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Sample records for designing cost optimal

Design optimization for cost and quality: The robust design approach

Science.gov (United States)

Unal, Resit

1990-01-01

Designing reliable, low cost, and operable space systems has become the key to future space operations. Designing high quality space systems at low cost is an economic and technological challenge to the designer. A systematic and efficient way to meet this challenge is a new method of design optimization for performance, quality, and cost, called Robust Design. Robust Design is an approach for design optimization. It consists of: making system performance insensitive to material and subsystem variation, thus allowing the use of less costly materials and components; making designs less sensitive to the variations in the operating environment, thus improving reliability and reducing operating costs; and using a new structured development process so that engineering time is used most productively. The objective in Robust Design is to select the best combination of controllable design parameters so that the system is most robust to uncontrollable noise factors. The robust design methodology uses a mathematical tool called an orthogonal array, from design of experiments theory, to study a large number of decision variables with a significantly small number of experiments. Robust design also uses a statistical measure of performance, called a signal-to-noise ratio, from electrical control theory, to evaluate the level of performance and the effect of noise factors. The purpose is to investigate the Robust Design methodology for improving quality and cost, demonstrate its application by the use of an example, and suggest its use as an integral part of space system design process.
Cost-Optimal Analysis for Nearly Zero Energy Buildings Design and Optimization: A Critical Review

Directory of Open Access Journals (Sweden)

Maria Ferrara

2018-06-01

Full Text Available Since the introduction of the recast of the EPBD European Directive 2010/31/EU, many studies on the cost-effective feasibility of nearly zero-energy buildings (NZEBs were carried out either by academic research bodies and by national bodies. In particular, the introduction of the cost-optimal methodology has given a strong impulse to research in this field. This paper presents a comprehensive and significant review on scientific works based on the application of cost-optimal analysis applications in Europe since the EPBD recast entered into force, pointing out the differences in the analyzed studies and comparing their outcomes before the new recast of EPBD enters into force in 2018. The analysis is conducted with special regard to the methods used for the energy performance assessment, the global cost calculation, and for the selection of the energy efficiency measures leading to design optimization. A critical discussion about the assumptions on which the studies are based and the resulting gaps between the resulting cost-optimal performance and the zero energy target is provided together with a summary of the resulting cost-optimal set of technologies to be used for cost-optimal NZEB design in different contexts. It is shown that the cost-optimal approach results as an effective method for delineating the future of NZEB design throughout Europe while emerging criticalities and open research issues are presented.
Cost Optimal Design of a Single-Phase Dry Power Transformer

Directory of Open Access Journals (Sweden)

Raju Basak

2015-08-01

Full Text Available The Dry type transformers are preferred to their oil-immersed counterparts for various reasons, particularly because their operation is hazardless. The application of dry transformers was limited to small ratings in the earlier days. But now these are being used for considerably higher ratings. Therefore, their cost-optimal design has gained importance. This paper deals with the design procedure for achieving cost optimal design of a dry type single-phase power transformer of small rating, subject to usual design constraints on efficiency and voltage regulation. The selling cost for the transformer has been taken as the objective function. Only two key variables have been chosen, the turns/volt and the height: width ratio of window, which affects the cost function to high degrees. Other variables have been chosen on the basis of designers’ experience. Copper has been used as conductor material and CRGOS as core material to achieve higher efficiency, lower running cost and compact design. The electrical and magnetic loadings have been kept at their maximum values without violating the design constraints. The optimal solution has been obtained by the method of exhaustive search using nested loops.
Optimal Cost-Analysis and Design of Circular Footings

Directory of Open Access Journals (Sweden)

Prabir K. Basudhar

2012-10-01

Full Text Available The study pertains to the optimal cost-analysis and design of a circular footing subjected to generalized loadings using sequential unconstrained minimization technique (SUMT in conjunction with Powell’s conjugate direction method for multidimensional search and quadratic interpolation method for one dimensional minimization. The cost of the footing is minimized satisfying all the structural and geotechnical engineering design considerations. As extended penalty function method has been used to convert the constrained problem into an unconstrained one, the developed technique is capable of handling both feasible and infeasible initial design vector. The net saving in cost starting from the best possible manual design ranges from 10 to 20 %. For all practical purposes, the optimum cost is independent of the initial design point. It was observed that for better convergence, the transition parameter  should be chosen at least 100 times the initial penalty parameter kr .
Cost Optimal System Identification Experiment Design

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning

A structural system identification experiment design method is formulated in the light of decision theory, structural reliability theory and optimization theory. The experiment design is based on a preposterior analysis, well-known from the classical decision theory. I.e. the decisions concerning...... reflecting the cost of the experiment and the value of obtained additional information. An example concerning design of an experiment for parametric identification of a single degree of freedom structural system shows the applicability of the experiment design method....... the experiment design are not based on obtained experimental data. Instead the decisions are based on the expected experimental data assumed to be obtained from the measurements, estimated based on prior information and engineering judgement. The design method provides a system identification experiment design...
Affordable Design: A Methodolgy to Implement Process-Based Manufacturing Cost into the Traditional Performance-Focused Multidisciplinary Design Optimization

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Bao, Han P.; Samareh, J. A.

2000-01-01

The primary objective of this paper is to demonstrate the use of process-based manufacturing and assembly cost models in a traditional performance-focused multidisciplinary design and optimization process. The use of automated cost-performance analysis is an enabling technology that could bring realistic processbased manufacturing and assembly cost into multidisciplinary design and optimization. In this paper, we present a new methodology for incorporating process costing into a standard multidisciplinary design optimization process. Material, manufacturing processes, and assembly processes costs then could be used as the objective function for the optimization method. A case study involving forty-six different configurations of a simple wing is presented, indicating that a design based on performance criteria alone may not necessarily be the most affordable as far as manufacturing and assembly cost is concerned.
Derating design for optimizing reliability and cost with an application to liquid rocket engines

International Nuclear Information System (INIS)

Kim, Kyungmee O.; Roh, Taeseong; Lee, Jae-Woo; Zuo, Ming J.

2016-01-01

Derating is the operation of an item at a stress that is lower than its rated design value. Previous research has indicated that reliability can be increased from operational derating. In order to derate an item in field operation, however, an engineer must rate the design of the item at a stress level higher than the operational stress level, which increases the item's nominal failure rate and development costs. At present, there is no model available to quantify the cost and reliability that considers the design uprating as well as the operational derating. In this paper, we establish the reliability expression in terms of the derating level assuming that the nominal failure rate is constant with time for a fixed rated design value. The total development cost is expressed in terms of the rated design value and the number of tests necessary to demonstrate the reliability requirement. The properties of the optimal derating level are explained for maximizing the reliability or for minimizing the cost. As an example, the proposed model is applied to the design of liquid rocket engines. - Highlights: • Modeled the effect of derating design on the reliability and the development cost. • Discovered that derating design may reduce the cost of reliability demonstration test. • Optimized the derating design parameter for reliability maximization or cost minimization.
Designing the optimal bit: balancing energetic cost, speed and reliability.

Science.gov (United States)

Deshpande, Abhishek; Gopalkrishnan, Manoj; Ouldridge, Thomas E; Jones, Nick S

2017-08-01

We consider the challenge of operating a reliable bit that can be rapidly erased. We find that both erasing and reliability times are non-monotonic in the underlying friction, leading to a trade-off between erasing speed and bit reliability. Fast erasure is possible at the expense of low reliability at moderate friction, and high reliability comes at the expense of slow erasure in the underdamped and overdamped limits. Within a given class of bit parameters and control strategies, we define 'optimal' designs of bits that meet the desired reliability and erasing time requirements with the lowest operational work cost. We find that optimal designs always saturate the bound on the erasing time requirement, but can exceed the required reliability time if critically damped. The non-trivial geometry of the reliability and erasing time scales allows us to exclude large regions of parameter space as suboptimal. We find that optimal designs are either critically damped or close to critical damping under the erasing procedure.
Optimal Design and Operation of In-Situ Chemical Oxidation Using Stochastic Cost Optimization Toolkit

Science.gov (United States)

Kim, U.; Parker, J.; Borden, R. C.

2014-12-01

In-situ chemical oxidation (ISCO) has been applied at many dense non-aqueous phase liquid (DNAPL) contaminated sites. A stirred reactor-type model was developed that considers DNAPL dissolution using a field-scale mass transfer function, instantaneous reaction of oxidant with aqueous and adsorbed contaminant and with readily oxidizable natural oxygen demand ("fast NOD"), and second-order kinetic reactions with "slow NOD." DNAPL dissolution enhancement as a function of oxidant concentration and inhibition due to manganese dioxide precipitation during permanganate injection are included in the model. The DNAPL source area is divided into multiple treatment zones with different areas, depths, and contaminant masses based on site characterization data. The performance model is coupled with a cost module that involves a set of unit costs representing specific fixed and operating costs. Monitoring of groundwater and/or soil concentrations in each treatment zone is employed to assess ISCO performance and make real-time decisions on oxidant reinjection or ISCO termination. Key ISCO design variables include the oxidant concentration to be injected, time to begin performance monitoring, groundwater and/or soil contaminant concentrations to trigger reinjection or terminate ISCO, number of monitoring wells or geoprobe locations per treatment zone, number of samples per sampling event and location, and monitoring frequency. Design variables for each treatment zone may be optimized to minimize expected cost over a set of Monte Carlo simulations that consider uncertainty in site parameters. The model is incorporated in the Stochastic Cost Optimization Toolkit (SCOToolkit) program, which couples the ISCO model with a dissolved plume transport model and with modules for other remediation strategies. An example problem is presented that illustrates design tradeoffs required to deal with characterization and monitoring uncertainty. Monitoring soil concentration changes during ISCO
Designer's unified cost model

Science.gov (United States)

Freeman, William T.; Ilcewicz, L. B.; Swanson, G. D.; Gutowski, T.

1992-01-01

A conceptual and preliminary designers' cost prediction model has been initiated. The model will provide a technically sound method for evaluating the relative cost of different composite structural designs, fabrication processes, and assembly methods that can be compared to equivalent metallic parts or assemblies. The feasibility of developing cost prediction software in a modular form for interfacing with state of the art preliminary design tools and computer aided design programs is being evaluated. The goal of this task is to establish theoretical cost functions that relate geometric design features to summed material cost and labor content in terms of process mechanics and physics. The output of the designers' present analytical tools will be input for the designers' cost prediction model to provide the designer with a data base and deterministic cost methodology that allows one to trade and synthesize designs with both cost and weight as objective functions for optimization. The approach, goals, plans, and progress is presented for development of COSTADE (Cost Optimization Software for Transport Aircraft Design Evaluation).
Taguchi Approach to Design Optimization for Quality and Cost: An Overview

Science.gov (United States)

Unal, Resit; Dean, Edwin B.

1990-01-01

Calibrations to existing cost of doing business in space indicate that to establish human presence on the Moon and Mars with the Space Exploration Initiative (SEI) will require resources, felt by many, to be more than the national budget can afford. In order for SEI to succeed, we must actually design and build space systems at lower cost this time, even with tremendous increases in quality and performance requirements, such as extremely high reliability. This implies that both government and industry must change the way they do business. Therefore, new philosophy and technology must be employed to design and produce reliable, high quality space systems at low cost. In recognizing the need to reduce cost and improve quality and productivity, Department of Defense (DoD) and National Aeronautics and Space Administration (NASA) have initiated Total Quality Management (TQM). TQM is a revolutionary management strategy in quality assurance and cost reduction. TQM requires complete management commitment, employee involvement, and use of statistical tools. The quality engineering methods of Dr. Taguchi, employing design of experiments (DOE), is one of the most important statistical tools of TQM for designing high quality systems at reduced cost. Taguchi methods provide an efficient and systematic way to optimize designs for performance, quality, and cost. Taguchi methods have been used successfully in Japan and the United States in designing reliable, high quality products at low cost in such areas as automobiles and consumer electronics. However, these methods are just beginning to see application in the aerospace industry. The purpose of this paper is to present an overview of the Taguchi methods for improving quality and reducing cost, describe the current state of applications and its role in identifying cost sensitive design parameters.
Optimal Network-Topology Design

Science.gov (United States)

Li, Victor O. K.; Yuen, Joseph H.; Hou, Ting-Chao; Lam, Yuen Fung

1987-01-01

Candidate network designs tested for acceptability and cost. Optimal Network Topology Design computer program developed as part of study on topology design and analysis of performance of Space Station Information System (SSIS) network. Uses efficient algorithm to generate candidate network designs consisting of subsets of set of all network components, in increasing order of total costs and checks each design to see whether it forms acceptable network. Technique gives true cost-optimal network and particularly useful when network has many constraints and not too many components. Program written in PASCAL.
Designers' unified cost model

Science.gov (United States)

Freeman, W.; Ilcewicz, L.; Swanson, G.; Gutowski, T.

1992-01-01

The Structures Technology Program Office (STPO) at NASA LaRC has initiated development of a conceptual and preliminary designers' cost prediction model. The model will provide a technically sound method for evaluating the relative cost of different composite structural designs, fabrication processes, and assembly methods that can be compared to equivalent metallic parts or assemblies. The feasibility of developing cost prediction software in a modular form for interfacing with state-of-the-art preliminary design tools and computer aided design programs is being evaluated. The goal of this task is to establish theoretical cost functions that relate geometric design features to summed material cost and labor content in terms of process mechanics and physics. The output of the designers' present analytical tools will be input for the designers' cost prediction model to provide the designer with a database and deterministic cost methodology that allows one to trade and synthesize designs with both cost and weight as objective functions for optimization. This paper presents the team members, approach, goals, plans, and progress to date for development of COSTADE (Cost Optimization Software for Transport Aircraft Design Evaluation).
Toward a new spacecraft optimal design lifetime? Impact of marginal cost of durability and reduced launch price

Science.gov (United States)

Snelgrove, Kailah B.; Saleh, Joseph Homer

2016-10-01

The average design lifetime of satellites continues to increase, in part due to the expectation that the satellite cost per operational day decreases monotonically with increased design lifetime. In this work, we challenge this expectation by revisiting the durability choice problem for spacecraft in the face of reduced launch price and under various cost of durability models. We first provide a brief overview of the economic thought on durability and highlight its limitations as they pertain to our problem (e.g., the assumption of zero marginal cost of durability). We then investigate the merging influence of spacecraft cost of durability and launch price, and we identify conditions that give rise cost-optimal design lifetimes that are shorter than the longest lifetime technically achievable. For example, we find that high costs of durability favor short design lifetimes, and that under these conditions the optimal choice is relatively robust to reduction in launch prices. By contrast, lower costs of durability favor longer design lifetimes, and the optimal choice is highly sensitive to reduction in launch price. In both cases, reduction in launch prices translates into reduction of the optimal design lifetime. Our results identify a number of situations for which satellite operators would be better served by spacecraft with shorter design lifetimes. Beyond cost issues and repeat purchases, other implications of long design lifetime include the increased risk of technological slowdown given the lower frequency of purchases and technology refresh, and the increased risk for satellite operators that the spacecraft will be technologically obsolete before the end of its life (with the corollary of loss of value and competitive advantage). We conclude with the recommendation that, should pressure to extend spacecraft design lifetime continue, satellite manufacturers should explore opportunities to lease their spacecraft to operators, or to take a stake in the ownership
Multi-objective optimization approach for cost management during product design at the conceptual phase

Science.gov (United States)

Durga Prasad, K. G.; Venkata Subbaiah, K.; Narayana Rao, K.

2014-03-01

The effective cost management during the conceptual design phase of a product is essential to develop a product with minimum cost and desired quality. The integration of the methodologies of quality function deployment (QFD), value engineering (VE) and target costing (TC) could be applied to the continuous improvement of any product during product development. To optimize customer satisfaction and total cost of a product, a mathematical model is established in this paper. This model integrates QFD, VE and TC under multi-objective optimization frame work. A case study on domestic refrigerator is presented to show the performance of the proposed model. Goal programming is adopted to attain the goals of maximum customer satisfaction and minimum cost of the product.
Optimal cost-effective designs of Phase II proof of concept trials and associated go-no go decisions.

Science.gov (United States)

Chen, Cong; Beckman, Robert A

2009-01-01

This manuscript discusses optimal cost-effective designs for Phase II proof of concept (PoC) trials. Unlike a confirmatory registration trial, a PoC trial is exploratory in nature, and sponsors of such trials have the liberty to choose the type I error rate and the power. The decision is largely driven by the perceived probability of having a truly active treatment per patient exposure (a surrogate measure to development cost), which is naturally captured in an efficiency score to be defined in this manuscript. Optimization of the score function leads to type I error rate and power (and therefore sample size) for the trial that is most cost-effective. This in turn leads to cost-effective go-no go criteria for development decisions. The idea is applied to derive optimal trial-level, program-level, and franchise-level design strategies. The study is not meant to provide any general conclusion because the settings used are largely simplified for illustrative purposes. However, through the examples provided herein, a reader should be able to gain useful insight into these design problems and apply them to the design of their own PoC trials.
Process Cost Modeling for Multi-Disciplinary Design Optimization

Science.gov (United States)

Bao, Han P.; Freeman, William (Technical Monitor)

2002-01-01

For early design concepts, the conventional approach to cost is normally some kind of parametric weight-based cost model. There is now ample evidence that this approach can be misleading and inaccurate. By the nature of its development, a parametric cost model requires historical data and is valid only if the new design is analogous to those for which the model was derived. Advanced aerospace vehicles have no historical production data and are nowhere near the vehicles of the past. Using an existing weight-based cost model would only lead to errors and distortions of the true production cost. This report outlines the development of a process-based cost model in which the physical elements of the vehicle are costed according to a first-order dynamics model. This theoretical cost model, first advocated by early work at MIT, has been expanded to cover the basic structures of an advanced aerospace vehicle. Elemental costs based on the geometry of the design can be summed up to provide an overall estimation of the total production cost for a design configuration. This capability to directly link any design configuration to realistic cost estimation is a key requirement for high payoff MDO problems. Another important consideration in this report is the handling of part or product complexity. Here the concept of cost modulus is introduced to take into account variability due to different materials, sizes, shapes, precision of fabrication, and equipment requirements. The most important implication of the development of the proposed process-based cost model is that different design configurations can now be quickly related to their cost estimates in a seamless calculation process easily implemented on any spreadsheet tool. In successive sections, the report addresses the issues of cost modeling as follows. First, an introduction is presented to provide the background for the research work. Next, a quick review of cost estimation techniques is made with the intention to
Optimal cost design of base-isolated pool structures for the storage of nuclear spent fuel

International Nuclear Information System (INIS)

Ko, H. M.; Park, K. S.; Song, J. H.

1999-01-01

A method of cost-effectiveness evaluation for seismic isolated pool structures is presented. Input ground motion is modeled as spectral density function compatible with response spectrum for combination of acceleration coefficient and site coefficient. Interaction effects between flexible walls and contained fluid are considered in the form of added mass matrix. Wall thickness and isolator stiffness are adopted as design variables for optimization. Transfer function vector of the structure-isolator system is derived from the equation of motion. Spectral analysis method based on random vibration theories is used for the calculation of failure probability. The exemplifying designs and analyses show that cost-effectiveness of isolated pool structure is relatively high in low-moderate seismic region and stiff soil condition. Sensitiveness of optimal design variables to assumed damage scales is relatively low in such region
Life-cycle cost assessment of optimally designed reinforced concrete buildings under seismic actions

International Nuclear Information System (INIS)

Mitropoulou, Chara Ch.; Lagaros, Nikos D.; Papadrakakis, Manolis

2011-01-01

Life-cycle cost analysis (LCCA) is an assessment tool for studying the performance of systems in many fields of engineering. In earthquake engineering LCCA demands the calculation of the cost components that are related to the performance of the structure in multiple earthquake hazard levels. Incremental static and dynamic analyses are two procedures that can be used for estimating the seismic capacity of a structural system and can therefore be incorporated into the LCCA methodology. In this work the effect of the analysis procedure, the number of seismic records imposed, the performance criterion used and the structural type (regular or irregular) is investigated, on the life-cycle cost analysis of 3D reinforced concrete structures. Furthermore, the influence of uncertainties on the seismic response of structural systems and their impact on LCCA is examined. The uncertainty on the material properties, the cross-section dimensions and the record-incident angle is taking into account with the incorporation of the Latin hypercube sampling method into the incremental dynamic analysis procedure. In addition, the LCCA methodology is used as an assessment tool for the designs obtained by means of prescriptive and performance-based optimum design methodologies. The first one is obtained from a single-objective optimization problem, where the initial construction cost was the objective to be minimized, while the second one as a two-objective optimization problem where the life-cycle cost was the additional objective also to be minimized.
Divertor design through shape optimization

International Nuclear Information System (INIS)

Dekeyser, W.; Baelmans, M.; Reiter, D.

2012-01-01

Due to the conflicting requirements, complex physical processes and large number of design variables, divertor design for next step fusion reactors is a challenging problem, often relying on large numbers of computationally expensive numerical simulations. In this paper, we attempt to partially automate the design process by solving an appropriate shape optimization problem. Design requirements are incorporated in a cost functional which measures the performance of a certain design. By means of changes in the divertor shape, which in turn lead to changes in the plasma state, this cost functional can be minimized. Using advanced adjoint methods, optimal solutions are computed very efficiently. The approach is illustrated by designing divertor targets for optimal power load spreading, using a simplified edge plasma model (copyright 2012 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

Optimization methods applied to hybrid vehicle design

Science.gov (United States)

Donoghue, J. F.; Burghart, J. H.

1983-01-01

The use of optimization methods as an effective design tool in the design of hybrid vehicle propulsion systems is demonstrated. Optimization techniques were used to select values for three design parameters (battery weight, heat engine power rating and power split between the two on-board energy sources) such that various measures of vehicle performance (acquisition cost, life cycle cost and petroleum consumption) were optimized. The apporach produced designs which were often significant improvements over hybrid designs already reported on in the literature. The principal conclusions are as follows. First, it was found that the strategy used to split the required power between the two on-board energy sources can have a significant effect on life cycle cost and petroleum consumption. Second, the optimization program should be constructed so that performance measures and design variables can be easily changed. Third, the vehicle simulation program has a significant effect on the computer run time of the overall optimization program; run time can be significantly reduced by proper design of the types of trips the vehicle takes in a one year period. Fourth, care must be taken in designing the cost and constraint expressions which are used in the optimization so that they are relatively smooth functions of the design variables. Fifth, proper handling of constraints on battery weight and heat engine rating, variables which must be large enough to meet power demands, is particularly important for the success of an optimization study. Finally, the principal conclusion is that optimization methods provide a practical tool for carrying out the design of a hybrid vehicle propulsion system.
Fermilab D-0 Experimental Facility: Energy conservation report and mechanical systems design optimization and cost analysis study

International Nuclear Information System (INIS)

Krstulovich, S.F.

1987-01-01

This report is developed as part of the Fermilab D-0 Experimental Facility Project Title II Design Documentation Update. As such, it concentrates primarily on HVAC mechanical systems design optimization and cost analysis
Optimal design and allocation of electrified vehicles and dedicated charging infrastructure for minimum life cycle greenhouse gas emissions and cost

International Nuclear Information System (INIS)

Traut, Elizabeth; Hendrickson, Chris; Klampfl, Erica; Liu, Yimin; Michalek, Jeremy J.

2012-01-01

Electrified vehicles can reduce greenhouse gas (GHG) emissions by shifting energy demand from gasoline to electricity. GHG reduction potential depends on vehicle design, adoption, driving and charging patterns, charging infrastructure, and electricity generation mix. We construct an optimization model to study these factors by determining optimal design of conventional vehicles, hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs) with optimal allocation of vehicle designs and dedicated workplace charging infrastructure in the fleet for minimum life cycle cost or GHG emissions over a range of scenarios. We focus on vehicles with similar body size and acceleration to a Toyota Prius under government 5-cycle driving conditions. We find that under the current US grid mix, PHEVs offer only small GHG emissions reductions compared to HEVs, and workplace charging is insignificant. With grid decarbonization, PHEVs and BEVs offer substantial GHG emissions reductions, and workplace charging provides additional benefits. HEVs are optimal or near-optimal for minimum cost in most scenarios. High gas prices and low vehicle and battery costs are the major drivers for PHEVs and BEVs to enter and dominate the cost-optimal fleet. Carbon prices have little effect. Cost and range restrictions limit penetration of BEVs. - Highlights: ► We pose an MINLP model to minimize cost and GHG emissions of electrified vehicles. ► We design PHEVs and BEVs and assign vehicles and charging infrastructure in US fleet. ► Under US grid mix, PEVs provide minor GHG reductions and work chargers do little. ► HEVs are robust; PEVs and work charging potential improve with a decarbonized grid. ► We quantify factors needed for PEVs to enter and dominate the optimal fleet.
Multi-objective optimization of aircraft design for emission and cost reductions

Directory of Open Access Journals (Sweden)

Wang Yu

2014-02-01

Full Text Available Pollutant gases emitted from the civil jet are doing more and more harm to the environment with the rapid development of the global commercial aviation transport. Low environmental impact has become a new requirement for aircraft design. In this paper, estimation method for emission in aircraft conceptual design stage is improved based on the International Civil Aviation Organization (ICAO aircraft engine emissions databank and the polynomial curve fitting methods. The greenhouse gas emission (CO2 equivalent per seat per kilometer is proposed to measure the emissions. An approximate sensitive analysis and a multi-objective optimization of aircraft design for tradeoff between greenhouse effect and direct operating cost (DOC are performed with five geometry variables of wing configuration and two flight operational parameters. The results indicate that reducing the cruise altitude and Mach number may result in a decrease of the greenhouse effect but an increase of DOC. And the two flight operational parameters have more effects on the emissions than the wing configuration. The Pareto-optimal front shows that a decrease of 29.8% in DOC is attained at the expense of an increase of 10.8% in greenhouse gases.
Near Zero Energy House (NZEH) Design Optimization to Improve Life Cycle Cost Performance Using Genetic Algorithm

Science.gov (United States)

Latief, Y.; Berawi, M. A.; Koesalamwardi, A. B.; Supriadi, L. S. R.

2018-03-01

Near Zero Energy House (NZEH) is a housing building that provides energy efficiency by using renewable energy technologies and passive house design. Currently, the costs for NZEH are quite expensive due to the high costs of the equipment and materials for solar panel, insulation, fenestration and other renewable energy technology. Therefore, a study to obtain the optimum design of a NZEH is necessary. The aim of the optimum design is achieving an economical life cycle cost performance of the NZEH. One of the optimization methods that could be utilized is Genetic Algorithm. It provides the method to obtain the optimum design based on the combinations of NZEH variable designs. This paper discusses the study to identify the optimum design of a NZEH that provides an optimum life cycle cost performance using Genetic Algorithm. In this study, an experiment through extensive design simulations of a one-level house model was conducted. As a result, the study provide the optimum design from combinations of NZEH variable designs, which are building orientation, window to wall ratio, and glazing types that would maximize the energy generated by photovoltaic panel. Hence, the design would support an optimum life cycle cost performance of the house.
Optimization design of blade shapes for wind turbines

DEFF Research Database (Denmark)

Chen, Jin; Wang, Xudong; Shen, Wen Zhong

2010-01-01

For the optimization design of wind turbines, the new normal and tangential induced factors of wind turbines are given considering the tip loss of the normal and tangential forces based on the blade element momentum theory and traditional aerodynamic model. The cost model of the wind turbines...... and the optimization design model are developed. In the optimization model, the objective is the minimum cost of energy and the design variables are the chord length, twist angle and the relative thickness. Finally, the optimization is carried out for a 2 MW blade by using this optimization design model....... The performance of blades is validated through the comparison and analysis of the results. The reduced cost shows that the optimization model is good enough for the design of wind turbines. The results give a proof for the design and research on the blades of large scale wind turbines and also establish...
Optimizing cost-efficiency in mean exposure assessment--cost functions reconsidered.

Science.gov (United States)

Mathiassen, Svend Erik; Bolin, Kristian

2011-05-21

for informed design of exposure assessment strategies, provided that data are available on exposure variability and the costs of collecting and processing data. The present shortage of empirical evidence on costs and appropriate cost functions however impedes general conclusions on optimal exposure measurement strategies in different epidemiologic scenarios.
On cost-effective communication network designing

Science.gov (United States)

Zhang, Guo-Qiang

2010-02-01

How to efficiently design a communication network is a paramount task for network designing and engineering. It is, however, not a single objective optimization process as perceived by most previous researches, i.e., to maximize its transmission capacity, but a multi-objective optimization process, with lowering its cost to be another important objective. These two objectives are often contradictive in that optimizing one objective may deteriorate the other. After a deep investigation of the impact that network topology, node capability scheme and routing algorithm as well as their interplays have on the two objectives, this letter presents a systematic approach to achieve a cost-effective design by carefully choosing the three designing aspects. Only when routing algorithm and node capability scheme are elegantly chosen can BA-like scale-free networks have the potential of achieving good tradeoff between the two objectives. Random networks, on the other hand, have the built-in character for a cost-effective design, especially when other aspects cannot be determined beforehand.
Optimized design of low energy buildings

DEFF Research Database (Denmark)

Rudbeck, Claus Christian; Esbensen, Peter Kjær; Svendsen, Sv Aa Højgaard

1999-01-01

concern which can be seen during the construction of new buildings. People want energy-friendly solutions, but they should be economical optimized. An exonomical optimized building design with respect to energy consumption is the design with the lowest total cost (investment plus operational cost over its...... to evaluate different separate solutions when they interact in the building.When trying to optimize several parameters there is a need for a method, which will show the correct price-performance of each part of a building under design. The problem with not having such a method will first be showed...
Flat-plate photovoltaic array design optimization

Science.gov (United States)

Ross, R. G., Jr.

1980-01-01

An analysis is presented which integrates the results of specific studies in the areas of photovoltaic structural design optimization, optimization of array series/parallel circuit design, thermal design optimization, and optimization of environmental protection features. The analysis is based on minimizing the total photovoltaic system life-cycle energy cost including repair and replacement of failed cells and modules. This approach is shown to be a useful technique for array optimization, particularly when time-dependent parameters such as array degradation and maintenance are involved.
Site-specific design optimization of wind turbines

DEFF Research Database (Denmark)

Fuglsang, P.; Bak, C.; Schepers, J.G.

2002-01-01

This article reports results from a European project, where site characteristics were incorporated into the design process of wind turbines, to enable site-specific design. Two wind turbines of different concept were investigated at six different sites comprising normal flat terrain, offshore...... and complex terrain wind farms. Design tools based on numerical optimization and aeroelastic calculations were combined with a cost model to allow optimization for minimum cost of energy. Different scenarios were optimized ranging from modifications of selected individual components to the complete design...... of a new wind turbine. Both annual energy yield and design-determining loads depended on site characteristics, and this represented a potential for site-specific design. The maximum variation in annual energy yield was 37% and the maximum variation in blade root fatigue loads was 62%. Optimized site...
LIFE-CYCLE COST MODEL AND DESIGN OPTIMIZATION OF BASE ISOLATED BUILDING STRUCTURES

Directory of Open Access Journals (Sweden)

Chara C. Mitropoulou

2016-11-01

Full Text Available Design of economic structures adequately resistant to withstand during their service life, without catastrophic failures, all possible loading conditions and to absorb the induced seismic energy in a controlled fashion, has been the subject of intensive research so far. Modern buildings usually contain extremely sensitive and costly equipment that are vital in business, commerce, education and/or health care. The building contents frequently are more valuable than the buildings them-selves. Furthermore, hospitals, communication and emergency centres, police and fire stations must be operational when needed most: immediately after an earthquake. Conventional con-struction can cause very high floor accelerations in stiff buildings and large interstorey drifts in flexible structures. These two factors cause difficulties in insuring the safety of both building and its contents. For this reason base-isolated structures are considered as an efficient alternative design practice to the conventional fixed-base one. In this study a systematic assessment of op-timized fixed and base-isolated reinforced concrete buildings is presented in terms of their initial and total cost taking into account the life-cycle cost of the structures.
Equipment cost optimization

International Nuclear Information System (INIS)

Ribeiro, E.M.; Farias, M.A.; Dreyer, S.R.B.

1995-01-01

Considering the importance of the cost of material and equipment in the overall cost profile of an oil company, which in the case of Petrobras, represents approximately 23% of the total operational cost or 10% of the sales, an organization for the optimization of such costs has been established within Petrobras. Programs are developed aiming at: optimization of life-cycle cost of material and equipment; optimization of industrial processes costs through material development. This paper describes the methodology used in the management of the development programs and presents some examples of concluded and ongoing programs, which are conducted in permanent cooperation with suppliers, technical laboratories and research institutions and have been showing relevant results
Reliability-Based Optimal Design for Very Large Floating Structure

Institute of Scientific and Technical Information of China (English)

ZHANG Shu-hua(张淑华); FUJIKUBO Masahiko

2003-01-01

Costs and losses induced by possible future extreme environmental conditions and difficulties in repairing post-yielding damage strongly suggest the need for proper consideration in design rather than just life loss prevention. This can be addressed through the development of design methodology that balances the initial cost of the very large floating structure (VLFS) against the expected potential losses resulting from future extreme wave-induced structural damage. Here, the development of a methodology for determining optimal, cost-effective design will be presented and applied to a VLFS located in the Tokyo bay. Optimal design criteria are determined based on the total expected life-cycle cost and acceptable damage probability and curvature of the structure, and a set of sizes of the structure are obtained. The methodology and applications require expressions of the initial cost and the expected life-cycle damage cost as functions of the optimal design variables. This study includes the methodology, total life-cycle cost function, structural damage modeling, and reliability analysis.
Cost Overrun Optimism: Fact or Fiction

Science.gov (United States)

2016-02-29

Base, OH. Homgren, C. T. (1990). In G. Foster (Ed.), Cost accounting : A managerial emphasis (7th ed.). Englewood Cliffs, NJ: Prentice Hall. Morrison... Accounting Office. Gansler, J. S. (1989). Affording defense. Cambridge, MA: The MIT Press. Heise, S. R. (1991). A review of cost performance index...Image designed by Diane Fleischer Cost Overrun Optimism: FACT or FICTION? Maj David D. Christensen, USAF Program managers are advocates by
Design optimization of jacket structures for mass production

DEFF Research Database (Denmark)

Sandal, Kasper

This thesis presents models and applications for structural optimization of jacket structures for offshore wind turbines. The motivation is that automatic design procedures can be used to obtain more cost efficient designs, and thus reduce the levelized cost of energy from offshore wind. A struct......This thesis presents models and applications for structural optimization of jacket structures for offshore wind turbines. The motivation is that automatic design procedures can be used to obtain more cost efficient designs, and thus reduce the levelized cost of energy from offshore wind....... A structural finite element model is developed specifically for the analysis and optimization of jacket structures. The model uses Timoshenko beam elements, and assumes thin walled tubular beams and a linear elastic structural response. The finite element model is implemented in a Matlab package called JADOP...... (Jacket Design Optimization), and the static and dynamic structural response is verified with the commercial finite element software Abaqus. A parametric mesh of the offshore wind turbine structure makes it relatively easy to represent various structures from the literature, as well as exploring...
Optimization design of solar enhanced natural draft dry cooling tower

International Nuclear Information System (INIS)

Zou, Zheng; Guan, Zhiqiang; Gurgenci, Hal

2013-01-01

Highlights: • We proposed a cost model for solar enhanced natural draft dry cooling tower. • We proposed an optimization scheme for this new cooling system. • We optimally designed one for a 50 MW EGS geothermal plant as a demonstration. • Results proved its economic advantages for EGS geothermal application. - Abstract: This paper proposed an optimization scheme for solar enhanced natural draft dry cooling tower design, in which a detailed cost model was proposed including capital, labour, maintenance and operation costs of each component. Based on the developed cost model, the optimal design option can be identified in terms of the relatively lower annual cost and the relatively higher total extra income over the Solar Enhanced Natural Draft Dry Cooling Tower (SENDDCT) lifetime. As a case study, a SENDDCT was optimally designed to meet the cooling demand for a 50 MW geothermal power plant with Engineered Geothermal System (EGS) technology. The results showed that the optimized SENDDCT not only has better cooling performance during the daytime but also is a cost effective option for EGS geothermal power plants
Optimal Design of Modern Transformerless PV Inverter Topologies

DEFF Research Database (Denmark)

Saridakis, Stefanos; Koutroulis, Eftichios; Blaabjerg, Frede

2013-01-01

the operational lifetime period of the PV installation, is also considered in the optimization process. According to the results of the proposed design method, different optimal values of the PV inverter design variables are derived for each PV inverter topology and installation site. The H5, H6, neutral point...... clamped, active-neutral point clamped and conergy-NPC PV inverters designed using the proposed optimization process feature lower levelized cost of generated electricity and lifetime cost, longer mean time between failures and inject more PV-generated energy into the electric grid than their nonoptimized......The design optimization of H5, H6, neutral point clamped, active-neutral point clamped, and conergy-NPC transformerless photovoltaic (PV) inverters is presented in this paper. The components reliability in terms of the corresponding malfunctions, affecting the PV inverter maintenance cost during...
Cost optimization of load carrying thin-walled precast high performance concrete sandwich panels

DEFF Research Database (Denmark)

Hodicky, Kamil; Hansen, Sanne; Hulin, Thomas

2015-01-01

and HPCSP’s geometrical parameters as well as on material cost function in the HPCSP design. Cost functions are presented for High Performance Concrete (HPC), insulation layer, reinforcement and include labour-related costs. The present study reports the economic data corresponding to specific manufacturing......The paper describes a procedure to find the structurally and thermally efficient design of load-carrying thin-walled precast High Performance Concrete Sandwich Panels (HPCSP) with an optimal economical solution. A systematic optimization approach is based on the selection of material’s performances....... The solution of the optimization problem is performed in the computer package software Matlab® with SQPlab package and integrates the processes of HPCSP design, quantity take-off and cost estimation. The proposed optimization process outcomes in complex HPCSP design proposals to achieve minimum cost of HPCSP....
GASIFICATION PLANT COST AND PERFORMANCE OPTIMIZATION

Energy Technology Data Exchange (ETDEWEB)

Samuel S. Tam

2002-05-01

The goal of this series of design and estimating efforts was to start from the as-built design and actual operating data from the DOE sponsored Wabash River Coal Gasification Repowering Project and to develop optimized designs for several coal and petroleum coke IGCC power and coproduction projects. First, the team developed a design for a grass-roots plant equivalent to the Wabash River Coal Gasification Repowering Project to provide a starting point and a detailed mid-year 2000 cost estimate based on the actual as-built plant design and subsequent modifications (Subtask 1.1). This unoptimized plant has a thermal efficiency of 38.3% (HHV) and a mid-year 2000 EPC cost of 1,681 $/kW. This design was enlarged and modified to become a Petroleum Coke IGCC Coproduction Plant (Subtask 1.2) that produces hydrogen, industrial grade steam, and fuel gas for an adjacent Gulf Coast petroleum refinery in addition to export power. A structured Value Improving Practices (VIP) approach was applied to reduce costs and improve performance. The base case (Subtask 1.3) Optimized Petroleum Coke IGCC Coproduction Plant increased the power output by 16% and reduced the plant cost by 23%. The study looked at several options for gasifier sparing to enhance availability. Subtask 1.9 produced a detailed report on this availability analyses study. The Subtask 1.3 Next Plant, which retains the preferred spare gasification train approach, only reduced the cost by about 21%, but it has the highest availability (94.6%) and produces power at 30 $/MW-hr (at a 12% ROI). Thus, such a coke-fueled IGCC coproduction plant could fill a near term niche market. In all cases, the emissions performance of these plants is superior to the Wabash River project. Subtasks 1.5A and B developed designs for single-train coal and coke-fueled power plants. This side-by-side comparison of these plants, which contain the Subtask 1.3 VIP enhancements, showed their similarity both in design and cost (1,318 $/kW for the

Interactive Reliability-Based Optimal Design

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Thoft-Christensen, Palle; Siemaszko, A.

1994-01-01

Interactive design/optimization of large, complex structural systems is considered. The objective function is assumed to model the expected costs. The constraints are reliability-based and/or related to deterministic code requirements. Solution of this optimization problem is divided in four main...... tasks, namely finite element analyses, sensitivity analyses, reliability analyses and application of an optimization algorithm. In the paper it is shown how these four tasks can be linked effectively and how existing information on design variables, Lagrange multipliers and the Hessian matrix can...
Data on cost-optimal Nearly Zero Energy Buildings (NZEBs across Europe

Directory of Open Access Journals (Sweden)

Delia D'Agostino

2018-04-01

Full Text Available This data article refers to the research paper A model for the cost-optimal design of Nearly Zero Energy Buildings (NZEBs in representative climates across Europe [1]. The reported data deal with the design optimization of a residential building prototype located in representative European locations. The study focus on the research of cost-optimal choices and efficiency measures in new buildings depending on the climate. The data linked within this article relate to the modelled building energy consumption, renewable production, potential energy savings, and costs. Data allow to visualize energy consumption before and after the optimization, selected efficiency measures, costs and renewable production. The reduction of electricity and natural gas consumption towards the NZEB target can be visualized together with incremental and cumulative costs in each location. Further data is available about building geometry, costs, CO2 emissions, envelope, materials, lighting, appliances and systems.
Data on cost-optimal Nearly Zero Energy Buildings (NZEBs) across Europe.

Science.gov (United States)

D'Agostino, Delia; Parker, Danny

2018-04-01

This data article refers to the research paper A model for the cost-optimal design of Nearly Zero Energy Buildings (NZEBs) in representative climates across Europe [1]. The reported data deal with the design optimization of a residential building prototype located in representative European locations. The study focus on the research of cost-optimal choices and efficiency measures in new buildings depending on the climate. The data linked within this article relate to the modelled building energy consumption, renewable production, potential energy savings, and costs. Data allow to visualize energy consumption before and after the optimization, selected efficiency measures, costs and renewable production. The reduction of electricity and natural gas consumption towards the NZEB target can be visualized together with incremental and cumulative costs in each location. Further data is available about building geometry, costs, CO 2 emissions, envelope, materials, lighting, appliances and systems.
RO-75, Reverse Osmosis Plant Design Optimization and Cost Optimization

International Nuclear Information System (INIS)

Glueckstern, P.; Reed, S.A.; Wilson, J.V.

1999-01-01

1 - Description of problem or function: RO75 is a program for the optimization of the design and economics of one- or two-stage seawater reverse osmosis plants. 2 - Method of solution: RO75 evaluates the performance of the applied membrane module (productivity and salt rejection) at assumed operating conditions. These conditions include the site parameters - seawater salinity and temperature, the membrane module operating parameters - pressure and product recovery, and the membrane module predicted long-term performance parameters - lifetime and long flux decline. RO75 calculates the number of first and second stage (if applied) membrane modules needed to obtain the required product capacity and quality and evaluates the required pumping units and the power recovery turbine (if applied). 3 - Restrictions on the complexity of the problem: The program does not optimize or design the membrane properties and the internal structure and flow characteristics of the membrane modules; it assumes operating characteristics defined by the membrane manufacturers
Analysis and design optimization of flexible pavement

Energy Technology Data Exchange (ETDEWEB)

Mamlouk, M.S.; Zaniewski, J.P.; He, W.

2000-04-01

A project-level optimization approach was developed to minimize total pavement cost within an analysis period. Using this approach, the designer is able to select the optimum initial pavement thickness, overlay thickness, and overlay timing. The model in this approach is capable of predicting both pavement performance and condition in terms of roughness, fatigue cracking, and rutting. The developed model combines the American Association of State Highway and Transportation Officials (AASHTO) design procedure and the mechanistic multilayer elastic solution. The Optimization for Pavement Analysis (OPA) computer program was developed using the prescribed approach. The OPA program incorporates the AASHTO equations, the multilayer elastic system ELSYM5 model, and the nonlinear dynamic programming optimization technique. The program is PC-based and can run in either a Windows 3.1 or a Windows 95 environment. Using the OPA program, a typical pavement section was analyzed under different traffic volumes and material properties. The optimum design strategy that produces the minimum total pavement cost in each case was determined. The initial construction cost, overlay cost, highway user cost, and total pavement cost were also calculated. The methodology developed during this research should lead to more cost-effective pavements for agencies adopting the recommended analysis methods.
Wind farm design optimization

Energy Technology Data Exchange (ETDEWEB)

Carreau, Michel; Morgenroth, Michael; Belashov, Oleg; Mdimagh, Asma; Hertz, Alain; Marcotte, Odile

2010-09-15

Innovative numerical computer tools have been developed to streamline the estimation, the design process and to optimize the Wind Farm Design with respect to the overall return on investment. The optimization engine can find the collector system layout automatically which provide a powerful tool to quickly study various alternative taking into account more precisely various constraints or factors that previously would have been too costly to analyze in details with precision. Our Wind Farm Tools have evolved through numerous projects and created value for our clients yielding Wind Farm projects with projected higher returns.
Enhancing product robustness in reliability-based design optimization

International Nuclear Information System (INIS)

Zhuang, Xiaotian; Pan, Rong; Du, Xiaoping

2015-01-01

Different types of uncertainties need to be addressed in a product design optimization process. In this paper, the uncertainties in both product design variables and environmental noise variables are considered. The reliability-based design optimization (RBDO) is integrated with robust product design (RPD) to concurrently reduce the production cost and the long-term operation cost, including quality loss, in the process of product design. This problem leads to a multi-objective optimization with probabilistic constraints. In addition, the model uncertainties associated with a surrogate model that is derived from numerical computation methods, such as finite element analysis, is addressed. A hierarchical experimental design approach, augmented by a sequential sampling strategy, is proposed to construct the response surface of product performance function for finding optimal design solutions. The proposed method is demonstrated through an engineering example. - Highlights: • A unifying framework for integrating RBDO and RPD is proposed. • Implicit product performance function is considered. • The design problem is solved by sequential optimization and reliability assessment. • A sequential sampling technique is developed for improving design optimization. • The comparison with traditional RBDO is provided
Optimal design of degradation tests in presence of cost constraint

International Nuclear Information System (INIS)

Wu, S.-J.; Chang, C.-T.

2002-01-01

Degradation test is a useful technique to provide information about the lifetime of highly reliable products. We obtain the degradation measurements over time in such a test. In general, the degradation data are modeled by a nonlinear regression model with random coefficients. If we can obtain the estimates of parameters under the model, then the failure time distribution can be estimated. However, in order to obtain a precise estimate of the percentile of failure time distribution, one needs to design an optimal degradation test. Therefore, this study proposes an approach to determine the number of units to test, inspection frequency, and termination time of a degradation test under a determined cost of experiment such that the variance of estimator of percentile of failure time distribution is minimum. The method will be applied to a numerical example and the sensitivity analysis will be discussed
Design optimization of transformerless grid-connected PV inverters including reliability

DEFF Research Database (Denmark)

Koutroulis, Eftichios; Blaabjerg, Frede

2012-01-01

Of the Electricity (LCOE) generated during the PV system lifetime period is minimized. The LCOE is calculated also considering the failure rates of the components, which affect the reliability performance and lifetime maintenance cost of the PV inverter. A design example is presented, demonstrating that compared...... to the non-optimized PV inverter structures, the PV inverters designed using the proposed optimization methodology exhibit lower total manufacturing and lifetime maintenance cost and inject more energy into the electric-grid and by that minimizing LCOE.......This paper presents a new methodology for optimal design of transformerless Photovoltaic (PV) inverters targeting a cost-effective deployment of grid-connected PV systems. The optimal values and types of the PV inverter components are calculated such that the PV inverter Levelized Cost...
OPTIMAL NETWORK TOPOLOGY DESIGN

Science.gov (United States)

Yuen, J. H.

1994-01-01

This program was developed as part of a research study on the topology design and performance analysis for the Space Station Information System (SSIS) network. It uses an efficient algorithm to generate candidate network designs (consisting of subsets of the set of all network components) in increasing order of their total costs, and checks each design to see if it forms an acceptable network. This technique gives the true cost-optimal network, and is particularly useful when the network has many constraints and not too many components. It is intended that this new design technique consider all important performance measures explicitly and take into account the constraints due to various technical feasibilities. In the current program, technical constraints are taken care of by the user properly forming the starting set of candidate components (e.g. nonfeasible links are not included). As subsets are generated, they are tested to see if they form an acceptable network by checking that all requirements are satisfied. Thus the first acceptable subset encountered gives the cost-optimal topology satisfying all given constraints. The user must sort the set of "feasible" link elements in increasing order of their costs. The program prompts the user for the following information for each link: 1) cost, 2) connectivity (number of stations connected by the link), and 3) the stations connected by that link. Unless instructed to stop, the program generates all possible acceptable networks in increasing order of their total costs. The program is written only to generate topologies that are simply connected. Tests on reliability, delay, and other performance measures are discussed in the documentation, but have not been incorporated into the program. This program is written in PASCAL for interactive execution and has been implemented on an IBM PC series computer operating under PC DOS. The disk contains source code only. This program was developed in 1985.
Problem statement for optimal design of steel structures

Directory of Open Access Journals (Sweden)

Ginzburg Aleksandr Vital'evich

2014-07-01

Full Text Available The presented article considers the following complex of tasks. The main stages of the life cycle of a building construction with the indication of process entrance and process exit are described. Requirements imposed on steel constructions are considered. The optimum range of application for steel designs is specified, as well as merits and demerits of a design material. The nomenclature of metal designs is listed - the block diagram is constructed. Possible optimality criteria of steel designs, offered by various authors for various types of constructions are considered. It is established that most often the criterion of a minimum of design mass is accepted as criterion of optimality; more rarely - a minimum of the given expenses, a minimum of a design cost in business. In the present article special attention is paid to a type of objective function of optimization problem. It is also established that depending on the accepted optimality criterion, the use of different types of functions is possible. This complexity of objective function depends on completeness of optimality criterion application. In the work the authors consider the following objective functions: the mass of the main element of a design; objective function by criterion of factory cost; objective function by criterion of cost in business. According to these examples it can be seen that objective functions by the criteria of labor expenses for production of designs are generally non-linear, which complicates solving the optimization problem. Another important factor influencing the problem of optimal design solution for steel designs, which is analyzed, is account for operating restrictions. In the article 8 groups of restrictions are analyzed. Attempts to completely account for the parameters of objective function optimized by particular optimality criteria, taking into account all the operating restrictions, considerably complicates the problem of designing. For solving this
Design Optimization and Construction of the Thyratron/PFN Based Cost Model Modulator for the NLC

International Nuclear Information System (INIS)

Koontz, Roland F

1999-01-01

As design studies and various R and D efforts continue on Next Linear Collider (NLC) systems, much R and D work is being done on X-Band klystron development, and development of pulse modulators to drive these X-Band klystrons. A workshop on this subject was held at SLAC in June of 1998, and a follow-up workshop is scheduled at SLAC June 23-25, 1999. At the 1998 workshop, several avenues of R and D were proposed using solid state switching, induction LINAC principles, high voltage hard tubes, and a few more esoteric ideas. An optimized version of the conventional thyratron-PFN-pulse transformer modulator for which there is extensive operating experience is also a strong candidate for use in the NLC. Such a modulator is currently under construction for base line demonstration purposes. The performance of this ''Cost Model'' modulator will be compared to other developing technologies. Important parameters including initial capital cost, operating maintenance cost, reliability, maintainability, power efficiency, in addition to the usual operating parameters of pulse flatness, timing and pulse height jitter, etc. will be considered in the choice of a modulator design for the NLC. This paper updates the progress on this ''Cost Model'' modulator design and construction
Optimal Design and Operation of Permanent Irrigation Systems

Science.gov (United States)

Oron, Gideon; Walker, Wynn R.

1981-01-01

Solid-set pressurized irrigation system design and operation are studied with optimization techniques to determine the minimum cost distribution system. The principle of the analysis is to divide the irrigation system into subunits in such a manner that the trade-offs among energy, piping, and equipment costs are selected at the minimum cost point. The optimization procedure involves a nonlinear, mixed integer approach capable of achieving a variety of optimal solutions leading to significant conclusions with regard to the design and operation of the system. Factors investigated include field geometry, the effect of the pressure head, consumptive use rates, a smaller flow rate in the pipe system, and outlet (sprinkler or emitter) discharge.
A Low Cost Structurally Optimized Design for Diverse Filter Types

Science.gov (United States)

Kazmi, Majida; Aziz, Arshad; Akhtar, Pervez; Ikram, Nassar

2016-01-01

A wide range of image processing applications deploys two dimensional (2D)-filters for performing diversified tasks such as image enhancement, edge detection, noise suppression, multi scale decomposition and compression etc. All of these tasks require multiple type of 2D-filters simultaneously to acquire the desired results. The resource hungry conventional approach is not a viable option for implementing these computationally intensive 2D-filters especially in a resource constraint environment. Thus it calls for optimized solutions. Mostly the optimization of these filters are based on exploiting structural properties. A common shortcoming of all previously reported optimized approaches is their restricted applicability only for a specific filter type. These narrow scoped solutions completely disregard the versatility attribute of advanced image processing applications and in turn offset their effectiveness while implementing a complete application. This paper presents an efficient framework which exploits the structural properties of 2D-filters for effectually reducing its computational cost along with an added advantage of versatility for supporting diverse filter types. A composite symmetric filter structure is introduced which exploits the identities of quadrant and circular T-symmetries in two distinct filter regions simultaneously. These T-symmetries effectually reduce the number of filter coefficients and consequently its multipliers count. The proposed framework at the same time empowers this composite filter structure with additional capabilities of realizing all of its Ψ-symmetry based subtypes and also its special asymmetric filters case. The two-fold optimized framework thus reduces filter computational cost up to 75% as compared to the conventional approach as well as its versatility attribute not only supports diverse filter types but also offers further cost reduction via resource sharing for sequential implementation of diversified image
Optimal design of water supply networks for enhancing seismic reliability

International Nuclear Information System (INIS)

Yoo, Do Guen; Kang, Doosun; Kim, Joong Hoon

2016-01-01

The goal of the present study is to construct a reliability evaluation model of a water supply system taking seismic hazards and present techniques to enhance hydraulic reliability of the design into consideration. To maximize seismic reliability with limited budgets, an optimal design model is developed using an optimization technique called harmony search (HS). The model is applied to actual water supply systems to determine pipe diameters that can maximize seismic reliability. The reliabilities between the optimal design and existing designs were compared and analyzed. The optimal design would both enhance reliability by approximately 8.9% and have a construction cost of approximately 1.3% less than current pipe construction cost. In addition, the reinforcement of the durability of individual pipes without considering the system produced ineffective results in terms of both cost and reliability. Therefore, to increase the supply ability of the entire system, optimized pipe diameter combinations should be derived. Systems in which normal status hydraulic stability and abnormal status available demand could be maximally secured if configured through the optimal design. - Highlights: • We construct a seismic reliability evaluation model of water supply system. • We present technique to enhance hydraulic reliability in the aspect of design. • Harmony search algorithm is applied in optimal designs process. • The effects of the proposed optimal design are improved reliability about by 9%. • Optimized pipe diameter combinations should be derived indispensably.
Integrated Reliability-Based Optimal Design of Structures

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Thoft-Christensen, Palle

1987-01-01

In conventional optimal design of structural systems the weight or the initial cost of the structure is usually used as objective function. Further, the constraints require that the stresses and/or strains at some critical points have to be less than some given values. Finally, all variables......-based optimal design is discussed. Next, an optimal inspection and repair strategy for existing structural systems is presented. An optimization problem is formulated , where the objective is to minimize the expected total future cost of inspection and repair subject to the constraint that the reliability...... value. The reliability can be measured from an element and/or a systems point of view. A number of methods to solve reliability-based optimization problems has been suggested, see e.g. Frangopol [I]. Murotsu et al. (2], Thoft-Christensen & Sørensen (3] and Sørensen (4). For structures where...
Optimization Method of a Low Cost, High Performance Ceramic Proppant by Orthogonal Experimental Design

Science.gov (United States)

Zhou, Y.; Tian, Y. M.; Wang, K. Y.; Li, G.; Zou, X. W.; Chai, Y. S.

2017-09-01

This study focused on optimization method of a ceramic proppant material with both low cost and high performance that met the requirements of Chinese Petroleum and Gas Industry Standard (SY/T 5108-2006). The orthogonal experimental design of L9(34) was employed to study the significance sequence of three factors, including weight ratio of white clay to bauxite, dolomite content and sintering temperature. For the crush resistance, both the range analysis and variance analysis reflected the optimally experimental condition was weight ratio of white clay to bauxite=3/7, dolomite content=3 wt.%, temperature=1350°C. For the bulk density, the most important factor was the sintering temperature, followed by the dolomite content, and then the ratio of white clay to bauxite.
Design Buildings Optimally: A Lifecycle Assessment Approach

KAUST Repository

Hosny, Ossama

2013-01-01

This paper structures a generic framework to support optimum design for multi-buildings in desert environment. The framework is targeting an environmental friendly design with minimum lifecycle cost, using Genetic Algorithms (Gas). GAs function through a set of success measures which evaluates the design, formulates a proper objective, and reflects possible tangible/intangible constraints. The framework optimizes the design and categorizes it under a certain environmental category at minimum Life Cycle Cost (LCC). It consists of three main modules: (1) a custom Building InformationModel (BIM) for desert buildings with a compatibility checker as a central interactive database; (2) a system evaluator module to evaluate the proposed success measures for the design; and (3) a GAs optimization module to ensure optimum design. The framework functions through three levels: the building components, integrated building, and multi-building levels. At the component level the design team should be able to select components in a designed sequence to ensure compatibility among various components, while at the building level; the team can relatively locate and orient each individual building. Finally, at the multi-building (compound) level the whole design can be evaluated using success measures of natural light, site capacity, shading impact on natural lighting, thermal change, visual access and energy saving. The framework through genetic algorithms optimizes the design by determining proper types of building components and relative buildings locations and orientations which ensure categorizing the design under a specific category or meet certain preferences at minimum lifecycle cost.
Design Optimization of Transformerless Grid-Connected PV Inverters Including Reliability

DEFF Research Database (Denmark)

Koutroulis, Eftichios; Blaabjerg, Frede

2013-01-01

such that the PV inverter LCOE generated during the PV system lifetime period is minimized. The LCOE is also calculated considering the failure rates of the components, which affect the reliability performance and lifetime maintenance cost of the PV inverter. A design example is presented, demonstrating...... that compared to the nonoptimized PV inverter structures, the PV inverters designed using the proposed optimization methodology exhibit lower total manufacturing and lifetime maintenance cost and inject more energy into the electric-grid and by that minimizing LCOE.......This paper presents a new methodology for optimal design of transformerless photovoltaic (PV) inverters targeting a cost-effective deployment of grid-connected PV systems. The optimal switching frequency as well as the optimal values and types of the PV inverter components is calculated...
Capital Cost Optimization for Prefabrication: A Factor Analysis Evaluation Model

Directory of Open Access Journals (Sweden)

Hong Xue

2018-01-01

Full Text Available High capital cost is a significant hindrance to the promotion of prefabrication. In order to optimize cost management and reduce capital cost, this study aims to explore the latent factors and factor analysis evaluation model. Semi-structured interviews were conducted to explore potential variables and then questionnaire survey was employed to collect professionals’ views on their effects. After data collection, exploratory factor analysis was adopted to explore the latent factors. Seven latent factors were identified, including “Management Index”, “Construction Dissipation Index”, “Productivity Index”, “Design Efficiency Index”, “Transport Dissipation Index”, “Material increment Index” and “Depreciation amortization Index”. With these latent factors, a factor analysis evaluation model (FAEM, divided into factor analysis model (FAM and comprehensive evaluation model (CEM, was established. The FAM was used to explore the effect of observed variables on the high capital cost of prefabrication, while the CEM was used to evaluate comprehensive cost management level on prefabrication projects. Case studies were conducted to verify the models. The results revealed that collaborative management had a positive effect on capital cost of prefabrication. Material increment costs and labor costs had significant impacts on production cost. This study demonstrated the potential of on-site management and standardization design to reduce capital cost. Hence, collaborative management is necessary for cost management of prefabrication. Innovation and detailed design were needed to improve cost performance. The new form of precast component factories can be explored to reduce transportation cost. Meanwhile, targeted strategies can be adopted for different prefabrication projects. The findings optimized the capital cost and improved the cost performance through providing an evaluation and optimization model, which helps managers to

Resilience-based optimal design of water distribution network

Science.gov (United States)

Suribabu, C. R.

