Machining Parameters Optimization using Hybrid Firefly Algorithm and Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

77 FR 3544 - Meeting and Webinar on the Active Traffic and Demand Management and Intelligent Network Flow...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-24

... Intelligent Network Flow Optimization Operational Concepts; Notice of Public Meeting AGENCY: Research and... Demand Management (ADTM) and Intelligent Network Flow Optimization (INFLO) operational concepts. The ADTM... February 8, 2012, 8:30 to 4:30 p.m. The location for both meetings is the Hall of States, 444 North Capitol...

Lockheed L-1011 Test Station on-board in support of the Adaptive Performance Optimization flight res

NASA Technical Reports Server (NTRS)

1997-01-01

This console and its compliment of computers, monitors and commmunications equipment make up the Research Engineering Test Station, the nerve center for a new aerodynamics experiment being conducted by NASA's Dryden Flight Research Center, Edwards, California. The equipment is installed on a modified Lockheed L-1011 Tristar jetliner operated by Orbital Sciences Corp., of Dulles, Va., for Dryden's Adaptive Performance Optimization project. The experiment seeks to improve the efficiency of long-range jetliners by using small movements of the ailerons to improve the aerodynamics of the wing at cruise conditions. About a dozen research flights in the Adaptive Performance Optimization project are planned over the next two to three years. Improving the aerodynamic efficiency should result in equivalent reductions in fuel usage and costs for airlines operating large, wide-bodied jetliners.

Operations research applications in nuclear energy

NASA Astrophysics Data System (ADS)

Johnson, Benjamin Lloyd

This dissertation consists of three papers; the first is published in Annals of Operations Research, the second is nearing submission to INFORMS Journal on Computing, and the third is the predecessor of a paper nearing submission to Progress in Nuclear Energy. We apply operations research techniques to nuclear waste disposal and nuclear safeguards. Although these fields are different, they allow us to showcase some benefits of using operations research techniques to enhance nuclear energy applications. The first paper, "Optimizing High-Level Nuclear Waste Disposal within a Deep Geologic Repository," presents a mixed-integer programming model that determines where to place high-level nuclear waste packages in a deep geologic repository to minimize heat load concentration. We develop a heuristic that increases the size of solvable model instances. The second paper, "Optimally Configuring a Measurement System to Detect Diversions from a Nuclear Fuel Cycle," introduces a simulation-optimization algorithm and an integer-programming model to find the best, or near-best, resource-limited nuclear fuel cycle measurement system with a high degree of confidence. Given location-dependent measurement method precisions, we (i) optimize the configuration of n methods at n locations of a hypothetical nuclear fuel cycle facility, (ii) find the most important location at which to improve method precision, and (iii) determine the effect of measurement frequency on near-optimal configurations and objective values. Our results correspond to existing outcomes but we obtain them at least an order of magnitude faster. The third paper, "Optimizing Nuclear Material Control and Accountability Measurement Systems," extends the integer program from the second paper to locate measurement methods in a larger, hypothetical nuclear fuel cycle scenario given fixed purchase and utilization budgets. This paper also presents two mixed-integer quadratic programming models to increase the precision of existing methods given a fixed improvement budget and to reduce the measurement uncertainty in the system while limiting improvement costs. We quickly obtain similar or better solutions compared to several intuitive analyses that take much longer to perform.

Generalized Differential Calculus and Applications to Optimization

NASA Astrophysics Data System (ADS)

Rector, Robert Blake Hayden

This thesis contains contributions in three areas: the theory of generalized calculus, numerical algorithms for operations research, and applications of optimization to problems in modern electric power systems. A geometric approach is used to advance the theory and tools used for studying generalized notions of derivatives for nonsmooth functions. These advances specifically pertain to methods for calculating subdifferentials and to expanding our understanding of a certain notion of derivative of set-valued maps, called the coderivative, in infinite dimensions. A strong understanding of the subdifferential is essential for numerical optimization algorithms, which are developed and applied to nonsmooth problems in operations research, including non-convex problems. Finally, an optimization framework is applied to solve a problem in electric power systems involving a smart solar inverter and battery storage system providing energy and ancillary services to the grid.

Matthew O'Connell | NREL

Science.gov Websites

operation, especially in the WECC interconnection (Western US) Data analysis and analysis code development Research Interests Impact of increased renewables on electric grid operation and architechture Optimizing

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.

Standardized Methods for Electronic Shearography

NASA Technical Reports Server (NTRS)

Lansing, Matthew D.

1997-01-01

Research was conducted in development of operating procedures and standard methods to evaluate fiber reinforced composite materials, bonded or sprayed insulation, coatings, and laminated structures with MSFC electronic shearography systems. Optimal operating procedures were developed for the Pratt and Whitney Electronic Holography/Shearography Inspection System (EH/SIS) operating in shearography mode, as well as the Laser Technology, Inc. (LTI) SC-4000 and Ettemeyer SHS-94 ISTRA shearography systems. Operating practices for exciting the components being inspected were studied, including optimal methods for transient heating with heat lamps and other methods as appropriate to enhance inspection capability.

Future Marine Polar Research Capacities - Science Planning and Research Services for a Multi-National Research Icebreaker

NASA Astrophysics Data System (ADS)

Biebow, N.; Lembke-Jene, L.; Wolff-Boenisch, B.; Bergamasco, A.; De Santis, L.; Eldholm, O.; Mevel, C.; Willmott, V.; Thiede, J.

2011-12-01

Despite significant advances in Arctic and Antarctic marine science over the past years, the polar Southern Ocean remains a formidable frontier due to challenging technical and operational requirements. Thus, key data and observations from this important region are still missing or lack adequate lateral and temporal coverage, especially from time slots outside optimal weather seasons and ice conditions. These barriers combined with the obligation to efficiently use financial resources and funding for expeditions call for new approaches to create optimally equipped, but cost-effective infrastructures. These must serve the international science community in a dedicated long-term mode and enable participation in multi-disciplinary expeditions, with secured access to optimally equipped marine platforms for world-class research in a wide range of Antarctic science topics. The high operational and technical performance capacity of a future joint European Research Icebreaker and Deep-sea Drilling Vessel (the AURORA BOREALIS concept) aims at integrating still separately operating national science programmes with different strategic priorities into joint development of long-term research missions with international cooperation both in Arctic and Antarctica. The icebreaker is planned to enable, as a worldwide first, autonomous year-round operations in the central Arctic and polar Southern Ocean, including severest ice conditions in winter, and serving all polar marine disciplines. It will facilitate the implementation of atmospheric, oceanographic, cryospheric or geophysical observatories for long-term monitoring of the polar environment. Access to the biosphere and hydrosphere e.g. beneath ice shelves or in remote regions is made possible by acting as advanced deployment platform for instruments, robotic and autonomous vehicles and ship-based air operations. In addition to a report on the long-term strategic science and operational planning objectives, we describe foreseen on- and offshore science support infrastructure, recommended operational and scientific support structures and the relevance of AURORA BOREALIS for other present and future Antarctic science programmes and initiatives.

Optimal Facility-Location

PubMed Central

Goldman, A. J.

2006-01-01

Dr. Christoph Witzgall, the honoree of this Symposium, can count among his many contributions to applied mathematics and mathematical operations research a body of widely-recognized work on the optimal location of facilities. The present paper offers to non-specialists a sketch of that field and its evolution, with emphasis on areas most closely related to Witzgall’s research at NBS/NIST. PMID:27274920

Optimizing water purchases for an Environmental Water Account

NASA Astrophysics Data System (ADS)

Lund, J. R.; Hollinshead, S. P.

2005-12-01

State and federal agencies in California have established an Environmental Water Account (EWA) to buy water to protect endangered fish in the San Francisco Bay/ Sacramento-San Joaquin Delta Estuary. This paper presents a three-stage probabilistic optimization model that identifies least-cost strategies for purchasing water for the EWA given hydrologic, operational, and biological uncertainties. This approach minimizes the expected cost of long-term, spot, and option water purchases to meet uncertain flow dedications for fish. The model prescribes the location, timing, and type of optimal water purchases and can illustrate how least-cost strategies change with hydrologic, operational, biological, and cost inputs. Details of the optimization model's application to California's EWA are provided with a discussion of its utility for strategic planning and policy purposes. Limitations in and sensitivity analysis of the model's representation of EWA operations are discussed, as are operational and research recommendations.

Optimization Research of Generation Investment Based on Linear Programming Model

NASA Astrophysics Data System (ADS)

Wu, Juan; Ge, Xueqian

Linear programming is an important branch of operational research and it is a mathematical method to assist the people to carry out scientific management. GAMS is an advanced simulation and optimization modeling language and it will combine a large number of complex mathematical programming, such as linear programming LP, nonlinear programming NLP, MIP and other mixed-integer programming with the system simulation. In this paper, based on the linear programming model, the optimized investment decision-making of generation is simulated and analyzed. At last, the optimal installed capacity of power plants and the final total cost are got, which provides the rational decision-making basis for optimized investments.

Flight Test of an Adaptive Configuration Optimization System for Transport Aircraft

NASA Technical Reports Server (NTRS)

Gilyard, Glenn B.; Georgie, Jennifer; Barnicki, Joseph S.

1999-01-01

A NASA Dryden Flight Research Center program explores the practical application of real-time adaptive configuration optimization for enhanced transport performance on an L-1011 aircraft. This approach is based on calculation of incremental drag from forced-response, symmetric, outboard aileron maneuvers. In real-time operation, the symmetric outboard aileron deflection is directly optimized, and the horizontal stabilator and angle of attack are indirectly optimized. A flight experiment has been conducted from an onboard research engineering test station, and flight research results are presented herein. The optimization system has demonstrated the capability of determining the minimum drag configuration of the aircraft in real time. The drag-minimization algorithm is capable of identifying drag to approximately a one-drag-count level. Optimizing the symmetric outboard aileron position realizes a drag reduction of 2-3 drag counts (approximately 1 percent). Algorithm analysis of maneuvers indicate that two-sided raised-cosine maneuvers improve definition of the symmetric outboard aileron drag effect, thereby improving analysis results and consistency. Ramp maneuvers provide a more even distribution of data collection as a function of excitation deflection than raised-cosine maneuvers provide. A commercial operational system would require airdata calculations and normal output of current inertial navigation systems; engine pressure ratio measurements would be optional.

Intel Xeon Phi accelerated Weather Research and Forecasting (WRF) Goddard microphysics scheme

NASA Astrophysics Data System (ADS)

Mielikainen, J.; Huang, B.; Huang, A. H.-L.

2014-12-01

The Weather Research and Forecasting (WRF) model is a numerical weather prediction system designed to serve both atmospheric research and operational forecasting needs. The WRF development is a done in collaboration around the globe. Furthermore, the WRF is used by academic atmospheric scientists, weather forecasters at the operational centers and so on. The WRF contains several physics components. The most time consuming one is the microphysics. One microphysics scheme is the Goddard cloud microphysics scheme. It is a sophisticated cloud microphysics scheme in the Weather Research and Forecasting (WRF) model. The Goddard microphysics scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. Compared to the earlier microphysics schemes, the Goddard scheme incorporates a large number of improvements. Thus, we have optimized the Goddard scheme code. In this paper, we present our results of optimizing the Goddard microphysics scheme on Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a high performance on-die bidirectional interconnect. The Intel MIC is capable of executing a full operating system and entire programs rather than just kernels as the GPU does. The MIC coprocessor supports all important Intel development tools. Thus, the development environment is one familiar to a vast number of CPU developers. Although, getting a maximum performance out of MICs will require using some novel optimization techniques. Those optimization techniques are discussed in this paper. The results show that the optimizations improved performance of Goddard microphysics scheme on Xeon Phi 7120P by a factor of 4.7×. In addition, the optimizations reduced the Goddard microphysics scheme's share of the total WRF processing time from 20.0 to 7.5%. Furthermore, the same optimizations improved performance on Intel Xeon E5-2670 by a factor of 2.8× compared to the original code.

Study of dynamics of X-14B VTOL aircraft

NASA Technical Reports Server (NTRS)

Loscutoff, W. V.; Mitchiner, J. L.; Roesener, R. A.; Seevers, J. A.

1973-01-01

Research was initiated to investigate certain facets of modern control theory and their integration with a digital computer to provide a tractable flight control system for a VTOL aircraft. Since the hover mode is the most demanding phase in the operation of a VTOL aircraft, the research efforts were concentrated in this mode of aircraft operation. Research work on three different aspects of the operation of the X-14B VTOL aircraft is discussed. A general theory for optimal, prespecified, closed-loop control is developed. The ultimate goal was optimal decoupling of the modes of the VTOL aircraft to simplify the pilot's task of handling the aircraft. Modern control theory is used to design deterministic state estimators which provide state variables not measured directly, but which are needed for state variable feedback control. The effect of atmospheric turbulence on the X-14B is investigated. A maximum magnitude gust envelope within which the aircraft could operate stably with the available control power is determined.

Combinational Optimal Stopping Problems

DTIC Science & Technology

2016-04-01

such as final, technical, interim, memorandum, master’s thesis, progress, quarterly, research , special, group study, etc. 3. DATES COVERED...Vinel, A. and P. Krokhmal (2015) Certainty equivalent measures of risk, Annals of Operations Research , DOI:10.1007/s10479-015-1801-0. [3] Chernikov...Operations Research , 50(3):415–423, 2002. [16] I. Ljubi, P. Mutzel, and B. Zey. Stochastic survivable network design problems. Electronic Notes in Discrete

Application of the Software as a Service Model to the Control of Complex Building Systems

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

Stadler, Michael; Donadee, Jonathan; Marnay, Chris

2011-03-17

In an effort to create broad access to its optimization software, Lawrence Berkeley National Laboratory (LBNL), in collaboration with the University of California at Davis (UC Davis) and OSISoft, has recently developed a Software as a Service (SaaS) Model for reducing energy costs, cutting peak power demand, and reducing carbon emissions for multipurpose buildings. UC Davis currently collects and stores energy usage data from buildings on its campus. Researchers at LBNL sought to demonstrate that a SaaS application architecture could be built on top of this data system to optimize the scheduling of electricity and heat delivery in the building.more » The SaaS interface, known as WebOpt, consists of two major parts: a) the investment& planning and b) the operations module, which builds on the investment& planning module. The operational scheduling and load shifting optimization models within the operations module use data from load prediction and electrical grid emissions models to create an optimal operating schedule for the next week, reducing peak electricity consumption while maintaining quality of energy services. LBNL's application also provides facility managers with suggested energy infrastructure investments for achieving their energy cost and emission goals based on historical data collected with OSISoft's system. This paper describes these models as well as the SaaS architecture employed by LBNL researchers to provide asset scheduling services to UC Davis. The peak demand, emissions, and cost implications of the asset operation schedule and investments suggested by this optimization model are analysed.« less

Application of the Software as a Service Model to the Control of Complex Building Systems

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

Stadler, Michael; Donadee, Jon; Marnay, Chris

2011-03-18

In an effort to create broad access to its optimization software, Lawrence Berkeley National Laboratory (LBNL), in collaboration with the University of California at Davis (UC Davis) and OSISoft, has recently developed a Software as a Service (SaaS) Model for reducing energy costs, cutting peak power demand, and reducing carbon emissions for multipurpose buildings. UC Davis currently collects and stores energy usage data from buildings on its campus. Researchers at LBNL sought to demonstrate that a SaaS application architecture could be built on top of this data system to optimize the scheduling of electricity and heat delivery in the building.more » The SaaS interface, known as WebOpt, consists of two major parts: a) the investment& planning and b) the operations module, which builds on the investment& planning module. The operational scheduling and load shifting optimization models within the operations module use data from load prediction and electrical grid emissions models to create an optimal operating schedule for the next week, reducing peak electricity consumption while maintaining quality of energy services. LBNL's application also provides facility managers with suggested energy infrastructure investments for achieving their energy cost and emission goals based on historical data collected with OSISoft's system. This paper describes these models as well as the SaaS architecture employed by LBNL researchers to provide asset scheduling services to UC Davis. The peak demand, emissions, and cost implications of the asset operation schedule and investments suggested by this optimization model are analyzed.« less

Tuning the heat transfer medium and operating conditions in magnetic refrigeration

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

Ghahremani, Mohammadreza, E-mail: mghahrem@shepherd.edu; Dept. of Electrical and Computer Engineering, The George Washington University, Washington DC 20052; Aslani, Amir

A new experimental test bed has been designed, built, and tested to evaluate the effect of the system’s parameters on a reciprocating Active Magnetic Regenerator (AMR) near room temperature. Bulk gadolinium was used as the refrigerant, silicon oil as the heat transfer medium, and a magnetic field of 1.3 T was cycled. This study focuses on the methodology of single stage AMR operation conditions to get a high temperature span near room temperature. Herein, the main objective is not to report the absolute maximum attainable temperature span seen in an AMR system, but rather to find the system’s optimal operatingmore » conditions to reach that maximum span. The results of this research show that there is a optimal operating frequency, heat transfer fluid flow rate, flow duration, and displaced volume ratio in any AMR system. By optimizing these parameters in our AMR apparatus the temperature span between the hot and cold ends increased by 24%. The optimized values are system dependent and need to be determined and measured for any AMR system by following the procedures that are introduced in this research. It is expected that such optimization will permit the design of a more efficient magnetic refrigeration system.« less

Natural Environmental Service Support to NASA Vehicle, Technology, and Sensor Development Programs

NASA Technical Reports Server (NTRS)

1993-01-01

The research performed under this contract involved definition of the natural environmental parameters affecting the design, development, and operation of space and launch vehicles. The Universities Space Research Association (USRA) provided the manpower and resources to accomplish the following tasks: defining environmental parameters critical for design, development, and operation of launch vehicles; defining environmental forecasts required to assure optimal utilization of launch vehicles; and defining orbital environments of operation and developing models on environmental parameters affecting launch vehicle operations.

The technological raw material heating furnaces operation efficiency improving issue

NASA Astrophysics Data System (ADS)

Paramonov, A. M.

2017-08-01

The issue of fuel oil applying efficiency improving in the technological raw material heating furnaces by means of its combustion intensification is considered in the paper. The technical and economic optimization problem of the fuel oil heating before combustion is solved. The fuel oil heating optimal temperature defining method and algorithm analytically considering the correlation of thermal, operating parameters and discounted costs for the heating furnace were developed. The obtained optimization functionality provides the heating furnace appropriate thermal indices achievement at minimum discounted costs. The carried out research results prove the expediency of the proposed solutions using.

Optimal assignment of workers to supporting services in a hospital

NASA Astrophysics Data System (ADS)

Sawik, Bartosz; Mikulik, Jerzy

2008-01-01

Supporting services play an important role in health care institutions such as hospitals. This paper presents an application of operations research model for optimal allocation of workers among supporting services in a public hospital. The services include logistics, inventory management, financial management, operations management, medical analysis, etc. The optimality criterion of the problem is to minimize operations costs of supporting services subject to some specific constraints. The constraints represent specific conditions for resource allocation in a hospital. The overall problem is formulated as an integer program in the literature known as the assignment problem, where the decision variables represent the assignment of people to various jobs. The results of some computational experiments modeled on a real data from a selected Polish hospital are reported.

Modeling and Optimization of Coordinative Operation of Hydro-wind-photovoltaic Considering Power Generation and Output Fluctuation

NASA Astrophysics Data System (ADS)

Wang, Xianxun; Mei, Yadong

2017-04-01

Coordinative operation of hydro-wind-photovoltaic is the solution of mitigating the conflict of power generation and output fluctuation of new energy and conquering the bottleneck of new energy development. Due to the deficiencies of characterizing output fluctuation, depicting grid construction and disposal of power abandon, the research of coordinative mechanism is influenced. In this paper, the multi-object and multi-hierarchy model of coordinative operation of hydro-wind-photovoltaic is built with the aim of maximizing power generation and minimizing output fluctuation and the constraints of topotaxy of power grid and balanced disposal of power abandon. In the case study, the comparison of uncoordinative and coordinative operation is carried out with the perspectives of power generation, power abandon and output fluctuation. By comparison from power generation, power abandon and output fluctuation between separate operation and coordinative operation of multi-power, the coordinative mechanism is studied. Compared with running solely, coordinative operation of hydro-wind-photovoltaic can gain the compensation benefits. Peak-alternation operation reduces the power abandon significantly and maximizes resource utilization effectively by compensating regulation of hydropower. The Pareto frontier of power generation and output fluctuation is obtained through multiple-objective optimization. It clarifies the relationship of mutual influence between these two objects. When coordinative operation is taken, output fluctuation can be markedly reduced at the cost of a slight decline of power generation. The power abandon also drops sharply compared with operating separately. Applying multi-objective optimization method to optimize the coordinate operation, Pareto optimal solution set of power generation and output fluctuation is achieved.

Opportunities for research in space life sciences aboard commercial suborbital flights.

PubMed

Wagner, Erika B; Charles, John B; Cuttino, Charles Marsh

2009-11-01

The emergence of commercial suborbital spaceflight offers a wide range of new research and development opportunities for those in the space life sciences. Large numbers of diverse flyers, frequent re-flights, and flexible operations provide a fertile ground for both basic and applied science, as well as technology demonstrations. This commentary explores some of the unique features available to the space life science community and encourages engagement with commercial developers and operators during the design phase to help optimize platform designs and operations for future research.

Optimal Learning for Efficient Experimentation in Nanotechnology and Biochemistry

DTIC Science & Technology

2015-12-22

AFRL-AFOSR-VA-TR-2016-0018 Optimal Learning for Efficient Experimentation in Nanotechnology , Biochemistry Warren Powell TRUSTEES OF PRINCETON...3. DATES COVERED (From - To) 01-07-2012 to 30-09-2015 4. TITLE AND SUBTITLE Optimal Learning for Efficient Experimentation in Nanotechnology and...in Nanotechnology and Biochemistry Principal Investigators: Warren B. Powell Princeton University Department of Operations Research and

Premium cost optimization of operational and maintenance of green building in Indonesia using life cycle assessment method

NASA Astrophysics Data System (ADS)

Latief, Yusuf; Berawi, Mohammed Ali; Basten, Van; Budiman, Rachmat; Riswanto

2017-06-01

Building has a big impact on the environmental developments. There are three general motives in building, namely the economy, society, and environment. Total completed building construction in Indonesia increased by 116% during 2009 to 2011. It made the energy consumption increased by 11% within the last three years. In fact, 70% of energy consumption is used for electricity needs on commercial buildings which leads to an increase of greenhouse gas emissions by 25%. Green Building cycle costs is known as highly building upfront cost in Indonesia. The purpose of optimization in this research improves building performance with some of green concept alternatives. Research methodology is mixed method of qualitative and quantitative approaches through questionnaire surveys and case study. Assessing the successful of optimization functions in the existing green building is based on the operational and maintenance phase with the Life Cycle Assessment Method. Choosing optimization results were based on the largest efficiency of building life cycle and the most effective cost to refund.

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

PubMed

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

2018-05-01

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

Research on Operation Strategy for Bundled Wind-thermal Generation Power Systems Based on Two-Stage Optimization Model

NASA Astrophysics Data System (ADS)

Sun, Congcong; Wang, Zhijie; Liu, Sanming; Jiang, Xiuchen; Sheng, Gehao; Liu, Tianyu

2017-05-01

Wind power has the advantages of being clean and non-polluting and the development of bundled wind-thermal generation power systems (BWTGSs) is one of the important means to improve wind power accommodation rate and implement “clean alternative” on generation side. A two-stage optimization strategy for BWTGSs considering wind speed forecasting results and load characteristics is proposed. By taking short-term wind speed forecasting results of generation side and load characteristics of demand side into account, a two-stage optimization model for BWTGSs is formulated. By using the environmental benefit index of BWTGSs as the objective function, supply-demand balance and generator operation as the constraints, the first-stage optimization model is developed with the chance-constrained programming theory. By using the operation cost for BWTGSs as the objective function, the second-stage optimization model is developed with the greedy algorithm. The improved PSO algorithm is employed to solve the model and numerical test verifies the effectiveness of the proposed strategy.

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.

Integrated Urban Flood Analysis considering Optimal Operation of Flood Control Facilities in Urban Drainage Networks

NASA Astrophysics Data System (ADS)

Moon, Y. I.; Kim, M. S.; Choi, J. H.; Yuk, G. M.

2017-12-01

eavy rainfall has become a recent major cause of urban area flooding due to the climate change and urbanization. To prevent property damage along with casualties, a system which can alert and forecast urban flooding must be developed. Optimal performance of reducing flood damage can be expected of urban drainage facilities when operated in smaller rainfall events over extreme ones. Thus, the purpose of this study is to execute: A) flood forecasting system using runoff analysis based on short term rainfall; and B) flood warning system which operates based on the data from pump stations and rainwater storage in urban basins. In result of the analysis, it is shown that urban drainage facilities using short term rainfall forecasting data by radar will be more effective to reduce urban flood damage than using only the inflow data of the facility. Keywords: Heavy Rainfall, Urban Flood, Short-term Rainfall Forecasting, Optimal operating of urban drainage facilities. AcknowledgmentsThis research was supported by a grant (17AWMP-B066744-05) from Advanced Water Management Research Program (AWMP) funded by Ministry of Land, Infrastructure and Transport of Korean government.

Collaboration pathway(s) using new tools for optimizing `operational' climate monitoring from space

NASA Astrophysics Data System (ADS)

Helmuth, Douglas B.; Selva, Daniel; Dwyer, Morgan M.

2015-09-01

Consistently collecting the earth's climate signatures remains a priority for world governments and international scientific organizations. Architecting a long term solution requires transforming scientific missions into an optimized robust `operational' constellation that addresses the collective needs of policy makers, scientific communities and global academic users for trusted data. The application of new tools offers pathways for global architecture collaboration. Recent rule-based expert system (RBES) optimization modeling of the intended NPOESS architecture becomes a surrogate for global operational climate monitoring architecture(s). These rulebased systems tools provide valuable insight for global climate architectures, by comparison/evaluation of alternatives and the sheer range of trade space explored. Optimization of climate monitoring architecture(s) for a partial list of ECV (essential climate variables) is explored and described in detail with dialogue on appropriate rule-based valuations. These optimization tool(s) suggest global collaboration advantages and elicit responses from the audience and climate science community. This paper will focus on recent research exploring joint requirement implications of the high profile NPOESS architecture and extends the research and tools to optimization for a climate centric case study. This reflects work from SPIE RS Conferences 2013 and 2014, abridged for simplification30, 32. First, the heavily securitized NPOESS architecture; inspired the recent research question - was Complexity (as a cost/risk factor) overlooked when considering the benefits of aggregating different missions into a single platform. Now years later a complete reversal; should agencies considering Disaggregation as the answer. We'll discuss what some academic research suggests. Second, using the GCOS requirements of earth climate observations via ECV (essential climate variables) many collected from space-based sensors; and accepting their definitions of global coverages intended to ensure the needs of major global and international organizations (UNFCCC and IPCC) are met as a core objective. Consider how new optimization tools like rule-based engines (RBES) offer alternative methods of evaluating collaborative architectures and constellations? What would the trade space of optimized operational climate monitoring architectures of ECV look like? Third, using the RBES tool kit (2014) demonstrate with application to a climate centric rule-based decision engine - optimizing architectural trades of earth observation satellite systems, allowing comparison(s) to existing architectures and gaining insights for global collaborative architectures. How difficult is it to pull together an optimized climate case study - utilizing for example 12 climate based instruments on multiple existing platforms and nominal handful of orbits; for best cost and performance benefits against the collection requirements of representative set of ECV. How much effort and resources would an organization expect to invest to realize these analysis and utility benefits?

A method to combine hydrodynamics and constructive design in the optimization of the runner blades of Kaplan turbines

NASA Astrophysics Data System (ADS)

Miclosina, C. O.; Balint, D. I.; Campian, C. V.; Frunzaverde, D.; Ion, I.

2012-11-01

This paper deals with the optimization of the axial hydraulic turbines of Kaplan type. The optimization of the runner blade is presented systematically from two points of view: hydrodynamic and constructive. Combining these aspects in order to gain a safer operation when unsteady effects occur in the runner of the turbine is attempted. The design and optimization of the runner blade is performed with QTurbo3D software developed at the Center for Research in Hydraulics, Automation and Thermal Processes (CCHAPT) from "Eftimie Murgu" University of Resita, Romania. QTurbo3D software offers possibilities to design the meridian channel of hydraulic turbines design the blades and optimize the runner blade. 3D modeling and motion analysis of the runner blade operating mechanism are accomplished using SolidWorks software. The purpose of motion study is to obtain forces, torques or stresses in the runner blade operating mechanism, necessary to estimate its lifetime. This paper clearly states the importance of combining the hydrodynamics with the structural design in the optimization procedure of the runner of hydraulic turbines.

A mixed integer linear programming model for operational planning of a biodiesel supply chain network from used cooking oil

NASA Astrophysics Data System (ADS)

Jonrinaldi, Hadiguna, Rika Ampuh; Salastino, Rades

2017-11-01

Environmental consciousness has paid many attention nowadays. It is not only about how to recycle, remanufacture or reuse used end products but it is also how to optimize the operations of the reverse system. A previous research has proposed a design of reverse supply chain of biodiesel network from used cooking oil. However, the research focused on the design of the supply chain strategy not the operations of the supply chain. It only decided how to design the structure of the supply chain in the next few years, and the process of each stage will be conducted in the supply chain system in general. The supply chain system has not considered operational policies to be conducted by the companies in the supply chain. Companies need a policy for each stage of the supply chain operations to be conducted so as to produce the optimal supply chain system, including how to use all the resources that have been designed in order to achieve the objectives of the supply chain system. Therefore, this paper proposes a model to optimize the operational planning of a biodiesel supply chain network from used cooking oil. A mixed integer linear programming is developed to model the operational planning of biodiesel supply chain in order to minimize the total operational cost of the supply chain. Based on the implementation of the model developed, the total operational cost of the biodiesel supply chain incurred by the system is less than the total operational cost of supply chain based on the previous research during seven days of operational planning about amount of 2,743,470.00 or 0.186%. Production costs contributed to 74.6 % of total operational cost and the cost of purchasing the used cooking oil contributed to 24.1 % of total operational cost. So, the system should pay more attention to these two aspects as changes in the value of these aspects will cause significant effects to the change in the total operational cost of the supply chain.

Self-Averaging Property of Minimal Investment Risk of Mean-Variance Model.

PubMed

Shinzato, Takashi

2015-01-01

In portfolio optimization problems, the minimum expected investment risk is not always smaller than the expected minimal investment risk. That is, using a well-known approach from operations research, it is possible to derive a strategy that minimizes the expected investment risk, but this strategy does not always result in the best rate of return on assets. Prior to making investment decisions, it is important to an investor to know the potential minimal investment risk (or the expected minimal investment risk) and to determine the strategy that will maximize the return on assets. We use the self-averaging property to analyze the potential minimal investment risk and the concentrated investment level for the strategy that gives the best rate of return. We compare the results from our method with the results obtained by the operations research approach and with those obtained by a numerical simulation using the optimal portfolio. The results of our method and the numerical simulation are in agreement, but they differ from that of the operations research approach.

Systematic design for trait introgression projects.

PubMed

Cameron, John N; Han, Ye; Wang, Lizhi; Beavis, William D

2017-10-01

Using an Operations Research approach, we demonstrate design of optimal trait introgression projects with respect to competing objectives. We demonstrate an innovative approach for designing Trait Introgression (TI) projects based on optimization principles from Operations Research. If the designs of TI projects are based on clear and measurable objectives, they can be translated into mathematical models with decision variables and constraints that can be translated into Pareto optimality plots associated with any arbitrary selection strategy. The Pareto plots can be used to make rational decisions concerning the trade-offs between maximizing the probability of success while minimizing costs and time. The systematic rigor associated with a cost, time and probability of success (CTP) framework is well suited to designing TI projects that require dynamic decision making. The CTP framework also revealed that previously identified 'best' strategies can be improved to be at least twice as effective without increasing time or expenses.

Social Emotional Optimization Algorithm for Nonlinear Constrained Optimization Problems

NASA Astrophysics Data System (ADS)

Xu, Yuechun; Cui, Zhihua; Zeng, Jianchao

Nonlinear programming problem is one important branch in operational research, and has been successfully applied to various real-life problems. In this paper, a new approach called Social emotional optimization algorithm (SEOA) is used to solve this problem which is a new swarm intelligent technique by simulating the human behavior guided by emotion. Simulation results show that the social emotional optimization algorithm proposed in this paper is effective and efficiency for the nonlinear constrained programming problems.

Common Methodology for Efficient Airspace Operations

NASA Technical Reports Server (NTRS)

Sridhar, Banavar

2012-01-01

Topics include: a) Developing a common methodology to model and avoid disturbances affecting airspace. b) Integrated contrails and emission models to a national level airspace simulation. c) Developed capability to visualize, evaluate technology and alternate operational concepts and provide inputs for policy-analysis tools to reduce the impact of aviation on the environment. d) Collaborating with Volpe Research Center, NOAA and DLR to leverage expertise and tools in aircraft emissions and weather/climate modeling. Airspace operations is a trade-off balancing safety, capacity, efficiency and environmental considerations. Ideal flight: Unimpeded wind optimal route with optimal climb and descent. Operations degraded due to reduction in airport and airspace capacity caused by inefficient procedures and disturbances.

Housing Operation Taking into Account Obsolescence and Physical Deterioration

NASA Astrophysics Data System (ADS)

Petrenko, L.; Manjilevskaja, S.

2017-11-01

The article focuses on the basic theory and practical aspects of improving the strategic management in terms of enhancing the quality of a technological process: these aspects have been proven experimentally by their introduction in company operations. The authors have worked out some proposals aimed at selecting an optimal supplier for building companies as well as the algorithm for the analysis and optimization of a construction company basing on scientific and practical research and the experimental data obtained in the experiment

Optimization of an interactive distributive computer network

NASA Technical Reports Server (NTRS)

Frederick, V.

1985-01-01

The activities under a cooperative agreement for the development of a computer network are briefly summarized. Research activities covered are: computer operating systems optimization and integration; software development and implementation of the IRIS (Infrared Imaging of Shuttle) Experiment; and software design, development, and implementation of the APS (Aerosol Particle System) Experiment.

Algorithms for Mathematical Programming with Emphasis on Bi-level Models

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

Goldfarb, Donald; Iyengar, Garud

2014-05-22

The research supported by this grant was focused primarily on first-order methods for solving large scale and structured convex optimization problems and convex relaxations of nonconvex problems. These include optimal gradient methods, operator and variable splitting methods, alternating direction augmented Lagrangian methods, and block coordinate descent methods.

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.

[Early activation of heart-operated patients as a tool for optimization of cardio-surgery curation (review)].

PubMed

2014-04-01

During last years in foreign countries there was widely introduced tactic of early activation of cardio-surgery patients. Necessary components of this methodical approach are early finishing of post-operation artificial respiration and extubation of trachea, shortening of time spending in intensive therapy till 1 day and sign out from stationary after 5 days. As a result of reducing hospitalization period, the curation costs are reduced significantly. Goal of this research was the analysis of methods of anesthesia that allow early extubation and activation after cardio-surgery interventions. There were analyzed data of protocols of anesthesia and post-operation periods for 270 patients. It was concluded that applied methods of anesthesia ensure adequate protection from operation stress and allow reduce time of post-operation artificial respiration, early activation of patients without reducing level of their safety. It was also proved that application of any type of anesthesia medicines is not influencing the temp of post-operation activation. Conducted research is proving the advisability of using tactic of early activation of patients after heart operations and considers this as a tool for optimization of cardio-surgery curation.

HURON (HUman and Robotic Optimization Network) Multi-Agent Temporal Activity Planner/Scheduler

NASA Technical Reports Server (NTRS)

Hua, Hook; Mrozinski, Joseph J.; Elfes, Alberto; Adumitroaie, Virgil; Shelton, Kacie E.; Smith, Jeffrey H.; Lincoln, William P.; Weisbin, Charles R.

2012-01-01

HURON solves the problem of how to optimize a plan and schedule for assigning multiple agents to a temporal sequence of actions (e.g., science tasks). Developed as a generic planning and scheduling tool, HURON has been used to optimize space mission surface operations. The tool has also been used to analyze lunar architectures for a variety of surface operational scenarios in order to maximize return on investment and productivity. These scenarios include numerous science activities performed by a diverse set of agents: humans, teleoperated rovers, and autonomous rovers. Once given a set of agents, activities, resources, resource constraints, temporal constraints, and de pendencies, HURON computes an optimal schedule that meets a specified goal (e.g., maximum productivity or minimum time), subject to the constraints. HURON performs planning and scheduling optimization as a graph search in state-space with forward progression. Each node in the graph contains a state instance. Starting with the initial node, a graph is automatically constructed with new successive nodes of each new state to explore. The optimization uses a set of pre-conditions and post-conditions to create the children states. The Python language was adopted to not only enable more agile development, but to also allow the domain experts to easily define their optimization models. A graphical user interface was also developed to facilitate real-time search information feedback and interaction by the operator in the search optimization process. The HURON package has many potential uses in the fields of Operations Research and Management Science where this technology applies to many commercial domains requiring optimization to reduce costs. For example, optimizing a fleet of transportation truck routes, aircraft flight scheduling, and other route-planning scenarios involving multiple agent task optimization would all benefit by using HURON.

Model-based optimal design of active cool thermal energy storage for maximal life-cycle cost saving from demand management in commercial buildings

DOE PAGES

Cui, Borui; Gao, Dian-ce; Xiao, Fu; ...

2016-12-23

This article provides a method in comprehensive evaluation of cost-saving potential of active cool thermal energy storage (CTES) integrated with HVAC system for demand management in non-residential building. The active storage is beneficial by shifting peak demand for peak load management (PLM) as well as providing longer duration and larger capacity of demand response (DR). In this research, a model-based optimal design method using genetic algorithm is developed to optimize the capacity of active CTES aiming for maximizing the life-cycle cost saving concerning capital cost associated with storage capacity as well as incentives from both fast DR and PLM. Inmore » the method, the active CTES operates under a fast DR control strategy during DR events while under the storage-priority operation mode to shift peak demand during normal days. The optimal storage capacities, maximum annual net cost saving and corresponding power reduction set-points during DR event are obtained by using the proposed optimal design method. Lastly, this research provides guidance in comprehensive evaluation of cost-saving potential of CTES integrated with HVAC system for building demand management including both fast DR and PLM.« less

Model-based optimal design of active cool thermal energy storage for maximal life-cycle cost saving from demand management in commercial buildings

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

Cui, Borui; Gao, Dian-ce; Xiao, Fu

This article provides a method in comprehensive evaluation of cost-saving potential of active cool thermal energy storage (CTES) integrated with HVAC system for demand management in non-residential building. The active storage is beneficial by shifting peak demand for peak load management (PLM) as well as providing longer duration and larger capacity of demand response (DR). In this research, a model-based optimal design method using genetic algorithm is developed to optimize the capacity of active CTES aiming for maximizing the life-cycle cost saving concerning capital cost associated with storage capacity as well as incentives from both fast DR and PLM. Inmore » the method, the active CTES operates under a fast DR control strategy during DR events while under the storage-priority operation mode to shift peak demand during normal days. The optimal storage capacities, maximum annual net cost saving and corresponding power reduction set-points during DR event are obtained by using the proposed optimal design method. Lastly, this research provides guidance in comprehensive evaluation of cost-saving potential of CTES integrated with HVAC system for building demand management including both fast DR and PLM.« less

Optimal Semi-Adaptive Search With False Targets

DTIC Science & Technology

2017-12-01

we do not execute a full experimental design to attempt to build a response surface for the performance of these model under various combinations of...the degree of MASTER OF SCIENCE IN OPERATIONS RESEARCH from the NAVAL POSTGRADUATE SCHOOL December 2017 Approved by: Johannes O. Royset, Ph.D. Thesis...Advisor Dashi I. Singham, Ph.D. Second Reader Patricia A. Jacobs, Ph.D. Chair, Department of Operations Research iii THIS PAGE INTENTIONALLY LEFT

Performance analysis and optimization of power plants with gas turbines

NASA Astrophysics Data System (ADS)

Besharati-Givi, Maryam

The gas turbine is one of the most important applications for power generation. The purpose of this research is performance analysis and optimization of power plants by using different design systems at different operation conditions. In this research, accurate efficiency calculation and finding optimum values of efficiency for design of chiller inlet cooling and blade cooled gas turbine are investigated. This research shows how it is possible to find the optimum design for different operation conditions, like ambient temperature, relative humidity, turbine inlet temperature, and compressor pressure ratio. The simulated designs include the chiller, with varied COP and fogging cooling for a compressor. In addition, the overall thermal efficiency is improved by adding some design systems like reheat and regenerative heating. The other goal of this research focuses on the blade-cooled gas turbine for higher turbine inlet temperature, and consequently, higher efficiency. New film cooling equations, along with changing film cooling effectiveness for optimum cooling air requirement at the first-stage blades, and an internal and trailing edge cooling for the second stage, are innovated for optimal efficiency calculation. This research sets the groundwork for using the optimum value of efficiency calculation, while using inlet cooling and blade cooling designs. In the final step, the designed systems in the gas cycles are combined with a steam cycle for performance improvement.

Research reactor loading pattern optimization using estimation of distribution algorithms

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

Jiang, S.; Ziver, K.; AMCG Group, RM Consultants, Abingdon

2006-07-01

A new evolutionary search based approach for solving the nuclear reactor loading pattern optimization problems is presented based on the Estimation of Distribution Algorithms. The optimization technique developed is then applied to the maximization of the effective multiplication factor (K{sub eff}) of the Imperial College CONSORT research reactor (the last remaining civilian research reactor in the United Kingdom). A new elitism-guided searching strategy has been developed and applied to improve the local convergence together with some problem-dependent information based on the 'stand-alone K{sub eff} with fuel coupling calculations. A comparison study between the EDAs and a Genetic Algorithm with Heuristicmore » Tie Breaking Crossover operator has shown that the new algorithm is efficient and robust. (authors)« less

Nutrition in peri-operative esophageal cancer management.

PubMed

Steenhagen, Elles; van Vulpen, Jonna K; van Hillegersberg, Richard; May, Anne M; Siersema, Peter D

2017-07-01

Nutritional status and dietary intake are increasingly recognized as essential areas in esophageal cancer management. Nutritional management of esophageal cancer is a continuously evolving field and comprises an interesting area for scientific research. Areas covered: This review encompasses the current literature on nutrition in the pre-operative, peri-operative, and post-operative phases of esophageal cancer. Both established interventions and potential novel targets for nutritional management are discussed. Expert commentary: To ensure an optimal pre-operative status and to reduce peri-operative complications, it is key to assess nutritional status in all pre-operative esophageal cancer patients and to apply nutritional interventions accordingly. Since esophagectomy results in a permanent anatomical change, a special focus on nutritional strategies is needed in the post-operative phase, including early initiation of enteral feeding, nutritional interventions for post-operative complications, and attention to long-term nutritional intake and status. Nutritional aspects of pre-optimization and peri-operative management should be incorporated in novel Enhanced Recovery After Surgery programs for esophageal cancer.

Evolutionary Optimization of a Geometrically Refined Truss

NASA Technical Reports Server (NTRS)

Hull, P. V.; Tinker, M. L.; Dozier, G. V.

2007-01-01

Structural optimization is a field of research that has experienced noteworthy growth for many years. Researchers in this area have developed optimization tools to successfully design and model structures, typically minimizing mass while maintaining certain deflection and stress constraints. Numerous optimization studies have been performed to minimize mass, deflection, and stress on a benchmark cantilever truss problem. Predominantly traditional optimization theory is applied to this problem. The cross-sectional area of each member is optimized to minimize the aforementioned objectives. This Technical Publication (TP) presents a structural optimization technique that has been previously applied to compliant mechanism design. This technique demonstrates a method that combines topology optimization, geometric refinement, finite element analysis, and two forms of evolutionary computation: genetic algorithms and differential evolution to successfully optimize a benchmark structural optimization problem. A nontraditional solution to the benchmark problem is presented in this TP, specifically a geometrically refined topological solution. The design process begins with an alternate control mesh formulation, multilevel geometric smoothing operation, and an elastostatic structural analysis. The design process is wrapped in an evolutionary computing optimization toolset.

Multi-objective Operation Chart Optimization for Aquatic Species Habitat Conservation of Cascaded Hydropower System on Yuan River, Southwestern China

NASA Astrophysics Data System (ADS)

Wen, X.; Lei, X.; Fang, G.; Huang, X.

2017-12-01

Extensive cascading hydropower exploitation in southwestern China has been the subject of debate and conflict in recent years. Introducing limited ecological curves, a novel approach for derivation of hydropower-ecological joint operation chart of cascaded hydropower system was proposed, aiming to optimize the general hydropower and ecological benefits, and to alleviate the ecological deterioration in specific flood/dry conditions. The physical habitat simulation model is proposed initially to simulate the relationship between streamflow and physical habitat of target fish species and to determine the optimal ecological flow range of representative reach. The ecological—hydropower joint optimization model is established to produce the multi-objective operation chart of cascaded hydropower system. Finally, the limited ecological guiding curves were generated and added into the operation chart. The JS-MDS cascaded hydropower system on the Yuan River in southwestern China is employed as the research area. As the result, the proposed guiding curves could increase the hydropower production amount by 1.72% and 5.99% and optimize ecological conservation degree by 0.27% and 1.13% for JS and MDS Reservoir, respectively. Meanwhile, the ecological deterioration rate also sees a decrease from 6.11% to 1.11% for JS Reservoir and 26.67% to 3.89% for MDS Reservoir.

Optimal Trajectories and Control Strategies for the Helicopter in One-Engine-Inoperative Terminal-Area Operations

NASA Technical Reports Server (NTRS)

Chen, Robert T. N.; Zhao, Yi-Yuan; Aiken, Edwin W. (Technical Monitor)

1995-01-01

Engine failure represents a major safety concern to helicopter operations, especially in the critical flight phases of takeoff and landing from/to small, confined areas. As a result, the JAA and FAA both certificate a transport helicopter as either Category-A or Category-B according to the ability to continue its operations following engine failures. A Category-B helicopter must be able to land safely in the event of one or all engine failures. There is no requirement, however, for continued flight capability. In contrast, Category-A certification, which applies to multi-engine transport helicopters with independent engine systems, requires that they continue the flight with one engine inoperative (OEI). These stringent requirements, while permitting its operations from rooftops and oil rigs and flight to areas where no emergency landing sites are available, restrict the payload of a Category-A transport helicopter to a value safe for continued flight as well as for landing with one engine inoperative. The current certification process involves extensive flight tests, which are potentially dangerous, costly, and time consuming. These tests require the pilot to simulate engine failures at increasingly critical conditions, Flight manuals based on these tests tend to provide very conservative recommendations with regard to maximum takeoff weight or required runway length. There are very few theoretical studies on this subject to identify the fundamental parameters and tradeoff factors involved. Furthermore, a capability for real-time generation of OEI optimal trajectories is very desirable for providing timely cockpit display guidance to assist the pilot in reducing his workload and to increase safety in a consistent and reliable manner. A joint research program involving NASA Ames Research Center, the FAA, and the University of Minnesota is being conducted to determine OEI optimal control strategies and the associated optimal,trajectories for continued takeoff (CTO), rejected takeoff (RTO), balked landing (BL), and continued landing (CL) for a twin engine helicopter in both VTOL and STOL terminal-area operations. This proposed paper will present the problem formulation, the optimal control solution methods, and the key results of the trajectory optimization studies for both STOL and VTOL OEI operations. In addition, new results concerning the recently developed methodology, which enable a real-time generation of optimal OEI trajectories, will be presented in the paper. This new real-time capability was developed to support the second piloted simulator investigation on cockpit displays for Category-A operations being scheduled for the NASA Ames Vertical Motion Simulator in June-August of 1995. The first VMS simulation was conducted in 1994 and reported.

Wireless Sensor Network Optimization: Multi-Objective Paradigm.

PubMed

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-07-20

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Self-Averaging Property of Minimal Investment Risk of Mean-Variance Model

PubMed Central

Shinzato, Takashi

2015-01-01

In portfolio optimization problems, the minimum expected investment risk is not always smaller than the expected minimal investment risk. That is, using a well-known approach from operations research, it is possible to derive a strategy that minimizes the expected investment risk, but this strategy does not always result in the best rate of return on assets. Prior to making investment decisions, it is important to an investor to know the potential minimal investment risk (or the expected minimal investment risk) and to determine the strategy that will maximize the return on assets. We use the self-averaging property to analyze the potential minimal investment risk and the concentrated investment level for the strategy that gives the best rate of return. We compare the results from our method with the results obtained by the operations research approach and with those obtained by a numerical simulation using the optimal portfolio. The results of our method and the numerical simulation are in agreement, but they differ from that of the operations research approach. PMID:26225761

Optimization techniques applied to passive measures for in-orbit spacecraft survivability

NASA Technical Reports Server (NTRS)

Mog, Robert A.; Helba, Michael J.; Hill, Janeil B.

1992-01-01

The purpose of this research is to provide Space Station Freedom protective structures design insight through the coupling of design/material requirements, hypervelocity impact phenomenology, meteoroid and space debris environment sensitivities, optimization techniques and operations research strategies, and mission scenarios. The goals of the research are: (1) to develop a Monte Carlo simulation tool which will provide top level insight for Space Station protective structures designers; (2) to develop advanced shielding concepts relevant to Space Station Freedom using unique multiple bumper approaches; and (3) to investigate projectile shape effects on protective structures design.

Improving the prevention, diagnosis and treatment of TB among people living with HIV: the role of operational research

PubMed Central

2011-01-01

Operational research is necessary to improve the access to and delivery of tuberculosis prevention, diagnosis and treatment interventions for people living with HIV. We conducted an extensive review of the literature and reports from recent expert consultations and research-related meetings organized by the World Health Organization and the Stop TB Partnership to identify a TB/HIV operational research agenda. We present critical operational research questions in a series of key areas: optimizing TB prevention by enhancing the uptake of isoniazid preventive therapy and the implementation of infection control measures; assessing the effectiveness of existing diagnostic tools and scaling up new technologies; improving service delivery models; and reducing risk factors for mortality among TB patients living with HIV. We discuss the potential impact that addressing the operational research questions may have on improving programmes’ performance, assessing new strategies or interventions for TB control, or informing global or national policy formulation. Financial resources to implement these operational research questions should be mobilized from existing and new funding mechanisms. National TB and HIV/AIDS programmes should develop their operational research agendas based on these questions, and conduct the research that they consider crucial for improving TB and HIV control in their settings in collaboration with research stakeholders. PMID:21967874

Robust Neighboring Optimal Guidance for the Advanced Launch System

NASA Technical Reports Server (NTRS)

Hull, David G.

1993-01-01

In recent years, optimization has become an engineering tool through the availability of numerous successful nonlinear programming codes. Optimal control problems are converted into parameter optimization (nonlinear programming) problems by assuming the control to be piecewise linear, making the unknowns the nodes or junction points of the linear control segments. Once the optimal piecewise linear control (suboptimal) control is known, a guidance law for operating near the suboptimal path is the neighboring optimal piecewise linear control (neighboring suboptimal control). Research conducted under this grant has been directed toward the investigation of neighboring suboptimal control as a guidance scheme for an advanced launch system.

Meta-control of combustion performance with a data mining approach

NASA Astrophysics Data System (ADS)

Song, Zhe

Large scale combustion process is complex and proposes challenges of optimizing its performance. Traditional approaches based on thermal dynamics have limitations on finding optimal operational regions due to time-shift nature of the process. Recent advances in information technology enable people collect large volumes of process data easily and continuously. The collected process data contains rich information about the process and, to some extent, represents a digital copy of the process over time. Although large volumes of data exist in industrial combustion processes, they are not fully utilized to the level where the process can be optimized. Data mining is an emerging science which finds patterns or models from large data sets. It has found many successful applications in business marketing, medical and manufacturing domains The focus of this dissertation is on applying data mining to industrial combustion processes, and ultimately optimizing the combustion performance. However the philosophy, methods and frameworks discussed in this research can also be applied to other industrial processes. Optimizing an industrial combustion process has two major challenges. One is the underlying process model changes over time and obtaining an accurate process model is nontrivial. The other is that a process model with high fidelity is usually highly nonlinear, solving the optimization problem needs efficient heuristics. This dissertation is set to solve these two major challenges. The major contribution of this 4-year research is the data-driven solution to optimize the combustion process, where process model or knowledge is identified based on the process data, then optimization is executed by evolutionary algorithms to search for optimal operating regions.

Study on the water resources optimal operation based on riverbed wind erosion control in West Liaohe River plain

NASA Astrophysics Data System (ADS)

Wanguang, Sun; Chengzhen, Li; Baoshan, Fan

2018-06-01

Rivers are drying up most frequently in West Liaohe River plain and the bare river beds present fine sand belts on land. These sand belts, which yield a dust heavily in windy days, stress the local environment deeply as the riverbeds are eroded by wind. The optimal operation of water resources, thus, is one of the most important methods for preventing the wind erosion of riverbeds. In this paper, optimal operation model for water resources based on riverbed wind erosion control has been established, which contains objective function, constraints, and solution method. The objective function considers factors which include water volume diverted into reservoirs, river length and lower threshold of flow rate, etc. On the basis of ensuring the water requirement of each reservoir, the destruction of the vegetation in the riverbed by the frequent river flow is avoided. The multi core parallel solving method for optimal water resources operation in the West Liaohe River Plain is proposed, which the optimal solution is found by DPSA method under the POA framework and the parallel computing program is designed in Fork/Join mode. Based on the optimal operation results, the basic rules of water resources operation in the West Liaohe River Plain are summarized. Calculation results show that, on the basis of meeting the requirement of water volume of every reservoir, the frequency of reach river flow which from Taihekou to Talagan Water Diversion Project in the Xinkai River is reduced effectively. The speedup and parallel efficiency of parallel algorithm are 1.51 and 0.76 respectively, and the computing time is significantly decreased. The research results show in this paper can provide technical support for the prevention and control of riverbed wind erosion in the West Liaohe River plain.

The integrated manual and automatic control of complex flight systems

NASA Technical Reports Server (NTRS)

Schmidt, David K.

1991-01-01

Research dealt with the general area of optimal flight control synthesis for manned flight vehicles. The work was generic; no specific vehicle was the focus of study. However, the class of vehicles generally considered were those for which high authority, multivariable control systems might be considered, for the purpose of stabilization and the achievement of optimal handling characteristics. Within this scope, the topics of study included several optimal control synthesis techniques, control-theoretic modeling of the human operator in flight control tasks, and the development of possible handling qualities metrics and/or measures of merit. Basic contributions were made in all these topics, including human operator (pilot) models for multi-loop tasks, optimal output feedback flight control synthesis techniques; experimental validations of the methods developed, and fundamental modeling studies of the air-to-air tracking and flared landing tasks.

Computer optimization techniques for NASA Langley's CSI evolutionary model's real-time control system

NASA Technical Reports Server (NTRS)

Elliott, Kenny B.; Ugoletti, Roberto; Sulla, Jeff

1992-01-01

The evolution and optimization of a real-time digital control system is presented. The control system is part of a testbed used to perform focused technology research on the interactions of spacecraft platform and instrument controllers with the flexible-body dynamics of the platform and platform appendages. The control system consists of Computer Automated Measurement and Control (CAMAC) standard data acquisition equipment interfaced to a workstation computer. The goal of this work is to optimize the control system's performance to support controls research using controllers with up to 50 states and frame rates above 200 Hz. The original system could support a 16-state controller operating at a rate of 150 Hz. By using simple yet effective software improvements, Input/Output (I/O) latencies and contention problems are reduced or eliminated in the control system. The final configuration can support a 16-state controller operating at 475 Hz. Effectively the control system's performance was increased by a factor of 3.

Optimal and Approximately Optimal Control Policies for Queues in Heavy Traffic,

DTIC Science & Technology

1987-03-01

optimal and ’nearly optimal’ control problems for the open queueing networks in heavy traffic of the type dealt with in the fundamental papers of Reiman ...then the covariance is precisely that obtained by Reiman [1] (with a different notation used there). It is evident from (4.4) and the cited...wU’ ’U, d A K . " -50- References [1] M.I. Reiman , "Open queueing networks in heavy traffic", Math. of Operations Research, 9, 1984, p. 441-458. [2] J

Towards computer-assisted surgery in shoulder joint replacement

NASA Astrophysics Data System (ADS)

Valstar, Edward R.; Botha, Charl P.; van der Glas, Marjolein; Rozing, Piet M.; van der Helm, Frans C. T.; Post, Frits H.; Vossepoel, Albert M.

