such, a certain shafting testing platform was studied as the object on which a finite model was built, and the relationship between longitudinal stiffness and longitudinal vibration in the shaft system was analyzed in a straight alignment state. Furthermore, a longitudinal damping model of the shaft system was built in which the parameters of the vibration absorber were non-dimensionalized, the weight of the vibration absorber was set as a constant, and an optimizing algorithm was used to calculate the optimized stiffness and damping coefficient of the vibration absorber. Finally, the longitudinal vibration frequency response of the shafting testing platform before and after optimizing the parameters of the longitudinal vibration absorber were compared, and the results indicated that the longitudinal vibration of the shafting testing platform was decreased effectively, which suggests that it could provide a theoretical foundation for the parameter optimization of longitudinal vibration absorbers.

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.

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.

Process development for treatment of fluoride containing wastes

Energy Technology Data Exchange (ETDEWEB)

Singh, Mahesh; Kanvinde, V Y [Chemical Engineering Division, Bhabha Atomic Research Centre, Mumbai (India)

1994-06-01

Many chemical and metallurgical industries generate liquid wastes containing high values of fluorides in association of nitrates and other metals. Due to harmful effects of fluorides these type of wastes can not be disposed off in the environment without proper treatment. Bench-scale laboratory experiments were conducted to develop a process scheme to fix the fluorides as non-leachable solid waste and fluoride free treated liquid waste for their disposal. To optimize the important parameters, simulated synthetic and actual wastes were used. For this study, three waste streams were collected from Nuclear Fuel Complex, Hyderabad. (author). 6 tabs., 1 fig.

Steam generators lay-up optimization and derived wastes reduction

International Nuclear Information System (INIS)

Rabeau, A.M.; Viricel, L.; Foct, F.; Lemaire, P.; Moreaux, D.

2002-01-01

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 μg/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

Parameter Optimization for Quantitative Signal-Concentration Mapping Using Spoiled Gradient Echo MRI

Directory of Open Access Journals (Sweden)

Gasser Hathout

2012-01-01

Full Text Available Rationale and Objectives. Accurate signal to tracer concentration maps are critical to quantitative MRI. The purpose of this study was to evaluate and optimize spoiled gradient echo (SPGR MR sequences for the use of gadolinium (Gd-DTPA as a kinetic tracer. Methods. Water-gadolinium phantoms were constructed for a physiologic range of gadolinium concentrations. Observed and calculated SPGR signal to concentration curves were generated. Using a percentage error determination, optimal pulse parameters for signal to concentration mapping were obtained. Results. The accuracy of the SPGR equation is a function of the chosen MR pulse parameters, particularly the time to repetition (TR and the flip angle (FA. At all experimental values of TR, increasing FA decreases the ratio between observed and calculated signals. Conversely, for a constant FA, increasing TR increases this ratio. Using optimized pulse parameter sets, it is possible to achieve excellent accuracy (approximately 5% over a physiologic range of concentration tracer concentrations. Conclusion. Optimal pulse parameter sets exist and their use is essential for deriving accurate signal to concentration curves in quantitative MRI.

Establishment of cementation parameters of dried waste from evaporation coming from NPP operation

International Nuclear Information System (INIS)

Faria, Érica R.; Tello, Clédola C.O.; Costa, Bruna S.

2017-01-01

The radioactive wastes generated in Brazil are treated and sent to initial and intermediate storages. The 'Project RBMN' proposes the implantation of the Brazilian repository to receive and permanently dispose the low and intermediate level radioactive wastes. The CNEN NN 6.09 standard - Acceptance Criteria for Disposal of Low and Intermediate Radioactive Wastes (LIRW) - establishes the fundamental requirements to accept the wastes packages in the repository. The evaporator concentrate is one of liquid wastes generated in a Nuclear Power Plant (NPP) operation and usually it is cemented directly inside the packing. The objective of this research is to increase the amount of the incorporated waste in each package, using the drying process before the cementation, consequently reducing the volume of the waste to be disposed. Drying and cementation parameters were established in order to scale-up the process aiming at waste products that comply with the requirements of CNEN standard. The cementation of the resulting dry wastes was carried out with different formulations, varying the amount of cement, dry waste and water. These tests were analyzed in order to select the best products, with higher waste incorporation than current process and its complying the requirements of the standard CNEN NN 6.09. (author)

Establishment of cementation parameters of dried waste from evaporation coming from NPP operation

Energy Technology Data Exchange (ETDEWEB)

Faria, Érica R.; Tello, Clédola C.O., E-mail: erica.engqui@gmail.com [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte/MG (Brazil); Costa, Bruna S., E-mail: brusilveirac@gmail.com [Universidade Federal de Minas Gerais, Belo Horizonte, MG (Brazil)

2017-07-01

The radioactive wastes generated in Brazil are treated and sent to initial and intermediate storages. The 'Project RBMN' proposes the implantation of the Brazilian repository to receive and permanently dispose the low and intermediate level radioactive wastes. The CNEN NN 6.09 standard - Acceptance Criteria for Disposal of Low and Intermediate Radioactive Wastes (LIRW) - establishes the fundamental requirements to accept the wastes packages in the repository. The evaporator concentrate is one of liquid wastes generated in a Nuclear Power Plant (NPP) operation and usually it is cemented directly inside the packing. The objective of this research is to increase the amount of the incorporated waste in each package, using the drying process before the cementation, consequently reducing the volume of the waste to be disposed. Drying and cementation parameters were established in order to scale-up the process aiming at waste products that comply with the requirements of CNEN standard. The cementation of the resulting dry wastes was carried out with different formulations, varying the amount of cement, dry waste and water. These tests were analyzed in order to select the best products, with higher waste incorporation than current process and its complying the requirements of the standard CNEN NN 6.09. (author)

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.

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.

Systematic optimization of subcritical and transcritical organic Rankine cycles (ORCs) constrained by technical parameters in multiple applications

International Nuclear Information System (INIS)

Maraver, Daniel; Royo, Javier; Lemort, Vincent; Quoilin, Sylvain

2014-01-01

Highlights: • ORC optimization for different target applications. • Model developed to allow computation in subcritical and transcritical operation. • Regenerative and non-regenerative cycles evaluated through second law efficiency. • Common working fluids: R134a, R245fa, Solkatherm, n-Pentane, MDM, Toluene. • Thermodynamic and technological approaches lead to optimal design guidelines. - Abstract: The present work is focused on the thermodynamic optimization of organic Rankine cycles (ORCs) for power generation and CHP from different average heat source profiles (waste heat recovery, thermal oil for cogeneration and geothermal). The general goal is to provide optimization guidelines for a wide range of operating conditions, for subcritical and transcritical, regenerative and non-regenerative cycles. A parameter assessment of the main equipment in the cycle (expander, heat exchangers and feed pump) was also carried out. An optimization model of the ORC (available as an electronic annex) is proposed to predict the best cycle performance (subcritical or transcritical), in terms of its exergy efficiency, with different working fluids. The working fluids considered are those most commonly used in commercial ORC units (R134a, R245fa, Solkatherm, n-Pentane, Octamethyltrisiloxane and Toluene). The optimal working fluid and operating conditions from a purely thermodynamic approach are limited by the technological constraints of the expander, the heat exchangers and the feed pump. Hence, a complementary assessment of both approaches is more adequate to obtain some preliminary design guidelines for ORC units

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

Science.gov (United States)

Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

2018-03-01

A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models.

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.

Parameters, test criteria and fault assessment in random sampling of waste barrels from non-qualified processes

International Nuclear Information System (INIS)

Martens, B.R.

1989-01-01

In the context of random sampling tests, parameters are checked on the waste barrels and criteria are given on which these tests are based. Also, it is shown how faulty data on the properties of the waste or faulty waste barrels should be treated. To decide the extent of testing, the properties of the waste relevant to final storage are determined based on the conditioning process used. (DG) [de

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.

Optimal Parameter Selection of Power System Stabilizer using Genetic Algorithm

Energy Technology Data Exchange (ETDEWEB)

Chung, Hyeng Hwan; Chung, Dong Il; Chung, Mun Kyu [Dong-AUniversity (Korea); Wang, Yong Peel [Canterbury Univeristy (New Zealand)

1999-06-01

In this paper, it is suggested that the selection method of optimal parameter of power system stabilizer (PSS) with robustness in low frequency oscillation for power system using real variable elitism genetic algorithm (RVEGA). The optimal parameters were selected in the case of power system stabilizer with one lead compensator, and two lead compensator. Also, the frequency responses characteristics of PSS, the system eigenvalues criterion and the dynamic characteristics were considered in the normal load and the heavy load, which proved usefulness of RVEGA compare with Yu's compensator design theory. (author). 20 refs., 15 figs., 8 tabs.

Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology

Directory of Open Access Journals (Sweden)

Rupert Faltermeier

2015-01-01

Full Text Available Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP and intracranial pressure (ICP. Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP, with the outcome of the patients represented by the Glasgow Outcome Scale (GOS. For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.

Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology.

Science.gov (United States)

Faltermeier, Rupert; Proescholdt, Martin A; Bele, Sylvia; Brawanski, Alexander

2015-01-01

Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.

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.

Sensitive parameters' optimization of the permanent magnet supporting mechanism

Energy Technology Data Exchange (ETDEWEB)

Liu, Yongguang; Gao, Xiaohui; Wang, Yixuan; Yang, Xiaowei [Beihang University, Beijing (China)

2014-07-15

The fast development of the ultra-high speed vertical rotor promotes the study and exploration for the supporting mechanism. It has become the focus of research that how to improve the speed and overcome the vibration when the rotors pass through the low-order critical frequencies. This paper introduces a kind of permanent magnet (PM) supporting mechanism and describes an optimization method of its sensitive parameters, which can make the vertical rotor system reach 80000 r/min smoothly. Firstly we find the sensitive parameters through analyzing the rotor's features in the process of achieving high-speed, then, study these sensitive parameters and summarize the regularities with the method of combining the experiment and the finite element method (FEM), at last, achieve the optimization method of these parameters. That will not only get a stable effect of raising speed and shorten the debugging time greatly, but also promote the extensive application of the PM supporting mechanism in the ultra-high speed vertical rotors.

Optimization of fly ash incorporation into cow dung-waste paper mixtures for enhanced vermidegradation and nutrient release.

Science.gov (United States)

Mupambwa, Hupenyu A; Mnkeni, Pearson N S

2015-05-01

This study was conducted to establish an appropriate mixture ratio of fly ash (F) to optimized cow dung-waste paper mixtures (CP) to develop a high-quality vermicompost using earthworms (). Fly ash was mixed with cow dung-waste paper mixtures at ratios of (F:CP) 1:1, 1:2, 1:3, 2:1, and 3:1 or CP alone and composted for 14 wk. Olsen P, inorganic N (NO, NO, and NH), C:N ratio, ash content, microbial biomass C, and humification parameters were measured together with scanning electron micrograph images to determine compost maturity. Based on C:N ratio, the extent of vermidegradation of the waste mixtures followed the decreasing order (F:CP) of 1:3 > 1:2 > 1:1 > CP alone > 2:1 > 3:1. Similarly, Olsen P was significantly higher ( percentage increase in extractable P was in the order CP alone > 1:2 > 1:3 > 1:1 > 2:1 > 3:1, with earthworm addition almost doubling P release across the 1:1, 1:2, and CP alone treatments. Fly ash incorporation enhanced conversion of organic N to the plant-available inorganic forms, with the 1:3 treatment resulting in the highest conversion. Scanning electron micrograph images confirmed the extent of vermidegradation reflected by the various humification parameters determined. Fly ash incorporation at the 1:2 ratio proved to be the most appropriate because it allows processing of more fly ash while giving a vermicompost with desirable maturity and nutritional properties. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Challenges when performing economic optimization of waste treatment: A review

DEFF Research Database (Denmark)

Juul, Nina; Münster, Marie; Ravn, H.