2017-11-01

Optimal design of water distribution network is generally aimed to minimize the capital cost of the investments on tanks, pipes, pumps, and other appurtenances. Minimizing the cost of pipes is usually considered as a prime objective as its proportion in capital cost of the water distribution system project is very high. However, minimizing the capital cost of the pipeline alone may result in economical network configuration, but it may not be a promising solution in terms of resilience point of view. Resilience of the water distribution network has been considered as one of the popular surrogate measures to address ability of network to withstand failure scenarios. To improve the resiliency of the network, the pipe network optimization can be performed with two objectives, namely minimizing the capital cost as first objective and maximizing resilience measure of the configuration as secondary objective. In the present work, these two objectives are combined as single objective and optimization problem is solved by differential evolution technique. The paper illustrates the procedure for normalizing the objective functions having distinct metrics. Two of the existing resilience indices and power efficiency are considered for optimal design of water distribution network. The proposed normalized objective function is found to be efficient under weighted method of handling multi-objective water distribution design problem. The numerical results of the design indicate the importance of sizing pipe telescopically along shortest path of flow to have enhanced resiliency indices.
Optimal design of NPC and Active-NPC transformerless PV inverters

DEFF Research Database (Denmark)

Saridakis, Stefanos; Koutroulis, Eftichios; Blaabjerg, Frede

2012-01-01

Targeting at a cost-effective deployment of grid-connected PhotoVoltaic (PV) systems, this paper presents a new methodology for the optimal design of transformerless PV inverters, which are based on the Neutral Point Clamped (NPC) and the Active-Neutral Point Clamped (ANPC) topologies. The design...... optimization results demonstrate that a different set of optimal values of the PV inverter switching frequency and output filter components are derived for the NPC and ANPC topologies, respectively, as well as for each of the PV inverter installation sites under study. The NPC and ANPC PV inverter structures......, which are derived using the proposed design optimization methodology exhibit lower Levelized Cost Of generated Electricity (LCOE) and manufacturing cost and they are simultaneously capable to inject more energy into the electric grid than the corresponding non-optimized PV inverters. Thus, the proposed...
Optimal design of a NGNP heat exchanger with cost model

International Nuclear Information System (INIS)

Ridluan, Artit; Danchus, William; Tokuhiro, Akira

2009-01-01

With steady increase in energy consumption, the vulnerability of the fossil fuel supply, and environmental concerns, the U.S. Department of Energy (DOE) has initiated the Next Generation Nuclear Power Plants (NGNP), also known as Very High Temperature Reactor (VHTR). The VHTR is planned to be operational by 2021 with possible demonstration of a hydrogen generating plant. Various engineering design studies on both the reactor plant and energy conversion system are underway. For this and related Generation IV plants, it is the goal to not only meet safety criteria but to also be efficient, economically competitive, and environmentally friendly (proliferation resistant). Traditionally, heat exchanger (HX) design is based on two main approaches: Log-Mean Temperature Difference (LMTD) and effectiveness-NTU (ε-NTU). These methods yield the dimension of the HX under anticipate condition and vice-versa. However, one is not assured that the dimension calculated give the best performing HX when economics are also considered. Here, we develop and show a specific optimization algorithm (exercise) using LMTD and simple (optimal) design theory to establish a reference case for the Printed Circuit Heat Exchanger (PCHE). Computational Fluid Dynamics (CFD) was further used as a design tool to investigate the optimal design of PCHE thermohydraulic flow. The CFD results were validated against the Blasius correlation before being subjected to optimal design analyses. Benchmark results for the pipe flow indicated that the predictive ability of SST k-ω is superior to the other (standard and RNG k-ε and RSM) turbulence models. The difference between CFD and the empirical expression is less than 10%. (author)
Design Optimization of Space Launch Vehicles Using a Genetic Algorithm

National Research Council Canada - National Science Library

Bayley, Douglas J

2007-01-01

.... A genetic algorithm (GA) was employed to optimize the design of the space launch vehicle. A cost model was incorporated into the optimization process with the goal of minimizing the overall vehicle cost...
Equation of costs and function objective for the optimization of the design of nets of flow of liquids to pressure

International Nuclear Information System (INIS)

Narvaez R, Paulo Cesar; Galeano P, Haiver

2002-01-01

Optimal design problem of liquid distribution systems has been viewed as the selection of pipe sizes and pumps, which will minimize overall costs, accomplishing the flow and pressure constraints. There is a set of methods for least cost design of liquids distribution networks (6). In the last years, some of them have been studied broadly: linear programming (1, 4, 5, 7], non-linear programming [8, 9], and genetic algorithms (3, 10, 13). This paper describes the development of a cost equation and the objective function for liquid distribution networks that together to the mathematical model and the solution method of the flow problem developed by Narvaez (11), were used by in a computer model that involves the application of an genetic algorithm to the problem of least cost design of liquids distribution networks
Review of design optimization methods for turbomachinery aerodynamics

Science.gov (United States)

Li, Zhihui; Zheng, Xinqian

2017-08-01

In today's competitive environment, new turbomachinery designs need to be not only more efficient, quieter, and ;greener; but also need to be developed at on much shorter time scales and at lower costs. A number of advanced optimization strategies have been developed to achieve these requirements. This paper reviews recent progress in turbomachinery design optimization to solve real-world aerodynamic problems, especially for compressors and turbines. This review covers the following topics that are important for optimizing turbomachinery designs. (1) optimization methods, (2) stochastic optimization combined with blade parameterization methods and the design of experiment methods, (3) gradient-based optimization methods for compressors and turbines and (4) data mining techniques for Pareto Fronts. We also present our own insights regarding the current research trends and the future optimization of turbomachinery designs.
Robotic lower limb prosthesis design through simultaneous computer optimizations of human and prosthesis costs

Science.gov (United States)

Handford, Matthew L.; Srinivasan, Manoj

2016-02-01

Robotic lower limb prostheses can improve the quality of life for amputees. Development of such devices, currently dominated by long prototyping periods, could be sped up by predictive simulations. In contrast to some amputee simulations which track experimentally determined non-amputee walking kinematics, here, we explicitly model the human-prosthesis interaction to produce a prediction of the user’s walking kinematics. We obtain simulations of an amputee using an ankle-foot prosthesis by simultaneously optimizing human movements and prosthesis actuation, minimizing a weighted sum of human metabolic and prosthesis costs. The resulting Pareto optimal solutions predict that increasing prosthesis energy cost, decreasing prosthesis mass, and allowing asymmetric gaits all decrease human metabolic rate for a given speed and alter human kinematics. The metabolic rates increase monotonically with speed. Remarkably, by performing an analogous optimization for a non-amputee human, we predict that an amputee walking with an appropriately optimized robotic prosthesis can have a lower metabolic cost - even lower than assuming that the non-amputee’s ankle torques are cost-free.
A Response Surface-Based Cost Model for Wind Farm Design

International Nuclear Information System (INIS)

Zhang Jie; Chowdhury, Souma; Messac, Achille; Castillo, Luciano

2012-01-01

A Response Surface-Based Wind Farm Cost (RS-WFC) model is developed for the engineering planning of wind farms. The RS-WFC model is developed using Extended Radial Basis Functions (E-RBF) for onshore wind farms in the U.S. This model is then used to explore the influences of different design and economic parameters, including number of turbines, rotor diameter and labor cost, on the cost of a wind farm. The RS-WFC model is composed of three components that estimate the effects of engineering and economic factors on (i) the installation cost, (ii) the annual Operation and Maintenance (O and M) cost, and (iii) the total annual cost of a wind farm. The accuracy of the cost model is favorably established through comparison with pertinent commercial data. The final RS-WFC model provided interesting insights into cost variation with respect to critical engineering and economic parameters. In addition, a newly developed analytical wind farm engineering model is used to determine the power generated by the farm, and the subsequent Cost of Energy (COE). This COE is optimized for a unidirectional uniform “incoming wind speed” scenario using Particle Swarm Optimization (PSO). We found that the COE could be appreciably minimized through layout optimization, thereby yielding significant cost savings. - Highlights: ► We present a Response Surface-Based Wind Farm Cost (RS-WFC) model for wind farm design. ► The model could estimate installation cost, Operation and Maintenance cost, and total annual cost of a wind farm. ► The Cost of Energy is optimized using Particle Swarm Optimization. ► Layout optimization could yield significant cost savings.
An efficient cost function for the optimization of an n-layered isotropic cloaked cylinder

International Nuclear Information System (INIS)

Paul, Jason V; Collins, Peter J; Coutu, Ronald A Jr

2013-01-01

In this paper, we present an efficient cost function for optimizing n-layered isotropic cloaked cylinders. Cost function efficiency is achieved by extracting the expression for the angle independent scatterer contribution of an associated Green's function. Therefore, since this cost function is not a function of angle, accounting for every bistatic angle is not necessary and thus more efficient than other cost functions. With this general and efficient cost function, isotropic cloaked cylinders can be optimized for many layers and material parameters. To demonstrate this, optimized cloaked cylinders made of 10, 20 and 30 equal thickness layers are presented for TE and TM incidence. Furthermore, we study the effect layer thickness has on optimized cloaks by optimizing a 10 layer cloaked cylinder over the material parameters and individual layer thicknesses. The optimized material parameters in this effort do not exhibit the dual nature that is evident in the ideal transformation optics design. This indicates that the inevitable field penetration and subsequent PEC boundary condition at the cylinder must be taken into account for an optimal cloaked cylinder design. Furthermore, a more effective cloaked cylinder can be designed by optimizing both layer thickness and material parameters than by additional layers alone. (paper)
Optimization of the National Ignition Facility primary shield design

International Nuclear Information System (INIS)

Annese, C.E.; Watkins, E.F.; Greenspan, E.; Miller, W.F.

1993-10-01

Minimum cost design concepts of the primary shield for the National Ignition laser fusion experimental Facility (NIF) are searched with the help of the optimization code SWAN. The computational method developed for this search involves incorporating the time dependence of the delayed photon field within effective delayed photon production cross sections. This method enables one to address the time-dependent problem using relatively simple, time-independent transport calculations, thus significantly simplifying the design process. A novel approach was used for the identification of the optimal combination of constituents that will minimize the shield cost; it involves the generation, with SWAN, of effectiveness functions for replacing materials on an equal cost basis. The minimum cost shield design concept was found to consist of a mixture of polyethylene and low cost, low activation materials such as SiC, with boron added near the shield boundaries
A Study of Joint Cost Inclusion in Linear Programming Optimization

Directory of Open Access Journals (Sweden)

P. Armaos

2013-08-01

Full Text Available The concept of Structural Optimization has been a topic or research over the past century. Linear Programming Optimization has proved being the most reliable method of structural optimization. Global advances in linear programming optimization have been recently powered by University of Sheffield researchers, to include joint cost, self-weight and buckling considerations. A joint cost inclusion scopes to reduce the number of joints existing in an optimized structural solution, transforming it to a practically viable solution. The topic of the current paper is to investigate the effects of joint cost inclusion, as this is currently implemented in the optimization code. An extended literature review on this subject was conducted prior to familiarization with small scale optimization software. Using IntelliFORM software, a structured series of problems were set and analyzed. The joint cost tests examined benchmark problems and their consequent changes in the member topology, as the design domain was expanding. The findings of the analyses were remarkable and are being commented further on. The distinct topologies of solutions created by optimization processes are also recognized. Finally an alternative strategy of penalizing joints is presented.
Multidisciplinary design optimization of large wind turbines—Technical, economic, and design challenges

International Nuclear Information System (INIS)

Ashuri, Turaj; Zaaijer, Michiel B.; Martins, Joaquim R.R.A.; Zhang, Jie

2016-01-01

Highlights: • 5, 10 and 20 MW wind turbines are developed using multidisciplinary design optimization. • Technical feasibility and economy of large wind turbines are investigated. • Critical upscaling trends of existing wind turbines are presented up to 20 MW. • Design challenges of large wind turbines are identified, and design solutions proposed. • With no design innovation, upscaling of existing turbines will increase the costs. - Abstract: Wind energy has experienced a continuous cost reduction in the last decades. A popular cost reduction technique is to increase the rated power of the wind turbine by making it larger. However, it is not clear whether further upscaling of the existing wind turbines beyond the 5–7 MW range is technically feasible and economically attractive. To address this question, this study uses 5, 10, and 20 MW wind turbines that are developed using multidisciplinary design optimization as upscaling data points. These wind turbines are upwind, 3-bladed, pitch-regulated, variable-speed machines with a tubular tower. Based on the design data and properties of these wind turbines, scaling trends such as loading, mass, and cost are developed. These trends are used to study the technical and economical aspects of upscaling and its impact on the design and cost. The results of this research show the technical feasibility of the existing wind turbines up to 20 MW, but the design of such an upscaled machine is cost prohibitive. Mass increase of the rotor is identified as a main design challenge to overcome. The results of this research support the development of alternative lightweight materials and design concepts such as a two-bladed downwind design for upscaling to remain a cost effective solution for future wind turbines.
Scalable and near-optimal design space exploration for embedded systems

CERN Document Server

Kritikakou, Angeliki; Goutis, Costas

2014-01-01

This book describes scalable and near-optimal, processor-level design space exploration (DSE) methodologies. The authors present design methodologies for data storage and processing in real-time, cost-sensitive data-dominated embedded systems. Readers will be enabled to reduce time-to-market, while satisfying system requirements for performance, area, and energy consumption, thereby minimizing the overall cost of the final design. • Describes design space exploration (DSE) methodologies for data storage and processing in embedded systems, which achieve near-optimal solutions with scalable exploration time; • Presents a set of principles and the processes which support the development of the proposed scalable and near-optimal methodologies; • Enables readers to apply scalable and near-optimal methodologies to the intra-signal in-place optimization step for both regular and irregular memory accesses.
Design optimization of space launch vehicles using a genetic algorithm

Science.gov (United States)

Bayley, Douglas James

The United States Air Force (USAF) continues to have a need for assured access to space. In addition to flexible and responsive spacelift, a reduction in the cost per launch of space launch vehicles is also desirable. For this purpose, an investigation of the design optimization of space launch vehicles has been conducted. Using a suite of custom codes, the performance aspects of an entire space launch vehicle were analyzed. A genetic algorithm (GA) was employed to optimize the design of the space launch vehicle. A cost model was incorporated into the optimization process with the goal of minimizing the overall vehicle cost. The other goals of the design optimization included obtaining the proper altitude and velocity to achieve a low-Earth orbit. Specific mission parameters that are particular to USAF space endeavors were specified at the start of the design optimization process. Solid propellant motors, liquid fueled rockets, and air-launched systems in various configurations provided the propulsion systems for two, three and four-stage launch vehicles. Mass properties models, an aerodynamics model, and a six-degree-of-freedom (6DOF) flight dynamics simulator were all used to model the system. The results show the feasibility of this method in designing launch vehicles that meet mission requirements. Comparisons to existing real world systems provide the validation for the physical system models. However, the ability to obtain a truly minimized cost was elusive. The cost model uses an industry standard approach, however, validation of this portion of the model was challenging due to the proprietary nature of cost figures and due to the dependence of many existing systems on surplus hardware.
Design and Analysis of an Airborne, solid Propelled, Nanosatellite Launch Vehicle using Multidisciplinary Design Optimization

NARCIS (Netherlands)

Van Kesteren, M.W.; Zandbergen, B.T.C.; Naeije, M.C.; Van Kleef, A.J.P.

2015-01-01

The work focusses on the use of multidisciplinary optimization to design a cost optimized airborne nanosatellite launch vehicle capable of bringing a 10 kg payload into low earth orbit (LEO). Piggyback or shared launch options currently available for nanosatellites are relatively low cost (~45,000
Reliability-Based Robust Design Optimization of Structures Considering Uncertainty in Design Variables

Directory of Open Access Journals (Sweden)

Shujuan Wang

2015-01-01

Full Text Available This paper investigates the structural design optimization to cover both the reliability and robustness under uncertainty in design variables. The main objective is to improve the efficiency of the optimization process. To address this problem, a hybrid reliability-based robust design optimization (RRDO method is proposed. Prior to the design optimization, the Sobol sensitivity analysis is used for selecting key design variables and providing response variance as well, resulting in significantly reduced computational complexity. The single-loop algorithm is employed to guarantee the structural reliability, allowing fast optimization process. In the case of robust design, the weighting factor balances the response performance and variance with respect to the uncertainty in design variables. The main contribution of this paper is that the proposed method applies the RRDO strategy with the usage of global approximation and the Sobol sensitivity analysis, leading to the reduced computational cost. A structural example is given to illustrate the performance of the proposed method.
Optimal design for rectangular isolated footings using the real soil pressure

Directory of Open Access Journals (Sweden)

Arnulfo Luévanos Rojas

2017-05-01

Full Text Available The standard design method (classical method for reinforced concrete rectangular footings is: First, a dimension is proposed and should comply with the allowable stresses; subsequently, the effective depth is obtained from the maximum moment and is checked against the bending shear and the punching shear until, it complies with these conditions and, then, steel reinforcement is obtained, but it is not guarantee that the minimum cost will be obtained. This paper shows an optimal design for reinforced concrete rectangular footings using the new model. A numerical experimentation is presented to show the model capability to estimate the minimum cost design of the materials used for a rectangular footing that supports an axial load and moments in two directions in accordance to the building code requirements for structural concrete and commentary (ACI 318-13. Also, a comparison is made between the optimal design and current design for rectangular footings. The solutions show that the optimal design is more economical and more precise with respect to the current design, because standard design is done by trial and error. Then, the optimal design should be used to obtain the minimum cost design for reinforced concrete rectangular footings.
Optimal Design of Modern Transformerless PV Inverter Topologies

OpenAIRE

Saridakis, Stefanos; Koutroulis, Eftichios; Blaabjerg, Frede

2013-01-01

The design optimization of H5, H6, neutral point clamped, active-neutral point clamped, and conergy-NPC transformerless photovoltaic (PV) inverters is presented in this paper. The components reliability in terms of the corresponding malfunctions, affecting the PV inverter maintenance cost during the operational lifetime period of the PV installation, is also considered in the optimization process. According to the results of the proposed design method, different optimal values of the PV inver...
Multi-objective optimization design method of radiation shielding

International Nuclear Information System (INIS)

Yang Shouhai; Wang Weijin; Lu Daogang; Chen Yixue

2012-01-01

Due to the shielding design goals of diversification and uncertain process of many factors, it is necessary to develop an optimization design method of intelligent shielding by which the shielding scheme selection will be achieved automatically and the uncertainties of human impact will be reduced. For economical feasibility to achieve a radiation shielding design for automation, the multi-objective genetic algorithm optimization of screening code which combines the genetic algorithm and discrete-ordinate method was developed to minimize the costs, size, weight, and so on. This work has some practical significance for gaining the optimization design of shielding. (authors)
Improved Cost-Base Design of Water Distribution Networks using Genetic Algorithm

Science.gov (United States)

Moradzadeh Azar, Foad; Abghari, Hirad; Taghi Alami, Mohammad; Weijs, Steven

2010-05-01

Population growth and progressive extension of urbanization in different places of Iran cause an increasing demand for primary needs. The water, this vital liquid is the most important natural need for human life. Providing this natural need is requires the design and construction of water distribution networks, that incur enormous costs on the country's budget. Any reduction in these costs enable more people from society to access extreme profit least cost. Therefore, investment of Municipal councils need to maximize benefits or minimize expenditures. To achieve this purpose, the engineering design depends on the cost optimization techniques. This paper, presents optimization models based on genetic algorithm(GA) to find out the minimum design cost Mahabad City's (North West, Iran) water distribution network. By designing two models and comparing the resulting costs, the abilities of GA were determined. the GA based model could find optimum pipe diameters to reduce the design costs of network. Results show that the water distribution network design using Genetic Algorithm could lead to reduction of at least 7% in project costs in comparison to the classic model. Keywords: Genetic Algorithm, Optimum Design of Water Distribution Network, Mahabad City, Iran.

Assessing cost-effectiveness of specific LID practice designs in response to large storm events

Science.gov (United States)

Chui, Ting Fong May; Liu, Xin; Zhan, Wenting

2016-02-01

Low impact development (LID) practices have become more important in urban stormwater management worldwide. However, most research on design optimization focuses on relatively large scale, and there is very limited information or guideline regarding individual LID practice designs (i.e., optimal depth, width and length). The objective of this study is to identify the optimal design by assessing the hydrological performance and the cost-effectiveness of different designs of LID practices at a household or business scale, and to analyze the sensitivity of the hydrological performance and the cost of the optimal design to different model and design parameters. First, EPA SWMM, automatically controlled by MATLAB, is used to obtain the peak runoff of different designs of three specific LID practices (i.e., green roof, bioretention and porous pavement) under different design storms (i.e., 2 yr and 50 yr design storms of Hong Kong, China and Seattle, U.S.). Then, life cycle cost is estimated for the different designs, and the optimal design, defined as the design with the lowest cost and at least 20% peak runoff reduction, is identified. Finally, sensitivity of the optimal design to the different design parameters is examined. The optimal design of green roof tends to be larger in area but thinner, while the optimal designs of bioretention and porous pavement tend to be smaller in area. To handle larger storms, however, it is more effective to increase the green roof depth, and to increase the area of the bioretention and porous pavement. Porous pavement is the most cost-effective for peak flow reduction, followed by bioretention and then green roof. The cost-effectiveness, measured as the peak runoff reduction/thousand Dollars of LID practices in Hong Kong (e.g., 0.02 L/103 US s, 0.15 L/103 US s and 0.93 L/103 US s for green roof, bioretention and porous pavement for 2 yr storm) is lower than that in Seattle (e.g., 0.03 L/103 US s, 0.29 L/103 US s and 1.58 L/103 US s for
A Novel Design Method for Optimizing an Indirect Forced Circulation Solar Water Heating System Based on Life Cycle Cost Using a Genetic Algorithm

Directory of Open Access Journals (Sweden)

Myeong Jin Ko

2015-10-01

Full Text Available To maximize the energy performance and economic benefits of solar water heating (SWH systems, the installation and operation-related design variables as well as those related to capacity must be optimized. This paper presents a novel design method for simultaneously optimizing the various design variables of an indirect forced-circulation SWH system that is based on the life cycle cost and uses a genetic algorithm. The effectiveness of the proposed method is assessed by evaluating the long-term performance corresponding to four cases, which are optimized using different annual solar fractions and sets of the design variables. When the installation and operation-related design variables were taken into consideration, it resulted in an efficient and economic design and an extra cost reduction of 3.2%–6.1% over when only the capacity-related design variables were considered. In addition, the results of parametric studies show that the slope and mass flow rate of the collector have a significant impact on the energy and economic performances of SWH systems. In contrast, the mass flow rate in the secondary circuit and the differences in the temperatures of the upper and lower dead bands of the differential controller have a smaller impact.
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.
Asteroid Rendezvous Mission Design Using Multiobjective Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Ya-zhong Luo

2014-01-01

Full Text Available A new preliminary trajectory design method for asteroid rendezvous mission using multiobjective optimization techniques is proposed. This method can overcome the disadvantages of the widely employed Pork-Chop method. The multiobjective integrated launch window and multi-impulse transfer trajectory design model is formulated, which employes minimum-fuel cost and minimum-time transfer as two objective functions. The multiobjective particle swarm optimization (MOPSO is employed to locate the Pareto solution. The optimization results of two different asteroid mission designs show that the proposed approach can effectively and efficiently demonstrate the relations among the mission characteristic parameters such as launch time, transfer time, propellant cost, and number of maneuvers, which will provide very useful reference for practical asteroid mission design. Compared with the PCP method, the proposed approach is demonstrated to be able to provide much more easily used results, obtain better propellant-optimal solutions, and have much better efficiency. The MOPSO shows a very competitive performance with respect to the NSGA-II and the SPEA-II; besides a proposed boundary constraint optimization strategy is testified to be able to improve its performance.
Quantum cost optimized design of 4-bit reversible universal shift register using reduced number of logic gate

Science.gov (United States)

Maity, H.; Biswas, A.; Bhattacharjee, A. K.; Pal, A.

In this paper, we have proposed the design of quantum cost (QC) optimized 4-bit reversible universal shift register (RUSR) using reduced number of reversible logic gates. The proposed design is very useful in quantum computing due to its low QC, less no. of reversible logic gate and less delay. The QC, no. of gates, garbage outputs (GOs) are respectively 64, 8 and 16 for proposed work. The improvement of proposed work is also presented. The QC is 5.88% to 70.9% improved, no. of gate is 60% to 83.33% improved with compared to latest reported result.
Optimal design of emission control systems for a fossil power plants

International Nuclear Information System (INIS)

Sfez, D.; Muginstein, A.; Naeh, Y.

1998-01-01

The detrimental environmental effects of pulverized coal power stations are enforcing the installation of additional emission control equipment. Utilization of this equipment significantly increases the installation and operation costs of the power station, which raises the cost of the electricity generated by this power station. Focusing on the flue gas cleaning equipment can substantially reduce the electricity-generating rate. Improving the equipment design is the only available way to reduce the flue gas cleaning costs, without affecting the power station flexibility and availability. An optimal design is defined as the one achieving the least expensive cleaning system (capital and operating costs) while maintaining the original power station operation flexibility (coal variety and partial load performances). Two main changes in the conventional design need to be carried out in order to reach the above-mentioned optimized design. The first modification is to integrate the ESP and FGD at the design criteria stage while considering the influence of each piece of equipment on the other. The second stage is to set one common best efficiency design point to the ESP and the FGD together. Achieving this one common best efficiency point requires some equipment addition and modifications to the conventional ESP and FGD systems. The technology involved in this modification is available and is well proven in operation. Using this technology with the optimal design concept will lead to a significant reduction of the flue gas cleaning costs and will reduce, by this, the electricity production costs
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems

DEFF Research Database (Denmark)

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

The design of measurement programs devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost that is the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contribution of the approach is that the optimal number of sensors can be estimated. This is shown in a numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement program...
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems

DEFF Research Database (Denmark)

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

1993-01-01

The design of a measurement program devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost that is the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contribution of the approach is that the optimal number of sensory can be estimated. This is shown in an numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement...
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems

DEFF Research Database (Denmark)

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

1991-01-01

The design of a measurement program devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost, i.e. the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contributions of the approach is that the optimal number of sensors can be estimated. This is shown in a numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement...
An Expert System-Driven Method for Parametric Trajectory Optimization During Conceptual Design

Science.gov (United States)

Dees, Patrick D.; Zwack, Mathew R.; Steffens, Michael; Edwards, Stephen; Diaz, Manuel J.; Holt, James B.

2015-01-01

During the early phases of engineering design, the costs committed are high, costs incurred are low, and the design freedom is high. It is well documented that decisions made in these early design phases drive the entire design's life cycle cost. In a traditional paradigm, key design decisions are made when little is known about the design. As the design matures, design changes become more difficult in both cost and schedule to enact. The current capability-based paradigm, which has emerged because of the constrained economic environment, calls for the infusion of knowledge usually acquired during later design phases into earlier design phases, i.e. bringing knowledge acquired during preliminary and detailed design into pre-conceptual and conceptual design. An area of critical importance to launch vehicle design is the optimization of its ascent trajectory, as the optimal trajectory will be able to take full advantage of the launch vehicle's capability to deliver a maximum amount of payload into orbit. Hence, the optimal ascent trajectory plays an important role in the vehicle's affordability posture yet little of the information required to successfully optimize a trajectory is known early in the design phase. Thus, the current paradigm of optimizing ascent trajectories involves generating point solutions for every change in a vehicle's design parameters. This is often a very tedious, manual, and time-consuming task for the analysts. Moreover, the trajectory design space is highly non-linear and multi-modal due to the interaction of various constraints. When these obstacles are coupled with the Program to Optimize Simulated Trajectories (POST), an industry standard program to optimize ascent trajectories that is difficult to use, expert trajectory analysts are required to effectively optimize a vehicle's ascent trajectory. Over the course of this paper, the authors discuss a methodology developed at NASA Marshall's Advanced Concepts Office to address these issues
A Virtual Tool for Minimum Cost Design of a Wind Turbine Tower with Ring Stiffeners

Directory of Open Access Journals (Sweden)

Fatih Karpat

2013-07-01

Full Text Available Currently, renewable energy resources are becoming more important to reduce greenhouse gas emissions and increase energy efficiency. Researchers have focused on all components of wind turbines to increase reliability and minimize cost. In this paper, a procedure including a cost analysis method and a particle swarm optimization algorithm has been presented to efficiently design low cost steel wind turbine towers. A virtual tool is developed in MATLAB for the cost optimization of wind turbine steel towers with ring stiffeners using a particle swarm optimization algorithm. A wind turbine tower optimization problem in the literature is solved using the developed computer program. In the optimization procedure the optimization results match very well with the optimization results obtained previously. The wall thickness of the shell segments and the dimensions of the ring stiffeners are selected as the design variables, and the limits of the local buckling for the flat ring stiffeners, the local shell buckling limit, the panel ring buckling limit and the limitation of the frequency are considered the design constraints. Numerical examples are presented to understand the impacts of the design variables on the total cost of the wind turbine tower.
Multi-objective three stage design optimization for island microgrids

International Nuclear Information System (INIS)

Sachs, Julia; Sawodny, Oliver

2016-01-01

Highlights: • An enhanced multi-objective three stage design optimization for microgrids is given. • Use of an optimal control problem for the calculation of the optimal operation. • The inclusion of a detailed battery model with CC/CV charging control. • The determination of a representative profile with optimized number of days. • The proposed method finds its direct application in a design tool for microgids. - Abstract: Hybrid off-grid energy systems enable a cost efficient and reliable energy supply to rural areas around the world. The main potential for a low cost operation and uninterrupted power supply lies in the optimal sizing and operation of such microgrids. In particular, sudden variations in load demand or in the power supply from renewables underline the need for an optimally sized system. This paper presents an efficient multi-objective model based optimization approach for the optimal sizing of all components and the determination of the best power electronic layout. The presented method is divided into three optimization problems to minimize economic and environmental objectives. This design optimization includes detailed components models and an optimized energy dispatch strategy which enables the optimal design of the energy system with respect to an adequate control for the specific configuration. To significantly reduce the computation time without loss of accuracy, the presented method contains the determination of a representative load profile using a k-means clustering method. The k-means algorithm itself is embedded in an optimization problem for the calculation of the optimal number of clusters. The benefits in term of reduced computation time, inclusion of optimal energy dispatch and optimization of power electronic architecture, of the presented optimization method are illustrated using a case study.
Optimization approach for saddling cost of medical cyclotrons with fuzziness

International Nuclear Information System (INIS)

Abass, S.A.; Massoud, E.M.A.

2007-01-01

Most radiation fields are combinations of different kinds of radiation. The radiations of most significance are fast neutrons, thermal neutrons, primary gammas and secondary gammas. Thermos's composite shielding materials are designed to attenuate these types of radiation. The shielding design requires an accurate cost-benefit analysis based on uncertainty optimization technique. The theory of fuzzy sets has been employed to formulate and solve the problem of cost-benefit analysis of medical cyclotron. This medical radioisotope production cyclotron is based in Sydney, Australia
MCMC-ODPR: Primer design optimization using Markov Chain Monte Carlo sampling

Directory of Open Access Journals (Sweden)

Kitchen James L

2012-11-01

Full Text Available Abstract Background Next generation sequencing technologies often require numerous primer designs that require good target coverage that can be financially costly. We aimed to develop a system that would implement primer reuse to design degenerate primers that could be designed around SNPs, thus find the fewest necessary primers and the lowest cost whilst maintaining an acceptable coverage and provide a cost effective solution. We have implemented Metropolis-Hastings Markov Chain Monte Carlo for optimizing primer reuse. We call it the Markov Chain Monte Carlo Optimized Degenerate Primer Reuse (MCMC-ODPR algorithm. Results After repeating the program 1020 times to assess the variance, an average of 17.14% fewer primers were found to be necessary using MCMC-ODPR for an equivalent coverage without implementing primer reuse. The algorithm was able to reuse primers up to five times. We compared MCMC-ODPR with single sequence primer design programs Primer3 and Primer-BLAST and achieved a lower primer cost per amplicon base covered of 0.21 and 0.19 and 0.18 primer nucleotides on three separate gene sequences, respectively. With multiple sequences, MCMC-ODPR achieved a lower cost per base covered of 0.19 than programs BatchPrimer3 and PAMPS, which achieved 0.25 and 0.64 primer nucleotides, respectively. Conclusions MCMC-ODPR is a useful tool for designing primers at various melting temperatures at good target coverage. By combining degeneracy with optimal primer reuse the user may increase coverage of sequences amplified by the designed primers at significantly lower costs. Our analyses showed that overall MCMC-ODPR outperformed the other primer-design programs in our study in terms of cost per covered base.
MCMC-ODPR: primer design optimization using Markov Chain Monte Carlo sampling.

Science.gov (United States)

Kitchen, James L; Moore, Jonathan D; Palmer, Sarah A; Allaby, Robin G

2012-11-05

Next generation sequencing technologies often require numerous primer designs that require good target coverage that can be financially costly. We aimed to develop a system that would implement primer reuse to design degenerate primers that could be designed around SNPs, thus find the fewest necessary primers and the lowest cost whilst maintaining an acceptable coverage and provide a cost effective solution. We have implemented Metropolis-Hastings Markov Chain Monte Carlo for optimizing primer reuse. We call it the Markov Chain Monte Carlo Optimized Degenerate Primer Reuse (MCMC-ODPR) algorithm. After repeating the program 1020 times to assess the variance, an average of 17.14% fewer primers were found to be necessary using MCMC-ODPR for an equivalent coverage without implementing primer reuse. The algorithm was able to reuse primers up to five times. We compared MCMC-ODPR with single sequence primer design programs Primer3 and Primer-BLAST and achieved a lower primer cost per amplicon base covered of 0.21 and 0.19 and 0.18 primer nucleotides on three separate gene sequences, respectively. With multiple sequences, MCMC-ODPR achieved a lower cost per base covered of 0.19 than programs BatchPrimer3 and PAMPS, which achieved 0.25 and 0.64 primer nucleotides, respectively. MCMC-ODPR is a useful tool for designing primers at various melting temperatures at good target coverage. By combining degeneracy with optimal primer reuse the user may increase coverage of sequences amplified by the designed primers at significantly lower costs. Our analyses showed that overall MCMC-ODPR outperformed the other primer-design programs in our study in terms of cost per covered base.
Comparison of optimal design methods in inverse problems

International Nuclear Information System (INIS)

Banks, H T; Holm, K; Kappel, F

2011-01-01

Typical optimal design methods for inverse or parameter estimation problems are designed to choose optimal sampling distributions through minimization of a specific cost function related to the resulting error in parameter estimates. It is hoped that the inverse problem will produce parameter estimates with increased accuracy using data collected according to the optimal sampling distribution. Here we formulate the classical optimal design problem in the context of general optimization problems over distributions of sampling times. We present a new Prohorov metric-based theoretical framework that permits one to treat succinctly and rigorously any optimal design criteria based on the Fisher information matrix. A fundamental approximation theory is also included in this framework. A new optimal design, SE-optimal design (standard error optimal design), is then introduced in the context of this framework. We compare this new design criterion with the more traditional D-optimal and E-optimal designs. The optimal sampling distributions from each design are used to compute and compare standard errors; the standard errors for parameters are computed using asymptotic theory or bootstrapping and the optimal mesh. We use three examples to illustrate ideas: the Verhulst–Pearl logistic population model (Banks H T and Tran H T 2009 Mathematical and Experimental Modeling of Physical and Biological Processes (Boca Raton, FL: Chapman and Hall/CRC)), the standard harmonic oscillator model (Banks H T and Tran H T 2009) and a popular glucose regulation model (Bergman R N, Ider Y Z, Bowden C R and Cobelli C 1979 Am. J. Physiol. 236 E667–77; De Gaetano A and Arino O 2000 J. Math. Biol. 40 136–68; Toffolo G, Bergman R N, Finegood D T, Bowden C R and Cobelli C 1980 Diabetes 29 979–90)
Comparison of optimal design methods in inverse problems

Science.gov (United States)

Banks, H. T.; Holm, K.; Kappel, F.

2011-07-01

Typical optimal design methods for inverse or parameter estimation problems are designed to choose optimal sampling distributions through minimization of a specific cost function related to the resulting error in parameter estimates. It is hoped that the inverse problem will produce parameter estimates with increased accuracy using data collected according to the optimal sampling distribution. Here we formulate the classical optimal design problem in the context of general optimization problems over distributions of sampling times. We present a new Prohorov metric-based theoretical framework that permits one to treat succinctly and rigorously any optimal design criteria based on the Fisher information matrix. A fundamental approximation theory is also included in this framework. A new optimal design, SE-optimal design (standard error optimal design), is then introduced in the context of this framework. We compare this new design criterion with the more traditional D-optimal and E-optimal designs. The optimal sampling distributions from each design are used to compute and compare standard errors; the standard errors for parameters are computed using asymptotic theory or bootstrapping and the optimal mesh. We use three examples to illustrate ideas: the Verhulst-Pearl logistic population model (Banks H T and Tran H T 2009 Mathematical and Experimental Modeling of Physical and Biological Processes (Boca Raton, FL: Chapman and Hall/CRC)), the standard harmonic oscillator model (Banks H T and Tran H T 2009) and a popular glucose regulation model (Bergman R N, Ider Y Z, Bowden C R and Cobelli C 1979 Am. J. Physiol. 236 E667-77 De Gaetano A and Arino O 2000 J. Math. Biol. 40 136-68 Toffolo G, Bergman R N, Finegood D T, Bowden C R and Cobelli C 1980 Diabetes 29 979-90).
Implementing the cost-optimal methodology in EU countries

DEFF Research Database (Denmark)

Atanasiu, Bogdan; Kouloumpi, Ilektra; Thomsen, Kirsten Engelund

This study presents three cost-optimal calculations. The overall aim is to provide a deeper analysis and to provide additional guidance on how to properly implement the cost-optimality methodology in Member States. Without proper guidance and lessons from exemplary case studies using realistic...... input data (reflecting the likely future development), there is a risk that the cost-optimal methodology may be implemented at sub-optimal levels. This could lead to a misalignment between the defined cost-optimal levels and the long-term goals, leaving a significant energy saving potential unexploited....... Therefore, this study provides more evidence on the implementation of the cost-optimal methodology and highlights the implications of choosing different values for key factors (e.g. discount rates, simulation variants/packages, costs, energy prices) at national levels. The study demonstrates how existing...
Design optimization of shell-and-tube heat exchangers using single objective and multiobjective particle swarm optimization

International Nuclear Information System (INIS)

Elsays, Mostafa A.; Naguib Aly, M; Badawi, Alya A.

2010-01-01

The Particle Swarm Optimization (PSO) algorithm is used to optimize the design of shell-and-tube heat exchangers and determine the optimal feasible solutions so as to eliminate trial-and-error during the design process. The design formulation takes into account the area and the total annual cost of heat exchangers as two objective functions together with operating as well as geometrical constraints. The Nonlinear Constrained Single Objective Particle Swarm Optimization (NCSOPSO) algorithm is used to minimize and find the optimal feasible solution for each of the nonlinear constrained objective functions alone, respectively. Then, a novel Nonlinear Constrained Mult-objective Particle Swarm Optimization (NCMOPSO) algorithm is used to minimize and find the Pareto optimal solutions for both of the nonlinear constrained objective functions together. The experimental results show that the two algorithms are very efficient, fast and can find the accurate optimal feasible solutions of the shell and tube heat exchangers design optimization problem. (orig.)
GENETIC ALGORITHM IN OPTIMIZATION DESIGN OF INTERIOR PERMANENT MAGNET SYNCHRONOUS MOTOR

Directory of Open Access Journals (Sweden)

Phuong Le Ngo

2017-01-01

Full Text Available Classical method of designing electric motors help to achieve functional motor, but doesn’t ensure minimal cost in manufacturing and operating. Recently optimization is becoming an important part in modern electric motor design process. The objective of the optimization process is usually to minimize cost, energy loss, mass, or maximize torque and efficiency. Most of the requirements for electrical machine design are in contradiction to each other (reduction in volume or mass, improvement in efficiency etc.. Optimization in design permanent magnet synchronous motor (PMSM is a multi-objective optimization problem. There are two approaches for solving this problem, one of them is evolution algorithms, which gain a lot of attentions recently. For designing PMSM, evolution algorithms are more attractive approach. Genetic algorithm is one of the most common. This paper presents components and procedures of genetic algorithms, and its implementation on computer. In optimization process, analytical and finite element method are used together for better performance and precision. Result from optimization process is a set of solutions, from which engineer will choose one. This method was used to design a permanent magnet synchronous motor based on an asynchronous motor type АИР112МВ8.

Low cost design of microprocessor EDAC circuit

International Nuclear Information System (INIS)

Hao Li; Yu Lixin; Peng Heping; Zhuang Wei

2015-01-01

An optimization method of error detection and correction (EDAC) circuit design is proposed. The method involves selecting or constructing EDAC codes of low cost hardware, associated with operation scheduling implementation based on 2-input XOR gates structure, and two actions for reducing hardware cells, which can reduce the delay penalties and area costs of the EDAC circuit effectively. The 32-bit EDAC circuit hardware implementation is selected to make a prototype, based on the 180 nm process. The delay penalties and area costs of the EDAC circuit are evaluated. Results show that the time penalty and area cost of the EDAC circuitries are affected with different parity-check matrices and different hardware implementation for the EDAC codes with the same capability of correction and detection code. This method can be used as a guide for low-cost radiation-hardened microprocessor EDAC circuit design and for more advanced technologies. (paper)
Starship Sails Propelled by Cost-Optimized Directed Energy

Science.gov (United States)

Benford, J.

Microwave and laser-propelled sails are a new class of spacecraft using photon acceleration. It is the only method of interstellar flight that has no physics issues. Laboratory demonstrations of basic features of beam-driven propulsion, flight, stability (`beam-riding'), and induced spin, have been completed in the last decade, primarily in the microwave. It offers much lower cost probes after a substantial investment in the launcher. Engineering issues are being addressed by other applications: fusion (microwave, millimeter and laser sources) and astronomy (large aperture antennas). There are many candidate sail materials: carbon nanotubes and microtrusses, beryllium, graphene, etc. For acceleration of a sail, what is the cost-optimum high power system? Here the cost is used to constrain design parameters to estimate system power, aperture and elements of capital and operating cost. From general relations for cost-optimal transmitter aperture and power, system cost scales with kinetic energy and inversely with sail diameter and frequency. So optimal sails will be larger, lower in mass and driven by higher frequency beams. Estimated costs include economies of scale. We present several starship point concepts. Systems based on microwave, millimeter wave and laser technologies are of equal cost at today's costs. The frequency advantage of lasers is cancelled by the high cost of both the laser and the radiating optic. Cost of interstellar sailships is very high, driven by current costs for radiation source, antennas and especially electrical power. The high speeds necessary for fast interstellar missions make the operating cost exceed the capital cost. Such sailcraft will not be flown until the cost of electrical power in space is reduced orders of magnitude below current levels.
Research on the optimization of quota design in real estate

Science.gov (United States)

Sun, Chunling; Ma, Susu; Zhong, Weichao

2017-11-01

Quota design is one of the effective methods of cost control in real estate development project and widely used in the current real estate development project to control the engineering construction cost, but quota design have many deficiencies in design process. For this purpose, this paper put forward a method to achieve investment control of real estate development project, which combine quota design and value engineering(VE) at the stage of design. Specifically, it’s an optimizing for the structure of quota design. At first, determine the design limits by investment estimate value, then using VE to carry on initial allocation of design limits and gain the functional target cost, finally, consider the whole life cycle cost (LCC) and operational problem in practical application to finish complex correction for the functional target cost. The improved process can control the project cost more effectively. It not only can control investment in a certain range, but also make the project realize maximum value within investment.
Optimal design of integrated CHP systems for housing complexes

International Nuclear Information System (INIS)

Fuentes-Cortés, Luis Fabián; Ponce-Ortega, José María; Nápoles-Rivera, Fabricio; Serna-González, Medardo; El-Halwagi, Mahmoud M.

2015-01-01

Highlights: • An optimization formulation for designing domestic CHP systems is presented. • The operating scheme, prime mover and thermal storage system are optimized. • Weather conditions and behavior demands are considered. • Simultaneously economic and environmental objectives are considered. • Two case studies from Mexico are presented. - Abstract: This paper presents a multi-objective optimization approach for designing residential cogeneration systems based on a new superstructure that allows satisfying the demands of hot water and electricity at the minimum cost and the minimum environmental impact. The optimization involves the selection of technologies, size of required units and operating modes of equipment. Two residential complexes in different cities of the State of Michoacán in Mexico were considered as case studies. One is located on the west coast and the other one is in the mountainous area. The results show that the implementation of the proposed optimization method yields significant economic and environmental benefits due to the simultaneous reduction in the total annual cost and overall greenhouse gas emissions
Design and Optimization of Capacitated Supply Chain Networks Including Quality Measures

Directory of Open Access Journals (Sweden)

Krystel K. Castillo-Villar

2014-01-01

Full Text Available This paper presents (1 a novel capacitated model for supply chain network design which considers manufacturing, distribution, and quality costs (named SCND-COQ model and (2 five combinatorial optimization methods, based on nonlinear optimization, heuristic, and metaheuristic approaches, which are used to solve realistic instances of practical size. The SCND-COQ model is a mixed-integer nonlinear problem which can be used at a strategic planning level to design a supply chain network that maximizes the total profit subject to meeting an overall quality level of the final product at minimum costs. The SCND-COQ model computes the quality-related costs for the whole supply chain network considering the interdependencies among business entities. The effectiveness of the proposed solution approaches is shown using numerical experiments. These methods allow solving more realistic (capacitated supply chain network design problems including quality-related costs (inspections, rework, opportunity costs, and others within a reasonable computational time.
Simulated annealing algorithm for reactor in-core design optimizations

International Nuclear Information System (INIS)

Zhong Wenfa; Zhou Quan; Zhong Zhaopeng

2001-01-01

A nuclear reactor must be optimized for in core fuel management to make full use of the fuel, to reduce the operation cost and to flatten the power distribution reasonably. The author presents a simulated annealing algorithm. The optimized objective function and the punishment function were provided for optimizing the reactor physics design. The punishment function was used to practice the simulated annealing algorithm. The practical design of the NHR-200 was calculated. The results show that the K eff can be increased by 2.5% and the power distribution can be flattened
Design Optimization of Time- and Cost-Constrained Fault-Tolerant Distributed Embedded Systems

DEFF Research Database (Denmark)

Izosimov, Viacheslav; Pop, Paul; Eles, Petru

2005-01-01

In this paper we present an approach to the design optimization of fault-tolerant embedded systems for safety-critical applications. Processes are statically scheduled and communications are performed using the time-triggered protocol. We use process re-execution and replication for tolerating...... transient faults. Our design optimization approach decides the mapping of processes to processors and the assignment of fault-tolerant policies to processes such that transient faults are tolerated and the timing constraints of the application are satisfied. We present several heuristics which are able...
Towards robust optimal design of storm water systems

Science.gov (United States)

Marquez Calvo, Oscar; Solomatine, Dimitri

2015-04-01

In this study the focus is on the design of a storm water or a combined sewer system. Such a system should be capable to handle properly most of the storm to minimize the damages caused by flooding due to the lack of capacity of the system to cope with rain water at peak times. This problem is a multi-objective optimization problem: we have to take into account the minimization of the construction costs, the minimization of damage costs due to flooding, and possibly other criteria. One of the most important factors influencing the design of storm water systems is the expected amount of water to deal with. It is common that this infrastructure is developed with the capacity to cope with events that occur once in, say 10 or 20 years - so-called design rainfall events. However, rainfall is a random variable and such uncertainty typically is not taken explicitly into account in optimization. Rainfall design data is based on historical information of rainfalls, but many times this data is based on unreliable measures; or in not enough historical information; or as we know, the patterns of rainfall are changing regardless of historical information. There are also other sources of uncertainty influencing design, for example, leakages in the pipes and accumulation of sediments in pipes. In the context of storm water or combined sewer systems design or rehabilitation, robust optimization technique should be able to find the best design (or rehabilitation plan) within the available budget but taking into account uncertainty in those variables that were used to design the system. In this work we consider various approaches to robust optimization proposed by various authors (Gabrel, Murat, Thiele 2013; Beyer, Sendhoff 2007) and test a novel method ROPAR (Solomatine 2012) to analyze robustness. References Beyer, H.G., & Sendhoff, B. (2007). Robust optimization - A comprehensive survey. Comput. Methods Appl. Mech. Engrg., 3190-3218. Gabrel, V.; Murat, C., Thiele, A. (2014
Optimal design of earth-moving machine elements with cusp catastrophe theory application

Science.gov (United States)

Pitukhin, A. V.; Skobtsov, I. G.

2017-10-01

This paper deals with the optimal design problem solution for the operator of an earth-moving machine with a roll-over protective structure (ROPS) in terms of the catastrophe theory. A brief description of the catastrophe theory is presented, the cusp catastrophe is considered, control parameters are viewed as Gaussian stochastic quantities in the first part of the paper. The statement of optimal design problem is given in the second part of the paper. It includes the choice of the objective function and independent design variables, establishment of system limits. The objective function is determined as mean total cost that includes initial cost and cost of failure according to the cusp catastrophe probability. Algorithm of random search method with an interval reduction subject to side and functional constraints is given in the last part of the paper. The way of optimal design problem solution can be applied to choose rational ROPS parameters, which will increase safety and reduce production and exploitation expenses.
DESIGN OPTIMIZATION OF A FOOT VALVE BY USING ANSYS®

Directory of Open Access Journals (Sweden)

Serdar KARAOĞLU

2008-02-01

Full Text Available In this study, main components of a foot valve, being produced by casting, were optimized for minimum weight. The study was focused on the minimization of casting costs by reducing the volumes of two main parts of the foot valve. ANSYS® finite elements package was used in the study. In the optimization stage, parametrical dimensions were determined according to manufacturer's design criteria and related standards. Final design of the foot valve was completed by using the calculated values of optimum dimensions of the main components. Design optimization procedure gave about 8.5% of weight reductions in the main foot valve components.
Cost optimization of ADS design: Comparative study of externally driven heterogeneous and homogeneous two-zone subcritical reactor systems

International Nuclear Information System (INIS)

Gulik, Volodymyr; Tkaczyk, Alan H.

2014-01-01

Highlights: • The optimization of two-zone homogeneous subcritical systems has been performed. • A Serpent model for two-zone heterogeneous subcritical systems has been developed. • The optimization of two-zone heterogeneous subcritical systems has been carried out. • Economically optimal core composition of two-zone subcritical system was found. • The neutron spectra of the heterogeneous subcritical systems have been obtained. - Abstract: Subcritical systems driven by external neutron sources, commonly known as Accelerator-Driven System (ADS), are one type of advanced nuclear reactor exhibiting attractive characteristics, distinguished from the traditional critical systems by their intrinsic safety features. In addition, an ADS can be used for the transmutation of the nuclear waste, accumulated during the operation of existing reactors. The optimization of a subcritical nuclear reactor in terms of materials (fuel content, coolant, etc.), geometrical, and economical parameters is a crucial step in the process of their design and construction. This article describes the optimization modeling performed for homogeneous and heterogeneous two-zone subcritical systems in terms of geometry of the fuel zones. Economical assessment was also carried out for the costs of the fuel in the core of the system. Optimization modeling was performed with the Serpent-1.1.18 Monte Carlo code. The model of a two-zone subcritical system with a fast inner and a thermal gas-cooled graphite-moderated outer zone was developed, simulated, and analyzed. The optimal value for the pitch of fuel elements in the thermal outer zone was investigated from the viewpoint of the cost of subcritical system. As the main goal of ADS development is nuclear waste transmutation, neutron spectra for both fast and thermal zones were obtained for different system configurations. The results of optimization modeling of homogeneous and heterogeneous two-zone subcritical systems show that an optimal
Optimal design of a maintainable cold-standby system

Energy Technology Data Exchange (ETDEWEB)

Yu Haiyang [Universite de technologie de Troyes, ISTIT, Rue Marie Curie, BP 2060, 10010 TROYES (France)]. E-mail: Haiyang.YU@utt.fr; Yalaoui, Farouk [Universite de technologie de Troyes, ISTIT, Rue Marie Curie, BP 2060, 10010 TROYES (France); Chatelet, Eric [Universite de technologie de Troyes, ISTIT, Rue Marie Curie, BP 2060, 10010 TROYES (France); Chu Chengbin [Universite de technologie de Troyes, ISTIT, Rue Marie Curie, BP 2060, 10010 TROYES (France); Management School, Hefei University of Technology, Hefei (China)

2007-01-15

This paper considers a framework to optimally design a maintainable cold-standby system. Not only the maintenance policy is to be determined, but also the reliability character of the components will be taken into account. Hence, the mean time to failure of the components and the policy time of good-as-new maintenances are proposed as decision variables. Following probability analyses, the system cost rate and the system availability are formulated as the optimization object and the constraint, respectively. Then, this optimization problem is directly resolved by recognizing its underlying properties. Moreover, the resolving procedure is found to be independent of the failure distributions of the components and the forms of the system cost, which is illustrated through a numerical example. As a conclusion, an exact method is successfully established to minimize the cost rate of a cold-standby system with the given maintenance facility.
Optimal design of a maintainable cold-standby system

International Nuclear Information System (INIS)

Yu Haiyang; Yalaoui, Farouk; Chatelet, Eric; Chu Chengbin

2007-01-01

This paper considers a framework to optimally design a maintainable cold-standby system. Not only the maintenance policy is to be determined, but also the reliability character of the components will be taken into account. Hence, the mean time to failure of the components and the policy time of good-as-new maintenances are proposed as decision variables. Following probability analyses, the system cost rate and the system availability are formulated as the optimization object and the constraint, respectively. Then, this optimization problem is directly resolved by recognizing its underlying properties. Moreover, the resolving procedure is found to be independent of the failure distributions of the components and the forms of the system cost, which is illustrated through a numerical example. As a conclusion, an exact method is successfully established to minimize the cost rate of a cold-standby system with the given maintenance facility
Optimal Vehicle Design Using the Integrated System and Cost Modeling Tool Suite

Science.gov (United States)

2010-08-01

Space Vehicle Costing ( ACEIT ) • New Small Sat Model Development & Production Cost O&M Cost Module  Radiation Exposure  Radiation Detector Response...Reliability OML Availability Risk l l Tools CEA, SRM Model, POST, ACEIT , Inflation Model, Rotor Blade Des, Microsoft Project, ATSV, S/1-iABP...space STK, SOAP – Specific mission • Space Vehicle Design (SMAD) • Space Vehicle Propulsion • Orbit Propagation • Space Vehicle Costing ( ACEIT ) • New
Contingency Contractor Optimization Phase 3 Sustainment Software Design Document - Contingency Contractor Optimization Tool - Prototype

Energy Technology Data Exchange (ETDEWEB)

Durfee, Justin David; Frazier, Christopher Rawls; Bandlow, Alisa; Jones, Katherine A

2016-05-01

This document describes the final software design of the Contingency Contractor Optimization Tool - Prototype. Its purpose is to provide the overall architecture of the software and the logic behind this architecture. Documentation for the individual classes is provided in the application Javadoc. The Contingency Contractor Optimization project is intended to address Department of Defense mandates by delivering a centralized strategic planning tool that allows senior decision makers to quickly and accurately assess the impacts, risks, and mitigation strategies associated with utilizing contract support. The Contingency Contractor Optimization Tool - Prototype was developed in Phase 3 of the OSD ATL Contingency Contractor Optimization project to support strategic planning for contingency contractors. The planning tool uses a model to optimize the Total Force mix by minimizing the combined total costs for selected mission scenarios. The model optimizes the match of personnel types (military, DoD civilian, and contractors) and capabilities to meet mission requirements as effectively as possible, based on risk, cost, and other requirements.
Optimal design of multi-state weighted k-out-of-n systems based on component design

International Nuclear Information System (INIS)

Li Wei; Zuo, Ming J.

2008-01-01

This paper presents a study on design optimization of multi-state weighted k-out-of-n systems. The studied system reliability model is more general than the traditional k-out-of-n system model. The system and its components are capable of assuming a whole range of performance levels, varying from perfect functioning to complete failure. A utility value corresponding to each state is used to indicate the corresponding performance level. A widely studied reliability optimization problem is the 'component selection problem', which involves selection of components with known reliability and cost characteristics. Less adequately addressed has been the problem of determining system cost and utility based on the relationships between component reliability, cost and utility. This paper addresses this topic. All the optimization problems dealt with in this paper can be categorized as either minimizing the expected total system cost subject to system reliability requirements, or maximizing system reliability subject to total system cost limitation. The resulting optimization problems are too complicated to be solved by traditional optimization approaches; therefore, genetic algorithm (GA) is used to solve them. Our results show that GA is a powerful tool for solving these kinds of problems
Cost optimization of wind turbines for large-scale offshore wind farms

International Nuclear Information System (INIS)

Fuglsang, P.; Thomsen, K.

1998-02-01

This report contains a preliminary investigation of site specific design of off-shore wind turbines for a large off-shore wind farm project at Roedsand that is currently being proposed by ELKRAFT/SEAS. The results were found using a design tool for wind turbines that involve numerical optimization and aeroelastic calculations of response. The wind climate was modeled in detail and a cost function was used to estimate costs from manufacture and installation. Cost of energy is higher for off-shore installations. A comparison of an off-shore wind farm site with a typical stand alone on-shore site showed an increase of the annual production of 28% due to the difference in wind climate. Extreme loads and blade fatigue loads were nearly identical, however,fatigue loads on other main components increased significantly. Optimizations were carried out to find the optimum overall off-shore wind turbine design. A wind turbine for the off-shore wind farm should be different compared with a stand-alone on-shore wind turbine. The overall design changed were increased swept area and rated power combined with reduced rotor speed and tower height. Cost was reduced by 12% for the final 5D/14D off-shore wind turbine from 0.306 DKr/kWh to 0.270 DKr/kWh. These figures include capital costs from manufacture and installation but not on-going costs from maintenance. These results make off-shore wind farms more competitive and comparable to the reference on-shore stand-alone wind turbine. A corresponding reduction of cost of energy could not be found for the stand alone on-shore wind turbine. Furthermore the fatigue loads on wind turbines in on-shore wind farms will increase and cost of energy will increase in favor of off-shore wind farms. (au) EFP-95; EU-JOULE-3; 21 tabs., 7 ills., 8 refs
Optimal soil venting design using Bayesian Decision analysis

OpenAIRE

Kaluarachchi, J. J.; Wijedasa, A. H.

1994-01-01

Remediation of hydrocarbon-contaminated sites can be costly and the design process becomes complex in the presence of parameter uncertainty. Classical decision theory related to remediation design requires the parameter uncertainties to be stipulated in terms of statistical estimates based on site observations. In the absence of detailed data on parameter uncertainty, classical decision theory provides little contribution in designing a risk-based optimal design strategy. Bayesian decision th...
Cost-Optimal ATCs in Zonal Electricity Markets

DEFF Research Database (Denmark)

Jensen, Tue Vissing; Kazempour, Jalal; Pinson, Pierre

2017-01-01

from the physical ATCs based on security indices only typically used in zonal electricity markets today. Determining cost-optimal ATCs requires viewing ATCs as an endogenous market construct, and leads naturally to the definition of a market entity whose responsibility is to optimize ATCs....... The optimization problem which this entity solves is a stochastic bilevel problem, which we decompose to yield a computationally tractable formulation. We show that cost-optimal ATCs depend non-trivially on the underlying network structure, and the problem of finding a setof cost-optimal ATCs is in general non...... by a factor of 2 or more, and ATCs which are zero between well-connected areas.Our results indicate that the perceived efficiency gap between zonal and nodal markets may be exagerrated if non-optimal ATCs are used....
Design search and optimization in aerospace engineering.

Science.gov (United States)

Keane, A J; Scanlan, J P

2007-10-15

In this paper, we take a design-led perspective on the use of computational tools in the aerospace sector. We briefly review the current state-of-the-art in design search and optimization (DSO) as applied to problems from aerospace engineering, focusing on those problems that make heavy use of computational fluid dynamics (CFD). This ranges over issues of representation, optimization problem formulation and computational modelling. We then follow this with a multi-objective, multi-disciplinary example of DSO applied to civil aircraft wing design, an area where this kind of approach is becoming essential for companies to maintain their competitive edge. Our example considers the structure and weight of a transonic civil transport wing, its aerodynamic performance at cruise speed and its manufacturing costs. The goals are low drag and cost while holding weight and structural performance at acceptable levels. The constraints and performance metrics are modelled by a linked series of analysis codes, the most expensive of which is a CFD analysis of the aerodynamics using an Euler code with coupled boundary layer model. Structural strength and weight are assessed using semi-empirical schemes based on typical airframe company practice. Costing is carried out using a newly developed generative approach based on a hierarchical decomposition of the key structural elements of a typical machined and bolted wing-box assembly. To carry out the DSO process in the face of multiple competing goals, a recently developed multi-objective probability of improvement formulation is invoked along with stochastic process response surface models (Krigs). This approach both mitigates the significant run times involved in CFD computation and also provides an elegant way of balancing competing goals while still allowing the deployment of the whole range of single objective optimizers commonly available to design teams.

Effects of cost metric on cost-effectiveness of protected-area network design in urban landscapes.

Science.gov (United States)

Burkhalter, J C; Lockwood, J L; Maslo, B; Fenn, K H; Leu, K

2016-04-01

A common goal in conservation planning is to acquire areas that are critical to realizing biodiversity goals in the most cost-effective manner. The way monetary acquisition costs are represented in such planning is an understudied but vital component to realizing cost efficiencies. We sought to design a protected-area network within a forested urban region that would protect 17 birds of conservation concern. We compared the total costs and spatial structure of the optimal protected-area networks produced using three acquisition-cost surrogates (area, agricultural land value, and tax-assessed land value). Using the tax-assessed land values there was a 73% and 78% cost savings relative to networks derived using area or agricultural land value, respectively. This cost reduction was due to the considerable heterogeneity in acquisition costs revealed in tax-assessed land values, especially for small land parcels, and the corresponding ability of the optimization algorithm to identify lower-cost parcels for inclusion that had equal value to our target species. Tax-assessed land values also reflected the strong spatial differences in acquisition costs (US$0.33/m(2)-$55/m(2)) and thus allowed the algorithm to avoid inclusion of high-cost parcels when possible. Our results add to a nascent but growing literature that suggests conservation planners must consider the cost surrogate they use when designing protected-area networks. We suggest that choosing cost surrogates that capture spatial- and size-dependent heterogeneity in acquisition costs may be relevant to establishing protected areas in urbanizing ecosystems. © 2015 Society for Conservation Biology.
Cost benefit analysis for optimization of radiation protection

International Nuclear Information System (INIS)

Lindell, B.

1984-01-01

ICRP recommends three basic principles for radiation protection. One is the justification of the source. Any use of radiation should be justified with regard to its benefit. The second is the optimization of radiation protection, i.e. all radiation exposure should be kept as low as resonably achievable. And the third principle is that there should be a limit for the radiation dose that any individual receives. Cost benefit assessment or cost benefit analysis is one tool to achieve the optimization, but the optimization is not identical with cost benefit analysis. Basically, in principle, the cost benefit analysis for the optimization of radiation protection is to find the minimum sum of the cost of protection and some cost of detriment. (Mori, K.)
Genetic algorithms applied to nuclear reactor design optimization

International Nuclear Information System (INIS)

Pereira, C.M.N.A.; Schirru, R.; Martinez, A.S.

2000-01-01

A genetic algorithm is a powerful search technique that simulates natural evolution in order to fit a population of computational structures to the solution of an optimization problem. This technique presents several advantages over classical ones such as linear programming based techniques, often used in nuclear engineering optimization problems. However, genetic algorithms demand some extra computational cost. Nowadays, due to the fast computers available, the use of genetic algorithms has increased and its practical application has become a reality. In nuclear engineering there are many difficult optimization problems related to nuclear reactor design. Genetic algorithm is a suitable technique to face such kind of problems. This chapter presents applications of genetic algorithms for nuclear reactor core design optimization. A genetic algorithm has been designed to optimize the nuclear reactor cell parameters, such as array pitch, isotopic enrichment, dimensions and cells materials. Some advantages of this genetic algorithm implementation over a classical method based on linear programming are revealed through the application of both techniques to a simple optimization problem. In order to emphasize the suitability of genetic algorithms for design optimization, the technique was successfully applied to a more complex problem, where the classical method is not suitable. Results and comments about the applications are also presented. (orig.)
Transportation package design using numerical optimization

International Nuclear Information System (INIS)

Harding, D.C.; Witkowski, W.R.

1993-01-01

Since the design of transportation packages involves a complex coupling of structural, thermal and radiation shielding analyses and must follow very strict design constraints, numerical optimization provides the potential for more efficient container designs. In numerical optimization, the requirements of the design problem are mathematically formulated through the use of an objective function and constraints. The objective function(s), e.g., package weight, cost, volume, or combination thereof, is the function to be minimized or maximized by altering a set of design variables that define the package's shape and dimensions. Constraints are limitations on the performance of the system, such as resisting structural and thermal accident environments. Two constraints defined for an example wire mesh composite Type B package are: 1) deformation in the containment vessel seal region remains small enough throughout the 10 CFR-71 accident conditions to meet containment criteria, and 2) the elastomeric seal region remains below its operational temperature limit to guarantee seal integrity in the fire environment. The first constraint of a minimum energy absorbing layer thickness is evaluated with finite element analyses of the proposed dynamic crush accident criteria. The second constraint is evaluated with a 1-D transient thermal finite difference code parametrized for variable composite layer thicknesses, and is integrated with the optimization process. (J.P.N.)
Robust Optimization of Fourth Party Logistics Network Design under Disruptions

Directory of Open Access Journals (Sweden)

Jia Li

2015-01-01

Full Text Available The Fourth Party Logistics (4PL network faces disruptions of various sorts under the dynamic and complex environment. In order to explore the robustness of the network, the 4PL network design with consideration of random disruptions is studied. The purpose of the research is to construct a 4PL network that can provide satisfactory service to customers at a lower cost when disruptions strike. Based on the definition of β-robustness, a robust optimization model of 4PL network design under disruptions is established. Based on the NP-hard characteristic of the problem, the artificial fish swarm algorithm (AFSA and the genetic algorithm (GA are developed. The effectiveness of the algorithms is tested and compared by simulation examples. By comparing the optimal solutions of the 4PL network for different robustness level, it is indicated that the robust optimization model can evade the market risks effectively and save the cost in the maximum limit when it is applied to 4PL network design.
Optimization of administrative management costs

OpenAIRE

Podolchak, N.; Chepil, B.