A research programme that aims to improve the state of the art in shoulder joint replacement surgery has been initiated at the Delft University of Technology. Development of improved endoprostheses for the upper extremities (DIPEX), as this effort is called, is a clinically driven multidisciplinary programme consisting of many contributory aspects. A part of this research programme focuses on the pre-operative planning and per-operative guidance issues. The ultimate goal of this part of the DIPEX project is to create a surgical support infrastructure that can be used to predict the optimal surgical protocol and can assist with the selection of the most suitable endoprosthesis for a particular patient. In the pre-operative planning phase, advanced biomechanical models of the endoprosthesis fixation and the musculo-skeletal system of the shoulder will be incorporated, which are adjusted to the individual's morphology. Subsequently, the support infrastructure must assist the surgeon during the operation in executing his surgical plan. In the per-operative phase, the chosen optimal position of the endoprosthesis can be realised using camera-assisted tools or mechanical guidance tools. In this article, the pathway towards the desired surgical support infrastructure is described. Furthermore, we discuss the pre-operative planning phase and the per-operative guidance phase, the initial work performed, and finally, possible approaches for improving prosthesis placement.

Optimization study on multiple train formation scheme of urban rail transit

NASA Astrophysics Data System (ADS)

Xia, Xiaomei; Ding, Yong; Wen, Xin

2018-05-01

The new organization method, represented by the mixed operation of multi-marshalling trains, can adapt to the characteristics of the uneven distribution of passenger flow, but the research on this aspect is still not perfect enough. This paper introduced the passenger sharing rate and congestion penalty coefficient with different train formations. On this basis, this paper established an optimization model with the minimum passenger cost and operation cost as objective, and operation frequency and passenger demand as constraint. The ideal point method is used to solve this model. Compared with the fixed marshalling operation model, the overall cost of this scheme saves 9.24% and 4.43% respectively. This result not only validates the validity of the model, but also illustrate the advantages of the multiple train formations scheme.

Biospecimen Core Resource - TCGA

Cancer.gov

The Cancer Genome Atlas (TCGA) Biospecimen Core Resource centralized laboratory reviews and processes blood and tissue samples and their associated data using optimized standard operating procedures for the entire TCGA Research Network.

Anaerobic digestion of food waste: A review focusing on process stability.

PubMed

Li, Lei; Peng, Xuya; Wang, Xiaoming; Wu, Di

2018-01-01

Food waste (FW) is rich in biomass energy, and increasing numbers of national programs are being established to recover energy from FW using anaerobic digestion (AD). However process instability is a common operational issue for AD of FW. Process monitoring and control as well as microbial management can be used to control instability and increase the energy conversion efficiency of anaerobic digesters. Here, we review research progress related to these methods and identify existing limitations to efficient AD; recommendations for future research are also discussed. Process monitoring and control are suitable for evaluating the current operational status of digesters, whereas microbial management can facilitate early diagnosis and process optimization. Optimizing and combining these two methods are necessary to improve AD efficiency. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cognitive Performance in Operational Environments

NASA Technical Reports Server (NTRS)

Russo, Michael; McGhee, James; Friedler, Edna; Thomas, Maria

2005-01-01

Optimal cognition during complex and sustained operations is a critical component for success in current and future military operations. "Cognitive Performance, Judgment, and Decision-making" (CPJD) is a newly organized U.S. Army Medical Research and Materiel Command research program focused on sustaining operational effectiveness of Future Force Warriors by developing paradigms through which militarily-relevant, higher-order cognitive performance, judgment, and decision-making can be assessed and sustained in individuals, small teams, and leaders of network-centric fighting units. CPJD evaluates the impact of stressors intrinsic to military operational environments (e.g., sleep deprivation, workload, fatigue, temperature extremes, altitude, environmental/physiological disruption) on military performance, evaluates noninvasive automated methods for monitoring and predicting cognitive performance, and investigates pharmaceutical strategies (e.g., stimulant countermeasures, hypnotics) to mitigate performance decrements. This manuscript describes the CPJD program, discusses the metrics utilized to relate militarily applied research findings to academic research, and discusses how the simulated combat capabilities of a synthetic battle laboratory may facilitate future cognitive performance research.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

On sustainable and efficient design of ground-source heat pump systems

NASA Astrophysics Data System (ADS)

Grassi, W.; Conti, P.; Schito, E.; Testi, D.

2015-11-01

This paper is mainly aimed at stressing some fundamental features of the GSHP design and is based on a broad research we are performing at the University of Pisa. In particular, we focus the discussion on an environmentally sustainable approach, based on performance optimization during the entire operational life. The proposed methodology aims at investigating design and management strategies to find the optimal level of exploitation of the ground source and refer to other technical means to cover the remaining energy requirements and modulate the power peaks. The method is holistic, considering the system as a whole, rather than focusing only on some components, usually considered as the most important ones. Each subsystem is modeled and coupled to the others in a full set of equations, which is used within an optimization routine to reproduce the operative performances of the overall GSHP system. As a matter of fact, the recommended methodology is a 4-in-1 activity, including sizing of components, lifecycle performance evaluation, optimization process, and feasibility analysis. The paper reviews also some previous works concerning possible applications of the proposed methodology. In conclusion, we describe undergoing research activities and objectives of future works.

Multi-Objective Ant Colony Optimization Based on the Physarum-Inspired Mathematical Model for Bi-Objective Traveling Salesman Problems

PubMed Central

Zhang, Zili; Gao, Chao; Lu, Yuxiao; Liu, Yuxin; Liang, Mingxin

2016-01-01

Bi-objective Traveling Salesman Problem (bTSP) is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs) have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM). PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs. PMID:26751562

Multi-Objective Ant Colony Optimization Based on the Physarum-Inspired Mathematical Model for Bi-Objective Traveling Salesman Problems.

PubMed

Zhang, Zili; Gao, Chao; Lu, Yuxiao; Liu, Yuxin; Liang, Mingxin

2016-01-01

Bi-objective Traveling Salesman Problem (bTSP) is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs) have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM). PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs.

Optimization research of railway passenger transfer scheme based on ant colony algorithm

NASA Astrophysics Data System (ADS)

Ni, Xiang

2018-05-01

The optimization research of railway passenger transfer scheme can provide strong support for railway passenger transport system, and its essence is path search. This paper realized the calculation of passenger transfer scheme for high speed railway when giving the time and stations of departure and arrival. The specific method that used were generating a passenger transfer service network of high-speed railway, establishing optimization model and searching by Ant Colony Algorithm. Finally, making analysis on the scheme from LanZhouxi to BeiJingXi which were based on high-speed railway network of China in 2017. The results showed that the transfer network and model had relatively high practical value and operation efficiency.

Multi-objective optimisation of aircraft flight trajectories in the ATM and avionics context

NASA Astrophysics Data System (ADS)

Gardi, Alessandro; Sabatini, Roberto; Ramasamy, Subramanian

2016-05-01

The continuous increase of air transport demand worldwide and the push for a more economically viable and environmentally sustainable aviation are driving significant evolutions of aircraft, airspace and airport systems design and operations. Although extensive research has been performed on the optimisation of aircraft trajectories and very efficient algorithms were widely adopted for the optimisation of vertical flight profiles, it is only in the last few years that higher levels of automation were proposed for integrated flight planning and re-routing functionalities of innovative Communication Navigation and Surveillance/Air Traffic Management (CNS/ATM) and Avionics (CNS+A) systems. In this context, the implementation of additional environmental targets and of multiple operational constraints introduces the need to efficiently deal with multiple objectives as part of the trajectory optimisation algorithm. This article provides a comprehensive review of Multi-Objective Trajectory Optimisation (MOTO) techniques for transport aircraft flight operations, with a special focus on the recent advances introduced in the CNS+A research context. In the first section, a brief introduction is given, together with an overview of the main international research initiatives where this topic has been studied, and the problem statement is provided. The second section introduces the mathematical formulation and the third section reviews the numerical solution techniques, including discretisation and optimisation methods for the specific problem formulated. The fourth section summarises the strategies to articulate the preferences and to select optimal trajectories when multiple conflicting objectives are introduced. The fifth section introduces a number of models defining the optimality criteria and constraints typically adopted in MOTO studies, including fuel consumption, air pollutant and noise emissions, operational costs, condensation trails, airspace and airport operations. A brief overview of atmospheric and weather modelling is also included. Key equations describing the optimality criteria are presented, with a focus on the latest advancements in the respective application areas. In the sixth section, a number of MOTO implementations in the CNS+A systems context are mentioned with relevant simulation case studies addressing different operational tasks. The final section draws some conclusions and outlines guidelines for future research on MOTO and associated CNS+A system implementations.

Smart-Grid Backbone Network Real-Time Delay Reduction via Integer Programming.

PubMed

Pagadrai, Sasikanth; Yilmaz, Muhittin; Valluri, Pratyush

2016-08-01

This research investigates an optimal delay-based virtual topology design using integer linear programming (ILP), which is applied to the current backbone networks such as smart-grid real-time communication systems. A network traffic matrix is applied and the corresponding virtual topology problem is solved using the ILP formulations that include a network delay-dependent objective function and lightpath routing, wavelength assignment, wavelength continuity, flow routing, and traffic loss constraints. The proposed optimization approach provides an efficient deterministic integration of intelligent sensing and decision making, and network learning features for superior smart grid operations by adaptively responding the time-varying network traffic data as well as operational constraints to maintain optimal virtual topologies. A representative optical backbone network has been utilized to demonstrate the proposed optimization framework whose simulation results indicate that superior smart-grid network performance can be achieved using commercial networks and integer programming.

Lessons Learned During Solutions of Multidisciplinary Design Optimization Problems

NASA Technical Reports Server (NTRS)

Patnaik, Suna N.; Coroneos, Rula M.; Hopkins, Dale A.; Lavelle, Thomas M.

2000-01-01

Optimization research at NASA Glenn Research Center has addressed the design of structures, aircraft and airbreathing propulsion engines. During solution of the multidisciplinary problems several issues were encountered. This paper lists four issues and discusses the strategies adapted for their resolution: (1) The optimization process can lead to an inefficient local solution. This deficiency was encountered during design of an engine component. The limitation was overcome through an augmentation of animation into optimization. (2) Optimum solutions obtained were infeasible for aircraft and air-breathing propulsion engine problems. Alleviation of this deficiency required a cascading of multiple algorithms. (3) Profile optimization of a beam produced an irregular shape. Engineering intuition restored the regular shape for the beam. (4) The solution obtained for a cylindrical shell by a subproblem strategy converged to a design that can be difficult to manufacture. Resolution of this issue remains a challenge. The issues and resolutions are illustrated through six problems: (1) design of an engine component, (2) synthesis of a subsonic aircraft, (3) operation optimization of a supersonic engine, (4) design of a wave-rotor-topping device, (5) profile optimization of a cantilever beam, and (6) design of a cvlindrical shell. The combined effort of designers and researchers can bring the optimization method from academia to industry.

Wireless Sensor Network Optimization: Multi-Objective Paradigm

PubMed Central

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-01-01

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks. PMID:26205271

An Optimization-Based Approach to Determine Requirements and Aircraft Design under Multi-domain Uncertainties

NASA Astrophysics Data System (ADS)

Govindaraju, Parithi

Determining the optimal requirements for and design variable values of new systems, which operate along with existing systems to provide a set of overarching capabilities, as a single task is challenging due to the highly interconnected effects that setting requirements on a new system's design can have on how an operator uses this newly designed system. This task of determining the requirements and the design variable values becomes even more difficult because of the presence of uncertainties in the new system design and in the operational environment. This research proposed and investigated aspects of a framework that generates optimum design requirements of new, yet-to-be-designed systems that, when operating alongside other systems, will optimize fleet-level objectives while considering the effects of various uncertainties. Specifically, this research effort addresses the issues of uncertainty in the design of the new system through reliability-based design optimization methods, and uncertainty in the operations of the fleet through descriptive sampling methods and robust optimization formulations. In this context, fleet-level performance metrics result from using the new system alongside other systems to accomplish an overarching objective or mission. This approach treats the design requirements of a new system as decision variables in an optimization problem formulation that a user in the position of making an acquisition decision could solve. This solution would indicate the best new system requirements-and an associated description of the best possible design variable variables for that new system-to optimize the fleet level performance metric(s). Using a problem motivated by recorded operations of the United States Air Force Air Mobility Command for illustration, the approach is demonstrated first for a simplified problem that only considers demand uncertainties in the service network and the proposed methodology is used to identify the optimal design requirements and optimal aircraft sizing variables of new, yet-to-be-introduced aircraft. With this new aircraft serving alongside other existing aircraft, the fleet of aircraft satisfy the desired demand for cargo transportation, while maximizing fleet productivity and minimizing fuel consumption via a multi-objective problem formulation. The approach is then extended to handle uncertainties in both the design of the new system and in the operations of the fleet. The propagation of uncertainties associated with the conceptual design of the new aircraft to the uncertainties associated with the subsequent operations of the new and existing aircraft in the fleet presents some unique challenges. A computationally tractable hybrid robust counterpart formulation efficiently handles the confluence of the two types of domain-specific uncertainties. This hybrid formulation is tested on a larger route network problem to demonstrate the scalability of the approach. Following the presentation of the results obtained, a summary discussion indicates how decision-makers might use these results to set requirements for new aircraft that meet operational needs while balancing the environmental impact of the fleet with fleet-level performance. Comparing the solutions from the uncertainty-based and deterministic formulations via a posteriori analysis demonstrates the efficacy of the robust and reliability-based optimization formulations in addressing the different domain-specific uncertainties. Results suggest that the aircraft design requirements and design description determined through the hybrid robust counterpart formulation approach differ from solutions obtained from the simplistic deterministic approach, and leads to greater fleet-level fuel savings, when subjected to real-world uncertain scenarios (more robust to uncertainty). The research, though applied to a specific air cargo application, is technically agnostic in nature and can be applied to other facets of policy and acquisition management, to explore capability trade spaces for different vehicle systems, mitigate risks, define policy and potentially generate better returns on investment. Other domains relevant to policy and acquisition decisions could utilize the problem formulation and solution approach proposed in this dissertation provided that the problem can be split into a non-linear programming problem to describe the new system sizing and the fleet operations problem can be posed as a linear/integer programming problem.

Optimal operating rules definition in complex water resource systems combining fuzzy logic, expert criteria and stochastic programming

NASA Astrophysics Data System (ADS)

Macian-Sorribes, Hector; Pulido-Velazquez, Manuel

2016-04-01

This contribution presents a methodology for defining optimal seasonal operating rules in multireservoir systems coupling expert criteria and stochastic optimization. Both sources of information are combined using fuzzy logic. The structure of the operating rules is defined based on expert criteria, via a joint expert-technician framework consisting in a series of meetings, workshops and surveys carried out between reservoir managers and modelers. As a result, the decision-making process used by managers can be assessed and expressed using fuzzy logic: fuzzy rule-based systems are employed to represent the operating rules and fuzzy regression procedures are used for forecasting future inflows. Once done that, a stochastic optimization algorithm can be used to define optimal decisions and transform them into fuzzy rules. Finally, the optimal fuzzy rules and the inflow prediction scheme are combined into a Decision Support System for making seasonal forecasts and simulate the effect of different alternatives in response to the initial system state and the foreseen inflows. The approach presented has been applied to the Jucar River Basin (Spain). Reservoir managers explained how the system is operated, taking into account the reservoirs' states at the beginning of the irrigation season and the inflows previewed during that season. According to the information given by them, the Jucar River Basin operating policies were expressed via two fuzzy rule-based (FRB) systems that estimate the amount of water to be allocated to the users and how the reservoir storages should be balanced to guarantee those deliveries. A stochastic optimization model using Stochastic Dual Dynamic Programming (SDDP) was developed to define optimal decisions, which are transformed into optimal operating rules embedding them into the two FRBs previously created. As a benchmark, historical records are used to develop alternative operating rules. A fuzzy linear regression procedure was employed to foresee future inflows depending on present and past hydrological and meteorological variables actually used by the reservoir managers to define likely inflow scenarios. A Decision Support System (DSS) was created coupling the FRB systems and the inflow prediction scheme in order to give the user a set of possible optimal releases in response to the reservoir states at the beginning of the irrigation season and the fuzzy inflow projections made using hydrological and meteorological information. The results show that the optimal DSS created using the FRB operating policies are able to increase the amount of water allocated to the users in 20 to 50 Mm3 per irrigation season with respect to the current policies. Consequently, the mechanism used to define optimal operating rules and transform them into a DSS is able to increase the water deliveries in the Jucar River Basin, combining expert criteria and optimization algorithms in an efficient way. This study has been partially supported by the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economía y Competitividad) and FEDER funds. It also has received funding from the European Union's Horizon 2020 research and innovation programme under the IMPREX project (grant agreement no: 641.811).

A Comparison of the DISASTER (Trademark) Scheduling Software with a Simultaneous Scheduling Algorithm for Minimizing Maximum Tardiness in Job Shops

DTIC Science & Technology

1993-09-01

goal ( Heizer , Render , and Stair, 1993:94). Integer Prgronmming. Integer programming is a general purpose approach used to optimally solve job shop...Scheduling," Operations Research Journal. 29, No 4: 646-667 (July-August 1981). Heizer , Jay, Barry Render and Ralph M. Stair, Jr. Production and Operations

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.

Continued research on selected parameters to minimize community annoyance from airplane noise

NASA Technical Reports Server (NTRS)

Frair, L.

1981-01-01

Results from continued research on selected parameters to minimize community annoyance from airport noise are reported. First, a review of the initial work on this problem is presented. Then the research focus is expanded by considering multiobjective optimization approaches for this problem. A multiobjective optimization algorithm review from the open literature is presented. This is followed by the multiobjective mathematical formulation for the problem of interest. A discussion of the appropriate solution algorithm for the multiobjective formulation is conducted. Alternate formulations and associated solution algorithms are discussed and evaluated for this airport noise problem. Selected solution algorithms that have been implemented are then used to produce computational results for example airports. These computations involved finding the optimal operating scenario for a moderate size airport and a series of sensitivity analyses for a smaller example airport.

Research on global path planning based on ant colony optimization for AUV

NASA Astrophysics Data System (ADS)

Wang, Hong-Jian; Xiong, Wei

2009-03-01

Path planning is an important issue for autonomous underwater vehicles (AUVs) traversing an unknown environment such as a sea floor, a jungle, or the outer celestial planets. For this paper, global path planning using large-scale chart data was studied, and the principles of ant colony optimization (ACO) were applied. This paper introduced the idea of a visibility graph based on the grid workspace model. It also brought a series of pheromone updating rules for the ACO planning algorithm. The operational steps of the ACO algorithm are proposed as a model for a global path planning method for AUV. To mimic the process of smoothing a planned path, a cutting operator and an insertion-point operator were designed. Simulation results demonstrated that the ACO algorithm is suitable for global path planning. The system has many advantages, including that the operating path of the AUV can be quickly optimized, and it is shorter, safer, and smoother. The prototype system successfully demonstrated the feasibility of the concept, proving it can be applied to surveys of unstructured unmanned environments.

Mixed oxidizer hybrid propulsion system optimization under uncertainty using applied response surface methodology and Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Whitehead, James Joshua

The analysis documented herein provides an integrated approach for the conduct of optimization under uncertainty (OUU) using Monte Carlo Simulation (MCS) techniques coupled with response surface-based methods for characterization of mixture-dependent variables. This novel methodology provides an innovative means of conducting optimization studies under uncertainty in propulsion system design. Analytic inputs are based upon empirical regression rate information obtained from design of experiments (DOE) mixture studies utilizing a mixed oxidizer hybrid rocket concept. Hybrid fuel regression rate was selected as the target response variable for optimization under uncertainty, with maximization of regression rate chosen as the driving objective. Characteristic operational conditions and propellant mixture compositions from experimental efforts conducted during previous foundational work were combined with elemental uncertainty estimates as input variables. Response surfaces for mixture-dependent variables and their associated uncertainty levels were developed using quadratic response equations incorporating single and two-factor interactions. These analysis inputs, response surface equations and associated uncertainty contributions were applied to a probabilistic MCS to develop dispersed regression rates as a function of operational and mixture input conditions within design space. Illustrative case scenarios were developed and assessed using this analytic approach including fully and partially constrained operational condition sets over all of design mixture space. In addition, optimization sets were performed across an operationally representative region in operational space and across all investigated mixture combinations. These scenarios were selected as representative examples relevant to propulsion system optimization, particularly for hybrid and solid rocket platforms. Ternary diagrams, including contour and surface plots, were developed and utilized to aid in visualization. The concept of Expanded-Durov diagrams was also adopted and adapted to this study to aid in visualization of uncertainty bounds. Regions of maximum regression rate and associated uncertainties were determined for each set of case scenarios. Application of response surface methodology coupled with probabilistic-based MCS allowed for flexible and comprehensive interrogation of mixture and operating design space during optimization cases. Analyses were also conducted to assess sensitivity of uncertainty to variations in key elemental uncertainty estimates. The methodology developed during this research provides an innovative optimization tool for future propulsion design efforts.

A programing system for research and applications in structural optimization

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, J.; Rogers, J. L., Jr.

1981-01-01

The paper describes a computer programming system designed to be used for methodology research as well as applications in structural optimization. The flexibility necessary for such diverse utilizations is achieved by combining, in a modular manner, a state-of-the-art optimization program, a production level structural analysis program, and user supplied and problem dependent interface programs. Standard utility capabilities existing in modern computer operating systems are used to integrate these programs. This approach results in flexibility of the optimization procedure organization and versatility in the formulation of contraints and design variables. Features shown in numerical examples include: (1) variability of structural layout and overall shape geometry, (2) static strength and stiffness constraints, (3) local buckling failure, and (4) vibration constraints. The paper concludes with a review of the further development trends of this programing system.

Dynamics and control of detumbling a disabled spacecraft during rescue operations

NASA Technical Reports Server (NTRS)

Kaplan, M. H.

1973-01-01

Results of a two-year research effort on dynamics and control of detumbling a disabled spacecraft during rescue operations are summarized. Answers to several basic questions about associated techniques and hardware requirements were obtained. Specifically, efforts have included development of operational procedures, conceptual design of remotely controlled modules, feasibility of internal moving mass for stabilization, and optimal techniques for minimum-time detumbling. Results have been documented in several reports and publications.

Balancing the risks and the benefits.

PubMed

Klopack

2000-04-01

Pharmaceutical research organizations can benefit from outsourcing discovery activities that are not core competencies of the organization. The core competencies for a discovery operation are the expertise and systems that give the organization an advantage over its competition. Successful outsourcing ventures result in cost reduction, increased operation efficiency and optimization of resource allocation. While there are pitfalls to outsourcing, including poor partner selection and inadequate implementation, outsourcing can be a powerful tool for enhancing drug discovery operations.

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.

A systematic approach of removal mechanisms, control and optimization of silver nanoparticle in wastewater treatment plants.

PubMed

Vilela, Paulina; Liu, Hongbin; Lee, SeungChul; Hwangbo, Soonho; Nam, KiJeon; Yoo, ChangKyoo

2018-08-15

The release of silver nanoparticles (AgNPs) to wastewater caused by over-generation and poor treatment of the remaining nanomaterial has raised the interest of researchers. AgNPs can have a negative impact on watersheds and generate degradation of the effluent quality of wastewater treatment plants (WWTPs). The aim of this research is to design and analyze an integrated model system for the removal of AgNPs with high effluent quality in WWTPs using a systematic approach of removal mechanisms modeling, optimization, and control of the removal of silver nanoparticles. The activated sludge model 1 was modified with the inclusion of AgNPs removal mechanisms, such as adsorption/desorption, dissolution, and inhibition of microbial organisms. Response surface methodology was performed to minimize the AgNPs and total nitrogen concentrations in the effluent by optimizing operating conditions of the system. Then, the optimal operating conditions were utilized for the implementation of control strategies into the system for further analysis of enhancement of AgNPs removal efficiency. Thus, the overall AgNP removal efficiency was found to be slightly higher than 80%, which was an improvement of almost 7% compared to the BSM1 reference value. This study provides a systematic approach to find an optimal solution for enhancing AgNP removal efficiency in WWTPs and thereby to prevent pollution in the environment. Copyright © 2018 Elsevier B.V. All rights reserved.

Optimizing zonal advection of the Advanced Research WRF (ARW) dynamics for Intel MIC

NASA Astrophysics Data System (ADS)

Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.

2014-10-01

The Weather Research and Forecast (WRF) model is the most widely used community weather forecast and research model in the world. There are two distinct varieties of WRF. The Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-NMM) has been designed for forecasting operations. WRF consists of dynamics code and several physics modules. The WRF-ARW core is based on an Eulerian solver for the fully compressible nonhydrostatic equations. In the paper, we will use Intel Intel Many Integrated Core (MIC) architecture to substantially increase the performance of a zonal advection subroutine for optimization. It is of the most time consuming routines in the ARW dynamics core. Advection advances the explicit perturbation horizontal momentum equations by adding in the large-timestep tendency along with the small timestep pressure gradient tendency. We will describe the challenges we met during the development of a high-speed dynamics code subroutine for MIC architecture. Furthermore, lessons learned from the code optimization process will be discussed. The results show that the optimizations improved performance of the original code on Xeon Phi 5110P by a factor of 2.4x.

Optimizing meridional advection of the Advanced Research WRF (ARW) dynamics for Intel Xeon Phi coprocessor

NASA Astrophysics Data System (ADS)

Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.-L.

2015-05-01

The most widely used community weather forecast and research model in the world is the Weather Research and Forecast (WRF) model. Two distinct varieties of WRF exist. The one we are interested is the Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-NMM) has been designed for forecasting operations. WRF consists of dynamics code and several physics modules. The WRF-ARW core is based on an Eulerian solver for the fully compressible nonhydrostatic equations. In the paper, we optimize a meridional (north-south direction) advection subroutine for Intel Xeon Phi coprocessor. Advection is of the most time consuming routines in the ARW dynamics core. It advances the explicit perturbation horizontal momentum equations by adding in the large-timestep tendency along with the small timestep pressure gradient tendency. We will describe the challenges we met during the development of a high-speed dynamics code subroutine for MIC architecture. Furthermore, lessons learned from the code optimization process will be discussed. The results show that the optimizations improved performance of the original code on Xeon Phi 7120P by a factor of 1.2x.

Operative planning of functional sessions for multisatellite observation and communication systems

NASA Astrophysics Data System (ADS)

Darnopykh, Valeriy V.; Malyshev, Veniamin V.

2012-04-01

An important control aspect of modern satellite observation and communication systems is the control of the functional processes. Functional sessions proceed under conditions of restricted technical ability, large amounts or information to be processed by the on-board equipment, practice inequality of the received information, intentions of system management and operators, interests of customers and other factors. A large number of spacecrafts (SC) in orbital constellation is one of the most important factors affecting the functional process also. Besides that some modern projects of satellite systems are multifunctional that is mixed operations of observation and communication. Therefore the functioning of SC on-board equipment must be accurately co-ordinate. That is why the problem of operative planning the functioning of these systems, while directly affecting the efficiency of the system, is very complex and actual at present. A methodical approach and software package for operative planning of functional processes for satellite observation and communication systems, including multifunctional projects, are considered in the paper. The base scheme of this approach consists of four main stages: stage 1—modeling of SC orbital kinematics and dynamics; stage 2—modeling of system functional processes with all kind of restrictions and criterion function values; stage 3—solving an optimization tasks by numerical applicable algorithms and constructing the optimal (or accuracy) plans; stage 4—repeated plan optimization (different variants) and analyzing. Such scheme is the result of authors practical research which have been realized during last 15 years by the operative planning as for any kinds of single SC as for satellite systems with different structure of orbital constellation. The research helps to unify the procedure of operative planning, to formulate basic principles and approaches for its solving, to develop special software package. The main aspects of the approach proposed are illustrated in the paper. The results of the calculations of applied planning problems are presented. The objects of research in these problems are: projects of CBERS observation systems (1-3 SC) and projects of Iridium (66 SC) global communication system.

Optimized Algorithms for Prediction Within Robotic Tele-Operative Interfaces

NASA Technical Reports Server (NTRS)

Martin, Rodney A.; Wheeler, Kevin R.; Allan, Mark B.; SunSpiral, Vytas

2010-01-01

Robonaut, the humanoid robot developed at the Dexterous Robotics Labo ratory at NASA Johnson Space Center serves as a testbed for human-rob ot collaboration research and development efforts. One of the recent efforts investigates how adjustable autonomy can provide for a safe a nd more effective completion of manipulation-based tasks. A predictiv e algorithm developed in previous work was deployed as part of a soft ware interface that can be used for long-distance tele-operation. In this work, Hidden Markov Models (HMM?s) were trained on data recorded during tele-operation of basic tasks. In this paper we provide the d etails of this algorithm, how to improve upon the methods via optimization, and also present viable alternatives to the original algorithmi c approach. We show that all of the algorithms presented can be optim ized to meet the specifications of the metrics shown as being useful for measuring the performance of the predictive methods. 1

Optimisation des trajectoires d'un systeme de gestion de vol d'avions pour la reduction des couts de vol

NASA Astrophysics Data System (ADS)

Sidibe, Souleymane

The implementation and monitoring of operational flight plans is a major occupation for a crew of commercial flights. The purpose of this operation is to set the vertical and lateral trajectories followed by airplane during phases of flight: climb, cruise, descent, etc. These trajectories are subjected to conflicting economical constraints: minimization of flight time and minimization of fuel consumed and environmental constraints. In its task of mission planning, the crew is assisted by the Flight Management System (FMS) which is used to construct the path to follow and to predict the behaviour of the aircraft along the flight plan. The FMS considered in our research, particularly includes an optimization model of flight only by calculating the optimal speed profile that minimizes the overall cost of flight synthesized by a criterion of cost index following a steady cruising altitude. However, the model based solely on optimization of the speed profile is not sufficient. It is necessary to expand the current optimization for simultaneous optimization of the speed and altitude in order to determine an optimum cruise altitude that minimizes the overall cost when the path is flown with the optimal speed profile. Then, a new program was developed. The latter is based on the method of dynamic programming invented by Bellman to solve problems of optimal paths. In addition, the improvement passes through research new patterns of trajectories integrating ascendant cruises and using the lateral plane with the effect of the weather: wind and temperature. Finally, for better optimization, the program takes into account constraint of flight domain of aircrafts which utilize the FMS.

Piston Bowl Optimization for RCCI Combustion in a Light-Duty Multi-Cylinder Engine

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

Hanson, Reed M; Curran, Scott; Wagner, Robert M

2012-01-01

Reactivity Controlled Compression Ignition (RCCI) is an engine combustion strategy that that produces low NO{sub x} and PM emissions with high thermal efficiency. Previous RCCI research has been investigated in single-cylinder heavy-duty engines. The current study investigates RCCI operation in a light-duty multi-cylinder engine at 3 operating points. These operating points were chosen to cover a range of conditions seen in the US EPA light-duty FTP test. The operating points were chosen by the Ad Hoc working group to simulate operation in the FTP test. The fueling strategy for the engine experiments consisted of in-cylinder fuel blending using port fuel-injectionmore » (PFI) of gasoline and early-cycle, direct-injection (DI) of diesel fuel. At these 3 points, the stock engine configuration is compared to operation with both the original equipment manufacturer (OEM) and custom machined pistons designed for RCCI operation. The pistons were designed with assistance from the KIVA 3V computational fluid dynamics (CFD) code. By using a genetic algorithm optimization, in conjunction with KIVA, the piston bowl profile was optimized for dedicated RCCI operation to reduce unburned fuel emissions and piston bowl surface area. By reducing these parameters, the thermal efficiency of the engine was improved while maintaining low NOx and PM emissions. Results show that with the new piston bowl profile and an optimized injection schedule, RCCI brake thermal efficiency was increased from 37%, with the stock EURO IV configuration, to 40% at the 2,600 rev/min, 6.9 bar BMEP condition, and NOx and PM emissions targets were met without the need for exhaust after-treatment.« less

NETL- AVESTAR

ScienceCinema

None

2018-02-13

NETL's Advanced Virtual Energy Simulation Training and Research, or AVESTAR, Center is designed to promote operational excellence for the nation's energy systems, from smart power plants to smart grid. The AVESTAR Center brings together advanced dynamic simulation and control technologies, state-of-the-art simulation-based training facilities, and leading industry experts to focus on the optimal operation of clean energy plants in the smart grid era.

Optimal timing for performing hysterectomy according to different phase of menstrual cycle: Which is best?

PubMed

Kim, Jeong Jin; Kang, Jun Hyeok; Lee, Kyo Won; Kim, Kye Hyun; Song, Taejong

2017-05-01

The aim of this study was to determine whether the different phases of the menstrual cycle could affect operative bleeding in women undergoing laparoscopic hysterectomy. This was a retrospective comparative study. Based on the adjusted day of menstrual cycle, 212 women who underwent laparoscopic hysterectomy were classified into three groups: the follicular phase (n = 51), luteal phase group (n = 125), and menstruation group (n = 36). The primary outcome measure was the operative bleeding. There was no difference in the baseline characteristics of the patients belonging to the three groups. For the groups, there were no significant differences in operative bleeding (p = .469) and change in haemoglobin (p = .330), including operative time, length of hospital stay and complications. The menstrual cycle did not affect the operative bleeding and other parameters. Therefore, no phase of the menstrual cycle could be considered as an optimal timing for performing laparoscopic hysterectomy with minimal operative bleeding. Impact statement What is already known on this subject: the menstrual cycle results in periodic changes in haemostasis and blood flow in the reproductive organs. What the results of this study add: the menstrual cycle did not affect the operative bleeding and other operative parameters during laparoscopic hysterectomy. What the implications are of these findings for clinical practice and/or further research: no phase of the menstrual cycle could be considered as an optimal timing for performing laparoscopic hysterectomy with minimal operative bleeding.

Optimizing Integrated Terminal Airspace Operations Under Uncertainty

NASA Technical Reports Server (NTRS)

Bosson, Christabelle; Xue, Min; Zelinski, Shannon

2014-01-01

In the terminal airspace, integrated departures and arrivals have the potential to increase operations efficiency. Recent research has developed geneticalgorithm- based schedulers for integrated arrival and departure operations under uncertainty. This paper presents an alternate method using a machine jobshop scheduling formulation to model the integrated airspace operations. A multistage stochastic programming approach is chosen to formulate the problem and candidate solutions are obtained by solving sample average approximation problems with finite sample size. Because approximate solutions are computed, the proposed algorithm incorporates the computation of statistical bounds to estimate the optimality of the candidate solutions. A proof-ofconcept study is conducted on a baseline implementation of a simple problem considering a fleet mix of 14 aircraft evolving in a model of the Los Angeles terminal airspace. A more thorough statistical analysis is also performed to evaluate the impact of the number of scenarios considered in the sampled problem. To handle extensive sampling computations, a multithreading technique is introduced.

The Analytic Methods of Operations Research

DTIC Science & Technology

1977-01-01

stock market behavior (Fama, 1970), but few other applications . A 2*1 - --- 41 12. QUEUEING THEORY The study of congestion in service...Behavior," by T. von Neumann and 0. MHrgenstern, and an esoteric j - 2 paperbrtk by Charnes. Cooper, and Henderson on the optimal mixing of peanuKs and...2nd-order conditions, then i X is also globally optimal . This enables one to use local exploration to lead to the global

Optimized Waterspace Management and Scheduling Using Mixed-Integer Linear Programming

DTIC Science & Technology

2016-01-01

Complete [30]. Proposition 4.1 satisfies the first criterion. For the second criterion, we will use the Traveling Salesman Problem (TSP), which has been...A branch and cut algorithm for the symmetric generalized traveling salesman problem , Operations Research 45 (1997) 378–394. [33] J. Silberholz, B...Golden, The generalized traveling salesman problem : A new genetic algorithm ap- proach, Extended Horizons: Advances in Computing, Optimization, and

Good Data Can Be Better Data - How Data Management Maturity Can Help Repositories Improve Operations, Data Quality, And Usability, Helping Researchers

NASA Astrophysics Data System (ADS)

Stall, S.

2015-12-01

Much earth and space science data and metadata are managed and supported by an infrastructure of repositories, ranging from large agency or instrument facilities, to institutions, to smaller repositories including labs. Scientists face many challenges in this ecosystem both on storing their data and in accessing data from others for new research. Critical for all uses is ensuring the credibility and integrity of the data and conveying that and provenance information now and in the future. Accurate information is essential for future researchers to find (or discover) the data, evaluate the data for use (content, temporal, geolocation, precision) and finally select (or discard) that data as meeting a "fit-for-purpose" criteria. We also need to optimize the effort it takes in describing the data for these determinations, which means making it efficient for the researchers who collect the data. At AGU we are developing a program aimed at helping repositories, and thereby researchers, improve data quality and data usability toward these goals. AGU has partnered with the CMMI Institute to develop their Data Management Maturity (DMM) framework within the Earth and space sciences. The CMMI DMM framework guides best practices in a range of data operations, and the application of the DMM, through an assessment, reveals how repositories and institutions can best optimize efforts to improve operations and functionality throughout the data lifecycle and elevate best practices across a variety of data management operations. Supporting processes like data operations, data governance, and data architecture are included. An assessment involves identifying accomplishment, and weaknesses compared to leading practices for data management. Broad application of the DMM can help improve quality in data and operations, and consistency across the community that will facilitate interoperability, discovery, preservation, and reuse. Good data can be better data. Consistency results in sustainability.

Runway Operations Planning: A Two-Stage Solution Methodology

NASA Technical Reports Server (NTRS)

Anagnostakis, Ioannis; Clarke, John-Paul

2003-01-01

The airport runway is a scarce resource that must be shared by different runway operations (arrivals, departures and runway crossings). Given the possible sequences of runway events, careful Runway Operations Planning (ROP) is required if runway utilization is to be maximized. Thus, Runway Operations Planning (ROP) is a critical component of airport operations planning in general and surface operations planning in particular. From the perspective of departures, ROP solutions are aircraft departure schedules developed by optimally allocating runway time for departures given the time required for arrivals and crossings. In addition to the obvious objective of maximizing throughput, other objectives, such as guaranteeing fairness and minimizing environmental impact, may be incorporated into the ROP solution subject to constraints introduced by Air Traffic Control (ATC) procedures. Generating optimal runway operations plans was approached in with a 'one-stage' optimization routine that considered all the desired objectives and constraints, and the characteristics of each aircraft (weight class, destination, Air Traffic Control (ATC) constraints) at the same time. Since, however, at any given point in time, there is less uncertainty in the predicted demand for departure resources in terms of weight class than in terms of specific aircraft, the ROP problem can be parsed into two stages. In the context of the Departure Planner (OP) research project, this paper introduces Runway Operations Planning (ROP) as part of the wider Surface Operations Optimization (SOO) and describes a proposed 'two stage' heuristic algorithm for solving the Runway Operations Planning (ROP) problem. Focus is specifically given on including runway crossings in the planning process of runway operations. In the first stage, sequences of departure class slots and runwy crossings slots are generated and ranked based on departure runway throughput under stochastic conditions. In the second stage, the departure class slots are populated with specific flights from the pool of available aircraft, by solving an integer program. Preliminary results from the algorithm implementation on real-world traffic data are included.

Solving Two-Level Optimization Problems with Applications to Robust Design and Energy Markets

DTIC Science & Technology

2011-01-01

additional a transportation system operator (TSO) who manages the congestion and 172 flows. The TSO’s linear program is as follows (where other...were tested are shown in Table 5.11 below. Node 1 Node 2 Producer A Producer B Producer C Producer D Transmission System Operator 174... Systems to Solve Problems that are Not Linear. Operational Research Quarterly , 26, 609–618. 9. Beale, E., & Tomlin, J. (1970). Special Facilities

Evaluation of green building rating tools based on existing green building achievement in Indonesia using Life Cycle Assessment Method

NASA Astrophysics Data System (ADS)

Basten, Van; Latief, Yusuf; Berawi, Mohammed Ali; Budiman, Rachmat; Riswanto

2017-03-01

Total completed building construction value in Indonesia increased 116% during 2009 to 2011. That's followed by increasing 11% energy consumption in Indonesia in the last three years with 70% energy met to the electricity needs of commercial building. In addition, a few application of green building concept in Indonesia made the greenhouse gas emissions or CO2 amount increased by 25%. Construction, operation, and maintain of building cost consider relatively high. The evaluation in this research is used to improve the building performance with some of green concept alternatives. The research methodology is conducted by combination of qualitative and quantitative approaches through interview and case study. Assessing the successful of optimization functions in the existing green building is based on the operational and maintenance phase with the Life Cycle Assessment (LCA) Method. The result of optimization that is the largest efficiency and effective of building life cycle.

Can We Practically Bring Physics-based Modeling Into Operational Analytics Tools?

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

Granderson, Jessica; Bonvini, Marco; Piette, Mary Ann

We present that analytics software is increasingly used to improve and maintain operational efficiency in commercial buildings. Energy managers, owners, and operators are using a diversity of commercial offerings often referred to as Energy Information Systems, Fault Detection and Diagnostic (FDD) systems, or more broadly Energy Management and Information Systems, to cost-effectively enable savings on the order of ten to twenty percent. Most of these systems use data from meters and sensors, with rule-based and/or data-driven models to characterize system and building behavior. In contrast, physics-based modeling uses first-principles and engineering models (e.g., efficiency curves) to characterize system and buildingmore » behavior. Historically, these physics-based approaches have been used in the design phase of the building life cycle or in retrofit analyses. Researchers have begun exploring the benefits of integrating physics-based models with operational data analytics tools, bridging the gap between design and operations. In this paper, we detail the development and operator use of a software tool that uses hybrid data-driven and physics-based approaches to cooling plant FDD and optimization. Specifically, we describe the system architecture, models, and FDD and optimization algorithms; advantages and disadvantages with respect to purely data-driven approaches; and practical implications for scaling and replicating these techniques. Finally, we conclude with an evaluation of the future potential for such tools and future research opportunities.« less

Optimized resolved rate control of seven-degree-of-freedom Laboratory Telerobotic Manipulator (LTM) with application to three-dimensional graphics simulation

NASA Technical Reports Server (NTRS)

Barker, L. Keith; Mckinney, William S., Jr.

1989-01-01

The Laboratory Telerobotic Manipulator (LTM) is a seven-degree-of-freedom robot arm. Two of the arms were delivered to Langley Research Center for ground-based research to assess the use of redundant degree-of-freedom robot arms in space operations. Resolved-rate control equations for the LTM are derived. The equations are based on a scheme developed at the Oak Ridge National Laboratory for computing optimized joint angle rates in real time. The optimized joint angle rates actually represent a trade-off, as the hand moves, between small rates (least-squares solution) and those rates which work toward satisfying a specified performance criterion of joint angles. In singularities where the optimization scheme cannot be applied, alternate control equations are devised. The equations developed were evaluated using a real-time computer simulation to control a 3-D graphics model of the LTM.

Research on the Optimization Method of Arm Movement in the Assembly Workshop Based on Ergonomics

NASA Astrophysics Data System (ADS)

Hu, X. M.; Qu, H. W.; Xu, H. J.; Yang, L.; Yu, C. C.

2017-12-01

In order to improve the work efficiency and comfortability, Ergonomics is used to research the work of the operator in the assembly workshop. An optimization algorithm of arm movement in the assembly workshop is proposed. In the algorithm, a mathematical model of arm movement is established based on multi rigid body movement model and D-H method. The solution of inverse kinematics equation on arm movement is solved through kinematics theory. The evaluation functions of each joint movement and the whole arm movement are given based on the comfortability of human body joint. The solution method of the optimal arm movement posture based on the evaluation functions is described. The software CATIA is used to verify that the optimal arm movement posture is valid in an example and the experimental result show the effectiveness of the algorithm.

Relations between information, time, and value of water

NASA Astrophysics Data System (ADS)

Weijs, S. V.; Galindo, L. C.

2015-12-01

This research uses with stochastic dynamic programming (SDP) as a tool to reveal economic information about managed water resources. An application to the operation of an example hydropower reservoir is presented. SDP explicitly balances the marginal value of water for immediate use and its expected opportunity cost of not having more water available for future use. The result of an SDP analysis is a steady state policy, which gives the optimal decision as a function of the state. A commonly applied form gives the optimal release as a function of the month, current reservoir level and current inflow to the reservoir. The steady state policy can be complemented with a real-time management strategy, that can depend on more real-time information. An information-theoretical perspective is given on how this information influences the value of water, and how to deal with that influence in hydropower reservoir optimization. This results in some conjectures about how the information gain from real-time operation could affect the optimal long term policy. Another issue is the sharing of increased benefits that result from this information gain in a multi-objective setting. It is argued that this should be accounted for in negotiations about an operation policy.

Optimization of Airport Surface Traffic: A Case-Study of Incheon International Airport

NASA Technical Reports Server (NTRS)

Eun, Yeonju; Jeon, Daekeun; Lee, Hanbong; Jung, Yoon C.; Zhu, Zhifan; Jeong, Myeongsook; Kim, Hyounkong; Oh, Eunmi; Hong, Sungkwon

2017-01-01

This study aims to develop a controllers decision support tool for departure and surface management of ICN. Airport surface traffic optimization for Incheon International Airport (ICN) in South Korea was studied based on the operational characteristics of ICN and airspace of Korea. For surface traffic optimization, a multiple runway scheduling problem and a taxi scheduling problem were formulated into two Mixed Integer Linear Programming (MILP) optimization models. The Miles-In-Trail (MIT) separation constraint at the departure fix shared by the departure flights from multiple runways and the runway crossing constraints due to the taxi route configuration specific to ICN were incorporated into the runway scheduling and taxiway scheduling problems, respectively. Since the MILP-based optimization model for the multiple runway scheduling problem may be computationally intensive, computation times and delay costs of different solving methods were compared for a practical implementation. This research was a collaboration between Korea Aerospace Research Institute (KARI) and National Aeronautics and Space Administration (NASA).

Optimization of Airport Surface Traffic: A Case-Study of Incheon International Airport

NASA Technical Reports Server (NTRS)

Eun, Yeonju; Jeon, Daekeun; Lee, Hanbong; Jung, Yoon Chul; Zhu, Zhifan; Jeong, Myeong-Sook; Kim, Hyoun Kyoung; Oh, Eunmi; Hong, Sungkwon

2017-01-01

This study aims to develop a controllers' decision support tool for departure and surface management of ICN. Airport surface traffic optimization for Incheon International Airport (ICN) in South Korea was studied based on the operational characteristics of ICN and airspace of Korea. For surface traffic optimization, a multiple runway scheduling problem and a taxi scheduling problem were formulated into two Mixed Integer Linear Programming (MILP) optimization models. The Miles-In-Trail (MIT) separation constraint at the departure fix shared by the departure flights from multiple runways and the runway crossing constraints due to the taxi route configuration specific to ICN were incorporated into the runway scheduling and taxiway scheduling problems, respectively. Since the MILP-based optimization model for the multiple runway scheduling problem may be computationally intensive, computation times and delay costs of different solving methods were compared for a practical implementation. This research was a collaboration between Korea Aerospace Research Institute (KARI) and National Aeronautics and Space Administration (NASA).

Information Foraging in Nuclear Power Plant Control Rooms

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

R.L. Boring

2011-09-01

nformation foraging theory articulates the role of the human as an 'informavore' that seeks information and follows optimal foraging strategies (i.e., the 'information scent') to find meaningful information. This paper briefly reviews the findings from information foraging theory outside the nuclear domain and then discusses the types of information foraging strategies operators employ for normal and off-normal operations in the control room. For example, operators may employ a predatory 'wolf' strategy of hunting for information in the face of a plant upset. However, during routine operations, the operators may employ a trapping 'spider' strategy of waiting for relevant indicators tomore » appear. This delineation corresponds to information pull and push strategies, respectively. No studies have been conducted to determine explicitly the characteristics of a control room interface that is optimized for both push and pull information foraging strategies, nor has there been empirical work to validate operator performance when transitioning between push and pull strategies. This paper explores examples of control room operators as wolves vs. spiders and con- cludes by proposing a set of research questions to investigate information foraging in control room settings.« less

Lockheed L-1011 TriStar to support Adaptive Performance Optimization study with NASA F-18 chase plan

NASA Technical Reports Server (NTRS)

1995-01-01

This Lockheed L-1011 Tristar, seen here June 1995, is currently the subject of a new flight research experiment developed by NASA's Dryden Flight Research Center, Edwards, California, to improve the effiecency of large transport aircraft. Shown with a NASA F-18 chase plane over California's Sierra Nevada mountains during an earlier baseline flight, the jetliner operated by Oribtal Sciences Corp., recently flew its first data-gathering mission in the Adaptive Performance Optimization project. The experiment seeks to reduce fuel comsumption of large jetliners by improving the aerodynamic efficiency of their wings at cruise conditions. A research computer employing a sophisticated software program adapts to changing flight conditions by commanding small movements of the L-1011's outboard ailerons to give its wings the most efficient - or optimal - airfoil. Up to a dozen research flights will be flown in the current and follow-on phases of the project over the next couple years.

Optimization of Typological Requirements for Low-Cost Detached Houses

NASA Astrophysics Data System (ADS)

Kuráň, Jozef

2017-09-01

The presented paper deals with an analysis of the legislative, hygienic, functional and operational requirements for the design of detached houses and individual dwellings in terms of typological requirements. The article also presents a sociological survey about the preferences and subjective requirements of relevant public group segments in terms of living in a detached house or an individual dwelling. The aim of the paper is to define the possibilities for the optimization of typological requirements. The optimization methods are based on principles already applied to contemporary detached house preferences and trends. The main idea is to reduce the amount of floor space, thus lowering construction and operating costs. The goal is to design an optimized floor plan, while preserving the hygienic criteria for individual residential dwellings. By applying optimization methods, a so-called rationalized and conditioned floor plan results in an individual dwelling floor plan design that can be compared to a reference model with an accurate quantification comparison. The significant sources of research are the legislative and normative requirements in the field of house construction in Slovakia, the Czech Republic and abroad.

Staying Alive! Training High-Risk Teams for Self Correction

NASA Technical Reports Server (NTRS)

Slack, Kelley; Noe, Raymond; Weaver, Sallie

2011-01-01

Research examining teams working in high-risk operations has been lacking. The present symposium showcases research on team training that helps to optimize team performance in environments characterized by life or death situations arising spontaneously after long periods of mundane activity by pulling experts from diverse areas of industry: space flight, health care, and medical simulation.

Solar Market Research and Analysis Projects | Solar Research | NREL

Science.gov Websites

increase the effectiveness and reduce the variability and cost of PV operations and maintenance (O&M significantly drive up the cost of electricity for PV systems. To help reduce PV O&M costs and improve PV -Storage: Reducing Barriers Through Cost-Optimization and Market Characterization While falling costs have

Model-based minimization algorithm of a supercritical helium loop consumption subject to operational constraints

NASA Astrophysics Data System (ADS)

Bonne, F.; Bonnay, P.; Girard, A.; Hoa, C.; Lacroix, B.; Le Coz, Q.; Nicollet, S.; Poncet, J.-M.; Zani, L.

2017-12-01

Supercritical helium loops at 4.2 K are the baseline cooling strategy of tokamaks superconducting magnets (JT-60SA, ITER, DEMO, etc.). This loops work with cryogenic circulators that force a supercritical helium flow through the superconducting magnets in order that the temperature stay below the working range all along their length. This paper shows that a supercritical helium loop associated with a saturated liquid helium bath can satisfy temperature constraints in different ways (playing on bath temperature and on the supercritical flow), but that only one is optimal from an energy point of view (every Watt consumed at 4.2 K consumes at least 220 W of electrical power). To find the optimal operational conditions, an algorithm capable of minimizing an objective function (energy consumption at 5 bar, 5 K) subject to constraints has been written. This algorithm works with a supercritical loop model realized with the Simcryogenics [2] library. This article describes the model used and the results of constrained optimization. It will be possible to see that the changes in operating point on the temperature of the magnet (e.g. in case of a change in the plasma configuration) involves large changes on the cryodistribution optimal operating point. Recommendations will be made to ensure that the energetic consumption is kept as low as possible despite the changing operating point. This work is partially supported by EUROfusion Consortium through the Euratom Research and Training Program 20142018 under Grant 633053.

Energy and water quality management systems for water utility's operations: a review.

PubMed

Cherchi, Carla; Badruzzaman, Mohammad; Oppenheimer, Joan; Bros, Christopher M; Jacangelo, Joseph G

2015-04-15

Holistic management of water and energy resources is critical for water utilities facing increasing energy prices, water supply shortage and stringent regulatory requirements. In the early 1990s, the concept of an integrated Energy and Water Quality Management System (EWQMS) was developed as an operational optimization framework for solving water quality, water supply and energy management problems simultaneously. Approximately twenty water utilities have implemented an EWQMS by interfacing commercial or in-house software optimization programs with existing control systems. For utilities with an installed EWQMS, operating cost savings of 8-15% have been reported due to higher use of cheaper tariff periods and better operating efficiencies, resulting in the reduction in energy consumption of ∼6-9%. This review provides the current state-of-knowledge on EWQMS typical structural features and operational strategies and benefits and drawbacks are analyzed. The review also highlights the challenges encountered during installation and implementation of EWQMS and identifies the knowledge gaps that should motivate new research efforts. Copyright © 2015 Elsevier Ltd. All rights reserved.

Advanced in-duct sorbent injection for SO{sub 2} control. Topical report No. 2, Subtask 2.2: Design optimization

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

Rosenhoover, W.A.; Stouffer, M.R.; Withum, J.A.

1994-12-01

The objective of this research project is to develop second-generation duct injection technology as a cost-effective SO{sub 2} control option for the 1990 Clean Air Act Amendments. Research is focused on the Advanced Coolside process, which has shown the potential for achieving the performance targets of 90% SO{sub 2} removal and 60% sorbent utilization. In Subtask 2.2, Design Optimization, process improvement was sought by optimizing sorbent recycle and by optimizing process equipment for reduced cost. The pilot plant recycle testing showed that 90% SO{sub 2} removal could be achieved at sorbent utilizations up to 75%. This testing also showed thatmore » the Advanced Coolside process has the potential to achieve very high removal efficiency (90 to greater than 99%). Two alternative contactor designs were developed, tested and optimized through pilot plant testing; the improved designs will reduce process costs significantly, while maintaining operability and performance essential to the process. Also, sorbent recycle handling equipment was optimized to reduce cost.« less

Analysis of decision support system for dredging operations management.

DOT National Transportation Integrated Search

2005-12-01

This research developed an improved method for optimizing the disposal of dredged material : at offshore disposal sites. A nonlinear programming model has been developed to assist in : the development of dredging plans at open water disposal sites. T...

Advanced Intelligent System Application to Load Forecasting and Control for Hybrid Electric Bus

NASA Technical Reports Server (NTRS)

Momoh, James; Chattopadhyay, Deb; Elfayoumy, Mahmoud

1996-01-01

The primary motivation for this research emanates from providing a decision support system to the electric bus operators in the municipal and urban localities which will guide the operators to maintain an optimal compromise among the noise level, pollution level, fuel usage etc. This study is backed up by our previous studies on study of battery characteristics, permanent magnet DC motor studies and electric traction motor size studies completed in the first year. The operator of the Hybrid Electric Car must determine optimal power management schedule to meet a given load demand for different weather and road conditions. The decision support system for the bus operator comprises three sub-tasks viz. forecast of the electrical load for the route to be traversed divided into specified time periods (few minutes); deriving an optimal 'plan' or 'preschedule' based on the load forecast for the entire time-horizon (i.e., for all time periods) ahead of time; and finally employing corrective control action to monitor and modify the optimal plan in real-time. A fully connected artificial neural network (ANN) model is developed for forecasting the kW requirement for hybrid electric bus based on inputs like climatic conditions, passenger load, road inclination, etc. The ANN model is trained using back-propagation algorithm employing improved optimization techniques like projected Lagrangian technique. The pre-scheduler is based on a Goal-Programming (GP) optimization model with noise, pollution and fuel usage as the three objectives. GP has the capability of analyzing the trade-off among the conflicting objectives and arriving at the optimal activity levels, e.g., throttle settings. The corrective control action or the third sub-task is formulated as an optimal control model with inputs from the real-time data base as well as the GP model to minimize the error (or deviation) from the optimal plan. These three activities linked with the ANN forecaster proving the output to the GP model which in turn produces the pre-schedule of the optimal control model. Some preliminary results based on a hypothetical test case will be presented for the load forecasting module. The computer codes for the three modules will be made available fe adoption by bus operating agencies. Sample results will be provided using these models. The software will be a useful tool for supporting the control systems for the Electric Bus project of NASA.