2013-01-01

-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...... 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...

Parameters for characterizing sites for disposal of low-level radioactive waste

International Nuclear Information System (INIS)

Lutton, R.J.; Malone, P.G.; Meade, R.B.; Patrick, D.M.

1982-05-01

Sixty-seven site parameters and parameter groups are identified as important characteristics of sites for disposal of low-level radioactive waste and require detailed evaluation. Several of the most important parameters are needed for hydrological analysis while others are needed for facility design, construction, and operation. Still others are needed for baseline and detection stages of monitoring. It is recommended that all parameters be evaluated by technically qualified personnel. Appropriate tests and documentation methods are discussed in a second report, which will follow. However, site-specific testing or elaborate field measurement will not always be necessary, i.e., where indicated to be unnecessary on a technical basis. Much of this report, Appendices A through G, is directed to explaining the importances of parameters and to establishing site-specific limitations

A choice of the parameters of NPP steam generators on the basis of vector optimization

International Nuclear Information System (INIS)

Lemeshev, V.U.; Metreveli, D.G.

1981-01-01

The optimization problem of the parameters of the designed systems is considered as the problem of multicriterion optimization. It is proposed to choose non-dominant, optimal according to Pareto, parameters. An algorithm is built on the basis of the required and sufficient non-dominant conditions to find non-dominant solutions. This algorithm has been employed to solve the problem on a choice of optimal parameters for the counterflow shell-tube steam generator of NPP of BRGD type [ru

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.

CHALLENGES AND OPPORTUNITIES--INTEGRATED LIFE-CYCLE OPTIMIZATION INITIATIVES FOR THE HANFORD RIVER PROTECTION PROJECT--WASTE TREATMENT PLANT

International Nuclear Information System (INIS)

Auclair, K. D.

2002-01-01

This paper describes the ongoing integrated life-cycle optimization efforts to achieve both design flexibility and design stability for activities associated with the Waste Treatment Plant at Hanford. Design flexibility is required to support the Department of Energy Office of River Protection Balance of Mission objectives, and design stability to meet the Waste Treatment Plant construction and commissioning requirements in order to produce first glass in 2007. The Waste Treatment Plant is a large complex project that is driven by both technology and contractual requirements. It is also part of a larger overall mission, as a component of the River Protection Project, which is driven by programmatic requirements and regulatory, legal, and fiscal constraints. These issues are further complicated by the fact that both of the major contractors involved have a different contract type with DOE, and neither has a contract with the other. This combination of technical and programmatic drivers, constraints, and requirements will continue to provide challenges and opportunities for improvement and optimization. The Bechtel National, Inc. team is under contract to engineer, procure, construct, commission and test the Waste Treatment Plant on or ahead of schedule, at or under cost, and with a throughput capacity equal to or better than specified. The Department of Energy is tasked with the long term mission of waste retrieval, treatment, and disposal. While each mission is a compliment and inextricably linked to one another, they are also at opposite ends of the spectrum, in terms of expectations of one another. These mission requirements, that are seemingly in opposition to one another, pose the single largest challenge and opportunity for optimization: one of balance. While it is recognized that design maturation and optimization are the normal responsibility of any engineering firm responsible for any given project, the aspects of integrating requirements and the management

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

International Nuclear Information System (INIS)

Jayalal, M.L.; Kumar, L. Satish; Jehadeesan, R.; Rajeswari, S.; Satya Murty, S.A.V.; Balasubramaniyan, V.; Chetal, S.C.

2011-01-01

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

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.

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.

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.

Life-cycle cost as basis to optimize waste collection in space and time: A methodology for obtaining a detailed cost breakdown structure.

Science.gov (United States)

Sousa, Vitor; Dias-Ferreira, Celia; Vaz, João M; Meireles, Inês

2018-05-01

Extensive research has been carried out on waste collection costs mainly to differentiate costs of distinct waste streams and spatial optimization of waste collection services (e.g. routes, number, and location of waste facilities). However, waste collection managers also face the challenge of optimizing assets in time, for instance deciding when to replace and how to maintain, or which technological solution to adopt. These issues require a more detailed knowledge about the waste collection services' cost breakdown structure. The present research adjusts the methodology for buildings' life-cycle cost (LCC) analysis, detailed in the ISO 15686-5:2008, to the waste collection assets. The proposed methodology is then applied to the waste collection assets owned and operated by a real municipality in Portugal (Cascais Ambiente - EMAC). The goal is to highlight the potential of the LCC tool in providing a baseline for time optimization of the waste collection service and assets, namely assisting on decisions regarding equipment operation and replacement.

Optimalization studies concerning volume reduction and conditioning of radioactive waste in view of storage and disposal (geological disposal into clay)

International Nuclear Information System (INIS)

Dejonghe, P.; Van De Voorde, N.; Bonne, A.

1984-01-01

Volume reduction of low-level and medium-level wastes, and simultaneous optimization of the quality of the conditioned end-product is a major challenge in the management of radioactive wastes. Comments will be given on recent achievements in treatment of non-high-level liquid and solid wastes from power reactors and low-level plutonium contaminated wastes. The latter results can contribute to an overall optimization of a radioactive waste management scheme, including the final disposal of the conditioned materials. Some detailed results will be given concerning volume reduction, decontamination factors, degree of immobilization of the contained radioelements, and cost considerations

Life Cycle Assessment and Optimization-Based Decision Analysis of Construction Waste Recycling for a LEED-Certified University Building

Directory of Open Access Journals (Sweden)

Murat Kucukvar

2016-01-01

Full Text Available The current waste management literature lacks a comprehensive LCA of the recycling of construction materials that considers both process and supply chain-related impacts as a whole. Furthermore, an optimization-based decision support framework has not been also addressed in any work, which provides a quantifiable understanding about the potential savings and implications associated with recycling of construction materials from a life cycle perspective. The aim of this research is to present a multi-criteria optimization model, which is developed to propose economically-sound and environmentally-benign construction waste management strategies for a LEED-certified university building. First, an economic input-output-based hybrid life cycle assessment model is built to quantify the total environmental impacts of various waste management options: recycling, conventional landfilling and incineration. After quantifying the net environmental pressures associated with these waste treatment alternatives, a compromise programming model is utilized to determine the optimal recycling strategy considering environmental and economic impacts, simultaneously. The analysis results show that recycling of ferrous and non-ferrous metals significantly contributed to reductions in the total carbon footprint of waste management. On the other hand, recycling of asphalt and concrete increased the overall carbon footprint due to high fuel consumption and emissions during the crushing process. Based on the multi-criteria optimization results, 100% recycling of ferrous and non-ferrous metals, cardboard, plastic and glass is suggested to maximize the environmental and economic savings, simultaneously. We believe that the results of this research will facilitate better decision making in treating construction and debris waste for LEED-certified green buildings by combining the results of environmental LCA with multi-objective optimization modeling.

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.

Optimization of physico-chemical and nutritional parameters for ...

African Journals Online (AJOL)

Optimization of physico-chemical and nutritional parameters for pullulan production by a mutant of thermotolerant Aureobasidium pullulans, in fed batch ... minutes, having killing rate of 70% level, produced 6 g l-1 higher pullulan as compared to the wild type without loosing thermotolerant and non-melanin producing ability.

Optimization of process parameters for synthesis of silica–Ni ...

Indian Academy of Sciences (India)

Optimization of process parameters for synthesis of silica–Ni nanocomposite by design of experiment ... Sol–gel; Ni; design of experiments; nanocomposites. ... Kolkata 700 032, India; Rustech Products Pvt. Ltd., Kolkata 700 045, India ...

On the effect of response transformations in sequential parameter optimization.

Science.gov (United States)

Wagner, Tobias; Wessing, Simon

2012-01-01

Parameter tuning of evolutionary algorithms (EAs) is attracting more and more interest. In particular, the sequential parameter optimization (SPO) framework for the model-assisted tuning of stochastic optimizers has resulted in established parameter tuning algorithms. In this paper, we enhance the SPO framework by introducing transformation steps before the response aggregation and before the actual modeling. Based on design-of-experiments techniques, we empirically analyze the effect of integrating different transformations. We show that in particular, a rank transformation of the responses provides significant improvements. A deeper analysis of the resulting models and additional experiments with adaptive procedures indicates that the rank and the Box-Cox transformation are able to improve the properties of the resultant distributions with respect to symmetry and normality of the residuals. Moreover, model-based effect plots document a higher discriminatory power obtained by the rank transformation.

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

Science.gov (United States)

Wang, Qianqian; Zhao, Jing; Gong, Yong; Hao, Qun; Peng, Zhong

2017-11-20

A hybrid artificial bee colony (ABC) algorithm inspired by the best-so-far solution and bacterial chemotaxis was introduced to optimize the parameters of the five-parameter bidirectional reflectance distribution function (BRDF) model. To verify the performance of the hybrid ABC algorithm, we measured BRDF of three kinds of samples and simulated the undetermined parameters of the five-parameter BRDF model using the hybrid ABC algorithm and the genetic algorithm, respectively. The experimental results demonstrate that the hybrid ABC algorithm outperforms the genetic algorithm in convergence speed, accuracy, and time efficiency under the same conditions.

Construction of Biodigesters to Optimize the Production of Biogas from Anaerobic Co-Digestion of Food Waste and Sewage

Directory of Open Access Journals (Sweden)

Claudinei de Souza Guimarães

2018-04-01

Full Text Available The objective of this study was to build and develop anaerobic biodigesters for optimization of biogas production using food waste (FW and sewage (S co-digestion from a wastewater treatment plant (WWTP. The biodigesters operated with different mixtures and in mesophilic phase (37 °C. During the 60 days of experiments, all control and monitoring parameters of the biodigesters necessary for biogas production were tested and evaluated. The biodigester containing FW, S and anaerobic sludge presented the biggest reduction of organic matter, expressed with removal of 88.3% TVS (total volatile solid and 84.7% COD (chemical oxygen demand the biggest biogas production (63 L and the highest methane percentage (95%. Specific methane production was 0.299 LCH4/gVS and removed. The use of biodigesters to produce biogas through anaerobic digestion may play an important role in local economies due to the opportunity to produce a renewable fuel from organic waste and also as an alternative to waste treatment. Finally, the embedded control and automation system was simple, effective, and robust, and the supervisory software was efficient in all aspects defined at its conception.

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.)

Optimization and validation of a chemical process for uranium, mercury and cesium leaching from cemented radioactive wastes

Energy Technology Data Exchange (ETDEWEB)

Reynier, N.; Lastra, R.; Laviolette, C.; Bouzoubaa, N., E-mail: nicolas.reynier@canada.ca [Natural Resources Canada, CanmetMINING, Ottawa, Ontario (Canada); Chapman, M. [Canadian Nuclear Laboratories, Chalk River, Ontario (Canada)

2015-12-15

Canadian Nuclear Laboratories (CNL) is developing a treatment and long-term management strategy for a legacy cemented radioactive waste that contains uranium, mercury, and fission products. Extracting the uranium would be advantageous for decreasing the waste classification and reducing the cost of long-term management. The chemical leachability of 3 key elements (U, Hg, and Cs) from a surrogate cemented waste (SCW) was studied with several lixiviants. The results showed that the most promising approach to leach and recover U, Hg, and Cs is the direct leaching of the SCW with H{sub 2}SO{sub 4} in strong saline media. Operating parameters such as particle size, temperature, pulp density, leaching time, acid and salt concentrations, number of leaching/washing steps, etc. were optimized to improve key elements solubilization. Sulfuric leaching in saline media of a SCW (U5) containing 1182 ppm of U, 1598 ppm of Hg, and 7.9 ppm of Cs in the optimized conditions allows key elements solubilisation of 98.5 ± 0.4%, 96.6 ± 0.1%, and 93.8 ± 1.1% of U, Hg, and Cs, respectively. This solubilization process was then applied in triplicate to 7 other SCWs prepared with different cements, liquid ratios, and at different aging times and temperatures. Concentrated sulfuric acid is added to the slurry until the pH is about 2, which causes the complete degradation of cement and the formation of CaSO{sub 4}. Sulfuric acid is particularly useful because it produces a leachate that is amenable to conventional ion exchange technology for the separation and recovery of uranium. (author)

Physical property parameter set for modeling ICPP aqueous wastes with ASPEN electrolyte NRTL model

International Nuclear Information System (INIS)

Schindler, R.E.