2015-01-01

It is important to determine the optimal level of administrative costs in order to achieve main targets of any enterprise, to perform definite tasks, to implement these tasks and not to worsen condition and motivation of the workers. Also it is essential to remember about strategic goals in the area of HR on the long run. The refore, the main idea in using optimization model for assessing the effectiveness of management costs will be to find the minimum level of expenses within the given l...
Numerical optimization of Combined Heat and Power Organic Rankine Cycles – Part A: Design optimization

International Nuclear Information System (INIS)

Martelli, Emanuele; Capra, Federico; Consonni, Stefano

2015-01-01

This two-part paper proposes an approach based on state-of-the-art numerical optimization methods for simultaneously determining the most profitable design and part-load operation of Combined Heat and Power Organic Rankine Cycles. Compared to the usual design practice, the important advantages of the proposed approach are (i) to consider the part-load performance of the ORC at the design stage, (ii) to optimize not only the cycle variables, but also the main turbine design variables (number of stages, stage loads, rotational speed). In this first part (Part A), the design model and the optimization algorithm are presented and tested on a real-world test case. PGS-COM, a recently proposed hybrid derivative-free algorithm, allows to efficiently tackle the challenging non-smooth black-box problem. - Highlights: • Algorithm for the simultaneous optimization Organic Rakine Cycle and turbine. • Thermodynamic and economic models of boiler, cycle, turbine are developed. • Non-smooth black-box optimization problem is successfully tackled with PGS-COM. • Test cases show that the algorithm returns optimal solutions within 4 min. • Toluene outperforms MDM (a siloxane) in terms of efficiency and costs.
Estimation of Partial Safety Factors and Target Failure Probability Based on Cost Optimization of Rubble Mound Breakwaters

DEFF Research Database (Denmark)

Kim, Seung-Woo; Suh, Kyung-Duck; Burcharth, Hans F.

2010-01-01

The breakwaters are designed by considering the cost optimization because a human risk is seldom considered. Most breakwaters, however, were constructed without considering the cost optimization. In this study, the optimum return period, target failure probability and the partial safety factors...
Marginal abatement cost curves and the optimal timing of mitigation measures

International Nuclear Information System (INIS)

Vogt-Schilb, Adrien; Hallegatte, Stéphane

2014-01-01

Decision makers facing abatement targets need to decide which abatement measures to implement, and in which order. Measure-explicit marginal abatement cost curves depict the cost and abating potential of available mitigation options. Using a simple intertemporal optimization model, we demonstrate why this information is not sufficient to design emission reduction strategies. Because the measures required to achieve ambitious emission reductions cannot be implemented overnight, the optimal strategy to reach a short-term target depends on longer-term targets. For instance, the best strategy to achieve European's −20% by 2020 target may be to implement some expensive, high-potential, and long-to-implement options required to meet the −75% by 2050 target. Using just the cheapest abatement options to reach the 2020 target can create a carbon-intensive lock-in and make the 2050 target too expensive to reach. Designing mitigation policies requires information on the speed at which various measures to curb greenhouse gas emissions can be implemented, in addition to the information on the costs and potential of such measures provided by marginal abatement cost curves. - Highlights: • Classification of existing Marginal Abatement Cost Curves (MACC). • MACCs do not provide separated data on the speed at which measures can be implemented. • Optimal measures to reach a short-term target depend on longer-term targets. • Unique carbon price or aggregated emission-reduction target may be insufficient. • Room for short-term sectoral policies if agents are myopic or governments cannot commit
Designing optimal greenhouse gas monitoring networks for Australia

Science.gov (United States)

Ziehn, T.; Law, R. M.; Rayner, P. J.; Roff, G.

2016-01-01

Atmospheric transport inversion is commonly used to infer greenhouse gas (GHG) flux estimates from concentration measurements. The optimal location of ground-based observing stations that supply these measurements can be determined by network design. Here, we use a Lagrangian particle dispersion model (LPDM) in reverse mode together with a Bayesian inverse modelling framework to derive optimal GHG observing networks for Australia. This extends the network design for carbon dioxide (CO2) performed by Ziehn et al. (2014) to also minimise the uncertainty on the flux estimates for methane (CH4) and nitrous oxide (N2O), both individually and in a combined network using multiple objectives. Optimal networks are generated by adding up to five new stations to the base network, which is defined as two existing stations, Cape Grim and Gunn Point, in southern and northern Australia respectively. The individual networks for CO2, CH4 and N2O and the combined observing network show large similarities because the flux uncertainties for each GHG are dominated by regions of biologically productive land. There is little penalty, in terms of flux uncertainty reduction, for the combined network compared to individually designed networks. The location of the stations in the combined network is sensitive to variations in the assumed data uncertainty across locations. A simple assessment of economic costs has been included in our network design approach, considering both establishment and maintenance costs. Our results suggest that, while site logistics change the optimal network, there is only a small impact on the flux uncertainty reductions achieved with increasing network size.
Need for Cost Optimization of Space Life Support Systems

Science.gov (United States)

Jones, Harry W.; Anderson, Grant

2017-01-01

As the nation plans manned missions that go far beyond Earth orbit to Mars, there is an urgent need for a robust, disciplined systems engineering methodology that can identify an optimized Environmental Control and Life Support (ECLSS) architecture for long duration deep space missions. But unlike the previously used Equivalent System Mass (ESM), the method must be inclusive of all driving parameters and emphasize the economic analysis of life support system design. The key parameter for this analysis is Life Cycle Cost (LCC). LCC takes into account the cost for development and qualification of the system, launch costs, operational costs, maintenance costs and all other relevant and associated costs. Additionally, an effective methodology must consider system technical performance, safety, reliability, maintainability, crew time, and other factors that could affect the overall merit of the life support system.
Machine Learning Techniques in Optimal Design

Science.gov (United States)

Cerbone, Giuseppe

1992-01-01

Many important applications can be formalized as constrained optimization tasks. For example, we are studying the engineering domain of two-dimensional (2-D) structural design. In this task, the goal is to design a structure of minimum weight that bears a set of loads. A solution to a design problem in which there is a single load (L) and two stationary support points (S1 and S2) consists of four members, E1, E2, E3, and E4 that connect the load to the support points is discussed. In principle, optimal solutions to problems of this kind can be found by numerical optimization techniques. However, in practice [Vanderplaats, 1984] these methods are slow and they can produce different local solutions whose quality (ratio to the global optimum) varies with the choice of starting points. Hence, their applicability to real-world problems is severely restricted. To overcome these limitations, we propose to augment numerical optimization by first performing a symbolic compilation stage to produce: (a) objective functions that are faster to evaluate and that depend less on the choice of the starting point and (b) selection rules that associate problem instances to a set of recommended solutions. These goals are accomplished by successive specializations of the problem class and of the associated objective functions. In the end, this process reduces the problem to a collection of independent functions that are fast to evaluate, that can be differentiated symbolically, and that represent smaller regions of the overall search space. However, the specialization process can produce a large number of sub-problems. This is overcome by deriving inductively selection rules which associate problems to small sets of specialized independent sub-problems. Each set of candidate solutions is chosen to minimize a cost function which expresses the tradeoff between the quality of the solution that can be obtained from the sub-problem and the time it takes to produce it. The overall solution
Techno-economic optimization for the design of solar chimney power plants

International Nuclear Information System (INIS)

Ali, Babkir

2017-01-01

Highlights: • Chimney height and collector area of different designs were optimized. • Simple actual and minimum payback periods were developed. • Comparative assessment was conducted for different designs configuration. • Effects of uncertain parameters on the payback period were studied. - Abstract: This paper aims to propose a methodology for optimization of solar chimney power plants taking into account the techno-economic parameters. The indicator used for optimization is the comparison between the actual achieved simple payback period for the design and the minimum possible (optimum) simple payback period as a reference. An optimization model was executed for different twelve designs in the range 5–200 MW to cover reinforced concrete chimney, sloped collector, and floating chimney. The height of the chimney was optimized and the associated collector area was calculated accordingly. Relationships between payback periods, electricity price, and the peak power capacity of each power plant were developed. The resulted payback periods for the floating chimney power plants were the shortest compared to the other studied designs. For a solar chimney power plant with 100 MW at electricity price 0.10 USD/kWh, the simple payback period for the reference case was 4.29 years for floating chimney design compared to 23.47 and 16.88 years for reinforced concrete chimney and sloped collector design, respectively. After design optimization for 100 MW power plant of each of reinforced concrete, sloped collector, and floating chimney, a save of 19.63, 2.22, and 2.24 million USD, respectively from the initial cost of the reference case is achieved. Sensitivity analysis was conducted in this study to evaluate the impacts of varied running cost, solar radiation, and electricity price on the payback periods of solar chimney power plant. Floating chimney design is still performing after applying the highest ratio of annual running cost to the annual revenue. The
A comparison of the economic benefits of centralized and distributed model predictive control strategies for optimal and sub-optimal mine dewatering system designs

International Nuclear Information System (INIS)

Romero, Alberto; Millar, Dean; Carvalho, Monica; Maestre, José M.; Camacho, Eduardo F.

2015-01-01

Mine dewatering can represent up to 5% of the total energy demand of a mine, and is one of the mine systems that aim to guarantee safe operating conditions. As mines go deeper, dewatering pumping heads become bigger, potentially involving several lift stages. Greater depth does not only mean greater dewatering cost, but more complex systems that require more sophisticated control systems, especially if mine operators wish to gain benefits from demand response incentives that are becoming a routine part of electricity tariffs. This work explores a two stage economic optimization procedure of an underground mine dewatering system, comprising two lifting stages, each one including a pump station and a water reservoir. First, the system design is optimized considering hourly characteristic dewatering demands for twelve days, one day representing each month of the year to account for seasonal dewatering demand variations. This design optimization minimizes the annualized cost of the system, and therefore includes the investment costs in underground reservoirs. Reservoir size, as well as an hourly pumping operation plan are calculated for specific operating environments, defined by characteristic hourly electricity prices and water inflows (seepage and water use from production activities), at best known through historical observations for the previous year. There is no guarantee that the system design will remain optimal when it faces the water inflows and market determined electricity prices of the year ahead, or subsequent years ahead, because these remain unknown at design time. Consequently, the dewatering optimized system design is adopted subsequently as part of a Model Predictive Control (MPC) strategy that adaptively maintains optimality during the operations phase. Centralized, distributed and non-centralized MPC strategies are explored. Results show that the system can be reliably controlled using any of these control strategies proposed. Under the operating
An Invocation Cost Optimization Method for Web Services in Cloud Environment

Directory of Open Access Journals (Sweden)

Lianyong Qi

2017-01-01

Full Text Available The advent of cloud computing technology has enabled users to invoke various web services in a “pay-as-you-go” manner. However, due to the flexible pricing model of web services in cloud environment, a cloud user’ service invocation cost may be influenced by many factors (e.g., service invocation time, which brings a great challenge for cloud users’ cost-effective web service invocation. In view of this challenge, in this paper, we first investigate the multiple factors that influence the invocation cost of a cloud service, for example, user’s job size, service invocation time, and service quality level; and afterwards, a novel Cloud Service Cost Optimization Method named CS-COM is put forward, by considering the above multiple impact factors. Finally, a set of experiments are designed, deployed, and tested to validate the feasibility of our proposal in terms of cost optimization. The experiment results show that our proposed CS-COM method outperforms other related methods.
Optimal synthesis and design of the number of cycles in the leaching process for surimi production.

Science.gov (United States)

Reinheimer, M Agustina; Scenna, Nicolás J; Mussati, Sergio F

2016-12-01

Water consumption required during the leaching stage in the surimi manufacturing process strongly depends on the design and the number and size of stages connected in series for the soluble protein extraction target, and it is considered as the main contributor to the operating costs. Therefore, the optimal synthesis and design of the leaching stage is essential to minimize the total annual cost. In this study, a mathematical optimization model for the optimal design of the leaching operation is presented. Precisely, a detailed Mixed Integer Nonlinear Programming (MINLP) model including operating and geometric constraints was developed based on our previous optimization model (NLP model). Aspects about quality, water consumption and main operating parameters were considered. The minimization of total annual costs, which considered a trade-off between investment and operating costs, led to an optimal solution with lesser number of stages (2 instead of 3 stages) and higher volumes of the leaching tanks comparing with previous results. An analysis was performed in order to investigate how the optimal solution was influenced by the variations of the unitary cost of fresh water, waste treatment and capital investment.
Simulative design and process optimization of the two-stage stretch-blow molding process

Energy Technology Data Exchange (ETDEWEB)

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

2015-05-22

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

International Nuclear Information System (INIS)

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

2015-01-01

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

Science.gov (United States)

Tian, Jiandong; Cheng, Jilin; Gong, Yi

2018-03-01

Accelerated urbanization places extraordinary demands on sewer networks; thus optimization research to improve the design of these systems has practical significance. In this article, a subsystem nonlinear programming model is developed to optimize pumping station layout and sewage pipe network design. The subsystem model is expanded into a large-scale complex nonlinear programming system model to find the minimum total annual cost of the pumping station and network of all pipe segments. A comparative analysis is conducted using the sewage network in Taizhou City, China, as an example. The proposed method demonstrated that significant cost savings could have been realized if the studied system had been optimized using the techniques described in this article. Therefore, the method has practical value for optimizing urban sewage projects and provides a reference for theoretical research on optimization of urban drainage pumping station layouts.
Pareto Optimal Design for Synthetic Biology.

Science.gov (United States)

Patanè, Andrea; Santoro, Andrea; Costanza, Jole; Carapezza, Giovanni; Nicosia, Giuseppe

2015-08-01

Recent advances in synthetic biology call for robust, flexible and efficient in silico optimization methodologies. We present a Pareto design approach for the bi-level optimization problem associated to the overproduction of specific metabolites in Escherichia coli. Our method efficiently explores the high dimensional genetic manipulation space, finding a number of trade-offs between synthetic and biological objectives, hence furnishing a deeper biological insight to the addressed problem and important results for industrial purposes. We demonstrate the computational capabilities of our Pareto-oriented approach comparing it with state-of-the-art heuristics in the overproduction problems of i) 1,4-butanediol, ii) myristoyl-CoA, i ii) malonyl-CoA , iv) acetate and v) succinate. We show that our algorithms are able to gracefully adapt and scale to more complex models and more biologically-relevant simulations of the genetic manipulations allowed. The Results obtained for 1,4-butanediol overproduction significantly outperform results previously obtained, in terms of 1,4-butanediol to biomass formation ratio and knock-out costs. In particular overproduction percentage is of +662.7%, from 1.425 mmolh⁻¹gDW⁻¹ (wild type) to 10.869 mmolh⁻¹gDW⁻¹, with a knockout cost of 6. Whereas, Pareto-optimal designs we have found in fatty acid optimizations strictly dominate the ones obtained by the other methodologies, e.g., biomass and myristoyl-CoA exportation improvement of +21.43% (0.17 h⁻¹) and +5.19% (1.62 mmolh⁻¹gDW⁻¹), respectively. Furthermore CPU time required by our heuristic approach is more than halved. Finally we implement pathway oriented sensitivity analysis, epsilon-dominance analysis and robustness analysis to enhance our biological understanding of the problem and to improve the optimization algorithm capabilities.

STANDALONE PHOTOVOLTAIC SYSTEMS SIZING OPTIMIZATION USING DESIGN SPACE APPROACH: CASE STUDY FOR RESIDENTIAL LIGHTING LOAD

Directory of Open Access Journals (Sweden)

D. F. AL RIZA

2015-07-01

Full Text Available This paper presents a sizing optimization methodology of panel and battery capacity in a standalone photovoltaic system with lighting load. Performance of the system is identified by performing Loss of Power Supply Probability (LPSP calculation. Input data used for the calculation is the daily weather data and system components parameters. Capital Cost and Life Cycle Cost (LCC is calculated as optimization parameters. Design space for optimum system configuration is identified based on a given LPSP value, Capital Cost and Life Cycle Cost. Excess energy value is used as an over-design indicator in the design space. An economic analysis, including cost of the energy and payback period, for selected configurations are also studied.
A Study on Development of a Cost Optimal and Energy Saving Building Model: Focused on Industrial Building

Directory of Open Access Journals (Sweden)

Hye Yeon Kim

2016-03-01

Full Text Available This study suggests an optimization method for the life cycle cost (LCC in an economic feasibility analysis when applying energy saving techniques in the early design stage of a building. Literature and previous studies were reviewed to select appropriate optimization and LCC analysis techniques. The energy simulation (Energy Plus and computational program (MATLAB were linked to provide an automated optimization process. From the results, it is suggested that this process could outline the cost optimization model with which it is possible to minimize the LCC. To aid in understanding the model, a case study on an industrial building was performed to outline the operations of the cost optimization model including energy savings. An energy optimization model was also presented to illustrate the need for the cost optimization model.
A combined geostatistical-optimization model for the optimal design of a groundwater quality monitoring network

Science.gov (United States)

Kolosionis, Konstantinos; Papadopoulou, Maria P.

2017-04-01

Monitoring networks provide essential information for water resources management especially in areas with significant groundwater exploitation due to extensive agricultural activities. In this work, a simulation-optimization framework is developed based on heuristic optimization methodologies and geostatistical modeling approaches to obtain an optimal design for a groundwater quality monitoring network. Groundwater quantity and quality data obtained from 43 existing observation locations at 3 different hydrological periods in Mires basin in Crete, Greece will be used in the proposed framework in terms of Regression Kriging to develop the spatial distribution of nitrates concentration in the aquifer of interest. Based on the existing groundwater quality mapping, the proposed optimization tool will determine a cost-effective observation wells network that contributes significant information to water managers and authorities. The elimination of observation wells that add little or no beneficial information to groundwater level and quality mapping of the area can be obtain using estimations uncertainty and statistical error metrics without effecting the assessment of the groundwater quality. Given the high maintenance cost of groundwater monitoring networks, the proposed tool could used by water regulators in the decision-making process to obtain a efficient network design that is essential.
Automated magnetic divertor design for optimal power exhaust

Energy Technology Data Exchange (ETDEWEB)

Blommaert, Maarten

2017-07-01

The so-called divertor is the standard particle and power exhaust system of nuclear fusion tokamaks. In essence, the magnetic configuration hereby 'diverts' the plasma to a specific divertor structure. The design of this divertor is still a key issue to be resolved to evolve from experimental fusion tokamaks to commercial power plants. The focus of this dissertation is on one particular design requirement: avoiding excessive heat loads on the divertor structure. The divertor design process is assisted by plasma edge transport codes that simulate the plasma and neutral particle transport in the edge of the reactor. These codes are computationally extremely demanding, not in the least due to the complex collisional processes between plasma and neutrals that lead to strong radiation sinks and macroscopic heat convection near the vessel walls. One way of improving the heat exhaust is by modifying the magnetic confinement that governs the plasma flow. In this dissertation, automated design of the magnetic configuration is pursued using adjoint based optimization methods. A simple and fast perturbation model is used to compute the magnetic field in the vacuum vessel. A stable optimal design method of the nested type is then elaborated that strictly accounts for several nonlinear design constraints and code limitations. Using appropriate cost function definitions, the heat is spread more uniformly over the high-heat load plasma-facing components in a practical design example. Furthermore, practical in-parts adjoint sensitivity calculations are presented that provide a way to an efficient optimization procedure. Results are elaborated for a fictituous JET (Joint European Torus) case. The heat load is strongly reduced by exploiting an expansion of the magnetic flux towards the solid divertor structure. Subsequently, shortcomings of the perturbation model for magnetic field calculations are discussed in comparison to a free boundary equilibrium (FBE) simulation
Automated magnetic divertor design for optimal power exhaust

International Nuclear Information System (INIS)

Blommaert, Maarten

2017-01-01

The so-called divertor is the standard particle and power exhaust system of nuclear fusion tokamaks. In essence, the magnetic configuration hereby 'diverts' the plasma to a specific divertor structure. The design of this divertor is still a key issue to be resolved to evolve from experimental fusion tokamaks to commercial power plants. The focus of this dissertation is on one particular design requirement: avoiding excessive heat loads on the divertor structure. The divertor design process is assisted by plasma edge transport codes that simulate the plasma and neutral particle transport in the edge of the reactor. These codes are computationally extremely demanding, not in the least due to the complex collisional processes between plasma and neutrals that lead to strong radiation sinks and macroscopic heat convection near the vessel walls. One way of improving the heat exhaust is by modifying the magnetic confinement that governs the plasma flow. In this dissertation, automated design of the magnetic configuration is pursued using adjoint based optimization methods. A simple and fast perturbation model is used to compute the magnetic field in the vacuum vessel. A stable optimal design method of the nested type is then elaborated that strictly accounts for several nonlinear design constraints and code limitations. Using appropriate cost function definitions, the heat is spread more uniformly over the high-heat load plasma-facing components in a practical design example. Furthermore, practical in-parts adjoint sensitivity calculations are presented that provide a way to an efficient optimization procedure. Results are elaborated for a fictituous JET (Joint European Torus) case. The heat load is strongly reduced by exploiting an expansion of the magnetic flux towards the solid divertor structure. Subsequently, shortcomings of the perturbation model for magnetic field calculations are discussed in comparison to a free boundary equilibrium (FBE) simulation. These flaws
Cost-constrained design point for the Reversed-Field Pinch Reactor (RFPR)

International Nuclear Information System (INIS)

Hagenson, R.L.; Krakowski, R.A.

1978-01-01

A broad spectrum of Reversed-Field Pinch Reactor (RFPR) operating modes are compared on an economics basis. An RFPR with superconducting coils and an air-core poloidal field transformer optimizes to give a minimum cost system when compared to normal-conducting coils and the iron-core transformer used in earlier designs. An interim design is described that exhibits a thermally stable, unrefueled, 21 s burn (burnup 50 percent) with an energy containment time equal to 200 times the Bohm time, which is consistent with present-day tokamak experiments. This design operates near the minimum energy state (THETA = B/sub THETA/(r/sub w/)/[B/sub z/] = 2.0 and F = B/sub z/(r/sub w/)/[B/sub z/] = 1.0 from the High Beta Model) of the RFP configuration. This cost-optimized design produces a reactor of 1.5-m minor radius and 12.8-m major radius, that generates 1000 MWe (net) with a recirculating power fraction of 0.15 at a direct capital cost of 970 $/kWe
Design of optimal wind farm configuration using a binary particle swarm optimization at Huasai district, Southern Thailand

International Nuclear Information System (INIS)

Pookpunt, Sittichoke; Ongsakul, Weerakorn

2016-01-01

Highlights: • Real wind data form a wind distributed map use in wind farm optimization algorithm. • Practical cost benefit is evaluated in the objective function. • Learning curve is developed to determine a wind farm cost model. • BPSO-TVAC simultaneously optimizes wind farm spacing, position, sizing, hub height. • Optimal placement shows improvement of operating income over conventional layout. - Abstract: This paper proposes the design of optimal wind farm configuration using a new wind probability distribution map at Huasai district, the east coast of Southern Thailand. The new wind probability distribution map integrates both frequency of wind speed and direction data at a monitoring site. The linear wake effect model is used to determine the wind speed at downstream turbines for the total power extraction from a wind farm array. The component cost model and learning curve is used to express the initial investment cost, levelized cost and the annual energy production cost of a wind farm, depending on the number of wind turbines, the installed size, hub height and wake loss within a wind farm. Based on Thailand wind energy selling price consisting of the fixed wind premium on top of base tariff, the profit depends on revenue of selling electricity and cost of energy. In this paper, Binary Particle Swarm Optimization with Time-Varying Acceleration Coefficients (BPSO-TVAC) is proposed to maximize profit subject to turbine position, turbine size, hub height, annual energy production, investment budget, land lease cost, operation and maintenance cost and levelized replacement cost constraints. Test results indicate that BPSO-TVAC optimally locate wind turbines directly facing the high frequent wind speed and direction, leading to a higher profit than the conventional wind farm layout.
Cost optimization on example of hotel-restaurant complex enterprises

Directory of Open Access Journals (Sweden)

Volkovska I.V.

2017-08-01

Full Text Available Optimization of costs is important for increasing competitiveness and profitability of the enterprise, therefore, the purpose of the study is to establish and visualize the basis of cost optimization on the example of hotel-restaurant complex enterprises. The essence of cost optimization is investigated through the analysis of the views of various scholars for this purpose. It is established that cost optimization is the process of planning, accounting, analysis, cost control for searching and selecting of the most effective methods of managing of the conditions of limited resources. The author has developed the sequence of cost optimization on the example of enterprises of the hotel-restaurant complex, which helps to structure the process of cost management. In this sequence, there are areas where costs can be reduced, and the technical and economic conditions under which they can be changed. In addition, it is noted that such implementation is important in the cost management at the enterprise. It is also proposed to optimize costs using the simplex method to carry out a quantitative assessment of the quality of services by the qualimetric method. It is noted that it is necessary to form alternative ways of using resources for rational use of scarce resources. The article proposes cost grouping by the XYZ-analysis with individual approaches to cost management, namely, target costing, the theory of constrains, lean manufacturing. For this purpose, the author develops the table that should be filled in to compare which costs and ways can be reduced or replaced. Besides, the author has added recommendations for filling in the table and commented that with this analysis a transaction and unreasonable costs can be controlled. Thus, with such a sequence of actions, redistribution of funds is possible to optimize costs and save money, which can be directed to enterprise development. The conclusion is made of the need of system analysis to use
Mechanical Design Optimization Using Advanced Optimization Techniques

CERN Document Server

Rao, R Venkata

2012-01-01

Mechanical design includes an optimization process in which designers always consider objectives such as strength, deflection, weight, wear, corrosion, etc. depending on the requirements. However, design optimization for a complete mechanical assembly leads to a complicated objective function with a large number of design variables. It is a good practice to apply optimization techniques for individual components or intermediate assemblies than a complete assembly. Analytical or numerical methods for calculating the extreme values of a function may perform well in many practical cases, but may fail in more complex design situations. In real design problems, the number of design parameters can be very large and their influence on the value to be optimized (the goal function) can be very complicated, having nonlinear character. In these complex cases, advanced optimization algorithms offer solutions to the problems, because they find a solution near to the global optimum within reasonable time and computational ...
Low-cost modular array-field designs for flat-panel and concentrator photovoltaic systems

Science.gov (United States)

Post, H. N.; Carmichael, D. C.; Alexander, G.; Castle, J. A.

1982-09-01

Described are the design and development of low-cost, modular array fields for flat-panel and concentrator photovoltaic (PV) systems. The objective of the work was to reduce substantially the cost of the array-field Balance-of-System (BOS) subsystems and site-specific design costs as compared to previous PV installations. These subsystems include site preparation, foundations, support structures, electrical writing, grounding, lightning protection, electromagnetic interference considerations, and controls. To reduce these BOS and design costs, standardized modular (building-block) designs for flat-panel and concentrator array fields have been developed that are fully integrated and optimized for lowest life-cycle costs. Using drawings and specifications now available, these building-block designs can be used in multiples to install various size array fields. The developed designs are immediately applicable (1982) and reduce the array-field BOS costs to a fraction of previous costs.
Least-cost groundwater remediation design using uncertain hydrogeological information. 1998 annual progress report

International Nuclear Information System (INIS)

Pinder, G.F.

1998-01-01

'The objective of the project is to formulate, test, and evaluate a new approach to the least-cost design of groundwater contamination containment and decontamination systems. The proposed methodology employs robust optimization, the outer-approximation method of non-linear programming, and groundwater flow and transport modeling to find the most cost-effective pump-and-treat design possible given the physical parameters describing the groundwater reservoir are known with uncertainty. The result is a methodology that will provide the least-cost groundwater remediation design possible given a specified set of design objectives and physical and sociological constraints. As of the end of the first year of this 3-year project the author has developed and tested the concept of robust optimization within the framework of least-cost groundwater-contamination-containment design. The outer-approximation method has been employed in this context for the relatively simple linear-constraint case associated with the containment problem. In an effort to enhance the efficiency and applicability of this methodology, a new strategy for selecting the various realizations arising out of the Monte-Carlo underpinnings of the robust-optimization technique has been developed and tested. Based upon observations arising out of this work a yet more promising approach has been discovered. The theoretical foundation for this most recent approach has been, and continues to be, the primary focus of the research.'
Design of High-Efficiency and Low-Cost Six-Phase Permanent Magnet Synchronous Generator for Direct-Drive Small-Scale Wind Power Application

Directory of Open Access Journals (Sweden)

M. E. Moazzen

2017-06-01

Full Text Available Permanent magnet synchronous generators (PMSG have a huge potential for direct-drive wind power applications. Therefore, optimal design of these generators is necessary to maximize their efficiency and to reduce their manufacturing cost and total volume. In this paper, an optimal design of a six-phase 3.5 KW direct-drive PMSG to generate electricity for domestic needs is performed. The aim of optimal design is to reduce the manufacturing cost, losses and total volume of PMSG. To find the best design, single/multi-objective design optimization is carried out. Cuckoo optimization algorithm (COA is adopted to solve the optimization problem. Comparison between the results of the single-objective and multi-objective models shows that simultaneous optimization of manufacturing cost, losses and total volume leads to more suitable design for PMSG. Finally, finite-element method (FEM is employed to validate the optimal design, which show a good agreement between the theoretical work and simulation results.
Integrated design and optimization of technologies for utilizing low grade heat in process industries

International Nuclear Information System (INIS)

Kwak, Dong-Hun; Binns, Michael; Kim, Jin-Kuk

2014-01-01

Highlights: • Implementation of a modeling and design framework for the utilization of low grade heat. • Application of process simulator and optimization techniques for the design of technologies for heat recovery. • Systematic and holistic exploitation for the recovery of industrial low grade heat. • Demonstration of the applicability and benefit of integrated design and optimization framework through a case study. - Abstract: The utilization of low grade heat in process industries has significant potential for improving site-wide energy efficiency. This paper focuses on the techno-economic analysis of key technologies for energy recovery and re-use, namely: Organic Rankine Cycles (ORC), boiler feed water heating, heat pumping and absorption refrigeration in the context of process integration. Process modeling and optimization in a holistic manner identifies the optimal integrated configuration of these technologies, with rigorous assessment of costs and technical feasibility of these technologies. For the systematic screening and evaluation of design options, detailed process simulator models are evaluated and optimization proceeds subject to design constraints for the particular economic scenarios where technology using low grade heat is introduced into the process site. Case studies are presented to illustrate how the proposed modeling and optimization framework can be useful and effective in practice, in terms of providing design guidelines and conceptual insights for the application of technologies using low grade heat. From the case study, the best options during winter are the ORC giving a 6.4% cost reduction for the ideal case with low grade heat available at a fixed temperature and boiler feed water heating giving a 2.5% cost reduction for the realistic case with low grade heat available at a range of temperatures. Similarly during summer boiler feed water heating was found to be the best option giving a 3.1% reduction of costs considering a
Optimal design of RTCs in digital circuit fault self-repair based on global signal optimization

Institute of Scientific and Technical Information of China (English)

Zhang Junbin; Cai Jinyan; Meng Yafeng

2016-01-01

Since digital circuits have been widely and thoroughly applied in various fields, electronic systems are increasingly more complicated and require greater reliability. Faults may occur in elec-tronic systems in complicated environments. If immediate field repairs are not made on the faults, elec-tronic systems will not run normally, and this will lead to serious losses. The traditional method for improving system reliability based on redundant fault-tolerant technique has been unable to meet the requirements. Therefore, on the basis of (evolvable hardware)-based and (reparation balance technology)-based electronic circuit fault self-repair strategy proposed in our preliminary work, the optimal design of rectification circuits (RTCs) in electronic circuit fault self-repair based on global sig-nal optimization is deeply researched in this paper. First of all, the basic theory of RTC optimal design based on global signal optimization is proposed. Secondly, relevant considerations and suitable ranges are analyzed. Then, the basic flow of RTC optimal design is researched. Eventually, a typical circuit is selected for simulation verification, and detailed simulated analysis is made on five circumstances that occur during RTC evolution. The simulation results prove that compared with the conventional design method based RTC, the global signal optimization design method based RTC is lower in hardware cost, faster in circuit evolution, higher in convergent precision, and higher in circuit evolution success rate. Therefore, the global signal optimization based RTC optimal design method applied in the elec-tronic circuit fault self-repair technology is proven to be feasible, effective, and advantageous.
Demand-Based Optimal Design of Storage Tank with Inerter System

Directory of Open Access Journals (Sweden)

Shiming Zhang

2017-01-01

Full Text Available A parameter optimal design method for a tank with an inerter system is proposed in this study based on the requirements of tank vibration control to improve the effectiveness and efficiency of vibration control. Moreover, a response indicator and a cost control indicator are selected based on the control targets for liquid storage tanks for simultaneously minimizing the dynamic response and controlling costs. These indicators are reformulated through a random vibration analysis under virtual excitation. The problem is then transformed from a multiobjective optimization problem to a single-objective nonlinear problem using the ε-constraint method, which is consistent with the demand-based method. White noise excitation can be used to design the tank with the inerter system under seismic excitation to simplify the calculation. Subsequently, a MATLAB-based calculation program is compiled, and several optimization cases are examined under different excitation conditions. The effectiveness of the demand-based method is proven through a time history analysis. The results show that specific vibration control requirements can be met at the lowest cost with a simultaneous reduction in base shears and overturning base moments.
Fusion blanket design and optimization techniques

International Nuclear Information System (INIS)

Gohar, Y.

2005-01-01

In fusion reactors, the blanket design and its characteristics have a major impact on the reactor performance, size, and economics. The selection and arrangement of the blanket materials, dimensions of the different blanket zones, and different requirements of the selected materials for a satisfactory performance are the main parameters, which define the blanket performance. These parameters translate to a large number of variables and design constraints, which need to be simultaneously considered in the blanket design process. This represents a major design challenge because of the lack of a comprehensive design tool capable of considering all these variables to define the optimum blanket design and satisfying all the design constraints for the adopted figure of merit and the blanket design criteria. The blanket design techniques of the First Wall/Blanket/Shield Design and Optimization System (BSDOS) have been developed to overcome this difficulty and to provide the state-of-the-art techniques and tools for performing blanket design and analysis. This report describes some of the BSDOS techniques and demonstrates its use. In addition, the use of the optimization technique of the BSDOS can result in a significant blanket performance enhancement and cost saving for the reactor design under consideration. In this report, examples are presented, which utilize an earlier version of the ITER solid breeder blanket design and a high power density self-cooled lithium blanket design for demonstrating some of the BSDOS blanket design techniques
Enabling Parametric Optimal Ascent Trajectory Modeling During Early Phases of Design

Science.gov (United States)

Holt, James B.; Dees, Patrick D.; Diaz, Manuel J.

2015-01-01

During the early phases of engineering design, the costs committed are high, costs incurred are low, and the design freedom is high. It is well documented that decisions made in these early design phases drive the entire design's life cycle. In a traditional paradigm, key design decisions are made when little is known about the design. As the design matures, design changes become more difficult -- in both cost and schedule -- to enact. Indeed, the current capability-based paradigm that has emerged because of the constrained economic environment calls for the infusion of knowledge acquired during later design phases into earlier design phases, i.e. bring knowledge acquired during preliminary and detailed design into pre-conceptual and conceptual design. An area of critical importance to launch vehicle design is the optimization of its ascent trajectory, as the optimal trajectory will be able to take full advantage of the launch vehicle's capability to deliver a maximum amount of payload into orbit. Hence, the optimal ascent trajectory plays an important role in the vehicle's affordability posture as the need for more economically viable access to space solutions are needed in today's constrained economic environment. The problem of ascent trajectory optimization is not a new one. There are several programs that are widely used in industry that allows trajectory analysts to, based on detailed vehicle and insertion orbit parameters, determine the optimal ascent trajectory. Yet, little information is known about the launch vehicle early in the design phase - information that is required of many different disciplines in order to successfully optimize the ascent trajectory. Thus, the current paradigm of optimizing ascent trajectories involves generating point solutions for every change in a vehicle's design parameters. This is often a very tedious, manual, and time-consuming task for the analysts. Moreover, the trajectory design space is highly non-linear and multi
Space tourism optimized reusable spaceplane design

Energy Technology Data Exchange (ETDEWEB)

Penn, J.P.; Lindley, C.A. [The Aerospace Corporation El Segundo, California90245-4691 (United States)

1997-01-01

Market surveys suggest that a viable space tourism industry will require flight rates about two orders of magnitude higher than those required for conventional spacelift. Although enabling round-trip cost goals for a viable space tourism business are about {dollar_sign}240 per pound ({dollar_sign}529/kg), or {dollar_sign}72,000 per passenger round-trip, goals should be about {dollar_sign}50 per pound ({dollar_sign}110/kg) or approximately {dollar_sign}15,000 for a typical passenger and baggage. The lower price will probably open space tourism to the general population. Vehicle reliabilities must approach those of commercial aircraft as closely as possible. This paper addresses the development of spaceplanes optimized for the ultra-high flight rate and high reliability demands of the space tourism mission. It addresses the fundamental operability, reliability, and cost drivers needed to satisfy this mission need. Figures of merit similar to those used to evaluate the economic viability of conventional commercial aircraft are developed, including items such as payload/vehicle dry weight, turnaround time, propellant cost per passenger, and insurance and depreciation costs, which show that infrastructure can be developed for a viable space tourism industry. A reference spaceplane design optimized for space tourism is described. Subsystem allocations for reliability, operability, and costs are made and a route to developing such a capability is discussed. The vehicle{close_quote}s ability to also satisfy the traditional spacelift market is shown. {copyright} {ital 1997 American Institute of Physics.}
Design Optimization of Transformerless Grid-Connected PV Inverters Including Reliability

OpenAIRE

Koutroulis, Eftichios; Blaabjerg, Frede

2013-01-01

This paper presents a new methodology for optimal design of transformerless photovoltaic (PV) inverters targeting a cost-effective deployment of grid-connected PV systems. The optimal switching frequency as well as the optimal values and types of the PV inverter components is calculated such that the PV inverter LCOE generated during the PV system lifetime period is minimized. The LCOE is also calculated considering the failure rates of the components, which affect the reliability performance...
Optimal design of district heating and cooling pipe network of seawater-source heat pump

Energy Technology Data Exchange (ETDEWEB)

Li, Xiang-li; Duanmu, Lin; Shu, Hai-wen [School of Civil and Hydraulic Engineering, Dalian University of Technology, Dalian, Liaoning Province 116024 (China)

2010-01-15

The district heating and cooling (DHC) system of a seawater-source heat pump is large system engineering. The investments and the operational cost of DHC pipe network are higher than a tradition system. Traditional design methods only satisfy the needs of the technology but dissatisfy the needs of the economy, which not only waste a mass of money but also bring problems to the operation, the maintenance and the management. So we build a least-annualized-cost global optimal mathematic model that comprises all constrict conditions. Furthermore, this model considers the variety of heating load and cooling load, the operational adjustment in different periods of the year. Genetic algorithm (GA) is used to obtain the optimal combinations of discrete diameters. Some operators of GA are selected to reduce the calculation time and obtain good calculation accuracy. This optimal method is used to the design of the DHC network of Xinghai Bay commercial district which is a real engineering. The design optimization can avoid the matter of the hydraulic unbalance of the system, enhance the running efficiency and greatly reduce the annualized-cost comparing with the traditional design method. (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.
Efficiency and cost optimization of a regenerative Organic Rankine Cycle power plant through the multi-objective approach

International Nuclear Information System (INIS)

Gimelli, A.; Luongo, A.; Muccillo, M.

2017-01-01

Highlights: • Multi-objective optimization method for ORC design has been addressed. • Trade-off between electric efficiency and overall heat exchangers area is evaluated. • The heat exchangers area was used as objective function to minimize the plant cost. • MDM was considered as organic working fluid for the thermodynamic cycle. • Electric efficiency: 14.1–18.9%. Overall heat exchangers area: 446–1079 m 2 . - Abstract: Multi-objective optimization could be, in the industrial sector, a fundamental strategic approach for defining the target design specifications and operating parameters of new competitive products for the market, especially in renewable energy and energy savings fields. Vector optimization mostly enabled the determination of a set of optimal solutions characterized by different costs, sizes, efficiencies and other key features. The designer can subsequently select the solution with the best compromise between the objective functions for the specific application and constraints. In this paper, a multi-objective optimization problem addressing an Organic Rankine Cycle system is solved with consideration for the electric efficiency and overall heat exchangers area as quantities that should be optimized. In fact, considering that the overall capital cost of the ORC system is dominated by the cost of the heat exchangers rather than that of the pump and turbine, this area is related to the cost of the plant and so it was used to indirectly optimize the economic system performance. For this reason, although cost data have not been used, the heat exchangers area was used as a second objective function to minimize the plant cost. Pareto optimal solutions highlighted a trade-off between the two conflicting objective functions. Octamethyltrisiloxane (MDM) was considered organic working fluid, while the following input parameters were used as decision variables: minimum and maximum pressure of the thermodynamic cycle; superheating and subcooling
Optimal Design of the Feeder-Bus Network Based on the Transfer System

Directory of Open Access Journals (Sweden)

Lianbo Deng

2013-01-01

Full Text Available This paper studied the classic feeder-bus network design problem (FBNDP, which can be described as follows: for the passenger travel demand between rail stations and bus stops on a given urban transit network, it designs the optimal feeder bus routes and frequencies so as to minimize the passengers’ travel expense and the operator’s cost. We extended the demand pattern of M-to-1 in most existing researches to M-to-M. We comprehensively considered the passenger travel cost, which includes the waiting and riding cost on the bus, riding cost on rail, and transfer cost between these two transportation modes, and presented a new genetic algorithm that determines the optimal feeder-bus operating frequencies under strict constraint conditions. The numerical examples under different demand patterns have been experienced and analysed, which showed the robustness and efficiency of the presented algorithm. We also found that the distribution pattern of the travel demand has a significant influence on the feeder-bus network construction.
Optimal Sequential Diagnostic Strategy Generation Considering Test Placement Cost for Multimode Systems

Directory of Open Access Journals (Sweden)

Shigang Zhang

2015-10-01

Full Text Available Sequential fault diagnosis is an approach that realizes fault isolation by executing the optimal test step by step. The strategy used, i.e., the sequential diagnostic strategy, has great influence on diagnostic accuracy and cost. Optimal sequential diagnostic strategy generation is an important step in the process of diagnosis system construction, which has been studied extensively in the literature. However, previous algorithms either are designed for single mode systems or do not consider test placement cost. They are not suitable to solve the sequential diagnostic strategy generation problem considering test placement cost for multimode systems. Therefore, this problem is studied in this paper. A formulation is presented. Two algorithms are proposed, one of which is realized by system transformation and the other is newly designed. Extensive simulations are carried out to test the effectiveness of the algorithms. A real-world system is also presented. All the results show that both of them have the ability to solve the diagnostic strategy generation problem, and they have different characteristics.
Optimal Sequential Diagnostic Strategy Generation Considering Test Placement Cost for Multimode Systems

Science.gov (United States)

Zhang, Shigang; Song, Lijun; Zhang, Wei; Hu, Zheng; Yang, Yongmin

2015-01-01

Sequential fault diagnosis is an approach that realizes fault isolation by executing the optimal test step by step. The strategy used, i.e., the sequential diagnostic strategy, has great influence on diagnostic accuracy and cost. Optimal sequential diagnostic strategy generation is an important step in the process of diagnosis system construction, which has been studied extensively in the literature. However, previous algorithms either are designed for single mode systems or do not consider test placement cost. They are not suitable to solve the sequential diagnostic strategy generation problem considering test placement cost for multimode systems. Therefore, this problem is studied in this paper. A formulation is presented. Two algorithms are proposed, one of which is realized by system transformation and the other is newly designed. Extensive simulations are carried out to test the effectiveness of the algorithms. A real-world system is also presented. All the results show that both of them have the ability to solve the diagnostic strategy generation problem, and they have different characteristics. PMID:26457709
Full load synthesis/design optimization of a hybrid SOFC-GT power plant

International Nuclear Information System (INIS)

Calise, F.; Dentice d' Accadia, M.; Vanoli, L.; Spakovsky, Michael R. von

2007-01-01

In this paper, the optimization of a hybrid solid oxide fuel cell-gas turbine (SOFC-GT) power plant is presented. The plant layout is based on an internal reforming SOFC stack; it also consists of a radial gas turbine, centrifugal compressors and plate-fin heat exchangers. In the first part of the paper, the bulk-flow model used to simulate the plant is presented. In the second part, a thermoeconomic model is developed by introducing capital cost functions. The whole plant is first simulated for a fixed configuration of the most important synthesis/design (S/D) parameters in order to establish a reference design configuration. Next a S/D optimization of the plant is carried out using a traditional single-level approach, based on a genetic algorithm. The optimization determined a set of S/D decision variable values with a capital cost significantly lower than that of the reference design, even though the net electrical efficiency for the optimal configuration was very close to that of the initial one. Furthermore, the optimization procedure dramatically reduced the SOFC active area and the compact heat exchanger areas
Assessment of various failure theories for weight and cost optimized laminated composites using genetic algorithm

Energy Technology Data Exchange (ETDEWEB)

Goyal, T. [Indian Institute of Technology Kanpur. Dept. of Aerospace Engineering, UP (India); Gupta, R. [Infotech Enterprises Ltd., Hyderabad (India)

2012-07-01

In this work, minimum weight-cost design for laminated composites is presented. A genetic algorithm has been developed for the optimization process. Maximum-Stress, Tsai-Wu and Tsai-Hill failure criteria have been used along with buckling analysis parameter for the margin of safety calculations. The design variables include three materials; namely Carbon-Epoxy, Glass-Epoxy, Kevlar-Epoxy; number of plies; ply orientation angles, varying from -75 deg. to 90 deg. in the intervals of 15 deg. and ply thicknesses which depend on the material in use. The total cost is a sum of material cost and layup cost. Layup cost is a function of the ply angle. Validation studies for solution convergence and weight-cost inverse proportionality are carried out. One set of results for shear loading are also validated from literature for a particular case. A Pareto-Optimal solution set is demonstrated for biaxial loading conditions. It is then extended to applied moments. It is found that global optimum for a given loading condition is a function of the failure criteria for shear loading, with Maximum Stress criteria giving the lightest-cheapest and Tsai-Wu criteria giving the heaviest-costliest optimized laminates. Optimized weight results are plotted from the three criteria to do a comparative study. This work gives a global optimized laminated composite and also a set of other local optimum laminates for a given set of loading conditions. The current algorithm also provides with adequate data to supplement the use of different failure criteria for varying loadings. This work can find use in the industry and/or academia considering the increased use of laminated composites in modern wind blades. (Author)
Inclusion of tank configurations as a variable in the cost optimization of branched piped-water networks

Science.gov (United States)

Hooda, Nikhil; Damani, Om

2017-06-01

The classic problem of the capital cost optimization of branched piped networks consists of choosing pipe diameters for each pipe in the network from a discrete set of commercially available pipe diameters. Each pipe in the network can consist of multiple segments of differing diameters. Water networks also consist of intermediate tanks that act as buffers between incoming flow from the primary source and the outgoing flow to the demand nodes. The network from the primary source to the tanks is called the primary network, and the network from the tanks to the demand nodes is called the secondary network. During the design stage, the primary and secondary networks are optimized separately, with the tanks acting as demand nodes for the primary network. Typically the choice of tank locations, their elevations, and the set of demand nodes to be served by different tanks is manually made in an ad hoc fashion before any optimization is done. It is desirable therefore to include this tank configuration choice in the cost optimization process itself. In this work, we explain why the choice of tank configuration is important to the design of a network and describe an integer linear program model that integrates the tank configuration to the standard pipe diameter selection problem. In order to aid the designers of piped-water networks, the improved cost optimization formulation is incorporated into our existing network design system called JalTantra.
Optimal design of permanent magnet flux switching generator for wind applications via artificial neural network and multi-objective particle swarm optimization hybrid approach

International Nuclear Information System (INIS)

Meo, Santolo; Zohoori, Alireza; Vahedi, Abolfazl

2016-01-01

Highlights: • A new optimal design of flux switching permanent magnet generator is developed. • A prototype is employed to validate numerical data used for optimization. • A novel hybrid multi-objective particle swarm optimization approach is proposed. • Optimization targets are weight, cost, voltage and its total harmonic distortion. • The hybrid approach preference is proved compared with other optimization methods. - Abstract: In this paper a new hybrid approach obtained combining a multi-objective particle swarm optimization and artificial neural network is proposed for the design optimization of a direct-drive permanent magnet flux switching generators for low power wind applications. The targets of the proposed multi-objective optimization are to reduce the costs and weight of the machine while maximizing the amplitude of the induced voltage as well as minimizing its total harmonic distortion. The permanent magnet width, the stator and rotor tooth width, the rotor teeth number and stator pole number of the machine define the search space for the optimization problem. Four supervised artificial neural networks are designed for modeling the complex relationships among the weight, the cost, the amplitude and the total harmonic distortion of the output voltage respect to the quantities of the search space. Finite element analysis is adopted to generate training dataset for the artificial neural networks. Finite element analysis based model is verified by experimental results with a 1.5 kW permanent magnet flux switching generator prototype suitable for renewable energy applications, having 6/19 stator poles/rotor teeth. Finally the effectiveness of the proposed hybrid procedure is compared with the results given by conventional multi-objective optimization algorithms. The obtained results show the soundness of the proposed multi objective optimization technique and its feasibility to be adopted as suitable methodology for optimal design of permanent
Optimization design of spar cap layup for wind turbine blade

Institute of Scientific and Technical Information of China (English)

2012-01-01

Based on the aerodynamic shape and structural form of the blade are fixed,a mathematical model of optimization design for wind turbine blade is established.The model is pursued with respect to minimum the blade mass to reduce the cost of wind turbine production.The material layup numbers of the spar cap are chosen as the design variables;while the demands of strength,stiffness and stability of the blade are employed as the constraint conditions.The optimization design for a 1.5 MW wind turbine blade is carried out by combing above objective and constraint conditions at the action of ultimate flapwise loads with the finite element software ANSYS.Compared with the original design,the optimization design result achieves a reduction of 7.2% of the blade mass,the stress and strain distribution of the blade is more reasonable,and there is no occurrence of resonance,therefore its effectiveness is verified.
Thermo-economic design optimization of parabolic trough solar plants for industrial process heat applications with memetic algorithms

International Nuclear Information System (INIS)

Silva, R.; Berenguel, M.; Pérez, M.; Fernández-Garcia, A.

2014-01-01

Highlights: • A thermo-economic optimization of a parabolic-trough solar plant for industrial process heat applications is developed. • An analysis of the influence of economic cost functions on optimal design point location is presented. • A multi-objective optimization approach to the design routine is proposed. • A sensitivity analysis of the optimal point location to economic, operational, and ambient conditions is developed. • Design optimization of a parabolic trough plant for a reference industrial application is developed. - Abstract: A thermo-economic design optimization of a parabolic trough solar plant for industrial processes with memetic algorithms is developed. The design domain variables considered in the optimization routine are the number of collectors in series, number of collector rows, row spacing, and storage volume. Life cycle savings, levelized cost of energy, and payback time objective functions are compared to study the influence on optimal design point location. Furthermore a multi-objective optimization approach is proposed to analyze the design problem from a multi-economic criteria point of view. An extensive set of optimization cases are performed to estimate the influence of fuel price trend, plant location, demand profile, operation conditions, solar field orientation, and radiation uncertainty on optimal design. The results allow quantifying as thermo-economic design optimization based on short term criteria as the payback time leads to smaller plants with higher solar field efficiencies and smaller solar fractions, while the consideration of optimization criteria based on long term performance of the plants, as life cycle savings based optimization, leads to the reverse conclusion. The role of plant location and future evolution of gas prices in the thermo-economic performance of the solar plant has been also analyzed. Thermo-economic optimization of a parabolic trough solar plant design for the reference industrial
Allocation base of general production costs as optimization of prime costs

Directory of Open Access Journals (Sweden)

Levytska I.O.

2017-03-01

Full Text Available Qualified management aimed at optimizing financial results is the key factor in today's society. Effective management decisions depend on the necessary information about the costs of production process in all its aspects – their structure, types, accounting policies of reflecting costs. General production costs, the so-called indirect costs that are not directly related to the production process, but provide its functioning in terms of supporting structural divisions and create the necessary conditions of production, play a significant role in calculating prime costs of goods (works, services. However, the accurate estimate of prime costs of goods (works, services should be determined with the value of indirect costs (in other words, general production costs, and properly determined with the base of their allocation. The choice of allocation base of general production costs is the significant moment, depending on the nature of business, which must guarantee fair distribution regarding to the largest share of direct expenses in the total structure of production costs. The study finds the essence of general production costs based on the analysis of key definitions of leading Ukrainian economists. The optimal allocation approach of general production costs is to calculate these costs as direct production costs within each subsidiary division (department separately without selecting a base as the main one to the their total amount.
Photovoltaic optimizer boost converters: Temperature influence and electro-thermal design

International Nuclear Information System (INIS)

Graditi, G.; Adinolfi, G.; Tina, G.M.

2014-01-01

process many times, many different feasible solutions can be found. An elaboration step follows to the “optima” power optimizer recognition among the whole obtained converters. In this case, a multi-objective optimization, consisting in the maximization of the solutions European efficiency and in the minimization of their cost, is executed and all not dominated solutions with respect to at least one of the two objectives are selected. The strength of the described method is represented by accurate PV generators and optimizer devices models. In detail, in the developed models particular attention is reserved to the thermal factor and to the quantification of the temperature action on devices parameters and performances. In fact, in such multiple and continuous changing working conditions, the temperature influence on components behavior can considerably vary their properties causing the whole converter performances worsening. The other important aspect, the converter reliability, is estimated by the reliability prediction model Military Handbook 217F. Results: The proposed tool is applied to Diode Rectification (DR) boosts and Synchronous (SR) boosts design. To completely characterize the obtained solutions their efficiency, cost and reliability performances are evaluated. In detail, Pareto fronts in terms of European efficiency and cost are identified for the SR and DR cases. Among the whole not dominated solutions, a SR converter characterized by a European efficiency of 97.1% and a DR boost characterized by a European efficiency of 95.5% are chosen. Their cost is comparable and equal about to $11. Then their reliability performances are evaluated by means of the Military Handbook 217F Notice 2. The carried out analysis shows that, for the same device cost, the SR solution represents the best one if efficiency is the most critical aspect. DR boost is, instead, the optimum solution if reliability represents the tighter requirement. Conclusion: The proposed DMPPT
Design windows and cost analysis on helical reactors

International Nuclear Information System (INIS)

Kozaki, Y.; Imagawa, S.; Sagara, A.

2007-01-01

The LHD type helical reactors are characterized by a large major radius but slender helical coil, which give us different approaches for power plants from tokamak reactors. For searching design windows of helical reactors and discussing their potential as power plants, we have developed a mass-cost estimating model linked with system design code (HeliCos), thorough studying the relationships between major plasma parameters and reactor parameters, and weight of major components. In regard to cost data we have much experience through preparing ITER construction. To compare the weight and cost of magnet systems between tokamak and helical reactors, we broke down magnet systems and cost factors, such as weights of super conducting strands, conduits, support structures, and winding unit costs, through estimating ITER cost data basis. Based on FFHR2m1 deign we considered a typical 3 GWth helical plant (LHD type) with the same magnet size, coil major radius Rc 14 m, magnetic energy 120 GJ, but increasing plasma densities. We evaluated the weight and cost of magnet systems of 3 GWth helical plant, the total magnet weights of 16,000ton and costs of 210 BYen, which are similar values of tokamak reactors (10,200 ton, 110 BYen in ITER 2002 report, and 21,900 ton, 275 BYen in ITER FDR1999). The costs of strands and winding occupy 70% of total magnet costs, and influence entire power plants economics. The design windows analysis and comparative economics studies to optimize the main reactor parameters have been carried out. Economics studies show that it is misunderstanding to consider helical coils are too large and too expensive to achieve power plants. But we should notice that the helical reactor design windows and economics are very sensitive to allowable blanket space (depend on ergodic layer conditions) and diverter configuration for decreasing heat loads. (orig.)
Techniques for the optimal design of photovoltaic inverters interconnected with the electric grid

DEFF Research Database (Denmark)

Koutroulis, Eftichios; Blaabjerg, Frede

2011-01-01

the Genetic Algorithm-based optimization procedure is the PV inverter Levelized Cost Of the Electricity generated (LCOE). The proposed method has been applied for the optimal design of PV inverters installed at various sites in Europe. The simulation results indicate that the optimal values of the PV inverter...
Prediction of Optimal Design and Deflection of Space Structures Using Neural Networks

Directory of Open Access Journals (Sweden)

Reza Kamyab Moghadas

2012-01-01

Full Text Available The main aim of the present work is to determine the optimal design and maximum deflection of double layer grids spending low computational cost using neural networks. The design variables of the optimization problem are cross-sectional area of the elements as well as the length of the span and height of the structures. In this paper, a number of double layer grids with various random values of length and height are selected and optimized by simultaneous perturbation stochastic approximation algorithm. Then, radial basis function (RBF and generalized regression (GR neural networks are trained to predict the optimal design and maximum deflection of the structures. The numerical results demonstrate the efficiency of the proposed methodology.
A cost-effective methodology to internalize nuclear safety in nuclear reactor conceptual design

International Nuclear Information System (INIS)

Gimenez, M.; Grinblat, P.; Schlamp, M.

2003-01-01

A new methodology to perform nuclear reactor design, balancing safety and economics at the conceptual engineering stage, is presented in this work. The goal of this integral methodology is to take into account safety aspects in an optimization design process where the design variables are balanced in order to obtain a better figure of merit related with reactor economic performance. Design parameter effects on characteristic or critical safety variables, chosen from reactor behavior during accidents (safety performance indicators), are synthesized on Design Maps. These maps allow one to compare the safety indicator with limits, which are determined by design criteria or regulations, and to transfer these restrictions to the design parameters. In this way, reactor dynamic response and other safety aspects are integrated in a global optimization process, by means of additional rules to the neutronic, thermal-hydraulic, and mechanical calculations. An application of the methodology, implemented in Integrated Reactor Evaluation Program 3 (IREP3) code, to optimize safety systems of CAREM prototype is presented. It consists in balancing the designs of the Emergency Injection System (EIS), the Residual Heat Removal System (RHRS), the primary circuit water inventory and the containment height, to cope with loss of coolant and loss of heat sink (LOHS) accidental sequences, taking into account cost and reactor performance. This methodology turns out to be promising to internalize cost-efficiently safety issues. It also allows one to evaluate the incremental costs of implementing higher safety levels
Optimal tariff design under consumer self-selection

Energy Technology Data Exchange (ETDEWEB)

Raesaenen, M.; Ruusunen, J.; Haemaelaeinen, R.

1995-12-31

This report considers the design of electricity tariffs which guides an individual consumer to select the tariff designed for his consumption pattern. In the model the utility maximizes the weighted sum of individual consumers` benefits of electricity consumption subject to the utility`s revenue requirement constraints. The consumers` free choice of tariffs is ensured with the so-called self-selection constraints. The relationship between the consumers` optimal choice of tariffs and the weights in the aggregated consumers` benefit function is analyzed. If such weights exist, they will guarantee both the consumers` optimal choice of tariffs and the efficient consumption patterns. Also the welfare effects are analyzed by using demand parameters estimated from a Finnish dynamic pricing experiment. The results indicate that it is possible to design an efficient tariff menu with the welfare losses caused by the self-selection constraints being small compared with the costs created when some consumers choose tariffs other than assigned for them. (author)
Multiobjective optimization design of green building envelope material using a non-dominated sorting genetic algorithm

International Nuclear Information System (INIS)

Yang, Ming-Der; Lin, Min-Der; Lin, Yu-Hao; Tsai, Kang-Ting

2017-01-01

Highlights: • An effective envelope energy performance model (BEM) was developed. • We integrated NSGA-II with the BEM to optimize the green building envelope. • A tradeoff plan of green building design for three conflict objectives was obtained. • The optimal envelope design efficiently reduced the construction cost of green building. - Abstract: To realize the goal of environmental sustainability, improving energy efficiency in buildings is a major priority worldwide. However, the practical design of green building envelopes for energy conservation is a highly complex optimization problem, and architects must make multiobjective decisions. In practice, methods such as multicriteria analyses that entail capitalizing on possibly many (but in nearly any case limited) alternatives are commonly employed. This study investigated the feasibility of applying a multiobjective optimal model on building envelope design (MOPBEM), which involved integrating a building envelope energy performance model with a multiobjective optimizer. The MOPBEM was established to provide a reference for green designs. A nondominated sorting genetic algorithm-II (NSGA-II) was used to achieve a tradeoff design set between three conflicting objectives, namely minimizing the envelope construction cost (ENVCOST), minimizing the envelope energy performance (ENVLOAD), and maximizing the window opening rate (WOPR). A real office building case was designed using the MOPBEM to identify the potential strengths and weaknesses of the proposed MOPBEM. The results showed that a high ENVCOST was expended in simultaneously satisfying the low ENVLOAD and high WOPR. Various designs exhibited obvious cost reductions compared with the original architects' manual design, demonstrating the practicability of the MOPBEM.
Survey of research on the optimal design of sea harbours

Directory of Open Access Journals (Sweden)

Hassan Diab

2017-07-01

Full Text Available The design of harbours, as with any other system design, must be an optimization process. In this study, a global examination of the different constraints in coastal engineering was performed and an optimization problem was defined. The problem has multiple objectives, and the criteria to be minimized are the structure cost and wave height disturbance inside a harbour. As concluded in this survey, the constraints are predefined parameters, mandatory constraints or optional constraints. All of these constraints are categorized into four categories: environmental, fluid mechanical, structural and manoeuvring.

An overview of the Douglas Aircraft Company Aeroelastic Design Optimization Program (ADOP)

Science.gov (United States)

Dodd, Alan J.

1989-01-01

From a program manager's viewpoint, the history, scope and architecture of a major structural design program at Douglas Aircraft Company called Aeroelastic Design Optimization Program (ADOP) are described. ADOP was originally intended for the rapid, accurate, cost-effective evaluation of relatively small structural models at the advanced design level, resulting in improved proposal competitiveness and avoiding many costly changes later in the design cycle. Before release of the initial version in November 1987, however, the program was expanded to handle very large production-type analyses.
Cost Optimization of Product Families using Analytic Cost Models

DEFF Research Database (Denmark)

Brunø, Thomas Ditlev; Nielsen, Peter

2012-01-01

This paper presents a new method for analysing the cost structure of a mass customized product family. The method uses linear regression and backwards selection to reduce the complexity of a data set describing a number of historical product configurations and incurred costs. By reducing the data...... set, the configuration variables which best describe the variation in product costs are identified. The method is tested using data from a Danish manufacturing company and the results indicate that the method is able to identify the most critical configuration variables. The method can be applied...... in product family redesign projects focusing on cost reduction to identify which modules contribute the most to cost variation and should thus be optimized....
A cost optimization model for 100% renewable residential energy supply systems

DEFF Research Database (Denmark)

Milan, Christian; Bojesen, Carsten; Nielsen, Mads Pagh

2012-01-01

The concept of net zero energy buildings (Net ZEB) has received increased attention throughout the last years. A well adapted and optimized design of the energy supply system is crucial for the performance of these buildings. To achieve this, a holistic approach is needed which accounts for the i......The concept of net zero energy buildings (Net ZEB) has received increased attention throughout the last years. A well adapted and optimized design of the energy supply system is crucial for the performance of these buildings. To achieve this, a holistic approach is needed which accounts......'s involving on-site production of heat and electricity in combination with electricity exchanged with the public grid. The model is based on linear programming and determines the optimal capacities for each relevant supply technology in terms of the overall system costs. It has been successfully applied...
Dimensions of design space: a decision-theoretic approach to optimal research design.

