Portfolio Optimization of Nanomaterial Use in Clean Energy Technologies.

PubMed

Moore, Elizabeth A; Babbitt, Callie W; Gaustad, Gabrielle; Moore, Sean T

2018-04-03

While engineered nanomaterials (ENMs) are increasingly incorporated in diverse applications, risks of ENM adoption remain difficult to predict and mitigate proactively. Current decision-making tools do not adequately account for ENM uncertainties including varying functional forms, unique environmental behavior, economic costs, unknown supply and demand, and upstream emissions. The complexity of the ENM system necessitates a novel approach: in this study, the adaptation of an investment portfolio optimization model is demonstrated for optimization of ENM use in renewable energy technologies. Where a traditional investment portfolio optimization model maximizes return on investment through optimal selection of stock, ENM portfolio optimization maximizes the performance of energy technology systems by optimizing selective use of ENMs. Cumulative impacts of multiple ENM material portfolios are evaluated in two case studies: organic photovoltaic cells (OPVs) for renewable energy and lithium-ion batteries (LIBs) for electric vehicles. Results indicate ENM adoption is dependent on overall performance and variance of the material, resource use, environmental impact, and economic trade-offs. From a sustainability perspective, improved clean energy applications can help extend product lifespans, reduce fossil energy consumption, and substitute ENMs for scarce incumbent materials.

Optimal planning and design of a renewable energy based supply system for microgrids

DOE PAGES

Hafez, Omar; Bhattacharya, Kankar

2012-03-03

This paper presents a technique for optimal planning and design of hybrid renewable energy systems for microgrid applications. The Distributed Energy Resources Customer Adoption Model (DER-CAM) is used to determine the optimal size and type of distributed energy resources (DERs) and their operating schedules for a sample utility distribution system. Using the DER-CAM results, an evaluation is performed to evaluate the electrical performance of the distribution circuit if the DERs selected by the DER-CAM optimization analyses are incorporated. Results of analyses regarding the economic benefits of utilizing the optimal locations identified for the selected DER within the system are alsomore » presented. The actual Brookhaven National Laboratory (BNL) campus electrical network is used as an example to show the effectiveness of this approach. The results show that these technical and economic analyses of hybrid renewable energy systems are essential for the efficient utilization of renewable energy resources for microgird applications.« less

Use of constrained optimization in the conceptual design of a medium-range subsonic transport

NASA Technical Reports Server (NTRS)

Sliwa, S. M.

1980-01-01

Constrained parameter optimization was used to perform the optimal conceptual design of a medium range transport configuration. The impact of choosing a given performance index was studied, and the required income for a 15 percent return on investment was proposed as a figure of merit. A number of design constants and constraint functions were systematically varied to document the sensitivities of the optimal design to a variety of economic and technological assumptions. A comparison was made for each of the parameter variations between the baseline configuration and the optimally redesigned configuration.

Large Scale Multi-area Static/Dynamic Economic Dispatch using Nature Inspired Optimization

NASA Astrophysics Data System (ADS)

Pandit, Manjaree; Jain, Kalpana; Dubey, Hari Mohan; Singh, Rameshwar

2017-04-01

Economic dispatch (ED) ensures that the generation allocation to the power units is carried out such that the total fuel cost is minimized and all the operating equality/inequality constraints are satisfied. Classical ED does not take transmission constraints into consideration, but in the present restructured power systems the tie-line limits play a very important role in deciding operational policies. ED is a dynamic problem which is performed on-line in the central load dispatch centre with changing load scenarios. The dynamic multi-area ED (MAED) problem is more complex due to the additional tie-line, ramp-rate and area-wise power balance constraints. Nature inspired (NI) heuristic optimization methods are gaining popularity over the traditional methods for complex problems. This work presents the modified particle swarm optimization (PSO) based techniques where parameter automation is effectively used for improving the search efficiency by avoiding stagnation to a sub-optimal result. This work validates the performance of the PSO variants with traditional solver GAMS for single as well as multi-area economic dispatch (MAED) on three test cases of a large 140-unit standard test system having complex constraints.

Economic Analysis and Optimal Sizing for behind-the-meter Battery Storage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Di; Kintner-Meyer, Michael CW; Yang, Tao

This paper proposes methods to estimate the potential benefits and determine the optimal energy and power capacity for behind-the-meter BSS. In the proposed method, a linear programming is first formulated only using typical load profiles, energy/demand charge rates, and a set of battery parameters to determine the maximum saving in electric energy cost. The optimization formulation is then adapted to include battery cost as a function of its power and energy capacity in order to capture the trade-off between benefits and cost, and therefore to determine the most economic battery size. Using the proposed methods, economic analysis and optimal sizingmore » have been performed for a few commercial buildings and utility rate structures that are representative of those found in the various regions of the Continental United States. The key factors that affect the economic benefits and optimal size have been identified. The proposed methods and case study results cannot only help commercial and industrial customers or battery vendors to evaluate and size the storage system for behind-the-meter application, but can also assist utilities and policy makers to design electricity rate or subsidies to promote the development of energy storage.« less

REopt: A Platform for Energy System Integration and Optimization: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simpkins, T.; Cutler, D.; Anderson, K.

2014-08-01

REopt is NREL's energy planning platform offering concurrent, multi-technology integration and optimization capabilities to help clients meet their cost savings and energy performance goals. The REopt platform provides techno-economic decision-support analysis throughout the energy planning process, from agency-level screening and macro planning to project development to energy asset operation. REopt employs an integrated approach to optimizing a site?s energy costs by considering electricity and thermal consumption, resource availability, complex tariff structures including time-of-use, demand and sell-back rates, incentives, net-metering, and interconnection limits. Formulated as a mixed integer linear program, REopt recommends an optimally-sized mix of conventional and renewable energy, andmore » energy storage technologies; estimates the net present value associated with implementing those technologies; and provides the cost-optimal dispatch strategy for operating them at maximum economic efficiency. The REopt platform can be customized to address a variety of energy optimization scenarios including policy, microgrid, and operational energy applications. This paper presents the REopt techno-economic model along with two examples of recently completed analysis projects.« less

Economic-Oriented Stochastic Optimization in Advanced Process Control of Chemical Processes

PubMed Central

Dobos, László; Király, András; Abonyi, János

2012-01-01

Finding the optimal operating region of chemical processes is an inevitable step toward improving economic performance. Usually the optimal operating region is situated close to process constraints related to product quality or process safety requirements. Higher profit can be realized only by assuring a relatively low frequency of violation of these constraints. A multilevel stochastic optimization framework is proposed to determine the optimal setpoint values of control loops with respect to predetermined risk levels, uncertainties, and costs of violation of process constraints. The proposed framework is realized as direct search-type optimization of Monte-Carlo simulation of the controlled process. The concept is illustrated throughout by a well-known benchmark problem related to the control of a linear dynamical system and the model predictive control of a more complex nonlinear polymerization process. PMID:23213298

Improving the Signal for U.S. Navy Officer Productivity

DTIC Science & Technology

2014-12-01

American Economic Review, 93(1), 216–240. Retrieved from http://www.jstor.org/stable/3132169 Mankiw , G., Romer, D., & Weil, D. (1992). A contribution...individual perfonnance appraisal system to optimally signal officer productivity. This paper utilizes the economics literature on individual perfonnance...signal officer productivity. This paper utilizes the economics literature on individual performance appraisals and promotion systems as the lens

Self-Organizing Hierarchical Particle Swarm Optimization with Time-Varying Acceleration Coefficients for Economic Dispatch with Valve Point Effects and Multifuel Options

NASA Astrophysics Data System (ADS)

Polprasert, Jirawadee; Ongsakul, Weerakorn; Dieu, Vo Ngoc

2011-06-01

This paper proposes a self-organizing hierarchical particle swarm optimization (SPSO) with time-varying acceleration coefficients (TVAC) for solving economic dispatch (ED) problem with non-smooth functions including multiple fuel options (MFO) and valve-point loading effects (VPLE). The proposed SPSO with TVAC is the new approach optimizer and good performance for solving ED problems. It can handle the premature convergence of the problem by re-initialization of velocity whenever particles are stagnated in the search space. To properly control both local and global explorations of the swarm during the optimization process, the performance of TVAC is included. The proposed method is tested in different ED problems with non-smooth cost functions and the obtained results are compared to those from many other methods in the literature. The results have revealed that the proposed SPSO with TVAC is effective in finding higher quality solutions for non-smooth ED problems than many other methods.

Method for Household Refrigerators Efficiency Increasing

NASA Astrophysics Data System (ADS)

Lebedev, V. V.; Sumzina, L. V.; Maksimov, A. V.

2017-11-01

The relevance of working processes parameters optimization in air conditioning systems is proved in the work. The research is performed with the use of the simulation modeling method. The parameters optimization criteria are considered, the analysis of target functions is given while the key factors of technical and economic optimization are considered in the article. The search for the optimal solution at multi-purpose optimization of the system is made by finding out the minimum of the dual-target vector created by the Pareto method of linear and weight compromises from target functions of the total capital costs and total operating costs. The tasks are solved in the MathCAD environment. The research results show that the values of technical and economic parameters of air conditioning systems in the areas relating to the optimum solutions’ areas manifest considerable deviations from the minimum values. At the same time, the tendencies for significant growth in deviations take place at removal of technical parameters from the optimal values of both the capital investments and operating costs. The production and operation of conditioners with the parameters which are considerably deviating from the optimal values will lead to the increase of material and power costs. The research allows one to establish the borders of the area of the optimal values for technical and economic parameters at air conditioning systems’ design.

Optimizing cultivation of agricultural products using socio-economic and environmental scenarios.

PubMed

RaheliNamin, Behnaz; Mortazavi, Samar; Salmanmahiny, Abdolrassoul

2016-11-01

The combination of degrading natural conditions and resources, climate change, growing population, urban development, and competition in a global market complicate optimization of land for agricultural products. The use of pesticides and fertilizers for crop production in the agricultural fields has become excessive in the recent years and Golestan Province of Iran is no exception in this regard. For this, effective management with an efficient and cost-effective practice should be undertaken, maintaining public service at a high level and preserving the environment. Improving the production efficiency of agriculture, efficient use of water resources, decreasing the use of pesticides and fertilizers, improving farmer revenue, and conservation of natural resources are the main objectives of the allocation, ranking, and optimization of agricultural products. The goal of this paper is to use an optimization procedure to lower the negative effects of agriculture while maintaining a high production rate, which is currently a gap in the study area. We collected information about fertilizer and pesticide consumption and other data in croplands of eastern Golestan Province through face-to-face interviews with farmers to optimize cultivation of the agricultural products. The toxicity of pesticides according to LD50 was also included in the optimization model. A decision-support software system called multiple criteria analysis tool was used to simultaneously minimize consumption of water, chemical fertilizers, and pesticides and maximize socio-economic returns. Three scenarios for optimization of agricultural products were generated that alternatively emphasized on environmental and socio-economic goals. Comparing socio-economic and environmental performance of the optimized agricultural products under the three scenarios illustrated the conflict between social, economic, and environmental objectives. Of the six crops studied (wheat, barley, rice, soybeans, oilseed rape, and maize), rice ranked second in the social and fifth in the economic scenarios. Soybeans had the lowest rank for economic and social scenarios and its cultivation in the study area, in terms of economic and social goals, was rejected by the model. However, cultivation of soybeans continues in the area as a responsibility to cater for the major need of the country. Because of subsidized prices of water, fertilizers, and pesticides, the use of these items are far from optimized in the current agricultural practices in the area.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fang Baolong; Department of Mathematics and Physics, Hefei University, Hefei 230022; Yang Zhen

We propose a scheme for implementing a partial general quantum cloning machine with superconducting quantum-interference devices coupled to a nonresonant cavity. By regulating the time parameters, our system can perform optimal symmetric (asymmetric) universal quantum cloning, optimal symmetric (asymmetric) phase-covariant cloning, and optimal symmetric economical phase-covariant cloning. In the scheme the cavity is only virtually excited, thus, the cavity decay is suppressed during the cloning operations.

Optimizing point-of-care testing in clinical systems management.

PubMed

Kost, G J

1998-01-01

The goal of improving medical and economic outcomes calls for leadership based on fundamental principles. The manager of clinical systems works collaboratively within the acute care center to optimize point-of-care testing through systematic approaches such as integrative strategies, algorithms, and performance maps. These approaches are effective and efficacious for critically ill patients. Optimizing point-of-care testing throughout the entire health-care system is inherently more difficult. There is potential to achieve high-quality testing, integrated disease management, and equitable health-care delivery. Despite rapid change and economic uncertainty, a macro-strategic, information-integrated, feedback-systems, outcomes-oriented approach is timely, challenging, effective, and uplifting to the creative human spirit.

The economics of motion perception and invariants of visual sensitivity.

PubMed

Gepshtein, Sergei; Tyukin, Ivan; Kubovy, Michael

2007-06-21

Neural systems face the challenge of optimizing their performance with limited resources, just as economic systems do. Here, we use tools of neoclassical economic theory to explore how a frugal visual system should use a limited number of neurons to optimize perception of motion. The theory prescribes that vision should allocate its resources to different conditions of stimulation according to the degree of balance between measurement uncertainties and stimulus uncertainties. We find that human vision approximately follows the optimal prescription. The equilibrium theory explains why human visual sensitivity is distributed the way it is and why qualitatively different regimes of apparent motion are observed at different speeds. The theory offers a new normative framework for understanding the mechanisms of visual sensitivity at the threshold of visibility and above the threshold and predicts large-scale changes in visual sensitivity in response to changes in the statistics of stimulation and system goals.

The future of hospital economic health.

PubMed

Gerber, David R; Bekes, Carolyn E; Parrillo, Joseph E

2006-03-01

To evaluate factors which may influence the economic future of academic medical centers (AMCs). A literature search was performed to identify publications which reviewed the areas of revenue sources for AMCs, costs and expenses incurred by these institutions, and mechanisms for optimizing institutional economic stability. Data were reviewed and evaluated in two primary contexts: hospital revenues and organizational and administrative factors influencing hospital economic health. Increasing economic stress will require AMCs to make efforts both to increase revenue through a variety of mechanisms and to minimize expenses without compromising their mission or impairing worker morale.

Economic Model Predictive Control of Bihormonal Artificial Pancreas System Based on Switching Control and Dynamic R-parameter.

PubMed

Tang, Fengna; Wang, Youqing

2017-11-01

Blood glucose (BG) regulation is a long-term task for people with diabetes. In recent years, more and more researchers have attempted to achieve automated regulation of BG using automatic control algorithms, called the artificial pancreas (AP) system. In clinical practice, it is equally important to guarantee the treatment effect and reduce the treatment costs. The main motivation of this study is to reduce the cure burden. The dynamic R-parameter economic model predictive control (R-EMPC) is chosen to regulate the delivery rates of exogenous hormones (insulin and glucagon). It uses particle swarm optimization (PSO) to optimize the economic cost function and the switching logic between insulin delivery and glucagon delivery is designed based on switching control theory. The proposed method is first tested on the standard subject; the result is compared with the switching PID and the switching MPC. The effect of the dynamic R-parameter on improving the control performance is illustrated by comparing the results of the EMPC and the R-EMPC. Finally, the robustness tests on meal change (size and timing), hormone sensitivity (insulin and glucagon), and subject variability are performed. All results show that the proposed method can improve the control performance and reduce the economic costs. The simulation results verify the effectiveness of the proposed algorithm on improving the tracking performance, enhancing robustness, and reducing economic costs. The method proposed in this study owns great worth in practical application.

Tolerance Is Not Enough: The Moderating Role of Optimism on Perceptions of Regional Economic Performance

ERIC Educational Resources Information Center

Lopes, Miguel Pereira; da Palma, Patricia Jardim; e Cunha, Miguel Pina

2011-01-01

Current theories on economic growth are stressing the important role of creativity and innovation as a main driver of regional development. Some perspectives, like Richard Florida's "creative class theory", have elected tolerance and diversity as a core concept in explaining differential development between different places, but his assumptions…

Performance assessment and optimization of an irreversible nano-scale Stirling engine cycle operating with Maxwell-Boltzmann gas

NASA Astrophysics Data System (ADS)

Ahmadi, Mohammad H.; Ahmadi, Mohammad-Ali; Pourfayaz, Fathollah

2015-09-01

Developing new technologies like nano-technology improves the performance of the energy industries. Consequently, emerging new groups of thermal cycles in nano-scale can revolutionize the energy systems' future. This paper presents a thermo-dynamical study of a nano-scale irreversible Stirling engine cycle with the aim of optimizing the performance of the Stirling engine cycle. In the Stirling engine cycle the working fluid is an Ideal Maxwell-Boltzmann gas. Moreover, two different strategies are proposed for a multi-objective optimization issue, and the outcomes of each strategy are evaluated separately. The first strategy is proposed to maximize the ecological coefficient of performance (ECOP), the dimensionless ecological function (ecf) and the dimensionless thermo-economic objective function ( F . Furthermore, the second strategy is suggested to maximize the thermal efficiency ( η), the dimensionless ecological function (ecf) and the dimensionless thermo-economic objective function ( F). All the strategies in the present work are executed via a multi-objective evolutionary algorithms based on NSGA∥ method. Finally, to achieve the final answer in each strategy, three well-known decision makers are executed. Lastly, deviations of the outcomes gained in each strategy and each decision maker are evaluated separately.

Dataset of working conditions and thermo-economic performances for hybrid organic Rankine plants fed by solar and low-grade energy sources.

PubMed

Scardigno, Domenico; Fanelli, Emanuele; Viggiano, Annarita; Braccio, Giacobbe; Magi, Vinicio

2016-06-01

This article provides the dataset of operating conditions of a hybrid organic Rankine plant generated by the optimization procedure employed in the research article "A genetic optimization of a hybrid organic Rankine plant for solar and low-grade energy sources" (Scardigno et al., 2015) [1]. The methodology used to obtain the data is described. The operating conditions are subdivided into two separate groups: feasible and unfeasible solutions. In both groups, the values of the design variables are given. Besides, the subset of feasible solutions is described in details, by providing the thermodynamic and economic performances, the temperatures at some characteristic sections of the thermodynamic cycle, the net power, the absorbed powers and the area of the heat exchange surfaces.

Thermodynamic Analysis and Optimization of a High Temperature Triple Absorption Heat Transformer

PubMed Central

Khamooshi, Mehrdad; Yari, Mortaza; Egelioglu, Fuat; Salati, Hana

2014-01-01

First law of thermodynamics has been used to analyze and optimize inclusively the performance of a triple absorption heat transformer operating with LiBr/H2O as the working pair. A thermodynamic model was developed in EES (engineering equation solver) to estimate the performance of the system in terms of the most essential parameters. The assumed parameters are the temperature of the main components, weak and strong solutions, economizers' efficiencies, and bypass ratios. The whole cycle is optimized by EES software from the viewpoint of maximizing the COP via applying the direct search method. The optimization results showed that the COP of 0.2491 is reachable by the proposed cycle. PMID:25136702

Evolutionary Bi-objective Optimization for Bulldozer and Its Blade in Soil Cutting

NASA Astrophysics Data System (ADS)

Sharma, Deepak; Barakat, Nada

2018-02-01

An evolutionary optimization approach is adopted in this paper for simultaneously achieving the economic and productive soil cutting. The economic aspect is defined by minimizing the power requirement from the bulldozer, and the soil cutting is made productive by minimizing the time of soil cutting. For determining the power requirement, two force models are adopted from the literature to quantify the cutting force on the blade. Three domain-specific constraints are also proposed, which are limiting the power from the bulldozer, limiting the maximum force on the bulldozer blade and achieving the desired production rate. The bi-objective optimization problem is solved using five benchmark multi-objective evolutionary algorithms and one classical optimization technique using the ɛ-constraint method. The Pareto-optimal solutions are obtained with the knee-region. Further, the post-optimal analysis is performed on the obtained solutions to decipher relationships among the objectives and decision variables. Such relationships are later used for making guidelines for selecting the optimal set of input parameters. The obtained results are then compared with the experiment results from the literature that show a close agreement among them.

A FRAMEWORK TO DESIGN AND OPTIMIZE CHEMICAL FLOODING PROCESSES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mojdeh Delshad; Gary A. Pope; Kamy Sepehrnoori

2005-07-01

The goal of this proposed research is to provide an efficient and user friendly simulation framework for screening and optimizing chemical/microbial enhanced oil recovery processes. The framework will include (1) a user friendly interface to identify the variables that have the most impact on oil recovery using the concept of experimental design and response surface maps, (2) UTCHEM reservoir simulator to perform the numerical simulations, and (3) an economic model that automatically imports the simulation production data to evaluate the profitability of a particular design. Such a reservoir simulation framework is not currently available to the oil industry. The objectivesmore » of Task 1 are to develop three primary modules representing reservoir, chemical, and well data. The modules will be interfaced with an already available experimental design model. The objective of the Task 2 is to incorporate UTCHEM reservoir simulator and the modules with the strategic variables and developing the response surface maps to identify the significant variables from each module. The objective of the Task 3 is to develop the economic model designed specifically for the chemical processes targeted in this proposal and interface the economic model with UTCHEM production output. Task 4 is on the validation of the framework and performing simulations of oil reservoirs to screen, design and optimize the chemical processes.« less

A Framework to Design and Optimize Chemical Flooding Processes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mojdeh Delshad; Gary A. Pope; Kamy Sepehrnoori

2006-08-31

The goal of this proposed research is to provide an efficient and user friendly simulation framework for screening and optimizing chemical/microbial enhanced oil recovery processes. The framework will include (1) a user friendly interface to identify the variables that have the most impact on oil recovery using the concept of experimental design and response surface maps, (2) UTCHEM reservoir simulator to perform the numerical simulations, and (3) an economic model that automatically imports the simulation production data to evaluate the profitability of a particular design. Such a reservoir simulation framework is not currently available to the oil industry. The objectivesmore » of Task 1 are to develop three primary modules representing reservoir, chemical, and well data. The modules will be interfaced with an already available experimental design model. The objective of the Task 2 is to incorporate UTCHEM reservoir simulator and the modules with the strategic variables and developing the response surface maps to identify the significant variables from each module. The objective of the Task 3 is to develop the economic model designed specifically for the chemical processes targeted in this proposal and interface the economic model with UTCHEM production output. Task 4 is on the validation of the framework and performing simulations of oil reservoirs to screen, design and optimize the chemical processes.« less

A FRAMEWORK TO DESIGN AND OPTIMIZE CHEMICAL FLOODING PROCESSES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mojdeh Delshad; Gary A. Pope; Kamy Sepehrnoori

2004-11-01

The goal of this proposed research is to provide an efficient and user friendly simulation framework for screening and optimizing chemical/microbial enhanced oil recovery processes. The framework will include (1) a user friendly interface to identify the variables that have the most impact on oil recovery using the concept of experimental design and response surface maps, (2) UTCHEM reservoir simulator to perform the numerical simulations, and (3) an economic model that automatically imports the simulation production data to evaluate the profitability of a particular design. Such a reservoir simulation framework is not currently available to the oil industry. The objectivesmore » of Task 1 are to develop three primary modules representing reservoir, chemical, and well data. The modules will be interfaced with an already available experimental design model. The objective of the Task 2 is to incorporate UTCHEM reservoir simulator and the modules with the strategic variables and developing the response surface maps to identify the significant variables from each module. The objective of the Task 3 is to develop the economic model designed specifically for the chemical processes targeted in this proposal and interface the economic model with UTCHEM production output. Task 4 is on the validation of the framework and performing simulations of oil reservoirs to screen, design and optimize the chemical processes.« less

Potential of connected devices to optimize cattle reproduction.

PubMed

Saint-Dizier, Marie; Chastant-Maillard, Sylvie

2018-05-01

Estrus and calving are two major events of reproduction that benefit from connected devices because of their crucial importance in herd economics and the amount of time required for their detection. The objectives of this review are to: 1) provide an update on performances reached by sensor systems to detect estrus and calving time; 2) discuss current economic issues related to connected devices for the management of cattle reproduction; 3) propose perspectives for these devices. The main physiological parameters monitored separately or in combination by connected devices are the cow activity, body temperature and rumination or eating behavior. The combination of several indicators in one sensor may maximize the performances of estrus and calving detection. An effort remains to be made for the prediction of calvings that will require human assistance (dystocia). The main reasons to invest in connected devices are to optimize herd reproductive performances and reduce labor on farm. The economic benefit was evaluated for estrus detection and depends on the initial herd performances, herd size, labor cost and price of the equipment. Major issues associated with the use of automated sensor systems are the weight of financial investment, the lack of economic analysis and limited skills of the users to manage associated technologies. In the near future, connected devices may allow a precise phenotyping of reproductive and health traits on animals and could help to improve animal welfare and public perception of animal production. Copyright © 2017 Elsevier Inc. All rights reserved.

[Imaging center - optimization of the imaging process].

PubMed

Busch, H-P

2013-04-01

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

Realizing a partial general quantum cloning machine with superconducting quantum-interference devices in a cavity QED

NASA Astrophysics Data System (ADS)

Fang, Bao-Long; Yang, Zhen; Ye, Liu

2009-05-01

We propose a scheme for implementing a partial general quantum cloning machine with superconducting quantum-interference devices coupled to a nonresonant cavity. By regulating the time parameters, our system can perform optimal symmetric (asymmetric) universal quantum cloning, optimal symmetric (asymmetric) phase-covariant cloning, and optimal symmetric economical phase-covariant cloning. In the scheme the cavity is only virtually excited, thus, the cavity decay is suppressed during the cloning operations.

Economic Benefits of Improved Information on Worldwide Crop Production: An Optimal Decision Model of Production and Distribution with Application to Wheat, Corn, and Soybeans

NASA Technical Reports Server (NTRS)

Andrews, J.

1977-01-01

An optimal decision model of crop production, trade, and storage was developed for use in estimating the economic consequences of improved forecasts and estimates of worldwide crop production. The model extends earlier distribution benefits models to include production effects as well. Application to improved information systems meeting the goals set in the large area crop inventory experiment (LACIE) indicates annual benefits to the United States of $200 to $250 million for wheat, $50 to $100 million for corn, and $6 to $11 million for soybeans, using conservative assumptions on expected LANDSAT system performance.

Modeling uncertainty in producing natural gas from tight sands

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chermak, J.M.; Dahl, C.A.; Patrick, R.H

1995-12-31

Since accurate geologic, petroleum engineering, and economic information are essential ingredients in making profitable production decisions for natural gas, we combine these ingredients in a dynamic framework to model natural gas reservoir production decisions. We begin with the certainty case before proceeding to consider how uncertainty might be incorporated in the decision process. Our production model uses dynamic optimal control to combine economic information with geological constraints to develop optimal production decisions. To incorporate uncertainty into the model, we develop probability distributions on geologic properties for the population of tight gas sand wells and perform a Monte Carlo study tomore » select a sample of wells. Geological production factors, completion factors, and financial information are combined into the hybrid economic-petroleum reservoir engineering model to determine the optimal production profile, initial gas stock, and net present value (NPV) for an individual well. To model the probability of the production abandonment decision, the NPV data is converted to a binary dependent variable. A logit model is used to model this decision as a function of the above geological and economic data to give probability relationships. Additional ways to incorporate uncertainty into the decision process include confidence intervals and utility theory.« less

Applying a multi-criteria genetic algorithm framework for brownfield reuse optimization: improving redevelopment options based on stakeholder preferences.

PubMed

Morio, Maximilian; Schädler, Sebastian; Finkel, Michael

2013-11-30

The reuse of underused or abandoned contaminated land, so-called brownfields, is increasingly seen as an important means for reducing the consumption of land and natural resources. Many existing decision support systems are not appropriate because they focus mainly on economic aspects, while neglecting sustainability issues. To fill this gap, we present a framework for spatially explicit, integrated planning and assessment of brownfield redevelopment options. A multi-criteria genetic algorithm allows us to determine optimal land use configurations with respect to assessment criteria and given constraints on the composition of land use classes, according to, e.g., stakeholder preferences. Assessment criteria include sustainability indicators as well as economic aspects, including remediation costs and land value. The framework is applied to a case study of a former military site near Potsdam, Germany. Emphasis is placed on the trade-off between possibly conflicting objectives (e.g., economic goals versus the need for sustainable development in the regional context of the brownfield site), which may represent different perspectives of involved stakeholders. The economic analysis reveals the trade-off between the increase in land value due to reuse and the costs for remediation required to make reuse possible. We identify various reuse options, which perform similarly well although they exhibit different land use patterns. High-cost high-value options dominated by residential land use and low-cost low-value options with less sensitive land use types may perform equally well economically. The results of the integrated analysis show that the quantitative integration of sustainability may change optimal land use patterns considerably. Copyright © 2013 Elsevier Ltd. All rights reserved.

A CPV Thesis

NASA Astrophysics Data System (ADS)

Schultz, David S.; Ghosh, Shondip; Grimmer, Christopher S.; Mack, Hunter

2011-10-01

The viability of a concentrator technology is determined by five interrelated factors: economic benefit, cell performance under concentration, thermal management, optical performance and manufacturability. Considering these factors, the 5- 10x concentration range is ideal for silicon-based receivers because this level of concentration captures the bulk of available economic gains while mitigating technical risk. Significant gains in capital efficiency are forsaken below the 5x concentration level. Above the 10x level of concentration, marginal improvements to economic benefit are achieved, but threats to reliability emerge and tend to erode the available economic benefit. Furthermore, optic solutions that provide for concentration above 10x tend to force a departure from low-profile flat-plate designs that are most adoptable. For silicon based receivers, a 5-10x level of concentration within a traditional module form factor is optimal.

Investigating the enhanced Best Performance Algorithm for Annual Crop Planning problem based on economic factors.

PubMed

Adewumi, Aderemi Oluyinka; Chetty, Sivashan

2017-01-01

The Annual Crop Planning (ACP) problem was a recently introduced problem in the literature. This study further expounds on this problem by presenting a new mathematical formulation, which is based on market economic factors. To determine solutions, a new local search metaheuristic algorithm is investigated which is called the enhanced Best Performance Algorithm (eBPA). eBPA's results are compared against two well-known local search metaheuristic algorithms; these include Tabu Search and Simulated Annealing. The results show the potential of the eBPA for continuous optimization problems.

More Health Expenditure, Better Economic Performance? Empirical Evidence From OECD Countries.

PubMed

Wang, Fuhmei

2015-01-01

Recent economic downturns have led many countries to reduce health spending dramatically, with the World Health Organization raising concerns over the effects of this, in particular among the poor and vulnerable. With the provision of appropriate health care, the population of a country could have better health, thus strengthening the nation's human capital, which could contribute to economic growth through improved productivity. How much should countries spend on health care? This study aims to estimate the optimal health care expenditure in a growing economy. Applying the experiences of countries from the Organization for Economic Co-Operation and Development (OECD) over the period 1990 to 2009, this research introduces the method of system generalized method of moments (GMM) to derive the design of the estimators of the focal variables. Empirical evidence indicates that when the ratio of health spending to gross domestic product (GDP) is less than the optimal level of 7.55%, increases in health spending effectively lead to better economic performance. Above this, more spending does not equate to better care. The real level of health spending in OECD countries is 5.48% of GDP, with a 1.87% economic growth rate. The question which is posed by this study is a pertinent one, especially in the current context of financially constrained health systems around the world. The analytical results of this work will allow policymakers to better allocate scarce resources to achieve their macroeconomic goals. © The Author(s) 2015.

More Health Expenditure, Better Economic Performance? Empirical Evidence From OECD Countries

PubMed Central

Wang, Fuhmei

2015-01-01

Recent economic downturns have led many countries to reduce health spending dramatically, with the World Health Organization raising concerns over the effects of this, in particular among the poor and vulnerable. With the provision of appropriate health care, the population of a country could have better health, thus strengthening the nation’s human capital, which could contribute to economic growth through improved productivity. How much should countries spend on health care? This study aims to estimate the optimal health care expenditure in a growing economy. Applying the experiences of countries from the Organization for Economic Co-Operation and Development (OECD) over the period 1990 to 2009, this research introduces the method of system generalized method of moments (GMM) to derive the design of the estimators of the focal variables. Empirical evidence indicates that when the ratio of health spending to gross domestic product (GDP) is less than the optimal level of 7.55%, increases in health spending effectively lead to better economic performance. Above this, more spending does not equate to better care. The real level of health spending in OECD countries is 5.48% of GDP, with a 1.87% economic growth rate. The question which is posed by this study is a pertinent one, especially in the current context of financially constrained health systems around the world. The analytical results of this work will allow policymakers to better allocate scarce resources to achieve their macroeconomic goals. PMID:26310501

Design of shared unit-dose drug distribution network using multi-level particle swarm optimization.

PubMed

Chen, Linjie; Monteiro, Thibaud; Wang, Tao; Marcon, Eric

2018-03-01

Unit-dose drug distribution systems provide optimal choices in terms of medication security and efficiency for organizing the drug-use process in large hospitals. As small hospitals have to share such automatic systems for economic reasons, the structure of their logistic organization becomes a very sensitive issue. In the research reported here, we develop a generalized multi-level optimization method - multi-level particle swarm optimization (MLPSO) - to design a shared unit-dose drug distribution network. Structurally, the problem studied can be considered as a type of capacitated location-routing problem (CLRP) with new constraints related to specific production planning. This kind of problem implies that a multi-level optimization should be performed in order to minimize logistic operating costs. Our results show that with the proposed algorithm, a more suitable modeling framework, as well as computational time savings and better optimization performance are obtained than that reported in the literature on this subject.

Engineering and organizational solutions for improvement of engineering and economic characteristics of the TPE-216 boilers equipped with MV-3300/800/490 pulverizing fans

NASA Astrophysics Data System (ADS)

Kirillov, M. V.; Safronov, P. G.

2014-07-01

Efficiency of coal-fired boilers is determined in many respects by optimal operation of the coal-pulverizing plants that are increasingly frequently equipped with pulverizing fans. By an example of retrofitted MV-3300/800/490 pulverizing fans, the effects of different factors on the performance and economic efficiency of the coal-pulverizing plants are analyzed. The experience gained in retrofitting MV-3300/800/490 pulverizing fans by introducing the three-crusher operation mode of a TPE-216 boiler employing the internal recirculation and a blading device in the classifier was also studied. Optimization of the boiler's operation mode was made when switching over from the four-crusher to the three-crusher mode, which considerably improved the engineering and economic characteristics.

Optimal Management of Geothermal Heat Extraction

NASA Astrophysics Data System (ADS)

Patel, I. H.; Bielicki, J. M.; Buscheck, T. A.

2015-12-01

Geothermal energy technologies use the constant heat flux from the subsurface in order to produce heat or electricity for societal use. As such, a geothermal energy system is not inherently variable, like systems based on wind and solar resources, and an operator can conceivably control the rate at which heat is extracted and used directly, or converted into a commodity that is used. Although geothermal heat is a renewable resource, this heat can be depleted over time if the rate of heat extraction exceeds the natural rate of renewal (Rybach, 2003). For heat extraction used for commodities that are sold on the market, sustainability entails balancing the rate at which the reservoir renews with the rate at which heat is extracted and converted into profit, on a net present value basis. We present a model that couples natural resource economic approaches for managing renewable resources with simulations of geothermal reservoir performance in order to develop an optimal heat mining strategy that balances economic gain with the performance and renewability of the reservoir. Similar optimal control approaches have been extensively studied for renewable natural resource management of fisheries and forests (Bonfil, 2005; Gordon, 1954; Weitzman, 2003). Those models determine an optimal path of extraction of fish or timber, by balancing the regeneration of stocks of fish or timber that are not harvested with the profit from the sale of the fish or timber that is harvested. Our model balances the regeneration of reservoir temperature with the net proceeds from extracting heat and converting it to electricity that is sold to consumers. We used the Non-isothermal Unconfined-confined Flow and Transport (NUFT) model (Hao, Sun, & Nitao, 2011) to simulate the performance of a sedimentary geothermal reservoir under a variety of geologic and operational situations. The results of NUFT are incorporated into the natural resource economics model to determine production strategies that maximize net present value given the performance of the geothermal resource.

Effect of land tenure and stakeholders attitudes on optimization of conservation practices in agricultural watersheds

NASA Astrophysics Data System (ADS)

Piemonti, A. D.; Babbar-Sebens, M.; Luzar, E. J.

2012-12-01

Modeled watershed management plans have become valuable tools for evaluating the effectiveness and impacts of conservation practices on hydrologic processes in watersheds. In multi-objective optimization approaches, several studies have focused on maximizing physical, ecological, or economic benefits of practices in a specific location, without considering the relationship between social systems and social attitudes on the overall optimality of the practice at that location. For example, objectives that have been commonly used in spatial optimization of practices are economic costs, sediment loads, nutrient loads and pesticide loads. Though the benefits derived from these objectives are generally oriented towards community preferences, they do not represent attitudes of landowners who might operate their land differently than their neighbors (e.g. farm their own land or rent the land to someone else) and might have different social/personal drivers that motivate them to adopt the practices. In addition, a distribution of such landowners could exist in the watershed, leading to spatially varying preferences to practices. In this study we evaluated the effect of three different land tenure types on the spatial-optimization of conservation practices. To perform the optimization, we used a uniform distribution of land tenure type and a spatially varying distribution of land tenure type. Our results show that for a typical Midwestern agricultural watershed, the most optimal solutions (i.e. highest benefits for minimum economic costs) found were for a uniform distribution of landowners who operate their own land. When a different land-tenure was used for the watershed, the optimized alternatives did not change significantly for nitrates reduction benefits and sediment reduction benefits, but were attained at economic costs much higher than the costs of the landowner who farms her/his own land. For example, landowners who rent to cash-renters would have to spend ~120% higher costs than landowners who operate their own land, to attain the same benefits. We also tested the effect of different social attitudes on the final preferences of the optimized alternatives and its consequences over the total effectiveness of the standard optimization approaches. The results suggest that, for example, when practices were removed from the system due to landowners' attitudes driven by economic profits, then the modified alternatives experienced a decrease in nitrates reduction by 2-50%, and decrease in peak flow reductions by 11-98 %, and decrease in sediments reduction by 20-77%.

Assessing groundwater policy with coupled economic-groundwater hydrologic modeling

NASA Astrophysics Data System (ADS)

Mulligan, Kevin B.; Brown, Casey; Yang, Yi-Chen E.; Ahlfeld, David P.

2014-03-01

This study explores groundwater management policies and the effect of modeling assumptions on the projected performance of those policies. The study compares an optimal economic allocation for groundwater use subject to streamflow constraints, achieved by a central planner with perfect foresight, with a uniform tax on groundwater use and a uniform quota on groundwater use. The policies are compared with two modeling approaches, the Optimal Control Model (OCM) and the Multi-Agent System Simulation (MASS). The economic decision models are coupled with a physically based representation of the aquifer using a calibrated MODFLOW groundwater model. The results indicate that uniformly applied policies perform poorly when simulated with more realistic, heterogeneous, myopic, and self-interested agents. In particular, the effects of the physical heterogeneity of the basin and the agents undercut the perceived benefits of policy instruments assessed with simple, single-cell groundwater modeling. This study demonstrates the results of coupling realistic hydrogeology and human behavior models to assess groundwater management policies. The Republican River Basin, which overlies a portion of the Ogallala aquifer in the High Plains of the United States, is used as a case study for this analysis.

Optimal technology investment strategies for a reusable launch vehicle

NASA Technical Reports Server (NTRS)

Moore, A. A.; Braun, R. D.; Powell, R. W.

1995-01-01

Within the present budgetary environment, developing the technology that leads to an operationally efficient space transportation system with the required performance is a challenge. The present research focuses on a methodology to determine high payoff technology investment strategies. Research has been conducted at Langley Research Center in which design codes for the conceptual analysis of space transportation systems have been integrated in a multidisciplinary design optimization approach. The current study integrates trajectory, propulsion, weights and sizing, and cost disciplines where the effect of technology maturation on the development cost of a single stage to orbit reusable launch vehicle is examined. Results show that the technology investment prior to full-scale development has a significant economic payoff. The design optimization process is used to determine strategic allocations of limited technology funding to maximize the economic payoff.

Optimal system sizing in grid-connected photovoltaic applications

NASA Astrophysics Data System (ADS)

Simoens, H. M.; Baert, D. H.; de Mey, G.

A costs/benefits analysis for optimizing the combination of photovoltaic (PV) panels, batteries and an inverter for grid interconnected systems at a 500 W/day Belgian residence is presented. It is assumed that some power purchases from the grid will always be necessary, and that excess PV power can be fed into the grid. A minimal value for the cost divided by the performance is defined for economic optimization. Shortages and excesses are calculated for PV panels of 0.5-10 kWp output, with consideration given to the advantages of a battery back-up. The minimal economic value is found to increase with the magnitude of PV output, and an inverter should never be rated at more than half the array maximum output. A maximum panel size for the Belgian residence is projected to be 6 kWp.

Model Predictive Control-based Optimal Coordination of Distributed Energy Resources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming

2013-01-07

Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive controlmore » (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.« less

Model Predictive Control-based Optimal Coordination of Distributed Energy Resources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming

2013-04-03

Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive controlmore » (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.« less

Intelligent and robust optimization frameworks for smart grids

NASA Astrophysics Data System (ADS)

Dhansri, Naren Reddy

A smart grid implies a cyberspace real-time distributed power control system to optimally deliver electricity based on varying consumer characteristics. Although smart grids solve many of the contemporary problems, they give rise to new control and optimization problems with the growing role of renewable energy sources such as wind or solar energy. Under highly dynamic nature of distributed power generation and the varying consumer demand and cost requirements, the total power output of the grid should be controlled such that the load demand is met by giving a higher priority to renewable energy sources. Hence, the power generated from renewable energy sources should be optimized while minimizing the generation from non renewable energy sources. This research develops a demand-based automatic generation control and optimization framework for real-time smart grid operations by integrating conventional and renewable energy sources under varying consumer demand and cost requirements. Focusing on the renewable energy sources, the intelligent and robust control frameworks optimize the power generation by tracking the consumer demand in a closed-loop control framework, yielding superior economic and ecological benefits and circumvent nonlinear model complexities and handles uncertainties for superior real-time operations. The proposed intelligent system framework optimizes the smart grid power generation for maximum economical and ecological benefits under an uncertain renewable wind energy source. The numerical results demonstrate that the proposed framework is a viable approach to integrate various energy sources for real-time smart grid implementations. The robust optimization framework results demonstrate the effectiveness of the robust controllers under bounded power plant model uncertainties and exogenous wind input excitation while maximizing economical and ecological performance objectives. Therefore, the proposed framework offers a new worst-case deterministic optimization algorithm for smart grid automatic generation control.

Development of performance properties of ternary mixtures : field demonstrations and project summary.

DOT National Transportation Integrated Search

2012-07-01

Supplementary cementitious materials (SCM) have become common parts of modern concrete practice. The blending of two or three : cementitious materials to optimize durability, strength, or economics provides owners, engineers, materials suppliers, and...

Optimizing the nitrogen application rate for maize and wheat based on yield and environment on the Northern China Plain.

PubMed

Zhang, Yitao; Wang, Hongyuan; Lei, Qiuliang; Luo, Jiafa; Lindsey, Stuart; Zhang, Jizong; Zhai, Limei; Wu, Shuxia; Zhang, Jingsuo; Liu, Xiaoxia; Ren, Tianzhi; Liu, Hongbin

2018-03-15

Optimizing the nitrogen (N) application rate can increase crop yield while reducing the environmental risks. However, the optimal N rates vary substantially when different targets such as maximum yield or maximum economic benefit are considered. Taking the wheat-maize rotation cropping system on the North China Plain as a case study, we quantified the variation of N application rates when targeting constraints on yield, economic performance, N uptake and N utilization, by conducting field experiments between 2011 and 2013. Results showed that the optimal N application rate was highest when targeting N uptake (240kgha -1 for maize, and 326kgha -1 for wheat), followed by crop yield (208kgha -1 for maize, and 277kgha -1 for wheat) and economic income (191kgha -1 for maize, and 253kgha -1 for wheat). If environmental costs were considered, the optimal N application rates were further reduced by 20-30% compared to those when targeting maximum economic income. However, the optimal N rate, with environmental cost included, may result in soil nutrient mining under maize, and an extra input of 43kgNha -1 was needed to make the soil N balanced and maintain soil fertility in the long term. To obtain a win-win situation for both yield and environment, the optimal N rate should be controlled at 179kgha -1 for maize, which could achieve above 99.5% of maximum yield and have a favorable N balance, and at 202kgha -1 for wheat to achieve 97.4% of maximum yield, which was about 20kgNha -1 higher than that when N surplus was nil. Although these optimal N rates vary on spatial and temporal scales, they are still effective for the North China Plain where 32% of China's total maize and 45% of China's total wheat are produced. More experiments are still needed to determine the optimal N application rates in other regions. Use of these different optimal N rates would contribute to improving the sustainability of agricultural development in China. Copyright © 2017 Elsevier B.V. All rights reserved.

Value versus Accuracy: application of seasonal forecasts to a hydro-economic optimization model for the Sudanese Blue Nile

NASA Astrophysics Data System (ADS)

Satti, S.; Zaitchik, B. F.; Siddiqui, S.; Badr, H. S.; Shukla, S.; Peters-Lidard, C. D.

2015-12-01

The unpredictable nature of precipitation within the East African (EA) region makes it one of the most vulnerable, food insecure regions in the world. There is a vital need for forecasts to inform decision makers, both local and regional, and to help formulate the region's climate change adaptation strategies. Here, we present a suite of different seasonal forecast models, both statistical and dynamical, for the EA region. Objective regionalization is performed for EA on the basis of interannual variability in precipitation in both observations and models. This regionalization is applied as the basis for calculating a number of standard skill scores to evaluate each model's forecast accuracy. A dynamically linked Land Surface Model (LSM) is then applied to determine forecasted flows, which drive the Sudanese Hydroeconomic Optimization Model (SHOM). SHOM combines hydrologic, agronomic and economic inputs to determine the optimal decisions that maximize economic benefits along the Sudanese Blue Nile. This modeling sequence is designed to derive the potential added value of information of each forecasting model to agriculture and hydropower management. A rank of each model's forecasting skill score along with its added value of information is analyzed in order compare the performance of each forecast. This research aims to improve understanding of how characteristics of accuracy, lead time, and uncertainty of seasonal forecasts influence their utility to water resources decision makers who utilize them.

Optimization of Land Use Suitability for Agriculture Using Integrated Geospatial Model and Genetic Algorithms

NASA Astrophysics Data System (ADS)

Mansor, S. B.; Pormanafi, S.; Mahmud, A. R. B.; Pirasteh, S.

2012-08-01

In this study, a geospatial model for land use allocation was developed from the view of simulating the biological autonomous adaptability to environment and the infrastructural preference. The model was developed based on multi-agent genetic algorithm. The model was customized to accommodate the constraint set for the study area, namely the resource saving and environmental-friendly. The model was then applied to solve the practical multi-objective spatial optimization allocation problems of land use in the core region of Menderjan Basin in Iran. The first task was to study the dominant crops and economic suitability evaluation of land. Second task was to determine the fitness function for the genetic algorithms. The third objective was to optimize the land use map using economical benefits. The results has indicated that the proposed model has much better performance for solving complex multi-objective spatial optimization allocation problems and it is a promising method for generating land use alternatives for further consideration in spatial decision-making.

Economic and environmental optimization of a multi-site utility network for an industrial complex.

PubMed

Kim, Sang Hun; Yoon, Sung-Geun; Chae, Song Hwa; Park, Sunwon

2010-01-01

Most chemical companies consume a lot of steam, water and electrical resources in the production process. Given recent record fuel costs, utility networks must be optimized to reduce the overall cost of production. Environmental concerns must also be considered when preparing modifications to satisfy the requirements for industrial utilities, since wastes discharged from the utility networks are restricted by environmental regulations. Construction of Eco-Industrial Parks (EIPs) has drawn attention as a promising approach for retrofitting existing industrial parks to improve energy efficiency. The optimization of the utility network within an industrial complex is one of the most important undertakings to minimize energy consumption and waste loads in the EIP. In this work, a systematic approach to optimize the utility network of an industrial complex is presented. An important issue in the optimization of a utility network is the desire of the companies to achieve high profits while complying with the environmental regulations. Therefore, the proposed optimization was performed with consideration of both economic and environmental factors. The proposed approach consists of unit modeling using thermodynamic principles, mass and energy balances, development of a multi-period Mixed Integer Linear Programming (MILP) model for the integration of utility systems in an industrial complex, and an economic/environmental analysis of the results. This approach is applied to the Yeosu Industrial Complex, considering seasonal utility demands. The results show that both the total utility cost and waste load are reduced by optimizing the utility network of an industrial complex. 2009 Elsevier Ltd. All rights reserved.

Nonlinear Multiobjective MPC-Based Optimal Operation of a High Consistency Refining System in Papermaking

DOE PAGES

Li, Mingjie; Zhou, Ping; Wang, Hong; ...

2017-09-19

As one of the most important unit in the papermaking industry, the high consistency (HC) refining system is confronted with challenges such as improving pulp quality, energy saving, and emissions reduction in its operation processes. Here in this correspondence, an optimal operation of HC refining system is presented using nonlinear multiobjective model predictive control strategies that aim at set-point tracking objective of pulp quality, economic objective, and specific energy (SE) consumption objective, respectively. First, a set of input and output data at different times are employed to construct the subprocess model of the state process model for the HC refiningmore » system, and then the Wiener-type model can be obtained through combining the mechanism model of Canadian Standard Freeness and the state process model that determines their structures based on Akaike information criterion. Second, the multiobjective optimization strategy that optimizes both the set-point tracking objective of pulp quality and SE consumption is proposed simultaneously, which uses NSGA-II approach to obtain the Pareto optimal set. Furthermore, targeting at the set-point tracking objective of pulp quality, economic objective, and SE consumption objective, the sequential quadratic programming method is utilized to produce the optimal predictive controllers. In conclusion, the simulation results demonstrate that the proposed methods can make the HC refining system provide a better performance of set-point tracking of pulp quality when these predictive controllers are employed. In addition, while the optimal predictive controllers orienting with comprehensive economic objective and SE consumption objective, it has been shown that they have significantly reduced the energy consumption.« less

Nonlinear Multiobjective MPC-Based Optimal Operation of a High Consistency Refining System in Papermaking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Mingjie; Zhou, Ping; Wang, Hong

As one of the most important unit in the papermaking industry, the high consistency (HC) refining system is confronted with challenges such as improving pulp quality, energy saving, and emissions reduction in its operation processes. Here in this correspondence, an optimal operation of HC refining system is presented using nonlinear multiobjective model predictive control strategies that aim at set-point tracking objective of pulp quality, economic objective, and specific energy (SE) consumption objective, respectively. First, a set of input and output data at different times are employed to construct the subprocess model of the state process model for the HC refiningmore » system, and then the Wiener-type model can be obtained through combining the mechanism model of Canadian Standard Freeness and the state process model that determines their structures based on Akaike information criterion. Second, the multiobjective optimization strategy that optimizes both the set-point tracking objective of pulp quality and SE consumption is proposed simultaneously, which uses NSGA-II approach to obtain the Pareto optimal set. Furthermore, targeting at the set-point tracking objective of pulp quality, economic objective, and SE consumption objective, the sequential quadratic programming method is utilized to produce the optimal predictive controllers. In conclusion, the simulation results demonstrate that the proposed methods can make the HC refining system provide a better performance of set-point tracking of pulp quality when these predictive controllers are employed. In addition, while the optimal predictive controllers orienting with comprehensive economic objective and SE consumption objective, it has been shown that they have significantly reduced the energy consumption.« less

Thermodynamic and economic analysis of a gas turbine combined cycle plant with oxy-combustion

NASA Astrophysics Data System (ADS)

Kotowicz, Janusz; Job, Marcin

2013-12-01

This paper presents a gas turbine combined cycle plant with oxy-combustion and carbon dioxide capture. A gas turbine part of the unit with the operating parameters is presented. The methodology and results of optimization by the means of a genetic algorithm for the steam parts in three variants of the plant are shown. The variants of the plant differ by the heat recovery steam generator (HRSG) construction: the singlepressure HRSG (1P), the double-pressure HRSG with reheating (2PR), and the triple-pressure HRSG with reheating (3PR). For obtained results in all variants an economic evaluation was performed. The break-even prices of electricity were determined and the sensitivity analysis to the most significant economic factors were performed.

Model-based transportation performance : a comparative framework and literature synthesis [research brief].

DOT National Transportation Integrated Search

2012-04-01

In a time of serious fiscal and environmental constraints, there has been a renewed call to identify transportation investments and related policy decisions that will optimize transportation, environmental, economic, and equity outcomes. Several infl...

Selection of Sustainable Processes using Sustainability ...

EPA Pesticide Factsheets

Chemical products can be obtained by process pathways involving varying amounts and types of resources, utilities, and byproduct formation. When such competing process options such as six processes for making methanol as are considered in this study, it is necessary to identify the most sustainable option. Sustainability of a chemical process is generally evaluated with indicators that require process and chemical property data. These indicators individually reflect the impacts of the process on areas of sustainability, such as the environment or society. In order to choose among several alternative processes an overall comparative analysis is essential. Generally net profit will show the most economic process. A mixed integer optimization problem can also be solved to identify the most economic among competing processes. This method uses economic optimization and leaves aside the environmental and societal impacts. To make a decision on the most sustainable process, the method presented here rationally aggregates the sustainability indicators into a single index called sustainability footprint (De). Process flow and economic data were used to compute the indicator values. Results from sustainability footprint (De) are compared with those from solving a mixed integer optimization problem. In order to identify the rank order of importance of the indicators, a multivariate analysis is performed using partial least square variable importance in projection (PLS-VIP)

Combined Economic and Hydrologic Modeling to Support Collaborative Decision Making Processes

NASA Astrophysics Data System (ADS)

Sheer, D. P.

2008-12-01

For more than a decade, the core concept of the author's efforts in support of collaborative decision making has been a combination of hydrologic simulation and multi-objective optimization. The modeling has generally been used to support collaborative decision making processes. The OASIS model developed by HydroLogics Inc. solves a multi-objective optimization at each time step using a mixed integer linear program (MILP). The MILP can be configured to include any user defined objective, including but not limited too economic objectives. For example, an estimated marginal value for water for crops and M&I use were included in the objective function to drive trades in a model of the lower Rio Grande. The formulation of the MILP, constraints and objectives, in any time step is conditional: it changes based on the value of state variables and dynamic external forcing functions, such as rainfall, hydrology, market prices, arrival of migratory fish, water temperature, etc. It therefore acts as a dynamic short term multi-objective economic optimization for each time step. MILP is capable of solving a general problem that includes a very realistic representation of the physical system characteristics in addition to the normal multi-objective optimization objectives and constraints included in economic models. In all of these models, the short term objective function is a surrogate for achieving long term multi-objective results. The long term performance for any alternative (especially including operating strategies) is evaluated by simulation. An operating rule is the combination of conditions, parameters, constraints and objectives used to determine the formulation of the short term optimization in each time step. Heuristic wrappers for the simulation program have been developed improve the parameters of an operating rule, and are initiating research on a wrapper that will allow us to employ a genetic algorithm to improve the form of the rule (conditions, constraints, and short term objectives) as well. In the models operating rules represent different models of human behavior, and the objective of the modeling is to find rules for human behavior that perform well in terms of long term human objectives. The conceptual model used to represent human behavior incorporates economic multi-objective optimization for surrogate objectives, and rules that set those objectives based on current conditions and accounting for uncertainty, at least implicitly. The author asserts that real world operating rules follow this form and have evolved because they have been perceived as successful in the past. Thus, the modeling efforts focus on human behavior in much the same way that economic models focus on human behavior. This paper illustrates the above concepts with real world examples.

Investigating the enhanced Best Performance Algorithm for Annual Crop Planning problem based on economic factors

PubMed Central

2017-01-01

The Annual Crop Planning (ACP) problem was a recently introduced problem in the literature. This study further expounds on this problem by presenting a new mathematical formulation, which is based on market economic factors. To determine solutions, a new local search metaheuristic algorithm is investigated which is called the enhanced Best Performance Algorithm (eBPA). eBPA’s results are compared against two well-known local search metaheuristic algorithms; these include Tabu Search and Simulated Annealing. The results show the potential of the eBPA for continuous optimization problems. PMID:28792495

Optimization of a Future RLV Business Case using Multiple Strategic Market Prices

NASA Astrophysics Data System (ADS)

Charania, A.; Olds, J. R.

2002-01-01

There is a lack of depth in the current paradigm of conceptual level economic models used to evaluate the value and viability of future capital projects such as a commercial reusable launch vehicle (RLV). Current modeling methods assume a single price is charged to all customers, public or private, in order to optimize the economic metrics of interest. This assumption may not be valid given the different utility functions for space services of public and private entities. The government's requirements are generally more inflexible than its commercial counterparts. A government's launch schedules are much more rigid, choices of international launch services restricted, and launch specifications generally more stringent as well as numerous. These requirements generally make the government's demand curve more inelastic. Subsequently, a launch vehicle provider will charge a higher price (launch price per kg) to the government and may obtain a higher level of financial profit compared to an equivalent a commercial payload. This profit is not a sufficient condition to enable RLV development by itself but can help in making the financial situation slightly better. An RLV can potentially address multiple payload markets; each market has a different price elasticity of demand for both the commercial and government customer. Thus, a more resilient examination of the economic landscape requires optimization of multiple prices in which each price affects a different demand curve. Such an examination is performed here using the Cost and Business Analysis Module (CABAM), an MS-Excel spreadsheet-based model that attempts to couple both the demand and supply for space transportation services in the future. The demand takes the form of market assumptions (both near-term and far-term) and the supply comes from user-defined vehicles that are placed into the model. CABAM represents RLV projects as commercial endeavors with the possibility to model the effects of government contribution, tax-breaks, loan guarantees, etc. The optimization performed here is for a 3rd Generation RLV program. The economic metric being optimized (maximized) is Net Present Value (NPV) based upon a given company financial structure and cost of capital assumptions. Such an optimization process demands more sophisticated optimizers and can result in non-unique solutions/local minimums if using gradient-based optimization. Domain spanning/evolutionary algorithms are used to obtain the optimized solution in the design space. These capabilities generally increase model calculation time but incorporate realistic pricing portfolios than just assuming one unified price for all launch markets. This analysis is conducted with CABAM running in Phoenix Integration's ModelCenter 4.0 collaborative design environment using the SpaceWorks Engineering, Inc. (SEI) OptWorks suite of optimization components.

A conceptual framework for economic optimization of an animal health surveillance portfolio.

PubMed

Guo, X; Claassen, G D H; Oude Lansink, A G J M; Saatkamp, H W

2016-04-01

Decision making on hazard surveillance in livestock product chains is a multi-hazard, multi-stakeholder, and multi-criteria process that includes a variety of decision alternatives. The multi-hazard aspect means that the allocation of the scarce resource for surveillance should be optimized from the point of view of a surveillance portfolio (SP) rather than a single hazard. In this paper, we present a novel conceptual approach for economic optimization of a SP to address the resource allocation problem for a surveillance organization from a theoretical perspective. This approach uses multi-criteria techniques to evaluate the performances of different settings of a SP, taking cost-benefit aspects of surveillance and stakeholders' preferences into account. The credibility of the approach has also been checked for conceptual validity, data needs and operational validity; the application potentials of the approach are also discussed.

Optimal ordering and production policy for a recoverable item inventory system with learning effect

NASA Astrophysics Data System (ADS)

Tsai, Deng-Maw

2012-02-01

This article presents two models for determining an optimal integrated economic order quantity and economic production quantity policy in a recoverable manufacturing environment. The models assume that the unit production time of the recovery process decreases with the increase in total units produced as a result of learning. A fixed proportion of used products are collected from customers and then recovered for reuse. The recovered products are assumed to be in good condition and acceptable to customers. Constant demand can be satisfied by utilising both newly purchased products and recovered products. The aim of this article is to show how to minimise total inventory-related cost. The total cost functions of the two models are derived and two simple search procedures are proposed to determine optimal policy parameters. Numerical examples are provided to illustrate the proposed models. In addition, sensitivity analyses have also been performed and are discussed.

Distributed Optimal Consensus Over Resource Allocation Network and Its Application to Dynamical Economic Dispatch.

PubMed

Li, Chaojie; Yu, Xinghuo; Huang, Tingwen; He, Xing; Chaojie Li; Xinghuo Yu; Tingwen Huang; Xing He; Li, Chaojie; Huang, Tingwen; He, Xing; Yu, Xinghuo

2018-06-01

The resource allocation problem is studied and reformulated by a distributed interior point method via a -logarithmic barrier. By the facilitation of the graph Laplacian, a fully distributed continuous-time multiagent system is developed for solving the problem. Specifically, to avoid high singularity of the -logarithmic barrier at boundary, an adaptive parameter switching strategy is introduced into this dynamical multiagent system. The convergence rate of the distributed algorithm is obtained. Moreover, a novel distributed primal-dual dynamical multiagent system is designed in a smart grid scenario to seek the saddle point of dynamical economic dispatch, which coincides with the optimal solution. The dual decomposition technique is applied to transform the optimization problem into easily solvable resource allocation subproblems with local inequality constraints. The good performance of the new dynamical systems is, respectively, verified by a numerical example and the IEEE six-bus test system-based simulations.

A techno-economic assessment of grid connected photovoltaic system for hospital building in Malaysia

NASA Astrophysics Data System (ADS)

Mat Isa, Normazlina; Tan, Chee Wei; Yatim, AHM

2017-07-01

Conventionally, electricity in hospital building are supplied by the utility grid which uses mix fuel including coal and gas. Due to enhancement in renewable technology, many building shall moving forward to install their own PV panel along with the grid to employ the advantages of the renewable energy. This paper present an analysis of grid connected photovoltaic (GCPV) system for hospital building in Malaysia. A discussion is emphasized on the economic analysis based on Levelized Cost of Energy (LCOE) and total Net Present Post (TNPC) in regards with the annual interest rate. The analysis is performed using Hybrid Optimization Model for Electric Renewables (HOMER) software which give optimization and sensitivity analysis result. An optimization result followed by the sensitivity analysis also being discuss in this article thus the impact of the grid connected PV system has be evaluated. In addition, the benefit from Net Metering (NeM) mechanism also discussed.

Effective Teaching of Economics: A Constrained Optimization Problem?

ERIC Educational Resources Information Center

Hultberg, Patrik T.; Calonge, David Santandreu

2017-01-01

One of the fundamental tenets of economics is that decisions are often the result of optimization problems subject to resource constraints. Consumers optimize utility, subject to constraints imposed by prices and income. As economics faculty, instructors attempt to maximize student learning while being constrained by their own and students'…

An Investigation of Generalized Differential Evolution Metaheuristic for Multiobjective Optimal Crop-Mix Planning Decision

PubMed Central

Olugbara, Oludayo

2014-01-01

This paper presents an annual multiobjective crop-mix planning as a problem of concurrent maximization of net profit and maximization of crop production to determine an optimal cropping pattern. The optimal crop production in a particular planting season is a crucial decision making task from the perspectives of economic management and sustainable agriculture. A multiobjective optimal crop-mix problem is formulated and solved using the generalized differential evolution 3 (GDE3) metaheuristic to generate a globally optimal solution. The performance of the GDE3 metaheuristic is investigated by comparing its results with the results obtained using epsilon constrained and nondominated sorting genetic algorithms—being two representatives of state-of-the-art in evolutionary optimization. The performance metrics of additive epsilon, generational distance, inverted generational distance, and spacing are considered to establish the comparability. In addition, a graphical comparison with respect to the true Pareto front for the multiobjective optimal crop-mix planning problem is presented. Empirical results generally show GDE3 to be a viable alternative tool for solving a multiobjective optimal crop-mix planning problem. PMID:24883369

An investigation of generalized differential evolution metaheuristic for multiobjective optimal crop-mix planning decision.

PubMed

Adekanmbi, Oluwole; Olugbara, Oludayo; Adeyemo, Josiah

2014-01-01

This paper presents an annual multiobjective crop-mix planning as a problem of concurrent maximization of net profit and maximization of crop production to determine an optimal cropping pattern. The optimal crop production in a particular planting season is a crucial decision making task from the perspectives of economic management and sustainable agriculture. A multiobjective optimal crop-mix problem is formulated and solved using the generalized differential evolution 3 (GDE3) metaheuristic to generate a globally optimal solution. The performance of the GDE3 metaheuristic is investigated by comparing its results with the results obtained using epsilon constrained and nondominated sorting genetic algorithms-being two representatives of state-of-the-art in evolutionary optimization. The performance metrics of additive epsilon, generational distance, inverted generational distance, and spacing are considered to establish the comparability. In addition, a graphical comparison with respect to the true Pareto front for the multiobjective optimal crop-mix planning problem is presented. Empirical results generally show GDE3 to be a viable alternative tool for solving a multiobjective optimal crop-mix planning problem.

Value for money: protecting endangered species on Danish heathland.

PubMed

Strange, Niels; Jacobsen, Jette B; Thorsen, Bo J; Tarp, Peter

2007-11-01

Biodiversity policies in the European Union (EU) are mainly implemented through the Birds and Habitats Directives as well as the establishment of Natura 2000, a network of protected areas throughout the EU. Considerable resources must be allocated for fulfilling the Directives and the question of optimal allocation is as important as it is difficult. In general, economic evaluations of conservation targets at most consider the costs and seldom the welfare economic benefits. In the present study, we use welfare economic benefit estimates concerning the willingness-to-pay for preserving endangered species and for the aggregate area of heathland preserved in Denmark. Similarly, we obtain estimates of the welfare economic cost of habitat restoration and maintenance. Combining these welfare economic measures with expected species coverage, we are able to estimate the potential welfare economic contribution of a conservation network. We compare three simple nonprobabilistic strategies likely to be used in day-to-day policy implementation: i) a maximum selected area strategy, ii) a hotspot selection strategy, and iii) a minimizing cost strategy, and two more advanced and informed probabilistic strategies: i) a maximum expected coverage strategy and ii) a strategy for maximum expected welfare economic gain. We show that the welfare economic performance of the strategies differ considerably. The comparison between the expected coverage and expected welfare shows that for the case considered, one may identify an optimal protection level above which additional coverage only comes at increasing welfare economic loss.