Analysis and Algorithms for Imperfect Sensor Deployment and Operations

DTIC Science & Technology

2016-05-23

fortification-interdiction-routing games that take place over the traveling salesman problem (TSP) in reference 16. This study reveals that a straightforward...Journal on Optimization. 16. Lozano, L., Smith, J.C., and Kurz, M.E., Solving the Traveling Salesman Problem with Interdiction and Fortification...the Traveling Salesman Problem with Interdiction and Fortification, submitted to Operations Research Letters. Tadayon, B. and Smith, J.C., A Survey of

The molecular matching problem

NASA Technical Reports Server (NTRS)

Kincaid, Rex K.

1993-01-01

Molecular chemistry contains many difficult optimization problems that have begun to attract the attention of optimizers in the Operations Research community. Problems including protein folding, molecular conformation, molecular similarity, and molecular matching have been addressed. Minimum energy conformations for simple molecular structures such as water clusters, Lennard-Jones microclusters, and short polypeptides have dominated the literature to date. However, a variety of interesting problems exist and we focus here on a molecular structure matching (MSM) problem.

Optimizing the US Navy’s Combat Logistics Force

DTIC Science & Technology

2008-01-01

Optimizing the US Navy’s Combat Logistics Force Gerald G. Brown, W. Matthew Carlyle Operations Research Department, Naval Postgraduate School...Wiley InterScience (www.interscience.wiley.com). Abstract: We study how changes to the composition and employment of the US Navy combat logistic force...evaluate new CLF ship designs, advise what number of ships in a new ship class would be needed, test concepts for forward at-sea logistics bases in lieu

On the use of controls for subsonic transport performance improvement: Overview and future directions

NASA Technical Reports Server (NTRS)

Gilyard, Glenn; Espana, Martin

1994-01-01

Increasing competition among airline manufacturers and operators has highlighted the issue of aircraft efficiency. Fewer aircraft orders have led to an all-out efficiency improvement effort among the manufacturers to maintain if not increase their share of the shrinking number of aircraft sales. Aircraft efficiency is important in airline profitability and is key if fuel prices increase from their current low. In a continuing effort to improve aircraft efficiency and develop an optimal performance technology base, NASA Dryden Flight Research Center developed and flight tested an adaptive performance seeking control system to optimize the quasi-steady-state performance of the F-15 aircraft. The demonstrated technology is equally applicable to transport aircraft although with less improvement. NASA Dryden, in transitioning this technology to transport aircraft, is specifically exploring the feasibility of applying adaptive optimal control techniques to performance optimization of redundant control effectors. A simulation evaluation of a preliminary control law optimizes wing-aileron camber for minimum net aircraft drag. Two submodes are evaluated: one to minimize fuel and the other to maximize velocity. This paper covers the status of performance optimization of the current fleet of subsonic transports. Available integrated controls technologies are reviewed to define approaches using active controls. A candidate control law for adaptive performance optimization is presented along with examples of algorithm operation.

Peak-Seeking Optimization of Trim for Reduced Fuel Consumption: Flight-Test Results

NASA Technical Reports Server (NTRS)

Brown, Nelson Andrew; Schaefer, Jacob Robert

2013-01-01

A peak-seeking control algorithm for real-time trim optimization for reduced fuel consumption has been developed by researchers at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center to address the goals of the NASA Environmentally Responsible Aviation project to reduce fuel burn and emissions. The peak-seeking control algorithm is based on a steepest-descent algorithm using a time-varying Kalman filter to estimate the gradient of a performance function of fuel flow versus control surface positions. In real-time operation, deflections of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of an F/A-18 airplane (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) are used for optimization of fuel flow. Results from six research flights are presented herein. The optimization algorithm found a trim configuration that required approximately 3 percent less fuel flow than the baseline trim at the same flight condition. The algorithm consistently rediscovered the solution from several initial conditions. These results show that the algorithm has good performance in a relevant environment.

Peak-Seeking Optimization of Trim for Reduced Fuel Consumption: Flight-test Results

NASA Technical Reports Server (NTRS)

Brown, Nelson Andrew; Schaefer, Jacob Robert

2013-01-01

A peak-seeking control algorithm for real-time trim optimization for reduced fuel consumption has been developed by researchers at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center to address the goals of the NASA Environmentally Responsible Aviation project to reduce fuel burn and emissions. The peak-seeking control algorithm is based on a steepest-descent algorithm using a time-varying Kalman filter to estimate the gradient of a performance function of fuel flow versus control surface positions. In real-time operation, deflections of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of an F/A-18 airplane (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) are used for optimization of fuel flow. Results from six research flights are presented herein. The optimization algorithm found a trim configuration that required approximately 3 percent less fuel flow than the baseline trim at the same flight condition. The algorithm consistently rediscovered the solution from several initial conditions. These results show that the algorithm has good performance in a relevant environment.

A Cockpit-Based Application for Traffic Aware Trajectory Optimization

NASA Technical Reports Server (NTRS)

Woods, Sharon E.; Vivona, Robert A.; Roscoe, David A.; LeFebvre, Brendan C.; Wing, David J.; Ballin, Mark G.

2013-01-01

The Traffic Aware Planner (TAP) is a cockpit-based advisory tool designed to be hosted on a Class 2 Electronic Flight Bag and developed to enable the concept of Traffic Aware Strategic Aircrew Requests (TASAR). This near-term concept provides pilots with optimized route changes that reduce fuel burn or flight time, avoids interactions with known traffic, weather and restricted airspace, and may be used by the pilots to request a trajectory change from air traffic control. TAP's internal architecture and algorithms are derived from the Autonomous Operations Planner, a flight-deck automation system developed by NASA to support research into aircraft self-separation. This paper reviews the architecture, functionality and operation of TAP.

Combinatorial optimization problem solution based on improved genetic algorithm

NASA Astrophysics Data System (ADS)

Zhang, Peng

2017-08-01

Traveling salesman problem (TSP) is a classic combinatorial optimization problem. It is a simplified form of many complex problems. In the process of study and research, it is understood that the parameters that affect the performance of genetic algorithm mainly include the quality of initial population, the population size, and crossover probability and mutation probability values. As a result, an improved genetic algorithm for solving TSP problems is put forward. The population is graded according to individual similarity, and different operations are performed to different levels of individuals. In addition, elitist retention strategy is adopted at each level, and the crossover operator and mutation operator are improved. Several experiments are designed to verify the feasibility of the algorithm. Through the experimental results analysis, it is proved that the improved algorithm can improve the accuracy and efficiency of the solution.

Neural networks for aircraft control

NASA Technical Reports Server (NTRS)

Linse, Dennis

1990-01-01

Current research in Artificial Neural Networks indicates that networks offer some potential advantages in adaptation and fault tolerance. This research is directed at determining the possible applicability of neural networks to aircraft control. The first application will be to aircraft trim. Neural network node characteristics, network topology and operation, neural network learning and example histories using neighboring optimal control with a neural net are discussed.

40 Years of AEDC Development, Evolution and Application of Numerical Simulations for Integrated Test and Evaluation of Turbine Engine Turbomachinery Operability Issues

DTIC Science & Technology

2010-03-01

distribution is unlimited.  Provide pretest prediction and posttest assessment of aircraft test matrix to optimize wind tunnel inlet testing...Development of Production Simulations ........................................................... 417 A.4 Research and Development Activities...174 Figure 3.175 Two-Stage HTSC as Tested at the Compressor Research Facility [3.125] ........ 174

A programing system for research and applications in structural optimization

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, J.; Rogers, J. L., Jr.

1981-01-01

The flexibility necessary for such diverse utilizations is achieved by combining, in a modular manner, a state-of-the-art optimization program, a production level structural analysis program, and user supplied and problem dependent interface programs. Standard utility capabilities in modern computer operating systems are used to integrate these programs. This approach results in flexibility of the optimization procedure organization and versatility in the formulation of constraints and design variables. Features shown in numerical examples include: variability of structural layout and overall shape geometry, static strength and stiffness constraints, local buckling failure, and vibration constraints.

4-channels coherent perfect absorption (CPA)-type demultiplexer using plasmonic nano spheres

NASA Astrophysics Data System (ADS)

Soltani, Mohamadreza; Keshavarzi, Rasul

2017-10-01

The current research represents a nanoscale and compact 4-channels plasmonic demultiplexer. It includes eight coherent perfect absorption (CPA) - type filters. The operation principle is based on the absorbable formation of a conductive path in the dielectric layer of a plasmonic nano-spheres waveguide. Since the CPA efficiency depends strongly on the number of plasmonic nano-spheres and the nano spheres location, an efficient binary optimization method based on the Particle Swarm Optimization algorithm is used to design an optimized array of the plasmonic nano-sphere in order to achieve the maximum absorption coefficient in the 'off' state.

Replica Analysis for Portfolio Optimization with Single-Factor Model

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2017-06-01

In this paper, we use replica analysis to investigate the influence of correlation among the return rates of assets on the solution of the portfolio optimization problem. We consider the behavior of an optimal solution for the case where the return rate is described with a single-factor model and compare the findings obtained from our proposed methods with correlated return rates with those obtained with independent return rates. We then analytically assess the increase in the investment risk when correlation is included. Furthermore, we also compare our approach with analytical procedures for minimizing the investment risk from operations research.

Optimization of Vertical Double-Diffused Metal-Oxide Semiconductor (VDMOS) Power Transistor Structure for Use in High Frequencies and Medical Devices

PubMed Central

Farhadi, Rozita; Farhadi, Bita

2014-01-01

Power transistors, such as the vertical, double-diffused, metal-oxide semiconductor (VDMOS), are used extensively in the amplifier circuits of medical devices. The aim of this research was to construct a VDMOS power transistor with an optimized structure to enhance the operation of medical devices. First, boron was implanted in silicon by implanting unclamped inductive switching (UIS) and a Faraday shield. The Faraday shield was implanted in order to replace the gate-field parasitic capacitor on the entry part of the device. Also, implanting the UIS was used in order to decrease the effect of parasitic bipolar junction transistor (BJT) of the VDMOS power transistor. The research tool used in this study was Silvaco software. By decreasing the transistor entry resistance in the optimized VDMOS structure, power losses and noise at the entry of the transistor were decreased, and, by increasing the breakdown voltage, the lifetime of the VDMOS transistor lifetime was increased, which resulted in increasing drain flow and decreasing Ron. This consequently resulted in enhancing the operation of high-frequency medical devices that use transistors, such as Radio Frequency (RF) and electrocardiograph machines. PMID:25763152

Optimization of Vertical Double-Diffused Metal-Oxide Semiconductor (VDMOS) Power Transistor Structure for Use in High Frequencies and Medical Devices.

PubMed

Farhadi, Rozita; Farhadi, Bita

2014-01-01

Power transistors, such as the vertical, double-diffused, metal-oxide semiconductor (VDMOS), are used extensively in the amplifier circuits of medical devices. The aim of this research was to construct a VDMOS power transistor with an optimized structure to enhance the operation of medical devices. First, boron was implanted in silicon by implanting unclamped inductive switching (UIS) and a Faraday shield. The Faraday shield was implanted in order to replace the gate-field parasitic capacitor on the entry part of the device. Also, implanting the UIS was used in order to decrease the effect of parasitic bipolar junction transistor (BJT) of the VDMOS power transistor. The research tool used in this study was Silvaco software. By decreasing the transistor entry resistance in the optimized VDMOS structure, power losses and noise at the entry of the transistor were decreased, and, by increasing the breakdown voltage, the lifetime of the VDMOS transistor lifetime was increased, which resulted in increasing drain flow and decreasing Ron. This consequently resulted in enhancing the operation of high-frequency medical devices that use transistors, such as Radio Frequency (RF) and electrocardiograph machines.

Open and Shut: The Case for Optimizing Air Component Resilient Basing Strategies in an Anti-Access/Area Denial Operating Environment

DTIC Science & Technology

2018-04-09

The research focuses on gaps in current doctrine, command relationships, command and control, force structure of ABO forces, posture, training for...identifying conceptual challenges and methodologies to address them as well as describing areas for further research . 15. SUBJECT TERMS Airbase Opening...Denial environment. The research focuses on gaps in current doctrine, command relationships, command and control, force structure of ABO forces

Space Station Habitability Research

NASA Technical Reports Server (NTRS)

Clearwater, Yvonne A.

1988-01-01

The purpose and scope of the Habitability Research Group within the Space Human Factors Office at the NASA/Ames Research Center is described. Both near-term and long-term research objectives in the space human factors program pertaining to the U.S. manned Space Station are introduced. The concept of habitability and its relevancy to the U.S. space program is defined within a historical context. The relationship of habitability research to the optimization of environmental and operational determinants of productivity is discussed. Ongoing habitability research efforts pertaining to living and working on the Space Station are described.

Space Station habitability research

NASA Technical Reports Server (NTRS)

Clearwater, Y. A.

1986-01-01

The purpose and scope of the Habitability Research Group within the Space Human Factors Office at the NASA/Ames Research Cente is described. Both near-term and long-term research objectives in the space human factors program pertaining to the U.S. manned Space Station are introduced. The concept of habitability and its relevancy to the U.S. space program is defined within a historical context. The relationship of habitability research to the optimization of environmental and operational determinants of productivity is discussed. Ongoing habitability research efforts pertaining to living and working on the Space Station are described.

Space Station habitability research.

PubMed

Clearwater, Y A

1988-02-01

The purpose and scope of the Habitability Research Group within the Space Human Factors Office at the NASA/Ames Research Center is described. Both near-term and long-term research objectives in the space human factors program pertaining to the U.S. manned Space Station are introduced. The concept of habitability and its relevancy to the U.S. space program is defined within a historical context. The relationship of habitability research to the optimization of environmental and operational determinants of productivity is discussed. Ongoing habitability research efforts pertaining to living and working on the Space Station are described.

Optimal Collision Avoidance Trajectories for Unmanned/Remotely Piloted Aircraft

DTIC Science & Technology

2014-12-26

projected operational tempos (OPTEMPOs)” [15]. The Oce of the Secretary of Defense (OSD) Unmanned Systems Roadmap [15] goes on to say that the airspace...methods [63]. In an indirect method, the researcher derives the first- order necessary conditions for optimality “via the calculus of variations and...region around the ownship using a variation of a superquadric. From [116], the standard equation for a superellipsoid appears as: ✓ x a1 ◆ 2 ✏ 2

Optimizing a Laser Process for Making Carbon Nanotubes

NASA Technical Reports Server (NTRS)

Arepalli, Sivaram; Nikolaev, Pavel; Holmes, William

2010-01-01

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

Estimating irrigation water demand using an improved method and optimizing reservoir operation for water supply and hydropower generation: a case study of the Xinfengjiang reservoir in southern China

USGS Publications Warehouse

Wu, Yiping; Chen, Ji

2013-01-01

The ever-increasing demand for water due to growth of population and socioeconomic development in the past several decades has posed a worldwide threat to water supply security and to the environmental health of rivers. This study aims to derive reservoir operating rules through establishing a multi-objective optimization model for the Xinfengjiang (XFJ) reservoir in the East River Basin in southern China to minimize water supply deficit and maximize hydropower generation. Additionally, to enhance the estimation of irrigation water demand from the downstream agricultural area of the XFJ reservoir, a conventional method for calculating crop water demand is improved using hydrological model simulation results. Although the optimal reservoir operating rules are derived for the XFJ reservoir with three priority scenarios (water supply only, hydropower generation only, and equal priority), the river environmental health is set as the basic demand no matter which scenario is adopted. The results show that the new rules derived under the three scenarios can improve the reservoir operation for both water supply and hydropower generation when comparing to the historical performance. Moreover, these alternative reservoir operating policies provide the flexibility for the reservoir authority to choose the most appropriate one. Although changing the current operating rules may influence its hydropower-oriented functions, the new rules can be significant to cope with the increasingly prominent water shortage and degradation in the aquatic environment. Overall, our results and methods (improved estimation of irrigation water demand and formulation of the reservoir optimization model) can be useful for local watershed managers and valuable for other researchers worldwide.

Intelligent control for modeling of real-time reservoir operation, part II: artificial neural network with operating rule curves

NASA Astrophysics Data System (ADS)

Chang, Ya-Ting; Chang, Li-Chiu; Chang, Fi-John

2005-04-01

To bridge the gap between academic research and actual operation, we propose an intelligent control system for reservoir operation. The methodology includes two major processes, the knowledge acquired and implemented, and the inference system. In this study, a genetic algorithm (GA) and a fuzzy rule base (FRB) are used to extract knowledge based on the historical inflow data with a design objective function and on the operating rule curves respectively. The adaptive network-based fuzzy inference system (ANFIS) is then used to implement the knowledge, to create the fuzzy inference system, and then to estimate the optimal reservoir operation. To investigate its applicability and practicability, the Shihmen reservoir, Taiwan, is used as a case study. For the purpose of comparison, a simulation of the currently used M-5 operating rule curve is also performed. The results demonstrate that (1) the GA is an efficient way to search the optimal input-output patterns, (2) the FRB can extract the knowledge from the operating rule curves, and (3) the ANFIS models built on different types of knowledge can produce much better performance than the traditional M-5 curves in real-time reservoir operation. Moreover, we show that the model can be more intelligent for reservoir operation if more information (or knowledge) is involved.

Results from the first operation phase of W7-X

NASA Astrophysics Data System (ADS)

Pedersen, Thomas Sunn

2016-10-01

This talk will give a review of stellarator physics and the mission of Wendelstein 7-X (W7-X), and will summarize the most important results obtained during its first operation phase, OP1.1, which was completed in March 2016. The HELIAS reactor vision and open issues in stellarator research will also be discussed. The stellarator concept dates back to the 1950's. It has several intrinsic advantages, including being free of current-driven disruptions, and not needing current drive. However, the stellarator has been lagging behind the tokamak with respect to energy confinement. Recent advances in plasma theory and computational power have led to renewed interest in stellarators since they allow a complex but effective optimization of the confinement properties, one that should allow for tokamak-like confinement times. W7-X is the largest and most optimized stellarator in the world, and aims to show that the earlier weaknesses of the stellarator concept have been addressed successfully by optimization, and that the intrinsic advantages of the concept persist, also at plasma parameters approaching those of a future fusion power plant. It is built for steady-state operation, featuring 70 superconducting coils, and a confinement volume of about 30 m3. During OP1.1, it was operated at full field (B = 2.5 T on axis), with ECRH power up to 4.3 MW (later to be extended to 10 MW). Plasma operation was performed with helium and hydrogen, with deuterium planned for later phases. More than 2,000 discharges were created during the 10 operation weeks of OP1.1. Core Te 8 keV and Ti 2 keV were reached in discharge with densities in the low to mid 1019 range, and confinement times were on the order of 100-150 ms, within expectation. This work has been carried out within the framework of the EUROfusion Consortium and has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement Number 633053.

Sourcing in the Air Force: An Optimization Approach

DTIC Science & Technology

2009-09-01

quality supplies and services at the lowest cost ( Gabbard , 2004). The commodity sourcing strategy focuses on developing a specific sourcing strategy...Springer Series in Operations Research. New York: Springer-Verlag. Gabbard , E.G. (2004, April). Strategic sourcing: Critical elements and keys to success

Optimizing snow plowing operations in urban road networks : final research report.

DOT National Transportation Integrated Search

2015-01-01

Due to the disruptive effect of snowstorms on cities, both in terms of : mobility and safety, the faster the streets can be cleared the better. Yet in : most cities (including Pittsburgh), static plans for snowplowing are : developed using simple all...

Optimizing integrated airport surface and terminal airspace operations under uncertainty

NASA Astrophysics Data System (ADS)

Bosson, Christabelle S.

In airports and surrounding terminal airspaces, the integration of surface, arrival and departure scheduling and routing have the potential to improve the operations efficiency. Moreover, because both the airport surface and the terminal airspace are often altered by random perturbations, the consideration of uncertainty in flight schedules is crucial to improve the design of robust flight schedules. Previous research mainly focused on independently solving arrival scheduling problems, departure scheduling problems and surface management scheduling problems and most of the developed models are deterministic. This dissertation presents an alternate method to model the integrated operations by using a machine job-shop scheduling formulation. A multistage stochastic programming approach is chosen to formulate the problem in the presence of uncertainty and candidate solutions are obtained by solving sample average approximation problems with finite sample size. The developed mixed-integer-linear-programming algorithm-based scheduler is capable of computing optimal aircraft schedules and routings that reflect the integration of air and ground operations. The assembled methodology is applied to a Los Angeles case study. To show the benefits of integrated operations over First-Come-First-Served, a preliminary proof-of-concept is conducted for a set of fourteen aircraft evolving under deterministic conditions in a model of the Los Angeles International Airport surface and surrounding terminal areas. Using historical data, a representative 30-minute traffic schedule and aircraft mix scenario is constructed. The results of the Los Angeles application show that the integration of air and ground operations and the use of a time-based separation strategy enable both significant surface and air time savings. The solution computed by the optimization provides a more efficient routing and scheduling than the First-Come-First-Served solution. Additionally, a data driven analysis is performed for the Los Angeles environment and probabilistic distributions of pertinent uncertainty sources are obtained. A sensitivity analysis is then carried out to assess the methodology performance and find optimal sampling parameters. Finally, simulations of increasing traffic density in the presence of uncertainty are conducted first for integrated arrivals and departures, then for integrated surface and air operations. To compare the optimization results and show the benefits of integrated operations, two aircraft separation methods are implemented that offer different routing options. The simulations of integrated air operations and the simulations of integrated air and surface operations demonstrate that significant traveling time savings, both total and individual surface and air times, can be obtained when more direct routes are allowed to be traveled even in the presence of uncertainty. The resulting routings induce however extra take off delay for departing flights. As a consequence, some flights cannot meet their initial assigned runway slot which engenders runway position shifting when comparing resulting runway sequences computed under both deterministic and stochastic conditions. The optimization is able to compute an optimal runway schedule that represents an optimal balance between total schedule delays and total travel times.

Infusion of innovative technologies for mission operations

NASA Astrophysics Data System (ADS)

Donati, Alessandro

2010-11-01

The Advanced Mission Concepts and Technologies Office (Mission Technologies Office, MTO for short) at the European Space Operations Centre (ESOC) of ESA is entrusted with research and development of innovative mission operations concepts systems and provides operations support to special projects. Visions of future missions and requests for improvements from currently flying missions are the two major sources of inspiration to conceptualize innovative or improved mission operations processes. They include monitoring and diagnostics, planning and scheduling, resource management and optimization. The newly identified operations concepts are then proved by means of prototypes, built with embedded, enabling technology and deployed as shadow applications in mission operations for an extended validation phase. The technology so far exploited includes informatics, artificial intelligence and operational research branches. Recent outstanding results include artificial intelligence planning and scheduling applications for Mars Express, advanced integrated space weather monitoring system for the Integral space telescope and a suite of growing client applications for MUST (Mission Utilities Support Tools). The research, development and validation activities at the Mission technologies office are performed together with a network of research institutes across Europe. The objective is narrowing the gap between enabling and innovative technology and space mission operations. The paper first addresses samples of technology infusion cases with their lessons learnt. The second part is focused on the process and the methodology used at the Mission technologies office to fulfill its objectives.

Optimization of Driving Styles for Fuel Economy Improvement

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

Malikopoulos, Andreas; Aguilar, Juan P.

2012-01-01

Modern vehicles have sophisticated electronic control units, particularly to control engine operation with respect to a balance between fuel economy, emissions, and power. These control units are designed for specific driving conditions and testing. However, each individual driving style is different and rarely meets those driving conditions. In the research reported here we investigate those driving style factors that have a major impact on fuel economy. An optimization framework is proposed with the aim of optimizing driving styles with respect to these driving factors. A set of polynomial metamodels are constructed to reflect the responses produced by changes of themore » driving factors. Then we compare the optimized driving styles to the original ones and evaluate the efficiency and effectiveness of the optimization formulation.« less

Peak-Seeking Control For Reduced Fuel Consumption: Flight-Test Results For The Full-Scale Advanced Systems Testbed FA-18 Airplane

NASA Technical Reports Server (NTRS)

Brown, Nelson

2013-01-01

A peak-seeking control algorithm for real-time trim optimization for reduced fuel consumption has been developed by researchers at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center to address the goals of the NASA Environmentally Responsible Aviation project to reduce fuel burn and emissions. The peak-seeking control algorithm is based on a steepest-descent algorithm using a time-varying Kalman filter to estimate the gradient of a performance function of fuel flow versus control surface positions. In real-time operation, deflections of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of an F/A-18 airplane are used for optimization of fuel flow. Results from six research flights are presented herein. The optimization algorithm found a trim configuration that required approximately 3 percent less fuel flow than the baseline trim at the same flight condition. This presentation also focuses on the design of the flight experiment and the practical challenges of conducting the experiment.

Bi-level Optimization Method of Air-conditioning System Based on Office Building Energy Storage Characteristics

NASA Astrophysics Data System (ADS)

Wang, Qingze; Chen, Xingying; Ji, Li; Liao, Yingchen; Yu, Kun

2017-05-01

The air-conditioning system of office building is a large power consumption terminal equipment, whose unreasonable operation mode leads to low energy efficiency. Realizing the optimization of the air-conditioning system has become one of the important research contents of the electric power demand response. In this paper, in order to save electricity cost and improve energy efficiency, bi-level optimization method of air-conditioning system based on TOU price is put forward by using the energy storage characteristics of the office building itself. In the upper level, the operation mode of the air-conditioning system is optimized in order to minimize the uses’ electricity cost in the premise of ensuring user’ comfort according to the information of outdoor temperature and TOU price, and the cooling load of the air-conditioning is output to the lower level; In the lower level, the distribution mode of cooling load among the multi chillers is optimized in order to maximize the energy efficiency according to the characteristics of each chiller. Finally, the experimental results under different modes demonstrate that the strategy can improve the energy efficiency of chillers and save the electricity cost for users.

Optimization of wastewater treatment plant operation for greenhouse gas mitigation.

PubMed

Kim, Dongwook; Bowen, James D; Ozelkan, Ertunga C

2015-11-01

This study deals with the determination of optimal operation of a wastewater treatment system for minimizing greenhouse gas emissions, operating costs, and pollution loads in the effluent. To do this, an integrated performance index that includes three objectives was established to assess system performance. The ASMN_G model was used to perform system optimization aimed at determining a set of operational parameters that can satisfy three different objectives. The complex nonlinear optimization problem was simulated using the Nelder-Mead Simplex optimization algorithm. A sensitivity analysis was performed to identify influential operational parameters on system performance. The results obtained from the optimization simulations for six scenarios demonstrated that there are apparent trade-offs among the three conflicting objectives. The best optimized system simultaneously reduced greenhouse gas emissions by 31%, reduced operating cost by 11%, and improved effluent quality by 2% compared to the base case operation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Naval Medical Research and Development News. Volume 8, Issue 7, July 2016

DTIC Science & Technology

2016-07-01

potent, broad-spectrum activity against microbial infections. AMPs display various antibacterial action mechanisms including membrane permeabilization...optimize the operational health and readiness of the nation’s armed forces. In proximity to more than 95,000 active duty service members, world-class...asymptomatic cases that go undetected by current surveillance activities . A recent collaboration between Navy Medicine researchers and partners in

Literature Survey on Operational Voltage Control and Reactive Power Management on Transmission and Sub-Transmission Networks

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

Elizondo, Marcelo A.; Samaan, Nader A.; Makarov, Yuri V.

Voltage and reactive power system control is generally performed following usual patterns of loads, based on off-line studies for daily and seasonal operations. This practice is currently challenged by the inclusion of distributed renewable generation, such as solar. There has been focus on resolving this problem at the distribution level; however, the transmission and sub-transmission levels have received less attention. This paper provides a literature review of proposed methods and solution approaches to coordinate and optimize voltage control and reactive power management, with an emphasis on applications at transmission and sub-transmission level. The conclusion drawn from the survey is thatmore » additional research is needed in the areas of optimizing switch shunt actions and coordinating all available resources to deal with uncertain patterns from increasing distributed renewable generation in the operational time frame. These topics are not deeply explored in the literature.« less

Research and application of borehole structure optimization based on pre-drill risk assessment

NASA Astrophysics Data System (ADS)

Zhang, Guohui; Liu, Xinyun; Chenrong; Hugui; Yu, Wenhua; Sheng, Yanan; Guan, Zhichuan

2017-11-01

Borehole structure design based on pre-drill risk assessment and considering risks related to drilling operation is the pre-condition for safe and smooth drilling operation. Major risks of drilling operation include lost circulation, blowout, sidewall collapsing, sticking and failure of drilling tools etc. In the study, studying data from neighboring wells was used to calculate the profile of formation pressure with credibility in the target well, then the borehole structure design for the target well assessment by using the drilling risk assessment to predict engineering risks before drilling. Finally, the prediction results were used to optimize borehole structure design to prevent such drilling risks. The newly-developed technique provides a scientific basis for lowering probability and frequency of drilling engineering risks, and shortening time required to drill a well, which is of great significance for safe and high-efficient drilling.

The optimization problems of CP operation

NASA Astrophysics Data System (ADS)

Kler, A. M.; Stepanova, E. L.; Maximov, A. S.

2017-11-01

The problem of enhancing energy and economic efficiency of CP is urgent indeed. One of the main methods for solving it is optimization of CP operation. To solve the optimization problems of CP operation, Energy Systems Institute, SB of RAS, has developed a software. The software makes it possible to make optimization calculations of CP operation. The software is based on the techniques and software tools of mathematical modeling and optimization of heat and power installations. Detailed mathematical models of new equipment have been developed in the work. They describe sufficiently accurately the processes that occur in the installations. The developed models include steam turbine models (based on the checking calculation) which take account of all steam turbine compartments and regeneration system. They also enable one to make calculations with regenerative heaters disconnected. The software for mathematical modeling of equipment and optimization of CP operation has been developed. It is based on the technique for optimization of CP operating conditions in the form of software tools and integrates them in the common user interface. The optimization of CP operation often generates the need to determine the minimum and maximum possible total useful electricity capacity of the plant at set heat loads of consumers, i.e. it is necessary to determine the interval on which the CP capacity may vary. The software has been applied to optimize the operating conditions of the Novo-Irkutskaya CP of JSC “Irkutskenergo”. The efficiency of operating condition optimization and the possibility for determination of CP energy characteristics that are necessary for optimization of power system operation are shown.

EPA Recognized for Research on Reducing Risks to Drinking ...

EPA Pesticide Factsheets

Technical Brief Threat Ensemble Vulnerability Assessment (TEVA) among finalists for Edelman Award On February 7, 2008, the Institute for Operations Research and the Management Sciences (INFORMS ® of Hanover, MD) announced that a TEVA Research project is one of six finalists vying for this year’s prestigious Franz Edelman Award. The project is called “Reducing Security Risks in American Drinking Water Systems.” Edelman Award Information This is the thirty-seventh year of the Edelman competition. Every year, the competition recognizes outstanding operations research-based projects that transform companies, entire industries, and people’s lives. Operations research uses advanced analytical methods to make optimal decisions in order to solve complex problems. The winner of the award will be announced in mid-April 2008. Past Edelman Award finalists include Travelocity; IBM; Merrill Lynch; the Memorial Sloan-Kettering Cancer Center; and Georgia Tech. The winning team for 2007 reduced both patient suffering and health care costs from the treatment of prostate and breast cancer. The Edelman competition attests to the contributions of operations research in the profit and nonprofit sectors. It is estimated that the cumulative dollar benefits from Edelman finalist projects between 1984 and 2006 reached the $100 billion mark. TEVA Research Program The TEVA research program has focused on reducing the security risks to drinking water systems. Ad

Performance Optimization of a Rotor Alone Nacelle for Acoustic Fan Testing

NASA Technical Reports Server (NTRS)

Cunningham, C. C.; Thompson, W. K.; Hughes, C. E.

2000-01-01

This paper describes the techniques, equipment, and results from the optimization of a two-axis traverse actuation system used to maintain concentricity between a sting-mounted fan and a wall-mounted nacelle in the 9 x 15 (9 Foot by 15 Foot Test Section) Low Speed Wind Tunnel (LSWT) at the NASA Glenn Research Center (GRC). The Rotor Alone Nacelle (RAN) system, developed at GRC by the Engineering Design and Analysis Division (EDAD) and the Acoustics Branch, used nacelle-mounted lasers and an automated control system to maintain concentricity as thermal and thrust operating loads displace the fan relative to the nacelle. This effort was critical to ensuring rig/facility safety and experimental consistency of the acoustic data from a statorless, externally supported nacelle configuration. Although the tip clearances were originally predicted to be about 0.020 in. at maximum rotor (fan) operating speed, proximity probe measurements showed that the nominal clearance was less than 0.004 in. As a result, the system was optimized through control-loop modifications, active laser cooling, data filtering and averaging, and the development of strict operational procedures. The resultant concentricity error of RAN was reduced to +/- 0.0031 in. in the Y-direction (horizontal) and +0.0035 in./-0.001 3 in. in the Z-direction (vertical), as determined by error analysis and experimental results. Based on the success of this project, the RAN system will be transitioned to other wind tunnel research programs at NASA GRC.

Efficient droplet router for digital microfluidic biochip using particle swarm optimizer

NASA Astrophysics Data System (ADS)

Pan, Indrajit; Samanta, Tuhina

2013-01-01

Digital Microfluidic Biochip has emerged as a revolutionary finding in the field of micro-electromechanical research. Different complex bioassays and pathological analysis are being efficiently performed on this miniaturized chip with negligible amount of sample specimens. Initially biochip was invented on continuous-fluid-flow mechanism but later it has evolved with more efficient concept of digital-fluid-flow. These second generation biochips are capable of serving more complex bioassays. This operational change in biochip technology emerged with the requirement of high end computer aided design needs for physical design automation. The change also paved new avenues of research to assist the proficient design automation. Droplet routing is one of those major aspects where it necessarily requires minimization of both routing completion time and total electrode usage. This task involves optimization of multiple associated parameters. In this paper we have proposed a particle swarm optimization based approach for droplet outing. The process mainly operates in two phases where initially we perform clustering of state space and classification of nets into designated clusters. This helps us to reduce solution space by redefining local sub optimal target in the interleaved space between source and global target of a net. In the next phase we resolve the concurrent routing issues of every sub optimal situation to generate final routing schedule. The method was applied on some standard test benches and hard test sets. Comparative analysis of experimental results shows good improvement on the aspect of unit cell usage, routing completion time and execution time over some well existing methods.

Circadian rhythms, sleep, and performance in space.

PubMed

Mallis, M M; DeRoshia, C W

2005-06-01

Maintaining optimal alertness and neurobehavioral functioning during space operations is critical to enable the National Aeronautics and Space Administration's (NASA's) vision "to extend humanity's reach to the Moon, Mars and beyond" to become a reality. Field data have demonstrated that sleep times and performance of crewmembers can be compromised by extended duty days, irregular work schedules, high workload, and varying environmental factors. This paper documents evidence of significant sleep loss and disruption of circadian rhythms in astronauts and associated performance decrements during several space missions, which demonstrates the need to develop effective countermeasures. Both sleep and circadian disruptions have been identified in the Behavioral Health and Performance (BH&P) area and the Advanced Human Support Technology (AHST) area of NASA's Bioastronautics Critical Path Roadmap. Such disruptions could have serious consequences on the effectiveness, health, and safety of astronaut crews, thus reducing the safety margin and increasing the chances of an accident or incident. These decrements oftentimes can be difficult to detect and counter effectively in restrictive operational environments. NASA is focusing research on the development of optimal sleep/wake schedules and countermeasure timing and application to help mitigate the cumulative effects of sleep and circadian disruption and enhance operational performance. Investing research in humans is one of NASA's building blocks that will allow for both short- and long-duration space missions and help NASA in developing approaches to manage and overcome the human limitations of space travel. In addition to reviewing the current state of knowledge concerning sleep and circadian disruptions during space operations, this paper provides an overview of NASA's broad research goals. Also, NASA-funded research, designed to evaluate the relationships between sleep quality, circadian rhythm stability, and performance proficiency in both ground-based simulations and space mission studies, as described in the 2003 NASA Task Book, will be reviewed.

Circadian rhythms, sleep, and performance in space

NASA Technical Reports Server (NTRS)

Mallis, M. M.; DeRoshia, C. W.

2005-01-01

Maintaining optimal alertness and neurobehavioral functioning during space operations is critical to enable the National Aeronautics and Space Administration's (NASA's) vision "to extend humanity's reach to the Moon, Mars and beyond" to become a reality. Field data have demonstrated that sleep times and performance of crewmembers can be compromised by extended duty days, irregular work schedules, high workload, and varying environmental factors. This paper documents evidence of significant sleep loss and disruption of circadian rhythms in astronauts and associated performance decrements during several space missions, which demonstrates the need to develop effective countermeasures. Both sleep and circadian disruptions have been identified in the Behavioral Health and Performance (BH&P) area and the Advanced Human Support Technology (AHST) area of NASA's Bioastronautics Critical Path Roadmap. Such disruptions could have serious consequences on the effectiveness, health, and safety of astronaut crews, thus reducing the safety margin and increasing the chances of an accident or incident. These decrements oftentimes can be difficult to detect and counter effectively in restrictive operational environments. NASA is focusing research on the development of optimal sleep/wake schedules and countermeasure timing and application to help mitigate the cumulative effects of sleep and circadian disruption and enhance operational performance. Investing research in humans is one of NASA's building blocks that will allow for both short- and long-duration space missions and help NASA in developing approaches to manage and overcome the human limitations of space travel. In addition to reviewing the current state of knowledge concerning sleep and circadian disruptions during space operations, this paper provides an overview of NASA's broad research goals. Also, NASA-funded research, designed to evaluate the relationships between sleep quality, circadian rhythm stability, and performance proficiency in both ground-based simulations and space mission studies, as described in the 2003 NASA Task Book, will be reviewed.

Innovative Method of Analysis of Actual Cost of Work in Progress

NASA Astrophysics Data System (ADS)

Fil, O.; Terentev, V.

2017-11-01

The article focuses on the basic theory and practical aspects of improving the strategic management in terms of enhancing the quality of a technological process: these aspects have been proven experimentally by their introduction in company operations. The authors have worked out some proposals aimed at selecting an optimal supplier for building companies as well as the algorithm for the analysis and optimization of a construction company basing on scientific and practical research and the experimental data obtained in the experiment

Air breathing engine/rocket trajectory optimization

NASA Technical Reports Server (NTRS)

Smith, V. K., III

1979-01-01

This research has focused on improving the mathematical models of the air-breathing propulsion systems, which can be mated with the rocket engine model and incorporated in trajectory optimization codes. Improved engine simulations provided accurate representation of the complex cycles proposed for advanced launch vehicles, thereby increasing the confidence in propellant use and payload calculations. The versatile QNEP (Quick Navy Engine Program) was modified to allow treatment of advanced turboaccelerator cycles using hydrogen or hydrocarbon fuels and operating in the vehicle flow field.

Command History Calendar Year 1992 (Navy Personnel Research and Development Center)

DTIC Science & Technology

1993-07-01

efficiently. and manage our personnel resources optimally. By combining a deep understanding of operational requirements with first-rate scientific and...the needs of manpower, personnel, and training managers in the Navy, Marine Corps, and Department of Defense (DOD); to the operating forces; and to the...NPRDC Professional Publications Award and the 1990 Commander’s Award for Management Excellence. He is a fellow of the American Association for the

Extensions of algebraic image operators: An approach to model-based vision

NASA Technical Reports Server (NTRS)

Lerner, Bao-Ting; Morelli, Michael V.

1990-01-01

Researchers extend their previous research on a highly structured and compact algebraic representation of grey-level images which can be viewed as fuzzy sets. Addition and multiplication are defined for the set of all grey-level images, which can then be described as polynomials of two variables. Utilizing this new algebraic structure, researchers devised an innovative, efficient edge detection scheme. An accurate method for deriving gradient component information from this edge detector is presented. Based upon this new edge detection system researchers developed a robust method for linear feature extraction by combining the techniques of a Hough transform and a line follower. The major advantage of this feature extractor is its general, object-independent nature. Target attributes, such as line segment lengths, intersections, angles of intersection, and endpoints are derived by the feature extraction algorithm and employed during model matching. The algebraic operators are global operations which are easily reconfigured to operate on any size or shape region. This provides a natural platform from which to pursue dynamic scene analysis. A method for optimizing the linear feature extractor which capitalizes on the spatially reconfiguration nature of the edge detector/gradient component operator is discussed.

New knowledge-based genetic algorithm for excavator boom structural optimization

NASA Astrophysics Data System (ADS)

Hua, Haiyan; Lin, Shuwen

2014-03-01

Due to the insufficiency of utilizing knowledge to guide the complex optimal searching, existing genetic algorithms fail to effectively solve excavator boom structural optimization problem. To improve the optimization efficiency and quality, a new knowledge-based real-coded genetic algorithm is proposed. A dual evolution mechanism combining knowledge evolution with genetic algorithm is established to extract, handle and utilize the shallow and deep implicit constraint knowledge to guide the optimal searching of genetic algorithm circularly. Based on this dual evolution mechanism, knowledge evolution and population evolution can be connected by knowledge influence operators to improve the configurability of knowledge and genetic operators. Then, the new knowledge-based selection operator, crossover operator and mutation operator are proposed to integrate the optimal process knowledge and domain culture to guide the excavator boom structural optimization. Eight kinds of testing algorithms, which include different genetic operators, are taken as examples to solve the structural optimization of a medium-sized excavator boom. By comparing the results of optimization, it is shown that the algorithm including all the new knowledge-based genetic operators can more remarkably improve the evolutionary rate and searching ability than other testing algorithms, which demonstrates the effectiveness of knowledge for guiding optimal searching. The proposed knowledge-based genetic algorithm by combining multi-level knowledge evolution with numerical optimization provides a new effective method for solving the complex engineering optimization problem.

Minimal investment risk of a portfolio optimization problem with budget and investment concentration constraints

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2017-02-01

In the present paper, the minimal investment risk for a portfolio optimization problem with imposed budget and investment concentration constraints is considered using replica analysis. Since the minimal investment risk is influenced by the investment concentration constraint (as well as the budget constraint), it is intuitive that the minimal investment risk for the problem with an investment concentration constraint can be larger than that without the constraint (that is, with only the budget constraint). Moreover, a numerical experiment shows the effectiveness of our proposed analysis. In contrast, the standard operations research approach failed to identify accurately the minimal investment risk of the portfolio optimization problem.

First-order design of geodetic networks using the simulated annealing method

NASA Astrophysics Data System (ADS)

Berné, J. L.; Baselga, S.

2004-09-01

The general problem of the optimal design for a geodetic network subject to any extrinsic factors, namely the first-order design problem, can be dealt with as a numeric optimization problem. The classic theory of this problem and the optimization methods are revised. Then the innovative use of the simulated annealing method, which has been successfully applied in other fields, is presented for this classical geodetic problem. This method, belonging to iterative heuristic techniques in operational research, uses a thermodynamical analogy to crystalline networks to offer a solution that converges probabilistically to the global optimum. Basic formulation and some examples are studied.

Operations research investigations of satellite power stations

NASA Technical Reports Server (NTRS)

Cole, J. W.; Ballard, J. L.

1976-01-01

A systems model reflecting the design concepts of Satellite Power Stations (SPS) was developed. The model is of sufficient scope to include the interrelationships of the following major design parameters: the transportation to and between orbits; assembly of the SPS; and maintenance of the SPS. The systems model is composed of a set of equations that are nonlinear with respect to the system parameters and decision variables. The model determines a figure of merit from which alternative concepts concerning transportation, assembly, and maintenance of satellite power stations are studied. A hybrid optimization model was developed to optimize the system's decision variables. The optimization model consists of a random search procedure and the optimal-steepest descent method. A FORTRAN computer program was developed to enable the user to optimize nonlinear functions using the model. Specifically, the computer program was used to optimize Satellite Power Station system components.

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.

Economic optimization of operations for hybrid energy systems under variable markets

DOE PAGES

Chen, Jen; Garcia, Humberto E.

2016-05-21

We prosed a hybrid energy systems (HES) which is an important element to enable increasing penetration of clean energy. Our paper investigates the operations flexibility of HES, and develops a methodology for operations optimization for maximizing economic value based on predicted renewable generation and market information. A multi-environment computational platform for performing such operations optimization is also developed. In order to compensate for prediction error, a control strategy is accordingly designed to operate a standby energy storage element (ESE) to avoid energy imbalance within HES. The proposed operations optimizer allows systematic control of energy conversion for maximal economic value. Simulationmore » results of two specific HES configurations are included to illustrate the proposed methodology and computational capability. These results demonstrate the economic viability of HES under proposed operations optimizer, suggesting the diversion of energy for alternative energy output while participating in the ancillary service market. Economic advantages of such operations optimizer and associated flexible operations are illustrated by comparing the economic performance of flexible operations against that of constant operations. Sensitivity analysis with respect to market variability and prediction error, are also performed.« less

Economic optimization of operations for hybrid energy systems under variable markets

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

Chen, Jen; Garcia, Humberto E.

We prosed a hybrid energy systems (HES) which is an important element to enable increasing penetration of clean energy. Our paper investigates the operations flexibility of HES, and develops a methodology for operations optimization for maximizing economic value based on predicted renewable generation and market information. A multi-environment computational platform for performing such operations optimization is also developed. In order to compensate for prediction error, a control strategy is accordingly designed to operate a standby energy storage element (ESE) to avoid energy imbalance within HES. The proposed operations optimizer allows systematic control of energy conversion for maximal economic value. Simulationmore » results of two specific HES configurations are included to illustrate the proposed methodology and computational capability. These results demonstrate the economic viability of HES under proposed operations optimizer, suggesting the diversion of energy for alternative energy output while participating in the ancillary service market. Economic advantages of such operations optimizer and associated flexible operations are illustrated by comparing the economic performance of flexible operations against that of constant operations. Sensitivity analysis with respect to market variability and prediction error, are also performed.« less

Energy-Water Microgrid Case Study at the University of Arizona's BioSphere 2

NASA Astrophysics Data System (ADS)

Daw, J.; Macknick, J.; Kandt, A.; Giraldez, J.

2016-12-01

Microgrids can provide reliable and cost-effective energy services in a variety of conditions and locations. To date, there has been minimal effort invested in developing energy-water microgrids that demonstrate the feasibility and leverage the synergies associated with designing and operating renewable energy and water systems in a coordinated framework. Water and wastewater treatment equipment can be operated in ways to provide ancillary services to the electrical grid and renewable energy can be utilized to power water-related infrastructure, but the potential for co-managed systems has not yet been quantified or fully characterized. Co-management and optimization of energy and water resources could lead to improved reliability and economic operating conditions. Energy-water microgrids could be a promising solution to improve energy and water resource management for islands, rural communities, distributed generation, Defense operations, and many parts of the world lacking critical infrastructure.The National Renewable Energy Laboratory (NREL) and the University of Arizona have been jointly researching energy-water microgrid opportunities through an effort at the university's BioSphere 2 (B2) Earth systems science research facility. B2 is an ideal case study for an energy-water microgrid test site, given its size, its unique mission and operations, the existence and criticality of water and energy infrastructure, and its ability to operate connected-to or disconnected-from the local electrical grid. Moreover, the B2 is a premier facility for undertaking agricultural research, providing an excellent opportunity to evaluate connections and tradeoffs in the food-energy-water nexus. The research effort at B2 identified the technical potential and associated benefits of an energy-water microgrid through the evaluation of energy ancillary services and peak load reductions and quantified the potential for B2 water-related loads to be utilized and modified to provide grid services in the context of an optimized energy-water microgrid. The foundational work performed at B2 also serves a model that can be built upon for identifying relevant energy-water microgrid data, analytical requirements, and operational challenges associated with development of future energy-water microgrids.

Soil bed reactor work of the Environmental Research Lab. of the University of Arizona in support of the research and development of Biosphere 2

NASA Technical Reports Server (NTRS)

Frye, Robert

1990-01-01

Research at the Environmental Research Lab in support of Biosphere 2 was both basic and applied in nature. One aspect of the applied research involved the use of biological reactors for the scrubbing of trace atmospheric organic contaminants. The research involved a quantitative study of the efficiency of operation of Soil Bed Reactors (SBR) and the optimal operating conditions for contaminant removal. The basic configuration of a SBR is that air is moved through a living soil that supports a population of plants. Upon exposure to the soil, contaminants are either passively adsorbed onto the surface of soil particles, chemically transformed in the soil to usable compounds that are taken up by the plants or microbes as a metabolic energy source and converted to CO2 and water.

Neural network based optimal control of HVAC&R systems

NASA Astrophysics Data System (ADS)

Ning, Min

Heating, Ventilation, Air-Conditioning and Refrigeration (HVAC&R) systems have wide applications in providing a desired indoor environment for different types of buildings. It is well acknowledged that 30%-40% of the total energy generated is consumed by buildings and HVAC&R systems alone account for more than 50% of the building energy consumption. Low operational efficiency especially under partial load conditions and poor control are part of reasons for such high energy consumption. To improve energy efficiency, HVAC&R systems should be properly operated to maintain a comfortable and healthy indoor environment under dynamic ambient and indoor conditions with the least energy consumption. This research focuses on the optimal operation of HVAC&R systems. The optimization problem is formulated and solved to find the optimal set points for the chilled water supply temperature, discharge air temperature and AHU (air handling unit) fan static pressure such that the indoor environment is maintained with the least chiller and fan energy consumption. To achieve this objective, a dynamic system model is developed first to simulate the system behavior under different control schemes and operating conditions. The system model is modular in structure, which includes a water-cooled vapor compression chiller model and a two-zone VAV system model. A fuzzy-set based extended transformation approach is then applied to investigate the uncertainties of this model caused by uncertain parameters and the sensitivities of the control inputs with respect to the interested model outputs. A multi-layer feed forward neural network is constructed and trained in unsupervised mode to minimize the cost function which is comprised of overall energy cost and penalty cost when one or more constraints are violated. After training, the network is implemented as a supervisory controller to compute the optimal settings for the system. In order to implement the optimal set points predicted by the supervisory controller, a set of five adaptive PI (proportional-integral) controllers are designed for each of the five local control loops of the HVAC&R system. The five controllers are used to track optimal set points and zone air temperature set points. Parameters of these PI controllers are tuned online to reduce tracking errors. The updating rules are derived from Lyapunov stability analysis. Simulation results show that compared to the conventional night reset operation scheme, the optimal operation scheme saves around 10% energy under full load condition and 19% energy under partial load conditions.

Parametric Optimization of Some Critical Operating System Functions--An Alternative Approach to the Study of Operating Systems Design

ERIC Educational Resources Information Center

Sobh, Tarek M.; Tibrewal, Abhilasha

2006-01-01

Operating systems theory primarily concentrates on the optimal use of computing resources. This paper presents an alternative approach to teaching and studying operating systems design and concepts by way of parametrically optimizing critical operating system functions. Detailed examples of two critical operating systems functions using the…

Optimization of life support systems and their systems reliability

NASA Technical Reports Server (NTRS)

Fan, L. T.; Hwang, C. L.; Erickson, L. E.

1971-01-01

The identification, analysis, and optimization of life support systems and subsystems have been investigated. For each system or subsystem that has been considered, the procedure involves the establishment of a set of system equations (or mathematical model) based on theory and experimental evidences; the analysis and simulation of the model; the optimization of the operation, control, and reliability; analysis of sensitivity of the system based on the model; and, if possible, experimental verification of the theoretical and computational results. Research activities include: (1) modeling of air flow in a confined space; (2) review of several different gas-liquid contactors utilizing centrifugal force: (3) review of carbon dioxide reduction contactors in space vehicles and other enclosed structures: (4) application of modern optimal control theory to environmental control of confined spaces; (5) optimal control of class of nonlinear diffusional distributed parameter systems: (6) optimization of system reliability of life support systems and sub-systems: (7) modeling, simulation and optimal control of the human thermal system: and (8) analysis and optimization of the water-vapor eletrolysis cell.

Transportation Deployment Support | Transportation Research | NREL

Science.gov Websites

initiative complements the NPS Climate Friendly Parks program. Commercial Fleets Through the National Clean clearinghouse of medium- and heavy-duty commercial fleet vehicle operating data for optimizing vehicle improvement. Commercial Vehicle Technology Evaluations NREL conducts real-world evaluations of commercial

HyPEP FY06 Report: Models and Methods

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

DOE report

2006-09-01

The Department of Energy envisions the next generation very high-temperature gas-cooled reactor (VHTR) as a single-purpose or dual-purpose facility that produces hydrogen and electricity. The Ministry of Science and Technology (MOST) of the Republic of Korea also selected VHTR for the Nuclear Hydrogen Development and Demonstration (NHDD) Project. This research project aims at developing a user-friendly program for evaluating and optimizing cycle efficiencies of producing hydrogen and electricity in a Very-High-Temperature Reactor (VHTR). Systems for producing electricity and hydrogen are complex and the calculations associated with optimizing these systems are intensive, involving a large number of operating parameter variations andmore » many different system configurations. This research project will produce the HyPEP computer model, which is specifically designed to be an easy-to-use and fast running tool for evaluating nuclear hydrogen and electricity production facilities. The model accommodates flexible system layouts and its cost models will enable HyPEP to be well-suited for system optimization. Specific activities of this research are designed to develop the HyPEP model into a working tool, including (a) identifying major systems and components for modeling, (b) establishing system operating parameters and calculation scope, (c) establishing the overall calculation scheme, (d) developing component models, (e) developing cost and optimization models, and (f) verifying and validating the program. Once the HyPEP model is fully developed and validated, it will be used to execute calculations on candidate system configurations. FY-06 report includes a description of reference designs, methods used in this study, models and computational strategies developed for the first year effort. Results from computer codes such as HYSYS and GASS/PASS-H used by Idaho National Laboratory and Argonne National Laboratory, respectively will be benchmarked with HyPEP results in the following years.« less

Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining.

PubMed

Salehi, Mojtaba; Bahreininejad, Ardeshir

2011-08-01

Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously.

Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining

PubMed Central

Salehi, Mojtaba

2010-01-01

Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously. PMID:21845020

Research and application of key technology of electric submersible plunger pump

NASA Astrophysics Data System (ADS)

Qian, K.; Sun, Y. N.; Zheng, S.; Du, W. S.; Li, J. N.; Pei, G. Z.; Gao, Y.; Wu, N.

2018-06-01

Electric submersible plunger pump is a new generation of rodless oil production equipment, whose improvements and upgrades of key technologies are conducive to its large-scale application and reduce the cost and improve the efficiency. In this paper, the operating mechanism of the unit in-depth study, aimed at the problems existing in oilfield production, to propose an optimization method creatively, including the optimal design of a linear motor for submersible oil, development of new double-acting load-relief pump, embedded flexible closed-loop control technology, research and development of low-cost power cables. 90 oil wells were used on field application, the average pump inspection cycle is 608 days, the longest pump check cycle has exceeded 1037 days, the average power saving rate is 45.6%. Application results show that the new technology of optimization and upgrading can further improve the reliability and adaptability of electric submersible plunger pump, reduce the cost of investment.

Data-based adjoint and H2 optimal control of the Ginzburg-Landau equation

NASA Astrophysics Data System (ADS)

Banks, Michael; Bodony, Daniel

2017-11-01

Equation-free, reduced-order methods of control are desirable when the governing system of interest is of very high dimension or the control is to be applied to a physical experiment. Two-phase flow optimal control problems, our target application, fit these criteria. Dynamic Mode Decomposition (DMD) is a data-driven method for model reduction that can be used to resolve the dynamics of very high dimensional systems and project the dynamics onto a smaller, more manageable basis. We evaluate the effectiveness of DMD-based forward and adjoint operator estimation when applied to H2 optimal control approaches applied to the linear and nonlinear Ginzburg-Landau equation. Perspectives on applying the data-driven adjoint to two phase flow control will be given. Office of Naval Research (ONR) as part of the Multidisciplinary University Research Initiatives (MURI) Program, under Grant Number N00014-16-1-2617.

CFD research, parallel computation and aerodynamic optimization

NASA Technical Reports Server (NTRS)

Ryan, James S.

1995-01-01

Over five years of research in Computational Fluid Dynamics and its applications are covered in this report. Using CFD as an established tool, aerodynamic optimization on parallel architectures is explored. The objective of this work is to provide better tools to vehicle designers. Submarine design requires accurate force and moment calculations in flow with thick boundary layers and large separated vortices. Low noise production is critical, so flow into the propulsor region must be predicted accurately. The High Speed Civil Transport (HSCT) has been the subject of recent work. This vehicle is to be a passenger vehicle with the capability of cutting overseas flight times by more than half. A successful design must surpass the performance of comparable planes. Fuel economy, other operational costs, environmental impact, and range must all be improved substantially. For all these reasons, improved design tools are required, and these tools must eventually integrate optimization, external aerodynamics, propulsion, structures, heat transfer and other disciplines.

Application of Spatial Neural Network Model for Optimal Operation of Urban Drainage System

NASA Astrophysics Data System (ADS)

KIM, B. J.; Lee, J. Y.; KIM, H. I.; Son, A. L.; Han, K. Y.