1996-09-01

The aqueous waste evaporators at the Idaho Chemical Processing Plant (ICPP) are being modeled using ASPEN software. The ASPEN software calculates chemical and vapor-liquid equilibria with activity coefficients calculated using the electrolyte Non-Random Two Liquid (NRTL) model for local excess Gibbs free energies of interactions between ions and molecules in solution. The use of the electrolyte NRTL model requires the determination of empirical parameters for the excess Gibbs free energies of the interactions between species in solution. This report covers the development of a set parameters, from literature data, for the use of the electrolyte NRTL model with the major solutes in the ICPP aqueous wastes

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.

AI-guided parameter optimization in inverse treatment planning

International Nuclear Information System (INIS)

Yan Hui; Yin Fangfang; Guan Huaiqun; Kim, Jae Ho

2003-01-01

An artificial intelligence (AI)-guided inverse planning system was developed to optimize the combination of parameters in the objective function for intensity-modulated radiation therapy (IMRT). In this system, the empirical knowledge of inverse planning was formulated with fuzzy if-then rules, which then guide the parameter modification based on the on-line calculated dose. Three kinds of parameters (weighting factor, dose specification, and dose prescription) were automatically modified using the fuzzy inference system (FIS). The performance of the AI-guided inverse planning system (AIGIPS) was examined using the simulated and clinical examples. Preliminary results indicate that the expected dose distribution was automatically achieved using the AI-guided inverse planning system, with the complicated compromising between different parameters accomplished by the fuzzy inference technique. The AIGIPS provides a highly promising method to replace the current trial-and-error approach

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

Science.gov (United States)

Sharma, G. V. S. S.; Rao, R. Umamaheswara; Rao, P. Srinivasa

2017-06-01

High-density polyethylene (HDPE) pipes find versatile applicability for transportation of water, sewage and slurry from one place to another. Hence, these pipes undergo tremendous pressure by the fluid carried. The present work entails the optimization of the withstanding pressure of the HDPE pipes using Taguchi technique. The traditional heuristic methodology stresses on a trial and error approach and relies heavily upon the accumulated experience of the process engineers for determining the optimal process control parameters. This results in setting up of less-than-optimal values. Hence, there arouse a necessity to determine optimal process control parameters for the pipe extrusion process, which can ensure robust pipe quality and process reliability. In the proposed optimization strategy, the design of experiments (DoE) are conducted wherein different control parameter combinations are analyzed by considering multiple setting levels of each control parameter. The concept of signal-to-noise ratio ( S/ N ratio) is applied and ultimately optimum values of process control parameters are obtained as: pushing zone temperature of 166 °C, Dimmer speed at 08 rpm, and Die head temperature to be 192 °C. Confirmation experimental run is also conducted to verify the analysis and research result and values proved to be in synchronization with the main experimental findings and the withstanding pressure showed a significant improvement from 0.60 to 1.004 Mpa.

Multi-Objective Thermo-Economic Optimization Strategy for ORCs Applied to Subcritical and Transcritical Cycles for Waste Heat Recovery

Directory of Open Access Journals (Sweden)

Steven Lecompte

2015-04-01

Full Text Available Organic Rankine cycles (ORCs are an established technology to convert waste heat to electricity. Although several commercial implementations exist, there is still considerable potential for thermo-economic optimization. As such, a novel framework for designing optimized ORC systems is proposed based on a multi-objective optimization scheme in combination with financial appraisal in a post-processing step. The suggested methodology provides the flexibility to quickly assess several economic scenarios and this without the need of knowing the complex design procedure. This novel way of optimizing and interpreting results is applied to a waste heat recovery case. Both the transcritical ORC and subcritical ORC are investigated and compared using the suggested optimization strategy.

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.

Optimization of nonlinear wave function parameters

International Nuclear Information System (INIS)

Shepard, R.; Minkoff, M.; Chemistry

2006-01-01

An energy-based optimization method is presented for our recently developed nonlinear wave function expansion form for electronic wave functions. This expansion form is based on spin eigenfunctions, using the graphical unitary group approach (GUGA). The wave function is expanded in a basis of product functions, allowing application to closed-shell and open-shell systems and to ground and excited electronic states. Each product basis function is itself a multiconfigurational function that depends on a relatively small number of nonlinear parameters called arc factors. The energy-based optimization is formulated in terms of analytic arc factor gradients and orbital-level Hamiltonian matrices that correspond to a specific kind of uncontraction of each of the product basis functions. These orbital-level Hamiltonian matrices give an intuitive representation of the energy in terms of disjoint subsets of the arc factors, they provide for an efficient computation of gradients of the energy with respect to the arc factors, and they allow optimal arc factors to be determined in closed form for subspaces of the full variation problem. Timings for energy and arc factor gradient computations involving expansion spaces of > 10 24 configuration state functions are reported. Preliminary convergence studies and molecular dissociation curves are presented for some small molecules

Repository environmental parameters and models/methodologies relevant to assessing the performance of high-level waste packages in basalt, tuff, and salt

Energy Technology Data Exchange (ETDEWEB)

Claiborne, H.C.; Croff, A.G.; Griess, J.C.; Smith, F.J.

1987-09-01

This document provides specifications for models/methodologies that could be employed in determining postclosure repository environmental parameters relevant to the performance of high-level waste packages for the Basalt Waste Isolation Project (BWIP) at Richland, Washington, the tuff at Yucca Mountain by the Nevada Test Site, and the bedded salt in Deaf Smith County, Texas. Guidance is provided on the identify of the relevant repository environmental parameters; the models/methodologies employed to determine the parameters, and the input data base for the models/methodologies. Supporting studies included are an analysis of potential waste package failure modes leading to identification of the relevant repository environmental parameters, an evaluation of the credible range of the repository environmental parameters, and a summary of the review of existing models/methodologies currently employed in determining repository environmental parameters relevant to waste package performance. 327 refs., 26 figs., 19 tabs.

Repository environmental parameters and models/methodologies relevant to assessing the performance of high-level waste packages in basalt, tuff, and salt

International Nuclear Information System (INIS)

Claiborne, H.C.; Croff, A.G.; Griess, J.C.; Smith, F.J.

1987-09-01

This document provides specifications for models/methodologies that could be employed in determining postclosure repository environmental parameters relevant to the performance of high-level waste packages for the Basalt Waste Isolation Project (BWIP) at Richland, Washington, the tuff at Yucca Mountain by the Nevada Test Site, and the bedded salt in Deaf Smith County, Texas. Guidance is provided on the identify of the relevant repository environmental parameters; the models/methodologies employed to determine the parameters, and the input data base for the models/methodologies. Supporting studies included are an analysis of potential waste package failure modes leading to identification of the relevant repository environmental parameters, an evaluation of the credible range of the repository environmental parameters, and a summary of the review of existing models/methodologies currently employed in determining repository environmental parameters relevant to waste package performance. 327 refs., 26 figs., 19 tabs

Central Plant Optimization for Waste Energy Reduction (CPOWER). ESTCP Cost and Performance Report

Science.gov (United States)

2016-12-01

meet all demands, and not necessarily for fuel economy or energy efficiency. Plant operators run the equipment according to a pre-set, fixed strategy ...exchanger, based on the site protocol. Thermal Energy Storage Tank Site-specific optimal operating strategies were developed for the chilled water...being served by the central plant Hypothesis The hypothesis tested that the optimized operation reduces wasted energy and energy costs by smart

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.

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

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

International Nuclear Information System (INIS)

Zarepisheh, M; Li, R; Xing, L; Ye, Y; Boyd, S

2014-01-01

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

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.

Optimization of radioactive waste management system by application of multiobjective linear programming

International Nuclear Information System (INIS)

Shimizu, Yoshiaki

1981-01-01

A mathematical procedure is proposed to make a radioactive waste management plan comprehensively. Since such planning is relevant to some different goals in management, decision making has to be formulated as a multiobjective optimization problem. A mathematical programming method was introduced to make a decision through an interactive manner which enables us to assess the preference of decision maker step by step among the conflicting objectives. The reference system taken as an example is the radioactive waste management system at the Research Reactor Institute of Kyoto University (KUR). Its linear model was built based on the experience in the actual management at KUR. The best-compromise model was then formulated as a multiobjective linear programming by the aid of the computational analysis through a conventional optimization. It was shown from the numerical results that the proposed approach could provide some useful informations to make an actual management plan. (author)

Standardless quantification by parameter optimization in electron probe microanalysis

International Nuclear Information System (INIS)

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

2012-01-01

A method for standardless quantification by parameter optimization in electron probe microanalysis is presented. The method consists in minimizing the quadratic differences between an experimental spectrum and an analytical function proposed to describe it, by optimizing the parameters involved in the analytical prediction. This algorithm, implemented in the software POEMA (Parameter Optimization in Electron Probe Microanalysis), allows the determination of the elemental concentrations, along with their uncertainties. The method was tested in a set of 159 elemental constituents corresponding to 36 spectra of standards (mostly minerals) that include trace elements. The results were compared with those obtained with the commercial software GENESIS Spectrum® for standardless quantification. The quantifications performed with the method proposed here are better in the 74% of the cases studied. In addition, the performance of the method proposed is compared with the first principles standardless analysis procedure DTSA for a different data set, which excludes trace elements. The relative deviations with respect to the nominal concentrations are lower than 0.04, 0.08 and 0.35 for the 66% of the cases for POEMA, GENESIS and DTSA, respectively. - Highlights: ► A method for standardless quantification in EPMA is presented. ► It gives better results than the commercial software GENESIS Spectrum. ► It gives better results than the software DTSA. ► It allows the determination of the conductive coating thickness. ► It gives an estimation for the concentration uncertainties.

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.

Parameter optimization for reproducible cardiac 1 H-MR spectroscopy at 3 Tesla.

Science.gov (United States)

de Heer, Paul; Bizino, Maurice B; Lamb, Hildo J; Webb, Andrew G

2016-11-01

To optimize data acquisition parameters in cardiac proton MR spectroscopy, and to evaluate the intra- and intersession variability in myocardial triglyceride content. Data acquisition parameters at 3 Tesla (T) were optimized and reproducibility measured using, in total, 49 healthy subjects. The signal-to-noise-ratio (SNR) and the variance in metabolite amplitude between averages were measured for: (i) global versus local power optimization; (ii) static magnetic field (B 0 ) shimming performed during free-breathing or within breathholds; (iii) post R-wave peak measurement times between 50 and 900 ms; (iv) without respiratory compensation, with breathholds and with navigator triggering; and (v) frequency selective excitation, Chemical Shift Selective (CHESS) and Multiply Optimized Insensitive Suppression Train (MOIST) water suppression techniques. Using the optimized parameters intra- and intersession myocardial triglyceride content reproducibility was measured. Two cardiac proton spectra were acquired with the same parameters and compared (intrasession reproducibility) after which the subject was removed from the scanner and placed back in the scanner and a third spectrum was acquired which was compared with the first measurement (intersession reproducibility). Local power optimization increased SNR on average by 22% compared with global power optimization (P = 0.0002). The average linewidth was not significantly different for pencil beam B 0 shimming using free-breathing or breathholds (19.1 Hz versus 17.5 Hz; P = 0.15). The highest signal stability occurred at a cardiac trigger delay around 240 ms. The mean amplitude variation was significantly lower for breathholds versus free-breathing (P = 0.03) and for navigator triggering versus free-breathing (P = 0.03) as well as for navigator triggering versus breathhold (P = 0.02). The mean residual water signal using CHESS (1.1%, P = 0.01) or MOIST (0.7%, P = 0.01) water suppression was significantly lower than using

Optimization of cryogenic cooled EDM process parameters using grey relational analysis

International Nuclear Information System (INIS)

Kumar, S Vinoth; Kumar, M Pradeep

2014-01-01

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

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 ...