Quantum cloning by cellular automata

NASA Astrophysics Data System (ADS)

D'Ariano, G. M.; Macchiavello, C.; Rossi, M.

2013-03-01

We introduce a quantum cellular automaton that achieves approximate phase-covariant cloning of qubits. The automaton is optimized for 1→2N economical cloning. The use of the automaton for cloning allows us to exploit different foliations for improving the performance with given resources.

Marine vessels as substitutes for heavy-duty trucks in Great Lakes freight transportation.

PubMed

Comer, Bryan; Corbett, James J; Hawker, J Scott; Korfmacher, Karl; Lee, Earl E; Prokop, Chris; Winebrake, James J

2010-07-01

This paper applies a geospatial network optimization model to explore environmental, economic, and time-of-delivery tradeoffs associated with the application of marine vessels as substitutes for heavy-duty trucks operating in the Great Lakes region. The geospatial model integrates U.S. and Canadian highway, rail, and waterway networks to create an intermodal network and characterizes this network using temporal, economic, and environmental attributes (including emissions of carbon dioxide, particulate matter, carbon monoxide, sulfur oxides, volatile organic compounds, and nitrogen oxides). A case study evaluates tradeoffs associated with containerized traffic flow in the Great Lakes region, demonstrating how choice of freight mode affects the environmental performance of movement of goods. These results suggest opportunities to improve the environmental performance of freight transport through infrastructure development, technology implementation, and economic incentives.

Optimal Incentives for Public Sector Workers: The Case of Teacher-Designed Incentive Pay in Texas. Working Paper 2009-05

ERIC Educational Resources Information Center

Taylor, Lori L.; Springer, Matthew G.

2009-01-01

Pay for performance is a popular public education reform, and millions of dollars are currently being targeted for pay for performance programs. These reforms are popular because economic and management theories suggest that well-designed incentive pay programs could improve teacher effectiveness. There is little evidence about the characteristics…

Optimal control of a harmonic oscillator: Economic interpretations

NASA Astrophysics Data System (ADS)

Janová, Jitka; Hampel, David

2013-10-01

Optimal control is a popular technique for modelling and solving the dynamic decision problems in economics. A standard interpretation of the criteria function and Lagrange multipliers in the profit maximization problem is well known. On a particular example, we aim to a deeper understanding of the possible economic interpretations of further mathematical and solution features of the optimal control problem: we focus on the solution of the optimal control problem for harmonic oscillator serving as a model for Phillips business cycle. We discuss the economic interpretations of arising mathematical objects with respect to well known reasoning for these in other problems.

Status on the Development of a Modeling and Simulation Framework for the Economic Assessment of Nuclear Hybrid Energy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Epiney, Aaron Simon; Chen, Jun; Rabiti, Cristian

Continued effort to design and build a modeling and simulation framework to assess the economic viability of Nuclear Hybrid Energy Systems (NHES) was undertaken in fiscal year (FY) 2016. The purpose of this report is to document the various tasks associated with the development of such a framework and to provide a status of their progress. Several tasks have been accomplished. First, a synthetic time history generator has been developed in RAVEN, which consists of Fourier series and autoregressive moving average model. The former is used to capture the seasonal trend in historical data, while the latter is to characterizemore » the autocorrelation in residue time series (e.g., measurements with seasonal trends subtracted). As demonstration, both synthetic wind speed and grid demand are generated, showing matching statistics with database. In order to build a design and operations optimizer in RAVEN, a new type of sampler has been developed with highly object-oriented design. In particular, simultaneous perturbation stochastic approximation algorithm is implemented. The optimizer is capable to drive the model to optimize a scalar objective function without constraint in the input space, while the constraints handling is a work in progress and will be implemented to improve the optimization capability. Furthermore, a simplified cash flow model of the performance of an NHES in the electric market has been developed in Python and used as external model in RAVEN to confirm expectations on the analysis capability of RAVEN to provide insight into system economics and to test the capability of RAVEN to identify limit surfaces. Finally, an example calculation is performed that shows the integration and proper data passing in RAVEN of the synthetic time history generator, the cash flow model and the optimizer. It has been shown that the developed Python models external to RAVEN are able to communicate with RAVEN and each other through the newly developed RAVEN capability called “EnsembleModel”.« less

A technical, economic, and environmental performance of grid-connected hybrid (photovoltaic-wind) power system in Algeria.

PubMed

Saheb-Koussa, Djohra; Koussa, Mustapha; Said, Nourredine

2013-01-01

This paper studies the technical, economic, and environmental analysis of wind and photovoltaic power systems connected to a conventional grid. The main interest in such systems is on-site consumption of the produced energy, system hybridization, pooling of resources, and contribution to the environment protection. To ensure a better management of system energy, models have been used for determining the power that the constituting subsystems can deliver under specific weather conditions. Simulation is performed using MATLAB-SIMULINK. While, the economic and environmental study is performed using HOMER software. From an economic point of view, this allows to compare the financial constraints on each part of the system for the case of Adrar site which is located to the northern part of the south of Algeria. It also permits to optimally size and select the system presenting the best features on the basis of two parameters, that is, cost and effectiveness. From an environmental point of view, this study allows highlighting the role of renewable energy in reducing gas emissions related to greenhouse effects. In addition, through a set of sensitivity analysis, it is found that the wind speed has more effects on the environmental and economic performances of grid-connected hybrid (photovoltaic-wind) power systems.

A Technical, Economic, and Environmental Performance of Grid-Connected Hybrid (Photovoltaic-Wind) Power System in Algeria

PubMed Central

Saheb-Koussa, Djohra; Koussa, Mustapha; Said, Nourredine

2013-01-01

This paper studies the technical, economic, and environmental analysis of wind and photovoltaic power systems connected to a conventional grid. The main interest in such systems is on-site consumption of the produced energy, system hybridization, pooling of resources, and contribution to the environment protection. To ensure a better management of system energy, models have been used for determining the power that the constituting subsystems can deliver under specific weather conditions. Simulation is performed using MATLAB-SIMULINK. While, the economic and environmental study is performed using HOMER software. From an economic point of view, this allows to compare the financial constraints on each part of the system for the case of Adrar site which is located to the northern part of the south of Algeria. It also permits to optimally size and select the system presenting the best features on the basis of two parameters, that is, cost and effectiveness. From an environmental point of view, this study allows highlighting the role of renewable energy in reducing gas emissions related to greenhouse effects. In addition, through a set of sensitivity analysis, it is found that the wind speed has more effects on the environmental and economic performances of grid-connected hybrid (photovoltaic-wind) power systems. PMID:24489488

Economic evaluations in pain management: principles and methods.

PubMed

Asche, Carl V; Seal, Brian; Jackson, Kenneth C; Oderda, Gary M

2006-01-01

This paper describes how investigators may design, conduct, and report economic evaluations of pharmacotherapy for pain and symptom management. Because economic evaluation of therapeutic interventions is becoming increasingly important, there is a need for guidance on how economic evaluations can be optimally conducted. The steps required to conduct an economic evaluation are described to provide this guidance. Economic evaluations require two or more therapeutic interventions to be compared in relation to costs and effects. There are five types of economic evaluations, based on analysis of: (1) cost-effectiveness, (2) cost-utility, (3) cost-minimization, (4) cost-consequence, and (5) cost-benefit analyses. The six required steps are: identify the perspective of the study; identify the alternatives that will be compared; identify the relevant costs and effects; determine how to collect the cost and effect data; determine how to perform calculation for cost and effects data; and determine the manner in which to depict the results and draw comparisons.

Nozzle Mounting Method Optimization Based on Robot Kinematic Analysis

NASA Astrophysics Data System (ADS)

Chen, Chaoyue; Liao, Hanlin; Montavon, Ghislain; Deng, Sihao

2016-08-01

Nowadays, the application of industrial robots in thermal spray is gaining more and more importance. A desired coating quality depends on factors such as a balanced robot performance, a uniform scanning trajectory and stable parameters (e.g. nozzle speed, scanning step, spray angle, standoff distance). These factors also affect the mass and heat transfer as well as the coating formation. Thus, the kinematic optimization of all these aspects plays a key role in order to obtain an optimal coating quality. In this study, the robot performance was optimized from the aspect of nozzle mounting on the robot. An optimized nozzle mounting for a type F4 nozzle was designed, based on the conventional mounting method from the point of view of robot kinematics validated on a virtual robot. Robot kinematic parameters were obtained from the simulation by offline programming software and analyzed by statistical methods. The energy consumptions of different nozzle mounting methods were also compared. The results showed that it was possible to reasonably assign the amount of robot motion to each axis during the process, so achieving a constant nozzle speed. Thus, it is possible optimize robot performance and to economize robot energy.

A Comparative Study of Spatial Aggregation Methodologies under the BioEarth Framework

NASA Astrophysics Data System (ADS)

Chandrasekharan, B.; Rajagopalan, K.; Malek, K.; Stockle, C. O.; Adam, J. C.; Brady, M.

2014-12-01

The increasing probability of water resource scarcity due to climate change has highlighted the need for adopting an economic focus in modelling water resource uses. Hydro-economic models, developed by integrating economic optimization with biophysical crop models, are driven by the economic value of water, revealing it's most efficient uses and helping policymakers evaluate different water management strategies. One of the challenges in integrating biophysical models with economic models is the difference in the spatial scales in which they operate. Biophysical models that provide crop production functions typically run at smaller scale than economic models, and substantial spatial aggregation is required. However, any aggregation introduces a bias, i.e., a discrepancy between the functional value at the higher spatial scale and the value at the spatial scale of the aggregated units. The objective of this work is to study the sensitivity of net economic benefits in the Yakima River basin (YRB) to different spatial aggregation methods for crop production functions. The spatial aggregation methodologies that we compare involve agro-ecological zones (AEZs) and aggregation levels that reflect water management regimes (e.g. irrigation districts). Aggregation bias can distort the underlying data and result in extreme solutions. In order to avoid this we use an economic optimization model that incorporates the synthetic and historical crop mixes approach (Onal & Chen, 2012). This restricts the solutions between the weighted averages of historical and simulated feasible planting decisions, with the weights associated with crop mixes being treated as endogenous variables. This study is focused on 5 major irrigation districts of the YRB in the Pacific Northwest US. The biophysical modeling framework we use, BioEarth, includes the coupled hydrology and crop growth model, VIC-Cropsyst and an economic optimization model. Preliminary findings indicate that the standard approach of developing AEZs does not perform well when overlaid with irrigation districts. Moreover, net economic benefits were significantly different between the two aggregation methodologies. Therefore, while developing hydro-economic models, significant consideration should be placed on the aggregation methodology.

Dairy cow culling strategies: making economical culling decisions.

PubMed

Lehenbauer, T W; Oltjen, J W

1998-01-01

The purpose of this report was to examine important economic elements of culling decisions, to review progress in development of culling decision support systems, and to discern some of the potentially rewarding areas for future research on culling models. Culling decisions have an important influence on the economic performance of the dairy but are often made in a nonprogrammed fashion and based partly on the intuition of the decision maker. The computer technology that is available for dairy herd management has made feasible the use of economic models to support culling decisions. Financial components--including profit, cash flow, and risk--are major economic factors affecting culling decisions. Culling strategies are further influenced by short-term fluctuations in cow numbers as well as by planned herd expansion. Changes in herd size affect the opportunity cost for postponed replacement and may alter the relevance of optimization strategies that assume a fixed herd size. Improvements in model components related to biological factors affecting future cow performance, including milk production, reproductive status, and mastitis, appear to offer the greatest economic potential for enhancing culling decision support systems. The ultimate value of any culling decision support system for developing economic culling strategies will be determined by its results under field conditions.

Optimisation structurelle des systemes energetiques

NASA Astrophysics Data System (ADS)

Saloux, Etienne

The development of renewable energies is growing over the last decade to face environmental issues due to the world fossil fuel consumption increase. These energies are highly involved in houses and commercial buildings and numerous systems have been proposed to meet their energy demand. Therefore, improving both efficiency and use of systems, i.e. improving energy management, appears essential to limit the ecological footprint of humanity on the planet. However, system integration yields a very complex problem to be solved due to the large number of units and theirs technology, size, working conditions and interconnections. This situation highlights the lack of systematic analysis for comparing integrated system performance and for correctly pointing out their potential. As a result, the objective of this thesis is to develop and to present such a method, in other words the structural optimization of energy systems. It will be helpful to choose the optimal equipment by identifying all the possibilities of system arrangements and for comparing their performance. Combinations have then been subjected to environmental (climate), structural (available area) and economical constrains while assessment criteria have considered both energy, economic and ecological aspects. For that reason, as well as energy and economic analyses, the exergy concept has also been applied to the equipment. Nevertheless, the high degree of complexity of integrated systems and the tedious numerical calculations make the resolution by using standard software very difficult. It is clear that the whole optimization project would be considerable and the aim is to develop models and optimization tools. First of all, an exhaustive review of energy equipment including photovoltaic panels, solar collectors, heat pumps and thermal energy storage systems, has been performed. Afterwards, energy and exergy models have been developed and tested for two specific energy scenarios: a) a solar assisted heat pump using ice and warm water storages and b) an ambient air heat pump associated to photovoltaic panels. A superstructure has then been constructed to account for every system combination possibility. The different energy paths have been illustrated while irreversibility along every path is identified. Thus, it allows the system operation to be clearly understood. Besides, an exergy diagram has been developed and permits energy and exergy assessment of system and system arrangements to be not only identified but also quantified and separated depending on their (renewable or non-renewable) source. Finally, dimensions and operation variables have been optimized according to exergy and economic criteria for the aforementioned scenarios; the potential of each energy option has been estimated and yield a better energy management to be reached.

Multi-objective Optimization Strategies Using Adjoint Method and Game Theory in Aerodynamics

NASA Astrophysics Data System (ADS)

Tang, Zhili

2006-08-01

There are currently three different game strategies originated in economics: (1) Cooperative games (Pareto front), (2) Competitive games (Nash game) and (3) Hierarchical games (Stackelberg game). Each game achieves different equilibria with different performance, and their players play different roles in the games. Here, we introduced game concept into aerodynamic design, and combined it with adjoint method to solve multi-criteria aerodynamic optimization problems. The performance distinction of the equilibria of these three game strategies was investigated by numerical experiments. We computed Pareto front, Nash and Stackelberg equilibria of the same optimization problem with two conflicting and hierarchical targets under different parameterizations by using the deterministic optimization method. The numerical results show clearly that all the equilibria solutions are inferior to the Pareto front. Non-dominated Pareto front solutions are obtained, however the CPU cost to capture a set of solutions makes the Pareto front an expensive tool to the designer.

Optimal design of reverse osmosis module networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maskan, F.; Wiley, D.E.; Johnston, L.P.M.

2000-05-01

The structure of individual reverse osmosis modules, the configuration of the module network, and the operating conditions were optimized for seawater and brackish water desalination. The system model included simple mathematical equations to predict the performance of the reverse osmosis modules. The optimization problem was formulated as a constrained multivariable nonlinear optimization. The objective function was the annual profit for the system, consisting of the profit obtained from the permeate, capital cost for the process units, and operating costs associated with energy consumption and maintenance. Optimization of several dual-stage reverse osmosis systems were investigated and compared. It was found thatmore » optimal network designs are the ones that produce the most permeate. It may be possible to achieve economic improvements by refining current membrane module designs and their operating pressures.« less

Designing Industrial Networks Using Ecological Food Web Metrics.

PubMed

Layton, Astrid; Bras, Bert; Weissburg, Marc

2016-10-18

Biologically Inspired Design (biomimicry) and Industrial Ecology both look to natural systems to enhance the sustainability and performance of engineered products, systems and industries. Bioinspired design (BID) traditionally has focused on a unit operation and single product level. In contrast, this paper describes how principles of network organization derived from analysis of ecosystem properties can be applied to industrial system networks. Specifically, this paper examines the applicability of particular food web matrix properties as design rules for economically and biologically sustainable industrial networks, using an optimization model developed for a carpet recycling network. Carpet recycling network designs based on traditional cost and emissions based optimization are compared to designs obtained using optimizations based solely on ecological food web metrics. The analysis suggests that networks optimized using food web metrics also were superior from a traditional cost and emissions perspective; correlations between optimization using ecological metrics and traditional optimization ranged generally from 0.70 to 0.96, with flow-based metrics being superior to structural parameters. Four structural food parameters provided correlations nearly the same as that obtained using all structural parameters, but individual structural parameters provided much less satisfactory correlations. The analysis indicates that bioinspired design principles from ecosystems can lead to both environmentally and economically sustainable industrial resource networks, and represent guidelines for designing sustainable industry networks.

Multi-time Scale Coordination of Distributed Energy Resources in Isolated Power Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayhorn, Ebony; Xie, Le; Butler-Purry, Karen

2016-03-31

In isolated power systems, including microgrids, distributed assets, such as renewable energy resources (e.g. wind, solar) and energy storage, can be actively coordinated to reduce dependency on fossil fuel generation. The key challenge of such coordination arises from significant uncertainty and variability occurring at small time scales associated with increased penetration of renewables. Specifically, the problem is with ensuring economic and efficient utilization of DERs, while also meeting operational objectives such as adequate frequency performance. One possible solution is to reduce the time step at which tertiary controls are implemented and to ensure feedback and look-ahead capability are incorporated tomore » handle variability and uncertainty. However, reducing the time step of tertiary controls necessitates investigating time-scale coupling with primary controls so as not to exacerbate system stability issues. In this paper, an optimal coordination (OC) strategy, which considers multiple time-scales, is proposed for isolated microgrid systems with a mix of DERs. This coordination strategy is based on an online moving horizon optimization approach. The effectiveness of the strategy was evaluated in terms of economics, technical performance, and computation time by varying key parameters that significantly impact performance. The illustrative example with realistic scenarios on a simulated isolated microgrid test system suggests that the proposed approach is generalizable towards designing multi-time scale optimal coordination strategies for isolated power systems.« less

An economic evaluation and assessment of environmental impact of the municipal solid waste management system for Taichung City in Taiwan.

PubMed

Chang, Yao-Jen; Chu, Chien-Wei; Lin, Min-Der

2012-05-01

Municipal solid waste management (MSWM) is an important environmental challenge and subject in urban planning. For sustainable MSWM strategies, the critical management factors to be considered include not only economic efficiency of MSW treatment but also life-cycle assessment of the environmental impact. This paper employed linear programming technique to establish optimal MSWM strategies considering economic efficiency and the air pollutant emissions during the life cycle of a MSWM system, and investigated the correlations between the economical optimization and pollutant emissions. A case study based on real-world MSW operating parameters in Taichung City is also presented. The results showed that the costs, benefits, streams of MSW, and throughputs of incinerators and landfills will be affected if pollution emission reductions are implemented in the MSWM strategies. In addition, the quantity of particulate matter is the best pollutant indicator for the MSWM system performance of emission reduction. In particular this model will assist the decision maker in drawing up a friendly MSWM strategy for Taichung City in Taiwan. Recently, life-cycle assessments of municipal solid waste management (MSWM) strategies have been given more considerations. However, what seems to be lacking is the consideration of economic factors and environmental impacts simultaneously. This work analyzed real-world data to establish optimal MSWM strategies considering economic efficiency and the air pollutant emissions during the life cycle of the MSWM system. The results indicated that the consideration of environmental impacts will affect the costs, benefits, streams of MSW, and throughputs of incinerators and landfills. This work is relevant to public discussion and may establish useful guidelines for the MSWM policies.

The credibility crisis in research: Can economics tools help?

PubMed Central

Gall, Thomas; Ioannidis, John P. A.; Maniadis, Zacharias

2017-01-01

The issue of nonreplicable evidence has attracted considerable attention across biomedical and other sciences. This concern is accompanied by an increasing interest in reforming research incentives and practices. How to optimally perform these reforms is a scientific problem in itself, and economics has several scientific methods that can help evaluate research reforms. Here, we review these methods and show their potential. Prominent among them are mathematical modeling and laboratory experiments that constitute affordable ways to approximate the effects of policies with wide-ranging implications. PMID:28445470

The credibility crisis in research: Can economics tools help?

PubMed

Gall, Thomas; Ioannidis, John P A; Maniadis, Zacharias

2017-04-01

The issue of nonreplicable evidence has attracted considerable attention across biomedical and other sciences. This concern is accompanied by an increasing interest in reforming research incentives and practices. How to optimally perform these reforms is a scientific problem in itself, and economics has several scientific methods that can help evaluate research reforms. Here, we review these methods and show their potential. Prominent among them are mathematical modeling and laboratory experiments that constitute affordable ways to approximate the effects of policies with wide-ranging implications.

A new rational-based optimal design strategy of ship structure based on multi-level analysis and super-element modeling method

NASA Astrophysics Data System (ADS)

Sun, Li; Wang, Deyu

2011-09-01

A new multi-level analysis method of introducing the super-element modeling method, derived from the multi-level analysis method first proposed by O. F. Hughes, has been proposed in this paper to solve the problem of high time cost in adopting a rational-based optimal design method for ship structural design. Furthermore, the method was verified by its effective application in optimization of the mid-ship section of a container ship. A full 3-D FEM model of a ship, suffering static and quasi-static loads, was used as the analyzing object for evaluating the structural performance of the mid-ship module, including static strength and buckling performance. Research results reveal that this new method could substantially reduce the computational cost of the rational-based optimization problem without decreasing its accuracy, which increases the feasibility and economic efficiency of using a rational-based optimal design method in ship structural design.

The Army Study Program Fiscal Year 1993 Report

DTIC Science & Technology

1992-11-16

results of the PERFORMER: CAA Ardennes campaign and, if necessary, to recommend modifications to CEM. PROJECT TITLE: Economic Analysis Of HODA Automation...DCSOPS PERFORMER: CAA PROJECT TITLE: Wartime Requirements, FY 99 PUIC: CSCAMNO15 To assist HODA in determining conventional munition requirements...STUDY WILL ATTEMPT TO DEVELOP A MULTIPLE CRITERIA OPTIMIZATION MODEL DTIC NUMBER: TO AID IN THE PROGRAMMING OF ARMY ACQUISITION FUNDS AT HODA . THE

Evaluation of solar thermal power plants using economic and performance simulations

NASA Technical Reports Server (NTRS)

El-Gabawali, N.

1980-01-01

An energy cost analysis is presented for central receiver power plants with thermal storage and point focusing power plants with electrical storage. The present approach is based on optimizing the size of the plant to give the minimum energy cost (in mills/kWe hr) of an annual plant energy production. The optimization is done by considering the trade-off between the collector field size and the storage capacity for a given engine size. The energy cost is determined by the plant cost and performance. The performance is estimated by simulating the behavior of the plant under typical weather conditions. Plant capital and operational costs are estimated based on the size and performance of different components. This methodology is translated into computer programs for automatic and consistent evaluation.

Optimal sequence of tests for the mediastinal staging of non-small cell lung cancer.

PubMed

Luque, Manuel; Díez, Francisco Javier; Disdier, Carlos

2016-01-26

Non-small cell lung cancer (NSCLC) is the most prevalent type of lung cancer and the most difficult to predict. When there are no distant metastases, the optimal therapy depends mainly on whether there are malignant lymph nodes in the mediastinum. Given the vigorous debate among specialists about which tests should be used, our goal was to determine the optimal sequence of tests for each patient. We have built an influence diagram (ID) that represents the possible tests, their costs, and their outcomes. This model is equivalent to a decision tree containing millions of branches. In the first evaluation, we only took into account the clinical outcomes (effectiveness). In the second, we used a willingness-to-pay of € 30,000 per quality adjusted life year (QALY) to convert economic costs into effectiveness. We assigned a second-order probability distribution to each parameter in order to conduct several types of sensitivity analysis. Two strategies were obtained using two different criteria. When considering only effectiveness, a positive computed tomography (CT) scan must be followed by a transbronchial needle aspiration (TBNA), an endobronchial ultrasound (EBUS), and an endoscopic ultrasound (EUS). When the CT scan is negative, a positron emission tomography (PET), EBUS, and EUS are performed. If the TBNA or the PET is positive, then a mediastinoscopy is performed only if the EBUS and EUS are negative. If the TBNA or the PET is negative, then a mediastinoscopy is performed only if the EBUS and the EUS give contradictory results. When taking into account economic costs, a positive CT scan is followed by a TBNA; an EBUS is done only when the CT scan or the TBNA is negative. This recommendation of performing a TBNA in certain cases should be discussed by the pneumology community because TBNA is a cheap technique that could avoid an EBUS, an expensive test, for many patients. We have determined the optimal sequence of tests for the mediastinal staging of NSCLC by considering sensitivity, specificity, and the economic cost of each test. The main novelty of our study is the recommendation of performing TBNA whenever the CT scan is positive. Our model is publicly available so that different experts can populate it with their own parameters and re-examine its conclusions. It is therefore proposed as an evidence-based instrument for reaching a consensus.

Insecticide Resistance and Malaria Vector Control: The Importance of Fitness Cost Mechanisms in Determining Economically Optimal Control Trajectories

PubMed Central

Brown, Zachary S.; Dickinson, Katherine L.; Kramer, Randall A.

2014-01-01

The evolutionary dynamics of insecticide resistance in harmful arthropods has economic implications, not only for the control of agricultural pests (as has been well studied), but also for the control of disease vectors, such as malaria-transmitting Anopheles mosquitoes. Previous economic work on insecticide resistance illustrates the policy relevance of knowing whether insecticide resistance mutations involve fitness costs. Using a theoretical model, this article investigates economically optimal strategies for controlling malaria-transmitting mosquitoes when there is the potential for mosquitoes to evolve resistance to insecticides. Consistent with previous literature, we find that fitness costs are a key element in the computation of economically optimal resistance management strategies. Additionally, our models indicate that different biological mechanisms underlying these fitness costs (e.g., increased adult mortality and/or decreased fecundity) can significantly alter economically optimal resistance management strategies. PMID:23448053

SEASAT economic assessment. Volume 1: Summary and conclusions. [management analysis of the economic benefits of the SEASAT program

NASA Technical Reports Server (NTRS)

1975-01-01

A summary is presented of the economic benefits that can be derived from using the SEASAT Satellite System. A statement of the major findings of case studies of the practical applications of the SEASAT program to the following areas is given: (1) offshore oil and natural gas industry, (2) ocean mining, (3) coastal zones, (4) oil exploration in Arctic regions, (5) ocean fishing, and (6) ports and harbors. Also given is a description of the SEASAT System and its performance. A computer program, used to optimize SEASAT System's costs and operational requirements, is also considered.

Using GeoRePORT to report socio-economic potential for geothermal development

DOE Office of Scientific and Technical Information (OSTI.GOV)

Young, Katherine R.; Levine, Aaron

The Geothermal Resource Portfolio Optimization and Reporting Tool (GeoRePORT, http://en.openei.org/wiki/GeoRePORT) was developed for reporting resource grades and project readiness levels, providing the U.S. Department of Energy a consistent and comprehensible means of evaluating projects. The tool helps funding organizations (1) quantitatively identify barriers, (2) develop measureable goals, (3) objectively evaluate proposals, including contribution to goals, (4) monitor progress, and (5) report portfolio performance. GeoRePORT assesses three categories: geological, technical, and socio-economic. Here, we describe GeoRePORT, then focus on the socio-economic assessment and its applications for assessing deployment potential in the U.S. Socio-economic attributes include land access, permitting, transmission, and market.

Reducing maintenance costs in agreement with CNC machine tools reliability

NASA Astrophysics Data System (ADS)

Ungureanu, A. L.; Stan, G.; Butunoi, P. A.

2016-08-01

Aligning maintenance strategy with reliability is a challenge due to the need to find an optimal balance between them. Because the various methods described in the relevant literature involve laborious calculations or use of software that can be costly, this paper proposes a method that is easier to implement on CNC machine tools. The new method, called the Consequence of Failure Analysis (CFA) is based on technical and economic optimization, aimed at obtaining a level of required performance with minimum investment and maintenance costs.

Optimum dry-cooling sub-systems for a solar air conditioner

NASA Technical Reports Server (NTRS)

Chen, J. L. S.; Namkoong, D.

1978-01-01

Dry-cooling sub-systems for residential solar powered Rankine compression air conditioners were economically optimized and compared with the cost of a wet cooling tower. Results in terms of yearly incremental busbar cost due to the use of dry-cooling were presented for Philadelphia and Miami. With input data corresponding to local weather, energy rate and capital costs, condenser surface designs and performance, the computerized optimization program yields design specifications of the sub-system which has the lowest annual incremental cost.

Synthetic spider silk sustainability verification by techno-economic and life cycle analysis

NASA Astrophysics Data System (ADS)

Edlund, Alan

Major ampullate spider silk represents a promising biomaterial with diverse commercial potential ranging from textiles to medical devices due to the excellent physical and thermal properties from the protein structure. Recent advancements in synthetic biology have facilitated the development of recombinant spider silk proteins from Escherichia coli (E. coli), alfalfa, and goats. This study specifically investigates the economic feasibility and environmental impact of synthetic spider silk manufacturing. Pilot scale data was used to validate an engineering process model that includes all of the required sub-processing steps for synthetic fiber manufacture: production, harvesting, purification, drying, and spinning. Modeling was constructed modularly to support assessment of alternative protein production methods (alfalfa and goats) as well as alternative down-stream processing technologies. The techno-economic analysis indicates a minimum sale price from pioneer and optimized E. coli plants at 761 kg-1 and 23 kg-1 with greenhouse gas emissions of 572 kg CO2-eq. kg-1 and 55 kg CO2-eq. kg-1, respectively. Spider silk sale price estimates from goat pioneer and optimized results are 730 kg-1 and 54 kg-1, respectively, with pioneer and optimized alfalfa plants are 207 kg-1 and 9.22 kg-1 respectively. Elevated costs and emissions from the pioneer plant can be directly tied to the high material consumption and low protein yield. Decreased production costs associated with the optimized plants include improved protein yield, process optimization, and an Nth plant assumption. Discussion focuses on the commercial potential of spider silk, the production performance requirements for commercialization, and impact of alternative technologies on the sustainability of the system.

Applying complex models to poultry production in the future--economics and biology.

PubMed

Talpaz, H; Cohen, M; Fancher, B; Halley, J

2013-09-01

The ability to determine the optimal broiler feed nutrient density that maximizes margin over feeding cost (MOFC) has obvious economic value. To determine optimal feed nutrient density, one must consider ingredient prices, meat values, the product mix being marketed, and the projected biological performance. A series of 8 feeding trials was conducted to estimate biological responses to changes in ME and amino acid (AA) density. Eight different genotypes of sex-separate reared broilers were fed diets varying in ME (2,723-3,386 kcal of ME/kg) and AA (0.89-1.65% digestible lysine with all essential AA acids being indexed to lysine) levels. Broilers were processed to determine carcass component yield at many different BW (1.09-4.70 kg). Trial data generated were used in model constructed to discover the dietary levels of ME and AA that maximize MOFC on a per broiler or per broiler annualized basis (bird × number of cycles/year). The model was designed to estimate the effects of dietary nutrient concentration on broiler live weight, feed conversion, mortality, and carcass component yield. Estimated coefficients from the step-wise regression process are subsequently used to predict the optimal ME and AA concentrations that maximize MOFC. The effects of changing feed or meat prices across a wide spectrum on optimal ME and AA levels can be evaluated via parametric analysis. The model can rapidly compare both biological and economic implications of changing from current practice to the simulated optimal solution. The model can be exploited to enhance decision making under volatile market conditions.

An Economic Evaluation of Optimal Intermodal Soybean Flows in Arkansas with Projected Effects of the North American Free Trade Agreement

DOT National Transportation Integrated Search

1999-04-01

Grain marketing may be defined as "the performance of all business activities that coordinate the flow of goods and services from grain producers to consumers and users." This analysis examines the transportation component of the grain marketing syst...

Cost analysis of the stroke volume variation guided perioperative hemodynamic optimization - an economic evaluation of the SVVOPT trial results.

PubMed

Benes, Jan; Zatloukal, Jan; Simanova, Alena; Chytra, Ivan; Kasal, Eduard

2014-01-01

Perioperative goal directed therapy (GDT) can substantially improve the outcomes of high risk surgical patients as shown by many clinical studies. However, the approach needs initial investment and can increase the already very high staff workload. These economic imperatives may be at least partly responsible for weak adherence to the GDT concept. A few models are available for the evaluation of GDT cost-effectiveness, but studies of real economic data based on a recent clinical trial are lacking. In order to address this we have performed a retrospective analysis of the data from the "Intraoperative fluid optimization using stroke volume variation in high risk surgical patients" trial (ISRCTN95085011). The health-care payers perspective was used in order to evaluate the perioperative hemodynamic optimization costs. Hospital invoices from all patients included in the trial were extracted. A direct comparison between the study (GDT, N = 60) and control (N = 60) groups was performed. A cost tree was constructed and major cost drivers evaluated. The trial showed a significant improvement in clinical outcomes for GDT treated patients. The mean cost per patient were lower in the GDT group 2877 ± 2336€ vs. 3371 ± 3238€ in controls, but without reaching a statistical significance (p = 0.596). The mean cost of all items except for intraoperative monitoring and infusions were lower for GDT than control but due to the high variability they all failed to reach statistical significance. Those costs associated with clinical care (68 ± 177€ vs. 212 ± 593€; p = 0.023) and ward stay costs (213 ± 108€ vs. 349 ± 467€; p = 0.082) were the most important differences in favour of the GDT group. Intraoperative fluid optimization with the use of stroke volume variation and Vigileo/FloTrac system showed not only a substantial improvement of morbidity, but was associated with an economic benefit. The cost-savings observed in the overall costs of postoperative care trend to offset the investment needed to run the GDT strategy and intraoperative monitoring. ISRCTN95085011.

A conceptual framework for economic optimization of single hazard surveillance in livestock production chains.

PubMed

Guo, Xuezhen; Claassen, G D H; Oude Lansink, A G J M; Saatkamp, H W

2014-06-01

Economic analysis of hazard surveillance in livestock production chains is essential for surveillance organizations (such as food safety authorities) when making scientifically based decisions on optimization of resource allocation. To enable this, quantitative decision support tools are required at two levels of analysis: (1) single-hazard surveillance system and (2) surveillance portfolio. This paper addresses the first level by presenting a conceptual approach for the economic analysis of single-hazard surveillance systems. The concept includes objective and subjective aspects of single-hazard surveillance system analysis: (1) a simulation part to derive an efficient set of surveillance setups based on the technical surveillance performance parameters (TSPPs) and the corresponding surveillance costs, i.e., objective analysis, and (2) a multi-criteria decision making model to evaluate the impacts of the hazard surveillance, i.e., subjective analysis. The conceptual approach was checked for (1) conceptual validity and (2) data validity. Issues regarding the practical use of the approach, particularly the data requirement, were discussed. We concluded that the conceptual approach is scientifically credible for economic analysis of single-hazard surveillance systems and that the practicability of the approach depends on data availability. Copyright © 2014 Elsevier B.V. All rights reserved.

Optimization of Biosorptive Removal of Dye from Aqueous System by Cone Shell of Calabrian Pine

PubMed Central

Deniz, Fatih

2014-01-01

The biosorption performance of raw cone shell of Calabrian pine for C.I. Basic Red 46 as a model azo dye from aqueous system was optimized using Taguchi experimental design methodology. L9 (33) orthogonal array was used to optimize the dye biosorption by the pine cone shell. The selected factors and their levels were biosorbent particle size, dye concentration, and contact time. The predicted dye biosorption capacity for the pine cone shell from Taguchi design was obtained as 71.770 mg g−1 under optimized biosorption conditions. This experimental design provided reasonable predictive performance of dye biosorption by the biosorbent (R 2: 0.9961). Langmuir model fitted better to the biosorption equilibrium data than Freundlich model. This displayed the monolayer coverage of dye molecules on the biosorbent surface. Dubinin-Radushkevich model and the standard Gibbs free energy change proposed physical biosorption for predominant mechanism. The logistic function presented the best fit to the data of biosorption kinetics. The kinetic parameters reflecting biosorption performance were also evaluated. The optimization study revealed that the pine cone shell can be an effective and economically feasible biosorbent for the removal of dye. PMID:25405213

Designing Flood Management Systems for Joint Economic and Ecological Robustness

NASA Astrophysics Data System (ADS)

Spence, C. M.; Grantham, T.; Brown, C. M.; Poff, N. L.

2015-12-01

Freshwater ecosystems across the United States are threatened by hydrologic change caused by water management operations and non-stationary climate trends. Nonstationary hydrology also threatens flood management systems' performance. Ecosystem managers and flood risk managers need tools to design systems that achieve flood risk reduction objectives while sustaining ecosystem functions and services in an uncertain hydrologic future. Robust optimization is used in water resources engineering to guide system design under climate change uncertainty. Using principles introduced by Eco-Engineering Decision Scaling (EEDS), we extend robust optimization techniques to design flood management systems that meet both economic and ecological goals simultaneously across a broad range of future climate conditions. We use three alternative robustness indices to identify flood risk management solutions that preserve critical ecosystem functions in a case study from the Iowa River, where recent severe flooding has tested the limits of the existing flood management system. We seek design modifications to the system that both reduce expected cost of flood damage while increasing ecologically beneficial inundation of riparian floodplains across a wide range of plausible climate futures. The first robustness index measures robustness as the fraction of potential climate scenarios in which both engineering and ecological performance goals are met, implicitly weighting each climate scenario equally. The second index builds on the first by using climate projections to weight each climate scenario, prioritizing acceptable performance in climate scenarios most consistent with climate projections. The last index measures robustness as mean performance across all climate scenarios, but penalizes scenarios with worse performance than average, rewarding consistency. Results stemming from alternate robustness indices reflect implicit assumptions about attitudes toward risk and reveal the tradeoffs between using structural and non-structural flood management strategies to ensure economic and ecological robustness.

Optimization of educational paths for higher education

NASA Astrophysics Data System (ADS)

Tarasyev, Alexandr A.; Agarkov, Gavriil; Medvedev, Aleksandr

2017-11-01

In our research, we combine the theory of economic behavior and the methodology of increasing efficiency of the human capital to estimate the optimal educational paths. We provide an optimization model for higher education process to analyze possible educational paths for each rational individual. The preferences of each rational individual are compared to the best economically possible educational path. The main factor of the individual choice, which is formed by the formation of optimal educational path, deals with higher salaries level in the chosen economic sector after graduation. Another factor that influences on the economic profit is the reduction of educational costs or the possibility of the budget support for the student. The main outcome of this research consists in correction of the governmental policy of investment in human capital based on the results of educational paths optimal control.

Optimized design of total energy systems: The RETE project

NASA Astrophysics Data System (ADS)

Alia, P.; Dallavalle, F.; Denard, C.; Sanson, F.; Veneziani, S.; Spagni, G.

1980-05-01

The RETE (Reggio Emilia Total Energy) project is discussed. The total energy system (TES) was developed to achieve the maximum quality matching on the thermal energy side between plant and user and perform an open scheme on the electrical energy side by connection with the Italian electrical network. The most significant qualitative considerations at the basis of the plant economic energy optimization and the selection of the operating criterion most fitting the user consumption characteristics and the external system constraints are reported. The design methodology described results in a TES that: in energy terms achieves a total efficiency evaluated on a yearly basis to be equal to about 78 percent and a fuel saving of about 28 percent and in economic terms allows a recovery of the investment required as to conventional solutions, in about seven years.

On the Water-Food Nexus: an Optimization Approach for Water and Food Security

NASA Astrophysics Data System (ADS)

Mortada, Sarah; Abou Najm, Majdi; Yassine, Ali; Alameddine, Ibrahim; El-Fadel, Mutasem

2016-04-01

Water and food security is facing increased challenges with population increase, climate and land use change, as well as resource depletion coupled with pollution and unsustainable practices. Coordinated and effective management of limited natural resources have become an imperative to meet these challenges by optimizing the usage of resources under various constraints. In this study, an optimization model is developed for optimal resource allocation towards sustainable water and food security under nutritional, socio-economic, agricultural, environmental, and natural resources constraints. The core objective of this model is to maximize the composite water-food security status by recommending an optimal water and agricultural strategy. The model balances between the healthy nutritional demand side and the constrained supply side while considering the supply chain in between. It equally ensures that the population achieves recommended nutritional guidelines and population food-preferences by quantifying an optimum agricultural and water policy through transforming optimum food demands into optimum cropping policy given the water and land footprints of each crop or agricultural product. Through this process, water and food security are optimized considering factors that include crop-food transformation (food processing), water footprints, crop yields, climate, blue and green water resources, irrigation efficiency, arable land resources, soil texture, and economic policies. The model performance regarding agricultural practices and sustainable food and water security was successfully tested and verified both at a hypothetical and pilot scale levels.

Economical quantum cloning in any dimension

NASA Astrophysics Data System (ADS)

Durt, Thomas; Fiurášek, Jaromír; Cerf, Nicolas J.

2005-11-01

The possibility of cloning a d -dimensional quantum system without an ancilla is explored, extending on the economical phase-covariant cloning machine for qubits found in Phys. Rev. A 60, 2764 (1999). We prove the impossibility of constructing an economical version of the optimal universal 1→2 cloning machine in any dimension. We also show, using an ansatz on the generic form of cloning machines, that the d -dimensional 1→2 phase-covariant cloner, which optimally clones all balanced superpositions with arbitrary phases, can be realized economically only in dimension d=2 . The used ansatz is supported by numerical evidence up to d=7 . An economical phase-covariant cloner can nevertheless be constructed for d>2 , albeit with a slightly lower fidelity than that of the optimal cloner requiring an ancilla. Finally, using again an ansatz on cloning machines, we show that an economical version of the 1→2 Fourier-covariant cloner, which optimally clones the computational basis and its Fourier transform, is also possible only in dimension d=2 .

Integrated solar energy system optimization

NASA Astrophysics Data System (ADS)

Young, S. K.

1982-11-01

The computer program SYSOPT, intended as a tool for optimizing the subsystem sizing, performance, and economics of integrated wind and solar energy systems, is presented. The modular structure of the methodology additionally allows simulations when the solar subsystems are combined with conventional technologies, e.g., a utility grid. Hourly energy/mass flow balances are computed for interconnection points, yielding optimized sizing and time-dependent operation of various subsystems. The program requires meteorological data, such as insolation, diurnal and seasonal variations, and wind speed at the hub height of a wind turbine, all of which can be taken from simulations like the TRNSYS program. Examples are provided for optimization of a solar-powered (wind turbine and parabolic trough-Rankine generator) desalinization plant, and a design analysis for a solar powered greenhouse.

Structured Innovation of High-Performance Wave Energy Converter Technology: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weber, Jochem W.; Laird, Daniel

Wave energy converter (WEC) technology development has not yet delivered the desired commercial maturity nor, and more importantly, the techno-economic performance. The reasons for this have been recognized and fundamental requirements for successful WEC technology development have been identified. This paper describes a multi-year project pursued in collaboration by the National Renewable Energy Laboratory and Sandia National Laboratories to innovate and develop new WEC technology. It specifies the project strategy, shows how this differs from the state-of-the-art approach and presents some early project results. Based on the specification of fundamental functional requirements of WEC technology, structured innovation and systemic problemmore » solving methodologies are applied to invent and identify new WEC technology concepts. Using Technology Performance Levels (TPL) as an assessment metric of the techno-economic performance potential, high performance technology concepts are identified and selected for further development. System performance is numerically modelled and optimized and key performance aspects are empirically validated. The project deliverables are WEC technology specifications of high techno-economic performance technologies of TPL 7 or higher at TRL 3 with some key technology challenges investigated at higher TRL. These wave energy converter technology specifications will be made available to industry for further, full development and commercialisation (TRL 4 - TRL 9).« less

The development of multi-objective optimization model for excess bagasse utilization: A case study for Thailand

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buddadee, Bancha; Wirojanagud, Wanpen; Watts, Daniel J.

In this paper, a multi-objective optimization model is proposed as a tool to assist in deciding for the proper utilization scheme of excess bagasse produced in sugarcane industry. Two major scenarios for excess bagasse utilization are considered in the optimization. The first scenario is the typical situation when excess bagasse is used for the onsite electricity production. In case of the second scenario, excess bagasse is processed for the offsite ethanol production. Then the ethanol is blended with an octane rating of 91 gasoline by a portion of 10% and 90% by volume respectively and the mixture is used asmore » alternative fuel for gasoline vehicles in Thailand. The model proposed in this paper called 'Environmental System Optimization' comprises the life cycle impact assessment of global warming potential (GWP) and the associated cost followed by the multi-objective optimization which facilitates in finding out the optimal proportion of the excess bagasse processed in each scenario. Basic mathematical expressions for indicating the GWP and cost of the entire process of excess bagasse utilization are taken into account in the model formulation and optimization. The outcome of this study is the methodology developed for decision-making concerning the excess bagasse utilization available in Thailand in view of the GWP and economic effects. A demonstration example is presented to illustrate the advantage of the methodology which may be used by the policy maker. The methodology developed is successfully performed to satisfy both environmental and economic objectives over the whole life cycle of the system. It is shown in the demonstration example that the first scenario results in positive GWP while the second scenario results in negative GWP. The combination of these two scenario results in positive or negative GWP depending on the preference of the weighting given to each objective. The results on economics of all scenarios show the satisfied outcomes.« less

Structural vibration passive control and economic analysis of a high-rise building in Beijing

NASA Astrophysics Data System (ADS)

Chen, Yongqi; Cao, Tiezhu; Ma, Liangzhe; Luo, Chaoying

2009-12-01

Performance analysis of the Pangu Plaza under earthquake and wind loads is described in this paper. The plaza is a 39-story steel high-rise building, 191 m high, located in Beijing close to the 2008 Olympic main stadium. It has both fluid viscous dampers (FVDs) and buckling restrained braces or unbonded brace (BRB or UBB) installed. A repeated iteration procedure in its design and analysis was adopted for optimization. Results from the seismic response analysis in the horizontal and vertical directions show that the FVDs are highly effective in reducing the response of both the main structure and the secondary system. A comparative analysis of structural seismic performance and economic impact was conducted using traditional methods, i.e., increased size of steel columns and beams and/or use of an increased number of seismic braces versus using FVD. Both the structural response and economic analysis show that using FVD to absorb seismic energy not only satisfies the Chinese seismic design code for a “rare” earthquake, but is also the most economical way to improve seismic performance both for one-time direct investment and long term maintenance.

Economic implications of current systems

NASA Technical Reports Server (NTRS)

Daniel, R. E.; Aster, R. W.

1983-01-01

The primary goals of this study are to estimate the value of R&D to photovoltaic (PV) metallization systems cost, and to provide a method for selecting an optimal metallization method for any given PV system. The value-added cost and relative electrical performance of 25 state-of-the-art (SOA) and advanced metallization system techniques are compared.

A user's manual for DELSOL3: A computer code for calculating the optical performance and optimal system design for solar thermal central receiver plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kistler, B.L.

DELSOL3 is a revised and updated version of the DELSOL2 computer program (SAND81-8237) for calculating collector field performance and layout and optimal system design for solar thermal central receiver plants. The code consists of a detailed model of the optical performance, a simpler model of the non-optical performance, an algorithm for field layout, and a searching algorithm to find the best system design based on energy cost. The latter two features are coupled to a cost model of central receiver components and an economic model for calculating energy costs. The code can handle flat, focused and/or canted heliostats, and externalmore » cylindrical, multi-aperture cavity, and flat plate receivers. The program optimizes the tower height, receiver size, field layout, heliostat spacings, and tower position at user specified power levels subject to flux limits on the receiver and land constraints for field layout. DELSOL3 maintains the advantages of speed and accuracy which are characteristics of DELSOL2.« less

An assessment of alternative fuel cell designs for residential and commercial cogeneration

NASA Technical Reports Server (NTRS)

Wakefield, R. A.

1980-01-01

A comparative assessment of three fuel cell systems for application in different buildings and geographic locations is presented. The study was performed at the NASA Lewis Center and comprised the fuel cell design, performance in different conditions, and the economic parameters. Applications in multifamily housing, stores and hospitals were considered, with a load of 10kW-1 MW. Designs were traced through system sizing, simulation/evaluation, and reliability analysis, and a computer simulation based on a fourth-order representation of a generalized system was performed. The cells were all phosphoric acid type cells, and were found to be incompatible with gas/electric systems and more favorable economically than the gas/electric systems in hospital uses. The methodology used provided an optimized energy-use pattern and minimized back-up system turn-on.

Is There an Optimal Speed for Economical Running?

PubMed

Black, Matthew I; Handsaker, Joseph C; Allen, Sam J; Forrester, Stephanie E; Folland, Jonathan P

2018-01-01

The influence of running speed and sex on running economy is unclear and may have been confounded by measurements of oxygen cost that do not account for known differences in substrate metabolism, across a limited range of speeds, and differences in performance standard. Therefore, this study assessed the energy cost of running over a wide range of speeds in high-level and recreational runners to investigate the effect of speed (in absolute and relative terms) and sex (men vs women of equivalent performance standard) on running economy. To determine the energy cost (kcal · kg -1  · km -1 ) of submaximal running, speed at lactate turn point (sLTP), and maximal rate of oxygen uptake, 92 healthy runners (high-level men, n = 14; high-level women, n = 10; recreational men, n = 35; recreational women, n = 33) completed a discontinuous incremental treadmill test. There were no sex-specific differences in the energy cost of running for the recreational or high-level runners when compared at absolute or relative running speeds (P > .05). The absolute and relative speed-energy cost relationships for the high-level runners demonstrated a curvilinear U shape with a nadir reflecting the most economical speed at 13 km/h or 70% sLTP. The high-level runners were more economical than the recreational runners at all absolute and relative running speeds (P < .05). These findings demonstrate that there is an optimal speed for economical running, there is no sex-specific difference, and high-level endurance runners exhibit better running economy than recreational endurance runners.

Implementing two optimal economical quantum cloning with superconducting quantum interference devices in a cavity

NASA Astrophysics Data System (ADS)

Ye, Liu; Hu, GuiYu; Li, AiXia

2011-01-01

We propose a unified scheme to implement the optimal 1 → 3 economical phase-covariant quantum cloning and optimal 1 → 3 economical real state cloning with superconducting quantum interference devices (SQUIDs) in a cavity. During this process, no transfer of quantum information between the SQUIDs and cavity is required. The cavity field is only virtually excited. The scheme is insensitive to cavity decay. Therefore, the scheme can be experimentally realized in the range of current cavity QED techniques.

An interval programming model for continuous improvement in micro-manufacturing

NASA Astrophysics Data System (ADS)

Ouyang, Linhan; Ma, Yizhong; Wang, Jianjun; Tu, Yiliu; Byun, Jai-Hyun

2018-03-01

Continuous quality improvement in micro-manufacturing processes relies on optimization strategies that relate an output performance to a set of machining parameters. However, when determining the optimal machining parameters in a micro-manufacturing process, the economics of continuous quality improvement and decision makers' preference information are typically neglected. This article proposes an economic continuous improvement strategy based on an interval programming model. The proposed strategy differs from previous studies in two ways. First, an interval programming model is proposed to measure the quality level, where decision makers' preference information is considered in order to determine the weight of location and dispersion effects. Second, the proposed strategy is a more flexible approach since it considers the trade-off between the quality level and the associated costs, and leaves engineers a larger decision space through adjusting the quality level. The proposed strategy is compared with its conventional counterparts using an Nd:YLF laser beam micro-drilling process.

Advanced Cogeneration Technology Economic Optimization Study (ACTEOS)

NASA Technical Reports Server (NTRS)

Nanda, P.; Ansu, Y.; Manuel, E. H., Jr.; Price, W. G., Jr.

1980-01-01

The advanced cogeneration technology economic optimization study (ACTEOS) was undertaken to extend the results of the cogeneration technology alternatives study (CTAS). Cost comparisons were made between designs involving advanced cogeneration technologies and designs involving either conventional cogeneration technologies or not involving cogeneration. For the specific equipment cost and fuel price assumptions made, it was found that: (1) coal based cogeneration systems offered appreciable cost savings over the no cogeneration case, while systems using coal derived liquids offered no costs savings; and (2) the advanced cogeneration systems provided somewhat larger cost savings than the conventional systems. Among the issues considered in the study included: (1) temporal variations in steam and electric demands; (2) requirements for reliability/standby capacity; (3) availability of discrete equipment sizes; (4) regional variations in fuel and electricity prices; (5) off design system performance; and (6) separate demand and energy charges for purchased electricity.

Modeling the role of information and limited optimal treatment on disease prevalence.

PubMed

Kumar, Anuj; Srivastava, Prashant K; Takeuchi, Yasuhiro

2017-02-07

Disease outbreaks induce behavioural changes in healthy individuals to avoid contracting infection. We first propose a compartmental model which accounts for the effect of individual's behavioural response due to information of the disease prevalence. It is assumed that the information is growing as a function of infective population density that saturates at higher density of infective population and depends on active educational and social programmes. Model analysis has been performed and the global stability of equilibrium points is established. Further, choosing the treatment (a pharmaceutical intervention) and the effect of information (a non-pharmaceutical intervention) as controls, an optimal control problem is formulated to minimize the cost and disease fatality. In the cost functional, the nonlinear effect of controls is accounted. Analytical characterization of optimal control paths is done with the help of Pontryagin's Maximum Principle. Numerical findings suggest that if only control via information is used, it is effective and economical for early phase of disease spread whereas treatment works well for long term control except for initial phase. Furthermore, we observe that the effect of information induced behavioural response plays a crucial role in the absence of pharmaceutical control. Moreover, comprehensive use of both the control interventions is more effective than any single applied control policy and it reduces the number of infective individuals and minimizes the economic cost generated from disease burden and applied controls. Thus, the combined effect of both the control policies is found more economical during the entire epidemic period whereas the implementation of a single policy is not found economically viable. Copyright © 2016 Elsevier Ltd. All rights reserved.

A risk explicit interval linear programming model for uncertainty-based environmental economic optimization in the Lake Fuxian watershed, China.

PubMed

Zhang, Xiaoling; Huang, Kai; Zou, Rui; Liu, Yong; Yu, Yajuan

2013-01-01

The conflict of water environment protection and economic development has brought severe water pollution and restricted the sustainable development in the watershed. A risk explicit interval linear programming (REILP) method was used to solve integrated watershed environmental-economic optimization problem. Interval linear programming (ILP) and REILP models for uncertainty-based environmental economic optimization at the watershed scale were developed for the management of Lake Fuxian watershed, China. Scenario analysis was introduced into model solution process to ensure the practicality and operability of optimization schemes. Decision makers' preferences for risk levels can be expressed through inputting different discrete aspiration level values into the REILP model in three periods under two scenarios. Through balancing the optimal system returns and corresponding system risks, decision makers can develop an efficient industrial restructuring scheme based directly on the window of "low risk and high return efficiency" in the trade-off curve. The representative schemes at the turning points of two scenarios were interpreted and compared to identify a preferable planning alternative, which has the relatively low risks and nearly maximum benefits. This study provides new insights and proposes a tool, which was REILP, for decision makers to develop an effectively environmental economic optimization scheme in integrated watershed management.

A Risk Explicit Interval Linear Programming Model for Uncertainty-Based Environmental Economic Optimization in the Lake Fuxian Watershed, China

PubMed Central

Zou, Rui; Liu, Yong; Yu, Yajuan

2013-01-01

The conflict of water environment protection and economic development has brought severe water pollution and restricted the sustainable development in the watershed. A risk explicit interval linear programming (REILP) method was used to solve integrated watershed environmental-economic optimization problem. Interval linear programming (ILP) and REILP models for uncertainty-based environmental economic optimization at the watershed scale were developed for the management of Lake Fuxian watershed, China. Scenario analysis was introduced into model solution process to ensure the practicality and operability of optimization schemes. Decision makers' preferences for risk levels can be expressed through inputting different discrete aspiration level values into the REILP model in three periods under two scenarios. Through balancing the optimal system returns and corresponding system risks, decision makers can develop an efficient industrial restructuring scheme based directly on the window of “low risk and high return efficiency” in the trade-off curve. The representative schemes at the turning points of two scenarios were interpreted and compared to identify a preferable planning alternative, which has the relatively low risks and nearly maximum benefits. This study provides new insights and proposes a tool, which was REILP, for decision makers to develop an effectively environmental economic optimization scheme in integrated watershed management. PMID:24191144

Optimizing Biorefinery Design and Operations via Linear Programming Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Talmadge, Michael; Batan, Liaw; Lamers, Patrick

The ability to assess and optimize economics of biomass resource utilization for the production of fuels, chemicals and power is essential for the ultimate success of a bioenergy industry. The team of authors, consisting of members from the National Renewable Energy Laboratory (NREL) and the Idaho National Laboratory (INL), has developed simple biorefinery linear programming (LP) models to enable the optimization of theoretical or existing biorefineries. The goal of this analysis is to demonstrate how such models can benefit the developing biorefining industry. It focuses on a theoretical multi-pathway, thermochemical biorefinery configuration and demonstrates how the biorefinery can use LPmore » models for operations planning and optimization in comparable ways to the petroleum refining industry. Using LP modeling tools developed under U.S. Department of Energy's Bioenergy Technologies Office (DOE-BETO) funded efforts, the authors investigate optimization challenges for the theoretical biorefineries such as (1) optimal feedstock slate based on available biomass and prices, (2) breakeven price analysis for available feedstocks, (3) impact analysis for changes in feedstock costs and product prices, (4) optimal biorefinery operations during unit shutdowns / turnarounds, and (5) incentives for increased processing capacity. These biorefinery examples are comparable to crude oil purchasing and operational optimization studies that petroleum refiners perform routinely using LPs and other optimization models. It is important to note that the analyses presented in this article are strictly theoretical and they are not based on current energy market prices. The pricing structure assigned for this demonstrative analysis is consistent with $4 per gallon gasoline, which clearly assumes an economic environment that would favor the construction and operation of biorefineries. The analysis approach and examples provide valuable insights into the usefulness of analysis tools for maximizing the potential benefits of biomass utilization for production of fuels, chemicals and power.« less

Exergy & economic analysis of biogas fueled solid oxide fuel cell systems

NASA Astrophysics Data System (ADS)

Siefert, Nicholas S.; Litster, Shawn

2014-12-01

We present an exergy and an economic analysis of a power plant that uses biogas produced from a thermophilic anaerobic digester (AD) to fuel a solid oxide fuel cell (SOFC). We performed a 4-variable parametric analysis of the AD-SOFC system in order to determine the optimal design operation conditions, depending on the objective function of interest. We present results on the exergy efficiency (%), power normalized capital cost ( kW-1), and the internal rate of return on investment, IRR, (% yr-1) as a function of the current density, the stack pressure, the fuel utilization, and the total air stoichiometric ratio. To the authors' knowledge, this is the first AD-SOFC paper to include the cost of the AD when conducting economic optimization of the AD-SOFC plant. Our calculations show that adding a new AD-SOFC system to an existing waste water treatment (WWT) plant could yield positives values of IRR at today's average electricity prices and could significantly out-compete other options for using biogas to generate electricity. AD-SOFC systems could likely convert WWT plants into net generators of electricity rather than net consumers of electricity while generating economically viable rates of return on investment if the costs of SOFC systems are within a factor of two of the DOE/SECA cost targets.

Optimization Control of the Color-Coating Production Process for Model Uncertainty

PubMed Central

He, Dakuo; Wang, Zhengsong; Yang, Le; Mao, Zhizhong

2016-01-01

Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the model uncertainty, the robust optimization approach is introduced to improve the feasibility of the optimized solution. Iterative learning control is then utilized to further refine the model uncertainty. The constrained film thickness is transformed into one of the tracked targets to overcome the drawback that traditional iterative learning control cannot address constraints. The goal setting of economic efficiency is updated continuously according to the film thickness setting until this reaches its desired value. Finally, fuzzy parameter adjustment is adopted to ensure that the economic efficiency and film thickness converge rapidly to their optimized values under the constraint conditions. The effectiveness of the proposed optimization control strategy is validated by simulation results. PMID:27247563

Optimization Control of the Color-Coating Production Process for Model Uncertainty.

PubMed

He, Dakuo; Wang, Zhengsong; Yang, Le; Mao, Zhizhong

2016-01-01

Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the model uncertainty, the robust optimization approach is introduced to improve the feasibility of the optimized solution. Iterative learning control is then utilized to further refine the model uncertainty. The constrained film thickness is transformed into one of the tracked targets to overcome the drawback that traditional iterative learning control cannot address constraints. The goal setting of economic efficiency is updated continuously according to the film thickness setting until this reaches its desired value. Finally, fuzzy parameter adjustment is adopted to ensure that the economic efficiency and film thickness converge rapidly to their optimized values under the constraint conditions. The effectiveness of the proposed optimization control strategy is validated by simulation results.

Solar energy system economic evaluation for Elcam-Tempe, Tempe, Arizona and Elcam-San Diego, San Diego, California

NASA Technical Reports Server (NTRS)

1980-01-01

The long term economic performance of the solar energy system at its installation site is analyzed and four additional locations selected to demonstrate the viability of the design over a broad range of environmental and economic conditions. The economic analysis of the solar energy systems that were installed at Tempe, Arizona and San Diego, California, is developed for these and four other sites typical of a wide range of environmental and economic conditions in the continental United States. This analysis is accomplished based on the technical and economic models in the f Chart design procedure with inputs based on the characteristics of the installed system and local conditions. The results are expressed in terms of the economic parameters of present worth of system cost over a projected twenty year life: life cycle savings; year of positive savings; and year of payback for the optimized solar energy system at each of the analysis sites. The sensitivity of the economic evaluation to uncertainites in constituent system and economic variables is also investigated. The results demonstrate that the solar energy system is economically viable at all of the sites for which the analysis was conducted.

A prototype scanning system for optimal edging and trimming of rough hardwood lumber

Treesearch

Sang-Mook Lee; A. Lynn Abbott; Philip A. Araman; Daniel L. Schmoldt

2003-01-01

This paper is concerned with scanning and assessment of hardwood lumber early in the manufacturing process. Scanning operations that take place immediately after the headrig have significantly greater potential to reduce loss and improve economic value, as compared to scanning that is performed during subsequent manufacturing steps. In spite of this, the scanning of...

Timber RAM. . .a long-range planning method for commercial timber lands under multiple-use management

Treesearch

Daniel I. Navon

1971-01-01

Timber RAM (Resource Allocation Method) is a long-range planning method for commercial timber lands under multiple-use management. Timber RAM can produce cutting and reforestation schedules and related harvest and economic reports. Each schedule optimizes an index of performance, subject to periodic constraints on revenues, costs, and, harvest levels. Periodic...

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Shaughnessy, Eric; Ardani, Kristen; Cutler, Dylan

Solar 'plus' refers to an emerging approach to distributed solar photovoltaic (PV) deployment that uses energy storage and controllable devices to optimize customer economics. The solar plus approach increases customer system value through technologies such as electric batteries, smart domestic water heaters, smart air-conditioner (AC) units, and electric vehicles We use an NREL optimization model to explore the customer-side economics of solar plus under various utility rate structures and net metering rates. We explore optimal solar plus applications in five case studies with different net metering rates and rate structures. The model deploys different configurations of PV, batteries, smart domesticmore » water heaters, and smart AC units in response to different rate structures and customer load profiles. The results indicate that solar plus improves the customer economics of PV and may mitigate some of the negative impacts of evolving rate structures on PV economics. Solar plus may become an increasingly viable model for optimizing PV customer economics in an evolving rate environment.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Durt, Thomas; Fiurasek, Jaromir; Department of Optics, Palacky University, 17. listopadu 50, 77200 Olomouc

The possibility of cloning a d-dimensional quantum system without an ancilla is explored, extending on the economical phase-covariant cloning machine for qubits found in Phys. Rev. A 60, 2764 (1999). We prove the impossibility of constructing an economical version of the optimal universal 1{yields}2 cloning machine in any dimension. We also show, using an ansatz on the generic form of cloning machines, that the d-dimensional 1{yields}2 phase-covariant cloner, which optimally clones all balanced superpositions with arbitrary phases, can be realized economically only in dimension d=2. The used ansatz is supported by numerical evidence up to d=7. An economical phase-covariant clonermore » can nevertheless be constructed for d>2, albeit with a slightly lower fidelity than that of the optimal cloner requiring an ancilla. Finally, using again an ansatz on cloning machines, we show that an economical version of the 1{yields}2 Fourier-covariant cloner, which optimally clones the computational basis and its Fourier transform, is also possible only in dimension d=2.« less

Solar Plus: A Holistic Approach to Distributed Solar PV

DOE Office of Scientific and Technical Information (OSTI.GOV)

OShaughnessy, Eric J.; Ardani, Kristen B.; Cutler, Dylan S.

Solar 'plus' refers to an emerging approach to distributed solar photovoltaic (PV) deployment that uses energy storage and controllable devices to optimize customer economics. The solar plus approach increases customer system value through technologies such as electric batteries, smart domestic water heaters, smart air-conditioner (AC) units, and electric vehicles We use an NREL optimization model to explore the customer-side economics of solar plus under various utility rate structures and net metering rates. We explore optimal solar plus applications in five case studies with different net metering rates and rate structures. The model deploys different configurations of PV, batteries, smart domesticmore » water heaters, and smart AC units in response to different rate structures and customer load profiles. The results indicate that solar plus improves the customer economics of PV and may mitigate some of the negative impacts of evolving rate structures on PV economics. Solar plus may become an increasingly viable model for optimizing PV customer economics in an evolving rate environment.« less

cost and benefits optimization model for fault-tolerant aircraft electronic systems

NASA Technical Reports Server (NTRS)

1983-01-01

The factors involved in economic assessment of fault tolerant systems (FTS) and fault tolerant flight control systems (FTFCS) are discussed. Algorithms for optimization and economic analysis of FTFCS are documented.

A multi-objective optimization approach for the selection of working fluids of geothermal facilities: Economic, environmental and social aspects.