2017-12-01

The significance of real-time operation of drainage pump and warning system for inundation becomes recently increased in order to coping with runoff by high intensity precipitation such as localized heavy rain that frequently and suddenly happen. However existing operation of drainage pump station has been made a decision according to opinion of manager based on stage because of not expecting exact time that peak discharge occur in pump station. Therefore the scale of pump station has been excessively estimated. Although it is necessary to perform quick and accurate inundation in analysis downtown area due to huge property damage from flood and typhoon, previous studies contained risk deducting incorrect result that differs from actual result owing to the diffusion aspect of flow by effect on building and road. The purpose of this study is to develop the data driven model for the real-time operation of drainage pump station and two-dimensional inundation analysis that are improved the problems of the existing hydrology and hydrological model. Neuro-Fuzzy system for real time prediction about stage was developed by estimating the type and number of membership function. Based on forecasting stage, it was decided when pump machine begin to work and how much water scoop up by using penalizing genetic algorithm. It is practicable to forecast stage, optimize pump operation and simulate inundation analysis in real time through the methodologies suggested in this study. This study can greatly contribute to the establishment of disaster information map that prevent and mitigate inundation in urban drainage area. The applicability of the development model for the five drainage pump stations in the Mapo drainage area was verified. It is considered to be able to effectively manage urban drainage facilities in the development of these operating rules. Keywords : Urban flooding; Geo-ANFIS method; Optimal operation; Drainage system; AcknowlegementThis research was supported by a grant (17AWMP-B079625-04) from Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Optimization problems in natural gas transportation systems. A state-of-the-art review

DOE PAGES

Ríos-Mercado, Roger Z.; Borraz-Sánchez, Conrado

2015-03-24

Our paper provides a review on the most relevant research works conducted to solve natural gas transportation problems via pipeline systems. The literature reveals three major groups of gas pipeline systems, namely gathering, transmission, and distribution systems. In this work, we aim at presenting a detailed discussion of the efforts made in optimizing natural gas transmission lines.There is certainly a vast amount of research done over the past few years on many decision-making problems in the natural gas industry and, specifically, in pipeline network optimization. In this work, we present a state-of-the-art survey focusing on specific categories that include short-termmore » basis storage (line-packing problems), gas quality satisfaction (pooling problems), and compressor station modeling (fuel cost minimization problems). We also discuss both steady-state and transient optimization models highlighting the modeling aspects and the most relevant solution approaches known to date. Although the literature on natural gas transmission system problems is quite extensive, this is, to the best of our knowledge, the first comprehensive review or survey covering this specific research area on natural gas transmission from an operations research perspective. Furthermore, this paper includes a discussion of the most important and promising research areas in this field. Hence, our paper can serve as a useful tool to gain insight into the evolution of the many real-life applications and most recent advances in solution methodologies arising from this exciting and challenging research area of decision-making problems.« less

Optimization problems in natural gas transportation systems. A state-of-the-art review

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

Ríos-Mercado, Roger Z.; Borraz-Sánchez, Conrado

Our paper provides a review on the most relevant research works conducted to solve natural gas transportation problems via pipeline systems. The literature reveals three major groups of gas pipeline systems, namely gathering, transmission, and distribution systems. In this work, we aim at presenting a detailed discussion of the efforts made in optimizing natural gas transmission lines.There is certainly a vast amount of research done over the past few years on many decision-making problems in the natural gas industry and, specifically, in pipeline network optimization. In this work, we present a state-of-the-art survey focusing on specific categories that include short-termmore » basis storage (line-packing problems), gas quality satisfaction (pooling problems), and compressor station modeling (fuel cost minimization problems). We also discuss both steady-state and transient optimization models highlighting the modeling aspects and the most relevant solution approaches known to date. Although the literature on natural gas transmission system problems is quite extensive, this is, to the best of our knowledge, the first comprehensive review or survey covering this specific research area on natural gas transmission from an operations research perspective. Furthermore, this paper includes a discussion of the most important and promising research areas in this field. Hence, our paper can serve as a useful tool to gain insight into the evolution of the many real-life applications and most recent advances in solution methodologies arising from this exciting and challenging research area of decision-making problems.« less

Algorithms for optimization of the transport system in living and artificial cells.

PubMed

Melkikh, A V; Sutormina, M I

2011-06-01

An optimization of the transport system in a cell has been considered from the viewpoint of the operations research. Algorithms for an optimization of the transport system of a cell in terms of both the efficiency and a weak sensitivity of a cell to environmental changes have been proposed. The switching of various systems of transport is considered as the mechanism of weak sensitivity of a cell to changes in environment. The use of the algorithms for an optimization of a cardiac cell has been considered by way of example. We received theoretically for a cell of a cardiac muscle that at the increase of potassium concentration in the environment switching of transport systems for this ion takes place. This conclusion qualitatively coincides with experiments. The problem of synthesizing an optimal system in an artificial cell has been stated.

Golden Rays - July 2017 | Solar Research | Solar Research | NREL

Science.gov Websites

Operator, First Solar, and NREL tested a 300-MW PV plant to demonstrate that, with proper controls, PV can technique to measure charge-carrier transport in PV materials. Solar Plus: A Holistic Approach to Distribution Solar PV By optimizing how PV interacts with other electricity loads at the household- and grid

Can modeling of HIV treatment processes improve outcomes? Capitalizing on an operations research approach to the global pandemic

PubMed Central

Xiong, Wei; Hupert, Nathaniel; Hollingsworth, Eric B; O'Brien, Megan E; Fast, Jessica; Rodriguez, William R

2008-01-01

Background Mathematical modeling has been applied to a range of policy-level decisions on resource allocation for HIV care and treatment. We describe the application of classic operations research (OR) techniques to address logistical and resource management challenges in HIV treatment scale-up activities in resource-limited countries. Methods We review and categorize several of the major logistical and operational problems encountered over the last decade in the global scale-up of HIV care and antiretroviral treatment for people with AIDS. While there are unique features of HIV care and treatment that pose significant challenges to effective modeling and service improvement, we identify several analogous OR-based solutions that have been developed in the service, industrial, and health sectors. Results HIV treatment scale-up includes many processes that are amenable to mathematical and simulation modeling, including forecasting future demand for services; locating and sizing facilities for maximal efficiency; and determining optimal staffing levels at clinical centers. Optimization of clinical and logistical processes through modeling may improve outcomes, but successful OR-based interventions will require contextualization of response strategies, including appreciation of both existing health care systems and limitations in local health workforces. Conclusion The modeling techniques developed in the engineering field of operations research have wide potential application to the variety of logistical problems encountered in HIV treatment scale-up in resource-limited settings. Increasing the number of cross-disciplinary collaborations between engineering and public health will help speed the appropriate development and application of these tools. PMID:18680594

Free-form Airfoil Shape Optimization Under Uncertainty Using Maximum Expected Value and Second-order Second-moment Strategies

NASA Technical Reports Server (NTRS)

Huyse, Luc; Bushnell, Dennis M. (Technical Monitor)

2001-01-01

Free-form shape optimization of airfoils poses unexpected difficulties. Practical experience has indicated that a deterministic optimization for discrete operating conditions can result in dramatically inferior performance when the actual operating conditions are different from the - somewhat arbitrary - design values used for the optimization. Extensions to multi-point optimization have proven unable to adequately remedy this problem of "localized optimization" near the sampled operating conditions. This paper presents an intrinsically statistical approach and demonstrates how the shortcomings of multi-point optimization with respect to "localized optimization" can be overcome. The practical examples also reveal how the relative likelihood of each of the operating conditions is automatically taken into consideration during the optimization process. This is a key advantage over the use of multipoint methods.

Theory, Design, and Algorithms for Optimal Control of wireless Networks

DTIC Science & Technology

2010-06-09

The implementation of network-centric warfare technologies is an abiding, critical interest of Air Force Science and Technology efforts for the Warfighter. Wireless communications, strategic signaling are areas of critical Air Force Mission need. Autonomous networks of multiple, heterogeneous Throughput enhancement and robust connectivity in communications and sensor networks are critical factors in net-centric USAF operations. This research directly supports the Air Force vision of information dominance and the development of anywhere, anytime operational readiness.

Preliminary analysis of posttraumatic stress disorder screening within specialty clinic setting for OIF/OEF veterans seeking care for neck or back pain.

PubMed

Dunn, Andrew S; Julian, Terri; Formolo, Lance R; Green, Bart N; Chicoine, David R

2011-01-01

Escalating prevalence estimates of posttraumatic stress disorder (PTSD) among recently returning Operation Iraqi Freedom/Operation Enduring Freedom (OIF/OEF) veterans highlight the need for early detection and management for reducing chronic mental illness and disability. Because PTSD and chronic pain are common comorbid conditions among veterans, PTSD screening within specialty clinic settings addressing musculoskeletal pain may be of value. This retrospective study evaluated measures of diagnostic value for the PTSD Checklist (PCL) for a sample (n = 79) of OIF/OEF veterans seeking care for neck or back pain within a Department of Veterans Affairs specialty clinic. Because published accounts of optimal PCL cutoff scores vary considerably, we used receiver operating characteristic curves to identify whether the optimal PCL cutoff score for the sample differed from a conventional cutoff score of 50. A clinical psychologist experienced in diagnosing and managing PTSD confirmed the diagnosis of PTSD for 37 veterans through a review of clinical records. The prevalence of diagnosed PTSD was 46.8%, with an optimal PCL cutoff score of 44. These findings may guide future research and influence clinical practice regarding PTSD screening for recently returning veterans with chronic pain.

The Improvement of Particle Swarm Optimization: a Case Study of Optimal Operation in Goupitan Reservoir

NASA Astrophysics Data System (ADS)

Li, Haichen; Qin, Tao; Wang, Weiping; Lei, Xiaohui; Wu, Wenhui

2018-02-01

Due to the weakness in holding diversity and reaching global optimum, the standard particle swarm optimization has not performed well in reservoir optimal operation. To solve this problem, this paper introduces downhill simplex method to work together with the standard particle swarm optimization. The application of this approach in Goupitan reservoir optimal operation proves that the improved method had better accuracy and higher reliability with small investment.

Design and development of bio-inspired framework for reservoir operation optimization

NASA Astrophysics Data System (ADS)

Asvini, M. Sakthi; Amudha, T.

2017-12-01

Frameworks for optimal reservoir operation play an important role in the management of water resources and delivery of economic benefits. Effective utilization and conservation of water from reservoirs helps to manage water deficit periods. The main challenge in reservoir optimization is to design operating rules that can be used to inform real-time decisions on reservoir release. We develop a bio-inspired framework for the optimization of reservoir release to satisfy the diverse needs of various stakeholders. In this work, single-objective optimization and multiobjective optimization problems are formulated using an algorithm known as "strawberry optimization" and tested with actual reservoir data. Results indicate that well planned reservoir operations lead to efficient deployment of the reservoir water with the help of optimal release patterns.

A Mixed Integer Efficient Global Optimization Framework: Applied to the Simultaneous Aircraft Design, Airline Allocation and Revenue Management Problem

NASA Astrophysics Data System (ADS)

Roy, Satadru

Traditional approaches to design and optimize a new system, often, use a system-centric objective and do not take into consideration how the operator will use this new system alongside of other existing systems. This "hand-off" between the design of the new system and how the new system operates alongside other systems might lead to a sub-optimal performance with respect to the operator-level objective. In other words, the system that is optimal for its system-level objective might not be best for the system-of-systems level objective of the operator. Among the few available references that describe attempts to address this hand-off, most follow an MDO-motivated subspace decomposition approach of first designing a very good system and then provide this system to the operator who decides the best way to use this new system along with the existing systems. The motivating example in this dissertation presents one such similar problem that includes aircraft design, airline operations and revenue management "subspaces". The research here develops an approach that could simultaneously solve these subspaces posed as a monolithic optimization problem. The monolithic approach makes the problem a Mixed Integer/Discrete Non-Linear Programming (MINLP/MDNLP) problem, which are extremely difficult to solve. The presence of expensive, sophisticated engineering analyses further aggravate the problem. To tackle this challenge problem, the work here presents a new optimization framework that simultaneously solves the subspaces to capture the "synergism" in the problem that the previous decomposition approaches may not have exploited, addresses mixed-integer/discrete type design variables in an efficient manner, and accounts for computationally expensive analysis tools. The framework combines concepts from efficient global optimization, Kriging partial least squares, and gradient-based optimization. This approach then demonstrates its ability to solve an 11 route airline network problem consisting of 94 decision variables including 33 integer and 61 continuous type variables. This application problem is a representation of an interacting group of systems and provides key challenges to the optimization framework to solve the MINLP problem, as reflected by the presence of a moderate number of integer and continuous type design variables and expensive analysis tool. The result indicates simultaneously solving the subspaces could lead to significant improvement in the fleet-level objective of the airline when compared to the previously developed sequential subspace decomposition approach. In developing the approach to solve the MINLP/MDNLP challenge problem, several test problems provided the ability to explore performance of the framework. While solving these test problems, the framework showed that it could solve other MDNLP problems including categorically discrete variables, indicating that the framework could have broader application than the new aircraft design-fleet allocation-revenue management problem.

Query-Time Optimization Techniques for Structured Queries in Information Retrieval

ERIC Educational Resources Information Center

Cartright, Marc-Allen

2013-01-01

The use of information retrieval (IR) systems is evolving towards larger, more complicated queries. Both the IR industrial and research communities have generated significant evidence indicating that in order to continue improving retrieval effectiveness, increases in retrieval model complexity may be unavoidable. From an operational perspective,…

Acoustic Sensor Network Design for Position Estimation

DTIC Science & Technology

2009-05-01

A., Pollock, S., Netter, B., and Low, B. S. 2005. Anisogamy, expenditure of reproductive effort, and the optimality of having two sexes. Operations...Research 53, 3, 560–567. Evans, M., Hastings, N., and Peacock , B. 2000. Statistical distributions. Ed. Wiley & Sons. New York. Feeney, L. and Nilsson, M

A Sequential Quadratic Programming Algorithm Using an Incomplete Solution of the Subproblem

DTIC Science & Technology

1990-09-01

Electr6nica e Inform’itica Industrial E.T.S. Ingenieros Industriales Universidad Polit6cnica, Madrid Technical Report SOL 90-12 September 1990 -Y...MURRAY* AND FRANCISCO J. PRIETOt *Systems Optimization Laboratory Department of Operations Research Stanford University tDept. de Automitica, Ingenieria

Getting the Best out of Excel

ERIC Educational Resources Information Center

Heys, Chris

2008-01-01

Excel, Microsoft's spreadsheet program, offers several tools which have proven useful in solving some optimization problems that arise in operations research. We will look at two such tools, the Excel modules called Solver and Goal Seek--this after deriving an equation, called the "cash accumulation equation", to be used in conjunction with them.

TRACC_PB SOSS Integrated Traffic Simulation for CLT Ramp Operation

NASA Technical Reports Server (NTRS)

Okuniek, Nikolai; Zhu, Zhifan

2017-01-01

This presentation provides the current task under the NASA-DLR research collaboration for airport surface. It presents the effort done to adapt TRACC and SOSS software components to simulate airport (CLT) ramp area traffic management using TRACC's conflict free taxi trajectory optimization and SOSS's fast time simulation platform.

SU-E-T-266: Development of Evaluation System of Optimal Synchrotron Controlling Parameter for Spot Scanning Proton Therapy with Multiple Gate Irradiations in One Operation Cycle

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

Yamada, T; Fujii, Y; Hitachi Ltd., Hitachi-shi, Ibaraki

2015-06-15

Purpose: We have developed a gated spot scanning proton beam therapy system with real-time tumor-tracking. This system has the ability of multiple-gated irradiation in a single synchrotron operation cycle controlling the wait-time for consecutive gate signals during a flat-top phase so that the decrease in irradiation efficiency induced by irregular variation of gate signal is reduced. Our previous studies have shown that a 200 ms wait-time is appropriate to increase the average irradiation efficiency, but the optimal wait-time can vary patient by patient and day by day. In this research, we have developed an evaluation system of the optimal wait-timemore » in each irradiation based on the log data of the real-time-image gated proton beam therapy (RGPT) system. Methods: The developed system consists of logger for operation of RGPT system and software for evaluation of optimal wait-time. The logger records timing of gate on/off, timing and the dose of delivered beam spots, beam energy and timing of X-ray irradiation. The evaluation software calculates irradiation time in the case of different wait-time by simulating the multiple-gated irradiation operation using several timing information. Actual data preserved in the log data are used for gate on and off time, spot irradiation time, and time moving to the next spot. Design values are used for the acceleration and deceleration times. We applied this system to a patient treated with the RGPT system. Results: The evaluation system found the optimal wait-time of 390 ms that reduced the irradiation time by about 10 %. The irradiation time with actual wait-time used in treatment was reproduced with accuracy of 0.2 ms. Conclusion: For spot scanning proton therapy system with multiple-gated irradiation in one synchrotron operation cycle, an evaluation system of the optimal wait-time in each irradiation based on log data has been developed. Funding Support: Japan Society for the Promotion of Science (JSPS) through the FIRST Program.« less

State-of-The-Art of Modeling Methodologies and Optimization Operations in Integrated Energy System

NASA Astrophysics Data System (ADS)

Zheng, Zhan; Zhang, Yongjun

2017-08-01

Rapid advances in low carbon technologies and smart energy communities are reshaping future patterns. Uncertainty in energy productions and demand sides are paving the way towards decentralization management. Current energy infrastructures could not meet with supply and consumption challenges, along with emerging environment and economic requirements. Integrated Energy System(IES) whereby electric power, natural gas, heating couples with each other demonstrates that such a significant technique would gradually become one of main comprehensive and optimal energy solutions with high flexibility, friendly renewables absorption and improving efficiency. In these global energy trends, we summarize this literature review. Firstly the accurate definition and characteristics of IES have been presented. Energy subsystem and coupling elements modeling issues are analyzed. It is pointed out that decomposed and integrated analysis methods are the key algorithms for IES optimization operations problems, followed by exploring the IES market mechanisms. Finally several future research tendencies of IES, such as dynamic modeling, peer-to-peer trading, couple market design, sare under discussion.

Optimal economic order quantity for buyer-distributor-vendor supply chain with backlogging derived without derivatives

NASA Astrophysics Data System (ADS)

Teng, Jinn-Tsair; Cárdenas-Barrón, Leopoldo Eduardo; Lou, Kuo-Ren; Wee, Hui Ming

2013-05-01

In this article, we first complement an inappropriate mathematical error on the total cost in the previously published paper by Chung and Wee [2007, 'Optimal the Economic Lot Size of a Three-stage Supply Chain With Backlogging Derived Without Derivatives', European Journal of Operational Research, 183, 933-943] related to buyer-distributor-vendor three-stage supply chain with backlogging derived without derivatives. Then, an arithmetic-geometric inequality method is proposed not only to simplify the algebraic method of completing prefect squares, but also to complement their shortcomings. In addition, we provide a closed-form solution to integral number of deliveries for the distributor and the vendor without using complex derivatives. Furthermore, our method can solve many cases in which their method cannot, because they did not consider that a squared root of a negative number does not exist. Finally, we use some numerical examples to show that our proposed optimal solution is cheaper to operate than theirs.

Selection of operating parameters on the basis of hydrodynamics in centrifugal partition chromatography for the purification of nybomycin derivatives.

PubMed

Adelmann, S; Baldhoff, T; Koepcke, B; Schembecker, G

2013-01-25

The selection of solvent systems in centrifugal partition chromatography (CPC) is the most critical point in setting up a separation. Therefore, lots of research was done on the topic in the last decades. But the selection of suitable operating parameters (mobile phase flow rate, rotational speed and mode of operation) with respect to hydrodynamics and pressure drop limit in CPC is still mainly driven by experience of the chromatographer. In this work we used hydrodynamic analysis for the prediction of most suitable operating parameters. After selection of different solvent systems with respect to partition coefficients for the target compound the hydrodynamics were visualized. Based on flow pattern and retention the operating parameters were selected for the purification runs of nybomycin derivatives that were carried out with a 200 ml FCPC(®) rotor. The results have proven that the selection of optimized operating parameters by analysis of hydrodynamics only is possible. As the hydrodynamics are predictable by the physical properties of the solvent system the optimized operating parameters can be estimated, too. Additionally, we found that dispersion and especially retention are improved if the less viscous phase is mobile. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

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.

Modeling the Environmental Impact of Air Traffic Operations

NASA Technical Reports Server (NTRS)

Chen, Neil

2011-01-01

There is increased interest to understand and mitigate the impacts of air traffic on the climate, since greenhouse gases, nitrogen oxides, and contrails generated by air traffic can have adverse impacts on the climate. The models described in this presentation are useful for quantifying these impacts and for studying alternative environmentally aware operational concepts. These models have been developed by leveraging and building upon existing simulation and optimization techniques developed for the design of efficient traffic flow management strategies. Specific enhancements to the existing simulation and optimization techniques include new models that simulate aircraft fuel flow, emissions and contrails. To ensure that these new models are beneficial to the larger climate research community, the outputs of these new models are compatible with existing global climate modeling tools like the FAA's Aviation Environmental Design Tool.

An evolutionary algorithm technique for intelligence, surveillance, and reconnaissance plan optimization

NASA Astrophysics Data System (ADS)

Langton, John T.; Caroli, Joseph A.; Rosenberg, Brad

2008-04-01

To support an Effects Based Approach to Operations (EBAO), Intelligence, Surveillance, and Reconnaissance (ISR) planners must optimize collection plans within an evolving battlespace. A need exists for a decision support tool that allows ISR planners to rapidly generate and rehearse high-performing ISR plans that balance multiple objectives and constraints to address dynamic collection requirements for assessment. To meet this need we have designed an evolutionary algorithm (EA)-based "Integrated ISR Plan Analysis and Rehearsal System" (I2PARS) to support Effects-based Assessment (EBA). I2PARS supports ISR mission planning and dynamic replanning to coordinate assets and optimize their routes, allocation and tasking. It uses an evolutionary algorithm to address the large parametric space of route-finding problems which is sometimes discontinuous in the ISR domain because of conflicting objectives such as minimizing asset utilization yet maximizing ISR coverage. EAs are uniquely suited for generating solutions in dynamic environments and also allow user feedback. They are therefore ideal for "streaming optimization" and dynamic replanning of ISR mission plans. I2PARS uses the Non-dominated Sorting Genetic Algorithm (NSGA-II) to automatically generate a diverse set of high performing collection plans given multiple objectives, constraints, and assets. Intended end users of I2PARS include ISR planners in the Combined Air Operations Centers and Joint Intelligence Centers. Here we show the feasibility of applying the NSGA-II algorithm and EAs in general to the ISR planning domain. Unique genetic representations and operators for optimization within the ISR domain are presented along with multi-objective optimization criteria for ISR planning. Promising results of the I2PARS architecture design, early software prototype, and limited domain testing of the new algorithm are discussed. We also present plans for future research and development, as well as technology transition goals.

Defining a region of optimization based on engine usage data

DOEpatents

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

2015-08-04

Methods and systems for engine control optimization are provided. One or more operating conditions of a vehicle engine are detected. A value for each of a plurality of engine control parameters is determined based on the detected one or more operating conditions of the vehicle engine. A range of the most commonly detected operating conditions of the vehicle engine is identified and a region of optimization is defined based on the range of the most commonly detected operating conditions of the vehicle engine. The engine control optimization routine is initiated when the one or more operating conditions of the vehicle engine are within the defined region of optimization.

Layout design-based research on optimization and assessment method for shipbuilding workshop

NASA Astrophysics Data System (ADS)

Liu, Yang; Meng, Mei; Liu, Shuang

2013-06-01

The research study proposes to examine a three-dimensional visualization program, emphasizing on improving genetic algorithms through the optimization of a layout design-based standard and discrete shipbuilding workshop. By utilizing a steel processing workshop as an example, the principle of minimum logistic costs will be implemented to obtain an ideological equipment layout, and a mathematical model. The objectiveness is to minimize the total necessary distance traveled between machines. An improved control operator is implemented to improve the iterative efficiency of the genetic algorithm, and yield relevant parameters. The Computer Aided Tri-Dimensional Interface Application (CATIA) software is applied to establish the manufacturing resource base and parametric model of the steel processing workshop. Based on the results of optimized planar logistics, a visual parametric model of the steel processing workshop is constructed, and qualitative and quantitative adjustments then are applied to the model. The method for evaluating the results of the layout is subsequently established through the utilization of AHP. In order to provide a mode of reference to the optimization and layout of the digitalized production workshop, the optimized discrete production workshop will possess a certain level of practical significance.

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

Network Virtualization - Opportunities and Challenges for Operators

NASA Astrophysics Data System (ADS)

Carapinha, Jorge; Feil, Peter; Weissmann, Paul; Thorsteinsson, Saemundur E.; Etemoğlu, Çağrı; Ingþórsson, Ólafur; Çiftçi, Selami; Melo, Márcio

In the last few years, the concept of network virtualization has gained a lot of attention both from industry and research projects. This paper evaluates the potential of network virtualization from an operator's perspective, with the short-term goal of optimizing service delivery and rollout, and on a longer term as an enabler of technology integration and migration. Based on possible scenarios for implementing and using network virtualization, new business roles and models are examined. Open issues and topics for further evaluation are identified. In summary, the objective is to identify the challenges but also new opportunities for telecom operators raised by network virtualization.

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

Smith, Brennan T; Jager, Yetta; March, Patrick

Reservoir releases are typically operated to maximize the efficiency of hydropower production and the value of hydropower produced. In practice, ecological considerations are limited to those required by law. We first describe reservoir optimization methods that include mandated constraints on environmental and other water uses. Next, we describe research to formulate and solve reservoir optimization problems involving both energy and environmental water needs as objectives. Evaluating ecological objectives is a challenge in these problems for several reasons. First, it is difficult to predict how biological populations will respond to flow release patterns. This problem can be circumvented by using ecologicalmore » models. Second, most optimization methods require complex ecological responses to flow to be quantified by a single metric, preferably a currency that can also represent hydropower benefits. Ecological valuation of instream flows can make optimization methods that require a single currency for the effects of flow on energy and river ecology possible. Third, holistic reservoir optimization problems are unlikely to be structured such that simple solution methods can be used, necessitating the use of flexible numerical methods. One strong advantage of optimal control is the ability to plan for the effects of climate change. We present ideas for developing holistic methods to the point where they can be used for real-time operation of reservoirs. We suggest that developing ecologically sound optimization tools should be a priority for hydropower in light of the increasing value placed on sustaining both the ecological and energy benefits of riverine ecosystems long into the future.« less

New Approaches to HSCT Multidisciplinary Design and Optimization

NASA Technical Reports Server (NTRS)

Schrage, D. P.; Craig, J. I.; Fulton, R. E.; Mistree, F.

1996-01-01

The successful development of a capable and economically viable high speed civil transport (HSCT) is perhaps one of the most challenging tasks in aeronautics for the next two decades. At its heart it is fundamentally the design of a complex engineered system that has significant societal, environmental and political impacts. As such it presents a formidable challenge to all areas of aeronautics, and it is therefore a particularly appropriate subject for research in multidisciplinary design and optimization (MDO). In fact, it is starkly clear that without the availability of powerful and versatile multidisciplinary design, analysis and optimization methods, the design, construction and operation of im HSCT simply cannot be achieved. The present research project is focused on the development and evaluation of MDO methods that, while broader and more general in scope, are particularly appropriate to the HSCT design problem. The research aims to not only develop the basic methods but also to apply them to relevant examples from the NASA HSCT R&D effort. The research involves a three year effort aimed first at the HSCT MDO problem description, next the development of the problem, and finally a solution to a significant portion of the problem.

Podoconiosis, non-filarial elephantiasis, and lymphology.

PubMed

Davey, G

2010-12-01

Several recent reviews of podoconiosis already exist in journals and on public access websites. After briefly covering the historical and epidemiological background, this narrative review will therefore attempt explicitly to link podoconiosis with lymphology, examining gaps in what is known of pathogenesis and identifying the areas of research in which input from lymphologists is most required. Finally, prevention and treatment will be described and the need for operational research to optimize community-based interventions outlined.

Predicting Ranger Assessment and Selection Program 1 Success and Optimizing Class Composition

DTIC Science & Technology

2017-06-01

some type of survival function. We use some of the manpower and force management research above to assist in the development of RANGr. We differ from...Generation. Operations Research Masters Thesis, Monterey: Naval Postgraduate School. Yamada WS (2000) An Infinite Horizon Military Manpower Model...demand. For example, we find the Ranger Regiment could reduce the number of annual RASP1 classes from ten to eight based on several realistic

Infrastructure, Components and System Level Testing and Analysis of Electric Vehicles: Cooperative Research and Development Final Report, CRADA Number CRD-09-353

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

Neubauer, J.

2013-05-01

Battery technology is critical for the development of innovative electric vehicle networks, which can enhance transportation sustainability and reduce dependence on petroleum. This cooperative research proposed by Better Place and NREL will focus on predicting the life-cycle economics of batteries, characterizing battery technologies under various operating and usage conditions, and designing optimal usage profiles for battery recharging and use.

Research on charging and discharging control strategy for electric vehicles as distributed energy storage devices

NASA Astrophysics Data System (ADS)

Zhang, Min; Yang, Feng; Zhang, Dongqing; Tang, Pengcheng

2018-02-01

A large number of electric vehicles are connected to the family micro grid will affect the operation safety of the power grid and the quality of power. Considering the factors of family micro grid price and electric vehicle as a distributed energy storage device, a two stage optimization model is established, and the improved discrete binary particle swarm optimization algorithm is used to optimize the parameters in the model. The proposed control strategy of electric vehicle charging and discharging is of practical significance for the rational control of electric vehicle as a distributed energy storage device and electric vehicle participating in the peak load regulation of power consumption.

Timing of Operative Debridement in Open Fractures.

PubMed

Rozell, Joshua C; Connolly, Keith P; Mehta, Samir

2017-01-01

The optimal treatment of open fractures continues to be an area of debate in the orthopedic literature. Recent research has challenged the dictum that open fractures should be debrided within 6 hours of injury. However, the expedient administration of intravenous antibiotics remains of paramount importance in infection prevention. Multiple factors, including fracture severity, thoroughness of debridement, time to initial treatment, and antibiotic administration, among other variables, contribute to the incidence of infection and complicate identifying an optimal time to debridement. Copyright © 2016 Elsevier Inc. All rights reserved.

Application of Strategic Management Principles as Tool to Improve Quality of Construction Technological Process

NASA Astrophysics Data System (ADS)

Kluchnikova, O.; Pobegaylov, O.

2017-11-01

The article focuses on the basic theory and practical aspects of the strategic management improving in terms of enhancing the quality of a technological process: these aspects have been proven experimentally by their introduction in company operations. The authors have worked out some proposals aimed at the selection of an optimal supplier for building companies as well as the algorithm for the analysis and optimization of a construction company basing on scientific and practical research as well as on the experimental data obtained in the experiment.

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

Jager, Yetta; Smith, Brennan T

Hydroelectric power provides a cheap source of electricity with few carbon emissions. Yet, reservoirs are not operated sustainably, which we define as meeting societal needs for water and power while protecting long-term health of the river ecosystem. Reservoirs that generate hydropower are typically operated with the goal of maximizing energy revenue, while meeting other legal water requirements. Reservoir optimization schemes used in practice do not seek flow regimes that maximize aquatic ecosystem health. Here, we review optimization studies that considered environmental goals in one of three approaches. The first approach seeks flow regimes that maximize hydropower generations while satisfying legalmore » requirements, including environmental (or minimum) flows. Solutions from this approach are often used in practice to operate hydropower projects. In the second approach, flow releases from a dam are timed to meet water quality constraints on dissolved oxygen (DO), temperature and nutrients. In the third approach, flow releases are timed to improve the health of fish populations. We conclude by suggesting three steps for bringing multi-objective reservoir operation closer to the goal of ecological sustainability: (1) conduct research to identify which features of flow variation are essential for river health and to quantify these relationships, (2) develop valuation methods to assess the total value of river health and (3) develop optimal control softwares that combine water balance modeling with models that predict ecosystem responses to flow.« less

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

Jager, Yetta; Smith, Brennan T

Hydroelectric power provides a cheap source of electricity with few carbon emissions. Yet, reservoirs are not operated sustainably, which we define as meeting societal needs for water and power while protecting long-term health of the river ecosystem. Reservoirs that generate hydropower are typically operated with the goal of maximizing energy revenue, while meeting other legal water requirements. Reservoir optimization schemes used in practice do not seek flow regimes that maximize aquatic ecosystem health. Here, we review optimization studies that considered environmental goals in one of three approaches. The first approach seeks flow regimes that maximize hydropower generation, while satisfying legalmore » requirements, including environmental (or minimum) flows. Solutions from this approach are often used in practice to operate hydropower projects. In the second approach, flow releases from a dam are timed to meet water quality constraints on dissolved oxygen (DO), temperature and nutrients. In the third approach, flow releases are timed to improve the health of fish populations. We conclude by suggesting three steps for bringing multi-objective reservoir operation closer to the goal of ecological sustainability: (1) conduct research to identify which features of flow variation are essential for river health and to quantify these relationships, (2) develop valuation methods to assess the total value of river health and (3) develop optimal control softwares that combine water balance modelling with models that predict ecosystem responses to flow.« less

A Virtual Reality Framework to Optimize Design, Operation and Refueling of GEN-IV Reactors.

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

Rizwan-uddin; Nick Karancevic; Stefano Markidis

2008-04-23

many GEN-IV candidate designs are currently under investigation. Technical issues related to material, safety and economics are being addressed at research laboratories, industry and in academia. After safety, economic feasibility is likely to be the most important crterion in the success of GEN-IV design(s). Lessons learned from the designers and operators of GEN-II (and GEN-III) reactors must play a vital role in achieving both safety and economic feasibility goals.

Peak Seeking Control for Reduced Fuel Consumption with Preliminary Flight Test Results

NASA Technical Reports Server (NTRS)

Brown, Nelson

2012-01-01

The Environmentally Responsible Aviation project seeks to accomplish the simultaneous reduction of fuel burn, noise, and emissions. A project at NASA Dryden Flight Research Center is contributing to ERAs goals by exploring the practical application of real-time trim configuration optimization for enhanced performance and reduced fuel consumption. This peak-seeking control approach is based on Newton-Raphson algorithm using a time-varying Kalman filter to estimate the gradient of the performance function. In real-time operation, deflection of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of a modified F-18 are directly optimized, and the horizontal stabilators and angle of attack are indirectly optimized. Preliminary results from three research flights are presented herein. The optimization system found a trim configuration that required approximately 3.5% less fuel flow than the baseline trim at the given flight condition. The algorithm consistently rediscovered the solution from several initial conditions. These preliminary results show the algorithm has good performance and is expected to show similar results at other flight conditions and aircraft configurations.

Manual control aspects of orbital flight

NASA Technical Reports Server (NTRS)

Brody, Adam R.

1990-01-01

Studies of spacecraft rendezvous and docking operations began in the Gemini program in preparation for the two dockings required to send a crew to the moon and return them safely to Earth. However, the goal of getting to the moon before the end of the decade was of greater concern than mission optimization so little or no time or money was expended in researching human factors implications of operational aspects such as braking gates or control modes. Also, with sixteen operational dockings over a six year period (12 Apollo, 3 Skylab, and 1 ASTP) in the United States space program, economies of scale were not yet available to justify extensive research into decreasing the time or fuel necessary for a successful docking. With an operational space station era approaching in which orbital maneuvering vehicle (OMV), orbital transfer vehicle (OTV), shuttle orbiter, and other traffic will play a major role, a concerted research effort now could help avoid many potential problems later in addition to increasing safety, fuel economy, and productivity. A knowledge of manual control capabilities associated with piloted spaceflight could help save a life if the operational flight envelope can be safely enlarged to include faster dockings that currently envisioned. For example, current and future research is designed to acquire the appropriate information.

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.

Mission-based Scenario Research: Experimental Design And Analysis

DTIC Science & Technology

2012-01-01

neurotechnologies called Brain-Computer Interaction Technologies. 15. SUBJECT TERMS neuroimaging, EEG, task loading, neurotechnologies , ground... neurotechnologies called Brain-Computer Interaction Technologies. INTRODUCTION Imagine a system that can identify operator fatigue during a long-term...BCIT), a class of neurotechnologies , that aim to improve task performance by incorporating measures of brain activity to optimize the interactions

Using Spreadsheet Modeling to Teach Exchange Curves (Optimal Policy Curves) in Inventory Management

ERIC Educational Resources Information Center

Strakos, Joshua K.

2016-01-01

Inventory management is widely researched and the topic is taught in business programs across the spectrum of operations and supply chain management. However, the concepts are notoriously difficult for students to practice once they finish school and become managers responsible for inventory control. This article explains the structure and details…

Rolling-element bearings: A review of the state of the art

NASA Technical Reports Server (NTRS)

Anderson, W. J.; Zaretsky, E. V.

1973-01-01

Some of the research conducted which has brought rolling-element technology to its present state is discussed. Areas touched upon are material effects, processing variables, operating variables, design optimization, lubricant effects and lubrication methods. Finally, problem areas are discussed in relation to the present state-of-the-art and anticipated requirements.

DOTD support for UTC project : development of an optimal ramp metering control strategy for I-12, [research project capsule].

DOT National Transportation Integrated Search

2013-10-01

From June to November of 2010, the Louisiana Department of Transportation and : Development (DOTD) deployed ramp metering control, using a simple pre-timed operation : with a xed cycle length (2 seconds of green/2 seconds of red), along a 15-mile ...

An Integer Programming-Based Generalized Vehicle Routing Approach for Printed Circuit Board Assembly Optimization

ERIC Educational Resources Information Center

Seth, Anupam

2009-01-01

Production planning and scheduling for printed circuit, board assembly has so far defied standard operations research approaches due to the size and complexity of the underlying problems, resulting in unexploited automation flexibility. In this thesis, the increasingly popular collect-and-place machine configuration is studied and the assembly…

Creating and supporting a mixed methods health services research team.

PubMed

Bowers, Barbara; Cohen, Lauren W; Elliot, Amy E; Grabowski, David C; Fishman, Nancy W; Sharkey, Siobhan S; Zimmerman, Sheryl; Horn, Susan D; Kemper, Peter

2013-12-01

To use the experience from a health services research evaluation to provide guidance in team development for mixed methods research. The Research Initiative Valuing Eldercare (THRIVE) team was organized by the Robert Wood Johnson Foundation to evaluate The Green House nursing home culture change program. This article describes the development of the research team and provides insights into how funders might engage with mixed methods research teams to maximize the value of the team. Like many mixed methods collaborations, the THRIVE team consisted of researchers from diverse disciplines, embracing diverse methodologies, and operating under a framework of nonhierarchical, shared leadership that required new collaborations, engagement, and commitment in the context of finite resources. Strategies to overcome these potential obstacles and achieve success included implementation of a Coordinating Center, dedicated time for planning and collaborating across researchers and methodologies, funded support for in-person meetings, and creative optimization of resources. Challenges are inevitably present in the formation and operation of effective mixed methods research teams. However, funders and research teams can implement strategies to promote success. © Health Research and Educational Trust.

Experimental analysis of performance and emission on DI diesel engine fueled with diesel-palm kernel methyl ester-triacetin blends: a Taguchi fuzzy-based optimization.

PubMed

Panda, Jibitesh Kumar; Sastry, Gadepalli Ravi Kiran; Rai, Ram Naresh

2018-05-25

The energy situation and the concerns about global warming nowadays have ignited research interest in non-conventional and alternative fuel resources to decrease the emission and the continuous dependency on fossil fuels, particularly for various sectors like power generation, transportation, and agriculture. In the present work, the research is focused on evaluating the performance, emission characteristics, and combustion of biodiesel such as palm kernel methyl ester with the addition of diesel additive "triacetin" in it. A timed manifold injection (TMI) system was taken up to examine the influence of durations of several blends induced on the emission and performance characteristics as compared to normal diesel operation. This experimental study shows better performance and releases less emission as compared with mineral diesel and in turn, indicates that high performance and low emission is promising in PKME-triacetin fuel operation. This analysis also attempts to describe the application of the fuzzy logic-based Taguchi analysis to optimize the emission and performance parameters.

Multidisciplinary Optimization Approach for Design and Operation of Constrained and Complex-shaped Space Systems

NASA Astrophysics Data System (ADS)

Lee, Dae Young

The design of a small satellite is challenging since they are constrained by mass, volume, and power. To mitigate these constraint effects, designers adopt deployable configurations on the spacecraft that result in an interesting and difficult optimization problem. The resulting optimization problem is challenging due to the computational complexity caused by the large number of design variables and the model complexity created by the deployables. Adding to these complexities, there is a lack of integration of the design optimization systems into operational optimization, and the utility maximization of spacecraft in orbit. The developed methodology enables satellite Multidisciplinary Design Optimization (MDO) that is extendable to on-orbit operation. Optimization of on-orbit operations is possible with MDO since the model predictive controller developed in this dissertation guarantees the achievement of the on-ground design behavior in orbit. To enable the design optimization of highly constrained and complex-shaped space systems, the spherical coordinate analysis technique, called the "Attitude Sphere", is extended and merged with an additional engineering tools like OpenGL. OpenGL's graphic acceleration facilitates the accurate estimation of the shadow-degraded photovoltaic cell area. This technique is applied to the design optimization of the satellite Electric Power System (EPS) and the design result shows that the amount of photovoltaic power generation can be increased more than 9%. Based on this initial methodology, the goal of this effort is extended from Single Discipline Optimization to Multidisciplinary Optimization, which includes the design and also operation of the EPS, Attitude Determination and Control System (ADCS), and communication system. The geometry optimization satisfies the conditions of the ground development phase; however, the operation optimization may not be as successful as expected in orbit due to disturbances. To address this issue, for the ADCS operations, controllers based on Model Predictive Control that are effective for constraint handling were developed and implemented. All the suggested design and operation methodologies are applied to a mission "CADRE", which is space weather mission scheduled for operation in 2016. This application demonstrates the usefulness and capability of the methodology to enhance CADRE's capabilities, and its ability to be applied to a variety of missions.

Coupling of Transport and Chemical Processes in Catalytic Combustion

NASA Technical Reports Server (NTRS)

Bracco, F. V.; Bruno, C.; Royce, B. S. H.; Santavicca, D. A.; Sinha, N.; Stein, Y.

1983-01-01

Catalytic combustors have demonstrated the ability to operate efficiently over a much wider range of fuel air ratios than are imposed by the flammability limits of conventional combustors. Extensive commercial use however needs the following: (1) the design of a catalyst with low ignition temperature and high temperature stability, (2) reducing fatigue due to thermal stresses during transient operation, and (3) the development of mathematical models that can be used as design optimization tools to isolate promising operating ranges for the numerous operating parameters. The current program of research involves the development of a two dimensional transient catalytic combustion model and the development of a new catalyst with low temperature light-off and high temperature stablity characteristics.

Toward the establishment of design guidelines for effective 3D perspective interfaces

NASA Astrophysics Data System (ADS)

Fitzhugh, Elisabeth; Dixon, Sharon; Aleva, Denise; Smith, Eric; Ghrayeb, Joseph; Douglas, Lisa

2009-05-01

The propagation of information operation technologies, with correspondingly vast amounts of complex network information to be conveyed, significantly impacts operator workload. Information management research is rife with efforts to develop schemes to aid operators to identify, review, organize, and retrieve the wealth of available data. Data may take on such distinct forms as intelligence libraries, logistics databases, operational environment models, or network topologies. Increased use of taxonomies and semantic technologies opens opportunities to employ network visualization as a display mechanism for diverse information aggregations. The broad applicability of network visualizations is still being tested, but in current usage, the complexity of densely populated abstract networks suggests the potential utility of 3D. Employment of 2.5D in network visualization, using classic perceptual cues, creates a 3D experience within a 2D medium. It is anticipated that use of 3D perspective (2.5D) will enhance user ability to visually inspect large, complex, multidimensional networks. Current research for 2.5D visualizations demonstrates that display attributes, including color, shape, size, lighting, atmospheric effects, and shadows, significantly impact operator experience. However, guidelines for utilization of attributes in display design are limited. This paper discusses pilot experimentation intended to identify potential problem areas arising from these cues and determine how best to optimize perceptual cue settings. Development of optimized design guidelines will ensure that future experiments, comparing network displays with other visualizations, are not confounded or impeded by suboptimal attribute characterization. Current experimentation is anticipated to support development of cost-effective, visually effective methods to implement 3D in military applications.

Crew interface analysis: Selected articles on space human factors research, 1987 - 1991

NASA Technical Reports Server (NTRS)

Bagian, Tandi (Compiler)

1993-01-01

As part of the Flight Crew Support Division at NASA, the Crew Interface Analysis Section is dedicated to the study of human factors in the manned space program. It assumes a specialized role that focuses on answering operational questions pertaining to NASA's Space Shuttle and Space Station Freedom Programs. One of the section's key contributions is to provide knowledge and information about human capabilities and limitations that promote optimal spacecraft and habitat design and use to enhance crew safety and productivity. The section provides human factors engineering for the ongoing missions as well as proposed missions that aim to put human settlements on the Moon and Mars. Research providing solutions to operational issues is the primary objective of the Crew Interface Analysis Section. The studies represent such subdisciplines as ergonomics, space habitability, man-computer interaction, and remote operator interaction.

Autonomous Control of Nuclear Power Plants

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

Basher, H.

2003-10-20

A nuclear reactor is a complex system that requires highly sophisticated controllers to ensure that desired performance and safety can be achieved and maintained during its operations. Higher-demanding operational requirements such as reliability, lower environmental impacts, and improved performance under adverse conditions in nuclear power plants, coupled with the complexity and uncertainty of the models, necessitate the use of an increased level of autonomy in the control methods. In the opinion of many researchers, the tasks involved during nuclear reactor design and operation (e.g., design optimization, transient diagnosis, and core reload optimization) involve important human cognition and decisions that maymore » be more easily achieved with intelligent methods such as expert systems, fuzzy logic, neural networks, and genetic algorithms. Many experts in the field of control systems share the idea that a higher degree of autonomy in control of complex systems such as nuclear plants is more easily achievable through the integration of conventional control systems and the intelligent components. Researchers have investigated the feasibility of the integration of fuzzy logic, neural networks, genetic algorithms, and expert systems with the conventional control methods to achieve higher degrees of autonomy in different aspects of reactor operations such as reactor startup, shutdown in emergency situations, fault detection and diagnosis, nuclear reactor alarm processing and diagnosis, and reactor load-following operations, to name a few. With the advancement of new technologies and computing power, it is feasible to automate most of the nuclear reactor control and operation, which will result in increased safety and economical benefits. This study surveys current status, practices, and recent advances made towards developing autonomous control systems for nuclear reactors.« 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.

Traffic Flow Management and Optimization

NASA Technical Reports Server (NTRS)

Rios, Joseph Lucio

2014-01-01

This talk will present an overview of Traffic Flow Management (TFM) research at NASA Ames Research Center. Dr. Rios will focus on his work developing a large-scale, parallel approach to solving traffic flow management problems in the national airspace. In support of this talk, Dr. Rios will provide some background on operational aspects of TFM as well a discussion of some of the tools needed to perform such work including a high-fidelity airspace simulator. Current, on-going research related to TFM data services in the national airspace system and general aviation will also be presented.

RBCC Mixing Studies: Ejector Ramjet Design Optimization

NASA Technical Reports Server (NTRS)

1999-01-01

The research project reported herein extended over a period from October 1997 through August 1999. The research resulted in three technical papers presented at the AIAA/SAE/ASME/ASEE 35th Joint Propulsion Conference in Los Angeles in July 1999. These three papers are attached to this Executive Summary to constitute the final report. Objective: The objective of this research was to determine the mixing characteristics between the primary rocket jets and the turbine exhaust stream in a simulated Rocket Based Combined Cycle propulsion concept operating in the air augmented rocket mode.

[Research on the preparative method of Arctigenin].

PubMed

Zhang, Li-Ying; Yang, Yi-Shun; Zhang, Tong; Ding, Yue; Cai, Zhen-Zhen; Tao, Jian-Sheng

2012-03-01

To research on the preparation of Arctigenin in vitro. Took enzyme concentration, time course and substrate concentration as investigation factors, used Box-Behnken design-response surface methodology to optimize the enzyme hydrolysis path of Arctigenin. The best operational path for Arctigenin was as follows: the temperature was 50 degrees C, pH was 4.8, enzyme concentration was 0.44 U/mL, time course was 46.81 min, substrate concentration was 0.29 mg/mL, the conversion rate was 90.94%. This research can be regarded as a referencein preparing Arctigenin in vitro.

Creating and Supporting a Mixed Methods Health Services Research Team

PubMed Central

Bowers, Barbara; Cohen, Lauren W; Elliot, Amy E; Grabowski, David C; Fishman, Nancy W; Sharkey, Siobhan S; Zimmerman, Sheryl; Horn, Susan D; Kemper, Peter

2013-01-01

Objective. To use the experience from a health services research evaluation to provide guidance in team development for mixed methods research. Methods. The Research Initiative Valuing Eldercare (THRIVE) team was organized by the Robert Wood Johnson Foundation to evaluate The Green House nursing home culture change program. This article describes the development of the research team and provides insights into how funders might engage with mixed methods research teams to maximize the value of the team. Results. Like many mixed methods collaborations, the THRIVE team consisted of researchers from diverse disciplines, embracing diverse methodologies, and operating under a framework of nonhierarchical, shared leadership that required new collaborations, engagement, and commitment in the context of finite resources. Strategies to overcome these potential obstacles and achieve success included implementation of a Coordinating Center, dedicated time for planning and collaborating across researchers and methodologies, funded support for in-person meetings, and creative optimization of resources. Conclusions. Challenges are inevitably present in the formation and operation of effective mixed methods research teams. However, funders and research teams can implement strategies to promote success. PMID:24138774

Aircraft Optimization for Minimum Environmental Impact

NASA Technical Reports Server (NTRS)

Antoine, Nicolas; Kroo, Ilan M.

2001-01-01

The objective of this research is to investigate the tradeoff between operating cost and environmental acceptability of commercial aircraft. This involves optimizing the aircraft design and mission to minimize operating cost while constraining exterior noise and emissions. Growth in air traffic and airport neighboring communities has resulted in increased pressure to severely penalize airlines that do not meet strict local noise and emissions requirements. As a result, environmental concerns have become potent driving forces in commercial aviation. Traditionally, aircraft have been first designed to meet performance and cost goals, and adjusted to satisfy the environmental requirements at given airports. The focus of the present study is to determine the feasibility of including noise and emissions constraints in the early design of the aircraft and mission. This paper introduces the design tool and results from a case study involving a 250-passenger airliner.

Research on strategy and optimization method of PRT empty vehicles resource allocation based on traffic demand forecast

NASA Astrophysics Data System (ADS)

Xiang, Yu; Tao, Cheng

2018-05-01

During the operation of the personal rapid transit system(PRT), the empty vehicle resources is distributed unevenly because of different passenger demand. In order to maintain the balance between supply and demand, and to meet the passenger needs of the ride, PRT empty vehicle resource allocation model is constructed based on the future demand forecasted by historical demand in this paper. The improved genetic algorithm is implied in distribution of the empty vehicle which can reduce the customers waiting time and improve the operation efficiency of the PRT system so that all passengers can take the PRT vehicles in the shortest time. The experimental result shows that the improved genetic algorithm can allocate the empty vehicle from the system level optimally, and realize the distribution of the empty vehicle resources reasonably in the system.

Nonexpansiveness of a linearized augmented Lagrangian operator for hierarchical convex optimization

NASA Astrophysics Data System (ADS)

Yamagishi, Masao; Yamada, Isao

2017-04-01

Hierarchical convex optimization concerns two-stage optimization problems: the first stage problem is a convex optimization; the second stage problem is the minimization of a convex function over the solution set of the first stage problem. For the hierarchical convex optimization, the hybrid steepest descent method (HSDM) can be applied, where the solution set of the first stage problem must be expressed as the fixed point set of a certain nonexpansive operator. In this paper, we propose a nonexpansive operator that yields a computationally efficient update when it is plugged into the HSDM. The proposed operator is inspired by the update of the linearized augmented Lagrangian method. It is applicable to characterize the solution set of recent sophisticated convex optimization problems found in the context of inverse problems, where the sum of multiple proximable convex functions involving linear operators must be minimized to incorporate preferable properties into the minimizers. For such a problem formulation, there has not yet been reported any nonexpansive operator that yields an update free from the inversions of linear operators in cases where it is utilized in the HSDM. Unlike previously known nonexpansive operators, the proposed operator yields an inversion-free update in such cases. As an application of the proposed operator plugged into the HSDM, we also present, in the context of the so-called superiorization, an algorithmic solution to a convex optimization problem over the generalized convex feasible set where the intersection of the hard constraints is not necessarily simple.

Modified quadrupole mass analyzer RGA-100 for beam plasma research in forevacuum pressure range

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

Zolotukhin, D. B.; Tyunkov, A. V.; Yushkov, Yu. G., E-mail: yuyushkov@gmail.com

2015-12-15

The industrial quadrupole RGA-100 residual gas analyzer was modified for the research of electron beam-generated plasma at forevacuum pressure range. The standard ionizer of the RGA-100 was replaced by three electrode extracting unit. We made the optimization of operation parameters in order to provide the maximum values of measured currents of any ion species. The modified analyzer was successfully tested with beam plasma of argon, nitrogen, oxygen, and hydrocarbons.

Use of a Food and Drug Administration-Approved Type 1 Diabetes Mellitus Simulator to Evaluate and Optimize a Proportional-Integral-Derivative Controller

DTIC Science & Technology

2012-11-01

performance . The simulations confirm that the PID algorithm can be applied to this cohort without the risk of hypoglycemia . Funding: The study was... Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command...safe operating region, type 1 diabetes mellitus simulator Corresponding Author: Jaques Reifman, Ph.D., DoD Biotechnology High- Performance Computing

NMR System for a Type II Quantum Computer

DTIC Science & Technology

2007-06-01

Kevin Henry, Jr., "Coherent Control in QIP" June 2007. Please see Appendix pdf file pages 296-399. 4 Chapter 1 Introduction Recent research [1, 2, 3...can often by reduced by careful design of the time dependence of control fields. This is possible since the operators underlying the incoherence are...ob- tained by measurement. 21 1.2 Optimal Control Theory applied to Quantum Systems One of the main goals for theoretical research in quantum control

An Application of Multi-Criteria Shortest Path to a Customizable Hex-Map Environment

DTIC Science & Technology

2015-03-26

forces which could act as intermediate destinations or obstacles to movement through the network. This is similar to a traveling salesman problem ...118 Abstract The shortest path problem of finding the optimal path through a complex network is well-studied in the field of operations research. This...research presents an applica- tion of the shortest path problem to a customizable map with terrain features and enemy engagement risk. The PathFinder

Currency arbitrage detection using a binary integer programming model

NASA Astrophysics Data System (ADS)

Soon, Wanmei; Ye, Heng-Qing

2011-04-01

In this article, we examine the use of a new binary integer programming (BIP) model to detect arbitrage opportunities in currency exchanges. This model showcases an excellent application of mathematics to the real world. The concepts involved are easily accessible to undergraduate students with basic knowledge in Operations Research. Through this work, students can learn to link several types of basic optimization models, namely linear programming, integer programming and network models, and apply the well-known sensitivity analysis procedure to accommodate realistic changes in the exchange rates. Beginning with a BIP model, we discuss how it can be reduced to an equivalent but considerably simpler model, where an efficient algorithm can be applied to find the arbitrages and incorporate the sensitivity analysis procedure. A simple comparison is then made with a different arbitrage detection model. This exercise helps students learn to apply basic Operations Research concepts to a practical real-life example, and provides insights into the processes involved in Operations Research model formulations.

[How can institutional structures make clinical research in France more operational?].

PubMed

Funck-Brentano, C; Brouard, R

The laws regulating the practice of clinical research in France, in particular the law of 20 December 1988, the so-called Huriet's law, constitute a major advance for medical progress. However, their implementation by administrative offices generates practical difficulties which impair the development of applied research in human beings. Beyond the laws themselves, it appears that our institutions are unprepared to optimize the conduct of such research. This round table sought to list the existing problems and to propose constructive solutions or objectives to be reached to optimize clinical research in France, with a view to improving French participation in international collaborative programmes, notably European ones. Evaluation of projects and practices, financial support and accounting, and some aspects of existing laws have been identified as the major sources of our difficulties. Harmonization and clarification of our procedures as well as improvement of training should be our primary objectives to achieve a higher level of medical, scientific, financial and administrative quality in the conduct of clinical research. Creation of a referential Web site, designed and updated by a central public organization, is an imperative step towards reaching these objectives.