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.

Study of Use Ozone Oxydan at Liquid Waste Processing of Prawn Industry

International Nuclear Information System (INIS)

Isyuniarto; Agus-Purwadi

2006-01-01

Study of use ozone oxidant at liquid waste processing prawn industry was done. This research target is to study the influence of utilization of ozone oxidant to degrade the BOD, COD and TSS in liquid waste processing of prawn industrial. Waste volume for every treatment is 500 ml, ozonization time 10 minute, with the variation of pH: 7; 8; 9; 10 and 11 by gift calcify. With pH optimal then used for the treatment variation of time of ozone gift: 0; 5; 10; 15; 20; and 25 minute. From the experiment it was obtained that the optimal condition is reached at pH = 9 and time of ozonization 20 minute. At this condition is obtained the three following parameters: BOD = 41 mg/l, COD = 54 mg/l, and TSS = 25 mg/l. The parameter have pursuant to permanent standard quality of industrial liquid waste processing of prawn according to Decree of The State's Minister of Environment No. Piece. 51/MENLH/10/1995 and Decision of Gubernur DIY No. 281/KPTS/1998, as conditions of waste of faction III. (author)

A parameter estimation for DC servo motor by using optimization process

International Nuclear Information System (INIS)

Arjoni Amir

2010-01-01

Modeling and simulation parameters of DC servo motor using Matlab Simulink software have been done. The objective to define the DC servo motor parameter estimation is to get DC servo motor parameter values (B, La, Ra, Km, J) which are significant value that can be used for actuation process of control systems. In the analysis of control systems DC the servo motor expressed by transfer function equation to make faster to be analyzed as a component of the actuator. To obtain the data model parameters and initial conditions of the DC servo motors is then carried out the processor modeling and simulation in which the DC servo motor combined with other components. To obtain preliminary data of the DC servo motor parameters as estimated venue, it is obtained from the data factory of the DC servo motor. The initial data parameters of the DC servo motor are applied for the optimization process by using nonlinear least square algorithm and minimize the cost function value so that the DC servo motors parameter values are obtained significantly. The result of the optimization process of the DC servo motor parameter values are B = 0.039881, J= 1.2608e-007, Km = 0.069648, La = 2.3242e-006 and Ra = 1.8837. (author)

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

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

International Nuclear Information System (INIS)

Rao, R. Venkata; Rai, Dhiraj P.

2017-01-01

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

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).

Comparisons of criteria in the assessment model parameter optimizations

International Nuclear Information System (INIS)

Liu Xinhe; Zhang Yongxing

1993-01-01

Three criteria (chi square, relative chi square and correlation coefficient) used in model parameter optimization (MPO) process that aims at significant reduction of prediction uncertainties were discussed and compared to each other with the aid of a well-controlled tracer experiment

Optimal evaluation of infectious medical waste disposal companies using the fuzzy analytic hierarchy process

International Nuclear Information System (INIS)

Ho, Chao Chung

2011-01-01

Ever since Taiwan's National Health Insurance implemented the diagnosis-related groups payment system in January 2010, hospital income has declined. Therefore, to meet their medical waste disposal needs, hospitals seek suppliers that provide high-quality services at a low cost. The enactment of the Waste Disposal Act in 1974 had facilitated some improvement in the management of waste disposal. However, since the implementation of the National Health Insurance program, the amount of medical waste from disposable medical products has been increasing. Further, of all the hazardous waste types, the amount of infectious medical waste has increased at the fastest rate. This is because of the increase in the number of items considered as infectious waste by the Environmental Protection Administration. The present study used two important findings from previous studies to determine the critical evaluation criteria for selecting infectious medical waste disposal firms. It employed the fuzzy analytic hierarchy process to set the objective weights of the evaluation criteria and select the optimal infectious medical waste disposal firm through calculation and sorting. The aim was to propose a method of evaluation with which medical and health care institutions could objectively and systematically choose appropriate infectious medical waste disposal firms.

Applying the principles of thermoeconomics to the organic Rankine Cycle for low temperature waste heat recovery

International Nuclear Information System (INIS)

Xiao, F.; Lilun, Q.; Changsun, S.

1989-01-01

In this paper, thermoeconomic principle is used to study the selection of working fluids and the option of the cycle parameters in the organic Rankine cycle of low temperature waste heat recovery. The parameter ξ, the product of the ratio of waste heat recovery and real cycle thermal efficiency, is suggested as a unified thermodynamic criterion for the selection of the working fluids. The mathematical expressions are developed to determine the optimal boiling temperature and the optimal pin point temperature difference in the heat recovery exchanger by way of thermoeconomic principle

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

International Nuclear Information System (INIS)

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

2017-01-01

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

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....

Optimized production of biodiesel from waste cooking oil by lipase immobilized on magnetic nanoparticles.

Science.gov (United States)

Yu, Chi-Yang; Huang, Liang-Yu; Kuan, I-Ching; Lee, Shiow-Ling

2013-12-11

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.

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.

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.

A methodology for optimal MSW management, with an application in the waste transportation of Attica Region, Greece

International Nuclear Information System (INIS)

Economopoulou, M.A.; Economopoulou, A.A.; Economopoulos, A.P.

2013-01-01

Highlights: • A two-step (strategic and detailed optimal planning) methodology is used for solving complex MSW management problems. • A software package is outlined, which can be used for generating detailed optimal plans. • Sensitivity analysis compares alternative scenarios that address objections and/or wishes of local communities. • A case study shows the application of the above procedure in practice and demonstrates the results and benefits obtained. - Abstract: The paper describes a software system capable of formulating alternative optimal Municipal Solid Wastes (MSWs) management plans, each of which meets a set of constraints that may reflect selected objections and/or wishes of local communities. The objective function to be minimized in each plan is the sum of the annualized capital investment and annual operating cost of all transportation, treatment and final disposal operations involved, taking into consideration the possible income from the sale of products and any other financial incentives or disincentives that may exist. For each plan formulated, the system generates several reports that define the plan, analyze its cost elements and yield an indicative profile of selected types of installations, as well as data files that facilitate the geographic representation of the optimal solution in maps through the use of GIS. A number of these reports compare the technical and economic data from all scenarios considered at the study area, municipality and installation level constituting in effect sensitivity analysis. The generation of alternative plans offers local authorities the opportunity of choice and the results of the sensitivity analysis allow them to choose wisely and with consensus. The paper presents also an application of this software system in the capital Region of Attica in Greece, for the purpose of developing an optimal waste transportation system in line with its approved waste management plan. The formulated plan was able to

A methodology for optimal MSW management, with an application in the waste transportation of Attica Region, Greece

Energy Technology Data Exchange (ETDEWEB)

Economopoulou, M.A. [Hellenic Statistical Authority, Pireos 46 and Eponiton, Pireus 185 10 (Greece); Economopoulou, A.A. [Ministry of Environment, Energy and Climatic Change, 15 Amaliados Street, Athens 11523 (Greece); Economopoulos, A.P., E-mail: eco@otenet.gr [Environmental Engineering Dept., Technical University of Crete, Chania 73100 (Greece)

2013-11-15

Highlights: • A two-step (strategic and detailed optimal planning) methodology is used for solving complex MSW management problems. • A software package is outlined, which can be used for generating detailed optimal plans. • Sensitivity analysis compares alternative scenarios that address objections and/or wishes of local communities. • A case study shows the application of the above procedure in practice and demonstrates the results and benefits obtained. - Abstract: The paper describes a software system capable of formulating alternative optimal Municipal Solid Wastes (MSWs) management plans, each of which meets a set of constraints that may reflect selected objections and/or wishes of local communities. The objective function to be minimized in each plan is the sum of the annualized capital investment and annual operating cost of all transportation, treatment and final disposal operations involved, taking into consideration the possible income from the sale of products and any other financial incentives or disincentives that may exist. For each plan formulated, the system generates several reports that define the plan, analyze its cost elements and yield an indicative profile of selected types of installations, as well as data files that facilitate the geographic representation of the optimal solution in maps through the use of GIS. A number of these reports compare the technical and economic data from all scenarios considered at the study area, municipality and installation level constituting in effect sensitivity analysis. The generation of alternative plans offers local authorities the opportunity of choice and the results of the sensitivity analysis allow them to choose wisely and with consensus. The paper presents also an application of this software system in the capital Region of Attica in Greece, for the purpose of developing an optimal waste transportation system in line with its approved waste management plan. The formulated plan was able to

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.

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

Directory of Open Access Journals (Sweden)

Yue Xiao

2018-01-01

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

A Genetic Algorithm Approach to the Optimization of a Radioactive Waste Treatment System

International Nuclear Information System (INIS)

Yang, Yeongjin; Lee, Kunjai; Koh, Y.; Mun, J.H.; Kim, H.S.

1998-01-01

This study is concerned with the applications of goal programming and genetic algorithm techniques to the analysis of management and operational problems in the radioactive waste treatment system (RWTS). A typical RWTS is modeled and solved by goal program and genetic algorithm to study and resolve the effects of conflicting objectives such as cost, limitation of released radioactivity to the environment, equipment utilization and total treatable radioactive waste volume before discharge and disposal. The developed model is validated and verified using actual data obtained from the RWTS at Kyoto University in Japan. The solution by goal programming and genetic algorithm would show the optimal operation point which is to maximize the total treatable radioactive waste volume and minimize the released radioactivity of liquid waste even under the restricted resources. The comparison of two methods shows very similar results. (author)

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

African Journals Online (AJOL)

Optimization of CNC end milling process parameters using PCA-based Taguchi method. ... International Journal of Engineering, Science and Technology ... To meet the basic assumption of Taguchi method; in the present work, individual response correlations have been eliminated first by means of Principal Component ...

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.

The primary ion source for construction and optimization of operation parameters

International Nuclear Information System (INIS)

Synowiecki, A.; Gazda, E.

1986-01-01

The construction of primary ion source for SIMS has been presented. The influence of individual operation parameters on the properties of ion source has been investigated. Optimization of these parameters has allowed to appreciate usefulness of the ion source for SIMS study. 14 refs., 8 figs., 2 tabs. (author)

Optimization of virtual source parameters in neutron scattering instrumentation

International Nuclear Information System (INIS)

Habicht, K; Skoulatos, M

2012-01-01

We report on phase-space optimizations for neutron scattering instruments employing horizontal focussing crystal optics. Defining a figure of merit for a generic virtual source configuration we identify a set of optimum instrumental parameters. In order to assess the quality of the instrumental configuration we combine an evolutionary optimization algorithm with the analytical Popovici description using multidimensional Gaussian distributions. The optimum phase-space element which needs to be delivered to the virtual source by preceding neutron optics may be obtained using the same algorithm which is of general interest in instrument design.

Application of Factorial Design for Gas Parameter Optimization in CO2 Laser Welding

DEFF Research Database (Denmark)

Gong, Hui; Dragsted, Birgitte; Olsen, Flemming Ove

1997-01-01

The effect of different gas process parameters involved in CO2 laser welding has been studied by applying two-set of three-level complete factorial designs. In this work 5 gas parameters, gas type, gas flow rate, gas blowing angle, gas nozzle diameter, gas blowing point-offset, are optimized...... to be a very useful tool for parameter optimi-zation in laser welding process. Keywords: CO2 laser welding, gas parameters, factorial design, Analysis of Variance........ The bead-on-plate welding specimens are evaluated by a number of quality char-acteristics, such as the penetration depth and the seam width. The significance of the gas pa-rameters and their interactions are based on the data found by the Analysis of Variance-ANOVA. This statistic methodology is proven...