PubMed

Martínez-Gomez, Juan; Peña-Lamas, Javier; Martín, Mariano; Ponce-Ortega, José María

2017-12-01

The selection of the working fluid for Organic Rankine Cycles has traditionally been addressed from systematic heuristic methods, which perform a characterization and prior selection considering mainly one objective, thus avoiding a selection considering simultaneously the objectives related to sustainability and safety. The objective of this work is to propose a methodology for the optimal selection of the working fluid for Organic Rankine Cycles. The model is presented as a multi-objective approach, which simultaneously considers the economic, environmental and safety aspects. The economic objective function considers the profit obtained by selling the energy produced. Safety was evaluated in terms of individual risk for each of the components of the Organic Rankine Cycles and it was formulated as a function of the operating conditions and hazardous properties of each working fluid. The environmental function is based on carbon dioxide emissions, considering carbon dioxide mitigation, emission due to the use of cooling water as well emissions due material release. The methodology was applied to the case of geothermal facilities to select the optimal working fluid although it can be extended to waste heat recovery. The results show that the hydrocarbons represent better solutions, thus among a list of 24 working fluids, toluene is selected as the best fluid. Copyright © 2017 Elsevier Ltd. All rights reserved.

Economic feasibility and environmental impact of synthetic spider silk production from escherichia coli.

PubMed

Edlund, Alan M; Jones, Justin; Lewis, Randolph; Quinn, Jason C

2018-05-25

Major ampullate spider silk represents a promising protein-based biomaterial with diverse commercial potential ranging from textiles to medical devices due to its excellent physical and thermal properties. Recent advancements in synthetic biology have facilitated the development of recombinant spider silk proteins from Escherichia coli (E. coli). This study specifically investigates the economic feasibility and environmental impact of synthetic spider silk manufacturing. Pilot scale data was used to validate an engineering process model that includes all of the required sub-processing steps for synthetic fiber manufacture: production, harvesting, purification, drying, and spinning. Modeling was constructed modularly to support assessment of alternative downstream processing technologies. The techno-economic analysis indicates a minimum sale price from pioneer and optimized E. coli plants of $761 kg -1 and $23 kg -1 with greenhouse gas emissions of 572 kg CO 2-eq. kg -1 and 55 kg CO 2-eq. kg -1 , respectively. Elevated costs and emissions from the pioneer plant can be directly tied to the high material consumption and low protein yield. Decreased production costs associated with the optimized plant includes improved protein yield, process optimization, and an N th plant assumption. Discussion focuses on the commercial potential of spider silk, the production performance requirements for commercialization, and the impact of alternative technologies on the system. Copyright © 2018 Elsevier B.V. All rights reserved.

Executive Order 13514: Federal Leadership in Environmental, Energy, and Economic Performance; Comprehensive Federal Fleet Management Handbook (Book)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daley, R.; Ahdieh, N.; Bentley, J.

2014-01-01

A comprehensive Federal Fleet Management Handbook that builds upon the "Guidance for Federal Agencies on E.O. 13514 Section 12-Federal Fleet Management" and provides information to help fleet managers select optimal greenhouse gas and petroleum reduction strategies for each location, meeting or exceeding related fleet requirements, acquiring vehicles to support these strategies while minimizing fleet size and vehicle miles traveled, and refining strategies based on agency performance.

Generalized DSS shell for developing simulation and optimization hydro-economic models of complex water resources systems

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, Manuel; Lopez-Nicolas, Antonio; Harou, Julien J.; Andreu, Joaquin

2013-04-01

Hydrologic-economic models allow integrated analysis of water supply, demand and infrastructure management at the river basin scale. These models simultaneously analyze engineering, hydrology and economic aspects of water resources management. Two new tools have been designed to develop models within this approach: a simulation tool (SIM_GAMS), for models in which water is allocated each month based on supply priorities to competing uses and system operating rules, and an optimization tool (OPT_GAMS), in which water resources are allocated optimally following economic criteria. The characterization of the water resource network system requires a connectivity matrix representing the topology of the elements, generated using HydroPlatform. HydroPlatform, an open-source software platform for network (node-link) models, allows to store, display and export all information needed to characterize the system. Two generic non-linear models have been programmed in GAMS to use the inputs from HydroPlatform in simulation and optimization models. The simulation model allocates water resources on a monthly basis, according to different targets (demands, storage, environmental flows, hydropower production, etc.), priorities and other system operating rules (such as reservoir operating rules). The optimization model's objective function is designed so that the system meets operational targets (ranked according to priorities) each month while following system operating rules. This function is analogous to the one used in the simulation module of the DSS AQUATOOL. Each element of the system has its own contribution to the objective function through unit cost coefficients that preserve the relative priority rank and the system operating rules. The model incorporates groundwater and stream-aquifer interaction (allowing conjunctive use simulation) with a wide range of modeling options, from lumped and analytical approaches to parameter-distributed models (eigenvalue approach). Such functionality is not typically included in other water DSS. Based on the resulting water resources allocation, the model calculates operating and water scarcity costs caused by supply deficits based on economic demand functions for each demand node. The optimization model allocates the available resource over time based on economic criteria (net benefits from demand curves and cost functions), minimizing the total water scarcity and operating cost of water use. This approach provides solutions that optimize the economic efficiency (as total net benefit) in water resources management over the optimization period. Both models must be used together in water resource planning and management. The optimization model provides an initial insight on economically efficient solutions, from which different operating rules can be further developed and tested using the simulation model. The hydro-economic simulation model allows assessing economic impacts of alternative policies or operating criteria, avoiding the perfect foresight issues associated with the optimization. The tools have been applied to the Jucar river basin (Spain) in order to assess the economic results corresponding to the current modus operandi of the system and compare them with the solution from the optimization that maximizes economic efficiency. Acknowledgments: The study has been partially supported by the European Community 7th Framework Project (GENESIS project, n. 226536) and the Plan Nacional I+D+I 2008-2011 of the Spanish Ministry of Science and Innovation (CGL2009-13238-C02-01 and CGL2009-13238-C02-02).

Forecasting Optimal Solar Energy Supply in Jiangsu Province (China): A Systematic Approach Using Hybrid of Weather and Energy Forecast Models

PubMed Central

Zhao, Xiuli; Yiranbon, Ethel

2014-01-01

The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, “least-cost,” and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor. PMID:24511292

Forecasting optimal solar energy supply in Jiangsu Province (China): a systematic approach using hybrid of weather and energy forecast models.

PubMed

Zhao, Xiuli; Asante Antwi, Henry; Yiranbon, Ethel

2014-01-01

The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, "least-cost," and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor.

Decentralized Optimal Dispatch of Photovoltaic Inverters in Residential Distribution Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall'Anese, Emiliano; Dhople, Sairaj V.; Johnson, Brian B.

Summary form only given. Decentralized methods for computing optimal real and reactive power setpoints for residential photovoltaic (PV) inverters are developed in this paper. It is known that conventional PV inverter controllers, which are designed to extract maximum power at unity power factor, cannot address secondary performance objectives such as voltage regulation and network loss minimization. Optimal power flow techniques can be utilized to select which inverters will provide ancillary services, and to compute their optimal real and reactive power setpoints according to well-defined performance criteria and economic objectives. Leveraging advances in sparsity-promoting regularization techniques and semidefinite relaxation, this papermore » shows how such problems can be solved with reduced computational burden and optimality guarantees. To enable large-scale implementation, a novel algorithmic framework is introduced - based on the so-called alternating direction method of multipliers - by which optimal power flow-type problems in this setting can be systematically decomposed into sub-problems that can be solved in a decentralized fashion by the utility and customer-owned PV systems with limited exchanges of information. Since the computational burden is shared among multiple devices and the requirement of all-to-all communication can be circumvented, the proposed optimization approach scales favorably to large distribution networks.« less

An economic assessment of STOL aircraft potential including terminal area environmental considerations, volume 1

NASA Technical Reports Server (NTRS)

Solomon, H. L.; Sokolsky, S.

1974-01-01

The results of an economic and environmental study of short haul airline systems using short takeoff and landing (STOL) aircraft are presented. The STOL system characteristics were optimized for maximum patronage at a specified return on investment, while maintaining noise impact compatibility with the terminal area. Supporting studies of aircraft air pollution and hub airport congestion relief were also performed. The STOL concept specified for this study was an Augmentor Wing turbofan aircraft having a field length capability of 2,000 ft. and an effective perceived noise level of 95 EPNdB at 500 ft. sideline distance. An economic and environmental assessment of the defined STOL system and a summary of the methodology, STOL system characteristics and arena characteristics are provided.

Village power options

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lilienthal, P.

1997-12-01

This paper describes three different computer codes which have been written to model village power applications. The reasons which have driven the development of these codes include: the existance of limited field data; diverse applications can be modeled; models allow cost and performance comparisons; simulations generate insights into cost structures. The models which are discussed are: Hybrid2, a public code which provides detailed engineering simulations to analyze the performance of a particular configuration; HOMER - the hybrid optimization model for electric renewables - which provides economic screening for sensitivity analyses; and VIPOR the village power model - which is amore » network optimization model for comparing mini-grids to individual systems. Examples of the output of these codes are presented for specific applications.« less

Recovery Act: Innovative CO 2 Sequestration from Flue Gas Using Industrial Sources and Innovative Concept for Beneficial CO 2 Use

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dando, Neal; Gershenzon, Mike; Ghosh, Rajat

2012-07-31

The overall goal of this DOE Phase 2 project was to further develop and conduct pilot-scale and field testing of a biomimetic in-duct scrubbing system for the capture of gaseous CO 2 coupled with sequestration of captured carbon by carbonation of alkaline industrial wastes. The Phase 2 project, reported on here, combined efforts in enzyme development, scrubber optimization, and sequestrant evaluations to perform an economic feasibility study of technology deployment. The optimization of carbonic anhydrase (CA) enzyme reactivity and stability are critical steps in deployment of this technology. A variety of CA enzyme variants were evaluated for reactivity and stabilitymore » in both bench scale and in laboratory pilot scale testing to determine current limits in enzyme performance. Optimization of scrubber design allowed for improved process economics while maintaining desired capture efficiencies. A range of configurations, materials, and operating conditions were examined at the Alcoa Technical Center on a pilot scale scrubber. This work indicated that a cross current flow utilizing a specialized gas-liquid contactor offered the lowest system operating energy. Various industrial waste materials were evaluated as sources of alkalinity for the scrubber feed solution and as sources of calcium for precipitation of carbonate. Solids were mixed with a simulated sodium bicarbonate scrubber blowdown to comparatively examine reactivity. Supernatant solutions and post-test solids were analyzed to quantify and model the sequestration reactions. The best performing solids were found to sequester between 2.3 and 2.9 moles of CO 2 per kg of dry solid in 1-4 hours of reaction time. These best performing solids were cement kiln dust, circulating dry scrubber ash, and spray dryer absorber ash. A techno-economic analysis was performed to evaluate the commercial viability of the proposed carbon capture and sequestration process in full-scale at an aluminum smelter and a refinery location. For both cases the in-duct scrubber technology was compared to traditional amine- based capture. Incorporation of the laboratory results showed that for the application at the aluminum smelter, the in-duct scrubber system is more economical than traditional methods. However, the reverse is true for the refinery case, where the bauxite residue is not effective enough as a sequestrant, combined with challenges related to contaminants in the bauxite residue accumulating in and fouling the scrubber absorbent. Sensitivity analyses showed that the critical variables by which process economics could be improved are enzyme concentration, efficiency, and half-life. At the end of the first part of the Phase 2 project, a gate review (DOE Decision Zero Gate Point) was conducted to decide on the next stages of the project. The original plan was to follow the pre-testing phase with a detailed design for the field testing. Unfavorable process economics, however, resulted in a decision to conclude the project before moving to field testing. It is noted that CO 2 Solutions proposed an initial solution to reduce process costs through more advanced enzyme management, however, DOE program requirements restricting any technology development extending beyond 2014 as commercial deployment timeline did not allow this solution to be undertaken.« less

Generalized Convexity and Concavity Properties of the Optimal Value Function in Parametric Nonlinear Programming.

DTIC Science & Technology

1983-04-11

existing ones. * -37- !I T-472 REFERENCES [1] Avriel, M., W. E. Diewert, S. Schaible and W. T. Ziemba (1981). Introduction to concave and generalized concave...functions. In Generalized Concavity in Optimization and Economics (S. Schaible and W. T. Ziemba , eds.), Academic Press, New York, pp. 21-50. (21 Bank...Optimality conditions involving generalized convex mappings. In Generalized Concavity in Optimization and Economics (S. Schaible and W. T. Ziemba

Swarm based mean-variance mapping optimization (MVMOS) for solving economic dispatch

NASA Astrophysics Data System (ADS)

Khoa, T. H.; Vasant, P. M.; Singh, M. S. Balbir; Dieu, V. N.

2014-10-01

The economic dispatch (ED) is an essential optimization task in the power generation system. It is defined as the process of allocating the real power output of generation units to meet required load demand so as their total operating cost is minimized while satisfying all physical and operational constraints. This paper introduces a novel optimization which named as Swarm based Mean-variance mapping optimization (MVMOS). The technique is the extension of the original single particle mean-variance mapping optimization (MVMO). Its features make it potentially attractive algorithm for solving optimization problems. The proposed method is implemented for three test power systems, including 3, 13 and 20 thermal generation units with quadratic cost function and the obtained results are compared with many other methods available in the literature. Test results have indicated that the proposed method can efficiently implement for solving economic dispatch.

Game theory and risk-based leveed river system planning with noncooperation

NASA Astrophysics Data System (ADS)

Hui, Rui; Lund, Jay R.; Madani, Kaveh

2016-01-01

Optimal risk-based levee designs are usually developed for economic efficiency. However, in river systems with multiple levees, the planning and maintenance of different levees are controlled by different agencies or groups. For example, along many rivers, levees on opposite riverbanks constitute a simple leveed river system with each levee designed and controlled separately. Collaborative planning of the two levees can be economically optimal for the whole system. Independent and self-interested landholders on opposite riversides often are willing to separately determine their individual optimal levee plans, resulting in a less efficient leveed river system from an overall society-wide perspective (the tragedy of commons). We apply game theory to simple leveed river system planning where landholders on each riverside independently determine their optimal risk-based levee plans. Outcomes from noncooperative games are analyzed and compared with the overall economically optimal outcome, which minimizes net flood cost system-wide. The system-wide economically optimal solution generally transfers residual flood risk to the lower-valued side of the river, but is often impractical without compensating for flood risk transfer to improve outcomes for all individuals involved. Such compensation can be determined and implemented with landholders' agreements on collaboration to develop an economically optimal plan. By examining iterative multiple-shot noncooperative games with reversible and irreversible decisions, the costs of myopia for the future in making levee planning decisions show the significance of considering the externalities and evolution path of dynamic water resource problems to improve decision-making.

Economic evaluation of genomic selection in small ruminants: a sheep meat breeding program.

PubMed

Shumbusho, F; Raoul, J; Astruc, J M; Palhiere, I; Lemarié, S; Fugeray-Scarbel, A; Elsen, J M

2016-06-01

Recent genomic evaluation studies using real data and predicting genetic gain by modeling breeding programs have reported moderate expected benefits from the replacement of classic selection schemes by genomic selection (GS) in small ruminants. The objectives of this study were to compare the cost, monetary genetic gain and economic efficiency of classic selection and GS schemes in the meat sheep industry. Deterministic methods were used to model selection based on multi-trait indices from a sheep meat breeding program. Decisional variables related to male selection candidates and progeny testing were optimized to maximize the annual monetary genetic gain (AMGG), that is, a weighted sum of meat and maternal traits annual genetic gains. For GS, a reference population of 2000 individuals was assumed and genomic information was available for evaluation of male candidates only. In the classic selection scheme, males breeding values were estimated from own and offspring phenotypes. In GS, different scenarios were considered, differing by the information used to select males (genomic only, genomic+own performance, genomic+offspring phenotypes). The results showed that all GS scenarios were associated with higher total variable costs than classic selection (if the cost of genotyping was 123 euros/animal). In terms of AMGG and economic returns, GS scenarios were found to be superior to classic selection only if genomic information was combined with their own meat phenotypes (GS-Pheno) or with their progeny test information. The predicted economic efficiency, defined as returns (proportional to number of expressions of AMGG in the nucleus and commercial flocks) minus total variable costs, showed that the best GS scenario (GS-Pheno) was up to 15% more efficient than classic selection. For all selection scenarios, optimization increased the overall AMGG, returns and economic efficiency. As a conclusion, our study shows that some forms of GS strategies are more advantageous than classic selection, provided that GS is already initiated (i.e. the initial reference population is available). Optimizing decisional variables of the classic selection scheme could be of greater benefit than including genomic information in optimized designs.

Production of biosolid fuels from municipal sewage sludge: Technical and economic optimisation.

PubMed

Wzorek, Małgorzata; Tańczuk, Mariusz

2015-08-01

The article presents the technical and economic analysis of the production of fuels from municipal sewage sludge. The analysis involved the production of two types of fuel compositions: sewage sludge with sawdust (PBT fuel) and sewage sludge with meat and bone meal (PBM fuel). The technology of the production line of these sewage fuels was proposed and analysed. The main objective of the study is to find the optimal production capacity. The optimisation analysis was performed for the adopted technical and economic parameters under Polish conditions. The objective function was set as a maximum of the net present value index and the optimisation procedure was carried out for the fuel production line input capacity from 0.5 to 3 t h(-1), using the search step 0.5 t h(-1). On the basis of technical and economic assumptions, economic efficiency indexes of the investment were determined for the case of optimal line productivity. The results of the optimisation analysis show that under appropriate conditions, such as prices of components and prices of produced fuels, the production of fuels from sewage sludge can be profitable. In the case of PBT fuel, calculated economic indexes show the best profitability for the capacity of a plant over 1.5 t h(-1) output, while production of PBM fuel is beneficial for a plant with the maximum of searched capacities: 3.0 t h(-1). Sensitivity analyses carried out during the investigation show that influence of both technical and economic assessments on the location of maximum of objective function (net present value) is significant. © The Author(s) 2015.

A New Tool for Environmental and Economic Optimization of Hydropower Operations

NASA Astrophysics Data System (ADS)

Saha, S.; Hayse, J. W.

2012-12-01

As part of a project funded by the U.S. Department of Energy, researchers from Argonne, Oak Ridge, Pacific Northwest, and Sandia National Laboratories collaborated on the development of an integrated toolset to enhance hydropower operational decisions related to economic value and environmental performance. As part of this effort, we developed an analytical approach (Index of River Functionality, IRF) and an associated software tool to evaluate how well discharge regimes achieve ecosystem management goals for hydropower facilities. This approach defines site-specific environmental objectives using relationships between environmental metrics and hydropower-influenced flow characteristics (e.g., discharge or temperature), with consideration given to seasonal timing, duration, and return frequency requirements for the environmental objectives. The IRF approach evaluates the degree to which an operational regime meets each objective and produces a score representing how well that regime meets the overall set of defined objectives. When integrated with other components in the toolset that are used to plan hydropower operations based upon hydrologic forecasts and various constraints on operations, the IRF approach allows an optimal release pattern to be developed based upon tradeoffs between environmental performance and economic value. We tested the toolset prototype to generate a virtual planning operation for a hydropower facility located in the Upper Colorado River basin as a demonstration exercise. We conducted planning as if looking five months into the future using data for the recently concluded 2012 water year. The environmental objectives for this demonstration were related to spawning and nursery habitat for endangered fishes using metrics associated with maintenance of instream habitat and reconnection of the main channel with floodplain wetlands in a representative reach of the river. We also applied existing mandatory operational constraints for the facility during the demonstration. We compared the optimized virtual operation identified by the toolset to actual operations at the facility for the same time period to evaluate implications of the optimized operational regime on power/revenue generation and environmental performance. Argonne National Laboratory's work was part of a larger "Water-Use-Optimization" project supported by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy, Water Power Program, under Announcement DE-FOA-0000070. The submitted manuscript has been created by UChicago Argonne, LLC, Operator of Argonne National Laboratory ("Argonne"). Argonne, a U.S. Department of Energy Office of Science laboratory, is operated under Contract No. DE-AC02-06CH11357. The U.S. Government retains for itself, and others acting on its behalf, a paid-up nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly, by or on behalf of the Government.

Climate change, urbanization, and optimal long-term floodplain protection

NASA Astrophysics Data System (ADS)

Zhu, Tingju; Lund, Jay R.; Jenkins, Marion W.; Marques, Guilherme F.; Ritzema, Randall S.

2007-06-01

This paper examines levee-protected floodplains and economic aspects of adaptation to increasing long-term flood risk due to urbanization and climate change. The lower American River floodplain in the Sacramento, California, metropolitan area is used as an illustration to explore the course of optimal floodplain protection decisions over long periods. A dynamic programming model is developed and suggests economically desirable adaptations for floodplain levee systems given simultaneous changes in flood climate and urban land values. Economic engineering optimization analyses of several climate change and urbanization scenarios are made. Sensitivity analyses consider assumptions about future values of floodplain land and damageable property along with the discount rate. Methodological insights and policy lessons are drawn from modeling results, reflecting the joint effects and relationships that climate, economic costs, and regional economic growth can have on floodplain levee planning decisions.

Conceptual design study of 1985 commercial VTOL transports that utilize rotors

NASA Technical Reports Server (NTRS)

Kefford, N. F. K.; Munch, C. L.

1975-01-01

Conceptual design studies of pure and compound helicopter commercial short-haul transport aircraft for initial fabrication in 1980 were performed to determine their technical and economic feasibility. One-hundred-passenger configurations were optimized for minimum direct operating cost consistent with producibility and marketability, with emphasis on proper account of mass properties, performance and handling qualities adequacy, and suppression of internal and external noise. The effect of external noise constraints was assessed, in terms of gross weight and direct operating cost, for each aircraft.

Overcoming the Range Limitation of Medium-Duty Battery Electric Vehicles through the use of Hydrogen Fuel-Cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wood, E.; Wang, L.; Gonder, J.

2013-10-01

Battery electric vehicles possess great potential for decreasing lifecycle costs in medium-duty applications, a market segment currently dominated by internal combustion technology. Characterized by frequent repetition of similar routes and daily return to a central depot, medium-duty vocations are well positioned to leverage the low operating costs of battery electric vehicles. Unfortunately, the range limitation of commercially available battery electric vehicles acts as a barrier to widespread adoption. This paper describes the National Renewable Energy Laboratory's collaboration with the U.S. Department of Energy and industry partners to analyze the use of small hydrogen fuel-cell stacks to extend the range ofmore » battery electric vehicles as a means of improving utility, and presumably, increasing market adoption. This analysis employs real-world vocational data and near-term economic assumptions to (1) identify optimal component configurations for minimizing lifecycle costs, (2) benchmark economic performance relative to both battery electric and conventional powertrains, and (3) understand how the optimal design and its competitiveness change with respect to duty cycle and economic climate. It is found that small fuel-cell power units provide extended range at significantly lower capital and lifecycle costs than additional battery capacity alone. And while fuel-cell range-extended vehicles are not deemed economically competitive with conventional vehicles given present-day economic conditions, this paper identifies potential future scenarios where cost equivalency is achieved.« less

Reduction of liquid hydrogen boiloff: Optimal reliquefaction system design and cost study

NASA Technical Reports Server (NTRS)

1978-01-01

A preliminary design and economic analysis of candidate hydrogen reliquefaction systems was performed. All candidate systems are of the same general type; differences and size, compressor arrangement, and amount of hydrogen venting. The potential application of the hydrogen reliquefaction will be to reduce the boil-off from the 850,000 gallon storage dewars at LC-39.

Technical and economical optimization of a full-scale poultry manure treatment process: total ammonia nitrogen balance.

PubMed

Alejo-Alvarez, Luz; Guzmán-Fierro, Víctor; Fernández, Katherina; Roeckel, Marlene

2016-11-01

A full-scale process for the treatment of 80 tons per day of poultry manure was designed and optimized. A total ammonia nitrogen (TAN) balance was performed at steady state, considering the stoichiometry and the kinetic data from the anaerobic digestion and the anaerobic ammonia oxidation. The equipment, reactor design, investment costs, and operational costs were considered. The volume and cost objective functions optimized the process in terms of three variables: the water recycle ratio, the protein conversion during AD, and the TAN conversion in the process. The processes were compared with and without water recycle; savings of 70% and 43% in the annual fresh water consumption and the heating costs, respectively, were achieved. The optimal process complies with the Chilean environmental legislation limit of 0.05 g total nitrogen/L.

Optimal Sizing Tool for Battery Storage in Grid Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

2015-09-24

The battery storage sizing tool developed at Pacific Northwest National Laboratory can be used to evaluate economic performance and determine the optimal size of battery storage in different use cases considering multiple power system applications. The considered use cases include i) utility owned battery storage, and ii) battery storage behind customer meter. The power system applications from energy storage include energy arbitrage, balancing services, T&D deferral, outage mitigation, demand charge reduction etc. Most of existing solutions consider only one or two grid services simultaneously, such as balancing service and energy arbitrage. ES-select developed by Sandia and KEMA is able tomore » consider multiple grid services but it stacks the grid services based on priorities instead of co-optimization. This tool is the first one that provides a co-optimization for systematic and local grid services.« less

Planning water supply under uncertainty - benefits and limitations of RDM, Info-Gap, economic optimization and many-objective optimization

NASA Astrophysics Data System (ADS)

Matrosov, E.; Padula, S.; Huskova, I.; Harou, J. J.

2012-12-01

Population growth and the threat of drier or changed climates are likely to increase water scarcity world-wide. A combination of demand management (water conservation) and new supply infrastructure is often needed to meet future projected demands. In this case system planners must decide what to implement, when and at what capacity. Choices can range from infrastructure to policies or a mix of the two, culminating in a complex planning problem. Decision making under uncertainty frameworks can be used to help planners with this planning problem. This presentation introduces, applies and compares four decision making under uncertainty frameworks. The application is to the Thames basin water resource system which includes the city of London. The approaches covered here include least-economic cost capacity expansion optimization (EO), Robust Decision Making (RDM), Info-Gap Decision Theory (Info-gap) and many-objective evolutionary optimization (MOEO). EO searches for the least-economic cost program, i.e. the timing, sizing, and choice of supply-demand management actions/upgrades which meet projected water demands. Instead of striving for optimality, the RDM and Info-gap approaches help build plans that are robust to 'deep' uncertainty in future conditions. The MOEO framework considers multiple performance criteria and uses water systems simulators as a function evaluator for the evolutionary algorithm. Visualizations show Pareto approximate tradeoffs between multiple objectives. In this presentation we detail the application of each framework to the Thames basin (including London) water resource planning problem. Supply and demand options are proposed by the major water companies in the basin. We apply the EO method using a 29 year time horizon and an annual time step considering capital, operating (fixed and variable), social and environmental costs. The method considers all plausible combinations of supply and conservation schemes and capacities proposed by water companies and generates the least-economic cost annual plan. The RDM application uses stochastic simulation under a weekly time-step and regret analysis to choose a candidate strategy. We then use a statistical cluster algorithm to identify future states of the world under which the strategy is vulnerable. The method explicitly considers the effects of uncertainty in supply, demands and energy price on multiple performance criteria. The Info-gap approach produces robustness and opportuneness plots that show the performance of different plans under the most dire and favorable sets of future conditions. The same simulator, supply and demand options and uncertainties are considered as in the RDM application. The MOEO application considers many more combinations of supply and demand options while still employing a simulator that enables a more realistic representation of the physical system and operating rules. A computer cluster is employed to ease the computational burden. Visualization software allows decision makers to interactively view tradeoffs in many dimensions. Benefits and limitations of each framework are discussed and recommendations for future planning in the basin are provided.

Global Design Optimization for Aerodynamics and Rocket Propulsion Components

NASA Technical Reports Server (NTRS)

Shyy, Wei; Papila, Nilay; Vaidyanathan, Rajkumar; Tucker, Kevin; Turner, James E. (Technical Monitor)

2000-01-01

Modern computational and experimental tools for aerodynamics and propulsion applications have matured to a stage where they can provide substantial insight into engineering processes involving fluid flows, and can be fruitfully utilized to help improve the design of practical devices. In particular, rapid and continuous development in aerospace engineering demands that new design concepts be regularly proposed to meet goals for increased performance, robustness and safety while concurrently decreasing cost. To date, the majority of the effort in design optimization of fluid dynamics has relied on gradient-based search algorithms. Global optimization methods can utilize the information collected from various sources and by different tools. These methods offer multi-criterion optimization, handle the existence of multiple design points and trade-offs via insight into the entire design space, can easily perform tasks in parallel, and are often effective in filtering the noise intrinsic to numerical and experimental data. However, a successful application of the global optimization method needs to address issues related to data requirements with an increase in the number of design variables, and methods for predicting the model performance. In this article, we review recent progress made in establishing suitable global optimization techniques employing neural network and polynomial-based response surface methodologies. Issues addressed include techniques for construction of the response surface, design of experiment techniques for supplying information in an economical manner, optimization procedures and multi-level techniques, and assessment of relative performance between polynomials and neural networks. Examples drawn from wing aerodynamics, turbulent diffuser flows, gas-gas injectors, and supersonic turbines are employed to help demonstrate the issues involved in an engineering design context. Both the usefulness of the existing knowledge to aid current design practices and the need for future research are identified.

Optimizing DER Participation in Inertial and Primary-Frequency Response

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall-Anese, Emiliano; Zhao, Changhong; Guggilam, Swaroop

This paper develops an approach to enable the optimal participation of distributed energy resources (DERs) in inertial and primary-frequency response alongside conventional synchronous generators. Leveraging a reduced-order model description of frequency dynamics, DERs' synthetic inertias and droop coefficients are designed to meet time-domain performance objectives of frequency overshoot and steady-state regulation. Furthermore, an optimization-based method centered around classical economic dispatch is developed to ensure that DERs share the power injections for inertial- and primary-frequency response in proportion to their power ratings. Simulations for a modified New England test-case system composed of ten synchronous generators and six instances of the IEEEmore » 37-node test feeder with frequency-responsive DERs validate the design strategy.« less

Numerical solution of a conspicuous consumption model with constant control delay☆

PubMed Central

Huschto, Tony; Feichtinger, Gustav; Hartl, Richard F.; Kort, Peter M.; Sager, Sebastian; Seidl, Andrea

2011-01-01

We derive optimal pricing strategies for conspicuous consumption products in periods of recession. To that end, we formulate and investigate a two-stage economic optimal control problem that takes uncertainty of the recession period length and delay effects of the pricing strategy into account. This non-standard optimal control problem is difficult to solve analytically, and solutions depend on the variable model parameters. Therefore, we use a numerical result-driven approach. We propose a structure-exploiting direct method for optimal control to solve this challenging optimization problem. In particular, we discretize the uncertainties in the model formulation by using scenario trees and target the control delays by introduction of slack control functions. Numerical results illustrate the validity of our approach and show the impact of uncertainties and delay effects on optimal economic strategies. During the recession, delayed optimal prices are higher than the non-delayed ones. In the normal economic period, however, this effect is reversed and optimal prices with a delayed impact are smaller compared to the non-delayed case. PMID:22267871

A comprehensive approach for diagnosing opportunities for improving the performance of a WWTP.

PubMed

Silva, C; Matos, J Saldanha; Rosa, M J

2016-12-01

High quality services of wastewater treatment require a continuous assessment and improvement of the technical, environmental and economic performance. This paper demonstrates a comprehensive approach for benchmarking wastewater treatment plants (WWTPs), using performance indicators (PIs) and indices (PXs), in a 'plan-do-check-act' cycle routine driven by objectives. The performance objectives herein illustrated were to diagnose the effectiveness and energy performance of an oxidation ditch WWTP. The PI and PX results demonstrated an effective and reliable oxidation ditch (good-excellent performance), and a non-reliable UV disinfection (unsatisfactory-excellent performance) related with influent transmittance and total suspended solids. The energy performance increased with the treated wastewater volume and was unsatisfactory below 50% of plant capacity utilization. The oxidation ditch aeration performed unsatisfactorily and represented 38% of the plant energy consumption. The results allowed diagnosing opportunities for improving the energy and economic performance considering the influent flows, temperature and concentrations, and for levering the WWTP performance to acceptable-good effectiveness, reliability and energy efficiency. Regarding the plant reliability for fecal coliforms, improvement of UV lamp maintenance and optimization of the UV dose applied and microscreen recommissioning were suggested.

Development of cost-effective surfactant flooding technology, Quarterly report, October 1995--December 1995

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pope, G.A.; Sepehrnoori, K.

1995-12-31

The objective of this research is to develop cost-effective surfactant flooding technology by using simulation studies to evaluate and optimize alternative design strategies taking into account reservoir characteristics process chemistry, and process design options such as horizontal wells. Task 1 is the development of an improved numerical method for our simulator that will enable us to solve a wider class of these difficult simulation problems accurately and affordably. Task 2 is the application of this simulator to the optimization of surfactant flooding to reduce its risk and cost. In this quarter, we have continued working on Task 2 to optimizemore » surfactant flooding design and have included economic analysis to the optimization process. An economic model was developed using a spreadsheet and the discounted cash flow (DCF) method of economic analysis. The model was designed specifically for a domestic onshore surfactant flood and has been used to economically evaluate previous work that used a technical approach to optimization. The DCF model outputs common economic decision making criteria, such as net present value (NPV), internal rate of return (IRR), and payback period.« less

[Clinical economics: a concept to optimize healthcare services].

PubMed

Porzsolt, F; Bauer, K; Henne-Bruns, D

2012-03-01

Clinical economics strives to support healthcare decisions by economic considerations. Making economic decisions does not mean saving costs but rather comparing the gained added value with the burden which has to be accepted. The necessary rules are offered in various disciplines, such as economy, epidemiology and ethics. Medical doctors have recognized these rules but are not applying them in daily clinical practice. This lacking orientation leads to preventable errors. Examples of these errors are shown for diagnosis, screening, prognosis and therapy. As these errors can be prevented by application of clinical economic principles the possible consequences for optimization of healthcare are discussed.

Optimal house elevation for reducing flood-related losses

NASA Astrophysics Data System (ADS)

Xian, Siyuan; Lin, Ning; Kunreuther, Howard

2017-05-01

FEMA recommends that houses in coastal flood zones be elevated to at least 1 foot above the base flood elevation (BFE). However, this guideline is not specific and ignores characteristics of houses that affect their vulnerability. An economically optimal elevation level (OEL) is proposed that minimizes the combined cost of elevation and cumulative insurance premiums over the lifespan of the house. As an illustration, analysis is performed for various coastal houses in Ortley Beach, NJ. Compared with the strategy of raising houses to 1 foot above BFE, the strategy of raising houses to their OELs is much more economical for the homeowners. Elevating to the OELs also significantly reduces government spending on subsidizing low-income homeowners through, for example, a voucher program, to mitigate flood risk. These results suggest that policy makers should consider vulnerability factors in developing risk-reduction strategies. FEMA may recommend OELs to homeowners based on their flood hazards as well as house characteristics or at least providing more information and tools to homeowners to assist them in making more economical decisions. The OEL strategy can also be coupled with a voucher program to make the program more cost-effective.

Investigation and optimization of the depth of flue gas heat recovery in surface heat exchangers

NASA Astrophysics Data System (ADS)

Bespalov, V. V.; Bespalov, V. I.; Melnikov, D. V.

2017-09-01

Economic issues associated with designing deep flue gas heat recovery units for natural gas-fired boilers are examined. The governing parameter affecting the performance and cost of surface-type condensing heat recovery heat exchangers is the heat transfer surface area. When firing natural gas, the heat recovery depth depends on the flue gas temperature at the condenser outlet and determines the amount of condensed water vapor. The effect of the outlet flue gas temperature in a heat recovery heat exchanger on the additionally recovered heat power is studied. A correlation has been derived enabling one to determine the best heat recovery depth (or the final cooling temperature) maximizing the anticipated reduced annual profit of a power enterprise from implementation of energy-saving measures. Results of optimization are presented for a surface-type condensing gas-air plate heat recovery heat exchanger for the climatic conditions and the economic situation in Tomsk. The predictions demonstrate that it is economically feasible to design similar heat recovery heat exchangers for a flue gas outlet temperature of 10°C. In this case, the payback period for the investment in the heat recovery heat exchanger will be 1.5 years. The effect of various factors on the optimal outlet flue gas temperature was analyzed. Most climatic, economical, or technological factors have a minor effect on the best outlet temperature, which remains between 5 and 20°C when varying the affecting factors. The derived correlation enables us to preliminary estimate the outlet (final) flue gas temperature that should be used in designing the heat transfer surface of a heat recovery heat exchanger for a gas-fired boiler as applied to the specific climatic conditions.

Optimizing Multiple QoS for Workflow Applications using PSO and Min-Max Strategy

NASA Astrophysics Data System (ADS)

Umar Ambursa, Faruku; Latip, Rohaya; Abdullah, Azizol; Subramaniam, Shamala

2017-08-01

Workflow scheduling under multiple QoS constraints is a complicated optimization problem. Metaheuristic techniques are excellent approaches used in dealing with such problem. Many metaheuristic based algorithms have been proposed, that considers various economic and trustworthy QoS dimensions. However, most of these approaches lead to high violation of user-defined QoS requirements in tight situation. Recently, a new Particle Swarm Optimization (PSO)-based QoS-aware workflow scheduling strategy (LAPSO) is proposed to improve performance in such situations. LAPSO algorithm is designed based on synergy between a violation handling method and a hybrid of PSO and min-max heuristic. Simulation results showed a great potential of LAPSO algorithm to handling user requirements even in tight situations. In this paper, the performance of the algorithm is anlysed further. Specifically, the impact of the min-max strategy on the performance of the algorithm is revealed. This is achieved by removing the violation handling from the operation of the algorithm. The results show that LAPSO based on only the min-max method still outperforms the benchmark, even though the LAPSO with the violation handling performs more significantly better.

Cocoa based agroforestry: An economic perspective in resource scarcity conflict era

NASA Astrophysics Data System (ADS)

Jumiyati, S.; Arsyad, M.; Rajindra; Pulubuhu, D. A. T.; Hadid, A.

2018-05-01

Agricultural development towards food self-sufficiency based on increasing production alone has caused the occurrence of environmental disasters that are the impact of the exploitation of natural resources resulting in the scarcity of resources. This paper describes the optimization of land area, revenue, cost (production inputs), income and use of production input based on economic and ecological aspects. In order to sustainability farming by integrating environmental and economic consideration can be made through farmers’ decision making with the goal of optimizing revenue based on cost optimization through cocoa based agroforestry model in order to cope with a resource conflict resolution.

Optimal Assignment Problem Applications of Finite Mathematics to Business and Economics. [and] Difference Equations with Applications. Applications of Difference Equations to Economics and Social Sciences. [and] Selected Applications of Mathematics to Finance and Investment. Applications of Elementary Algebra to Finance. [and] Force of Interest. Applications of Calculus to Finance. UMAP Units 317, 322, 381, 382.

ERIC Educational Resources Information Center

Gale, David; And Others

Four units make up the contents of this document. The first examines applications of finite mathematics to business and economies. The user is expected to learn the method of optimization in optimal assignment problems. The second module presents applications of difference equations to economics and social sciences, and shows how to: 1) interpret…

Pricing strategy for aesthetic surgery: economic analysis of a resident clinic's change in fees.

PubMed

Krieger, L M; Shaw, W W

1999-02-01

The laws of microeconomics explain how prices affect consumer purchasing decisions and thus overall revenues and profits. These principles can easily be applied to the behavior aesthetic plastic surgery patients. The UCLA Division of Plastic Surgery resident aesthetics clinic recently offered a radical price change for its services. The effects of this change on demand for services and revenue were tracked. Economic analysis was applied to see if this price change resulted in the maximization of total revenues, or if additional price changes could further optimize them. Economic analysis of pricing involves several steps. The first step is to assess demand. The number of procedures performed by a given practice at different price levels can be plotted to create a demand curve. From this curve, price sensitivities of consumers can be calculated (price elasticity of demand). This information can then be used to determine the pricing level that creates demand for the exact number of procedures that yield optimal revenues. In economic parlance, revenues are maximized by pricing services such that elasticity is equal to 1 (the point of unit elasticity). At the UCLA resident clinic, average total fees per procedure were reduced by 40 percent. This resulted in a 250-percent increase in procedures performed for representative 4-month periods before and after the price change. Net revenues increased by 52 percent. Economic analysis showed that the price elasticity of demand before the price change was 6.2. After the price change it was 1. We conclude that the magnitude of the price change resulted in a fee schedule that yielded the highest possible revenues from the resident clinic. These results show that changes in price do affect total revenue and that the nature of these effects can be understood, predicted, and maximized using the tools of microeconomics.

Concepts for 18/30 GHz satellite communication system study. Executive summary

NASA Technical Reports Server (NTRS)

Baker, M.; Davies, R.; Cuccia, L.; Mitchell, C.

1979-01-01

An examination of a multiplicity of interconnected parameters ranging from specific technology details to total system economic costs for satellite communication systems at the 18/30 GHz transmission bands are presented. It was determined that K sub A band systems can incur a small communications outage during very heavy rainfall periods and that reducing the outage to zero would lead to prohibitive system costs. On the other hand, the economics of scale, ie, one spacecraft accommodating 2.5 GHz of bandwidth coupled with multiple beam frequency reuse, leads to very low costs for those users who can tolerate the 5 to 50 hours per year of downtime. A multiple frequency band satellite network can provide the ultimate optimized match to the consumer performance/economics demands.

The regrets of procrastination in climate policy

NASA Astrophysics Data System (ADS)

Keller, Klaus; Robinson, Alexander; Bradford, David F.; Oppenheimer, Michael

2007-04-01

Anthropogenic carbon dioxide (CO2) emissions are projected to impose economic costs due to the associated climate change impacts. Climate change impacts can be reduced by abating CO2 emissions. What would be an economically optimal investment in abating CO2 emissions? Economic models typically suggest that reducing CO2 emissions by roughly ten to twenty per cent relative to business-as-usual would be an economically optimal strategy. The currently implemented CO2 abatement of a few per cent falls short of this benchmark. Hence, the global community may be procrastinating in implementing an economically optimal strategy. Here we use a simple economic model to estimate the regrets of this procrastination—the economic costs due to the suboptimal strategy choice. The regrets of procrastination can range from billions to trillions of US dollars. The regrets increase with increasing procrastination period and with decreasing limits on global mean temperature increase. Extended procrastination may close the window of opportunity to avoid crossing temperature limits interpreted by some as 'dangerous anthropogenic interference with the climate system' in the sense of Article 2 of the United Nations Framework Convention on Global Climate Change.

Hybrid Geothermal Heat Pumps for Cooling Telecommunications Data Centers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beckers, Koenraad J; Zurmuhl, David P.; Lukawski, Maciej Z.

The technical and economic performance of geothermal heat pump (GHP) systems supplying year-round cooling to representative small data centers with cooling loads less than 500 kWth were analyzed and compared to air-source heat pumps (ASHPs). A numerical model was developed in TRNSYS software to simulate the operation of air-source and geothermal heat pumps with and without supplementary air cooled heat exchangers - dry coolers (DCs). The model was validated using data measured at an experimental geothermal system installed in Ithaca, NY, USA. The coefficient of performance (COP) and cooling capacity of the GHPs were calculated over a 20-year lifetime andmore » compared to the performance of ASHPs. The total cost of ownership (TCO) of each of the cooling systems was calculated to assess its economic performance. Both the length of the geothermal borehole heat exchangers (BHEs) and the dry cooler temperature set point were optimized to minimize the TCO of the geothermal systems. Lastly, a preliminary analysis of the performance of geothermal heat pumps for cooling dominated systems was performed for other locations including Dallas, TX, Sacramento, CA, and Minneapolis, MN.« less

Planning of distributed generation in distribution network based on improved particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Li, Jinze; Qu, Zhi; He, Xiaoyang; Jin, Xiaoming; Li, Tie; Wang, Mingkai; Han, Qiu; Gao, Ziji; Jiang, Feng

2018-02-01

Large-scale access of distributed power can improve the current environmental pressure, at the same time, increasing the complexity and uncertainty of overall distribution system. Rational planning of distributed power can effectively improve the system voltage level. To this point, the specific impact on distribution network power quality caused by the access of typical distributed power was analyzed and from the point of improving the learning factor and the inertia weight, an improved particle swarm optimization algorithm (IPSO) was proposed which could solve distributed generation planning for distribution network to improve the local and global search performance of the algorithm. Results show that the proposed method can well reduce the system network loss and improve the economic performance of system operation with distributed generation.

Robust optimization based energy dispatch in smart grids considering demand uncertainty

NASA Astrophysics Data System (ADS)

Nassourou, M.; Puig, V.; Blesa, J.

2017-01-01

In this study we discuss the application of robust optimization to the problem of economic energy dispatch in smart grids. Robust optimization based MPC strategies for tackling uncertain load demands are developed. Unexpected additive disturbances are modelled by defining an affine dependence between the control inputs and the uncertain load demands. The developed strategies were applied to a hybrid power system connected to an electrical power grid. Furthermore, to demonstrate the superiority of the standard Economic MPC over the MPC tracking, a comparison (e.g average daily cost) between the standard MPC tracking, the standard Economic MPC, and the integration of both in one-layer and two-layer approaches was carried out. The goal of this research is to design a controller based on Economic MPC strategies, that tackles uncertainties, in order to minimise economic costs and guarantee service reliability of the system.

Operations Optimization of Nuclear Hybrid Energy Systems

DOE PAGES

Chen, Jun; Garcia, Humberto E.; Kim, Jong Suk; ...

2016-08-01

We proposed a plan for nuclear hybrid energy systems (NHES) as an effective element to incorporate high penetration of clean energy. Our paper focuses on the operations optimization of two specific NHES configurations to address the variability raised from various markets and renewable generation. Both analytical and numerical approaches are used to obtain the optimization solutions. Furthermore, key economic figures of merit are evaluated under optimized and constant operations to demonstrate the benefit of the optimization, which also suggests the economic viability of considered NHES under proposed operations optimizer. Furthermore, sensitivity analysis on commodity price is conducted for better understandingmore » of considered NHES.« less

Operations Optimization of Nuclear Hybrid Energy Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Jun; Garcia, Humberto E.; Kim, Jong Suk

We proposed a plan for nuclear hybrid energy systems (NHES) as an effective element to incorporate high penetration of clean energy. Our paper focuses on the operations optimization of two specific NHES configurations to address the variability raised from various markets and renewable generation. Both analytical and numerical approaches are used to obtain the optimization solutions. Furthermore, key economic figures of merit are evaluated under optimized and constant operations to demonstrate the benefit of the optimization, which also suggests the economic viability of considered NHES under proposed operations optimizer. Furthermore, sensitivity analysis on commodity price is conducted for better understandingmore » of considered NHES.« less

Optimization of a low-cost defined medium for alcoholic fermentation--a case study for potential application in bioethanol production from industrial wastewaters.

PubMed

Comelli, Raúl N; Seluy, Lisandro G; Isla, Miguel A

2016-01-25

In bioethanol production processes, the media composition has an impact on product concentration, yields and the overall process economics. The main purpose of this research was to develop a low-cost mineral-based supplement for successful alcoholic fermentation in an attempt to provide an economically feasible alternative to produce bioethanol from novel sources, for example, sugary industrial wastewaters. Statistical experimental designs were used to select essential nutrients for yeast fermentation, and its optimal concentrations were estimated by Response Surface Methodology. Fermentations were performed on synthetic media inoculated with 2.0 g L(-1) of yeast, and the evolution of biomass, sugar, ethanol, CO2 and glycerol were monitored over time. A mix of salts [10.6 g L(-1) (NH4)2HPO4; 6.4 g L(-1) MgSO4·7H2O and 7.5 mg L(-1) ZnSO4·7H2O] was found to be optimal. It led to the complete fermentation of the sugars in less than 12h with an average ethanol yield of 0.42 g ethanol/g sugar. A general C-balance indicated that no carbonaceous compounds different from biomass, ethanol, CO2 or glycerol were produced in significant amounts in the fermentation process. Similar results were obtained when soft drink wastewaters were tested to evaluate the potential industrial application of this supplement. The ethanol yields were very close to those obtained when yeast extract was used as the supplement, but the optimized mineral-based medium is six times cheaper, which favorably impacts the process economics and makes this supplement more attractive from an industrial viewpoint. Copyright © 2015 Elsevier B.V. All rights reserved.

Optimal groundwater security management policies by control of inexact health risks under dual uncertainty in slope factors.

PubMed

Lu, Hongwei; Li, Jing; Ren, Lixia; Chen, Yizhong

2018-05-01

Groundwater remediation is a complicated system with time-consuming and costly challenges, which should be carefully controlled by appropriate groundwater management. This study develops an integrated optimization method for groundwater remediation management regarding cost, contamination distribution and health risk under multiple uncertainties. The integration of health risk into groundwater remediation optimization management is capable of not only adequately considering the influence of health risk on optimal remediation strategies, but also simultaneously completing remediation optimization design and risk assessment. A fuzzy chance-constrained programming approach is presented to handle multiple uncertain properties in the process of health risk assessment. The capabilities and effectiveness of the developed method are illustrated through an application of a naphthalene contaminated case in Anhui, China. Results indicate that (a) the pump-and-treat remediation system leads to a low naphthalene contamination but high remediation cost for a short-time remediation, and natural attenuation significantly affects naphthalene removal from groundwater for a long-time remediation; (b) the weighting coefficients have significant influences on the remediation cost and the performances both for naphthalene concentrations and health risks; (c) an increased level of slope factor (sf) for naphthalene corresponds to more optimal strategies characterized by higher environmental benefits and lower economic sacrifice. The developed method could be simultaneously beneficial for public health and environmental protection. Decision makers could obtain the most appropriate remediation strategies according to their specific requirements with high flexibility of economic, environmental, and risk concerns. Copyright © 2018 Elsevier Ltd. All rights reserved.

Economic thermoregulatory response explains mismatch between thermal physiology and behaviour in newts.

PubMed

Gvoždík, Lumír; Kristín, Peter

2017-03-15

Temperature is an important factor determining distribution and abundance of organisms. Predicting the impact of warming climate on ectotherm populations requires information about species' thermal requirements, i.e. their so-called 'thermal niche'. The characterization of thermal niche remains a complicated task. We compared the applicability of two indirect approaches, based on reaction norm (aerobic scope curve) and optimality (preferred body temperature) concepts, for indirect estimation of thermal niche while using newts, Ichthyosaura alpestris , as a study system. If the two approaches are linked, then digesting newts should keep their body temperatures close to values maximizing aerobic scope for digestion. After feeding, newts maintained their body temperatures within a narrower range than did hungry individuals. The range of preferred body temperatures was well below the temperature maximizing aerobic scope for digestion. Optimal temperatures for factorial aerobic scope fell within the preferred body temperature range of digesting individuals. We conclude that digesting newts prefer body temperatures that are optimal for the maximum aerobic performance but relative to the maintenance costs. What might be termed the 'economic' thermoregulatory response explains the mismatch between thermal physiology and behaviour in this system. © 2017. Published by The Company of Biologists Ltd.

Development of a CSP plant energy yield calculation tool applying predictive models to analyze plant performance sensitivities

NASA Astrophysics Data System (ADS)

Haack, Lukas; Peniche, Ricardo; Sommer, Lutz; Kather, Alfons

2017-06-01

At early project stages, the main CSP plant design parameters such as turbine capacity, solar field size, and thermal storage capacity are varied during the techno-economic optimization to determine most suitable plant configurations. In general, a typical meteorological year with at least hourly time resolution is used to analyze each plant configuration. Different software tools are available to simulate the annual energy yield. Software tools offering a thermodynamic modeling approach of the power block and the CSP thermal cycle, such as EBSILONProfessional®, allow a flexible definition of plant topologies. In EBSILON, the thermodynamic equilibrium for each time step is calculated iteratively (quasi steady state), which requires approximately 45 minutes to process one year with hourly time resolution. For better presentation of gradients, 10 min time resolution is recommended, which increases processing time by a factor of 5. Therefore, analyzing a large number of plant sensitivities, as required during the techno-economic optimization procedure, the detailed thermodynamic simulation approach becomes impracticable. Suntrace has developed an in-house CSP-Simulation tool (CSPsim), based on EBSILON and applying predictive models, to approximate the CSP plant performance for central receiver and parabolic trough technology. CSPsim significantly increases the speed of energy yield calculations by factor ≥ 35 and has automated the simulation run of all predefined design configurations in sequential order during the optimization procedure. To develop the predictive models, multiple linear regression techniques and Design of Experiment methods are applied. The annual energy yield and derived LCOE calculated by the predictive model deviates less than ±1.5 % from the thermodynamic simulation in EBSILON and effectively identifies the optimal range of main design parameters for further, more specific analysis.

Optimal GENCO bidding strategy

NASA Astrophysics Data System (ADS)

Gao, Feng

Electricity industries worldwide are undergoing a period of profound upheaval. The conventional vertically integrated mechanism is being replaced by a competitive market environment. Generation companies have incentives to apply novel technologies to lower production costs, for example: Combined Cycle units. Economic dispatch with Combined Cycle units becomes a non-convex optimization problem, which is difficult if not impossible to solve by conventional methods. Several techniques are proposed here: Mixed Integer Linear Programming, a hybrid method, as well as Evolutionary Algorithms. Evolutionary Algorithms share a common mechanism, stochastic searching per generation. The stochastic property makes evolutionary algorithms robust and adaptive enough to solve a non-convex optimization problem. This research implements GA, EP, and PS algorithms for economic dispatch with Combined Cycle units, and makes a comparison with classical Mixed Integer Linear Programming. The electricity market equilibrium model not only helps Independent System Operator/Regulator analyze market performance and market power, but also provides Market Participants the ability to build optimal bidding strategies based on Microeconomics analysis. Supply Function Equilibrium (SFE) is attractive compared to traditional models. This research identifies a proper SFE model, which can be applied to a multiple period situation. The equilibrium condition using discrete time optimal control is then developed for fuel resource constraints. Finally, the research discusses the issues of multiple equilibria and mixed strategies, which are caused by the transmission network. Additionally, an advantage of the proposed model for merchant transmission planning is discussed. A market simulator is a valuable training and evaluation tool to assist sellers, buyers, and regulators to understand market performance and make better decisions. A traditional optimization model may not be enough to consider the distributed, large-scale, and complex energy market. This research compares the performance and searching paths of different artificial life techniques such as Genetic Algorithm (GA), Evolutionary Programming (EP), and Particle Swarm (PS), and look for a proper method to emulate Generation Companies' (GENCOs) bidding strategies. After deregulation, GENCOs face risk and uncertainty associated with the fast-changing market environment. A profit-based bidding decision support system is critical for GENCOs to keep a competitive position in the new environment. Most past research do not pay special attention to the piecewise staircase characteristic of generator offer curves. This research proposes an optimal bidding strategy based on Parametric Linear Programming. The proposed algorithm is able to handle actual piecewise staircase energy offer curves. The proposed method is then extended to incorporate incomplete information based on Decision Analysis. Finally, the author develops an optimal bidding tool (GenBidding) and applies it to the RTS96 test system.

PSOLA: A Heuristic Land-Use Allocation Model Using Patch-Level Operations and Knowledge-Informed Rules.

PubMed

Liu, Yaolin; Peng, Jinjin; Jiao, Limin; Liu, Yanfang

2016-01-01

Optimizing land-use allocation is important to regional sustainable development, as it promotes the social equality of public services, increases the economic benefits of land-use activities, and reduces the ecological risk of land-use planning. Most land-use optimization models allocate land-use using cell-level operations that fragment land-use patches. These models do not cooperate well with land-use planning knowledge, leading to irrational land-use patterns. This study focuses on building a heuristic land-use allocation model (PSOLA) using particle swarm optimization. The model allocates land-use with patch-level operations to avoid fragmentation. The patch-level operations include a patch-edge operator, a patch-size operator, and a patch-compactness operator that constrain the size and shape of land-use patches. The model is also integrated with knowledge-informed rules to provide auxiliary knowledge of land-use planning during optimization. The knowledge-informed rules consist of suitability, accessibility, land use policy, and stakeholders' preference. To validate the PSOLA model, a case study was performed in Gaoqiao Town in Zhejiang Province, China. The results demonstrate that the PSOLA model outperforms a basic PSO (Particle Swarm Optimization) in the terms of the social, economic, ecological, and overall benefits by 3.60%, 7.10%, 1.53% and 4.06%, respectively, which confirms the effectiveness of our improvements. Furthermore, the model has an open architecture, enabling its extension as a generic tool to support decision making in land-use planning.

PSOLA: A Heuristic Land-Use Allocation Model Using Patch-Level Operations and Knowledge-Informed Rules

PubMed Central

Liu, Yaolin; Peng, Jinjin; Jiao, Limin; Liu, Yanfang

2016-01-01

Optimizing land-use allocation is important to regional sustainable development, as it promotes the social equality of public services, increases the economic benefits of land-use activities, and reduces the ecological risk of land-use planning. Most land-use optimization models allocate land-use using cell-level operations that fragment land-use patches. These models do not cooperate well with land-use planning knowledge, leading to irrational land-use patterns. This study focuses on building a heuristic land-use allocation model (PSOLA) using particle swarm optimization. The model allocates land-use with patch-level operations to avoid fragmentation. The patch-level operations include a patch-edge operator, a patch-size operator, and a patch-compactness operator that constrain the size and shape of land-use patches. The model is also integrated with knowledge-informed rules to provide auxiliary knowledge of land-use planning during optimization. The knowledge-informed rules consist of suitability, accessibility, land use policy, and stakeholders’ preference. To validate the PSOLA model, a case study was performed in Gaoqiao Town in Zhejiang Province, China. The results demonstrate that the PSOLA model outperforms a basic PSO (Particle Swarm Optimization) in the terms of the social, economic, ecological, and overall benefits by 3.60%, 7.10%, 1.53% and 4.06%, respectively, which confirms the effectiveness of our improvements. Furthermore, the model has an open architecture, enabling its extension as a generic tool to support decision making in land-use planning. PMID:27322619

A systematic review of economic evaluations of treatments for patients with epilepsy.

PubMed

Wijnen, Ben F M; van Mastrigt, Ghislaine A P G; Evers, Silvia M A A; Gershuni, Olga; Lambrechts, Danielle A J E; Majoie, Marian H J M; Postulart, Debby; Aldenkamp, Bert A P; de Kinderen, Reina J A

2017-05-01

The increasing number of treatment options and the high costs associated with epilepsy have fostered the development of economic evaluations in epilepsy. It is important to examine the availability and quality of these economic evaluations and to identify potential research gaps. As well as looking at both pharmacologic (antiepileptic drugs [AEDs]) and nonpharmacologic (e.g., epilepsy surgery, ketogenic diet, vagus nerve stimulation) therapies, this review examines the methodologic quality of the full economic evaluations included. Literature search was performed in MEDLINE, EMBASE, NHS Economic Evaluation Database (NHS EED), Econlit, Web of Science, and CEA Registry. In addition, Cochrane Reviews, Cochrane DARE and Cochrane Health Technology Assessment Databases were used. To identify relevant studies, predefined clinical search strategies were combined with a search filter designed to identify health economic studies. Specific search strategies were devised for the following topics: (1) AEDs, (2) patients with cognitive deficits, (3) elderly patients, (4) epilepsy surgery, (5) ketogenic diet, (6) vagus nerve stimulation, and (7) treatment of (non)convulsive status epilepticus. A total of 40 publications were included in this review, 29 (73%) of which were articles about pharmacologic interventions. Mean quality score of all articles on the Consensus Health Economic Criteria (CHEC)-extended was 81.8%, the lowest quality score being 21.05%, whereas five studies had a score of 100%. Looking at the Consolidated Health Economic Evaluation Reporting Standards (CHEERS), the average quality score was 77.0%, the lowest being 22.7%, and four studies rated as 100%. There was a substantial difference in methodology in all included articles, which hampered the attempt to combine information meaningfully. Overall, the methodologic quality was acceptable; however, some studies performed significantly worse than others. The heterogeneity between the studies stresses the need to define a reference case (e.g., how should an economic evaluation within epilepsy be performed) and to derive consensus on what constitutes "standard optimal care." Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Inspection error and its adverse effects - A model with implications for practitioners

NASA Technical Reports Server (NTRS)

Collins, R. D., Jr.; Case, K. E.; Bennett, G. K.

1978-01-01

Inspection error has clearly been shown to have adverse effects upon the results desired from a quality assurance sampling plan. These effects upon performance measures have been well documented from a statistical point of view. However, little work has been presented to convince the QC manager of the unfavorable cost consequences resulting from inspection error. This paper develops a very general, yet easily used, mathematical cost model. The basic format of the well-known Guthrie-Johns model is used. However, it is modified as required to assess the effects of attributes sampling errors of the first and second kind. The economic results, under different yet realistic conditions, will no doubt be of interest to QC practitioners who face similar problems daily. Sampling inspection plans are optimized to minimize economic losses due to inspection error. Unfortunately, any error at all results in some economic loss which cannot be compensated for by sampling plan design; however, improvements over plans which neglect the presence of inspection error are possible. Implications for human performance betterment programs are apparent, as are trade-offs between sampling plan modification and inspection and training improvements economics.

Minimizing Uncertainties Impact in Decision Making with an Applicability Study for Economic Power Dispatch

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Hong; Wang, Shaobu; Fan, Rui

This report summaries the work performed under the LDRD project on the preliminary study on knowledge automation, where specific focus has been made on the investigation of the impact of uncertainties of human decision making onto the optimization of the process operation. At first the statistics on signals from the Brain-Computing Interface (BCI) is analyzed so as to obtain the uncertainties characterization of human operators during the decision making phase using the electroencephalogram (EEG) signals. This is then followed by the discussions of an architecture that reveals the equivalence between optimization and closed loop feedback control design, where it hasmore » been shown that all the optimization problems can be transferred into the control design problem for closed loop systems. This has led to a “closed loop” framework, where the structure of the decision making is shown to be subjected to both process disturbances and controller’s uncertainties. The latter can well represent the uncertainties or randomness occurred during human decision making phase. As a result, a stochastic optimization problem has been formulated and a novel solution has been proposed using probability density function (PDF) shaping for both the cost function and the constraints using stochastic distribution control concept. A sufficient condition has been derived that guarantees the convergence of the optimal solution and discussions have been made for both the total probabilistic solution and chanced constrained optimization which have been well-studied in optimal power flows (OPF) area. A simple case study has been carried out for the economic dispatch of powers for a grid system when there are distributed energy resources (DERs) in the system, and encouraging results have been obtained showing that a significant savings on the generation cost can be expected.« less

Optimal deployment of thermal energy storage under diverse economic and climate conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeForest, Nicholas; Mendes, Gonçalo; Stadler, Michael

2014-04-01

This paper presents an investigation of the economic benefit of thermal energy storage (TES) for cooling, across a range of economic and climate conditions. Chilled water TES systems are simulated for a large office building in four distinct locations, Miami in the U.S.; Lisbon, Portugal; Shanghai, China; and Mumbai, India. Optimal system size and operating schedules are determined using the optimization model DER-CAM, such that total cost, including electricity and amortized capital costs are minimized. The economic impacts of each optimized TES system is then compared to systems sized using a simple heuristic method, which bases system size as fractionmore » (50percent and 100percent) of total on-peak summer cooling loads. Results indicate that TES systems of all sizes can be effective in reducing annual electricity costs (5percent-15percent) and peak electricity consumption (13percent-33percent). The investigation also indentifies a number of criteria which drive TES investment, including low capital costs, electricity tariffs with high power demand charges and prolonged cooling seasons. In locations where these drivers clearly exist, the heuristically sized systems capture much of the value of optimally sized systems; between 60percent and 100percent in terms of net present value. However, in instances where these drivers are less pronounced, the heuristic tends to oversize systems, and optimization becomes crucial to ensure economically beneficial deployment of TES, increasing the net present value of heuristically sized systems by as much as 10 times in some instances.« less

Decolorization of Acid Orange 7 by an electric field-assisted modified orifice plate hydrodynamic cavitation system: Optimization of operational parameters.

PubMed

Jung, Kyung-Won; Park, Dae-Seon; Hwang, Min-Jin; Ahn, Kyu-Hong

2015-09-01

In this study, the decolorization of Acid Orange 7 (AO-7) with intensified performance was obtained using hydrodynamic cavitation (HC) combined with an electric field (graphite electrodes). As a preliminary step, various HC systems were compared in terms of decolorization, and, among them, the electric field-assisted modified orifice plate HC (EFM-HC) system exhibited perfect decolorization performance within 40 min of reaction time. Interestingly, when H2O2 was injected into the EFM-HC system as an additional oxidant, the reactor performance gradually decreased as the dosing ratio increased; thus, the remaining experiments were performed without H2O2. Subsequently, an optimization process was conducted using response surface methodology with a Box-Behnken design. The inlet pressure, initial pH, applied voltage, and reaction time were chosen as operational key factors, while decolorization was selected as the response variable. The overall performance revealed that the selected parameters were either slightly interdependent, or had significant interactive effects on the decolorization. In the verification test, complete decolorization was observed under statistically optimized conditions. This study suggests that EFM-HC is a useful method for pretreatment of dye wastewater with positive economic and commercial benefits. Copyright © 2015 Elsevier B.V. All rights reserved.

Improving energy sustainability for public buildings in Italian mountain communities.

PubMed

Mutani, Guglielmina; Cornaglia, Mauro; Berto, Massimo

2018-05-01

The objective of this work is to analyze and then optimize thermal energy consumptions of public buildings located within the mountain community of Lanzo, Ceronda and Casternone Valleys. Some measures have been proposed to reduce energy consumption and consequently the economic cost for energy production, as well as the harmful GHG emissions in the atmosphere. Initially, a study of the mountain territory has been carried out, because of its vast extension and climatic differences. Defined the communities and the buildings under investigation, energy dependant data were collected for the analysis of energy consumption monitoring: consumption data of three heating seasons, geometric buildings characteristics, type of opaque and transparent envelope, heating systems information with boiler performance and climatic data. Afterward, five buildings with critical energy performances were selected; for each of these buildings, different retrofit interventions have been hypothesized to reduce the energy consumption, with thermal insulation of vertical or horizontal structures, new windows or boiler substitution. The cost-optimal technique was used to choose the interventions that offered higher energy performance at lower costs; then a retrofit scenario has been planned with a specific financial investment. Finally, results showed possible future developments and scenarios related to buildings energy efficiency with regard to the topic of biomass exploitation and its local availability in this area. In this context, the biomass energy resource could to create a virtuous environmental, economic and social process, favouring also local development.