Blast optimization for improved dragline productivity

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

Humphreys, M.; Baldwin, G.

1994-12-31

A project aimed at blast optimization for large open pit coal mines is utilizing blast monitoring and analysis techniques, advanced dragline monitoring equipment, and blast simulation software, to assess the major controlling factors affecting both blast performance and subsequent dragline productivity. This has involved collaborative work between the explosives supplier, mine operator, monitoring equipment manufacturer, and a mining research organization. The results from trial blasts and subsequently monitored dragline production have yielded promising results and continuing studies are being conducted as part of a blast optimization program. It should be stressed that the optimization of blasting practices for improved draglinemore » productivity is a site specific task, achieved through controlled and closely monitored procedures. The benefits achieved at one location can not be simply transferred to another minesite unless similar improvement strategies are first implemented.« less

Spacecraft formation flying for Earth-crossing object deflections using a power limited laser ablating

NASA Astrophysics Data System (ADS)

Yoo, Sung-Moon; Song, Young-Joo; Park, Sang-Young; Choi, Kyu-Hong

2009-06-01

A formation flying strategy with an Earth-crossing object (ECO) is proposed to avoid the Earth collision. Assuming that a future conceptual spacecraft equipped with a powerful laser ablation tool already rendezvoused with a fictitious Earth collision object, the optimal required laser operating duration and direction histories are accurately derived to miss the Earth. Based on these results, the concept of formation flying between the object and the spacecraft is applied and analyzed as to establish the spacecraft's orbital motion design strategy. A fictitious "Apophis"-like object is established to impact with the Earth and two major deflection scenarios are designed and analyzed. These scenarios include the cases for the both short and long laser operating duration to avoid the Earth impact. Also, requirement of onboard laser tool's for both cases are discussed. As a result, the optimal initial conditions for the spacecraft to maintain its relative trajectory to the object are discovered. Additionally, the discovered optimal initial conditions also satisfied the optimal required laser operating conditions with no additional spacecraft's own fuel expenditure to achieve the spacecraft formation flying with the ECO. The initial conditions founded in the current research can be used as a spacecraft's initial rendezvous points with the ECO when designing the future deflection missions with laser ablation tools. The results with proposed strategy are expected to make more advances in the fields of the conceptual studies, especially for the future deflection missions using powerful laser ablation tools.

Optimization of urban water supply portfolios combining infrastructure capacity expansion and water use decisions

NASA Astrophysics Data System (ADS)

Medellin-Azuara, J.; Fraga, C. C. S.; Marques, G.; Mendes, C. A.

2015-12-01

The expansion and operation of urban water supply systems under rapidly growing demands, hydrologic uncertainty, and scarce water supplies requires a strategic combination of various supply sources for added reliability, reduced costs and improved operational flexibility. The design and operation of such portfolio of water supply sources merits decisions of what and when to expand, and how much to use of each available sources accounting for interest rates, economies of scale and hydrologic variability. The present research provides a framework and an integrated methodology that optimizes the expansion of various water supply alternatives using dynamic programming and combining both short term and long term optimization of water use and simulation of water allocation. A case study in Bahia Do Rio Dos Sinos in Southern Brazil is presented. The framework couples an optimization model with quadratic programming model in GAMS with WEAP, a rain runoff simulation models that hosts the water supply infrastructure features and hydrologic conditions. Results allow (a) identification of trade offs between cost and reliability of different expansion paths and water use decisions and (b) evaluation of potential gains by reducing water system losses as a portfolio component. The latter is critical in several developing countries where water supply system losses are high and often neglected in favor of more system expansion. Results also highlight the potential of various water supply alternatives including, conservation, groundwater, and infrastructural enhancements over time. The framework proves its usefulness for planning its transferability to similarly urbanized systems.

Optimal Control of Micro Grid Operation Mode Seamless Switching Based on Radau Allocation Method

NASA Astrophysics Data System (ADS)

Chen, Xiaomin; Wang, Gang

2017-05-01

The seamless switching process of micro grid operation mode directly affects the safety and stability of its operation. According to the switching process from island mode to grid-connected mode of micro grid, we establish a dynamic optimization model based on two grid-connected inverters. We use Radau allocation method to discretize the model, and use Newton iteration method to obtain the optimal solution. Finally, we implement the optimization mode in MATLAB and get the optimal control trajectory of the inverters.

Development of a Control Optimization System for Real Time Monitoring of Managed Aquifer Recharge and Recovery Systems Using Intelligent Sensors

NASA Astrophysics Data System (ADS)

Smits, K. M.; Drumheller, Z. W.; Lee, J. H.; Illangasekare, T. H.; Regnery, J.; Kitanidis, P. K.

2015-12-01

Aquifers around the world show troubling signs of irreversible depletion and seawater intrusion as climate change, population growth, and urbanization lead to reduced natural recharge rates and overuse. Scientists and engineers have begun to revisit the technology of managed aquifer recharge and recovery (MAR) as a means to increase the reliability of the diminishing and increasingly variable groundwater supply. Unfortunately, MAR systems remain wrought with operational challenges related to the quality and quantity of recharged and recovered water stemming from a lack of data-driven, real-time control. This research seeks to develop and validate a general simulation-based control optimization algorithm that relies on real-time data collected though embedded sensors that can be used to ease the operational challenges of MAR facilities. Experiments to validate the control algorithm were conducted at the laboratory scale in a two-dimensional synthetic aquifer under both homogeneous and heterogeneous packing configurations. The synthetic aquifer used well characterized technical sands and the electrical conductivity signal of an inorganic conservative tracer as a surrogate measure for water quality. The synthetic aquifer was outfitted with an array of sensors and an autonomous pumping system. Experimental results verified the feasibility of the approach and suggested that the system can improve the operation of MAR facilities. The dynamic parameter inversion reduced the average error between the simulated and observed pressures between 12.5 and 71.4%. The control optimization algorithm ran smoothly and generated optimal control decisions. Overall, results suggest that with some improvements to the inversion and interpolation algorithms, which can be further advanced through testing with laboratory experiments using sensors, the concept can successfully improve the operation of MAR facilities.

Theoretical and experimental researches on the operating costs of a wastewater treatment plant

NASA Astrophysics Data System (ADS)

Panaitescu, M.; Panaitescu, F.-V.; Anton, I.-A.

2015-11-01

Purpose of the work: The total cost of a sewage plants is often determined by the present value method. All of the annual operating costs for each process are converted to the value of today's correspondence and added to the costs of investment for each process, which leads to getting the current net value. The operating costs of the sewage plants are subdivided, in general, in the premises of the investment and operating costs. The latter can be stable (normal operation and maintenance, the establishment of power) or variables (chemical and power sludge treatment and disposal, of effluent charges). For the purpose of evaluating the preliminary costs so that an installation can choose between different alternatives in an incipient phase of a project, can be used cost functions. In this paper will be calculated the operational cost to make several scenarios in order to optimize its. Total operational cost (fixed and variable) is dependent global parameters of wastewater treatment plant. Research and methodology: The wastewater treatment plant costs are subdivided in investment and operating costs. We can use different cost functions to estimate fixed and variable operating costs. In this study we have used the statistical formulas for cost functions. The method which was applied to study the impact of the influent characteristics on the costs is economic analysis. Optimization of plant design consist in firstly, to assess the ability of the smallest design to treat the maximum loading rates to a given effluent quality and, secondly, to compare the cost of the two alternatives for average and maximum loading rates. Results: In this paper we obtained the statistical values for the investment cost functions, operational fixed costs and operational variable costs for wastewater treatment plant and its graphical representations. All costs were compared to the net values. Finally we observe that it is more economical to build a larger plant, especially if maximum loading rates are reached. The actual target of operational management is to directly implement the presented cost functions in a software tool, in which the design of a plant and the simulation of its behaviour are evaluated simultaneously.

A tabu search evalutionary algorithm for multiobjective optimization: Application to a bi-criterion aircraft structural reliability problem

NASA Astrophysics Data System (ADS)

Long, Kim Chenming

Real-world engineering optimization problems often require the consideration of multiple conflicting and noncommensurate objectives, subject to nonconvex constraint regions in a high-dimensional decision space. Further challenges occur for combinatorial multiobjective problems in which the decision variables are not continuous. Traditional multiobjective optimization methods of operations research, such as weighting and epsilon constraint methods, are ill-suited to solving these complex, multiobjective problems. This has given rise to the application of a wide range of metaheuristic optimization algorithms, such as evolutionary, particle swarm, simulated annealing, and ant colony methods, to multiobjective optimization. Several multiobjective evolutionary algorithms have been developed, including the strength Pareto evolutionary algorithm (SPEA) and the non-dominated sorting genetic algorithm (NSGA), for determining the Pareto-optimal set of non-dominated solutions. Although numerous researchers have developed a wide range of multiobjective optimization algorithms, there is a continuing need to construct computationally efficient algorithms with an improved ability to converge to globally non-dominated solutions along the Pareto-optimal front for complex, large-scale, multiobjective engineering optimization problems. This is particularly important when the multiple objective functions and constraints of the real-world system cannot be expressed in explicit mathematical representations. This research presents a novel metaheuristic evolutionary algorithm for complex multiobjective optimization problems, which combines the metaheuristic tabu search algorithm with the evolutionary algorithm (TSEA), as embodied in genetic algorithms. TSEA is successfully applied to bicriteria (i.e., structural reliability and retrofit cost) optimization of the aircraft tail structure fatigue life, which increases its reliability by prolonging fatigue life. A comparison for this application of the proposed algorithm, TSEA, with several state-of-the-art multiobjective optimization algorithms reveals that TSEA outperforms these algorithms by providing retrofit solutions with greater reliability for the same costs (i.e., closer to the Pareto-optimal front) after the algorithms are executed for the same number of generations. This research also demonstrates that TSEA competes with and, in some situations, outperforms state-of-the-art multiobjective optimization algorithms such as NSGA II and SPEA 2 when applied to classic bicriteria test problems in the technical literature and other complex, sizable real-world applications. The successful implementation of TSEA contributes to the safety of aeronautical structures by providing a systematic way to guide aircraft structural retrofitting efforts, as well as a potentially useful algorithm for a wide range of multiobjective optimization problems in engineering and other fields.

Dynamic modeling, experimental evaluation, optimal design and control of integrated fuel cell system and hybrid energy systems for building demands

NASA Astrophysics Data System (ADS)

Nguyen, Gia Luong Huu

Fuel cells can produce electricity with high efficiency, low pollutants, and low noise. With the advent of fuel cell technologies, fuel cell systems have since been demonstrated as reliable power generators with power outputs from a few watts to a few megawatts. With proper equipment, fuel cell systems can produce heating and cooling, thus increased its overall efficiency. To increase the acceptance from electrical utilities and building owners, fuel cell systems must operate more dynamically and integrate well with renewable energy resources. This research studies the dynamic performance of fuel cells and the integration of fuel cells with other equipment in three levels: (i) the fuel cell stack operating on hydrogen and reformate gases, (ii) the fuel cell system consisting of a fuel reformer, a fuel cell stack, and a heat recovery unit, and (iii) the hybrid energy system consisting of photovoltaic panels, fuel cell system, and energy storage. In the first part, this research studied the steady-state and dynamic performance of a high temperature PEM fuel cell stack. Collaborators at Aalborg University (Aalborg, Denmark) conducted experiments on a high temperature PEM fuel cell short stack at steady-state and transients. Along with the experimental activities, this research developed a first-principles dynamic model of a fuel cell stack. The dynamic model developed in this research was compared to the experimental results when operating on different reformate concentrations. Finally, the dynamic performance of the fuel cell stack for a rapid increase and rapid decrease in power was evaluated. The dynamic model well predicted the performance of the well-performing cells in the experimental fuel cell stack. The second part of the research studied the dynamic response of a high temperature PEM fuel cell system consisting of a fuel reformer, a fuel cell stack, and a heat recovery unit with high thermal integration. After verifying the model performance with the obtained experimental data, the research studied the control of airflow to regulate the temperature of reactors within the fuel processor. The dynamic model provided a platform to test the dynamic response for different control gains. With sufficient sensing and appropriate control, a rapid response to maintain the temperature of the reactor despite an increase in power was possible. The third part of the research studied the use of a fuel cell in conjunction with photovoltaic panels, and energy storage to provide electricity for buildings. This research developed an optimization framework to determine the size of each device in the hybrid energy system to satisfy the electrical demands of buildings and yield the lowest cost. The advantage of having the fuel cell with photovoltaic and energy storage was the ability to operate the fuel cell at baseload at night, thus reducing the need for large battery systems to shift the solar power produced in the day to the night. In addition, the dispatchability of the fuel cell provided an extra degree of freedom necessary for unforeseen disturbances. An operation framework based on model predictive control showed that the method is suitable for optimizing the dispatch of the hybrid energy system.

In vivo RF powering for advanced biological research.

PubMed

Zimmerman, Mark D; Chaimanonart, Nattapon; Young, Darrin J

2006-01-01

An optimized remote powering architecture with a miniature and implantable RF power converter for an untethered small laboratory animal inside a cage is proposed. The proposed implantable device exhibits dimensions less than 6 mmx6 mmx1 mm, and a mass of 100 mg including a medical-grade silicon coating. The external system consists of a Class-E power amplifier driving a tuned 15 cmx25 cm external coil placed underneath the cage. The implant device is located in the animal's abdomen in a plane parallel to the external coil and utilizes inductive coupling to receive power from the external system. A half-wave rectifier rectifies the received AC voltage and passes the resulting DC current to a 2.5 kOmega resistor, which represents the loading of an implantable microsystem. An optimal operating point with respect to operating frequency and number of turns in each coil inductor was determined by analyzing the system efficiency. The determined optimal operating condition is based on a 4-turn external coil and a 20-turn internal coil operating at 4 MHz. With the Class-E amplifier consuming a constant power of 25 W, this operating condition is sufficient to supply a desired 3.2 V with 1.3 mA to the load over a cage size of 10 cmx20 cm with an animal tilting angle of up to 60 degrees, which is the worst case considered for the prototype design. A voltage regulator can be designed to regulate the received DC power to a stable supply for the bio-implant microsystem.

Minimal complexity control law synthesis

NASA Technical Reports Server (NTRS)

Bernstein, Dennis S.; Haddad, Wassim M.; Nett, Carl N.

1989-01-01

A paradigm for control law design for modern engineering systems is proposed: Minimize control law complexity subject to the achievement of a specified accuracy in the face of a specified level of uncertainty. Correspondingly, the overall goal is to make progress towards the development of a control law design methodology which supports this paradigm. Researchers achieve this goal by developing a general theory of optimal constrained-structure dynamic output feedback compensation, where here constrained-structure means that the dynamic-structure (e.g., dynamic order, pole locations, zero locations, etc.) of the output feedback compensation is constrained in some way. By applying this theory in an innovative fashion, where here the indicated iteration occurs over the choice of the compensator dynamic-structure, the paradigm stated above can, in principle, be realized. The optimal constrained-structure dynamic output feedback problem is formulated in general terms. An elegant method for reducing optimal constrained-structure dynamic output feedback problems to optimal static output feedback problems is then developed. This reduction procedure makes use of star products, linear fractional transformations, and linear fractional decompositions, and yields as a byproduct a complete characterization of the class of optimal constrained-structure dynamic output feedback problems which can be reduced to optimal static output feedback problems. Issues such as operational/physical constraints, operating-point variations, and processor throughput/memory limitations are considered, and it is shown how anti-windup/bumpless transfer, gain-scheduling, and digital processor implementation can be facilitated by constraining the controller dynamic-structure in an appropriate fashion.

Divergent estimation error in portfolio optimization and in linear regression

NASA Astrophysics Data System (ADS)

Kondor, I.; Varga-Haszonits, I.

2008-08-01

The problem of estimation error in portfolio optimization is discussed, in the limit where the portfolio size N and the sample size T go to infinity such that their ratio is fixed. The estimation error strongly depends on the ratio N/T and diverges for a critical value of this parameter. This divergence is the manifestation of an algorithmic phase transition, it is accompanied by a number of critical phenomena, and displays universality. As the structure of a large number of multidimensional regression and modelling problems is very similar to portfolio optimization, the scope of the above observations extends far beyond finance, and covers a large number of problems in operations research, machine learning, bioinformatics, medical science, economics, and technology.

Engineering tradeoff problems viewed as multiple objective optimizations and the VODCA methodology

NASA Astrophysics Data System (ADS)

Morgan, T. W.; Thurgood, R. L.

1984-05-01

This paper summarizes a rational model for making engineering tradeoff decisions. The model is a hybrid from the fields of social welfare economics, communications, and operations research. A solution methodology (Vector Optimization Decision Convergence Algorithm - VODCA) firmly grounded in the economic model is developed both conceptually and mathematically. The primary objective for developing the VODCA methodology was to improve the process for extracting relative value information about the objectives from the appropriate decision makers. This objective was accomplished by employing data filtering techniques to increase the consistency of the relative value information and decrease the amount of information required. VODCA is applied to a simplified hypothetical tradeoff decision problem. Possible use of multiple objective analysis concepts and the VODCA methodology in product-line development and market research are discussed.

Distinctions between intelligent manufactured and constructed systems and a new discipline for intelligent infrastructure hypersystems

NASA Astrophysics Data System (ADS)

Aktan, A. Emin

2003-08-01

Although the interconnected systems nature of the infrastructures, and the complexity of interactions between their engineered, socio-technical and natural constituents have been recognized for some time, the principles of effectively operating, protecting and preserving such systems by taking full advantage of "modeling, simulations, optimization, control and decision making" tools developed by the systems engineering and operations research community have not been adequately studied or discussed by many engineers including the writer. Differential and linear equation systems, numerical and finite element modeling techniques, statistical and probabilistic representations are universal, however, different disciplines have developed their distinct approaches to conceptualizing, idealizing and modeling the systems they commonly deal with. The challenge is in adapting and integrating deterministic and stochastic, geometric and numerical, physics-based and "soft (data-or-knowledge based)", macroscopic or microscopic models developed by various disciplines for simulating infrastructure systems. There is a lot to be learned by studying how different disciplines have studied, improved and optimized the systems relating to various processes and products in their domains. Operations research has become a fifty-year old discipline addressing complex systems problems. Its mathematical tools range from linear programming to decision processes and game theory. These tools are used extensively in management and finance, as well as by industrial engineers for optimizing and quality control. Progressive civil engineering academic programs have adopted "systems engineering" as a focal area. However, most of the civil engineering systems programs remain focused on constructing and analyzing highly idealized, often generic models relating to the planning or operation of transportation, water or waste systems, maintenance management, waste management or general infrastructure hazards risk management. We further note that in the last decade there have been efforts for "agent-based" modeling of synthetic infrastructure systems by taking advantage of supercomputers at various DOE Laboratories. However, whether there is any similitude between such synthetic and actual systems needs investigating further.

Improving the performance of surgery-based clinical pathways: a simulation-optimization approach.

PubMed

Ozcan, Yasar A; Tànfani, Elena; Testi, Angela

2017-03-01

This paper aims to improve the performance of clinical processes using clinical pathways (CPs). The specific goal of this research is to develop a decision support tool, based on a simulation-optimization approach, which identify the proper adjustment and alignment of resources to achieve better performance for both the patients and the health-care facility. When multiple perspectives are present in a decision problem, critical issues arise and often require the balancing of goals. In our approach, meeting patients' clinical needs in a timely manner, and to avoid worsening of clinical conditions, we assess the level of appropriate resources. The simulation-optimization model seeks and evaluates alternative resource configurations aimed at balancing the two main objectives-meeting patient needs and optimal utilization of beds and operating rooms.Using primary data collected at a Department of Surgery of a public hospital located in Genoa, Italy. The simulation-optimization modelling approach in this study has been applied to evaluate the thyroid surgical treatment together with the other surgery-based CPs. The low rate of bed utilization and the long elective waiting lists of the specialty under study indicates that the wards were oversized while the operating room capacity was the bottleneck of the system. The model enables hospital managers determine which objective has to be given priority, as well as the corresponding opportunity costs.

Surgery scheduling optimization considering real life constraints and comprehensive operation cost of operating room.

PubMed

Xiang, Wei; Li, Chong

2015-01-01

Operating Room (OR) is the core sector in hospital expenditure, the operation management of which involves a complete three-stage surgery flow, multiple resources, prioritization of the various surgeries, and several real-life OR constraints. As such reasonable surgery scheduling is crucial to OR management. To optimize OR management and reduce operation cost, a short-term surgery scheduling problem is proposed and defined based on the survey of the OR operation in a typical hospital in China. The comprehensive operation cost is clearly defined considering both under-utilization and overutilization. A nested Ant Colony Optimization (nested-ACO) incorporated with several real-life OR constraints is proposed to solve such a combinatorial optimization problem. The 10-day manual surgery schedules from a hospital in China are compared with the optimized schedules solved by the nested-ACO. Comparison results show the advantage using the nested-ACO in several measurements: OR-related time, nurse-related time, variation in resources' working time, and the end time. The nested-ACO considering real-life operation constraints such as the difference between first and following case, surgeries priority, and fixed nurses in pre/post-operative stage is proposed to solve the surgery scheduling optimization problem. The results clearly show the benefit of using the nested-ACO in enhancing the OR management efficiency and minimizing the comprehensive overall operation cost.

Correlation analysis on real-time tab-delimited network monitoring data

DOE PAGES

Pan, Aditya; Majumdar, Jahin; Bansal, Abhay; ...

2016-01-01

End-End performance monitoring in the Internet, also called PingER is a part of SLAC National Accelerator Laboratory’s research project. It was created to answer the growing need to monitor network both to analyze current performance and to designate resources to optimize execution between research centers, and the universities and institutes co-operating on present and future operations. The monitoring support reflects the broad geographical area of the collaborations and requires a comprehensive number of research and financial channels. The data architecture retrieval and methodology of the interpretation have emerged over numerous years. Analyzing this data is the main challenge due tomore » its high volume. Finally, by using correlation analysis, we can make crucial conclusions about how the network data affects the performance of the hosts and how it depends from countries to countries.« less

Intelligent systems installed in building of research centre for research purposes

NASA Astrophysics Data System (ADS)

Matusov, Jozef; Mokry, Marian; Kolkova, Zuzana; Sedivy, Stefan

2016-06-01

The attractiveness of intelligent buildings is nowadays directly connected with higher level of comfort and also the economic mode of consumption energy for heating, cooling and the total consumption of electricity for electric devices. The technologies of intelligent buildings compared with conventional solutions allow dynamic optimization in real time and make it easy for operational message. The basic division of functionality in horizontal direction is possible divide in to two areas such as Economical sophisticated residential care about the comfort of people in the building and Security features. The paper deals with description of intelligent systems which has a building of Research Centre. The building has installed the latest technology for utilization of renewable energy and also latest systems of controlling and driving all devices which contribute for economy operation by achieving the highest thermal comfort and overall safety.

Research Turbine Leaves Legacy in Its Wake | News | NREL

Science.gov Websites

110. Two 340-foot cranes were needed to install the larger, 175-foot blades optimized for intermediate depending, to remove the blades, then the nacelle, and finally the tower, section by section. "Site operating the turbine, but also performing complex procedures-like changing out blades that weigh more than

An Analysis of Excellent Early Educational Practices: Preliminary Report.

ERIC Educational Resources Information Center

White, Burton L.

This document reports the first phase of a longitudinal research project designed to produce information on how to raise children so their basic abilities may develop optimally during the first six years of life. Although this Preschool Project has been in operation five years, the study is not yet completed because statements about the effects of…

Optimizing the Disposition and Retrograde of United States Air Force Class VII Equipment from Afghanistan

DTIC Science & Technology

2014-03-27

1959). On a linear-programming, combinatorial approach to the traveling - salesman problem . Operations Research, 58-66. Daugherty, P. J., Myers, M. B...1 Problem Statement... Problem Statement As of 01 September 2013, the USAF is tracking 12,571 individual Class VII assets valued at $213.5 million for final disposition

Space Human Factors: Research to Application

NASA Technical Reports Server (NTRS)

Woolford, Barbara

2008-01-01

Human Factors has been instrumental in preventing potential on-orbit hazards and increasing overall crew safety. Poor performance & operational learning curves on-orbit are mitigated. Human-centered design is applied to optimize design and minimize potentially hazardous conditions, especially with larger crew sizes and habitat constraints. Lunar and Mars requirements and design developments are enhanced, based on ISS Lessons Learned.

A rapid and low energy consumption method to decolorize the high concentration triphenylmethane dye wastewater: operational parameters optimization for the ultrasonic-assisted ozone oxidation process.

PubMed

Zhou, Xian-Jiao; Guo, Wan-Qian; Yang, Shan-Shan; Ren, Nan-Qi

2012-02-01

This research set up an ultrasonic-assisted ozone oxidation process (UAOOP) to decolorize the triphenylmethane dyes wastewater. Five factors - temperature, initial pH, reaction time, ultrasonic power (low frequency 20 kHz), and ozone concentration - were investigated. Response surface methodology was used to find out the major factors influencing color removal rate and the interactions between these factors, and optimized the operating parameters as well. Under the experimental conditions: reaction temperature 39.81 °C, initial pH 5.29, ultrasonic power 60 W and ozone concentration 0.17 g/L, the highest color removals were achieved with 10 min reaction time and the initial concentration of the MG solution was 1000 mg/L. The optimal results indicated that the UAOOP was a rapid, efficient and low energy consumption technique to decolorize the high concentration MG wastewater. The predicted model was approximately in accordance with the experimental cases with correlation coefficients R(2) and R(adj)(2) of 0.9103 and 0.8386. Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.

Optimization of Multiple and Multipurpose Reservoir System Operations by Using Matrix Structure (Case Study: Karun and Dez Reservoir Dams)

PubMed Central

Othman, Faridah; Taghieh, Mahmood

2016-01-01

Optimal operation of water resources in multiple and multipurpose reservoirs is very complicated. This is because of the number of dams, each dam’s location (Series and parallel), conflict in objectives and the stochastic nature of the inflow of water in the system. In this paper, performance optimization of the system of Karun and Dez reservoir dams have been studied and investigated with the purposes of hydroelectric energy generation and providing water demand in 6 dams. On the Karun River, 5 dams have been built in the series arrangements, and the Dez dam has been built parallel to those 5 dams. One of the main achievements in this research is the implementation of the structure of production of hydroelectric energy as a function of matrix in MATLAB software. The results show that the role of objective function structure for generating hydroelectric energy in weighting method algorithm is more important than water supply. Nonetheless by implementing ε- constraint method algorithm, we can both increase hydroelectric power generation and supply around 85% of agricultural and industrial demands. PMID:27248152

Optimization of the time-dependent traveling salesman problem with Monte Carlo methods.

PubMed

Bentner, J; Bauer, G; Obermair, G M; Morgenstern, I; Schneider, J

2001-09-01

A problem often considered in operations research and computational physics is the traveling salesman problem, in which a traveling salesperson has to find the shortest closed tour between a certain set of cities. This problem has been extended to more realistic scenarios, e.g., the "real" traveling salesperson has to take rush hours into consideration. We will show how this extended problem is treated with physical optimization algorithms. We will present results for a specific instance of Reinelt's library TSPLIB95, in which we define a zone with traffic jams in the afternoon.

NOAA Marine and Arctic Monitoring Using UASs

NASA Astrophysics Data System (ADS)

Jacobs, T.; Coffey, J. J.; Hood, R. E.; Hall, P.; Adler, J.

2014-12-01

Unmanned systems have the potential to efficiently, effectively, economically and safely bridging critical observation requirements in an environmentally friendly manner. As the United States' Marine and Arctic areas of interest expand and include hard-to-reach regions of the Earth (such as the Arctic and remote oceanic areas) optimizing unmanned capabilities will be needed to advance the United States' science, technology and security efforts. Through increased multi-mission and multi-agency operations using improved inter-operable and autonomous unmanned systems, the research and operations communities will better collect environmental intelligence and better protect our Country against hazardous weather, environmental, marine and polar hazards. This presentation will examine NOAA's Marine and Arctic Monitoring UAS strategies which includes developing a coordinated effort to maximize the efficiency and capabilities of unmanned systems across the federal government and research partners. Numerous intra- and inter-agency operational demonstrations and assessments have been made to verify and validated these strategies. The presentation will also discuss the requisite sUAS capabilities and our experience in using them.

Research on breakdown characteristics of converter transformer oil-paper insulation under compound electric field in alpine region

NASA Astrophysics Data System (ADS)

Xu, C.; Gao, Z. W.; Lan, S.; Guo, H. X.; Gong, M. C.

2018-01-01

In the paper, existing research and operating experience was summarized. On the basis, the particularity of oil-paper insulation operation condition for converter transformer was combined for studying the influence of temperature on oil-paper insulation field intensity distribution of converter transformers under different AC contents within wide temperature scope (-40°C∼105°C). The law of temperature gradients on space charge accumulation was analyzed. The breakdown or flashover characteristics of typical oil-paper compound insulation structure under the action of DC, AC and AC-DC superposition voltage at different temperatures were explored. The design principles of converter transformer oil-paper insulation structures in alpine region was proposed. The principle was adjusted and optimized properly according to the operation temperature scope and withstood AC-DC proportion. The reliability of transformer operation was improved on the one hand, and the insulating medium can be rationally utilized for reducing the manufacturing cost of the transformer on the other hand.

Advanced I&C for Fault-Tolerant Supervisory Control of Small Modular Reactors

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

Cole, Daniel G.

In this research, we have developed a supervisory control approach to enable automated control of SMRs. By design the supervisory control system has an hierarchical, interconnected, adaptive control architecture. A considerable advantage to this architecture is that it allows subsystems to communicate at different/finer granularity, facilitates monitoring of process at the modular and plant levels, and enables supervisory control. We have investigated the deployment of automation, monitoring, and data collection technologies to enable operation of multiple SMRs. Each unit's controller collects and transfers information from local loops and optimize that unit’s parameters. Information is passed from the each SMR unitmore » controller to the supervisory controller, which supervises the actions of SMR units and manage plant processes. The information processed at the supervisory level will provide operators the necessary information needed for reactor, unit, and plant operation. In conjunction with the supervisory effort, we have investigated techniques for fault-tolerant networks, over which information is transmitted between local loops and the supervisory controller to maintain a safe level of operational normalcy in the presence of anomalies. The fault-tolerance of the supervisory control architecture, the network that supports it, and the impact of fault-tolerance on multi-unit SMR plant control has been a second focus of this research. To this end, we have investigated the deployment of advanced automation, monitoring, and data collection and communications technologies to enable operation of multiple SMRs. We have created a fault-tolerant multi-unit SMR supervisory controller that collects and transfers information from local loops, supervise their actions, and adaptively optimize the controller parameters. The goal of this research has been to develop the methodologies and procedures for fault-tolerant supervisory control of small modular reactors. To achieve this goal, we have identified the following objectives. These objective are an ordered approach to the research: I) Development of a supervisory digital I&C system II) Fault-tolerance of the supervisory control architecture III) Automated decision making and online monitoring.« less

Distortionary effects of a production-sharing fiscal system in a sequential modular offshore petroleum project

NASA Astrophysics Data System (ADS)

Neves de Campos, Thiago

This research examines the distortionary effects of a discovered and undeveloped sequential modular offshore project under five different designs for a production-sharing agreement (PSA). The model differs from previous research by looking at the effect of taxation from the perspective of a host government, where the objective is to maximize government utility over government revenue generated by the project and the non-pecuniary benefits to society. This research uses Modern Asset Pricing (MAP) theory, which is able to provide a good measure of the asset value accruing to various stakeholders in the project combined with the optimal decision rule for the development of the investment opportunity. Monte Carlo simulation was also applied to incorporate into the model the most important sources of risk associated with the project and to account for non-linearity in the cash flows. For a complete evaluation of how the fiscal system affects the project development, an investor's behavioral model was constructed, incorporating three operational decisions: investment timing, capacity size and early abandonment. The model considers four sources of uncertainty that affect the project value and the firm's optimal decision: the long run oil price and short-run deviations from that price, cost escalation and the reservoir recovery rate. The optimizations outcomes show that all fiscal systems evaluated produce distortion over the companies' optimal decisions, and companies adjust their choices to avoid taxation in different ways according to the fiscal system characteristics. Moreover, it is revealed that fiscal systems with tax provisions that try to capture additional project profits based on production profitability measures leads to stronger distortions in the project investment and output profile. It is also shown that a model based on a fixed percentage rate is the system that creates the least distortion. This is because companies will be subjected to the same government share of profit oil independently of any operational decision which they can make to change the production profile to evade taxation.

Metaheuristic simulation optimisation for the stochastic multi-retailer supply chain

NASA Astrophysics Data System (ADS)

Omar, Marina; Mustaffa, Noorfa Haszlinna H.; Othman, Siti Norsyahida

2013-04-01

Supply Chain Management (SCM) is an important activity in all producing facilities and in many organizations to enable vendors, manufacturers and suppliers to interact gainfully and plan optimally their flow of goods and services. A simulation optimization approach has been widely used in research nowadays on finding the best solution for decision-making process in Supply Chain Management (SCM) that generally faced a complexity with large sources of uncertainty and various decision factors. Metahueristic method is the most popular simulation optimization approach. However, very few researches have applied this approach in optimizing the simulation model for supply chains. Thus, this paper interested in evaluating the performance of metahueristic method for stochastic supply chains in determining the best flexible inventory replenishment parameters that minimize the total operating cost. The simulation optimization model is proposed based on the Bees algorithm (BA) which has been widely applied in engineering application such as training neural networks for pattern recognition. BA is a new member of meta-heuristics. BA tries to model natural behavior of honey bees in food foraging. Honey bees use several mechanisms like waggle dance to optimally locate food sources and to search new ones. This makes them a good candidate for developing new algorithms for solving optimization problems. This model considers an outbound centralised distribution system consisting of one supplier and 3 identical retailers and is assumed to be independent and identically distributed with unlimited supply capacity at supplier.

Service-Oriented Architectures and Project Optimization for a Special Cost Management Problem Creating Synergies for Informed Change between Qualitative and Quantitative Strategic Management Processes

DTIC Science & Technology

2010-05-01

Science, Werner Heisenberg -Weg 39,85577 Neubiberg, Germany,CA,93943 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S...University of the Federal Armed Forces of Germany Institute for Theoretic Computer Science Mathematics and Operations Research Werner Heisenberg -Weg...Research Werner Heisenberg -Weg 39 85577 Neubiberg, Germany Phone +49 89 6004 2400 Marco Schuler—Marco Schuler is an active Officer of the Federal

EC97-44347-15

NASA Image and Video Library

1997-12-11

This console and its compliment of computers, monitors and commmunications equipment make up the Research Engineering Test Station, the nerve center for an aerodynamics experiment conducted by NASA's Dryden Flight Research Center, Edwards, California. The equipment was installed on a modified Lockheed L-1011 Tristar jetliner operated by Orbital Sciences Corp., of Dulles, Va., for Dryden's Adaptive Performance Optimization project. The experiment sought to improve the efficiency of long-range jetliners by using small movements of the ailerons to improve the aerodynamics of the wing at cruise conditions.

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

Rios-Torres, Jackeline; Malikopoulos, Andreas A.

Connected and automated vehicles (CAVs) have the potential to improve safety by reducing and mitigating traffic accidents. They can also provide opportunities to reduce transportation energy consumption and emissions by improving traffic flow. Vehicle communication with traffic structures and traffic lights can allow individual vehicles to optimize their operation and account for unpredictable changes. This paper summarizes the developments and the research trends in coordination with the CAVs that have been reported in the literature to date. In conclusion, remaining challenges and potential future research directions are also discussed.

Leveraging Trauma Lessons from War to Win in a Complex Global Environment.

PubMed

Remick, Kyle N

2016-01-01

The US military has made great strides in combat casualty care since 2001. As the Army concludes combat operations in Iraq and Afghanistan, it faces new operational challenges in trauma care. The military medical community must stay ahead of the curve through sustaining current investments in combat casualty care research. This article describes lessons learned at war from a Joint Trauma System perspective in order to place in context how we should proceed in order to provide optimal care for our Warfighters in the future.

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.

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.

Restless Tuneup of High-Fidelity Qubit Gates

NASA Astrophysics Data System (ADS)

Rol, M. A.; Bultink, C. C.; O'Brien, T. E.; de Jong, S. R.; Theis, L. S.; Fu, X.; Luthi, F.; Vermeulen, R. F. L.; de Sterke, J. C.; Bruno, A.; Deurloo, D.; Schouten, R. N.; Wilhelm, F. K.; Dicarlo, L.

We present a tuneup protocol for qubit gates with tenfold speedup over traditional methods reliant on qubit initialization by energy relax- ation. This speedup is achieved by constructing a cost function for Nelder-Mead optimization from real-time correlation of non-demolition measurements interleaving gate operations without pause. Applying the protocol on a transmon qubit achieves 0.999 average Clifford fidelity in one minute, as independently verified using randomized benchmarking and gate set tomography. The adjustable sensitivity of the cost function allows detecting fractional reductions in gate error with constant signal- to-noise ratio. The restless concept here demonstrated can be readily extended to the tuneup of two-qubit gates and measurement operations. Research funded by IARPA, an ERC Synergy Grant, Microsoft Research, and the China Scholarship Council.

Development and application of computer assisted optimal method for treatment of femoral neck fracture.

PubMed

Wang, Monan; Zhang, Kai; Yang, Ning

2018-04-09

To help doctors decide their treatment from the aspect of mechanical analysis, the work built a computer assisted optimal system for treatment of femoral neck fracture oriented to clinical application. The whole system encompassed the following three parts: Preprocessing module, finite element mechanical analysis module, post processing module. Preprocessing module included parametric modeling of bone, parametric modeling of fracture face, parametric modeling of fixed screw and fixed position and input and transmission of model parameters. Finite element mechanical analysis module included grid division, element type setting, material property setting, contact setting, constraint and load setting, analysis method setting and batch processing operation. Post processing module included extraction and display of batch processing operation results, image generation of batch processing operation, optimal program operation and optimal result display. The system implemented the whole operations from input of fracture parameters to output of the optimal fixed plan according to specific patient real fracture parameter and optimal rules, which demonstrated the effectiveness of the system. Meanwhile, the system had a friendly interface, simple operation and could improve the system function quickly through modifying single module.

Optimal robust control strategy of a solid oxide fuel cell system

NASA Astrophysics Data System (ADS)

Wu, Xiaojuan; Gao, Danhui

2018-01-01

Optimal control can ensure system safe operation with a high efficiency. However, only a few papers discuss optimal control strategies for solid oxide fuel cell (SOFC) systems. Moreover, the existed methods ignore the impact of parameter uncertainty on system instantaneous performance. In real SOFC systems, several parameters may vary with the variation of operation conditions and can not be identified exactly, such as load current. Therefore, a robust optimal control strategy is proposed, which involves three parts: a SOFC model with parameter uncertainty, a robust optimizer and robust controllers. During the model building process, boundaries of the uncertain parameter are extracted based on Monte Carlo algorithm. To achieve the maximum efficiency, a two-space particle swarm optimization approach is employed to obtain optimal operating points, which are used as the set points of the controllers. To ensure the SOFC safe operation, two feed-forward controllers and a higher-order robust sliding mode controller are presented to control fuel utilization ratio, air excess ratio and stack temperature afterwards. The results show the proposed optimal robust control method can maintain the SOFC system safe operation with a maximum efficiency under load and uncertainty variations.

Application of the gravity search algorithm to multi-reservoir operation optimization

NASA Astrophysics Data System (ADS)

Bozorg-Haddad, Omid; Janbaz, Mahdieh; Loáiciga, Hugo A.

2016-12-01

Complexities in river discharge, variable rainfall regime, and drought severity merit the use of advanced optimization tools in multi-reservoir operation. The gravity search algorithm (GSA) is an evolutionary optimization algorithm based on the law of gravity and mass interactions. This paper explores the GSA's efficacy for solving benchmark functions, single reservoir, and four-reservoir operation optimization problems. The GSA's solutions are compared with those of the well-known genetic algorithm (GA) in three optimization problems. The results show that the GSA's results are closer to the optimal solutions than the GA's results in minimizing the benchmark functions. The average values of the objective function equal 1.218 and 1.746 with the GSA and GA, respectively, in solving the single-reservoir hydropower operation problem. The global solution equals 1.213 for this same problem. The GSA converged to 99.97% of the global solution in its average-performing history, while the GA converged to 97% of the global solution of the four-reservoir problem. Requiring fewer parameters for algorithmic implementation and reaching the optimal solution in fewer number of functional evaluations are additional advantages of the GSA over the GA. The results of the three optimization problems demonstrate a superior performance of the GSA for optimizing general mathematical problems and the operation of reservoir systems.

Gamifying quantum research: harnessing human intuition

NASA Astrophysics Data System (ADS)

Sherson, Jacob

In the emerging field of citizen science ordinary citizens have already contributed to research in as diverse fields as astronomy, protein and RNA folding, and neuron mapping by playing online games. In the www.scienceathome.org project, we have extended this democratized research to the realm of quantum physics by gamifying a class of challenges related to optimization of gate operations in a quantum computer. The games have been played by more than 150,000 players and perhaps surprisingly we observe that a large fraction of the players outperform state-of-the-art optimization algorithms. With a palette of additional games within cognitive science, behavioral economics, and corporate innovation we investigate the general features of individual and collaborative problem solving to shed additional light on the process of human intuition and innovation and potentially develop novel models of artificial intelligence. We have also developed and tested in classrooms educational games within classical and quantum physics and mathematics at high-school and university level. The games provide individualized learning and enhance motivation for the core curriculum by actively creating links to modern research challenges, see eg. Finally, we have recently launched our new democratic lab: an easily accessible remote interface for our ultra-cold atoms experiment allowing amateur scientists, students, and research institutions world-wide to perform state-of-the-art quantum experimentation. In first tests, nearly a thousand players helped optimize the production of our BEC and discovered novel efficient strategies.

Estimating patient-specific soft-tissue properties in a TKA knee.

PubMed

Ewing, Joseph A; Kaufman, Michelle K; Hutter, Erin E; Granger, Jeffrey F; Beal, Matthew D; Piazza, Stephen J; Siston, Robert A

2016-03-01

Surgical technique is one factor that has been identified as critical to success of total knee arthroplasty. Researchers have shown that computer simulations can aid in determining how decisions in the operating room generally affect post-operative outcomes. However, to use simulations to make clinically relevant predictions about knee forces and motions for a specific total knee patient, patient-specific models are needed. This study introduces a methodology for estimating knee soft-tissue properties of an individual total knee patient. A custom surgical navigation system and stability device were used to measure the force-displacement relationship of the knee. Soft-tissue properties were estimated using a parameter optimization that matched simulated tibiofemoral kinematics with experimental tibiofemoral kinematics. Simulations using optimized ligament properties had an average root mean square error of 3.5° across all tests while simulations using generic ligament properties taken from literature had an average root mean square error of 8.4°. Specimens showed large variability among ligament properties regardless of similarities in prosthetic component alignment and measured knee laxity. These results demonstrate the importance of soft-tissue properties in determining knee stability, and suggest that to make clinically relevant predictions of post-operative knee motions and forces using computer simulations, patient-specific soft-tissue properties are needed. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Costs of Limiting Route Optimization to Published Waypoints in the Traffic Aware Planner

NASA Technical Reports Server (NTRS)

Karr, David A.; Vivona, Robert A.; Wing, David J.

2013-01-01

The Traffic Aware Planner (TAP) is an airborne advisory tool that generates optimized, traffic-avoiding routes to support the aircraft crew in making strategic reroute requests to Air Traffic Control (ATC). TAP is derived from a research-prototype self-separation tool, the Autonomous Operations Planner (AOP), in which optimized route modifications that avoid conflicts with traffic and weather, using waypoints at explicit latitudes and longitudes (a technique supported by self-separation concepts), are generated by maneuver patterns applied to the existing route. For use in current-day operations in which trajectory changes must be requested from ATC via voice communication, TAP produces optimized routes described by advisories that use only published waypoints prior to a reconnection waypoint on the existing route. We describe how the relevant algorithms of AOP have been modified to implement this requirement. The modifications include techniques for finding appropriate published waypoints in a maneuver pattern and a method for combining the genetic algorithm of AOP with an exhaustive search of certain types of advisory. We demonstrate methods to investigate the increased computation required by these techniques and to estimate other costs (measured in terms such as time to destination and fuel burned) that may be incurred when only published waypoints are used.

Effect and interaction study of acetamiprid photodegradation using experimental design.

PubMed

Tassalit, Djilali; Chekir, Nadia; Benhabiles, Ouassila; Mouzaoui, Oussama; Mahidine, Sarah; Merzouk, Nachida Kasbadji; Bentahar, Fatiha; Khalil, Abbas

2016-10-01

The methodology of experimental research was carried out using the MODDE 6.0 software to study the acetamiprid photodegradation depending on the operating parameters, such as the initial concentration of acetamiprid, concentration and type of the used catalyst and the initial pH of the medium. The results showed the importance of the pollutant concentration effect on the acetamiprid degradation rate. On the other hand, the amount and type of the used catalyst have a considerable influence on the elimination kinetics of this pollutant. The degradation of acetamiprid as an environmental pesticide pollutant via UV irradiation in the presence of titanium dioxide was assessed and optimized using response surface methodology with a D-optimal design. The acetamiprid degradation ratio was found to be sensitive to the different studied factors. The maximum value of discoloration under the optimum operating conditions was determined to be 99% after 300 min of UV irradiation.

DIII-D accomplishments and plans in support of fusion next steps

DOE PAGES

Buttery, R. J; Eidietis, N.; Holcomb, C.; ...

2013-06-01

DIII-D is using its flexibility and diagnostics to address the critical science required to enable next step fusion devices. We have adapted operating scenarios for ITER to low torque and are now being optimized for transport. Three ELM mitigation scenarios have been developed to near-ITER parameters. New control techniques are managing the most challenging plasma instabilities. Disruption mitigation tools show promising dissipation strategies for runaway electrons and heat load. An off axis neutral beam upgrade has enabled sustainment of high βN capable steady state regimes. Divertor research is identifying the challenge, physics and candidate solutions for handling the hot plasmamore » exhaust with notable progress in heat flux reduction using the snowflake configuration. Our work is helping optimize design choices and prepare the scientific tools for operation in ITER, and resolve key elements of the plasma configuration and divertor solution for an FNSF.« less

Fuzzy linear model for production optimization of mining systems with multiple entities

NASA Astrophysics Data System (ADS)

Vujic, Slobodan; Benovic, Tomo; Miljanovic, Igor; Hudej, Marjan; Milutinovic, Aleksandar; Pavlovic, Petar

2011-12-01

Planning and production optimization within multiple mines or several work sites (entities) mining systems by using fuzzy linear programming (LP) was studied. LP is the most commonly used operations research methods in mining engineering. After the introductory review of properties and limitations of applying LP, short reviews of the general settings of deterministic and fuzzy LP models are presented. With the purpose of comparative analysis, the application of both LP models is presented using the example of the Bauxite Basin Niksic with five mines. After the assessment, LP is an efficient mathematical modeling tool in production planning and solving many other single-criteria optimization problems of mining engineering. After the comparison of advantages and deficiencies of both deterministic and fuzzy LP models, the conclusion presents benefits of the fuzzy LP model but is also stating that seeking the optimal plan of production means to accomplish the overall analysis that will encompass the LP model approaches.

Optimal Control Method of Robot End Position and Orientation Based on Dynamic Tracking Measurement

NASA Astrophysics Data System (ADS)

Liu, Dalong; Xu, Lijuan

2018-01-01

In order to improve the accuracy of robot pose positioning and control, this paper proposed a dynamic tracking measurement robot pose optimization control method based on the actual measurement of D-H parameters of the robot, the parameters is taken with feedback compensation of the robot, according to the geometrical parameters obtained by robot pose tracking measurement, improved multi sensor information fusion the extended Kalan filter method, with continuous self-optimal regression, using the geometric relationship between joint axes for kinematic parameters in the model, link model parameters obtained can timely feedback to the robot, the implementation of parameter correction and compensation, finally we can get the optimal attitude angle, realize the robot pose optimization control experiments were performed. 6R dynamic tracking control of robot joint robot with independent research and development is taken as experimental subject, the simulation results show that the control method improves robot positioning accuracy, and it has the advantages of versatility, simplicity, ease of operation and so on.

Applications of Evolutionary Technology to Manufacturing and Logistics Systems : State-of-the Art Survey

NASA Astrophysics Data System (ADS)

Gen, Mitsuo; Lin, Lin

Many combinatorial optimization problems from industrial engineering and operations research in real-world are very complex in nature and quite hard to solve them by conventional techniques. Since the 1960s, there has been an increasing interest in imitating living beings to solve such kinds of hard combinatorial optimization problems. Simulating the natural evolutionary process of human beings results in stochastic optimization techniques called evolutionary algorithms (EAs), which can often outperform conventional optimization methods when applied to difficult real-world problems. In this survey paper, we provide a comprehensive survey of the current state-of-the-art in the use of EA in manufacturing and logistics systems. In order to demonstrate the EAs which are powerful and broadly applicable stochastic search and optimization techniques, we deal with the following engineering design problems: transportation planning models, layout design models and two-stage logistics models in logistics systems; job-shop scheduling, resource constrained project scheduling in manufacturing system.

An Optimization Framework for Driver Feedback Systems

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

Malikopoulos, Andreas; Aguilar, Juan P.

2013-01-01

Modern vehicles have sophisticated electronic control units that can control engine operation with discretion to balance fuel economy, emissions, and power. These control units are designed for specific driving conditions (e.g., different speed profiles for highway and city driving). However, individual driving styles are different and rarely match the specific driving conditions for which the units were designed. In the research reported here, we investigate driving-style factors that have a major impact on fuel economy and construct an optimization framework to optimize individual driving styles with respect to these driving factors. In this context, we construct a set of polynomialmore » metamodels to reflect the responses produced in fuel economy by changing the driving factors. Then, we compare the optimized driving styles to the original driving styles and evaluate the effectiveness of the optimization framework. Finally, we use this proposed framework to develop a real-time feedback system, including visual instructions, to enable drivers to alter their driving styles in response to actual driving conditions to improve fuel efficiency.« less

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

NASA Astrophysics Data System (ADS)

Sue-Ann, Goh; Ponnambalam, S. G.

This paper focuses on the operational issues of a Two-echelon Single-Vendor-Multiple-Buyers Supply chain (TSVMBSC) under vendor managed inventory (VMI) mode of operation. To determine the optimal sales quantity for each buyer in TSVMBC, a mathematical model is formulated. Based on the optimal sales quantity can be obtained and the optimal sales price that will determine the optimal channel profit and contract price between the vendor and buyer. All this parameters depends upon the understanding of the revenue sharing between the vendor and buyers. A Particle Swarm Optimization (PSO) is proposed for this problem. Solutions obtained from PSO is compared with the best known results reported in literature.

Analytical design of an industrial two-term controller for optimal regulatory control of open-loop unstable processes under operational constraints.

PubMed

Tchamna, Rodrigue; Lee, Moonyong

2018-01-01

This paper proposes a novel optimization-based approach for the design of an industrial two-term proportional-integral (PI) controller for the optimal regulatory control of unstable processes subjected to three common operational constraints related to the process variable, manipulated variable and its rate of change. To derive analytical design relations, the constrained optimal control problem in the time domain was transformed into an unconstrained optimization problem in a new parameter space via an effective parameterization. The resulting optimal PI controller has been verified to yield optimal performance and stability of an open-loop unstable first-order process under operational constraints. The proposed analytical design method explicitly takes into account the operational constraints in the controller design stage and also provides useful insights into the optimal controller design. Practical procedures for designing optimal PI parameters and a feasible constraint set exclusive of complex optimization steps are also proposed. The proposed controller was compared with several other PI controllers to illustrate its performance. The robustness of the proposed controller against plant-model mismatch has also been investigated. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

System and method of cylinder deactivation for optimal engine torque-speed map operation

DOEpatents

Sujan, Vivek A; Frazier, Timothy R; Follen, Kenneth; Moon, Suk-Min

2014-11-11

This disclosure provides a system and method for determining cylinder deactivation in a vehicle engine to optimize fuel consumption while providing the desired or demanded power. In one aspect, data indicative of terrain variation is utilized in determining a vehicle target operating state. An optimal active cylinder distribution and corresponding fueling is determined from a recommendation from a supervisory agent monitoring the operating state of the vehicle of a subset of the total number of cylinders, and a determination as to which number of cylinders provides the optimal fuel consumption. Once the optimal cylinder number is determined, a transmission gear shift recommendation is provided in view of the determined active cylinder distribution and target operating state.

Design of a high-performance rotary stratified-charge research aircraft engine

NASA Technical Reports Server (NTRS)

Jones, C.; Mount, R. E.

1984-01-01

The power section for an advanced rotary stratified-charge general aviation engine has been designed under contract to NASA. The single-rotor research engine of 40 cubic-inches displacement (RCI-40), now being procured for test initiation this summer, is targeted for 320 T.O. horse-power in a two-rotor production engine. The research engine is designed for operating on jet-fuel, gasoline or diesel fuel and will be used to explore applicable advanced technologies and to optimize high output performance variables. Design of major components of the engine is described in this paper.

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.

An optimization model to agroindustrial sector in antioquia (Colombia, South America)

NASA Astrophysics Data System (ADS)

Fernandez, J.

2015-06-01

This paper develops a proposal of a general optimization model for the flower industry, which is defined by using discrete simulation and nonlinear optimization, whose mathematical models have been solved by using ProModel simulation tools and Gams optimization. It defines the operations that constitute the production and marketing of the sector, statistically validated data taken directly from each operation through field work, the discrete simulation model of the operations and the linear optimization model of the entire industry chain are raised. The model is solved with the tools described above and presents the results validated in a case study.

The Aeronautical Data Link: Decision Framework for Architecture Analysis

NASA Technical Reports Server (NTRS)

Morris, A. Terry; Goode, Plesent W.

2003-01-01

A decision analytic approach that develops optimal data link architecture configuration and behavior to meet multiple conflicting objectives of concurrent and different airspace operations functions has previously been developed. The approach, premised on a formal taxonomic classification that correlates data link performance with operations requirements, information requirements, and implementing technologies, provides a coherent methodology for data link architectural analysis from top-down and bottom-up perspectives. This paper follows the previous research by providing more specific approaches for mapping and transitioning between the lower levels of the decision framework. The goal of the architectural analysis methodology is to assess the impact of specific architecture configurations and behaviors on the efficiency, capacity, and safety of operations. This necessarily involves understanding the various capabilities, system level performance issues and performance and interface concepts related to the conceptual purpose of the architecture and to the underlying data link technologies. Efficient and goal-directed data link architectural network configuration is conditioned on quantifying the risks and uncertainties associated with complex structural interface decisions. Deterministic and stochastic optimal design approaches will be discussed that maximize the effectiveness of architectural designs.

Impact characteristics for high-pressure large-flow water-based emulsion pilot operated check valve reverse opening

NASA Astrophysics Data System (ADS)

Liu, Lei; Huang, Chuanhui; Yu, Ping; Zhang, Lei

2017-10-01

To improve the dynamic characteristics and cavitation characteristics of large-flow pilot operated check valve, consider the pilot poppet as the research object, analyses working principle and design three different kinds of pilot poppets. The vibration characteristics and impact characteristics are analyzed. The simulation model is established through flow field simulation software. The cavitation characteristics of large-flow pilot operated check valve are studied and discussed. On this basis, high-pressure large-flow impact experimental system is used for impact experiment, and the cavitation index is discussed. Then optimal structure is obtained. Simulation results indicate that the increase of pilot poppet half cone angle can effectively reduce the cavitation area, reducing the generation of cavitation. Experimental results show that the pressure impact is not decreasing with increasing of pilot poppet half cone angle in process of unloading, but the unloading capacity, response speed and pilot poppet half cone angle are positively correlated. The impact characteristics of 60° pilot poppet, and its cavitation index is lesser, which indicates 60° pilot poppet is the optimal structure, with the theory results are basically identical.

Mathematical model for the analysis of structure and optimal operational parameters of a solid oxide fuel cell generator

NASA Astrophysics Data System (ADS)

Coralli, Alberto; Villela de Miranda, Hugo; Espiúca Monteiro, Carlos Felipe; Resende da Silva, José Francisco; Valadão de Miranda, Paulo Emílio

2014-12-01

Solid oxide fuel cells are globally recognized as a very promising technology in the area of highly efficient electricity generation with a low environmental impact. This technology can be advantageously implemented in many situations in Brazil and it is well suited to the use of ethanol as a primary energy source, an important feature given the highly developed Brazilian ethanol industry. In this perspective, a simplified mathematical model is developed for a fuel cell and its balance of plant, in order to identify the optimal system structure and the most convenient values for the operational parameters, with the aim of maximizing the global electric efficiency. In this way it is discovered the best operational configuration for the desired application, which is the distributed generation in the concession area of the electricity distribution company Elektro. The data regarding this configuration are required for the continuation of the research project, i.e. the development of a prototype, a cost analysis of the developed system and a detailed perspective of the market opportunities in Brazil.