Science.gov (United States)

Conti, Stefano; Claxton, Karl

2009-01-01

Bayesian decision theory can be used not only to establish the optimal sample size and its allocation in a single clinical study but also to identify an optimal portfolio of research combining different types of study design. Within a single study, the highest societal payoff to proposed research is achieved when its sample sizes and allocation between available treatment options are chosen to maximize the expected net benefit of sampling (ENBS). Where a number of different types of study informing different parameters in the decision problem could be conducted, the simultaneous estimation of ENBS across all dimensions of the design space is required to identify the optimal sample sizes and allocations within such a research portfolio. This is illustrated through a simple example of a decision model of zanamivir for the treatment of influenza. The possible study designs include: 1) a single trial of all the parameters, 2) a clinical trial providing evidence only on clinical endpoints, 3) an epidemiological study of natural history of disease, and 4) a survey of quality of life. The possible combinations, samples sizes, and allocation between trial arms are evaluated over a range of cost-effectiveness thresholds. The computational challenges are addressed by implementing optimization algorithms to search the ENBS surface more efficiently over such large dimensions.
Optimal Ground Source Heat Pump System Design

Energy Technology Data Exchange (ETDEWEB)

Ozbek, Metin [Environ Holdings Inc., Princeton, NJ (United States); Yavuzturk, Cy [Univ. of Hartford, West Hartford, CT (United States); Pinder, George [Univ. of Vermont, Burlington, VT (United States)

2015-04-01

Despite the facts that GSHPs first gained popularity as early as the 1940’s and they can achieve 30 to 60 percent in energy savings and carbon emission reductions relative to conventional HVAC systems, the use of geothermal energy in the U.S. has been less than 1 percent of the total energy consumption. The key barriers preventing this technically-mature technology from reaching its full commercial potential have been its high installation cost and limited consumer knowledge and trust in GSHP systems to deliver the technology in a cost-effective manner in the market place. Led by ENVIRON, with support from University Hartford and University of Vermont, the team developed and tested a software-based a decision making tool (‘OptGSHP’) for the least-cost design of ground-source heat pump (‘GSHP’) systems. OptGSHP combines state of the art optimization algorithms with GSHP-specific HVAC and groundwater flow and heat transport simulation. The particular strength of OptGSHP is in integrating heat transport due to groundwater flow into the design, which most of the GSHP designs do not get credit for and therefore are overdesigned.
Design optimization and uncertainty analysis of SMA morphing structures

International Nuclear Information System (INIS)

Oehler, S D; Hartl, D J; Lopez, R; Malak, R J; Lagoudas, D C

2012-01-01

The continuing implementation of shape memory alloys (SMAs) as lightweight solid-state actuators in morphing structures has now motivated research into finding optimized designs for use in aerospace control systems. This work proposes methods that use iterative analysis techniques to determine optimized designs for morphing aerostructures and consider the impact of uncertainty in model variables on the solution. A combination of commercially available and custom coded tools is utilized. ModelCenter, a suite of optimization algorithms and simulation process management tools, is coupled with the Abaqus finite element analysis suite and a custom SMA constitutive model to assess morphing structure designs in an automated fashion. The chosen case study involves determining the optimized configuration of a morphing aerostructure assembly that includes SMA flexures. This is accomplished by altering design inputs representing the placement of active components to minimize a specified cost function. An uncertainty analysis is also conducted using design of experiment methods to determine the sensitivity of the solution to a set of uncertainty variables. This second study demonstrates the effective use of Monte Carlo techniques to simulate the variance of model variables representing the inherent uncertainty in component fabrication processes. This paper outlines the modeling tools used to execute each case study, details the procedures for constructing the optimization problem and uncertainty analysis, and highlights the results from both studies. (paper)
Flash memories economic principles of performance, cost and reliability optimization

CERN Document Server

Richter, Detlev

2014-01-01

The subject of this book is to introduce a model-based quantitative performance indicator methodology applicable for performance, cost and reliability optimization of non-volatile memories. The complex example of flash memories is used to introduce and apply the methodology. It has been developed by the author based on an industrial 2-bit to 4-bit per cell flash development project. For the first time, design and cost aspects of 3D integration of flash memory are treated in this book. Cell, array, performance and reliability effects of flash memories are introduced and analyzed. Key performance parameters are derived to handle the flash complexity. A performance and array memory model is developed and a set of performance indicators characterizing architecture, cost and durability is defined. Flash memories are selected to apply the Performance Indicator Methodology to quantify design and technology innovation. A graphical representation based on trend lines is introduced to support a requirement based pr...
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...
Optimal design of pressurized irrigation systems. Application cases (Ecuador

Directory of Open Access Journals (Sweden)

Carmen Mireya Lapo Pauta

2013-05-01

Full Text Available This paper presents research completed with the intention of finding the most economical solution in the design of pressurized irrigation networks, while efficiently meet service delivery. A systematic methodology is proposed that combines two optimization techniques through a “hybrid method” in, which linear programming, nonlinear programming and genetic algorithms are fused. The overall formulations of the problem of optimal dimensioning consist of minimizing an objective function constituted through the associated cost of the pipes that form the network. This methodology was implemented in three networks a fictitious irrigation and two irrigation networks (Tuncarta and Cariyacu located in the cities of Loja and Chimborazo which yielded optimal design solutions. Finally different scenarios were simulated in both models to obtain an overview of the operation of the hydraulic variables
Modelling and Optimal Control of Typhoid Fever Disease with Cost-Effective Strategies.

Science.gov (United States)

Tilahun, Getachew Teshome; Makinde, Oluwole Daniel; Malonza, David

2017-01-01

We propose and analyze a compartmental nonlinear deterministic mathematical model for the typhoid fever outbreak and optimal control strategies in a community with varying population. The model is studied qualitatively using stability theory of differential equations and the basic reproductive number that represents the epidemic indicator is obtained from the largest eigenvalue of the next-generation matrix. Both local and global asymptotic stability conditions for disease-free and endemic equilibria are determined. The model exhibits a forward transcritical bifurcation and the sensitivity analysis is performed. The optimal control problem is designed by applying Pontryagin maximum principle with three control strategies, namely, the prevention strategy through sanitation, proper hygiene, and vaccination; the treatment strategy through application of appropriate medicine; and the screening of the carriers. The cost functional accounts for the cost involved in prevention, screening, and treatment together with the total number of the infected persons averted. Numerical results for the typhoid outbreak dynamics and its optimal control revealed that a combination of prevention and treatment is the best cost-effective strategy to eradicate the disease.
A method of network topology optimization design considering application process characteristic

Science.gov (United States)

Wang, Chunlin; Huang, Ning; Bai, Yanan; Zhang, Shuo

2018-03-01

Communication networks are designed to meet the usage requirements of users for various network applications. The current studies of network topology optimization design mainly considered network traffic, which is the result of network application operation, but not a design element of communication networks. A network application is a procedure of the usage of services by users with some demanded performance requirements, and has obvious process characteristic. In this paper, we first propose a method to optimize the design of communication network topology considering the application process characteristic. Taking the minimum network delay as objective, and the cost of network design and network connective reliability as constraints, an optimization model of network topology design is formulated, and the optimal solution of network topology design is searched by Genetic Algorithm (GA). Furthermore, we investigate the influence of network topology parameter on network delay under the background of multiple process-oriented applications, which can guide the generation of initial population and then improve the efficiency of GA. Numerical simulations show the effectiveness and validity of our proposed method. Network topology optimization design considering applications can improve the reliability of applications, and provide guidance for network builders in the early stage of network design, which is of great significance in engineering practices.
Site specific optimization of wind turbines energy cost: Iterative approach

International Nuclear Information System (INIS)

Rezaei Mirghaed, Mohammad; Roshandel, Ramin

2013-01-01

Highlights: • Optimization model of wind turbine parameters plus rectangular farm layout is developed. • Results show that levelized cost for single turbine fluctuates between 46.6 and 54.5 $/MW h. • Modeling results for two specific farms reported optimal sizing and farm layout. • Results show that levelized cost of the wind farms fluctuates between 45.8 and 67.2 $/MW h. - Abstract: The present study was aimed at developing a model to optimize the sizing parameters and farm layout of wind turbines according to the wind resource and economic aspects. The proposed model, including aerodynamic, economic and optimization sub-models, is used to achieve minimum levelized cost of electricity. The blade element momentum theory is utilized for aerodynamic modeling of pitch-regulated horizontal axis wind turbines. Also, a comprehensive cost model including capital costs of all turbine components is considered. An iterative approach is used to develop the optimization model. The modeling results are presented for three potential regions in Iran: Khaf, Ahar and Manjil. The optimum configurations and sizing for a single turbine with minimum levelized cost of electricity are presented. The optimal cost of energy for one turbine is calculated about 46.7, 54.5 and 46.6 dollars per MW h in the studied sites, respectively. In addition, optimal size of turbines, annual electricity production, capital cost, and wind farm layout for two different rectangular and square shaped farms in the proposed areas have been recognized. According to the results, optimal system configuration corresponds to minimum levelized cost of electricity about 45.8 to 67.2 dollars per MW h in the studied wind farms
Design Optimization and Site Matching of Direct-Drive Permanent Magnet Wind Generator Systems

DEFF Research Database (Denmark)

Li, H.; Chen, Zhe

2009-01-01

This paper investigates the possible site matching of the direct-drive wind turbine concepts based on the electromagnetic design optimization of permanent magnet (PM) generator systems. Firstly, the analytical models of a three-phase radial-flux PM generator with a back-to-back power converter...... of the maximum wind energy capture, the rotor diameter and the rated wind speed of a direct-drive wind turbine with the optimum PM generator are determined. The annual energy output (AEO) is also presented using the Weibull density function. Finally, the maximum AEO per cost (AEOPC) of the optimized wind...... are presented. The optimum design models of direct-drive PM wind generation system are developed with an improved genetic algorithm, and a 500-kW direct-drive PM generator for the minimal generator active material cost is compared to demonstrate the effectiveness of the design optimization. Forty-five PM...
Optimal design of a system containing mixed redundancies with respect to reliability and cost

International Nuclear Information System (INIS)

Misra, K.B.

1975-01-01

A nuclear system generally consists of subsystems that may employ any of the partial, standby, and active redundancies, and is, therefore, a system with mixed type of redundancies. Optimization of reliability or availability of such systems at the design stage is a difficult problem. There appears to be no published work on the optimal design of maintained systems consisting of mixed redundancies. An attempt is therefore made, to present the basis of design and the solution technique to achieve this. An algorithm is described which makes the solution of this mathematically difficult problem possible. Some examples are demonstrated. To achieve further efficiency a study was organized and the recommendations for obtaining a minimum solution time are provided. Although, in the illustration, only the linear constraints and reliability, as the only design parameter, have been considered, the algorithm works well with the nonlinear type of constraints and can be used with other design parameters also. (author)
Cost model relationships between textile manufacturing processes and design details for transport fuselage elements

Science.gov (United States)

Metschan, Stephen L.; Wilden, Kurtis S.; Sharpless, Garrett C.; Andelman, Rich M.

1993-01-01

Textile manufacturing processes offer potential cost and weight advantages over traditional composite materials and processes for transport fuselage elements. In the current study, design cost modeling relationships between textile processes and element design details were developed. Such relationships are expected to help future aircraft designers to make timely decisions on the effect of design details and overall configurations on textile fabrication costs. The fundamental advantage of a design cost model is to insure that the element design is cost effective for the intended process. Trade studies on the effects of processing parameters also help to optimize the manufacturing steps for a particular structural element. Two methods of analyzing design detail/process cost relationships developed for the design cost model were pursued in the current study. The first makes use of existing databases and alternative cost modeling methods (e.g. detailed estimating). The second compares design cost model predictions with data collected during the fabrication of seven foot circumferential frames for ATCAS crown test panels. The process used in this case involves 2D dry braiding and resin transfer molding of curved 'J' cross section frame members having design details characteristic of the baseline ATCAS crown design.
Design and economic optimization of shell and tube heat exchangers using Artificial Bee Colony (ABC) algorithm

International Nuclear Information System (INIS)

Sencan Sahin, Arzu; Kilic, Bayram; Kilic, Ulas

2011-01-01

Highlights: → Artificial Bee Colony for shell and tube heat exchanger optimization is used. → The total cost is minimized by varying design variables. → This new approach can be applied for optimization of heat exchangers. - Abstract: In this study, a new shell and tube heat exchanger optimization design approach is developed. Artificial Bee Colony (ABC) has been applied to minimize the total cost of the equipment including capital investment and the sum of discounted annual energy expenditures related to pumping of shell and tube heat exchanger by varying various design variables such as tube length, tube outer diameter, pitch size, baffle spacing, etc. Finally, the results are compared to those obtained by literature approaches. The obtained results indicate that Artificial Bee Colony (ABC) algorithm can be successfully applied for optimal design of shell and tube heat exchangers.
Design and economic optimization of shell and tube heat exchangers using Artificial Bee Colony (ABC) algorithm

Energy Technology Data Exchange (ETDEWEB)

Sencan Sahin, Arzu, E-mail: sencan@tef.sdu.edu.tr [Department of Mechanical Education, Technical Education Faculty, Sueleyman Demirel University, 32260 Isparta (Turkey); Kilic, Bayram, E-mail: bayramkilic@hotmail.com [Bucak Emin Guelmez Vocational School, Mehmet Akif Ersoy University, Bucak (Turkey); Kilic, Ulas, E-mail: ulaskilic@mehmetakif.edu.tr [Bucak Emin Guelmez Vocational School, Mehmet Akif Ersoy University, Bucak (Turkey)

2011-10-15

Highlights: {yields} Artificial Bee Colony for shell and tube heat exchanger optimization is used. {yields} The total cost is minimized by varying design variables. {yields} This new approach can be applied for optimization of heat exchangers. - Abstract: In this study, a new shell and tube heat exchanger optimization design approach is developed. Artificial Bee Colony (ABC) has been applied to minimize the total cost of the equipment including capital investment and the sum of discounted annual energy expenditures related to pumping of shell and tube heat exchanger by varying various design variables such as tube length, tube outer diameter, pitch size, baffle spacing, etc. Finally, the results are compared to those obtained by literature approaches. The obtained results indicate that Artificial Bee Colony (ABC) algorithm can be successfully applied for optimal design of shell and tube heat exchangers.
Extremely Efficient Design of Organic Thin Film Solar Cells via Learning-Based Optimization

Directory of Open Access Journals (Sweden)

Mine Kaya

2017-11-01

Full Text Available Design of efficient thin film photovoltaic (PV cells require optical power absorption to be computed inside a nano-scale structure of photovoltaics, dielectric and plasmonic materials. Calculating power absorption requires Maxwell’s electromagnetic equations which are solved using numerical methods, such as finite difference time domain (FDTD. The computational cost of thin film PV cell design and optimization is therefore cumbersome, due to successive FDTD simulations. This cost can be reduced using a surrogate-based optimization procedure. In this study, we deploy neural networks (NNs to model optical absorption in organic PV structures. We use the corresponding surrogate-based optimization procedure to maximize light trapping inside thin film organic cells infused with metallic particles. Metallic particles are known to induce plasmonic effects at the metal–semiconductor interface, thus increasing absorption. However, a rigorous design procedure is required to achieve the best performance within known design guidelines. As a result of using NNs to model thin film solar absorption, the required time to complete optimization is decreased by more than five times. The obtained NN model is found to be very reliable. The optimization procedure results in absorption enhancement greater than 200%. Furthermore, we demonstrate that once a reliable surrogate model such as the developed NN is available, it can be used for alternative analyses on the proposed design, such as uncertainty analysis (e.g., fabrication error.
Irreversibility analysis for optimization design of plate fin heat exchangers using a multi-objective cuckoo search algorithm

International Nuclear Information System (INIS)

Wang, Zhe; Li, Yanzhong

2015-01-01

Highlights: • The first application of IMOCS for plate-fin heat exchanger design. • Irreversibility degrees of heat transfer and fluid friction are minimized. • Trade-off of efficiency, total cost and pumping power is achieved. • Both EGM and EDM methods have been compared in the optimization of PFHE. • This study has superiority over other single-objective optimization design. - Abstract: This paper introduces and applies an improved multi-objective cuckoo search (IMOCS) algorithm, a novel met-heuristic optimization algorithm based on cuckoo breeding behavior, for the multi-objective optimization design of plate-fin heat exchangers (PFHEs). A modified irreversibility degree of the PFHE is separated into heat transfer and fluid friction irreversibility degrees which are adopted as two initial objective functions to be minimized simultaneously for narrowing the search scope of the design. The maximization efficiency, minimization of pumping power, and total annual cost are considered final objective functions. Results obtained from a two dimensional normalized Pareto-optimal frontier clearly demonstrate the trade-off between heat transfer and fluid friction irreversibility. Moreover, a three dimensional Pareto-optimal frontier reveals a relationship between efficiency, total annual cost, and pumping power in the PFHE design. Three examples presented here further demonstrate that the presented method is able to obtain optimum solutions with higher accuracy, lower irreversibility, and fewer iterations as compared to the previous methods and single-objective design approaches
Estimation of optimal educational cost per medical student.

Science.gov (United States)

Yang, Eunbae B; Lee, Seunghee

2009-09-01

This study aims to estimate the optimal educational cost per medical student. A private medical college in Seoul was targeted by the study, and its 2006 learning environment and data from the 2003~2006 budget and settlement were carefully analyzed. Through interviews with 3 medical professors and 2 experts in the economics of education, the study attempted to establish the educational cost estimation model, which yields an empirically computed estimate of the optimal cost per student in medical college. The estimation model was based primarily upon the educational cost which consisted of direct educational costs (47.25%), support costs (36.44%), fixed asset purchases (11.18%) and costs for student affairs (5.14%). These results indicate that the optimal cost per student is approximately 20,367,000 won each semester; thus, training a doctor costs 162,936,000 won over 4 years. Consequently, we inferred that the tuition levels of a local medical college or professional medical graduate school cover one quarter or one-half of the per- student cost. The findings of this study do not necessarily imply an increase in medical college tuition; the estimation of the per-student cost for training to be a doctor is one matter, and the issue of who should bear this burden is another. For further study, we should consider the college type and its location for general application of the estimation method, in addition to living expenses and opportunity costs.

Value Engineering. "A Working Tool for Cost Control in the Design of Educational Facilities."

Science.gov (United States)

Lawrence, Jerry

Value Engineering (VE) is a cost optimizing technique used to analyze design quality and cost-effectiveness. The application of VE procedures to the design and construction of school facilities has been adopted by the state of Washington. By using VE, the optimum value for every life cycle dollar spent on a facility is obtained by identifying not…
Multi-Objective Optimization Design for a Hybrid Energy System Using the Genetic Algorithm

Directory of Open Access Journals (Sweden)

Myeong Jin Ko

2015-04-01

Full Text Available To secure a stable energy supply and bring renewable energy to buildings within a reasonable cost range, a hybrid energy system (HES that integrates both fossil fuel energy systems (FFESs and new and renewable energy systems (NRESs needs to be designed and applied. This paper presents a methodology to optimize a HES consisting of three types of NRESs and six types of FFESs while simultaneously minimizing life cycle cost (LCC, maximizing penetration of renewable energy and minimizing annual greenhouse gas (GHG emissions. An elitist non-dominated sorting genetic algorithm is utilized for multi-objective optimization. As an example, we have designed the optimal configuration and sizing for a HES in an elementary school. The evolution of Pareto-optimal solutions according to the variation in the economic, technical and environmental objective functions through generations is discussed. The pair wise trade-offs among the three objectives are also examined.
A proposal of optimal sampling design using a modularity strategy

Science.gov (United States)

Simone, A.; Giustolisi, O.; Laucelli, D. B.

2016-08-01

In real water distribution networks (WDNs) are present thousands nodes and optimal placement of pressure and flow observations is a relevant issue for different management tasks. The planning of pressure observations in terms of spatial distribution and number is named sampling design and it was faced considering model calibration. Nowadays, the design of system monitoring is a relevant issue for water utilities e.g., in order to manage background leakages, to detect anomalies and bursts, to guarantee service quality, etc. In recent years, the optimal location of flow observations related to design of optimal district metering areas (DMAs) and leakage management purposes has been faced considering optimal network segmentation and the modularity index using a multiobjective strategy. Optimal network segmentation is the basis to identify network modules by means of optimal conceptual cuts, which are the candidate locations of closed gates or flow meters creating the DMAs. Starting from the WDN-oriented modularity index, as a metric for WDN segmentation, this paper proposes a new way to perform the sampling design, i.e., the optimal location of pressure meters, using newly developed sampling-oriented modularity index. The strategy optimizes the pressure monitoring system mainly based on network topology and weights assigned to pipes according to the specific technical tasks. A multiobjective optimization minimizes the cost of pressure meters while maximizing the sampling-oriented modularity index. The methodology is presented and discussed using the Apulian and Exnet networks.
Cost-benefit study of consumer product take-back programs using IBM's WIT reverse logistics optimization tool

Science.gov (United States)

Veerakamolmal, Pitipong; Lee, Yung-Joon; Fasano, J. P.; Hale, Rhea; Jacques, Mary

2002-02-01

In recent years, there has been increased focus by regulators, manufacturers, and consumers on the issue of product end of life management for electronics. This paper presents an overview of a conceptual study designed to examine the costs and benefits of several different Product Take Back (PTB) scenarios for used electronics equipment. The study utilized a reverse logistics supply chain model to examine the effects of several different factors in PTB programs. The model was done using the IBM supply chain optimization tool known as WIT (Watson Implosion Technology). Using the WIT tool, we were able to determine a theoretical optimal cost scenario for PTB programs. The study was designed to assist IBM internally in determining theoretical optimal Product Take Back program models and determining potential incentives for increasing participation rates.
Efficient Solutions and Cost-Optimal Analysis for Existing School Buildings

Directory of Open Access Journals (Sweden)

Paolo Maria Congedo

2016-10-01

Full Text Available The recast of the energy performance of buildings directive (EPBD describes a comparative methodological framework to promote energy efficiency and establish minimum energy performance requirements in buildings at the lowest costs. The aim of the cost-optimal methodology is to foster the achievement of nearly zero energy buildings (nZEBs, the new target for all new buildings by 2020, characterized by a high performance with a low energy requirement almost covered by renewable sources. The paper presents the results of the application of the cost-optimal methodology in two existing buildings located in the Mediterranean area. These buildings are a kindergarten and a nursery school that differ in construction period, materials and systems. Several combinations of measures have been applied to derive cost-effective efficient solutions for retrofitting. The cost-optimal level has been identified for each building and the best performing solutions have been selected considering both a financial and a macroeconomic analysis. The results illustrate the suitability of the methodology to assess cost-optimality and energy efficiency in school building refurbishment. The research shows the variants providing the most cost-effective balance between costs and energy saving. The cost-optimal solution reduces primary energy consumption by 85% and gas emissions by 82%–83% in each reference building.
Solving bi-level optimization problems in engineering design using kriging models

Science.gov (United States)

Xia, Yi; Liu, Xiaojie; Du, Gang

2018-05-01

Stackelberg game-theoretic approaches are applied extensively in engineering design to handle distributed collaboration decisions. Bi-level genetic algorithms (BLGAs) and response surfaces have been used to solve the corresponding bi-level programming models. However, the computational costs for BLGAs often increase rapidly with the complexity of lower-level programs, and optimal solution functions sometimes cannot be approximated by response surfaces. This article proposes a new method, namely the optimal solution function approximation by kriging model (OSFAKM), in which kriging models are used to approximate the optimal solution functions. A detailed example demonstrates that OSFAKM can obtain better solutions than BLGAs and response surface-based methods, and at the same time reduce the workload of computation remarkably. Five benchmark problems and a case study of the optimal design of a thin-walled pressure vessel are also presented to illustrate the feasibility and potential of the proposed method for bi-level optimization in engineering design.
Design and optimization of an RFID-enabled passport tracking system

Directory of Open Access Journals (Sweden)

Abdulsalam Dukyil

2018-01-01

Full Text Available The implementation of RFID technology has been subject to ever-increasing popularity in relation to the traceability of products as one of the most cutting edge technologies. Implementing such a technology leads to an increase in the visibility management of products. Notwithstanding this, RFID communication performance is potentially affected by interference between the RFID devices. It is also subject to additional costs in investment that should be taken into account. Consequently, seeking a cost-effective design with a desired communication performance for RFID-enabled systems has become a key factor in order to be competitive in today’s markets. This study presents a cost and performance-effective design for a proposed RFID-enabled passport tracking system through the development of a multi-objective model that takes in account economic, performance and social criteria. The developed model is aimed at solving the design problem by (i allocating the optimal numbers of related facilities that should be established and (ii obtaining trade-offs among three objectives: minimising implementation and operational costs; minimising RFID reader interference; and maximising the social impact measured in the number of created jobs. To come closer to real design in terms of considering the uncertain parameters, the developed multi-objective model was developed in terms of a fuzzy multi-objective model (FMOM. To solve the fuzzy multi-objective optimization problem, two solution methods were used and a decision-making method was employed to select the final trade-off solution. A case study was applied to examine the applicability of the developed model and the proposed solution methods.
Multidisciplinary design and optimization (MDO) methodology for the aircraft conceptual design

Science.gov (United States)

Iqbal, Liaquat Ullah

An integrated design and optimization methodology has been developed for the conceptual design of an aircraft. The methodology brings higher fidelity Computer Aided Design, Engineering and Manufacturing (CAD, CAE and CAM) Tools such as CATIA, FLUENT, ANSYS and SURFCAM into the conceptual design by utilizing Excel as the integrator and controller. The approach is demonstrated to integrate with many of the existing low to medium fidelity codes such as the aerodynamic panel code called CMARC and sizing and constraint analysis codes, thus providing the multi-fidelity capabilities to the aircraft designer. The higher fidelity design information from the CAD and CAE tools for the geometry, aerodynamics, structural and environmental performance is provided for the application of the structured design methods such as the Quality Function Deployment (QFD) and the Pugh's Method. The higher fidelity tools bring the quantitative aspects of a design such as precise measurements of weight, volume, surface areas, center of gravity (CG) location, lift over drag ratio, and structural weight, as well as the qualitative aspects such as external geometry definition, internal layout, and coloring scheme early in the design process. The performance and safety risks involved with the new technologies can be reduced by modeling and assessing their impact more accurately on the performance of the aircraft. The methodology also enables the design and evaluation of the novel concepts such as the blended (BWB) and the hybrid wing body (HWB) concepts. Higher fidelity computational fluid dynamics (CFD) and finite element analysis (FEA) allow verification of the claims for the performance gains in aerodynamics and ascertain risks of structural failure due to different pressure distribution in the fuselage as compared with the tube and wing design. The higher fidelity aerodynamics and structural models can lead to better cost estimates that help reduce the financial risks as well. This helps in
Nonfragile Guaranteed Cost Control and Optimization for Interconnected Systems of Neutral Type

Directory of Open Access Journals (Sweden)

Heli Hu

2013-01-01

Full Text Available The design and optimization problems of the nonfragile guaranteed cost control are investigated for a class of interconnected systems of neutral type. A novel scheme, viewing the interconnections with time-varying delays as effective information but not disturbances, is developed to decrease the conservatism. Many techniques on decomposing and magnifying the matrices are utilized to obtain the guaranteed cost of the considered system. Also, an algorithm is proposed to solve the nonlinear problem of the interconnected matrices. Based on this algorithm, the minimization of the guaranteed cost of the considered system is obtained by optimization. Further, the state feedback control is extended to the case in which the underlying system is dependent on uncertain parameters. Finally, two numerical examples are given to illustrate the proposed method, and some comparisons are made to show the advantages of the schemes of dealing with the interconnections.
Manufacturing enterprise’s logistics operational cost simulation and optimization from the perspective of inter-firm network

Directory of Open Access Journals (Sweden)

Chun Fu

2015-05-01

Full Text Available Purpose: By studying the case of a Changsha engineering machinery manufacturing firm, this paper aims to find out the optimization tactics to reduce enterprise’s logistics operational cost. Design/methodology/approach: This paper builds the structure model of manufacturing enterprise’s logistics operational costs from the perspective of inter-firm network and simulates the model based on system dynamics. Findings: It concludes that applying system dynamics in the research of manufacturing enterprise’s logistics cost control can better reflect the relationship of factors in the system. And the case firm can optimize the logistics costs by implement joint distribution. Research limitations/implications: This study still lacks comprehensive consideration about the variables quantities and quantitative of the control factors. In the future, we should strengthen the collection of data and information about the engineering manufacturing firms and improve the logistics operational cost model. Practical implications: This study puts forward some optimization tactics to reduce enterprise’s logistics operational cost. And it is of great significance for enterprise’s supply chain management optimization and logistics cost control. Originality/value: Differing from the existing literatures, this paper builds the structure model of manufacturing enterprise’s logistics operational costs from the perspective of inter-firm network and simulates the model based on system dynamics.
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...
Design of permanent magnet synchronous motor within minimum cost

OpenAIRE

Півняк, Геннадій Григорович; Бешта, Олександр Степанович; Фурса, Сергій Григорійович; Neuberger, Nikolaus; Nolle, N.

2010-01-01

The article describes design and simulation experience of permanent magnet synchronous motor (PMSM). The design goal is to develop PMSM of the least possible cost. For that purpose the standard induction motor stator was applied as a basic solution and permanent magnets were installed in rotor. Simulation results are presented, the dependence of efficiency and total loss on magnet material mass are obtained. The optimal value of permanent magnets is estimated for the given electric motor frame.
Aeroelastic multidisciplinary design optimization of a swept wind turbine blade

DEFF Research Database (Denmark)

Pavese, Christian; Tibaldi, Carlo; Zahle, Frederik

2017-01-01

Mitigating loads on a wind turbine rotor can reduce the cost of energy. Sweeping blades produces a structural coupling between flapwise bending and torsion, which can be used for load alleviation purposes. A multidisciplinary design optimization (MDO) problem is formulated including the blade sweep...
Reliability-Based Optimal Design of Experiment Plans for Offshore Structures

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Faber, Michael Havbro; Kroon, I. B.

1993-01-01

Design of cost optimal experiment plans on the basis of a preposterior analysis is discussed. In particular the planning of on-site response measurements on offshore structures in order to update probabilistic models for fatigue life estimation is addressed. Special emphasis is given to modelling...
Optimal design of cluster-based ad-hoc networks using probabilistic solution discovery

International Nuclear Information System (INIS)

Cook, Jason L.; Ramirez-Marquez, Jose Emmanuel

2009-01-01

The reliability of ad-hoc networks is gaining popularity in two areas: as a topic of academic interest and as a key performance parameter for defense systems employing this type of network. The ad-hoc network is dynamic and scalable and these descriptions are what attract its users. However, these descriptions are also synonymous for undefined and unpredictable when considering the impacts to the reliability of the system. The configuration of an ad-hoc network changes continuously and this fact implies that no single mathematical expression or graphical depiction can describe the system reliability-wise. Previous research has used mobility and stochastic models to address this challenge successfully. In this paper, the authors leverage the stochastic approach and build upon it a probabilistic solution discovery (PSD) algorithm to optimize the topology for a cluster-based mobile ad-hoc wireless network (MAWN). Specifically, the membership of nodes within the back-bone network or networks will be assigned in such as way as to maximize reliability subject to a constraint on cost. The constraint may also be considered as a non-monetary cost, such as weight, volume, power, or the like. When a cost is assigned to each component, a maximum cost threshold is assigned to the network, and the method is run; the result is an optimized allocation of the radios enabling back-bone network(s) to provide the most reliable network possible without exceeding the allowable cost. The method is intended for use directly as part of the architectural design process of a cluster-based MAWN to efficiently determine an optimal or near-optimal design solution. It is capable of optimizing the topology based upon all-terminal reliability (ATR), all-operating terminal reliability (AoTR), or two-terminal reliability (2TR)
Optimizing Teleportation Cost in Distributed Quantum Circuits

Science.gov (United States)

Zomorodi-Moghadam, Mariam; Houshmand, Mahboobeh; Houshmand, Monireh

2018-03-01

The presented work provides a procedure for optimizing the communication cost of a distributed quantum circuit (DQC) in terms of the number of qubit teleportations. Because of technology limitations which do not allow large quantum computers to work as a single processing element, distributed quantum computation is an appropriate solution to overcome this difficulty. Previous studies have applied ad-hoc solutions to distribute a quantum system for special cases and applications. In this study, a general approach is proposed to optimize the number of teleportations for a DQC consisting of two spatially separated and long-distance quantum subsystems. To this end, different configurations of locations for executing gates whose qubits are in distinct subsystems are considered and for each of these configurations, the proposed algorithm is run to find the minimum number of required teleportations. Finally, the configuration which leads to the minimum number of teleportations is reported. The proposed method can be used as an automated procedure to find the configuration with the optimal communication cost for the DQC. This cost can be used as a basic measure of the communication cost for future works in the distributed quantum circuits.
Complex Method Mixed with PSO Applying to Optimization Design of Bridge Crane Girder

Directory of Open Access Journals (Sweden)

He Yan

2017-01-01

Full Text Available In engineer design, basic complex method has not enough global search ability for the nonlinear optimization problem, so it mixed with particle swarm optimization (PSO has been presented in the paper,that is the optimal particle evaluated from fitness function of particle swarm displacement complex vertex in order to realize optimal principle of the largest complex central distance.This method is applied to optimization design problems of box girder of bridge crane with constraint conditions.At first a mathematical model of the girder optimization has been set up,in which box girder cross section area of bridge crane is taken as the objective function, and its four sizes parameters as design variables, girder mechanics performance, manufacturing process, border sizes and so on requirements as constraint conditions. Then complex method mixed with PSO is used to solve optimization design problem of cane box girder from constrained optimization studying approach, and its optimal results have achieved the goal of lightweight design and reducing the crane manufacturing cost . The method is reliable, practical and efficient by the practical engineer calculation and comparative analysis with basic complex method.
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.
Reliability-Based and Cost-Oriented Product Optimization Integrating Fuzzy Reasoning Petri Nets, Interval Expert Evaluation and Cultural-Based DMOPSO Using Crowding Distance Sorting

Directory of Open Access Journals (Sweden)

Zhaoxi Hong

2017-08-01

Full Text Available In reliability-based and cost-oriented product optimization, the target product reliability is apportioned to subsystems or components to achieve the maximum reliability and minimum cost. Main challenges to conducting such optimization design lie in how to simultaneously consider subsystem division, uncertain evaluation provided by experts for essential factors, and dynamic propagation of product failure. To overcome these problems, a reliability-based and cost-oriented product optimization method integrating fuzzy reasoning Petri net (FRPN, interval expert evaluation and cultural-based dynamic multi-objective particle swarm optimization (DMOPSO using crowding distance sorting is proposed in this paper. Subsystem division is performed based on failure decoupling, and then subsystem weights are calculated with FRPN reflecting dynamic and uncertain failure propagation, as well as interval expert evaluation considering six essential factors. A mathematical model of reliability-based and cost-oriented product optimization is established, and the cultural-based DMOPSO with crowding distance sorting is utilized to obtain the optimized design scheme. The efficiency and effectiveness of the proposed method are demonstrated by the numerical example of the optimization design for a computer numerically controlled (CNC machine tool.
On the optimal design of risk retention in securitisation

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Metin Kaptan

2011-09-01

Full Text Available This paper examines the optimal design of retention in securitisation, in order to maximize welfare of screening per unit of retention, assuming that screening is costly and that the bank intends to securitise its loans. In contrast to the focus of previous literature on tranche retention, we deviate from the constitutional mechanisms of tranche retention to present a pareto-optimal method of tranche retention. Unlike the current ad-hoc-regulations, we derive the optimal design of retention from a utility maximization problem. We show that the level of retention per tranche should be dependent on the rate of credit default, i.e. the higher the rate of default, the higher the optimal rate of retention required to provide an incentive to screen carefully. From this approach, it follows that the rate of retention per tranche should be higher, the higher the position within the ranking order of subordination. Accordingly, the efficiency of tranche retention can be enhanced, reducing the level of retention required to maintain a given level of screening-effort. This retention design entails a recovery of the bank’s equity capital, thereby increasing liquidity and lending capacities.

Cost versus life cycle assessment-based environmental impact optimization of drinking water production plants.

Science.gov (United States)

Capitanescu, F; Rege, S; Marvuglia, A; Benetto, E; Ahmadi, A; Gutiérrez, T Navarrete; Tiruta-Barna, L

2016-07-15

Empowering decision makers with cost-effective solutions for reducing industrial processes environmental burden, at both design and operation stages, is nowadays a major worldwide concern. The paper addresses this issue for the sector of drinking water production plants (DWPPs), seeking for optimal solutions trading-off operation cost and life cycle assessment (LCA)-based environmental impact while satisfying outlet water quality criteria. This leads to a challenging bi-objective constrained optimization problem, which relies on a computationally expensive intricate process-modelling simulator of the DWPP and has to be solved with limited computational budget. Since mathematical programming methods are unusable in this case, the paper examines the performances in tackling these challenges of six off-the-shelf state-of-the-art global meta-heuristic optimization algorithms, suitable for such simulation-based optimization, namely Strength Pareto Evolutionary Algorithm (SPEA2), Non-dominated Sorting Genetic Algorithm (NSGA-II), Indicator-based Evolutionary Algorithm (IBEA), Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), Differential Evolution (DE), and Particle Swarm Optimization (PSO). The results of optimization reveal that good reduction in both operating cost and environmental impact of the DWPP can be obtained. Furthermore, NSGA-II outperforms the other competing algorithms while MOEA/D and DE perform unexpectedly poorly. Copyright © 2016 Elsevier Ltd. All rights reserved.
Life cycle cost optimization of buildings with regard to energy use, thermal indoor environment and daylight

DEFF Research Database (Denmark)

Nielsen, Toke Rammer; Svendsen, Svend

2002-01-01

by the life cycle cost taking all expenses in the buildings service life into consideration. Also the performance of buildings is important as the performance influences the comfort of the occupants, heating demand etc. Different performance requirements are stated in building codes, standards......Buildings represent a large economical investment and have long service lives through which expenses for heating, cooling, maintenance and replacement depends on the chosen building design. Therefore, the building cost should not only be evaluated by the initial investment cost but rather...... and by the customer. The influence of different design variables on life cycle cost and building performance is very complicated and the design variables can be combined in an almost unlimited number of ways. Optimization can be applied to achieve a building design with low life cycle cost and good performance...
Data of cost-optimal solutions and retrofit design methods for school renovation in a warm climate.

Science.gov (United States)

Zacà, Ilaria; Tornese, Giuliano; Baglivo, Cristina; Congedo, Paolo Maria; D'Agostino, Delia

2016-12-01

"Efficient Solutions and Cost-Optimal Analysis for Existing School Buildings" (Paolo Maria Congedo, Delia D'Agostino, Cristina Baglivo, Giuliano Tornese, Ilaria Zacà) [1] is the paper that refers to this article. It reports the data related to the establishment of several variants of energy efficient retrofit measures selected for two existing school buildings located in the Mediterranean area. In compliance with the cost-optimal analysis described in the Energy Performance of Buildings Directive and its guidelines (EU, Directive, EU 244,) [2], [3], these data are useful for the integration of renewable energy sources and high performance technical systems for school renovation. The data of cost-efficient high performance solutions are provided in tables that are explained within the following sections. The data focus on the describe school refurbishment sector to which European policies and investments are directed. A methodological approach already used in previous studies about new buildings is followed (Baglivo Cristina, Congedo Paolo Maria, D׳Agostino Delia, Zacà Ilaria, 2015; IlariaZacà, Delia D'Agostino, Paolo Maria Congedo, Cristina Baglivo; Baglivo Cristina, Congedo Paolo Maria, D'Agostino Delia, Zacà Ilaria, 2015; Ilaria Zacà, Delia D'Agostino, Paolo Maria Congedo, Cristina Baglivo, 2015; Paolo Maria Congedo, Cristina Baglivo, IlariaZacà, Delia D'Agostino,2015) [4], [5], [6], [7], [8]. The files give the cost-optimal solutions for a kindergarten (REF1) and a nursery (REF2) school located in Sanarica and Squinzano (province of Lecce Southern Italy). The two reference buildings differ for construction period, materials and systems. The eleven tables provided contain data about the localization of the buildings, geometrical features and thermal properties of the envelope, as well as the energy efficiency measures related to walls, windows, heating, cooling, dhw and renewables. Output values of energy consumption, gas emission and costs are given for a
Discounted cost model for condition-based maintenance optimization

International Nuclear Information System (INIS)

Weide, J.A.M. van der; Pandey, M.D.; Noortwijk, J.M. van

2010-01-01

This paper presents methods to evaluate the reliability and optimize the maintenance of engineering systems that are damaged by shocks or transients arriving randomly in time and overall degradation is modeled as a cumulative stochastic point process. The paper presents a conceptually clear and comprehensive derivation of formulas for computing the discounted cost associated with a maintenance policy combining both condition-based and age-based criteria for preventive maintenance. The proposed discounted cost model provides a more realistic basis for optimizing the maintenance policies than those based on the asymptotic, non-discounted cost rate criterion.
Design optimization of superconducting magnetic energy storage coil

Energy Technology Data Exchange (ETDEWEB)

Bhunia, Uttam, E-mail: ubhunia@vecc.gov.in; Saha, Subimal; Chakrabarti, Alok

2014-05-15

Highlights: • We modeled the optimization formulation that minimizes overall refrigeration load into the SMES cryostat. • Higher the operating current reduces the dynamic load but increases static heat load into the cryostat. • Higher allowable hoop stress reduces both coil volume and refrigeration load. • The formulation can be in general be utilized for any arbitrary specification of SMES coil and conductor type. - Abstract: An optimization formulation has been developed for a superconducting magnetic energy storage (SMES) solenoid-type coil with niobium titanium (Nb–Ti) based Rutherford-type cable that minimizes the cryogenic refrigeration load into the cryostat. Minimization of refrigeration load reduces the operating cost and opens up the possibility to adopt helium re-condensing system using cryo-cooler especially for small-scale SMES system. Dynamic refrigeration load during charging or discharging operational mode of the coil dominates over steady state load. The paper outlines design optimization with practical design constraints like actual critical characteristics of the superconducting cable, maximum allowable hoop stress on winding, etc., with the objective to minimize refrigeration load into the SMES cryostat. Effect of design parameters on refrigeration load is also investigated.
Scope Oriented Thermoeconomic analysis of energy systems. Part II: Formation Structure of Optimality for robust design

International Nuclear Information System (INIS)

Piacentino, Antonio; Cardona, Ennio

2010-01-01

This paper represents the Part II of a paper in two parts. In Part I the fundamentals of Scope Oriented Thermoeconomics have been introduced, showing a scarce potential for the cost accounting of existing plants; in this Part II the same concepts are applied to the optimization of a small set of design variables for a vapour compression chiller. The method overcomes the limit of most conventional optimization techniques, which are usually based on hermetic algorithms not enabling the energy analyst to recognize all the margins for improvement. The Scope Oriented Thermoeconomic optimization allows us to disassemble the optimization process, thus recognizing the Formation Structure of Optimality, i.e. the specific influence of any thermodynamic and economic parameter in the path toward the optimal design. Finally, the potential applications of such an in-depth understanding of the inner driving forces of the optimization are discussed in the paper, with a particular focus on the sensitivity analysis to the variation of energy and capital costs and on the actual operation-oriented design.
Optimization of costs versus radiation exposures in decommissioning

International Nuclear Information System (INIS)

Konzek, G.J.

1979-01-01

The estimated worth of decommissioning optimization planning during each phase of the reactor's life cycle is dependent on many variables. The major variables are tabulated and relatively ranked. For each phase, optimization qualitative values (i.e., cost, safety, maintainability, ALARA, and decommissioning considerations) are estimated and ranked according to their short-term and long-term potential benefits. These estimates depend on the quality of the input data, interpretation of that data, and engineering judgment. Once identified and ranked, these considerations form an integral part of the information data base from which estimates, decisions, and alternatives are derived. The optimization of costs and the amount of occupational radiation exposure reductions are strongly interrelated during decommissioning. Realizing that building the necessary infrastructure for decommissioning will take time is an important first step in any decommissioning plan. In addition, the following conclusions are established to achieve optimization of costs and reduced occupational radiation exposures: the assignment of cost versus man-rem is item-specific and sensitive to the expertise of many interrelated disciplines; a commitment to long-term decommissioning planning by management will provide the conditions needed to achieve optimization; and, to be most effective, costs and exposure reduction are sensitive to the nearness of the decommissioning operation. For a new plant, it is best to start at the beginning of the cycle, update continually, consider innovations, and realize full potential and benefits of this concept. For an older plant, the life cycle methodology permits a comprehensive review of the plant history and the formulation of an orderly decommissioning program based on planning, organization, and effort
Design optimization and analysis of vertical axis wind turbine blade

International Nuclear Information System (INIS)

Jarral, A.; Ali, M.; Sahir, M.H.

2013-01-01

Wind energy is clean and renwable source of energy and is also the world's fastest growing energy resource. Keeping in view power shortages and growing cost of energy, the low cost wind energy has become a primary solution. It is imperative that economies and individuals begin to conserve energy and focus on the production of energy from renewable sources. Present study describes a wind turbine blade designed with enhanced aerodynamic properties. Vertical axis turbine is chosen because of its easy installment, less noisy and having environmental friendly characteristics. Vertical axis wind turbines are thought to be ideal for installations where wind conditions are not consistent. The presented turbine blade is best suitable for roadsides where the rated speed due to vehicles is most /sup -1/ often 8 ms .To get an optimal shape design symmetrical profile NACA0025 has been considered which is then analyzed for stability and aerodynamic characteristics at optimal conditions using analysis tools ANSYS and CFD tools. (author)
Analysis and Design Optimization of a Coaxial Surface-Mounted Permanent-Magnet Magnetic Gear

DEFF Research Database (Denmark)

Zhang, Xiaoxu; Liu, Xiao; Wang, Chao

2014-01-01

). The analytical field solution allows the prediction of the magnetic torque, which is formulated as a function of design parameters. The impacts of key design parameters on the torque capability are then studied and some significant observations are summarized. Furthermore, the particle swarm optimization (PSO...... on one or another. The results shows that the highest torque density of 157 kNm/m3 is achieved with the consideration focusing on the torque capability only, then the highest torque per permanent magnet (PM) consumption could be improved to 145 Nm/kg by taking the material cost into account....... By synthesizing the torque capability and material cost, a 124 kNm/m3 of torque density and a 128 Nm/kg of torque per PM consumption could be achieved simultaneously by the optimal design....
Genetic algorithm for project time-cost optimization in fuzzy environment

Directory of Open Access Journals (Sweden)

Khan Md. Ariful Haque

2012-12-01

Full Text Available Purpose: The aim of this research is to develop a more realistic approach to solve project time-cost optimization problem under uncertain conditions, with fuzzy time periods. Design/methodology/approach: Deterministic models for time-cost optimization are never efficient considering various uncertainty factors. To make such problems realistic, triangular fuzzy numbers and the concept of a-cut method in fuzzy logic theory are employed to model the problem. Because of NP-hard nature of the project scheduling problem, Genetic Algorithm (GA has been used as a searching tool. Finally, Dev-C++ 4.9.9.2 has been used to code this solver. Findings: The solution has been performed under different combinations of GA parameters and after result analysis optimum values of those parameters have been found for the best solution. Research limitations/implications: For demonstration of the application of the developed algorithm, a project on new product (Pre-paid electric meter, a project under government finance launching has been chosen as a real case. The algorithm is developed under some assumptions. Practical implications: The proposed model leads decision makers to choose the desired solution under different risk levels. Originality/value: Reports reveal that project optimization problems have never been solved under multiple uncertainty conditions. Here, the function has been optimized using Genetic Algorithm search technique, with varied level of risks and fuzzy time periods.
Optimal Design of Gravitational Sewer Networks with General Cellular Automata

Directory of Open Access Journals (Sweden)

Mohammad Hadi Afshar

2014-05-01

Full Text Available In this paper, a Cellular Automata method is applied for the optimal design of sewer networks. The solution of sewer network optimization problems requires the determination of pipe diameters and average pipe cover depths, minimizing the total cost of the sewer network subject to operational constraints. In this paper, the network nodes and upstream and downstream pipe cover depths are considered as CA cells and cell states, respectively, and the links around each cell are taken into account as neighborhood. The proposed method is a general and flexible method for the optimization of sewer networks as it can be used to optimally design both gravity and pumped network due to the use of pipe nodal cover depths as the decision variables. The proposed method is tested against two gravitational sewer networks and the comparison of results with other methods such as Genetic algorithm, Cellular Automata, Ant Colony Optimization Algorithm and Particle Swarm Optimization show the efficiency and effectiveness of the proposed method.
Cost-optimal levels for energy performance requirements

DEFF Research Database (Denmark)

Thomsen, Kirsten Engelund; Aggerholm, Søren; Kluttig-Erhorn, Heike

2011-01-01

The CA conducted a study on experiences and challenges for setting cost optimal levels for energy performance requirements. The results were used as input by the EU Commission in their work of establishing the Regulation on a comparative methodology framework for calculating cost optimal levels...... of minimum energy performance requirements. In addition to the summary report released in August 2011, the full detailed report on this study is now also made available, just as the EC is about to publish its proposed Regulation for MS to apply in their process to update national building requirements....
Tradeoffs between costs and greenhouse gas emissions in the design of urban transit systems

International Nuclear Information System (INIS)

Griswold, Julia B; Madanat, Samer; Horvath, Arpad

2013-01-01

Recent investments in the transit sector to address greenhouse gas emissions have concentrated on purchasing efficient replacement vehicles and inducing mode shift from the private automobile. There has been little focus on the potential of network and operational improvements, such as changes in headways, route spacing, and stop spacing, to reduce transit emissions. Most models of transit system design consider user and agency cost while ignoring emissions and the potential environmental benefit of operational improvements. We use a model to evaluate the user and agency costs as well as greenhouse gas benefit of design and operational improvements to transit systems. We examine how the operational characteristics of urban transit systems affect both costs and greenhouse gas emissions. The research identifies the Pareto frontier for designing an idealized transit network. Modes considered include bus, bus rapid transit (BRT), light rail transit (LRT), and metro (heavy) rail, with cost and emissions parameters appropriate for the United States. Passenger demand follows a many-to-many travel pattern with uniformly distributed origins and destinations. The approaches described could be used to optimize the network design of existing bus service or help to select a mode and design attributes for a new transit system. The results show that BRT provides the lowest cost but not the lowest emissions for our large city scenarios. Bus and LRT systems have low costs and the lowest emissions for our small city scenarios. Relatively large reductions in emissions from the cost-optimal system can be achieved with only minor increases in user travel time. (letter)
METHODS FOR DETERMINATION AND OPTIMIZATION OF LOGISTICS COSTS

OpenAIRE

Mihaela STET

2016-01-01

The paper is dealing with the problems of logistics costs, highlighting some methods for estimation and determination of specific costs for different transport modes in freight distribution. There are highlighted, besides costs of transports, the other costs in supply chain, as well as costing methods used in logistics activities. In this context, there are also revealed some optimization means of transport costs in logistics chain.
Investigation of Cost and Energy Optimization of Drinking Water Distribution Systems.

Science.gov (United States)

Cherchi, Carla; Badruzzaman, Mohammad; Gordon, Matthew; Bunn, Simon; Jacangelo, Joseph G

2015-11-17

Holistic management of water and energy resources through energy and water quality management systems (EWQMSs) have traditionally aimed at energy cost reduction with limited or no emphasis on energy efficiency or greenhouse gas minimization. This study expanded the existing EWQMS framework and determined the impact of different management strategies for energy cost and energy consumption (e.g., carbon footprint) reduction on system performance at two drinking water utilities in California (United States). The results showed that optimizing for cost led to cost reductions of 4% (Utility B, summer) to 48% (Utility A, winter). The energy optimization strategy was successfully able to find the lowest energy use operation and achieved energy usage reductions of 3% (Utility B, summer) to 10% (Utility A, winter). The findings of this study revealed that there may be a trade-off between cost optimization (dollars) and energy use (kilowatt-hours), particularly in the summer, when optimizing the system for the reduction of energy use to a minimum incurred cost increases of 64% and 184% compared with the cost optimization scenario. Water age simulations through hydraulic modeling did not reveal any adverse effects on the water quality in the distribution system or in tanks from pump schedule optimization targeting either cost or energy minimization.
Aerodynamics and Optimal Design of Biplane Wind Turbine Blades

Science.gov (United States)

Chiu, Phillip

In order to improve energy capture and reduce the cost of wind energy, in the past few decades wind turbines have grown significantly larger. As their blades get longer, the design of the inboard region (near the blade root) becomes a trade-off between competing structural and aerodynamic requirements. State-of-the-art blades require thick airfoils near the root to efficiently support large loads inboard, but those thick airfoils have inherently poor aerodynamic performance. New designs are required to circumvent this design compromise. One such design is the "biplane blade", in which the thick airfoils in the inboard region are replaced with thinner airfoils in a biplane configuration. This design was shown previously to have significantly increased structural performance over conventional blades. In addition, the biplane airfoils can provide increased lift and aerodynamic efficiency compared to thick monoplane inboard airfoils, indicating a potential for increased power extraction. This work investigates the fundamental aerodynamic aspects, aerodynamic design and performance, and optimal structural design of the biplane blade. First, the two-dimensional aerodynamics of biplanes with relatively thick airfoils are investigated, showing unique phenomena which arise as a result of airfoil thickness. Next, the aerodynamic design of the full biplane blade is considered. Two biplane blades are designed for optimal aerodynamic loading, and their aerodynamic performance quantified. Considering blades with practical chord distributions and including the drag of the mid-blade joint, it is shown that biplane blades have comparable power output to conventional monoplane designs. The results of this analysis also show that the biplane blades can be designed with significantly less chord than conventional designs, a characteristic which enables larger blade designs. The aerodynamic loads on the biplane blades are shown to be increased in gust conditions and decreased under
Environomic design of vehicle energy systems for optimal mobility service

OpenAIRE

Dimitrova, Zlatina Kirilova; Maréchal, François

2014-01-01

The main design criteria for the modern sustainable development of vehicle powertrains are the high energy efficiency of the conversion system, the competitive cost and the lowest possible environmental impacts. An innovative decision making methodology, using multi-objective optimization technics is currently under development. The idea is to obtain a population of possible design solutions corresponding to the most efficient energy system definition. These solutions meet technical, economic...
Limited applicability of cost-effectiveness and cost-benefit analyses for the optimization of radon remedial measures

International Nuclear Information System (INIS)

Jiránek, Martin; Rovenská, Kateřina

2010-01-01

Ways of using different decision-aiding techniques for optimizing and evaluating radon remedial measures have been studied on a large set of data obtained from the remediation of 32 houses that had an original indoor radon concentration level above 1,000 Bq/m 3 (around 0.2 % of all dwellings in the Czech Republic have a radon concentration higher than 1,000 Bq/ m 3 ). Detailed information about radon concentrations before and after remediation, type and extent of remedial measures and installation and operation costs were used as the input parameters for a comparison of costs and for determining the efficiencies, for a cost-benefit analysis and a cost-effectiveness analysis, in order to find out whether these criteria and techniques provide sufficient and relevant information for the improvement and optimization of remediation. The study has delivered quite new results. It is confirmed that the installation costs of remedial measures do not depend on the original level of indoor radon concentration, but on the technical state of the building. In addition, the study reveals that the efficiency of remediation does not depend on the installation costs. Each of the studied remedial measures will on an average save 0.3 lives and gain 4.3 years of life. On one hand, the general decision-aiding techniques - cost-benefit analysis and cost-effectiveness analysis - lead to the conclusion that the remedial measures reducing the indoor radon concentration from values above 1,000 Bq/m 3 to values below the action level of 400 Bq/m 3 are always acceptable and reasonable. On the other hand, these analytical techniques can neither help the designer to choose the proper remedial measure nor provide information resulting in improved remediation. (author)
Cost-benefit analysis for design of environmentally conscious manufacturing

International Nuclear Information System (INIS)

Matysiak, L.M.

1993-01-01

In recent years, much attention has been focused on reducing the environmental impacts of products and manufacturing processes. Concerned about rising compliance costs and stringent regulatory requirements, companies are carefully evaluating the environmental impacts of their products. In response, designers, engineers, and managers are beginning to use life-cycle analysis, design for environment techniques, and environmentally conscious manufacturing (ECM) as tools to help them to not only do what is best for the environment, but also to do what is best for their company. These tools are also a useful aid in evaluating the trade-offs that may exist between different product and process alternatives. However, how does one choose the optimal solution from these various product and process alternatives? Cost versus benefit analysis is an effective tool that can be used to evaluate various manufacturing alternatives and to choose a solution that is both cost effective and environmentally compatible. Many companies are beginning to use cost benefit analyses as a means to justify product or process modifications that result in a benefit to the environment
Acoustic performance design and optimal allocation of sound package in ship cabin noise reduction

Directory of Open Access Journals (Sweden)

YANG Deqing

2017-08-01

Full Text Available The sound package in noise reduction design of ship cabins has become the main approach for the future. The sound package is a specially designed acoustic component consisting of damping materials, absorption materials, sound isolation materials and base structural materials which can achieve the prescribed performance of noise reduction. Based on the Statistical Energy Analysis(SEAmethod, quick evaluation and design methods, and the optimal allocation theory of sound packages are investigated. The standard numerical acoustic performance evaluation model, sound package optimization design model and sound package optimal allocation model are presented. A genetic algorithm is applied to solve the presented optimization problems. Design examples demonstrate the validity and efficiency of the proposed models and solutions. The presented theory and methods benefit the standardization and programming of sound package design, and decrease noise reduction costs.

Genetic algorithm based optimization on modeling and design of hybrid renewable energy systems

International Nuclear Information System (INIS)

Ismail, M.S.; Moghavvemi, M.; Mahlia, T.M.I.

2014-01-01

Highlights: • Solar data was analyzed in the location under consideration. • A program was developed to simulate operation of the PV hybrid system. • Genetic algorithm was used to optimize the sizes of the hybrid system components. • The costs of the pollutant emissions were considered in the optimization. • It is cost effective to power houses in remote areas with such hybrid systems. - Abstract: A sizing optimization of a hybrid system consisting of photovoltaic (PV) panels, a backup source (microturbine or diesel), and a battery system minimizes the cost of energy production (COE), and a complete design of this optimized system supplying a small community with power in the Palestinian Territories is presented in this paper. A scenario that depends on a standalone PV, and another one that depends on a backup source alone were analyzed in this study. The optimization was achieved via the usage of genetic algorithm. The objective function minimizes the COE while covering the load demand with a specified value for the loss of load probability (LLP). The global warming emissions costs have been taken into account in this optimization analysis. Solar radiation data is firstly analyzed, and the tilt angle of the PV panels is then optimized. It was discovered that powering a small rural community using this hybrid system is cost-effective and extremely beneficial when compared to extending the utility grid to supply these remote areas, or just using conventional sources for this purpose. This hybrid system decreases both operating costs and the emission of pollutants. The hybrid system that realized these optimization purposes is the one constructed from a combination of these sources
Optimizing an experimental design for an electromagnetic experiment

Science.gov (United States)

Roux, Estelle; Garcia, Xavier

2013-04-01

Most of geophysical studies focus on data acquisition and analysis, but another aspect which is gaining importance is the discussion on acquisition of suitable datasets. This can be done through the design of an optimal experiment. Optimizing an experimental design implies a compromise between maximizing the information we get about the target and reducing the cost of the experiment, considering a wide range of constraints (logistical, financial, experimental …). We are currently developing a method to design an optimal controlled-source electromagnetic (CSEM) experiment to detect a potential CO2 reservoir and monitor this reservoir during and after CO2 injection. Our statistical algorithm combines the use of linearized inverse theory (to evaluate the quality of one given design via the objective function) and stochastic optimization methods like genetic algorithm (to examine a wide range of possible surveys). The particularity of our method is that it uses a multi-objective genetic algorithm that searches for designs that fit several objective functions simultaneously. One main advantage of this kind of technique to design an experiment is that it does not require the acquisition of any data and can thus be easily conducted before any geophysical survey. Our new experimental design algorithm has been tested with a realistic one-dimensional resistivity model of the Earth in the region of study (northern Spain CO2 sequestration test site). We show that a small number of well distributed observations have the potential to resolve the target. This simple test also points out the importance of a well chosen objective function. Finally, in the context of CO2 sequestration that motivates this study, we might be interested in maximizing the information we get about the reservoir layer. In that case, we show how the combination of two different objective functions considerably improve its resolution.
Usage of Numerical Optimization in Wind Turbine Airfoil Design

Energy Technology Data Exchange (ETDEWEB)

Grasso, F. [ECN Wind Energy, Petten (Netherlands)

2011-01-15

One important key element in the aerodynamic design of wind turbines is the use of specially tailored airfoils to increase the ratio of energy capture to the loading and thereby to reduce the cost of energy. This work is focused on the design of a wind turbine airfoil by using numerical optimization. First, the requirements for this class of airfoils are illustrated and discussed in order to have an exhaustive outline of the complexity of the problem. Then the optimization approach is presented; a gradient-based algorithm is used, coupled with RFOIL solver and a composite Bezier geometrical parameterization. A particularly sensitive point is the choice and implementation of constraints; to formalize the design requirements in the most complete and effective way, the effects of activating specific constraints are discussed. Finally, a numerical example regarding the design of a high-efficiency airfoil for the outer part of a blade is illustrated, and the results are compared with existing wind turbine airfoils.
METHODS FOR DETERMINATION AND OPTIMIZATION OF LOGISTICS COSTS

Directory of Open Access Journals (Sweden)

Mihaela STET

2016-12-01

Full Text Available The paper is dealing with the problems of logistics costs, highlighting some methods for estimation and determination of specific costs for different transport modes in freight distribution. There are highlighted, besides costs of transports, the other costs in supply chain, as well as costing methods used in logistics activities. In this context, there are also revealed some optimization means of transport costs in logistics chain.
Cost optimization of induction linac drivers for linear colliders

International Nuclear Information System (INIS)

Barletta, W.A.

1986-01-01

Recent developments in high reliability components for linear induction accelerators (LIA) make possible the use of these devices as economical power drives for very high gradient linear colliders. A particularly attractive realization of this ''two-beam accelerator'' approach is to configure the LIA as a monolithic relativistic klystron operating at 10 to 12 GHz with induction cells providing periodic reacceleration of the high current beam. Based upon a recent engineering design of a state-of-the-art, 10- to 20-MeV LIA at Lawrence Livermore National Laboratory, this paper presents an algorithm for scaling the cost of the relativistic klystron to the parameter regime of interest for the next generation high energy physics machines. The algorithm allows optimization of the collider luminosity with respect to cost by varying the characteristics (pulse length, drive current, repetition rate, etc.) of the klystron. It also allows us to explore cost sensitivities as a guide to research strategies for developing advanced accelerator technologies
Robust Optimization for Time-Cost Tradeoff Problem in Construction Projects

OpenAIRE

Li, Ming; Wu, Guangdong

2014-01-01

Construction projects are generally subject to uncertainty, which influences the realization of time-cost tradeoff in project management. This paper addresses a time-cost tradeoff problem under uncertainty, in which activities in projects can be executed in different construction modes corresponding to specified time and cost with interval uncertainty. Based on multiobjective robust optimization method, a robust optimization model for time-cost tradeoff problem is developed. In order to illus...
Design of homo-organic acid producing strains using multi-objective optimization

DEFF Research Database (Denmark)

Kim, Tae Yong; Park, Jong Myoung; Kim, Hyun Uk

2015-01-01

Production of homo-organic acids without byproducts is an important challenge in bioprocess engineering to minimize operation cost for separation processes. In this study, we used multi-objective optimization to design Escherichia coli strains with the goals of maximally producing target organic ...
Fuel mechanical design as a boundary condition for fuel management optimization

International Nuclear Information System (INIS)

Wunderlich, F.; Aisch, F.W.; Heins, L.