Use of Empty Fruit Bunches from the oil palm for bioethanol production: a thorough comparison between dilute acid and dilute alkali pretreatment.

PubMed

Chiesa, S; Gnansounou, E

2014-05-01

In the present work, two pretreatment techniques using either dilute acid (H2SO4) or dilute alkali (NaOH) have been compared for producing bioethanol from Empty Fruit Bunches (EFBs) from oil palm tree, a relevant feedstock for tropical countries. Treatments' performances under different conditions have been assessed and statistically optimized with respect to the response upon standardized enzymatic saccharification. The dilute acid treatment performed at optimal conditions (161.5°C, 9.44 min and 1.51% acid loading) gave 85.5% glucose yield, comparable to those of other commonly investigated feedstocks. Besides, the possibility of using fibers instead of finely ground biomass may be of economic interest. Oppositely, treatment with dilute alkali has shown lower performances under the conditions explored, most likely given the relatively significant lignin content, suggesting that the use of stronger alkali regime (with the associated drawbacks) is unavoidable to improve the performance of this treatment. Copyright © 2014 Elsevier Ltd. All rights reserved.

Promoting Affordability in Defense Acquisitions: A Multi-Period Portfolio Approach

DTIC Science & Technology

2014-04-30

has evolved out of many areas of research, ranging from economics to modern control theory (Powell, 2011). The general form of a dynamic programming...states 5 School of Aeronautics & Astronautics A Portfolio Approach: Background • Balance expected profit (performance) against risk ( variance ) in...investments (Markowitz 1952) • Efficiency frontier of optimal portfolios given investor risk averseness • Extends to multi-period case with various

Optimizing Orbital Debris Monitoring with Optical Telescopes

DTIC Science & Technology

2010-09-01

poses an increasing risk to manned space missions and operational satellites ; however, the majority of debris large enough to cause catastrophic...cameras hosted on GEO- based satellites for monitoring GEO. Performance analysis indicates significant potential contributions of these systems as a...concerns over the long term-viability of the space environment and the resulting economic impacts. The 2007 China anti- satellite test and the 2009

Blanket design and optimization demonstrations of the first wall/blanket/shield design and optimization system (BSDOS).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gohar, Y.; Nuclear Engineering Division

2005-05-01

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 definemore » the optimum blanket design and satisfying all the design constraints for the adopted figure of merit and the blanket design criteria. The blanket design capabilities 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 research and design tool for performing blanket design analyses. This paper describes some of the BSDOS capabilities and demonstrates its use. In addition, the use of the optimization capability of the BSDOS can result in a significant blanket performance enhancement and cost saving for the reactor design under consideration. In this paper, 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 capabilities.« less

Blanket Design and Optimization Demonstrations of the First Wall/Blanket/Shield Design and Optimization System (BSDOS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gohar, Yousry

2005-05-15

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 definemore » the optimum blanket design and satisfying all the design constraints for the adopted figure of merit and the blanket design criteria. The blanket design capabilities 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 research and design tool for performing blanket design analyses. This paper describes some of the BSDOS capabilities and demonstrates its use. In addition, the use of the optimization capability of the BSDOS can result in a significant blanket performance enhancement and cost saving for the reactor design under consideration. In this paper, 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 capabilities.« less

Operations Optimization of Hybrid Energy Systems under Variable Markets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Jun; Garcia, Humberto E.

Hybrid energy systems (HES) have been proposed to be an important element to enable increasing penetration of clean energy. This paper investigates the operations flexibility of HES, and develops a methodology for operations optimization to maximize its economic value based on predicted renewable generation and market information. The proposed operations optimizer allows systematic control of energy conversion for maximal economic value, and is illustrated by numerical results.

Conceptual design of reduced energy transports

NASA Technical Reports Server (NTRS)

Ardema, M. D.; Harper, M.; Smith, C. L.; Waters, M. H.; Williams, L. J.

1975-01-01

This paper reports the results of a conceptual design study of new, near-term fuel-conservative aircraft. A parametric study was made to determine the effects of cruise Mach number and fuel cost on the 'optimum' configuration characteristics and on economic performance. Supercritical wing technology and advanced engine cycles were assumed. For each design, the wing geometry was optimized to give maximum return on investment at a particular fuel cost. Based on the results of the parametric study, a reduced energy configuration was selected. Compared with existing transport designs, the reduced energy design has a higher aspect ratio wing with lower sweep, and cruises at a lower Mach number. It yields about 30% more seat-miles/gal than current wide-body aircraft. At the higher fuel costs anticipated in the future, the reduced energy design has about the same economic performance as existing designs.

A generalized disjunctive programming framework for the optimal synthesis and analysis of processes for ethanol production from corn stover.

PubMed

Scott, Felipe; Aroca, Germán; Caballero, José Antonio; Conejeros, Raúl

2017-07-01

The aim of this study is to analyze the techno-economic performance of process configurations for ethanol production involving solid-liquid separators and reactors in the saccharification and fermentation stage, a family of process configurations where few alternatives have been proposed. Since including these process alternatives creates a large number of possible process configurations, a framework for process synthesis and optimization is proposed. This approach is supported on kinetic models fed with experimental data and a plant-wide techno-economic model. Among 150 process configurations, 40 show an improved MESP compared to a well-documented base case (BC), almost all include solid separators and some show energy retrieved in products 32% higher compared to the BC. Moreover, 16 of them also show a lower capital investment per unit of ethanol produced per year. Several of the process configurations found in this work have not been reported in the literature. Copyright © 2017 Elsevier Ltd. All rights reserved.

Lead-lag cross-sectional structure and detection of correlated anticorrelated regime shifts: Application to the volatilities of inflation and economic growth rates

NASA Astrophysics Data System (ADS)

Zhou, Wei-Xing; Sornette, Didier

2007-07-01

We have recently introduced the “thermal optimal path” (TOP) method to investigate the real-time lead-lag structure between two time series. The TOP method consists in searching for a robust noise-averaged optimal path of the distance matrix along which the two time series have the greatest similarity. Here, we generalize the TOP method by introducing a more general definition of distance which takes into account possible regime shifts between positive and negative correlations. This generalization to track possible changes of correlation signs is able to identify possible transitions from one convention (or consensus) to another. Numerical simulations on synthetic time series verify that the new TOP method performs as expected even in the presence of substantial noise. We then apply it to investigate changes of convention in the dependence structure between the historical volatilities of the USA inflation rate and economic growth rate. Several measures show that the new TOP method significantly outperforms standard cross-correlation methods.

Economic optimization software applied to JFK airport heating and cooling plant

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gay, R.R.; McCoy, L.

This paper describes the on-line economic optimization routine developed by Enter Software, Inc. for application at the heating and cooling plant for the JFK International Airport near New York City. The objective of the economic optimization is to find the optimum plant configuration (which gas turbines to run, power levels of each gas turbine, duct firing levels, which auxiliary water heaters to run, which electric chillers to run, and which absorption chillers to run) which produces maximum net income at the plant as plant loads and the prices vary. The routines also include a planner which runs a series ofmore » optimizations over multiple plant configurations to simulate the varying plant operating conditions for the purpose of predicting the overall plant results over a period of time.« less

Multi-objective optimization of an arch dam shape under static loads using an evolutionary game method

NASA Astrophysics Data System (ADS)

Meng, Rui; Cheong, Kang Hao; Bao, Wei; Wong, Kelvin Kian Loong; Wang, Lu; Xie, Neng-gang

2018-06-01

This article attempts to evaluate the safety and economic performance of an arch dam under the action of static loads. The geometric description of a crown cantilever section and the horizontal arch ring is presented. A three-objective optimization model of arch dam shape is established based on the arch dam volume, maximum principal tensile stress and total strain energy. The evolutionary game method is then applied to obtain the optimal solution. In the evolutionary game technique, a novel and more efficient exploration method of the game players' strategy space, named the 'sorting partition method under the threshold limit', is presented, with the game profit functions constructed according to both competitive and cooperative behaviour. By way of example, three optimization goals have all shown improvements over the initial solutions. In particular, the evolutionary game method has potentially faster convergence. This demonstrates the preliminary proof of principle of the evolutionary game method.

High speed civil transport aerodynamic optimization

NASA Technical Reports Server (NTRS)

Ryan, James S.

1994-01-01

This is a report of work in support of the Computational Aerosciences (CAS) element of the Federal HPCC program. Specifically, CFD and aerodynamic optimization are being performed on parallel computers. The long-range goal of this work is to facilitate teraflops-rate multidisciplinary optimization of aerospace vehicles. This year's work is targeted for application to the High Speed Civil Transport (HSCT), one of four CAS grand challenges identified in the HPCC FY 1995 Blue Book. This vehicle is to be a passenger aircraft, with the promise of cutting overseas flight time by more than half. To meet fuel economy, operational costs, environmental impact, noise production, and range requirements, improved design tools are required, and these tools must eventually integrate optimization, external aerodynamics, propulsion, structures, heat transfer, controls, and perhaps other disciplines. The fundamental goal of this project is to contribute to improved design tools for U.S. industry, and thus to the nation's economic competitiveness.

Optimization Research on Ampacity of Underground High Voltage Cable Based on Interior Point Method

NASA Astrophysics Data System (ADS)

Huang, Feng; Li, Jing

2017-12-01

The conservative operation method which takes unified current-carrying capacity as maximum load current can’t make full use of the overall power transmission capacity of the cable. It’s not the optimal operation state for the cable cluster. In order to improve the transmission capacity of underground cables in cluster, this paper regards the maximum overall load current as the objective function and the temperature of any cables lower than maximum permissible temperature as constraint condition. The interior point method which is very effective for nonlinear problem is put forward to solve the extreme value of the problem and determine the optimal operating current of each loop. The results show that the optimal solutions obtained with the purposed method is able to increase the total load current about 5%. It greatly improves the economic performance of the cable cluster.

Analyse et design aerodynamique haute-fidelite de l'integration moteur sur un avion BWB

NASA Astrophysics Data System (ADS)

Mirzaei Amirabad, Mojtaba

BWB (Blended Wing Body) is an innovative type of aircraft based on the flying wing concept. In this configuration, the wing and the fuselage are blended together smoothly. BWB offers economical and environmental advantages by reducing fuel consumption through improving aerodynamic performance. In this project, the goal is to improve the aerodynamic performance by optimizing the main body of BWB that comes from conceptual design. The high fidelity methods applied in this project have been less frequently addressed in the literature. This research develops an automatic optimization procedure in order to reduce the drag force on the main body. The optimization is carried out in two main stages: before and after engine installation. Our objective is to minimize the drag by taking into account several constraints in high fidelity optimization. The commercial software, Isight is chosen as an optimizer in which MATLAB software is called to start the optimization process. Geometry is generated using ANSYS-DesignModeler, unstructured mesh is created by ANSYS-Mesh and CFD calculations are done with the help of ANSYS-Fluent. All of these software are coupled together in ANSYS-Workbench environment which is called by MATLAB. The high fidelity methods are used during optimization by solving Navier-Stokes equations. For verifying the results, a finer structured mesh is created by ICEM software to be used in each stage of optimization. The first stage includes a 3D optimization on the surface of the main body, before adding the engine. The optimized case is then used as an input for the second stage in which the nacelle is added. It could be concluded that this study leads us to obtain appropriate reduction in drag coefficient for BWB without nacelle. In the second stage (adding the nacelle) a drag minimization is also achieved by performing a local optimization. Furthermore, the flow separation, created in the main body-nacelle zone, is reduced.

Using economic instruments to develop effective management of invasive species: insights from a bioeconomic model.

PubMed

McDermott, Shana M; Irwin, Rebecca E; Taylor, Brad W

2013-07-01

Economic growth is recognized as an important factor associated with species invasions. Consequently, there is increasing need to develop solutions that combine economics and ecology to inform invasive species management. We developed a model combining economic, ecological, and sociological factors to assess the degree to which economic policies can be used to control invasive plants. Because invasive plants often spread across numerous properties, we explored whether property owners should manage invaders cooperatively as a group by incorporating the negative effects of invader spread in management decisions (collective management) or independently, whereby the negative effects of invasive plant spread are ignored (independent management). Our modeling approach used a dynamic optimization framework, and we applied the model to invader spread using Linaria vulgaris. Model simulations allowed us to determine the optimal management strategy based on net benefits for a range of invader densities. We found that optimal management strategies varied as a function of initial plant densities. At low densities, net benefits were high for both collective and independent management to eradicate the invader, suggesting the importance of early detection and eradication. At moderate densities, collective management led to faster and more frequent invader eradication compared to independent management. When we used a financial penalty to ensure that independent properties were managed collectively, we found that the penalty would be most feasible when levied on a property's perimeter boundary to control spread among properties. At the highest densities, the optimal management strategy was "do nothing" because the economic costs of removal were too high relative to the benefits of removal. Spatial variation in L. vulgaris densities resulted in different optimal management strategies for neighboring properties, making a formal economic policy to encourage invasive species removal critical. To accomplish the management and enforcement of these economic policies, we discuss modification of existing agencies and infrastructure. Finally, a sensitivity analysis revealed that lowering the economic cost of invader removal would strongly increase the probability of invader eradication. Taken together, our results provide quantitative insight into management decisions and economic policy instruments that can encourage invasive species removal across a social landscape.

Optimizations on supply and distribution of dissolved oxygen in constructed wetlands: A review.

PubMed

Liu, Huaqing; Hu, Zhen; Zhang, Jian; Ngo, Huu Hao; Guo, Wenshan; Liang, Shuang; Fan, Jinlin; Lu, Shaoyong; Wu, Haiming

2016-08-01

Dissolved oxygen (DO) is one of the most important factors that can influence pollutants removal in constructed wetlands (CWs). However, problems of insufficient oxygen supply and inappropriate oxygen distribution commonly exist in traditional CWs. Detailed analyses of DO supply and distribution characteristics in different types of CWs were introduced. It can be concluded that atmospheric reaeration (AR) served as the promising point on oxygen intensification. The paper summarized possible optimizations of DO in CWs to improve its decontamination performance. Process (tidal flow, drop aeration, artificial aeration, hybrid systems) and parameter (plant, substrate and operating) optimizations are particularly discussed in detail. Since economic and technical defects are still being cited in current studies, future prospects of oxygen research in CWs terminate this review. Copyright © 2016. Published by Elsevier Ltd.

Method of Optimizing the Construction of Machining, Assembly and Control Devices

NASA Astrophysics Data System (ADS)

Iordache, D. M.; Costea, A.; Niţu, E. L.; Rizea, A. D.; Babă, A.

2017-10-01

Industry dynamics, driven by economic and social requirements, must generate more interest in technological optimization, capable of ensuring a steady development of advanced technical means to equip machining processes. For these reasons, the development of tools, devices, work equipment and control, as well as the modernization of machine tools, is the certain solution to modernize production systems that require considerable time and effort. This type of approach is also related to our theoretical, experimental and industrial applications of recent years, presented in this paper, which have as main objectives the elaboration and use of mathematical models, new calculation methods, optimization algorithms, new processing and control methods, as well as some structures for the construction and configuration of technological equipment with a high level of performance and substantially reduced costs..

Performance evaluation of a health insurance in Nigeria using optimal resource use: health care providers perspectives

PubMed Central

2014-01-01

Background Performance measures are often neglected during the transition period of national health insurance scheme implementation in many low and middle income countries. These measurements evaluate the extent to which various aspects of the schemes meet their key objectives. This study assesses the implementation of a health insurance scheme using optimal resource use domains and examines possible factors that influence each domain, according to providers’ perspectives. Methods A retrospective, cross-sectional survey was done between August and December 2010 in Kaduna state, and 466 health care provider personnel were interviewed. Optimal-resource-use was defined in four domains: provider payment mechanism (capitation and fee-for-service payment methods), benefit package, administrative efficiency, and active monitoring mechanism. Logistic regression analysis was used to identify provider factors that may influence each domain. Results In the provider payment mechanism domain, capitation payment method (95%) performed better than fee-for-service payment method (62%). Benefit package domain performed strongly (97%), while active monitoring mechanism performed weakly (37%). In the administrative efficiency domain, both promptness of referral system (80%) and prompt arrival of funds (93%) performed well. At the individual level, providers with fewer enrolees encountered difficulties with reimbursement. Other factors significantly influenced each of the optimal-resource-use domains. Conclusions Fee-for-service payment method and claims review, in the provider payment and active monitoring mechanisms, respectively, performed weakly according to the providers’ (at individual-level) perspectives. A short-fall on the supply-side of health insurance could lead to a direct or indirect adverse effect on the demand-side of the scheme. Capitation payment per enrolees should be revised to conform to economic circumstances. Performance indicators and providers’ characteristics and experiences associated with resource use can assist policy makers to monitor and evaluate health insurance implementation. PMID:24628889

Confidence bands for measured economically optimal nitrogen rates

USDA-ARS?s Scientific Manuscript database

While numerous researchers have computed economically optimal N rate (EONR) values from measured yield – N rate data, nearly all have neglected to compute or estimate the statistical reliability of these EONR values. In this study, a simple method for computing EONR and its confidence bands is descr...

The 18 and 30 GHz fixed service communications satellite system study. [to determine the cost and performance characteristics

NASA Technical Reports Server (NTRS)

Bronstein, L. M.

1979-01-01

The use of the 18 and 30 GHz bands for fixed service satellite communications is examined. The cost and performance expected of 18 and 30 GHz hardware is assessed, selected trunking and direct to user concepts are optimized, and the cost of these systems are estimated. The effect of rain attenuation on the technical and economic viability of the system and methods circumventing the problem are discussed. Technology developments are investigated and cost estimates of these developments are presented.

Comparative analysis of economic models in selected solar energy computer programs

NASA Astrophysics Data System (ADS)

Powell, J. W.; Barnes, K. A.

1982-01-01

The economic evaluation models in five computer programs widely used for analyzing solar energy systems (F-CHART 3.0, F-CHART 4.0, SOLCOST, BLAST, and DOE-2) are compared. Differences in analysis techniques and assumptions among the programs are assessed from the point of view of consistency with the Federal requirements for life cycle costing (10 CFR Part 436), effect on predicted economic performance, and optimal system size, case of use, and general applicability to diverse systems types and building types. The FEDSOL program developed by the National Bureau of Standards specifically to meet the Federal life cycle cost requirements serves as a basis for the comparison. Results of the study are illustrated in test cases of two different types of Federally owned buildings: a single family residence and a low rise office building.

Economic repercussions of fisheries-induced evolution

PubMed Central

Eikeset, Anne Maria; Richter, Andries; Dunlop, Erin S.; Dieckmann, Ulf; Stenseth, Nils Chr.

2013-01-01

Fish stocks experiencing high fishing mortality show a tendency to mature earlier and at a smaller size, which may have a genetic component and therefore long-lasting economic and biological effects. To date, the economic effects of such ecoevolutionary dynamics have not been empirically investigated. Using 70 y of data, we develop a bioeconomic model for Northeast Arctic cod to compare the economic yield in a model in which life-history traits can vary only through phenotypic plasticity with a model in which, in addition, genetic changes can occur. We find that evolutionary changes toward faster growth and earlier maturation occur consistently even if a stock is optimally managed. However, if a stock is managed optimally, the evolutionary changes actually increase economic yield because faster growth and earlier maturation raise the stock’s productivity. The optimal fishing mortality is almost identical for the evolutionary and nonevolutionary model and substantially lower than what it has been historically. Therefore, the costs of ignoring evolution under optimal management regimes are negligible. However, if fishing mortality is as high as it has been historically, evolutionary changes may result in economic losses, but only if the fishery is selecting for medium-sized individuals. Because evolution facilitates growth, the fish are younger and still immature when they are susceptible to getting caught, which outweighs the increase in productivity due to fish spawning at an earlier age. PMID:23836660

Optimized MBR for greywater reuse systems in hotel facilities.

PubMed

Atanasova, Natasa; Dalmau, Montserrat; Comas, Joaquim; Poch, Manel; Rodriguez-Roda, Ignasi; Buttiglieri, Gianluigi

2017-05-15

Greywater is an important alternative water source, particularly in semi-arid, touristic areas, where the biggest water demand is usually in the dry period. By using this source wisely, tourist facilities can substantially reduce the pressure to scarce water resources. In densely urbanized touristic areas, where space has high value, compact solutions such as MBR based greywater reuse systems appear very appropriate. This research focuses on technical and economical evaluation of such solution by implementing a pilot MBR to a hotel with separated grey water. The pilot was operated for 6 months, with thorough characterisation of the GW performed, its operation was monitored and its energy consumption was optimized by applying a control system for the air scour. Based on the pilot operation a design and economic model was set to estimate the feasibility (CAPEX, OPEX, payback period of investment) of appropriate scales of MBR based GW systems, including separation of GW, MBR technology, clean water storage and disinfection. The model takes into account water and energy prices in Spain and a planning period of 20 years. The results demonstrated an excellent performance in terms of effluent quality, while the energy demand for air-scour was reduced by up to 35.2%, compared to the manufacturer recommendations. Economical evaluation of the entire MBR based GW reuse system shows its feasibility for sizes already at 5 m 3 /day (60 PE). The payback period of the investment for hotels like the demonstration hotel, treating 30 m 3 /day is 3 years. Copyright © 2017 Elsevier Ltd. All rights reserved.

Feasibility Study of a Satellite Solar Power Station

NASA Technical Reports Server (NTRS)

Glaser, P. E.; Maynard, O. E.; Mackovciak, J. J. R.; Ralph, E. I.

1974-01-01

A feasibility study of a satellite solar power station (SSPS) was conducted to: (1) explore how an SSPS could be flown and controlled in orbit; (2) determine the techniques needed to avoid radio frequency interference (RFI); and (3) determine the key environmental, technological, and economic issues involved. Structural and dynamic analyses of the SSPS structure were performed, and deflections and internal member loads were determined. Desirable material characteristics were assessed and technology developments identified. Flight control performance of the SSPS baseline design was evaluated and parametric sizing studies were performed. The study of RFI avoidance techniques covered (1) optimization of the microwave transmission system; (2) device design and expected RFI; and (3) SSPS RFI effects. The identification of key issues involved (1) microwave generation, transmissions, and rectification and solar energy conversion; (2) environmental-ecological impact and biological effects; and (3) economic issues, i.e., costs and benefits associated with the SSPS. The feasibility of the SSPS based on the parameters of the study was established.

Alfalfa (Medicago sativa L.)/maize (Zea mays L.) intercropping provides a feasible way to improve yield and economic incomes in farming and pastoral areas of northeast China.

PubMed

Sun, Baoru; Peng, Yi; Yang, Hongyu; Li, Zhijian; Gao, Yingzhi; Wang, Chao; Yan, Yuli; Liu, Yanmei

2014-01-01

Given the growing challenges to food and eco-environmental security as well as sustainable development of animal husbandry in the farming and pastoral areas of northeast China, it is crucial to identify advantageous intercropping modes and some constraints limiting its popularization. In order to assess the performance of various intercropping modes of maize and alfalfa, a field experiment was conducted in a completely randomized block design with five treatments: maize monoculture in even rows, maize monoculture in alternating wide and narrow rows, alfalfa monoculture, maize intercropped with one row of alfalfa in wide rows and maize intercropped with two rows of alfalfa in wide rows. Results demonstrate that maize monoculture in alternating wide and narrow rows performed best for light transmission, grain yield and output value, compared to in even rows. When intercropped, maize intercropped with one row of alfalfa in wide rows was identified as the optimal strategy and the largely complementary ecological niches of alfalfa and maize were shown to account for the intercropping advantages, optimizing resource utilization and improving yield and economic incomes. These findings suggest that alfalfa/maize intercropping has obvious advantages over monoculture and is applicable to the farming and pastoral areas of northeast China.

Alfalfa (Medicago sativa L.)/Maize (Zea mays L.) Intercropping Provides a Feasible Way to Improve Yield and Economic Incomes in Farming and Pastoral Areas of Northeast China

PubMed Central

Sun, Baoru; Peng, Yi; Yang, Hongyu; Li, Zhijian; Gao, Yingzhi; Wang, Chao; Yan, Yuli; Liu, Yanmei

2014-01-01

Given the growing challenges to food and eco-environmental security as well as sustainable development of animal husbandry in the farming and pastoral areas of northeast China, it is crucial to identify advantageous intercropping modes and some constraints limiting its popularization. In order to assess the performance of various intercropping modes of maize and alfalfa, a field experiment was conducted in a completely randomized block design with five treatments: maize monoculture in even rows, maize monoculture in alternating wide and narrow rows, alfalfa monoculture, maize intercropped with one row of alfalfa in wide rows and maize intercropped with two rows of alfalfa in wide rows. Results demonstrate that maize monoculture in alternating wide and narrow rows performed best for light transmission, grain yield and output value, compared to in even rows. When intercropped, maize intercropped with one row of alfalfa in wide rows was identified as the optimal strategy and the largely complementary ecological niches of alfalfa and maize were shown to account for the intercropping advantages, optimizing resource utilization and improving yield and economic incomes. These findings suggest that alfalfa/maize intercropping has obvious advantages over monoculture and is applicable to the farming and pastoral areas of northeast China. PMID:25329376

Computer Assisted Design, Prediction, and Execution of Economical Organic Syntheses

NASA Astrophysics Data System (ADS)

Gothard, Nosheen Akber

The synthesis of useful organic molecules via simple and cost-effective routes is a core challenge in organic chemistry. In industry or academia, organic chemists use their chemical intuition, technical expertise and published procedures to determine an optimal pathway. This approach, not only takes time and effort, but also is cost prohibitive. Many potential optimal routes scratched on paper fail to get experimentally tested. In addition, with new methods being discovered daily are often overlooked by established techniques. This thesis reports a computational technique that assist the discovery of economical synthetic routes to useful organic targets. Organic chemistry exists as a network where chemicals are connected by reactions, analogous to citied connected by roads in a geographic map. This network topology of organic reactions in the network of organic chemistry (NOC) allows the application of graph-theory to devise algorithms for synthetic optimization of organic targets. A computational approach comprised of customizable algorithms, pre-screening filters, and existing chemoinformatic techniques is capable of answering complex questions and perform mechanistic tasks desired by chemists such as optimization of organic syntheses. One-pot reactions are central to modern synthesis since they save resources and time by avoiding isolation, purification, characterization, and production of chemical waste after each synthetic step. Sometimes, such reactions are identified by chance or, more often, by careful inspection of individual steps that are to be wired together. Algorithms are used to discover one-pot reactions and validated experimentally. Which demonstrate that the computationally predicted sequences can indeed by carried out experimentally in good overall yields. The experimental examples are chosen to from small networks of reactions around useful chemicals such as quinoline scaffolds, quinoline-based inhibitors of phosphoinositide 3-kinase delta (PI3Kdelta) enzyme, and thiophene derivatives. In this way, we replace individual synthetic connections with two-, three-, or even four-step one-pot sequences. Lastly, the computational method is utilized to devise hypothetical synthetic route to popular pharmaceutical drugs like NaproxenRTM and TaxolRTM. The algorithmically generated optimal pathways are evaluated with chemistry logic. By applying labor/cost factor It was revealed that not all shorter synthesis routes are economical, sometimes "Longest way round is the shortest way home" lengthier routes are found to be more economical and environmentally friendly.

Fundamental differences between optimization code test problems in engineering applications

NASA Technical Reports Server (NTRS)

Eason, E. D.

1984-01-01

The purpose here is to suggest that there is at least one fundamental difference between the problems used for testing optimization codes and the problems that engineers often need to solve; in particular, the level of precision that can be practically achieved in the numerical evaluation of the objective function, derivatives, and constraints. This difference affects the performance of optimization codes, as illustrated by two examples. Two classes of optimization problem were defined. Class One functions and constraints can be evaluated to a high precision that depends primarily on the word length of the computer. Class Two functions and/or constraints can only be evaluated to a moderate or a low level of precision for economic or modeling reasons, regardless of the computer word length. Optimization codes have not been adequately tested on Class Two problems. There are very few Class Two test problems in the literature, while there are literally hundreds of Class One test problems. The relative performance of two codes may be markedly different for Class One and Class Two problems. Less sophisticated direct search type codes may be less likely to be confused or to waste many function evaluations on Class Two problems. The analysis accuracy and minimization performance are related in a complex way that probably varies from code to code. On a problem where the analysis precision was varied over a range, the simple Hooke and Jeeves code was more efficient at low precision while the Powell code was more efficient at high precision.

Variable selection based near infrared spectroscopy quantitative and qualitative analysis on wheat wet gluten

NASA Astrophysics Data System (ADS)

Lü, Chengxu; Jiang, Xunpeng; Zhou, Xingfan; Zhang, Yinqiao; Zhang, Naiqian; Wei, Chongfeng; Mao, Wenhua

2017-10-01

Wet gluten is a useful quality indicator for wheat, and short wave near infrared spectroscopy (NIRS) is a high performance technique with the advantage of economic rapid and nondestructive test. To study the feasibility of short wave NIRS analyzing wet gluten directly from wheat seed, 54 representative wheat seed samples were collected and scanned by spectrometer. 8 spectral pretreatment method and genetic algorithm (GA) variable selection method were used to optimize analysis. Both quantitative and qualitative model of wet gluten were built by partial least squares regression and discriminate analysis. For quantitative analysis, normalization is the optimized pretreatment method, 17 wet gluten sensitive variables are selected by GA, and GA model performs a better result than that of all variable model, with R2V=0.88, and RMSEV=1.47. For qualitative analysis, automatic weighted least squares baseline is the optimized pretreatment method, all variable models perform better results than those of GA models. The correct classification rates of 3 class of <24%, 24-30%, >30% wet gluten content are 95.45, 84.52, and 90.00%, respectively. The short wave NIRS technique shows potential for both quantitative and qualitative analysis of wet gluten for wheat seed.

Economic impact of ovarian stimulation with corifollitropin alfa versus conventional daily gonadotropins in oocyte donors: a randomized study.

PubMed

Cruz, María; Alamá, Pilar; Muñoz, Manuel; Collado, Diana; Blanes, Carlos; Solbes, Enrique; Requena, Antonio

2017-06-01

Assisted reproductive technologies are well-established treatments for many types of subfertility representing substantial economic and healthcare implications for patients, healthcare providers and society as a whole. In order to optimize outcomes according to the type of gonadotrophins within an oocyte donor programme, we performed an economic evaluation based on data collected in a multicentre, prospective, randomized study within three private clinics belonging to the IVI Group. Results showed no relevant between-group differences in the clinical variables. According to the economic analysis, ovarian stimulation with corifollitropin alfa increased the overall cost of the treatment as well as the cost per retrieved and effective oocyte, although the differences were not statistically significant. In conclusion, cost savings can be achieved using cheaper gonadotrophins during ovarian stimulation. The cost of corifollitropin alfa compared with recombinant FSH and highly purified human menopausal gonadotrophin should be considered when making treatment decisions. Copyright © 2017 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

Engineering tolerance to industrially relevant stress factors in yeast cell factories.

PubMed

Deparis, Quinten; Claes, Arne; Foulquié-Moreno, Maria R; Thevelein, Johan M

2017-06-01

The main focus in development of yeast cell factories has generally been on establishing optimal activity of heterologous pathways and further metabolic engineering of the host strain to maximize product yield and titer. Adequate stress tolerance of the host strain has turned out to be another major challenge for obtaining economically viable performance in industrial production. Although general robustness is a universal requirement for industrial microorganisms, production of novel compounds using artificial metabolic pathways presents additional challenges. Many of the bio-based compounds desirable for production by cell factories are highly toxic to the host cells in the titers required for economic viability. Artificial metabolic pathways also turn out to be much more sensitive to stress factors than endogenous pathways, likely because regulation of the latter has been optimized in evolution in myriads of environmental conditions. We discuss different environmental and metabolic stress factors with high relevance for industrial utilization of yeast cell factories and the experimental approaches used to engineer higher stress tolerance. Improving stress tolerance in a predictable manner in yeast cell factories should facilitate their widespread utilization in the bio-based economy and extend the range of products successfully produced in large scale in a sustainable and economically profitable way. © FEMS 2017.

Engineering tolerance to industrially relevant stress factors in yeast cell factories

PubMed Central

Deparis, Quinten; Claes, Arne; Foulquié-Moreno, Maria R.

2017-01-01

Abstract The main focus in development of yeast cell factories has generally been on establishing optimal activity of heterologous pathways and further metabolic engineering of the host strain to maximize product yield and titer. Adequate stress tolerance of the host strain has turned out to be another major challenge for obtaining economically viable performance in industrial production. Although general robustness is a universal requirement for industrial microorganisms, production of novel compounds using artificial metabolic pathways presents additional challenges. Many of the bio-based compounds desirable for production by cell factories are highly toxic to the host cells in the titers required for economic viability. Artificial metabolic pathways also turn out to be much more sensitive to stress factors than endogenous pathways, likely because regulation of the latter has been optimized in evolution in myriads of environmental conditions. We discuss different environmental and metabolic stress factors with high relevance for industrial utilization of yeast cell factories and the experimental approaches used to engineer higher stress tolerance. Improving stress tolerance in a predictable manner in yeast cell factories should facilitate their widespread utilization in the bio-based economy and extend the range of products successfully produced in large scale in a sustainable and economically profitable way. PMID:28586408

Fracture stimulation treatment design optimization: What can the NPV vs X{sub f} plot tell us?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huffman, C.H.; Harkrider, J.D.; Thompson, R.S.

1996-12-31

Fracture stimulation production response coupled with the hydrocarbon sales price determines the value of a fracture stimulation treatment. Many factors can significantly effect the production response of a fracture stimulated well. Some examples include stimulation fluid selection, proppant selection, pumping rates, rock properties, reservoir fluid properties, in-situ stresses, stress variations, on-site execution, post-treatment stimulation fluid recovery, and operating practices. The production response in economic terms portrays the net effect of these variables. This paper presents a case study that demonstrates how post-treatment evaluations expressed in economic terms can be used to assess the performance of stimulations and to guide futuremore » design choices.« less

Assessing the potential of economic instruments for managing drought risk at river basin scale

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, M.; Lopez-Nicolas, A.; Macian-Sorribes, H.

2015-12-01

Economic instruments work as incentives to adapt individual decisions to collectively agreed goals. Different types of economic instruments have been applied to manage water resources, such as water-related taxes and charges (water pricing, environmental taxes, etc.), subsidies, markets or voluntary agreements. Hydroeconomic models (HEM) provide useful insight on optimal strategies for coping with droughts by simultaneously analysing engineering, hydrology and economics of water resources management. We use HEMs for evaluating the potential of economic instruments on managing drought risk at river basin scale, considering three criteria for assessing drought risk: reliability, resilience and vulnerability. HEMs allow to calculate water scarcity costs as the economic losses due to water deliveries below the target demands, which can be used as a vulnerability descriptor of drought risk. Two generic hydroeconomic DSS tools, SIMGAMS and OPTIGAMS ( both programmed in GAMS) have been developed to evaluate water scarcity cost at river basin scale based on simulation and optimization approaches. The simulation tool SIMGAMS allocates water according to the system priorities and operating rules, and evaluate the scarcity costs using economic demand functions. The optimization tool allocates water resources for maximizing net benefits (minimizing total water scarcity plus operating cost of water use). SIMGAS allows to simulate incentive water pricing policies based on water availability in the system (scarcity pricing), while OPTIGAMS is used to simulate the effect of ideal water markets by economic optimization. These tools have been applied to the Jucar river system (Spain), highly regulated and with high share of water use for crop irrigation (greater than 80%), where water scarcity, irregular hydrology and groundwater overdraft cause droughts to have significant economic, social and environmental consequences. An econometric model was first used to explain the variation of the production value of irrigated agriculture during droughts, assessing revenue responses to varying crop prices and water availability. Hydroeconomic approaches were then used to show the potential of economic instruments in setting incentives for a more efficient management of water resources systems.

An Economic Analysis of Solar Water & Space Heating.

ERIC Educational Resources Information Center

Energy Research and Development Administration, Washington, DC. Div. of Solar Energy.

Solar system designs for 13 cities were optimized so as to minimize the life cycle cost over the assumed 20-year lifetime of the solar energy systems. A number of major assumptions were made regarding the solar system, type and use of building, financial considerations, and economic environment used in the design optimization. Seven optimum…

Self-Selection, Optimal Income Taxation, and Redistribution

ERIC Educational Resources Information Center

Amegashie, J. Atsu

2009-01-01

The author makes a pedagogical contribution to optimal income taxation. Using a very simple model adapted from George A. Akerlof (1978), he demonstrates a key result in the approach to public economics and welfare economics pioneered by Nobel laureate James Mirrlees. He shows how incomplete information, in addition to the need to preserve…

Efficient greedy algorithms for economic manpower shift planning

NASA Astrophysics Data System (ADS)

Nearchou, A. C.; Giannikos, I. C.; Lagodimos, A. G.

2015-01-01

Consideration is given to the economic manpower shift planning (EMSP) problem, an NP-hard capacity planning problem appearing in various industrial settings including the packing stage of production in process industries and maintenance operations. EMSP aims to determine the manpower needed in each available workday shift of a given planning horizon so as to complete a set of independent jobs at minimum cost. Three greedy heuristics are presented for the EMSP solution. These practically constitute adaptations of an existing algorithm for a simplified version of EMSP which had shown excellent performance in terms of solution quality and speed. Experimentation shows that the new algorithms perform very well in comparison to the results obtained by both the CPLEX optimizer and an existing metaheuristic. Statistical analysis is deployed to rank the algorithms in terms of their solution quality and to identify the effects that critical planning factors may have on their relative efficiency.

Optimizing conservation practices in watersheds: Do community preferences matter?

NASA Astrophysics Data System (ADS)

Piemonti, Adriana D.; Babbar-Sebens, Meghna; Jane Luzar, E.

2013-10-01

This paper focuses on investigating (a) how landowner tenure and attitudes of farming communities affect the preference of individual conservation practices in agricultural watersheds, (b) how spatial distribution of landowner tenure affects the spatial optimization of conservation practices on a watershed scale, and (c) how the different attitudes and preferences of stakeholders can modify the effectiveness of alternatives obtained via classic optimization approaches that do not include the influence of existing social attitudes in a watershed during the search process. Results show that for Eagle Creek Watershed in central Indiana, USA, the most optimal alternatives (i.e., highest benefits for minimum economic costs) are for a scenario when the watershed consists of landowners who operate as farmers on their own land. When a different land-tenure scenario was used for the watershed (e.g., share renters and cash renters), the optimized alternatives had similar nitrate reduction benefits and sediment reduction benefits, but at higher economic costs. Our experiments also demonstrated that social attitudes can lead to alteration of optimized alternatives found via typical optimization approaches. For example, when certain practices were rejected by landowner operators whose attitudes toward practices were driven by economic profits, removal of these practices from the optimized alternatives led to a setback of nitrates reduction by 2-50%, peak flow reductions by 11-98 %, and sediments reduction by 20-77%. In conclusion, this study reveals the potential loss in optimality of optimized alternatives possible, when socioeconomic data on farmer preferences and land tenure are not incorporated within watershed optimization investigations.

Wind farm topology-finding algorithm considering performance, costs, and environmental impacts.

PubMed

Tazi, Nacef; Chatelet, Eric; Bouzidi, Youcef; Meziane, Rachid

2017-06-05

Optimal power in wind farms turns to be a modern problem for investors and decision makers; onshore wind farms are subject to performance and economic and environmental constraints. The aim of this work is to define the best installed capacity (best topology) with maximum performance and profits and consider environmental impacts as well. In this article, we continue the work recently done on wind farm topology-finding algorithm. The proposed resolution technique is based on finding the best topology of the system that maximizes the wind farm performance (availability) under the constraints of costs and capital investments. Global warming potential of wind farm is calculated and taken into account in the results. A case study is done using data and constraints similar to those collected from wind farm constructors, managers, and maintainers. Multi-state systems (MSS), universal generating function (UGF), wind, and load charge functions are applied. An economic study was conducted to assess the wind farm investment. Net present value (NPV) and levelized cost of energy (LCOE) were calculated for best topologies found.

Addressing Hydro-economic Modeling Limitations - A Limited Foresight Sacramento Valley Model and an Open-source Modeling Platform

NASA Astrophysics Data System (ADS)

Harou, J. J.; Hansen, K. M.

2008-12-01

Increased scarcity of world water resources is inevitable given the limited supply and increased human pressures. The idea that "some scarcity is optimal" must be accepted for rational resource use and infrastructure management decisions to be made. Hydro-economic systems models are unique at representing the overlap of economic drivers, socio-political forces and distributed water resource systems. They demonstrate the tangible benefits of cooperation and integrated flexible system management. Further improvement of models, quality control practices and software will be needed for these academic policy tools to become accepted into mainstream water resource practice. Promising features include: calibration methods, limited foresight optimization formulations, linked simulation-optimization approaches (e.g. embedding pre-existing calibrated simulation models), spatial groundwater models, stream-aquifer interactions and stream routing, etc.. Conventional user-friendly decision support systems helped spread simulation models on a massive scale. Hydro-economic models must also find a means to facilitate construction, distribution and use. Some of these issues and model features are illustrated with a hydro-economic optimization model of the Sacramento Valley. Carry-over storage value functions are used to limit hydrologic foresight of the multi- period optimization model. Pumping costs are included in the formulation by tracking regional piezometric head of groundwater sub-basins. To help build and maintain this type of network model, an open-source water management modeling software platform is described and initial project work is discussed. The objective is to generically facilitate the connection of models, such as those developed in a modeling environment (GAMS, MatLab, Octave, "), to a geographic user interface (drag and drop node-link network) and a database (topology, parameters and time series). These features aim to incrementally move hydro- economic models in the direction of more practical implementation.

Multiobjective Particle Swarm Optimization for the optimal design of photovoltaic grid-connected systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kornelakis, Aris

2010-12-15

Particle Swarm Optimization (PSO) is a highly efficient evolutionary optimization algorithm. In this paper a multiobjective optimization algorithm based on PSO applied to the optimal design of photovoltaic grid-connected systems (PVGCSs) is presented. The proposed methodology intends to suggest the optimal number of system devices and the optimal PV module installation details, such that the economic and environmental benefits achieved during the system's operational lifetime period are both maximized. The objective function describing the economic benefit of the proposed optimization process is the lifetime system's total net profit which is calculated according to the method of the Net Present Valuemore » (NPV). The second objective function, which corresponds to the environmental benefit, equals to the pollutant gas emissions avoided due to the use of the PVGCS. The optimization's decision variables are the optimal number of the PV modules, the PV modules optimal tilt angle, the optimal placement of the PV modules within the available installation area and the optimal distribution of the PV modules among the DC/AC converters. (author)« less

Optimization of Water Resources and Agricultural Activities for Economic Benefit in Colorado

NASA Astrophysics Data System (ADS)

LIM, J.; Lall, U.

2017-12-01

The limited water resources available for irrigation are a key constraint for the important agricultural sector of Colorado's economy. As climate change and groundwater depletion reshape these resources, it is essential to understand the economic potential of water resources under different agricultural production practices. This study uses a linear programming optimization at the county spatial scale and annual temporal scales to study the optimal allocation of water withdrawal and crop choices. The model, AWASH, reflects streamflow constraints between different extraction points, six field crops, and a distinct irrigation decision for maize and wheat. The optimized decision variables, under different environmental, social, economic, and physical constraints, provide long-term solutions for ground and surface water distribution and for land use decisions so that the state can generate the maximum net revenue. Colorado, one of the largest agricultural producers, is tested as a case study and the sensitivity on water price and on climate variability is explored.

A crowdsourced nickel-and-dime approach to analog OBM research: A behavioral economic framework for understanding workforce attrition.

PubMed

Henley, Amy J; DiGennaro Reed, Florence D; Reed, Derek D; Kaplan, Brent A

2016-09-01

Incentives are a popular method to achieve desired employee performance; however, research on optimal incentive magnitude is lacking. Behavioral economic demand curves model persistence of responding in the face of increasing cost and may be suitable to examine the reinforcing value of incentives on work performance. The present use-inspired basic study integrated an experiential human operant task within a crowdsourcing platform to evaluate the applicability of behavioral economics for quantifying changes in workforce attrition. Participants included 88 Amazon Mechanical Turk Workers who earned either a $0.05 or $0.10 incentive for completing a progressively increasing response requirement. Analyses revealed statistically significant differences in breakpoint between the two groups. Additionally, a novel translation of the Kaplan-Meier survival-curve analyses for use within a demand curve framework allowed for examination of elasticity of workforce attrition. Results indicate greater inelastic attrition in the $0.05 group. We discuss the benefits of a behavioral economic approach to modeling employee behavior, how the metrics obtained from the elasticity of workforce attrition analyses (e.g., P max ) may be used to set goals for employee behavior while balancing organizational costs, and how economy type may have influenced observed outcomes. © 2016 Society for the Experimental Analysis of Behavior.

Selection of Hidden Layer Neurons and Best Training Method for FFNN in Application of Long Term Load Forecasting

NASA Astrophysics Data System (ADS)

Singh, Navneet K.; Singh, Asheesh K.; Tripathy, Manoj

2012-05-01

For power industries electricity load forecast plays an important role for real-time control, security, optimal unit commitment, economic scheduling, maintenance, energy management, and plant structure planning etc. A new technique for long term load forecasting (LTLF) using optimized feed forward artificial neural network (FFNN) architecture is presented in this paper, which selects optimal number of neurons in the hidden layer as well as the best training method for the case study. The prediction performance of proposed technique is evaluated using mean absolute percentage error (MAPE) of Thailand private electricity consumption and forecasted data. The results obtained are compared with the results of classical auto-regressive (AR) and moving average (MA) methods. It is, in general, observed that the proposed method is prediction wise more accurate.

[Techniques and strategy of pathological sampling in the diagnostic and therapeutic management of lung cancer].

PubMed

Remmelink, M; Sokolow, Y; Leduc, D

2015-04-01

Histopathology is key to the diagnosis and staging of lung cancer. This analysis requires tissue sampling from primary and/or metastatic lesions. The choice of sampling technique is intended to optimize diagnostic yield while avoiding unnecessarily invasive procedures. Recent developments in targeted therapy require increasingly precise histological and molecular characterization of the tumor. Therefore, pathologists must be economical with tissue samples to ensure that they have the opportunity to perform all the analyses required. More than ever, good communication between clinician, endoscopist or surgeon, and pathologist is essential. This is necessary to ensure that all participants in the process of lung cancer diagnosis collaborate to ensure that the appropriate number and type of biopsies are performed with the appropriate tissue sampling treatment. This will allow performance of all the necessary analyses leading to a more precise characterization of the tumor, and thus the optimal treatment for patients with lung cancer. Copyright © 2015 SPLF. Published by Elsevier Masson SAS. All rights reserved.

Aerodynamic Design Using Neural Networks

NASA Technical Reports Server (NTRS)

Rai, Man Mohan; Madavan, Nateri K.

2003-01-01

The design of aerodynamic components of aircraft, such as wings or engines, involves a process of obtaining the most optimal component shape that can deliver the desired level of component performance, subject to various constraints, e.g., total weight or cost, that the component must satisfy. Aerodynamic design can thus be formulated as an optimization problem that involves the minimization of an objective function subject to constraints. A new aerodynamic design optimization procedure based on neural networks and response surface methodology (RSM) incorporates the advantages of both traditional RSM and neural networks. The procedure uses a strategy, denoted parameter-based partitioning of the design space, to construct a sequence of response surfaces based on both neural networks and polynomial fits to traverse the design space in search of the optimal solution. Some desirable characteristics of the new design optimization procedure include the ability to handle a variety of design objectives, easily impose constraints, and incorporate design guidelines and rules of thumb. It provides an infrastructure for variable fidelity analysis and reduces the cost of computation by using less-expensive, lower fidelity simulations in the early stages of the design evolution. The initial or starting design can be far from optimal. The procedure is easy and economical to use in large-dimensional design space and can be used to perform design tradeoff studies rapidly. Designs involving multiple disciplines can also be optimized. Some practical applications of the design procedure that have demonstrated some of its capabilities include the inverse design of an optimal turbine airfoil starting from a generic shape and the redesign of transonic turbines to improve their unsteady aerodynamic characteristics.

Data envelopment analysis for estimating efficiency of intensive care units: a case study in Iran.

PubMed

Bahrami, Mohammad Amin; Rafiei, Sima; Abedi, Mahdieh; Askari, Roohollah

2018-05-14

Purpose As hospitals are the most costly service providers in every healthcare systems, special attention should be given to their performance in terms of resource allocation and consumption. The purpose of this paper is to evaluate technical, allocative and economic efficiency in intensive care units (ICUs) of hospitals affiliated by Yazd University of Medical Sciences (YUMS) in 2015. Design/methodology/approach This was a descriptive, analytical study conducted in ICUs of seven training hospitals affiliated by YUMS using data envelopment analysis (DEA) in 2015. The number of physicians, nurses, active beds and equipment were regarded as input variables and bed occupancy rate, the number of discharged patients, economic information such as bed price and physicians' fees were mentioned as output variables of the study. Available data from study variables were retrospectively gathered and analyzed through the Deap 2.1 software using the variable returns to scale methodology. Findings The study findings revealed the average scores of allocative, economic, technical, managerial and scale efficiency to be relatively 0.956, 0.866, 0.883, 0.89 and 0.913. Regarding to latter three types of efficiency, five hospitals had desirable performance. Practical implications Given that additional costs due to an extra number of manpower or unnecessary capital resources impose economic pressure on hospitals also the fact that reduction of surplus production plays a major role in reducing such expenditures in hospitals, it is suggested that departments with low efficiency reduce their input surpluses to achieve the optimal level of performance. Originality/value The authors applied a DEA approach to measure allocative, economic, technical, managerial and scale efficiency of under-study hospitals. This is a helpful linear programming method which acts as a powerful and understandable approach for comparative performance assessment in healthcare settings and a guidance for healthcare managers to improve their departments' performance.

Efficient computation of optimal actions.

PubMed

Todorov, Emanuel

2009-07-14

Optimal choice of actions is a fundamental problem relevant to fields as diverse as neuroscience, psychology, economics, computer science, and control engineering. Despite this broad relevance the abstract setting is similar: we have an agent choosing actions over time, an uncertain dynamical system whose state is affected by those actions, and a performance criterion that the agent seeks to optimize. Solving problems of this kind remains hard, in part, because of overly generic formulations. Here, we propose a more structured formulation that greatly simplifies the construction of optimal control laws in both discrete and continuous domains. An exhaustive search over actions is avoided and the problem becomes linear. This yields algorithms that outperform Dynamic Programming and Reinforcement Learning, and thereby solve traditional problems more efficiently. Our framework also enables computations that were not possible before: composing optimal control laws by mixing primitives, applying deterministic methods to stochastic systems, quantifying the benefits of error tolerance, and inferring goals from behavioral data via convex optimization. Development of a general class of easily solvable problems tends to accelerate progress--as linear systems theory has done, for example. Our framework may have similar impact in fields where optimal choice of actions is relevant.

Dynamic control of supplemental lighting for greenhouse

NASA Astrophysics Data System (ADS)

Wang, Yuanxv; Wei, Ruihua; Xu, Lihong

2018-04-01

The development of light-emitting diodes (LED) technology to a large extent reduce the energy consumption of greenhouse, however, the light control methods to realize the energy saving still have great potential. The aim of this paper is to develop a more efficient control method of dynamic control of the LED top-lighting (TL) intensity and the LED inter-lighting (IL) intensity for the greatest economic benefits. A dynamic lighting control algorithm (DLC) based on model is proposed, which defines the economic benefit performance criterion of the supplemental lighting control. The optimal light intensity of TL and IL is calculated in real time according to the algorithm. The simulation shows that economic benefit can be increased by up to 107.35% compared to TL on-off control. It is concluded that DLC is a feasible supplemental light control method, especially under low natural light conditions.

The design of sport and touring aircraft

NASA Technical Reports Server (NTRS)

Eppler, R.; Guenther, W.

1984-01-01

General considerations concerning the design of a new aircraft are discussed, taking into account the objective to develop an aircraft can satisfy economically a certain spectrum of tasks. Requirements related to the design of sport and touring aircraft included in the past mainly a high cruising speed and short take-off and landing runs. Additional requirements for new aircraft are now low fuel consumption and optimal efficiency. A computer program for the computation of flight performance makes it possible to vary automatically a number of parameters, such as flight altitude, wing area, and wing span. The appropriate design characteristics are to a large extent determined by the selection of the flight altitude. Three different wing profiles are compared. Potential improvements with respect to the performance of the aircraft and its efficiency are related to the use of fiber composites, the employment of better propeller profiles, more efficient engines, and the utilization of suitable instrumentation for optimal flight conduction.

Optimality problem of network topology in stocks market analysis

NASA Astrophysics Data System (ADS)

Djauhari, Maman Abdurachman; Gan, Siew Lee

2015-02-01

Since its introduction fifteen years ago, minimal spanning tree has become an indispensible tool in econophysics. It is to filter the important economic information contained in a complex system of financial markets' commodities. Here we show that, in general, that tool is not optimal in terms of topological properties. Consequently, the economic interpretation of the filtered information might be misleading. To overcome that non-optimality problem, a set of criteria and a selection procedure of an optimal minimal spanning tree will be developed. By using New York Stock Exchange data, the advantages of the proposed method will be illustrated in terms of the power-law of degree distribution.

Calcium Supplementation Abates the Inhibition Effects of Acetic Acid on Saccharomyces cerevisiae.

PubMed

Zhao, Hongwei; Li, Jingyuan; Wang, Jiming; Xu, Xin; Xian, Mo; Liu, Huizhou; Zhang, Haibo

2017-04-01

The toxic level of acetic acid could be released during the pretreatment of lignocellulosic biomass, and an economical method was reported to minimize the acidic stress on the fermentation of Saccharomyces cerevisiae by cation supplementation. A dose-dependent protection of Ca 2+ was monitored, and the optimal concentration of Ca 2+ was 8 mM under 4.5 g/L acetic acid stress. The activities of catalase and superoxide dismutase of yeast cells supplemented with optimal Ca 2+ increased by 18.6 and 27.3 %, respectively, coupling with an obvious decrease of reactive oxygen species content. Cell viability also performed a significant increase from 52.4 % (without Ca 2+ addition) to 73.56 % (with 8 mM Ca 2+ addition). No significant improvements were found in the bioethanol yields by Ca 2+ supplementation; however, the fermentation time was shortened by about 8 h obviously. Our results illustrated that the Ca 2+ supplementation could be an economical method to make the bioethanol production more efficient and cost-effective.

A review on economic emission dispatch problems using quantum computational intelligence

NASA Astrophysics Data System (ADS)

Mahdi, Fahad Parvez; Vasant, Pandian; Kallimani, Vish; Abdullah-Al-Wadud, M.

2016-11-01

Economic emission dispatch (EED) problems are one of the most crucial problems in power systems. Growing energy demand, limitation of natural resources and global warming make this topic into the center of discussion and research. This paper reviews the use of Quantum Computational Intelligence (QCI) in solving Economic Emission Dispatch problems. QCI techniques like Quantum Genetic Algorithm (QGA) and Quantum Particle Swarm Optimization (QPSO) algorithm are discussed here. This paper will encourage the researcher to use more QCI based algorithm to get better optimal result for solving EED problems.

Ecological and economical efficiency of monitoring systems for oil and gas production on the shelf

NASA Astrophysics Data System (ADS)

Kurakin, A. L.; Lobkovsky, L. I.

2014-02-01

Requirements for signals' reliability of monitoring systems (with respect to the errors of the 1st and 2nd kinds, i.e., false alarms and skipping of danger) are deduced from the ratio of expenditures of different kinds (of exploitation expenses and losses due to accidents). The expressions obtained in the research may be used for economic foundations (and optimization) of specifications for monitoring systems. In cases when optimal parameters are not available, the sufficient condition of monitoring systems economical efficiency is presented.

Optimal scheduling and its Lyapunov stability for advanced load-following energy plants with CO 2 capture

DOE PAGES

Bankole, Temitayo; Jones, Dustin; Bhattacharyya, Debangsu; ...

2017-11-03

In this study, a two-level control methodology consisting of an upper-level scheduler and a lower-level supervisory controller is proposed for an advanced load-following energy plant with CO 2 capture. With the use of an economic objective function that considers fluctuation in electricity demand and price at the upper level, optimal scheduling of energy plant electricity production and carbon capture with respect to several carbon tax scenarios is implemented. The optimal operational profiles are then passed down to corresponding lower-level supervisory controllers designed using a methodological approach that balances control complexity with performance. Finally, it is shown how optimal carbon capturemore » and electricity production rate profiles for an energy plant such as the integrated gasification combined cycle (IGCC) plant are affected by electricity demand and price fluctuations under different carbon tax scenarios. As a result, the paper also presents a Lyapunov stability analysis of the proposed scheme.« less

Optimal scheduling and its Lyapunov stability for advanced load-following energy plants with CO 2 capture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bankole, Temitayo; Jones, Dustin; Bhattacharyya, Debangsu

In this study, a two-level control methodology consisting of an upper-level scheduler and a lower-level supervisory controller is proposed for an advanced load-following energy plant with CO 2 capture. With the use of an economic objective function that considers fluctuation in electricity demand and price at the upper level, optimal scheduling of energy plant electricity production and carbon capture with respect to several carbon tax scenarios is implemented. The optimal operational profiles are then passed down to corresponding lower-level supervisory controllers designed using a methodological approach that balances control complexity with performance. Finally, it is shown how optimal carbon capturemore » and electricity production rate profiles for an energy plant such as the integrated gasification combined cycle (IGCC) plant are affected by electricity demand and price fluctuations under different carbon tax scenarios. As a result, the paper also presents a Lyapunov stability analysis of the proposed scheme.« less

Data centers as dispatchable loads to harness stranded power

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Kibaek; Yang, Fan; Zavala, Victor M.

Here, we analyze how traditional data center placement and optimal placement of dispatchable data centers affect power grid efficiency. We use detailed network models, stochastic optimization formulations, and diverse renewable generation scenarios to perform our analysis. Our results reveal that significant spillage and stranded power will persist in power grids as wind power levels are increased. A counter-intuitive finding is that collocating data centers with inflexible loads next to wind farms has limited impacts on renewable portfolio standard (RPS) goals because it provides limited system-level flexibility. Such an approach can, in fact, increase stranded power and fossil-fueled generation. In contrast,more » optimally placing data centers that are dispatchable provides system-wide flexibility, reduces stranded power, and improves efficiency. In short, optimally placed dispatchable computing loads can enable better scaling to high RPS. In our case study, we find that these dispatchable computing loads are powered to 60-80% of their requested capacity, indicating that there are significant economic incentives provided by stranded power.« less

Data centers as dispatchable loads to harness stranded power

DOE PAGES

Kim, Kibaek; Yang, Fan; Zavala, Victor M.; ...

2016-07-20

Here, we analyze how traditional data center placement and optimal placement of dispatchable data centers affect power grid efficiency. We use detailed network models, stochastic optimization formulations, and diverse renewable generation scenarios to perform our analysis. Our results reveal that significant spillage and stranded power will persist in power grids as wind power levels are increased. A counter-intuitive finding is that collocating data centers with inflexible loads next to wind farms has limited impacts on renewable portfolio standard (RPS) goals because it provides limited system-level flexibility. Such an approach can, in fact, increase stranded power and fossil-fueled generation. In contrast,more » optimally placing data centers that are dispatchable provides system-wide flexibility, reduces stranded power, and improves efficiency. In short, optimally placed dispatchable computing loads can enable better scaling to high RPS. In our case study, we find that these dispatchable computing loads are powered to 60-80% of their requested capacity, indicating that there are significant economic incentives provided by stranded power.« less

Experimental analysis of the performance of optimized fin structures in a latent heat energy storage test rig

NASA Astrophysics Data System (ADS)

Johnson, Maike; Hübner, Stefan; Reichmann, Carsten; Schönberger, Manfred; Fiß, Michael

2017-06-01

Energy storage systems are a key technology for developing a more sustainable energy supply system and lowering overall CO2 emissions. Among the variety of storage technologies, high temperature phase change material (PCM) storage is a promising option with a wide range of applications. PCM storages using an extended finned tube storage concept have been designed and techno-economically optimized for solar thermal power plant operations. These finned tube components were experimentally tested in order to validate the optimized design and simulation models used. Analysis of the charging and discharging characteristics of the storage at the pilot scale gives insight into the heat distribution both axially as well as radially in the storage material, thereby allowing for a realistic validation of the design. The design was optimized for discharging of the storage, as this is the more critical operation mode in power plant applications. The data show good agreement between the model and the experiments for discharging.

Optimal Energy Management for Microgrids

NASA Astrophysics Data System (ADS)

Zhao, Zheng

Microgrid is a recent novel concept in part of the development of smart grid. A microgrid is a low voltage and small scale network containing both distributed energy resources (DERs) and load demands. Clean energy is encouraged to be used in a microgrid for economic and sustainable reasons. A microgrid can have two operational modes, the stand-alone mode and grid-connected mode. In this research, a day-ahead optimal energy management for a microgrid under both operational modes is studied. The objective of the optimization model is to minimize fuel cost, improve energy utilization efficiency and reduce gas emissions by scheduling generations of DERs in each hour on the next day. Considering the dynamic performance of battery as Energy Storage System (ESS), the model is featured as a multi-objectives and multi-parametric programming constrained by dynamic programming, which is proposed to be solved by using the Advanced Dynamic Programming (ADP) method. Then, factors influencing the battery life are studied and included in the model in order to obtain an optimal usage pattern of battery and reduce the correlated cost. Moreover, since wind and solar generation is a stochastic process affected by weather changes, the proposed optimization model is performed hourly to track the weather changes. Simulation results are compared with the day-ahead energy management model. At last, conclusions are presented and future research in microgrid energy management is discussed.

Stochastic multi-objective model for optimal energy exchange optimization of networked microgrids with presence of renewable generation under risk-based strategies.

PubMed

Gazijahani, Farhad Samadi; Ravadanegh, Sajad Najafi; Salehi, Javad

2018-02-01

The inherent volatility and unpredictable nature of renewable generations and load demand pose considerable challenges for energy exchange optimization of microgrids (MG). To address these challenges, this paper proposes a new risk-based multi-objective energy exchange optimization for networked MGs from economic and reliability standpoints under load consumption and renewable power generation uncertainties. In so doing, three various risk-based strategies are distinguished by using conditional value at risk (CVaR) approach. The proposed model is specified as a two-distinct objective function. The first function minimizes the operation and maintenance costs, cost of power transaction between upstream network and MGs as well as power loss cost, whereas the second function minimizes the energy not supplied (ENS) value. Furthermore, the stochastic scenario-based approach is incorporated into the approach in order to handle the uncertainty. Also, Kantorovich distance scenario reduction method has been implemented to reduce the computational burden. Finally, non-dominated sorting genetic algorithm (NSGAII) is applied to minimize the objective functions simultaneously and the best solution is extracted by fuzzy satisfying method with respect to risk-based strategies. To indicate the performance of the proposed model, it is performed on the modified IEEE 33-bus distribution system and the obtained results show that the presented approach can be considered as an efficient tool for optimal energy exchange optimization of MGs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Streamflow variability and optimal capacity of run-of-river hydropower plants

NASA Astrophysics Data System (ADS)

Basso, S.; Botter, G.

2012-10-01

The identification of the capacity of a run-of-river plant which allows for the optimal utilization of the available water resources is a challenging task, mainly because of the inherent temporal variability of river flows. This paper proposes an analytical framework to describe the energy production and the economic profitability of small run-of-river power plants on the basis of the underlying streamflow regime. We provide analytical expressions for the capacity which maximize the produced energy as a function of the underlying flow duration curve and minimum environmental flow requirements downstream of the plant intake. Similar analytical expressions are derived for the capacity which maximize the economic return deriving from construction and operation of a new plant. The analytical approach is applied to a minihydro plant recently proposed in a small Alpine catchment in northeastern Italy, evidencing the potential of the method as a flexible and simple design tool for practical application. The analytical model provides useful insight on the major hydrologic and economic controls (e.g., streamflow variability, energy price, costs) on the optimal plant capacity and helps in identifying policy strategies to reduce the current gap between the economic and energy optimizations of run-of-river plants.

Evaluating quantity and quality of literature focusing on health economics and pharmacoeconomics in Gulf Cooperation Council countries.

PubMed

Eljilany, Islam; El-Dahiyat, Faris; Curley, Louise Elizabeth; Babar, Zaheer-Ud-Din

2018-05-30

The importance of pharmacoeconomics and health economics has been augmented. It has the potential to provide evidence to aid in optimal decision-making in the funding of cost-effective medicines and services in Gulf Cooperation Council countries (G.C.C). To evaluate the quality and quantity of health economic researches published until the end of 2017 in G.C.C. and to identify the factors that affect the quality of studies. Studies were included according to predefined inclusion and exclusion criteria. The quantity was recorded, and the quality was assessed using the Quality of Health Economic Studies (QHES) instrument. Forty-nine studies were included. The mean (SD) quality score of all studies was 57.83 (25.05), and a high number of reviewed studies (47%) were evaluated as either poor or extremely poor quality. The factors that affect the quality of studies with statistical significance were, the type and method of economic evaluation, the economic outcome was the objective of the research, author`s background, the perspective of the study, health intervention and source of funding. The use of economic evaluation studies in G.C.C was limited. Different factors that affect the quality of articles such as performing a full economic evaluation and choosing societal perspective were identified. Strategies to improve the quality of future studies were recommended.