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

Science.gov (United States)

Azmi, Nur Iffah Mohamed; Arifin Mat Piah, Kamal; Yusoff, Wan Azhar Wan; Romlay, Fadhlur Rahman Mohd

2018-03-01

Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. Tuning PID control method is divided into two namely the classical methods and the methods of artificial intelligence. Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey- Taguchi Design of Experiment (DOE) method. This is done by conducting the DOE on the two PSO optimizing parameters: the particle velocity limit and the weight distribution factor. Computer simulations and physical experiments were conducted by using the proposed PSO- PID with the Variable Weight Grey-Taguchi DOE and the classical Ziegler-Nichols methods. They are implemented on the hydraulic positioning system. Simulation results show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE has reduced the rise time by 48.13% and settling time by 48.57% compared to the Ziegler-Nichols method. Furthermore, the physical experiment results also show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE tuning method responds better than Ziegler-Nichols tuning. In conclusion, this research has improved the PSO-PID parameter by applying the PSO-PID algorithm together with the Variable Weight Grey-Taguchi DOE method as a tuning method in the hydraulic positioning system.

Parameters and criteria influencing the selection of waste emplacement configurations in mined geologic repositories

International Nuclear Information System (INIS)

Bechthold, W.; Closs, K.D.; Papp, R.

1988-01-01

Reference concepts for repositories in deep geological formations have been developed in several countries. For these concepts, emplacement configurations vary within a wide range that comprises drift emplacement of unshielded or self-shielded packages and horizontal or vertical borehole emplacement. This is caused by different parameters, criteria, and criteria weighting factors. Examples for parameters are the country's nuclear power program and waste management policy, its geological situation, and safety requirements, examples for criteria and repository area requirements, expenditures of mining and drilling, and efforts for emplacement and, if required, retrieval. Due to the variety of these factors and their ranking in different countries, requirements for a safe, dependable and cost-effective disposal of radioactive waste can be met in various ways

Optimal design of advanced distillation configuration for enhanced energy efficiency of waste solvent recovery process in semiconductor industry

International Nuclear Information System (INIS)

Chaniago, Yus Donald; Minh, Le Quang; Khan, Mohd Shariq; Koo, Kee-Kahb; Bahadori, Alireza; Lee, Moonyong

2015-01-01

Highlights: • Thermally coupled distillation process is proposed for waste solvent recovery. • A systematic optimization procedure is used to optimize distillation columns. • Response surface methodology is applied to optimal design of distillation column. • Proposed advanced distillation allows energy efficient waste solvent recovery. - Abstract: The semiconductor industry is one of the largest industries in the world. On the other hand, the huge amount of solvent used in the industry results in high production cost and potential environmental damage because most of the valuable chemicals discharged from the process are incinerated at high temperatures. A distillation process is used to recover waste solvent, reduce the production-related costs and protect the environment from the semiconductor industrial waste. Therefore, in this study, a distillation process was used to recover the valuable chemicals from semiconductor industry discharge, which otherwise would have been lost to the environment. The conventional sequence of distillation columns, which was optimized using the Box and sequential quadratic programming method for minimum energy objectives, was used. The energy demands of a distillation problem may have a substantial influence on the profitability of a process. A thermally coupled distillation and heat pump-assisted distillation sequence was implemented to further improve the distillation performance. Finally, a comparison was made between the conventional and advanced distillation sequences, and the optimal conditions for enhancing recovery were determined. The proposed advanced distillation configuration achieved a significant energy saving of 40.5% compared to the conventional column sequence

Web-GIS oriented systems viability for municipal solid waste selective collection optimization in developed and transient economies

Energy Technology Data Exchange (ETDEWEB)

Rada, E.C., E-mail: Elena.Rada@ing.unitn.it [University of Trento, Department of Civil, Environmental and Mechanical Engineering, Via Mesiano, 77, 38123 Trento (Italy); Ragazzi, M. [University of Trento, Department of Civil, Environmental and Mechanical Engineering, Via Mesiano, 77, 38123 Trento (Italy); Fedrizzi, P. [I and S, Informatica e Servizi srl, Via Solteri, 74, 38121 Trento (Italy)

2013-04-15

Highlights: ► As an appropriate solution for MSW management in developed and transient countries. ► As an option to increase the efficiency of MSW selective collection. ► As an opportunity to integrate MSW management needs and services inventories. ► As a tool to develop Urban Mining actions. - Abstract: Municipal solid waste management is a multidisciplinary activity that includes generation, source separation, storage, collection, transfer and transport, processing and recovery, and, last but not least, disposal. The optimization of waste collection, through source separation, is compulsory where a landfill based management must be overcome. In this paper, a few aspects related to the implementation of a Web-GIS based system are analyzed. This approach is critically analyzed referring to the experience of two Italian case studies and two additional extra-European case studies. The first case is one of the best examples of selective collection optimization in Italy. The obtained efficiency is very high: 80% of waste is source separated for recycling purposes. In the second reference case, the local administration is going to be faced with the optimization of waste collection through Web-GIS oriented technologies for the first time. The starting scenario is far from an optimized management of municipal solid waste. The last two case studies concern pilot experiences in China and Malaysia. Each step of the Web-GIS oriented strategy is comparatively discussed referring to typical scenarios of developed and transient economies. The main result is that transient economies are ready to move toward Web oriented tools for MSW management, but this opportunity is not yet well exploited in the sector.

Web-GIS oriented systems viability for municipal solid waste selective collection optimization in developed and transient economies

International Nuclear Information System (INIS)

Rada, E.C.; Ragazzi, M.; Fedrizzi, P.

2013-01-01

Highlights: ► As an appropriate solution for MSW management in developed and transient countries. ► As an option to increase the efficiency of MSW selective collection. ► As an opportunity to integrate MSW management needs and services inventories. ► As a tool to develop Urban Mining actions. - Abstract: Municipal solid waste management is a multidisciplinary activity that includes generation, source separation, storage, collection, transfer and transport, processing and recovery, and, last but not least, disposal. The optimization of waste collection, through source separation, is compulsory where a landfill based management must be overcome. In this paper, a few aspects related to the implementation of a Web-GIS based system are analyzed. This approach is critically analyzed referring to the experience of two Italian case studies and two additional extra-European case studies. The first case is one of the best examples of selective collection optimization in Italy. The obtained efficiency is very high: 80% of waste is source separated for recycling purposes. In the second reference case, the local administration is going to be faced with the optimization of waste collection through Web-GIS oriented technologies for the first time. The starting scenario is far from an optimized management of municipal solid waste. The last two case studies concern pilot experiences in China and Malaysia. Each step of the Web-GIS oriented strategy is comparatively discussed referring to typical scenarios of developed and transient economies. The main result is that transient economies are ready to move toward Web oriented tools for MSW management, but this opportunity is not yet well exploited in the sector

Aerobic composting of waste activated sludge: Kinetic analysis for microbiological reaction and oxygen consumption

International Nuclear Information System (INIS)

Yamada, Y.; Kawase, Y.

2006-01-01

In order to examine the optimal design and operating parameters, kinetics for microbiological reaction and oxygen consumption in composting of waste activated sludge were quantitatively examined. A series of experiments was conducted to discuss the optimal operating parameters for aerobic composting of waste activated sludge obtained from Kawagoe City Wastewater Treatment Plant (Saitama, Japan) using 4 and 20 L laboratory scale bioreactors. Aeration rate, compositions of compost mixture and height of compost pile were investigated as main design and operating parameters. The optimal aerobic composting of waste activated sludge was found at the aeration rate of 2.0 L/min/kg (initial composting mixture dry weight). A compost pile up to 0.5 m could be operated effectively. A simple model for composting of waste activated sludge in a composting reactor was developed by assuming that a solid phase of compost mixture is well mixed and the kinetics for microbiological reaction is represented by a Monod-type equation. The model predictions could fit the experimental data for decomposition of waste activated sludge with an average deviation of 2.14%. Oxygen consumption during composting was also examined using a simplified model in which the oxygen consumption was represented by a Monod-type equation and the axial distribution of oxygen concentration in the composting pile was described by a plug-flow model. The predictions could satisfactorily simulate the experiment results for the average maximum oxygen consumption rate during aerobic composting with an average deviation of 7.4%

Evaluation of Stability Parameters in In-Vessel Compositing of Municipal Solid Waste

Directory of Open Access Journals (Sweden)

M. M. Amin

2011-10-01

Full Text Available Composting is a reliable technology for production of stabilized organic matter that is suitable for agriculture, but this process should be carefully monitored with appropriate indices. Quality of compost is important from maturity and stability viewpoint, but in most compost factories proper attention is not paid to it. This study was designed to evaluate the stability indices in municipal solid waste composting, for selecting the best index in quality monitoring of the wastes. Processed and shredded municipal solid waste from Isfahan compost plant was used as raw material in an in-vessel composting process. A cylindrical reactor with 1 m height and 50 cm diameter made of Pyrex glass was designed. Air was supplied at a specifically flow rate 0.2 L/min.kg to maintain aerobic condition. NH4+/ NO3 ratio, dehydrogenase enzyme activity (DA, pH, oxidation reduction potential (ORP or Eh and specific oxygen uptake rate (SOUR were used as stability indices. These parameters were measured during 40 days of composting process. Changes in these parameters during this period were surveyed and analyzed. Statistical analysis was carried out to choose best of them. Results showed that among the indices, SOUR can show the different stages of microbial decomposition and a numerical value for compost stability also SOUR value less than 2 mg O2/gVS.h can show the full stability of compost.

Sensitivity of the optimal parameter settings for a LTE packet scheduler

NARCIS (Netherlands)

Fernandez-Diaz, I.; Litjens, R.; van den Berg, C.A.; Dimitrova, D.C.; Spaey, K.

Advanced packet scheduling schemes in 3G/3G+ mobile networks provide one or more parameters to optimise the trade-off between QoS and resource efficiency. In this paper we study the sensitivity of the optimal parameter setting for packet scheduling in LTE radio networks with respect to various

Survey of Optimal Temperature and Moisture for Worms Growth and Operating Vermicompost Production of Food Wastes

OpenAIRE

A Eslami; A Nabaey; R Rostami

2009-01-01

"n "nBackground and Objectives:Nowadays vermicompost production of food wastes is posed as one of appropriate methods to food wastes. disposal, its production used in agriculture and gardening. Moreover this process has some by products beside useful fertilizer that one of them is the worms. we can use them in variety of products specially in production of poultry and fish food. So determination of optimal condition for operating vermicompost production process of food wastes and worms. growt...

Iterative choice of the optimal regularization parameter in TV image deconvolution

International Nuclear Information System (INIS)

Sixou, B; Toma, A; Peyrin, F; Denis, L

2013-01-01

We present an iterative method for choosing the optimal regularization parameter for the linear inverse problem of Total Variation image deconvolution. This approach is based on the Morozov discrepancy principle and on an exponential model function for the data term. The Total Variation image deconvolution is performed with the Alternating Direction Method of Multipliers (ADMM). With a smoothed l 2 norm, the differentiability of the value of the Lagrangian at the saddle point can be shown and an approximate model function obtained. The choice of the optimal parameter can be refined with a Newton method. The efficiency of the method is demonstrated on a blurred and noisy bone CT cross section

Optimization of CHA-PCFC Hybrid Material for the Removal of Radioactive Cs from Waste Seawater

Energy Technology Data Exchange (ETDEWEB)

Lee, Keun-Young; Kim, Jimin; Park, Minsung; Kim, Kwang-Wook; Lee, Eil-Hee; Chung, Dong-Yong; Moon, Jei-Kwon [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2015-05-15

The liquid waste treatment processes in the normal operation of nuclear power plant are commercialized, those in the abnormal accidents have not been fully developed until now. In the present study, as a preliminary research for the development of precipitation-based treatment process specialized for the removal of Cs from waste seawater generated in the emergency case, the performance test of a hybrid material combining chabazite and potassium cobalt ferrocyanide was conducted. Also the synthesis method for the hybrid adsorbent was optimized for the best Cs removal efficiency on the actual contamination level of waste seawater. Because the temperature effect on the synthesis of PCFC was confirmed by preliminary experiments, the optimization of CHA-PCFC synthesis was also conducted. The hybrid material synthesized at 40 .deg. C showed the highest distribution coefficient of Cs in the same manner of the performance of PCFC synthesized at the lower temperature than that of conventional methods.