1988-01-01

The incentive to reduce fuel cycle costs as well as the amount of active waste requires, among others, measures to optimize fuel management. Improved fuel management in this sense calls, e.g., for reduction of parasitic neutron absorption, for reduction of neutron leakage, and particularly for burnup extension. Such measures result in increased demands for fuel mechanical design. In the first part of this paper their impact on fuel mechanical behaviour is described. In the second part, some examples of practical importance for the interaction between fuel management optimization and fuel mechanical design are discussed. (orig.) [de
Optimal Solution for VLSI Physical Design Automation Using Hybrid Genetic Algorithm

Directory of Open Access Journals (Sweden)

I. Hameem Shanavas

2014-01-01

Full Text Available In Optimization of VLSI Physical Design, area minimization and interconnect length minimization is an important objective in physical design automation of very large scale integration chips. The objective of minimizing the area and interconnect length would scale down the size of integrated chips. To meet the above objective, it is necessary to find an optimal solution for physical design components like partitioning, floorplanning, placement, and routing. This work helps to perform the optimization of the benchmark circuits with the above said components of physical design using hierarchical approach of evolutionary algorithms. The goal of minimizing the delay in partitioning, minimizing the silicon area in floorplanning, minimizing the layout area in placement, minimizing the wirelength in routing has indefinite influence on other criteria like power, clock, speed, cost, and so forth. Hybrid evolutionary algorithm is applied on each of its phases to achieve the objective. Because evolutionary algorithm that includes one or many local search steps within its evolutionary cycles to obtain the minimization of area and interconnect length. This approach combines a hierarchical design like genetic algorithm and simulated annealing to attain the objective. This hybrid approach can quickly produce optimal solutions for the popular benchmarks.
Design and optimization of all-optical networks

Science.gov (United States)

Xiao, Gaoxi

1999-10-01

In this thesis, we present our research results on the design and optimization of all-optical networks. We divide our results into the following four parts: 1.In the first part, we consider broadcast-and-select networks. In our research, we propose an alternative and cheaper network configuration to hide the tuning time. In addition, we derive lower bounds on the optimal schedule lengths and prove that they are tighter than the best existing bounds. 2.In the second part, we consider all-optical wide area networks. We propose a set of algorithms for allocating a given number of WCs to the nodes. We adopt a simulation-based optimization approach, in which we collect utilization statistics of WCs from computer simulation and then perform optimization to allocate the WCs. Therefore, our algorithms are widely applicable and they are not restricted to any particular model and assumption. We have conducted extensive computer simulation on regular and irregular networks under both uniform and non-uniform traffic. We see that our method can get nearly the same performance as that of full wavelength conversion by using a much smaller number of WCs. Compared with the best existing method, the results show that our algorithms can significantly reduce (1)the overall blocking probability (i.e., better mean quality of service) and (2)the maximum of the blocking probabilities experienced at all the source nodes (i.e., better fairness). Equivalently, for a given performance requirement on blocking probability, our algorithms can significantly reduce the number of WCs required. 3.In the third part, we design and optimize the physical topology of all-optical wide area networks. We show that the design problem is NP-complete and we propose a heuristic algorithm called two-stage cut saturation algorithm for this problem. Simulation results show that (1)the proposed algorithm can efficiently design networks with low cost and high utilization, and (2)if wavelength converters are
Technology-design-manufacturing co-optimization for advanced mobile SoCs

Science.gov (United States)

Yang, Da; Gan, Chock; Chidambaram, P. R.; Nallapadi, Giri; Zhu, John; Song, S. C.; Xu, Jeff; Yeap, Geoffrey

2014-03-01

How to maintain the Moore's Law scaling beyond the 193 immersion resolution limit is the key question semiconductor industry needs to answer in the near future. Process complexity will undoubtfully increase for 14nm node and beyond, which brings both challenges and opportunities for technology development. A vertically integrated design-technologymanufacturing co-optimization flow is desired to better address the complicated issues new process changes bring. In recent years smart mobile wireless devices have been the fastest growing consumer electronics market. Advanced mobile devices such as smartphones are complex systems with the overriding objective of providing the best userexperience value by harnessing all the technology innovations. Most critical system drivers are better system performance/power efficiency, cost effectiveness, and smaller form factors, which, in turns, drive the need of system design and solution with More-than-Moore innovations. Mobile system-on-chips (SoCs) has become the leading driver for semiconductor technology definition and manufacturing. Here we highlight how the co-optimization strategy influenced architecture, device/circuit, process technology and package, in the face of growing process cost/complexity and variability as well as design rule restrictions.
Optimization of airfoil-type PCHE for the recuperator of small scale brayton cycle by cost-based objective function

International Nuclear Information System (INIS)

Kwon, Jin Gyu; Kim, Tae Ho; Park, Hyun Sun; Cha, Jae Eun; Kim, Moo Hwan

2016-01-01

Highlights: • Suggest the Nusselt number and Fanning friction factor correlation for airfoil-type PCHE. • Show that cost-based optimization is available to airfoil-type PCHE. • Suggest the recuperator design for SCIEL test loop at KAERI by cost-based objective function with correlations from numerical analysis. - Abstract: Supercritical carbon dioxide (SCO_2) Brayton cycle gives high efficiency of power cycle with small size. Printed circuit heat exchangers (PCHE) are proper selection for the Brayton cycle because their operability at high temperature and high pressure with small size. Airfoil fin PCHE was suggested by Kim et al. (2008b), it can provide high heat transfer-like zigzag channel PCHE with low pressure drop-like straight channel PCHE. Optimization of the airfoil fin PCHE was not performed like the zigzag channel PCHE. For optimization of the airfoil fin PCHE, the operating condition of the recuperator of SCO_2 Integral Experiment Loop (SCIEL) Brayton cycle test loop at Korea Atomic Energy Research Institute (KAERI) was used. We performed CFD analysis for various airfoil fin configurations using ANSYS CFX 15.0, and made correlations for predicting the Nusselt number and the Fanning friction factor. The recuperator was designed by the simple energy balance code with our correlations. Using the cost-based objective function with production cost and operation cost from size and pressure drop of the recuperator, we evaluated airfoil fin configuration by using total cost and suggested the optimization configuration of the airfoil fin PCHE.
Optimization of airfoil-type PCHE for the recuperator of small scale brayton cycle by cost-based objective function

Energy Technology Data Exchange (ETDEWEB)

Kwon, Jin Gyu [Division of Advanced Nuclear Engineering, POSTECH, Pohang 790-784 (Korea, Republic of); Kim, Tae Ho [Department of Mechanical Engineering, POSTECH, Pohang 790-784 (Korea, Republic of); Park, Hyun Sun, E-mail: hejsunny@postech.ac.kr [Division of Advanced Nuclear Engineering, POSTECH, Pohang 790-784 (Korea, Republic of); Cha, Jae Eun [Korea Atomic Energy Research Institute, Daejeon 305-353 (Korea, Republic of); Kim, Moo Hwan [Division of Advanced Nuclear Engineering, POSTECH, Pohang 790-784 (Korea, Republic of); Korea Institute of Nuclear Safety, Daejeon 305-338 (Korea, Republic of)

2016-03-15

Highlights: • Suggest the Nusselt number and Fanning friction factor correlation for airfoil-type PCHE. • Show that cost-based optimization is available to airfoil-type PCHE. • Suggest the recuperator design for SCIEL test loop at KAERI by cost-based objective function with correlations from numerical analysis. - Abstract: Supercritical carbon dioxide (SCO{sub 2}) Brayton cycle gives high efficiency of power cycle with small size. Printed circuit heat exchangers (PCHE) are proper selection for the Brayton cycle because their operability at high temperature and high pressure with small size. Airfoil fin PCHE was suggested by Kim et al. (2008b), it can provide high heat transfer-like zigzag channel PCHE with low pressure drop-like straight channel PCHE. Optimization of the airfoil fin PCHE was not performed like the zigzag channel PCHE. For optimization of the airfoil fin PCHE, the operating condition of the recuperator of SCO{sub 2} Integral Experiment Loop (SCIEL) Brayton cycle test loop at Korea Atomic Energy Research Institute (KAERI) was used. We performed CFD analysis for various airfoil fin configurations using ANSYS CFX 15.0, and made correlations for predicting the Nusselt number and the Fanning friction factor. The recuperator was designed by the simple energy balance code with our correlations. Using the cost-based objective function with production cost and operation cost from size and pressure drop of the recuperator, we evaluated airfoil fin configuration by using total cost and suggested the optimization configuration of the airfoil fin PCHE.
Rotorcraft Optimization Tools: Incorporating Rotorcraft Design Codes into Multi-Disciplinary Design, Analysis, and Optimization

Science.gov (United States)

Meyn, Larry A.

2018-01-01

One of the goals of NASA's Revolutionary Vertical Lift Technology Project (RVLT) is to provide validated tools for multidisciplinary design, analysis and optimization (MDAO) of vertical lift vehicles. As part of this effort, the software package, RotorCraft Optimization Tools (RCOTOOLS), is being developed to facilitate incorporating key rotorcraft conceptual design codes into optimizations using the OpenMDAO multi-disciplinary optimization framework written in Python. RCOTOOLS, also written in Python, currently supports the incorporation of the NASA Design and Analysis of RotorCraft (NDARC) vehicle sizing tool and the Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics II (CAMRAD II) analysis tool into OpenMDAO-driven optimizations. Both of these tools use detailed, file-based inputs and outputs, so RCOTOOLS provides software wrappers to update input files with new design variable values, execute these codes and then extract specific response variable values from the file outputs. These wrappers are designed to be flexible and easy to use. RCOTOOLS also provides several utilities to aid in optimization model development, including Graphical User Interface (GUI) tools for browsing input and output files in order to identify text strings that are used to identify specific variables as optimization input and response variables. This paper provides an overview of RCOTOOLS and its use
Design, performance and cost of energy from high concentration and flat-plate utility-scale PV systems

International Nuclear Information System (INIS)

Stolte, W.J.; Whisnant, R.A.; McGowin, C.R.

1993-01-01

This paper presents the results of a recent study to assess the near-term cost of power in central station applications. Three PV technologies were evaluated: Fresnel-lens high-concentration photovoltaic (HCPV), central receiver HCPV, and flat-plate PV using thin-film copper indium diselenide (CIS) cell technology. Baseline assumptions included PV cell designs and performances projected for the 1995 timeframe, 25 and 100 MW/year cell manufacturing rates, 50 MW power plant size, and mature technology cost and performance estimates. The plant design characteristics are highlighted. Potential sites were evaluated and selected for the PV power plants (Carrisa Plains, CA and Apalachicola, FL) and cell manufacturing plants (Dallas-Fort Worth, TX). Conceptual designs and cost estimates were developed for the plants and their components. Plant performance was modeled and the designs were optimized to minimize levelized energy costs. Overall, the flat plate design exhibited the lowest energy costs among the designs evaluated. Its levelized energy costs at the Carrisa Plains site were estimated to be 11.8 and 10.8 cents/kWh (1990 $) for 25 and 100 MW/year module production rates, respectively. This meets the 12 cents/kWh DOE near-term goal. The energy cost of the Fresnel lens plant (at Carrisa Plains and a 100 MW/year cell production rate) was estimated to be 12.4 cents/kWh and the corresponding central receiver energy cost was estimated to be 13.1 cents/kWh, both of which are very close to the DOE goal. Further design optimization efforts are still warranted and can be expected to reduce plant capital costs
Staged Optimization Design for Updating Urban Drainage Systems in a City of China

Directory of Open Access Journals (Sweden)

Kui Xu

2018-01-01

Full Text Available Flooding has been reported more often than in the past in most cities of China in recent years. In response, China’s State Council has urged the 36 largest cities to update the preparedness to handle the 50-year rainfall, which would be a massive project with large investments. We propose a staged optimization design for updating urban drainage that is not only a flexible option against environmental changes, but also an effective way to reduce the cost of the project. The staged cost optimization model involving the hydraulic model was developed in Fuzhou City, China. This model was established to minimize the total present costs, including intervention costs and flooding costs, with full consideration of the constraints of specific local conditions. The results show that considerable financial savings could be achieved by a staged design rather than the implement-once scheme. The model’s sensitivities to four data parameters were analyzed, including rainfall increase rate, flood unit cost, storage unit cost, and discount rate. The results confirm the applicability and robustness of the model for updating drainage systems to meet the requirements. The findings of this study may have important implications on urban flood management in the cities of developing countries with limited construction investments.
Design of a low-cost thermoacoustic electricity generator and its experimental verification

Energy Technology Data Exchange (ETDEWEB)

Backhaus, Scott N [Los Alamos National Laboratory; Yu, Z [UNIV OF MANCHESTER; Jaworski, A J [UNIV OF MANCHESTER

2010-01-01

This paper describes the design and testing of a low cost thermoacoustic generator. A travelling-wave thermoacoustic engine with a configuration of a looped-tube resonator is designed and constructed to convert heat to acoustic power. A commercially available, low-cost loudspeaker is adopted as the alternator to convert the engine's acoustic power to electricity. The whole system is designed using linear thermoacoustic theory. The optimization of different parts of the thermoacoustic generator, as well as the matching between the thermoacoustic engine and the alternator are discussed in detail. A detailed comparison between the preliminary test results and linear thermoacoustic predictions is provided.
Economical optimization of building elements for use in design of nearly zero energy buildings

DEFF Research Database (Denmark)

Hansen, Sanne

2012-01-01

Nearly zero energy buildings are to become a requirement as part of the European energy policy. There are many ways of designing nearly zero energy buildings, but there is a lack of knowledge on how to end up with the most economical optimal solution. Therefore this paper present a method...... for finding the economical optimal solutions based on the use of the cost of conserved energy for each main building envelope part and building service system and cost of produced energy for each energy producing system. By use of information on construction cost and developed models of the yearly energy use...
Design and analysis of stochastic DSS query optimizers in a distributed database system

Directory of Open Access Journals (Sweden)

Manik Sharma

2016-07-01

Full Text Available Query optimization is a stimulating task of any database system. A number of heuristics have been applied in recent times, which proposed new algorithms for substantially improving the performance of a query. The hunt for a better solution still continues. The imperishable developments in the field of Decision Support System (DSS databases are presenting data at an exceptional rate. The massive volume of DSS data is consequential only when it is able to access and analyze by distinctive researchers. Here, an innovative stochastic framework of DSS query optimizer is proposed to further optimize the design of existing query optimization genetic approaches. The results of Entropy Based Restricted Stochastic Query Optimizer (ERSQO are compared with the results of Exhaustive Enumeration Query Optimizer (EAQO, Simple Genetic Query Optimizer (SGQO, Novel Genetic Query Optimizer (NGQO and Restricted Stochastic Query Optimizer (RSQO. In terms of Total Costs, EAQO outperforms SGQO, NGQO, RSQO and ERSQO. However, stochastic approaches dominate in terms of runtime. The Total Costs produced by ERSQO is better than SGQO, NGQO and RGQO by 12%, 8% and 5% respectively. Moreover, the effect of replicating data on the Total Costs of DSS query is also examined. In addition, the statistical analysis revealed a 2-tailed significant correlation between the number of join operations and the Total Costs of distributed DSS query. Finally, in regard to the consistency of stochastic query optimizers, the results of SGQO, NGQO, RSQO and ERSQO are 96.2%, 97.2%, 97.45 and 97.8% consistent respectively.
Deterministic Design Optimization of Structures in OpenMDAO Framework

Science.gov (United States)

Coroneos, Rula M.; Pai, Shantaram S.

2012-01-01

Nonlinear programming algorithms play an important role in structural design optimization. Several such algorithms have been implemented in OpenMDAO framework developed at NASA Glenn Research Center (GRC). OpenMDAO is an open source engineering analysis framework, written in Python, for analyzing and solving Multi-Disciplinary Analysis and Optimization (MDAO) problems. It provides a number of solvers and optimizers, referred to as components and drivers, which users can leverage to build new tools and processes quickly and efficiently. Users may download, use, modify, and distribute the OpenMDAO software at no cost. This paper summarizes the process involved in analyzing and optimizing structural components by utilizing the framework s structural solvers and several gradient based optimizers along with a multi-objective genetic algorithm. For comparison purposes, the same structural components were analyzed and optimized using CometBoards, a NASA GRC developed code. The reliability and efficiency of the OpenMDAO framework was compared and reported in this report.

Reliability-oriented Design of a Cost-effective Active Capacitor

DEFF Research Database (Denmark)

Wang, Haoran; Wang, Huai

2017-01-01

This paper presents the reliability-oriented design of a two-terminal active capacitor proposed recently. The two-terminal active capacitor has the same level of convenience as a passive capacitor with reduced requirement of overall energy storage. In order to fully explore the potential...... of the proposed concept, a comprehensive design procedure is necessary to optimally sizing the key components of the active capacitor in terms of cost and reliability. Moreover, the inherent condition monitoring capability of the active capacitor is discussed by utilizing the existing feedback signals. A 500 W...
Determination of optimal LWR containment design, excluding accidents more severe than Class 8

International Nuclear Information System (INIS)

Cave, L.; Min, T.K.

1980-04-01

Information is presented concerning the restrictive effect of existing NRC requirements; definition of possible targets for containment; possible containment systems for LWR; optimization of containment design for class 3 through class 8 accidents (PWR); estimated costs of some possible containment arrangements for PWR relative to the standard dry containment system; estimated costs of BWR containment
Design and implementation of a cost-effective microscope for fabrication and imaging

International Nuclear Information System (INIS)

Trout, G; Basu, S

2009-01-01

The use of lasers and optical systems for advanced research and demonstrative purposes has traditionally been cost-prohibitive for many researchers. In this note, we present the design and optimization of a low-cost microscopy setup capable of imaging, fabrication or photopolymerization via multiphoton excitation of a photoactivator and the study of processes such as diffusion using fluorescence recovery after photobleaching (FRAP). The setup features a continuous wave (CW) Ar-ion laser, a pulsed Nd 3+ :YAG laser, an inverted microscope with a CCD camera and appropriate optics. The setup is cost-effective and puts a once-expensive setup within reach of more researchers interested in micron- and sub-micron-scale processes. (technical design note)
The REVAMP trial to evaluate HIV resistance testing in sub-Saharan Africa: a case study in clinical trial design in resource limited settings to optimize effectiveness and cost effectiveness estimates.

Science.gov (United States)

Siedner, Mark J; Bwana, Mwebesa B; Moosa, Mahomed-Yunus S; Paul, Michelle; Pillay, Selvan; McCluskey, Suzanne; Aturinda, Isaac; Ard, Kevin; Muyindike, Winnie; Moodley, Pravikrishnen; Brijkumar, Jaysingh; Rautenberg, Tamlyn; George, Gavin; Johnson, Brent; Gandhi, Rajesh T; Sunpath, Henry; Marconi, Vincent C

2017-07-01

In sub-Saharan Africa, rates of sustained HIV virologic suppression remain below international goals. HIV resistance testing, while common in resource-rich settings, has not gained traction due to concerns about cost and sustainability. We designed a randomized clinical trial to determine the feasibility, effectiveness, and cost-effectiveness of routine HIV resistance testing in sub-Saharan Africa. We describe challenges common to intervention studies in resource-limited settings, and strategies used to address them, including: (1) optimizing generalizability and cost-effectiveness estimates to promote transition from study results to policy; (2) minimizing bias due to patient attrition; and (3) addressing ethical issues related to enrollment of pregnant women. The study randomizes people in Uganda and South Africa with virologic failure on first-line therapy to standard of care virologic monitoring or immediate resistance testing. To strengthen external validity, study procedures are conducted within publicly supported laboratory and clinical facilities using local staff. To optimize cost estimates, we collect primary data on quality of life and medical resource utilization. To minimize losses from observation, we collect locally relevant contact information, including Whatsapp account details, for field-based tracking of missing participants. Finally, pregnant women are followed with an adapted protocol which includes an increased visit frequency to minimize risk to them and their fetuses. REVAMP is a pragammatic randomized clinical trial designed to test the effectiveness and cost-effectiveness of HIV resistance testing versus standard of care in sub-Saharan Africa. We anticipate the results will directly inform HIV policy in sub-Saharan Africa to optimize care for HIV-infected patients.
Optimally Stopped Optimization

Science.gov (United States)

Vinci, Walter; Lidar, Daniel

We combine the fields of heuristic optimization and optimal stopping. We propose a strategy for benchmarking randomized optimization algorithms that minimizes the expected total cost for obtaining a good solution with an optimal number of calls to the solver. To do so, rather than letting the objective function alone define a cost to be minimized, we introduce a further cost-per-call of the algorithm. We show that this problem can be formulated using optimal stopping theory. The expected cost is a flexible figure of merit for benchmarking probabilistic solvers that can be computed when the optimal solution is not known, and that avoids the biases and arbitrariness that affect other measures. The optimal stopping formulation of benchmarking directly leads to a real-time, optimal-utilization strategy for probabilistic optimizers with practical impact. We apply our formulation to benchmark the performance of a D-Wave 2X quantum annealer and the HFS solver, a specialized classical heuristic algorithm designed for low tree-width graphs. On a set of frustrated-loop instances with planted solutions defined on up to N = 1098 variables, the D-Wave device is between one to two orders of magnitude faster than the HFS solver.
Exploring Optimization Opportunities in Four-Point Suspension Wind Turbine Drivetrains through Integrated Design Approaches

Energy Technology Data Exchange (ETDEWEB)

Sethuraman, Latha [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Guo, Yi [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dykes, Katherine L [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2018-01-12

Drivetrain design has significant influence on the costs of wind power generation. Current industry practices usually approach the drivetrain design with loads and system requirements defined by the turbine manufacturer. Several different manufacturers are contracted to supply individual components from the low-speed shaft to the generator - each receiving separate design specifications from the turbine manufacturer. Increasingly, more integrated approaches to turbine design have shown promise for blades and towers. Yet, integrated drivetrain design is a challenging task owing to the complex physical behavior of the important load-bearing components, namely the main bearings, gearbox, and the generator. In this paper we combine two of NREL's systems engineering design tools, DriveSE and GeneratorSE, to enable a comprehensive system-level drivetrain optimization for the IEAWind reference turbine for land-based applications. We compare a more traditional design with integrated approaches employing decoupled and coupled design optimization. It is demonstrated that both approaches have the potential to realize notable mass savings with opportunities to lower the costs of energy.
Conceptual optimal design of jackets

DEFF Research Database (Denmark)

Sandal, Kasper; Verbart, Alexander; Stolpe, Mathias

Structural optimization can explore a large design space (400 jackets) in a short time (2 hours), and thus lead to better conceptual jacket designs.......Structural optimization can explore a large design space (400 jackets) in a short time (2 hours), and thus lead to better conceptual jacket designs....
Low cost balancing unit design

Science.gov (United States)

Golembiovsky, Matej; Dedek, Jan; Slanina, Zdenek

2017-06-01

This article deals with the design of a low-cost balancing system which consist of battery balancing units, accumulator pack units and coordinator unit with interface for higher level of battery management system. This solution allows decentralized mode of operation and the aim of this work is implementation of controlling and diagnostic mechanism into an electric scooter project realized at Technical university of Ostrava. In todays world which now fully enjoys the prime of electromobility, off-grid battery systems and other, it is important to seek the optimal balance between functionality and the economy side of BMS that being electronics which deals with secondary cells of batery packs. There were numerous sophisticated, but not too practical BMS models in the past, such as centralized system or standalone balance modules of individual cells. This article aims at development of standalone balance modules which are able to communicate with the coordinator, adjust their parameters and ensure their cells safety in case of a communication failure. With the current worldwide cutting cost trend in mind, the emphasis was put on the lowest price possible for individual component. The article is divided into two major categories, the first one being desing of power electronics with emphasis on quality, safety (cooling) and also cost. The second part describes development of a communication interface with reliability and cost in mind. The article contains numerous graphs from practical measurements. The outcome of the work and its possible future is defined in the conclusion.
System Approach of Logistic Costs Optimization Solution in Supply Chain

OpenAIRE

Majerčák, Peter; Masárová, Gabriela; Buc, Daniel; Majerčáková, Eva

2013-01-01

This paper is focused on the possibility of using the costs simulation in supply chain, which are on relative high level. Our goal is to determine the costs using logistic costs optimization which must necessarily be used in business activities in the supply chain management. The paper emphasizes the need to perform not isolated optimization in the whole supply chain. Our goal is to compare classic approach, when every part tracks its costs isolated, a try to minimize them, with the system (l...
Passive designs and renewable energy systems optimization of a net zero energy building in Embrun/France

Science.gov (United States)

Harkouss, F.; Biwole, P. H.; Fardoun, F.

2018-05-01

Buildings’ optimization is a smart method to inspect the available design choices starting from passive strategies, to energy efficient systems and finally towards the adequate renewable energy system to be implemented. This paper outlines the methodology and the cost-effectiveness potential for optimizing the design of net-zero energy building in a French city; Embrun. The non-dominated sorting genetic algorithm is chosen in order to minimize thermal, electrical demands and life cycle cost while reaching the net zero energy balance; and thus getting the Pareto-front. Elimination and Choice Expressing the Reality decision making method is applied to the Pareto-front so as to obtain one optimal solution. A wide range of energy efficiency measures are investigated, besides solar energy systems are employed to produce required electricity and hot water for domestic purposes. The results indicate that the appropriate selection of the passive parameters is very important and critical in reducing the building energy consumption. The optimum design parameters yield to a decrease of building’s thermal loads and life cycle cost by 32.96% and 14.47% respectively.
Optimal covariate designs theory and applications

CERN Document Server

Das, Premadhis; Mandal, Nripes Kumar; Sinha, Bikas Kumar

2015-01-01

This book primarily addresses the optimality aspects of covariate designs. A covariate model is a combination of ANOVA and regression models. Optimal estimation of the parameters of the model using a suitable choice of designs is of great importance; as such choices allow experimenters to extract maximum information for the unknown model parameters. The main emphasis of this monograph is to start with an assumed covariate model in combination with some standard ANOVA set-ups such as CRD, RBD, BIBD, GDD, BTIBD, BPEBD, cross-over, multi-factor, split-plot and strip-plot designs, treatment control designs, etc. and discuss the nature and availability of optimal covariate designs. In some situations, optimal estimations of both ANOVA and the regression parameters are provided. Global optimality and D-optimality criteria are mainly used in selecting the design. The standard optimality results of both discrete and continuous set-ups have been adapted, and several novel combinatorial techniques have been applied for...
Optimal design and operation of solid oxide fuel cell systems for small-scale stationary applications

Science.gov (United States)

Braun, Robert Joseph

The advent of maturing fuel cell technologies presents an opportunity to achieve significant improvements in energy conversion efficiencies at many scales; thereby, simultaneously extending our finite resources and reducing "harmful" energy-related emissions to levels well below that of near-future regulatory standards. However, before realization of the advantages of fuel cells can take place, systems-level design issues regarding their application must be addressed. Using modeling and simulation, the present work offers optimal system design and operation strategies for stationary solid oxide fuel cell systems applied to single-family detached dwellings. A one-dimensional, steady-state finite-difference model of a solid oxide fuel cell (SOFC) is generated and verified against other mathematical SOFC models in the literature. Fuel cell system balance-of-plant components and costs are also modeled and used to provide an estimate of system capital and life cycle costs. The models are used to evaluate optimal cell-stack power output, the impact of cell operating and design parameters, fuel type, thermal energy recovery, system process design, and operating strategy on overall system energetic and economic performance. Optimal cell design voltage, fuel utilization, and operating temperature parameters are found using minimization of the life cycle costs. System design evaluations reveal that hydrogen-fueled SOFC systems demonstrate lower system efficiencies than methane-fueled systems. The use of recycled cell exhaust gases in process design in the stack periphery are found to produce the highest system electric and cogeneration efficiencies while achieving the lowest capital costs. Annual simulations reveal that efficiencies of 45% electric (LHV basis), 85% cogenerative, and simple economic paybacks of 5--8 years are feasible for 1--2 kW SOFC systems in residential-scale applications. Design guidelines that offer additional suggestions related to fuel cell
Designing cost effective water demand management programs in Australia.

Science.gov (United States)

White, S B; Fane, S A

2002-01-01

This paper describes recent experience with integrated resource planning (IRP) and the application of least cost planning (LCP) for the evaluation of demand management strategies in urban water. Two Australian case studies, Sydney and Northern New South Wales (NSW) are used in illustration. LCP can determine the most cost effective means of providing water services or alternatively the cheapest forms of water conservation. LCP contrasts to a traditional approach of evaluation which looks only at means of increasing supply. Detailed investigation of water usage, known as end-use analysis, is required for LCP. End-use analysis allows both rigorous demand forecasting, and the development and evaluation of conservation strategies. Strategies include education campaigns, increasing water use efficiency and promoting wastewater reuse or rainwater tanks. The optimal mix of conservation strategies and conventional capacity expansion is identified based on levelised unit cost. IRP uses LCP in the iterative process, evaluating and assessing options, investing in selected options, measuring the results, and then re-evaluating options. Key to this process is the design of cost effective demand management programs. IRP however includes a range of parameters beyond least economic cost in the planning process and program designs, including uncertainty, benefit partitioning and implementation considerations.
Cost-effectiveness analysis of optimal strategy for tumor treatment

International Nuclear Information System (INIS)

Pang, Liuyong; Zhao, Zhong; Song, Xinyu

2016-01-01

We propose and analyze an antitumor model with combined immunotherapy and chemotherapy. Firstly, we explore the treatment effects of single immunotherapy and single chemotherapy, respectively. Results indicate that neither immunotherapy nor chemotherapy alone are adequate to cure a tumor. Hence, we apply optimal theory to investigate how the combination of immunotherapy and chemotherapy should be implemented, for a certain time period, in order to reduce the number of tumor cells, while minimizing the implementation cost of the treatment strategy. Secondly, we establish the existence of the optimality system and use Pontryagin’s Maximum Principle to characterize the optimal levels of the two treatment measures. Furthermore, we calculate the incremental cost-effectiveness ratios to analyze the cost-effectiveness of all possible combinations of the two treatment measures. Finally, numerical results show that the combination of immunotherapy and chemotherapy is the most cost-effective strategy for tumor treatment, and able to eliminate the entire tumor with size 4.470 × 10"8 in a year.
Limitations on the application of optimization methods in the design of radiation protection in large installations

International Nuclear Information System (INIS)

Hock, R.; Brauns, J.; Steinicke, P.

1986-01-01

In a society where prices of goods are not regulated, optimization is best achieved by competition and not by the decisions of an authority. In order to improve its competitive position, a company may attach increasing importance to cost-benefit analyses both internally and in its discussions with customers. Some limitations and problems of this methodology are analysed in the paper. It is concluded that an increase in design effort (analysis of more options) beyond a planned level, in order to reduce radiation exposure, can only be justified in rational terms if exposure limits are involved. An increase in design effort could also be justified if solutions with lower equipment and operating costs but higher radiation exposure were acceptable. Because of the high competitive value of radiation protection, however, it is difficult to gain acceptance for such optimization. The cost of the investigation itself requires optimal procedures for the optimization process and therefore limitation of the number of options to be analysed. This is demonstrated for the example of a shielding wall. Another problem is the probabilistic nature of many of the parameters involved. In most cases this probability distribution is only inaccurately known. Deterministic 'design basis assumptions' therefore have to be made. The choice of these assumptions may greatly influence the result of the optimization, as demonstrated in an example taken from practice. (author)
Review of Reliability-Based Design Optimization Approach and Its Integration with Bayesian Method

Science.gov (United States)

Zhang, Xiangnan

2018-03-01

A lot of uncertain factors lie in practical engineering, such as external load environment, material property, geometrical shape, initial condition, boundary condition, etc. Reliability method measures the structural safety condition and determine the optimal design parameter combination based on the probabilistic theory. Reliability-based design optimization (RBDO) is the most commonly used approach to minimize the structural cost or other performance under uncertainty variables which combines the reliability theory and optimization. However, it cannot handle the various incomplete information. The Bayesian approach is utilized to incorporate this kind of incomplete information in its uncertainty quantification. In this paper, the RBDO approach and its integration with Bayesian method are introduced.
Exergy based methods for economic and risk design optimization of energy systems: Application to a gas turbine

International Nuclear Information System (INIS)

Cassetti, G.; Rocco, M.V.; Colombo, E.

2014-01-01

Exergy based analyses are considered by the scientific community appropriate tools for the design and the performance evaluation and improvements of energy systems. Moreover, they are today recognized as proper instruments to assess economic, environmental and social externalities of energy systems. This paper presents the results of a study in which different exergy analysis methods are adopted to determine the optimal design configuration of a gas turbine operating in simple Joule Brayton cycle. Standard exergy and Thermoeconomic analyses are performed to identify the highest thermodynamic efficiency and minimum economic cost configurations of the system, while for the environmental analysis Authors propose an innovative method in which the exergy analysis is combined with a Risk Analysis. With this method the total risk associated to the system is used as objective function in the same way as monetary cost is for standard Thermoeconomic analysis. These three methods aims therefore to determine the optimal design configurations of the system with respect to their specific objective functions, respectively: exergy cost (J/J), monetary (exergoeconomic) cost (€/J) and risk (injured/J) of the product. Results lead to three different optimal design parameters for the system, according to the objective of each analysis procedure. - Highlights: • An original implementation of Thermoeconomic framework is proposed. • Standard Exergy and Thermoeconomic analysis are performed on a case study. • A new model using exergy as allocation criteria for Risk Analysis is performed. • Different optimal configurations are obtained and compared
An improved version of Inverse Distance Weighting metamodel assisted Harmony Search algorithm for truss design optimization

Directory of Open Access Journals (Sweden)

Y. Gholipour

Full Text Available This paper focuses on a metamodel-based design optimization algorithm. The intention is to improve its computational cost and convergence rate. Metamodel-based optimization method introduced here, provides the necessary means to reduce the computational cost and convergence rate of the optimization through a surrogate. This algorithm is a combination of a high quality approximation technique called Inverse Distance Weighting and a meta-heuristic algorithm called Harmony Search. The outcome is then polished by a semi-tabu search algorithm. This algorithm adopts a filtering system and determines solution vectors where exact simulation should be applied. The performance of the algorithm is evaluated by standard truss design problems and there has been a significant decrease in the computational effort and improvement of convergence rate.
Optimal design of uptime-guarantee contracts under IGFR valuations and convex costs

OpenAIRE

Hezarkhni, Behzad

2016-01-01

An uptime-guarantee contract commits a service provider to maintain the functionality of a customer’s equipment at least for certain fraction of working time during a contracted period. This paper addresses the optimal design of uptime-guarantee contracts for the service provider when the customer’s valuation of a contract with a given guaranteed uptime level has an Increasing Generalized Failure Rate (IGFR) distribution. We first consider the case where the service provider proposes only one...
Global optimization methods for engineering design

Science.gov (United States)

Arora, Jasbir S.

1990-01-01

The problem is to find a global minimum for the Problem P. Necessary and sufficient conditions are available for local optimality. However, global solution can be assured only under the assumption of convexity of the problem. If the constraint set S is compact and the cost function is continuous on it, existence of a global minimum is guaranteed. However, in view of the fact that no global optimality conditions are available, a global solution can be found only by an exhaustive search to satisfy Inequality. The exhaustive search can be organized in such a way that the entire design space need not be searched for the solution. This way the computational burden is reduced somewhat. It is concluded that zooming algorithm for global optimizations appears to be a good alternative to stochastic methods. More testing is needed; a general, robust, and efficient local minimizer is required. IDESIGN was used in all numerical calculations which is based on a sequential quadratic programming algorithm, and since feasible set keeps on shrinking, a good algorithm to find an initial feasible point is required. Such algorithms need to be developed and evaluated.

Global optimization for integrated design and control of computationally expensive process models

NARCIS (Netherlands)

Egea, J.A.; Vries, D.; Alonso, A.A.; Banga, J.R.

2007-01-01

The problem of integrated design and control optimization of process plants is discussed in this paper. We consider it as a nonlinear programming problem subject to differential-algebraic constraints. This class of problems is frequently multimodal and "costly" (i.e., computationally expensive to
District Heating Network Design and Configuration Optimization with Genetic Algorithm

DEFF Research Database (Denmark)

Li, Hongwei; Svendsen, Svend

2013-01-01

In this paper, the configuration of a district heating network which connects from the heating plant to the end users is optimized. Each end user in the network represents a building block. The connections between the heat generation plant and the end users are represented with mixed integer...... and the pipe friction and heat loss formulations are non-linear. In order to find the optimal district heating network configuration, genetic algorithm which handles the mixed integer nonlinear programming problem is chosen. The network configuration is represented with binary and integer encoding...... and it is optimized in terms of the net present cost. The optimization results indicates that the optimal DH network configuration is determined by multiple factors such as the consumer heating load, the distance between the heating plant to the consumer, the design criteria regarding the pressure and temperature...
Design optimization applied in structural dynamics

NARCIS (Netherlands)

Akcay-Perdahcioglu, Didem; de Boer, Andries; van der Hoogt, Peter; Tiskarna, T

2007-01-01

This paper introduces the design optimization strategies, especially for structures which have dynamic constraints. Design optimization involves first the modeling and then the optimization of the problem. Utilizing the Finite Element (FE) model of a structure directly in an optimization process
Cost optimization for buildings with hybrid ventilation systems

Science.gov (United States)

Ji, Kun; Lu, Yan

2018-02-13

A method including: computing a total cost for a first zone in a building, wherein the total cost is equal to an actual energy cost of the first zone plus a thermal discomfort cost of the first zone; and heuristically optimizing the total cost to identify temperature setpoints for a mechanical heating/cooling system and a start time and an end time of the mechanical heating/cooling system, based on external weather data and occupancy data of the first zone.
Pareto optimal design of sectored toroidal superconducting magnet for SMES

Science.gov (United States)

Bhunia, Uttam; Saha, Subimal; Chakrabarti, Alok

2014-10-01

A novel multi-objective optimization design approach for sectored toroidal superconducting magnetic energy storage coil has been developed considering the practical engineering constraints. The objectives include the minimization of necessary superconductor length and torus overall size or volume, which determines a significant part of cost towards realization of SMES. The best trade-off between the necessary conductor length for winding and magnet overall size is achieved in the Pareto-optimal solutions, the compact magnet size leads to increase in required superconducting cable length or vice versa The final choice among Pareto optimal configurations can be done in relation to other issues such as AC loss during transient operation, stray magnetic field at outside the coil assembly, and available discharge period, which is not considered in the optimization process. The proposed design approach is adapted for a 4.5 MJ/1 MW SMES system using low temperature niobium-titanium based Rutherford type cable. Furthermore, the validity of the representative Pareto solutions is confirmed by finite-element analysis (FEA) with a reasonably acceptable accuracy.
Optimal Joint Liability Lending and with Costly Peer Monitoring

NARCIS (Netherlands)

Carli, Francesco; Uras, R.B.

2014-01-01

This paper characterizes an optimal group loan contract with costly peer monitoring. Using a fairly standard moral hazard framework, we show that the optimal group lending contract could exhibit a joint-liability scheme. However, optimality of joint-liability requires the involvement of a group
Multi-Objective Design Of Optimal Greenhouse Gas Observation Networks

Science.gov (United States)

Lucas, D. D.; Bergmann, D. J.; Cameron-Smith, P. J.; Gard, E.; Guilderson, T. P.; Rotman, D.; Stolaroff, J. K.

2010-12-01

One of the primary scientific functions of a Greenhouse Gas Information System (GHGIS) is to infer GHG source emission rates and their uncertainties by combining measurements from an observational network with atmospheric transport modeling. Certain features of the observational networks that serve as inputs to a GHGIS --for example, sampling location and frequency-- can greatly impact the accuracy of the retrieved GHG emissions. Observation System Simulation Experiments (OSSEs) provide a framework to characterize emission uncertainties associated with a given network configuration. By minimizing these uncertainties, OSSEs can be used to determine optimal sampling strategies. Designing a real-world GHGIS observing network, however, will involve multiple, conflicting objectives; there will be trade-offs between sampling density, coverage and measurement costs. To address these issues, we have added multi-objective optimization capabilities to OSSEs. We demonstrate these capabilities by quantifying the trade-offs between retrieval error and measurement costs for a prototype GHGIS, and deriving GHG observing networks that are Pareto optimal. [LLNL-ABS-452333: This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
Probabilistic framework for product design optimization and risk management

Science.gov (United States)

Keski-Rahkonen, J. K.

2018-05-01

Probabilistic methods have gradually gained ground within engineering practices but currently it is still the industry standard to use deterministic safety margin approaches to dimensioning components and qualitative methods to manage product risks. These methods are suitable for baseline design work but quantitative risk management and product reliability optimization require more advanced predictive approaches. Ample research has been published on how to predict failure probabilities for mechanical components and furthermore to optimize reliability through life cycle cost analysis. This paper reviews the literature for existing methods and tries to harness their best features and simplify the process to be applicable in practical engineering work. Recommended process applies Monte Carlo method on top of load-resistance models to estimate failure probabilities. Furthermore, it adds on existing literature by introducing a practical framework to use probabilistic models in quantitative risk management and product life cycle costs optimization. The main focus is on mechanical failure modes due to the well-developed methods used to predict these types of failures. However, the same framework can be applied on any type of failure mode as long as predictive models can be developed.
Cost and performance optimization of natural draft dry cooling towers using genetic algorithm. Paper no. IGEC-1-002

International Nuclear Information System (INIS)

Shokuhmand, H.; Ghaempanah, B.

2005-01-01

In this paper the cost - performance optimization of natural draft dry cooling towers with specific kind of heat exchangers, known as Forgo T60 has been investigated. These cooling towers are used in combined and steam cycle power plants. The optimization has been done using genetic algorithm. The objective function has two parts, which are minimizing the cost and maximizing the performance. In the first part the geometrical and operating parameters are defined and for the next part the performance of the designed tower for different ambient temperatures during a year is calculated considering the characteristic curve of the turbine. The applied genetic algorithm has been tuned up using the data of some working power cycles. The results show it is possible to find an optimum for all design parameters; however it is very dependent on how exact the cost analysis is. (author)
Optimal Design and Related Areas in Optimization and Statistics

CERN Document Server

Pronzato, Luc

2009-01-01

This edited volume, dedicated to Henry P. Wynn, reflects his broad range of research interests, focusing in particular on the applications of optimal design theory in optimization and statistics. It covers algorithms for constructing optimal experimental designs, general gradient-type algorithms for convex optimization, majorization and stochastic ordering, algebraic statistics, Bayesian networks and nonlinear regression. Written by leading specialists in the field, each chapter contains a survey of the existing literature along with substantial new material. This work will appeal to both the
Some considerations on cost-benefit analysis in the optimization of radiation protection

International Nuclear Information System (INIS)

Doi, Masahiro; Nakashima, Yoshiyuki.

1988-01-01

To carry out Cost-Benefit Analysis in the optimization of radiation protection, first, we have to overcome the paradoxical problem in ethics, that is, how to convert radiological detriments into monetary value. Radiological detriments are composed of not only the objective health detriment (alpha-detriment) but also subjective non-health ones due to psychological stresses against radiological risks (beta-detriments). Nevertheless we can't neglect the problem of Cost-Benefit Analysis because of the fact that protectional costs are apt to be reduced as other fundamental production costs from the managemental point of view. The authors have proposed following two different situations concerning the treatment of radiological detriments in the decision-making processes for the optimization of radiation protection. That is. (1) Since protectional decision making processes for workers are parts of the total safety planning of the facility of interest, beta-detriments for workers should be discussed and determined in the labour-management negotiations. (2) In case of publics, subjective non-health detriments arise from the gap between radiation risks and radiation risk perception that can be clarified by social research techniques. In addition, this study has clarified criteria in planning of social researches for beta-detriments and constructed a theoretical model designed for these. (author)
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.
Co-optimized design of microchannel heat exchangers and thermoelectric generators

DEFF Research Database (Denmark)

Kolaei, Alireza Rezania; Yazawa, K.; Rosendahl, Lasse

2013-01-01

Designs of heat exchangers have mostly been disconnected to the performance of thermoelectric generator (TEG) systems. The development work, mostly focused on thermoelectric materials, required a significant amount of engineering parametric analysis. In this work, a micro plate-fin heat exchanger...... applied to a TEG is investigated and optimized to maximize the output power and the cost performance of generic TEG systems. The cost per performance is counted by a measure of price per power output ($/W). The channel width, channel height, fin thickness of heat exchanger, and fill factor of TEG...... are theoretically optimized for a wide range of pumping power. In conjunction with effective numeric tests, the model discusses the optimum size of the system components’ dimensions at two area sizes of the substrate plate of heat exchanger. Results show that at every pumping power, there are particular values...
Pareto optimal design of sectored toroidal superconducting magnet for SMES

Energy Technology Data Exchange (ETDEWEB)

Bhunia, Uttam, E-mail: ubhunia@vecc.gov.in; Saha, Subimal; Chakrabarti, Alok

2014-10-15

Highlights: • The optimization approach minimizes both the magnet size and necessary cable length of a sectored toroidal SMES unit. • Design approach is suitable for low temperature superconducting cable suitable for medium size SMES unit. • It investigates coil parameters with respect to practical engineering aspects. - Abstract: A novel multi-objective optimization design approach for sectored toroidal superconducting magnetic energy storage coil has been developed considering the practical engineering constraints. The objectives include the minimization of necessary superconductor length and torus overall size or volume, which determines a significant part of cost towards realization of SMES. The best trade-off between the necessary conductor length for winding and magnet overall size is achieved in the Pareto-optimal solutions, the compact magnet size leads to increase in required superconducting cable length or vice versa The final choice among Pareto optimal configurations can be done in relation to other issues such as AC loss during transient operation, stray magnetic field at outside the coil assembly, and available discharge period, which is not considered in the optimization process. The proposed design approach is adapted for a 4.5 MJ/1 MW SMES system using low temperature niobium–titanium based Rutherford type cable. Furthermore, the validity of the representative Pareto solutions is confirmed by finite-element analysis (FEA) with a reasonably acceptable accuracy.
Pareto optimal design of sectored toroidal superconducting magnet for SMES

International Nuclear Information System (INIS)

Bhunia, Uttam; Saha, Subimal; Chakrabarti, Alok

2014-01-01

Highlights: • The optimization approach minimizes both the magnet size and necessary cable length of a sectored toroidal SMES unit. • Design approach is suitable for low temperature superconducting cable suitable for medium size SMES unit. • It investigates coil parameters with respect to practical engineering aspects. - Abstract: A novel multi-objective optimization design approach for sectored toroidal superconducting magnetic energy storage coil has been developed considering the practical engineering constraints. The objectives include the minimization of necessary superconductor length and torus overall size or volume, which determines a significant part of cost towards realization of SMES. The best trade-off between the necessary conductor length for winding and magnet overall size is achieved in the Pareto-optimal solutions, the compact magnet size leads to increase in required superconducting cable length or vice versa The final choice among Pareto optimal configurations can be done in relation to other issues such as AC loss during transient operation, stray magnetic field at outside the coil assembly, and available discharge period, which is not considered in the optimization process. The proposed design approach is adapted for a 4.5 MJ/1 MW SMES system using low temperature niobium–titanium based Rutherford type cable. Furthermore, the validity of the representative Pareto solutions is confirmed by finite-element analysis (FEA) with a reasonably acceptable accuracy
Cost-Effectiveness Comparison of Coupler Designs of Wireless Power Transfer for Electric Vehicle Dynamic Charging

Directory of Open Access Journals (Sweden)

Weitong Chen

2016-11-01

Full Text Available This paper presents a cost-effectiveness comparison of coupler designs for wireless power transfer (WPT, meant for electric vehicle (EV dynamic charging. The design comparison of three common types of couplers is first based on the raw material cost, output power, transfer efficiency, tolerance of horizontal offset, and flux density. Then, the optimal cost-effectiveness combination is selected for EV dynamic charging. The corresponding performances of the proposed charging system are compared and analyzed by both simulation and experimentation. The results verify the validity of the proposed dynamic charging system for EVs.
Uncertainties in Early Stage Capital Cost Estimation of Process Design – A case study on biorefinery design

Directory of Open Access Journals (Sweden)

Gurkan eSin

2015-02-01

Full Text Available Capital investment, next to the product demand, sales and production costs, is one of the key metrics commonly used for project evaluation and feasibility assessment. Estimating the investment costs of a new product/process alternative during early stage design is a challenging task. This is especially important in biorefinery research, where available information and experiences with new technologies is limited. A systematic methodology for uncertainty analysis of cost data is proposed that employs (a Bootstrapping as a regression method when cost data is available and (b the Monte Carlo technique as an error propagation method based on expert input when cost data is not available. Four well-known models for early stage cost estimation are reviewed an analyzed using the methodology. The significance of uncertainties of cost data for early stage process design is highlighted using the synthesis and design of a biorefinery as a case study. The impact of uncertainties in cost estimation on the identification of optimal processing paths is found to be profound. To tackle this challenge, a comprehensive techno-economic risk analysis framework is presented to enable robust decision making under uncertainties. One of the results using an order-of-magnitude estimate shows that the production of diethyl ether and 1,3-butadiene are the most promising with economic risks of 0.24 MM$/a and 4.6 MM$/a due to uncertainties in cost estimations, respectively.
Reduced cost mission design using surrogate models

Science.gov (United States)

Feldhacker, Juliana D.; Jones, Brandon A.; Doostan, Alireza; Hampton, Jerrad

2016-01-01

This paper uses surrogate models to reduce the computational cost associated with spacecraft mission design in three-body dynamical systems. Sampling-based least squares regression is used to project the system response onto a set of orthogonal bases, providing a representation of the ΔV required for rendezvous as a reduced-order surrogate model. Models are presented for mid-field rendezvous of spacecraft in orbits in the Earth-Moon circular restricted three-body problem, including a halo orbit about the Earth-Moon L2 libration point (EML-2) and a distant retrograde orbit (DRO) about the Moon. In each case, the initial position of the spacecraft, the time of flight, and the separation between the chaser and the target vehicles are all considered as design inputs. The results show that sample sizes on the order of 102 are sufficient to produce accurate surrogates, with RMS errors reaching 0.2 m/s for the halo orbit and falling below 0.01 m/s for the DRO. A single function call to the resulting surrogate is up to two orders of magnitude faster than computing the same solution using full fidelity propagators. The expansion coefficients solved for in the surrogates are then used to conduct a global sensitivity analysis of the ΔV on each of the input parameters, which identifies the separation between the spacecraft as the primary contributor to the ΔV cost. Finally, the models are demonstrated to be useful for cheap evaluation of the cost function in constrained optimization problems seeking to minimize the ΔV required for rendezvous. These surrogate models show significant advantages for mission design in three-body systems, in terms of both computational cost and capabilities, over traditional Monte Carlo methods.
POBE: A Computer Program for Optimal Design of Multi-Subject Blocked fMRI Experiments

Directory of Open Access Journals (Sweden)

Bärbel Maus

2014-01-01

Full Text Available For functional magnetic resonance imaging (fMRI studies, researchers can use multi-subject blocked designs to identify active brain regions for a certain stimulus type of interest. Before performing such an experiment, careful planning is necessary to obtain efficient stimulus effect estimators within the available financial resources. The optimal number of subjects and the optimal scanning time for a multi-subject blocked design with fixed experimental costs can be determined using optimal design methods. In this paper, the user-friendly computer program POBE 1.2 (program for optimal design of blocked experiments, version 1.2 is presented. POBE provides a graphical user interface for fMRI researchers to easily and efficiently design their experiments. The computer program POBE calculates the optimal number of subjects and the optimal scanning time for user specified experimental factors and model parameters so that the statistical efficiency is maximised for a given study budget. POBE can also be used to determine the minimum budget for a given power. Furthermore, a maximin design can be determined as efficient design for a possible range of values for the unknown model parameters. In this paper, the computer program is described and illustrated with typical experimental factors for a blocked fMRI experiment.

Design and optimization of tidal turbine airfoil

Energy Technology Data Exchange (ETDEWEB)

Grasso, F. [ECN Wind Energy, Petten (Netherlands)

2011-07-15

In order to increase the ratio of energy capture to the loading and thereby to reduce cost of energy, the use of specially tailored airfoils is needed. This work is focused on the design of an airfoil for marine application. Firstly, the requirements for this class of airfoils are illustrated and discussed with reference to the requirements for wind turbine airfoils. Then, the design approach is presented. This is a numerical optimization scheme in which a gradient based algorithm is used, coupled with RFOIL solver and a composite Bezier geometrical parameterization. A particularly sensitive point is the choice and implementation of constraints; in order to formalize in the most complete and effective way the design requirements, the effects of activating specific constraints are discussed. Particularly importance is given to the cavitation phenomenon. Finally, a numerical example regarding the design of a high efficiency, tidal turbine airfoil is illustrated and the results are compared with existing turbine airfoils.
Cost optimization model and its heuristic genetic algorithms

International Nuclear Information System (INIS)

Liu Wei; Wang Yongqing; Guo Jilin

1999-01-01

Interest and escalation are large quantity in proportion to the cost of nuclear power plant construction. In order to optimize the cost, the mathematics model of cost optimization for nuclear power plant construction was proposed, which takes the maximum net present value as the optimization goal. The model is based on the activity networks of the project and is an NP problem. A heuristic genetic algorithms (HGAs) for the model was introduced. In the algorithms, a solution is represented with a string of numbers each of which denotes the priority of each activity for assigned resources. The HGAs with this encoding method can overcome the difficulty which is harder to get feasible solutions when using the traditional GAs to solve the model. The critical path of the activity networks is figured out with the concept of predecessor matrix. An example was computed with the HGAP programmed in C language. The results indicate that the model is suitable for the objectiveness, the algorithms is effective to solve the model
Techno–economic design of hybrid electric vehicles and possibilities of the multi-objective optimization structure

International Nuclear Information System (INIS)

Dimitrova, Zlatina; Maréchal, François

2016-01-01

Highlights: • The full hybrid electric vehicle suits for sustainable urban mobility and customer investment. • The full hybrid electric urban vehicle is efficient, with consumption less than 2 L/100 km. • The range extender vehicle is a technology for low CO_2 emissions – less than 20 g/km CO_2_. • The total CO_2 emissions for range extender and plug-in vehicles are sensitive to the use place. - Abstract: The design criteria for modern sustainable development of vehicle powertrain are the high energy efficiency of the conversion system, the competitive cost and the lowest possible environmental impacts. In this article a multi-objective optimization methodology is applied on hybrid electric vehicles study in order to define the optimal powertrain configurations of the vehicle, estimate the cost of the powertrain equipment and show the environmental impact of the technical choices on the lifecycle perspective of the vehicle. The study illustrates optimal design solutions for low fuel consumption vehicles – between 2 L/100 km and 3 L/100 km. For that a simulation model of a hybrid electric vehicle is made. This model is coupled with a cost model for the vehicle. The techno–economic optimizations are performed for two case studies, illustrating the possibilities of the optimization superstructure. Firstly the life cycle inventory is written as a function of the parameters of the techno–economic model. In this way, the obtained environmental indicators from the life cycle assessment are calculated as a function of the decision variables for the vehicle design. In the second example the parameters of the energy distribution function are included as decision variables in the techno–economic optimization and are simultaneously optimized.
A mathematical model for optimization of an integrated network logistic design

Directory of Open Access Journals (Sweden)

Lida Tafaghodi

2011-10-01

Full Text Available In this study, the integrated forward/reverse logistics network is investigated, and a capacitated multi-stage, multi-product logistics network design is proposed by formulating a generalized logistics network problem into a mixed-integer nonlinear programming model (MINLP for minimizing the total cost of the closed-loop supply chain network. Moreover, the proposed model is solved by using optimization solver, which provides the decisions related to the facility location problem, optimum quantity of shipped product, and facility capacity. Numerical results show the power of the proposed MINLP model to avoid th sub-optimality caused by separate design of forward and reverse logistics networks and to handle various transportation modes and periodic demand.
Exploring Optimization Opportunities in Four-Point Suspension Wind Turbine Drivetrains Through Integrated Design Approaches: Preprint

Energy Technology Data Exchange (ETDEWEB)

Sethuraman, Latha [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Guo, Yi [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dykes, Katherine L [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2018-02-13

Drivetrain design has significant influence on the costs of wind power generation. Current industry practices usually approach the drivetrain design with loads and system requirements defined by the turbine manufacturer. Several different manufacturers are contracted to supply individual components from the low-speed shaft to the generator - each receiving separate design specifications from the turbine manufacturer. Increasingly, more integrated approaches to turbine design have shown promise for blades and towers. Yet, integrated drivetrain design is a challenging task owing to the complex physical behavior of the important load-bearing components, namely the main bearings, gearbox, and the generator. In this paper we combine two of NREL's systems engineering design tools, DriveSE and GeneratorSE, to enable a comprehensive system-level drivetrain optimization for the IEAWind reference turbine for land-based applications. We compare a more traditional design with integrated approaches employing decoupled and coupled design optimization. It is demonstrated that both approaches have the potential to realize notable mass savings with opportunities to lower the costs of energy.
A surrogate based multistage-multilevel optimization procedure for multidisciplinary design optimization

OpenAIRE

Yao, W.; Chen, X.; Ouyang, Q.; Van Tooren, M.

2011-01-01

Optimization procedure is one of the key techniques to address the computational and organizational complexities of multidisciplinary design optimization (MDO). Motivated by the idea of synthetically exploiting the advantage of multiple existing optimization procedures and meanwhile complying with the general process of satellite system design optimization in conceptual design phase, a multistage-multilevel MDO procedure is proposed in this paper by integrating multiple-discipline-feasible (M...
Optimization of 3D Field Design

Science.gov (United States)

Logan, Nikolas; Zhu, Caoxiang

2017-10-01

Recent progress in 3D tokamak modeling is now leveraged to create a conceptual design of new external 3D field coils for the DIII-D tokamak. Using the IPEC dominant mode as a target spectrum, the Finding Optimized Coils Using Space-curves (FOCUS) code optimizes the currents and 3D geometry of multiple coils to maximize the total set's resonant coupling. The optimized coils are individually distorted in space, creating toroidal ``arrays'' containing a variety of shapes that often wrap around a significant poloidal extent of the machine. The generalized perturbed equilibrium code (GPEC) is used to determine optimally efficient spectra for driving total, core, and edge neoclassical toroidal viscosity (NTV) torque and these too provide targets for the optimization of 3D coil designs. These conceptual designs represent a fundamentally new approach to 3D coil design for tokamaks targeting desired plasma physics phenomena. Optimized coil sets based on plasma response theory will be relevant to designs for future reactors or on any active machine. External coils, in particular, must be optimized for reliable and efficient fusion reactor designs. Work supported by the US Department of Energy under DE-AC02-09CH11466.
Optimal Market Design

NARCIS (Netherlands)

Boone, J.; Goeree, J.K.

2010-01-01

This paper introduces three methodological advances to study the optimal design of static and dynamic markets. First, we apply a mechanism design approach to characterize all incentive-compatible market equilibria. Second, we conduct a normative analysis, i.e. we evaluate alternative competition and
Modeling and Design of Capacitive Micromachined Ultrasonic Transducers Based-on Database Optimization

International Nuclear Information System (INIS)

Chang, M W; Gwo, T J; Deng, T M; Chang, H C

2006-01-01

A Capacitive Micromachined Ultrasonic Transducers simulation database, based on electromechanical coupling theory, has been fully developed for versatile capacitive microtransducer design and analysis. Both arithmetic and graphic configurations are used to find optimal parameters based on serial coupling simulations. The key modeling parameters identified can improve microtransducer's character and reliability effectively. This method could be used to reduce design time and fabrication cost, eliminating trial-and-error procedures. Various microtransducers, with optimized characteristics, can be developed economically using the developed database. A simulation to design an ultrasonic microtransducer is completed as an executed example. The dependent relationship between membrane geometry, vibration displacement and output response is demonstrated. The electromechanical coupling effects, mechanical impedance and frequency response are also taken into consideration for optimal microstructures. The microdevice parameters with the best output signal response are predicted, and microfabrication processing constraints and realities are also taken into consideration
Uncertainties in Early-Stage Capital Cost Estimation of Process Design – A Case Study on Biorefinery Design

International Nuclear Information System (INIS)

Cheali, Peam; Gernaey, Krist V.; Sin, Gürkan

2015-01-01

Capital investment, next to the product demand, sales, and production costs, is one of the key metrics commonly used for project evaluation and feasibility assessment. Estimating the investment costs of a new product/process alternative during early-stage design is a challenging task, which is especially relevant in biorefinery research where information about new technologies and experience with new technologies is limited. A systematic methodology for uncertainty analysis of cost data is proposed that employs: (a) bootstrapping as a regression method when cost data are available; and, (b) the Monte Carlo technique as an error propagation method based on expert input when cost data are not available. Four well-known models for early-stage cost estimation are reviewed and analyzed using the methodology. The significance of uncertainties of cost data for early-stage process design is highlighted using the synthesis and design of a biorefinery as a case study. The impact of uncertainties in cost estimation on the identification of optimal processing paths is indeed found to be profound. To tackle this challenge, a comprehensive techno-economic risk analysis framework is presented to enable robust decision-making under uncertainties. One of the results using order-of-magnitude estimates shows that the production of diethyl ether and 1,3-butadiene are the most promising with the lowest economic risks (among the alternatives considered) of 0.24 MM$/a and 4.6 MM$/a, respectively.
Uncertainties in Early-Stage Capital Cost Estimation of Process Design – A Case Study on Biorefinery Design

Energy Technology Data Exchange (ETDEWEB)

Cheali, Peam; Gernaey, Krist V.; Sin, Gürkan, E-mail: gsi@kt.dtu.dk [Department of Chemical and Biochemical Engineering, Technical University of Denmark, Lyngby (Denmark)

2015-02-06

Capital investment, next to the product demand, sales, and production costs, is one of the key metrics commonly used for project evaluation and feasibility assessment. Estimating the investment costs of a new product/process alternative during early-stage design is a challenging task, which is especially relevant in biorefinery research where information about new technologies and experience with new technologies is limited. A systematic methodology for uncertainty analysis of cost data is proposed that employs: (a) bootstrapping as a regression method when cost data are available; and, (b) the Monte Carlo technique as an error propagation method based on expert input when cost data are not available. Four well-known models for early-stage cost estimation are reviewed and analyzed using the methodology. The significance of uncertainties of cost data for early-stage process design is highlighted using the synthesis and design of a biorefinery as a case study. The impact of uncertainties in cost estimation on the identification of optimal processing paths is indeed found to be profound. To tackle this challenge, a comprehensive techno-economic risk analysis framework is presented to enable robust decision-making under uncertainties. One of the results using order-of-magnitude estimates shows that the production of diethyl ether and 1,3-butadiene are the most promising with the lowest economic risks (among the alternatives considered) of 0.24 MM$/a and 4.6 MM$/a, respectively.
ATHENA optimized coating design

DEFF Research Database (Denmark)

Ferreira, Desiree Della Monica; Christensen, Finn Erland; Jakobsen, Anders Clemen

2012-01-01

The optimization of coating design for the ATHENA mission si described and the possibility of increasing the telescope effective area in the range between 0.1 and 10 keV is investigated. An independent computation of the on-axis effective area based on the mirror design of ATHENA is performed...... in order to review the current coating baseline. The performance of several material combinations, considering a simple bi-layer, simple multilayer and linear graded multilayer coatings are tested and simulation of the mirror performance considering both the optimized coating design and the coating...
Charging cost optimization for EV buses using neural network based energy predictor

NARCIS (Netherlands)

Nageshrao, S.P.; Jacob, J.; Wilkins, S.