A fuzzy stochastic framework for managing hydro-environmental and socio-economic interactions under uncertainty

NASA Astrophysics Data System (ADS)

Subagadis, Yohannes Hagos; Schütze, Niels; Grundmann, Jens

2014-05-01

An amplified interconnectedness between a hydro-environmental and socio-economic system brings about profound challenges of water management decision making. In this contribution, we present a fuzzy stochastic approach to solve a set of decision making problems, which involve hydrologically, environmentally, and socio-economically motivated criteria subjected to uncertainty and ambiguity. The proposed methodological framework combines objective and subjective criteria in a decision making procedure for obtaining an acceptable ranking in water resources management alternatives under different type of uncertainty (subjective/objective) and heterogeneous information (quantitative/qualitative) simultaneously. The first step of the proposed approach involves evaluating the performance of alternatives with respect to different types of criteria. The ratings of alternatives with respect to objective and subjective criteria are evaluated by simulation-based optimization and fuzzy linguistic quantifiers, respectively. Subjective and objective uncertainties related to the input information are handled through linking fuzziness and randomness together. Fuzzy decision making helps entail the linguistic uncertainty and a Monte Carlo simulation process is used to map stochastic uncertainty. With this framework, the overall performance of each alternative is calculated using an Order Weighted Averaging (OWA) aggregation operator accounting for decision makers' experience and opinions. Finally, ranking is achieved by conducting pair-wise comparison of management alternatives. This has been done on the basis of the risk defined by the probability of obtaining an acceptable ranking and mean difference in total performance for the pair of management alternatives. The proposed methodology is tested in a real-world hydrosystem, to find effective and robust intervention strategies for the management of a coastal aquifer system affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. The results show that the approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.

Environmental and economic trade-offs in a watershed when using corn stover for bioenergy.

PubMed

Gramig, Benjamin M; Reeling, Carson J; Cibin, Raj; Chaubey, Indrajeet

2013-02-19

There is an abundant supply of corn stover in the United States that remains after grain is harvested which could be used to produce cellulosic biofuels mandated by the current Renewable Fuel Standard (RFS). This research integrates the Soil Water Assessment Tool (SWAT) watershed model and the DayCent biogeochemical model to investigate water quality and soil greenhouse gas flux that results when corn stover is collected at two different rates from corn-soybean and continuous corn crop rotations with and without tillage. Multiobjective watershed-scale optimizations are performed for individual pollutant-cost minimization criteria based on the economic cost of each cropping practice and (individually) the effect on nitrate, total phosphorus, sediment, or global warming potential. We compare these results with a purely economic optimization that maximizes stover production at the lowest cost without taking environmental impacts into account. We illustrate trade-offs between cost and different environmental performance criteria, assuming that nutrients contained in any stover collected must be replaced. The key finding is that stover collection using the practices modeled results in increased contributions to atmospheric greenhouse gases while reducing nitrate and total phosphorus loading to the watershed relative to the status quo without stover collection. Stover collection increases sediment loading to waterways relative to when no stover is removed for each crop rotation-tillage practice combination considered; no-till in combination with stover collection reduced sediment loading below baseline conditions without stover collection. Our results suggest that additional information is needed about (i) the level of nutrient replacement required to maintain grain yields and (ii) cost-effective management practices capable of reducing soil erosion when crop residues are removed in order to avoid contributions to climate change and water quality impairments as a result of using corn stover to satisfy the RFS.

Allogeneic Cell Therapy Bioprocess Economics and Optimization: Single-Use Cell Expansion Technologies

PubMed Central

Simaria, Ana S; Hassan, Sally; Varadaraju, Hemanthram; Rowley, Jon; Warren, Kim; Vanek, Philip; Farid, Suzanne S

2014-01-01

For allogeneic cell therapies to reach their therapeutic potential, challenges related to achieving scalable and robust manufacturing processes will need to be addressed. A particular challenge is producing lot-sizes capable of meeting commercial demands of up to 109 cells/dose for large patient numbers due to the current limitations of expansion technologies. This article describes the application of a decisional tool to identify the most cost-effective expansion technologies for different scales of production as well as current gaps in the technology capabilities for allogeneic cell therapy manufacture. The tool integrates bioprocess economics with optimization to assess the economic competitiveness of planar and microcarrier-based cell expansion technologies. Visualization methods were used to identify the production scales where planar technologies will cease to be cost-effective and where microcarrier-based bioreactors become the only option. The tool outputs also predict that for the industry to be sustainable for high demand scenarios, significant increases will likely be needed in the performance capabilities of microcarrier-based systems. These data are presented using a technology S-curve as well as windows of operation to identify the combination of cell productivities and scale of single-use bioreactors required to meet future lot sizes. The modeling insights can be used to identify where future R&D investment should be focused to improve the performance of the most promising technologies so that they become a robust and scalable option that enables the cell therapy industry reach commercially relevant lot sizes. The tool outputs can facilitate decision-making very early on in development and be used to predict, and better manage, the risk of process changes needed as products proceed through the development pathway. Biotechnol. Bioeng. 2014;111: 69–83. © 2013 Wiley Periodicals, Inc. PMID:23893544

Allogeneic cell therapy bioprocess economics and optimization: single-use cell expansion technologies.

PubMed

Simaria, Ana S; Hassan, Sally; Varadaraju, Hemanthram; Rowley, Jon; Warren, Kim; Vanek, Philip; Farid, Suzanne S

2014-01-01

For allogeneic cell therapies to reach their therapeutic potential, challenges related to achieving scalable and robust manufacturing processes will need to be addressed. A particular challenge is producing lot-sizes capable of meeting commercial demands of up to 10(9) cells/dose for large patient numbers due to the current limitations of expansion technologies. This article describes the application of a decisional tool to identify the most cost-effective expansion technologies for different scales of production as well as current gaps in the technology capabilities for allogeneic cell therapy manufacture. The tool integrates bioprocess economics with optimization to assess the economic competitiveness of planar and microcarrier-based cell expansion technologies. Visualization methods were used to identify the production scales where planar technologies will cease to be cost-effective and where microcarrier-based bioreactors become the only option. The tool outputs also predict that for the industry to be sustainable for high demand scenarios, significant increases will likely be needed in the performance capabilities of microcarrier-based systems. These data are presented using a technology S-curve as well as windows of operation to identify the combination of cell productivities and scale of single-use bioreactors required to meet future lot sizes. The modeling insights can be used to identify where future R&D investment should be focused to improve the performance of the most promising technologies so that they become a robust and scalable option that enables the cell therapy industry reach commercially relevant lot sizes. The tool outputs can facilitate decision-making very early on in development and be used to predict, and better manage, the risk of process changes needed as products proceed through the development pathway. © 2013 Wiley Periodicals, Inc.

Operation management of daily economic dispatch using novel hybrid particle swarm optimization and gravitational search algorithm with hybrid mutation strategy

NASA Astrophysics Data System (ADS)

Wang, Yan; Huang, Song; Ji, Zhicheng

2017-07-01

This paper presents a hybrid particle swarm optimization and gravitational search algorithm based on hybrid mutation strategy (HGSAPSO-M) to optimize economic dispatch (ED) including distributed generations (DGs) considering market-based energy pricing. A daily ED model was formulated and a hybrid mutation strategy was adopted in HGSAPSO-M. The hybrid mutation strategy includes two mutation operators, chaotic mutation, Gaussian mutation. The proposed algorithm was tested on IEEE-33 bus and results show that the approach is effective for this problem.

Design and demonstration of a storage assisted air conditioning system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Avril, F.; Irvine, T.F.

1982-04-01

The report describes the design and demonstration of a storage-assisted air conditioning system for residential central air conditioning applications. The system was designed to reduce peak air conditioning loads by storing coolness to fulfill daytime air conditioning requirements. The system design analyses, as well as performance data obtained from a residential installation on Long Island, are presented, along with an economic evaluation of the system. The results of the study indicate that such a system can reduce air conditioning peak load requirements while maintaining house temperature and humidity within prescribed limits. However, further system optimization is required, as well asmore » either equipment costs reduction or increased incentives, to make this system economically attractive for use in New York State.« less

Do humans make good decisions?

PubMed Central

Summerfield, Christopher; Tsetsos, Konstantinos

2014-01-01

Human performance on perceptual classification tasks approaches that of an ideal observer, but economic decisions are often inconsistent and intransitive, with preferences reversing according to the local context. We discuss the view that suboptimal choices may result from the efficient coding of decision-relevant information, a strategy that allows expected inputs to be processed with higher gain than unexpected inputs. Efficient coding leads to ‘robust’ decisions that depart from optimality but maximise the information transmitted by a limited-capacity system in a rapidly-changing world. We review recent work showing that when perceptual environments are variable or volatile, perceptual decisions exhibit the same suboptimal context-dependence as economic choices, and propose a general computational framework that accounts for findings across the two domains. PMID:25488076

A Bayesian approach for incorporating economic factors in sample size design for clinical trials of individual drugs and portfolios of drugs.

PubMed

Patel, Nitin R; Ankolekar, Suresh

2007-11-30

Classical approaches to clinical trial design ignore economic factors that determine economic viability of a new drug. We address the choice of sample size in Phase III trials as a decision theory problem using a hybrid approach that takes a Bayesian view from the perspective of a drug company and a classical Neyman-Pearson view from the perspective of regulatory authorities. We incorporate relevant economic factors in the analysis to determine the optimal sample size to maximize the expected profit for the company. We extend the analysis to account for risk by using a 'satisficing' objective function that maximizes the chance of meeting a management-specified target level of profit. We extend the models for single drugs to a portfolio of clinical trials and optimize the sample sizes to maximize the expected profit subject to budget constraints. Further, we address the portfolio risk and optimize the sample sizes to maximize the probability of achieving a given target of expected profit.

Optimization of wastewater treatment alternative selection by hierarchy grey relational analysis.

PubMed

Zeng, Guangming; Jiang, Ru; Huang, Guohe; Xu, Min; Li, Jianbing

2007-01-01

This paper describes an innovative systematic approach, namely hierarchy grey relational analysis for optimal selection of wastewater treatment alternatives, based on the application of analytic hierarchy process (AHP) and grey relational analysis (GRA). It can be applied for complicated multicriteria decision-making to obtain scientific and reasonable results. The effectiveness of this approach was verified through a real case study. Four wastewater treatment alternatives (A(2)/O, triple oxidation ditch, anaerobic single oxidation ditch and SBR) were evaluated and compared against multiple economic, technical and administrative performance criteria, including capital cost, operation and maintenance (O and M) cost, land area, removal of nitrogenous and phosphorous pollutants, sludge disposal effect, stability of plant operation, maturity of technology and professional skills required for O and M. The result illustrated that the anaerobic single oxidation ditch was the optimal scheme and would obtain the maximum general benefits for the wastewater treatment plant to be constructed.

"Utilizing" signal detection theory.

PubMed

Lynn, Spencer K; Barrett, Lisa Feldman

2014-09-01

What do inferring what a person is thinking or feeling, judging a defendant's guilt, and navigating a dimly lit room have in common? They involve perceptual uncertainty (e.g., a scowling face might indicate anger or concentration, for which different responses are appropriate) and behavioral risk (e.g., a cost to making the wrong response). Signal detection theory describes these types of decisions. In this tutorial, we show how incorporating the economic concept of utility allows signal detection theory to serve as a model of optimal decision making, going beyond its common use as an analytic method. This utility approach to signal detection theory clarifies otherwise enigmatic influences of perceptual uncertainty on measures of decision-making performance (accuracy and optimality) and on behavior (an inverse relationship between bias magnitude and sensitivity optimizes utility). A "utilized" signal detection theory offers the possibility of expanding the phenomena that can be understood within a decision-making framework. © The Author(s) 2014.

Analysis of Bioactive Amino Acids from Fish Hydrolysates with a New Bioinformatic Intelligent System Approach.

PubMed

Elaziz, Mohamed Abd; Hemdan, Ahmed Monem; Hassanien, AboulElla; Oliva, Diego; Xiong, Shengwu

2017-09-07

The current economics of the fish protein industry demand rapid, accurate and expressive prediction algorithms at every step of protein production especially with the challenge of global climate change. This help to predict and analyze functional and nutritional quality then consequently control food allergies in hyper allergic patients. As, it is quite expensive and time-consuming to know these concentrations by the lab experimental tests, especially to conduct large-scale projects. Therefore, this paper introduced a new intelligent algorithm using adaptive neuro-fuzzy inference system based on whale optimization algorithm. This algorithm is used to predict the concentration levels of bioactive amino acids in fish protein hydrolysates at different times during the year. The whale optimization algorithm is used to determine the optimal parameters in adaptive neuro-fuzzy inference system. The results of proposed algorithm are compared with others and it is indicated the higher performance of the proposed algorithm.

Modeling and prediction of copper removal from aqueous solutions by nZVI/rGO magnetic nanocomposites using ANN-GA and ANN-PSO.

PubMed

Fan, Mingyi; Hu, Jiwei; Cao, Rensheng; Xiong, Kangning; Wei, Xionghui

2017-12-21

Reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) magnetic nanocomposites were prepared and then applied in the Cu(II) removal from aqueous solutions. Scanning electron microscopy, transmission electron microscopy, X-ray photoelectron spectroscopy and superconduction quantum interference device magnetometer were performed to characterize the nZVI/rGO nanocomposites. In order to reduce the number of experiments and the economic cost, response surface methodology (RSM) combined with artificial intelligence (AI) techniques, such as artificial neural network (ANN), genetic algorithm (GA) and particle swarm optimization (PSO), has been utilized as a major tool that can model and optimize the removal processes, because a tremendous advance has recently been made on AI that may result in extensive applications. Based on RSM, ANN-GA and ANN-PSO were employed to model the Cu(II) removal process and optimize the operating parameters, e.g., operating temperature, initial pH, initial concentration and contact time. The ANN-PSO model was proven to be an effective tool for modeling and optimizing the Cu(II) removal with a low absolute error and a high removal efficiency. Furthermore, the isotherm, kinetic, thermodynamic studies and the XPS analysis were performed to explore the mechanisms of Cu(II) removal process.

Electric power market agent design

NASA Astrophysics Data System (ADS)

Oh, Hyungseon

The electric power industry in many countries has been restructured in the hope of a more economically efficient system. In the restructured system, traditional operating and planning tools based on true marginal cost do not perform well since information required is strictly confidential. For developing a new tool, it is necessary to understand offer behavior. The main objective of this study is to create a new tool for power system planning. For the purpose, this dissertation develops models for a market and market participants. A new model is developed in this work for explaining a supply-side offer curve, and several variables are introduced to characterize the curve. Demand is estimated using a neural network, and a numerical optimization process is used to determine the values of the variables that maximize the profit of the agent. The amount of data required for the optimization is chosen with the aid of nonlinear dynamics. To suggest an optimal demand-side bidding function, two optimization problems are constructed and solved for maximizing consumer satisfaction based on the properties of two different types of demands: price-based demand and must-be-served demand. Several different simulations are performed to test how an agent reacts in various situations. The offer behavior depends on locational benefit as well as the offer strategies of competitors.

The economics of optimal health and productivity in the commercial dairy.

PubMed

Galligan, D T

1999-08-01

Dairy production practices are changing; in order to remain viable, producers must optimise the health and productivity of dairy herds in economic terms. Health care is important in economic terms because disease can substantially reduce the productivity of individual animals. Preventive disease control programmes can thus result in economic gains for the dairy producer. The author describes new approaches to preventing postpartum diseases and dealing with fertility problems which can result from these diseases. Other aspects of dairy production are also changing, employing new technologies where these are judged to be profitable. Innovations include: the use of bovine somatotropin; systematic breeding/culling programmes; new mathematical modelling techniques to determine optimum feed composition and to define optimal growth levels for accelerated heifer-rearing programmes; the use of computers to collect, store and analyse data on animal production and health; and semen selection programmes. Increasing awareness of bio-security is also vital, not least because of the large investment present in dairy herds. Whatever practices are employed, they must offer economic returns to producers that compete with alternative uses of capital. Optimal levels of disease control must be determined for a particular production situation, taking into account not only the economic health of the producer, but also the well-being of the animals.

Structure analysis of tax revenue and inflation rate in Banda Aceh using vector error correction model with multiple alpha

NASA Astrophysics Data System (ADS)

Sofyan, Hizir; Maulia, Eva; Miftahuddin

2017-11-01

A country has several important parameters to achieve economic prosperity, such as tax revenue and inflation rate. One of the largest revenues of the State Budget in Indonesia comes from the tax sector. Meanwhile, the rate of inflation occurring in a country can be used as an indicator, to measure the good and bad economic problems faced by the country. Given the importance of tax revenue and inflation rate control in achieving economic prosperity, it is necessary to analyze the structure of tax revenue relations and inflation rate. This study aims to produce the best VECM (Vector Error Correction Model) with optimal lag using various alpha and perform structural analysis using the Impulse Response Function (IRF) of the VECM models to examine the relationship of tax revenue, and inflation in Banda Aceh. The results showed that the best model for the data of tax revenue and inflation rate in Banda Aceh City using alpha 0.01 is VECM with optimal lag 2, while the best model for data of tax revenue and inflation rate in Banda Aceh City using alpha 0.05 and 0,1 VECM with optimal lag 3. However, the VECM model with alpha 0.01 yielded four significant models of income tax model, inflation rate of Banda Aceh, inflation rate of health and inflation rate of education in Banda Aceh. While the VECM model with alpha 0.05 and 0.1 yielded one significant model that is income tax model. Based on the VECM models, then there are two structural analysis IRF which is formed to look at the relationship of tax revenue, and inflation in Banda Aceh, the IRF with VECM (2) and IRF with VECM (3).

Land Use Strategies for Optimizing Carbon Sequestration within the Head of the Lower Mississippi Watershed

NASA Astrophysics Data System (ADS)

Weaver, L.

2015-12-01

The world is currently in a stage of extreme growth, characterized by increasing demands for food and increasing greenhouse gas emissions. The population for 2050 is forecasted to grow by 2.3 billion people, resulting in close to a 40% increase in food demand (Alexandratos, Bruinsma 2012). This will severely increase pressure on the earth and on crop harvesting processes to incorporate carbon emissions reduction strategies. Optimal land use analysis and innovation can provide feasible solutions for these problems. A key environmental feature around which land use systems should be carefully planned and maintained is the Mississippi River, the largest watershed system in the United States. Along head of the Lower Mississippi Watershed lie several farming communities including Cairo, Illinois. The primary land use for the area inhabited by these communities consists of soybeans, corn, and pasture. These crops have varying carbon storage capacities, economic and social benefits, and environmental consequences. In order to maximize social, economic, and environmental benefits and sustainability, these crops were analyzed over time, spatial correlation, and crop size area. When considering risks of carbon emissions, economic decline, landscape erosion and harmful runoff, a localized switchgrass buffer remains a feasible solution. Its strengths as a native, reliable plant with high carbon sequestration and biomass harvest potential yield it to be more prevalently implemented at the head of the Lower Mississippi Watershed. However, there are multiple factors that must be considered before implementing broad agricultural policies and practices. Thorough analyses should be performed frequently to assess the effects of major land use change and can be used to identify the optimized applications for farmers and communities.

Optimal mission planning of GEO on-orbit refueling in mixed strategy

NASA Astrophysics Data System (ADS)

Chen, Xiao-qian; Yu, Jing

2017-04-01

The mission planning of GEO on-orbit refueling (OOR) in Mixed strategy is studied in this paper. Specifically, one SSc will be launched to an orbital slot near the depot when multiple GEO satellites are reaching their end of lives. The SSc replenishes fuel from the depot and then extends the lifespan of the target satellites via refueling. In the mixed scenario, only some of the target satellites could be served by the SSc, and the remaining ones will be fueled by Pseudo SScs (the target satellite which has already been refueled by the SSc and now has sufficient fuel for its operation as well as the fuel to refuel other target satellites is called Pseudo SSc here). The mission sequences and fuel mass of the SSc and Pseudo SScs, the dry mass of the SSc are used as design variables, whereas the economic benefit of the whole mission is used as design objective. The economic cost and benefit models are stated first, and then a mathematical optimization model is proposed. A comprehensive solution method involving enumeration, particle swarm optimization and modification is developed. Numerical examples are carried out to demonstrate the effectiveness of the model and solution method. Economic efficiencies of different OOR strategies are compared and discussed. The mixed strategy would perform better than the other strategies only when the target satellites satisfy some conditions. This paper presents an available mixed strategy scheme for users and analyzes its advantages and disadvantages by comparing with some other OOR strategies, providing helpful references to decision makers. The best strategy in practical applications depends on the specific demands and user preference.

Optimizing the creation of base populations for aquaculture breeding programs using phenotypic and genomic data and its consequences on genetic progress.

PubMed

Fernández, Jesús; Toro, Miguel Á; Sonesson, Anna K; Villanueva, Beatriz

2014-01-01

The success of an aquaculture breeding program critically depends on the way in which the base population of breeders is constructed since all the genetic variability for the traits included originally in the breeding goal as well as those to be included in the future is contained in the initial founders. Traditionally, base populations were created from a number of wild strains by sampling equal numbers from each strain. However, for some aquaculture species improved strains are already available and, therefore, mean phenotypic values for economically important traits can be used as a criterion to optimize the sampling when creating base populations. Also, the increasing availability of genome-wide genotype information in aquaculture species could help to refine the estimation of relationships within and between candidate strains and, thus, to optimize the percentage of individuals to be sampled from each strain. This study explores the advantages of using phenotypic and genome-wide information when constructing base populations for aquaculture breeding programs in terms of initial and subsequent trait performance and genetic diversity level. Results show that a compromise solution between diversity and performance can be found when creating base populations. Up to 6% higher levels of phenotypic performance can be achieved at the same level of global diversity in the base population by optimizing the selection of breeders instead of sampling equal numbers from each strain. The higher performance observed in the base population persisted during 10 generations of phenotypic selection applied in the subsequent breeding program.

Optimization of the resources management in fighting wildfires.

PubMed

Martin-Fernández, Susana; Martínez-Falero, Eugenio; Pérez-González, J Manuel

2002-09-01

Wildfires lead to important economic, social, and environmental losses, especially in areas of Mediterranean climate where they are of a high intensity and frequency. Over the past 30 years there has been a dramatic surge in the development and use of fire spread models. However, given the chaotic nature of environmental systems, it is very difficult to develop real-time fire-extinguishing models. This article proposes a method of optimizing the performance of wildfire fighting resources such that losses are kept to a minimum. The optimization procedure includes discrete simulation algorithms and Bayesian optimization methods for discrete and continuous problems (simulated annealing and Bayesian global optimization). Fast calculus algorithms are applied to provide optimization outcomes in short periods of time such that the predictions of the model and the real behavior of the fire, combat resources, and meteorological conditions are similar. In addition, adaptive algorithms take into account the chaotic behavior of wildfire so that the system can be updated with data corresponding to the real situation to obtain a new optimum solution. The application of this method to the Northwest Forest of Madrid (Spain) is also described. This application allowed us to check that it is a helpful tool in the decision-making process.

Optimization of the Resources Management in Fighting Wildfires

NASA Astrophysics Data System (ADS)

Martin-Fernández, Susana; Martínez-Falero, Eugenio; Pérez-González, J. Manuel

2002-09-01

Wildfires lead to important economic, social, and environmental losses, especially in areas of Mediterranean climate where they are of a high intensity and frequency. Over the past 30 years there has been a dramatic surge in the development and use of fire spread models. However, given the chaotic nature of environmental systems, it is very difficult to develop real-time fire-extinguishing models. This article proposes a method of optimizing the performance of wildfire fighting resources such that losses are kept to a minimum. The optimization procedure includes discrete simulation algorithms and Bayesian optimization methods for discrete and continuous problems (simulated annealing and Bayesian global optimization). Fast calculus algorithms are applied to provide optimization outcomes in short periods of time such that the predictions of the model and the real behavior of the fire, combat resources, and meteorological conditions are similar. In addition, adaptive algorithms take into account the chaotic behavior of wildfire so that the system can be updated with data corresponding to the real situation to obtain a new optimum solution. The application of this method to the Northwest Forest of Madrid (Spain) is also described. This application allowed us to check that it is a helpful tool in the decision-making process.

How to optimize the economic viability of thyroid surgery in a French public hospital?

PubMed

D'Hubert, E; Proske, J-M

2010-08-01

Physicians in France have been asked to change their day-to-day medical practice to reduce overall costs. We examine ways to achieve this goal in thyroid surgery. We defined and implemented a clinical pathway to optimize the economic viability of thyroid surgery by increasing revenues and lowering expenses. An increase in revenue was achieved by decreasing patient length of stay (LOS) through the use of a fast-track rehabilitation protocol. Expenses were decreased by performing all pre-operative work-up in the out-patient setting and by decreasing costs in the operating room. For 292 consecutive patients who underwent thyroidectomy, the average LOS has been decreased over time to a mean of 2.03 days in 2008; 96% of patients were discharged on the first postoperative day. These results were primarily achieved by using a fast-track rehabilitation clinical pathway, and no increase in postoperative morbidity was noted. Operating time was decreased by 20% through the use of a second surgical assistant and hemostatic scissors but this improvement did not translate into better daily utilization of the operating room. The economic profitability of thyroid surgery is improved when mean LOS is reduced to 2 days through a fast-track protocol. Decreasing the duration of hospitalization was more effective than decreasing operative duration in controlling overall costs. Copyright © 2010 Elsevier Masson SAS. All rights reserved.

Particle swarm optimization with recombination and dynamic linkage discovery.

PubMed

Chen, Ying-Ping; Peng, Wen-Chih; Jian, Ming-Chung

2007-12-01

In this paper, we try to improve the performance of the particle swarm optimizer by incorporating the linkage concept, which is an essential mechanism in genetic algorithms, and design a new linkage identification technique called dynamic linkage discovery to address the linkage problem in real-parameter optimization problems. Dynamic linkage discovery is a costless and effective linkage recognition technique that adapts the linkage configuration by employing only the selection operator without extra judging criteria irrelevant to the objective function. Moreover, a recombination operator that utilizes the discovered linkage configuration to promote the cooperation of particle swarm optimizer and dynamic linkage discovery is accordingly developed. By integrating the particle swarm optimizer, dynamic linkage discovery, and recombination operator, we propose a new hybridization of optimization methodologies called particle swarm optimization with recombination and dynamic linkage discovery (PSO-RDL). In order to study the capability of PSO-RDL, numerical experiments were conducted on a set of benchmark functions as well as on an important real-world application. The benchmark functions used in this paper were proposed in the 2005 Institute of Electrical and Electronics Engineers Congress on Evolutionary Computation. The experimental results on the benchmark functions indicate that PSO-RDL can provide a level of performance comparable to that given by other advanced optimization techniques. In addition to the benchmark, PSO-RDL was also used to solve the economic dispatch (ED) problem for power systems, which is a real-world problem and highly constrained. The results indicate that PSO-RDL can successfully solve the ED problem for the three-unit power system and obtain the currently known best solution for the 40-unit system.

Exploring the optimal economic timing for crop tree release treatments in hardwoods: results from simulation

Treesearch

Chris B. LeDoux; Gary W. Miller

2008-01-01

In this study we used data from 16 Appalachian hardwood stands, a growth and yield computer simulation model, and stump-to-mill logging cost-estimating software to evaluate the optimal economic timing of crop tree release (CTR) treatments. The simulated CTR treatments consisted of one-time logging operations at stand age 11, 23, 31, or 36 years, with the residual...

Environmental and economic evaluation of selective non-catalytic reduction of nitrogen oxides

NASA Astrophysics Data System (ADS)

Parchevskii, V. M.; Shchederkina, T. E.; Proshina, A. O.

2017-11-01

There are two groups of atmosphere protecting measures: technology (primary) and treatment (secondary). When burning high-calorie low-volatile brands of coals in the furnaces with liquid slag removal to achieve emission standards required joint use of these two methods, for example, staged combustion and selective non-catalytic reduction recovery (SNCR). For the economically intelligent combination of these two methods it is necessary to have information not only about the environmental performance of each method, but also the operating costs per unit of reduced emission. The authors of this report are made an environmental-economic analysis of SNCR on boiler Π-50P Kashirskaya power station. The obtained results about the dependence of costs from the load of the boiler and the mass emissions of nitrogen oxides then approximates into empirical formulas, is named as environmental and economic characteristics, which is suitable for downloading into controllers and other control devices for subsequent implementation of optimal control of emissions to ensure compliance with environmental regulations at the lowest cost at any load of the boiler.

Economic assessment and optimal operation of CSP systems with TES in California electricity markets

NASA Astrophysics Data System (ADS)

Dowling, Alexander W.; Dyreson, Ana; Miller, Franklin; Zavala, Victor M.

2017-06-01

The economics and performance of concentrated power (CSP) systems with thermal energy storage (TES) inherently depend on operating policies and the surrounding weather conditions and electricity markets. We present an integrated economic assessment framework to quantify the maximum possible revenues from simultaneous energy and ancillary services sales by CSP systems. The framework includes both discrete start-up/shutdown restrictions and detailed physical models. Analysis of coinci-dental historical market and meteorological data reveals provision of ancillary services increases market revenue 18% to 37% relative to energy-only participation. Surprisingly, only 53% to 62% of these revenues are available through sole participation in the day-ahead market, indicating significant opportunities at faster timescales. Motivated by water-usage concerns and permitting requirements, we also describe a new nighttime radiative-enhanced dry-cooling system with cold-side storage that consumes no water and offers higher effciencies than traditional air-cooled designs. Operation of this new system is complicated by the cold-side storage and inherent coupling between the cooling system and power plant, further motivating integrated economic analysis.

Game Theory and Risk-Based Levee System Design

NASA Astrophysics Data System (ADS)

Hui, R.; Lund, J. R.; Madani, K.

2014-12-01

Risk-based analysis has been developed for optimal levee design for economic efficiency. Along many rivers, two levees on opposite riverbanks act as a simple levee system. Being rational and self-interested, land owners on each river bank would tend to independently optimize their levees with risk-based analysis, resulting in a Pareto-inefficient levee system design from the social planner's perspective. Game theory is applied in this study to analyze decision making process in a simple levee system in which the land owners on each river bank develop their design strategies using risk-based economic optimization. For each land owner, the annual expected total cost includes expected annual damage cost and annualized construction cost. The non-cooperative Nash equilibrium is identified and compared to the social planner's optimal distribution of flood risk and damage cost throughout the system which results in the minimum total flood cost for the system. The social planner's optimal solution is not feasible without appropriate level of compensation for the transferred flood risk to guarantee and improve conditions for all parties. Therefore, cooperative game theory is then employed to develop an economically optimal design that can be implemented in practice. By examining the game in the reversible and irreversible decision making modes, the cost of decision making myopia is calculated to underline the significance of considering the externalities and evolution path of dynamic water resource problems for optimal decision making.

Network models for solving the problem of multicriterial adaptive optimization of investment projects control with several acceptable technologies

NASA Astrophysics Data System (ADS)

Shorikov, A. F.; Butsenko, E. V.

2017-10-01

This paper discusses the problem of multicriterial adaptive optimization the control of investment projects in the presence of several technologies. On the basis of network modeling proposed a new economic and mathematical model and a method for solving the problem of multicriterial adaptive optimization the control of investment projects in the presence of several technologies. Network economic and mathematical modeling allows you to determine the optimal time and calendar schedule for the implementation of the investment project and serves as an instrument to increase the economic potential and competitiveness of the enterprise. On a meaningful practical example, the processes of forming network models are shown, including the definition of the sequence of actions of a particular investment projecting process, the network-based work schedules are constructed. The calculation of the parameters of network models is carried out. Optimal (critical) paths have been formed and the optimal time for implementing the chosen technologies of the investment project has been calculated. It also shows the selection of the optimal technology from a set of possible technologies for project implementation, taking into account the time and cost of the work. The proposed model and method for solving the problem of managing investment projects can serve as a basis for the development, creation and application of appropriate computer information systems to support the adoption of managerial decisions by business people.

Geographical determination of an optimal network of landing sites for Hermes

NASA Astrophysics Data System (ADS)

Goester, J. F.

Once its mission is done, Hermès will perform a deorbit burn, then will pilot towards a specially equipped landing site. As the atmospheric re-entry corridor is limited (the maximum cross range is 1500 km) Hermès will have to be situated on or-bits going near the runway. For safety reasons, we need to get one return opportunity per revolution, so it may be necessary to consider several landing sites and to fit out them. This proposed method allows to find, with easiness and quickness, the geographic areas getting the optimal solutions in term of number of runways, solutions amongst which we will choose already existing sites, checking other meteorologic, politic and economic constraints.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baone, Chaitanya; Acharya, Naresh; Wiegman, Herman

As microgrid installations are steadily growing in the United States and around the world, widespread adoption of commercial microgrids would rely upon the economic benefit to the owners and operators. With the introduction of new market mechanisms and growing penetration of non-traditional generation assets, there is an increasing need and interest in allowing distributed assets to participate in traditional grid services such as frequency regulation. This paper considers the problem of determining the optimal balance of energy and ancillary services for individual microgrid generation assets to participate in such markets. An optimization framework that maximizes the predicted performance of themore » microgrid over a day-ahead time horizon while accounting for individual asset constraints is proposed. Simulation results on a realistic test system with practical considerations are presented.« less

Economic Optimization Analysis of Chengdu Electric Community Bus Operation

NASA Astrophysics Data System (ADS)

Yidong, Wang; Yun, Cai; Zhengping, Tan; Xiong, Wan

2018-03-01

In recent years, the government has strongly supported and promoted electric vehicles and has given priority to demonstration and popularization in the field of public transport. The economy of public transport operations has drawn increasing attention. In this paper, Chengdu wireless charging pure electric community bus is used as the research object, the battery, air conditioning, driver’s driving behavior and other economic influence factors were analyzed, and optimizing the operation plan through case data analysis, through the reasonable battery matching and mode of operation to help businesses effectively save operating costs and enhance economic efficiency.

The Optimization dispatching of Micro Grid Considering Load Control

NASA Astrophysics Data System (ADS)

Zhang, Pengfei; Xie, Jiqiang; Yang, Xiu; He, Hongli

2018-01-01

This paper proposes an optimization control of micro-grid system economy operation model. It coordinates the new energy and storage operation with diesel generator output, so as to achieve the economic operation purpose of micro-grid. In this paper, the micro-grid network economic operation model is transformed into mixed integer programming problem, which is solved by the mature commercial software, and the new model is proved to be economical, and the load control strategy can reduce the charge and discharge times of energy storage devices, and extend the service life of the energy storage device to a certain extent.

Links between economic and financial theory in graduate health administration education.

PubMed

Pink, G H; Coyte, P C

1989-01-01

The curricula of graduate health administration programs have, historically, not articulated the theoretical links between health economics and health finance, although an understanding of these links could enhance comprehension of both disciplines. We provide a pedagogical approach that can be used to clarify these interconnections. It compares the standard neoclassical microeconomic concept of the hospital with the financial concept of the hospital, for the purpose of relating the optimal output decision in microeconomic theory to the optimal investment decision in financial theory. This approach can be taught in an advanced course in either economics or finance.

The economics of project analysis: Optimal investment criteria and methods of study

NASA Technical Reports Server (NTRS)

Scriven, M. C.

1979-01-01

Insight is provided toward the development of an optimal program for investment analysis of project proposals offering commercial potential and its components. This involves a critique of economic investment criteria viewed in relation to requirements of engineering economy analysis. An outline for a systems approach to project analysis is given Application of the Leontief input-output methodology to analysis of projects involving multiple processes and products is investigated. Effective application of elements of neoclassical economic theory to investment analysis of project components is demonstrated. Patterns of both static and dynamic activity levels are incorporated.

Grassland biodiversity can pay.

PubMed

Binder, Seth; Isbell, Forest; Polasky, Stephen; Catford, Jane A; Tilman, David

2018-04-10

The biodiversity-ecosystem functioning (BEF) literature provides strong evidence of the biophysical basis for the potential profitability of greater diversity but does not address questions of optimal management. BEF studies typically focus on the ecosystem outputs produced by randomly assembled communities that only differ in their biodiversity levels, measured by indices such as species richness. Landholders, however, do not randomly select species to plant; they choose particular species that collectively maximize profits. As such, their interest is not in comparing the average performance of randomly assembled communities at each level of biodiversity but rather comparing the best-performing communities at each diversity level. Assessing the best-performing mixture requires detailed accounting of species' identities and relative abundances. It also requires accounting for the financial cost of individual species' seeds, and the economic value of changes in the quality, quantity, and variability of the species' collective output-something that existing multifunctionality indices fail to do. This study presents an assessment approach that integrates the relevant factors into a single, coherent framework. It uses ecological production functions to inform an economic model consistent with the utility-maximizing decisions of a potentially risk-averse private landowner. We demonstrate the salience and applicability of the framework using data from an experimental grassland to estimate production relationships for hay and carbon storage. For that case, our results suggest that even a risk-neutral, profit-maximizing landowner would favor a highly diverse mix of species, with optimal species richness falling between the low levels currently found in commercial grasslands and the high levels found in natural grasslands.

A Statistical Analysis of the Economic Drivers of Battery Energy Storage in Commercial Buildings: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Long, Matthew; Simpkins, Travis; Cutler, Dylan

There is significant interest in using battery energy storage systems (BESS) to reduce peak demand charges, and therefore the life cycle cost of electricity, in commercial buildings. This paper explores the drivers of economic viability of BESS in commercial buildings through statistical analysis. A sample population of buildings was generated, a techno-economic optimization model was used to size and dispatch the BESS, and the resulting optimal BESS sizes were analyzed for relevant predictor variables. Explanatory regression analyses were used to demonstrate that peak demand charges are the most significant predictor of an economically viable battery, and that the shape ofmore » the load profile is the most significant predictor of the size of the battery.« less

A Statistical Analysis of the Economic Drivers of Battery Energy Storage in Commercial Buildings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Long, Matthew; Simpkins, Travis; Cutler, Dylan

There is significant interest in using battery energy storage systems (BESS) to reduce peak demand charges, and therefore the life cycle cost of electricity, in commercial buildings. This paper explores the drivers of economic viability of BESS in commercial buildings through statistical analysis. A sample population of buildings was generated, a techno-economic optimization model was used to size and dispatch the BESS, and the resulting optimal BESS sizes were analyzed for relevant predictor variables. Explanatory regression analyses were used to demonstrate that peak demand charges are the most significant predictor of an economically viable battery, and that the shape ofmore » the load profile is the most significant predictor of the size of the battery.« less

[Medico-economic evaluation of therapeutic strategies at hospital: A systematic review of French studies].

PubMed

Baudouin, A; Armoiry, X; Dussart, C

2017-05-01

Therapeutic innovation contributes to the increase of health care expenditures in France. Medico-economic evaluation has still a minor role in the decision-making for the registration of drugs and medical devices in hospitals. This study aimed to systematically review published works on medico-economic studies conducted within French hospitals. A literature review was carried out to search for medico-economic studies conducted by hospital teams on therapeutic or diagnostic strategies employed within French hospitals and published from 2010 to 2014. Quality assessment of selected studies was performed according to Drummond et al.'s checklist, which is also used within French guidelines. Of the 44 analyzed articles, methods for identification and measure of costs and results complied with guidelines in 95 % of cases. For results interpretation, compliance was 91 %. Costs discounting (29 %) and the use of sensitivity analysis to account for results uncertainty (70 %) were the parameters with the lowest compliance to guidelines. A good training of health professionals in using economic and statistic tools, and the transferability of results of medico-economic studies are essential and should be optimized to enable a broader use of medico-economic evaluation within the scope of decision-making in French hospitals. Copyright © 2016 Académie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights reserved.

Sensitivity of California water supply to changes in runoff magnitude and timing: A bottom-up assessment of vulnerabilities and adaptation strategies

NASA Astrophysics Data System (ADS)

Fefer, M.; Dogan, M. S.; Herman, J. D.

2017-12-01

Long-term shifts in the timing and magnitude of reservoir inflows will potentially have significant impacts on water supply reliability in California, though projections remain uncertain. Here we assess the vulnerability of the statewide system to changes in total annual runoff (a function of precipitation) and the fraction of runoff occurring during the winter months (primarily a function of temperature). An ensemble of scenarios is sampled using a bottom-up approach and compared to the most recent available streamflow projections from the state's 4th Climate Assessment. We evaluate these scenarios using a new open-source version of the CALVIN model, a network flow optimization model encompassing roughly 90% of the urban and agricultural water demands in California, which is capable of running scenario ensembles on a high-performance computing cluster. The economic representation of water demand in the model yields several advantages for this type of analysis: optimized reservoir operating policies to minimize shortage cost and the marginal value of adaptation opportunities, defined by shadow prices on infrastructure and regulatory constraints. Results indicate a shift in optimal reservoir operations and high marginal value of additional reservoir storage in the winter months. The collaborative management of reservoirs in CALVIN yields increased storage in downstream reservoirs to store the increased winter runoff. This study contributes an ensemble evaluation of a large-scale network model to investigate uncertain climate projections, and an approach to interpret the results of economic optimization through the lens of long-term adaptation strategies.

The Linear Quadratic Gaussian Multistage Game with Nonclassical Information Pattern Using a Direct Solution Method

NASA Astrophysics Data System (ADS)

Clemens, Joshua William

Game theory has application across multiple fields, spanning from economic strategy to optimal control of an aircraft and missile on an intercept trajectory. The idea of game theory is fascinating in that we can actually mathematically model real-world scenarios and determine optimal decision making. It may not always be easy to mathematically model certain real-world scenarios, nonetheless, game theory gives us an appreciation for the complexity involved in decision making. This complexity is especially apparent when the players involved have access to different information upon which to base their decision making (a nonclassical information pattern). Here we will focus on the class of adversarial two-player games (sometimes referred to as pursuit-evasion games) with nonclassical information pattern. We present a two-sided (simultaneous) optimization solution method for the two-player linear quadratic Gaussian (LQG) multistage game. This direct solution method allows for further interpretation of each player's decision making (strategy) as compared to previously used formal solution methods. In addition to the optimal control strategies, we present a saddle point proof and we derive an expression for the optimal performance index value. We provide some numerical results in order to further interpret the optimal control strategies and to highlight real-world application of this game-theoretic optimal solution.

Kate Anderson | NREL

Science.gov Websites

private entities with techno-economic modeling and analysis, field assessments, design, and implementation Force. Research Interests Energy optimization Techno-economic modeling Value of resiliency Solar+storage -Resilient Solar Project: Economic and Resiliency Impact of PV and Storage on New York Critical

Economics in the School Curriculum.

ERIC Educational Resources Information Center

Brenneke, Judith Staley; Soper, John C.

1987-01-01

Various approaches to developing and implementing economics curricula are explored, including positive and normative economics, teacher-developed informal curriculum, district-developed formal curriculum, "outside" curriculum, the infusion approach, or as a separate course. It is suggested that a "blend" of the alternatives may optimize the…

Spatial and Temporal Self-Calibration of a Hydroeconomic Model

NASA Astrophysics Data System (ADS)

Howitt, R. E.; Hansen, K. M.

2008-12-01

Hydroeconomic modeling of water systems where risk and reliability of water supply are of critical importance must address explicitly how to model water supply uncertainty. When large fluctuations in annual precipitation and significant variation in flows by location are present, a model which solves with perfect foresight of future water conditions may be inappropriate for some policy and research questions. We construct a simulation-optimization model with limited foresight of future water conditions using positive mathematical programming and self-calibration techniques. This limited foresight netflow (LFN) model signals the value of storing water for future use and reflects a more accurate economic value of water at key locations, given that future water conditions are unknown. Failure to explicitly model this uncertainty could lead to undervaluation of storage infrastructure and contractual mechanisms for managing water supply risk. A model based on sequentially updated information is more realistic, since water managers make annual storage decisions without knowledge of yet to be realized future water conditions. The LFN model runs historical hydrological conditions through the current configuration of the California water system to determine the economically efficient allocation of water under current economic conditions and infrastructure. The model utilizes current urban and agricultural demands, storage and conveyance infrastructure, and the state's hydrological history to indicate the scarcity value of water at key locations within the state. Further, the temporal calibration penalty functions vary by year type, reflecting agricultural water users' ability to alter cropping patterns in response to water conditions. The model employs techniques from positive mathematical programming (Howitt, 1995; Howitt, 1998; Cai and Wang, 2006) to generate penalty functions that are applied to deviations from observed data. The functions are applied to monthly flows across key nodes on the network and to annual carryover storage at ground and surface water storage facilities. To our knowledge, this is the first hydroeconomic model to perform spatial and temporal calibration simultaneously. The base for the LFN model is CALVIN, a hydroeconomic optimization model of the California water system developed at the University of California, Davis (Draper, et al. 2003). The LFN model, programmed in GAMS, is nonlinear, which permits incorporation of dynamic groundwater pumping costs that reflect head elevation. Hydropower production, also nonlinear in storage levels, could be added in the future. In this paper, we describe model implementation and performance over a sequence of water years drawn from the historical hydrologic record in California. Preliminary findings indicate that calibration occurs within acceptable limits and simulations replicate base case results well. Cai, X., and Wang, D. 2006. "Calibrating Holistic Water Resources-Economic Models." Journal of Water Resources Planning and Management November-December. Draper, A.J., M.W. Jenkins, K.W. Kirby, J.R. Lund, and R.E. Howitt. 2003. "Economic-Engineering Optimization for California Water Management." Journal of Water Resources Planning and Management 129(3):155-164. Howitt, R.E. 1995. "Positive Mathematical Programming." American Journal of Agricultural Economics 77:329-342. Howitt, R.E. 1998. "Self-Calibrating Network Flow Models." Working Paper, Department of Agricultural and Resource Economics, University of California, Davis. October 1998. class="ab'>

Perfection Of Methods Of Mathematical Analysis For Increasing The Completeness Of Subsoil Development

NASA Astrophysics Data System (ADS)

Fokina, Mariya

2017-11-01

The economy of Russia is based around the mineral-raw material complex to the highest degree. The mining industry is a prioritized and important area. Given the high competitiveness of businesses in this sector, increasing the efficiency of completed work and manufactured products will become a central issue. Improvement of planning and management in this sector should be based on multivariant study and the optimization of planning decisions, the appraisal of their immediate and long-term results, taking the dynamic of economic development into account. All of this requires the use of economic mathematic models and methodsApplying an economic-mathematic model to determine optimal ore mine production capacity, we receive a figure of 4,712,000 tons. The production capacity of the Uchalinsky ore mine is 1560 thousand tons, and the Uzelginsky ore mine - 3650 thousand. Conducting a corresponding analysis of the production of OAO "Uchalinsky Gok", an optimal production plan was received: the optimal production of copper - 77961,4 rubles; the optimal production of zinc - 17975.66 rubles. The residual production volume of the two main ore mines of OAO "UGOK" is 160 million tons of ore.

Optimal planning for the sustainable utilization of municipal solid waste.

PubMed

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

2013-12-01

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

Climate change mitigation: comparative assessment of Malaysian and ASEAN scenarios.

PubMed

Rasiah, Rajah; Ahmed, Adeel; Al-Amin, Abul Quasem; Chenayah, Santha

2017-01-01

This paper analyses empirically the optimal climate change mitigation policy of Malaysia with the business as usual scenario of ASEAN to compare their environmental and economic consequences over the period 2010-2110. A downscaling empirical dynamic model is constructed using a dual multidisciplinary framework combining economic, earth science, and ecological variables to analyse the long-run consequences. The model takes account of climatic variables, including carbon cycle, carbon emission, climatic damage, carbon control, carbon concentration, and temperature. The results indicate that without optimal climate policy and action, the cumulative cost of climate damage for Malaysia and ASEAN as a whole over the period 2010-2110 would be MYR40.1 trillion and MYR151.0 trillion, respectively. Under the optimal policy, the cumulative cost of climatic damage for Malaysia would fall to MYR5.3 trillion over the 100 years. Also, the additional economic output of Malaysia will rise from MYR2.1 billion in 2010 to MYR3.6 billion in 2050 and MYR5.5 billion in 2110 under the optimal climate change mitigation scenario. The additional economic output for ASEAN would fall from MYR8.1 billion in 2010 to MYR3.2 billion in 2050 before rising again slightly to MYR4.7 billion in 2110 in the business as usual ASEAN scenario.

Progress Towards Highly Efficient Windows for Zero—Energy Buildings

NASA Astrophysics Data System (ADS)

Selkowitz, Stephen

2008-09-01

Energy efficient windows could save 4 quads/year, with an additional 1 quad/year gain from daylighting in commercial buildings. This corresponds to 13% of energy used by US buildings and 5% of all energy used by the US. The technical potential is thus very large and the economic potential is slowly becoming a reality. This paper describes the progress in energy efficient windows that employ low-emissivity glazing, electrochromic switchable coatings and other novel materials. Dynamic systems are being developed that use sensors and controls to modulate daylighting and shading contributions in response to occupancy, comfort and energy needs. Improving the energy performance of windows involves physics in a variety of application: optics, heat transfer, materials science and applied engineering. Technical solutions must also be compatible with national policy, codes and standards, economics, business practice and investment, real and perceived risks, comfort, health, safety, productivity, amenities, and occupant preference and values. The challenge is to optimize energy performance by understanding and reinforcing the synergetic coupling between these many issues.

Implementing economic evaluation in simulation-based medical education: challenges and opportunities.

PubMed

Lin, Yiqun; Cheng, Adam; Hecker, Kent; Grant, Vincent; Currie, Gillian R

2018-02-01

Simulation-based medical education (SBME) is now ubiquitous at all levels of medical training. Given the substantial resources needed for SBME, economic evaluation of simulation-based programmes or curricula is required to demonstrate whether improvement in trainee performance (knowledge, skills and attitudes) and health outcomes justifies the cost of investment. Current literature evaluating SBME fails to provide consistent and interpretable information on the relative costs and benefits of alternatives. Economic evaluation is widely applied in health care, but is relatively scarce in medical education. Therefore, in this paper, using a focus on SBME, we define economic evaluation, describe the key components, and discuss the challenges associated with conducting an economic evaluation of medical education interventions. As a way forward to the rigorous and state of the art application of economic evaluation in medical education, we outline the steps to gather the necessary information to conduct an economic evaluation of simulation-based education programmes and curricula, and describe the main approaches to conducting an economic evaluation. A properly conducted economic evaluation can help stakeholders (i.e., programme directors, policy makers and curriculum designers) to determine the optimal use of resources in selecting the modality or method of assessment in simulation. It also helps inform broader decision making about allocation of scarce resources within an educational programme, as well as between education and clinical care. Economic evaluation in medical education research is still in its infancy, and there is significant potential for state-of-the-art application of these methods in this area. © 2017 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

Paying the right price for pharmaceuticals: a case study of why the comparator matters.

PubMed

Spinks, Jean M; Richardson, Jeff R J

2011-08-01

This article considers the pricing policy for pharmaceuticals in Australia, which is widely seen as having achieved low drug prices. However, compared to New Zealand, the evidence implies that Australia might have improved its performance significantly if it had proactively sought market best pricing. The Australian record suggests that the information sought by authorities may not be sufficient for optimal pricing and that the economic evaluation of pharmaceuticals may be neither necessary nor sufficient for achieving this goal.

Considerations with respect to the design of solar photovoltaic power systems for terrestrial applications

NASA Technical Reports Server (NTRS)

Berman, P. A.

1972-01-01

The various factors involved in the development of solar photovoltaic power systems for terrestrial application are discussed. The discussion covers the tradeoffs, compromises, and optimization studies which must be performed in order to develop a viable terrestrial solar array system. It is concluded that the technology now exists for the fabrication of terrestrial solar arrays but that the economics are prohibitive. Various approaches to cost reduction are presented, and the general requirements for materials and processes to be used are delineated.

Plasma-Enabled Carbon Nanostructures for Early Diagnosis of Neurodegenerative Diseases

PubMed Central

Pineda, Shafique; Han, Zhao Jun; Ostrikov, Kostya (Ken)

2014-01-01

Carbon nanostructures (CNs) are amongst the most promising biorecognition nanomaterials due to their unprecedented optical, electrical and structural properties. As such, CNs may be harnessed to tackle the detrimental public health and socio-economic adversities associated with neurodegenerative diseases (NDs). In particular, CNs may be tailored for a specific determination of biomarkers indicative of NDs. However, the realization of such a biosensor represents a significant technological challenge in the uniform fabrication of CNs with outstanding qualities in order to facilitate a highly-sensitive detection of biomarkers suspended in complex biological environments. Notably, the versatility of plasma-based techniques for the synthesis and surface modification of CNs may be embraced to optimize the biorecognition performance and capabilities. This review surveys the recent advances in CN-based biosensors, and highlights the benefits of plasma-processing techniques to enable, enhance, and tailor the performance and optimize the fabrication of CNs, towards the construction of biosensors with unparalleled performance for the early diagnosis of NDs, via a plethora of energy-efficient, environmentally-benign, and inexpensive approaches. PMID:28788112

Counterfactual quantum cloning without transmitting any physical particles

NASA Astrophysics Data System (ADS)

Guo, Qi; Zhai, Shuqin; Cheng, Liu-Yong; Wang, Hong-Fu; Zhang, Shou

2017-11-01

We propose a counterfactual 1 →2 economical phase-covariant cloning scheme. Compared with the existing protocols using flying qubits, the main difference of the presented scheme is that the cloning can be achieved without transmitting the photon between the two parties. In addition, this counterfactual scheme does not need to construct controlled quantum gates to perform joint logical operations between the cloned qubit and the blank copy. We also numerically evaluate the performance of the present scheme in the practical experiment, which shows this cloning scheme can be implemented with a high success of probability and the fidelity is close to the optimal value in the ideal asymptotic limit.

Optimal design of a for middle-low-speed maglev trains

NASA Astrophysics Data System (ADS)

Xiao, Song; Zhang, Kunlun; Liu, Guoqing; Jing, Yongzhi; Sykulski, Jan K.

2018-04-01

A middle-low-speed maglev train is supported by an electromagnetic force between the suspension electromagnet (EM) and the steel rail and is driven by a linear induction motor. The capability of the suspension system has a direct bearing on safety and the technical and economic performance of the train. This paper focuses on the dependence of the electromagnetic force on the structural configuration of the EM with the purpose of improving performance of a conventional EM. Finally, a novel configuration is proposed of a hybrid suspension magnet, which combines permanent magnets and coils, in order to increase the suspension force while reducing the suspension power loss.

Modelling the interaction between flooding events and economic growth

NASA Astrophysics Data System (ADS)

Grames, J.; Prskawetz, A.; Grass, D.; Blöschl, G.

2015-06-01

Socio-hydrology describes the interaction between the socio-economy and water. Recent models analyze the interplay of community risk-coping culture, flooding damage and economic growth (Di Baldassarre et al., 2013; Viglione et al., 2014). These models descriptively explain the feedbacks between socio-economic development and natural disasters like floods. Contrary to these descriptive models, our approach develops an optimization model, where the intertemporal decision of an economic agent interacts with the hydrological system. In order to build this first economic growth model describing the interaction between the consumption and investment decisions of an economic agent and the occurrence of flooding events, we transform an existing descriptive stochastic model into an optimal deterministic model. The intermediate step is to formulate and simulate a descriptive deterministic model. We develop a periodic water function to approximate the former discrete stochastic time series of rainfall events. Due to the non-autonomous exogenous periodic rainfall function the long-term path of consumption and investment will be periodic.

Are there common mathematical structures in economics and physics?

NASA Astrophysics Data System (ADS)

Mimkes, Jürgen

2016-12-01

Economics is a field that looks into the future. We may know a few things ahead (ex ante), but most things we only know, afterwards (ex post). How can we work in a field, where much of the important information is missing? Mathematics gives two answers: 1. Probability theory leads to microeconomics: the Lagrange function optimizes utility under constraints of economic terms (like costs). The utility function is the entropy, the logarithm of probability. The optimal result is given by a probability distribution and an integrating factor. 2. Calculus leads to macroeconomics: In economics we have two production factors, capital and labour. This requires two dimensional calculus with exact and not-exact differentials, which represent the "ex ante" and "ex post" terms of economics. An integrating factor turns a not-exact term (like income) into an exact term (entropy, the natural production function). The integrating factor is the same as in microeconomics and turns the not-exact field of economics into an exact physical science.

The Conference Proceedings of the 1998 Air Transport Research Group (ATRG) of the WCTR Society. Volume 2

NASA Technical Reports Server (NTRS)

Oum, Tae Hoon (Editor); Bowen, Brent D. (Editor)

1998-01-01

Contents include the following: Airport choice in a multiple airport region: an empirical analysis for the San Francisco bay area. Liberalization of the westeuropian aviation: choice of a new hub airport for an airline. Austin Bergstrom airport traffic control tower establishment of a major activity level tower. A study to optimize the environmental capacity of Amsterdam airport schiphol.Airport performance in stakeholder involvement and communication strategies: a comparison of major Australian and North American air carrier and general aviation airports. Airport planning and location.Location of international airport and regional development. A simulation technique for analysis of Brasilian airport passanger terminal building.Multimodal airport access in Japan. Planning surface access provision at major airports Airline economics and the inclusion of environmental costs on airport hub pricing: a theoretical analysis. Airport financing and user charge systems in the USA. Optimal demand for operating lease of aircraft. Aircraft leasing industry and social welfare.The development of performance indicators for airports: a management perspective. Study about operational effect of the "security check-in" implantation in Brasilian international airports.Austin Bergstrom west loop cable system.and Optimal resource allocation model for airport passanger terminals.

Synthesis of optimal usage of available aggregates in highway construction and maintenance.

DOT National Transportation Integrated Search

2009-11-01

The optimization of available aggregates for highway construction and maintenance is vital both from an economic and environmental perspective. By not optimizing the aggregate supply, project costs escalate as a simple response to supply and demand. ...

Wind Energy Conference, Boulder, Colo., April 9-11, 1980, Technical Papers

NASA Astrophysics Data System (ADS)

1980-03-01

Papers are presented concerning the technology, and economics of wind energy conversion systems. Specific topics include the aerodynamic analysis of the Darrieus rotor, the numerical calculation of the flow near horizontal-axis wind turbine rotors, the calculation of dynamic wind turbine rotor loads, markets for wind energy systems, an oscillating-wing windmill, wind tunnel tests of wind rotors, wind turbine generator wakes, the application of a multi-speed electrical generator to wind turbines, the feasibility of wind-powered systems for dairy farms, and wind characteristics over uniform and complex terrain. Attention is also given to performance tests of the DOE/NASA MOD-1 2000-kW wind turbine generator, the assessment of utility-related test data, offshore wind energy conversion systems, and the optimization of wind energy utilization economics through load management.

Optimization of antireflection coating design for multijunction solar cells and concentrator systems

NASA Astrophysics Data System (ADS)

Valdivia, Christopher E.; Desfonds, Eric; Masson, Denis; Fafard, Simon; Carlson, Andrew; Cook, John; Hall, Trevor J.; Hinzer, Karin

2008-06-01

Photovoltaic solar cells are a route towards local, environmentally benign, sustainable and affordable energy solutions. Antireflection coatings are necessary to input a high percentage of available light for photovoltaic conversion, and therefore have been widely exploited for silicon solar cells. Multi-junction III-V semiconductor solar cells have achieved the highest efficiencies of any photovoltaic technology, yielding up to 40% in the laboratory and 37% in commercial devices under varying levels of concentrated light. These devices benefit from a wide absorption spectrum (300- 1800 nm), but this also introduces significant challenges for antireflection coating design. Each sub-cell junction is electrically connected in series, limiting the overall device photocurrent by the lowest current-producing junction. Therefore, antireflection coating optimization must maximize the current from the limiting sub-cells at the expense of the others. Solar concentration, necessary for economical terrestrial deployment of multi-junction solar cells, introduces an angular-dependent irradiance spectrum. Antireflection coatings are optimized for both direct normal incidence in air and angular incidence in an Opel Mk-I concentrator, resulting in as little as 1-2% loss in photocurrent as compared to an ideal zero-reflectance solar cell, showing a similar performance to antireflection coatings on silicon solar cells. A transparent conductive oxide layer has also been considered to replace the metallic-grid front electrode and for inclusion as part of a multi-layer antireflection coating. Optimization of the solar cell, antireflection coating, and concentrator system should be considered simultaneously to enable overall optimal device performance.

Near Zero Energy House (NZEH) Design Optimization to Improve Life Cycle Cost Performance Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

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.

[Valorisation of brachytherapy and medico-economic considerations].

PubMed

Pommier, P; Morelle, M; Millet-Lagarde, F; Peiffert, D; Gomez, F; Perrier, L

2013-04-01

Economic data in the literature for brachytherapy are still sparse and heterogeneous, with few controlled prospective studies and a perspective most often limited to those of the provider (health insurances). Moreover, these observation and conclusions are difficult to generalize in France. The prospective health economic studies performed in France in the framework of a national program to sustain innovative and costly therapies (STIC program) launched by the French cancer national institute are therefore of most importance. With the exception of prostate brachytherapy with permanent seeds, the valorisation of the brachytherapy activity by the French national health insurance does not take into account the degree of complexity and the real costs supported by health institutions (i.e. no specific valorisation for 3D image-based treatment planning and dose optimization and for the use of pulsed dose rate brachytherapy). Copyright © 2013 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

Techno-economic feasibility and life cycle assessment of dairy effluent to renewable diesel via hydrothermal liquefaction.

PubMed

Summers, Hailey M; Ledbetter, Rhesa N; McCurdy, Alex T; Morgan, Michael R; Seefeldt, Lance C; Jena, Umakanta; Hoekman, S Kent; Quinn, Jason C

2015-11-01

The economic feasibility and environmental impact is investigated for the conversion of agricultural waste, delactosed whey permeate, through yeast fermentation to a renewable diesel via hydrothermal liquefaction. Process feasibility was demonstrated at laboratory-scale with data leveraged to validate systems models used to perform industrial-scale economic and environmental impact analyses. Results show a minimum fuel selling price of $4.78 per gallon of renewable diesel, a net energy ratio of 0.81, and greenhouse gas emissions of 30.0g-CO2-eqMJ(-1). High production costs and greenhouse gas emissions can be attributed to operational temperatures and durations of both fermentation and hydrothermal liquefaction. However, high lipid yields of the yeast counter these operational demands, resulting in a favorable net energy ratio. Results are presented on the optimization of the process based on economy of scale and a sensitivity analysis highlights improvements in conversion efficiency, yeast biomass productivity and hydrotreating efficiency can dramatically improve commercial feasibility. Copyright © 2015 Elsevier Ltd. All rights reserved.

Eco-Efficiency Analysis of biotechnological processes.

PubMed

Saling, Peter

2005-07-01

Eco-Efficiency has been variously defined and analytically implemented by several workers. In most cases, Eco-Efficiency is taken to mean the ecological optimization of overall systems while not disregarding economic factors. Eco-Efficiency should increase the positive ecological performance of a commercial company in relation to economic value creation--or to reduce negative effects. Several companies use Eco-Efficiency Analysis for decision-making processes; and industrial examples of best practices in developing and implementing Eco-Efficiency have been reviewed. They clearly demonstrate the environmental and business benefits of Eco-Efficiency. An instrument for the early recognition and systematic detection of economic and environmental opportunities and risks for production processes in the chemical industry began use in 1997, since when different new features have been developed, leading to many examples. This powerful Eco-Efficiency Analysis allows a feasibility evaluation of existing and future business activities and is applied by BASF. In many cases, decision-makers are able to choose among alternative processes for making a product.

A Systematic Review of Economic Analysis of Surgical Mission Trips Using the World Health Organization Criteria.

PubMed

Nolte, Michael T; Maroukis, Brianna L; Chung, Kevin C; Mahmoudi, Elham

2016-08-01

Although the World Health Organization (WHO) has developed tools to standardize economic evaluations of global health interventions, little is known about the cost-effectiveness of surgical mission trips and their economic values. Our objective was to systematically evaluate the current literature on surgical volunteering trips to measure their adherence to WHO CHOosing Interventions that are cost-effective (WHO-CHOICE). We hypothesized that the majority of studies use some type of cost-effectiveness analysis that do not adhere to these standards. A systematic review of Pubmed, Medline, and Embase databases was performed in accordance with PRISMA guidelines, with inclusion criteria set a priori. Of the 908 publications screened, 72 were selected for full text review; 17 met inclusion criteria. Only 17 out of 72 studies reported some type of economic analysis. We categorized the studies into service, educational, and combination (service and educational) surgical trips. Although seven of the service studies calculated the cost per disability-adjusted life year averted, the results were not based on WHO-CHOICE standards to facilitate comparisons among alternative options. Furthermore, none of the three educational trips calculated the value of the education provided, but only published cost estimates of the resources used during the trip. Although a few studies performed some type of economic analysis, owing to their non-adherence to WHO-CHOICE standards, the results were not comparable to other studies. International surgical trips are expensive. To improve the efficacy and optimal use of limited resources, studies on surgical trips should follow the guidelines set by the WHO-CHOICE.

Modelling the interaction between flooding events and economic growth

NASA Astrophysics Data System (ADS)

Grames, Johanna; Grass, Dieter; Prskawetz, Alexia; Blöschl, Günther

2015-04-01

Socio-hydrology describes the interaction between the socio-economy, water and population dynamics. Recent models analyze the interplay of community risk-coping culture, flooding damage and economic growth (Di Baldassarre, 2013, Viglione, 2014). These models descriptively explain the feedbacks between socio-economic development and natural disasters like floods. Contrary to these descriptive models, our approach develops an optimization model, where the intertemporal decision of an economic agent interacts with the hydrological system. This is the first economic growth model describing the interaction between the consumption and investment decisions of an economic agent and the occurrence of flooding events: Investments in defense capital can avoid floods even when the water level is high, but on the other hand such investment competes with investment in productive capital and hence may reduce the level of consumption. When floods occur, the flood damage therefore depends on the existing defense capital. The aim is to find an optimal tradeoff between investments in productive versus defense capital such as to optimize the stream of consumption in the long-term. We assume a non-autonomous exogenous periodic rainfall function (Yevjevich et.al. 1990, Zakaria 2001) which implies that the long-term equilibrium will be periodic . With our model we aim to derive mechanisms that allow consumption smoothing in the long term, and at the same time allow for optimal investment in flood defense to maximize economic output. We choose an aggregate welfare function that depends on the consumption level of the society as the objective function. I.e. we assume a social planer with perfect foresight that maximizes the aggregate welfare function. Within our model framework we can also study whether the path and level of defense capital (that protects people from floods) is related to the time preference rate of the social planner. Our model also allows to investigate how the frequency and the intensity of floods influence the investment behavior (i.e. the division between investing in productive versus defense capital).