Waste incineration models for operation optimization. Phase 1: Advanced measurement equipment for improved operation of waste fired plants; Affaldsforbraendingsmodeller til driftsoptimering. Fase 1: Avanceret maeleudstyr til forbedret drift af affaldsfyrede anlaeg

Energy Technology Data Exchange (ETDEWEB)

NONE

2005-06-01

This report describes results from the PSO projects ELTRA-5294 and ELTRA-5348: Waste incineration models for operation optimization. Phase 1, and Advanced measurement equipment for improved operation of waste fired plants. Phase 1. The two projects form the first step in a project course build on a long-term vision of a fully automatic system using a wide range of advanced measurement data, advanced dynamic models for prediction of operation and advanced regulation methods for optimization of the operation of waste incinerator plants. (BA)

Optimizing parameters of a technical system using quality function deployment method

Science.gov (United States)

Baczkowicz, M.; Gwiazda, A.

2015-11-01

The article shows the practical use of Quality Function Deployment (QFD) on the example of a mechanized mining support. Firstly it gives a short description of this method and shows how the designing process, from the constructor point of view, looks like. The proposed method allows optimizing construction parameters and comparing them as well as adapting to customer requirements. QFD helps to determine the full set of crucial construction parameters and then their importance and difficulty of their execution. Secondly it shows chosen technical system and presents its construction with figures of the existing and future optimized model. The construction parameters were selected from the designer point of view. The method helps to specify a complete set of construction parameters, from the point of view, of the designed technical system and customer requirements. The QFD matrix can be adjusted depending on designing needs and not every part of it has to be considered. Designers can choose which parts are the most important. Due to this QFD can be a very flexible tool. The most important is to define relationships occurring between parameters and that part cannot be eliminated from the analysis.

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

Directory of Open Access Journals (Sweden)

Daniel Santana-Cedrés

2016-12-01

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

Synthesis and characterization of CNTs using polypropylene waste as precursor

Energy Technology Data Exchange (ETDEWEB)

Bajad, Ganesh S. [Department of Chemical Engineering, Visvesvaraya National Institute of Technology, Nagpur 440010 (India); Tiwari, Saurabh K. [Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076 (India); Vijayakumar, R.P., E-mail: vijayakumarrp@che.vnit.ac.in [Department of Chemical Engineering, Visvesvaraya National Institute of Technology, Nagpur 440010 (India)

2015-04-15

Graphical abstract: - Highlights: • A facile method for producing CNTs from polypropylene waste is proposed. • Optimization of Ni/Mo mole ratio using RSM suggests the adequacy of cubic model. • Process parameters were optimized by RSM using Box–Behnken four factorial design. • Maximum desirability of one suggested that 514% of CNTs would yield over Ni{sub 4}Mo{sub 0.2}MgO{sub 1}. • Increase in Ni/Mo ratio from 0.5 to 20, inner diameter of CNTs decreases from 25 to 2 nm. - Abstract: We study the synthesis of MWCNTs using polypropylene waste as a precursor and Ni/Mo/MgO as a catalyst by the combustion technique. Molar ratios of Ni, Mo and MgO in the Ni/Mo/MgO catalyst were optimized using response surface methodology (RSM) to obtain the maximum yield of CNTs. The mole ratio 4/0.2/1 was found to yield more carbon product. Further, process parameters such as combustion temperature, combustion time, polymer and catalyst weight were optimized by RSM using Box–Behnken three-level and four-factorial design. The best possible combination of process parameters (combustion time of 10 min, combustion temperature of 800 °C, polymer weight of 5 g and catalyst weight of 150 mg) for maximum yield of CNTs was obtained. HRTEM indicates that the diameter of CNTs depends on the catalyst composition used for the synthesis of CNTs. The results of the study indicate a facile method for producing CNTs from polypropylene waste.

Synthesis and characterization of CNTs using polypropylene waste as precursor

International Nuclear Information System (INIS)

Bajad, Ganesh S.; Tiwari, Saurabh K.; Vijayakumar, R.P.

2015-01-01

Graphical abstract: - Highlights: • A facile method for producing CNTs from polypropylene waste is proposed. • Optimization of Ni/Mo mole ratio using RSM suggests the adequacy of cubic model. • Process parameters were optimized by RSM using Box–Behnken four factorial design. • Maximum desirability of one suggested that 514% of CNTs would yield over Ni 4 Mo 0.2 MgO 1 . • Increase in Ni/Mo ratio from 0.5 to 20, inner diameter of CNTs decreases from 25 to 2 nm. - Abstract: We study the synthesis of MWCNTs using polypropylene waste as a precursor and Ni/Mo/MgO as a catalyst by the combustion technique. Molar ratios of Ni, Mo and MgO in the Ni/Mo/MgO catalyst were optimized using response surface methodology (RSM) to obtain the maximum yield of CNTs. The mole ratio 4/0.2/1 was found to yield more carbon product. Further, process parameters such as combustion temperature, combustion time, polymer and catalyst weight were optimized by RSM using Box–Behnken three-level and four-factorial design. The best possible combination of process parameters (combustion time of 10 min, combustion temperature of 800 °C, polymer weight of 5 g and catalyst weight of 150 mg) for maximum yield of CNTs was obtained. HRTEM indicates that the diameter of CNTs depends on the catalyst composition used for the synthesis of CNTs. The results of the study indicate a facile method for producing CNTs from polypropylene waste

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.

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.

Multiobjective optimization for nuclear fleet evolution scenarios using COSI

Directory of Open Access Journals (Sweden)

Freynet David

2016-01-01

Full Text Available The consequences of various fleet evolution options on material inventories and flux in fuel cycle and waste can be analysed by means of transition scenario studies. The COSI code is currently simulating chronologically scenarios whose parameters are fully defined by the user and is coupled with the CESAR depletion code. As the interactions among reactors and fuel cycle facilities can be complex, and the ways in which they may be configured are many, the development of optimization methodology could improve scenario studies. The optimization problem definition needs to list: (i criteria (e.g. saving natural resources and minimizing waste production; (ii variables (scenario parameters related to reprocessing, reactor operation, installed power distribution, etc.; (iii constraints making scenarios industrially feasible. The large number of scenario calculations needed to solve an optimization problem can be time-consuming and hardly achievable; therefore, it requires the shortening of the COSI computation time. Given that CESAR depletion calculations represent about 95% of this computation time, CESAR surrogate models have been developed and coupled with COSI. Different regression models are compared to estimate CESAR outputs: first- and second-order polynomial regressions, Gaussian process and artificial neural network. This paper is about a first optimization study of a transition scenario from the current French nuclear fleet to a Sodium Fast Reactors fleet as defined in the frame of the 2006 French Act for waste management. The present article deals with obtaining the optimal scenarios and validating the methodology implemented, i.e. the coupling between the simulation software COSI, depletion surrogate models and a genetic algorithm optimization method.

Optimization of waste management in the EG with the aid of systems analysis methods

International Nuclear Information System (INIS)

Braun, H.W.M.; Ditterich, K.; Schneider, J.

1974-01-01

The problems of waste management range from their production when they must be collected to transport, conditioning etc., and, finally, to safe disposal. Until recently, the subsystems in waste management had for the most part been treated empirically and separately. In this paper, all subsystems are considered and related to each other with systems analysis methods. In this way the complex problem including the initial and end values can be optimized with regard to a maximum of security and reliability and a minimum of cost and environmental load. The annex contains a simplified example for the treatment of waste mangement by methods of systems analysis. (orig./AK) [de

Optimization of geometric parameters of heat exchange pipes pin finning

Science.gov (United States)

Akulov, K. A.; Golik, V. V.; Voronin, K. S.; Zakirzakov, A. G.

2018-05-01

The work is devoted to optimization of geometric parameters of the pin finning of heat-exchanging pipes. Pin fins were considered from the point of view of mechanics of a deformed solid body as overhang beams with a uniformly distributed load. It was found out under what geometric parameters of the nib (diameter and length); the stresses in it from the influence of the washer fluid will not exceed the yield strength of the material (aluminum). Optimal values of the geometric parameters of nibs were obtained for different velocities of the medium washed by them. As a flow medium, water and air were chosen, and the cross section of the nibs was round and square. Pin finning turned out to be more than 3 times more compact than circumferential finning, so its use makes it possible to increase the number of fins per meter of the heat-exchanging pipe. And it is well-known that this is the main method for increasing the heat transfer of a convective surface, giving them an indisputable advantage.

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.

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

Science.gov (United States)

Zhang, Shirong; Tang, Qian; Lin, Yu; Tang, Yuling

2017-05-01

Feed water treatment process (FWTP) is an essential part of utility boilers; and fault detection is expected for its reliability improvement. Classical principal component analysis (PCA) has been applied to FWTPs in our previous work; however, the noises of T 2 and SPE statistics result in false detections and missed detections. In this paper, Wavelet denoise (WD) is combined with PCA to form a new algorithm, (PCA-WD), where WD is intentionally employed to deal with the noises. The parameter selection of PCA-WD is further formulated as an optimization problem; and PSO is employed for optimization solution. A FWTP, sustaining two 1000MW generation units in a coal-fired power plant, is taken as a study case. Its operation data is collected for following verification study. The results show that the optimized WD is effective to restrain the noises of T 2 and SPE statistics, so as to improve the performance of PCA-WD algorithm. And, the parameter optimization enables PCA-WD to get its optimal parameters in an automatic way rather than on individual experience. The optimized PCA-WD is further compared with classical PCA and sliding window PCA (SWPCA), in terms of four cases as bias fault, drift fault, broken line fault and normal condition, respectively. The advantages of the optimized PCA-WD, against classical PCA and SWPCA, is finally convinced with the results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Optimization of design parameters for bulk micromachined silicon membranes for piezoresistive pressure sensing application

International Nuclear Information System (INIS)

Belwanshi, Vinod; Topkar, Anita

2016-01-01

Finite element analysis study has been carried out to optimize the design parameters for bulk micro-machined silicon membranes for piezoresistive pressure sensing applications. The design is targeted for measurement of pressure up to 200 bar for nuclear reactor applications. The mechanical behavior of bulk micro-machined silicon membranes in terms of deflection and stress generation has been simulated. Based on the simulation results, optimization of the membrane design parameters in terms of length, width and thickness has been carried out. Subsequent to optimization of membrane geometrical parameters, the dimensions and location of the high stress concentration region for implantation of piezoresistors have been obtained for sensing of pressure using piezoresistive sensing technique.

Optimization of design parameters for bulk micromachined silicon membranes for piezoresistive pressure sensing application

Science.gov (United States)

Belwanshi, Vinod; Topkar, Anita

2016-05-01

Finite element analysis study has been carried out to optimize the design parameters for bulk micro-machined silicon membranes for piezoresistive pressure sensing applications. The design is targeted for measurement of pressure up to 200 bar for nuclear reactor applications. The mechanical behavior of bulk micro-machined silicon membranes in terms of deflection and stress generation has been simulated. Based on the simulation results, optimization of the membrane design parameters in terms of length, width and thickness has been carried out. Subsequent to optimization of membrane geometrical parameters, the dimensions and location of the high stress concentration region for implantation of piezoresistors have been obtained for sensing of pressure using piezoresistive sensing technique.