2017-01-01

For conventional buses, based on the decades of their operational knowledge, public transport companies are able to optimize their cost of operation. However, with recent trend in the usage of electric buses, cost optimal operation can become challenging. In this paper an offline optimal charging
Optimal allocation of thermodynamic irreversibility for the integrated design of propulsion and thermal management systems

Science.gov (United States)

Maser, Adam Charles

work losses over the time history of the mission. The characterization of the thermodynamic irreversibility distribution helps give the propulsion systems designer an absolute and consistent view of the tradeoffs associated with the design of the entire integrated system. Consequently, this leads directly to the question of the proper allocation of irreversibility across each of the components. The process of searching for the most favorable allocation of this irreversibility is the central theme of the research and must take into account production cost and vehicle mission performance. The production cost element is accomplished by including an engine component weight and cost prediction capability within the system model. The vehicle mission performance is obtained by directly linking the propulsion and thermal management model to a vehicle performance model and flying it through a mission profile. A canonical propulsion and thermal management systems architecture is then presented to experimentally test each element of the methodology separately: first the integrated modeling and simulation, then the irreversibility, cost, and mission performance considerations, and then finally the proper technique to perform the optimal allocation. A goal of this research is the description of the optimal allocation of system irreversibility to enable an engine cycle design with improved performance and cost at the vehicle-level. To do this, a numerical optimization was first used to minimize system-level production and operating costs by fixing the performance requirements and identifying the best settings for all of the design variables. There are two major drawbacks to this approach: It does not allow the designer to directly trade off the performance requirements and it does not allow the individual component losses to directly factor into the optimization. An irreversibility allocation approach based on the economic concept of resource allocation is then compared to the
Research on Multidisciplinary Optimization Design of Bridge Crane

Directory of Open Access Journals (Sweden)

Tong Yifei

2013-01-01

Full Text Available Bridge crane is one of the most widely used cranes in our country, which is indispensable equipment for material conveying in the modern production. In this paper, the framework of multidisciplinary optimization for bridge crane is proposed. The presented research on crane multidisciplinary design technology for energy saving includes three levels, respectively: metal structures level, transmission design level, and electrical system design level. The shape optimal mathematical model of the crane is established for shape optimization design of metal structure level as well as size optimal mathematical model and topology optimal mathematical model of crane for topology optimization design of metal structure level is established. Finally, system-level multidisciplinary energy-saving optimization design of bridge crane is further carried out with energy-saving transmission design results feedback to energy-saving optimization design of metal structure. The optimization results show that structural optimization design can reduce total mass of crane greatly by using the finite element analysis and multidisciplinary optimization technology premised on the design requirements of cranes such as stiffness and strength; thus, energy-saving design can be achieved.
Development of an Nearly Zero Emission Building (nZEB Life Cycle Cost Assessment Tool for Fast Decision Making in the Early Design Phase

Directory of Open Access Journals (Sweden)

Hae Jin Kang

2017-01-01

Full Text Available An economic feasibility optimization method for the life cycle cost (LCC has been developed to apply energy saving techniques in the early design stages of a building. The method was developed using default data (e.g., operation schedules, energy consumption prediction equations and cost prediction equations utilizing design variables considered in the early design phase. With certain equations developed, an LCC model was constructed using the computational program MATLAB, to create an automated optimization process. To verify the results from the newly developed assessment tool, a case study on an office building was performed to outline the results of the designer’s proposed model and the cost optimal model.
A Systematic Optimization Design Method for Complex Mechatronic Products Design and Development

Directory of Open Access Journals (Sweden)

Jie Jiang

2018-01-01

Full Text Available Designing a complex mechatronic product involves multiple design variables, objectives, constraints, and evaluation criteria as well as their nonlinearly coupled relationships. The design space can be very big consisting of many functional design parameters, structural design parameters, and behavioral design (or running performances parameters. Given a big design space and inexplicit relations among them, how to design a product optimally in an optimization design process is a challenging research problem. In this paper, we propose a systematic optimization design method based on design space reduction and surrogate modelling techniques. This method firstly identifies key design parameters from a very big design space to reduce the design space, secondly uses the identified key design parameters to establish a system surrogate model based on data-driven modelling principles for optimization design, and thirdly utilizes the multiobjective optimization techniques to achieve an optimal design of a product in the reduced design space. This method has been tested with a high-speed train design. With comparison to others, the research results show that this method is practical and useful for optimally designing complex mechatronic products.
Cost-optimal power system extension under flow-based market coupling

Energy Technology Data Exchange (ETDEWEB)

Hagspiel, Simeon; Jaegemann, Cosima; Lindenberger, Dietmar [Koeln Univ. (Germany). Energiewirtschaftliches Inst.; Brown, Tom; Cherevatskiy, Stanislav; Troester, Eckehard [Energynautics GmbH, Langen (Germany)

2013-05-15

Electricity market models, implemented as dynamic programming problems, have been applied widely to identify possible pathways towards a cost-optimal and low carbon electricity system. However, the joint optimization of generation and transmission remains challenging, mainly due to the fact that different characteristics and rules apply to commercial and physical exchanges of electricity in meshed networks. This paper presents a methodology that allows to optimize power generation and transmission infrastructures jointly through an iterative approach based on power transfer distribution factors (PTDFs). As PTDFs are linear representations of the physical load flow equations, they can be implemented in a linear programming environment suitable for large scale problems. The algorithm iteratively updates PTDFs when grid infrastructures are modified due to cost-optimal extension and thus yields an optimal solution with a consistent representation of physical load flows. The method is first demonstrated on a simplified three-node model where it is found to be robust and convergent. It is then applied to the European power system in order to find its cost-optimal development under the prescription of strongly decreasing CO{sub 2} emissions until 2050.
A study of the use of linear programming techniques to improve the performance in design optimization problems

Science.gov (United States)

Young, Katherine C.; Sobieszczanski-Sobieski, Jaroslaw

1988-01-01

This project has two objectives. The first is to determine whether linear programming techniques can improve performance when handling design optimization problems with a large number of design variables and constraints relative to the feasible directions algorithm. The second purpose is to determine whether using the Kreisselmeier-Steinhauser (KS) function to replace the constraints with one constraint will reduce the cost of total optimization. Comparisons are made using solutions obtained with linear and non-linear methods. The results indicate that there is no cost saving using the linear method or in using the KS function to replace constraints.
Reduced design load basis for ultimate blade loads estimation in multidisciplinary design optimization frameworks

DEFF Research Database (Denmark)

Pavese, Christian; Tibaldi, Carlo; Larsen, Torben J.

2016-01-01

The aim is to provide a fast and reliable approach to estimate ultimate blade loads for a multidisciplinary design optimization (MDO) framework. For blade design purposes, the standards require a large amount of computationally expensive simulations, which cannot be efficiently run each cost...... function evaluation of an MDO process. This work describes a method that allows integrating the calculation of the blade load envelopes inside an MDO loop. Ultimate blade load envelopes are calculated for a baseline design and a design obtained after an iteration of an MDO. These envelopes are computed...... for a full standard design load basis (DLB) and a deterministic reduced DLB. Ultimate loads extracted from the two DLBs with the two blade designs each are compared and analyzed. Although the reduced DLB supplies ultimate loads of different magnitude, the shape of the estimated envelopes are similar...

Optimal household refrigerator replacement policy for life cycle energy, greenhouse gas emissions, and cost

International Nuclear Information System (INIS)

Kim, Hyung Chul; Keoleian, Gregory A.; Horie, Yuhta A.

2006-01-01

Although the last decade witnessed dramatic progress in refrigerator efficiencies, inefficient, outdated refrigerators are still in operation, sometimes consuming more than twice as much electricity per year compared with modern, efficient models. Replacing old refrigerators before their designed lifetime could be a useful policy to conserve electric energy and greenhouse gas emissions. However, from a life cycle perspective, product replacement decisions also induce additional economic and environmental burdens associated with disposal of old models and production of new models. This paper discusses optimal lifetimes of mid-sized refrigerator models in the US, using a life cycle optimization model based on dynamic programming. Model runs were conducted to find optimal lifetimes that minimize energy, global warming potential (GWP), and cost objectives over a time horizon between 1985 and 2020. The baseline results show that depending on model years, optimal lifetimes range 2-7 years for the energy objective, and 2-11 years for the GWP objective. On the other hand, an 18-year of lifetime minimizes the economic cost incurred during the time horizon. Model runs with a time horizon between 2004 and 2020 show that current owners should replace refrigerators that consume more than 1000 kWh/year of electricity (typical mid-sized 1994 models and older) as an efficient strategy from both cost and energy perspectives
Robust Optimization for Time-Cost Tradeoff Problem in Construction Projects

Directory of Open Access Journals (Sweden)

Ming Li

2014-01-01

Full Text Available Construction projects are generally subject to uncertainty, which influences the realization of time-cost tradeoff in project management. This paper addresses a time-cost tradeoff problem under uncertainty, in which activities in projects can be executed in different construction modes corresponding to specified time and cost with interval uncertainty. Based on multiobjective robust optimization method, a robust optimization model for time-cost tradeoff problem is developed. In order to illustrate the robust model, nondominated sorting genetic algorithm-II (NSGA-II is modified to solve the project example. The results show that, by means of adjusting the time and cost robust coefficients, the robust Pareto sets for time-cost tradeoff can be obtained according to different acceptable risk level, from which the decision maker could choose the preferred construction alternative.
Optimized universal color palette design for error diffusion

Science.gov (United States)

Kolpatzik, Bernd W.; Bouman, Charles A.

1995-04-01

Currently, many low-cost computers can only simultaneously display a palette of 256 color. However, this palette is usually selectable from a very large gamut of available colors. For many applications, this limited palette size imposes a significant constraint on the achievable image quality. We propose a method for designing an optimized universal color palette for use with halftoning methods such as error diffusion. The advantage of a universal color palette is that it is fixed and therefore allows multiple images to be displayed simultaneously. To design the palette, we employ a new vector quantization method known as sequential scalar quantization (SSQ) to allocate the colors in a visually uniform color space. The SSQ method achieves near-optimal allocation, but may be efficiently implemented using a series of lookup tables. When used with error diffusion, SSQ adds little computational overhead and may be used to minimize the visual error in an opponent color coordinate system. We compare the performance of the optimized algorithm to standard error diffusion by evaluating a visually weighted mean-squared-error measure. Our metric is based on the color difference in CIE L*AL*B*, but also accounts for the lowpass characteristic of human contrast sensitivity.
Space Based Radar-System Architecture Design and Optimization for a Space Based Replacement to AWACS

National Research Council Canada - National Science Library

Wickert, Douglas

1997-01-01

Through a process of system architecture design, system cost modeling, and system architecture optimization, we assess the feasibility of performing the next generation Airborne Warning and Control System (AWACS...
Methodological framework for economical and controllable design of heat exchanger networks: Steady-state analysis, dynamic simulation, and optimization

International Nuclear Information System (INIS)

Masoud, Ibrahim T.; Abdel-Jabbar, Nabil; Qasim, Muhammad; Chebbi, Rachid

2016-01-01

Highlights: • HEN total annualized cost, heat recovery, and controllability are considered in the framework. • Steady-state and dynamic simulations are performed. • Effect of bypass on total annualized cost and controllability is reported. • Optimum bypass fractions are found from closed and open-loop efforts. - Abstract: The problem of interaction between economic design and control system design of heat exchanger networks (HENs) is addressed in this work. The controllability issues are incorporated in the classical design of HENs. A new methodological framework is proposed to account for both economics and controllability of HENs. Two classical design methods are employed, namely, Pinch and superstructure designs. Controllability measures such as relative gain array (RGA) and singular value decomposition (SVD) are used. The proposed framework also presents a bypass placement strategy for optimal control of the designed network. A case study is used to test the applicability of the framework and to assess both economics and controllability. The results indicate that the superstructure design is more economical and controllable compared to the Pinch design. The controllability of the designed HEN is evaluated using Aspen-HYSYS closed-loop dynamic simulator. In addition, a sensitivity analysis is performed to study the effect of bypass fractions on the total annualized cost and controllability of the designed HEN. The analysis shows that increasing any bypass fraction increases the total annualized cost. However, the trend with the total annualized cost was not observed with respect to the control effort manifested by minimizing the integral of the squared errors (ISE) between the controlled stream temperatures and their targets (set-points). An optimal ISE point is found at a certain bypass fraction, which does not correspond to the minimal total annualized cost. The bypass fractions are validated via open-loop simulation and the additional cooling and
HTGR high temperature process heat design and cost status report

International Nuclear Information System (INIS)

1981-12-01

This report describes the status of the studies conducted on the 850 0 C ROT indirect cycle and the 950 0 C ROT direct cycle through the end of Fiscal Year 1981. Volume I provides summaries of the design and optimization studies and the resulting capital and product costs, for the HTGR/thermochemical pipeline concept. Additionally, preliminary evaluations are presented for coupling of candidate process applications to the HTGR system
Experimental design and multicriteria decision making methods for the optimization of ice cream composition

Directory of Open Access Journals (Sweden)

Cristian Rojas

2012-03-01

Full Text Available The aim of the present work was to optimize the sensorial and technological features of ice cream. The experimental work was performed in two stages: 1 optimization of lactose enzymatic hydrolysis, and 2 optimization of the process and product. For the first stage a complete factorial design was developed, optimized using both response surface and the steepest ascent method. In the second stage a mixture design was performed, combining the process variables. The product with the best sensorial acceptance, high yield and low cost was selected. The acceptance of the product was developed by an untrained taster’s panel. As a main result the sensorial and technological features of the final product were improved, establishing the optimum parameters for its elaboration.
Optimal design of marine steam turbine

International Nuclear Information System (INIS)

Liu Chengyang; Yan Changqi; Wang Jianjun

2012-01-01

The marine steam turbine is one of the key equipment in marine power plant, and it tends to using high power steam turbine, which makes the steam turbine to be heavier and larger, it causes difficulties to the design and arrangement of the steam turbine, and the marine maneuverability is seriously influenced. Therefore, it is necessary to apply optimization techniques to the design of the steam turbine in order to achieve the minimum weight or volume by means of finding the optimum combination of design parameters. The math model of the marine steam turbine design calculation was established. The sensitivities of condenser pressure, power ratio of HP turbine with LP turbine, and the ratio of diameter with height at the end stage of LP turbine, which influence the weight of the marine steam turbine, were analyzed. The optimal design of the marine steam turbine, aiming at the weight minimization while satisfying the structure and performance constraints, was carried out with the hybrid particle swarm optimization algorithm. The results show that, steam turbine weight is reduced by 3.13% with the optimization scheme. Finally, the optimization results were analyzed, and the steam turbine optimization design direction was indicated. (authors)
Nutritionally Optimized, Culturally Acceptable, Cost-Minimized Diets for Low Income Ghanaian Families Using Linear Programming.

Science.gov (United States)

Nykänen, Esa-Pekka A; Dunning, Hanna E; Aryeetey, Richmond N O; Robertson, Aileen; Parlesak, Alexandr

2018-04-07

The Ghanaian population suffers from a double burden of malnutrition. Cost of food is considered a barrier to achieving a health-promoting diet. Food prices were collected in major cities and in rural areas in southern Ghana. Linear programming (LP) was used to calculate nutritionally optimized diets (food baskets (FBs)) for a low-income Ghanaian family of four that fulfilled energy and nutrient recommendations in both rural and urban settings. Calculations included implementing cultural acceptability for families living in extreme and moderate poverty (food budget under USD 1.9 and 3.1 per day respectively). Energy-appropriate FBs minimized for cost, following Food Balance Sheets (FBS), lacked key micronutrients such as iodine, vitamin B12 and iron for the mothers. Nutritionally adequate FBs were achieved in all settings when optimizing for a diet cheaper than USD 3.1. However, when delimiting cost to USD 1.9 in rural areas, wild foods had to be included in order to meet nutritional adequacy. Optimization suggested to reduce roots, tubers and fruits and to increase cereals, vegetables and oil-bearing crops compared with FBS. LP is a useful tool to design culturally acceptable diets at minimum cost for low-income Ghanaian families to help advise national authorities how to overcome the double burden of malnutrition.
Optimization of prosthetic foot stiffness to reduce metabolic cost and intact knee loading during below-knee amputee walking: a theoretical study.

Science.gov (United States)

Fey, Nicholas P; Klute, Glenn K; Neptune, Richard R

2012-11-01

Unilateral below-knee amputees develop abnormal gait characteristics that include bilateral asymmetries and an elevated metabolic cost relative to non-amputees. In addition, long-term prosthesis use has been linked to an increased prevalence of joint pain and osteoarthritis in the intact leg knee. To improve amputee mobility, prosthetic feet that utilize elastic energy storage and return (ESAR) have been designed, which perform important biomechanical functions such as providing body support and forward propulsion. However, the prescription of appropriate design characteristics (e.g., stiffness) is not well-defined since its influence on foot function and important in vivo biomechanical quantities such as metabolic cost and joint loading remain unclear. The design of feet that improve these quantities could provide considerable advancements in amputee care. Therefore, the purpose of this study was to couple design optimization with dynamic simulations of amputee walking to identify the optimal foot stiffness that minimizes metabolic cost and intact knee joint loading. A musculoskeletal model and distributed stiffness ESAR prosthetic foot model were developed to generate muscle-actuated forward dynamics simulations of amputee walking. Dynamic optimization was used to solve for the optimal muscle excitation patterns and foot stiffness profile that produced simulations that tracked experimental amputee walking data while minimizing metabolic cost and intact leg internal knee contact forces. Muscle and foot function were evaluated by calculating their contributions to the important walking subtasks of body support, forward propulsion and leg swing. The analyses showed that altering a nominal prosthetic foot stiffness distribution by stiffening the toe and mid-foot while making the ankle and heel less stiff improved ESAR foot performance by offloading the intact knee during early to mid-stance of the intact leg and reducing metabolic cost. The optimal design also
Design Optimization Toolkit: Users' Manual

Energy Technology Data Exchange (ETDEWEB)

Aguilo Valentin, Miguel Alejandro [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Computational Solid Mechanics and Structural Dynamics

2014-07-01

The Design Optimization Toolkit (DOTk) is a stand-alone C++ software package intended to solve complex design optimization problems. DOTk software package provides a range of solution methods that are suited for gradient/nongradient-based optimization, large scale constrained optimization, and topology optimization. DOTk was design to have a flexible user interface to allow easy access to DOTk solution methods from external engineering software packages. This inherent flexibility makes DOTk barely intrusive to other engineering software packages. As part of this inherent flexibility, DOTk software package provides an easy-to-use MATLAB interface that enables users to call DOTk solution methods directly from the MATLAB command window.
Establishing a cost model when estimating product cost in early design phases

OpenAIRE

Jeppsson, Johanna; Sjöberg, Jessica

2017-01-01

About 75% of the total product cost is determined in the early design phase, which means that the possibilities to affect costs are relatively small when the design phase is completed. For companies, it is therefore vital to conduct reliable cost estimates in the early design phase, when selecting between different design choices. When conducting a cost estimate there are many uncertainties. The aim with this study is therefore to explore how uncertainties regarding product cost can be consid...
Design Optimization of Internal Flow Devices

DEFF Research Database (Denmark)

Madsen, Jens Ingemann

The power of computational fluid dynamics is boosted through the use of automated design optimization methodologies. The thesis considers both derivative-based search optimization and the use of response surface methodologies.......The power of computational fluid dynamics is boosted through the use of automated design optimization methodologies. The thesis considers both derivative-based search optimization and the use of response surface methodologies....
A cost-efficient method to optimize package size in emerging markets

NARCIS (Netherlands)

Gamez-Alban, H.M.; Soto-Cardona, O.C.; Mejia Argueta, C.; Sarmiento, A.T.

2015-01-01

Packaging links the entire supply chain and coordinates all participants in the process to give a flexible and effective response to customer needs in order to maximize satisfaction at optimal cost. This research proposes an optimization model to define the minimum total cost combination of outer
Tårs 10000 m2 CSP + Flat Plate Solar Collector Plant - Cost-Performance Optimization of the Design

DEFF Research Database (Denmark)

Perers, Bengt; Furbo, Simon; Tian, Zhiyong

2016-01-01

, was established. The optimization showed that there was a synergy in combining CSP and FP collectors. Even though the present cost per m² of the CSP collectors is high, the total energy cost is minimized by installing a combination of collectors in such solar heating plant. It was also found that the CSP......A novel solar heating plant with Concentrating Solar Power (CSP) collectors and Flat Plate (FP) collectors has been put into operation in Tårs since July 2015. To investigate economic performance of the plant, a TRNSYS-Genopt model, including a solar collector field and thermal storage tank...
Model-Based Predictive Control Scheme for Cost Optimization and Balancing Services for Supermarket Refrigeration Systems

DEFF Research Database (Denmark)

Weerts, Hermanus H. M.; Shafiei, Seyed Ehsan; Stoustrup, Jakob

2014-01-01

A new formulation of model predictive control for supermarket refrigeration systems is proposed to facilitate the regulatory power services as well as energy cost optimization of such systems in the smart grid. Nonlinear dynamics existed in large-scale refrigeration plants challenges the predictive...... control design. It is however shown that taking into account the knowledge of different time scales in the dynamical subsystems makes possible a linear formulation of a centralized predictive controller. A realistic scenario of regulatory power services in the smart grid is considered and formulated...... in the same objective as of cost optimization one. A simulation benchmark validated against real data and including significant dynamics of the system are employed to show the effectiveness of the proposed control scheme....
Optimal design of an in-situ bioremediation system using support vector machine and particle swarm optimization

Science.gov (United States)

ch, Sudheer; Kumar, Deepak; Prasad, Ram Kailash; Mathur, Shashi

2013-08-01

A methodology based on support vector machine and particle swarm optimization techniques (SVM-PSO) was used in this study to determine an optimal pumping rate and well location to achieve an optimal cost of an in-situ bioremediation system. In the first stage of the two stage methodology suggested for optimal in-situ bioremediation design, the optimal number of wells and their locations was determined from preselected candidate well locations. The pumping rate and well location in the first stage were subsequently optimized in the second stage of the methodology. The highly nonlinear system of equations governing in-situ bioremediation comprises the equations of flow and solute transport coupled with relevant biodegradation kinetics. A finite difference model was developed to simulate the process of in-situ bioremediation using an Alternate-Direction Implicit technique. This developed model (BIOFDM) yields the spatial and temporal distribution of contaminant concentration for predefined initial and boundary conditions. BIOFDM was later validated by comparing the simulated results with those obtained using BIOPLUME III for the case study of Shieh and Peralta (2005). The results were found to be in close agreement. Moreover, since the solution of the highly nonlinear equation otherwise requires significant computational effort, the computational burden in this study was managed within a practical time frame by replacing the BIOFDM model with a trained SVM model. Support Vector Machine which generates fast solutions in real time was considered to be a universal function approximator in the study. Apart from reducing the computational burden, this technique generates a set of near optimal solutions (instead of a single optimal solution) and creates a re-usable data base that could be used to address many other management problems. Besides this, the search for an optimal pumping pattern was directed by a simple PSO technique and a penalty parameter approach was adopted
Optimal design of an in-situ bioremediation system using support vector machine and particle swarm optimization.

Science.gov (United States)

ch, Sudheer; Kumar, Deepak; Prasad, Ram Kailash; Mathur, Shashi

2013-08-01

A methodology based on support vector machine and particle swarm optimization techniques (SVM-PSO) was used in this study to determine an optimal pumping rate and well location to achieve an optimal cost of an in-situ bioremediation system. In the first stage of the two stage methodology suggested for optimal in-situ bioremediation design, the optimal number of wells and their locations was determined from preselected candidate well locations. The pumping rate and well location in the first stage were subsequently optimized in the second stage of the methodology. The highly nonlinear system of equations governing in-situ bioremediation comprises the equations of flow and solute transport coupled with relevant biodegradation kinetics. A finite difference model was developed to simulate the process of in-situ bioremediation using an Alternate-Direction Implicit technique. This developed model (BIOFDM) yields the spatial and temporal distribution of contaminant concentration for predefined initial and boundary conditions. BIOFDM was later validated by comparing the simulated results with those obtained using BIOPLUME III for the case study of Shieh and Peralta (2005). The results were found to be in close agreement. Moreover, since the solution of the highly nonlinear equation otherwise requires significant computational effort, the computational burden in this study was managed within a practical time frame by replacing the BIOFDM model with a trained SVM model. Support Vector Machine which generates fast solutions in real time was considered to be a universal function approximator in the study. Apart from reducing the computational burden, this technique generates a set of near optimal solutions (instead of a single optimal solution) and creates a re-usable data base that could be used to address many other management problems. Besides this, the search for an optimal pumping pattern was directed by a simple PSO technique and a penalty parameter approach was adopted
Optimal distributed energy resources and the cost of reduced greenhouse gas emissions in a large retail shopping centre

International Nuclear Information System (INIS)

Braslavsky, Julio H.; Wall, Josh R.; Reedman, Luke J.

2015-01-01

Highlights: • Optimal options for distributed energy resources are analysed for a shopping centre. • A multiobjective optimisation model is formulated and solved using DER-CAM. • Cost and emission trade-offs are compared in four key optimal investment scenarios. • Moderate investment in DER technologies lowers emissions by 29.6% and costs by 8.5%. • Larger investment in DER technologies lowers emissions by 72% at 47% higher costs. - Abstract: This paper presents a case study on optimal options for distributed energy resource (DER) technologies to reduce greenhouse gas emissions in a large retail shopping centre located in Sydney, Australia. Large retail shopping centres take the largest share of energy consumed by all commercial buildings, and present a strong case for adoption of DER technologies to reduce energy costs and emissions. However, the complexity of optimally designing and operating DER systems has hindered their widespread adoption in practice. This paper examines and demonstrates the value of DER in reducing the carbon footprint of the shopping centre by formulating and solving a multiobjective optimisation problem using the Distributed Energy Resources Customer Adoption Model (DER-CAM) tool. An economic model of the shopping centre is developed in DER-CAM using on-site-specific demand, tariffs, and performance data for each DER technology option available. Four key optimal DER technology investment scenarios are then analysed by comparing: (1) solution trade-offs of costs and emissions, (2) the cost of reduced emissions attained in each investment scenario, and (3) investment benefits with respect to the business-as-usual scenario. The analysis shows that a moderate investment in combined cooling, heat and power (CCHP) technology alone can reduce annual energy costs by 8.5% and carbon dioxide-equivalent emissions by 29.6%. A larger investment in CCHP technology, in conjunction with on-site solar photovoltaic (PV) generation, can deliver
OPTIMIZATION OF I-SECTION PROFILE DESIGN BY THE FINITE ELEMENT METHOD

Directory of Open Access Journals (Sweden)

Patryk Różyło

2016-03-01

Full Text Available This paper discusses the problem of design optimization for an I-section profile. The optimization process was performed using the Abaqus program. The numerical analysis of a strictly static problem was based on the finite element method. The scope of the analysis involved both determination of stresses and displacements in the profile and structure topology optimization. The main focus of the numerical analysis was put on reducing profile volume while maintaining the same load and similar stresses prior to and after optimization. The solution of the optimization problem is just an example of the potential of using this method in combination with the finite element method in the Abaqus environment. Nowadays numerical analysis is the most effective cost-reducing alternative to experimental tests and it enables structure examination by means of a computer.

Machine learning paradigms in design optimization: Applications in turbine aerodynamic design

Science.gov (United States)

Goel, Sanjay

Mechanisms of incorporating machine learning paradigms in design optimization have been investigated in the current research. The primary focus of the work is on machine learning algorithms which use computational models that are analogous to the hypothesized principles of natural or biological learning. Examples from structural and aerodynamic optimization have been used to demonstrate the potential of the proposed schemes. The first strategy examined in the current work seeks to improve the convergence of optimization problems by pruning the search space of weak variables. Such variables are identified by learning from a database of existing designs using neural networks. By using clustering techniques, different sets of weak variables are identified in different regions of the design space. Parameter sensitivity information obtained in the process of identifying weak variables provides accurate heuristics for formulating design rules. The impact of this methodology on obtaining converged designs has been investigated for a turbine design problem. Optimization results from a three-stage power turbine and an aircraft engine turbine are presented in this thesis. The second scheme is an evolutionary design optimization technique which gets progressively 'smarter' during the optimization process by learning from computed domain knowledge. This technique employs adaptive learning mechanisms (classifiers) which recognize the influence of the design variables on the problem solution and then generalize them to dynamically create or change design rules during optimization. This technique, when applied to a constrained optimization problem, shows progressive improvement in convergence of search, as successive generations of rules evolve by learning from the environment. To investigate this methodology, a truss optimization problem is solved with an objective of minimizing the truss weight subject to stress constraints in the truss members. A distinct convergent trend is
Design and optimization of tidal turbine airfoil

Energy Technology Data Exchange (ETDEWEB)

Grasso, F. [ECN Wind Energy, Petten (Netherlands)

2012-03-15

To increase the ratio of energy capture to the loading and, thereby, to reduce cost of energy, the use of specially tailored airfoils is needed. This work is focused on the design of an airfoil for marine application. Firstly, the requirements for this class of airfoils are illustrated and discussed with reference to the requirements for wind turbine airfoils. Then, the design approach is presented. This is a numerical optimization scheme in which a gradient-based algorithm is used, coupled with the RFOIL solver and a composite Bezier geometrical parameterization. A particularly sensitive point is the choice and implementation of constraints .A section of the present work is dedicated to address this point; particular importance is given to the cavitation phenomenon. Finally, a numerical example regarding the design of a high-efficiency hydrofoil is illustrated, and the results are compared with existing turbine airfoils, considering also the effect on turbine performance due to different airfoils.
Multi-Disciplinary Design Optimization Using WAVE

Science.gov (United States)

Irwin, Keith

2000-01-01

The current preliminary design tools lack the product performance, quality and cost prediction fidelity required to design Six Sigma products. They are also frequently incompatible with the tools used in detailed design, leading to a great deal of rework and lost or discarded data in the transition from preliminary to detailed design. Thus, enhanced preliminary design tools are needed in order to produce adequate financial returns to the business. To achieve this goal, GEAE has focused on building the preliminary design system around the same geometric 3D solid model that will be used in detailed design. With this approach, the preliminary designer will no longer convert a flowpath sketch into an engine cross section but rather, automatically create 3D solid geometry for structural integrity, life, weight, cost, complexity, producibility, and maintainability assessments. Likewise, both the preliminary design and the detailed design can benefit from the use of the same preliminary part sizing routines. The design analysis tools will also be integrated with the 3D solid model to eliminate manual transfer of data between programs. GEAE has aggressively pursued the computerized control of engineering knowledge for many years. Through its study and validation of 3D CAD programs and processes, GEAE concluded that total system control was not feasible at that time. Prior CAD tools focused exclusively on detail part geometry and Knowledge Based Engineering systems concentrated on rules input and data output. A system was needed to bridge the gap between the two to capture the total system. With the introduction of WAVE Engineering from UGS, the possibilities of an engineering system control device began to formulate. GEAE decided to investigate the new WAVE functionality to accomplish this task. NASA joined GEAE in funding this validation project through Task Order No. 1. With the validation project complete, the second phase under Task Order No. 2 was established to
Sequential optimization of matrix chain multiplication relative to different cost functions

KAUST Repository

Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail

2011-01-01

In this paper, we present a methodology to optimize matrix chain multiplication sequentially relative to different cost functions such as total number of scalar multiplications, communication overhead in a multiprocessor environment, etc. For n matrices our optimization procedure requires O(n 3) arithmetic operations per one cost function. This work is done in the framework of a dynamic programming extension that allows sequential optimization relative to different criteria. © 2011 Springer-Verlag Berlin Heidelberg.
Optimal Design of a Novel Hybrid Electric Powertrain for Tracked Vehicles

Directory of Open Access Journals (Sweden)

Zhaobo Qin

2017-12-01

Full Text Available Tracked vehicles have been widely used in construction, agriculture, and the military. Major problems facing the industry, however, are high emissions and fuel consumption. Hybrid electric tracked vehicles have thus become increasingly popular because of their improved fuel economy and reduced emissions. While the series hybrid system has drawn the most attention and has been applied in most cases, the low efficiency caused by energy conversion losses and large propulsion motors has limited its development. A novel multi-mode powertrain with two output shafts controlling each side of the track independently is first proposed. The powertrain is a three-planetary-gear power-split system with one engine, three motors, and an ultracapacitor pack. Compared with the existing technologies, the proposed powertrain can realize skid steering without an extra steering mechanism, and significantly improve the overall efficiency. To demonstrate the advantages of the novel powertrain, a topology-control-size integrated optimization problem is solved based on drivability, fuel economy, and cost. Final simulation results show that the optimized design with downsized components can produce about a 30% improvement in drivability and a 15% improvement in fuel economy compared with the commonly used series hybrid benchmark. Moreover, the optimized design is verified to be much more economical taking cumulative cost into account, which is very attractive for potential industrial applications in the future.
No Cost – Low Cost Compressed Air System Optimization in Industry

Science.gov (United States)

Dharma, A.; Budiarsa, N.; Watiniasih, N.; Antara, N. G.

2018-04-01

Energy conservation is a systematic, integrated of effort, in order to preserve energy sources and improve energy utilization efficiency. Utilization of energy in efficient manner without reducing the energy usage it must. Energy conservation efforts are applied at all stages of utilization, from utilization of energy resources to final, using efficient technology, and cultivating an energy-efficient lifestyle. The most common way is to promote energy efficiency in the industry on end use and overcome barriers to achieve such efficiency by using system energy optimization programs. The facts show that energy saving efforts in the process usually only focus on replacing tools and not an overall system improvement effort. In this research, a framework of sustainable energy reduction work in companies that have or have not implemented energy management system (EnMS) will be conducted a systematic technical approach in evaluating accurately a compressed-air system and potential optimization through observation, measurement and verification environmental conditions and processes, then processing the physical quantities of systems such as air flow, pressure and electrical power energy at any given time measured using comparative analysis methods in this industry, to provide the potential savings of energy saving is greater than the component approach, with no cost to the lowest cost (no cost - low cost). The process of evaluating energy utilization and energy saving opportunities will provide recommendations for increasing efficiency in the industry and reducing CO2 emissions and improving environmental quality.
Optimal design of active EMC filters

Science.gov (United States)

Chand, B.; Kut, T.; Dickmann, S.

2013-07-01

A recent trend in automotive industry is adding electrical drive systems to conventional drives. The electrification allows an expansion of energy sources and provides great opportunities for environmental friendly mobility. The electrical powertrain and its components can also cause disturbances which couple into nearby electronic control units and communication cables. Therefore the communication can be degraded or even permanently disrupted. To minimize these interferences, different approaches are possible. One possibility is to use EMC filters. However, the diversity of filters is very large and the determination of an appropriate filter for each application is time-consuming. Therefore, the filter design is determined by using a simulation tool including an effective optimization algorithm. This method leads to improvements in terms of weight, volume and cost.
Bayesian Optimal Experimental Design Using Multilevel Monte Carlo

KAUST Repository

Ben Issaid, Chaouki; Long, Quan; Scavino, Marco; Tempone, Raul

2015-01-01

Experimental design is very important since experiments are often resource-exhaustive and time-consuming. We carry out experimental design in the Bayesian framework. To measure the amount of information, which can be extracted from the data in an experiment, we use the expected information gain as the utility function, which specifically is the expected logarithmic ratio between the posterior and prior distributions. Optimizing this utility function enables us to design experiments that yield the most informative data for our purpose. One of the major difficulties in evaluating the expected information gain is that the integral is nested and can be high dimensional. We propose using Multilevel Monte Carlo techniques to accelerate the computation of the nested high dimensional integral. The advantages are twofold. First, the Multilevel Monte Carlo can significantly reduce the cost of the nested integral for a given tolerance, by using an optimal sample distribution among different sample averages of the inner integrals. Second, the Multilevel Monte Carlo method imposes less assumptions, such as the concentration of measures, required by Laplace method. We test our Multilevel Monte Carlo technique using a numerical example on the design of sensor deployment for a Darcy flow problem governed by one dimensional Laplace equation. We also compare the performance of the Multilevel Monte Carlo, Laplace approximation and direct double loop Monte Carlo.
Bayesian Optimal Experimental Design Using Multilevel Monte Carlo

KAUST Repository

Ben Issaid, Chaouki

2015-01-07

Experimental design is very important since experiments are often resource-exhaustive and time-consuming. We carry out experimental design in the Bayesian framework. To measure the amount of information, which can be extracted from the data in an experiment, we use the expected information gain as the utility function, which specifically is the expected logarithmic ratio between the posterior and prior distributions. Optimizing this utility function enables us to design experiments that yield the most informative data for our purpose. One of the major difficulties in evaluating the expected information gain is that the integral is nested and can be high dimensional. We propose using Multilevel Monte Carlo techniques to accelerate the computation of the nested high dimensional integral. The advantages are twofold. First, the Multilevel Monte Carlo can significantly reduce the cost of the nested integral for a given tolerance, by using an optimal sample distribution among different sample averages of the inner integrals. Second, the Multilevel Monte Carlo method imposes less assumptions, such as the concentration of measures, required by Laplace method. We test our Multilevel Monte Carlo technique using a numerical example on the design of sensor deployment for a Darcy flow problem governed by one dimensional Laplace equation. We also compare the performance of the Multilevel Monte Carlo, Laplace approximation and direct double loop Monte Carlo.
Optimal design of the cable metro with unified intermediate supports

Directory of Open Access Journals (Sweden)

Lagerev A.V.

2017-12-01

Full Text Available In article was formulated and solved the problem of conditional nonlinear technical and economic optimization of the distance between intermediate supports, uniform in height, during the design of the cable metro lines in highly urban-ized city environment. The optimization problem involves a single-criterion objective function that expresses the cost of construction of the cable metro line (total cost of intermediate supports and their foundations, traction and carrying steel cables and technical equipment. The specified objective function subject to minimization by finding the optimal combination of the distance between intermediate supports and tension carrying ropes with accounting constructive, modal, structural and planning constraints in the form of nonlinear inequalities. The optimization algorithm was based on the direct method of optimization type, Hooke-Jeeves, which was modified taking into account the need of varying the height of intermediate supports with a constant step equal to the step of unification. When constructing the objective function were considered three possible forms sagging of carrying ropes, which can be implemented for various values of the efforts of their tension. Analysis was done of the influence of the step unification and minimum size of interme-diate supports on their optimum step, the cost of intermediate supports, the cost of 1 km cable metro line for different values of the angle of the longitudinal slope of the surface relief along the cable metro line. The graph of height of uni-fied supports from the angle of the longitudinal slope of the surface relief has discrete-step type. With the increase of the step unify the discreteness increases: the width of the range of angles of the longitudinal slope of the surface relief within which the height of the supports remains constant, increases. The graph of step installation of unified supports along the cable metro line from the angle of the longitudinal
Transportation package design using numerical optimization

International Nuclear Information System (INIS)

Harding, D.C.; Witkowski, W.R.

1991-01-01

The purpose of this overview is twofold: first, to outline the theory and basic elements of numerical optimization; and second, to show how numerical optimization can be applied to the transportation packaging industry and used to increase efficiency and safety of radioactive and hazardous material transportation packages. A more extensive review of numerical optimization and its applications to radioactive material transportation package design was performed previously by the authors (Witkowski and Harding 1992). A proof-of-concept Type B package design is also presented as a simplified example of potential improvements achievable using numerical optimization in the design process
Transportation package design using numerical optimization

International Nuclear Information System (INIS)

Harding, D.C.; Witkowski, W.R.

1992-01-01

The design of structures and engineering systems has always been an iterative process whose complexity was dependent upon the boundary conditions, constraints and available analytical tools. Transportation packaging design is no exception with structural, thermal and radiation shielding constraints based on regulatory hypothetical accident conditions. Transportation packaging design is often accomplished by a group of specialists, each designing a single component based on one or more simple criteria, pooling results with the group, evaluating the open-quotes pooledclose quotes design, and then reiterating the entire process until a satisfactory design is reached. The manual iterative methods used by the designer/analyst can be summarized in the following steps: design the part, analyze the part, interpret the analysis results, modify the part, and re-analyze the part. The inefficiency of this design practice and the frequently conservative result suggests the need for a more structured design methodology, which can simultaneously consider all of the design constraints. Numerical optimization is a structured design methodology whose maturity in development has allowed it to become a primary design tool in many industries. The purpose of this overview is twofold: first, to outline the theory and basic elements of numerical optimization; and second, to show how numerical optimization can be applied to the transportation packaging industry and used to increase efficiency and safety of radioactive and hazardous material transportation packages. A more extensive review of numerical optimization and its applications to radioactive material transportation package design was performed previously by the authors (Witkowski and Harding 1992). A proof-of-concept Type B package design is also presented as a simplified example of potential improvements achievable using numerical optimization in the design process
System optimization of solar hydrogen energy system based on hydrogen production cost. 2; Suiso seizo cost wo hyoka shihyo to shita taiyo suiso energy system no saiteki sekkei. 2

Energy Technology Data Exchange (ETDEWEB)

Ota, D; Yamagami, Y; Tani, T [Science University of Tokyo, Tokyo (Japan)

1996-10-27

In this paper, to evaluate the hydrogen production cost per unit volume, system optimization of solar hydrogen energy system is discussed. Based on the simulation of the I-V characteristics of amorphous Si (a-Si) photovoltaic array, the working point between the array and hydrogen generator was determined. The cost ratio of each design point was calculated. The optimum design points were 500 W/m{sup 2} for the single crystal Si system, and 600 W/m{sup 2} for the a-Si system. When the rating capacity of design point was constant, almost constant cost ratio was obtained independent of the type of photovoltaic cells. It was found that the photovoltaic cells can be fabricated in about 15% lower cost at maximum. It was also found that the optimum design point sifts to the lower insolation site due to reduction of the photovoltaic cell cost. Since the annual hydrogen generation quantity does not depend on the type of photovoltaic cells under the constant rating capacity of design point, hydrogen can be produced in lower cost by using photovoltaic cell of lower cost. 5 refs., 10 figs., 5 tabs.
Optimization of robustness of interdependent network controllability by redundant design.

Directory of Open Access Journals (Sweden)

Zenghu Zhang

Full Text Available Controllability of complex networks has been a hot topic in recent years. Real networks regarded as interdependent networks are always coupled together by multiple networks. The cascading process of interdependent networks including interdependent failure and overload failure will destroy the robustness of controllability for the whole network. Therefore, the optimization of the robustness of interdependent network controllability is of great importance in the research area of complex networks. In this paper, based on the model of interdependent networks constructed first, we determine the cascading process under different proportions of node attacks. Then, the structural controllability of interdependent networks is measured by the minimum driver nodes. Furthermore, we propose a parameter which can be obtained by the structure and minimum driver set of interdependent networks under different proportions of node attacks and analyze the robustness for interdependent network controllability. Finally, we optimize the robustness of interdependent network controllability by redundant design including node backup and redundancy edge backup and improve the redundant design by proposing different strategies according to their cost. Comparative strategies of redundant design are conducted to find the best strategy. Results shows that node backup and redundancy edge backup can indeed decrease those nodes suffering from failure and improve the robustness of controllability. Considering the cost of redundant design, we should choose BBS (betweenness-based strategy or DBS (degree based strategy for node backup and HDF(high degree first for redundancy edge backup. Above all, our proposed strategies are feasible and effective at improving the robustness of interdependent network controllability.
The Vertical-Tube Solar Collector: A Low-Cost Design Suitable for Temperate High-Latitude Locations

Directory of Open Access Journals (Sweden)

Luis Juanicó

2014-01-01

Full Text Available A new low-cost solar collector based on thick (4.5′′ vertical tubes related to the previous design based on long 1.5′′ plastic hoses connected directly between water-grid supply and consumption is presented. This novel design could noticeably improve its performance for temperate locations mid and high latitudes, as was demonstrated by dynamic thermal modeling. This tool has been useful for understanding the particular characteristics of this kind of water-pond collector and besides, for noticeably improving its performance by optimizing its parameters, like tube diameter and number of glazing layers. By this way, the optimized design could fully satisfy the household demand up to midnight along the whole year for Buenos Aires (35°S and during summers (remaining as a useful preheater for the whole year for Ushuaia (55°S. Besides, its high simplicity makes it available for user’s own construction, costing down 50 dollars for a single-family unit.
Design Optimization of Mixed-Criticality Real-Time Applications on Cost-Constrained Partitioned Architectures

DEFF Research Database (Denmark)

Tamas-Selicean, Domitian; Pop, Paul

2011-01-01

In this paper we are interested to implement mixed-criticality hard real-time applications on a given heterogeneous distributed architecture. Applications have different criticality levels, captured by their Safety-Integrity Level (SIL), and are scheduled using static-cyclic scheduling. Mixed......-criticality tasks can be integrated onto the same architecture only if there is enough spatial and temporal separation among them. We consider that the separation is provided by partitioning, such that applications run in separate partitions, and each partition is allocated several time slots on a processor. Tasks...... slots on each processor and (iv) the schedule tables, such that all the applications are schedulable and the development costs are minimized. We have proposed a Tabu Search-based approach to solve this optimization problem. The proposed algorithm has been evaluated using several synthetic and real...
A performance-oriented power transformer design methodology using multi-objective evolutionary optimization.

Science.gov (United States)

Adly, Amr A; Abd-El-Hafiz, Salwa K

2015-05-01

Transformers are regarded as crucial components in power systems. Due to market globalization, power transformer manufacturers are facing an increasingly competitive environment that mandates the adoption of design strategies yielding better performance at lower costs. In this paper, a power transformer design methodology using multi-objective evolutionary optimization is proposed. Using this methodology, which is tailored to be target performance design-oriented, quick rough estimation of transformer design specifics may be inferred. Testing of the suggested approach revealed significant qualitative and quantitative match with measured design and performance values. Details of the proposed methodology as well as sample design results are reported in the paper.
Hardware/software co-design and optimization for cyberphysical integration in digital microfluidic biochips

CERN Document Server

Luo, Yan; Ho, Tsung-Yi

2015-01-01

This book describes a comprehensive framework for hardware/software co-design, optimization, and use of robust, low-cost, and cyberphysical digital microfluidic systems. Readers with a background in electronic design automation will find this book to be a valuable reference for leveraging conventional VLSI CAD techniques for emerging technologies, e.g., biochips or bioMEMS. Readers from the circuit/system design community will benefit from methods presented to extend design and testing techniques from microelectronics to mixed-technology microsystems. For readers from the microfluidics domain,
A theoretical cost optimization model of reused flowback distribution network of regional shale gas development

International Nuclear Information System (INIS)

Li, Huajiao; An, Haizhong; Fang, Wei; Jiang, Meng

2017-01-01

The logistical issues surrounding the timing and transport of flowback generated by each shale gas well to the next is a big challenge. Due to more and more flowback being stored temporarily near the shale gas well and reused in the shale gas development, both transportation cost and storage cost are the heavy burden for the developers. This research proposed a theoretical cost optimization model to get the optimal flowback distribution solution for regional multi shale gas wells in a holistic perspective. Then, we used some empirical data of Marcellus Shale to do the empirical study. In addition, we compared the optimal flowback distribution solution by considering both the transportation cost and storage cost with the flowback distribution solution which only minimized the transportation cost or only minimized the storage cost. - Highlights: • A theoretical cost optimization model to get optimal flowback distribution solution. • An empirical study using the shale gas data in Bradford County of Marcellus Shale. • Visualization of optimal flowback distribution solutions under different scenarios. • Transportation cost is a more important factor for reducing the cost. • Help the developers to cut the storage and transportation cost of reusing flowback.
Design of microfluidic bioreactors using topology optimization

DEFF Research Database (Denmark)

Okkels, Fridolin; Bruus, Henrik

2007-01-01

We address the design of optimal reactors for supporting biological cultures using the method of topology optimization. For some years this method have been used to design various optimal microfluidic devices.1-4 We apply this method to distribute optimally biologic cultures within a flow...

Optimal design of a main driving mechanism for servo punch press based on performance atlases

Science.gov (United States)

Zhou, Yanhua; Xie, Fugui; Liu, Xinjun

2013-09-01

The servomotor drive turret punch press is attracting more attentions and being developed more intensively due to the advantages of high speed, high accuracy, high flexibility, high productivity, low noise, cleaning and energy saving. To effectively improve the performance and lower the cost, it is necessary to develop new mechanisms and establish corresponding optimal design method with uniform performance indices. A new patented main driving mechanism and a new optimal design method are proposed. In the optimal design, the performance indices, i.e., the local motion/force transmission indices ITI, OTI, good transmission workspace good transmission workspace(GTW) and the global transmission indices GTIs are defined. The non-dimensional normalization method is used to get all feasible solutions in dimensional synthesis. Thereafter, the performance atlases, which can present all possible design solutions, are depicted. As a result, the feasible solution of the mechanism with good motion/force transmission performance is obtained. And the solution can be flexibly adjusted by designer according to the practical design requirements. The proposed mechanism is original, and the presented design method provides a feasible solution to the optimal design of the main driving mechanism for servo punch press.
An Optimal Operating Strategy for Battery Life Cycle Costs in Electric Vehicles

Directory of Open Access Journals (Sweden)

Yinghua Han

2014-01-01

Full Text Available Impact on petroleum based vehicles on the environment, cost, and availability of fuel has led to an increased interest in electric vehicle as a means of transportation. Battery is a major component in an electric vehicle. Economic viability of these vehicles depends on the availability of cost-effective batteries. This paper presents a generalized formulation for determining the optimal operating strategy and cost optimization for battery. Assume that the deterioration of the battery is stochastic. Under the assumptions, the proposed operating strategy for battery is formulated as a nonlinear optimization problem considering reliability and failure number. And an explicit expression of the average cost rate is derived for battery lifetime. Results show that the proposed operating strategy enhances the availability and reliability at a low cost.
Evolutionary algorithms for multi-objective energetic and economic optimization in thermal system design

International Nuclear Information System (INIS)

Toffolo, A.; Lazzaretto, A.

2002-01-01

Thermoeconomic analyses in thermal system design are always focused on the economic objective. However, knowledge of only the economic minimum may not be sufficient in the decision making process, since solutions with a higher thermodynamic efficiency, in spite of small increases in total costs, may result in much more interesting designs due to changes in energy market prices or in energy policies. This paper suggests how to perform a multi-objective optimization in order to find solutions that simultaneously satisfy exergetic and economic objectives. This corresponds to a search for the set of Pareto optimal solutions with respect to the two competing objectives. The optimization process is carried out by an evolutionary algorithm, that features a new diversity preserving mechanism using as a test case the well-known CGAM problem. (author)
NSGA-II Algorithm with a Local Search Strategy for Multiobjective Optimal Design of Dry-Type Air-Core Reactor

Directory of Open Access Journals (Sweden)

Chengfen Zhang

2015-01-01

Full Text Available Dry-type air-core reactor is now widely applied in electrical power distribution systems, for which the optimization design is a crucial issue. In the optimization design problem of dry-type air-core reactor, the objectives of minimizing the production cost and minimizing the operation cost are both important. In this paper, a multiobjective optimal model is established considering simultaneously the two objectives of minimizing the production cost and minimizing the operation cost. To solve the multi-objective optimization problem, a memetic evolutionary algorithm is proposed, which combines elitist nondominated sorting genetic algorithm version II (NSGA-II with a local search strategy based on the covariance matrix adaptation evolution strategy (CMA-ES. NSGA-II can provide decision maker with flexible choices among the different trade-off solutions, while the local-search strategy, which is applied to nondominated individuals randomly selected from the current population in a given generation and quantity, can accelerate the convergence speed. Furthermore, another modification is that an external archive is set in the proposed algorithm for increasing the evolutionary efficiency. The proposed algorithm is tested on a dry-type air-core reactor made of rectangular cross-section litz-wire. Simulation results show that the proposed algorithm has high efficiency and it converges to a better Pareto front.
Growth Optimal Portfolio Selection Under Proportional Transaction Costs with Obligatory Diversification

International Nuclear Information System (INIS)

Duncan, T.; Pasik Duncan, B.; Stettner, L.

2011-01-01

A continuous time long run growth optimal or optimal logarithmic utility portfolio with proportional transaction costs consisting of a fixed proportional cost and a cost proportional to the volume of transaction is considered. The asset prices are modeled as exponent of diffusion with jumps whose parameters depend on a finite state Markov process of economic factors. An obligatory portfolio diversification is introduced, accordingly to which it is required to invest at least a fixed small portion of our wealth in each asset.
Mechanistic modeling of cyclic voltammetry: A helpful tool for understanding biosensor principles and supporting design optimization

DEFF Research Database (Denmark)

Semenova, Daria; Zubov, Alexandr; Silina, Yuliya E.

2018-01-01

Abstract Design, optimization and integration of biosensors hold a great potential for the development of cost-effective screening and point-of-care technologies. However, significant progress in this field can still be obtained on condition that sufficiently accurate mathematical models......, oxidized/reduced forms of the mediator - Prussian Blue/Prussian White). Furthermore, the developed model was applied under various operating conditions as a crucial tool for biosensor design optimization. The obtained qualitative and quantitative dependencies towards amperometric biosensors design...... optimization were independently supported by results of cyclic voltammetry and multi-analytical studies, such as scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX) and liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS). Remarkably, a linear...
System design optimization for stand-alone photovoltaic systems sizing by using superstructure model

International Nuclear Information System (INIS)

Azau, M A M; Jaafar, S; Samsudin, K

2013-01-01

Although the photovoltaic (PV) systems have been increasingly installed as an alternative and renewable green power generation, the initial set up cost, maintenance cost and equipment mismatch are some of the key issues that slows down the installation in small household. This paper presents the design optimization of stand-alone photovoltaic systems using superstructure model where all possible types of technology of the equipment are captured and life cycle cost analysis is formulated as a mixed integer programming (MIP). A model for investment planning of power generation and long-term decision model are developed in order to help the system engineer to build a cost effective system.
Design of Thermal Systems Using Topology Optimization

DEFF Research Database (Denmark)

Haertel, Jan Hendrik Klaas

printeddry-cooled power plant condensers using a simpliffed thermouid topology optimizationmodel is presented in another study. A benchmarking of the optimized geometriesagainst a conventional heat exchanger design is conducted and the topologyoptimized designs show a superior performance. A thermouid......The goalof this thesis is to apply topology optimization to the design of differentthermal systems such as heat sinks and heat exchangers in order to improve thethermal performance of these systems compared to conventional designs. Thedesign of thermal systems is a complex task that has...... of optimized designs are presentedwithin this thesis. The maincontribution of the thesis is the development of several numerical optimizationmodels that are applied to different design challenges within thermalengineering. Topology optimization isapplied in an industrial project to design the heat rejection...
Structural Design Optimization of Doubly-Fed Induction Generators Using GeneratorSE

Energy Technology Data Exchange (ETDEWEB)

Sethuraman, Latha [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Fingersh, Lee J [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dykes, Katherine L [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Arthurs, Claire [Georgia Institute of Technology

2017-11-13

A wind turbine with a larger rotor swept area can generate more electricity, however, this increases costs disproportionately for manufacturing, transportation, and installation. This poster presents analytical models for optimizing doubly-fed induction generators (DFIGs), with the objective of reducing the costs and mass of wind turbine drivetrains. The structural design for the induction machine includes models for the casing, stator, rotor, and high-speed shaft developed within the DFIG module in the National Renewable Energy Laboratory's wind turbine sizing tool, GeneratorSE. The mechanical integrity of the machine is verified by examining stresses, structural deflections, and modal properties. The optimization results are then validated using finite element analysis (FEA). The results suggest that our analytical model correlates with the FEA in some areas, such as radial deflection, differing by less than 20 percent. But the analytical model requires further development for axial deflections, torsional deflections, and stress calculations.
Design optimization for active twist rotor blades

Science.gov (United States)

Mok, Ji Won

This dissertation introduces the process of optimizing active twist rotor blades in the presence of embedded anisotropic piezo-composite actuators. Optimum design of active twist blades is a complex task, since it involves a rich design space with tightly coupled design variables. The study presents the development of an optimization framework for active helicopter rotor blade cross-sectional design. This optimization framework allows for exploring a rich and highly nonlinear design space in order to optimize the active twist rotor blades. Different analytical components are combined in the framework: cross-sectional analysis (UM/VABS), an automated mesh generator, a beam solver (DYMORE), a three-dimensional local strain recovery module, and a gradient based optimizer within MATLAB. Through the mathematical optimization problem, the static twist actuation performance of a blade is maximized while satisfying a series of blade constraints. These constraints are associated with locations of the center of gravity and elastic axis, blade mass per unit span, fundamental rotating blade frequencies, and the blade strength based on local three-dimensional strain fields under worst loading conditions. Through pre-processing, limitations of the proposed process have been studied. When limitations were detected, resolution strategies were proposed. These include mesh overlapping, element distortion, trailing edge tab modeling, electrode modeling and foam implementation of the mesh generator, and the initial point sensibility of the current optimization scheme. Examples demonstrate the effectiveness of this process. Optimization studies were performed on the NASA/Army/MIT ATR blade case. Even though that design was built and shown significant impact in vibration reduction, the proposed optimization process showed that the design could be improved significantly. The second example, based on a model scale of the AH-64D Apache blade, emphasized the capability of this framework to
Integrated management model. Methodology and software-enabled tood designed to assist a utility in developing a station-wide optimization

International Nuclear Information System (INIS)

Llovet, R.; Ibanez, R.; Woodcock, J.

2005-01-01

A key concern for utilities today is optimizing station aging and realibility management activities in a manner that maximizes the value of those activities withing an affordable budget. The Westinghouse Proactive Asset Management Model is a methodology and software-enabled tood designed to assist a utility in developing a station-wide optimization of those activities. The process and tool support the development of an optimized, station-wide plan for inspection, testing, maintenance, repaor and replacement of aging components. The optimization identifies the benefit and optimal timing of those activities based on minimizing unplanned outage costs (avoided costs) and maximizing station Net Present Value. (Author)
A comparison of two closely-related approaches to aerodynamic design optimization

Science.gov (United States)

Shubin, G. R.; Frank, P. D.

1991-01-01

Two related methods for aerodynamic design optimization are compared. The methods, called the implicit gradient approach and the variational (or optimal control) approach, both attempt to obtain gradients necessary for numerical optimization at a cost significantly less than that of the usual black-box approach that employs finite difference gradients. While the two methods are seemingly quite different, they are shown to differ (essentially) in that the order of discretizing the continuous problem, and of applying calculus, is interchanged. Under certain circumstances, the two methods turn out to be identical. We explore the relationship between these methods by applying them to a model problem for duct flow that has many features in common with transonic flow over an airfoil. We find that the gradients computed by the variational method can sometimes be sufficiently inaccurate to cause the optimization to fail.
Dynamic Portfolio Optimization with Transaction Costs and State-Dependent Drift

DEFF Research Database (Denmark)

Palczewski, Jan; Poulsen, Rolf; Schenk-Hoppe, Klaus Reiner

2015-01-01

The problem of dynamic portfolio choice with transaction costs is often addressed by constructing a Markov Chain approximation of the continuous time price processes. Using this approximation, we present an efficient numerical method to determine optimal portfolio strategies under time- and state......-dependent drift and proportional transaction costs. This scenario arises when investors have behavioral biases or the actual drift is unknown and needs to be estimated. Our numerical method solves dynamic optimal portfolio problems with an exponential utility function for time-horizons of up to 40 years....... It is applied to measure the value of information and the loss from transaction costs using the indifference principle....
Aerodynamic Optimization of a Wind Turbine Blade Designed for Egypt's Saharan Environment Using a Genetic Algorithm

Directory of Open Access Journals (Sweden)

Khaled Yassin

2015-08-01

Full Text Available This work aims to optimize the aerodynamic parameters (airfoil chord lengths and twist angles smoothed using Bezier curves of the NREL 5MW wind turbine and a wind turbine designed for site-specific wind conditions to increase the wind turbine's annual energy production (AEP under this site conditions. This optimization process is carried out using a Genetic Algorithm (GA developed in MATLAB and coupled with NREL's FAST Modularization Framework. The results shows that after optimizing the NREL 5MW wind turbine design, the AEP was improved by 5.9% of the baseline design AEP while a site-specific designed wind turbine using Schmitz equations shows 1.2% improvement in AEP. These results shows that optimization of wind turbine blade aerodynamic parameters for site-specific wind conditions leads to improvement in AEP and hence decreasing cost of energy generated by wind turbines.
Design of acoustic devices by topology optimization

DEFF Research Database (Denmark)

Sigmund, Ole; Jensen, Jakob Søndergaard

2003-01-01

The goal of this study is to design and optimize structures and devices that are subjected to acoustic waves. Examples are acoustic lenses, sound walls, waveguides and loud speakers. We formulate the design problem as a topology optimization problem, i.e. distribute material in a design domain...... such that the acoustic response is optimized....
An exact algorithm for optimal MAE stack filter design.

Science.gov (United States)

Dellamonica, Domingos; Silva, Paulo J S; Humes, Carlos; Hirata, Nina S T; Barrera, Junior

2007-02-01

We propose a new algorithm for optimal MAE stack filter design. It is based on three main ingredients. First, we show that the dual of the integer programming formulation of the filter design problem is a minimum cost network flow problem. Next, we present a decomposition principle that can be used to break this dual problem into smaller subproblems. Finally, we propose a specialization of the network Simplex algorithm based on column generation to solve these smaller subproblems. Using our method, we were able to efficiently solve instances of the filter problem with window size up to 25 pixels. To the best of our knowledge, this is the largest dimension for which this problem was ever solved exactly.
Configuration space analysis of common cost functions in radiotherapy beam-weight optimization algorithms

Energy Technology Data Exchange (ETDEWEB)

Rowbottom, Carl Graham [Joint Department of Physics, Institute of Cancer Research and the Royal Marsden NHS Trust, Sutton, Surrey (United Kingdom); Webb, Steve [Joint Department of Physics, Institute of Cancer Research and the Royal Marsden NHS Trust, Sutton, Surrey (United Kingdom)

2002-01-07

The successful implementation of downhill search engines in radiotherapy optimization algorithms depends on the absence of local minima in the search space. Such techniques are much faster than stochastic optimization methods but may become trapped in local minima if they exist. A technique known as 'configuration space analysis' was applied to examine the search space of cost functions used in radiotherapy beam-weight optimization algorithms. A downhill-simplex beam-weight optimization algorithm was run repeatedly to produce a frequency distribution of final cost values. By plotting the frequency distribution as a function of final cost, the existence of local minima can be determined. Common cost functions such as the quadratic deviation of dose to the planning target volume (PTV), integral dose to organs-at-risk (OARs), dose-threshold and dose-volume constraints for OARs were studied. Combinations of the cost functions were also considered. The simple cost function terms such as the quadratic PTV dose and integral dose to OAR cost function terms are not susceptible to local minima. In contrast, dose-threshold and dose-volume OAR constraint cost function terms are able to produce local minima in the example case studied. (author)
A stochastic discrete optimization model for designing container terminal facilities

Science.gov (United States)

Zukhruf, Febri; Frazila, Russ Bona; Burhani, Jzolanda Tsavalista

2017-11-01

As uncertainty essentially affect the total transportation cost, it remains important in the container terminal that incorporates several modes and transshipments process. This paper then presents a stochastic discrete optimization model for designing the container terminal, which involves the decision of facilities improvement action. The container terminal operation model is constructed by accounting the variation of demand and facilities performance. In addition, for illustrating the conflicting issue that practically raises in the terminal operation, the model also takes into account the possible increment delay of facilities due to the increasing number of equipment, especially the container truck. Those variations expectantly reflect the uncertainty issue in the container terminal operation. A Monte Carlo simulation is invoked to propagate the variations by following the observed distribution. The problem is constructed within the framework of the combinatorial optimization problem for investigating the optimal decision of facilities improvement. A new variant of glow-worm swarm optimization (GSO) is thus proposed for solving the optimization, which is rarely explored in the transportation field. The model applicability is tested by considering the actual characteristics of the container terminal.
Neural-Network-Based Robust Optimal Tracking Control for MIMO Discrete-Time Systems With Unknown Uncertainty Using Adaptive Critic Design.