Research on energy-saving optimal control of trains in a following operation under a fixed four-aspect autoblock system based on multi-dimension parallel GA

NASA Astrophysics Data System (ADS)

Lu, Qiheng; Feng, Xiaoyun

2013-03-01

After analyzing the working principle of the four-aspect fixed autoblock system, an energy-saving control model was created based on the dynamics equations of the trains in order to study the energy-saving optimal control strategy of trains in a following operation. Besides the safety and punctuality, the main aims of the model were the energy consumption and the time error. Based on this model, the static and dynamic speed restraints under a four-aspect fixed autoblock system were put forward. The multi-dimension parallel genetic algorithm (GA) and the external punishment function were adopted to solve this problem. By using the real number coding and the strategy of ramps divided into three parts, the convergence of GA was speeded up and the length of chromosomes was shortened. A vector of Gaussian random disturbance with zero mean was superposed to the mutation operator. The simulation result showed that the method could reduce the energy consumption effectively based on safety and punctuality.

Fuel management optimization using genetic algorithms and code independence

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

DeChaine, M.D.; Feltus, M.A.

1994-12-31

Fuel management optimization is a hard problem for traditional optimization techniques. Loading pattern optimization is a large combinatorial problem without analytical derivative information. Therefore, methods designed for continuous functions, such as linear programming, do not always work well. Genetic algorithms (GAs) address these problems and, therefore, appear ideal for fuel management optimization. They do not require derivative information and work well with combinatorial. functions. The GAs are a stochastic method based on concepts from biological genetics. They take a group of candidate solutions, called the population, and use selection, crossover, and mutation operators to create the next generation of bettermore » solutions. The selection operator is a {open_quotes}survival-of-the-fittest{close_quotes} operation and chooses the solutions for the next generation. The crossover operator is analogous to biological mating, where children inherit a mixture of traits from their parents, and the mutation operator makes small random changes to the solutions.« less

Understanding facilities design parameters for a remanufacturing system

NASA Astrophysics Data System (ADS)

Topcu, Aysegul; Cullinane, Thomas

2005-11-01

Remanufacturing is rapidly becoming a very important element in the economies of the world. Products such as washing machines, clothes driers, automobile parts, cell phones and a wide range of consumer durable goods are being reclaimed and sent through processes that restore these products to levels of operating performance that are as good or better than their new product performance. The operations involved in the remanufacturing process add several new dimensions to the work that must be performed. Disassembly is an operation that rarely appears on the operations chart of a typical production facility. The inspection and test functions in remanufacturing most often involve several more tasks than those involved in the first time manufacturing cycle. A close evaluation of most any remanufacturing operation reveals several points in the process in which parts must be cleaned, tested and stored. Although several researchers have focused their work on optimizing the disassembly function and the inspection, test and store functions, very little research has been devoted to studying the impact of the facilities design on the effectiveness of the remanufacturing process. The purpose of this paper will be to delineate the differences between first time manufacturing operations and remanufacturing operations for durable goods and to identify the features of the facilities design that must be considered if the remanufacturing operations are to be effective.

Microgrid Enabled Distributed Energy Solutions (MEDES) Fort Bliss Military Reservation

DTIC Science & Technology

2014-02-01

Logic Controller PF Power Factor PO Performance Objectives PPA Power Purchase Agreements PV Photovoltaic R&D Research and Development RDSI...controller, algorithms perform power flow analysis, short term optimization, and long-term forecasted planning. The power flow analysis ensures...renewable photovoltaic power and energy storage in this microgrid configuration, the available mission operational time of the backup generator can be

Conceptualizing School Leadership and Management from a Distributed Perspective: An Exploration of Some Study Operations and Measures

ERIC Educational Resources Information Center

Spillane, James P.; Healey, Kaleen

2010-01-01

A distributed perspective on school leadership and management has garnered considerable attention from policy makers, practitioners, and researchers in many countries over the past decade. However, we should be skeptical of its appeal as a measure of worth. While optimism is high with respect to taking a distributed perspective, we urge caution by…

Design of Stand-Alone Hybrid Power Generation System at Brumbun Beach Tulungagung East Java

NASA Astrophysics Data System (ADS)

Rahmat, A. N.; Hidayat, M. N.; Ronilaya, F.; Setiawan, A.

2018-04-01

Indonesian government insists to optimize the use of renewable energy resources in electricity generation. One of the efforts is launching Independent Energy Village plan. This program aims to fulfill the need of electricity for isolated or remote villages in Indonesia. In order to support the penetration of renewable energy resources in electricity generation, a hybrid power generation system is developed. The simulation in this research is based on the availability of renewable energy resources in Brumbun beach, Tulungagung, East Java. Initially, the electricity was supplied through stand-alone electricity generations which are installed at each house. Hence, the use of electricity between 5 p.m. – 9 p.m. requires high operational costs. Based on the problem above, this research is conducted to design a stand-alone hybrid electricity generation system, which may consist of diesel, wind, and photovoltaic. The design is done by using HOMER software to optimize the use of electricity from renewable resources and to reduce the operation of diesel generation. The combination of renewable energy resources in electricity generation resulted in NPC of 44.680, COE of 0,268, and CO2 emissions of 0,038 % much lower than the use of diesel generator only.

Phylogenetic search through partial tree mixing

PubMed Central

2012-01-01

Background Recent advances in sequencing technology have created large data sets upon which phylogenetic inference can be performed. Current research is limited by the prohibitive time necessary to perform tree search on a reasonable number of individuals. This research develops new phylogenetic algorithms that can operate on tens of thousands of species in a reasonable amount of time through several innovative search techniques. Results When compared to popular phylogenetic search algorithms, better trees are found much more quickly for large data sets. These algorithms are incorporated in the PSODA application available at http://dna.cs.byu.edu/psoda Conclusions The use of Partial Tree Mixing in a partition based tree space allows the algorithm to quickly converge on near optimal tree regions. These regions can then be searched in a methodical way to determine the overall optimal phylogenetic solution. PMID:23320449

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.

Smart grid technologies in local electric grids

NASA Astrophysics Data System (ADS)

Lezhniuk, Petro D.; Pijarski, Paweł; Buslavets, Olga A.

2017-08-01

The research is devoted to the creation of favorable conditions for the integration of renewable sources of energy into electric grids, which were designed to be supplied from centralized generation at large electric power stations. Development of distributed generation in electric grids influences the conditions of their operation - conflict of interests arises. The possibility of optimal functioning of electric grids and renewable sources of energy, when complex criterion of the optimality is balance reliability of electric energy in local electric system and minimum losses of electric energy in it. Multilevel automated system for power flows control in electric grids by means of change of distributed generation of power is developed. Optimization of power flows is performed by local systems of automatic control of small hydropower stations and, if possible, solar power plants.

Parameter Optimization for Turbulent Reacting Flows Using Adjoints

NASA Astrophysics Data System (ADS)

Lapointe, Caelan; Hamlington, Peter E.

2017-11-01

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

Modelling and multi objective optimization of WEDM of commercially Monel super alloy using evolutionary algorithms

NASA Astrophysics Data System (ADS)

Varun, Sajja; Reddy, Kalakada Bhargav Bal; Vardhan Reddy, R. R. Vishnu

2016-09-01

In this research work, development of a multi response optimization technique has been undertaken, using traditional desirability analysis and non-traditional particle swarm optimization techniques (for different customer's priorities) in wire electrical discharge machining (WEDM). Monel 400 has been selected as work material for experimentation. The effect of key process parameters such as pulse on time (TON), pulse off time (TOFF), peak current (IP), wire feed (WF) were on material removal rate (MRR) and surface roughness(SR) in WEDM operation were investigated. Further, the responses such as MRR and SR were modelled empirically through regression analysis. The developed models can be used by the machinists to predict the MRR and SR over a wide range of input parameters. The optimization of multiple responses has been done for satisfying the priorities of multiple users by using Taguchi-desirability function method and particle swarm optimization technique. The analysis of variance (ANOVA) is also applied to investigate the effect of influential parameters. Finally, the confirmation experiments were conducted for the optimal set of machining parameters, and the betterment has been proved.

An Optimization and Assessment on DG adoption in JapanesePrototype Buildings

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

Zhou, Nan; Marnay, Chris; Firestone, Ryan

2005-11-30

This research investigates a method of choosing economicallyoptimal DER, expanding on prior studies at the Berkeley Lab using the DERdesign optimization program, the Distributed Energy Resources CustomerAdoption Model (DER-CAM). DER-CAM finds the optimal combination ofinstalled equipment from available DER technologies, given prevailingutility tariffs, site electrical and thermal loads, and a menu ofavailable equipment. It provides a global optimization, albeit idealized,that shows how the site energy load scan be served at minimum cost byselection and operation of on-site generation, heat recovery, andcooling. Five prototype Japanese commercial buildings are examined andDER-CAM applied to select thee conomically optimal DER system for each.The fivemore » building types are office, hospital, hotel, retail, and sportsfacility. Based on the optimization results, energy and emissionreductions are evaluated. Furthermore, a Japan-U.S. comparison study ofpolicy, technology, and utility tariffs relevant to DER installation ispresented. Significant decreases in fuel consumption, carbon emissions,and energy costs were seen in the DER-CAM results. Savings were mostnoticeable in the sports facility, followed by the hospital, hotel, andoffice building.« less

Mixture optimization for mixed gas Joule-Thomson cycle

NASA Astrophysics Data System (ADS)

Detlor, J.; Pfotenhauer, J.; Nellis, G.

2017-12-01

An appropriate gas mixture can provide lower temperatures and higher cooling power when used in a Joule-Thomson (JT) cycle than is possible with a pure fluid. However, selecting gas mixtures to meet specific cooling loads and cycle parameters is a challenging design problem. This study focuses on the development of a computational tool to optimize gas mixture compositions for specific operating parameters. This study expands on prior research by exploring higher heat rejection temperatures and lower pressure ratios. A mixture optimization model has been developed which determines an optimal three-component mixture based on the analysis of the maximum value of the minimum value of isothermal enthalpy change, ΔhT , that occurs over the temperature range. This allows optimal mixture compositions to be determined for a mixed gas JT system with load temperatures down to 110 K and supply temperatures above room temperature for pressure ratios as small as 3:1. The mixture optimization model has been paired with a separate evaluation of the percent of the heat exchanger that exists in a two-phase range in order to begin the process of selecting a mixture for experimental investigation.

Adjustable control station with movable monitors and cameras for viewing systems in robotics and teleoperations

NASA Technical Reports Server (NTRS)

Diner, Daniel B. (Inventor)

1994-01-01

Real-time video presentations are provided in the field of operator-supervised automation and teleoperation, particularly in control stations having movable cameras for optimal viewing of a region of interest in robotics and teleoperations for performing different types of tasks. Movable monitors to match the corresponding camera orientations (pan, tilt, and roll) are provided in order to match the coordinate systems of all the monitors to the operator internal coordinate system. Automated control of the arrangement of cameras and monitors, and of the configuration of system parameters, is provided for optimal viewing and performance of each type of task for each operator since operators have different individual characteristics. The optimal viewing arrangement and system parameter configuration is determined and stored for each operator in performing each of many types of tasks in order to aid the automation of setting up optimal arrangements and configurations for successive tasks in real time. Factors in determining what is optimal include the operator's ability to use hand-controllers for each type of task. Robot joint locations, forces and torques are used, as well as the operator's identity, to identify the current type of task being performed in order to call up a stored optimal viewing arrangement and system parameter configuration.

Development of Fully Automated Low-Cost Immunoassay System for Research Applications.

PubMed

Wang, Guochun; Das, Champak; Ledden, Bradley; Sun, Qian; Nguyen, Chien

2017-10-01

Enzyme-linked immunosorbent assay (ELISA) automation for routine operation in a small research environment would be very attractive. A portable fully automated low-cost immunoassay system was designed, developed, and evaluated with several protein analytes. It features disposable capillary columns as the reaction sites and uses real-time calibration for improved accuracy. It reduces the overall assay time to less than 75 min with the ability of easy adaptation of new testing targets. The running cost is extremely low due to the nature of automation, as well as reduced material requirements. Details about system configuration, components selection, disposable fabrication, system assembly, and operation are reported. The performance of the system was initially established with a rabbit immunoglobulin G (IgG) assay, and an example of assay adaptation with an interleukin 6 (IL6) assay is shown. This system is ideal for research use, but could work for broader testing applications with further optimization.

A liquid metal-based structurally embedded vascular antenna: II. Multiobjective and parameterized design exploration

NASA Astrophysics Data System (ADS)

Hartl, D. J.; Frank, G. J.; Malak, R. J.; Baur, J. W.

2017-02-01

Research on the structurally embedded vascular antenna concept leverages past efforts on liquid metal (LM) reconfigurable electronics, microvascular composites, and structurally integrated and reconfigurable antennas. Such a concept has potential for reducing system weight or volume while simultaneously allowing in situ adjustment of resonant frequencies and/or changes in antenna directivity. This work considers a microvascular pattern embedded in a laminated composite and filled with LM. The conductive liquid provides radio frequency (RF) functionality while also allowing self-cooling. Models describing RF propagation and heat transfer, in addition to the structural effects of both the inclusion of channels and changes in temperature, were described in part 1 of this two-part work. In this part 2, the engineering models developed and demonstrated in part 1 toward the initial exploration of design trends are implemented into multiple optimization frameworks for more detailed design studies, one of which being novel and particularly applicable to this class of problem. The computational expense associated with the coupled multiphysical analysis of the structurally embedded LM transmitting antenna motivates the consideration of surrogate-based optimization methods. Both static and adaptive approaches are explored; it is shown that iteratively correcting the surrogate leads to more accurate optimized design predictions. The expected strong dependence of antenna performance on thermal environment motivates the consideration of a novel ‘parameterized’ optimization approach that simultaneously calculates whole families of optimal designs based on changes in design or operational variables generally beyond the control of the designer. The change in Pareto-optimal response with evolution in operating conditions is clearly demonstrated.

Value recovery from two mechanized bucking operations in the southeastern United States

Treesearch

Kevin Boston; Glen. Murphy

2003-01-01

The value recovered from two mechanized bucking operations in the southeastern United States was compared with the optimal value computed using an individual-stem log optimization program, AVIS. The first operation recovered 94% of the optimal value. The main cause for the value loss was a failure to capture potential sawlog volume; logs were bucked to a larger average...

Sootblowing optimization for improved boiler performance

DOEpatents

James, John Robert; McDermott, John; Piche, Stephen; Pickard, Fred; Parikh, Neel J.

2012-12-25

A sootblowing control system that uses predictive models to bridge the gap between sootblower operation and boiler performance goals. The system uses predictive modeling and heuristics (rules) associated with different zones in a boiler to determine an optimal sequence of sootblower operations and achieve boiler performance targets. The system performs the sootblower optimization while observing any operational constraints placed on the sootblowers.

Sootblowing optimization for improved boiler performance

DOEpatents

James, John Robert; McDermott, John; Piche, Stephen; Pickard, Fred; Parikh, Neel J

2013-07-30

A sootblowing control system that uses predictive models to bridge the gap between sootblower operation and boiler performance goals. The system uses predictive modeling and heuristics (rules) associated with different zones in a boiler to determine an optimal sequence of sootblower operations and achieve boiler performance targets. The system performs the sootblower optimization while observing any operational constraints placed on the sootblowers.

Matching relations for optimal entanglement concentration and purification

PubMed Central

Kong, Fan-Zhen; Xia, Hui-Zhi; Yang, Ming; Yang, Qing; Cao, Zhuo-Liang

2016-01-01

The bilateral controlled NOT (CNOT) operation plays a key role in standard entanglement purification process, but the CNOT operation may not be the optimal joint operation in the sense that the output entanglement is maximized. In this paper, the CNOT operations in both the Schmidt-projection based entanglement concentration and the entanglement purification schemes are replaced with a general joint unitary operation, and the optimal matching relations between the entangling power of the joint unitary operation and the non-maximal entangled channel are found for optimizing the entanglement in- crement or the output entanglement. The result is somewhat counter-intuitive for entanglement concentration. The output entanglement is maximized when the entangling power of the joint unitary operation and the quantum channel satisfy certain relation. There exist a variety of joint operations with non-maximal entangling power that can induce a maximal output entanglement, which will greatly broaden the set of the potential joint operations in entanglement concentration. In addition, the entanglement increment in purification process is maximized only by the joint unitary operations (including CNOT) with maximal entangling power. PMID:27189800

Engine With Regression and Neural Network Approximators Designed

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Hopkins, Dale A.

2001-01-01

At the NASA Glenn Research Center, the NASA engine performance program (NEPP, ref. 1) and the design optimization testbed COMETBOARDS (ref. 2) with regression and neural network analysis-approximators have been coupled to obtain a preliminary engine design methodology. The solution to a high-bypass-ratio subsonic waverotor-topped turbofan engine, which is shown in the preceding figure, was obtained by the simulation depicted in the following figure. This engine is made of 16 components mounted on two shafts with 21 flow stations. The engine is designed for a flight envelope with 47 operating points. The design optimization utilized both neural network and regression approximations, along with the cascade strategy (ref. 3). The cascade used three algorithms in sequence: the method of feasible directions, the sequence of unconstrained minimizations technique, and sequential quadratic programming. The normalized optimum thrusts obtained by the three methods are shown in the following figure: the cascade algorithm with regression approximation is represented by a triangle, a circle is shown for the neural network solution, and a solid line indicates original NEPP results. The solutions obtained from both approximate methods lie within one standard deviation of the benchmark solution for each operating point. The simulation improved the maximum thrust by 5 percent. The performance of the linear regression and neural network methods as alternate engine analyzers was found to be satisfactory for the analysis and operation optimization of air-breathing propulsion engines (ref. 4).

Development of a protocol to optimize electric power consumption and life cycle environmental impacts for operation of wastewater treatment plant.

PubMed

Piao, Wenhua; Kim, Changwon; Cho, Sunja; Kim, Hyosoo; Kim, Minsoo; Kim, Yejin

2016-12-01

In wastewater treatment plants (WWTPs), the portion of operating costs related to electric power consumption is increasing. If the electric power consumption decreased, however, it would be difficult to comply with the effluent water quality requirements. A protocol was proposed to minimize the environmental impacts as well as to optimize the electric power consumption under the conditions needed to meet the effluent water quality standards in this study. This protocol was comprised of six phases of procedure and was tested using operating data from S-WWTP to prove its applicability. The 11 major operating variables were categorized into three groups using principal component analysis and K-mean cluster analysis. Life cycle assessment (LCA) was conducted for each group to deduce the optimal operating conditions for each operating state. Then, employing mathematical modeling, six improvement plans to reduce electric power consumption were deduced. The electric power consumptions for suggested plans were estimated using an artificial neural network. This was followed by a second round of LCA conducted on the plans. As a result, a set of optimized improvement plans were derived for each group that were able to optimize the electric power consumption and life cycle environmental impact, at the same time. Based on these test results, the WWTP operating management protocol presented in this study is deemed able to suggest optimal operating conditions under which power consumption can be optimized with minimal life cycle environmental impact, while allowing the plant to meet water quality requirements.

Optimal synthesis and design of the number of cycles in the leaching process for surimi production.

PubMed

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

2016-12-01

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

Seasonal-Scale Optimization of Conventional Hydropower Operations in the Upper Colorado System

NASA Astrophysics Data System (ADS)

Bier, A.; Villa, D.; Sun, A.; Lowry, T. S.; Barco, J.

2011-12-01

Sandia National Laboratories is developing the Hydropower Seasonal Concurrent Optimization for Power and the Environment (Hydro-SCOPE) tool to examine basin-wide conventional hydropower operations at seasonal time scales. This tool is part of an integrated, multi-laboratory project designed to explore different aspects of optimizing conventional hydropower operations. The Hydro-SCOPE tool couples a one-dimensional reservoir model with a river routing model to simulate hydrology and water quality. An optimization engine wraps around this model framework to solve for long-term operational strategies that best meet the specific objectives of the hydrologic system while honoring operational and environmental constraints. The optimization routines are provided by Sandia's open source DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) software. Hydro-SCOPE allows for multi-objective optimization, which can be used to gain insight into the trade-offs that must be made between objectives. The Hydro-SCOPE tool is being applied to the Upper Colorado Basin hydrologic system. This system contains six reservoirs, each with its own set of objectives (such as maximizing revenue, optimizing environmental indicators, meeting water use needs, or other objectives) and constraints. This leads to a large optimization problem with strong connectedness between objectives. The systems-level approach used by the Hydro-SCOPE tool allows simultaneous analysis of these objectives, as well as understanding of potential trade-offs related to different objectives and operating strategies. The seasonal-scale tool will be tightly integrated with the other components of this project, which examine day-ahead and real-time planning, environmental performance, hydrologic forecasting, and plant efficiency.

Global stratospheric change: Requirements for a Very-High-Altitude Aircraft for Atmospheric Research

NASA Technical Reports Server (NTRS)

1989-01-01

The workshop on Requirements for a Very-High-Altitude Aircraft for Atmospheric Research, sponsored by NASA Ames Research Center, was held July 15 to 16, 1989, at Truckee, CA. The workshop had two purposes: to assess the scientific justification for a new aircraft that will support stratospheric research beyond the altitudes accessible to the NASA ER-2; and to determine the aircraft characteristics (e.g., ceiling altitude, payload accommodations, range, flight duration, operational capabilities) required to perform the stratospheric research referred to in the justification. To accomplish these purposes, the workshop brought together a cross-section of stratospheric scientists with several aircraft design and operations experts. The stratospheric scientists included theoreticians as well as experimenters with experience in remote and in situ measurements from satellites, rockets, balloons, aircraft, and the ground. Discussions of required aircraft characteristics focused on the needs of stratospheric research. It was recognized that an aircraft optimal for stratospheric science would also be useful for other applications, including remote measurements of Earth's surface. A brief description of these other applications was given at the workshop.

Altitude Wind Tunnel Control Room

NASA Image and Video Library

1945-05-21

Researchers at the National Advisory Committee for Aeronautics (NACA) Aircraft Engine Research Laboratory monitor a ramjet's performance in the Altitude Wind Tunnel from the control room. The soundproof control room was just a few feet from the tunnel’s 20-foot-diameter test section. In the control room, the operators could control all aspects of the tunnel’s operation, including the air density, temperature, and speed. They also operated the engine or test article in the test section by controlling the angle-of-attack, speed, power, and other parameters. The men in this photograph are monitoring the engine’s thrust and lift. A NACA-designed 20-inch-diameter ramjet was installed in the tunnel in May 1945. Thrust figures from these runs were compared with drag data from tests of scale models in small supersonic tunnels to verify the ramjet’s feasibility. The tunnel was used to analyze the ramjet’s overall performance up to altitudes of 47,000 feet and speeds to Mach 1.84. The researchers found that an increase in altitude caused a reduction in the engine’s horsepower and identified optimal flameholder configurations.

Optimizing desalinated sea water blending with other sources to meet magnesium requirements for potable and irrigation waters.

PubMed

Avni, Noa; Eben-Chaime, Moshe; Oron, Gideon

2013-05-01

Sea water desalination provides fresh water that typically lacks minerals essential to human health and to agricultural productivity. Thus the rising proportion of desalinated sea water consumed by both the domestic and agricultural sectors constitutes a public health risk. Research on low-magnesium water irrigation showed that crops developed magnesium deficiency symptoms that could lead to plant death, and tomato yields were reduced by 10-15%. The World Health Organization (WHO) reported on a relationship between sudden cardiac death rates and magnesium intake deficits. An optimization model, developed and tested to provide recommendations for Water Distribution System (WDS) quality control in terms of meeting optimal water quality requirements, was run in computational experiments based on an actual regional WDS. The expected magnesium deficit due to the operation of a large Sea Water Desalination Plant (SWDP) was simulated, and an optimal operation policy, in which remineralization at the SWDP was combined with blending desalinated and natural water to achieve the required quality, was generated. The effects of remineralization costs and WDS physical layout on the optimal policy were examined by sensitivity analysis. As part of the sensitivity blending natural and desalinated water near the treatment plants will be feasible up to 16.2 US cents/m(3), considering all expenses. Additional chemical injection was used to meet quality criteria when blending was not feasible. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

A Clustering Based Approach for Observability and Controllability Analysis for Optimal Placement of PMU

NASA Astrophysics Data System (ADS)

Murthy, Ch; MIEEE; Mohanta, D. K.; SMIEE; Meher, Mahendra

2017-08-01

Continuous monitoring and control of the power system is essential for its healthy operation. This can be achieved by making the system observable as well as controllable. Many efforts have been made by several researchers to make the system observable by placing the Phasor Measurement Units (PMUs) at the optimal locations. But so far the idea of controllability with PMUs is not considered. This paper contributes how to check whether the system is controllable or not, if not then how make it controllable using a clustering approach. IEEE 14 bus system is considered to illustrate the concept of controllability.

Optimal Trajectories for the Helicopter in One-Engine-Inoperative Terminal-Area Operations

NASA Technical Reports Server (NTRS)

Zhao, Yiyuan; Chen, Robert T. N.

1996-01-01

This paper presents a summary of a series of recent analytical studies conducted to investigate One-Engine-Inoperative (OEI) optimal control strategies and the associated optimal trajectories for a twin engine helicopter in Category-A terminal-area operations. These studies also examine the associated heliport size requirements and the maximum gross weight capability of the helicopter. Using an eight states, two controls, augmented point-mass model representative of the study helicopter, Continued TakeOff (CTO), Rejected TakeOff (RTO), Balked Landing (BL), and Continued Landing (CL) are investigated for both Vertical-TakeOff-and-Landing (VTOL) and Short-TakeOff-and-Landing (STOL) terminal-area operations. The formulation of the nonlinear optimal control problems with considerations for realistic constraints, solution methods for the two-point boundary-value problem, a new real-time generation method for the optimal OEI trajectories, and the main results of this series of trajectory optimization studies are presented. In particular, a new balanced- weight concept for determining the takeoff decision point for VTOL Category-A operations is proposed, extending the balanced-field length concept used for STOL operations.

Integrating operation design into infrastructure planning to foster robustness of planned water systems

NASA Astrophysics Data System (ADS)

Bertoni, Federica; Giuliani, Matteo; Castelletti, Andrea

2017-04-01

Over the past years, many studies have looked at the planning and management of water infrastructure systems as two separate problems, where the dynamic component (i.e., operations) is considered only after the static problem (i.e., planning) has been resolved. Most recent works have started to investigate planning and management as two strictly interconnected faces of the same problem, where the former is solved jointly with the latter in an integrated framework. This brings advantages to multi-purpose water reservoir systems, where several optimal operating strategies exist and similar system designs might perform differently on the long term depending on the considered short-term operating tradeoff. An operationally robust design will be therefore one performing well across multiple feasible tradeoff operating policies. This work aims at studying the interaction between short-term operating strategies and their impacts on long-term structural decisions, when long-lived infrastructures with complex ecological impacts and multi-sectoral demands to satisfy (i.e., reservoirs) are considered. A parametric reinforcement learning approach is adopted for nesting optimization and control yielding to both optimal reservoir design and optimal operational policies for water reservoir systems. The method is demonstrated on a synthetic reservoir that must be designed and operated for ensuring reliable water supply to downstream users. At first, the optimal design capacity derived is compared with the 'no-fail storage' computed through Rippl, a capacity design function that returns the minimum storage needed to satisfy specified water demands without allowing supply shortfall. Then, the optimal reservoir volume is used to simulate the simplified case study under other operating objectives than water supply, in order to assess whether and how the system performance changes. The more robust the infrastructural design, the smaller the difference between the performances of different operating strategies.

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.

Robust design optimization method for centrifugal impellers under surface roughness uncertainties due to blade fouling

NASA Astrophysics Data System (ADS)

Ju, Yaping; Zhang, Chuhua

2016-03-01

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

Remediation System Design Optimization: Field Demonstration at the Umatilla Army Deport

NASA Astrophysics Data System (ADS)

Zheng, C.; Wang, P. P.

2002-05-01

Since the early 1980s, many researchers have shown that the simulation-optimization (S/O) approach is superior to the traditional trial-and-error method for designing cost-effective groundwater pump-and-treat systems. However, the application of the S/O approach to real field problems has remained limited. This paper describes the application of a new general simulation-optimization code to optimize an existing pump-and-treat system at the Umatilla Army Depot in Oregon, as part of a field demonstration project supported by the Environmental Security Technology Certification Program (ESTCP). Two optimization formulations were developed to minimize the total capital and operational costs under the current and possibly expanded treatment plant capacities. A third formulation was developed to minimize the total contaminant mass of RDX and TNT remaining in the shallow aquifer by the end of the project duration. For the first two formulations, this study produced an optimal pumping strategy that would achieve the cleanup goal in 4 years with a total cost of 1.66 million US dollars in net present value. For comparison, the existing design in operation was calculated to require 17 years for cleanup with a total cost of 3.83 million US dollars in net present value. Thus, the optimal pumping strategy represents a reduction of 13 years in cleanup time and a reduction of 56.6 percent in the expected total expenditure. For the third formulation, this study identified an optimal dynamic pumping strategy that would reduce the total mass remaining in the shallow aquifer by 89.5 percent compared with that calculated for the existing design. In spite of their intensive computational requirements, this study shows that the global optimization techniques including tabu search and genetic algorithms can be applied successfully to large-scale field problems involving multiple contaminants and complex hydrogeological conditions.

Integrated controls design optimization

DOEpatents

Lou, Xinsheng; Neuschaefer, Carl H.

2015-09-01

A control system (207) for optimizing a chemical looping process of a power plant includes an optimizer (420), an income algorithm (230) and a cost algorithm (225) and a chemical looping process models. The process models are used to predict the process outputs from process input variables. Some of the process in puts and output variables are related to the income of the plant; and some others are related to the cost of the plant operations. The income algorithm (230) provides an income input to the optimizer (420) based on a plurality of input parameters (215) of the power plant. The cost algorithm (225) provides a cost input to the optimizer (420) based on a plurality of output parameters (220) of the power plant. The optimizer (420) determines an optimized operating parameter solution based on at least one of the income input and the cost input, and supplies the optimized operating parameter solution to the power plant.

The Applied Meteorology Unit: Nineteen Years Successfully Transitioning Research into Operations for America's Space Program

NASA Technical Reports Server (NTRS)

Madura, John T.; Bauman, William H.; Merceret, Francis J.; Roeder, William P.; Brody, Frank C.; Hagemeyer, Bartlett C.

2010-01-01

The Applied Meteorology Unit (AMU) provides technology transition and technique development to improve operational weather support to the Space Shuttle and the entire American space program. The AMU is funded and managed by NASA and operated by a contractor that provides five meteorologists with a diverse mix of advanced degrees, operational experience, and associated skills including data processing, statistics, and the development of graphical user interfaces. The AMU's primary customers are the U.S. Air Force 45th Weather Squadron at Patrick Air Force Base, the National Weather Service Spaceflight Meteorology Group at NASA Johnson Space Center, and the National Weather Service Melbourne FL Forecast Office. The AMU has transitioned research into operations for nineteen years and worked on a wide range of topics, including new forecasting techniques for lightning probability, synoptic peak winds,.convective winds, and summer severe weather; satellite tools to predict anvil cloud trajectories and evaluate camera line of sight for Space Shuttle launch; optimized radar scan strategies; evaluated and implemented local numerical models; evaluated weather sensors; and many more. The AMU has completed 113 projects with 5 more scheduled to be completed by the end of 2010. During this rich history, the AMU and its customers have learned many lessons on how to effectively transition research into operations. Some of these lessons learned include collocating with the operational customer and periodically visiting geographically separated customers, operator submitted projects, consensus tasking process, use of operator primary advocates for each project, customer AMU liaisons with experience in both operations and research, flexibility in adapting the project plan based on lessons learned during the project, and incorporating training and other transition assistance into the project plans. Operator involvement has been critical to the AMU's remarkable success and many awards from NASA, the National Weather Association, and two citations from the Navy's Center of Excellence for Best Manufacturing Practices. This paper will present the AMU's proven methods and explain how they may be applied by other organizations to effectively transition research into operations.

Optimizing Dispersed Air Operations: A Concept To Use Highways As Improved Airfields In A Contested Environment

DTIC Science & Technology

2015-04-01

capability to conduct airfield surveys outside of a permissive environment. Optimizing the Rapid Raptor Forward Arming and Refueling Point (FARP...9] An Initial Approach at Dispersing Air Operations: Rapid Raptor Concept ................... [12] Rapid Raptor : Optimized...Approach at Dispersing Air Operations: Rapid Raptor Concept The Air Force Rapid Raptor Fighter Forward Arming and Refueling (FARP) concept is an

[Optimization of end-tool parameters based on robot hand-eye calibration].

PubMed

Zhang, Lilong; Cao, Tong; Liu, Da

2017-04-01

A new one-time registration method was developed in this research for hand-eye calibration of a surgical robot to simplify the operation process and reduce the preparation time. And a new and practical method is introduced in this research to optimize the end-tool parameters of the surgical robot based on analysis of the error sources in this registration method. In the process with one-time registration method, firstly a marker on the end-tool of the robot was recognized by a fixed binocular camera, and then the orientation and position of the marker were calculated based on the joint parameters of the robot. Secondly the relationship between the camera coordinate system and the robot base coordinate system could be established to complete the hand-eye calibration. Because of manufacturing and assembly errors of robot end-tool, an error equation was established with the transformation matrix between the robot end coordinate system and the robot end-tool coordinate system as the variable. Numerical optimization was employed to optimize end-tool parameters of the robot. The experimental results showed that the one-time registration method could significantly improve the efficiency of the robot hand-eye calibration compared with the existing methods. The parameter optimization method could significantly improve the absolute positioning accuracy of the one-time registration method. The absolute positioning accuracy of the one-time registration method can meet the requirements of the clinical surgery.

Small unmanned aircraft system for remote contour mapping of a nuclear radiation field

NASA Astrophysics Data System (ADS)

Guss, Paul; McCall, Karen; Malchow, Russell; Fischer, Rick; Lukens, Michael; Adan, Mark; Park, Ki; Abbott, Roy; Howard, Michael; Wagner, Eric; Trainham, Clifford P.; Luke, Tanushree; Mukhopadhyay, Sanjoy; Oh, Paul; Brahmbhatt, Pareshkumar; Henderson, Eric; Han, Jinlu; Huang, Justin; Huang, Casey; Daniels, Jon

2017-09-01

For nuclear disasters involving radioactive contamination, small unmanned aircraft systems (sUASs) equipped with nuclear radiation detection and monitoring capability can be very important tools. Among the advantages of a sUAS are quick deployment, low-altitude flying that enhances sensitivity, wide area coverage, no radiation exposure health safety restriction, and the ability to access highly hazardous or radioactive areas. Additionally, the sUAS can be configured with the nuclear detecting sensor optimized to measure the radiation associated with the event. In this investigation, sUAS platforms were obtained for the installation of sensor payloads for radiation detection and electro-optical systems that were specifically developed for sUAS research, development, and operational testing. The sensor payloads were optimized for the contour mapping of a nuclear radiation field, which will result in a formula for low-cost sUAS platform operations with built-in formation flight control. Additional emphases of the investigation were to develop the relevant contouring algorithms; initiate the sUAS comprehensive testing using the Unmanned Systems, Inc. (USI) Sandstorm platforms and other acquired platforms; and both acquire and optimize the sensors for detection and localization. We demonstrated contour mapping through simulation and validated waypoint detection. We mounted a detector on a sUAS and operated it initially in the counts per second (cps) mode to perform field and flight tests to demonstrate that the equipment was functioning as designed. We performed ground truth measurements to determine the response of the detector as a function of source-to-detector distance. Operation of the radiation detector was tested using different unshielded sources.

Application of Decision Tree to Obtain Optimal Operation Rules for Reservoir Flood Control Considering Sediment Desilting-Case Study of Tseng Wen Reservoir

NASA Astrophysics Data System (ADS)

ShiouWei, L.

2014-12-01

Reservoirs are the most important water resources facilities in Taiwan.However,due to the steep slope and fragile geological conditions in the mountain area,storm events usually cause serious debris flow and flood,and the flood then will flush large amount of sediment into reservoirs.The sedimentation caused by flood has great impact on the reservoirs life.Hence,how to operate a reservoir during flood events to increase the efficiency of sediment desilting without risk the reservoir safety and impact the water supply afterward is a crucial issue in Taiwan. 　Therefore,this study developed a novel optimization planning model for reservoir flood operation considering flood control and sediment desilting,and proposed easy to use operating rules represented by decision trees.The decision trees rules have considered flood mitigation,water supply and sediment desilting.The optimal planning model computes the optimal reservoir release for each flood event that minimum water supply impact and maximum sediment desilting without risk the reservoir safety.Beside the optimal flood operation planning model,this study also proposed decision tree based flood operating rules that were trained by the multiple optimal reservoir releases to synthesis flood scenarios.The synthesis flood scenarios consists of various synthesis storm events,reservoir's initial storage and target storages at the end of flood operating. 　Comparing the results operated by the decision tree operation rules(DTOR) with that by historical operation for Krosa Typhoon in 2007,the DTOR removed sediment 15.4% more than that of historical operation with reservoir storage only8.38×106m3 less than that of historical operation.For Jangmi Typhoon in 2008,the DTOR removed sediment 24.4% more than that of historical operation with reservoir storage only 7.58×106m3 less than that of historical operation.The results show that the proposed DTOR model can increase the sediment desilting efficiency and extend the reservoir life.

Warfighter nutrition: current opportunities and advanced technologies report from a Department of Defense workshop.

PubMed

Deuster, Patricia A; Weinstein, Ali A; Sobel, Annette; Young, Andrew J

2009-07-01

The Uniformed Services University hosted a conference in July 2008 entitled "Warfighter Nutrition: Advanced Technologies and Opportunities" with Health Affairs and the Defense Advanced Research Projects Agency to develop strategic and tactical plans that could enhance Force Health Protection (FHP) by optimizing warfighter nutrition within the Department of Defense (DoD). The conference focused on three aspects of military nutrition: (1) fueling the forces, or garrison feeding; (2) performance optimization or operational feeding during deployment; and (3) nutritional interventions to support health reset and healing. Presentations by speakers addressed practical interventions (i.e., ready for implementation now) and advanced technologies (i.e., approaches meriting prioritized research and development efforts to transition into application). The conference concluded that nutritional optimization represents an integral and proactive approach to prevent illness, injury, and performance degradation throughout all phases of military service. The overarching consensus achieved was that warfighter nutrition, as a cornerstone of FHP, warrants the critical attention of both medical and line leadership to move quickly to support current initiatives and future advanced technologies.

Ant colony optimization for solving university facility layout problem

NASA Astrophysics Data System (ADS)

Mohd Jani, Nurul Hafiza; Mohd Radzi, Nor Haizan; Ngadiman, Mohd Salihin

2013-04-01

Quadratic Assignment Problems (QAP) is classified as the NP hard problem. It has been used to model a lot of problem in several areas such as operational research, combinatorial data analysis and also parallel and distributed computing, optimization problem such as graph portioning and Travel Salesman Problem (TSP). In the literature, researcher use exact algorithm, heuristics algorithm and metaheuristic approaches to solve QAP problem. QAP is largely applied in facility layout problem (FLP). In this paper we used QAP to model university facility layout problem. There are 8 facilities that need to be assigned to 8 locations. Hence we have modeled a QAP problem with n ≤ 10 and developed an Ant Colony Optimization (ACO) algorithm to solve the university facility layout problem. The objective is to assign n facilities to n locations such that the minimum product of flows and distances is obtained. Flow is the movement from one to another facility, whereas distance is the distance between one locations of a facility to other facilities locations. The objective of the QAP is to obtain minimum total walking (flow) of lecturers from one destination to another (distance).

The optimization of nuclear power plants operation modes in emergency situations

NASA Astrophysics Data System (ADS)

Zagrebayev, A. M.; Trifonenkov, A. V.; Ramazanov, R. N.

2018-01-01

An emergency situations resulting in the necessity for temporary reactor trip may occur at the nuclear power plant while normal operating mode. The paper deals with some of the operation c aspects of nuclear power plant operation in emergency situations and during threatened period. The xenon poisoning causes limitations on the variety of statements of the problem of calculating characteristics of a set of optimal reactor power off controls. The article show a possibility and feasibility of new sets of optimization tasks for the operation of nuclear power plants under conditions of xenon poisoning in emergency circumstances.

Intelligent Systems Approach for Automated Identification of Individual Control Behavior of a Human Operator

NASA Technical Reports Server (NTRS)

Zaychik, Kirill B.; Cardullo, Frank M.

2012-01-01

Results have been obtained using conventional techniques to model the generic human operator?s control behavior, however little research has been done to identify an individual based on control behavior. The hypothesis investigated is that different operators exhibit different control behavior when performing a given control task. Two enhancements to existing human operator models, which allow personalization of the modeled control behavior, are presented. One enhancement accounts for the testing control signals, which are introduced by an operator for more accurate control of the system and/or to adjust the control strategy. This uses the Artificial Neural Network which can be fine-tuned to model the testing control. Another enhancement takes the form of an equiripple filter which conditions the control system power spectrum. A novel automated parameter identification technique was developed to facilitate the identification process of the parameters of the selected models. This utilizes a Genetic Algorithm based optimization engine called the Bit-Climbing Algorithm. Enhancements were validated using experimental data obtained from three different sources: the Manual Control Laboratory software experiments, Unmanned Aerial Vehicle simulation, and NASA Langley Research Center Visual Motion Simulator studies. This manuscript also addresses applying human operator models to evaluate the effectiveness of motion feedback when simulating actual pilot control behavior in a flight simulator.

Status of black chrome coating research

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

Pettit, R.B.; Sowell, R.R.

1983-01-01

Recent results regarding the optimization of electrodeposited black chrome solar selective coatings for operation in solar collectors to temperatures up to 300/sup 0/C are summarized. Careful control of the electroplating-bath composition and special regard for bath contamination are required in order to obtain coatings that will survive daily collector operation for tens of years. An accelerated temperature aging test is presented which can be used both to estimate the coating lifetime and to monitor the coating during production. Finally, the use of sol-gel protective films to extend the lifetime of the black chrome coating is also discussed.

Pollution Reduction Technology Program for Small Jet Aircraft Engines, Phase 2

NASA Technical Reports Server (NTRS)

Bruce, T. W.; Davis, F. G.; Kuhn, T. E.; Mongia, H. C.

1978-01-01

A series of iterative combustor pressure rig tests were conducted on two combustor concepts applied to the AiResearch TFE731-2 turbofan engine combustion system for the purpose of optimizing combustor performance and operating characteristics consistant with low emissions. The two concepts were an axial air-assisted airblast fuel injection configuration with variable-geometry air swirlers and a staged premix/prevaporization configuration. The iterative rig testing and modification sequence on both concepts was intended to provide operational compatibility with the engine and determine one concept for further evaluation in a TFE731-2 engine.

Preliminary design of a mobile lunar power supply

NASA Technical Reports Server (NTRS)

Schmitz, Paul C.; Kenny, Barbara H.; Fulmer, Christopher R.

1991-01-01

A preliminary design for a Stirling isotope power system for use as a mobile lunar power supply is presented. Performance and mass of the components required for the system are estimated. These estimates are based on power requirements and the operating environment. Optimizations routines are used to determine minimum mass operational points. Shielding for the isotope system are given as a function of the allowed dose, distance from the source, and the time spent near the source. The technologies used in the power conversion and radiator systems are taken from ongoing research in the Civil Space Technology Initiative (CSTI) program.

The design of digital-adaptive controllers for VTOL aircraft

NASA Technical Reports Server (NTRS)

Stengel, R. F.; Broussard, J. R.; Berry, P. W.

1976-01-01

Design procedures for VTOL automatic control systems have been developed and are presented. Using linear-optimal estimation and control techniques as a starting point, digital-adaptive control laws have been designed for the VALT Research Aircraft, a tandem-rotor helicopter which is equipped for fully automatic flight in terminal area operations. These control laws are designed to interface with velocity-command and attitude-command guidance logic, which could be used in short-haul VTOL operations. Developments reported here include new algorithms for designing non-zero-set-point digital regulators, design procedures for rate-limited systems, and algorithms for dynamic control trim setting.

In situ observations of water production and distribution in an operating H2/O2 PEM fuel cell assembly using 1H NMR microscopy.

PubMed

Feindel, Kirk W; LaRocque, Logan P-A; Starke, Dieter; Bergens, Steven H; Wasylishen, Roderick E

2004-09-22

Proton NMR imaging was used to investigate in situ the distribution of water in a polymer electrolyte membrane fuel cell operating on H2 and O2. In a single experiment, water was monitored in the gas flow channels, the membrane electrode assembly, and in the membrane surrounding the catalysts. Radial gradient diffusion removes water from the catalysts into the surrounding membrane. This research demonstrates the strength of 1H NMR microscopy as an aid for designing fuel cells to optimize water management.

Optimization of CO2 Storage in Saline Aquifers Using Water-Alternating Gas (WAG) Scheme - Case Study for Utsira Formation

NASA Astrophysics Data System (ADS)

Agarwal, R. K.; Zhang, Z.; Zhu, C.

2013-12-01

For optimization of CO2 storage and reduced CO2 plume migration in saline aquifers, a genetic algorithm (GA) based optimizer has been developed which is combined with the DOE multi-phase flow and heat transfer numerical simulation code TOUGH2. Designated as GA-TOUGH2, this combined solver/optimizer has been verified by performing optimization studies on a number of model problems and comparing the results with brute-force optimization which requires a large number of simulations. Using GA-TOUGH2, an innovative reservoir engineering technique known as water-alternating-gas (WAG) injection has been investigated to determine the optimal WAG operation for enhanced CO2 storage capacity. The topmost layer (layer # 9) of Utsira formation at Sleipner Project, Norway is considered as a case study. A cylindrical domain, which possesses identical characteristics of the detailed 3D Utsira Layer #9 model except for the absence of 3D topography, was used. Topographical details are known to be important in determining the CO2 migration at Sleipner, and are considered in our companion model for history match of the CO2 plume migration at Sleipner. However, simplification on topography here, without compromising accuracy, is necessary to analyze the effectiveness of WAG operation on CO2 migration without incurring excessive computational cost. Selected WAG operation then can be simulated with full topography details later. We consider a cylindrical domain with thickness of 35 m with horizontal flat caprock. All hydrogeological properties are retained from the detailed 3D Utsira Layer #9 model, the most important being the horizontal-to-vertical permeability ratio of 10. Constant Gas Injection (CGI) operation with nine-year average CO2 injection rate of 2.7 kg/s is considered as the baseline case for comparison. The 30-day, 15-day, and 5-day WAG cycle durations are considered for the WAG optimization design. Our computations show that for the simplified Utsira Layer #9 model, the WAG operation with 5-day cycle leads to most noticeable reduction in plume migration. For 5-day WAG cycle, the values of design variables corresponding to optimal WAG operation are found as optimal CO2 injection ICO2,optimal = 11.56 kg/s, and optimal water injection Iwater,optimal = 7.62 kg/s. The durations of CO2 and water injection in one WAG cycle are 11 and 19 days, respectively. Identical WAG cycles are repeated 20 times to complete a two-year operation. Significant reduction (22%) in CO2 migration is achieved compared to CGI operation after only two years of WAG operation. In addition, CO2 dissolution is also significantly enhanced from about 9% to 22% of the total injected CO2 . The results obtained from this and other optimization studies suggest that over 50% reduction of in situ CO2 footprint, greatly enhanced CO2 dissolution, and significantly improved well injectivity can be achieved by employing GA-TOUGH2. The optimization code has also been employed to determine the optimal well placement in a multi-well injection operation. GA-TOUGH2 appears to hold great promise for studying a host of other optimization problems related to Carbon Storage.

Research on vehicles and cargos matching model based on virtual logistics platform

NASA Astrophysics Data System (ADS)

Zhuang, Yufeng; Lu, Jiang; Su, Zhiyuan

2018-04-01

Highway less than truckload (LTL) transportation vehicles and cargos matching problem is a joint optimization problem of typical vehicle routing and loading, which is also a hot issue of operational research. This article based on the demand of virtual logistics platform, for the problem of the highway LTL transportation, the matching model of the idle vehicle and the transportation order is set up and the corresponding genetic algorithm is designed. Then the algorithm is implemented by Java. The simulation results show that the solution is satisfactory.

Expected Improvements in Work Truck Efficiency Through Connectivity and Automation

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

Walkowicz, Kevin A

This presentation focuses on the potential impact of connected and automated technologies on commercial vehicle operations. It includes topics such as the U.S. Department of Energy's Energy Efficient Mobility Systems (EEMS) program and the Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Initiative. It also describes National Renewable Energy Laboratory (NREL) research findings pertaining to the potential energy impacts of connectivity and automation and stresses the need for integration and optimization to take advantage of the benefits offered by these transformative technologies while mitigating the potential negative consequences.

Path planning during combustion mode switch

DOEpatents

Jiang, Li; Ravi, Nikhil

2015-12-29

Systems and methods are provided for transitioning between a first combustion mode and a second combustion mode in an internal combustion engine. A current operating point of the engine is identified and a target operating point for the internal combustion engine in the second combustion mode is also determined. A predefined optimized transition operating point is selected from memory. While operating in the first combustion mode, one or more engine actuator settings are adjusted to cause the operating point of the internal combustion engine to approach the selected optimized transition operating point. When the engine is operating at the selected optimized transition operating point, the combustion mode is switched from the first combustion mode to the second combustion mode. While operating in the second combustion mode, one or more engine actuator settings are adjusted to cause the operating point of the internal combustion to approach the target operating point.

Peak-Seeking Optimization of Trim for Reduced Fuel Consumption: Architecture and Performance Predictions

NASA Technical Reports Server (NTRS)

Schaefer, Jacob; Brown, Nelson

2013-01-01

A peak-seeking control approach for real-time trim configuration optimization for reduced fuel consumption has been developed by researchers at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center to address the goals of the NASA Environmentally Responsible Aviation project to reduce fuel burn and emissions. The peak-seeking control approach is based on a steepest-descent algorithm using a time-varying Kalman filter to estimate the gradient of a performance function of fuel flow versus control surface positions. In real-time operation, deflections of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of an FA-18 airplane (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) are controlled for optimization of fuel flow. This presentation presents the design and integration of this peak-seeking controller on a modified NASA FA-18 airplane with research flight control computers. A research flight was performed to collect data to build a realistic model of the performance function and characterize measurement noise. This model was then implemented into a nonlinear six-degree-of-freedom FA-18 simulation along with the peak-seeking control algorithm. With the goal of eventual flight tests, the algorithm was first evaluated in the improved simulation environment. Results from the simulation predict good convergence on minimum fuel flow with a 2.5-percent reduction in fuel flow relative to the baseline trim of the aircraft.

Peak-Seeking Optimization of Trim for Reduced Fuel Consumption: Architecture and Performance Predictions

NASA Technical Reports Server (NTRS)

Schaefer, Jacob; Brown, Nelson A.

2013-01-01

A peak-seeking control approach for real-time trim configuration optimization for reduced fuel consumption has been developed by researchers at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center to address the goals of the NASA Environmentally Responsible Aviation project to reduce fuel burn and emissions. The peak-seeking control approach is based on a steepest-descent algorithm using a time-varying Kalman filter to estimate the gradient of a performance function of fuel flow versus control surface positions. In real-time operation, deflections of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of an F/A-18 airplane (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) are controlled for optimization of fuel flow. This paper presents the design and integration of this peak-seeking controller on a modified NASA F/A-18 airplane with research flight control computers. A research flight was performed to collect data to build a realistic model of the performance function and characterize measurement noise. This model was then implemented into a nonlinear six-degree-of-freedom F/A-18 simulation along with the peak-seeking control algorithm. With the goal of eventual flight tests, the algorithm was first evaluated in the improved simulation environment. Results from the simulation predict good convergence on minimum fuel flow with a 2.5-percent reduction in fuel flow relative to the baseline trim of the aircraft.

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.

Integration of Weather Data into Airspace and Traffic Operations Simulation (ATOS) for Trajectory- Based Operations Research

NASA Technical Reports Server (NTRS)

Peters, Mark; Boisvert, Ben; Escala, Diego

2009-01-01

Explicit integration of aviation weather forecasts with the National Airspace System (NAS) structure is needed to improve the development and execution of operationally effective weather impact mitigation plans and has become increasingly important due to NAS congestion and associated increases in delay. This article considers several contemporary weather-air traffic management (ATM) integration applications: the use of probabilistic forecasts of visibility at San Francisco, the Route Availability Planning Tool to facilitate departures from the New York airports during thunderstorms, the estimation of en route capacity in convective weather, and the application of mixed-integer optimization techniques to air traffic management when the en route and terminal capacities are varying with time because of convective weather impacts. Our operational experience at San Francisco and New York coupled with very promising initial results of traffic flow optimizations suggests that weather-ATM integrated systems warrant significant research and development investment. However, they will need to be refined through rapid prototyping at facilities with supportive operational users We have discussed key elements of an emerging aviation weather research area: the explicit integration of aviation weather forecasts with NAS structure to improve the effectiveness and timeliness of weather impact mitigation plans. Our insights are based on operational experiences with Lincoln Laboratory-developed integrated weather sensing and processing systems, and derivative early prototypes of explicit ATM decision support tools such as the RAPT in New York City. The technical components of this effort involve improving meteorological forecast skill, tailoring the forecast outputs to the problem of estimating airspace impacts, developing models to quantify airspace impacts, and prototyping automated tools that assist in the development of objective broad-area ATM strategies, given probabilistic weather forecasts. Lincoln Laboratory studies and prototype demonstrations in this area are helping to define the weather-assimilated decision-making system that is envisioned as a key capability for the multi-agency Next Generation Air Transportation System [1]. The Laboratory's work in this area has involved continuing, operations-based evolution of both weather forecasts and models for weather impacts on the NAS. Our experience has been that the development of usable ATM technologies that address weather impacts must proceed via rapid prototyping at facilities whose users are highly motivated to participate in system evolution.

Kinetics of Supercritical Water Oxidation

DTIC Science & Technology

1995-12-31

milestone and Sandia Technical Report. A much-needed report describing in detail the operation of the Supercritical Fluids Reactor (SFR) was also...years. In addition, the literature research required to arrive at this optimal design will be used to improve the performance of the Supercritical Fluids ...the Supercritical Fluids Reactor (SFR)" (Sandia National Laboratories Report SAND-8203, Livermore, CA, 1995). R. R. Steeper, "Methane and Methanol

Program for Research on Dietary Supplements in Military Operations and Healthcare Metabolically Optimized Brain - JWF

DTIC Science & Technology

2014-05-01

Alcohol; Vitamins / Minerals / Antioxidants / Dietary supplements (not specified); Herbal Medicine (Subsets: Ginseng and Gingko Biloba); Diet...looking specifically at the role of glucose (Hoyland 2008). c. Other Intervention Groupings considered: i. Herbal Medicine : 58 abstracts identified...involved herbal medicine (excluding gingko biloba and ginseng) as an intervention on the healthy adult population. 31 separate herb or herbal

Radiation -- A Cosmic Hazard to Human Habitation in Space

NASA Technical Reports Server (NTRS)

Lewis, Ruthan; Pellish, Jonathan

2017-01-01

Radiation exposure is one of the greatest environmental threats to the performance and success of human and robotic space missions. Radiation permeates all space and aeronautical systems, challenges optimal and reliable performance, and tests survival and survivability. We will discuss the broad scope of research, technological, and operational considerations to forecast and mitigate the effects of the radiation environment for deep space and planetary exploration.

Renewable Energy Institute International (REII): Cooperative Research and Development Final Report, CRADA Number CRD-10-387

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

Carpenter, D.

2014-11-01

NREL will provide the Renewable Energy Institute with detailed on-site biomass gasifier syngas monitoring, using the NREL transportable Molecular Beam Mass Spectrometer. This information will be used to optimize the parameters of the gasifier operation, insuring the quality of the syngas made in the Red Lion Bioenergy gasifier and its compatibility with catalytic conversion to fuels.

Preliminary investigation of power flow and electrode phenomena in a multi-megawatt coaxial plasma thruster

NASA Technical Reports Server (NTRS)

Schoenberg, Kurt; Gerwin, Richard; Henins, Ivars; Mayo, Robert; Scheuer, Jay; Nurden, Glen

1993-01-01

This paper summarizes preliminary experimental and theoretical research that was directed towards the study of quasisteady-state power flow in a large, un-optimized, multi-megawatt coaxial plasma thruster. The report addresses large coaxial thruster operation and includes evaluation and interpretation of the experimental results with a view to the development of efficient, steady-state megawatt-class magnetoplasmadynamic (MPD) thrusters.