Concerning the electrosynthesis of hydrogen peroxide and peroxodisulfates. Section 2: Optimization of electrolysis cells using an electrolyzer for peroxodisulfuric acid as an example

NASA Technical Reports Server (NTRS)

Schleiff, M.; Thiele, W.; Matschiner, H.

1986-01-01

The model is presented of an electrolyzer for peroxodisulfuric acid, and it is analyzed mathematically. Its application for engineering and economic optimization is investigated in detail. The mathematical analysis leads to conclusions concerning the change in position of the optimum with respect to the various target functions due to changes of the individual design-caused and economic parameters.

Economic analysis of transmission line engineering based on industrial engineering

NASA Astrophysics Data System (ADS)

Li, Yixuan

2017-05-01

The modern industrial engineering is applied to the technical analysis and cost analysis of power transmission and transformation engineering. It can effectively reduce the cost of investment. First, the power transmission project is economically analyzed. Based on the feasibility study of power transmission and transformation project investment, the proposal on the company system cost management is put forward through the economic analysis of the effect of the system. The cost management system is optimized. Then, through the cost analysis of power transmission and transformation project, the new situation caused by the cost of construction is found. It is of guiding significance to further improve the cost management of power transmission and transformation project. Finally, according to the present situation of current power transmission project cost management, concrete measures to reduce the cost of power transmission project are given from the two aspects of system optimization and technology optimization.

Value function in economic growth model

NASA Astrophysics Data System (ADS)

Bagno, Alexander; Tarasyev, Alexandr A.; Tarasyev, Alexander M.

2017-11-01

Properties of the value function are examined in an infinite horizon optimal control problem with an unlimited integrand index appearing in the quality functional with a discount factor. Optimal control problems of such type describe solutions in models of economic growth. Necessary and sufficient conditions are derived to ensure that the value function satisfies the infinitesimal stability properties. It is proved that value function coincides with the minimax solution of the Hamilton-Jacobi equation. Description of the growth asymptotic behavior for the value function is provided for the logarithmic, power and exponential quality functionals and an example is given to illustrate construction of the value function in economic growth models.

The economics and timing of preoperative antibiotics for orthopaedic procedures.

PubMed

Norman, B A; Bartsch, S M; Duggan, A P; Rodrigues, M B; Stuckey, D R; Chen, A F; Lee, B Y

2013-12-01

The efficacy of antibiotics in preventing surgical site infections (SSIs) depends on the timing of administration relative to the start of surgery. However, currently, both the timing of and recommendations for administration vary substantially. To determine how the economic value from the hospital perspective of preoperative antibiotics varies with the timing of administration for orthopaedic procedures. Computational decision and operational models were developed from the hospital perspective. Baseline analyses looked at current timing of administration, while additional analyses varied the timing of administration, compliance with recommended guidelines, and the goal time-interval. Beginning antibiotic administration within 0-30 min prior to surgery resulted in the lowest costs and SSIs. Operationally, linking to a pre-surgical activity, administering antibiotics prior to incision but after anaesthesia-ready time was optimal, as 92.1% of the time, antibiotics were administered in the optimal time-interval (0-30 min prior to incision). Improving administration compliance from 80% to 90% for this pre-surgical activity results in cost savings of $447 per year for a hospital performing 100 orthopaedic operations a year. This study quantifies the potential cost-savings when antibiotic administration timing is improved, which in turn can guide the amount hospitals should invest to address this issue.

What is a hospital bed day worth? A contingent valuation study of hospital Chief Executive Officers.

PubMed

Page, Katie; Barnett, Adrain G; Graves, Nicholas

2017-02-14

Decreasing hospital length of stay, and so freeing up hospital beds, represents an important cost saving which is often used in economic evaluations. The savings need to be accurately quantified in order to make optimal health care resource allocation decisions. Traditionally the accounting cost of a bed is used. We argue instead that the economic cost of a bed day is the better value for making resource decisions, and we describe our valuation method and estimations for costing this important resource. We performed a contingent valuation using 37 Australian Chief Executive Officers' (CEOs) willingness to pay (WTP) to release bed days in their hospitals, both generally and using specific cases. We provide a succinct thematic analysis from qualitative interviews post survey completion, which provide insight into the decision making process. On average CEOs are willing to pay a marginal rate of $216 for a ward bed day and $436 for an Intensive Care Unit (ICU) bed day, with estimates of uncertainty being greater for ICU beds. These estimates are significantly lower (four times for ward beds and seven times for ICU beds) than the traditional accounting costs often used. Key themes to emerge from the interviews include the importance of national funding and targets, and their associated incentive structures, as well as the aversion to discuss bed days as an economic resource. This study highlights the importance for valuing bed days as an economic resource to inform cost effectiveness models and thus improve hospital decision making and resource allocation. Significantly under or over valuing the resource is very likely to result in sub-optimal decision making. We discuss the importance of recognising the opportunity costs of this resource and highlight areas for future research.

Multi-criteria multi-stakeholder decision analysis using a fuzzy-stochastic approach for hydrosystem management

NASA Astrophysics Data System (ADS)

Subagadis, Y. H.; Schütze, N.; Grundmann, J.

2014-09-01

The conventional methods used to solve multi-criteria multi-stakeholder problems are less strongly formulated, as they normally incorporate only homogeneous information at a time and suggest aggregating objectives of different decision-makers avoiding water-society interactions. In this contribution, Multi-Criteria Group Decision Analysis (MCGDA) using a fuzzy-stochastic approach has been proposed to rank a set of alternatives in water management decisions incorporating heterogeneous information under uncertainty. The decision making framework takes hydrologically, environmentally, and socio-economically motivated conflicting objectives into consideration. The criteria related to the performance of the physical system are optimized using multi-criteria simulation-based optimization, and fuzzy linguistic quantifiers have been used to evaluate subjective criteria and to assess stakeholders' degree of optimism. The proposed methodology is applied to find effective and robust intervention strategies for the management of a coastal hydrosystem affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. Preliminary results show that the MCGDA based on a fuzzy-stochastic approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.

Urban water infrastructure optimization to reduce environmental impacts and costs.

PubMed

Lim, Seong-Rin; Suh, Sangwon; Kim, Jung-Hoon; Park, Hung Suck

2010-01-01

Urban water planning and policy have been focusing on environmentally benign and economically viable water management. The objective of this study is to develop a mathematical model to integrate and optimize urban water infrastructures for supply-side planning and policy: freshwater resources and treated wastewater are allocated to various water demand categories in order to reduce contaminants in the influents supplied for drinking water, and to reduce consumption of the water resources imported from the regions beyond a city boundary. A case study is performed to validate the proposed model. An optimal urban water system of a metropolitan city is calculated on the basis of the model and compared to the existing water system. The integration and optimization decrease (i) average concentrations of the influents supplied for drinking water, which can improve human health and hygiene; (ii) total consumption of water resources, as well as electricity, reducing overall environmental impacts; (iii) life cycle cost; and (iv) water resource dependency on other regions, improving regional water security. This model contributes to sustainable urban water planning and policy. 2009 Elsevier Ltd. All rights reserved.

Optimal Design of Biomass Utilization System for Rural Area Includes Technical and Economic Dimensions

NASA Astrophysics Data System (ADS)

Morioka, Yasuki; Nakata, Toshihiko

In order to design optimal biomass utilization system for rural area, OMNIBUS (The Optimization Model for Neo-Integrated Biomass Utilization System) has been developed. OMNIBUS can derive the optimal system configuration to meet different objective function, such as current account balance, amount of biomass energy supply, and CO2 emission. Most of biomass resources in a focused region e.g. wood biomass, livestock biomass, and crop residues are considered in the model. Conversion technologies considered are energy utilization technologies e.g. direct combustion and methane fermentation, and material utilization technologies e.g. composting and carbonization. Case study in Miyakojima, Okinawa prefecture, has been carried out for several objective functions and constraint conditions. Considering economics of the utilization system as a priority requirement, composting and combustion heat utilization are mainly chosen in the optimal system configuration. However gasification power plant and methane fermentation are included in optimal solutions, only when both biomass energy utilization and CO2 reduction have been set as higher priorities. External benefit of CO2 reduction has large impacts on the system configuration. Provided marginal external benefit of more than 50,000 JPY/t-C, external benefit becomes greater than the revenue from electricity and compost etc. Considering technological learning in the future, expensive technologies such as gasification power plant and methane fermentation will have economic feasibility as well as market competitiveness.

Design optimization for cost and quality: The robust design approach

NASA Technical Reports Server (NTRS)

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.

Economic Analysis of Biological Invasions in Forests

Treesearch

Tomas P. Holmes; Julian Aukema; Jeffrey Englin; Robert G. Haight; Kent Kovacs; Brian Leung

2014-01-01

Biological invasions of native forests by nonnative pests result from complex stochastic processes that are difficult to predict. Although economic optimization models describe efficient controls across the stages of an invasion, the ability to calibrate such models is constrained by lack of information on pest population dynamics and consequent economic damages. Here...

Modeling the Components of an Economy as a Complex Adaptive System

DTIC Science & Technology

principles of constrained optimization and fails to see economic variables as part of an interconnected network. While tools for forecasting economic...data sets such as the stock market . This research portrays the stock market as one component of a networked system of economic variables, with the

Synthesizing epidemiological and economic optima for control of immunizing infections.

PubMed

Klepac, Petra; Laxminarayan, Ramanan; Grenfell, Bryan T

2011-08-23

Epidemic theory predicts that the vaccination threshold required to interrupt local transmission of an immunizing infection like measles depends only on the basic reproductive number and hence transmission rates. When the search for optimal strategies is expanded to incorporate economic constraints, the optimum for disease control in a single population is determined by relative costs of infection and control, rather than transmission rates. Adding a spatial dimension, which precludes local elimination unless it can be achieved globally, can reduce or increase optimal vaccination levels depending on the balance of costs and benefits. For weakly coupled populations, local optimal strategies agree with the global cost-effective strategy; however, asymmetries in costs can lead to divergent control optima in more strongly coupled systems--in particular, strong regional differences in costs of vaccination can preclude local elimination even when elimination is locally optimal. Under certain conditions, it is locally optimal to share vaccination resources with other populations.

Optimal design and management of chlorination in drinking water networks: a multi-objective approach using Genetic Algorithms and the Pareto optimality concept

NASA Astrophysics Data System (ADS)

Nouiri, Issam

2017-11-01

This paper presents the development of multi-objective Genetic Algorithms to optimize chlorination design and management in drinking water networks (DWN). Three objectives have been considered: the improvement of the chlorination uniformity (healthy objective), the minimization of chlorine booster stations number, and the injected chlorine mass (economic objectives). The problem has been dissociated in medium and short terms ones. The proposed methodology was tested on hypothetical and real DWN. Results proved the ability of the developed optimization tool to identify relationships between the healthy and economic objectives as Pareto fronts. The proposed approach was efficient in computing solutions ensuring better chlorination uniformity while requiring the weakest injected chlorine mass when compared to other approaches. For the real DWN studied, chlorination optimization has been crowned by great improvement of free-chlorine-dosing uniformity and by a meaningful chlorine mass reduction, in comparison with the conventional chlorination.

Topography-based Flood Planning and Optimization Capability Development Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Judi, David R.; Tasseff, Byron A.; Bent, Russell W.

2014-02-26

Globally, water-related disasters are among the most frequent and costly natural hazards. Flooding inflicts catastrophic damage on critical infrastructure and population, resulting in substantial economic and social costs. NISAC is developing LeveeSim, a suite of nonlinear and network optimization models, to predict optimal barrier placement to protect critical regions and infrastructure during flood events. LeveeSim currently includes a high-performance flood model to simulate overland flow, as well as a network optimization model to predict optimal barrier placement during a flood event. The LeveeSim suite models the effects of flooding in predefined regions. By manipulating a domain’s underlying topography, developers alteredmore » flood propagation to reduce detrimental effects in areas of interest. This numerical altering of a domain’s topography is analogous to building levees, placing sandbags, etc. To induce optimal changes in topography, NISAC used a novel application of an optimization algorithm to minimize flooding effects in regions of interest. To develop LeveeSim, NISAC constructed and coupled hydrodynamic and optimization algorithms. NISAC first implemented its existing flood modeling software to use massively parallel graphics processing units (GPUs), which allowed for the simulation of larger domains and longer timescales. NISAC then implemented a network optimization model to predict optimal barrier placement based on output from flood simulations. As proof of concept, NISAC developed five simple test scenarios, and optimized topographic solutions were compared with intuitive solutions. Finally, as an early validation example, barrier placement was optimized to protect an arbitrary region in a simulation of the historic Taum Sauk dam breach.« less

Optimized protocol for quantitative multiple reaction monitoring-based proteomic analysis of formalin-fixed, paraffin embedded tissues

PubMed Central

Kennedy, Jacob J.; Whiteaker, Jeffrey R.; Schoenherr, Regine M.; Yan, Ping; Allison, Kimberly; Shipley, Melissa; Lerch, Melissa; Hoofnagle, Andrew N.; Baird, Geoffrey Stuart; Paulovich, Amanda G.

2016-01-01

Despite a clinical, economic, and regulatory imperative to develop companion diagnostics, precious few new biomarkers have been successfully translated into clinical use, due in part to inadequate protein assay technologies to support large-scale testing of hundreds of candidate biomarkers in formalin-fixed paraffin embedded (FFPE) tissues. While the feasibility of using targeted, multiple reaction monitoring-mass spectrometry (MRM-MS) for quantitative analyses of FFPE tissues has been demonstrated, protocols have not been systematically optimized for robust quantification across a large number of analytes, nor has the performance of peptide immuno-MRM been evaluated. To address this gap, we used a test battery approach coupled to MRM-MS with the addition of stable isotope labeled standard peptides (targeting 512 analytes) to quantitatively evaluate the performance of three extraction protocols in combination with three trypsin digestion protocols (i.e. 9 processes). A process based on RapiGest buffer extraction and urea-based digestion was identified to enable similar quantitation results from FFPE and frozen tissues. Using the optimized protocols for MRM-based analysis of FFPE tissues, median precision was 11.4% (across 249 analytes). There was excellent correlation between measurements made on matched FFPE and frozen tissues, both for direct MRM analysis (R2 = 0.94) and immuno-MRM (R2 = 0.89). The optimized process enables highly reproducible, multiplex, standardizable, quantitative MRM in archival tissue specimens. PMID:27462933

Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model.

PubMed

Qiu, Mingyue; Song, Yu

2016-01-01

In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders' expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day's price of the Japanese stock market index by using an optimized artificial neural network (ANN) model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA). We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately.

Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model

PubMed Central

Qiu, Mingyue; Song, Yu

2016-01-01

In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders’ expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day’s price of the Japanese stock market index by using an optimized artificial neural network (ANN) model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA). We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately. PMID:27196055

Did recent world record marathon runners employ optimal pacing strategies?

PubMed

Angus, Simon D

2014-01-01

We apply statistical analysis of high frequency (1 km) split data for the most recent two world-record marathon runs: Run 1 (2:03:59, 28 September 2008) and Run 2 (2:03:38, 25 September 2011). Based on studies in the endurance cycling literature, we develop two principles to approximate 'optimal' pacing in the field marathon. By utilising GPS and weather data, we test, and then de-trend, for each athlete's field response to gradient and headwind on course, recovering standardised proxies for power-based pacing traces. The resultant traces were analysed to ascertain if either runner followed optimal pacing principles; and characterise any deviations from optimality. Whereas gradient was insignificant, headwind was a significant factor in running speed variability for both runners, with Runner 2 targeting the (optimal) parallel variation principle, whilst Runner 1 did not. After adjusting for these responses, neither runner followed the (optimal) 'even' power pacing principle, with Runner 2's macro-pacing strategy fitting a sinusoidal oscillator with exponentially expanding envelope whilst Runner 1 followed a U-shaped, quadratic form. The study suggests that: (a) better pacing strategy could provide elite marathon runners with an economical pathway to significant performance improvements at world-record level; and (b) the data and analysis herein is consistent with a complex-adaptive model of power regulation.

An Iterative Approach for the Optimization of Pavement Maintenance Management at the Network Level

PubMed Central

Torres-Machí, Cristina; Chamorro, Alondra; Videla, Carlos; Yepes, Víctor

2014-01-01

Pavement maintenance is one of the major issues of public agencies. Insufficient investment or inefficient maintenance strategies lead to high economic expenses in the long term. Under budgetary restrictions, the optimal allocation of resources becomes a crucial aspect. Two traditional approaches (sequential and holistic) and four classes of optimization methods (selection based on ranking, mathematical optimization, near optimization, and other methods) have been applied to solve this problem. They vary in the number of alternatives considered and how the selection process is performed. Therefore, a previous understanding of the problem is mandatory to identify the most suitable approach and method for a particular network. This study aims to assist highway agencies, researchers, and practitioners on when and how to apply available methods based on a comparative analysis of the current state of the practice. Holistic approach tackles the problem considering the overall network condition, while the sequential approach is easier to implement and understand, but may lead to solutions far from optimal. Scenarios defining the suitability of these approaches are defined. Finally, an iterative approach gathering the advantages of traditional approaches is proposed and applied in a case study. The proposed approach considers the overall network condition in a simpler and more intuitive manner than the holistic approach. PMID:24741352

An iterative approach for the optimization of pavement maintenance management at the network level.

PubMed

Torres-Machí, Cristina; Chamorro, Alondra; Videla, Carlos; Pellicer, Eugenio; Yepes, Víctor

2014-01-01

Pavement maintenance is one of the major issues of public agencies. Insufficient investment or inefficient maintenance strategies lead to high economic expenses in the long term. Under budgetary restrictions, the optimal allocation of resources becomes a crucial aspect. Two traditional approaches (sequential and holistic) and four classes of optimization methods (selection based on ranking, mathematical optimization, near optimization, and other methods) have been applied to solve this problem. They vary in the number of alternatives considered and how the selection process is performed. Therefore, a previous understanding of the problem is mandatory to identify the most suitable approach and method for a particular network. This study aims to assist highway agencies, researchers, and practitioners on when and how to apply available methods based on a comparative analysis of the current state of the practice. Holistic approach tackles the problem considering the overall network condition, while the sequential approach is easier to implement and understand, but may lead to solutions far from optimal. Scenarios defining the suitability of these approaches are defined. Finally, an iterative approach gathering the advantages of traditional approaches is proposed and applied in a case study. The proposed approach considers the overall network condition in a simpler and more intuitive manner than the holistic approach.

Technical, hygiene, economic, and life cycle assessment of full-scale moving bed biofilm reactors for wastewater treatment in India.

PubMed

Singh, Anju; Kamble, Sheetal Jaisingh; Sawant, Megha; Chakravarthy, Yogita; Kazmi, Absar; Aymerich, Enrique; Starkl, Markus; Ghangrekar, Makarand; Philip, Ligy

2018-01-01

Moving bed biofilm reactor (MBBR) is a highly effective biological treatment process applied to treat both urban and industrial wastewaters in developing countries. The present study investigated the technical performance of ten full-scale MBBR systems located across India. The biochemical oxygen demand, chemical oxygen demand, total suspended solid, pathogens, and nutrient removal efficiencies were low as compared to the values claimed in literature. Plant 1 was considered for evaluation of environmental impacts using life cycle assessment approach. CML 2 baseline 2000 methodology was adopted, in which 11 impact categories were considered. The life cycle impact assessment results revealed that the main environmental hot spot of this system was energy consumption. Additionally, two scenarios were compared: scenario 1 (direct discharge of treated effluent, i.e., no reuse) and scenario 2 (effluent reuse and tap water replacement). The results showed that scenario 2 significantly reduce the environmental impact in all the categories ultimately decreasing the environmental burden. Moreover, significant economic and environmental benefits can be obtained in scenario 2 by replacing the freshwater demand for non-potable uses. To enhance the performance of wastewater treatment plant (WWTP), there is a need to optimize energy consumption and increase wastewater collection efficiency to maximize the operating capacity of plant and minimize overall environmental footprint. It was concluded that MBBR can be a good alternative for upgrading and optimizing existing municipal wastewater treatment plants with appropriate tertiary treatment. Graphical abstract ᅟ.

The Ecosystem Approach of Wanatani Semi Arid Equatorial to Sustainable Agriculutral Management (in Amarasi District, Kupang Regency, NTT)

NASA Astrophysics Data System (ADS)

Yanti, Rinda; Basukriadi, Adi; Hasroel Thayib, Moh.; Edhie Budhi Soesilo, Tri

2016-01-01

The existing condition of the wanatani management in Amarasi District, Kupang Regency, NTT, has not optimized the welfare of the farmers yet, and the land degradation keeps happening. The objectives of this research was to analyze and obtain information on the ecological, social, and economic benefits of sustainable wanatani in dry land management. The research result shows that based on the observation from the ecological function including vegetation, land fertility, micro climate, erotion, and land suitability, wanatani is at present not optimal and not sustainable in supporting productivity and land conservation. From the economic function, the productivity in wanatani should be optimal, but the lack of institutional support and social function causes the agricultural management to be not optimal and not sustainable.

Optimized design of embedded DSP system hardware supporting complex algorithms

NASA Astrophysics Data System (ADS)

Li, Yanhua; Wang, Xiangjun; Zhou, Xinling

2003-09-01

The paper presents an optimized design method for a flexible and economical embedded DSP system that can implement complex processing algorithms as biometric recognition, real-time image processing, etc. It consists of a floating-point DSP, 512 Kbytes data RAM, 1 Mbytes FLASH program memory, a CPLD for achieving flexible logic control of input channel and a RS-485 transceiver for local network communication. Because of employing a high performance-price ratio DSP TMS320C6712 and a large FLASH in the design, this system permits loading and performing complex algorithms with little algorithm optimization and code reduction. The CPLD provides flexible logic control for the whole DSP board, especially in input channel, and allows convenient interface between different sensors and DSP system. The transceiver circuit can transfer data between DSP and host computer. In the paper, some key technologies are also introduced which make the whole system work efficiently. Because of the characters referred above, the hardware is a perfect flat for multi-channel data collection, image processing, and other signal processing with high performance and adaptability. The application section of this paper presents how this hardware is adapted for the biometric identification system with high identification precision. The result reveals that this hardware is easy to interface with a CMOS imager and is capable of carrying out complex biometric identification algorithms, which require real-time process.

Can we do better? Economic analysis of human resource investment to improve home care service for the elderly in Serbia.

PubMed

Mihic, Marko M; Todorovic, Marija Lj; Obradovic, Vladimir Lj; Mitrovic, Zorica M

2016-01-01

Social services aimed at the elderly are facing great challenges caused by progressive aging of the global population but also by the constant pressure to spend funds in a rational manner. This paper focuses on analyzing the investments into human resources aimed at enhancing home care for the elderly since many countries have recorded progress in the area over the past years. The goal of this paper is to stress the significance of performing an economic analysis of the investment. This paper combines statistical analysis methods such as correlation and regression analysis, methods of economic analysis, and scenario method. The economic analysis of investing in human resources for home care service in Serbia showed that the both scenarios of investing in either additional home care hours or more beneficiaries are cost-efficient. However, the optimal solution with the positive (and the highest) value of economic net present value criterion is to invest in human resources to boost the number of home care hours from 6 to 8 hours per week and increase the number of the beneficiaries to 33%. This paper shows how the statistical and economic analysis results can be used to evaluate different scenarios and enable quality decision-making based on exact data in order to improve health and quality of life of the elderly and spend funds in a rational manner.

Optimizing Barrier Removal to Restore Connectivity in Utah's Weber Basin

NASA Astrophysics Data System (ADS)

Kraft, M.; Null, S. E.

2016-12-01

Instream barriers, such as dams, culverts and diversions are economically important for water supply, but negatively affect river ecosystems and disrupt hydrologic processes. Removal of uneconomical and aging in-stream barriers to improve habitat connectivity is increasingly used to restore river connectivity. Most past barrier removal projects focused on individual barriers using a score-and-rank technique, ignoring cumulative change from multiple, spatially-connected barrier removals. Similarly, most water supply models optimize either human water use or aquatic connectivity, failing to holistically represent human and environmental benefits. In this study, a dual objective optimization model identified in-stream barriers that impede aquatic habitat connectivity for trout, using streamflow, temperature, and channel gradient as indicators of aquatic habitat suitability. Water scarcity costs are minimized using agricultural and urban economic penalty functions to incorporate water supply benefits and a budget monetizes costs of removing small barriers like culverts and road crossings. The optimization model developed is applied to a case study in Utah's Weber basin to prioritize removal of the most environmentally harmful barriers, while maintaining human water uses. The dual objective solution basis was developed to quantify and graphically visualize tradeoffs between connected quality-weighted habitat for Bonneville cutthroat trout and economic water uses. Modeled results include a spectrum of barrier removal alternatives based on budget and quality-weighted reconnected habitat that can be communicated with local stakeholders. This research will help prioritize barrier removals and future restoration decisions. The modeling approach expands current barrier removal optimization methods by explicitly including economic and environmental water uses.

Applications of polynomial optimization in financial risk investment

NASA Astrophysics Data System (ADS)

Zeng, Meilan; Fu, Hongwei

2017-09-01

Recently, polynomial optimization has many important applications in optimization, financial economics and eigenvalues of tensor, etc. This paper studies the applications of polynomial optimization in financial risk investment. We consider the standard mean-variance risk measurement model and the mean-variance risk measurement model with transaction costs. We use Lasserre's hierarchy of semidefinite programming (SDP) relaxations to solve the specific cases. The results show that polynomial optimization is effective for some financial optimization problems.

Holistic irrigation water management approach based on stochastic soil water dynamics

NASA Astrophysics Data System (ADS)

Alizadeh, H.; Mousavi, S. J.

2012-04-01

Appreciating the essential gap between fundamental unsaturated zone transport processes and soil and water management due to low effectiveness of some of monitoring and modeling approaches, this study presents a mathematical programming model for irrigation management optimization based on stochastic soil water dynamics. The model is a nonlinear non-convex program with an economic objective function to address water productivity and profitability aspects in irrigation management through optimizing irrigation policy. Utilizing an optimization-simulation method, the model includes an eco-hydrological integrated simulation model consisting of an explicit stochastic module of soil moisture dynamics in the crop-root zone with shallow water table effects, a conceptual root-zone salt balance module, and the FAO crop yield module. Interdependent hydrology of soil unsaturated and saturated zones is treated in a semi-analytical approach in two steps. At first step analytical expressions are derived for the expected values of crop yield, total water requirement and soil water balance components assuming fixed level for shallow water table, while numerical Newton-Raphson procedure is employed at the second step to modify value of shallow water table level. Particle Swarm Optimization (PSO) algorithm, combined with the eco-hydrological simulation model, has been used to solve the non-convex program. Benefiting from semi-analytical framework of the simulation model, the optimization-simulation method with significantly better computational performance compared to a numerical Mote-Carlo simulation-based technique has led to an effective irrigation management tool that can contribute to bridging the gap between vadose zone theory and water management practice. In addition to precisely assessing the most influential processes at a growing season time scale, one can use the developed model in large scale systems such as irrigation districts and agricultural catchments. Accordingly, the model has been applied in Dasht-e-Abbas and Ein-khosh Fakkeh Irrigation Districts (DAID and EFID) of the Karkheh Basin in southwest of Iran. The area suffers from the water scarcity problem and therefore the trade-off between the level of deficit and economical profit should be assessed. Based on the results, while the maximum net benefit has been obtained for the stress-avoidance (SA) irrigation policy, the highest water profitability, defined by economical net benefit gained from unit irrigation water volume application, has been resulted when only about 60% of water used in the SA policy is applied.

High-potential Working Fluids for Next Generation Binary Cycle Geothermal Power Plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zia, Jalal; Sevincer, Edip; Chen, Huijuan

2013-06-29

A thermo-economic model has been built and validated for prediction of project economics of Enhanced Geothermal Projects. The thermo-economic model calculates and iteratively optimizes the LCOE (levelized cost of electricity) for a prospective EGS (Enhanced Geothermal) site. It takes into account the local subsurface temperature gradient, the cost of drilling and reservoir creation, stimulation and power plant configuration. It calculates and optimizes the power plant configuration vs. well depth. Thus outputs from the model include optimal well depth and power plant configuration for the lowest LCOE. The main focus of this final report was to experimentally validate the thermodynamic propertiesmore » that formed the basis of the thermo-economic model built in Phase 2, and thus build confidence that the predictions of the model could be used reliably for process downselection and preliminary design at a given set of geothermal (and/or waste heat) boundary conditions. The fluid and cycle downselected was based on a new proprietary fluid from a vendor in a supercritical ORC cycle at a resource condition of 200°C inlet temperature. The team devised and executed a series of experiments to prove the suitability of the new fluid in realistic ORC cycle conditions. Furthermore, the team performed a preliminary design study for a MW-scale turbo expander that would be used for a supercritical ORC cycle with this new fluid. The following summarizes the main findings in the investigative campaign that was undertaken: 1. Chemical compatibility of the new fluid with common seal/gasket/Oring materials was found to be problematic. Neoprene, Viton, and silicone materials were found to be incompatible, suffering chemical decomposition, swelling and/or compression set issues. Of the materials tested, only TEFLON was found to be compatible under actual ORC temperature and pressure conditions. 2. Thermal stability of the new fluid at 200°C and 40 bar was found to be acceptable after 399 hours of exposure?only 3% of the initial charge degraded into by products. The main degradation products being an isomer and a dimer. 3. In a comparative experiment between R245fa and the new fluid under subcritical conditions, it was found that the new fluid operated at 1 bar lower than R245fa for the same power output, which was also predicted in the Aspen HSYSY model. As a drop-in replacement fluid for R245fa, this new fluid was found to be at least as good as R245fa in terms of performance and stability. Further optimization of the subcritical cycle may lead to a significant improvement in performance for the new fluid. 4. For supercritical conditions, the experiment found a good match between the measured and model predicted state point property data and duties from the energy balance. The largest percent differences occurred with densities and evaporator duty (see Figure 78). It is therefore reasonable to conclude that the state point model was experimentally validated with a realistic ORC system. 5. The team also undertook a preliminary turbo-expander design study for a supercritical ORC cycle with the new working fluid. Variants of radial and axial turbo expander geometries went through preliminary design and rough costing. It was found that at 15MWe or higher power rating, a multi-stage axial turbine is most suitable providing the best performance and cost. However, at lower power ratings in the 5MWe range, the expander technology to be chosen depends on the application of the power block. For EGS power blocks, it is most optimal to use multi-stage axial machines. In conclusion, the predictions of the LCOE model that showed a supercritical cycle based on the new fluid to be most advantageous for geothermal power production at a resource temperature of ~ 200C have been experimentally validated. It was found that the cycle based on the new fluid is lower in LCOE and higher in net power output (for the same boundary conditions). The project, therefore has found a new optimal configuration for low temperature geothermal power production in the form of a supercritical ORC cycle based on a new vendor fluid.« less

An Enhanced Memetic Algorithm for Single-Objective Bilevel Optimization Problems.

PubMed

Islam, Md Monjurul; Singh, Hemant Kumar; Ray, Tapabrata; Sinha, Ankur

2017-01-01

Bilevel optimization, as the name reflects, deals with optimization at two interconnected hierarchical levels. The aim is to identify the optimum of an upper-level  leader problem, subject to the optimality of a lower-level follower problem. Several problems from the domain of engineering, logistics, economics, and transportation have an inherent nested structure which requires them to be modeled as bilevel optimization problems. Increasing size and complexity of such problems has prompted active theoretical and practical interest in the design of efficient algorithms for bilevel optimization. Given the nested nature of bilevel problems, the computational effort (number of function evaluations) required to solve them is often quite high. In this article, we explore the use of a Memetic Algorithm (MA) to solve bilevel optimization problems. While MAs have been quite successful in solving single-level optimization problems, there have been relatively few studies exploring their potential for solving bilevel optimization problems. MAs essentially attempt to combine advantages of global and local search strategies to identify optimum solutions with low computational cost (function evaluations). The approach introduced in this article is a nested Bilevel Memetic Algorithm (BLMA). At both upper and lower levels, either a global or a local search method is used during different phases of the search. The performance of BLMA is presented on twenty-five standard test problems and two real-life applications. The results are compared with other established algorithms to demonstrate the efficacy of the proposed approach.

Topology optimization analysis based on the direct coupling of the boundary element method and the level set method

NASA Astrophysics Data System (ADS)

Vitório, Paulo Cezar; Leonel, Edson Denner

2017-12-01

The structural design must ensure suitable working conditions by attending for safe and economic criteria. However, the optimal solution is not easily available, because these conditions depend on the bodies' dimensions, materials strength and structural system configuration. In this regard, topology optimization aims for achieving the optimal structural geometry, i.e. the shape that leads to the minimum requirement of material, respecting constraints related to the stress state at each material point. The present study applies an evolutionary approach for determining the optimal geometry of 2D structures using the coupling of the boundary element method (BEM) and the level set method (LSM). The proposed algorithm consists of mechanical modelling, topology optimization approach and structural reconstruction. The mechanical model is composed of singular and hyper-singular BEM algebraic equations. The topology optimization is performed through the LSM. Internal and external geometries are evolved by the LS function evaluated at its zero level. The reconstruction process concerns the remeshing. Because the structural boundary moves at each iteration, the body's geometry change and, consequently, a new mesh has to be defined. The proposed algorithm, which is based on the direct coupling of such approaches, introduces internal cavities automatically during the optimization process, according to the intensity of Von Mises stress. The developed optimization model was applied in two benchmarks available in the literature. Good agreement was observed among the results, which demonstrates its efficiency and accuracy.

Increase of efficiency and reliability of liquid fuel combustion in small-sized boilers

NASA Astrophysics Data System (ADS)

Roslyakov, P. V.; Proskurin, Yu V.; Ionkin, I. L.

2017-11-01

One of the ways to increase the efficiency of using fuels is to create highly efficient domestic energy equipment, in particular small-sized hot-water boilers in autonomous heating systems. Increasing the efficiency of the boiler requires a reduction in the temperature of the flue gases leaving, which, in turn, can be achieved by installing additional heating surfaces. The purpose of this work was to determine the principal design solutions and to develop a draft design for a high-efficiency 3-MW hot-water boiler using crude oil as its main fuel. Ensuring a high efficiency of the boiler is realized through the use of an external remote economizer, which makes it possible to reduce the dimensions of the boiler, facilitate the layout of equipment in a limited size block-modular boiler house and virtually eliminate low-temperature corrosion of boiler heat exchange surfaces. In the article the variants of execution of the water boiler and remote economizer are considered and the preliminary design calculations of the remote economizer for various schemes of the boiler layout in the Boiler Designer software package are made. Based on the results of the studies, a scheme was chosen with a three-way boiler and a two-way remote economizer. The design of a three-way fire tube hot water boiler and an external economizer with an internal arrangement of the collectors, providing for its location above the boiler in a block-modular boiler house and providing access for servicing both a remote economizer and a hot water boiler, is proposed. Its mass-dimensional and design parameters are determined. In the software package Boiler Designer thermal, hydraulic and aerodynamic calculations of the developed fire tube boiler have been performed. Optimization of the boiler design was performed, providing the required 94% efficiency value for crude oil combustion. The description of the developed flue and fire-tube hot water boiler and the value of the main design and technical and economic parameters are given.

Economical Unsteady High-Fidelity Aerodynamics for Structural Optimization with a Flutter Constraint

NASA Technical Reports Server (NTRS)

Bartels, Robert E.; Stanford, Bret K.

2017-01-01

Structural optimization with a flutter constraint for a vehicle designed to fly in the transonic regime is a particularly difficult task. In this speed range, the flutter boundary is very sensitive to aerodynamic nonlinearities, typically requiring high-fidelity Navier-Stokes simulations. However, the repeated application of unsteady computational fluid dynamics to guide an aeroelastic optimization process is very computationally expensive. This expense has motivated the development of methods that incorporate aspects of the aerodynamic nonlinearity, classical tools of flutter analysis, and more recent methods of optimization. While it is possible to use doublet lattice method aerodynamics, this paper focuses on the use of an unsteady high-fidelity aerodynamic reduced order model combined with successive transformations that allows for an economical way of utilizing high-fidelity aerodynamics in the optimization process. This approach is applied to the common research model wing structural design. As might be expected, the high-fidelity aerodynamics produces a heavier wing than that optimized with doublet lattice aerodynamics. It is found that the optimized lower skin of the wing using high-fidelity aerodynamics differs significantly from that using doublet lattice aerodynamics.

Water Market-scale Agricultural Planning: Promoting Competing Water Resource Use Efficiency Through Agro-Economics

NASA Astrophysics Data System (ADS)

Delorit, J. D.; Block, P. J.

2017-12-01

Where strong water rights law and corresponding markets exist as a coupled econo-legal mechanism, water rights holders are permitted to trade allocations to promote economic water resource use efficiency. In locations where hydrologic uncertainty drives the assignment of annual per-water right allocation values by water resource managers, collaborative water resource decision making by water rights holders, specifically those involved in agricultural production, can result in both resource and economic Pareto efficiency. Such is the case in semi-arid North Chile, where interactions between representative farmer groups, treated as competitive bilateral monopolies, and modeled at water market-scale, can provide both price and water right allocation distribution signals for unregulated, temporary water right leasing markets. For the range of feasible per-water right allocation values, a coupled agricultural-economic model is developed to describe the equilibrium distribution of water, the corresponding market price of water rights and the net surplus generated by collaboration between competing agricultural uses. Further, this research describes a per-water right inflection point for allocations where economic efficiency is not possible, and where price negotiation among competing agricultural uses is required. An investigation of the effects of water right supply and demand inequality at the market-scale is completed to characterize optimal market performance under existing water rights law. The broader insights of this research suggest that water rights holders engaged in agriculture can achieve economic benefits from forming crop-type cooperatives and by accurately assessing the economic value of allocation.

Confronting Decision Cliffs: Diagnostic Assessment of Multi-Objective Evolutionary Algorithms' Performance for Addressing Uncertain Environmental Thresholds

NASA Astrophysics Data System (ADS)

Ward, V. L.; Singh, R.; Reed, P. M.; Keller, K.

2014-12-01

As water resources problems typically involve several stakeholders with conflicting objectives, multi-objective evolutionary algorithms (MOEAs) are now key tools for understanding management tradeoffs. Given the growing complexity of water planning problems, it is important to establish if an algorithm can consistently perform well on a given class of problems. This knowledge allows the decision analyst to focus on eliciting and evaluating appropriate problem formulations. This study proposes a multi-objective adaptation of the classic environmental economics "Lake Problem" as a computationally simple but mathematically challenging MOEA benchmarking problem. The lake problem abstracts a fictional town on a lake which hopes to maximize its economic benefit without degrading the lake's water quality to a eutrophic (polluted) state through excessive phosphorus loading. The problem poses the challenge of maintaining economic activity while confronting the uncertainty of potentially crossing a nonlinear and potentially irreversible pollution threshold beyond which the lake is eutrophic. Objectives for optimization are maximizing economic benefit from lake pollution, maximizing water quality, maximizing the reliability of remaining below the environmental threshold, and minimizing the probability that the town will have to drastically change pollution policies in any given year. The multi-objective formulation incorporates uncertainty with a stochastic phosphorus inflow abstracting non-point source pollution. We performed comprehensive diagnostics using 6 algorithms: Borg, MOEAD, eMOEA, eNSGAII, GDE3, and NSGAII to ascertain their controllability, reliability, efficiency, and effectiveness. The lake problem abstracts elements of many current water resources and climate related management applications where there is the potential for crossing irreversible, nonlinear thresholds. We show that many modern MOEAs can fail on this test problem, indicating its suitability as a useful and nontrivial benchmarking problem.

A leader-follower-interactive method for regional water resources management with considering multiple water demands and eco-environmental constraints

NASA Astrophysics Data System (ADS)

Chen, Yizhong; Lu, Hongwei; Li, Jing; Ren, Lixia; He, Li

2017-05-01

This study presents the mathematical formulation and implementations of a synergistic optimization framework based on an understanding of water availability and reliability together with the characteristics of multiple water demands. This framework simultaneously integrates a set of leader-followers-interactive objectives established by different decision makers during the synergistic optimization. The upper-level model (leader's one) determines the optimal pollutants discharge to satisfy the environmental target. The lower-level model (follower's one) accepts the dispatch requirement from the upper-level one and dominates the optimal water-allocation strategy to maximize economic benefits representing the regional authority. The complicated bi-level model significantly improves upon the conventional programming methods through the mutual influence and restriction between the upper- and lower-level decision processes, particularly when limited water resources are available for multiple completing users. To solve the problem, a bi-level interactive solution algorithm based on satisfactory degree is introduced into the decision-making process for measuring to what extent the constraints are met and the objective reaches its optima. The capabilities of the proposed model are illustrated through a real-world case study of water resources management system in the district of Fengtai located in Beijing, China. Feasible decisions in association with water resources allocation, wastewater emission and pollutants discharge would be sequentially generated for balancing the objectives subject to the given water-related constraints, which can enable Stakeholders to grasp the inherent conflicts and trade-offs between the environmental and economic interests. The performance of the developed bi-level model is enhanced by comparing with single-level models. Moreover, in consideration of the uncertainty in water demand and availability, sensitivity analysis and policy analysis are employed for identifying their impacts on the final decisions and improving the practical applications.

Distributed Generators Allocation in Radial Distribution Systems with Load Growth using Loss Sensitivity Approach

NASA Astrophysics Data System (ADS)

Kumar, Ashwani; Vijay Babu, P.; Murty, V. V. S. N.

2017-06-01

Rapidly increasing electricity demands and capacity shortage of transmission and distribution facilities are the main driving forces for the growth of distributed generation (DG) integration in power grids. One of the reasons for choosing a DG is its ability to support voltage in a distribution system. Selection of effective DG characteristics and DG parameters is a significant concern of distribution system planners to obtain maximum potential benefits from the DG unit. The objective of the paper is to reduce the power losses and improve the voltage profile of the radial distribution system with optimal allocation of the multiple DG in the system. The main contribution in this paper is (i) combined power loss sensitivity (CPLS) based method for multiple DG locations, (ii) determination of optimal sizes for multiple DG units at unity and lagging power factor, (iii) impact of DG installed at optimal, that is, combined load power factor on the system performance, (iv) impact of load growth on optimal DG planning, (v) Impact of DG integration in distribution systems on voltage stability index, (vi) Economic and technical Impact of DG integration in the distribution systems. The load growth factor has been considered in the study which is essential for planning and expansion of the existing systems. The technical and economic aspects are investigated in terms of improvement in voltage profile, reduction in total power losses, cost of energy loss, cost of power obtained from DG, cost of power intake from the substation, and savings in cost of energy loss. The results are obtained on IEEE 69-bus radial distribution systems and also compared with other existing methods.

Status Report on Modelling and Simulation Capabilities for Nuclear-Renewable Hybrid Energy Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rabiti, C.; Epiney, A.; Talbot, P.

This report summarizes the current status of the modeling and simulation capabilities developed for the economic assessment of Nuclear-Renewable Hybrid Energy Systems (N-R HES). The increasing penetration of variable renewables is altering the profile of the net demand, with which the other generators on the grid have to cope. N-R HES analyses are being conducted to determine the potential feasibility of mitigating the resultant volatility in the net electricity demand by adding industrial processes that utilize either thermal or electrical energy as stabilizing loads. This coordination of energy generators and users is proposed to mitigate the increase in electricity costmore » and cost volatility through the production of a saleable commodity. Overall, the financial performance of a system that is comprised of peaking units (i.e. gas turbine), baseload supply (i.e. nuclear power plant), and an industrial process (e.g. hydrogen plant) should be optimized under the constraint of satisfying an electricity demand profile with a certain level of variable renewable (wind) penetration. The optimization should entail both the sizing of the components/subsystems that comprise the system and the optimal dispatch strategy (output at any given moment in time from the different subsystems). Some of the capabilities here described have been reported separately in [1, 2, 3]. The purpose of this report is to provide an update on the improvement and extension of those capabilities and to illustrate their integrated application in the economic assessment of N-R HES.« less

A hybrid optimization approach in non-isothermal glass molding

NASA Astrophysics Data System (ADS)

Vu, Anh-Tuan; Kreilkamp, Holger; Krishnamoorthi, Bharathwaj Janaki; Dambon, Olaf; Klocke, Fritz

2016-10-01

Intensively growing demands on complex yet low-cost precision glass optics from the today's photonic market motivate the development of an efficient and economically viable manufacturing technology for complex shaped optics. Against the state-of-the-art replication-based methods, Non-isothermal Glass Molding turns out to be a promising innovative technology for cost-efficient manufacturing because of increased mold lifetime, less energy consumption and high throughput from a fast process chain. However, the selection of parameters for the molding process usually requires a huge effort to satisfy precious requirements of the molded optics and to avoid negative effects on the expensive tool molds. Therefore, to reduce experimental work at the beginning, a coupling CFD/FEM numerical modeling was developed to study the molding process. This research focuses on the development of a hybrid optimization approach in Non-isothermal glass molding. To this end, an optimal configuration with two optimization stages for multiple quality characteristics of the glass optics is addressed. The hybrid Back-Propagation Neural Network (BPNN)-Genetic Algorithm (GA) is first carried out to realize the optimal process parameters and the stability of the process. The second stage continues with the optimization of glass preform using those optimal parameters to guarantee the accuracy of the molded optics. Experiments are performed to evaluate the effectiveness and feasibility of the model for the process development in Non-isothermal glass molding.

Mathematical programming models for the economic design and assessment of wind energy conversion systems

NASA Astrophysics Data System (ADS)

Reinert, K. A.

The use of linear decision rules (LDR) and chance constrained programming (CCP) to optimize the performance of wind energy conversion clusters coupled to storage systems is described. Storage is modelled by LDR and output by CCP. The linear allocation rule and linear release rule prescribe the size and optimize a storage facility with a bypass. Chance constraints are introduced to explicitly treat reliability in terms of an appropriate value from an inverse cumulative distribution function. Details of deterministic programming structure and a sample problem involving a 500 kW and a 1.5 MW WECS are provided, considering an installed cost of $1/kW. Four demand patterns and three levels of reliability are analyzed for optimizing the generator choice and the storage configuration for base load and peak operating conditions. Deficiencies in ability to predict reliability and to account for serial correlations are noted in the model, which is concluded useful for narrowing WECS design options.

Application of genetic algorithm in integrated setup planning and operation sequencing

NASA Astrophysics Data System (ADS)

Kafashi, Sajad; Shakeri, Mohsen

2011-01-01

Process planning is an essential component for linking design and manufacturing process. Setup planning and operation sequencing is two main tasks in process planning. Many researches solved these two problems separately. Considering the fact that the two functions are complementary, it is necessary to integrate them more tightly so that performance of a manufacturing system can be improved economically and competitively. This paper present a generative system and genetic algorithm (GA) approach to process plan the given part. The proposed approach and optimization methodology analyses the TAD (tool approach direction), tolerance relation between features and feature precedence relations to generate all possible setups and operations using workshop resource database. Based on these technological constraints the GA algorithm approach, which adopts the feature-based representation, optimizes the setup plan and sequence of operations using cost indices. Case study show that the developed system can generate satisfactory results in optimizing the setup planning and operation sequencing simultaneously in feasible condition.

The Music Industry as a Vehicle for Economic Analysis

ERIC Educational Resources Information Center

Klein, Christopher C.

2015-01-01

Issues arising in the music industry in response to the availability of digital music files provide an opportunity for exposing undergraduate students to economic analyses rarely covered in the undergraduate economics curriculum. Three of these analyses are covered here: the optimal copyright term, the effect of piracy or illegal file sharing, and…

The potential for distributed generation in Japanese prototype buildings: A DER-CAM analysis of policy, tariff design, building energy use, and technology development (English Version)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Nan; Marnay, Chris; Firestone, Ryan

The August 2003 blackout of the northeastern U.S. and CANADA caused great economic losses and inconvenience to New York City and other affected areas. The blackout was a warning to the rest of the world that the ability of conventional power systems to meet growing electricity demand is questionable. Failure of large power systems can lead to serious emergencies. Introduction of on-site generation, renewable energy such as solar and wind power and the effective utilization of exhaust heat is needed, to meet the growing energy demands of the residential and commercial sectors. Additional benefit can be achieved by integrating thesemore » distributed technologies into distributed energy resource (DER) systems. This work demonstrates a method for choosing and designing economically optimal DER systems. An additional purpose of this research is to establish a database of energy tariffs, DER technology cost and performance characteristics, and building energy consumption for Japan. This research builds on prior DER studies at the Ernest Orlando Lawrence Berkeley National Laboratory (LBNL) and with their associates in the Consortium for Electric Reliability Technology Solutions (CERTS) and operation, including the development of the microgrid concept, and the DER selection optimization program, the Distributed Energy Resources Customer Adoption Model (DER-CAM). DER-CAM is a tool designed to find the optimal combination of installed equipment and an idealized operating schedule to minimize a site's energy bills, given performance and cost data on available DER technologies, utility tariffs, and site electrical and thermal loads over a test period, usually an historic year. Since hourly electric and thermal energy data are rarely available, they are typically developed by building simulation for each of six end use loads used to model the building: electric-only loads, space heating, space cooling, refrigeration, water heating, and natural-gas-only loads. DER-CAM provides a global optimization, albeit idealized, that shows how the necessary useful energy loads can be provided for at minimum cost by selection and operation of on-site generation, heat recovery, cooling, and efficiency improvements. This study examines five prototype commercial buildings and uses DER-CAM to select the economically optimal DER system for each. The five building types are office, hospital, hotel, retail, and sports facility. Each building type was considered for both 5,000 and 10,000 square meter floor sizes. The energy consumption of these building types is based on building energy simulation and published literature. Based on the optimization results, energy conservation and the emissions reduction were also evaluated. Furthermore, a comparison study between Japan and the U.S. has been conducted covering the policy, technology and the utility tariffs effects on DER systems installations. This study begins with an examination of existing DER research. Building energy loads were then generated through simulation (DOE-2) and scaled to match available load data in the literature. Energy tariffs in Japan and the U.S. were then compared: electricity prices did not differ significantly, while commercial gas prices in Japan are much higher than in the U.S. For smaller DER systems, the installation costs in Japan are more than twice those in the U.S., but this difference becomes smaller with larger systems. In Japan, DER systems are eligible for a 1/3 rebate of installation costs, while subsidies in the U.S. vary significantly by region and application. For 10,000 m{sup 2} buildings, significant decreases in fuel consumption, carbon emissions, and energy costs were seen in the economically optimal results. This was most noticeable in the sports facility, followed the hospital and hotel. This research demonstrates that office buildings can benefit from CHP, in contrast to popular opinion. For hospitals and sports facilities, the use of waste heat is particularly effective for water and space heating. For the other building types, waste heat is most effectively used for both heating and cooling. The same examination was done for the 5,000 m{sup 2} buildings. Although CHP installation capacity is smaller and the payback periods are longer, economic, fuel efficiency, and environmental benefits are still seen. While these benefits remain even when subsidies are removed, the increased installation costs lead to lower levels of installation capacity and thus benefit.« less

Social Network Influence and Personal Financial Status

NASA Astrophysics Data System (ADS)

Luo, Shaojun; Morone, Flaviano; Sarraute, Carlos; Makse, Hernan

Networks of social ties emerging from individual economic needs display a highly structured architecture. In response to socio-economic demands, people reshape their circle of contacts for maximizing their social status, and ipso facto, the pattern of their interconnections is strongly correlates with their personal financial situation. In this work we transform this qualitative and verbal statement into an operative definition, which allows us to quantify the economic wellness of individuals trough a measure of their collective influence. We consider the network of mobile phone calls made by the Mexican population during three months, in order to study the correlation of person's economic situation with her network location. Notably, we find that rich people tend to be also the most influential nodes, i.e., they self-organize to optimally position themselves in the network. This finding may be also raised at the level of a principle, a fact that would explain the emergence of the phenomenon of collective influence itself as the result of the local optimization of socio-economic interactions. Our method represents a powerful and efficient indicator of socio-economic robustness, which may be applied to maximize the effect of large scale economic intervention and stimulus policies

An economic analysis of payment for health care services: the United States and Switzerland compared.

PubMed

Zweifel, Peter; Tai-Seale, Ming

2009-06-01

This article seeks to assess whether physician payment reforms in the United States and Switzerland were likely to attain their objectives. We first introduce basic contract theory, with the organizing principle being the degree of information asymmetry between the patient and the health care provider. Depending on the degree of information asymmetry, different forms of payment induce "appropriate" behavior. These theoretical results are then pitted against the RBRVS of the United States to find that a number of its aspects are not optimal. We then turn to Switzerland's Tarmed and find that it fails to conform with the prescriptions of economic contract theory as well. The article closes with a review of possible reforms that could do away with uniform fee schedules to improve the performance of the health care system.

Solving for Efficiency or Decision Criteria: When the Non-unique Nature of Solutions Becomes a Benefit

NASA Astrophysics Data System (ADS)

Pierce, S. A.; Ciarleglio, M.; Dulay, M.; Lowry, T. S.; Sharp, J. M.; Barnes, J. W.; Eaton, D. J.; Tidwell, V. C.

2006-12-01

Work in the literature for groundwater allocation emphasizes finding a truly optimal solution, often with the drawback of limiting the reported results to either maximizing net benefit in regional scale models or minimizing pumping costs for localized cases. From a policy perspective, limited insight can be gained from these studies because the results are restricted to a single, efficient solution and they neglect non-market values that may influence a management decision. Conversely, economically derived objective functions tend to exhibit a plateau upon nearing the optimal value. This plateau effect, or non-uniqueness, is actually a positive feature in the behavior of groundwater systems because it demonstrates that multiple management strategies, serving numerous community preferences, may be considered while still achieving similar quantitative results. An optimization problem takes the same set of initial conditions and looks for the most efficient solution while a decision problem looks at a situation and asks for a solution that meets certain user-defined criteria. In other words, the election of an alternative course of action using a decision support system will not always result in selection of the most `optimized' alternative. To broaden the analytical toolset available for science and policy interaction, we have developed a groundwater decision support system (GWDSS) that generates a suite of management alternatives by pairing a combinatorial search algorithm with a numerical groundwater model for consideration by decision makers and stakeholders. Subject to constraints as defined by community concerns, the tabu optimization engine systematically creates hypothetical management scenarios running hundreds, and even thousands, of simulations, and then saving the best performing realizations. Results of the search are then evaluated against stakeholder preference sets using ranking methods to aid in identifying a subset of alternatives for final consideration. Here we present the development of the GWDSS and its use in the decision making process for the Barton Springs segment of the Edwards Aquifer located in Austin Texas. Using hydrogeologic metrics, together with economic estimates and impervious cover valuations, representative rankings are determined. Post search multi-objective analysis reveals that some highly ranked alternatives meet the preference sets of more than one stakeholder and achieve similar quantitative aquifer performance. These results are important to both modelers and policy makers alike.

Landslide Risk: Economic Valuation in The North-Eastern Zone of Medellin City

NASA Astrophysics Data System (ADS)

Vega, Johnny Alexander; Hidalgo, César Augusto; Johana Marín, Nini

2017-10-01

Natural disasters of a geodynamic nature can cause enormous economic and human losses. The economic costs of a landslide disaster include relocation of communities and physical repair of urban infrastructure. However, when performing a quantitative risk analysis, generally, the indirect economic consequences of such an event are not taken into account. A probabilistic approach methodology that considers several scenarios of hazard and vulnerability to measure the magnitude of the landslide and to quantify the economic costs is proposed. With this approach, it is possible to carry out a quantitative evaluation of the risk by landslides, allowing the calculation of the economic losses before a potential disaster in an objective, standardized and reproducible way, taking into account the uncertainty of the building costs in the study zone. The possibility of comparing different scenarios facilitates the urban planning process, the optimization of interventions to reduce risk to acceptable levels and an assessment of economic losses according to the magnitude of the damage. For the development and explanation of the proposed methodology, a simple case study is presented, located in north-eastern zone of the city of Medellín. This area has particular geomorphological characteristics, and it is also characterized by the presence of several buildings in bad structural conditions. The proposed methodology permits to obtain an estimative of the probable economic losses by earthquake-induced landslides, taking into account the uncertainty of the building costs in the study zone. The obtained estimative shows that the structural intervention of the buildings produces a reduction the order of 21 % in the total landslide risk.

Performance monitoring algorithm for optimizing electrical power generated by using photovoltaic system

NASA Astrophysics Data System (ADS)

Pradeep, M. V. K.; Balbir, S. M. S.; Norani, M. M.

2016-11-01

Demand for electricity in Malaysia has seen a substantial hike in light of the nation's rapid economic development. The current method of generating electricity is through the combustion of fossil fuels which has led to the detrimental effects on the environment besides causing social and economic outbreaks due to its highly volatile prices. Thus the need for a sustainable energy source is paramount and one that is quickly gaining acceptance is solar energy. However, due to the various environmental and geographical factors that affect the generation of solar electricity, the capability of solar electricity generating system (SEGS) is unable to compete with the high conversion efficiencies of conventional energy sources. In order to effectively monitor SEGS, this study is proposing a performance monitoring system that is capable of detecting drops in the system's performance for parallel networks through a diagnostic mechanism. The performance monitoring system consists of microcontroller connected to relevant sensors for data acquisition. The acquired data is transferred to a microcomputer for software based monitoring and analysis. In order to enhance the interception of sunlight by the SEGS, a sensor based sun tracking system is interfaced to the same controller to allow the PV to maneuver itself autonomously to an angle of maximum sunlight exposure.

Total systems design analysis of high performance structures

NASA Technical Reports Server (NTRS)

Verderaime, V.

1993-01-01

Designer-control parameters were identified at interdiscipline interfaces to optimize structural systems performance and downstream development and operations with reliability and least life-cycle cost. Interface tasks and iterations are tracked through a matrix of performance disciplines integration versus manufacturing, verification, and operations interactions for a total system design analysis. Performance integration tasks include shapes, sizes, environments, and materials. Integrity integrating tasks are reliability and recurring structural costs. Significant interface designer control parameters were noted as shapes, dimensions, probability range factors, and cost. Structural failure concept is presented, and first-order reliability and deterministic methods, benefits, and limitations are discussed. A deterministic reliability technique combining benefits of both is proposed for static structures which is also timely and economically verifiable. Though launch vehicle environments were primarily considered, the system design process is applicable to any surface system using its own unique filed environments.

Optimizing Economic Indicators in the Case of Using Two Types of State-Subsidized Chemical Fertilizers for Agricultural Production

NASA Astrophysics Data System (ADS)

Boldea, M.; Sala, F.

2010-09-01

We admit that the mathematical relation between agricultural production f(x, y) and the two types of fertilizers x and y is given by function (1). The coefficients that appear are determined by using the least squares method by comparison with the experimental data. We took into consideration the following economic indicators: absolute benefit, relative benefit, profitableness and cost price. These are maximized or minimized, thus obtaining the optimal solutions by annulling the partial derivatives.

Optimizing your options: Extracting the full economic value of transmission when planning under uncertainty

DOE PAGES

Munoz, Francisco D.; Watson, Jean -Paul; Hobbs, Benjamin F.

2015-06-04

In this study, the anticipated magnitude of needed investments in new transmission infrastructure in the U.S. requires that these be allocated in a way that maximizes the likelihood of achieving society's goals for power system operation. The use of state-of-the-art optimization tools can identify cost-effective investment alternatives, extract more benefits out of transmission expansion portfolios, and account for the huge economic, technology, and policy uncertainties that the power sector faces over the next several decades.

Economics of adopting solar photovoltaic energy systems in irrigation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matlin, R.W.; Katzman, M.T.

An economic analysis concerning the adoption of solar photovoltaic energy systems in irrigation has been made compared to conventional fossil fuel energy sources. The basis for this analysis is presented along with a discussion as to the time of initial profitability, the time of optimal investment, the effects of the tax system, the cost per acre that would make irrigation unviable, and possible governmental incentives that would promote the deployment of photovoltaic irrigation systems between the time of initial profitability and the time of optimal investment.

On the Pontryagin maximum principle for systems with delays. Economic applications

NASA Astrophysics Data System (ADS)

Kim, A. V.; Kormyshev, V. M.; Kwon, O. B.; Mukhametshin, E. R.

2017-11-01

The Pontryagin maximum principle [6] is the key stone of finite-dimensional optimal control theory [1, 2, 5]. So beginning with opening the maximum principle it was important to extend the maximum principle on various classes of dynamical systems. In t he paper we consider some aspects of application of i-smooth analysis [3, 4] in the theory of the Pontryagin maximum principle [6] for systems with delays, obtained results can be applied by elaborating optimal program controls in economic models with delays.

Decision support for the management of water resources at Sub-middle of the São Francisco river basin in Brazil using integrated hydro-economic modeling and scenarios for land use changes

NASA Astrophysics Data System (ADS)

Moraes, M. G. A.; Souza da Silva, G.

2016-12-01

Hydro-economic models can measure the economic effects of different operating rules, environmental restrictions, ecosystems services, technical constraints and institutional constraints. Furthermore, water allocation can be improved by considering economical criteria's. Likewise, climate and land use change can be analyzed to provide resilience. We developed and applied a hydro-economic optimization model to determine the optimal water allocation of main users in the Lower-middle São Francisco River Basin in Northeast (NE) Brazil. The model uses demand curves for the irrigation projects, small farmers and human supply, rather than fixed requirements for water resources. This study analyzed various constraints and operating alternatives for the installed hydropower dams in economic terms. A seven-year period (2000-2006) with water scarcity in the past has been selected to analyze the water availability and the associated optimal economic water allocation. The used constraints are technical, socioeconomic and environmental. The economically impacts of scenarios like prioritizing human consumption, impacts of the implementation of the São Francisco river transposition, human supply without high distribution losses, environmental hydrographs, forced reservoir level control, forced reduced reservoir capacity, alteration of lower flow restriction were analyzed. The results in this period show that scarcity costs related ecosystem service and environmental constraints are significant, and have major impacts (increase of scarcity cost) for consumptive users like irrigation projects. In addition, institutional constraints such as prioritizing human supply, minimum release limits downstream of the reservoirs and the implementation of the transposition project impact the costs and benefits of the two main economic sectors (irrigation and power generation) in the region of the Lower-middle of the São Francisco river basin. Scarcity costs for irrigation users generally increase more (in percentage terms) than the other users associated to environmental and institutional constraints.

Finite horizon optimum control with and without a scrap value

NASA Astrophysics Data System (ADS)

Neck, R.; Blueschke-Nikolaeva, V.; Blueschke, D.

2017-06-01

In this paper, we study the effects of scrap values on the solutions of optimal control problems with finite time horizon. We show how to include a scrap value, either for the state variables or for the state and the control variables, in the OPTCON2 algorithm for the optimal control of dynamic economic systems. We ask whether the introduction of a scrap value can serve as a substitute for an infinite horizon in economic policy optimization problems where the latter option is not available. Using a simple numerical macroeconomic model, we demonstrate that the introduction of a scrap value cannot induce control policies which can be expected for problems with an infinite time horizon.

The ESPAT tool: a general-purpose DSS shell for solving stochastic optimization problems in complex river-aquifer systems

NASA Astrophysics Data System (ADS)

Macian-Sorribes, Hector; Pulido-Velazquez, Manuel; Tilmant, Amaury

2015-04-01

Stochastic programming methods are better suited to deal with the inherent uncertainty of inflow time series in water resource management. However, one of the most important hurdles in their use in practical implementations is the lack of generalized Decision Support System (DSS) shells, usually based on a deterministic approach. The purpose of this contribution is to present a general-purpose DSS shell, named Explicit Stochastic Programming Advanced Tool (ESPAT), able to build and solve stochastic programming problems for most water resource systems. It implements a hydro-economic approach, optimizing the total system benefits as the sum of the benefits obtained by each user. It has been coded using GAMS, and implements a Microsoft Excel interface with a GAMS-Excel link that allows the user to introduce the required data and recover the results. Therefore, no GAMS skills are required to run the program. The tool is divided into four modules according to its capabilities: 1) the ESPATR module, which performs stochastic optimization procedures in surface water systems using a Stochastic Dual Dynamic Programming (SDDP) approach; 2) the ESPAT_RA module, which optimizes coupled surface-groundwater systems using a modified SDDP approach; 3) the ESPAT_SDP module, capable of performing stochastic optimization procedures in small-size surface systems using a standard SDP approach; and 4) the ESPAT_DET module, which implements a deterministic programming procedure using non-linear programming, able to solve deterministic optimization problems in complex surface-groundwater river basins. The case study of the Mijares river basin (Spain) is used to illustrate the method. It consists in two reservoirs in series, one aquifer and four agricultural demand sites currently managed using historical (XIV century) rights, which give priority to the most traditional irrigation district over the XX century agricultural developments. Its size makes it possible to use either the SDP or the SDDP methods. The independent use of surface and groundwater can be examined with and without the aquifer. The ESPAT_DET, ESPATR and ESPAT_SDP modules were executed for the surface system, while the ESPAT_RA and the ESPAT_DET modules were run for the surface-groundwater system. The surface system's results show a similar performance between the ESPAT_SDP and ESPATR modules, with outperform the one showed by the current policies besides being outperformed by the ESPAT_DET results, which have the advantage of the perfect foresight. The surface-groundwater system's results show a robust situation in which the differences between the module's results and the current policies are lower due the use of pumped groundwater in the XX century crops when surface water is scarce. The results are realistic, with the deterministic optimization outperforming the stochastic one, which at the same time outperforms the current policies; showing that the tool is able to stochastically optimize river-aquifer water resources systems. We are currently working in the application of these tools in the analysis of changes in systems' operation under global change conditions. ACKNOWLEDGEMENT: This study has been partially supported by the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economía y Competitividad) funds.