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

DEFF Research Database (Denmark)

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

The design of a measured program devoted to parameter identification of structural dynamic systems is considered, the design problem is formulated as an optimization problem due to minimize the total expected cost of the measurement program. All the calculations are based on a priori knowledge...... and engineering judgement. One of the contribution of the approach is that the optimal nmber of sensors can be estimated. This is sown in an numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement program for estimating the modal damping parameters...

Coastal aquifer management under parameter uncertainty: Ensemble surrogate modeling based simulation-optimization

Science.gov (United States)

Janardhanan, S.; Datta, B.

2011-12-01

Surrogate models are widely used to develop computationally efficient simulation-optimization models to solve complex groundwater management problems. Artificial intelligence based models are most often used for this purpose where they are trained using predictor-predictand data obtained from a numerical simulation model. Most often this is implemented with the assumption that the parameters and boundary conditions used in the numerical simulation model are perfectly known. However, in most practical situations these values are uncertain. Under these circumstances the application of such approximation surrogates becomes limited. In our study we develop a surrogate model based coupled simulation optimization methodology for determining optimal pumping strategies for coastal aquifers considering parameter uncertainty. An ensemble surrogate modeling approach is used along with multiple realization optimization. The methodology is used to solve a multi-objective coastal aquifer management problem considering two conflicting objectives. Hydraulic conductivity and the aquifer recharge are considered as uncertain values. Three dimensional coupled flow and transport simulation model FEMWATER is used to simulate the aquifer responses for a number of scenarios corresponding to Latin hypercube samples of pumping and uncertain parameters to generate input-output patterns for training the surrogate models. Non-parametric bootstrap sampling of this original data set is used to generate multiple data sets which belong to different regions in the multi-dimensional decision and parameter space. These data sets are used to train and test multiple surrogate models based on genetic programming. The ensemble of surrogate models is then linked to a multi-objective genetic algorithm to solve the pumping optimization problem. Two conflicting objectives, viz, maximizing total pumping from beneficial wells and minimizing the total pumping from barrier wells for hydraulic control of

Engineering-Scale Demonstration of DuraLith and Ceramicrete Waste Forms

Energy Technology Data Exchange (ETDEWEB)

Josephson, Gary B.; Westsik, Joseph H.; Pires, Richard P.; Bickford, Jody; Foote, Martin W.

2011-09-23

To support the selection of a waste form for the liquid secondary wastes from the Hanford Waste Immobilization and Treatment Plant, Washington River Protection Solutions (WRPS) has initiated secondary waste form testing on four candidate waste forms. Two of the candidate waste forms have not been developed to scale as the more mature waste forms. This work describes engineering-scale demonstrations conducted on Ceramicrete and DuraLith candidate waste forms. Both candidate waste forms were successfully demonstrated at an engineering scale. A preliminary conceptual design could be prepared for full-scale production of the candidate waste forms. However, both waste forms are still too immature to support a detailed design. Formulations for each candidate waste form need to be developed so that the material has a longer working time after mixing the liquid and solid constituents together. Formulations optimized based on previous lab studies did not have sufficient working time to support large-scale testing. The engineering-scale testing was successfully completed using modified formulations. Further lab development and parametric studies are needed to optimize formulations with adequate working time and assess the effects of changes in raw materials and process parameters on the final product performance. Studies on effects of mixing intensity on the initial set time of the waste forms are also needed.

Multiobjective Optimization of Turning Cutting Parameters for J-Steel Material

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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.

Accuracy Analysis and Parameters Optimization in Urban Flood Simulation by PEST Model

Science.gov (United States)

Keum, H.; Han, K.; Kim, H.; Ha, C.

2017-12-01

The risk of urban flooding has been increasing due to heavy rainfall, flash flooding and rapid urbanization. Rainwater pumping stations, underground reservoirs are used to actively take measures against flooding, however, flood damage from lowlands continues to occur. Inundation in urban areas has resulted in overflow of sewer. Therefore, it is important to implement a network system that is intricately entangled within a city, similar to the actual physical situation and accurate terrain due to the effects on buildings and roads for accurate two-dimensional flood analysis. The purpose of this study is to propose an optimal scenario construction procedure watershed partitioning and parameterization for urban runoff analysis and pipe network analysis, and to increase the accuracy of flooded area prediction through coupled model. The establishment of optimal scenario procedure was verified by applying it to actual drainage in Seoul. In this study, optimization was performed by using four parameters such as Manning's roughness coefficient for conduits, watershed width, Manning's roughness coefficient for impervious area, Manning's roughness coefficient for pervious area. The calibration range of the parameters was determined using the SWMM manual and the ranges used in the previous studies, and the parameters were estimated using the automatic calibration method PEST. The correlation coefficient showed a high correlation coefficient for the scenarios using PEST. The RPE and RMSE also showed high accuracy for the scenarios using PEST. In the case of RPE, error was in the range of 13.9-28.9% in the no-parameter estimation scenarios, but in the scenario using the PEST, the error range was reduced to 6.8-25.7%. Based on the results of this study, it can be concluded that more accurate flood analysis is possible when the optimum scenario is selected by determining the appropriate reference conduit for future urban flooding analysis and if the results is applied to various

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

African Journals Online (AJOL)

In this study, optimization of process parameters such as moisture content, incubation temperature and initial pH (fixed) for the improvement of citric acid production from oil palm empty fruit bunches through solid state bioconversion was carried out using traditional one-factor-at-a-time (OFAT) method and response surface ...

Optimization of the blade trailing edge geometric parameters for a small scale ORC turbine

Science.gov (United States)

Zhang, L.; Zhuge, W. L.; Peng, J.; Liu, S. J.; Zhang, Y. J.

2013-12-01

In general, the method proposed by Whitfield and Baines is adopted for the turbine preliminary design. In this design procedure for the turbine blade trailing edge geometry, two assumptions (ideal gas and zero discharge swirl) and two experience values (WR and γ) are used to get the three blade trailing edge geometric parameters: relative exit flow angle β6, the exit tip radius R6t and hub radius R6h for the purpose of maximizing the rotor total-to-static isentropic efficiency. The method above is established based on the experience and results of testing using air as working fluid, so it does not provide a mathematical optimal solution to instruct the optimization of geometry parameters and consider the real gas effects of the organic, working fluid which must be taken into consideration for the ORC turbine design procedure. In this paper, a new preliminary design and optimization method is established for the purpose of reducing the exit kinetic energy loss to improve the turbine efficiency ηts, and the blade trailing edge geometric parameters for a small scale ORC turbine with working fluid R123 are optimized based on this method. The mathematical optimal solution to minimize the exit kinetic energy is deduced, which can be used to design and optimize the exit shroud/hub radius and exit blade angle. And then, the influence of blade trailing edge geometric parameters on turbine efficiency ηts are analysed and the optimal working ranges of these parameters for the equations are recommended in consideration of working fluid R123. This method is used to modify an existing ORC turbine exit kinetic energy loss from 11.7% to 7%, which indicates the effectiveness of the method. However, the internal passage loss increases from 7.9% to 9.4%, so the only way to consider the influence of geometric parameters on internal passage loss is to give the empirical ranges of these parameters, such as the recommended ranges that the value of γ is at 0.3 to 0.4, and the value

Optimization of the blade trailing edge geometric parameters for a small scale ORC turbine

International Nuclear Information System (INIS)

Zhang, L; Zhuge, W L; Liu, S J; Zhang, Y J; Peng, J

2013-01-01

In general, the method proposed by Whitfield and Baines is adopted for the turbine preliminary design. In this design procedure for the turbine blade trailing edge geometry, two assumptions (ideal gas and zero discharge swirl) and two experience values (W R and γ) are used to get the three blade trailing edge geometric parameters: relative exit flow angle β 6 , the exit tip radius R 6t and hub radius R 6h for the purpose of maximizing the rotor total-to-static isentropic efficiency. The method above is established based on the experience and results of testing using air as working fluid, so it does not provide a mathematical optimal solution to instruct the optimization of geometry parameters and consider the real gas effects of the organic, working fluid which must be taken into consideration for the ORC turbine design procedure. In this paper, a new preliminary design and optimization method is established for the purpose of reducing the exit kinetic energy loss to improve the turbine efficiency η ts , and the blade trailing edge geometric parameters for a small scale ORC turbine with working fluid R123 are optimized based on this method. The mathematical optimal solution to minimize the exit kinetic energy is deduced, which can be used to design and optimize the exit shroud/hub radius and exit blade angle. And then, the influence of blade trailing edge geometric parameters on turbine efficiency η ts are analysed and the optimal working ranges of these parameters for the equations are recommended in consideration of working fluid R123. This method is used to modify an existing ORC turbine exit kinetic energy loss from 11.7% to 7%, which indicates the effectiveness of the method. However, the internal passage loss increases from 7.9% to 9.4%, so the only way to consider the influence of geometric parameters on internal passage loss is to give the empirical ranges of these parameters, such as the recommended ranges that the value of γ is at 0.3 to 0.4, and the

Improving exergetic and sustainability parameters of a DI diesel engine using polymer waste dissolved in biodiesel as a novel diesel additive

International Nuclear Information System (INIS)

Aghbashlo, Mortaza; Tabatabaei, Meisam; Mohammadi, Pouya; Pourvosoughi, Navid; Nikbakht, Ali M.; Goli, Sayed Amir Hossein

2015-01-01

Highlights: • Exergy analysis of diesel engine fuelled with various SBE biodiesel–diesel blends containing EPS. • Profound effect of engine speed and load on exergetic performance parameters of diesel engine. • Selection of B5 containing 50 g EPS/L biodiesel as the best mixture. • Potential application of the applied framework for optimizing sustainability index of IC engines. - Abstract: Exergy analysis of a DI diesel engine running on several biodiesel/diesel blends (B5) containing various quantities of expanded polystyrene (EPS) was carried out. Neat diesel and B5 were also investigated during the engine tests. The biodiesel used was produced using waste oil extracted from spend bleaching earth (SBE). The experiments were conducted to assess the effects of fuel type, engine speed, and load on thermal efficiency, exergetic parameters, and sustainability index of the diesel engine. The obtained results revealed that the exergetic parameters strongly depended on the engine speed and load. Generally, increasing engine speed remarkably decreased the exergy efficiency and sustainability index of the diesel engine. However, increasing engine load initially enhanced the exergy efficiency and sustainability index, while its further augmentation did not profoundly affect these parameters. The maximum exergy efficiency and sustainability index of the diesel engine (i.e. 40.21% and 1.67, respectively) were achieved using B5 containing 50 g EPS/L biodiesel. Generally, the approach presented herein could be a promising strategy for energy recovery from polymer waste, emissions reduction, and performance improvement. The findings of the present study also confirmed that exergy analysis could be employed to minimize the irreversibility and losses occurring in modern engines and to enhance the sustainability index of combustion processes.

Density-based penalty parameter optimization on C-SVM.

Science.gov (United States)

Liu, Yun; Lian, Jie; Bartolacci, Michael R; Zeng, Qing-An

2014-01-01

The support vector machine (SVM) is one of the most widely used approaches for data classification and regression. SVM achieves the largest distance between the positive and negative support vectors, which neglects the remote instances away from the SVM interface. In order to avoid a position change of the SVM interface as the result of an error system outlier, C-SVM was implemented to decrease the influences of the system's outliers. Traditional C-SVM holds a uniform parameter C for both positive and negative instances; however, according to the different number proportions and the data distribution, positive and negative instances should be set with different weights for the penalty parameter of the error terms. Therefore, in this paper, we propose density-based penalty parameter optimization of C-SVM. The experiential results indicated that our proposed algorithm has outstanding performance with respect to both precision and recall.