Operations research for resource planning and -use in radiotherapy: a literature review.

PubMed

Vieira, Bruno; Hans, Erwin W; van Vliet-Vroegindeweij, Corine; van de Kamer, Jeroen; van Harten, Wim

2016-11-25

The delivery of radiotherapy (RT) involves the use of rather expensive resources and multi-disciplinary staff. As the number of cancer patients receiving RT increases, timely delivery becomes increasingly difficult due to the complexities related to, among others, variable patient inflow, complex patient routing, and the joint planning of multiple resources. Operations research (OR) methods have been successfully applied to solve many logistics problems through the development of advanced analytical models for improved decision making. This paper presents the state of the art in the application of OR methods for logistics optimization in RT, at various managerial levels. A literature search was performed in six databases covering several disciplines, from the medical to the technical field. Papers included in the review were published in peer-reviewed journals from 2000 to 2015. Data extraction includes the subject of research, the OR methods used in the study, the extent of implementation according to a six-stage model and the (potential) impact of the results in practice. From the 33 papers included in the review, 18 addressed problems related to patient scheduling (of which 12 focus on scheduling patients on linear accelerators), 8 focus on strategic decision making, 5 on resource capacity planning, and 2 on patient prioritization. Although calculating promising results, none of the papers reported a full implementation of the model with at least a thorough pre-post performance evaluation, indicating that, apart from possible reporting bias, implementation rates of OR models in RT are probably low. The literature on OR applications in RT covers a wide range of approaches from strategic capacity management to operational scheduling levels, and shows that considerable benefits in terms of both waiting times and resource utilization are likely to be achieved. Various fields can be further developed, for instance optimizing the coordination between the available capacity of different imaging devices or developing scheduling models that consider the RT chain of operations as a whole rather than the treatment machines alone.

Optimizing operational water management with soil moisture data from Sentinel-1 satellites

NASA Astrophysics Data System (ADS)

Pezij, Michiel; Augustijn, Denie; Hendriks, Dimmie; Hulscher, Suzanne

2016-04-01

In the Netherlands, regional water authorities are responsible for management and maintenance of regional water bodies. Due to socio-economic developments (e.g. agricultural intensification and on-going urbanisation) and an increase in climate variability, the pressure on these water bodies is growing. Optimization of water availability by taking into account the needs of different users, both in wet and dry periods, is crucial for sustainable developments. To support timely and well-directed operational water management, accurate information on the current state of the system as well as reliable models to evaluate water management optimization measures are essential. Previous studies showed that the use of remote sensing data (for example soil moisture data) in water management offers many opportunities (e.g. Wanders et al. (2014)). However, these data are not yet used in operational applications at a large scale. The Sentinel-1 satellites programme offers high spatiotemporal resolution soil moisture data (1 image per 6 days with a spatial resolution of 10 by 10 m) that are freely available. In this study, these data will be used to improve the Netherlands Hydrological Instrument (NHI). The NHI consists of coupled models for the unsaturated zone (MetaSWAP), groundwater (iMODFLOW) and surface water (Mozart and DM). The NHI is used for scenario analyses and operational water management in the Netherlands (De Lange et al., 2014). Due to the lack of soil moisture data, the unsaturated zone model is not yet thoroughly validated and its output is not used by regional water authorities for decision-making. Therefore, the newly acquired remotely sensed soil moisture data will be used to improve the skill of the MetaSWAP-model and the NHI as whole. The research will focus among other things on the calibration of soil parameters by comparing model output (MetaSWAP) with the remotely sensed soil moisture data. Eventually, we want to apply data-assimilation to improve operational water management in cooperation with users. As a first step, the current simulation of soil moisture processes within the NHI will be reviewed. We want to present the findings of this assessment as well as the research methodology. This PhD-research is part of the Optimizing Water Availability with Sentinel-1 Satellites (OWAS1S)-project in which two other PhD-students are participating. They are focussing on the translation of raw Sentinel-1 satellite data to surface soil moisture data and the application of the remotely sensed soil moisture data on crop water availability and trafficability on field scale. References: De Lange, W. J., Prinsen, G. F., Hoogewoud, J. C., Veldhuizen, A. A., Verkaik, J., Oude Essink, G. H. P., van Walsum, P. E. V., Delsman, J. R., Hunink, J. C., Massop, H. T. L., & Kroon, T. (2014). An operational, multi-scale, multi-model system for consensus-based, integrated water management and policy analysis: The Netherlands Hydrological Instrument. Environmental Modelling & Software, 59, 98-108. doi: 10.1016/j.envsoft.2014.05.009 Wanders, N., Karssenberg, D., de Roo, A., de Jong, S. M., & Bierkens, M. F. P. (2014). The suitability of remotely sensed soil moisture for improving operational flood forecasting. Hydrology and Earth System Sciences, 18(6), 2343-2357. doi: 10.5194/hess-18-2343-2014

Principled negotiation and distributed optimization for advanced air traffic management

NASA Astrophysics Data System (ADS)

Wangermann, John Paul

Today's aircraft/airspace system faces complex challenges. Congestion and delays are widespread as air traffic continues to grow. Airlines want to better optimize their operations, and general aviation wants easier access to the system. Additionally, the accident rate must decline just to keep the number of accidents each year constant. New technology provides an opportunity to rethink the air traffic management process. Faster computers, new sensors, and high-bandwidth communications can be used to create new operating models. The choice is no longer between "inflexible" strategic separation assurance and "flexible" tactical conflict resolution. With suitable operating procedures, it is possible to have strategic, four-dimensional separation assurance that is flexible and allows system users maximum freedom to optimize operations. This thesis describes an operating model based on principled negotiation between agents. Many multi-agent systems have agents that have different, competing interests but have a shared interest in coordinating their actions. Principled negotiation is a method of finding agreement between agents with different interests. By focusing on fundamental interests and searching for options for mutual gain, agents with different interests reach agreements that provide benefits for both sides. Using principled negotiation, distributed optimization by each agent can be coordinated leading to iterative optimization of the system. Principled negotiation is well-suited to aircraft/airspace systems. It allows aircraft and operators to propose changes to air traffic control. Air traffic managers check the proposal maintains required aircraft separation. If it does, the proposal is either accepted or passed to agents whose trajectories change as part of the proposal for approval. Aircraft and operators can use all the data at hand to develop proposals that optimize their operations, while traffic managers can focus on their primary duty of ensuring aircraft safety. This thesis describes how an aircraft/airspace system using principled negotiation operates, and reports simulation results on the concept. The results show safety is maintained while aircraft have freedom to optimize their operations.

A Study of the Optimal Planning Model for Reservoir Sustainable Management- A Case Study of Shihmen Reservoir

NASA Astrophysics Data System (ADS)

Chen, Y. Y.; Ho, C. C.; Chang, L. C.

2017-12-01

The reservoir management in Taiwan faces lots of challenge. Massive sediment caused by landslide were flushed into reservoir, which will decrease capacity, rise the turbidity, and increase supply risk. Sediment usually accompanies nutrition that will cause eutrophication problem. Moreover, the unevenly distribution of rainfall cause water supply instability. Hence, how to ensure sustainable use of reservoirs has become an important task in reservoir management. The purpose of the study is developing an optimal planning model for reservoir sustainable management to find out an optimal operation rules of reservoir flood control and sediment sluicing. The model applies Genetic Algorithms to combine with the artificial neural network of hydraulic analysis and reservoir sediment movement. The main objective of operation rules in this study is to prevent reservoir outflow caused downstream overflow, minimum the gap between initial and last water level of reservoir, and maximum sluicing sediment efficiency. A case of Shihmen reservoir was used to explore the different between optimal operating rule and the current operation of the reservoir. The results indicate optimal operating rules tended to open desilting tunnel early and extend open duration during flood discharge period. The results also show the sluicing sediment efficiency of optimal operating rule is 36%, 44%, 54% during Typhoon Jangmi, Typhoon Fung-Wong, and Typhoon Sinlaku respectively. The results demonstrate the optimal operation rules do play a role in extending the service life of Shihmen reservoir and protecting the safety of downstream. The study introduces a low cost strategy, alteration of operation reservoir rules, into reservoir sustainable management instead of pump dredger in order to improve the problem of elimination of reservoir sediment and high cost.

Mission Planning and Decision Support for Underwater Glider Networks: A Sampling on-Demand Approach

PubMed Central

Ferri, Gabriele; Cococcioni, Marco; Alvarez, Alberto

2015-01-01

This paper describes an optimal sampling approach to support glider fleet operators and marine scientists during the complex task of planning the missions of fleets of underwater gliders. Optimal sampling, which has gained considerable attention in the last decade, consists in planning the paths of gliders to minimize a specific criterion pertinent to the phenomenon under investigation. Different criteria (e.g., A, G, or E optimality), used in geosciences to obtain an optimum design, lead to different sampling strategies. In particular, the A criterion produces paths for the gliders that minimize the overall level of uncertainty over the area of interest. However, there are commonly operative situations in which the marine scientists may prefer not to minimize the overall uncertainty of a certain area, but instead they may be interested in achieving an acceptable uncertainty sufficient for the scientific or operational needs of the mission. We propose and discuss here an approach named sampling on-demand that explicitly addresses this need. In our approach the user provides an objective map, setting both the amount and the geographic distribution of the uncertainty to be achieved after assimilating the information gathered by the fleet. A novel optimality criterion, called Aη, is proposed and the resulting minimization problem is solved by using a Simulated Annealing based optimizer that takes into account the constraints imposed by the glider navigation features, the desired geometry of the paths and the problems of reachability caused by ocean currents. This planning strategy has been implemented in a Matlab toolbox called SoDDS (Sampling on-Demand and Decision Support). The tool is able to automatically download the ocean fields data from MyOcean repository and also provides graphical user interfaces to ease the input process of mission parameters and targets. The results obtained by running SoDDS on three different scenarios are provided and show that SoDDS, which is currently used at NATO STO Centre for Maritime Research and Experimentation (CMRE), can represent a step forward towards a systematic mission planning of glider fleets, dramatically reducing the efforts of glider operators. PMID:26712763

Mission Planning and Decision Support for Underwater Glider Networks: A Sampling on-Demand Approach.

PubMed

Ferri, Gabriele; Cococcioni, Marco; Alvarez, Alberto

2015-12-26

This paper describes an optimal sampling approach to support glider fleet operators and marine scientists during the complex task of planning the missions of fleets of underwater gliders. Optimal sampling, which has gained considerable attention in the last decade, consists in planning the paths of gliders to minimize a specific criterion pertinent to the phenomenon under investigation. Different criteria (e.g., A, G, or E optimality), used in geosciences to obtain an optimum design, lead to different sampling strategies. In particular, the A criterion produces paths for the gliders that minimize the overall level of uncertainty over the area of interest. However, there are commonly operative situations in which the marine scientists may prefer not to minimize the overall uncertainty of a certain area, but instead they may be interested in achieving an acceptable uncertainty sufficient for the scientific or operational needs of the mission. We propose and discuss here an approach named sampling on-demand that explicitly addresses this need. In our approach the user provides an objective map, setting both the amount and the geographic distribution of the uncertainty to be achieved after assimilating the information gathered by the fleet. A novel optimality criterion, called A η , is proposed and the resulting minimization problem is solved by using a Simulated Annealing based optimizer that takes into account the constraints imposed by the glider navigation features, the desired geometry of the paths and the problems of reachability caused by ocean currents. This planning strategy has been implemented in a Matlab toolbox called SoDDS (Sampling on-Demand and Decision Support). The tool is able to automatically download the ocean fields data from MyOcean repository and also provides graphical user interfaces to ease the input process of mission parameters and targets. The results obtained by running SoDDS on three different scenarios are provided and show that SoDDS, which is currently used at NATO STO Centre for Maritime Research and Experimentation (CMRE), can represent a step forward towards a systematic mission planning of glider fleets, dramatically reducing the efforts of glider operators.

Visibility monitoring in the southern California desert for the Department of Defense: Research on operations-limiting visual extinction, RESOLVE protocol

NASA Astrophysics Data System (ADS)

Blumenthal, D.; Trijonis, J.

1984-09-01

A decrease in visibility in the R2508 airspace (in the western Mojave Desert in southern California) since the mid-1940s, when flight test and training facilities were established in this region, is adversely affecting flight and test operations. The Joint Policy and Planning Board (JPPB) of the Department of Defense has initiated studies and discussions of the visibility issue with the goal of developing a management strategy to maintain and optimize the operational capabilities of the test facilities. To identify trends in and sources of visibility degradation in the desert, JPPB initiated two programs: (1) a compilation and review of the historical visibility and air quality data in the California desert region, to be coordinated by the California Desert Air Working Group (CDAWG) and funded by CDAWG participants; and (2) RESearch on Operations-Limiting Visual Extinction (RESOLVE), which involves measuring the visibility at key receptor sites (monitoring stations) in the R2508 region. The report describes the current status of and future plans for the RESOLVE program.

Optimisation multi-objectif des systemes energetiques

NASA Astrophysics Data System (ADS)

Dipama, Jean

The increasing demand of energy and the environmental concerns related to greenhouse gas emissions lead to more and more private or public utilities to turn to nuclear energy as an alternative for the future. Nuclear power plants are then called to experience large expansion in the coming years. Improved technologies will then be put in place to support the development of these plants. This thesis considers the optimization of the thermodynamic cycle of the secondary loop of Gentilly-2 nuclear power plant in terms of output power and thermal efficiency. In this thesis, investigations are carried out to determine the optimal operating conditions of steam power cycles by the judicious use of the combination of steam extraction at the different stages of the turbines. Whether it is the case of superheating or regeneration, we are confronted in all cases to an optimization problem involving two conflicting objectives, as increasing the efficiency imply the decrease of mechanical work and vice versa. Solving this kind of problem does not lead to unique solution, but to a set of solutions that are tradeoffs between the conflicting objectives. To search all of these solutions, called Pareto optimal solutions, the use of an appropriate optimization algorithm is required. Before starting the optimization of the secondary loop, we developed a thermodynamic model of the secondary loop which includes models for the main thermal components (e.g., turbine, moisture separator-superheater, condenser, feedwater heater and deaerator). This model is used to calculate the thermodynamic state of the steam and water at the different points of the installation. The thermodynamic model has been developed with Matlab and validated by comparing its predictions with the operating data provided by the engineers of the power plant. The optimizer developed in VBA (Visual Basic for Applications) uses an optimization algorithm based on the principle of genetic algorithms, a stochastic optimization method which is very robust and widely used to solve problems usually difficult to handle by traditional methods. Genetic algorithms (GAs) have been used in previous research and proved to be efficient in optimizing heat exchangers networks (HEN) (Dipama et al., 2008). So, HEN have been synthesized to recover the maximum heat in an industrial process. The optimization problem formulated in the context of this work consists of a single objective, namely the maximization of energy recovery. The optimization algorithm developed in this thesis extends the ability of GAs by taking into account several objectives simultaneously. This algorithm provides an innovation in the method of finding optimal solutions, by using a technique which consist of partitioning the solutions space in the form of parallel grids called "watching corridors". These corridors permit to specify areas (the observation corridors) in which the most promising feasible solutions are found and used to guide the search towards optimal solutions. A measure of the progress of the search is incorporated into the optimization algorithm to make it self-adaptive through the use of appropriate genetic operators at each stage of optimization process. The proposed method allows a fast convergence and ensure a diversity of solutions. Moreover, this method gives the algorithm the ability to overcome difficulties associated with optimizing problems with complex Pareto front landscapes (e.g., discontinuity, disjunction, etc.). The multi-objective optimization algorithm has been first validated using numerical test problems found in the literature as well as energy systems optimization problems. Finally, the proposed optimization algorithm has been applied for the optimization of the secondary loop of Gentilly-2 nuclear power plant, and a set of solutions have been found which permit to make the power plant operate in optimal conditions. (Abstract shortened by UMI.)

Optimal Model-Based Fault Estimation and Correction for Particle Accelerators and Industrial Plants Using Combined Support Vector Machines and First Principles Models

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

Sayyar-Rodsari, Bijan; Schweiger, Carl; /SLAC /Pavilion Technologies, Inc., Austin, TX

2010-08-25

Timely estimation of deviations from optimal performance in complex systems and the ability to identify corrective measures in response to the estimated parameter deviations has been the subject of extensive research over the past four decades. The implications in terms of lost revenue from costly industrial processes, operation of large-scale public works projects and the volume of the published literature on this topic clearly indicates the significance of the problem. Applications range from manufacturing industries (integrated circuits, automotive, etc.), to large-scale chemical plants, pharmaceutical production, power distribution grids, and avionics. In this project we investigated a new framework for buildingmore » parsimonious models that are suited for diagnosis and fault estimation of complex technical systems. We used Support Vector Machines (SVMs) to model potentially time-varying parameters of a First-Principles (FP) description of the process. The combined SVM & FP model was built (i.e. model parameters were trained) using constrained optimization techniques. We used the trained models to estimate faults affecting simulated beam lifetime. In the case where a large number of process inputs are required for model-based fault estimation, the proposed framework performs an optimal nonlinear principal component analysis of the large-scale input space, and creates a lower dimension feature space in which fault estimation results can be effectively presented to the operation personnel. To fulfill the main technical objectives of the Phase I research, our Phase I efforts have focused on: (1) SVM Training in a Combined Model Structure - We developed the software for the constrained training of the SVMs in a combined model structure, and successfully modeled the parameters of a first-principles model for beam lifetime with support vectors. (2) Higher-order Fidelity of the Combined Model - We used constrained training to ensure that the output of the SVM (i.e. the parameters of the beam lifetime model) are physically meaningful. (3) Numerical Efficiency of the Training - We investigated the numerical efficiency of the SVM training. More specifically, for the primal formulation of the training, we have developed a problem formulation that avoids the linear increase in the number of the constraints as a function of the number of data points. (4) Flexibility of Software Architecture - The software framework for the training of the support vector machines was designed to enable experimentation with different solvers. We experimented with two commonly used nonlinear solvers for our simulations. The primary application of interest for this project has been the sustained optimal operation of particle accelerators at the Stanford Linear Accelerator Center (SLAC). Particle storage rings are used for a variety of applications ranging from 'colliding beam' systems for high-energy physics research to highly collimated x-ray generators for synchrotron radiation science. Linear accelerators are also used for collider research such as International Linear Collider (ILC), as well as for free electron lasers, such as the Linear Coherent Light Source (LCLS) at SLAC. One common theme in the operation of storage rings and linear accelerators is the need to precisely control the particle beams over long periods of time with minimum beam loss and stable, yet challenging, beam parameters. We strongly believe that beyond applications in particle accelerators, the high fidelity and cost benefits of a combined model-based fault estimation/correction system will attract customers from a wide variety of commercial and scientific industries. Even though the acquisition of Pavilion Technologies, Inc. by Rockwell Automation Inc. in 2007 has altered the small business status of the Pavilion and it no longer qualifies for a Phase II funding, our findings in the course of the Phase I research have convinced us that further research will render a workable model-based fault estimation and correction for particle accelerators and industrial plants feasible.« less

Fuzzy multiobjective models for optimal operation of a hydropower system

NASA Astrophysics Data System (ADS)

Teegavarapu, Ramesh S. V.; Ferreira, André R.; Simonovic, Slobodan P.

2013-06-01

Optimal operation models for a hydropower system using new fuzzy multiobjective mathematical programming models are developed and evaluated in this study. The models use (i) mixed integer nonlinear programming (MINLP) with binary variables and (ii) integrate a new turbine unit commitment formulation along with water quality constraints used for evaluation of reservoir downstream impairment. Reardon method used in solution of genetic algorithm optimization problems forms the basis for development of a new fuzzy multiobjective hydropower system optimization model with creation of Reardon type fuzzy membership functions. The models are applied to a real-life hydropower reservoir system in Brazil. Genetic Algorithms (GAs) are used to (i) solve the optimization formulations to avoid computational intractability and combinatorial problems associated with binary variables in unit commitment, (ii) efficiently address Reardon method formulations, and (iii) deal with local optimal solutions obtained from the use of traditional gradient-based solvers. Decision maker's preferences are incorporated within fuzzy mathematical programming formulations to obtain compromise operating rules for a multiobjective reservoir operation problem dominated by conflicting goals of energy production, water quality and conservation releases. Results provide insight into compromise operation rules obtained using the new Reardon fuzzy multiobjective optimization framework and confirm its applicability to a variety of multiobjective water resources problems.

Smart distribution systems

DOE PAGES

Jiang, Yazhou; Liu, Chen -Ching; Xu, Yin

2016-04-19

The increasing importance of system reliability and resilience is changing the way distribution systems are planned and operated. To achieve a distribution system self-healing against power outages, emerging technologies and devices, such as remote-controlled switches (RCSs) and smart meters, are being deployed. The higher level of automation is transforming traditional distribution systems into the smart distribution systems (SDSs) of the future. The availability of data and remote control capability in SDSs provides distribution operators with an opportunity to optimize system operation and control. In this paper, the development of SDSs and resulting benefits of enhanced system capabilities are discussed. Amore » comprehensive survey is conducted on the state-of-the-art applications of RCSs and smart meters in SDSs. Specifically, a new method, called Temporal Causal Diagram (TCD), is used to incorporate outage notifications from smart meters for enhanced outage management. To fully utilize the fast operation of RCSs, the spanning tree search algorithm is used to develop service restoration strategies. Optimal placement of RCSs and the resulting enhancement of system reliability are discussed. Distribution system resilience with respect to extreme events is presented. Furthermore, test cases are used to demonstrate the benefit of SDSs. Active management of distributed generators (DGs) is introduced. Future research in a smart distribution environment is proposed.« less

Coupling long and short term decisions in the design of urban water supply infrastructure for added reliability and flexibility

NASA Astrophysics Data System (ADS)

Marques, G.; Fraga, C. C. S.; Medellin-Azuara, J.

2016-12-01

The expansion and operation of urban water supply systems under growing demands, hydrologic uncertainty and water scarcity requires a strategic combination of supply sources for reliability, reduced costs and improved operational flexibility. The design and operation of such portfolio of water supply sources involves integration of long and short term planning to determine what and when to expand, and how much to use of each supply source accounting for interest rates, economies of scale and hydrologic variability. This research presents an integrated methodology coupling dynamic programming optimization with quadratic programming to optimize the expansion (long term) and operations (short term) of multiple water supply alternatives. Lagrange Multipliers produced by the short-term model provide a signal about the marginal opportunity cost of expansion to the long-term model, in an iterative procedure. A simulation model hosts the water supply infrastructure and hydrologic conditions. Results allow (a) identification of trade offs between cost and reliability of different expansion paths and water use decisions; (b) evaluation of water transfers between urban supply systems; and (c) evaluation of potential gains by reducing water system losses as a portfolio component. The latter is critical in several developing countries where water supply system losses are high and often neglected in favor of more system expansion.

Impact of Capital and Current Costs Changes of the Incineration Process of the Medical Waste on System Management Cost

NASA Astrophysics Data System (ADS)

Jolanta Walery, Maria

2017-12-01

The article describes optimization studies aimed at analysing the impact of capital and current costs changes of medical waste incineration on the cost of the system management and its structure. The study was conducted on the example of an analysis of the system of medical waste management in the Podlaskie Province, in north-eastern Poland. 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. capital and current costs of medical waste incineration on economic efficiency index (E) and the spatial structure of the system was determined. Optimization studies were conducted for the following cases: with a 25% increase in capital and current costs of incineration process, followed by 50%, 75% and 100% increase. As a result of the calculations, the highest cost of system operation was achieved at the level of 3143.70 PLN/t with the assumption of 100% increase in capital and current costs of incineration process. There was an increase in the economic efficiency index (E) by about 97% in relation to run 1.

Optimization study on structural analyses for the J-PARC mercury target vessel

NASA Astrophysics Data System (ADS)

Guan, Wenhai; Wakai, Eiichi; Naoe, Takashi; Kogawa, Hiroyuki; Wakui, Takashi; Haga, Katsuhiro; Takada, Hiroshi; Futakawa, Masatoshi

2018-06-01

The spallation neutron source at the Japan Proton Accelerator Research Complex (J-PARC) mercury target vessel is used for various materials science studies, work is underway to achieve stable operation at 1 MW. This is very important for enhancing the structural integrity and durability of the target vessel, which is being developed for 1 MW operation. In the present study, to reduce thermal stress and relax stress concentrations more effectively in the existing target vessel in J-PARC, an optimization approach called the Taguchi method (TM) is applied to thermo-mechanical analysis. The ribs and their relative parameters, as well as the thickness of the mercury vessel and shrouds, were selected as important design parameters for this investigation. According to the analytical results of 18 model types designed using the TM, the optimal design was determined. It is characterized by discrete ribs and a thicker vessel wall than the current design. The maximum thermal stresses in the mercury vessel and the outer shroud were reduced by 14% and 15%, respectively. Furthermore, it was indicated that variations in rib width, left/right rib intervals, and shroud thickness could influence the maximum thermal stress performance. It is therefore concluded that the TM was useful for optimizing the structure of the target vessel and to reduce the thermal stress in a small number of calculation cases.

Clinical trials: bringing research to the bedside.

PubMed

Arvay, C A

1991-02-01

Over the years, clinical trials with their structured treatment plans and multicenter involvement have been instrumental in developing new treatments and establishing standard of care therapy. While clinical trials strive to advance medical knowledge, they provide scientifically sound, state of the art care and their use should be increased. The Brain Tumor Cooperative Group, one such NCI-sponsored cooperative group, has been the primary group for the treatment of malignant gliomas. As the field of neuro-oncology expands, the neuroscience nurse needs to develop an understanding of clinical trials and their operation. The nurse is in an optimal position to support medical research and the research participant.

Droplet microfluidics for synthetic biology

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

Gach, Philip Charles; Iwai, Kosuke; Kim, Peter Wonhee

Here, synthetic biology is an interdisciplinary field that aims to engineer biological systems for useful purposes. Organism engineering often requires the optimization of individual genes and/or entire biological pathways (consisting of multiple genes). Advances in DNA sequencing and synthesis have recently begun to enable the possibility of evaluating thousands of gene variants and hundreds of thousands of gene combinations. However, such large-scale optimization experiments remain cost-prohibitive to researchers following traditional molecular biology practices, which are frequently labor-intensive and suffer from poor reproducibility. Liquid handling robotics may reduce labor and improve reproducibility, but are themselves expensive and thus inaccessible to mostmore » researchers. Microfluidic platforms offer a lower entry price point alternative to robotics, and maintain high throughput and reproducibility while further reducing operating costs through diminished reagent volume requirements. Droplet microfluidics have shown exceptional promise for synthetic biology experiments, including DNA assembly, transformation/transfection, culturing, cell sorting, phenotypic assays, artificial cells and genetic circuits.« less

Feasibility study of using laser-generated neutron beam for BNCT.

PubMed

Kasesaz, Y; Rahmani, F; Khalafi, H

2015-09-01

The feasibility of using a laser-accelerated proton beam to produce a neutron source, via (p,n) reaction, for Boron Neutron Capture Therapy (BNCT) applications has been studied by MCNPX Monte Carlo code. After optimization of the target material and its thickness, a Beam Shaping Assembly (BSA) has been designed and optimized to provide appropriate neutron beam according to the recommended criteria by International Atomic Energy Agency. It was found that the considered laser-accelerated proton beam can provide epithermal neutron flux of ∼2×10(6) n/cm(2) shot. To achieve an appropriate epithermal neutron flux for BNCT treatment, the laser must operate at repetition rates of 1 kHz, which is rather ambitious at this moment. But it can be used in some BNCT researches field such as biological research. Copyright © 2015 Elsevier Ltd. All rights reserved.

Droplet microfluidics for synthetic biology

DOE PAGES

Gach, Philip Charles; Iwai, Kosuke; Kim, Peter Wonhee; ...

2017-08-10

Here, synthetic biology is an interdisciplinary field that aims to engineer biological systems for useful purposes. Organism engineering often requires the optimization of individual genes and/or entire biological pathways (consisting of multiple genes). Advances in DNA sequencing and synthesis have recently begun to enable the possibility of evaluating thousands of gene variants and hundreds of thousands of gene combinations. However, such large-scale optimization experiments remain cost-prohibitive to researchers following traditional molecular biology practices, which are frequently labor-intensive and suffer from poor reproducibility. Liquid handling robotics may reduce labor and improve reproducibility, but are themselves expensive and thus inaccessible to mostmore » researchers. Microfluidic platforms offer a lower entry price point alternative to robotics, and maintain high throughput and reproducibility while further reducing operating costs through diminished reagent volume requirements. Droplet microfluidics have shown exceptional promise for synthetic biology experiments, including DNA assembly, transformation/transfection, culturing, cell sorting, phenotypic assays, artificial cells and genetic circuits.« less

Using information Theory in Optimal Test Point Selection for Health Management in NASA's Exploration Vehicles

NASA Technical Reports Server (NTRS)

Mehr, Ali Farhang; Tumer, Irem

2005-01-01

In this paper, we will present a new methodology that measures the "worth" of deploying an additional testing instrument (sensor) in terms of the amount of information that can be retrieved from such measurement. This quantity is obtained using a probabilistic model of RLV's that has been partially developed in the NASA Ames Research Center. A number of correlated attributes are identified and used to obtain the worth of deploying a sensor in a given test point from an information-theoretic viewpoint. Once the information-theoretic worth of sensors is formulated and incorporated into our general model for IHM performance, the problem can be formulated as a constrained optimization problem where reliability and operational safety of the system as a whole is considered. Although this research is conducted specifically for RLV's, the proposed methodology in its generic form can be easily extended to other domains of systems health monitoring.

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

Chaos minimization in DC-DC boost converter using circuit parameter optimization

NASA Astrophysics Data System (ADS)

Sudhakar, N.; Natarajan, Rajasekar; Gourav, Kumar; Padmavathi, P.

2017-11-01

DC-DC converters are prone to several types of nonlinear phenomena including bifurcation, quasi periodicity, intermittency and chaos. These undesirable effects must be controlled for periodic operation of the converter to ensure the stability. In this paper an effective solution to control of chaos in solar fed DC-DC boost converter is proposed. Controlling of chaos is significantly achieved using optimal circuit parameters obtained through Bacterial Foraging Optimization Algorithm. The optimization renders the suitable parameters in minimum computational time. The obtained results are compared with the operation of traditional boost converter. Further the obtained results with BFA optimized parameter ensures the operations of the converter are within the controllable region. To elaborate the study of bifurcation analysis with optimized and unoptimized parameters are also presented.

NOAA Atmospheric, Marine and Arctic Monitoring Using UASs (including Rapid Response)

NASA Astrophysics Data System (ADS)

Coffey, J. J.; Jacobs, T.

2015-12-01

Unmanned systems have the potential to efficiently, effectively, economically, and safely bridge critical observation requirements in an environmentally friendly manner. As the United States' Atmospheric, Marine and Arctic areas of interest expand and include hard-to-reach regions of the Earth (such as the Arctic and remote oceanic areas) optimizing unmanned capabilities will be needed to advance the United States' science, technology and security efforts. Through increased multi-mission and multi-agency operations using improved inter-operable and autonomous unmanned systems, the research and operations communities will better collect environmental intelligence and better protect our Country against hazardous weather, environmental, marine and polar hazards. This presentation will examine NOAA's Atmospheric, Marine and Arctic Monitoring Unmanned Aircraft System (UAS) strategies which includes developing a coordinated effort to maximize the efficiency and capabilities of unmanned systems across the federal government and research partners. Numerous intra- and inter-agency operational demonstrations and assessments have been made to verify and validated these strategies. This includes the introduction of the Targeted Autonomous Insitu Sensing and Rapid Response (TAISRR) with UAS concept of operations. The presentation will also discuss the requisite UAS capabilities and our experience in using them.

Fuzzy logic controller optimization

DOEpatents

Sepe, Jr., Raymond B; Miller, John Michael

2004-03-23

A method is provided for optimizing a rotating induction machine system fuzzy logic controller. The fuzzy logic controller has at least one input and at least one output. Each input accepts a machine system operating parameter. Each output produces at least one machine system control parameter. The fuzzy logic controller generates each output based on at least one input and on fuzzy logic decision parameters. Optimization begins by obtaining a set of data relating each control parameter to at least one operating parameter for each machine operating region. A model is constructed for each machine operating region based on the machine operating region data obtained. The fuzzy logic controller is simulated with at least one created model in a feedback loop from a fuzzy logic output to a fuzzy logic input. Fuzzy logic decision parameters are optimized based on the simulation.

Prediction of wastewater treatment plants performance based on artificial fish school neural network

NASA Astrophysics Data System (ADS)

Zhang, Ruicheng; Li, Chong

2011-10-01

A reliable model for wastewater treatment plant is essential in providing a tool for predicting its performance and to form a basis for controlling the operation of the process. This would minimize the operation costs and assess the stability of environmental balance. For the multi-variable, uncertainty, non-linear characteristics of the wastewater treatment system, an artificial fish school neural network prediction model is established standing on actual operation data in the wastewater treatment system. The model overcomes several disadvantages of the conventional BP neural network. The results of model calculation show that the predicted value can better match measured value, played an effect on simulating and predicting and be able to optimize the operation status. The establishment of the predicting model provides a simple and practical way for the operation and management in wastewater treatment plant, and has good research and engineering practical value.

Progress Toward Future Runway Management

NASA Technical Reports Server (NTRS)

Lohr, Gary W.; Brown, Sherilyn A.; Atkins, Stephen; Eisenhawer, Stephen W.; Bott, Terrance F.; Long, Dou; Hasan, Shahab

2011-01-01

The runway is universally acknowledged as a constraining factor to capacity in the National Airspace System (NAS). It follows that investigation of the effective use of runways, both in terms of selection and assignment, is paramount to the efficiency of future NAS operations. The need to address runway management is not a new idea; however, as the complexities of factors affecting runway selection and usage increase, the need for effective research in this area correspondingly increases. Under the National Aeronautics and Space Administration s Airspace Systems Program, runway management is a key research area. To address a future NAS which promises to be a complex landscape of factors and competing interests among users and operators, effective runway management strategies and capabilities are required. This effort has evolved from an assessment of current practices, an understanding of research activities addressing surface and airspace operations, traffic flow management enhancements, among others. This work has yielded significant progress. Systems analysis work indicates that the value of System Oriented Runway Management tools is significantly increased in the metroplex environment over that of the single airport case. Algorithms have been developed to provide runway configuration recommendations for a single airport with multiple runways. A benefits analysis has been conducted that indicates the SORM benefits include supporting traffic growth, cost reduction as a result of system efficiency, NAS optimization from metroplex operations, fairness in aircraft operations, and rational decision making.

Minimization of Vibroacoustic Effects as a Criterion for Operation of Gear Transmissions in Accordance with Sustainable Development Principles

NASA Astrophysics Data System (ADS)

Wieczorek, Andrzej N.; Kruk, Radosław

2016-03-01

In correctly functioning maintenance systems it is most important to prevent possible failures. A reduction of the vibroacoustic effects accompanying the operation of machines and equipment, including transmissions, is among the factors that lower the probability of a failure. The paper presents the results of the research on the impact of operational factors on vibroacoustic conditions of transmissions. The factors covered by the analysis included a change in the mating conditions of gear wheels associated with the wear of tooth surfaces, operation of transmissions in subharmonic conditions of the main resonance and the temperature of the lubricating oil. The study demonstrated that it was possible to reduce the vibroacoustic effects generated by gear transmissions by changing the conditions of their operation. Based on the results obtained, it has been found that the operation of gear transmissions in accordance with the sustainable development principles requires technical services to take active measures consisting in the search for optimal operating conditions in terms of the vibroacoustic conditions.

Building coherence and synergy among global health initiatives.

PubMed

Zicker, Fabio; Faid, Miriam; Reeder, John; Aslanyan, Garry

2015-12-09

The fast growth of global health initiatives (GHIs) has raised concerns regarding achievement of coherence and synergy among distinct, complementary and sometimes competing activities. Herein, we propose an approach to compare GHIs with regard to their main purpose and operational aspects, using the Special Programme for Research and Training in Tropical Diseases (TDR/WHO) as a case study. The overall goal is to identify synergies and optimize efforts to provide solutions to reduce the burden of diseases. Twenty-six long-established GHIs were identified from among initiatives previously associated/partnered with TDR/WHO. All GHIs had working streams that would benefit from linking to the capacity building or implementation research focus of TDR. Individual profiles were created using a common template to collect information on relevant parameters. For analytical purposes, GHIs were simultaneously clustered in five and eight groups according to their 'intended outcome' and 'operational framework', respectively. A set of specific questions was defined to assess coherence/alignment against a TDR reference profile by attributing a score, which was subsequently averaged per GHI cluster. GHI alignment scores for intended outcome were plotted against scores for operational framework; based on the analysis of coherence/alignment with TDR functions and operations, a risk level (high, medium or low) of engagement was attributed to each GHI. The process allowed a bi-dimensional ranking of GHIs with regards to how adequately they fit with or match TDR features and perspectives. Overall, more consistence was observed with regard to the GHIs' main goals and expected outcomes than with their operational aspects, reflecting the diversity of GHI business models. Analysis of coherence indicated an increasing common trend for enhancing the engagement of developing country stakeholders, building research capacity and optimization of knowledge management platforms in support of improved access to healthcare. The process used offers a broader approach that could be adapted by other GHIs to build coherence and synergy with peer organizations and helps highlight the potential contribution of each GHI in the new era of sustainable development goals. Emerging opportunities and new trends suggest that engagement between GHIs should be selective and tailored to ensure efficient collaborations.

Resolving Off-Nominal Situations in Schedule-Based Terminal Area Operations: Results from a Human-in-the-Loop Simulation

NASA Technical Reports Server (NTRS)

Mercer, Joey; Callantine, Todd; Martin, Lynne

2012-01-01

A recent human-in-the-loop simulation in the Airspace Operations Laboratory (AOL) at NASA's Ames Research Center investigated the robustness of Controller-Managed Spacing (CMS) operations. CMS refers to AOL-developed controller tools and procedures for enabling arrivals to conduct efficient Optimized Profile Descents with sustained high throughput. The simulation provided a rich data set for examining how a traffic management supervisor and terminal-area controller participants used the CMS tools and coordinated to respond to off-nominal events. This paper proposes quantitative measures for characterizing the participants responses. Case studies of go-around events, replicated during the simulation, provide insights into the strategies employed and the role the CMS tools played in supporting them.

Research on the performance evaluation of agricultural products supply chain integrated operation

NASA Astrophysics Data System (ADS)

Jiang, Jiake; Wang, Xifu; Liu, Yang

2017-04-01

The agricultural product supply chain integrated operation can ensure the quality and efficiency of agricultural products, and achieve the optimal goal of low cost and high service. This paper establishes a performance evaluation index system of agricultural products supply chain integration operation based on the development status of agricultural products and SCOR, BSC and KPI model. And then, we constructing rough set theory and BP neural network comprehensive evaluation model with the aid of Rosetta and MATLAB tools and the case study is about the development of agricultural products integrated supply chain in Jing-Jin-Ji region. And finally, we obtain the corresponding performance results, and give some improvement measures and management recommendations to the managers.

Solving TSP problem with improved genetic algorithm

NASA Astrophysics Data System (ADS)

Fu, Chunhua; Zhang, Lijun; Wang, Xiaojing; Qiao, Liying

2018-05-01

The TSP is a typical NP problem. The optimization of vehicle routing problem (VRP) and city pipeline optimization can use TSP to solve; therefore it is very important to the optimization for solving TSP problem. The genetic algorithm (GA) is one of ideal methods in solving it. The standard genetic algorithm has some limitations. Improving the selection operator of genetic algorithm, and importing elite retention strategy can ensure the select operation of quality, In mutation operation, using the adaptive algorithm selection can improve the quality of search results and variation, after the chromosome evolved one-way evolution reverse operation is added which can make the offspring inherit gene of parental quality improvement opportunities, and improve the ability of searching the optimal solution algorithm.

Formulation and demonstration of a robust mean variance optimization approach for concurrent airline network and aircraft design

NASA Astrophysics Data System (ADS)

Davendralingam, Navindran

Conceptual design of aircraft and the airline network (routes) on which aircraft fly on are inextricably linked to passenger driven demand. Many factors influence passenger demand for various Origin-Destination (O-D) city pairs including demographics, geographic location, seasonality, socio-economic factors and naturally, the operations of directly competing airlines. The expansion of airline operations involves the identificaion of appropriate aircraft to meet projected future demand. The decisions made in incorporating and subsequently allocating these new aircraft to serve air travel demand affects the inherent risk and profit potential as predicted through the airline revenue management systems. Competition between airlines then translates to latent passenger observations of the routes served between OD pairs and ticket pricing---this in effect reflexively drives future states of demand. This thesis addresses the integrated nature of aircraft design, airline operations and passenger demand, in order to maximize future expected profits as new aircraft are brought into service. The goal of this research is to develop an approach that utilizes aircraft design, airline network design and passenger demand as a unified framework to provide better integrated design solutions in order to maximize expexted profits of an airline. This is investigated through two approaches. The first is a static model that poses the concurrent engineering paradigm above as an investment portfolio problem. Modern financial portfolio optimization techniques are used to leverage risk of serving future projected demand using a 'yet to be introduced' aircraft against potentially generated future profits. Robust optimization methodologies are incorporated to mitigate model sensitivity and address estimation risks associated with such optimization techniques. The second extends the portfolio approach to include dynamic effects of an airline's operations. A dynamic programming approach is employed to simulate the reflexive nature of airline supply-demand interactions by modeling the aggregate changes in demand that would result from tactical allocations of aircraft to maximize profit. The best yet-to-be-introduced aircraft maximizes profit by minimizing the long term fleetwide direct operating costs.

International Space Station Medical Project

NASA Technical Reports Server (NTRS)

Starkey, Blythe A.

2008-01-01

The goals and objectives of the ISS Medical Project (ISSMP) are to: 1) Maximize the utilization the ISS and other spaceflight platforms to assess the effects of longduration spaceflight on human systems; 2) Devise and verify strategies to ensure optimal crew performance; 3) Enable development and validation of a suite of integrated physical (e.g., exercise), pharmacologic and/or nutritional countermeasures against deleterious effects of space flight that may impact mission success or crew health. The ISSMP provides planning, integration, and implementation services for Human Research Program research tasks and evaluation activities requiring access to space or related flight resources on the ISS, Shuttle, Soyuz, Progress, or other spaceflight vehicles and platforms. This includes pre- and postflight activities; 2) ISSMP services include operations and sustaining engineering for HRP flight hardware; experiment integration and operation, including individual research tasks and on-orbit validation of next generation on-orbit equipment; medical operations; procedures development and validation; and crew training tools and processes, as well as operation and sustaining engineering for the Telescience Support Center; and 3) The ISSMP integrates the HRP approved flight activity complement and interfaces with external implementing organizations, such as the ISS Payloads Office and International Partners, to accomplish the HRP's objectives. This effort is led by JSC with Baseline Data Collection support from KSC.

Initial Concept for Terminal Area Conflict Detection, Alerting, and Resolution Capability on or Near the Airport Surface

NASA Technical Reports Server (NTRS)

Green, David F.; Otero, Sharon D.; Barker, Glover D.; Jones, Denise R.

2009-01-01

The Next Generation Air Transportation System (NextGen) concept for 2025 envisions the movement of large numbers of people and goods in a safe, efficient, and reliable manner. The NextGen will remove many of the constraints in the current air transportation system, support a wider range of operations, and deliver an overall system capacity up to 3 times that of current operating levels. In order to achieve the NextGen vision, research is necessary in the areas of surface traffic optimization, maximum runway capacity, reduced runway occupancy time, simultaneous single runway operations, and terminal area conflict prevention, among others. The National Aeronautics and Space Administration (NASA) is conducting Collision Avoidance for Airport Traffic (CAAT) research to develop technologies, data, and guidelines to enable Conflict Detection and Resolution (CD&R) in the Airport Terminal Maneuvering Area (ATMA) under current and emerging NextGen operating concepts. In this report, an initial concept for an aircraft-based method for CD&R in the ATMA is presented. This method is based upon previous NASA work in CD&R for runway incursion prevention, the Runway Incursion Prevention System (RIPS). CAAT research is conducted jointly under NASA's Airspace Systems Program, Airportal Project and the Aviation Safety Program, Integrated Intelligent Flight Deck Project.

Energy-efficient approach to minimizing the energy consumption in an extended job-shop scheduling problem

NASA Astrophysics Data System (ADS)

Tang, Dunbing; Dai, Min

2015-09-01

The traditional production planning and scheduling problems consider performance indicators like time, cost and quality as optimization objectives in manufacturing processes. However, environmentally-friendly factors like energy consumption of production have not been completely taken into consideration. Against this background, this paper addresses an approach to modify a given schedule generated by a production planning and scheduling system in a job shop floor, where machine tools can work at different cutting speeds. It can adjust the cutting speeds of the operations while keeping the original assignment and processing sequence of operations of each job fixed in order to obtain energy savings. First, the proposed approach, based on a mixed integer programming mathematical model, changes the total idle time of the given schedule to minimize energy consumption in the job shop floor while accepting the optimal solution of the scheduling objective, makespan. Then, a genetic-simulated annealing algorithm is used to explore the optimal solution due to the fact that the problem is strongly NP-hard. Finally, the effectiveness of the approach is performed smalland large-size instances, respectively. The experimental results show that the approach can save 5%-10% of the average energy consumption while accepting the optimal solution of the makespan in small-size instances. In addition, the average maximum energy saving ratio can reach to 13%. And it can save approximately 1%-4% of the average energy consumption and approximately 2.4% of the average maximum energy while accepting the near-optimal solution of the makespan in large-size instances. The proposed research provides an interesting point to explore an energy-aware schedule optimization for a traditional production planning and scheduling problem.

Autonomous Energy Grids: Preprint

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

Kroposki, Benjamin D; Dall-Anese, Emiliano; Bernstein, Andrey

With much higher levels of distributed energy resources - variable generation, energy storage, and controllable loads just to mention a few - being deployed into power systems, the data deluge from pervasive metering of energy grids, and the shaping of multi-level ancillary-service markets, current frameworks to monitoring, controlling, and optimizing large-scale energy systems are becoming increasingly inadequate. This position paper outlines the concept of 'Autonomous Energy Grids' (AEGs) - systems that are supported by a scalable, reconfigurable, and self-organizing information and control infrastructure, can be extremely secure and resilient (self-healing), and self-optimize themselves in real-time for economic and reliable performancemore » while systematically integrating energy in all forms. AEGs rely on scalable, self-configuring cellular building blocks that ensure that each 'cell' can self-optimize when isolated from a larger grid as well as partaking in the optimal operation of a larger grid when interconnected. To realize this vision, this paper describes the concepts and key research directions in the broad domains of optimization theory, control theory, big-data analytics, and complex system modeling that will be necessary to realize the AEG vision.« less

Optimal helicopter trajectory planning for terrain following flight

NASA Technical Reports Server (NTRS)

Menon, P. K. A.

1990-01-01

Helicopters operating in high threat areas have to fly close to the earth surface to minimize the risk of being detected by the adversaries. Techniques are presented for low altitude helicopter trajectory planning. These methods are based on optimal control theory and appear to be implementable onboard in realtime. Second order necessary conditions are obtained to provide a criterion for finding the optimal trajectory when more than one extremal passes through a given point. A second trajectory planning method incorporating a quadratic performance index is also discussed. Trajectory planning problem is formulated as a differential game. The objective is to synthesize optimal trajectories in the presence of an actively maneuvering adversary. Numerical methods for obtaining solutions to these problems are outlined. As an alternative to numerical method, feedback linearizing transformations are combined with the linear quadratic game results to synthesize explicit nonlinear feedback strategies for helicopter pursuit-evasion. Some of the trajectories generated from this research are evaluated on a six-degree-of-freedom helicopter simulation incorporating an advanced autopilot. The optimal trajectory planning methods presented are also useful for autonomous land vehicle guidance.

Interactive orbital proximity operations planning system instruction and training guide

NASA Technical Reports Server (NTRS)

Grunwald, Arthur J.; Ellis, Stephen R.

1994-01-01

This guide instructs users in the operation of a Proximity Operations Planning System. This system uses an interactive graphical method for planning fuel-efficient rendezvous trajectories in the multi-spacecraft environment of the space station and allows the operator to compose a multi-burn transfer trajectory between orbit initial chaser and target trajectories. The available task time (window) of the mission is predetermined and the maneuver is subject to various operational constraints, such as departure, arrival, spatial, plume impingement, and en route passage constraints. The maneuvers are described in terms of the relative motion experienced in a space station centered coordinate system. Both in-orbital plane as well as out-of-orbital plane maneuvering is considered. A number of visual optimization aids are used for assisting the operator in reaching fuel-efficient solutions. These optimization aids are based on the Primer Vector theory. The visual feedback of trajectory shapes, operational constraints, and optimization functions, provided by user-transparent and continuously active background computations, allows the operator to make fast, iterative design changes that rapidly converge to fuel-efficient solutions. The planning tool is an example of operator-assisted optimization of nonlinear cost functions.

Bi-Level Integrated System Synthesis (BLISS) for Concurrent and Distributed Processing

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, Jaroslaw; Altus, Troy D.; Phillips, Matthew; Sandusky, Robert

2002-01-01

The paper introduces a new version of the Bi-Level Integrated System Synthesis (BLISS) methods intended for optimization of engineering systems conducted by distributed specialty groups working concurrently and using a multiprocessor computing environment. The method decomposes the overall optimization task into subtasks associated with disciplines or subsystems where the local design variables are numerous and a single, system-level optimization whose design variables are relatively few. The subtasks are fully autonomous as to their inner operations and decision making. Their purpose is to eliminate the local design variables and generate a wide spectrum of feasible designs whose behavior is represented by Response Surfaces to be accessed by a system-level optimization. It is shown that, if the problem is convex, the solution of the decomposed problem is the same as that obtained without decomposition. A simplified example of an aircraft design shows the method working as intended. The paper includes a discussion of the method merits and demerits and recommendations for further research.

Optimization for Service Routes of Pallet Service Center Based on the Pallet Pool Mode

PubMed Central

He, Shiwei; Song, Rui

2016-01-01

Service routes optimization (SRO) of pallet service center should meet customers' demand firstly and then, through the reasonable method of lines organization, realize the shortest path of vehicle driving. The routes optimization of pallet service center is similar to the distribution problems of vehicle routing problem (VRP) and Chinese postman problem (CPP), but it has its own characteristics. Based on the relevant research results, the conditions of determining the number of vehicles, the one way of the route, the constraints of loading, and time windows are fully considered, and a chance constrained programming model with stochastic constraints is constructed taking the shortest path of all vehicles for a delivering (recycling) operation as an objective. For the characteristics of the model, a hybrid intelligent algorithm including stochastic simulation, neural network, and immune clonal algorithm is designed to solve the model. Finally, the validity and rationality of the optimization model and algorithm are verified by the case. PMID:27528865

AITSO: A Tool for Spatial Optimization Based on Artificial Immune Systems

PubMed Central

Zhao, Xiang; Liu, Yaolin; Liu, Dianfeng; Ma, Xiaoya

2015-01-01

A great challenge facing geocomputation and spatial analysis is spatial optimization, given that it involves various high-dimensional, nonlinear, and complicated relationships. Many efforts have been made with regard to this specific issue, and the strong ability of artificial immune system algorithms has been proven in previous studies. However, user-friendly professional software is still unavailable, which is a great impediment to the popularity of artificial immune systems. This paper describes a free, universal tool, named AITSO, which is capable of solving various optimization problems. It provides a series of standard application programming interfaces (APIs) which can (1) assist researchers in the development of their own problem-specific application plugins to solve practical problems and (2) allow the implementation of some advanced immune operators into the platform to improve the performance of an algorithm. As an integrated, flexible, and convenient tool, AITSO contributes to knowledge sharing and practical problem solving. It is therefore believed that it will advance the development and popularity of spatial optimization in geocomputation and spatial analysis. PMID:25678911

Using military friendships to optimize postdeployment reintegration for male Operation Iraqi Freedom/Operation Enduring Freedom veterans.

PubMed

Hinojosa, Ramon; Hinojosa, Melanie Sberna

2011-01-01

Social relationships are important to health out comes. The postdeployment family reintegration literature focuses on the role of the civilian family in facilitating the transition from Active Duty military deployment to civilian society. The focus on the civilian family relationship may miss other important personal connections in veterans' lives. One such connection is the relationship many veterans have with former military unit members who served with them when deployed. Drawing on interviews with male Operation Iraqi Freedom/Operation Enduring Freedom veterans conducted from 2008 to 2009, we argue that the members of a military unit, especially during armed conflict, should be considered a resource to help the "family" reintegration process rather than impede it. This research has implications for current reintegration policy and how best to assist veterans transitioning into civilian society.

NextGen Far-Term Concept Exploration for Integrated Gate-to-Gate Trajectory-Based Operations

NASA Technical Reports Server (NTRS)

Johnson, Sally C.; Barmore, Bryan E.

2016-01-01

NASA is currently conducting concept exploration studies toward the definition of a far-term, gate-to-gate concept for Trajectory-Based Operations. This paper presents a basic architectural framework for the far-term concept and discusses some observations about implementation of trajectory-based operations in the National Airspace System. Within the concept, operators and service providers collaboratively negotiate aircraft trajectories, providing agile, optimized, aircraft-specific routing to meet service provider gate-to-gate flow-management constraints and increasing capacity by smoothly and effectively combining flight-deck-based and ground-based metering, merging, and spacing in a mixed-equipage environment. The far-term TBO concept is intended to influence the direction of mid-term TBO research and to inform the definition of stable requirements and standards for TBO communications infrastructure and user equipage.

Improved Weather and Power Forecasts for Energy Operations - the German Research Project EWeLiNE

NASA Astrophysics Data System (ADS)

Lundgren, Kristina; Siefert, Malte; Hagedorn, Renate; Majewski, Detlev

2014-05-01

The German energy system is going through a fundamental change. Based on the energy plans of the German federal government, the share of electrical power production from renewables should increase to 35% by 2020. This means that, in the near future at certain times renewable energies will provide a major part of Germany's power production. Operating a power supply system with a large share of weather-dependent power sources in a secure way requires improved power forecasts. One of the most promising strategies to improve the existing wind power and PV power forecasts is to optimize the underlying weather forecasts and to enhance the collaboration between the meteorology and energy sectors. Deutscher Wetterdienst addresses these challenges in collaboration with Fraunhofer IWES within the research project EWeLiNE. The overarching goal of the project is to improve the wind and PV power forecasts by combining improved power forecast models and optimized weather forecasts. During the project, the numerical weather prediction models COSMO-DE and COSMO-DE-EPS (Ensemble Prediction System) by Deutscher Wetterdienst will be generally optimized towards improved wind power and PV forecasts. For instance, it will be investigated whether the assimilation of new types of data, e.g. power production data, can lead to improved weather forecasts. With regard to the probabilistic forecasts, the focus is on the generation of ensembles and ensemble calibration. One important aspect of the project is to integrate the probabilistic information into decision making processes by developing user-specified products. In this paper we give an overview of the project and present first results.

Optimizing Reservoir Operation to Adapt to the Climate Change

NASA Astrophysics Data System (ADS)

Madadgar, S.; Jung, I.; Moradkhani, H.

2010-12-01

Climate change and upcoming variation in flood timing necessitates the adaptation of current rule curves developed for operation of water reservoirs as to reduce the potential damage from either flood or draught events. This study attempts to optimize the current rule curves of Cougar Dam on McKenzie River in Oregon addressing some possible climate conditions in 21th century. The objective is to minimize the failure of operation to meet either designated demands or flood limit at a downstream checkpoint. A simulation/optimization model including the standard operation policy and a global optimization method, tunes the current rule curve upon 8 GCMs and 2 greenhouse gases emission scenarios. The Precipitation Runoff Modeling System (PRMS) is used as the hydrology model to project the streamflow for the period of 2000-2100 using downscaled precipitation and temperature forcing from 8 GCMs and two emission scenarios. An ensemble of rule curves, each associated with an individual scenario, is obtained by optimizing the reservoir operation. The simulation of reservoir operation, for all the scenarios and the expected value of the ensemble, is conducted and performance assessment using statistical indices including reliability, resilience, vulnerability and sustainability is made.

[Optimize dropping process of Ginkgo biloba dropping pills by using design space approach].