Decision making for best cogeneration power integration into a grid

NASA Astrophysics Data System (ADS)

Al Asmar, Joseph; Zakhia, Nadim; Kouta, Raed; Wack, Maxime

2016-07-01

Cogeneration systems are known to be efficient power systems for their ability to reduce pollution. Their integration into a grid requires simultaneous consideration of the economic and environmental challenges. Thus, an optimal cogeneration power are adopted to face such challenges. This work presents a novelty in selectinga suitable solution using heuristic optimization method. Its aim is to optimize the cogeneration capacity to be installed according to the economic and environmental concerns. This novelty is based on the sensitivity and data analysis method, namely, Multiple Linear Regression (MLR). This later establishes a compromise between power, economy, and pollution, which leads to find asuitable cogeneration power, and further, to be integrated into a grid. The data exploited were the results of the Genetic Algorithm (GA) multi-objective optimization. Moreover, the impact of the utility's subsidy on the selected power is shown.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, C.

Almost every computer architect dreams of achieving high system performance with low implementation costs. A multigauge machine can reconfigure its data-path width, provide parallelism, achieve better resource utilization, and sometimes can trade computational precision for increased speed. A simple experimental method is used here to capture the main characteristics of multigauging. The measurements indicate evidence of near-optimal speedups. Adapting these ideas in designing parallel processors incurs low costs and provides flexibility. Several operational aspects of designing a multigauge machine are discussed as well. Thus, this research reports the technical, economical, and operational feasibility studies of multigauging.

An EOQ model for weibull distribution deterioration with time-dependent cubic demand and backlogging

NASA Astrophysics Data System (ADS)

Santhi, G.; Karthikeyan, K.

2017-11-01

In this article we introduce an economic order quantity model with weibull deterioration and time dependent cubic demand rate where holding costs as a linear function of time. Shortages are allowed in the inventory system are partially and fully backlogging. The objective of this model is to minimize the total inventory cost by using the optimal order quantity and the cycle length. The proposed model is illustrated by numerical examples and the sensitivity analysis is performed to study the effect of changes in parameters on the optimum solutions.

Study for the optimization of a transport aircraft wing for maximum fuel efficiency. Volume 1: Methodology, criteria, aeroelastic model definition and results

NASA Technical Reports Server (NTRS)

Radovcich, N. A.; Dreim, D.; Okeefe, D. A.; Linner, L.; Pathak, S. K.; Reaser, J. S.; Richardson, D.; Sweers, J.; Conner, F.

1985-01-01

Work performed in the design of a transport aircraft wing for maximum fuel efficiency is documented with emphasis on design criteria, design methodology, and three design configurations. The design database includes complete finite element model description, sizing data, geometry data, loads data, and inertial data. A design process which satisfies the economics and practical aspects of a real design is illustrated. The cooperative study relationship between the contractor and NASA during the course of the contract is also discussed.

Use of mathematical decomposition to optimize investments in gas production and distribution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dougherty, E.L.; Lombardino, E.; Hutchinson, P.

1986-01-01

This paper presents an analytical approach based upon the decomposition method of mathematical programming for determining the optimal investment sequence in each year of a planning horizon for a group of reservoirs that produce gas and gas liquids through a trunk-line network and a gas processing plant. The paper describes the development of the simulation and investment planning system (SIPS) to perform the required calculations. Net present value (NPV) is maximized with the requirement that the incremental present value ratio (PWPI) of any investment in any reservoir be greater than a specified minimum value. A unique feature is a gasmore » reservoir simulation model that aids SIPS in evaluating field development investments. The optimal solution supplies specified dry gas offtake requirements through time until the remaining reserves are insufficient to meet requirements economically. The sales value of recovered liquids contributes significantly to NPV, while the required spare gas-producing capacity reduces NPV. Sips was used successfully for 4 years to generate annual investment plans and operating budgets, and to perform many special studies for a producing complex containing over 50 reservoirs. This experience is reviewed. In considering this large problem, SIPS converges to the optimal solution in 10 to 20 iterations. The primary factor that determines this number is how good the starting guess is. Although sips can generate a starting guess, beginning with a previous optimal solution ordinarily results in faster convergence. Computing time increases in proportion to the number of reservoirs because more than 90% of computing time is spent solving the, reservoir, subproblems.« less

Targeting water and energy conservation using big data

NASA Astrophysics Data System (ADS)

Escriva-Bou, A.; Pulido-Velazquez, M.; Lund, J. R.

2016-12-01

Water conservation is often the most cost effective source of additional water supply for water stressed regions to maintain supply reliability with increasing population and/or demands, or shorter-term droughts. In previous research we demonstrated how including energy savings of conserved water can increase willingness to adopt conservation measures, at the same time that increases energy and GHG emissions savings. But the capacity to save water, energy and GHG emissions depends fundamentally in the economic benefits for customers and utilities. Utilities have traditionally used rebates, subsidies or incentives to enhance water conservation. But the economic benefits originated by these rebates depend on the actual savings of the water, energy and GHG emissions. A crucial issue that is not considered in the financial analysis of these rebates is the heterogeneity in water consumption, resulting in rebating households that actually do not need improvements in certain appliances. Smart meters with end-use disaggregation allow to consider this heterogeneity and to target rebates. By using an optimization approach that minimizes water and energy residential costs—accounting for retrofit costs and individual benefits according to previous levels of consumption—we are able to assess economically optimal rebate programs both for customers and utilities. Three programs are considered: first, same economic incentives are provided to all households and then they do their optimal decisions; second, traditional appliance-focused rebates are assessed; and third, utilities provide only rebates to those households that maximize water, energy or GHG emissions savings. Results show that the most economically efficient options for households are not the best options for utilities, and that traditional appliance-focused rebates are much less optimal than targeted rebates.

The economics of optimal urban groundwater management in southwestern USA

NASA Astrophysics Data System (ADS)

Hansen, Jason K.

2012-08-01

Groundwater serves as the primary water source for approximately 80% of public water systems in the United States, and for many more as a secondary source. Traditionally management relies on groundwater to meet rising demand by increasing supply, but climate uncertainty and population growth require more judicious management to achieve efficiency and sustainability. Over-pumping leads to groundwater overdraft and jeopardizes the ability of future users to depend on the resource. Optimal urban groundwater pumping can play a role in solving this conundrum. This paper investigates to what extent and under what circumstances controlled pumping improves social welfare. It considers management in a hydro-economic framework and finds the optimal pumping path and the optimal price path. These allow for the identification of the social benefit of controlled pumping, and the scarcity rent, which is one tool to sustainably manage groundwater resources. The model is numerically illustrated with a case study from Albuquerque, New Mexico (USA). The Albuquerque results indicate that, in the presence of strong demand growth, controlled pumping improves social welfare by 22%, extends use of the resource, and provides planners with a mechanism to advance the economic sustainability of groundwater.

Multi-objective optimization for model predictive control.

PubMed

Wojsznis, Willy; Mehta, Ashish; Wojsznis, Peter; Thiele, Dirk; Blevins, Terry

2007-06-01

This paper presents a technique of multi-objective optimization for Model Predictive Control (MPC) where the optimization has three levels of the objective function, in order of priority: handling constraints, maximizing economics, and maintaining control. The greatest weights are assigned dynamically to control or constraint variables that are predicted to be out of their limits. The weights assigned for economics have to out-weigh those assigned for control objectives. Control variables (CV) can be controlled at fixed targets or within one- or two-sided ranges around the targets. Manipulated Variables (MV) can have assigned targets too, which may be predefined values or current actual values. This MV functionality is extremely useful when economic objectives are not defined for some or all the MVs. To achieve this complex operation, handle process outputs predicted to go out of limits, and have a guaranteed solution for any condition, the technique makes use of the priority structure, penalties on slack variables, and redefinition of the constraint and control model. An engineering implementation of this approach is shown in the MPC embedded in an industrial control system. The optimization and control of a distillation column, the standard Shell heavy oil fractionator (HOF) problem, is adequately achieved with this MPC.

Pebble Bed Reactors Design Optimization Methods and their Application to the Pebble Bed Fluoride Salt Cooled High Temperature Reactor (PB-FHR)

NASA Astrophysics Data System (ADS)

Cisneros, Anselmo Tomas, Jr.

The Fluoride salt cooled High temperature Reactor (FHR) is a class of advanced nuclear reactors that combine the robust coated particle fuel form from high temperature gas cooled reactors, direct reactor auxillary cooling system (DRACS) passive decay removal of liquid metal fast reactors, and the transparent, high volumetric heat capacitance liquid fluoride salt working fluids---flibe (33%7Li2F-67%BeF)---from molten salt reactors. This combination of fuel and coolant enables FHRs to operate in a high-temperature low-pressure design space that has beneficial safety and economic implications. In 2012, UC Berkeley was charged with developing a pre-conceptual design of a commercial prototype FHR---the Pebble Bed- Fluoride Salt Cooled High Temperature Reactor (PB-FHR)---as part of the Nuclear Energy University Programs' (NEUP) integrated research project. The Mark 1 design of the PB-FHR (Mk1 PB-FHR) is 236 MWt flibe cooled pebble bed nuclear heat source that drives an open-air Brayton combine-cycle power conversion system. The PB-FHR's pebble bed consists of a 19.8% enriched uranium fuel core surrounded by an inert graphite pebble reflector that shields the outer solid graphite reflector, core barrel and reactor vessel. The fuel reaches an average burnup of 178000 MWt-d/MT. The Mk1 PB-FHR exhibits strong negative temperature reactivity feedback from the fuel, graphite moderator and the flibe coolant but a small positive temperature reactivity feedback of the inner reflector and from the outer graphite pebble reflector. A novel neutronics and depletion methodology---the multiple burnup state methodology was developed for an accurate and efficient search for the equilibrium composition of an arbitrary continuously refueled pebble bed reactor core. The Burnup Equilibrium Analysis Utility (BEAU) computer program was developed to implement this methodology. BEAU was successfully benchmarked against published results generated with existing equilibrium depletion codes VSOP and PEBBED for a high temperature gas cooled pebble bed reactor. Three parametric studies were performed for exploring the design space of the PB-FHR---to select a fuel design for the PB-FHR] to select a core configuration; and to optimize the PB-FHR design. These parametric studies investigated trends in the dependence of important reactor performance parameters such as burnup, temperature reactivity feedback, radiation damage, etc on the reactor design variables and attempted to understand the underlying reactor physics responsible for these trends. A pebble fuel parametric study determined that pebble fuel should be designed with a carbon to heavy metal ratio (C/HM) less than 400 to maintain negative coolant temperature reactivity coefficients. Seed and thorium blanket-, seed and inert pebble reflector- and seed only core configurations were investigated for annular FHR PBRs---the C/HM of the blanket pebbles and discharge burnup of the thorium blanket pebbles were additional design variable for core configurations with thorium blankets. Either a thorium blanket or graphite pebble reflector is required to shield the outer graphite reflector enough to extend its service lifetime to 60 EFPY. The fuel fabrication costs and long cycle lengths of the thorium blanket fuel limit the potential economic advantages of using a thorium blanket. Therefore, the seed and pebble reflector core configuration was adopted as the baseline core configuration. Multi-objective optimization with respect to economics was performed for the PB-FHR accounting for safety and other physical design constraints derived from the high-level safety regulatory criteria. These physical constraints were applied along in a design tool, Nuclear Application Value Estimator, that evaluated a simplified cash flow economics model based on estimates of reactor performance parameters calculated using correlations based on the results of parametric design studies for a specific PB-FHR design and a set of economic assumptions about the electricity market to evaluate the economic implications of design decisions. The optimal PB-FHR design---Mark 1 PB-FHR---is described along with a detailed summary of its performance characteristics including: the burnup, the burnup evolution, temperature reactivity coefficients, the power distribution, radiation damage distributions, control element worths, decay heat curves and tritium production rates. The Mk1 PB-FHR satisfies the PB-FHR safety criteria. The fuel, moderator (pebble core, pebble shell, graphite matrix, TRISO layers) and coolant have global negative temperature reactivity coefficients and the fuel temperatures are well within their limits.

Integrating environmental and socio-economic indicators of a linked catchment-coastal system using variable environmental intensity.

PubMed

Dymond, John R; Davie, Tim J A; Fenemor, Andrew D; Ekanayake, Jagath C; Knight, Ben R; Cole, Anthony O; de Oca Munguia, Oscar Montes; Allen, Will J; Young, Roger G; Basher, Les R; Dresser, Marc; Batstone, Chris J

2010-09-01

Can we develop land use policy that balances the conflicting views of stakeholders in a catchment while moving toward long term sustainability? Adaptive management provides a strategy for this whereby measures of catchment performance are compared against performance goals in order to progressively improve policy. However, the feedback loop of adaptive management is often slow and irreversible impacts may result before policy has been adapted. In contrast, integrated modelling of future land use policy provides rapid feedback and potentially improves the chance of avoiding unwanted collapse events. Replacing measures of catchment performance with modelled catchment performance has usually required the dynamic linking of many models, both biophysical and socio-economic-and this requires much effort in software development. As an alternative, we propose the use of variable environmental intensity (defined as the ratio of environmental impact over economic output) in a loose coupling of models to provide a sufficient level of integration while avoiding significant effort required for software development. This model construct was applied to the Motueka Catchment of New Zealand where several biophysical (riverine water quantity, sediment, E. coli faecal bacteria, trout numbers, nitrogen transport, marine productivity) models, a socio-economic (gross output, gross margin, job numbers) model, and an agent-based model were linked. An extreme set of land use scenarios (historic, present, and intensive) were applied to this modelling framework. Results suggest that the catchment is presently in a near optimal land use configuration that is unlikely to benefit from further intensification. This would quickly put stress on water quantity (at low flow) and water quality (E. coli). To date, this model evaluation is based on a theoretical test that explores the logical implications of intensification at an unlikely extreme in order to assess the implications of likely growth trajectories from present use. While this has largely been a desktop exercise, it would also be possible to use this framework to model and explore the biophysical and economic impacts of individual or collective catchment visions. We are currently investigating the use of the model in this type of application.

Optimal Energy Extraction From a Hot Water Geothermal Reservoir

NASA Astrophysics Data System (ADS)

Golabi, Kamal; Scherer, Charles R.; Tsang, Chin Fu; Mozumder, Sashi

1981-01-01

An analytical decision model is presented for determining optimal energy extraction rates from hot water geothermal reservoirs when cooled brine is reinjected into the hot water aquifer. This applied economic management model computes the optimal fluid pumping rate and reinjection temperature and the project (reservoir) life consistent with maximum present worth of the net revenues from sales of energy for space heating. The real value of product energy is assumed to increase with time, as is the cost of energy used in pumping the aquifer. The economic model is implemented by using a hydrothermal model that relates hydraulic pumping rate to the quality (temperature) of remaining heat energy in the aquifer. The results of a numerical application to space heating show that profit-maximizing extraction rate increases with interest (discount) rate and decreases as the rate of rise of real energy value increases. The economic life of the reservoir generally varies inversely with extraction rate. Results were shown to be sensitive to permeability, initial equilibrium temperature, well cost, and well life.

Optimal social-networking strategy is a function of socioeconomic conditions.

PubMed

Oishi, Shigehiro; Kesebir, Selin

2012-12-01

In the two studies reported here, we examined the relation among residential mobility, economic conditions, and optimal social-networking strategy. In study 1, a computer simulation showed that regardless of economic conditions, having a broad social network with weak friendship ties is advantageous when friends are likely to move away. By contrast, having a small social network with deep friendship ties is advantageous when the economy is unstable but friends are not likely to move away. In study 2, we examined the validity of the computer simulation using a sample of American adults. Results were consistent with the simulation: American adults living in a zip code where people are residentially stable but economically challenged were happier if they had a narrow but deep social network, whereas in other socioeconomic conditions, people were generally happier if they had a broad but shallow networking strategy. Together, our studies demonstrate that the optimal social-networking strategy varies as a function of socioeconomic conditions.

An economical state-dependent telecloning for a multiparticle GHZ state

NASA Astrophysics Data System (ADS)

Meng, Fan-Xu; Yu, Xu-Tao; Zhang, Zai-Chen

2018-03-01

The scheme for a 1-3 economical state-dependent telecloning of a multiparticle GHZ state is proposed. It shows that every one of spatially separated three receivers obtains one copy which is dependent on original state. Fidelity can hit to the optimal fidelity 5/6. Meantime, we also propose a 1-3 asymmetric economical telecloning of a particular multiparticle GHZ state by parameterizing coefficients of state in the channel. The three fidelities can reach the best match that is the same as the symmetric case. Furthermore, the above two schemes can be generalized into the case of 1-M(M=2k+1,k>0) telecloning of a multiparticle GHZ state. Satisfying some certain conditions, optimal fidelities with 1/2+(M+1)/4M can be obtained. As without ancilla in the channel, the number of entangled particles is less than one in current schemes and fidelities can be optimal if the original state is an equatorial state.

Optimal allocation of bulk water supplies to competing use sectors based on economic criterion - An application to the Chao Phraya River Basin, Thailand

NASA Astrophysics Data System (ADS)

Divakar, L.; Babel, M. S.; Perret, S. R.; Gupta, A. Das

2011-04-01

SummaryThe study develops a model for optimal bulk allocations of limited available water based on an economic criterion to competing use sectors such as agriculture, domestic, industry and hydropower. The model comprises a reservoir operation module (ROM) and a water allocation module (WAM). ROM determines the amount of water available for allocation, which is used as an input to WAM with an objective function to maximize the net economic benefits of bulk allocations to different use sectors. The total net benefit functions for agriculture and hydropower sectors and the marginal net benefit from domestic and industrial sectors are established and are categorically taken as fixed in the present study. The developed model is applied to the Chao Phraya basin in Thailand. The case study results indicate that the WAM can improve net economic returns compared to the current water allocation practices.

Leveraging University Research to Serve Economic Development: An Analysis of Policy Dynamics in and across Three US States

ERIC Educational Resources Information Center

Warshaw, Jarrett B.; Hearn, James C.

2014-01-01

As economic competition becomes more global and knowledge-based, US states have independently pursued initiatives in research and development (R&D) and science and technology (S&T). Policy efforts often entwine government, universities, and industry, aiming to stimulate socially optimal levels of innovation and economic growth.…

Spatially dynamic forest management to sustain biodiversity and economic returns.

PubMed

Mönkkönen, Mikko; Juutinen, Artti; Mazziotta, Adriano; Miettinen, Kaisa; Podkopaev, Dmitry; Reunanen, Pasi; Salminen, Hannu; Tikkanen, Olli-Pekka

2014-02-15

Production of marketed commodities and protection of biodiversity in natural systems often conflict and thus the continuously expanding human needs for more goods and benefits from global ecosystems urgently calls for strategies to resolve this conflict. In this paper, we addressed what is the potential of a forest landscape to simultaneously produce habitats for species and economic returns, and how the conflict between habitat availability and timber production varies among taxa. Secondly, we aimed at revealing an optimal combination of management regimes that maximizes habitat availability for given levels of economic returns. We used multi-objective optimization tools to analyze data from a boreal forest landscape consisting of about 30,000 forest stands simulated 50 years into future. We included seven alternative management regimes, spanning from the recommended intensive forest management regime to complete set-aside of stands (protection), and ten different taxa representing a wide variety of habitat associations and social values. Our results demonstrate it is possible to achieve large improvements in habitat availability with little loss in economic returns. In general, providing dead-wood associated species with more habitats tended to be more expensive than providing requirements for other species. No management regime alone maximized habitat availability for the species, and systematic use of any single management regime resulted in considerable reductions in economic returns. Compared with an optimal combination of management regimes, a consistent application of the recommended management regime would result in 5% reduction in economic returns and up to 270% reduction in habitat availability. Thus, for all taxa a combination of management regimes was required to achieve the optimum. Refraining from silvicultural thinnings on a proportion of stands should be considered as a cost-effective management in commercial forests to reconcile the conflict between economic returns and habitat required by species associated with dead-wood. In general, a viable strategy to maintain biodiversity in production landscapes would be to diversify management regimes. Our results emphasize the importance of careful landscape level forest management planning because optimal combinations of management regimes were taxon-specific. For cost-efficiency, the results call for balanced and correctly targeted strategies among habitat types. Copyright © 2013 Elsevier Ltd. All rights reserved.

Practical application of economic well-performance criteria to the optimization of fracturing treatment design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, R.W.; Phillips, A.M.

1988-02-01

Low-permeability reservoirs are currently being propped with sand, resin-coated sand, intermediate-density proppants, and bauxite. This wide range of proppant cost and performance has resulted in a proliferation of proppant selection models. Initially, a rather vague relationship between well depth and proppant strength dictated the choice of proppant. More recently, computerized models of varying complexity have become available that use net-present-value (NPV) calculations. The input is based on the operator's performance goals for each well and on specific reservoir properties. Simpler, noncomputerized approaches also being used include cost/performance comparisons and nomographs. Each type of model, including several of the computerized models,more » will be examined. By use of these models and NPV calculations, optimum fracturing treatment designs have been developed for such low-permeability reservoirs as the Prue in Oklahoma. Typical well conditions are used in each of the selection models and the results are compared. The computerized models allow the operator to determine, before fracturing, how changes in proppant type, size, and quantity will affect postfracture production over time periods ranging from several months to many years. Thus, the operator can choose the fracturing treatment design that best satisfies the economic performance goals for a particular well, regardless of whether those goals are long or short term.« less

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

PubMed

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

2013-11-01

The paper describes a software system capable of formulating alternative optimal Municipal Solid Wastes (MSWs) management plans, each of which meets a set of constraints that may reflect selected objections and/or wishes of local communities. The objective function to be minimized in each plan is the sum of the annualized capital investment and annual operating cost of all transportation, treatment and final disposal operations involved, taking into consideration the possible income from the sale of products and any other financial incentives or disincentives that may exist. For each plan formulated, the system generates several reports that define the plan, analyze its cost elements and yield an indicative profile of selected types of installations, as well as data files that facilitate the geographic representation of the optimal solution in maps through the use of GIS. A number of these reports compare the technical and economic data from all scenarios considered at the study area, municipality and installation level constituting in effect sensitivity analysis. The generation of alternative plans offers local authorities the opportunity of choice and the results of the sensitivity analysis allow them to choose wisely and with consensus. The paper presents also an application of this software system in the capital Region of Attica in Greece, for the purpose of developing an optimal waste transportation system in line with its approved waste management plan. The formulated plan was able to: (a) serve 113 Municipalities and Communities that generate nearly 2 milliont/y of comingled MSW with distinctly different waste collection patterns, (b) take into consideration several existing waste transfer stations (WTS) and optimize their use within the overall plan, (c) select the most appropriate sites among the potentially suitable (new and in use) ones, (d) generate the optimal profile of each WTS proposed, and (e) perform sensitivity analysis so as to define the impact of selected sets of constraints (limitations in the availability of sites and in the capacity of their installations) on the design and cost of the ensuing optimal waste transfer system. The results show that optimal planning offers significant economic savings to municipalities, while reducing at the same time the present levels of traffic, fuel consumptions and air emissions in the congested Athens basin. Copyright © 2013 Elsevier Ltd. All rights reserved.

Economic trade-offs between genetic improvement and longevity in dairy cattle.

PubMed

De Vries, A

2017-05-01

Genetic improvement in sires used for artificial insemination (AI) is increasing faster compared with a decade ago. The genetic merit of replacement heifers is also increasing faster and the genetic lag with older cows in the herd increases. This may trigger greater cow culling to capture this genetic improvement. On the other hand, lower culling rates are often viewed favorably because the costs and environmental effects of maintaining herd size are generally lower. Thus, there is an economic trade-off between genetic improvement and longevity in dairy cattle. The objective of this study was to investigate the principles, literature, and magnitude of these trade-offs. Data from the Council on Dairy Cattle Breeding show that the estimated breeding value of the trait productive life has increased for 50 yr but the actual time cows spend in the herd has not increased. The average annual herd cull rate remains at approximately 36% and cow longevity is approximately 59 mo. The annual increase in average estimated breeding value of the economic index lifetime net merit of Holstein sires is accelerating from $40/yr when the sire entered AI around 2002 to $171/yr for sires that entered AI around 2012. The expectation is therefore that heifers born in 2015 are approximately $50 more profitable per lactation than heifers born in 2014. Asset replacement theory shows that assets should be replaced sooner when the challenging asset is technically improved. Few studies have investigated the direct effects of genetic improvement on optimal cull rates. A 35-yr-old study found that the economically optimal cull rates were in the range of 25 to 27%, compared with the lowest possible involuntary cull rate of 20%. Only a small effect was observed of using the best surviving dams to generate the replacement heifer calves. Genetic improvement from sires had little effect on the optimal cull rate. Another study that optimized culling decisions for individual cows also showed that the effect of changes in genetic improvement of milk revenue minus feed cost on herd longevity was relatively small. Reduced involuntary cull rates improved profitability, but also increased optimal voluntary culling. Finally, an economically optimal culling model with prices from 2015 confirmed that optimal annual cull rates were insensitive to heifer prices and therefore insensitive to genetic improvement in heifers. In conclusion, genetic improvement is important but does not warrant short cow longevity. Economic cow longevity continues to depends more on cow depreciation than on accelerated genetic improvements in heifers. This is confirmed by old and new studies. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Assessment of economically optimal water management and geospatial potential for large-scale water storage

NASA Astrophysics Data System (ADS)

Weerasinghe, Harshi; Schneider, Uwe A.

2010-05-01

Assessment of economically optimal water management and geospatial potential for large-scale water storage Weerasinghe, Harshi; Schneider, Uwe A Water is an essential but limited and vulnerable resource for all socio-economic development and for maintaining healthy ecosystems. Water scarcity accelerated due to population expansion, improved living standards, and rapid growth in economic activities, has profound environmental and social implications. These include severe environmental degradation, declining groundwater levels, and increasing problems of water conflicts. Water scarcity is predicted to be one of the key factors limiting development in the 21st century. Climate scientists have projected spatial and temporal changes in precipitation and changes in the probability of intense floods and droughts in the future. As scarcity of accessible and usable water increases, demand for efficient water management and adaptation strategies increases as well. Addressing water scarcity requires an intersectoral and multidisciplinary approach in managing water resources. This would in return safeguard the social welfare and the economical benefit to be at their optimal balance without compromising the sustainability of ecosystems. This paper presents a geographically explicit method to assess the potential for water storage with reservoirs and a dynamic model that identifies the dimensions and material requirements under an economically optimal water management plan. The methodology is applied to the Elbe and Nile river basins. Input data for geospatial analysis at watershed level are taken from global data repositories and include data on elevation, rainfall, soil texture, soil depth, drainage, land use and land cover; which are then downscaled to 1km spatial resolution. Runoff potential for different combinations of land use and hydraulic soil groups and for mean annual precipitation levels are derived by the SCS-CN method. Using the overlay and decision tree algorithms in GIS, potential water storage sites are identified for constructing regional reservoirs. Subsequently, sites are prioritized based on runoff generation potential (m3 per unit area), and geographical suitability for constructing storage structures. The results from the spatial analysis are used as input for the optimization model. Allocation of resources and appropriate dimension for dams and associated structures are identified using the optimization model. The model evaluates the capability of alternative reservoirs for cost-efficient water management. The Geographic Information System is used to store, analyze, and integrate spatially explicit and non-spatial attribute information whereas the algebraic modeling platform is used to develop the dynamic optimization model. The results of this methodology are validated over space against satellite remote sensing data and existing data on reservoir capacities and runoff. The method is suitable for application of on-farm water storage structures, water distribution networks, and moisture conservation structures in a global context.

Postgenomic approaches to using corynebacteria as biocatalysts.

PubMed

Vertès, Alain A; Inui, Masayuki; Yukawa, Hideaki

2012-01-01

Corynebacterium glutamicum exhibits numerous ideal intrinsic attributes as a factory of primary and secondary metabolites. The versatile capabilities of this organism have long been implemented at the industrial scale to produce an array of amino acids at high yields and conversion rates, thereby enabling the development of an entire industry. The postgenomic era provides a new technological platform not only to further optimize the intrinsic attributes of C. glutamicum whole cells as biocatalysts, but also to dramatically expand the product portfolio that can be manufactured by this organism, from amino acids to commodity chemicals. This review addresses the methods and strain optimization strategies enabled by genomic information and associated techniques. Their implementation has provided important additional incremental improvements to the economics of industry-scale manufacturing in which C. glutamicum and its episomal elements are used as a performing host-vector system.

Research on optimization of combustion efficiency of thermal power unit based on genetic algorithm

NASA Astrophysics Data System (ADS)

Zhou, Qiongyang

2018-04-01

In order to improve the economic performance and reduce pollutant emissions of thermal power units, the characteristics of neural network in establishing boiler combustion model are analyzed based on the analysis of the main factors affecting boiler efficiency by using orthogonal method. In addition, on the basis of this model, the genetic algorithm is used to find the best control amount of the furnace combustion in a certain working condition. Through the genetic algorithm based on real number encoding and roulette selection is concluded: the best control quantity at a condition of furnace combustion can be combined with the boiler combustion system model for neural network training. The precision of the neural network model is further improved, and the basic work is laid for the research of the whole boiler combustion optimization system.

Need for Cost Optimization of Space Life Support Systems

NASA Technical Reports Server (NTRS)

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.

The Application of Optimal Defaults to Improve Elementary School Lunch Selections: Proof of Concept

ERIC Educational Resources Information Center

Loeb, Katharine L.; Radnitz, Cynthia; Keller, Kathleen L.; Schwartz, Marlene B.; Zucker, Nancy; Marcus, Sue; Pierson, Richard N.; Shannon, Michael; DeLaurentis, Danielle

2018-01-01

Background: In this study, we applied behavioral economics to optimize elementary school lunch choices via parent-driven decisions. Specifically, this experiment tested an optimal defaults paradigm, examining whether strategically manipulating the health value of a default menu could be co-opted to improve school-based lunch selections. Methods:…

Overall Performance Evaluation of Tubular Scraper Conveyors Using a TOPSIS-Based Multiattribute Decision-Making Method

PubMed Central

Yao, Yanping; Kou, Ziming; Meng, Wenjun; Han, Gang

2014-01-01

Properly evaluating the overall performance of tubular scraper conveyors (TSCs) can increase their overall efficiency and reduce economic investments, but such methods have rarely been studied. This study evaluated the overall performance of TSCs based on the technique for order of preference by similarity to ideal solution (TOPSIS). Three conveyors of the same type produced in the same factory were investigated. Their scraper space, material filling coefficient, and vibration coefficient of the traction components were evaluated. A mathematical model of the multiattribute decision matrix was constructed; a weighted judgment matrix was obtained using the DELPHI method. The linguistic positive-ideal solution (LPIS), the linguistic negative-ideal solution (LNIS), and the distance from each solution to the LPIS and the LNIS, that is, the approximation degrees, were calculated. The optimal solution was determined by ordering the approximation degrees for each solution. The TOPSIS-based results were compared with the measurement results provided by the manufacturer. The ordering result based on the three evaluated parameters was highly consistent with the result provided by the manufacturer. The TOPSIS-based method serves as a suitable evaluation tool for the overall performance of TSCs. It facilitates the optimal deployment of TSCs for industrial purposes. PMID:24991646

Electrolyzers Enhancing Flexibility in Electric Grids

DOE PAGES

Mohanpurkar, Manish; Luo, Yusheng; Terlip, Danny; ...

2017-11-10

This paper presents a real-time simulation with a hardware-in-the-loop (HIL)-based approach for verifying the performance of electrolyzer systems in providing grid support. Hydrogen refueling stations may use electrolyzer systems to generate hydrogen and are proposed to have the potential of becoming smarter loads that can proactively provide grid services. On the basis of experimental findings, electrolyzer systems with balance of plant are observed to have a high level of controllability and hence can add flexibility to the grid from the demand side. A generic front end controller (FEC) is proposed, which enables an optimal operation of the load on themore » basis of market and grid conditions. This controller has been simulated and tested in a real-time environment with electrolyzer hardware for a performance assessment. It can optimize the operation of electrolyzer systems on the basis of the information collected by a communication module. Real-time simulation tests are performed to verify the performance of the FEC-driven electrolyzers to provide grid support that enables flexibility, greater economic revenue, and grid support for hydrogen producers under dynamic conditions. In conclusion, the FEC proposed in this paper is tested with electrolyzers, however, it is proposed as a generic control topology that is applicable to any load.« less

Multi-objective optimal dispatch of distributed energy resources

NASA Astrophysics Data System (ADS)

Longe, Ayomide

This thesis is composed of two papers which investigate the optimal dispatch for distributed energy resources. In the first paper, an economic dispatch problem for a community microgrid is studied. In this microgrid, each agent pursues an economic dispatch for its personal resources. In addition, each agent is capable of trading electricity with other agents through a local energy market. In this paper, a simple market structure is introduced as a framework for energy trades in a small community microgrid such as the Solar Village. It was found that both sellers and buyers benefited by participating in this market. In the second paper, Semidefinite Programming (SDP) for convex relaxation of power flow equations is used for optimal active and reactive dispatch for Distributed Energy Resources (DER). Various objective functions including voltage regulation, reduced transmission line power losses, and minimized reactive power charges for a microgrid are introduced. Combinations of these goals are attained by solving a multiobjective optimization for the proposed ORPD problem. Also, both centralized and distributed versions of this optimal dispatch are investigated. It was found that SDP made the optimal dispatch faster and distributed solution allowed for scalability.

Collective neurodynamic optimization for economic emission dispatch problem considering valve point effect in microgrid.

PubMed

Wang, Tiancai; He, Xing; Huang, Tingwen; Li, Chuandong; Zhang, Wei

2017-09-01

The economic emission dispatch (EED) problem aims to control generation cost and reduce the impact of waste gas on the environment. It has multiple constraints and nonconvex objectives. To solve it, the collective neurodynamic optimization (CNO) method, which combines heuristic approach and projection neural network (PNN), is attempted to optimize scheduling of an electrical microgrid with ten thermal generators and minimize the plus of generation and emission cost. As the objective function has non-derivative points considering valve point effect (VPE), differential inclusion approach is employed in the PNN model introduced to deal with them. Under certain conditions, the local optimality and convergence of the dynamic model for the optimization problem is analyzed. The capability of the algorithm is verified in a complicated situation, where transmission loss and prohibited operating zones are considered. In addition, the dynamic variation of load power at demand side is considered and the optimal scheduling of generators within 24 h is described. Copyright © 2017 Elsevier Ltd. All rights reserved.

An Analysis of the DER Adoption Climate in Japan UsingOptimization Results for Prototype Buildings with U.S. Comparisons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Nan; Marnay, Chris; Firestone, Ryan

2006-06-16

This research demonstrates economically optimal distributedenergy resource (DER) system choice using the DER choice and operationsoptimization program, the Distributed Energy Resources Customer AdoptionModel (DER-CAM). DER-CAM finds the optimal combination of installedequipment given prevailing utility tariffs and fuel prices, siteelectrical and thermal loads (including absorption cooling), and a menuof available equipment. It provides a global optimization, albeitidealized, that shows how site useful energy loads can be served atminimum cost. Five prototype Japanese commercial buildings are examinedand DER-CAM is applied to select the economically optimal DER system foreach. Based on the optimization results, energy and emission reductionsare evaluated. Significant decreases in fuelmore » consumption, carbonemissions, and energy costs were seen in the DER-CAM results. Savingswere most noticeable in the prototype sports facility, followed by thehospital, hotel, and office building. Results show that DER with combinedheat and power equipment is a promising efficiency and carbon mitigationstrategy, but that precise system design is necessary. Furthermore, aJapan-U.S. comparison study of policy, technology, and utility tariffsrelevant to DER installation is presented.« less

Economics of Third-Party Central Heating Plants to Supply the Army

DTIC Science & Technology

1992-01-01

Third-Party Gas-Fired Boiler Economics 52 APPENDIX C: Third-Party Gas Turbine Cogeneration Economics ( PURPA ) 58 APPENDIX D: Government Gas Turbine...Turbine Cogeneration Economics (Installation and PURPA Purchase) 76 APPENDIX G: Checklist for Identifying Optimal Third-Party Projects and Bidders 82...of scale 37 4 Relative costs of thermal energy from third-party cogeneration plants (@ 4C/kWh PURPA payment) 38 5 Comparison of life-cycle costs for

Optimizing basin-scale coupled water quantity and water quality man-agement with stochastic dynamic programming

NASA Astrophysics Data System (ADS)

Davidsen, Claus; Liu, Suxia; Mo, Xingguo; Engelund Holm, Peter; Trapp, Stefan; Rosbjerg, Dan; Bauer-Gottwein, Peter

2015-04-01

Few studies address water quality in hydro-economic models, which often focus primarily on optimal allocation of water quantities. Water quality and water quantity are closely coupled, and optimal management with focus solely on either quantity or quality may cause large costs in terms of the oth-er component. In this study, we couple water quality and water quantity in a joint hydro-economic catchment-scale optimization problem. Stochastic dynamic programming (SDP) is used to minimize the basin-wide total costs arising from water allocation, water curtailment and water treatment. The simple water quality module can handle conservative pollutants, first order depletion and non-linear reactions. For demonstration purposes, we model pollutant releases as biochemical oxygen demand (BOD) and use the Streeter-Phelps equation for oxygen deficit to compute the resulting min-imum dissolved oxygen concentrations. Inelastic water demands, fixed water allocation curtailment costs and fixed wastewater treatment costs (before and after use) are estimated for the water users (agriculture, industry and domestic). If the BOD concentration exceeds a given user pollution thresh-old, the user will need to pay for pre-treatment of the water before use. Similarly, treatment of the return flow can reduce the BOD load to the river. A traditional SDP approach is used to solve one-step-ahead sub-problems for all combinations of discrete reservoir storage, Markov Chain inflow clas-ses and monthly time steps. Pollution concentration nodes are introduced for each user group and untreated return flow from the users contribute to increased BOD concentrations in the river. The pollutant concentrations in each node depend on multiple decision variables (allocation and wastewater treatment) rendering the objective function non-linear. Therefore, the pollution concen-tration decisions are outsourced to a genetic algorithm, which calls a linear program to determine the remainder of the decision variables. This hybrid formulation keeps the optimization problem computationally feasible and represents a flexible and customizable method. The method has been applied to the Ziya River basin, an economic hotspot located on the North China Plain in Northern China. The basin is subject to severe water scarcity, and the rivers are heavily polluted with wastewater and nutrients from diffuse sources. The coupled hydro-economic optimiza-tion model can be used to assess costs of meeting additional constraints such as minimum water qual-ity or to economically prioritize investments in waste water treatment facilities based on economic criteria.

4E analysis and multi objective optimization of a micro gas turbine and solid oxide fuel cell hybrid combined heat and power system

NASA Astrophysics Data System (ADS)

Sanaye, Sepehr; Katebi, Arash

2014-02-01

Energy, exergy, economic and environmental (4E) analysis and optimization of a hybrid solid oxide fuel cell and micro gas turbine (SOFC-MGT) system for use as combined generation of heat and power (CHP) is investigated in this paper. The hybrid system is modeled and performance related results are validated using available data in literature. Then a multi-objective optimization approach based on genetic algorithm is incorporated. Eight system design parameters are selected for the optimization procedure. System exergy efficiency and total cost rate (including capital or investment cost, operational cost and penalty cost of environmental emissions) are the two objectives. The effects of fuel unit cost, capital investment and system power output on optimum design parameters are also investigated. It is observed that the most sensitive and important design parameter in the hybrid system is fuel cell current density which has a significant effect on the balance between system cost and efficiency. The selected design point from the Pareto distribution of optimization results indicates a total system exergy efficiency of 60.7%, with estimated electrical energy cost 0.057 kW-1 h-1, and payback period of about 6.3 years for the investment.

A multiple objective optimization approach to quality control

NASA Technical Reports Server (NTRS)

Seaman, Christopher Michael

1991-01-01

The use of product quality as the performance criteria for manufacturing system control is explored. The goal in manufacturing, for economic reasons, is to optimize product quality. The problem is that since quality is a rather nebulous product characteristic, there is seldom an analytic function that can be used as a measure. Therefore standard control approaches, such as optimal control, cannot readily be applied. A second problem with optimizing product quality is that it is typically measured along many dimensions: there are many apsects of quality which must be optimized simultaneously. Very often these different aspects are incommensurate and competing. The concept of optimality must now include accepting tradeoffs among the different quality characteristics. These problems are addressed using multiple objective optimization. It is shown that the quality control problem can be defined as a multiple objective optimization problem. A controller structure is defined using this as the basis. Then, an algorithm is presented which can be used by an operator to interactively find the best operating point. Essentially, the algorithm uses process data to provide the operator with two pieces of information: (1) if it is possible to simultaneously improve all quality criteria, then determine what changes to the process input or controller parameters should be made to do this; and (2) if it is not possible to improve all criteria, and the current operating point is not a desirable one, select a criteria in which a tradeoff should be made, and make input changes to improve all other criteria. The process is not operating at an optimal point in any sense if no tradeoff has to be made to move to a new operating point. This algorithm ensures that operating points are optimal in some sense and provides the operator with information about tradeoffs when seeking the best operating point. The multiobjective algorithm was implemented in two different injection molding scenarios: tuning of process controllers to meet specified performance objectives and tuning of process inputs to meet specified quality objectives. Five case studies are presented.

High titer L-lactic acid production from corn stover with minimum wastewater generation and techno-economic evaluation based on Aspen plus modeling.

PubMed

Liu, Gang; Sun, Jiaoe; Zhang, Jian; Tu, Yi; Bao, Jie

2015-12-01

Technological potentials of l-lactic acid production from corn stover feedstock were investigated by experimental and techno-economic studies. An optimal performance with 104.5 g/L in l-lactic acid titer and 71.5% in overall yield from cellulose in corn stover to l-lactic acid using an engineered Pediococcus acidilactici strain were obtained by overcoming several technical barriers. A rigorous Aspen plus model for l-lactic acid production starting from dry dilute acid pretreated and biodetoxified corn stover was developed. The techno-economic analysis shows that the minimum l-lactic acid selling price (MLSP) was $0.523 per kg, which was close to that of the commercial l-lactic acid produced from starch feedstock, and 24% less expensive than that of ethanol from corn stover, even though the xylose utilization was not considered. The study provided a prototype of industrial application and an evaluation model for high titer l-lactic acid production from lignocellulose feedstock. Copyright © 2015 Elsevier Ltd. All rights reserved.

Technical and economic assessment of different options for minor actinide transmutation: the French case

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chabert, C.; Coquelet-Pascal, C.; Saturnin, A.

Studies have been performed to assess the industrial perspectives of partitioning and transmutation of long-lived elements. These studies were carried out in tight connection with GEN-IV systems development. The results include the technical and economic evaluation of fuel cycle scenarios along with different options for optimizing the processes between the minor actinide transmutation in fast neutron reactors, their interim storage and geological disposal of ultimate waste. The results are analysed through several criteria (impacts on waste, on waste repository, on fuel cycle plants, on radiological exposure of workers, on costs and on industrial risks). These scenario evaluations take place inmore » the French context which considers the deployment of the first Sodium-cooled Fast Reactor (SFR) in 2040. 3 management options of minor actinides have been studied: no transmutation, transmutation in SFR and transmutation in an accelerator-driven system (ADS). Concerning economics the study shows that the cost overrun related to the transmutation process could vary between 5 to 9% in SFR and 26 % in the case of ADS.« less

The economic production of alcohol fuels from coal-derived synthesis gas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kugler, E.L.; Dadyburjor, D.B.; Yang, R.Y.K.

1995-12-31

The objectives of this project are to discover, (1) study and evaluate novel heterogeneous catalytic systems for the production of oxygenated fuel enhancers from synthesis gas. Specifically, alternative methods of preparing catalysts are to be investigated, and novel catalysts, including sulfur-tolerant ones, are to be pursued. (Task 1); (2) explore, analytically and on the bench scale, novel reactor and process concepts for use in converting syngas to liquid fuel products. (Task 1); (3) simulate by computer the most energy efficient and economically efficient process for converting coal to energy, with primary focus on converting syngas to fuel alcohols. (Task 2);more » (4) develop on the bench scale the best holistic combination of chemistry, catalyst, reactor and total process configuration integrated with the overall coal conversion process to achieve economic optimization for the conversion of syngas to liquid products within the framework of achieving the maximum cost effective transformation of coal to energy equivalents. (Tasks 1 and 2); and (5) evaluate the combustion, emission and performance characteristics of fuel alcohols and blends of alcohols with petroleum-based fuels. (Task 2)« less

Indicators for technological, environmental and economic sustainability of ozone contactors.

PubMed

Zhang, Jie; Tejada-Martinez, Andres E; Lei, Hongxia; Zhang, Qiong

2016-09-15

Various studies have attempted to improve disinfection efficiency as a way to improve the sustainability of ozone disinfection which is a critical unit process for water treatment. Baffling factor, CT10, and log-inactivation are commonly used indicators for quantifying disinfection credits. However the applicability of these indicators and the relationship between these indicators have not been investigated in depth. This study simulated flow, tracer transport, and chemical species transport in a full-scale ozone contactor operated by the City of Tampa Water Department and six other modified designs using computational fluid dynamics (CFD). Through analysis of the simulation results, we found that baffling factor and CT10 are not optimal indicators of disinfection performance. We also found that the relationship between effluent CT obtained from CT transport simulation and baffling factor depends on the location of ozone release. In addition, we analyzed the environmental and economic impacts of ozone contactor designs and upgrades and developed a composite indicator to quantify the sustainability in technological, environmental and economic dimensions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Lost opportunities and future avenues to reconcile hydropower and sediment transport in the Mekong Basin through optimal sequencing of dam portfolios.

NASA Astrophysics Data System (ADS)

Castelletti, A.; Schmitt, R. J. P.; Bizzi, S.; Kondolf, G. M.

2017-12-01

Dams are essential to meet growing water and energy demands. While dams cumulatively impact downstream rivers on network-scales, dam development is mostly based on ad-hoc economic and environmental assessments of single dams. Here, we provide evidence that replacing this ad-hoc approach with early strategic planning of entire dam portfolios can greatly reduce conflicts between economic and environmental objectives of dams. In the Mekong Basin (800,000km2), 123 major dam sites (status-quo: 56 built and under construction) could generate 280,000 GWh/yr of hydropower. Cumulatively, dams risk interrupting the basin's sediment dynamics with severe impacts on livelihoods and eco-systems. To evaluate cumulative impacts and benefits of the ad-hoc planned status-quo portfolio, we combine the CASCADE sediment connectivity model with data on hydropower production and sediment trapping at each dam site. We couple CASCADE to a multi-objective genetic algorithm (BORG) identifying a) portfolios resulting in an optimal trade-off between cumulative sediment trapping and hydropower production and b) an optimal development sequence for each portfolio. We perform this analysis first for the pristine basin (i.e., without pre-existing dams) and then starting from the status-quo portfolio, deriving policy recommendations for which dams should be prioritized in the near future. The status-quo portfolio creates a sub-optimal trade-off between hydropower and sediment trapping, exploiting 50 % of the basin's hydro-electric potential and trapping 60 % of the sediment load. Alternative optimal portfolios could have produced equivalent hydropower for 30 % sediment trapping. Imminent development of mega-dams in the lower basin will increase hydropower production by 20 % but increase sediment trapping to >90 %. In contrast, following an optimal development sequence can still increase hydropower by 30 % with limited additional sediment trapping by prioritizing dams in upper parts of the basin. Our findings argue for reconsidering some imminent dam developments in the Mekong. With nearly 3000 dams awaiting development world-wide, results from the Mekong are of global importance, demonstrating that strategic planning and sequencing of dams is instrumental for sustainable development of dams and hydropower.

Can we do better? Economic analysis of human resource investment to improve home care service for the elderly in Serbia

PubMed Central

Mihic, Marko M; Todorovic, Marija Lj; Obradovic, Vladimir Lj; Mitrovic, Zorica M

2016-01-01

Background Social services aimed at the elderly are facing great challenges caused by progressive aging of the global population but also by the constant pressure to spend funds in a rational manner. Purpose This paper focuses on analyzing the investments into human resources aimed at enhancing home care for the elderly since many countries have recorded progress in the area over the past years. The goal of this paper is to stress the significance of performing an economic analysis of the investment. Methods This paper combines statistical analysis methods such as correlation and regression analysis, methods of economic analysis, and scenario method. Results The economic analysis of investing in human resources for home care service in Serbia showed that the both scenarios of investing in either additional home care hours or more beneficiaries are cost-efficient. However, the optimal solution with the positive (and the highest) value of economic net present value criterion is to invest in human resources to boost the number of home care hours from 6 to 8 hours per week and increase the number of the beneficiaries to 33%. Conclusion This paper shows how the statistical and economic analysis results can be used to evaluate different scenarios and enable quality decision-making based on exact data in order to improve health and quality of life of the elderly and spend funds in a rational manner. PMID:26869778

Techno-economical evaluation of protein extraction for microalgae biorefinery

NASA Astrophysics Data System (ADS)

Sari, Y. W.; Sanders, J. P. M.; Bruins, M. E.

2016-01-01

Due to scarcity of fossil feedstocks, there is an increasing demand for biobased fuels. Microalgae are considered as promising biobased feedstocks. However, microalgae based fuels are not yet produced at large scale at present. Applying biorefinery, not only for oil, but also for other components, such as carbohydrates and protein, may lead to the sustainable and economical microalgae-based fuels. This paper discusses two relatively mild conditions for microalgal protein extraction, based on alkali and enzymes. Green microalgae (Chlorella fusca) with and without prior lipid removal were used as feedstocks. Under mild conditions, more protein could be extracted using proteases, with the highest yields for microalgae meal (without lipids). The data on protein extraction yields were used to calculate the costs for producing 1 ton of microalgal protein. The processing cost for the alkaline method was € 2448 /ton protein. Enzymatic method performed better from an economic point of view with € 1367 /ton protein on processing costs. However, this is still far from industrially feasible. For both extraction methods, biomass cost per ton of produced product were high. A higher protein extraction yield can partially solve this problem, lowering processing cost to €620 and 1180 /ton protein product, using alkali and enzyme, respectively. Although alkaline method has lower processing cost, optimization appears to be better achievable using enzymes. If the enzymatic method can be optimized by lowering the amount of alkali added, leading to processing cost of € 633/ton protein product. Higher revenue can be generated when the residue after protein extraction can be sold as fuel, or better as a highly digestible feed for cattle.

History matching through dynamic decision-making

PubMed Central

Maschio, Célio; Santos, Antonio Alberto; Schiozer, Denis; Rocha, Anderson

2017-01-01

History matching is the process of modifying the uncertain attributes of a reservoir model to reproduce the real reservoir performance. It is a classical reservoir engineering problem and plays an important role in reservoir management since the resulting models are used to support decisions in other tasks such as economic analysis and production strategy. This work introduces a dynamic decision-making optimization framework for history matching problems in which new models are generated based on, and guided by, the dynamic analysis of the data of available solutions. The optimization framework follows a ‘learning-from-data’ approach, and includes two optimizer components that use machine learning techniques, such as unsupervised learning and statistical analysis, to uncover patterns of input attributes that lead to good output responses. These patterns are used to support the decision-making process while generating new, and better, history matched solutions. The proposed framework is applied to a benchmark model (UNISIM-I-H) based on the Namorado field in Brazil. Results show the potential the dynamic decision-making optimization framework has for improving the quality of history matching solutions using a substantial smaller number of simulations when compared with a previous work on the same benchmark. PMID:28582413

Improving optimal control of grid-connected lithium-ion batteries through more accurate battery and degradation modelling

NASA Astrophysics Data System (ADS)

Reniers, Jorn M.; Mulder, Grietus; Ober-Blöbaum, Sina; Howey, David A.

2018-03-01

The increased deployment of intermittent renewable energy generators opens up opportunities for grid-connected energy storage. Batteries offer significant flexibility but are relatively expensive at present. Battery lifetime is a key factor in the business case, and it depends on usage, but most techno-economic analyses do not account for this. For the first time, this paper quantifies the annual benefits of grid-connected batteries including realistic physical dynamics and nonlinear electrochemical degradation. Three lithium-ion battery models of increasing realism are formulated, and the predicted degradation of each is compared with a large-scale experimental degradation data set (Mat4Bat). A respective improvement in RMS capacity prediction error from 11% to 5% is found by increasing the model accuracy. The three models are then used within an optimal control algorithm to perform price arbitrage over one year, including degradation. Results show that the revenue can be increased substantially while degradation can be reduced by using more realistic models. The estimated best case profit using a sophisticated model is a 175% improvement compared with the simplest model. This illustrates that using a simplistic battery model in a techno-economic assessment of grid-connected batteries might substantially underestimate the business case and lead to erroneous conclusions.

Water footprint characteristic of less developed water-rich regions: Case of Yunnan, China.

PubMed

Qian, Yiying; Dong, Huijuan; Geng, Yong; Zhong, Shaozhuo; Tian, Xu; Yu, Yanhong; Chen, Yihui; Moss, Dana Avery

2018-03-30

Rapid industrialization and urbanization pose pressure on water resources in China. Virtual water trade proves to be an increasingly useful tool in water stress alleviation for water-scarce regions, while bringing opportunities and challenges for less developed water-rich regions. In this study, Yunnan, a typical province in southwest China, was selected as the case study area to explore its potential in socio-economic development in the context of water sustainability. Both input-output analysis and structural decomposition analysis on Yunnan's water footprint for the period of 2002-2012 were performed at not only an aggregated level but also a sectoral level. Results show that although the virtual water content of all economic sectors decreased due to technological progress, Yunnan's total water footprint still increased as a result of economic scale expansion. From the sectoral perspective, sectors with large water footprints include construction sector, agriculture sector, food manufacturing & processing sector, and service sector, while metal products sector and food manufacturing & processing sector were the major virtual water exporters, and textile & clothing sector and construction sector were the major importers. Based on local conditions, policy suggestions were proposed, including economic structure and efficiency optimization, technology promotion and appropriate virtual water trade scheme. This study provides valuable insights for regions facing "resource curse" by exploring potential socio-economic progress while ensuring water security. Copyright © 2018 Elsevier Ltd. All rights reserved.

Intensive Care Nurses’ Belief Systems Regarding the Health Economics: A Focused Ethnography

PubMed Central

Heydari, Abbas; Vafaee-Najar, Ali; Bakhshi, Mahmoud

2016-01-01

Background: Health care beliefs can have an effect on the efficiency and effectiveness of nursing practices. Nevertheless, how belief systems impact on the economic performance of intensive care unit (ICU) nurses is not known. This study aimed to explore the ICU nurses’ beliefs and their effect on nurse’s: practices and behavior patterns regarding the health economics. Methods: In this study, a focused ethnography method was used. Twenty-four informants from ICU nurses and other professional individuals were purposively selected and interviewed. As well, 400 hours of ethnographic observations were used for data collection. Data analysis was performed using the methods described by Miles and Huberman (1994). Findings: Eight beliefs were found that gave meaning to ICU nurse’s practices regarding the health economics. 1. The registration of medications and supplies disrupt the nursing care; 2. Monitoring and auditing improve consumption; 3. There is a fear of possible shortage in the future; 4. Supply and replacement of equipment is difficult; 5. Higher prices lead to more accurate consumption; 6. The quality of care precedes the costs; 7. Clinical Guidelines are abundant but useful; and 8. Patient economy has priority over hospital economy. Maintaining the quality of patient care with least attention to hospital costs was the main focus of the beliefs formed up in the ICU regarding the health economics. Conclusions: ICU nurses’ belief systems have significantly shaped in relation to providing a high-quality care. Although high quality of care can lead to a rise in the effectiveness of nursing care, cost control perspective should also be considered in planning for improve the quality of care. Therefore, it is necessary to involve the ICU nurses in decision-making about unit cost management. They must become familiar with the principles of heath care economics and productivity by applying an effective cost management program. It may be optimal to implement the reforms in various aspects, such as the hospital’s strategic plan and supply chain management system. PMID:27157164

Intensive Care Nurses' Belief Systems Regarding the Health Economics: A Focused Ethnography.

PubMed

Heydari, Abbas; Vafaee-Najar, Ali; Bakhshi, Mahmoud

2016-09-01

Health care beliefs can have an effect on the efficiency and effectiveness of nursing practices. Nevertheless, how belief systems impact on the economic performance of intensive care unit (ICU) nurses is not known. This study aimed to explore the ICU nurses' beliefs and their effect on nurse's practices and behavior patterns regarding the health economics. In this study, a focused ethnography method was used. Twenty-four informants from ICU nurses and other professional individuals were purposively selected and interviewed. As well, 400 hours of ethnographic observations were used for data collection. Data analysis was performed using the methods described by Miles and Huberman (1994). Eight beliefs were found that gave meaning to ICU nurse's practices regarding the health economics. 1. The registration of medications and supplies disrupt the nursing care; 2.Monitoring and auditing improve consumption; 3.There is a fear of possible shortage in the future; 4.Supply and replacement of equipment is difficult; 5.Higher prices lead to more accurate consumption; 6.The quality of care precedes the costs; 7. Clinical Guidelines are abundant but useful; and 8.Patient economy has priority over hospital economy. Maintaining the quality of patient care with least attention to hospital costs was the main focus of the beliefs formed up in the ICU regarding the health economics. ICU nurses' belief systems have significantly shaped in relation to providing a high-quality care. Although high quality of care can lead to a rise in the effectiveness of nursing care, cost control perspective should also be considered in planning for improve the quality of care. Therefore, it is necessary to involve the ICU nurses in decision-making about unit cost management. They must become familiar with the principles of heath care economics and productivity by applying an effective cost management program. It may be optimal to implement the reforms in various aspects, such as the hospital's strategic plan and supply chain management system.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, Katherine H.; Cutler, Dylan S.; Olis, Daniel R.

REopt is a techno-economic decision support model used to optimize energy systems for buildings, campuses, communities, and microgrids. The primary application of the model is for optimizing the integration and operation of behind-the-meter energy assets. This report provides an overview of the model, including its capabilities and typical applications; inputs and outputs; economic calculations; technology descriptions; and model parameters, variables, and equations. The model is highly flexible, and is continually evolving to meet the needs of each analysis. Therefore, this report is not an exhaustive description of all capabilities, but rather a summary of the core components of the model.

Translations on Eastern Europe, Scientific Affairs, Number 591.

DTIC Science & Technology

1978-07-10

of the Sea conferences and negotiations, territorial seas and straits, coastal and international seabed economic areas, marine pollution...technological levels, and the economic effectiveness of their production. The People’s Republic of Bulgaria, for example, is the second country in...optimization of the technological processes and achieving high technical- economic para- meters—merit a particularly high appraisal. In this context, we

The economic cost of adverse health effects from wildfire-smoke exposure: A review

Treesearch

Ikuho Kochi; Geoffrey H. Donovan; Patricia A. Champ; John B. Loomis

2010-01-01

The economic costs of adverse health effects associated with exposure to wildfire smoke should be given serious consideration in determining the optimal wildfire management policy. Unfortunately, the literature in this research area is thin. In an effort to better understand the nature of these economic costs, we review and synthesise the relevant literature in three...

An Exploratory Case Study of Information-Sharing and Collaboration within Air Force Supply Chain Management

DTIC Science & Technology

2006-03-01

International Journal of Production Economics , Vol. 93-94, pp. 53-99, 2005. -----. “Approximate...Optimization of a Two-level Distribution Inventory System,” International Journal of Production Economics , Vol. 81-81, pp. 545-553, 2003...Scaling Down Multi-Echelon Inventory Problems,” International Journal of Production Economics , Vol. 71, pp. 255-261, 2001. Axsater, Sven

Empirical analyses on the development trend of non-ferrous metal industry under China’s new normal

NASA Astrophysics Data System (ADS)

Li, C. X.; Liu, C. X.; Zhang, Q. L.

2017-08-01

The CGE model of Yunnan’s macro economy was constructed based on the input-output data of Yunnan in 2012, and the development trend of the non-ferrous metals industry (NMI) under the China’s new normal was simulated. In view of this, according to different expected economic growth, and optimized economic structure, the impact on development of Yunnan NMI was simulated. The results show that the NMI growth rate is expected to decline when the economic growth show a downward trend, but the change of the proportion is relatively small. Moreover, the structure in proportion was adjusted to realize the economic structure optimization, while the proportion of NMI in GDP will decline. In contrast, the biggest influence on the NMI is the change of economic structure. From the statistics of last two years, we can see that NMI is growing, and at the same time, its proportion is declining, which is consistent with the results of simulation. But the adjustment of economic structure will take a long time. It is need to improve the proportion of deep-processing industry, extend the industrial chain, enhance the value chain, so as to be made good use of resource advantage.

Optimal allocation of thermodynamic irreversibility for the integrated design of propulsion and thermal management systems

NASA Astrophysics Data System (ADS)

Maser, Adam Charles

More electric aircraft systems, high power avionics, and a reduction in heat sink capacity have placed a larger emphasis on correctly satisfying aircraft thermal management requirements during conceptual design. Thermal management systems must be capable of dealing with these rising heat loads, while simultaneously meeting mission performance. Since all subsystem power and cooling requirements are ultimately traced back to the engine, the growing interactions between the propulsion and thermal management systems are becoming more significant. As a result, it is necessary to consider their integrated performance during the conceptual design of the aircraft gas turbine engine cycle to ensure that thermal requirements are met. This can be accomplished by using thermodynamic subsystem modeling and simulation while conducting the necessary design trades to establish the engine cycle. However, this approach also poses technical challenges associated with the existence of elaborate aircraft subsystem interactions. This research addresses these challenges through the creation of a parsimonious, transparent thermodynamic model of propulsion and thermal management systems performance with a focus on capturing the physics that have the largest impact on propulsion design choices. This modeling environment, known as Cycle Refinement for Aircraft Thermodynamically Optimized Subsystems (CRATOS), is capable of operating in on-design (parametric) and off-design (performance) modes and includes a system-level solver to enforce design constraints. A key aspect of this approach is the incorporation of physics-based formulations involving the concurrent usage of the first and second laws of thermodynamics, which are necessary to achieve a clearer view of the component-level losses across the propulsion and thermal management systems. This is facilitated by the direct prediction of the exergy destruction distribution throughout the system and the resulting quantification of available 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 numerical optimization. By posing the problem in economic terms, exergy destruction is treated as a true common currency to barter for improved efficiency, cost, and performance. This allows the designer to clearly see how changes in the irreversibility distribution impact the overall system. The inverse design is first performed through a filtered Monte Carlo to allow the designer to view the irreversibility design space. The designer can then directly perform the allocation using the exergy destruction, which helps to place the design choices on an even thermodynamic footing. Finally, two use cases are presented to show how the irreversibility allocation approach can assist the designer. The first describes a situation where the designer can better address competing system-level requirements; the second describes a different situation where the designer can choose from a number of options to improve a system in a manner that is more robust to future requirements.

A preliminary investigation into the effect of pressure on flotation performance

NASA Astrophysics Data System (ADS)

Young, Courtney A.

2007-10-01

In a previous study, various pyrite depressants were examined to improve the flotation performance of a copper-sulfide ore containing tetrahedrite (Cu12Sb4S13). Optimal results from this study were used to examine the effect of elevation on recovery and grade. Tests were conducted at elevations of 3,350 meters, 1,735 meters, 610 meters, and-760 meters, consisting of five repetitive experiments for statistical analysis. The experiments were performed both with and without airflow control. Tests were also performed in a glove box at Montana Tech of The University of Montana to mimic the pressure conditions. Results indicate that both recovery and grade are dependent on pressure via bubble size and airflow, suggesting that pressurized fl otation cells should be considered for operations, particularly those at high elevation. Economics are extremely favorable for implementation because ensuing capital expenses are inconsequential with minimal time for return-on-investment.

Use of single-well simulators and economic performance criteria to optimize fracturing treatment design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, R.W.; Phillips, A.M.

1990-02-01

Low-permeability reservoirs are currently being propped with sand, resin-coated sand, intermediate-density proppants, and bauxite. This wide range of proppant cost and performance has resulted in the proliferation of proppant selection models. Initially, a rather vague relationship between well depth and proppant strength dictated the choice of proppant. More recently, computerized models of varying complexity that use net-present-value (NPV) calculations have become available. The input is based on the operator's performance goals for each well and specific reservoir properties. Simpler, noncomputerized approaches include cost/performance comparisons and nomographs. Each type of model, including several of the computerized models, is examined here. Bymore » use of these models and NPV calculations, optimum fracturing treatment designs have been developed for such low-permeability reservoirs as the Prue in Oklahoma. Typical well conditions are used in each of the selection models, and the results are compared.« less

Invited review: Helping dairy farmers to improve economic performance utilizing data-driving decision support tools.

PubMed

Cabrera, V E

2018-01-01

The objective of this review paper is to describe the development and application of a suite of more than 40 computerized dairy farm decision support tools contained at the University of Wisconsin-Madison (UW) Dairy Management website http://DairyMGT.info. These data-driven decision support tools are aimed to help dairy farmers improve their decision-making, environmental stewardship and economic performance. Dairy farm systems are highly dynamic in which changing market conditions and prices, evolving policies and environmental restrictions together with every time more variable climate conditions determine performance. Dairy farm systems are also highly integrated with heavily interrelated components such as the dairy herd, soils, crops, weather and management. Under these premises, it is critical to evaluate a dairy farm following a dynamic integrated system approach. For this approach, it is crucial to use meaningful data records, which are every time more available. These data records should be used within decision support tools for optimal decision-making and economic performance. Decision support tools in the UW-Dairy Management website (http://DairyMGT.info) had been developed using combination and adaptation of multiple methods together with empirical techniques always with the primary goal for these tools to be: (1) highly user-friendly, (2) using the latest software and computer technologies, (3) farm and user specific, (4) grounded on the best scientific information available, (5) remaining relevant throughout time and (6) providing fast, concrete and simple answers to complex farmers' questions. DairyMGT.info is a translational innovative research website in various areas of dairy farm management that include nutrition, reproduction, calf and heifer management, replacement, price risk and environment. This paper discusses the development and application of 20 selected (http://DairyMGT.info) decision support tools.