Science.gov (United States)

Liu, Lei; Wang, Zhanshan; Zhang, Huaguang

2018-04-01

This paper is concerned with the robust optimal tracking control strategy for a class of nonlinear multi-input multi-output discrete-time systems with unknown uncertainty via adaptive critic design (ACD) scheme. The main purpose is to establish an adaptive actor-critic control method, so that the cost function in the procedure of dealing with uncertainty is minimum and the closed-loop system is stable. Based on the neural network approximator, an action network is applied to generate the optimal control signal and a critic network is used to approximate the cost function, respectively. In contrast to the previous methods, the main features of this paper are: 1) the ACD scheme is integrated into the controllers to cope with the uncertainty and 2) a novel cost function, which is not in quadric form, is proposed so that the total cost in the design procedure is reduced. It is proved that the optimal control signals and the tracking errors are uniformly ultimately bounded even when the uncertainty exists. Finally, a numerical simulation is developed to show the effectiveness of the present approach.
Designing to target cost: one approach to design/construction integration

DEFF Research Database (Denmark)

Jørgensen, Bo

2005-01-01

One approach to a more integrated construction delivery process is the concept of ‘designing to target cost’ of which the first examples of application within a lean construction framework have recently been seen. This paper introduces the main principles of the design to target cost method...... and discusses the applicability of this approach to construction. The low degree of organizational and technical continuity from one construction project to the next limits the applicability of the design for target cost approach when compared to its origin in product development of mass manufactured artefacts....... It can be argued that design to target cost may also provide a frame for developing the supply chain towards better coordination and collaboration. Thus methods of design to target cost may serve to facilitate the development of a more integrated supply chain....

Derivative-free optimization under uncertainty applied to costly simulators

International Nuclear Information System (INIS)

Pauwels, Benoit

2016-01-01

The modeling of complex phenomena encountered in industrial issues can lead to the study of numerical simulation codes. These simulators may require extensive execution time (from hours to days), involve uncertain parameters and even be intrinsically stochastic. Importantly within the context of simulation-based optimization, the derivatives of the outputs with respect to the inputs may be inexistent, inaccessible or too costly to approximate reasonably. This thesis is organized in four chapters. The first chapter discusses the state of the art in derivative-free optimization and uncertainty modeling. The next three chapters introduce three independent - although connected - contributions to the field of derivative-free optimization in the presence of uncertainty. The second chapter addresses the emulation of costly stochastic simulation codes - stochastic in the sense simulations run with the same input parameters may lead to distinct outputs. Such was the matter of the CODESTOCH project carried out at the Summer mathematical research center on scientific computing and its applications (CEMRACS) during the summer of 2013, together with two Ph.D. students from Electricity of France (EDF) and the Atomic Energy and Alternative Energies Commission (CEA). We designed four methods to build emulators for functions whose values are probability density functions. These methods were tested on two toy functions and applied to industrial simulation codes concerned with three complex phenomena: the spatial distribution of molecules in a hydrocarbon system (IFPEN), the life cycle of large electric transformers (EDF) and the repercussions of a hypothetical accidental in a nuclear plant (CEA). Emulation was a preliminary process towards optimization in the first two cases. In the third chapter we consider the influence of inaccurate objective function evaluations on direct search - a classical derivative-free optimization method. In real settings inaccuracy may never vanish
Marine Hydrokinetic Turbine Power-Take-Off Design for Optimal Performance and Low Impact on Cost-of-Energy: Preprint

Energy Technology Data Exchange (ETDEWEB)

Beam, M.; Kline, B.; Elbing, B.; Straka, W.; Fontaine, A.; Lawson, M.; Li, Y.; Thresher, R.; Previsic, M.

2013-02-01

Marine hydrokinetic devices are becoming a popular method for generating marine renewable energy worldwide. These devices generate electricity by converting the kinetic energy of moving water, wave motion or currents, into electrical energy through the use of a power-take-off (PTO) system. Most PTO systems incorporate a mechanical or hydraulic drivetrain, power generator, and electric control/conditioning system to deliver the generated electric power to the grid at the required state. Like wind turbine applications, the PTO system must be designed for high reliability, good efficiency, and long service life with reasonable maintenance requirements, low cost, and an appropriate mechanical design for anticipated applied steady and unsteady loads. The ultimate goal of a PTO design is high efficiency and low maintenance and cost, with a low impact on the device cost-of-energy (CoE).
Marine Hydrokinetic Turbine Power-Take-Off Design for Optimal Performance and Low Impact on Cost-of-Energy: Preprint

Energy Technology Data Exchange (ETDEWEB)

Beam, M.; Kline, B.; Elbing, B.; Straka, W.; Fontaine, A.; Lawson, M.; Li, Y.; Thresher, R.; Previsic, M.

2012-04-01

Marine hydrokinetic devices are becoming a popular method for generating marine renewable energy worldwide. These devices generate electricity by converting the kinetic energy of moving water, wave motion or currents, into electrical energy through the use of a Power-Take-Off (PTO) system. Most PTO systems incorporate a mechanical or hydraulic drive train, power generator and electric control/conditioning system to deliver the generated electric power to the grid at the required state. Like wind turbine applications, the PTO system must be designed for high reliability, good efficiency, and long service life with reasonable maintenance requirements, low cost and an appropriate mechanical design for anticipated applied steady and unsteady loads. The ultimate goal of a PTO design is high efficiency, low maintenance and cost with a low impact on the device Cost-of-Energy (CoE).
An expert system for integrated structural analysis and design optimization for aerospace structures

Science.gov (United States)

1992-04-01

The results of a research study on the development of an expert system for integrated structural analysis and design optimization is presented. An Object Representation Language (ORL) was developed first in conjunction with a rule-based system. This ORL/AI shell was then used to develop expert systems to provide assistance with a variety of structural analysis and design optimization tasks, in conjunction with procedural modules for finite element structural analysis and design optimization. The main goal of the research study was to provide expertise, judgment, and reasoning capabilities in the aerospace structural design process. This will allow engineers performing structural analysis and design, even without extensive experience in the field, to develop error-free, efficient and reliable structural designs very rapidly and cost-effectively. This would not only improve the productivity of design engineers and analysts, but also significantly reduce time to completion of structural design. An extensive literature survey in the field of structural analysis, design optimization, artificial intelligence, and database management systems and their application to the structural design process was first performed. A feasibility study was then performed, and the architecture and the conceptual design for the integrated 'intelligent' structural analysis and design optimization software was then developed. An Object Representation Language (ORL), in conjunction with a rule-based system, was then developed using C++. Such an approach would improve the expressiveness for knowledge representation (especially for structural analysis and design applications), provide ability to build very large and practical expert systems, and provide an efficient way for storing knowledge. Functional specifications for the expert systems were then developed. The ORL/AI shell was then used to develop a variety of modules of expert systems for a variety of modeling, finite element analysis, and
Low-cost satellite mechanical design and construction

Science.gov (United States)

Boisjolie-Gair, Nathaniel; Straub, Jeremy

2017-05-01

This paper presents a discussion of techniques for low-cost design and construction of a CubeSat mechanical structure that can serve as a basis for academic programs and a starting point for government, military and commercial large-scale sensing networks, where the cost of each node must be minimized to facilitate system affordability and lower the cost and associated risk of losing any node. Spacecraft Design plays a large role in manufacturability. An intentionally simplified mechanical design is presented which reduces machining costs, as compared to more intricate designs that were considered. Several fabrication approaches are evaluated relative to the low-cost goal.
The ITER reduced cost design

International Nuclear Information System (INIS)

Aymar, R.

2000-01-01

Six years of joint work under the international thermonuclear experimental reactor (ITER) EDA agreement yielded a mature design for ITER which met the objectives set for it (ITER final design report (FDR)), together with a corpus of scientific and technological data, large/full scale models or prototypes of key components/systems and progress in understanding which both validated the specific design and are generally applicable to a next step, reactor-oriented tokamak on the road to the development of fusion as an energy source. In response to requests from the parties to explore the scope for addressing ITER's programmatic objective at reduced cost, the study of options for cost reduction has been the main feature of ITER work since summer 1998, using the advances in physics and technology databases, understandings, and tools arising out of the ITER collaboration to date. A joint concept improvement task force drawn from the joint central team and home teams has overseen and co-ordinated studies of the key issues in physics and technology which control the possibility of reducing the overall investment and simultaneously achieving the required objectives. The aim of this task force is to achieve common understandings of these issues and their consequences so as to inform and to influence the best cost-benefit choice, which will attract consensus between the ITER partners. A report to be submitted to the parties by the end of 1999 will present key elements of a specific design of minimum capital investment, with a target cost saving of about 50% the cost of the ITER FDR design, and a restricted number of design variants. Outline conclusions from the work of the task force are presented in terms of physics, operations, and design of the main tokamak systems. Possible implications for the way forward are discussed
PSO Based Optimization of Testing and Maintenance Cost in NPPs

Directory of Open Access Journals (Sweden)

Qiang Chou

2014-01-01

Full Text Available Testing and maintenance activities of safety equipment have drawn much attention in Nuclear Power Plant (NPP to risk and cost control. The testing and maintenance activities are often implemented in compliance with the technical specification and maintenance requirements. Technical specification and maintenance-related parameters, that is, allowed outage time (AOT, maintenance period and duration, and so forth, in NPP are associated with controlling risk level and operating cost which need to be minimized. The above problems can be formulated by a constrained multiobjective optimization model, which is widely used in many other engineering problems. Particle swarm optimizations (PSOs have proved their capability to solve these kinds of problems. In this paper, we adopt PSO as an optimizer to optimize the multiobjective optimization problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. Numerical results have demonstrated the efficiency of our proposed algorithm.
Non-Linear Transaction Costs Inclusion in Mean-Variance Optimization

Directory of Open Access Journals (Sweden)

Christian Johannes Zimmer

2005-12-01

Full Text Available In this article we propose a new way to include transaction costs into a mean-variance portfolio optimization. We consider brokerage fees, bid/ask spread and the market impact of the trade. A pragmatic algorithm is proposed, which approximates the optimal portfolio, and we can show that is converges in the absence of restrictions. Using Brazilian financial market data we compare our approximation algorithm with the results of a non-linear optimizer.
Optimal experimental design with R

CERN Document Server

Rasch, Dieter; Verdooren, L R; Gebhardt, Albrecht

2011-01-01

Experimental design is often overlooked in the literature of applied and mathematical statistics: statistics is taught and understood as merely a collection of methods for analyzing data. Consequently, experimenters seldom think about optimal design, including prerequisites such as the necessary sample size needed for a precise answer for an experimental question. Providing a concise introduction to experimental design theory, Optimal Experimental Design with R: Introduces the philosophy of experimental design Provides an easy process for constructing experimental designs and calculating necessary sample size using R programs Teaches by example using a custom made R program package: OPDOE Consisting of detailed, data-rich examples, this book introduces experimenters to the philosophy of experimentation, experimental design, and data collection. It gives researchers and statisticians guidance in the construction of optimum experimental designs using R programs, including sample size calculations, hypothesis te...
ASTRID© - Advanced Solar Tubular ReceIver Design: A powerful tool for receiver design and optimization

Science.gov (United States)

Frantz, Cathy; Fritsch, Andreas; Uhlig, Ralf

2017-06-01

In solar tower power plants the receiver is one of the critical components. It converts the solar radiation into heat and must withstand high heat flux densities and high daily or even hourly gradients (due to passage of clouds). For this reason, the challenge during receiver design is to find a reasonable compromise between receiver efficiency, reliability, lifetime and cost. There is a strong interaction between the heliostat field, the receiver and the heat transfer fluid. Therefore, a proper receiver design needs to consider these components within the receiver optimization. There are several design and optimization tools for receivers, but most of them focus only on the receiver, ignoring the heliostat field and other parts of the plant. During the last years DLR developed the ASTRIDcode for tubular receiver concept simulation. The code comprises both a high and a low-detail model. The low-detail model utilizes a number of simplifications which allow the user to screen a high number of receiver concepts for optimization purposes. The high-detail model uses a FE model and is able to compute local absorber and salt temperatures with high accuracy. One key strength of the ASTRIDcode is its interface to a ray tracing software which simulates a realistic heat flux distributions on the receiver surface. The results generated by the ASTRIDcode have been validated by CFD simulations and measurement data.
Optimal Design of Gravity Pipeline Systems Using Genetic Algorithm and Mathematical Optimization

Directory of Open Access Journals (Sweden)

maryam rohani

2015-03-01

Full Text Available In recent years, the optimal design of pipeline systems has become increasingly important in the water industry. In this study, the two methods of genetic algorithm and mathematical optimization were employed for the optimal design of pipeline systems with the objective of avoiding the water hammer effect caused by valve closure. The problem of optimal design of a pipeline system is a constrained one which should be converted to an unconstrained optimization problem using an external penalty function approach in the mathematical programming method. The quality of the optimal solution greatly depends on the value of the penalty factor that is calculated by the iterative method during the optimization procedure such that the computational effort is simultaneously minimized. The results obtained were used to compare the GA and mathematical optimization methods employed to determine their efficiency and capabilities for the problem under consideration. It was found that the mathematical optimization method exhibited a slightly better performance compared to the GA method.
Integrated topology and shape optimization in structural design

Science.gov (United States)

Bremicker, M.; Chirehdast, M.; Kikuchi, N.; Papalambros, P. Y.

1990-01-01

Structural optimization procedures usually start from a given design topology and vary its proportions or boundary shapes to achieve optimality under various constraints. Two different categories of structural optimization are distinguished in the literature, namely sizing and shape optimization. A major restriction in both cases is that the design topology is considered fixed and given. Questions concerning the general layout of a design (such as whether a truss or a solid structure should be used) as well as more detailed topology features (e.g., the number and connectivities of bars in a truss or the number of holes in a solid) have to be resolved by design experience before formulating the structural optimization model. Design quality of an optimized structure still depends strongly on engineering intuition. This article presents a novel approach for initiating formal structural optimization at an earlier stage, where the design topology is rigorously generated in addition to selecting shape and size dimensions. A three-phase design process is discussed: an optimal initial topology is created by a homogenization method as a gray level image, which is then transformed to a realizable design using computer vision techniques; this design is then parameterized and treated in detail by sizing and shape optimization. A fully automated process is described for trusses. Optimization of two dimensional solid structures is also discussed. Several application-oriented examples illustrate the usefulness of the proposed methodology.
A Tool to Support Optimal Industrial Wastewater Treatment Design and Analysis

DEFF Research Database (Denmark)

Quaglia, Alberto; Pennati, Alessandra; Bozkurt, Hande

2013-01-01

may be suboptimal or disregard opportunities for water recycle or resource recovery and reuse. In this contribution, we propose a model-based toolbox developed to help wastewater professionals to screen among a large number of alternatives in order to identify the optimal treatment configuration from......Industrial Wastewater Treatment Plant (IWWTP) design is often based on in-house expert knowledge and experience. Because of time and resources constraints, only a small number of alternative treatment configurations and ideas are evaluated while designing an IWWTP. Consequently, the selected design...... an economic cost-benefit perspective. The toolbox is demonstrated through a case study, dealing with oil refinery wastewater treatment and water recycle....
How to design the cost-effectiveness appraisal process of new healthcare technologies to maximise population health: A conceptual framework.

Science.gov (United States)

Johannesen, Kasper M; Claxton, Karl; Sculpher, Mark J; Wailoo, Allan J

2018-02-01

This paper presents a conceptual framework to analyse the design of the cost-effectiveness appraisal process of new healthcare technologies. The framework characterises the appraisal processes as a diagnostic test aimed at identifying cost-effective (true positive) and non-cost-effective (true negative) technologies. Using the framework, factors that influence the value of operating an appraisal process, in terms of net gain to population health, are identified. The framework is used to gain insight into current policy questions including (a) how rigorous the process should be, (b) who should have the burden of proof, and (c) how optimal design changes when allowing for appeals, price reductions, resubmissions, and re-evaluations. The paper demonstrates that there is no one optimal appraisal process and the process should be adapted over time and to the specific technology under assessment. Optimal design depends on country-specific features of (future) technologies, for example, effect, price, and size of the patient population, which might explain the difference in appraisal processes across countries. It is shown that burden of proof should be placed on the producers and that the impact of price reductions and patient access schemes on the producer's price setting should be considered when designing the appraisal process. Copyright © 2017 John Wiley & Sons, Ltd.
Optimal Rotor Design of Line Start Permanent Magnet Synchronous Motor by Genetic Algorithm

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Bui Minh Dinh

2017-07-01

Full Text Available Line start permanent magnet synchronous motor (LSPMSM is one of the highest efficiency motors due to no rotor copper loss at synchronous speed and self-starting. LSPMSM has torque characteristics of both induction motor IM and Permanent Magnet Synchronous Motor-PMSM. Using Genetic Algorithm (GA for balancing magnetic cost and for copper loss minimization, the magnetic sizes and geometry parameter of stator and rotor are found and manufactured for industrial evaluation. This article is also taking account practical manufacturing factors to minimize mass production cost. In order to maximize efficiency, an optimal design method of cage-bars and magnet shape has to be considered. The geometry parameters of stator and rotor can be obtained by an analytical model method and validated by FEM simulation. This paper presents the optimal rotor design of a three-phase line-start permanent magnet motor (LSPM considering the starting torque and efficiency. To consider nonlinear characteristics, the design process is comprised of the FEM and analytical method. During this study, permanent-magnets and cage bars were designed using the magnetic equivalent circuit method and the barriers that control all magnetic flux were designed using the FEM, and the tradeoff of starting torque and efficiency is controlled by weight function in Taguchi method simulation. Finally, some practical results have been obtained and analyzed based on a LSPMSM test bench.
Cost optimal levels for energy performance requirements

DEFF Research Database (Denmark)

Thomsen, Kirsten Engelund; Aggerholm, Søren; Kluttig-Erhorn, Heike

This report summarises the work done within the Concerted Action EPBD from December 2010 to April 2011 in order to feed into the European Commission's proposal for a common European procedure for a Cost-Optimal methodology under the Directive on the Energy Performance of Buildings (recast) 2010/3...
Optimal structural design of the midship of a VLCC based on the strategy integrating SVM and GA

Science.gov (United States)

Sun, Li; Wang, Deyu

2012-03-01

In this paper a hybrid process of modeling and optimization, which integrates a support vector machine (SVM) and genetic algorithm (GA), was introduced to reduce the high time cost in structural optimization of ships. SVM, which is rooted in statistical learning theory and an approximate implementation of the method of structural risk minimization, can provide a good generalization performance in metamodeling the input-output relationship of real problems and consequently cuts down on high time cost in the analysis of real problems, such as FEM analysis. The GA, as a powerful optimization technique, possesses remarkable advantages for the problems that can hardly be optimized with common gradient-based optimization methods, which makes it suitable for optimizing models built by SVM. Based on the SVM-GA strategy, optimization of structural scantlings in the midship of a very large crude carrier (VLCC) ship was carried out according to the direct strength assessment method in common structural rules (CSR), which eventually demonstrates the high efficiency of SVM-GA in optimizing the ship structural scantlings under heavy computational complexity. The time cost of this optimization with SVM-GA has been sharply reduced, many more loops have been processed within a small amount of time and the design has been improved remarkably.
Optimal Design of Stiffeners for Bucket Foundations

DEFF Research Database (Denmark)

Courtney, William Tucker; Stolpe, Mathias; Buhl, Thomas

2015-01-01

Tosca Structure coupled with the finite element software Abaqus. The solutions to these optimization problems are then manually interpreted as a new design concept. Results show that shape optimization of the initial design can reduce stress concentrations by 38%. Additionally, topology optimization has...
Design and fabrication of a low cost Darrieus vertical axis wing turbine system. Phase I. Technical report

Energy Technology Data Exchange (ETDEWEB)

None,

1979-06-22

The contract has two phases, a design phase and a fabrication and installation phase. Presented is the work completed in Phase I, the design phase. The Sandia 17 m was used as the background machine from which design information was drawn. By concentrating the modifications on an existing design, emphasis was focused on component cost reduction rather than selection of optimal configuration or operating modes. The resulting design is a stretched version of the Sandia 17 m preserving the same rotor diameter and many other good features, but in the meantime lighter in weight, larger in capacity, and anticipated to be more cost effective.
Aero-Thermo-Structural Design Optimization of Internally Cooled Turbine Blades

Science.gov (United States)

Dulikravich, G. S.; Martin, T. J.; Dennis, B. H.; Lee, E.; Han, Z.-X.

1999-01-01

A set of robust and computationally affordable inverse shape design and automatic constrained optimization tools have been developed for the improved performance of internally cooled gas turbine blades. The design methods are applicable to the aerodynamics, heat transfer, and thermoelasticity aspects of the turbine blade. Maximum use of the existing proven disciplinary analysis codes is possible with this design approach. Preliminary computational results demonstrate possibilities to design blades with minimized total pressure loss and maximized aerodynamic loading. At the same time, these blades are capable of sustaining significantly higher inlet hot gas temperatures while requiring remarkably lower coolant mass flow rates. These results suggest that it is possible to design internally cooled turbine blades that will cost less to manufacture, will have longer life span, and will perform as good, if not better than, film cooled turbine blades.

Optimal design of CHP-based microgrids: Multiobjective optimisation and life cycle assessment

International Nuclear Information System (INIS)

Zhang, Di; Evangelisti, Sara; Lettieri, Paola; Papageorgiou, Lazaros G.

2015-01-01

As an alternative to current centralised energy generation systems, microgrids are adopted to provide local energy with lower energy expenses and gas emissions by utilising distributed energy resources (DER). Several micro combined heat and power technologies have been developed recently for applications at domestic scale. The optimal design of DERs within CHP-based microgrids plays an important role in promoting the penetration of microgrid systems. In this work, the optimal design of microgrids with CHP units is addressed by coupling environmental and economic sustainability in a multi-objective optimisation model which integrates the results of a life cycle assessment of the microgrids investigated. The results show that the installation of multiple CHP technologies has a lower cost with higher environmental saving compared with the case when only a single technology is installed in each site, meaning that the microgrid works in a more efficient way when multiple technologies are selected. In general, proton exchange membrane (PEM) fuel cells are chosen as the basic CHP technology for most solutions, which offers lower environmental impacts at low cost. However, internal combustions engines (ICE) and Stirling engines (SE) are preferred if the heat demand is high. - Highlights: • Optimal design of microgrids is addressed by coupling environmental and economic aspects. • An MILP model is formulated based on the ε-constraint method. • The model selects a combination of CHP technologies with different technical characteristics for optimum scenarios. • The global warming potential (GWP) and the acidification potential (AP) are determined. • The output of LCA is used as an input for the optimisation model
Inertial Sea Wave Energy Converter from Mediterranean Sea to Ocean - Design Optimization

Science.gov (United States)

Calleri, Marco

Optimization of the number of gyroscopes and flywheel rotational speed of a Wave Energy Converter able to produce 725 kW as the nominal power, in the chosen installation site, respecting some imposed constraints and some dimensions from the previous design, by minimizing the cost of the device and the bearing power losses, through the minimization of the LCOE of the device.
Optimum Performance-Based Seismic Design Using a Hybrid Optimization Algorithm

Directory of Open Access Journals (Sweden)

S. Talatahari

2014-01-01

Full Text Available A hybrid optimization method is presented to optimum seismic design of steel frames considering four performance levels. These performance levels are considered to determine the optimum design of structures to reduce the structural cost. A pushover analysis of steel building frameworks subject to equivalent-static earthquake loading is utilized. The algorithm is based on the concepts of the charged system search in which each agent is affected by local and global best positions stored in the charged memory considering the governing laws of electrical physics. Comparison of the results of the hybrid algorithm with those of other metaheuristic algorithms shows the efficiency of the hybrid algorithm.
Two-stage collaborative global optimization design model of the CHPG microgrid

Science.gov (United States)

Liao, Qingfen; Xu, Yeyan; Tang, Fei; Peng, Sicheng; Yang, Zheng

2017-06-01

With the continuous developing of technology and reducing of investment costs, renewable energy proportion in the power grid is becoming higher and higher because of the clean and environmental characteristics, which may need more larger-capacity energy storage devices, increasing the cost. A two-stage collaborative global optimization design model of the combined-heat-power-and-gas (abbreviated as CHPG) microgrid is proposed in this paper, to minimize the cost by using virtual storage without extending the existing storage system. P2G technology is used as virtual multi-energy storage in CHPG, which can coordinate the operation of electric energy network and natural gas network at the same time. Demand response is also one kind of good virtual storage, including economic guide for the DGs and heat pumps in demand side and priority scheduling of controllable loads. Two kinds of storage will coordinate to smooth the high-frequency fluctuations and low-frequency fluctuations of renewable energy respectively, and achieve a lower-cost operation scheme simultaneously. Finally, the feasibility and superiority of proposed design model is proved in a simulation of a CHPG microgrid.
An Integrated Modeling Approach to Evaluate and Optimize Data Center Sustainability, Dependability and Cost

Directory of Open Access Journals (Sweden)

Gustavo Callou

2014-01-01

Full Text Available Data centers have evolved dramatically in recent years, due to the advent of social networking services, e-commerce and cloud computing. The conflicting requirements are the high availability levels demanded against the low sustainability impact and cost values. The approaches that evaluate and optimize these requirements are essential to support designers of data center architectures. Our work aims to propose an integrated approach to estimate and optimize these issues with the support of the developed environment, Mercury. Mercury is a tool for dependability, performance and energy flow evaluation. The tool supports reliability block diagrams (RBD, stochastic Petri nets (SPNs, continuous-time Markov chains (CTMC and energy flow (EFM models. The EFM verifies the energy flow on data center architectures, taking into account the energy efficiency and power capacity that each device can provide (assuming power systems or extract (considering cooling components. The EFM also estimates the sustainability impact and cost issues of data center architectures. Additionally, a methodology is also considered to support the modeling, evaluation and optimization processes. Two case studies are presented to illustrate the adopted methodology on data center power systems.
On simultaneous shape and orientational design for eigenfrequency optimization

DEFF Research Database (Denmark)

Pedersen, Niels Leergaard

2007-01-01

Plates with an internal hole of fixed area are designed in order to maximize the performance with respect to eigenfrequencies. The optimization is performed by simultaneous shape, material, and orientational design. The shape of the hole is designed, and the material design is the design of an or......Plates with an internal hole of fixed area are designed in order to maximize the performance with respect to eigenfrequencies. The optimization is performed by simultaneous shape, material, and orientational design. The shape of the hole is designed, and the material design is the design...... of an orthotropic material that can be considered as a fiber-net within each finite element. This fiber-net is optimally oriented in the individual elements of the finite element discretization. The optimizations are performed using the finite element method for analysis, and the optimization approach is a two......-step method. In the first step, we find the best design on the basis of a recursive optimization procedure based on optimality criteria. In the second step, mathematical programming and sensitivity analysis are applied to find the final optimized design....
MEMS resonant load cells for micro-mechanical test frames: feasibility study and optimal design

Science.gov (United States)

Torrents, A.; Azgin, K.; Godfrey, S. W.; Topalli, E. S.; Akin, T.; Valdevit, L.

2010-12-01

This paper presents the design, optimization and manufacturing of a novel micro-fabricated load cell based on a double-ended tuning fork. The device geometry and operating voltages are optimized for maximum force resolution and range, subject to a number of manufacturing and electromechanical constraints. All optimizations are enabled by analytical modeling (verified by selected finite elements analyses) coupled with an efficient C++ code based on the particle swarm optimization algorithm. This assessment indicates that force resolutions of ~0.5-10 nN are feasible in vacuum (~1-50 mTorr), with force ranges as large as 1 N. Importantly, the optimal design for vacuum operation is independent of the desired range, ensuring versatility. Experimental verifications on a sub-optimal device fabricated using silicon-on-glass technology demonstrate a resolution of ~23 nN at a vacuum level of ~50 mTorr. The device demonstrated in this article will be integrated in a hybrid micro-mechanical test frame for unprecedented combinations of force resolution and range, displacement resolution and range, optical (or SEM) access to the sample, versatility and cost.
Optimization model for the design of distributed wastewater treatment networks

Directory of Open Access Journals (Sweden)

Ibrić Nidret

2012-01-01

Full Text Available In this paper we address the synthesis problem of distributed wastewater networks using mathematical programming approach based on the superstructure optimization. We present a generalized superstructure and optimization model for the design of the distributed wastewater treatment networks. The superstructure includes splitters, treatment units, mixers, with all feasible interconnections including water recirculation. Based on the superstructure the optimization model is presented. The optimization model is given as a nonlinear programming (NLP problem where the objective function can be defined to minimize the total amount of wastewater treated in treatment operations or to minimize the total treatment costs. The NLP model is extended to a mixed integer nonlinear programming (MINLP problem where binary variables are used for the selection of the wastewater treatment technologies. The bounds for all flowrates and concentrations in the wastewater network are specified as general equations. The proposed models are solved using the global optimization solvers (BARON and LINDOGlobal. The application of the proposed models is illustrated on the two wastewater network problems of different complexity. First one is formulated as the NLP and the second one as the MINLP. For the second one the parametric and structural optimization is performed at the same time where optimal flowrates, concentrations as well as optimal technologies for the wastewater treatment are selected. Using the proposed model both problems are solved to global optimality.
Design and Optimization of a Turbine Intake Structure

Directory of Open Access Journals (Sweden)

P. Fošumpaur

2005-01-01

Full Text Available The appropriate design of the turbine intake structure of a hydropower plant is based on assumptions about its suitable function, and the design will increase the total efficiency of operation. This paper deals with optimal design of the turbine structure of run-of-river hydropower plants. The study focuses mainly on optimization of the hydropower plant location with respect to the original river banks, and on the optimal design of a separating pier between the weir and the power plant. The optimal design of the turbine intake was determined with the use of 2-D mathematical modelling. A case study is performed for the optimal design of a turbine intake structure on the Nemen river in Belarus.
Energy optimization of crude oil distillation using different designs of pre-flash drums

International Nuclear Information System (INIS)

Al-Mayyahi, Mohmmad A.; Hoadley, Andrew F.A.; Rangaiah, G.P.

2014-01-01

The Crude Distillation Unit (CDU) is among the major CO 2 emitters in any petroleum refinery. In view of the simultaneous increase in the energy cost and environmental concerns, there is strong motivation to analyse alternative methods to improve the energy efficiency and consequently, to minimize CO 2 emissions from conventional crude distillation. Crude pre-flashing is among promising techniques for minimizing the heating energy requirements of the CDU. However, this might be at the cost of product yield and/or throughput. This paper investigates the effects of using different pre-flash designs on the energy efficiency and associated CO 2 emissions of the CDU. The resulting optimal solutions are presented and their significant features are discussed. - Highlights: • Single and multiple pre-flash designs of the crude distillation unit are studied. • The trade-off between CO 2 emissions and the residue yield has been investigated. • Multi-objective optimization was used to find the trade-off solutions. • Introducing crude pre-flashing reduces the total CO 2 emissions. • Optimum vapour feed location has been investigated
Economic Optimal HVAC Design for Hybrid GEOTABS Buildings and CO2 Emissions Analysis

Directory of Open Access Journals (Sweden)

Damien Picard

2018-02-01

Full Text Available In the early design phase of a building, the task of the Heating, Ventilation and Air Conditioning (HVAC engineer is to propose an appropriate HVAC system for a given building. This system should provide thermal comfort to the building occupants at all time, meet the building owner’s specific requirements, and have minimal investment, running, maintenance and replacement costs (i.e., the total cost and energy use or environmental impact. Calculating these different aspects is highly time-consuming and the HVAC engineer will therefore only be able to compare a (very limited number of alternatives leading to suboptimal designs. This study presents therefore a Python tool that automates the generation of all possible scenarios for given thermal power profiles and energy load and a given database of HVAC components. The tool sizes each scenario properly, computes its present total cost (PC and the total CO 2 emissions associated with the building energy use. Finally, the different scenarios can be searched and classified to pick the most appropriate scenario. The tool uses static calculations based on standards, manufacturer data and basic assumptions similar to those made by engineers in the early design phase. The current version of the tool is further focused on hybrid GEOTABS building, which combines a GEOthermal heat pump with a Thermally Activated System (TABS. It should further be noted that the tool optimizes the HVAC system but not the building envelope, while, ideally, both should be simultaneously optimized.
Optimal Spatial Design of Capacity and Quantity of Rainwater Harvesting Systems for Urban Flood Mitigation

Directory of Open Access Journals (Sweden)

Chien-Lin Huang

2015-09-01

Full Text Available This study adopts rainwater harvesting systems (RWHS into a stormwater runoff management model (SWMM for the spatial design of capacities and quantities of rain barrel for urban flood mitigation. A simulation-optimization model is proposed for effectively identifying the optimal design. First of all, we particularly classified the characteristic zonal subregions for spatial design by using fuzzy C-means clustering with the investigated data of urban roof, land use and drainage system. In the simulation method, a series of regular spatial arrangements specification are designed by using statistical quartiles analysis for rooftop area and rainfall frequency analysis; accordingly, the corresponding reduced flooding circumstances can be simulated by SWMM. Moreover, the most effective solution for the simulation method is identified from the calculated net benefit, which is equivalent to the subtraction of the facility cost from the decreased inundation loss. It serves as the initially identified solution for the optimization model. In the optimization method, backpropagation neural network (BPNN are first applied for developing a water level simulation model of urban drainage systems to substitute for SWMM to conform to newly considered interdisciplinary multi-objective optimization model, and a tabu search-based algorithm is used with the embedded BPNN-based SWMM to optimize the planning solution. The developed method is applied to the Zhong-He District, Taiwan. Results demonstrate that the application of tabu search and the BPNN-based simulation model into the optimization model can effectively, accurately and fast search optimal design considering economic net benefit. Furthermore, the optimized spatial rain barrel design could reduce 72% of inundation losses according to the simulated flood events.
LMI–based robust controller design approach in aircraft multidisciplinary design optimization problem

Directory of Open Access Journals (Sweden)

Qinghua Zeng

2015-07-01

Full Text Available This article proposes a linear matrix inequality–based robust controller design approach to implement the synchronous design of aircraft control discipline and other disciplines, in which the variation in design parameters is treated as equivalent perturbations. Considering the complicated mapping relationships between the coefficient arrays of aircraft motion model and the aircraft design parameters, the robust controller designed is directly based on the variation in these coefficient arrays so conservative that the multidisciplinary design optimization problem would be too difficult to solve, or even if there is a solution, the robustness of design result is generally poor. Therefore, this article derives the uncertainty model of disciplinary design parameters based on response surface approximation, converts the design problem of the robust controller into a problem of solving a standard linear matrix inequality, and theoretically gives a less conservative design method of the robust controller which is based on the variation in design parameters. Furthermore, the concurrent subspace approach is applied to the multidisciplinary system with this kind of robust controller in the design loop. A multidisciplinary design optimization of a tailless aircraft as example is shown that control discipline can be synchronous optimal design with other discipline, especially this method will greatly reduce the calculated amount of multidisciplinary design optimization and make multidisciplinary design optimization results more robustness of flight performance.
Design of an integrated forward and reverse logistics network optimi-zation model for commercial goods management

Directory of Open Access Journals (Sweden)

Eva Ponce-Cueto

2015-01-01

Full Text Available In this study, an optimization model is formulated for designing an integrated forward and reverse logistics network in the consumer goods industry. The resultant model is a mixed-integer linear programming model (MILP. Its purpose is to minimize the total costs of the closed-loop supply chain network. It is important to note that the design of the logistics network may involve a trade-off between the total costs and the optimality in commercial goods management. The model comprises a discrete set as potential locations of unlimited capacity warehouses and fixed locations of customers’ zones. It provides decisions related to the facility location and customers’ requirements satisfaction, all of this related with the inventory and shipment decisions of the supply chain. Finally, an application of this model is illustrated by a real-life case in the food and drinks industry. We can conclude that this model can significantly help companies to make decisions about problems associated with logistics network design.
Optimal hybrid renewable energy design in autonomous system using Modified Electric System Cascade Analysis and Homer software

International Nuclear Information System (INIS)

Zahboune, Hassan; Zouggar, Smail; Krajacic, Goran; Varbanov, Petar Sabev; Elhafyani, Mohammed; Ziani, Elmostafa

2016-01-01

Highlights: • New approach to integrate the Pinch Analysis illustrated. • Total annual cost and loss of power supply probability are the objective functions. • The new Hybrid Cascade Table to determine the optimal system design. • The performances of the new method are compared with Homer Pro. - Abstract: In this paper, a method for designing hybrid electricity generation systems is presented. It is based on the Modified Electric System Cascade Analysis method. The Power Pinch analysis is used as a guideline for development of an isolated power supply system, which consists of photovoltaic panels, wind turbines and energy storage units. The design procedure uses a simulation model, developed using MATLAB/SIMULINK and applies the developed algorithms for obtaining an optimal design. A validation of the Modified Electric System Cascade Analysis method is performed by comparing the obtained results with those from the Homer Pro software. The procedure takes as inputs hourly wind speed, solar radiation, demands, as well as cost data, for the generation and storage facilities. It is also applied to minimize the loss of power supply probability and to minimize the number of storage units. The algorithm has been demonstrated with a case study on a site in Oujda city, with daily electrical energy demand of 18.7 kWh, resulting in a combination of photovoltaic panels, wind turbine and batteries at minimal cost. The results from the Modified Electric System Cascade Analysis and HOMER Pro show that both tools successfully identified the optimal solution with difference of 0.04% in produced energy, 5.4% in potential excess of electricity and 0.07% in the cost of the energy.
A Review of Design Optimization Methods for Electrical Machines

Directory of Open Access Journals (Sweden)

Gang Lei

2017-11-01

Full Text Available Electrical machines are the hearts of many appliances, industrial equipment and systems. In the context of global sustainability, they must fulfill various requirements, not only physically and technologically but also environmentally. Therefore, their design optimization process becomes more and more complex as more engineering disciplines/domains and constraints are involved, such as electromagnetics, structural mechanics and heat transfer. This paper aims to present a review of the design optimization methods for electrical machines, including design analysis methods and models, optimization models, algorithms and methods/strategies. Several efficient optimization methods/strategies are highlighted with comments, including surrogate-model based and multi-level optimization methods. In addition, two promising and challenging topics in both academic and industrial communities are discussed, and two novel optimization methods are introduced for advanced design optimization of electrical machines. First, a system-level design optimization method is introduced for the development of advanced electric drive systems. Second, a robust design optimization method based on the design for six-sigma technique is introduced for high-quality manufacturing of electrical machines in production. Meanwhile, a proposal is presented for the development of a robust design optimization service based on industrial big data and cloud computing services. Finally, five future directions are proposed, including smart design optimization method for future intelligent design and production of electrical machines.
A system-level cost-of-energy wind farm layout optimization with landowner modeling

International Nuclear Information System (INIS)

Chen, Le; MacDonald, Erin

2014-01-01

Highlights: • We model the role of landowners in determining the success of wind projects. • A cost-of-energy (COE) model with realistic landowner remittances is developed. • These models are included in a system-level wind farm layout optimization. • Basic verification indicates the optimal COE is in-line with real-world data. • Land plots crucial to a project’s success can be identified with the approach. - Abstract: This work applies an enhanced levelized wind farm cost model, including landowner remittance fees, to determine optimal turbine placements under three landowner participation scenarios and two land-plot shapes. Instead of assuming a continuous piece of land is available for the wind farm construction, as in most layout optimizations, the problem formulation represents landowner participation scenarios as a binary string variable, along with the number of turbines. The cost parameters and model are a combination of models from the National Renewable Energy Laboratory (NREL), Lawrence Berkeley National Laboratory, and Windustry. The system-level cost-of-energy (COE) optimization model is also tested under two land-plot shapes: equally-sized square land plots and unequal rectangle land plots. The optimal COEs results are compared to actual COE data and found to be realistic. The results show that landowner remittances account for approximately 10% of farm operating costs across all cases. Irregular land-plot shapes are easily handled by the model. We find that larger land plots do not necessarily receive higher remittance fees. The model can help site developers identify the most crucial land plots for project success and the optimal positions of turbines, with realistic estimates of costs and profitability
A method for economic optimization of energy performance and indoor environment in the design of sustainable buildings

DEFF Research Database (Denmark)

Hansen, Sanne; Vanhoutteghem, Lies

2012-01-01

that takes into account the indoor thermal environment. By use of the criterion of cost of conserved energy implemented in a Microsoft Excel sheet, a cost optimal design according to a targeted energy frame can be found. The resulting indoor thermal environment is then evaluated based on parametric analysis...... that an economic design solution with good indoor environment can be identified. The example also shows that in order to ensure that buildings have low energy consumption, at minimum extra cost, more appropriate products and solutions will have to become available on the market at a competitive price....
Optimization of shell-and-tube heat exchangers conforming to TEMA standards with designs motivated by constructal theory

International Nuclear Information System (INIS)

Yang, Jie; Fan, Aiwu; Liu, Wei; Jacobi, Anthony M.

2014-01-01

Highlights: • A design method of heat exchangers motivated by constructal theory is proposed. • A genetic algorithm is applied and the TEMA standards are rigorously followed. • Three cases are studied to illustrate the advantage of the proposed design method. • The design method will reduce the total cost compared to two other methods. - Abstract: A modified optimization design approach motivated by constructal theory is proposed for shell-and-tube heat exchangers in the present paper. In this method, a shell-and-tube heat exchanger is divided into several in-series heat exchangers. The Tubular Exchanger Manufacturers Association (TEMA) standards are rigorously followed for all design parameters. The total cost of the whole shell-and-tube heat exchanger is set as the objective function, including the investment cost for initial manufacture and the operational cost involving the power consumption to overcome the frictional pressure loss. A genetic algorithm is applied to minimize the cost function by adjusting parameters such as the tube and shell diameters, tube length and tube arrangement. Three cases are studied which indicate that the modified design approach can significantly reduce the total cost compared to the original design method and traditional genetic algorithm design method
Drying of water based foundry coatings: Innovative test, process design and optimization methods

DEFF Research Database (Denmark)

Di Muoio, Giovanni Luca; Johansen, Bjørn Budolph

on real industrial cases. These tools have been developed in order to simulate and optimize the drying process and reduce drying time and power consumption as well as production process design time and cost of expensive drying equipment. Results show that test methods from other industries can be used...... capacity goals there is a need to understand how to design, control and optimize drying processes. The main focus of this project was on the critical parameters and properties to be controlled in production in order to achieve a stable and predictable drying process. We propose for each of these parameters...... of Denmark with the overall aim to optimize the drying process of water based foundry coatings. Drying of foundry coatings is a relatively new process in the foundry industry that followed the introduction of water as a solvent. In order to avoid moisture related quality problems and reach production...

Process design and simulation for optimizing the oxygen concentration in Czochralski-grown single-crystal silicon

International Nuclear Information System (INIS)

Jung, Y. J.; Kim, W. K.; Jung, J. H.

2014-01-01

The highest-concentration impurity in a single-crystal silicon ingot is oxygen, which infiltrates the ingot during growth stage. This oxygen adversely affects the wafer is quality. This study was aimed at finding an optimal design for the Czochralski (Cz) process to enable high-quality and low cost (by reducing power consumption) wafer production by controlling the oxygen concentration in the silicon ingots. In the Cz process, the characteristics of silicon ingots during crystallization are greatly influenced by the design and the configuration of the hot zone, and by crystallization rate. In order to identify process conditions for obtaining an optimal oxygen concentration of 11 - 13 ppma (required for industrial-grade ingots), designed two shield shapes for the hot zone. Furthermore, oxygen concentrations corresponding to these two shapes were compared by evaluating each shape at five different production speeds. In addition, simulations were performed to identify the optimal shield design for industrial applications.
Process design and simulation for optimizing the oxygen concentration in Czochralski-grown single-crystal silicon

Energy Technology Data Exchange (ETDEWEB)

Jung, Y. J.; Kim, W. K.; Jung, J. H. [Yeungnam University, Gyeongsan (Korea, Republic of)

2014-08-15

The highest-concentration impurity in a single-crystal silicon ingot is oxygen, which infiltrates the ingot during growth stage. This oxygen adversely affects the wafer is quality. This study was aimed at finding an optimal design for the Czochralski (Cz) process to enable high-quality and low cost (by reducing power consumption) wafer production by controlling the oxygen concentration in the silicon ingots. In the Cz process, the characteristics of silicon ingots during crystallization are greatly influenced by the design and the configuration of the hot zone, and by crystallization rate. In order to identify process conditions for obtaining an optimal oxygen concentration of 11 - 13 ppma (required for industrial-grade ingots), designed two shield shapes for the hot zone. Furthermore, oxygen concentrations corresponding to these two shapes were compared by evaluating each shape at five different production speeds. In addition, simulations were performed to identify the optimal shield design for industrial applications.
Optimization and Design for a Radial Flux Permanent Magnet Motor for Electric Vehicle

Directory of Open Access Journals (Sweden)

R. NEJI

2005-12-01

Full Text Available This paper deals with the design and the optimization of permanent magnet motors. Five trapezoidal and four sinusoidal wave-form motor configurations were investigated and analyzed. Firstly, an analytic sizing was led along with an electromagnetic modeling by finite element method. Secondly, a finer modeling with finite element was realized dynamically. The optimization of the traction motor cost under constraints by the genetic algorithms method has allowed choosing a motor with sinusoidal wave-form, five pole pairs and twelve slots. This motor belongs to the second configuration with sinusoidal wave-form.
New Methodology for Optimal Flight Control Using Differential Evolution Algorithms Applied on the Cessna Citation X Business Aircraft – Part 1. Design and Optimization

Directory of Open Access Journals (Sweden)

Yamina BOUGHARI

2017-06-01

Full Text Available Setting the appropriate controllers for aircraft stability and control augmentation systems are complicated and time consuming tasks. As in the Linear Quadratic Regulator method gains are found by selecting the appropriate weights or as in the Proportional Integrator Derivative control by tuning gains. A trial and error process is usually employed for the determination of weighting matrices, which is normally a time consuming procedure. Flight Control Law were optimized and designed by combining the Deferential Evolution algorithm, the Linear Quadratic Regulator method, and the Proportional Integral controller. The optimal controllers were used to reach satisfactory aircraft’s dynamic and safe flight operations with respect to the augmentation systems’ handling qualities, and design requirements for different flight conditions. Furthermore the design and the clearance of the controllers over the flight envelope were automated using a Graphical User Interface, which offers to the designer, the flexibility to change the design requirements. In the aim of reducing time, and costs of the Flight Control Law design, one fitness function has been used for both optimizations, and using design requirements as constraints. Consequently the Flight Control Law design process complexity was reduced by using the meta-heuristic algorithm.
How to optimize hydrogen plant designs

Energy Technology Data Exchange (ETDEWEB)

van Weenen, W F; Tielrooy, J

1983-01-01

In a typical hydrogen plant of the type which will be discussed, methane or higher hydrocarbons are reformed with steam in a steam hydrocarbon reformer operating at a pressure of 250 to 400 psig, a temperature of 1500 to 1600/sup 0/F, and with a ratio of steam to carbon in the feed of about 3.0. Following the reformer and cooling, there is a single stage of high temperature carbon monoxide shift conversion. Optionally, after further cooling, this may be followed by a second stage of carbon monoxide shift conversion operating at a lower temperature to obtain a more favourable equilibrium; this is called low temperature shift conversion. After cooling to ambient temperature, and separation of the condensate, the gas is passed through a Pressure Swing Adsorption (PSA)l unit which removes all the impurities along with a small amount of hydrogen. The waste gas from the PSA unit containing all the impurities is used as fuel to the reformer. Heat is recovered from the reformer flue gas, reformer product, high temperature shift converter product and low temperature shift converter product. This paper discusses some of the process variables and design variables which must be considered in arriving at an optimized design. Seven different flow schemes are discussed in the light of the objectives they are designed for. The seven schemes and their objectives are: Flow Scheme 1 - lowest first cost; moderate efficiency, Flow Scheme 2 - high efficiency, low cost; Flow Scheme 3 - low feed plus fuel, moderately high efficiency; Flow Scheme 4 - lowest feed plus fuel; Flow Scheme 5 - lowest feed, low fuel; Flow Scheme 6 -lowest feed, highest efficiency; and Flow Scheme 7 - lowest feed plus fuel, export electric power instead of export electric power instead of export steam. 15 figures, 1 table.
How to use an optimization-based method capable of balancing safety, reliability, and weight in an aircraft design process

International Nuclear Information System (INIS)

Johansson, Cristina; Derelov, Micael; Olvander, Johan

2017-01-01

In order to help decision-makers in the early design phase to improve and make more cost-efficient system safety and reliability baselines of aircraft design concepts, a method (Multi-objective Optimization for Safety and Reliability Trade-off) that is able to handle trade-offs such as system safety, system reliability, and other characteristics, for instance weight and cost, is used. Multi-objective Optimization for Safety and Reliability Trade-off has been developed and implemented at SAAB Aeronautics. The aim of this paper is to demonstrate how the implemented method might work to aid the selection of optimal design alternatives. The method is a three-step method: step 1 involves the modelling of each considered target, step 2 is optimization, and step 3 is the visualization and selection of results (results processing). The analysis is performed within Architecture Design and Preliminary Design steps, according to the company's Product Development Process. The lessons learned regarding the use of the implemented trade-off method in the three cases are presented. The results are a handful of solutions, a basis to aid in the selection of a design alternative. While the implementation of the trade-off method is performed for companies, there is nothing to prevent adapting this method, with minimal modifications, for use in other industrial applications
How to use an optimization-based method capable of balancing safety, reliability, and weight in an aircraft design process

Energy Technology Data Exchange (ETDEWEB)

Johansson, Cristina [Mendeley, Broderna Ugglasgatan, Linkoping (Sweden); Derelov, Micael; Olvander, Johan [Linkoping University, IEI, Dept. of Machine Design, Linkoping (Sweden)

2017-03-15

In order to help decision-makers in the early design phase to improve and make more cost-efficient system safety and reliability baselines of aircraft design concepts, a method (Multi-objective Optimization for Safety and Reliability Trade-off) that is able to handle trade-offs such as system safety, system reliability, and other characteristics, for instance weight and cost, is used. Multi-objective Optimization for Safety and Reliability Trade-off has been developed and implemented at SAAB Aeronautics. The aim of this paper is to demonstrate how the implemented method might work to aid the selection of optimal design alternatives. The method is a three-step method: step 1 involves the modelling of each considered target, step 2 is optimization, and step 3 is the visualization and selection of results (results processing). The analysis is performed within Architecture Design and Preliminary Design steps, according to the company's Product Development Process. The lessons learned regarding the use of the implemented trade-off method in the three cases are presented. The results are a handful of solutions, a basis to aid in the selection of a design alternative. While the implementation of the trade-off method is performed for companies, there is nothing to prevent adapting this method, with minimal modifications, for use in other industrial applications.
Reliability optimization for series systems under uncertain component failure rates in the design phase

NARCIS (Netherlands)

Ge, Q.; Peng, H.; van Houtum, G.J.J.A.N.; Adan, I.J.B.F.

2018-01-01

We develop an optimization model to determine the reliability design of critical components in a serial system. The system is under a service contract, and a penalty cost has to be paid by the OEM when the total system down time exceeds a predetermined level, which complicates the evaluation of the
Multi-objective optimization of design and testing of safety instrumented systems with MooN voting architectures using a genetic algorithm

International Nuclear Information System (INIS)

Torres-Echeverría, A.C.; Martorell, S.; Thompson, H.A.

2012-01-01

This paper presents the optimization of design and test policies of safety instrumented systems using MooN voting redundancies by a multi-objective genetic algorithm. The objectives to optimize are the Average Probability of Dangerous Failure on Demand, which represents the system safety integrity, the Spurious Trip Rate and the Lifecycle Cost. In this way safety, reliability and cost are included. This is done by using novel models of time-dependent probability of failure on demand and spurious trip rate, recently published by the authors. These models are capable of delivering the level of modeling detail required by the standard IEC 61508. Modeling includes common cause failure and diagnostic coverage. The Probability of Failure on Demand model also permits to quantify results with changing testing strategies. The optimization is performed using the multi-objective Genetic Algorithm NSGA-II. This allows weighting of the trade-offs between the three objectives and, thus, implementation of safety systems that keep a good balance between safety, reliability and cost. The complete methodology is applied to two separate case studies, one for optimization of system design with redundancy allocation and component selection and another for optimization of testing policies. Both optimization cases are performed for both systems with MooN redundancies and systems with only parallel redundancies. Their results are compared, demonstrating how introducing MooN architectures presents a significant improvement for the optimization process.
Optimal Design of Pumped Pipeline Systems Using Genetic Algorithm and Mathematical Optimization

Directory of Open Access Journals (Sweden)

Mohammadhadi Afshar

2007-12-01

Full Text Available In recent years, much attention has been paid to the optimal design of pipeline systems. In this study, the problem of pipeline system optimal design has been solved through genetic algorithm and mathematical optimization. Pipe diameters and their thicknesses are considered as decision variables to be designed in a manner that water column separation and excessive pressures are avoided in the event of pump failure. Capabilities of the genetic algorithm and the mathematical programming method are compared for the problem under consideration. For simulation of transient streams, explicit characteristic method is used in which devices such as pumps are defined as boundary conditions of the equations defining the hydraulic behavior of pipe segments. The problem of optimal design of pipeline systems is a constrained problem which is converted to an unconstrained optimization problem using an external penalty function approach. The efficiency of the proposed approaches is verified in one example and the results are presented.
Gasification Plant Cost and Performance Optimization

Energy Technology Data Exchange (ETDEWEB)

Samuel Tam; Alan Nizamoff; Sheldon Kramer; Scott Olson; Francis Lau; Mike Roberts; David Stopek; Robert Zabransky; Jeffrey Hoffmann; Erik Shuster; Nelson Zhan

2005-05-01

As part of an ongoing effort of the U.S. Department of Energy (DOE) to investigate the feasibility of gasification on a broader level, Nexant, Inc. was contracted to perform a comprehensive study to provide a set of gasification alternatives for consideration by the DOE. Nexant completed the first two tasks (Tasks 1 and 2) of the ''Gasification Plant Cost and Performance Optimization Study'' for the DOE's National Energy Technology Laboratory (NETL) in 2003. These tasks evaluated the use of the E-GAS{trademark} gasification technology (now owned by ConocoPhillips) for the production of power either alone or with polygeneration of industrial grade steam, fuel gas, hydrocarbon liquids, or hydrogen. NETL expanded this effort in Task 3 to evaluate Gas Technology Institute's (GTI) fluidized bed U-GAS{reg_sign} gasifier. The Task 3 study had three main objectives. The first was to examine the application of the gasifier at an industrial application in upstate New York using a Southeastern Ohio coal. The second was to investigate the GTI gasifier in a stand-alone lignite-fueled IGCC power plant application, sited in North Dakota. The final goal was to train NETL personnel in the methods of process design and systems analysis. These objectives were divided into five subtasks. Subtasks 3.2 through 3.4 covered the technical analyses for the different design cases. Subtask 3.1 covered management activities, and Subtask 3.5 covered reporting. Conceptual designs were developed for several coal gasification facilities based on the fluidized bed U-GAS{reg_sign} gasifier. Subtask 3.2 developed two base case designs for industrial combined heat and power facilities using Southeastern Ohio coal that will be located at an upstate New York location. One base case design used an air-blown gasifier, and the other used an oxygen-blown gasifier in order to evaluate their relative economics. Subtask 3.3 developed an advanced design for an air
Robust Guaranteed Cost Observer Design for Singular Markovian Jump Time-Delay Systems with Generally Incomplete Transition Probability

Directory of Open Access Journals (Sweden)

Yanbo Li

2014-01-01

Full Text Available This paper is devoted to the investigation of the design of robust guaranteed cost observer for a class of linear singular Markovian jump time-delay systems with generally incomplete transition probability. In this singular model, each transition rate can be completely unknown or only its estimate value is known. Based on stability theory of stochastic differential equations and linear matrix inequality (LMI technique, we design an observer to ensure that, for all uncertainties, the resulting augmented system is regular, impulse free, and robust stochastically stable with the proposed guaranteed cost performance. Finally, a convex optimization problem with LMI constraints is formulated to design the suboptimal guaranteed cost filters for linear singular Markovian jump time-delay systems with generally incomplete transition probability.
Design, Development and Optimization of a Low Cost System for Digital Industrial Radiology

International Nuclear Information System (INIS)

2013-01-01

regional training courses in which participants from Member States were given training in DIR techniques. The IAEA also supported establishing facilities for DIR techniques in some Member States. Realizing the need for easy construction and assembly of a low cost, more economically viable system for DIR technology, the IAEA conducted a coordinated research project (CRP) during 2007-2010 for research and development in the field of digital radiology, with the participation of 12 Member State laboratories. The current publication on design, development and optimization of a low cost DIR system is based on the findings of this CRP and inputs from other experts. The report provides guidelines to enable interested Member States to build their own DIR system in an affordable manner
Choosing the Right Technologies – A Model for Cost Optimized Design of a Renewable Supply System for Residential Zero Energy Buildings

DEFF Research Database (Denmark)

Milan, Christian

, individual performance models are defined. For small scale residential systems the hot water tank is one of the main components, connecting supply and demand side and acting as a buffer during mismatch periods. For this reason, the developed hot water tank model is rather detailed accounting for three...... different temperature layers, two different supply and demand loops as well as individual heat losses. It is presented at the end of the technology chapter. Subsequently, the methodology is validated by investigating the output with one single technology at a time and thus the individual performance models......This work presents a methodology to identify and investigate the cost optimal design of supply systems for Low and Net Zero Energy Buildings with the focus on residential single family houses. A preliminary analysis investigating relevant literature and existing computer tools resulted...
Robust design optimization method for centrifugal impellers under surface roughness uncertainties due to blade fouling

Science.gov (United States)

Ju, Yaping; Zhang, Chuhua

2016-03-01

Blade fouling has been proved to be a great threat to compressor performance in operating stage. The current researches on fouling-induced performance degradations of centrifugal compressors are based mainly on simplified roughness models without taking into account the realistic factors such as spatial non-uniformity and randomness of the fouling-induced surface roughness. Moreover, little attention has been paid to the robust design optimization of centrifugal compressor impellers with considerations of blade fouling. In this paper, a multi-objective robust design optimization method is developed for centrifugal impellers under surface roughness uncertainties due to blade fouling. A three-dimensional surface roughness map is proposed to describe the nonuniformity and randomness of realistic fouling accumulations on blades. To lower computational cost in robust design optimization, the support vector regression (SVR) metamodel is combined with the Monte Carlo simulation (MCS) method to conduct the uncertainty analysis of fouled impeller performance. The analyzed results show that the critical fouled region associated with impeller performance degradations lies at the leading edge of blade tip. The SVR metamodel has been proved to be an efficient and accurate means in the detection of impeller performance variations caused by roughness uncertainties. After design optimization, the robust optimal design is found to be more efficient and less sensitive to fouling uncertainties while maintaining good impeller performance in the clean condition. This research proposes a systematic design optimization method for centrifugal compressors with considerations of blade fouling, providing a practical guidance to the design of advanced centrifugal compressors.
OPTIMIZATION METHOD AND SOFTWARE FOR FUEL COST REDUCTION IN CASE OF ROAD TRANSPORT ACTIVITY

Directory of Open Access Journals (Sweden)

György Kovács

2017-06-01

Full Text Available The transport activity is one of the most expensive processes in the supply chain and the fuel cost is the highest cost among the cost components of transportation. The goal of the research is to optimize the transport costs in case of a given transport task both by the selecting the optimal petrol station and by determining the optimal amount of the refilled fuel. Recently, in practice, these two decisions have not been made centrally at the forwarding company, but they depend on the individual decision of the driver. The aim of this study is to elaborate a precise and reliable mathematical method for selecting the optimal refuelling stations and determining the optimal amount of the refilled fuel to fulfil the transport demands. Based on the elaborated model, new decision-supporting software is developed for the economical fulfilment of transport trips.
A unified modeling approach for physical experiment design and optimization in laser driven inertial confinement fusion

Energy Technology Data Exchange (ETDEWEB)

Li, Haiyan [Mechatronics Engineering School of Guangdong University of Technology, Guangzhou 510006 (China); Huang, Yunbao, E-mail: Huangyblhy@gmail.com [Mechatronics Engineering School of Guangdong University of Technology, Guangzhou 510006 (China); Jiang, Shaoen, E-mail: Jiangshn@vip.sina.com [Laser Fusion Research Center, China Academy of Engineering Physics, Mianyang 621900 (China); Jing, Longfei, E-mail: scmyking_2008@163.com [Laser Fusion Research Center, China Academy of Engineering Physics, Mianyang 621900 (China); Tianxuan, Huang; Ding, Yongkun [Laser Fusion Research Center, China Academy of Engineering Physics, Mianyang 621900 (China)

2015-11-15

Highlights: • A unified modeling approach for physical experiment design is presented. • Any laser facility can be flexibly defined and included with two scripts. • Complex targets and laser beams can be parametrically modeled for optimization. • Automatically mapping of laser beam energy facilitates targets shape optimization. - Abstract: Physical experiment design and optimization is very essential for laser driven inertial confinement fusion due to the high cost of each shot. However, only limited experiments with simple structure or shape on several laser facilities can be designed and evaluated in available codes, and targets are usually defined by programming, which may lead to it difficult for complex shape target design and optimization on arbitrary laser facilities. A unified modeling approach for physical experiment design and optimization on any laser facilities is presented in this paper. Its core idea includes: (1) any laser facility can be flexibly defined and included with two scripts, (2) complex shape targets and laser beams can be parametrically modeled based on features, (3) an automatically mapping scheme of laser beam energy onto discrete mesh elements of targets enable targets or laser beams be optimized without any additional interactive modeling or programming, and (4) significant computation algorithms are additionally presented to efficiently evaluate radiation symmetry on the target. Finally, examples are demonstrated to validate the significance of such unified modeling approach for physical experiments design and optimization in laser driven inertial confinement fusion.
Design and fabrication of topologically optimized structures;

DEFF Research Database (Denmark)

Feringa, Jelle; Søndergaard, Asbjørn

2012-01-01

Integral structural optimization and fabrication seeks the synthesis of two original approaches; that of topological optimization (TO) and robotic hotwire cutting (HWC) (Mcgee 2011). TO allows for the reduction of up to 70% of the volume of concrete to support a given structure (Sondergaard...... & Dombernowsky 2011). A strength of the method is that it allows to come up with structural designs that lie beyond the grasp of traditional means of design. A design space is a discretized volume, delimiting where the optimization will take place. The number of cells used to discretize the design space thus...
A surrogate based multistage-multilevel optimization procedure for multidisciplinary design optimization

NARCIS (Netherlands)

Yao, W.; Chen, X.; Ouyang, Q.; Van Tooren, M.

2011-01-01

Optimization procedure is one of the key techniques to address the computational and organizational complexities of multidisciplinary design optimization (MDO). Motivated by the idea of synthetically exploiting the advantage of multiple existing optimization procedures and meanwhile complying with
A new multi objective optimization model for designing a green supply chain network under uncertainty

Directory of Open Access Journals (Sweden)

Mohammad Mahdi Saffar

2015-01-01

Full Text Available Recently, researchers have focused on how to minimize the negative effects of industrial activities on environment. Consequently, they work on mathematical models, which minimize the environmental issues as well as optimizing the costs. In the field of supply chain network design, most managers consider economic and environmental issues, simultaneously. This paper introduces a bi-objective supply chain network design, which uses fuzzy programming to obtain the capability of resisting uncertain conditions. The design considers production, recovery, and distribution centers. The advantage of using this model includes the optimal facilities, locating them and assigning the optimal facilities to them. It also chooses the type and the number of technologies, which must be bought. The fuzzy programming converts the multi objective model to an auxiliary crisp model by Jimenez approach and solves it with ε-constraint. For solving large size problems, the Multi Objective Differential Evolutionary algorithm (MODE is applied.

Optimal Spatial Design of Capacity and Quantity of Rainwater Catchment Systems for Urban Flood Mitigation

Science.gov (United States)

Huang, C.; Hsu, N.