Intermolecular Force Field Parameters Optimization for Computer Simulations of CH4 in ZIF-8

Directory of Open Access Journals (Sweden)

Phannika Kanthima

2016-01-01

Full Text Available The differential evolution (DE algorithm is applied for obtaining the optimized intermolecular interaction parameters between CH4 and 2-methylimidazolate ([C4N2H5]− using quantum binding energies of CH4-[C4N2H5]− complexes. The initial parameters and their upper/lower bounds are obtained from the general AMBER force field. The DE optimized and the AMBER parameters are then used in the molecular dynamics (MD simulations of CH4 molecules in the frameworks of ZIF-8. The results show that the DE parameters are better for representing the quantum interaction energies than the AMBER parameters. The dynamical and structural behaviors obtained from MD simulations with both sets of parameters are also of notable differences.

Efficiency Optimization Control of IPM Synchronous Motor Drives with Online Parameter Estimation

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Sadegh Vaez-Zadeh

2011-04-01

Full Text Available This paper describes an efficiency optimization control method for high performance interior permanent magnet synchronous motor drives with online estimation of motor parameters. The control system is based on an input-output feedback linearization method which provides high performance control and simultaneously ensures the minimization of the motor losses. The controllable electrical loss can be minimized by the optimal control of the armature current vector. It is shown that parameter variations except at near the nominal conditions have undesirable effect on the controller performance. Therefore, a parameter estimation method based on the second method of Lyapunov is presented which guarantees the stability and convergence of the estimation. The extensive simulation results show the feasibility of the proposed controller and observer and their desirable performances.

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

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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.

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

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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.

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

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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.

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.

Application of response surface methodology optimization for the ...

African Journals Online (AJOL)

STORAGESEVER

2009-04-20

Apr 20, 2009 ... of CQAs in tobacco waste were identified as three isomers containing chlorogenic acid (5-caffecylquinic acid ... Key words: Caffeic acid, caffeoylquinic acids (CQAs), hydrolysis reaction parameter optimization, response surface ..... Rosmarinic acid and caffeic acid produce antidepressive-like effect in.

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

International Nuclear Information System (INIS)

Pan, Shu-Yuan; Chang, E.-E.; Kim, Hyunook; Chen, Yi-Hung; Chiang, Pen-Chi

2016-01-01

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 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 2 capture and utilization. However, the evaluation criteria of CaCO 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 3 standards, carbonated BOFS samples and synthetic CaCO 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 3 in BOFS was evaluated using Arrhenius equation and Kissinger equation. The proposed integrated thermal analyses for

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

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.

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

African Journals Online (AJOL)

Optimization of machining parameters of hard porcelain on a CNC machine by Taguchi-and RSM method. ... Journal Home > Vol 10, No 1 (2018) > ... The conduct of experiments was made by employing the Taguchi's L27 Orthogonal array to ...

Flash Cracking Reactor for Waste Plastic Processing

Science.gov (United States)

Timko, Michael T.; Wong, Hsi-Wu; Gonzalez, Lino A.; Broadbelt, Linda; Raviknishan, Vinu

2013-01-01

Conversion of waste plastic to energy is a growing problem that is especially acute in space exploration applications. Moreover, utilization of heavy hydrocarbon resources (wastes, waxes, etc.) as fuels and chemicals will be a growing need in the future. Existing technologies require a trade-off between product selectivity and feedstock conversion. The objective of this work was to maintain high plastic-to-fuel conversion without sacrificing the liquid yield. The developed technology accomplishes this goal with a combined understanding of thermodynamics, reaction rates, and mass transport to achieve high feed conversion without sacrificing product selectivity. The innovation requires a reaction vessel, hydrocarbon feed, gas feed, and pressure and temperature control equipment. Depending on the feedstock and desired product distribution, catalyst can be added. The reactor is heated to the desired tempera ture, pressurized to the desired pressure, and subject to a sweep flow at the optimized superficial velocity. Software developed under this project can be used to determine optimal values for these parameters. Product is vaporized, transferred to a receiver, and cooled to a liquid - a form suitable for long-term storage as a fuel or chemical. An important NASA application is the use of solar energy to convert waste plastic into a form that can be utilized during periods of low solar energy flux. Unlike previous work in this field, this innovation uses thermodynamic, mass transport, and reaction parameters to tune product distribution of pyrolysis cracking. Previous work in this field has used some of these variables, but never all in conjunction for process optimization. This method is useful for municipal waste incinerator operators and gas-to-liquids companies.

Optimization of parameters for the inline-injection system at Brookhaven Accelerator Test Facility

International Nuclear Information System (INIS)

Parsa, Z.; Ko, S.K.

1995-01-01

We present some of our parameter optimization results utilizing code PARMLEA, for the ATF Inline-Injection System. The new solenoid-Gun-Solenoid -- Drift-Linac Scheme would improve the beam quality needed for FEL and other experiments at ATF as compared to the beam quality of the original design injection system. To optimize the gain in the beam quality we have considered various parameters including the accelerating field gradient on the photoathode, the Solenoid field strengths, separation between the gun and entrance to the linac as well as the (type size) initial charge distributions. The effect of the changes in the parameters on the beam emittance is also given

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.

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.

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

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.

Optimization and validation of a chemical process for uranium, mercury and cesium leaching from cemented radioactive wastes

International Nuclear Information System (INIS)

Reynier, N.; Riveros, P.; Lastra, R.; Laviolette, C.; Bouzoubaa, N.; Chapman, M.

2015-01-01

Atomic Energy of Canada Limited (AECL) is developing a treatment and long-term management strategy for a legacy cemented radioactive waste that contains uranium, mercury and fission products. Extracting the uranium would be advantageous for decreasing the waste classification and reducing the cost of long-term management. Consequently, there are safety and economic and environmental incentives for the extraction of uranium, mercury and cesium before subjecting the cemented waste to a stabilization process. The mineralogical analysis of the surrogate cemented waste (SCW) indicated that uranium forms calcium uranate, CaUO 4 , occurring as layers of several millimeters or as grains of 20 μm. Hg is found mostly as large (∼50 μm) and small grains (5-8 μm) of HgO. The chemical leachability of three key elements (U, Hg, and Cs) from a SCW was studied with several leaching materials. The results showed that the most promising approach to leach and recover U, Hg, and Cs is the direct leaching of the SCW with H 2 SO 4 in strong saline media. Operating parameters such as particle size, temperature, pulp density, leaching time, acid and salt concentrations, number of leaching/rinsing step, etc. were optimized to improve key elements solubilization. Sulfuric leaching in saline media of a SCW (U5) containing 1182 ppm of U, 1598 ppm of Hg, and 7.9 ppm of Cs in the optimized conditions allows key elements recovery of 98.5 ± 0.4%, 96.6 ± 0.1%, and 93.8 ± 1.1% of U, Hg, and Cs respectively. This solubilization process was then applied in triplicate to seven other SCW prepared with different cement, liquid ratio and at different aging time and temperature. Concentrated sulfuric acid is added to the slurry until the pH is about 2, which causes the complete degradation of cement and the formation of CaSO 4 . At this pH, the acid consumption is moderate and the formation of amorphous silica gel is avoided. Sulfuric acid is particularly useful because it produces a leachate that

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.

Optimizing the vermicomposting of organic wastes amended with inorganic materials for production of nutrient-rich organic fertilizers: a review.

Science.gov (United States)

Mupambwa, Hupenyu Allan; Mnkeni, Pearson Nyari Stephano

2018-04-01

Vermicomposting is a bio-oxidative process that involves the action of mainly epigeic earthworm species and different micro-organisms to accelerate the biodegradation and stabilization of organic materials. There has been a growing realization that the process of vermicomposting can be used to greatly improve the fertilizer value of different organic materials, thus, creating an opportunity for their enhanced use as organic fertilizers in agriculture. The link between earthworms and micro-organisms creates a window of opportunity to optimize the vermi-degradation process for effective waste biodegradation, stabilization, and nutrient mineralization. In this review, we look at up-to-date research work that has been done on vermicomposting with the intention of highlighting research gaps on how further research can optimize vermi-degradation. Though several researchers have studied the vermicomposting process, critical parameters that drive this earthworm-microbe-driven process which are C/N and C/P ratios; substrate biodegradation fraction, earthworm species, and stocking density have yet to be adequately optimized. This review highlights that optimizing the vermicomposting process of composts amended with nutrient-rich inorganic materials such as fly ash and rock phosphate and inoculated with microbial inoculants can enable the development of commercially acceptable organic fertilizers, thus, improving their utilization in agriculture.

Concurrently adjusting interrelated control parameters to achieve optimal engine performance

Science.gov (United States)

Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna

2015-12-01

Methods and systems for real-time engine control optimization are provided. A value of an engine performance variable is determined, a value of a first operating condition and a value of a second operating condition of a vehicle engine are detected, and initial values for a first engine control parameter and a second engine control parameter are determined based on the detected first operating condition and the detected second operating condition. The initial values for the first engine control parameter and the second engine control parameter are adjusted based on the determined value of the engine performance variable to cause the engine performance variable to approach a target engine performance variable. In order to cause the engine performance variable to approach the target engine performance variable, adjusting the initial value for the first engine control parameter necessitates a corresponding adjustment of the initial value for the second engine control parameter.

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.

An inexact reverse logistics model for municipal solid waste management systems.

Science.gov (United States)

Zhang, Yi Mei; Huang, Guo He; He, Li

2011-03-01

This paper proposed an inexact reverse logistics model for municipal solid waste management systems (IRWM). Waste managers, suppliers, industries and distributors were involved in strategic planning and operational execution through reverse logistics management. All the parameters were assumed to be intervals to quantify the uncertainties in the optimization process and solutions in IRWM. To solve this model, a piecewise interval programming was developed to deal with Min-Min functions in both objectives and constraints. The application of the model was illustrated through a classical municipal solid waste management case. With different cost parameters for landfill and the WTE, two scenarios were analyzed. The IRWM could reflect the dynamic and uncertain characteristics of MSW management systems, and could facilitate the generation of desired management plans. The model could be further advanced through incorporating methods of stochastic or fuzzy parameters into its framework. Design of multi-waste, multi-echelon, multi-uncertainty reverse logistics model for waste management network would also be preferred. Copyright © 2010 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

Miyauchi, T.; Machimura, T.

2013-12-01

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

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.

Multi-objective optimization of organic Rankine cycles for waste heat recovery: Application in an offshore platform

DEFF Research Database (Denmark)

Pierobon, Leonardo; Nguyen, Tuong-Van; Larsen, Ulrik

2013-01-01

This paper aims at finding the optimal design of MW-size organic Rankine cycles by employing the multi-objective optimization with the genetic algorithm as the optimizer. We consider three objective functions: thermal efficiency, total volume of the system and net present value. The optimization...... for acetone. Other promising working fluids are cyclohexane, hexane and isohexane. The present methodology can be utilized in waste heat recovery applications where a compromise between performance, compactness and economic revenue is required. © 2013 Elsevier Ltd. All rights reserved....

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

Science.gov (United States)

Aleksandrova, Irina

2016-01-01

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

Modeling and Optimizing of Producing Recycled PET from Fabrics Waste via Falling Film-Rotating Disk Combined Reactor

Directory of Open Access Journals (Sweden)

Dan Qin

2017-01-01

Full Text Available Recycling and reusing of poly (ethylene terephthalate (PET fabrics waste are essential for reducing serious waste of resources and environmental pollution caused by low utilization rate. The liquid-phase polymerization method has advantages of short process flow, low energy consumption, and low production cost. However, unlike prepolymer, the material characteristics of PET fabrics waste (complex composition, high intrinsic viscosity, and large quality fluctuations make its recycling a technique challenge. In this study, the falling film-rotating disk combined reactor is proposed, and the continuous liquid-phase polymerization is modeled by optimizing and correcting existing models for the final stage of PET polymerization to improve the product quality in plant production. Through modeling and simulation, the weight analysis of indexes closely related to the product quality (intrinsic viscosity, carboxyl end group concentration, and diethylene glycol content was investigated to optimize the production process in order to obtain the desired polymer properties and meet specific product material characteristics. The model could be applied to other PET wastes (e.g., bottles and films and extended to investigate different aspects of the recycling process.

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