Discussion on joint operation of wind farm and pumped-storage hydroplant

NASA Astrophysics Data System (ADS)

Li, Caifang; Wu, Yichun; Liang, Hao; Li, Miao

2017-12-01

Due to the random fluctuations in wind power, large amounts of grid integration will have a negative impact on grid operation and the consumers. The joint operation with pumped-storage hydroplant with good peak shaving performance can effectively reduce the negative impact on the safety and economic operation of power grid, and improve the utilization of wind power. In addition, joint operation can achieve the optimization of green power and improve the comprehensive economic benefits. Actually, the rational profit distribution of joint operation is the premise of sustainable and stable cooperation. This paper focuses on the profit distribution of joint operation, and applies improved shapely value method, which taking the investments and the contributions of each participant in the cooperation into account, to determine the profit distribution. Moreover, the distribution scheme can provide an effective reference for the actual joint operation of wind farm and pumped-storage hydroplant.

Simulation and optimization model for irrigation planning and management

NASA Astrophysics Data System (ADS)

Kuo, Sheng-Feng; Liu, Chen-Wuing

2003-10-01

A simulation and optimization model was developed and applied to an irrigated area in Delta, Utah to optimize the economic benefit, simulate the water demand, and search the related crop area percentages with specified water supply and planted area constraints. The user interface model begins with the weather generation submodel, which produces daily weather data, which is based on long-term monthly average and standard deviation data from Delta, Utah. To simulate the daily crop water demand and relative crop yield for seven crops in two command areas, the information provided by this submodel was applied to the on-farm irrigation scheduling submodel. Furthermore, to optimize the project benefit by searching for the best allocation of planted crop areas given the constraints of projected water supply, the results were employed in the genetic algorithm submodel. Optimal planning for the 394·6-ha area of the Delta irrigation project is projected to produce the maximum economic benefit. That is, projected profit equals US$113 826 and projected water demand equals 3·03 × 106 m3. Also, area percentages of crops within UCA#2 command area are 70·1%, 19% and 10·9% for alfalfa, barley and corn, respectively, and within UCA#4 command area are 41·5%, 38·9%, 14·4% and 5·2% for alfalfa, barley, corn and wheat, respectively. As this model can plan irrigation application depths and allocate crop areas for optimal economic benefit, it can thus be applied to many irrigation projects. Copyright

Run-of-river power plants in Alpine regions: Whither optimal capacity?

NASA Astrophysics Data System (ADS)

Lazzaro, G.; Botter, G.

2015-07-01

Although run-of-river hydropower represents a key source of renewable energy, it cannot prevent stresses on river ecosystems and human well-being. This is especially true in Alpine regions, where the outflow of a plant is placed several kilometers downstream of the intake, inducing the depletion of river reaches of considerable length. Here multiobjective optimization is used in the design of the capacity of run-of-river plants to identify optimal trade-offs between two contrasting objectives: the maximization of the profitability and the minimization of the hydrologic disturbance between the intake and the outflow. The latter is evaluated considering different flow metrics: mean discharge, temporal autocorrelation, and streamflow variability. Efficient and Pareto-optimal plant sizes are devised for two representative case studies belonging to the Piave river (Italy). Our results show that the optimal design capacity is strongly affected by the flow regime at the plant intake. In persistent regimes with a reduced flow variability, the optimal trade-off between economic exploitation and hydrologic disturbance is obtained for a narrow range of capacities sensibly smaller than the economic optimum. In erratic regimes featured by an enhanced flow variability, instead, the Pareto front is discontinuous and multiple trade-offs can be identified, which imply either smaller or larger plants compared to the economic optimum. In particular, large capacities reduce the impact of the plant on the streamflow variability at seasonal and interannual time scale. Multiobjective analysis could provide a clue for the development of policy actions based on the evaluation of the environmental footprint of run-of-river plants.

Performance evaluation of Titanium nitride coated tool in turning of mild steel

NASA Astrophysics Data System (ADS)

Srinivas, B.; Pramod Kumar, G.; Cheepu, Muralimohan; Jagadeesh, N.; kumar, K. Ravi; Haribabu, S.

2018-03-01

The growth in demand for bio-gradable materials is opened as a venue for using vegetable oils, coconut oils etc., as alternate to the conventional coolants for machining operations. At present in manufacturing industries the demand for surface quality is increasing rapidly along with dimensional accuracy and geometric tolerances. The present study is influence of cutting parameters on the surface roughness during the turning of mild steel with TiN coated carbide tool using groundnut oil and soluble oil as coolants. The results showed vegetable gave closer surface finish compares with soluble oil. Cutting parameters has been optimized with Taguchi technique. In this paper, the main objective is to optimize the cutting parameters and reduce surface roughness analogous to increase the tool life by apply the coating on the carbide inserts. The cost of the coating is more, but economically efficient than changing the tools frequently. The plots were generated and analysed to find the relationship between them which are confirmed by performing a comparison study between the predicted results and theoretical results.

Solar energy system economic evaluation for IBM System 3, Glendo, Wyoming

NASA Technical Reports Server (NTRS)

1980-01-01

This analysis was based on the technical and economic models in f-chart design procedures with inputs based on the characteristics of the parameters of present worth of system cost over a projected twenty year life: life cycle savings, year of positive savings, and year of payback for the optimized solar energy system at each of the analysis sites. The sensitivity of the economic evaluation to uncertainties in constituent system and economic variables was also investigated.

Managing the water-energy-food nexus: Opportunities in Central Asia

NASA Astrophysics Data System (ADS)

Jalilov, Shokhrukh-Mirzo; Amer, Saud A.; Ward, Frank A.

2018-02-01

This article examines impacts of infrastructure development and climate variability on economic outcomes for the Amu Darya Basin in Central Asia. It aims to identify the most economically productive mix of expanded reservoir storage for economic benefit sharing to occur, in which economic welfare of all riparians is improved. Policies examined include four combinations of storage infrastructure for each of two climate futures. An empirical optimization model is developed and applied to identify opportunities for improving the welfare of Tajikistan, Uzbekistan, Afghanistan, and Turkmenistan. The analysis 1) characterizes politically constrained and economically optimized water-use patterns for these combinations of expanded reservoir storage capacity, 2) describes Pareto-Improving packages of expanded storage capacity that could raise economic welfare for all four riparians, and accounts for impacts for each of two climate scenarios. Results indicate that a combination of targeted water storage infrastructure and efficient water allocation could produce outcomes for which the discounted net present value of benefits are favorable for each riparian. Results identify a framework to provide economic motivation for all riparians to cooperate through development of water storage infrastructure. Our findings illustrate the principle that development of water infrastructure can expand the negotiation space by which all communities can gain economic benefits in the face of limited water supply. Still, despite our optimistic findings, patient and deliberate negotiation will be required to transform potential improvements into actual gains.

Clinical and economic impact of various strategies for varicella immunity screening and vaccination of health care personnel.

PubMed

Baracco, G J; Eisert, S; Saavedra, S; Hirsch, P; Marin, M; Ortega-Sanchez, I R

2015-10-01

Exposure to patients with varicella or herpes zoster causes considerable disruption to a health care facility's operations and has a significant health and economic impact. However, practices related to screening for immunity and immunization of health care personnel (HCP) for varicella vary widely. A decision tree model was built to evaluate the cost-effectiveness of 8 different strategies of screening and vaccinating HCP for varicella. The outcomes are presented as probability of acquiring varicella, economic impact of varicella per employee per year, and cost to prevent additional cases of varicella. Monte Carlo simulations and 1-way sensitivity analyses were performed to address the uncertainties inherent to the model. Alternative epidemiologic and technologic scenarios were also analyzed. Performing a clinical screening followed by serologic testing of HCP with negative history diminished the cost impact of varicella by >99% compared with not having a program. Vaccinating HCP with negative screen cost approximately $50,000 per case of varicella prevented at the current level of U.S. population immunity, but was projected to be cost-saving at 92% or lower immunity prevalence. Improving vaccine acceptance rates and using highly sensitive assays also optimize cost-effectiveness. Strategies relying on screening and vaccinating HCP for varicella on employment were shown to be cost-effective for health care facilities and are consistent with current national guidelines for varicella prevention. Published by Elsevier Inc.

Optimizing the sequence of diameter distributions and selection harvests for uneven-aged stand management

Treesearch

Robert G. Haight; J. Douglas Brodie; Darius M. Adams

1985-01-01

The determination of an optimal sequence of diameter distributions and selection harvests for uneven-aged stand management is formulated as a discrete-time optimal-control problem with bounded control variables and free-terminal point. An efficient programming technique utilizing gradients provides solutions that are stable and interpretable on the basis of economic...

Optimizing coffee cultivation and its impact on economic growth and export earnings of the producing countries: The case of Saudi Arabia.

PubMed

Al-Abdulkader, Ahmed M; Al-Namazi, Ali A; AlTurki, Turki A; Al-Khuraish, Muteb M; Al-Dakhil, Abdullah I

2018-05-01

Coffee is one of the historical socioeconomic crops. It has received an increasing attention at the global level, due to its positive interlinkage with the economic growth and on the gross domestic product for most of the producing countries, particularly, developing and least developed countries. Saudi Arabia is one of the coffee producing countries that has a relative comparative advantage of coffee cultivation. Yet, coffee cultivation has not received as much attention in Saudi Arabia as that of producing countries around the world. This study aims to assess the current state of coffee cultivation in Saudi Arabia and to investigate the potential to optimize coffee cultivation in Saudi Arabia that maximizes the net national economic return and export earnings, given limitation of cultivated areas, local market activities, and international trade activities. The study statistically analyzed primary data collected from around (65) coffee farms and traders in the study regions at the south and southwest Saudi Arabia, and optimized coffee cultivation in Saudi Arabia using LINGO optimization software. Empirical results of the study revealed the great potential of Saudi Arabia to expand coffee cultivation at south and southwest regions to meet the escalating local demand and to increase its share at the world market up to 2%. Optimization of coffee cultivation in Saudi Arabia showed a high potential to meet the local demand for coffee by producing 80.07 thousand tons grown over 2861.78 hectares and to generate a net return equivalent to $395.72 million a year, which is equivalent to $138.28 thousand per hectare and $4.94 thousand per ton of coffee. Optimizing coffee cultivation will play a substantial role to increase market share of Saudi Arabia to about 1-2% of the world market by increasing its export volume, respectively, to about 69.66 and 112.56 thousand tons, the national net economic return by about $395.86 and $395.95 million a year, and the export earnings of coffee by about $219.43-354.57 million a year, which in turns, will serve the national strategic trend to diversify the economic base and lower the dependency of incomes generated from oil exportation.

Roadmap to control HBV and HDV epidemics in China

DOE PAGES

Goyal, Ashish; Murray, John M.

2017-04-23

Hepatitis B virus (HBV) is endemic in China. Almost 10% of HBV infected individuals are also infected with hepatitis D virus (HDV) which has a 5–10 times higher mortality rate than HBV mono-infection. The aim of this manuscript is to devise strategies that can not only control HBV infections but also HDV infections in China under the current health care budget in an optimal manner. Furthermore, using a mathematical model, an annual budget of 10 billion dollars was optimally allocated among five interventions namely, testing and HBV adult vaccination, treatment for mono-infected and dually-infected individuals, second line treatment for HBVmore » mono-infections, and awareness programs. As a result, we determine that the optimal strategy is to test and treat both infections as early as possible while applying awareness programs at full intensity. Under this strategy, an additional 19.8 million HBV, 1.9 million HDV infections and 0.25 million lives will be saved over the next 10 years at a cost-savings of 79 billion dollars than performing no intervention. Introduction of second line treatment does not add a significant economic burden yet prevents 1.4 million new HBV infections and 15,000 new HDV infections. In conclusion, test and treatment programs are highly efficient in reducing HBV and HDV prevalence in the population. Under the current health budget in China, not only test and treat programs but awareness programs and second line treatment can also be implemented that minimizes prevalence and mortality, and maximizes economic benefits.« less

Economic Analysis of Screening Strategies for Rupture of Silicone Gel Breast Implants

PubMed Central

Chung, Kevin C.; Malay, Sunitha; Shauver, Melissa J.; Kim, H. Myra

2012-01-01

Background In 2006, the U.S. Food and Drug Administration (FDA) recommended screening of all women with silicone gel breast implants with magnetic resonance imaging (MRI) three years after implantation and every two years thereafter to assess their integrity. The cost for these serial examinations over the lifetime of the breast implants is an added burden to insurance payers and to women. We perform an economic analysis to determine the most optimal screening strategies by considering the diagnostic accuracy of the screening tests, the costs of the tests and subsequent implant removal. Methods We determined aggregate/pooled values for sensitivity and specificity of the screening tests ultrasound (US) and MRI in detecting silicone breast implant ruptures from the data obtained from published literature. We compiled costs, based on Medicare reimbursements for 2011, for the following elements: imaging modalities, anesthesia and 3 surgical treatment options for detected ruptures. We used decision tree to compare three alternate screening strategies of US only, MRI only and US followed by MRI in asymptomatic and symptomatic women. Results The cost per rupture of screening and management of rupture with US in asymptomatic women was $1,090, whereas in symptomatic women it was $1,622. Similar cost for MRI in asymptomatic women was $2,067, whereas in symptomatic women it was $2,143. Similar cost for US followed by MRI in asymptomatic women was $637, whereas in symptomatic women it was $2,908. Conclusion Screening with US followed by MRI was optimal for asymptomatic women and screening with US was optimal for symptomatic women. PMID:22743887

Roadmap to control HBV and HDV epidemics in China

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goyal, Ashish; Murray, John M.

Hepatitis B virus (HBV) is endemic in China. Almost 10% of HBV infected individuals are also infected with hepatitis D virus (HDV) which has a 5–10 times higher mortality rate than HBV mono-infection. The aim of this manuscript is to devise strategies that can not only control HBV infections but also HDV infections in China under the current health care budget in an optimal manner. Furthermore, using a mathematical model, an annual budget of 10 billion dollars was optimally allocated among five interventions namely, testing and HBV adult vaccination, treatment for mono-infected and dually-infected individuals, second line treatment for HBVmore » mono-infections, and awareness programs. As a result, we determine that the optimal strategy is to test and treat both infections as early as possible while applying awareness programs at full intensity. Under this strategy, an additional 19.8 million HBV, 1.9 million HDV infections and 0.25 million lives will be saved over the next 10 years at a cost-savings of 79 billion dollars than performing no intervention. Introduction of second line treatment does not add a significant economic burden yet prevents 1.4 million new HBV infections and 15,000 new HDV infections. In conclusion, test and treatment programs are highly efficient in reducing HBV and HDV prevalence in the population. Under the current health budget in China, not only test and treat programs but awareness programs and second line treatment can also be implemented that minimizes prevalence and mortality, and maximizes economic benefits.« less

Self-balancing dynamic scheduling of electrical energy for energy-intensive enterprises

NASA Astrophysics Data System (ADS)

Gao, Yunlong; Gao, Feng; Zhai, Qiaozhu; Guan, Xiaohong

2013-06-01

Balancing production and consumption with self-generation capacity in energy-intensive enterprises has huge economic and environmental benefits. However, balancing production and consumption with self-generation capacity is a challenging task since the energy production and consumption must be balanced in real time with the criteria specified by power grid. In this article, a mathematical model for minimising the production cost with exactly realisable energy delivery schedule is formulated. And a dynamic programming (DP)-based self-balancing dynamic scheduling algorithm is developed to obtain the complete solution set for such a multiple optimal solutions problem. For each stage, a set of conditions are established to determine whether a feasible control trajectory exists. The state space under these conditions is partitioned into subsets and each subset is viewed as an aggregate state, the cost-to-go function is then expressed as a function of initial and terminal generation levels of each stage and is proved to be a staircase function with finite steps. This avoids the calculation of the cost-to-go of every state to resolve the issue of dimensionality in DP algorithm. In the backward sweep process of the algorithm, an optimal policy is determined to maximise the realisability of energy delivery schedule across the entire time horizon. And then in the forward sweep process, the feasible region of the optimal policy with the initial and terminal state at each stage is identified. Different feasible control trajectories can be identified based on the region; therefore, optimising for the feasible control trajectory is performed based on the region with economic and reliability objectives taken into account.

Herbert A. Simon: Nobel Prize in Economic Sciences, 1978.

PubMed

Leahey, Thomas H

2003-09-01

In 1978, Herbert A. Simon won the Nobel Prize in Economic Sciences, the same Nobel won by Daniel Kahneman in 2002. Simon's work in fact paved the way for Kahneman's Nobel. Although trained in political science and economics rather than psychology, Simon applied psychological ideas to economic theorizing. Classical and neoclassical economic theories assume that people are perfectly rational and strive to optimize economic outcomes. Simon argued that human rationality is constrained, not perfect, and that people seek satisfactory rather than ideal outcomes. Despite his Nobel, Simon felt isolated in economics and ultimately moved into psychology. Nevertheless, his ideas percolated through the economic community, so that Kahneman, whose research advanced Simon's broad perspective, could be the psychologist who won the Nobel in economics.

Battery energy storage sizing when time of use pricing is applied.

PubMed

Carpinelli, Guido; Khormali, Shahab; Mottola, Fabio; Proto, Daniela

2014-01-01

Battery energy storage systems (BESSs) are considered a key device to be introduced to actuate the smart grid paradigm. However, the most critical aspect related to the use of such device is its economic feasibility as it is a still developing technology characterized by high costs and limited life duration. Particularly, the sizing of BESSs must be performed in an optimized way in order to maximize the benefits related to their use. This paper presents a simple and quick closed form procedure for the sizing of BESSs in residential and industrial applications when time-of-use tariff schemes are applied. A sensitivity analysis is also performed to consider different perspectives in terms of life span and future costs.

Battery Energy Storage Sizing When Time of Use Pricing Is Applied

PubMed Central

Khormali, Shahab

2014-01-01

Battery energy storage systems (BESSs) are considered a key device to be introduced to actuate the smart grid paradigm. However, the most critical aspect related to the use of such device is its economic feasibility as it is a still developing technology characterized by high costs and limited life duration. Particularly, the sizing of BESSs must be performed in an optimized way in order to maximize the benefits related to their use. This paper presents a simple and quick closed form procedure for the sizing of BESSs in residential and industrial applications when time-of-use tariff schemes are applied. A sensitivity analysis is also performed to consider different perspectives in terms of life span and future costs. PMID:25295309

Developing models that analyze the economic/environmental trade-offs implicit in water resource management

NASA Astrophysics Data System (ADS)

Howitt, R. E.

2016-12-01

Hydro-economic models have been used to analyze optimal supply management and groundwater use for the past 25 years. They are characterized by an objective function that usually maximizes economic measures such as consumer and producer surplus subject to hydrologic equations of motion or water distribution systems. The hydrologic and economic components are sometimes fully integrated. Alternatively they may use an iterative interactive process. Environmental considerations have been included in hydro-economic models as inequality constraints. Representing environmental requirements as constraints is a rigid approximation of the range of management alternatives that could be used to implement environmental objectives. The next generation of hydro-economic models, currently being developed, require that the environmental alternatives be represented by continuous or semi-continuous functions which relate water resource use allocated to the environment with the probabilities of achieving environmental objectives. These functions will be generated by process models of environmental and biological systems which are now advanced to the state that they can realistically represent environmental systems and flexibility to interact with economic models. Examples are crop growth models, climate modeling, and biological models of forest, fish, and fauna systems. These process models can represent environmental outcomes in a form that is similar to economic production functions. When combined with economic models the interacting process models can reproduce a range of trade-offs between economic and environmental objectives, and thus optimize social value of many water and environmental resources. Some examples of this next-generation of hydro-enviro- economic models are reviewed. In these models implicit production functions for environmental goods are combined with hydrologic equations of motion and economic response functions. We discuss models that show interaction between environmental goods and agricultural production, and others that address alternative climate change policies, or habitat provision.

Investigation on the energy absorption performance of a fixed-bottom pressure-differential wave energy converter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Babarit, A.; Wendt, F.; Yu, Y. -H.

2017-04-01

In this article, we investigate the energy absorption performance of a fixed-bottom pressure-differential wave energy converter. Two versions of the technology are considered: one has the moving surfaces on the bottom of the air chambers whereas the other has the moving surfaces on the top. We developed numerical models in the frequency domain, thereby enabling the power absorption of the two versions of the device to be assessed. It is observed that the moving surfaces on the top allow for easier tuning of the natural period of the system. Taking into account stroke limitations, the design is optimized. Results indicatemore » that the pressure-differential wave energy converter is a highly efficient technology both with respect to energy absorption and selected economic performance indicators.« less

Harvesting Atlantic Cod under Climate Variability

NASA Astrophysics Data System (ADS)

Oremus, K. L.

2016-12-01

Previous literature links the growth of a fishery to climate variability. This study uses an age-structured bioeconomic model to compare optimal harvest in the Gulf of Maine Atlantic cod fishery under a variable climate versus a static climate. The optimal harvest path depends on the relationship between fishery growth and the interest rate, with higher interest rates dictating greater harvests now at the cost of long-term stock sustainability. Given the time horizon of a single generation of fishermen under assumptions of a static climate, the model finds that the economically optimal management strategy is to harvest the entire stock in the short term and allow the fishery to collapse. However, if the biological growth of the fishery is assumed to vary with climate conditions, such as the North Atlantic Oscillation, there will always be pulses of high growth in the stock. During some of these high-growth years, the growth of the stock and its economic yield can exceed the growth rate of the economy even under high interest rates. This implies that it is not economically optimal to exhaust the New England cod fishery if NAO is included in the biological growth function. This finding may have theoretical implications for the management of other renewable yet exhaustible resources whose growth rates are subject to climate variability.

Population Modeling Approach to Optimize Crop Harvest Strategy. The Case of Field Tomato.

PubMed

Tran, Dinh T; Hertog, Maarten L A T M; Tran, Thi L H; Quyen, Nguyen T; Van de Poel, Bram; Mata, Clara I; Nicolaï, Bart M

2017-01-01

In this study, the aim is to develop a population model based approach to optimize fruit harvesting strategies with regard to fruit quality and its derived economic value. This approach was applied to the case of tomato fruit harvesting under Vietnamese conditions. Fruit growth and development of tomato (cv. "Savior") was monitored in terms of fruit size and color during both the Vietnamese winter and summer growing seasons. A kinetic tomato fruit growth model was applied to quantify biological fruit-to-fruit variation in terms of their physiological maturation. This model was successfully calibrated. Finally, the model was extended to translate the fruit-to-fruit variation at harvest into the economic value of the harvested crop. It can be concluded that a model based approach to the optimization of harvest date and harvest frequency with regard to economic value of the crop as such is feasible. This approach allows growers to optimize their harvesting strategy by harvesting the crop at more uniform maturity stages meeting the stringent retail demands for homogeneous high quality product. The total farm profit would still depend on the impact a change in harvesting strategy might have on related expenditures. This model based harvest optimisation approach can be easily transferred to other fruit and vegetable crops improving homogeneity of the postharvest product streams.

Prioritizing conservation activities using reserve site selection methods and population viability analysis.

PubMed

Newbold, Stephen C; Siikamäki, Juha

2009-10-01

In recent years a large literature on reserve site selection (RSS) has developed at the interface between ecology, operations research, and environmental economics. Reserve site selection models use numerical optimization techniques to select sites for a network of nature reserves for protecting biodiversity. In this paper, we develop a population viability analysis (PVA) model for salmon and incorporate it into an RSS framework for prioritizing conservation activities in upstream watersheds. We use spawner return data for three closely related salmon stocks in the upper Columbia River basin and estimates of the economic costs of watershed protection from NOAA to illustrate the framework. We compare the relative cost-effectiveness of five alternative watershed prioritization methods, based on various combinations of biological and economic information. Prioritization based on biological benefit-economic cost comparisons and accounting for spatial interdependencies among watersheds substantially outperforms other more heuristic methods. When using this best-performing prioritization method, spending 10% of the cost of protecting all upstream watersheds yields 79% of the biological benefits (increase in stock persistence) from protecting all watersheds, compared to between 20% and 64% for the alternative methods. We also find that prioritization based on either costs or benefits alone can lead to severe reductions in cost-effectiveness.

High-Fidelity Aerostructural Optimization of Nonplanar Wings for Commercial Transport Aircraft

NASA Astrophysics Data System (ADS)

Khosravi, Shahriar

Although the aerospace sector is currently responsible for a relatively small portion of global anthropogenic greenhouse gas emissions, the growth of the airline industry raises serious concerns about the future of commercial aviation. As a result, the development of new aircraft design concepts with the potential to improve fuel efficiency remains an important priority. Numerical optimization based on high-fidelity physics has become an increasingly attractive tool over the past fifteen years in the search for environmentally friendly aircraft designs that reduce fuel consumption. This approach is able to discover novel design concepts and features that may never be considered without optimization. This can help reduce the economic costs and risks associated with developing new aircraft concepts by providing a more realistic assessment early in the design process. This thesis provides an assessment of the potential efficiency improvements obtained from nonplanar wings through the application of fully coupled high-fidelity aerostructural optimization. In this work, we conduct aerostructural optimization using the Euler equations to model the flow along with a viscous drag estimate based on the surface area. A major focus of the thesis is on finding the optimal shape and performance benefits of nonplanar wingtip devices. Two winglet configurations are considered: winglet-up and winglet-down. These are compared to optimized planar wings of the same projected span in order to quantify the possible drag reductions offered by winglets. In addition, the drooped wing is studied in the context of exploratory optimization. The main results show that the winglet-down configuration is the most efficient winglet shape, reducing the drag by approximately 2% at the same weight in comparison to a planar wing. There are two reasons for the superior performance of this design. First, this configuration moves the tip vortex further away from the wing. Second, the winglet-down concept has a higher projected span at the deflected state due to the structural deflections. Finally, the exploratory optimization studies lead to a drooped wing with the potential to increase range by 4.9% relative to a planar wing.

The cost and management of different types of clinical mastitis in dairy cows estimated by dynamic programming.

PubMed

Cha, E; Bar, D; Hertl, J A; Tauer, L W; Bennett, G; González, R N; Schukken, Y H; Welcome, F L; Gröhn, Y T

2011-09-01

The objective of this study was to estimate the cost of 3 different types of clinical mastitis (CM) (caused by gram-positive bacteria, gram-negative bacteria, and other organisms) at the individual cow level and thereby identify the economically optimal management decision for each type of mastitis. We made modifications to an existing dynamic optimization and simulation model, studying the effects of various factors (incidence of CM, milk loss, pregnancy rate, and treatment cost) on the cost of different types of CM. The average costs per case (US$) of gram-positive, gram-negative, and other CM were $133.73, $211.03, and $95.31, respectively. This model provided a more informed decision-making process in CM management for optimal economic profitability and determined that 93.1% of gram-positive CM cases, 93.1% of gram-negative CM cases, and 94.6% of other CM cases should be treated. The main contributor to the total cost per case was treatment cost for gram-positive CM (51.5% of the total cost per case), milk loss for gram-negative CM (72.4%), and treatment cost for other CM (49.2%). The model affords versatility as it allows for parameters such as production costs, economic values, and disease frequencies to be altered. Therefore, cost estimates are the direct outcome of the farm-specific parameters entered into the model. Thus, this model can provide farmers economically optimal guidelines specific to their individual cows suffering from different types of CM. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Waste management as an effort to improve urban area cleanliness and community income (journal review)

NASA Astrophysics Data System (ADS)

Kinantan, Bag; Rahim Matondang, A.; Hidayati, Juliza

2018-02-01

The problem of urban waste has reached a point of concern. Population and economic growth are thought to be the cause of increasing the waste generation. The major problem related to this condition is the increasing of waste production which is not balance with the increase of its management capacity. Based on the Law Number 18 of 2008 that waste management starts from the source by applying the 3R approach (Reduction, Reuse, Recycle). This regulation provides a way which expect the waste management can be better, so that, the level of waste service can be improved and load on landfills (TPA) can be reduced.The cost of garbage collection and transport are 85% of the total waste management cost, so if this is optimized, it will optimize the system as a whole. Subsequent research focuses on how to optimize the garbage collection and transport sub-systems by finding the shortest route of transportation to the landfill by developing a Vehicle Routing Problem (VRP) model. The development of an urban area leads to the preparation of the best route is no longer an optimal solution. The complexity of the waste problem is not only related to the technical matters, but also the social and economic problems of the community. So, it is necessary to develop a model of waste management which does not only pay attention to the technical aspects, but also the social and economic. Waste is expected to be no longer a burden, but can also be utilized economically to increase community income.

An effective and comprehensive model for optimal rehabilitation of separate sanitary sewer systems.

PubMed

Diogo, António Freire; Barros, Luís Tiago; Santos, Joana; Temido, Jorge Santos

2018-01-15

In the field of rehabilitation of separate sanitary sewer systems, a large number of technical, environmental, and economic aspects are often relevant in the decision-making process, which may be modelled as a multi-objective optimization problem. Examples are those related with the operation and assessment of networks, optimization of structural, hydraulic, sanitary, and environmental performance, rehabilitation programmes, and execution works. In particular, the cost of investment, operation and maintenance needed to reduce or eliminate Infiltration from the underground water table and Inflows of storm water surface runoff (I/I) using rehabilitation techniques or related methods can be significantly lower than the cost of transporting and treating these flows throughout the lifespan of the systems or period studied. This paper presents a comprehensive I/I cost-benefit approach for rehabilitation that explicitly considers all elements of the systems and shows how the approximation is incorporated as an objective function in a general evolutionary multi-objective optimization model. It takes into account network performance and wastewater treatment costs, average values of several input variables, and rates that can reflect the adoption of different predictable or limiting scenarios. The approach can be used as a practical and fast tool to support decision-making in sewer network rehabilitation in any phase of a project. The fundamental aspects, modelling, implementation details and preliminary results of a two-objective optimization rehabilitation model using a genetic algorithm, with a second objective function related to the structural condition of the network and the service failure risk, are presented. The basic approach is applied to three real world cases studies of sanitary sewerage systems in Coimbra and the results show the simplicity, suitability, effectiveness, and usefulness of the approximation implemented and of the objective function proposed. Copyright © 2017 Elsevier B.V. All rights reserved.

Environmental Optimization Using the WAste Reduction Algorithm (WAR)

EPA Science Inventory

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

Single and multiple objective biomass-to-biofuel supply chain optimization considering environmental impacts

NASA Astrophysics Data System (ADS)

Valles Sosa, Claudia Evangelina

Bioenergy has become an important alternative source of energy to alleviate the reliance on petroleum energy. Bioenergy offers diminishing climate change by reducing Green House Gas Emissions, as well as providing energy security and enhancing rural development. The Energy Independence and Security Act mandate the use of 21 billion gallons of advanced biofuels including 16 billion gallons of cellulosic biofuels by the year 2022. It is clear that Biomass can make a substantial contribution to supply future energy demand in a sustainable way. However, the supply of sustainable energy is one of the main challenges that mankind will face over the coming decades. For instance, many logistical challenges will be faced in order to provide an efficient and reliable supply of quality feedstock to biorefineries. 700 million tons of biomass will be required to be sustainably delivered to biorefineries annually to meet the projected use of biofuels by the year of 2022. Approaching this complex logistic problem as a multi-commodity network flow structure, the present work proposes the use of a genetic algorithm as a single objective optimization problem that considers the maximization of profit and the present work also proposes the use of a Multiple Objective Evolutionary Algorithm to simultaneously maximize profit while minimizing global warming potential. Most transportation optimization problems available in the literature have mostly considered the maximization of profit or the minimization of total travel time as potential objectives to be optimized. However, on this research work, we take a more conscious and sustainable approach for this logistic problem. Planners are increasingly expected to adopt a multi-disciplinary approach, especially due to the rising importance of environmental stewardship. The role of a transportation planner and designer is shifting from simple economic analysis to promoting sustainability through the integration of environmental objectives. To respond to these new challenges, the Modified Multiple Objective Evolutionary Algorithm for the design optimization of a biomass to bio-refinery logistic system that considers the simultaneous maximization of the total profit and the minimization of three environmental impacts is presented. Sustainability balances economic, social and environmental goals and objectives. There exist several works in the literature that have considered economic and environmental objectives for the presented supply chain problem. However, there is a lack of research performed in the social aspect of a sustainable logistics system. This work proposes a methodology to integrate social aspect assessment, based on employment creation. Finally, most of the assessment methodologies considered in the literature only contemplate deterministic values, when in realistic situations uncertainties in the supply chain are present. In this work, Value-at-Risk, an advanced risk measure commonly used in portfolio optimization is included to consider the uncertainties in biofuel prices, among the others.

Economic optimization of natural hazard protection - conceptual study of existing approaches

NASA Astrophysics Data System (ADS)

Spackova, Olga; Straub, Daniel

2013-04-01

Risk-based planning of protection measures against natural hazards has become a common practice in many countries. The selection procedure aims at identifying an economically efficient strategy with regard to the estimated costs and risk (i.e. expected damage). A correct setting of the evaluation methodology and decision criteria should ensure an optimal selection of the portfolio of risk protection measures under a limited state budget. To demonstrate the efficiency of investments, indicators such as Benefit-Cost Ratio (BCR), Marginal Costs (MC) or Net Present Value (NPV) are commonly used. However, the methodologies for efficiency evaluation differ amongst different countries and different hazard types (floods, earthquakes etc.). Additionally, several inconsistencies can be found in the applications of the indicators in practice. This is likely to lead to a suboptimal selection of the protection strategies. This study provides a general formulation for optimization of the natural hazard protection measures from a socio-economic perspective. It assumes that all costs and risks can be expressed in monetary values. The study regards the problem as a discrete hierarchical optimization, where the state level sets the criteria and constraints, while the actual optimization is made on the regional level (towns, catchments) when designing particular protection measures and selecting the optimal protection level. The study shows that in case of an unlimited budget, the task is quite trivial, as it is sufficient to optimize the protection measures in individual regions independently (by minimizing the sum of risk and cost). However, if the budget is limited, the need for an optimal allocation of resources amongst the regions arises. To ensure this, minimum values of BCR or MC can be required by the state, which must be achieved in each region. The study investigates the meaning of these indicators in the optimization task at the conceptual level and compares their suitability. To illustrate the theoretical findings, the indicators are tested on a hypothetical example of five regions with different risk levels. Last but not least, political and societal aspects and limitations in the use of the risk-based optimization framework are discussed.

The effect of inflation rate on the cost of medical waste management system

NASA Astrophysics Data System (ADS)

Jolanta Walery, Maria

2017-11-01

This paper describes the optimization study aimed to analyse the impact of the parameter describing the inflation rate on the cost of the system and its structure. The study was conducted on the example of the analysis of medical waste management system in north-eastern Poland, in the Podlaskie Province. The scope of operational research carried out under the optimization study was divided into two stages of optimization calculations with assumed technical and economic parameters of the system. In the first stage, the lowest cost of functioning of the analysed system was generated, whereas in the second one the influence of the input parameter of the system, i.e. the inflation rate on the economic efficiency index (E) and the spatial structure of the system was determined. With the assumed inflation rate in the range of 1.00 to 1.12, the highest cost of the system was achieved at the level of PLN 2022.20/t (increase of economic efficiency index E by ca. 27% in comparison with run 1, with inflation rate = 1.12).

Assessing the economics of processing end-of-life vehicles through manual dismantling.

PubMed

Tian, Jin; Chen, Ming

2016-10-01

Most dismantling enterprises in a number of developing countries, such as China, usually adopt the "manual+mechanical" dismantling approach to process end-of-life vehicles. However, the automobile industry does not have a clear indicator to reasonably and effectively determine the manual dismantling degree for end-of-life vehicles. In this study, five different dismantling scenarios and an economic system for end-of-life vehicles were developed based on the actual situation of end-of-life vehicles. The fuzzy analytic hierarchy process was applied to set the weights of direct costs, indirect costs, and sales and to obtain an optimal manual dismantling scenario. Results showed that although the traditional method of "dismantling to the end" can guarantee the highest recycling rate, this method is not the best among all the scenarios. The profit gained in the optimal scenario is 100.6% higher than that in the traditional scenario. The optimal manual dismantling scenario showed that enterprises are required to select suitable parts to process through manual dismantling. Selecting suitable parts maximizes economic profit and improves dismantling speed. Copyright © 2016 Elsevier Ltd. All rights reserved.

The method of planning the energy consumption for electricity market

NASA Astrophysics Data System (ADS)

Russkov, O. V.; Saradgishvili, S. E.

2017-10-01

The limitations of existing forecast models are defined. The offered method is based on game theory, probabilities theory and forecasting the energy prices relations. New method is the basis for planning the uneven energy consumption of industrial enterprise. Ecological side of the offered method is disclosed. The program module performed the algorithm of the method is described. Positive method tests at the industrial enterprise are shown. The offered method allows optimizing the difference between planned and factual consumption of energy every hour of a day. The conclusion about applicability of the method for addressing economic and ecological challenges is made.

Large-scale-system effectiveness analysis. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patton, A.D.; Ayoub, A.K.; Foster, J.W.

1979-11-01

Objective of the research project has been the investigation and development of methods for calculating system reliability indices which have absolute, and measurable, significance to consumers. Such indices are a necessary prerequisite to any scheme for system optimization which includes the economic consequences of consumer service interruptions. A further area of investigation has been joint consideration of generation and transmission in reliability studies. Methods for finding or estimating the probability distributions of some measures of reliability performance have been developed. The application of modern Monte Carlo simulation methods to compute reliability indices in generating systems has been studied.

Numerical analysis and design optimization of supersonic after-burning with strut fuel injectors for scramjet engines

NASA Astrophysics Data System (ADS)

Candon, M. J.; Ogawa, H.

2018-06-01

Scramjets are a class of hypersonic airbreathing engine that offer promise for economical, reliable and high-speed access-to-space and atmospheric transport. The expanding flow in the scramjet nozzle comprises of unburned hydrogen. An after-burning scheme can be used to effectively utilize the remaining hydrogen by supplying additional oxygen into the nozzle, aiming to augment the thrust. This paper presents the results of a single-objective design optimization for a strut fuel injection scheme considering four design variables with the objective of maximizing thrust augmentation. Thrust is found to be augmented significantly owing to a combination of contributions from aerodynamic and combustion effects. Further understanding and physical insights have been gained by performing variance-based global sensitivity analysis, scrutinizing the nozzle flowfields, analyzing the distributions and contributions of the forces acting on the nozzle wall, and examining the combustion efficiency.

“UTILIZING” SIGNAL DETECTION THEORY

PubMed Central

Lynn, Spencer K.; Barrett, Lisa Feldman

2014-01-01

What do inferring what a person is thinking or feeling, deciding to report a symptom to your doctor, judging a defendant’s guilt, and navigating a dimly lit room have in common? They involve perceptual uncertainty (e.g., a scowling face might indicate anger or concentration, which engender different appropriate responses), and behavioral risk (e.g., a cost to making the wrong response). Signal detection theory describes these types of decisions. In this tutorial we show how, by incorporating the economic concept of utility, signal detection theory serves as a model of optimal decision making, beyond its common use as an analytic method. This utility approach to signal detection theory highlights potentially enigmatic influences of perceptual uncertainty on measures of decision-making performance (accuracy and optimality) and on behavior (a functional relationship between bias and sensitivity). A “utilized” signal detection theory offers the possibility of expanding the phenomena that can be understood within a decision-making framework. PMID:25097061

Assessing CO2 Mitigation Options Utilizing Detailed Electricity Characteristics and Including Renewable Generation

NASA Astrophysics Data System (ADS)

Bensaida, K.; Alie, Colin; Elkamel, A.; Almansoori, A.

2017-08-01

This paper presents a novel techno-economic optimization model for assessing the effectiveness of CO2 mitigation options for the electricity generation sub-sector that includes renewable energy generation. The optimization problem was formulated as a MINLP model using the GAMS modeling system. The model seeks the minimization of the power generation costs under CO2 emission constraints by dispatching power from low CO2 emission-intensity units. The model considers the detailed operation of the electricity system to effectively assess the performance of GHG mitigation strategies and integrates load balancing, carbon capture and carbon taxes as methods for reducing CO2 emissions. Two case studies are discussed to analyze the benefits and challenges of the CO2 reduction methods in the electricity system. The proposed mitigations options would not only benefit the environment, but they will as well improve the marginal cost of producing energy which represents an advantage for stakeholders.

Process change evaluation framework for allogeneic cell therapies: impact on drug development and commercialization.

PubMed

Hassan, Sally; Huang, Hsini; Warren, Kim; Mahdavi, Behzad; Smith, David; Jong, Simcha; Farid, Suzanne S

2016-04-01

Some allogeneic cell therapies requiring a high dose of cells for large indication groups demand a change in cell expansion technology, from planar units to microcarriers in single-use bioreactors for the market phase. The aim was to model the optimal timing for making this change. A development lifecycle cash flow framework was created to examine the implications of process changes to microcarrier cultures at different stages of a cell therapy's lifecycle. The analysis performed under assumptions used in the framework predicted that making this switch earlier in development is optimal from a total expected out-of-pocket cost perspective. From a risk-adjusted net present value view, switching at Phase I is economically competitive but a post-approval switch can offer the highest risk-adjusted net present value as the cost of switching is offset by initial market penetration with planar technologies. The framework can facilitate early decision-making during process development.

Environment and economic risk: An analysis of carbon emission market and portfolio management.

PubMed

Luo, Cuicui; Wu, Desheng

2016-08-01

Climate change has been one of the biggest and most controversial environmental issues of our times. It affects the global economy, environment and human health. Many researchers find that carbon dioxide (CO2) has contributed the most to climate change between 1750 and 2005. In this study, the orthogonal GARCH (OGARCH) model is applied to examine the time-varying correlations in European CO2 allowance, crude oil and stock markets in US, Europe and China during the Protocol's first commitment period. The results show that the correlations between EUA carbon spot price and the equity markets are higher and more volatile in US and Europe than in China. Then the optimal portfolios consisting these five time series are selected by Mean-Variance and Mean-CVAR models. It shows that the optimal portfolio selected by MV-OGARCH model has the best performance. Copyright © 2016 Elsevier Inc. All rights reserved.

[Experimental orthopedic surgery: the practical aspects and management].

PubMed

Di Denia, P; Caligiuri, G; Guzzardella, G A; Fini, M; Giardino, R

1996-01-01

The funds to grant for a scientific research project are more and more interesting public and private administrations. A quantitative analysis of experimental research prices in all its phases is mandatory for an optimization process. The aim of this paper is to define practical and economical aspects of the experimental 'in vivo' models designed for the validation of biomaterials, with particular respect to the managerial bookkeeping of consumer goods, based on the experience of our Institute. Some tables were realized in order to quantify the resources needed to perform experimental 'in vivo' models. These tables represent a reliable tool for a continuous monitoring of managerial costs for the current year and for an accurate budget planning for the future years considering the experimental projects in progress and the planned researches. A business organization of public research facilities may lead to an optimization of costs and an easier national and international funds achievement increasing, also, the partnership with private appointers.

Study on loading coefficient in steam explosion process of corn stalk.

PubMed

Sui, Wenjie; Chen, Hongzhang

2015-03-01

The object of this work was to evaluate the effect of loading coefficient on steam explosion process and efficacy of corn stalk. Loading coefficient's relation with loading pattern and material property was first revealed, then its effect on transfer process and pretreatment efficacy of steam explosion was assessed by established models and enzymatic hydrolysis tests, respectively, in order to propose its optimization strategy for improving the process economy. Results showed that loading coefficient was mainly determined by loading pattern, moisture content and chip size. Both compact loading pattern and low moisture content improved the energy efficiency of steam explosion pretreatment and overall sugar yield of pretreated materials, indicating that they are desirable to improve the process economy. Pretreatment of small chip size showed opposite effects in pretreatment energy efficiency and enzymatic hydrolysis performance, thus its optimization should be balanced in investigated aspects according to further techno-economical evaluation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Solar energy system economic evaluation: IBM System 4, Clinton, Mississippi

NASA Technical Reports Server (NTRS)

1980-01-01

An economic analysis of the solar energy system was developed for five sites, typical of a wide range of environmental and economic conditions in the continental United States. The analysis was based on the technical and economic models in the F-chart design procedure, with inputs based on the characteristic of the installed system and local conditions. The results are of the economic parameters of present worth of system cost over a 20 year time span: life cycle savings, year of positive savings and year of payback for the optimized solar energy system at each of the analysis sites. The sensitivity of the economic evaluation to uncertainties in constituent system and economic variables is also investigated.

An Approach to Economic Dispatch with Multiple Fuels Based on Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Sriyanyong, Pichet

2011-06-01

Particle Swarm Optimization (PSO), a stochastic optimization technique, shows superiority to other evolutionary computation techniques in terms of less computation time, easy implementation with high quality solution, stable convergence characteristic and independent from initialization. For this reason, this paper proposes the application of PSO to the Economic Dispatch (ED) problem, which occurs in the operational planning of power systems. In this study, ED problem can be categorized according to the different characteristics of its cost function that are ED problem with smooth cost function and ED problem with multiple fuels. Taking the multiple fuels into account will make the problem more realistic. The experimental results show that the proposed PSO algorithm is more efficient than previous approaches under consideration as well as highly promising in real world applications.

Electric vehicle (EV) storage supply chain risk and the energy market: A micro and macroeconomic risk management approach

NASA Astrophysics Data System (ADS)

Aguilar, Susanna D.

As a cost effective storage technology for renewable energy sources, Electric Vehicles can be integrated into energy grids. Integration must be optimized to ascertain that renewable energy is available through storage when demand exists so that cost of electricity is minimized. Optimization models can address economic risks associated with the EV supply chain- particularly the volatility in availability and cost of critical materials used in the manufacturing of EV motors and batteries. Supply chain risk can reflect itself in a shortage of storage, which can increase the price of electricity. We propose a micro-and macroeconomic framework for managing supply chain risk through utilization of a cost optimization model in combination with risk management strategies at the microeconomic and macroeconomic level. The study demonstrates how risk from the EVs vehicle critical material supply chain affects manufacturers, smart grid performance, and energy markets qualitatively and quantitatively. Our results illustrate how risk in the EV supply chain affects EV availability and the cost of ancillary services, and how EV critical material supply chain risk can be mitigated through managerial strategies and policy.

Co-Optimization of Fuels and Engines (Co-Optima) -- Introduction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farrell, John T; Wagner, Robert; Holladay, John

The Co-Optimization of Fuels and Engines (Co-Optima) initiative is a U.S. Department of Energy (DOE) effort funded by both the Vehicle and Bioenergy Technology Offices. The overall goal of the effort is to identify the combinations of fuel properties and engine characteristics that maximize efficiency, independent of production pathway or fuel composition, and accelerate commercialization of these technologies. Multiple research efforts are underway focused on both spark-ignition and compression-ignition strategies applicable across the entire light, medium, and heavy-duty fleet. A key objective of Co-Optima's research is to identify new blendstocks that enhance current petroleum blending components, increase blendstock diversity, andmore » provide refiners with increased flexibility to blend fuels with the key properties required to optimize advanced internal combustion engines. In addition to fuels and engines R&D, the initiative is guided by analyses assessing the near-term commercial feasibility of new blendstocks based on economics, environmental performance, compatibility, and large-scale production viability. This talk will provide an overview of the Co-Optima effort.« less

The effectiveness of Teratology Information Services (TIS).

PubMed

Hancock, Rebecca L; Koren, Gideon; Einarson, Adrienne; Ungar, Wendy J

2007-02-01

Women and their health care providers have few reliable sources of information regarding the safety of exposures in pregnancy and lactation. Evidence-based information on these topics is provided by Teratology Information Services (TIS). Access to TIS, however, is limited in many regions, and many services have difficulty maintaining ongoing funding. The objective of this review is to highlight published reports of the effectiveness of TIS in improving maternal and neonatal health. A search of the Pub Med and Econ Lit databases was performed with no date restriction, using the search terms teratology, information, counseling, pregnancy, effectiveness, birth defects. Information disseminated from TIS has been shown to prevent congenital malformations, unnecessary pregnancy terminations, and occupational risks. TIS support optimal nutritional supplementation in pregnancy and optimal drug therapy in pregnancy and breast-feeding. In addition, they correct misperceptions of risk and facilitate knowledge transfer and translation. TIS have the potential to provide health care cost savings. TIS are vital services in supporting optimal maternal and neonatal health. A formal economic evaluation of TIS is required in order to inform resource allocation decision-making and continued funding of these services.

Temporal Variations of Water Productivity in Irrigated Corn: An Analysis of Factors Influencing Yield and Water Use across Central Nebraska

PubMed Central

Carr, Tony; Yang, Haishun; Ray, Chittaranjan

2016-01-01

Water Productivity (WP) of a crop defines the relationship between the economic or physical yield of the crop and its water use. With this concept it is possible to identify disproportionate water use or water-limited yield gaps and thereby support improvements in agricultural water management. However, too often important qualitative and quantitative environmental factors are not part of a WP analysis and therefore neglect the aspect of maintaining a sustainable agricultural system. In this study, we examine both the physical and economic WP in perspective with temporally changing environmental conditions. The physical WP analysis was performed by comparing simulated maximum attainable corn yields per unit of water using the crop model Hybrid-Maize with observed data from 2005 through 2013 from 108 farm plots in the Central Platte and the Tri Basin Natural Resource Districts of Nebraska. In order to expand the WP analysis on external factors influencing yields, a second model, Maize-N, was used to estimate optimal nitrogen (N)–fertilizer rate for specific fields in the study area. Finally, a vadose zone flow and transport model, HYDRUS-1D for simulating vertical nutrient transport in the soil, was used to estimate locations of nitrogen pulses in the soil profile. The comparison of simulated and observed data revealed that WP was not on an optimal level, mainly due to large amounts of irrigation used in the study area. The further analysis illustrated year-to-year variations of WP during the nine consecutive years, as well as the need to improve fertilizer management to favor WP and environmental quality. In addition, we addressed the negative influence of groundwater depletion on the economic WP through increasing pumping costs. In summary, this study demonstrated that involving temporal variations of WP as well as associated environmental and economic issues can represent a bigger picture of WP that can help to create incentives to sustainably improve agricultural production. PMID:27575368

Integrated supply chain design for commodity chemicals production via woody biomass fast pyrolysis and upgrading.

PubMed

Zhang, Yanan; Hu, Guiping; Brown, Robert C

2014-04-01

This study investigates the optimal supply chain design for commodity chemicals (BTX, etc.) production via woody biomass fast pyrolysis and hydroprocessing pathway. The locations and capacities of distributed preprocessing hubs and integrated biorefinery facilities are optimized with a mixed integer linear programming model. In this integrated supply chain system, decisions on the biomass chipping methods (roadside chipping vs. facility chipping) are also explored. The economic objective of the supply chain model is to maximize the profit for a 20-year chemicals production system. In addition to the economic objective, the model also incorporates an environmental objective of minimizing life cycle greenhouse gas emissions, analyzing the trade-off between the economic and environmental considerations. The capital cost, operating cost, and revenues for the biorefinery facilities are based on techno-economic analysis, and the proposed approach is illustrated through a case study of Minnesota, with Minneapolis-St. Paul serving as the chemicals distribution hub. Copyright © 2014 Elsevier Ltd. All rights reserved.

Thermal energy and economic analysis of a PCM-enhanced household envelope considering different climate zones in Morocco

NASA Astrophysics Data System (ADS)

Kharbouch, Yassine; Mimet, Abdelaziz; El Ganaoui, Mohammed; Ouhsaine, Lahoucine

2018-07-01

This study investigates the thermal energy potentials and economic feasibility of an air-conditioned family household-integrated phase change material (PCM) considering different climate zones in Morocco. A simulation-based optimisation was carried out in order to define the optimal design of a PCM-enhanced household envelope for thermal energy effectiveness and cost-effectiveness of predefined candidate solutions. The optimisation methodology is based on coupling Energyplus® as a dynamic simulation tool and GenOpt® as an optimisation tool. Considering the obtained optimum design strategies, a thermal energy and economic analysis are carried out to investigate PCMs' integration feasibility in the Moroccan constructions. The results show that the PCM-integrated household envelope allows minimising the cooling/heating thermal energy demand vs. a reference household without PCM. While for the cost-effectiveness optimisation, it has been deduced that the economic feasibility is stilling insufficient under the actual PCM market conditions. The optimal design parameters results are also analysed.

Can marine protected areas enhance both economic and biological situations?

PubMed

Ami, Dominique; Cartigny, Pierre; Rapaport, Alain

2005-04-01

This paper investigates impacts of the creation of Marine Protected Areas (MPAs), in both economic and biological perspectives. The economic indicator is defined as the sum of discounted benefits derived from exploitation of the resource in the fishery sector, assumed to be optimally managed. The biological indicator is taken as the stock density of the resource. The basic fishery model (C.W. Clark, Mathematical Bioeconomics: The Optimal Management of Renewable Resources, second ed., John Wiley and Sons, New York, 1990) will serve as a convenient benchmark in comparing results with those that are derived from a model of two patchy populations (cf. R. Hannesson, Marine reserves: what would they accomplish, Mar. Resour. Econ. 13 (1998) 159). In the latter, a crucial characteristic is the migration coefficient with describes biological linkages between protected and unprotected areas. A set of situations where both economic and biological criteria are enhanced, after introducing a MPA, is presented. These results are obtained with the help of numerical simulations.

Health economic evaluation: important principles and methodology.

PubMed

Rudmik, Luke; Drummond, Michael

2013-06-01

To discuss health economic evaluation and improve the understanding of common methodology. This article discusses the methodology for the following types of economic evaluations: cost-minimization, cost-effectiveness, cost-utility, cost-benefit, and economic modeling. Topics include health-state utility measures, the quality-adjusted life year (QALY), uncertainty analysis, discounting, decision tree analysis, and Markov modeling. Economic evaluation is the comparative analysis of alternative courses of action in terms of both their costs and consequences. With increasing health care expenditure and limited resources, it is important for physicians to consider the economic impact of their interventions. Understanding common methodology involved in health economic evaluation will improve critical appraisal of the literature and optimize future economic evaluations. Copyright © 2012 The American Laryngological, Rhinological and Otological Society, Inc.

Life cycle thinking and assessment tools on environmentally-benign electronics: Convergent optimization of materials use, end-of-life strategy and environmental policies

NASA Astrophysics Data System (ADS)

Zhou, Xiaoying

The purpose of this study is to integrate the quantitative environmental performance assessment tools and the theory of multi-objective optimization within the boundary of electronic product systems to support the selection among design alternatives in terms of environmental impact, technical criteria, and economic feasibility. To meet with the requirements that result from emerging environmental legislation targeting electronics products, the research addresses an important analytical methodological approach to facilitate environmentally conscious design and end-of-life management with a life cycle viewpoint. A synthesis of diverse assessment tools is applied on a set of case studies: lead-free solder materials selection, cellular phone design, and desktop display technology assessment. In the first part of this work, an in-depth industrial survey of the status and concerns of the U.S. electronics industry on the elimination of lead (Pb) in solders is described. The results show that the trade-offs among environmental consequences, technology challenges, business risks, legislative compliance and stakeholders' preferences must be explicitly, simultaneously, and systematically addressed in the decision-making process used to guide multi-faceted planning of environmental solutions. In the second part of this work, the convergent optimization of the technical cycle, economic cycle and environmental cycle is addressed in a coherent and systematic way using the application of environmentally conscious design of cellular phones. The technical understanding of product structure, components analysis, and materials flow facilitates the development of "Design for Disassembly" guidelines. A bottom-up disassembly analysis on a "bill of materials" based structure at a micro-operational level is utilized to select optimal end-of-life strategies on the basis of economic feasibility. A macro-operational level life cycle model is used to investigate the environmental consequences linking environmental impact with the cellular phone production activities focusing on the upstream manufacturing and end-of-life life cycle stages. The last part of this work, the quantitative elicitation of weighting factors facilitates the comparison of trade-offs in the context of a multi-attribute problem. An integrated analytical approach, Integrated Industrial Ecology Function Deployment (I2-EFD), is proposed to assess alternatives at the design phase of a product system and is validated with the assessment of desktop display technologies and lead-free solder alternatives.

Social inequalities in adolescent depression: the role of parental social support and optimism.

PubMed

Piko, Bettina F; Luszczynska, Aleksandra; Fitzpatrick, Kevin M

2013-08-01

Interpersonal theory suggests relationships between socio-economic status (SES) and adolescent psychopathology mediated by negative parenting. This study examines the role of perceived parental social support and optimism in understanding adolescents' depression and self-rated health among a sample of Hungarian youth. Using a self-administered questionnaire, data (N = 881) were collected from high-school students (14-20 years old) in Szeged, Hungary (a regional centre in the southeastern region, near to the Serbian border, with a population of 170,000 inhabitants). To analyse the overall structure of the relationship between objective/subjective SES, parental support, optimism and health outcomes (depression, self-perceived health), structural equation modelling (SEM) was employed. Findings suggest the following: (1) SES variables generate social inequalities in adolescent depression through parental social support, particularly maternal support; and (2) parents provide youths with different levels of social support that in turn may strengthen or weaken optimism during the socialization process. In addressing depression prevention and treatment, we may want to take into account socio-economic differences in social networks and levels of optimism, which may influence youths' psychosocial adjustment and development of psychopathology.

Optimal CO2 mitigation under damage risk valuation

NASA Astrophysics Data System (ADS)

Crost, Benjamin; Traeger, Christian P.

2014-07-01

The current generation has to set mitigation policy under uncertainty about the economic consequences of climate change. This uncertainty governs both the level of damages for a given level of warming, and the steepness of the increase in damage per warming degree. Our model of climate and the economy is a stochastic version of a model employed in assessing the US Social Cost of Carbon (DICE). We compute the optimal carbon taxes and CO2 abatement levels that maximize welfare from economic consumption over time under different risk states. In accordance with recent developments in finance, we separate preferences about time and risk to improve the model's calibration of welfare to observed market interest. We show that introducing the modern asset pricing framework doubles optimal abatement and carbon taxation. Uncertainty over the level of damages at a given temperature increase can result in a slight increase of optimal emissions as compared to using expected damages. In contrast, uncertainty governing the steepness of the damage increase in temperature results in a substantially higher level of optimal mitigation.

A Hybrid Interval-Robust Optimization Model for Water Quality Management.

PubMed

Xu, Jieyu; Li, Yongping; Huang, Guohe

2013-05-01

In water quality management problems, uncertainties may exist in many system components and pollution-related processes ( i.e. , random nature of hydrodynamic conditions, variability in physicochemical processes, dynamic interactions between pollutant loading and receiving water bodies, and indeterminacy of available water and treated wastewater). These complexities lead to difficulties in formulating and solving the resulting nonlinear optimization problems. In this study, a hybrid interval-robust optimization (HIRO) method was developed through coupling stochastic robust optimization and interval linear programming. HIRO can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original chemical oxygen demand (COD) discharge constraints, HIRO enhances the robustness of the optimization processes and resulting solutions. This method was applied to planning of industry development in association with river-water pollution concern in New Binhai District of Tianjin, China. Results demonstrated that the proposed optimization model can effectively communicate uncertainties into the optimization process and generate a spectrum of potential inexact solutions supporting local decision makers in managing benefit-effective water quality management schemes. HIRO is helpful for analysis of policy scenarios related to different levels of economic penalties, while also providing insight into the tradeoff between system benefits and environmental requirements.

Enabling Parametric Optimal Ascent Trajectory Modeling During Early Phases of Design

NASA Technical Reports Server (NTRS)

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-modal due to the interaction of various constraints. Additionally, when these obstacles are coupled with The Program to Optimize Simulated Trajectories [1] (POST), an industry standard program to optimize ascent trajectories that is difficult to use, it requires expert trajectory analysts to effectively optimize a vehicle's ascent trajectory. As it has been pointed out, the paradigm of trajectory optimization is still a very manual one because using modern computational resources on POST is still a challenging problem. The nuances and difficulties involved in correctly utilizing, and therefore automating, the program presents a large problem. In order to address these issues, the authors will discuss a methodology that has been developed. The methodology is two-fold: first, a set of heuristics will be introduced and discussed that were captured while working with expert analysts to replicate the current state-of-the-art; secondly, leveraging the power of modern computing to evaluate multiple trajectories simultaneously, and therefore, enable the exploration of the trajectory's design space early during the pre-conceptual and conceptual phases of design. When this methodology is coupled with design of experiments in order to train surrogate models, the authors were able to visualize the trajectory design space, enabling parametric optimal ascent trajectory information to be introduced with other pre-conceptual and conceptual design tools. The potential impact of this methodology's success would be a fully automated POST evaluation suite for the purpose of conceptual and preliminary design trade studies. This will enable engineers to characterize the ascent trajectory's sensitivity to design changes in an arbitrary number of dimensions and for finding settings for trajectory specific variables, which result in optimal performance for a "dialed-in" launch vehicle design. The effort described in this paper was developed for the Advanced Concepts Office [2] at NASA Marshall Space Flight Center

Fractal attractors in economic growth models with random pollution externalities

NASA Astrophysics Data System (ADS)

La Torre, Davide; Marsiglio, Simone; Privileggi, Fabio

2018-05-01

We analyze a discrete time two-sector economic growth model where the production technologies in the final and human capital sectors are affected by random shocks both directly (via productivity and factor shares) and indirectly (via a pollution externality). We determine the optimal dynamics in the decentralized economy and show how these dynamics can be described in terms of a two-dimensional affine iterated function system with probability. This allows us to identify a suitable parameter configuration capable of generating exactly the classical Barnsley's fern as the attractor of the log-linearized optimal dynamical system.

Algorithm for solving of two-level hierarchical minimax program control problem of final state the regional socio-economic system in the presence of risks

NASA Astrophysics Data System (ADS)

Shorikov, A. F.

2017-10-01

In this paper we study the problem of optimization of guaranteed result for program control by the final state of regional social and economic system in the presence of risks. For this problem we propose a mathematical model in the form of two-level hierarchical minimax program control problem of the final state of this process with incomplete information. For solving of its problem we constructed the common algorithm that has a form of a recurrent procedure of solving a linear programming and a finite optimization problems.

Economic environmental dispatch using BSA algorithm

NASA Astrophysics Data System (ADS)

Jihane, Kartite; Mohamed, Cherkaoui

2018-05-01

Economic environmental dispatch problem (EED) is an important issue especially in the field of fossil fuel power plant system. It allows the network manager to choose among different units the most optimized in terms of fuel costs and emission level. The objective of this paper is to minimize the fuel cost with emissions constrained; the test is conducted for two cases: six generator unit and ten generator unit for the same power demand 1200Mw. The simulation has been computed in MATLAB and the result shows the robustness of the Backtracking Search optimization Algorithm (BSA) and the impact of the load demand on the emission.

Better Redd than Dead: Optimizing Reservoir Operations for Wild Fish Survival During Drought

NASA Astrophysics Data System (ADS)

Adams, L. E.; Lund, J. R.; Quiñones, R.

2014-12-01

Extreme droughts are difficult to predict and may incur large economic and ecological costs. Dam operations in drought usually consider minimizing economic costs. However, dam operations also offer an opportunity to increase wild fish survival under difficult conditions. Here, we develop a probabilistic optimization approach to developing reservoir release schedules to maximize fish survival in regulated rivers. A case study applies the approach to wild Fall-run Chinook Salmon below Folsom Dam on California's American River. Our results indicate that releasing more water early in the drought will, on average, save more wild fish over the long term.

The shutdown reactor: Optimizing spent fuel storage cost

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pennington, C.W.

1995-12-31

Several studies have indicated that the most prudent way to store fuel at a shutdown reactor site safely and economically is through the use of a dry storage facility licensed under 10CFR72. While such storage is certainly safe, is it true that the dry ISFSI represents the safest and most economical approach for the utility? While no one is really able to answer that question definitely, as yet, Holtec has studied this issue for some time and believes that both an economic and safety case can be made for an optimization strategy that calls for the use of both wetmore » and dry ISFSI storage of spent fuel at some plants. For the sake of brevity, this paper summarizes some of Holtec`s findings with respect to the economics of maintaining some fuel in wet storage at a shutdown reactor. The safety issue, or more importantly the perception of safety of spent fuel in wet storage, still varies too much with the eye of the beholder, and until a more rigorous presentation of safety analyses can be made in a regulatory setting, it is not practically useful to argue about how many angels can sit on the head of a safety-related pin. Holtec is prepared to present such analyses, but this does not appear to be the proper venue. Thus, this paper simply looks at certain economic elements of a wet ISFSI at a shutdown reactor to make a prima facie case that wet storage has some attractiveness at a shutdown reactor and should not be rejected out of hand. Indeed, an optimization study at certain plants may well show the economic vitality of keeping some fuel in the pool and converting the NRC licensing coverage from 10CFR50 to 10CFR72. If the economics look attractive, then the safety issue may be confronted with a compelling interest.« less

Performance of optimized McRAPD in identification of 9 yeast species frequently isolated from patient samples: potential for automation.

PubMed

Trtkova, Jitka; Pavlicek, Petr; Ruskova, Lenka; Hamal, Petr; Koukalova, Dagmar; Raclavsky, Vladislav

2009-11-10

Rapid, easy, economical and accurate species identification of yeasts isolated from clinical samples remains an important challenge for routine microbiological laboratories, because susceptibility to antifungal agents, probability to develop resistance and ability to cause disease vary in different species. To overcome the drawbacks of the currently available techniques we have recently proposed an innovative approach to yeast species identification based on RAPD genotyping and termed McRAPD (Melting curve of RAPD). Here we have evaluated its performance on a broader spectrum of clinically relevant yeast species and also examined the potential of automated and semi-automated interpretation of McRAPD data for yeast species identification. A simple fully automated algorithm based on normalized melting data identified 80% of the isolates correctly. When this algorithm was supplemented by semi-automated matching of decisive peaks in first derivative plots, 87% of the isolates were identified correctly. However, a computer-aided visual matching of derivative plots showed the best performance with average 98.3% of the accurately identified isolates, almost matching the 99.4% performance of traditional RAPD fingerprinting. Since McRAPD technique omits gel electrophoresis and can be performed in a rapid, economical and convenient way, we believe that it can find its place in routine identification of medically important yeasts in advanced diagnostic laboratories that are able to adopt this technique. It can also serve as a broad-range high-throughput technique for epidemiological surveillance.