2013-12-01

This study imports Low-Impact Development (LID) technology of rainwater catchment systems into a Storm-Water runoff Management Model (SWMM) to design the spatial capacity and quantity of rain barrel for urban flood mitigation. This study proposes a simulation-optimization model for effectively searching the optimal design. In simulation method, we design a series of regular spatial distributions of capacity and quantity of rainwater catchment facilities, and thus the reduced flooding circumstances using a variety of design forms could be simulated by SWMM. Moreover, we further calculate the net benefit that is equal to subtract facility cost from decreasing inundation loss and the best solution of simulation method would be the initial searching solution of the optimization model. In optimizing method, first we apply the outcome of simulation method and Back-Propagation Neural Network (BPNN) for developing a water level simulation model of urban drainage system in order to replace SWMM which the operating is based on a graphical user interface and is hard to combine with optimization model and method. After that we embed the BPNN-based simulation model into the developed optimization model which the objective function is minimizing the negative net benefit. Finally, we establish a tabu search-based algorithm to optimize the planning solution. This study applies the developed method in Zhonghe Dist., Taiwan. Results showed that application of tabu search and BPNN-based simulation model into the optimization model not only can find better solutions than simulation method in 12.75%, but also can resolve the limitations of previous studies. Furthermore, the optimized spatial rain barrel design can reduce 72% of inundation loss according to historical flood events.
Bayesian Optimal Experimental Design Using Multilevel Monte Carlo

KAUST Repository

Ben Issaid, Chaouki

2015-05-12

Experimental design can be vital when experiments are resource-exhaustive and time-consuming. In this work, we carry out experimental design in the Bayesian framework. To measure the amount of information that can be extracted from the data in an experiment, we use the expected information gain as the utility function, which specifically is the expected logarithmic ratio between the posterior and prior distributions. Optimizing this utility function enables us to design experiments that yield the most informative data about the model parameters. One of the major difficulties in evaluating the expected information gain is that it naturally involves nested integration over a possibly high dimensional domain. We use the Multilevel Monte Carlo (MLMC) method to accelerate the computation of the nested high dimensional integral. The advantages are twofold. First, MLMC can significantly reduce the cost of the nested integral for a given tolerance, by using an optimal sample distribution among different sample averages of the inner integrals. Second, the MLMC method imposes fewer assumptions, such as the asymptotic concentration of posterior measures, required for instance by the Laplace approximation (LA). We test the MLMC method using two numerical examples. The first example is the design of sensor deployment for a Darcy flow problem governed by a one-dimensional Poisson equation. We place the sensors in the locations where the pressure is measured, and we model the conductivity field as a piecewise constant random vector with two parameters. The second one is chemical Enhanced Oil Recovery (EOR) core flooding experiment assuming homogeneous permeability. We measure the cumulative oil recovery, from a horizontal core flooded by water, surfactant and polymer, for different injection rates. The model parameters consist of the endpoint relative permeabilities, the residual saturations and the relative permeability exponents for the three phases: water, oil and
Investigations of a Cost-Optimal Zero Energy Balance

DEFF Research Database (Denmark)

Marszal, Anna Joanna; Nørgaard, Jesper; Heiselberg, Per

2012-01-01

The Net Zero Energy Building (Net ZEB) concept is worldwide recognised as a promising solution for decreasing buildings’ energy use. Nevertheless, a consistent definition of the Net ZEB concept is constantly under discussion. One of the points on the Net ZEB agenda is the zero energy balance...... and taken a view point of private building owner to investigate what types of energy uses should be included in the cost-optimal zero energy balance. The analysis is conducted for five renewable energy supply systems and five user profiles with a study case of a multi-storey residential Net ZEB. The results...... have indicated that with current energy prices and technology, a cost-optimal Net ZEB zero energy balance accounts for only the building related energy use. Moreover, with high user related energy use is even more in favour of excluding appliances from the zero energy balance....
Optimization of economic load dispatch of higher order general cost polynomials and its sensitivity using modified particle swarm optimization

International Nuclear Information System (INIS)

Saber, Ahmed Yousuf; Chakraborty, Shantanu; Abdur Razzak, S.M.; Senjyu, Tomonobu

2009-01-01

This paper presents a modified particle swarm optimization (MPSO) for constrained economic load dispatch (ELD) problem. Real cost functions are more complex than conventional second order cost functions when multi-fuel operations, valve-point effects, accurate curve fitting, etc., are considering in deregulated changing market. The proposed modified particle swarm optimization (PSO) consists of problem dependent variable number of promising values (in velocity vector), unit vector and error-iteration dependent step length. It reliably and accurately tracks a continuously changing solution of the complex cost function and no extra concentration/effort is needed for the complex higher order cost polynomials in ELD. Constraint management is incorporated in the modified PSO. The modified PSO has balance between local and global searching abilities, and an appropriate fitness function helps to converge it quickly. To avoid the method to be frozen, stagnated/idle particles are reset. Sensitivity of the higher order cost polynomials is also analyzed visually to realize the importance of the higher order cost polynomials for the optimization of ELD. Finally, benchmark data sets and methods are used to show the effectiveness of the proposed method. (author)
Cost effective radiation risk management in a generic nuclear plant design

International Nuclear Information System (INIS)

Maan, M.A.

1982-11-01

To determine whether any further dose reduction measures are justified, a method appropriate for cost effective radiation risk management has been developed. This new method is based on the radiation detriment optimization measures advocated in the revised (1977) ALARA concept. The methodology includes the determination of available alternatives, and the determination of the variable monetary ceiling on expenditures to reduce the radiological detriment (both occupational and public). The method used to determine the maximum justifiable expenditure for additional reduction of detriment takes into account the economic and social climate, administrative/legal exposure limits, and the actual magnitude of risk. All these factors may vary from country to country. The variable monetary ceiling, sensitive to an actual level of risk, provides a handy measure allowing designers to make a decision whether or not the modification of design is necessary and/or cost effective. This will ensure rationally and consistently that the utilities and their customers (public) get maximum benefit for their safety dollars
Telemanipulator design and optimization software

Science.gov (United States)

Cote, Jean; Pelletier, Michel

1995-12-01

For many years, industrial robots have been used to execute specific repetitive tasks. In those cases, the optimal configuration and location of the manipulator only has to be found once. The optimal configuration or position where often found empirically according to the tasks to be performed. In telemanipulation, the nature of the tasks to be executed is much wider and can be very demanding in terms of dexterity and workspace. The position/orientation of the robot's base could be required to move during the execution of a task. At present, the choice of the initial position of the teleoperator is usually found empirically which can be sufficient in the case of an easy or repetitive task. In the converse situation, the amount of time wasted to move the teleoperator support platform has to be taken into account during the execution of the task. Automatic optimization of the position/orientation of the platform or a better designed robot configuration could minimize these movements and save time. This paper will present two algorithms. The first algorithm is used to optimize the position and orientation of a given manipulator (or manipulators) with respect to the environment on which a task has to be executed. The second algorithm is used to optimize the position or the kinematic configuration of a robot. For this purpose, the tasks to be executed are digitized using a position/orientation measurement system and a compact representation based on special octrees. Given a digitized task, the optimal position or Denavit-Hartenberg configuration of the manipulator can be obtained numerically. Constraints on the robot design can also be taken into account. A graphical interface has been designed to facilitate the use of the two optimization algorithms.
Video-on-demand network design and maintenance using fuzzy optimization.

Science.gov (United States)

Abadpour, Arash; Alfa, Attahiru Sule; Diamond, Jeff

2008-04-01

Video-on-demand (VoD) is the entertainment source that, in the future, will likely overtake regular television in many aspects. Although many companies have deployed working VoD services, some aspects of the VoD should still undergo further improvement in order for it to reach to the foreseen potentials. An important aspect of a VoD system is the underlying network in which it operates. According to the huge number of customers in this network, it should be carefully designed to fulfill certain performance criteria. This process should be capable of finding optimal locations for the nodes of the network as well as determining the content that should be cached in each one. While this problem is categorized in the general group of network optimization problems, its specific characteristics demand a new solution to be sought for it. In this paper, which is inspired by the successful use of fuzzy optimization in similar problems in other fields, a fuzzy objective function that is heuristically shown to minimize the communication cost in a VoD network is derived while also controlling the storage cost. Then, an iterative algorithm is proposed to find a locally optimal solution to the proposed objective function. Capitalizing on the unrepeatable tendency of the proposed algorithm, a heuristic method for picking a good solution from a bundle of solutions produced by the proposed algorithm is also suggested. This paper includes a formal statement of the problem and its mathematical analysis. In addition, different scenarios in which the proposed algorithm can be utilized are discussed.
CFD based draft tube hydraulic design optimization

International Nuclear Information System (INIS)

McNabb, J; Murry, N; Mullins, B F; Devals, C; Kyriacou, S A

2014-01-01

The draft tube design of a hydraulic turbine, particularly in low to medium head applications, plays an important role in determining the efficiency and power characteristics of the overall machine, since an important proportion of the available energy, being in kinetic form leaving the runner, needs to be recovered by the draft tube into static head. For large units, these efficiency and power characteristics can equate to large sums of money when considering the anticipated selling price of the energy produced over the machine's life-cycle. This same draft tube design is also a key factor in determining the overall civil costs of the powerhouse, primarily in excavation and concreting, which can amount to similar orders of magnitude as the price of the energy produced. Therefore, there is a need to find the optimum compromise between these two conflicting requirements. In this paper, an elaborate approach is described for dealing with this optimization problem. First, the draft tube's detailed geometry is defined as a function of a comprehensive set of design parameters (about 20 of which a subset is allowed to vary during the optimization process) and are then used in a non-uniform rational B-spline based geometric modeller to fully define the wetted surfaces geometry. Since the performance of the draft tube is largely governed by 3D viscous effects, such as boundary layer separation from the walls and swirling flow characteristics, which in turn governs the portion of the available kinetic energy which will be converted into pressure, a full 3D meshing and Navier-Stokes analysis is performed for each design. What makes this even more challenging is the fact that the inlet velocity distribution to the draft tube is governed by the runner at each of the various operating conditions that are of interest for the exploitation of the powerhouse. In order to determine these inlet conditions, a combined steady-state runner and an initial draft tube analysis
CFD based draft tube hydraulic design optimization

Science.gov (United States)

McNabb, J.; Devals, C.; Kyriacou, S. A.; Murry, N.; Mullins, B. F.

2014-03-01

The draft tube design of a hydraulic turbine, particularly in low to medium head applications, plays an important role in determining the efficiency and power characteristics of the overall machine, since an important proportion of the available energy, being in kinetic form leaving the runner, needs to be recovered by the draft tube into static head. For large units, these efficiency and power characteristics can equate to large sums of money when considering the anticipated selling price of the energy produced over the machine's life-cycle. This same draft tube design is also a key factor in determining the overall civil costs of the powerhouse, primarily in excavation and concreting, which can amount to similar orders of magnitude as the price of the energy produced. Therefore, there is a need to find the optimum compromise between these two conflicting requirements. In this paper, an elaborate approach is described for dealing with this optimization problem. First, the draft tube's detailed geometry is defined as a function of a comprehensive set of design parameters (about 20 of which a subset is allowed to vary during the optimization process) and are then used in a non-uniform rational B-spline based geometric modeller to fully define the wetted surfaces geometry. Since the performance of the draft tube is largely governed by 3D viscous effects, such as boundary layer separation from the walls and swirling flow characteristics, which in turn governs the portion of the available kinetic energy which will be converted into pressure, a full 3D meshing and Navier-Stokes analysis is performed for each design. What makes this even more challenging is the fact that the inlet velocity distribution to the draft tube is governed by the runner at each of the various operating conditions that are of interest for the exploitation of the powerhouse. In order to determine these inlet conditions, a combined steady-state runner and an initial draft tube analysis, using a
A two-stage optimal planning and design method for combined cooling, heat and power microgrid system

International Nuclear Information System (INIS)

Guo, Li; Liu, Wenjian; Cai, Jiejin; Hong, Bowen; Wang, Chengshan

2013-01-01

Highlights: • A two-stage optimal method is presented for CCHP microgrid system. • Economic and environmental performance are considered as assessment indicators. • Application case demonstrates its good economic and environmental performance. - Abstract: In this paper, a two-stage optimal planning and design method for combined cooling, heat and power (CCHP) microgrid system was presented. The optimal objective was to simultaneously minimize the total net present cost and carbon dioxide emission in life circle. On the first stage, multi-objective genetic algorithm based on non-dominated sorting genetic algorithm-II (NSGA-II) was applied to solve the optimal design problem including the optimization of equipment type and capacity. On the second stage, mixed-integer linear programming (MILP) algorithm was used to solve the optimal dispatch problem. The approach was applied to a typical CCHP microgrid system in a hospital as a case study, and the effectiveness of the proposed method was verified
The Optimization of Transportation Costs in Logistics Enterprises with Time-Window Constraints

Directory of Open Access Journals (Sweden)

Qingyou Yan

2015-01-01

Full Text Available This paper presents a model for solving a multiobjective vehicle routing problem with soft time-window constraints that specify the earliest and latest arrival times of customers. If a customer is serviced before the earliest specified arrival time, extra inventory costs are incurred. If the customer is serviced after the latest arrival time, penalty costs must be paid. Both the total transportation cost and the required fleet size are minimized in this model, which also accounts for the given capacity limitations of each vehicle. The total transportation cost consists of direct transportation costs, extra inventory costs, and penalty costs. This multiobjective optimization is solved by using a modified genetic algorithm approach. The output of the algorithm is a set of optimal solutions that represent the trade-off between total transportation cost and the fleet size required to service customers. The influential impact of these two factors is analyzed through the use of a case study.
An experimental strategy validated to design cost-effective culture media based on response surface methodology.

Science.gov (United States)

Navarrete-Bolaños, J L; Téllez-Martínez, M G; Miranda-López, R; Jiménez-Islas, H

2017-07-03

For any fermentation process, the production cost depends on several factors, such as the genetics of the microorganism, the process condition, and the culture medium composition. In this work, a guideline for the design of cost-efficient culture media using a sequential approach based on response surface methodology is described. The procedure was applied to analyze and optimize a culture medium of registered trademark and a base culture medium obtained as a result of the screening analysis from different culture media used to grow the same strain according to the literature. During the experiments, the procedure quantitatively identified an appropriate array of micronutrients to obtain a significant yield and find a minimum number of culture medium ingredients without limiting the process efficiency. The resultant culture medium showed an efficiency that compares favorably with the registered trademark medium at a 95% lower cost as well as reduced the number of ingredients in the base culture medium by 60% without limiting the process efficiency. These results demonstrated that, aside from satisfying the qualitative requirements, an optimum quantity of each constituent is needed to obtain a cost-effective culture medium. Study process variables for optimized culture medium and scaling-up production for the optimal values are desirable.
Cost Minimization for Joint Energy Management and Production Scheduling Using Particle Swarm Optimization

Science.gov (United States)

Shah, Rahul H.

Production costs account for the largest share of the overall cost of manufacturing facilities. With the U.S. industrial sector becoming more and more competitive, manufacturers are looking for more cost and resource efficient working practices. Operations management and production planning have shown their capability to dramatically reduce manufacturing costs and increase system robustness. When implementing operations related decision making and planning, two fields that have shown to be most effective are maintenance and energy. Unfortunately, the current research that integrates both is limited. Additionally, these studies fail to consider parameter domains and optimization on joint energy and maintenance driven production planning. Accordingly, production planning methodology that considers maintenance and energy is investigated. Two models are presented to achieve well-rounded operating strategy. The first is a joint energy and maintenance production scheduling model. The second is a cost per part model considering maintenance, energy, and production. The proposed methodology will involve a Time-of-Use electricity demand response program, buffer and holding capacity, station reliability, production rate, station rated power, and more. In practice, the scheduling problem can be used to determine a joint energy, maintenance, and production schedule. Meanwhile, the cost per part model can be used to: (1) test the sensitivity of the obtained optimal production schedule and its corresponding savings by varying key production system parameters; and (2) to determine optimal system parameter combinations when using the joint energy, maintenance, and production planning model. Additionally, a factor analysis on the system parameters is conducted and the corresponding performance of the production schedule under variable parameter conditions, is evaluated. Also, parameter optimization guidelines that incorporate maintenance and energy parameter decision making in the
Optimal treatment cost allocation methods in pollution control

International Nuclear Information System (INIS)

Chen Wenying; Fang Dong; Xue Dazhi

1999-01-01

Total emission control is an effective pollution control strategy. However, Chinese application of total emission control lacks reasonable and fair methods for optimal treatment cost allocation, a critical issue in total emission control. The author considers four approaches to allocate treatment costs. The first approach is to set up a multiple-objective planning model and to solve the model using the shortest distance ideal point method. The second approach is to define degree of satisfaction for cost allocation results for each polluter and to establish a method based on this concept. The third is to apply bargaining and arbitration theory to develop a model. The fourth is to establish a cooperative N-person game model which can be solved using the Shapley value method, the core method, the Cost Gap Allocation method or the Minimum Costs-Remaining Savings method. These approaches are compared using a practicable case study
Optimal Design of Porous Materials

DEFF Research Database (Denmark)

Andreassen, Erik

The focus of this thesis is topology optimization of material microstructures. That is, creating new materials, with attractive properties, by combining classic materials in periodic patterns. First, large-scale topology optimization is used to design complicated three-dimensional materials......, throughout the thesis extra attention is given to obtain structures that can be manufactured. That is also the case in the final part, where a simple multiscale method for the optimization of structural damping is presented. The method can be used to obtain an optimized component with structural details...
Implementation of the cost-optimal methodology according to the EPBD recast

DEFF Research Database (Denmark)

Wittchen, Kim Bjarne; Thomsen, Kirsten Engelund

2012-01-01

The EPBD recast states that Member States (MS) must ensure that minimum energy performance requirements for buildings are set “with a view to achieving cost-optimal levels”. The costoptimal level must be calculated in accordance with a comparative methodology.......The EPBD recast states that Member States (MS) must ensure that minimum energy performance requirements for buildings are set “with a view to achieving cost-optimal levels”. The costoptimal level must be calculated in accordance with a comparative methodology....
Extended exergy concept to facilitate designing and optimization of frequency-dependent direct energy conversion systems

International Nuclear Information System (INIS)

Wijewardane, S.; Goswami, Yogi

2014-01-01

Highlights: • Proved exergy method is not adequate to optimize frequency-dependent energy conversion. • Exergy concept is modified to facilitate the thermoeconomic optimization of photocell. • The exergy of arbitrary radiation is used for a practical purpose. • The utility of the concept is illustrated using pragmatic examples. - Abstract: Providing the radiation within the acceptable (responsive) frequency range(s) is a common method to increase the efficiency of the frequency-dependent energy conversion systems, such as photovoltaic and nano-scale rectenna. Appropriately designed auxiliary items such as spectrally selective thermal emitters, optical filters, and lenses are used for this purpose. However any energy conversion method that utilizes auxiliary components to increase the efficiency of a system has to justify the potential cost incurred by those auxiliary components through the economic gain emerging from the increased system efficiency. Therefore much effort should be devoted to design innovative systems, effectively integrating the auxiliary items and to optimize the system with economic considerations. Exergy is the widely used method to design and optimize conventional energy conversion systems. Although the exergy concept is used to analyze photovoltaic systems, it has not been used effectively to design and optimize such systems. In this manuscript, we present a modified exergy method in order to effectively design and economically optimize frequency-dependent energy conversion systems. Also, we illustrate the utility of this concept using examples of thermophotovoltaic, Photovoltaic/Thermal and concentrated solar photovoltaic
I-optimal mixture designs

OpenAIRE

GOOS, Peter; JONES, Bradley; SYAFITRI, Utami

2013-01-01

In mixture experiments, the factors under study are proportions of the ingredients of a mixture. The special nature of the factors in a mixture experiment necessitates specific types of regression models, and specific types of experimental designs. Although mixture experiments usually are intended to predict the response(s) for all possible formulations of the mixture and to identify optimal proportions for each of the ingredients, little research has been done concerning their I-optimal desi...
A Synergy-Based Optimally Designed Sensing Glove for Functional Grasp Recognition.

Science.gov (United States)

Ciotti, Simone; Battaglia, Edoardo; Carbonaro, Nicola; Bicchi, Antonio; Tognetti, Alessandro; Bianchi, Matteo

2016-06-02

Achieving accurate and reliable kinematic hand pose reconstructions represents a challenging task. The main reason for this is the complexity of hand biomechanics, where several degrees of freedom are distributed along a continuous deformable structure. Wearable sensing can represent a viable solution to tackle this issue, since it enables a more natural kinematic monitoring. However, the intrinsic accuracy (as well as the number of sensing elements) of wearable hand pose reconstruction (HPR) systems can be severely limited by ergonomics and cost considerations. In this paper, we combined the theoretical foundations of the optimal design of HPR devices based on hand synergy information, i.e., the inter-joint covariation patterns, with textile goniometers based on knitted piezoresistive fabrics (KPF) technology, to develop, for the first time, an optimally-designed under-sensed glove for measuring hand kinematics. We used only five sensors optimally placed on the hand and completed hand pose reconstruction (described according to a kinematic model with 19 degrees of freedom) leveraging upon synergistic information. The reconstructions we obtained from five different subjects were used to implement an unsupervised method for the recognition of eight functional grasps, showing a high degree of accuracy and robustness.
A Synergy-Based Optimally Designed Sensing Glove for Functional Grasp Recognition

Directory of Open Access Journals (Sweden)

Simone Ciotti

2016-06-01

Full Text Available Achieving accurate and reliable kinematic hand pose reconstructions represents a challenging task. The main reason for this is the complexity of hand biomechanics, where several degrees of freedom are distributed along a continuous deformable structure. Wearable sensing can represent a viable solution to tackle this issue, since it enables a more natural kinematic monitoring. However, the intrinsic accuracy (as well as the number of sensing elements of wearable hand pose reconstruction (HPR systems can be severely limited by ergonomics and cost considerations. In this paper, we combined the theoretical foundations of the optimal design of HPR devices based on hand synergy information, i.e., the inter-joint covariation patterns, with textile goniometers based on knitted piezoresistive fabrics (KPF technology, to develop, for the first time, an optimally-designed under-sensed glove for measuring hand kinematics. We used only five sensors optimally placed on the hand and completed hand pose reconstruction (described according to a kinematic model with 19 degrees of freedom leveraging upon synergistic information. The reconstructions we obtained from five different subjects were used to implement an unsupervised method for the recognition of eight functional grasps, showing a high degree of accuracy and robustness.

Cost-derived indices for building design and construction ...

African Journals Online (AJOL)

Also as multiples of gfi, substructure cost index, sci and roofing cost index, rci could predict componental costs of substructure and roofing for phased development purposes. Keywords: Cost Indices, Building Design, Building Construction Journal of Modeling, Design and Management of Engineering Systems, Vol.
Optimal design of lossy bandgap structures

DEFF Research Database (Denmark)

Jensen, Jakob Søndergaard

2004-01-01

The method of topology optimization is used to design structures for wave propagation with one lossy material component. Optimized designs for scalar elastic waves are presented for mininimum wave transmission as well as for maximum wave energy dissipation. The structures that are obtained...... are of the 1D or 2D bandgap type depending on the objective and the material parameters....
Cost optimal building performance requirements. Calculation methodology for reporting on national energy performance requirements on the basis of cost optimality within the framework of the EPBD

Energy Technology Data Exchange (ETDEWEB)

Boermans, T.; Bettgenhaeuser, K.; Hermelink, A.; Schimschar, S. [Ecofys, Utrecht (Netherlands)

2011-05-15

On the European level, the principles for the requirements for the energy performance of buildings are set by the Energy Performance of Buildings Directive (EPBD). Dating from December 2002, the EPBD has set a common framework from which the individual Member States in the EU developed or adapted their individual national regulations. The EPBD in 2008 and 2009 underwent a recast procedure, with final political agreement having been reached in November 2009. The new Directive was then formally adopted on May 19, 2010. Among other clarifications and new provisions, the EPBD recast introduces a benchmarking mechanism for national energy performance requirements for the purpose of determining cost-optimal levels to be used by Member States for comparing and setting these requirements. The previous EPBD set out a general framework to assess the energy performance of buildings and required Member States to define maximum values for energy delivered to meet the energy demand associated with the standardised use of the building. However it did not contain requirements or guidance related to the ambition level of such requirements. As a consequence, building regulations in the various Member States have been developed by the use of different approaches (influenced by different building traditions, political processes and individual market conditions) and resulted in different ambition levels where in many cases cost optimality principles could justify higher ambitions. The EPBD recast now requests that Member States shall ensure that minimum energy performance requirements for buildings are set 'with a view to achieving cost-optimal levels'. The cost optimum level shall be calculated in accordance with a comparative methodology. The objective of this report is to contribute to the ongoing discussion in Europe around the details of such a methodology by describing possible details on how to calculate cost optimal levels and pointing towards important factors and
Cost-optimal levels of minimum energy performance requirements in the Danish Building Regulations

Energy Technology Data Exchange (ETDEWEB)

Aggerholm, S.

2013-09-15

The purpose of the report is to analyse the cost optimality of the energy requirements in the Danish Building Regulations 2010, BR10 to new building and to existing buildings undergoing major renovation. The energy requirements in the Danish Building Regulations have by tradition always been based on the cost and benefits related to the private economical or financial perspective. Macro economical calculations have in the past only been made in addition. The cost optimum used in this report is thus based on the financial perspective. Due to the high energy taxes in Denmark there is a significant difference between the consumer price and the macro economical for energy. Energy taxes are also paid by commercial consumers when the energy is used for building operation e.g. heating, lighting, ventilation etc. In relation to the new housing examples the present minimum energy requirements in BR 10 all shows gaps that are negative with a deviation of up till 16 % from the point of cost optimality. With the planned tightening of the requirements to new houses in 2015 and in 2020, the energy requirements can be expected to be tighter than the cost optimal point, if the costs for the needed improvements don't decrease correspondingly. In relation to the new office building there is a gap of 31 % to the point of cost optimality in relation to the 2010 requirement. In relation to the 2015 and 2020 requirements there are negative gaps to the point of cost optimality based on today's prices. If the gaps for all the new buildings are weighted to an average based on mix of building types and heat supply for new buildings in Denmark there is a gap of 3 % in average for the new building. The excessive tightness with today's prices is 34 % in relation to the 2015 requirement and 49 % in relation to the 2020 requirement. The component requirement to elements in the building envelope and to installations in existing buildings adds up to significant energy efficiency
Irregular Shaped Building Design Optimization with Building Information Modelling

Directory of Open Access Journals (Sweden)

Lee Xia Sheng

2016-01-01

Full Text Available This research is to recognise the function of Building Information Modelling (BIM in design optimization for irregular shaped buildings. The study focuses on a conceptual irregular shaped “twisted” building design similar to some existing sculpture-like architectures. Form and function are the two most important aspects of new buildings, which are becoming more sophisticated as parts of equally sophisticated “systems” that we are living in. Nowadays, it is common to have irregular shaped or sculpture-like buildings which are very different when compared to regular buildings. Construction industry stakeholders are facing stiff challenges in many aspects such as buildability, cost effectiveness, delivery time and facility management when dealing with irregular shaped building projects. Building Information Modelling (BIM is being utilized to enable architects, engineers and constructors to gain improved visualization for irregular shaped buildings; this has a purpose of identifying critical issues before initiating physical construction work. In this study, three variations of design options differing in rotating angle: 30 degrees, 60 degrees and 90 degrees are created to conduct quantifiable comparisons. Discussions are focused on three major aspects including structural planning, usable building space, and structural constructability. This research concludes that Building Information Modelling is instrumental in facilitating design optimization for irregular shaped building. In the process of comparing different design variations, instead of just giving “yes or no” type of response, stakeholders can now easily visualize, evaluate and decide to achieve the right balance based on their own criteria. Therefore, construction project stakeholders are empowered with superior evaluation and decision making capability.
Optimal Design of Passive Power Filters Based on Pseudo-parallel Genetic Algorithm

Science.gov (United States)

Li, Pei; Li, Hongbo; Gao, Nannan; Niu, Lin; Guo, Liangfeng; Pei, Ying; Zhang, Yanyan; Xu, Minmin; Chen, Kerui

2017-05-01

The economic costs together with filter efficiency are taken as targets to optimize the parameter of passive filter. Furthermore, the method of combining pseudo-parallel genetic algorithm with adaptive genetic algorithm is adopted in this paper. In the early stages pseudo-parallel genetic algorithm is introduced to increase the population diversity, and adaptive genetic algorithm is used in the late stages to reduce the workload. At the same time, the migration rate of pseudo-parallel genetic algorithm is improved to change with population diversity adaptively. Simulation results show that the filter designed by the proposed method has better filtering effect with lower economic cost, and can be used in engineering.
Collaborative Systems Driven Aircraft Configuration Design Optimization

OpenAIRE

Shiva Prakasha, Prajwal; Ciampa, Pier Davide; Nagel, Björn

2016-01-01

A Collaborative, Inside-Out Aircraft Design approach is presented in this paper. An approach using physics based analysis to evaluate the correlations between the airframe design, as well as sub-systems integration from the early design process, and to exploit the synergies within a simultaneous optimization process. Further, the disciplinary analysis modules involved in the optimization task are located in different organization. Hence, the Airframe and Subsystem design tools are integrated ...
Parametric Optimization of Hospital Design

DEFF Research Database (Denmark)

Holst, Malene Kirstine; Kirkegaard, Poul Henning; Christoffersen, L.D.

2013-01-01

Present paper presents a parametric performancebased design model for optimizing hospital design. The design model operates with geometric input parameters defining the functional requirements of the hospital and input parameters in terms of performance objectives defining the design requirements...... and preferences of the hospital with respect to performances. The design model takes point of departure in the hospital functionalities as a set of defined parameters and rules describing the design requirements and preferences....
Solid Rocket Motor Design Using Hybrid Optimization

Directory of Open Access Journals (Sweden)

Kevin Albarado

2012-01-01

Full Text Available A particle swarm/pattern search hybrid optimizer was used to drive a solid rocket motor modeling code to an optimal solution. The solid motor code models tapered motor geometries using analytical burn back methods by slicing the grain into thin sections along the axial direction. Grains with circular perforated stars, wagon wheels, and dog bones can be considered and multiple tapered sections can be constructed. The hybrid approach to optimization is capable of exploring large areas of the solution space through particle swarming, but is also able to climb “hills” of optimality through gradient based pattern searching. A preliminary method for designing tapered internal geometry as well as tapered outer mold-line geometry is presented. A total of four optimization cases were performed. The first two case studies examines designing motors to match a given regressive-progressive-regressive burn profile. The third case study studies designing a neutrally burning right circular perforated grain (utilizing inner and external geometry tapering. The final case study studies designing a linearly regressive burning profile for right circular perforated (tapered grains.
Design optimization of highly asymmetrical layouts by 2D contour metrology

Science.gov (United States)

Hu, C. M.; Lo, Fred; Yang, Elvis; Yang, T. H.; Chen, K. C.

2018-03-01

As design pitch shrinks to the resolution limit of up-to-date optical lithography technology, the Critical Dimension (CD) variation tolerance has been dramatically decreased for ensuring the functionality of device. One of critical challenges associates with the narrower CD tolerance for whole chip area is the proximity effect control on asymmetrical layout environments. To fulfill the tight CD control of complex features, the Critical Dimension Scanning Electron Microscope (CD-SEM) based measurement results for qualifying process window and establishing the Optical Proximity Correction (OPC) model become insufficient, thus 2D contour extraction technique [1-5] has been an increasingly important approach for complementing the insufficiencies of traditional CD measurement algorithm. To alleviate the long cycle time and high cost penalties for product verification, manufacturing requirements are better to be well handled at design stage to improve the quality and yield of ICs. In this work, in-house 2D contour extraction platform was established for layout design optimization of 39nm half-pitch Self-Aligned Double Patterning (SADP) process layer. Combining with the adoption of Process Variation Band Index (PVBI), the contour extraction platform enables layout optimization speedup as comparing to traditional methods. The capabilities of identifying and handling lithography hotspots in complex layout environments of 2D contour extraction platform allow process window aware layout optimization to meet the manufacturing requirements.
Design the Cost Approach in Trade-Off's for Structural Components, Illustrated on the Baseline Selection of the Engine Thrust Frame of Ariane 5 ESC-B

Science.gov (United States)

Appolloni, L.; Juhls, A.; Rieck, U.

2002-01-01

Designing for value is one of the very actual upcoming methods for design optimization, which broke into the domain of aerospace engineering in the late 90's. In the frame of designing for value two main design philosophies exist: Design For Cost and Design To Cost. Design To Cost is the iterative redesign of a project until the content of the project meets a given budget. Designing For Cost is the conscious use of engineering process technology to reduce life cycle cost while satisfying, and hopefully exceeding, customer demands. The key to understanding cost, and hence to reducing cost, is the ability to measure cost accurately and to allocate it appropriately to products. Only then can intelligent decisions be made. Therefore the necessity of new methods as "Design For Value" or "Design For Competitiveness", set up with a generally multidisciplinary approach to find an optimized technical solution driven by many parameters, depending on the mission scenario and the customer/market needs. Very often three, but not more than five parametric drivers are sufficient. The more variable exist, the higher is in fact the risk to find just a sub-optimized local and not the global optimum, and the less robust is the found solution against change of input parameters. When the main parameters for optimization have been identified, the system engineer has to communicate them to all design engineers, who shall take care of these assessment variables during the entire design and decision process. The design process which has taken to the definition of the feasible structural concepts for the Engine Thrust Frame of the Ariane 5 Upper Cryogenic Stage ESC-B follows these most actual design philosophy methodologies, and combines a design for cost approach, to a design to cost optimization loop. Ariane 5 is the first member of a family of heavy-lift launchers. It aims to evolve into a family of launchers that responds to the space transportation challenges of the 21st century. New
Design optimization of axial flow hydraulic turbine runner: Part II - multi-objective constrained optimization method

Science.gov (United States)

Peng, Guoyi; Cao, Shuliang; Ishizuka, Masaru; Hayama, Shinji

2002-06-01

This paper is concerned with the design optimization of axial flow hydraulic turbine runner blade geometry. In order to obtain a better design plan with good performance, a new comprehensive performance optimization procedure has been presented by combining a multi-variable multi-objective constrained optimization model with a Q3D inverse computation and a performance prediction procedure. With careful analysis of the inverse design of axial hydraulic turbine runner, the total hydraulic loss and the cavitation coefficient are taken as optimization objectives and a comprehensive objective function is defined using the weight factors. Parameters of a newly proposed blade bound circulation distribution function and parameters describing positions of blade leading and training edges in the meridional flow passage are taken as optimization variables.The optimization procedure has been applied to the design optimization of a Kaplan runner with specific speed of 440 kW. Numerical results show that the performance of designed runner is successfully improved through optimization computation. The optimization model is found to be validated and it has the feature of good convergence. With the multi-objective optimization model, it is possible to control the performance of designed runner by adjusting the value of weight factors defining the comprehensive objective function. Copyright
Application of surrogate-based global optimization to aerodynamic design

CERN Document Server

Pérez, Esther

2016-01-01

Aerodynamic design, like many other engineering applications, is increasingly relying on computational power. The growing need for multi-disciplinarity and high fidelity in design optimization for industrial applications requires a huge number of repeated simulations in order to find an optimal design candidate. The main drawback is that each simulation can be computationally expensive – this becomes an even bigger issue when used within parametric studies, automated search or optimization loops, which typically may require thousands of analysis evaluations. The core issue of a design-optimization problem is the search process involved. However, when facing complex problems, the high-dimensionality of the design space and the high-multi-modality of the target functions cannot be tackled with standard techniques. In recent years, global optimization using meta-models has been widely applied to design exploration in order to rapidly investigate the design space and find sub-optimal solutions. Indeed, surrogat...
Optimal design of the heat pipe using TLBO (teaching–learning-based optimization) algorithm

International Nuclear Information System (INIS)

Rao, R.V.; More, K.C.

2015-01-01

Heat pipe is a highly efficient and reliable heat transfer component. It is a closed container designed to transfer a large amount of heat in system. Since the heat pipe operates on a closed two-phase cycle, the heat transfer capacity is greater than for solid conductors. Also, the thermal response time is less than with solid conductors. The three major elemental parts of the rotating heat pipe are: a cylindrical evaporator, a truncated cone condenser, and a fixed amount of working fluid. In this paper, a recently proposed new stochastic advanced optimization algorithm called TLBO (Teaching–Learning-Based Optimization) algorithm is used for single objective as well as multi-objective design optimization of heat pipe. It is easy to implement, does not make use of derivatives and it can be applied to unconstrained or constrained problems. Two examples of heat pipe are presented in this paper. The results of application of TLBO algorithm for the design optimization of heat pipe are compared with the NPGA (Niched Pareto Genetic Algorithm), GEM (Grenade Explosion Method) and GEO (Generalized External optimization). It is found that the TLBO algorithm has produced better results as compared to those obtained by using NPGA, GEM and GEO algorithms. - Highlights: • The TLBO (Teaching–Learning-Based Optimization) algorithm is used for the design and optimization of a heat pipe. • Two examples of heat pipe design and optimization are presented. • The TLBO algorithm is proved better than the other optimization algorithms in terms of results and the convergence
Refrigerator Optimal Scheduling to Minimise the Cost of Operation

Directory of Open Access Journals (Sweden)

Bálint Roland

2016-12-01

Full Text Available The cost optimal scheduling of a household refrigerator is presented in this work. The fundamental approach is the model predictive control methodology applied to the piecewise affine model of the refrigerator.
Global warming and carbon taxation. Optimal policy and the role of administration costs

International Nuclear Information System (INIS)

Williams, M.

1995-01-01

This paper develops a model relating CO 2 emissions to atmosphere concentrations, global temperature change and economic damages. For a variety of parameter assumptions, the model provides estimates of the marginal cost of emissions in various years. The optimal carbon tax is a function of the marginal emission cost and the costs of administering the tax. This paper demonstrates that under any reasonable assumptions, the optimal carbon tax is zero for at least several decades. (author)
Computerized systems analysis and optimization of aircraft engine performance, weight, and life cycle costs

Science.gov (United States)

Fishbach, L. H.

1979-01-01

The computational techniques utilized to determine the optimum propulsion systems for future aircraft applications and to identify system tradeoffs and technology requirements are described. The characteristics and use of the following computer codes are discussed: (1) NNEP - a very general cycle analysis code that can assemble an arbitrary matrix fans, turbines, ducts, shafts, etc., into a complete gas turbine engine and compute on- and off-design thermodynamic performance; (2) WATE - a preliminary design procedure for calculating engine weight using the component characteristics determined by NNEP; (3) POD DRG - a table look-up program to calculate wave and friction drag of nacelles; (4) LIFCYC - a computer code developed to calculate life cycle costs of engines based on the output from WATE; and (5) INSTAL - a computer code developed to calculate installation effects, inlet performance and inlet weight. Examples are given to illustrate how these computer techniques can be applied to analyze and optimize propulsion system fuel consumption, weight, and cost for representative types of aircraft and missions.
Application of an advanced cost model in the different design phases of an offshore wind turbine

Energy Technology Data Exchange (ETDEWEB)

Hendriks, H.B.; Lindenburg, C.; Kooijman, H.J.T.; Bulder, B.H. [ECN Wind, Petten (Netherlands); Bozelie, J.; Madsen, J.B. [NEG Micon Holland, Rhenen (Netherlands); Halfschepel, R. [Van Oord ACZ, Gorinchem (Netherlands); Molenaar, W. [Ballast Nedam, Amstelveen (Netherlands); Van den Berg, R. [LM Glasfiber Holland, Heerhugowaard (Netherlands); Zaaijer, M. [TU-Delft, Delft (Netherlands)

2001-09-01

The goal of the Dutch Offshore Wind Energy Converter (DOWEC) consortium is to develop concepts and technology in order to make large scale offshore wind energy economically feasible. The overall DOWEC development comprises of the design, the construction, and the prototype testing. Onshore testing of a 3 MW research and development prototype is scheduled for the end of 2002. The DOWEC Concept Study aims at the choice of the optimal wind turbine concept. The wind turbine will not be treated as an isolated system. Designs of different wind turbine concepts will be evaluated as an integral part of the complete large-scale offshore wind farm. All significant properties like the structural loads, the power performance, the system reliability, the costs of the electric infrastructure, maintenance costs and installation costs is determined for the optimised designs. A quantitative ranking is then based on the cost of energy generated. Furthermore qualitative criteria like development risk and market potential will be taken into consideration when finalising the choice of concept. An advanced cost model is being developed to facilitate the above evaluation on basis of estimated energy generating costs for each concept. The same methodology will also be used in the system and detail design phase. This paper describes the DOWEC project in general, focusing at the cost modelling aspects including some preliminary results. 4 refs.
Linear versus quadratic portfolio optimization model with transaction cost

Science.gov (United States)

Razak, Norhidayah Bt Ab; Kamil, Karmila Hanim; Elias, Siti Masitah

2014-06-01

Optimization model is introduced to become one of the decision making tools in investment. Hence, it is always a big challenge for investors to select the best model that could fulfill their goal in investment with respect to risk and return. In this paper we aims to discuss and compare the portfolio allocation and performance generated by quadratic and linear portfolio optimization models namely of Markowitz and Maximin model respectively. The application of these models has been proven to be significant and popular among others. However transaction cost has been debated as one of the important aspects that should be considered for portfolio reallocation as portfolio return could be significantly reduced when transaction cost is taken into consideration. Therefore, recognizing the importance to consider transaction cost value when calculating portfolio' return, we formulate this paper by using data from Shariah compliant securities listed in Bursa Malaysia. It is expected that, results from this paper will effectively justify the advantage of one model to another and shed some lights in quest to find the best decision making tools in investment for individual investors.
Fast Bayesian optimal experimental design for seismic source inversion

KAUST Repository

Long, Quan

2015-07-01

We develop a fast method for optimally designing experiments in the context of statistical seismic source inversion. In particular, we efficiently compute the optimal number and locations of the receivers or seismographs. The seismic source is modeled by a point moment tensor multiplied by a time-dependent function. The parameters include the source location, moment tensor components, and start time and frequency in the time function. The forward problem is modeled by elastodynamic wave equations. We show that the Hessian of the cost functional, which is usually defined as the square of the weighted L2 norm of the difference between the experimental data and the simulated data, is proportional to the measurement time and the number of receivers. Consequently, the posterior distribution of the parameters, in a Bayesian setting, concentrates around the "true" parameters, and we can employ Laplace approximation and speed up the estimation of the expected Kullback-Leibler divergence (expected information gain), the optimality criterion in the experimental design procedure. Since the source parameters span several magnitudes, we use a scaling matrix for efficient control of the condition number of the original Hessian matrix. We use a second-order accurate finite difference method to compute the Hessian matrix and either sparse quadrature or Monte Carlo sampling to carry out numerical integration. We demonstrate the efficiency, accuracy, and applicability of our method on a two-dimensional seismic source inversion problem. © 2015 Elsevier B.V.

Fast Bayesian Optimal Experimental Design for Seismic Source Inversion

KAUST Repository

Long, Quan

2016-01-06

We develop a fast method for optimally designing experiments [1] in the context of statistical seismic source inversion [2]. In particular, we efficiently compute the optimal number and locations of the receivers or seismographs. The seismic source is modeled by a point moment tensor multiplied by a time-dependent function. The parameters include the source location, moment tensor components, and start time and frequency in the time function. The forward problem is modeled by the elastic wave equations. We show that the Hessian of the cost functional, which is usually defined as the square of the weighted L2 norm of the difference between the experimental data and the simulated data, is proportional to the measurement time and the number of receivers. Consequently, the posterior distribution of the parameters, in a Bayesian setting, concentrates around the true parameters, and we can employ Laplace approximation and speed up the estimation of the expected Kullback-Leibler divergence (expected information gain), the optimality criterion in the experimental design procedure. Since the source parameters span several magnitudes, we use a scaling matrix for efficient control of the condition number of the original Hessian matrix. We use a second-order accurate finite difference method to compute the Hessian matrix and either sparse quadrature or Monte Carlo sampling to carry out numerical integration. We demonstrate the efficiency, accuracy, and applicability of our method on a two-dimensional seismic source inversion problem.
Fast Bayesian Optimal Experimental Design for Seismic Source Inversion

KAUST Repository

Long, Quan; Motamed, Mohammad; Tempone, Raul

2016-01-01

We develop a fast method for optimally designing experiments [1] in the context of statistical seismic source inversion [2]. In particular, we efficiently compute the optimal number and locations of the receivers or seismographs. The seismic source is modeled by a point moment tensor multiplied by a time-dependent function. The parameters include the source location, moment tensor components, and start time and frequency in the time function. The forward problem is modeled by the elastic wave equations. We show that the Hessian of the cost functional, which is usually defined as the square of the weighted L2 norm of the difference between the experimental data and the simulated data, is proportional to the measurement time and the number of receivers. Consequently, the posterior distribution of the parameters, in a Bayesian setting, concentrates around the true parameters, and we can employ Laplace approximation and speed up the estimation of the expected Kullback-Leibler divergence (expected information gain), the optimality criterion in the experimental design procedure. Since the source parameters span several magnitudes, we use a scaling matrix for efficient control of the condition number of the original Hessian matrix. We use a second-order accurate finite difference method to compute the Hessian matrix and either sparse quadrature or Monte Carlo sampling to carry out numerical integration. We demonstrate the efficiency, accuracy, and applicability of our method on a two-dimensional seismic source inversion problem.
Computational Sensing Using Low-Cost and Mobile Plasmonic Readers Designed by Machine Learning

KAUST Repository

Ballard, Zachary S.

2017-01-27

Plasmonic sensors have been used for a wide range of biological and chemical sensing applications. Emerging nanofabrication techniques have enabled these sensors to be cost-effectively mass manufactured onto various types of substrates. To accompany these advances, major improvements in sensor read-out devices must also be achieved to fully realize the broad impact of plasmonic nanosensors. Here, we propose a machine learning framework which can be used to design low-cost and mobile multispectral plasmonic readers that do not use traditionally employed bulky and expensive stabilized light sources or high-resolution spectrometers. By training a feature selection model over a large set of fabricated plasmonic nanosensors, we select the optimal set of illumination light-emitting diodes needed to create a minimum-error refractive index prediction model, which statistically takes into account the varied spectral responses and fabrication-induced variability of a given sensor design. This computational sensing approach was experimentally validated using a modular mobile plasmonic reader. We tested different plasmonic sensors with hexagonal and square periodicity nanohole arrays and revealed that the optimal illumination bands differ from those that are “intuitively” selected based on the spectral features of the sensor, e.g., transmission peaks or valleys. This framework provides a universal tool for the plasmonics community to design low-cost and mobile multispectral readers, helping the translation of nanosensing technologies to various emerging applications such as wearable sensing, personalized medicine, and point-of-care diagnostics. Beyond plasmonics, other types of sensors that operate based on spectral changes can broadly benefit from this approach, including e.g., aptamer-enabled nanoparticle assays and graphene-based sensors, among others.
On thermoeconomics of energy systems at variable load conditions: Integrated optimization of plant design and operation

International Nuclear Information System (INIS)

Piacentino, A.; Cardona, F.

2007-01-01

Thermoeconomics has been assuming a growing role among the disciplines oriented to the analysis of energy systems, its different methodologies allowing solution of problems in the fields of cost accounting, plant design optimisation and diagnostic of malfunctions. However, the thermoeconomic methodologies as such are particularly appropriate to analyse large industrial systems at steady or quasi-steady operation, but they can be hardly applied to small to medium scale units operating in unsteady conditions to cover a variable energy demand. In this paper, the fundamentals of thermoeconomics for systems operated at variable load are discussed, examining the cost formation process and, separately, the cost fractions related to capital depreciation (which require additional distinctions with respect to plants in steady operation) and to exergy consumption. The relevant effects of the efficiency penalty due to off design operation on the exergetic cost of internal flows are also examined. An original algorithm is proposed for the integrated optimization of plant design and operation based on an analytical solution by the Lagrange multipliers method and on a multi-objective decision function, expressed either in terms of net cash flow or primary energy saving. The method is suitable for application in complex energy systems, such as 'facilities of components of a same product' connected to external networks for power or heat distribution. For demonstrative purposes, the proposed thermoeconomically aided optimization is performed for a grid connected trigeneration system to be installed in a large hotel
Optimization of wind turbine rotors

Energy Technology Data Exchange (ETDEWEB)

Nygaard, Tor Anders

1999-07-01

The Constrained Steepest Descent method has been applied to the optimization of wind turbine rotors through the development of a numerical model. The model consists of an optimization kernel, an aerodynamic model, a structural dynamic model of a rotating beam, and a cost model for the wind turbine. The cost of energy is minimized directly by varying the blade design, the rotational speed and the resulting design of the drive-train and tower. The aerodynamic model is a combination of a fast engineering model based on strip-theory and two and three-dimensional Euler solvers. The two-dimensional Euler solver is used for generation of pre-stall airfoil data. Comparisons with experimental data verify that the engineering model effectively approximates non-stalled flow, except at the blade tip. The three-dimensional Euler solver is in good agreement with the experimental data at the tip, and is therefore a useful supplement for corrections of the tip-loss model, and evaluation of an optimized design. The structural dynamic model evaluates stresses and deformations for the blade. It is based on constitutive relations for a slender beam that are solved with the equations of motions using a finite-difference method. The cost model evaluates the design change of the wind turbine and the resulting costs that occur when a change in blade design modifies the blade mass and the overall forces. The cost model is based on engineering design rules for the drive-train and tower. The model was applied using a Danish 600 kW wind turbine as a reference. Two rotors were optimized using traditional NACA airfoils and a new low-lift airfoil family developed specifically for wind turbine purposes. The cost of energy decreased four percent for the NACA rotor, and seven percent for the low-lift rotor. Optimizations with a high number of degrees of freedom show that a designer has considerable flexibility in choosing some primary parameters such as rated power and rotor diameter, if the rest
A generic tool for cost estimating in aircraft design

NARCIS (Netherlands)

Castagne, S.; Curran, R.; Rothwell, A.; Price, M.; Benard, E.; Raghunathan, S.

2008-01-01

A methodology to estimate the cost implications of design decisions by integrating cost as a design parameter at an early design stage is presented. The model is developed on a hierarchical basis, the manufacturing cost of aircraft fuselage panels being analysed in this paper. The manufacturing cost
Sequential Optimization of Paths in Directed Graphs Relative to Different Cost Functions

KAUST Repository

Mahayni, Malek A.

2011-07-01

Finding optimal paths in directed graphs is a wide area of research that has received much of attention in theoretical computer science due to its importance in many applications (e.g., computer networks and road maps). Many algorithms have been developed to solve the optimal paths problem with different kinds of graphs. An algorithm that solves the problem of paths’ optimization in directed graphs relative to different cost functions is described in [1]. It follows an approach extended from the dynamic programming approach as it solves the problem sequentially and works on directed graphs with positive weights and no loop edges. The aim of this thesis is to implement and evaluate that algorithm to find the optimal paths in directed graphs relative to two different cost functions ( , ). A possible interpretation of a directed graph is a network of roads so the weights for the function represent the length of roads, whereas the weights for the function represent a constraint of the width or weight of a vehicle. The optimization aim for those two functions is to minimize the cost relative to the function and maximize the constraint value associated with the function. This thesis also includes finding and proving the relation between the two different cost functions ( , ). When given a value of one function, we can find the best possible value for the other function. This relation is proven theoretically and also implemented and experimented using Matlab®[2].
Sequential Optimization of Global Sequence Alignments Relative to Different Cost Functions

KAUST Repository

Odat, Enas M.

2011-05-01

The purpose of this dissertation is to present a methodology to model global sequence alignment problem as directed acyclic graph which helps to extract all possible optimal alignments. Moreover, a mechanism to sequentially optimize sequence alignment problem relative to different cost functions is suggested. Sequence alignment is mostly important in computational biology. It is used to find evolutionary relationships between biological sequences. There are many algo- rithms that have been developed to solve this problem. The most famous algorithms are Needleman-Wunsch and Smith-Waterman that are based on dynamic program- ming. In dynamic programming, problem is divided into a set of overlapping sub- problems and then the solution of each subproblem is found. Finally, the solutions to these subproblems are combined into a final solution. In this thesis it has been proved that for two sequences of length m and n over a fixed alphabet, the suggested optimization procedure requires O(mn) arithmetic operations per cost function on a single processor machine. The algorithm has been simulated using C#.Net programming language and a number of experiments have been done to verify the proved statements. The results of these experiments show that the number of optimal alignments is reduced after each step of optimization. Furthermore, it has been verified that as the sequence length increased linearly then the number of optimal alignments increased exponentially which also depends on the cost function that is used. Finally, the number of executed operations increases polynomially as the sequence length increase linearly.
Application of Reduced Order Transonic Aerodynamic Influence Coefficient Matrix for Design Optimization

Science.gov (United States)

Pak, Chan-gi; Li, Wesley W.

2009-01-01

Supporting the Aeronautics Research Mission Directorate guidelines, the National Aeronautics and Space Administration [NASA] Dryden Flight Research Center is developing a multidisciplinary design, analysis, and optimization [MDAO] tool. This tool will leverage existing tools and practices, and allow the easy integration and adoption of new state-of-the-art software. Today s modern aircraft designs in transonic speed are a challenging task due to the computation time required for the unsteady aeroelastic analysis using a Computational Fluid Dynamics [CFD] code. Design approaches in this speed regime are mainly based on the manual trial and error. Because of the time required for unsteady CFD computations in time-domain, this will considerably slow down the whole design process. These analyses are usually performed repeatedly to optimize the final design. As a result, there is considerable motivation to be able to perform aeroelastic calculations more quickly and inexpensively. This paper will describe the development of unsteady transonic aeroelastic design methodology for design optimization using reduced modeling method and unsteady aerodynamic approximation. The method requires the unsteady transonic aerodynamics be represented in the frequency or Laplace domain. Dynamically linear assumption is used for creating Aerodynamic Influence Coefficient [AIC] matrices in transonic speed regime. Unsteady CFD computations are needed for the important columns of an AIC matrix which corresponded to the primary modes for the flutter. Order reduction techniques, such as Guyan reduction and improved reduction system, are used to reduce the size of problem transonic flutter can be found by the classic methods, such as Rational function approximation, p-k, p, root-locus etc. Such a methodology could be incorporated into MDAO tool for design optimization at a reasonable computational cost. The proposed technique is verified using the Aerostructures Test Wing 2 actually designed
Optimal design of distributed control and embedded systems

CERN Document Server

Çela, Arben; Li, Xu-Guang; Niculescu, Silviu-Iulian

2014-01-01

Optimal Design of Distributed Control and Embedded Systems focuses on the design of special control and scheduling algorithms based on system structural properties as well as on analysis of the influence of induced time-delay on systems performances. It treats the optimal design of distributed and embedded control systems (DCESs) with respect to communication and calculation-resource constraints, quantization aspects, and potential time-delays induced by the associated communication and calculation model. Particular emphasis is put on optimal control signal scheduling based on the system state. In order to render this complex optimization problem feasible in real time, a time decomposition is based on periodicity induced by the static scheduling is operated. The authors present a co-design approach which subsumes the synthesis of the optimal control laws and the generation of an optimal schedule of control signals on real-time networks as well as the execution of control tasks on a single processor. The a...
Integrated emission management for cost optimal EGR-SCR balancing in diesels

NARCIS (Netherlands)

Willems, F.P.T.; Mentink, P.R.; Kupper, F.; Eijnden, E.A.C. van den

2013-01-01

The potential of a cost-based optimization method is experimentally demonstrated on a Euro-VI heavy-duty diesel engine. Based on the actual engine-aftertreatment state, this model-based Integrated Emission Management (IEM) strategy minimizes operational (fuel and AdBlue) costs within emission
Methodology for the optimal design of an integrated first and second generation ethanol production plant combined with power cogeneration.

Science.gov (United States)

Bechara, Rami; Gomez, Adrien; Saint-Antonin, Valérie; Schweitzer, Jean-Marc; Maréchal, François

2016-08-01

The application of methodologies for the optimal design of integrated processes has seen increased interest in literature. This article builds on previous works and applies a systematic methodology to an integrated first and second generation ethanol production plant with power cogeneration. The methodology breaks into process simulation, heat integration, thermo-economic evaluation, exergy efficiency vs. capital costs, multi-variable, evolutionary optimization, and process selection via profitability maximization. Optimization generated Pareto solutions with exergy efficiency ranging between 39.2% and 44.4% and capital costs from 210M$ to 390M$. The Net Present Value was positive for only two scenarios and for low efficiency, low hydrolysis points. The minimum cellulosic ethanol selling price was sought to obtain a maximum NPV of zero for high efficiency, high hydrolysis alternatives. The obtained optimal configuration presented maximum exergy efficiency, hydrolyzed bagasse fraction, capital costs and ethanol production rate, and minimum cooling water consumption and power production rate. Copyright © 2016 Elsevier Ltd. All rights reserved.
Performance-based Pareto optimal design

NARCIS (Netherlands)

Sariyildiz, I.S.; Bittermann, M.S.; Ciftcioglu, O.

2008-01-01

A novel approach for performance-based design is presented, where Pareto optimality is pursued. Design requirements may contain linguistic information, which is difficult to bring into computation or make consistent their impartial estimations from case to case. Fuzzy logic and soft computing are
Costs and benefits of realism and optimism.

Science.gov (United States)

Bortolotti, Lisa; Antrobus, Magdalena

2015-03-01

What is the relationship between rationality and mental health? By considering the psychological literature on depressive realism and unrealistic optimism, it was hypothesized that, in the context of judgments about the self, accurate cognitions are psychologically maladaptive and inaccurate cognitions are psychologically adaptive. Recent studies recommend being cautious in drawing any general conclusion about the style of thinking and mental health. Recent investigations suggest that people with depressive symptoms are more accurate than controls in tasks involving time perception and estimates of personal circumstances, but not in other tasks. Unrealistic optimism remains a robust phenomenon across a variety of tasks and domains, and researchers are starting to explore its neural bases. However, the challenge is to determine to what extent and in what way unrealistic optimism is beneficial. We should revisit the hypothesis that optimistic cognitions are psychologically adaptive, whereas realistic thinking is not. Realistic beliefs and expectations can be conducive to wellbeing and good functioning, and wildly optimistic cognitions have considerable psychological costs.
Individual Drilling Bit Design and Optimization in Mahu Area

Directory of Open Access Journals (Sweden)

Zhang Wenbo

2017-01-01

Full Text Available There are three sets of gravels in Mahu region. The gravels formation is characterized by high heterogeneity, high abrasiveness and poor drillability. It is so difficult to optimize bit that restrict seriously the overall exploration and development process. The compressive strength, internal friction angle, and drillability of the formation are tested to check the rock mechanical characteristic profile established by logging data. The individual bit design is carried out by the 3D simulation technology. A new PDC bit type is designed to form the drill bit series for Mahu area. Single PDC bit increases 90% of the drilling footage. The trip average footage is improved 3.45 times, the horizontal section average penetration increased 34.8%. The technical achievements have greatly improved economic development benefits of Mahu region by improving drilling speed and saving drilling costs.
Cost-optimal energy performance renovation measures of educational buildings in cold climate

International Nuclear Information System (INIS)

Niemelä, Tuomo; Kosonen, Risto; Jokisalo, Juha

2016-01-01

Highlights: • The proposed national nZEB target can be cost-effectively achieved in renovations. • Energy saving potential of HVAC systems is significant compared to the building envelope. • Modern renewable energy production technologies are cost-efficient and recommendable. • Improving the indoor climate conditions in deep renovations is recommendable. • Simulation-based optimization method is efficient in building performance analyzes. - Abstract: The paper discusses cost-efficient energy performance renovation measures for typical educational buildings built in the 1960s and 1970s in cold climate regions. The study analyzes the impact of different energy renovation measures on the energy efficiency and economic viability in a Finnish case study educational building located in Lappeenranta University of Technology (LUT) campus area. The main objective of the study was to determine the cost-optimal energy performance renovation measures to meet the proposed national nearly zero-energy building (nZEB) requirements, which are defined according to the primary energy consumption of buildings. The main research method of the study was simulation-based optimization (SBO) analysis, which was used to determine the cost-optimal renovation solutions. The results of the study indicate that the minimum national energy performance requirement of new educational buildings (E_p_r_i_m_a_r_y ⩽ 170 kWh/(m"2,a)) can be cost-effectively achieved in deep renovations of educational buildings. In addition, the proposed national nZEB-targets are also well achievable, while improving the indoor climate (thermal comfort and indoor air quality) conditions significantly at the same time. Cost-effective solutions included renovation of the original ventilation system, a ground source heat pump system with relatively small dimensioning power output, new energy efficient windows and a relatively large area of PV-panels for solar-based electricity production. The results and
Automated Design Framework for Synthetic Biology Exploiting Pareto Optimality.

Science.gov (United States)

Otero-Muras, Irene; Banga, Julio R

2017-07-21

In this work we consider Pareto optimality for automated design in synthetic biology. We present a generalized framework based on a mixed-integer dynamic optimization formulation that, given design specifications, allows the computation of Pareto optimal sets of designs, that is, the set of best trade-offs for the metrics of interest. We show how this framework can be used for (i) forward design, that is, finding the Pareto optimal set of synthetic designs for implementation, and (ii) reverse design, that is, analyzing and inferring motifs and/or design principles of gene regulatory networks from the Pareto set of optimal circuits. Finally, we illustrate the capabilities and performance of this framework considering four case studies. In the first problem we consider the forward design of an oscillator. In the remaining problems, we illustrate how to apply the reverse design approach to find motifs for stripe formation, rapid adaption, and fold-change detection, respectively.
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.
A systematic approach to designing statistically powerful heteroscedastic 2 × 2 factorial studies while minimizing financial costs

Directory of Open Access Journals (Sweden)

Show-Li Jan

2016-08-01

Full Text Available Abstract Background The 2 × 2 factorial design is widely used for assessing the existence of interaction and the extent of generalizability of two factors where each factor had only two levels. Accordingly, research problems associated with the main effects and interaction effects can be analyzed with the selected linear contrasts. Methods To correct for the potential heterogeneity of variance structure, the Welch-Satterthwaite test is commonly used as an alternative to the t test for detecting the substantive significance of a linear combination of mean effects. This study concerns the optimal allocation of group sizes for the Welch-Satterthwaite test in order to minimize the total cost while maintaining adequate power. The existing method suggests that the optimal ratio of sample sizes is proportional to the ratio of the population standard deviations divided by the square root of the ratio of the unit sampling costs. Instead, a systematic approach using optimization technique and screening search is presented to find the optimal solution. Results Numerical assessments revealed that the current allocation scheme generally does not give the optimal solution. Alternatively, the suggested approaches to power and sample size calculations give accurate and superior results under various treatment and cost configurations. Conclusions The proposed approach improves upon the current method in both its methodological soundness and overall performance. Supplementary algorithms are also developed to aid the usefulness and implementation of the recommended technique in planning 2 × 2 factorial designs.
A strategy for reducing turnaround time in design optimization using a distributed computer system

Science.gov (United States)

Young, Katherine C.; Padula, Sharon L.; Rogers, James L.

1988-01-01

There is a need to explore methods for reducing lengthly computer turnaround or clock time associated with engineering design problems. Different strategies can be employed to reduce this turnaround time. One strategy is to run validated analysis software on a network of existing smaller computers so that portions of the computation can be done in parallel. This paper focuses on the implementation of this method using two types of problems. The first type is a traditional structural design optimization problem, which is characterized by a simple data flow and a complicated analysis. The second type of problem uses an existing computer program designed to study multilevel optimization techniques. This problem is characterized by complicated data flow and a simple analysis. The paper shows that distributed computing can be a viable means for reducing computational turnaround time for engineering design problems that lend themselves to decomposition. Parallel computing can be accomplished with a minimal cost in terms of hardware and software.

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