PubMed

Shen, Ji-Chen; Wang, Qing-Qing; Chen, An; Pan, Fang-Lai; Gong, Xing-Chu; Qu, Hai-Bin

2017-07-01

In this paper, a design space approach was applied to optimize the dropping process of Ginkgo biloba dropping pills. Firstly, potential critical process parameters and potential process critical quality attributes were determined through literature research and pre-experiments. Secondly, experiments were carried out according to Box-Behnken design. Then the critical process parameters and critical quality attributes were determined based on the experimental results. Thirdly, second-order polynomial models were used to describe the quantitative relationships between critical process parameters and critical quality attributes. Finally, a probability-based design space was calculated and verified. The verification results showed that efficient production of Ginkgo biloba dropping pills can be guaranteed by operating within the design space parameters. The recommended operation ranges for the critical dropping process parameters of Ginkgo biloba dropping pills were as follows: dropping distance of 5.5-6.7 cm, and dropping speed of 59-60 drops per minute, providing a reference for industrial production of Ginkgo biloba dropping pills. Copyright© by the Chinese Pharmaceutical Association.

Crystallization in lactose refining-a review.

PubMed

Wong, Shin Yee; Hartel, Richard W

2014-03-01

In the dairy industry, crystallization is an important separation process used in the refining of lactose from whey solutions. In the refining operation, lactose crystals are separated from the whey solution through nucleation, growth, and/or aggregation. The rate of crystallization is determined by the combined effect of crystallizer design, processing parameters, and impurities on the kinetics of the process. This review summarizes studies on lactose crystallization, including the mechanism, theory of crystallization, and the impact of various factors affecting the crystallization kinetics. In addition, an overview of the industrial crystallization operation highlights the problems faced by the lactose manufacturer. The approaches that are beneficial to the lactose manufacturer for process optimization or improvement are summarized in this review. Over the years, much knowledge has been acquired through extensive research. However, the industrial crystallization process is still far from optimized. Therefore, future effort should focus on transferring the new knowledge and technology to the dairy industry. © 2014 Institute of Food Technologists®

OPAD-EDIFIS Real-Time Processing

NASA Technical Reports Server (NTRS)

Katsinis, Constantine

1997-01-01

The Optical Plume Anomaly Detection (OPAD) detects engine hardware degradation of flight vehicles through identification and quantification of elemental species found in the plume by analyzing the plume emission spectra in a real-time mode. Real-time performance of OPAD relies on extensive software which must report metal amounts in the plume faster than once every 0.5 sec. OPAD software previously written by NASA scientists performed most necessary functions at speeds which were far below what is needed for real-time operation. The research presented in this report improved the execution speed of the software by optimizing the code without changing the algorithms and converting it into a parallelized form which is executed in a shared-memory multiprocessor system. The resulting code was subjected to extensive timing analysis. The report also provides suggestions for further performance improvement by (1) identifying areas of algorithm optimization, (2) recommending commercially available multiprocessor architectures and operating systems to support real-time execution and (3) presenting an initial study of fault-tolerance requirements.

Optimal Operation and Dispatch of Voltage Regulation Devices Considering High Penetrations of Distributed Photovoltaic Generation

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

Mather, Barry A; Hodge, Brian S; Cho, Gyu-Jung

Voltage regulation devices have been traditionally installed and utilized to support distribution voltages. Installations of distributed energy resources (DERs) in distribution systems are rapidly increasing, and many of these generation resources have variable and uncertain power output. These generators can significantly change the voltage profile for a feeder; therefore, in the distribution system planning stage of the optimal operation and dispatch of voltage regulation devices, possible high penetrations of DERs should be considered. In this paper, we model the IEEE 34-bus test feeder, including all essential equipment. An optimization method is adopted to determine the optimal siting and operation ofmore » the voltage regulation devices in the presence of distributed solar power generation. Finally, we verify the optimal configuration of the entire system through the optimization and simulation results.« less

New Directions for Military Decision Making Research in Combat and Operational Settings

DTIC Science & Technology

1991-12-01

information; their search rules emphasize feasibility more than optimality; decisions depend on the order in which alternatives are presented...12:76-90. Easterbrook, J.A. "The effect of Emotion on Cue Utilization and the Organization of Behaviour." Psychological Review, 1959, 66:183-201...Acquisition and Affective State on Halo, Accuracy, Information Retrival , and Evaluations." Organizational Behavior and Human Decision Processes, 1988, 42:22

An Investigation of Run-Time Operations in a Heterogeneous Desktop Grid Environment: The Texas Tech University Desktop Grid Case Study

ERIC Educational Resources Information Center

Perez, Jerry F.

2013-01-01

The goal of the dissertation study was to evaluate the existing DG scheduling algorithm. The evaluation was developed through previously explored simulated analyses of DGs performed by researchers in the field of DG scheduling optimization and to improve the current RT framework of the DG at TTU. The author analyzed the RT of an actual DG, thereby…

Optimally Scheduling Basic Courses at the Defense Language Institute using Integer Programming

DTIC Science & Technology

2005-09-01

DLI’s manual schedules at best can train 8%, 7% and 64%. 15. NUMBER OF PAGES 59 14. SUBJECT TERMS Operations Research, Linear Programming...class in 2006, 2007, and 2008, whereas DLI’s manual schedules at best can train 8%, 7% and 64%. vi THIS PAGE...ARABIC INSTRUTOR LEVELS .....................................25 FIGURE 2. OCS1 AND OCS2 CHINESE-MANDARIN INSTRUTOR LEVELS ............26 FIGURE 3

Scheduling, revenue management, and fairness in an academic-hospital radiology division.

PubMed

Baum, Richard; Bertsimas, Dimitris; Kallus, Nathan

2014-10-01

Physician staff of academic hospitals today practice in several geographic locations including their main hospital. This is referred to as the extended campus. With extended campuses expanding, the growing complexity of a single division's schedule means that a naive approach to scheduling compromises revenue. Moreover, it may provide an unfair allocation of individual revenue, desirable or burdensome assignments, and the extent to which the preferences of each individual are met. This has adverse consequences on incentivization and employee satisfaction and is simply against business policy. We identify the daily scheduling of physicians in this context as an operational problem that incorporates scheduling, revenue management, and fairness. Noting previous success of operations research and optimization in each of these disciplines, we propose a simple unified optimization formulation of this scheduling problem using mixed-integer optimization. Through a study of implementing the approach at the Division of Angiography and Interventional Radiology at the Brigham and Women's Hospital, which is directed by one of the authors, we exemplify the flexibility of the model to adapt to specific applications, the tractability of solving the model in practical settings, and the significant impact of the approach, most notably in increasing revenue by 8.2% over previous operating revenue while adhering strictly to a codified fairness and objectivity. We found that the investment in implementing such a system is far outweighed by the large potential revenue increase and the other benefits outlined. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Development of a fixed bed gasifier model and optimal operating conditions determination

NASA Astrophysics Data System (ADS)

Dahmani, Manel; Périlhon, Christelle; Marvillet, Christophe; Hajjaji, Noureddine; Houas, Ammar; Khila, Zouhour

2017-02-01

The main objective of this study was to develop a fixed bed gasifier model of palm waste and to identify the optimal operating conditions to produce electricity from synthesis gas. First, the gasifier was simulated using Aspen PlusTM software. Gasification is a thermo-chemical process that has long been used, but it remains a perfectible technology. It means incomplete combustion of biomass solid fuel into synthesis gas through partial oxidation. The operating parameters (temperature and equivalence ratio (ER)) were thereafter varied to investigate their effect on the synthesis gas composition and to provide guidance for future research and development efforts in process design. The equivalence ratio is defined as the ratio of the amount of air actually supplied to the gasifier and the stoichiometric amount of air. Increasing ER decreases the production of CO and H2 and increases the production of CO2 and H2O while an increase in temperature increases the fraction of CO and H2. The results show that the optimum temperature to have a syngas able to be effectively used for power generation is 900°C and the optimum equivalence ratio is 0.1.

[Removal of toluene from waste gas by honeycomb adsorption rotor with modified 13X molecular sieves].

PubMed

Wang, Jia-De; Zheng, Liang-Wei; Zhu, Run-Ye; Yu, Yun-Feng

2013-12-01

The removal of toluene from waste gas by Honeycomb Adsorption Rotor with modified 13X molecular sieves was systematically investigated. The effects of the rotor operating parameters and the feed gas parameters on the adsorption efficiency were clarified. The experimental results indicated that the honeycomb adsorption rotor had a good humidity resistance. The removal efficiency of honeycomb adsorption rotor achieved the maximal value with optimal rotor speed and optimal generation air temperature. Moreover, for an appropriate flow rate ratio the removal efficiency and energy consumption should be taken into account. When the recommended operating parameters were regeneration air temperature of 180 degrees C, rotor speed of 2.8-5 r x h(-1), flow rate ratio of 8-12, the removal efficiency kept over 90% for the toluene gas with concentration of 100 mg x m(-3) and inlet velocity of 2 m x s(-1). The research provided design experience and operating parameters for industrial application of honeycomb adsorption rotor. It showed that lower empty bed velocity, faster rotor speed and higher temperature were necessary to purify organic waste gases of higher concentrations.

Intel Many Integrated Core (MIC) architecture optimization strategies for a memory-bound Weather Research and Forecasting (WRF) Goddard microphysics scheme

NASA Astrophysics Data System (ADS)

Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.

2014-10-01

The Goddard cloud microphysics scheme is a sophisticated cloud microphysics scheme in the Weather Research and Forecasting (WRF) model. The WRF is a widely used weather prediction system in the world. It development is a done in collaborative around the globe. The Goddard microphysics scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. Compared to the earlier microphysics schemes, the Goddard scheme incorporates a large number of improvements. Thus, we have optimized the code of this important part of WRF. In this paper, we present our results of optimizing the Goddard microphysics scheme on Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a high performance on-die bidirectional interconnect. The Intel MIC is capable of executing a full operating system and entire programs rather than just kernels as the GPU do. The MIC coprocessor supports all important Intel development tools. Thus, the development environment is familiar one to a vast number of CPU developers. Although, getting a maximum performance out of MICs will require using some novel optimization techniques. Those optimization techniques are discusses in this paper. The results show that the optimizations improved performance of the original code on Xeon Phi 7120P by a factor of 4.7x. Furthermore, the same optimizations improved performance on a dual socket Intel Xeon E5-2670 system by a factor of 2.8x compared to the original code.

Maintenance service contract model for heavy equipment in mining industry using principal agent theory

NASA Astrophysics Data System (ADS)

Pakpahan, Eka K. A.; Iskandar, Bermawi P.

2015-12-01

Mining industry is characterized by a high operational revenue, and hence high availability of heavy equipment used in mining industry is a critical factor to ensure the revenue target. To maintain high avaliability of the heavy equipment, the equipment's owner hires an agent to perform maintenance action. Contract is then used to control the relationship between the two parties involved. The traditional contracts such as fixed price, cost plus or penalty based contract studied is unable to push agent's performance to exceed target, and this in turn would lead to a sub-optimal result (revenue). This research deals with designing maintenance contract compensation schemes. The scheme should induce agent to select the highest possible maintenance effort level, thereby pushing agent's performance and achieve maximum utility for both parties involved. Principal agent theory is used as a modeling approach due to its ability to simultaneously modeled owner and agent decision making process. Compensation schemes considered in this research includes fixed price, cost sharing and revenue sharing. The optimal decision is obtained using a numerical method. The results show that if both parties are risk neutral, then there are infinite combination of fixed price, cost sharing and revenue sharing produced the same optimal solution. The combination of fixed price and cost sharing contract results in the optimal solution when the agent is risk averse, while the optimal combination of fixed price and revenue sharing contract is obtained when agent is risk averse. When both parties are risk averse, the optimal compensation scheme is a combination of fixed price, cost sharing and revenue sharing.

Towards Robust Designs Via Multiple-Objective Optimization Methods

NASA Technical Reports Server (NTRS)

Man Mohan, Rai

2006-01-01

Fabricating and operating complex systems involves dealing with uncertainty in the relevant variables. In the case of aircraft, flow conditions are subject to change during operation. Efficiency and engine noise may be different from the expected values because of manufacturing tolerances and normal wear and tear. Engine components may have a shorter life than expected because of manufacturing tolerances. In spite of the important effect of operating- and manufacturing-uncertainty on the performance and expected life of the component or system, traditional aerodynamic shape optimization has focused on obtaining the best design given a set of deterministic flow conditions. Clearly it is important to both maintain near-optimal performance levels at off-design operating conditions, and, ensure that performance does not degrade appreciably when the component shape differs from the optimal shape due to manufacturing tolerances and normal wear and tear. These requirements naturally lead to the idea of robust optimal design wherein the concept of robustness to various perturbations is built into the design optimization procedure. The basic ideas involved in robust optimal design will be included in this lecture. The imposition of the additional requirement of robustness results in a multiple-objective optimization problem requiring appropriate solution procedures. Typically the costs associated with multiple-objective optimization are substantial. Therefore efficient multiple-objective optimization procedures are crucial to the rapid deployment of the principles of robust design in industry. Hence the companion set of lecture notes (Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks ) deals with methodology for solving multiple-objective Optimization problems efficiently, reliably and with little user intervention. Applications of the methodologies presented in the companion lecture to robust design will be included here. The evolutionary method (DE) is first used to solve a relatively difficult problem in extended surface heat transfer wherein optimal fin geometries are obtained for different safe operating base temperatures. The objective of maximizing the safe operating base temperature range is in direct conflict with the objective of maximizing fin heat transfer. This problem is a good example of achieving robustness in the context of changing operating conditions. The evolutionary method is then used to design a turbine airfoil; the two objectives being reduced sensitivity of the pressure distribution to small changes in the airfoil shape and the maximization of the trailing edge wedge angle with the consequent increase in airfoil thickness and strength. This is a relevant example of achieving robustness to manufacturing tolerances and wear and tear in the presence of other objectives.

Methods and devices for optimizing the operation of a semiconductor optical modulator

DOEpatents

Zortman, William A.

2015-07-14

A semiconductor-based optical modulator includes a control loop to control and optimize the modulator's operation for relatively high data rates (above 1 GHz) and/or relatively high voltage levels. Both the amplitude of the modulator's driving voltage and the bias of the driving voltage may be adjusted using the control loop. Such adjustments help to optimize the operation of the modulator by reducing the number of errors present in a modulated data stream.

A Bayesian model averaging method for the derivation of reservoir operating rules

NASA Astrophysics Data System (ADS)

Zhang, Jingwen; Liu, Pan; Wang, Hao; Lei, Xiaohui; Zhou, Yanlai

2015-09-01

Because the intrinsic dynamics among optimal decision making, inflow processes and reservoir characteristics are complex, functional forms of reservoir operating rules are always determined subjectively. As a result, the uncertainty of selecting form and/or model involved in reservoir operating rules must be analyzed and evaluated. In this study, we analyze the uncertainty of reservoir operating rules using the Bayesian model averaging (BMA) model. Three popular operating rules, namely piecewise linear regression, surface fitting and a least-squares support vector machine, are established based on the optimal deterministic reservoir operation. These individual models provide three-member decisions for the BMA combination, enabling the 90% release interval to be estimated by the Markov Chain Monte Carlo simulation. A case study of China's the Baise reservoir shows that: (1) the optimal deterministic reservoir operation, superior to any reservoir operating rules, is used as the samples to derive the rules; (2) the least-squares support vector machine model is more effective than both piecewise linear regression and surface fitting; (3) BMA outperforms any individual model of operating rules based on the optimal trajectories. It is revealed that the proposed model can reduce the uncertainty of operating rules, which is of great potential benefit in evaluating the confidence interval of decisions.

Geometric Distribution-Based Readers Scheduling Optimization Algorithm Using Artificial Immune System.

PubMed

Duan, Litian; Wang, Zizhong John; Duan, Fu

2016-11-16

In the multiple-reader environment (MRE) of radio frequency identification (RFID) system, multiple readers are often scheduled to interrogate the randomized tags via operating at different time slots or frequency channels to decrease the signal interferences. Based on this, a Geometric Distribution-based Multiple-reader Scheduling Optimization Algorithm using Artificial Immune System (GD-MRSOA-AIS) is proposed to fairly and optimally schedule the readers operating from the viewpoint of resource allocations. GD-MRSOA-AIS is composed of two parts, where a geometric distribution function combined with the fairness consideration is first introduced to generate the feasible scheduling schemes for reader operation. After that, artificial immune system (including immune clone, immune mutation and immune suppression) quickly optimize these feasible ones as the optimal scheduling scheme to ensure that readers are fairly operating with larger effective interrogation range and lower interferences. Compared with the state-of-the-art algorithm, the simulation results indicate that GD-MRSOA-AIS could efficiently schedules the multiple readers operating with a fairer resource allocation scheme, performing in larger effective interrogation range.

Geometric Distribution-Based Readers Scheduling Optimization Algorithm Using Artificial Immune System

PubMed Central

Duan, Litian; Wang, Zizhong John; Duan, Fu

2016-01-01

In the multiple-reader environment (MRE) of radio frequency identification (RFID) system, multiple readers are often scheduled to interrogate the randomized tags via operating at different time slots or frequency channels to decrease the signal interferences. Based on this, a Geometric Distribution-based Multiple-reader Scheduling Optimization Algorithm using Artificial Immune System (GD-MRSOA-AIS) is proposed to fairly and optimally schedule the readers operating from the viewpoint of resource allocations. GD-MRSOA-AIS is composed of two parts, where a geometric distribution function combined with the fairness consideration is first introduced to generate the feasible scheduling schemes for reader operation. After that, artificial immune system (including immune clone, immune mutation and immune suppression) quickly optimize these feasible ones as the optimal scheduling scheme to ensure that readers are fairly operating with larger effective interrogation range and lower interferences. Compared with the state-of-the-art algorithm, the simulation results indicate that GD-MRSOA-AIS could efficiently schedules the multiple readers operating with a fairer resource allocation scheme, performing in larger effective interrogation range. PMID:27854342

An Analytical Method for Deriving Reservoir Operation Curves to Maximize Social Benefits from Multiple Uses of Water in the Willamette River Basin

NASA Astrophysics Data System (ADS)

Moore, K. M.; Jaeger, W. K.; Jones, J. A.

2013-12-01

A central characteristic of large river basins in the western US is the spatial and temporal disjunction between the supply of and demand for water. Water sources are typically concentrated in forested mountain regions distant from municipal and agricultural water users, while precipitation is super-abundant in winter and deficient in summer. To cope with these disparities, systems of reservoirs have been constructed throughout the West. These reservoir systems are managed to serve two main competing purposes: to control flooding during winter and spring, and to store spring runoff and deliver it to populated, agricultural valleys during the summer. The reservoirs also provide additional benefits, including recreation, hydropower and instream flows for stream ecology. Since the storage capacity of the reservoirs cannot be used for both flood control and storage at the same time, these uses are traded-off during spring, as the most important, or dominant use of the reservoir, shifts from buffering floods to storing water for summer use. This tradeoff is expressed in the operations rule curve, which specifies the maximum level to which a reservoir can be filled throughout the year, apart from real-time flood operations. These rule curves were often established at the time a reservoir was built. However, climate change and human impacts may be altering the timing and amplitude of flood events and water scarcity is expected to intensify with anticipated changes in climate, land cover and population. These changes imply that reservoir management using current rule curves may not match future societal values for the diverse uses of water from reservoirs. Despite a broad literature on mathematical optimization for reservoir operation, these methods are not often used because they 1) simplify the hydrologic system, raising doubts about the real-world applicability of the solutions, 2) exhibit perfect foresight and assume stationarity, whereas reservoir operators face uncertainty and risk daily, and 3) require complex computer programming. The proposed research addresses these critiques by pursuing a novel approach - the development of an analytical method to demonstrate how reservoir management could adapt to anticipated changes in water supply and demand, which incorporates some of the complexity of the hydrologic system, includes stochasticity, and can be readily implemented. Employing a normative economic framework of social welfare maximization, the research will 1) estimate the social benefits associated with reservoir uses, 2) analytically derive conditions for maximizing the benefits of reservoir operation, and 3) estimate the resulting optimal operating rules under future trajectories of climate, land cover, and population. The findings of this analysis will be used to address the following research questions: 1) How do the derived optimal operating rules compare to the existing rule curves? 2) How does the shape of the derived rule curves change under different scenarios of global change? 3) What is the change in net social benefits resulting from the use of these derived rule curves as compared to existing rule curves? 4) To the extent possible, what are the distributional and social justice implications of the derived changes in the rule curves?

CFD-Based Design Optimization Tool Developed for Subsonic Inlet

NASA Technical Reports Server (NTRS)

1995-01-01

The traditional approach to the design of engine inlets for commercial transport aircraft is a tedious process that ends with a less-than-optimum design. With the advent of high-speed computers and the availability of more accurate and reliable computational fluid dynamics (CFD) solvers, numerical optimization processes can effectively be used to design an aerodynamic inlet lip that enhances engine performance. The designers' experience at Boeing Corporation showed that for a peak Mach number on the inlet surface beyond some upper limit, the performance of the engine degrades excessively. Thus, our objective was to optimize efficiency (minimize the peak Mach number) at maximum cruise without compromising performance at other operating conditions. Using a CFD code NPARC, the NASA Lewis Research Center, in collaboration with Boeing, developed an integrated procedure at Lewis to find the optimum shape of a subsonic inlet lip and a numerical optimization code, ADS. We used a GRAPE-based three-dimensional grid generator to help automate the optimization procedure. The inlet lip shape at the crown and the keel was described as a superellipse, and the superellipse exponents and radii ratios were considered as design variables. Three operating conditions: cruise, takeoff, and rolling takeoff, were considered in this study. Three-dimensional Euler computations were carried out to obtain the flow field. At the initial design, the peak Mach numbers for maximum cruise, takeoff, and rolling takeoff conditions were 0.88, 1.772, and 1.61, respectively. The acceptable upper limits on the takeoff and rolling takeoff Mach numbers were 1.55 and 1.45. Since the initial design provided by Boeing was found to be optimum with respect to the maximum cruise condition, the sum of the peak Mach numbers at takeoff and rolling takeoff were minimized in the current study while the maximum cruise Mach number was constrained to be close to that at the existing design. With this objective, the optimum design satisfied the upper limits at takeoff and rolling takeoff while retaining the desirable cruise performance. Further studies are being conducted to include static and cross-wind operating conditions in the design optimization procedure. This work was carried out in collaboration with Dr. E.S. Reddy of NYMA, Inc.

Life cycle optimization model for integrated cogeneration and energy systems applications in buildings

NASA Astrophysics Data System (ADS)

Osman, Ayat E.

Energy use in commercial buildings constitutes a major proportion of the energy consumption and anthropogenic emissions in the USA. Cogeneration systems offer an opportunity to meet a building's electrical and thermal demands from a single energy source. To answer the question of what is the most beneficial and cost effective energy source(s) that can be used to meet the energy demands of the building, optimizations techniques have been implemented in some studies to find the optimum energy system based on reducing cost and maximizing revenues. Due to the significant environmental impacts that can result from meeting the energy demands in buildings, building design should incorporate environmental criteria in the decision making criteria. The objective of this research is to develop a framework and model to optimize a building's operation by integrating congregation systems and utility systems in order to meet the electrical, heating, and cooling demand by considering the potential life cycle environmental impact that might result from meeting those demands as well as the economical implications. Two LCA Optimization models have been developed within a framework that uses hourly building energy data, life cycle assessment (LCA), and mixed-integer linear programming (MILP). The objective functions that are used in the formulation of the problems include: (1) Minimizing life cycle primary energy consumption, (2) Minimizing global warming potential, (3) Minimizing tropospheric ozone precursor potential, (4) Minimizing acidification potential, (5) Minimizing NOx, SO 2 and CO2, and (6) Minimizing life cycle costs, considering a study period of ten years and the lifetime of equipment. The two LCA optimization models can be used for: (a) long term planning and operational analysis in buildings by analyzing the hourly energy use of a building during a day and (b) design and quick analysis of building operation based on periodic analysis of energy use of a building in a year. A Pareto-optimal frontier is also derived, which defines the minimum cost required to achieve any level of environmental emission or primary energy usage value or inversely the minimum environmental indicator and primary energy usage value that can be achieved and the cost required to achieve that value.

Evidence-Based Recommendations for Optimizing Light in Day-to-Day Spaceflight Operations

NASA Technical Reports Server (NTRS)

Whitmire, Alexandra; Leveton, Lauren; Barger, Laura; Clark, Toni; Bollweg, Laura; Ohnesorge, Kristine; Brainard, George

2015-01-01

NASA Behavioral Health and Performance Element (BHP) personnel have previously reported on efforts to transition evidence-based recommendations for a flexible lighting system on the International Space Station (ISS). Based on these recommendations, beginning in 2016 the ISS will replace the current fluorescent-based lights with an LED-based system to optimize visual performance, facilitate circadian alignment, promote sleep, and hasten schedule shifting. Additional efforts related to lighting countermeasures in spaceflight operations have also been underway. As an example, a recent BHP research study led by investigators at Harvard Medical School and Brigham and Women's Hospital, evaluated the acceptability, feasibility, and effectiveness of blue-enriched light exposure during exercise breaks for flight controllers working the overnight shift in the Mission Control Center (MCC) at NASA Johnson Space Center. This effort, along with published laboratory studies that have demonstrated the effectiveness of appropriately timed light for promoting alertness, served as an impetus for new light options, and educational protocols for flight controllers. In addition, a separate set of guidelines related to the light emitted from electronic devices, were provided to the Astronaut Office this past year. These guidelines were based on an assessment led by NASA's Lighting Environment Test Facility that included measuring the spectral power distribution, irradiance, and radiance of light emitted from ISS-grade laptops and I-Pads, as well as Android devices. Evaluations were conducted with and without the use of off-the-shelf screen filters as well as a software application that touts minimizing the short-wave length of the visible light spectrum. This presentation will focus on the transition for operations process related to lighting countermeasures in the MCC, as well as the evidence to support recommendations for optimal use of laptops, I-Pads, and Android devices during all phases of spaceflight operations.

25 Years of Atmospheric Science with the Balloon-borne Limb Sounder MIPAS-B

NASA Astrophysics Data System (ADS)

Oelhaf, H.; Friedl-Vallon, F.; Wetzel, G.; Ebersoldt, A.; Hoepfner, M.; Kleinert, A.; Maucher, G.; Maurer, K.; Nordmeyer, H.; Piesch, C.; Ruhnke, R.; Sartorius, C.; Sinnhuber, B. M.; Orphal, J.; Fischer, H.

2017-12-01

MIPAS-B (Michelson Interferometer for Passive Atmospheric Sounding - Balloon) is a balloon-borne limb-emission sounder for atmospheric research. The heart of the instrument is a Fourier spectrometer that covers the mid-infrared spectral range (4 to 14 µm) operating at a temperature of approximately 215 K. Essential for this application is the sophisticated line of sight stabilization system, which is based on an inertial navigation system and supplemented with a star camera reference system. The major scientific benefit of the instrument is the simultaneous detection of complete trace gas families in the stratosphere, without restrictions concerning time of the day and viewing directions. MIPAS-B is an in-house development that was started in the mid-eighties. It initially served as proof of concept for the proposed space borne MIPAS instrument that was later realized and operated on the ESA satellite ENVISAT between 2002 and 2012. But actually it soon became obvious that operation from stratospheric balloons offered a number of benefits to address dedicated scientific questions in an optimal way. MIPAS-B was operated in two versions during 24 flights at tropical, mid-latitudinal and arctic latitudes between 1989 and 2014 covering the `golden era' of ozone loss research and the full operational period of ENVISAT. This paper describes briefly specifications, design considerations, technological upgrades and the characterization of the instrument. Evolving skills with respect to its remote operation from ground and to data analysis in the course of the 25 years are outlined. Scientific applications in the field of atmospheric research, spectroscopy and satellite validation are highlighted with a focus on recent research concerning bromine nitrate and age of air.

Application of Multi-Objective Human Learning Optimization Method to Solve AC/DC Multi-Objective Optimal Power Flow Problem

NASA Astrophysics Data System (ADS)

Cao, Jia; Yan, Zheng; He, Guangyu

2016-06-01

This paper introduces an efficient algorithm, multi-objective human learning optimization method (MOHLO), to solve AC/DC multi-objective optimal power flow problem (MOPF). Firstly, the model of AC/DC MOPF including wind farms is constructed, where includes three objective functions, operating cost, power loss, and pollutant emission. Combining the non-dominated sorting technique and the crowding distance index, the MOHLO method can be derived, which involves individual learning operator, social learning operator, random exploration learning operator and adaptive strategies. Both the proposed MOHLO method and non-dominated sorting genetic algorithm II (NSGAII) are tested on an improved IEEE 30-bus AC/DC hybrid system. Simulation results show that MOHLO method has excellent search efficiency and the powerful ability of searching optimal. Above all, MOHLO method can obtain more complete pareto front than that by NSGAII method. However, how to choose the optimal solution from pareto front depends mainly on the decision makers who stand from the economic point of view or from the energy saving and emission reduction point of view.

Optimal Operation System of the Integrated District Heating System with Multiple Regional Branches

NASA Astrophysics Data System (ADS)

Kim, Ui Sik; Park, Tae Chang; Kim, Lae-Hyun; Yeo, Yeong Koo

This paper presents an optimal production and distribution management for structural and operational optimization of the integrated district heating system (DHS) with multiple regional branches. A DHS consists of energy suppliers and consumers, district heating pipelines network and heat storage facilities in the covered region. In the optimal management system, production of heat and electric power, regional heat demand, electric power bidding and sales, transport and storage of heat at each regional DHS are taken into account. The optimal management system is formulated as a mixed integer linear programming (MILP) where the objectives is to minimize the overall cost of the integrated DHS while satisfying the operation constraints of heat units and networks as well as fulfilling heating demands from consumers. Piecewise linear formulation of the production cost function and stairwise formulation of the start-up cost function are used to compute nonlinear cost function approximately. Evaluation of the total overall cost is based on weekly operations at each district heat branches. Numerical simulations show the increase of energy efficiency due to the introduction of the present optimal management system.

Combustion and fires in low gravity

NASA Technical Reports Server (NTRS)

Friedman, Robert

1994-01-01

Fire safety always receives priority attention in NASA mission designs and operations, with emphasis on fire prevention and material acceptance standards. Recently, interest in spacecraft fire-safety research and development has increased because improved understanding of the significant differences between low-gravity and normal-gravity combustion suggests that present fire-safety techniques may be inadequate or, at best, non-optimal; and the complex and permanent orbital operations in Space Station Freedom demand a higher level of safety standards and practices. This presentation outlines current practices and problems in fire prevention and detection for spacecraft, specifically the Space Station Freedom's fire protection. Also addressed are current practices and problems in fire extinguishment for spacecraft.

Solar stills for agricultural purposes

NASA Technical Reports Server (NTRS)

Selcuk, M. K.; Tran, V. V.

1975-01-01

Basic concepts of using desalinated water for agricultural purposes are outlined. A mathematical model describing heat and mass transfer in a system combining a solar still with a greenhouse, its solution, and test results of a small-scale unit built at the Middle East Technical University, Ankara, Turkey, are discussed. The unit was employed to demonstrate the technical feasibility of the system. Further development and modifications are necessary for larger-scale operations. The basis of an optimization study which is underway at the Brace Research Institute of McGill University in Montreal, Canada, aimed at finding the best combination of design and operation parameters is also presented.

ITER-FEAT operation

NASA Astrophysics Data System (ADS)

Shimomura, Y.; Aymar, R.; Chuyanov, V. A.; Huguet, M.; Matsumoto, H.; Mizoguchi, T.; Murakami, Y.; Polevoi, A. R.; Shimada, M.; ITER Joint Central Team; ITER Home Teams

2001-03-01

ITER is planned to be the first fusion experimental reactor in the world operating for research in physics and engineering. The first ten years of operation will be devoted primarily to physics issues at low neutron fluence and the following ten years of operation to engineering testing at higher fluence. ITER can accommodate various plasma configurations and plasma operation modes, such as inductive high Q modes, long pulse hybrid modes and non-inductive steady state modes, with large ranges of plasma current, density, beta and fusion power, and with various heating and current drive methods. This flexibility will provide an advantage for coping with uncertainties in the physics database, in studying burning plasmas, in introducing advanced features and in optimizing the plasma performance for the different programme objectives. Remote sites will be able to participate in the ITER experiment. This concept will provide an advantage not only in operating ITER for 24 hours a day but also in involving the worldwide fusion community and in promoting scientific competition among the ITER Parties.

The poststall nonlinear dynamics and control of an F-18: A preliminary investigation

NASA Technical Reports Server (NTRS)

Patten, William N.

1988-01-01

The successful high angle of attack (HAOA) operation of fighter aircraft will necessarily require the introduction of a new onboard control methodology that address the nonlinearity of the system when flown at the stall/poststall limits of the craft's flight envelope. As a precursor to this task, a researcher endeavored to familarize himself with the dynamics of one specific aircraft, the F-18, when it is flown at HAOA. This was accomplished by conducting a number of real time flight sorties using the NASA-Langley Research Center's F-18 simulator, which was operated with a pilot in the loop. In addition to developing a first hand familarity with the aircraft's dynamic characteristic at HAOA, work was also performed to identify the input/output operational footprint of the F-18's control surfaces. This investigator proposes to employ the nonlinear models of the plant identified this summer in a subsequent research effort that will make it possible to fly the F-18 effectively at poststall angles of attack. The controller design used there will rely on a new technique proposed by this investigator that provides for the automatic generation of online optimal control solutions for nonlinear dynamic systems.

Design and Operation of Cryogenic Distillation Research Column for Ultra-Low Background Experiments

NASA Astrophysics Data System (ADS)

Chiller, Christopher; Alanson Chiller, Angela; Jasinski, Benjamin; Snyder, Nathan; Mei, Dongming

2013-04-01

Motivated by isotopically enriched germanium (76Ge and 73Ge) for monocrystalline crystal growth for neutrinoless double-beta decay and dark matter experiments, a cryogenic distillation research column was developed. Without market availability of distillation columns in the temperature range of interest with capabilities necessary for our purposes, we designed, fabricated, tested, refined and operated a two-meter research column for purifying and separating gases in the temperature range from 100-200K. Due to interest in defining stratification, purity and throughput optimization, capillary lines were integrated at four equidistant points along the length of the column such that real-time residual gas analysis could guide the investigation. Interior gas column temperatures were monitored and controlled within 0.1oK accuracy at the top and bottom. Pressures were monitored at the top of the column to four significant figures. Subsequent impurities were measured at partial pressures below 2E-8torr. We report the performance of the column in this paper.

A survey on the coordination of connected and automated vehicles at intersections and merging at highway on-ramps

DOE PAGES

Rios-Torres, Jackeline; Malikopoulos, Andreas A.

2016-09-07

Connected and automated vehicles (CAVs) have the potential to improve safety by reducing and mitigating traffic accidents. They can also provide opportunities to reduce transportation energy consumption and emissions by improving traffic flow. Vehicle communication with traffic structures and traffic lights can allow individual vehicles to optimize their operation and account for unpredictable changes. This paper summarizes the developments and the research trends in coordination with the CAVs that have been reported in the literature to date. In conclusion, remaining challenges and potential future research directions are also discussed.

Aircraft Electric Propulsion Systems Applied Research at NASA

NASA Technical Reports Server (NTRS)

Clarke, Sean

2015-01-01

Researchers at NASA are investigating the potential for electric propulsion systems to revolutionize the design of aircraft from the small-scale general aviation sector to commuter and transport-class vehicles. Electric propulsion provides new degrees of design freedom that may enable opportunities for tightly coupled design and optimization of the propulsion system with the aircraft structure and control systems. This could lead to extraordinary reductions in ownership and operating costs, greenhouse gas emissions, and noise annoyance levels. We are building testbeds, high-fidelity aircraft simulations, and the first highly distributed electric inhabited flight test vehicle to begin to explore these opportunities.

2D/3D Synthetic Vision Navigation Display

NASA Technical Reports Server (NTRS)

Prinzel, Lawrence J., III; Kramer, Lynda J.; Arthur, J. J., III; Bailey, Randall E.; Sweeters, jason L.

2008-01-01

Flight-deck display software was designed and developed at NASA Langley Research Center to provide two-dimensional (2D) and three-dimensional (3D) terrain, obstacle, and flight-path perspectives on a single navigation display. The objective was to optimize the presentation of synthetic vision (SV) system technology that permits pilots to view multiple perspectives of flight-deck display symbology and 3D terrain information. Research was conducted to evaluate the efficacy of the concept. The concept has numerous unique implementation features that would permit enhanced operational concepts and efficiencies in both current and future aircraft.

Research on plasma-puff initiation of high Coulomb transfer switches

NASA Technical Reports Server (NTRS)

Venable, Demetrius D.; Han, Kwang S.

1993-01-01

The plasma-puff triggering mechanism based on hypocycloidal pinch geometry was investigated to determine the optimal operating conditions for an azimuthally uniform surface flashover which initiates plasma-puff under wide ranges of fill gas pressures of Ar, He and N2. Research is presented and resulting conference papers are attached. These papers include 'Characteristics of Plasma-Puff Trigger for an Inverse-Pinch Plasma Switch'; 'Ultra-High-Power Plasma Switch INPUTS for Pulse Power Systems'; 'Characteristics of Switching Plasma in an Inverse-Pinch Switch'; 'Comparative Study of INPIStron and Spark Gap'; and 'INPIStron Switched Pulsed Power for Dense Plasma Pinches.'

Laser beam machining of polycrystalline diamond for cutting tool manufacturing

NASA Astrophysics Data System (ADS)

Wyszyński, Dominik; Ostrowski, Robert; Zwolak, Marek; Bryk, Witold

2017-10-01

The paper concerns application of DPSS Nd: YAG 532nm pulse laser source for machining of polycrystalline WC based diamond inserts (PCD). The goal of the research was to determine optimal laser cutting parameters for cutting tool shaping. Basic criteria to reach the goal was cutting edge quality (minimalization of finishing operations), material removal rate (time and cost efficiency), choice of laser beam characteristics (polarization, power, focused beam diameter). The research was planned and realised and analysed according to design of experiment rules (DOE). The analysis of the cutting edge was prepared with use of Alicona Infinite Focus measurement system.

Tunable wavefront coded imaging system based on detachable phase mask: Mathematical analysis, optimization and underlying applications

NASA Astrophysics Data System (ADS)

Zhao, Hui; Wei, Jingxuan

2014-09-01

The key to the concept of tunable wavefront coding lies in detachable phase masks. Ojeda-Castaneda et al. (Progress in Electronics Research Symposium Proceedings, Cambridge, USA, July 5-8, 2010) described a typical design in which two components with cosinusoidal phase variation operate together to make defocus sensitivity tunable. The present study proposes an improved design and makes three contributions: (1) A mathematical derivation based on the stationary phase method explains why the detachable phase mask of Ojeda-Castaneda et al. tunes the defocus sensitivity. (2) The mathematical derivations show that the effective bandwidth wavefront coded imaging system is also tunable by making each component of the detachable phase mask move asymmetrically. An improved Fisher information-based optimization procedure was also designed to ascertain the optimal mask parameters corresponding to specific bandwidth. (3) Possible applications of the tunable bandwidth are demonstrated by simulated imaging.

Parameter optimization of electrochemical machining process using black hole algorithm

NASA Astrophysics Data System (ADS)

Singh, Dinesh; Shukla, Rajkamal

2017-12-01

Advanced machining processes are significant as higher accuracy in machined component is required in the manufacturing industries. Parameter optimization of machining processes gives optimum control to achieve the desired goals. In this paper, electrochemical machining (ECM) process is considered to evaluate the performance of the considered process using black hole algorithm (BHA). BHA considers the fundamental idea of a black hole theory and it has less operating parameters to tune. The two performance parameters, material removal rate (MRR) and overcut (OC) are considered separately to get optimum machining parameter settings using BHA. The variations of process parameters with respect to the performance parameters are reported for better and effective understanding of the considered process using single objective at a time. The results obtained using BHA are found better while compared with results of other metaheuristic algorithms, such as, genetic algorithm (GA), artificial bee colony (ABC) and bio-geography based optimization (BBO) attempted by previous researchers.

A quantile-based scenario analysis approach to biomass supply chain optimization under uncertainty

DOE PAGES

Zamar, David S.; Gopaluni, Bhushan; Sokhansanj, Shahab; ...

2016-11-21

Supply chain optimization for biomass-based power plants is an important research area due to greater emphasis on renewable power energy sources. Biomass supply chain design and operational planning models are often formulated and studied using deterministic mathematical models. While these models are beneficial for making decisions, their applicability to real world problems may be limited because they do not capture all the complexities in the supply chain, including uncertainties in the parameters. This study develops a statistically robust quantile-based approach for stochastic optimization under uncertainty, which builds upon scenario analysis. We apply and evaluate the performance of our approach tomore » address the problem of analyzing competing biomass supply chains subject to stochastic demand and supply. Finally, the proposed approach was found to outperform alternative methods in terms of computational efficiency and ability to meet the stochastic problem requirements.« less

A quantile-based scenario analysis approach to biomass supply chain optimization under uncertainty

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

Zamar, David S.; Gopaluni, Bhushan; Sokhansanj, Shahab

Supply chain optimization for biomass-based power plants is an important research area due to greater emphasis on renewable power energy sources. Biomass supply chain design and operational planning models are often formulated and studied using deterministic mathematical models. While these models are beneficial for making decisions, their applicability to real world problems may be limited because they do not capture all the complexities in the supply chain, including uncertainties in the parameters. This study develops a statistically robust quantile-based approach for stochastic optimization under uncertainty, which builds upon scenario analysis. We apply and evaluate the performance of our approach tomore » address the problem of analyzing competing biomass supply chains subject to stochastic demand and supply. Finally, the proposed approach was found to outperform alternative methods in terms of computational efficiency and ability to meet the stochastic problem requirements.« less

Optimization techniques applied to passive measures for in-orbit spacecraft survivability

NASA Technical Reports Server (NTRS)

Mog, Robert A.; Price, D. Marvin

1991-01-01

Spacecraft designers have always been concerned about the effects of meteoroid impacts on mission safety. The engineering solution to this problem has generally been to erect a bumper or shield placed outboard from the spacecraft wall to disrupt/deflect the incoming projectiles. Spacecraft designers have a number of tools at their disposal to aid in the design process. These include hypervelocity impact testing, analytic impact predictors, and hydrodynamic codes. Analytic impact predictors generally provide the best quick-look estimate of design tradeoffs. The most complete way to determine the characteristics of an analytic impact predictor is through optimization of the protective structures design problem formulated with the predictor of interest. Space Station Freedom protective structures design insight is provided through the coupling of design/material requirements, hypervelocity impact phenomenology, meteoroid and space debris environment sensitivities, optimization techniques and operations research strategies, and mission scenarios. Major results are presented.

Biological hydrogen production by dark fermentation: challenges and prospects towards scaled-up production.

PubMed

RenNanqi; GuoWanqian; LiuBingfeng; CaoGuangli; DingJie

2011-06-01

Among different technologies of hydrogen production, bio-hydrogen production exhibits perhaps the greatest potential to replace fossil fuels. Based on recent research on dark fermentative hydrogen production, this article reviews the following aspects towards scaled-up application of this technology: bioreactor development and parameter optimization, process modeling and simulation, exploitation of cheaper raw materials and combining dark-fermentation with photo-fermentation. Bioreactors are necessary for dark-fermentation hydrogen production, so the design of reactor type and optimization of parameters are essential. Process modeling and simulation can help engineers design and optimize large-scale systems and operations. Use of cheaper raw materials will surely accelerate the pace of scaled-up production of biological hydrogen. And finally, combining dark-fermentation with photo-fermentation holds considerable promise, and has successfully achieved maximum overall hydrogen yield from a single substrate. Future development of bio-hydrogen production will also be discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

Optimization and planning of operating theatre activities: an original definition of pathways and process modeling.

PubMed

Barbagallo, Simone; Corradi, Luca; de Ville de Goyet, Jean; Iannucci, Marina; Porro, Ivan; Rosso, Nicola; Tanfani, Elena; Testi, Angela

2015-05-17

The Operating Room (OR) is a key resource of all major hospitals, but it also accounts for up 40% of resource costs. Improving cost effectiveness, while maintaining a quality of care, is a universal objective. These goals imply an optimization of planning and a scheduling of the activities involved. This is highly challenging due to the inherent variable and unpredictable nature of surgery. A Business Process Modeling Notation (BPMN 2.0) was used for the representation of the "OR Process" (being defined as the sequence of all of the elementary steps between "patient ready for surgery" to "patient operated upon") as a general pathway ("path"). The path was then both further standardized as much as possible and, at the same time, keeping all of the key-elements that would allow one to address or define the other steps of planning, and the inherent and wide variability in terms of patient specificity. The path was used to schedule OR activity, room-by-room, and day-by-day, feeding the process from a "waiting list database" and using a mathematical optimization model with the objective of ending up in an optimized planning. The OR process was defined with special attention paid to flows, timing and resource involvement. Standardization involved a dynamics operation and defined an expected operating time for each operation. The optimization model has been implemented and tested on real clinical data. The comparison of the results reported with the real data, shows that by using the optimization model, allows for the scheduling of about 30% more patients than in actual practice, as well as to better exploit the OR efficiency, increasing the average operating room utilization rate up to 20%. The optimization of OR activity planning is essential in order to manage the hospital's waiting list. Optimal planning is facilitated by defining the operation as a standard pathway where all variables are taken into account. By allowing a precise scheduling, it feeds the process of planning and, further up-stream, the management of a waiting list in an interactive and bi-directional dynamic process.

Optimal Water-Power Flow Problem: Formulation and Distributed Optimal Solution

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

Dall-Anese, Emiliano; Zhao, Changhong; Zamzam, Admed S.

This paper formalizes an optimal water-power flow (OWPF) problem to optimize the use of controllable assets across power and water systems while accounting for the couplings between the two infrastructures. Tanks and pumps are optimally managed to satisfy water demand while improving power grid operations; {for the power network, an AC optimal power flow formulation is augmented to accommodate the controllability of water pumps.} Unfortunately, the physics governing the operation of the two infrastructures and coupling constraints lead to a nonconvex (and, in fact, NP-hard) problem; however, after reformulating OWPF as a nonconvex, quadratically-constrained quadratic problem, a feasible point pursuit-successivemore » convex approximation approach is used to identify feasible and optimal solutions. In addition, a distributed solver based on the alternating direction method of multipliers enables water and power operators to pursue individual objectives while respecting the couplings between the two networks. The merits of the proposed approach are demonstrated for the case of a distribution feeder coupled with a municipal water distribution network.« less

CAMS as a tool for human factors research in spaceflight

NASA Astrophysics Data System (ADS)

Sauer, Juergen

2004-01-01

The paper reviews a number of research studies that were carried out with a PC-based task environment called Cabin Air Management System (CAMS) simulating the operation of a spacecraft's life support system. As CAMS was a multiple task environment, it allowed the measurement of performance at different levels. Four task components of different priority were embedded in the task environment: diagnosis and repair of system faults, maintaining atmospheric parameters in a safe state, acknowledgement of system alarms (reaction time), and keeping a record of critical system resources (prospective memory). Furthermore, the task environment permitted the examination of different task management strategies and changes in crew member state (fatigue, anxiety, mental effort). A major goal of the research programme was to examine how crew members adapted to various forms of sub-optimal working conditions, such as isolation and confinement, sleep deprivation and noise. None of the studies provided evidence for decrements in primary task performance. However, the results showed a number of adaptive responses of crew members to adjust to the different sub-optimal working conditions. There was evidence for adjustments in information sampling strategies (usually reductions in sampling frequency) as a result of unfavourable working conditions. The results also showed selected decrements in secondary task performance. Prospective memory seemed to be somewhat more vulnerable to sub-optimal working conditions than performance on the reaction time task. Finally, suggestions are made for future research with the CAMS environment.

Data analytics and optimization of an ice-based energy storage system for commercial buildings

DOE PAGES

Luo, Na; Hong, Tianzhen; Li, Hui; ...

2017-07-25

Ice-based thermal energy storage (TES) systems can shift peak cooling demand and reduce operational energy costs (with time-of-use rates) in commercial buildings. The accurate prediction of the cooling load, and the optimal control strategy for managing the charging and discharging of a TES system, are two critical elements to improving system performance and achieving energy cost savings. This study utilizes data-driven analytics and modeling to holistically understand the operation of an ice–based TES system in a shopping mall, calculating the system’s performance using actual measured data from installed meters and sensors. Results show that there is significant savings potential whenmore » the current operating strategy is improved by appropriately scheduling the operation of each piece of equipment of the TES system, as well as by determining the amount of charging and discharging for each day. A novel optimal control strategy, determined by an optimization algorithm of Sequential Quadratic Programming, was developed to minimize the TES system’s operating costs. Three heuristic strategies were also investigated for comparison with our proposed strategy, and the results demonstrate the superiority of our method to the heuristic strategies in terms of total energy cost savings. Specifically, the optimal strategy yields energy costs of up to 11.3% per day and 9.3% per month compared with current operational strategies. A one-day-ahead hourly load prediction was also developed using machine learning algorithms, which facilitates the adoption of the developed data analytics and optimization of the control strategy in a real TES system operation.« less

Data analytics and optimization of an ice-based energy storage system for commercial buildings

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

Luo, Na; Hong, Tianzhen; Li, Hui

Ice-based thermal energy storage (TES) systems can shift peak cooling demand and reduce operational energy costs (with time-of-use rates) in commercial buildings. The accurate prediction of the cooling load, and the optimal control strategy for managing the charging and discharging of a TES system, are two critical elements to improving system performance and achieving energy cost savings. This study utilizes data-driven analytics and modeling to holistically understand the operation of an ice–based TES system in a shopping mall, calculating the system’s performance using actual measured data from installed meters and sensors. Results show that there is significant savings potential whenmore » the current operating strategy is improved by appropriately scheduling the operation of each piece of equipment of the TES system, as well as by determining the amount of charging and discharging for each day. A novel optimal control strategy, determined by an optimization algorithm of Sequential Quadratic Programming, was developed to minimize the TES system’s operating costs. Three heuristic strategies were also investigated for comparison with our proposed strategy, and the results demonstrate the superiority of our method to the heuristic strategies in terms of total energy cost savings. Specifically, the optimal strategy yields energy costs of up to 11.3% per day and 9.3% per month compared with current operational strategies. A one-day-ahead hourly load prediction was also developed using machine learning algorithms, which facilitates the adoption of the developed data analytics and optimization of the control strategy in a real TES system operation.« less

Analysis of the electricity demand of Greece for optimal planning of a large-scale hybrid renewable energy system

NASA Astrophysics Data System (ADS)

Tyralis, Hristos; Karakatsanis, Georgios; Tzouka, Katerina; Mamassis, Nikos

2015-04-01

The Greek electricity system is examined for the period 2002-2014. The demand load data are analysed at various time scales (hourly, daily, seasonal and annual) and they are related to the mean daily temperature and the gross domestic product (GDP) of Greece for the same time period. The prediction of energy demand, a product of the Greek Independent Power Transmission Operator, is also compared with the demand load. Interesting results about the change of the electricity demand scheme after the year 2010 are derived. This change is related to the decrease of the GDP, during the period 2010-2014. The results of the analysis will be used in the development of an energy forecasting system which will be a part of a framework for optimal planning of a large-scale hybrid renewable energy system in which hydropower plays the dominant role. Acknowledgement: This research was funded by the Greek General Secretariat for Research and Technology through the research project Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO; grant number 5145)

Principles of a clean operating room environment.

PubMed

Howard, James L; Hanssen, Arlen D

2007-10-01

Optimizing the operating room environment is necessary to minimize the prevalence of arthroplasty infection. Reduction of bacterial contamination in the operating room should be a primary focus of all members of the operating room team. However, in recent years, there has been a decline in the emphasis of the basic principles of antisepsis in many operating rooms. The purpose of this review is to highlight important considerations for optimizing the operating room environment. These principles should be actively promoted by orthopedic surgeons in their operating rooms as part of a comprehensive approach to minimizing arthroplasty infection.

Optimization of startup and shutdown operation of simulated moving bed chromatographic processes.

PubMed

Li, Suzhou; Kawajiri, Yoshiaki; Raisch, Jörg; Seidel-Morgenstern, Andreas

2011-06-24

This paper presents new multistage optimal startup and shutdown strategies for simulated moving bed (SMB) chromatographic processes. The proposed concept allows to adjust transient operating conditions stage-wise, and provides capability to improve transient performance and to fulfill product quality specifications simultaneously. A specially tailored decomposition algorithm is developed to ensure computational tractability of the resulting dynamic optimization problems. By examining the transient operation of a literature separation example characterized by nonlinear competitive isotherm, the feasibility of the solution approach is demonstrated, and the performance of the conventional and multistage optimal transient regimes is evaluated systematically. The quantitative results clearly show that the optimal operating policies not only allow to significantly reduce both duration of the transient phase and desorbent consumption, but also enable on-spec production even during startup and shutdown periods. With the aid of the developed transient procedures, short-term separation campaigns with small batch sizes can be performed more flexibly and efficiently by SMB chromatography. Copyright © 2011 Elsevier B.V. All rights reserved.

Overutilization and underutilization of operating rooms - insights from behavioral health care operations management.

PubMed

Fügener, Andreas; Schiffels, Sebastian; Kolisch, Rainer

2017-03-01

The planning of surgery durations is crucial for efficient usage of operating theaters. Both planning too long and too short durations for surgeries lead to undesirable consequences, e.g. idle time, overtime, or rescheduling of surgeries. We define these consequences as operating room inefficiency. The overall objective of planning surgery durations is to minimize expected operating room inefficiency, since surgery durations are stochastic. While most health care studies assume economically rational behavior of decision makers, experimental studies have shown that decision makers often do not act according to economic incentives. Based on insights from health care operations management, medical decision making, behavioral operations management, as well as empirical observations, we derive hypotheses that surgeons' behavior deviates from economically rational behavior. To investigate this, we undertake an experimental study where experienced surgeons are asked to plan surgeries with uncertain durations. We discover systematic deviations from optimal decision making and offer behavioral explanations for the observed biases. Our research provides new insights to tackle a major problem in hospitals, i.e. low operating room utilization going along with staff overtime.

The research of conformal optical design

NASA Astrophysics Data System (ADS)

Li, Lin; Li, Yan; Huang, Yi-fan; Du, Bao-lin

2009-07-01

Conformal optical domes are characterized as having external more elongated optical surfaces that are optimized to minimize drag, increased missile velocity and extended operational range. The outer surface of the conformal domes typically deviate greatly from spherical surface descriptions, so the inherent asymmetry of conformal surfaces leads to variations in the aberration content presented to the optical sensor as it is gimbaled across the field of regard, which degrades the sensor's ability to properly image targets of interest and then undermine the overall system performance. Consequently, the aerodynamic advantages of conformal domes cannot be realized in practical systems unless the dynamic aberration correction techniques are developed to restore adequate optical imaging capabilities. Up to now, many optical correction solutions have been researched in conformal optical design, including static aberrations corrections and dynamic aberrations corrections. There are three parts in this paper. Firstly, the combination of static and dynamic aberration correction is introduced. A system for correcting optical aberration created by a conformal dome has an outer surface and an inner surface. The optimization of the inner surface is regard as the static aberration correction; moreover, a deformable mirror is placed at the position of the secondary mirror in the two-mirror all reflective imaging system, which is the dynamic aberration correction. Secondly, the using of appropriate surface types is very important in conformal dome design. Better performing optical systems can result from surface types with adequate degrees of freedom to describe the proper corrector shape. Two surface types and the methods of using them are described, including Zernike polynomial surfaces used in correct elements and user-defined surfaces used in deformable mirror (DM). Finally, the Adaptive optics (AO) correction is presented. In order to correct the dynamical residual aberration in conformal optical design, the SPGD optimization algorithm is operated at each zoom position to calculate the optimized surface shape of the MEMS DM. The communication between MATLAB and Code V established via ActiveX technique is applied in simulation analysis.

Optimal inverse functions created via population-based optimization.

PubMed

Jennings, Alan L; Ordóñez, Raúl

2014-06-01

Finding optimal inputs for a multiple-input, single-output system is taxing for a system operator. Population-based optimization is used to create sets of functions that produce a locally optimal input based on a desired output. An operator or higher level planner could use one of the functions in real time. For the optimization, each agent in the population uses the cost and output gradients to take steps lowering the cost while maintaining their current output. When an agent reaches an optimal input for its current output, additional agents are generated in the output gradient directions. The new agents then settle to the local optima for the new output values. The set of associated optimal points forms an inverse function, via spline interpolation, from a desired output to an optimal input. In this manner, multiple locally optimal functions can be created. These functions are naturally clustered in input and output spaces allowing for a continuous inverse function. The operator selects the best cluster over the anticipated range of desired outputs and adjusts the set point (desired output) while maintaining optimality. This reduces the demand from controlling multiple inputs, to controlling a single set point with no loss in performance. Results are demonstrated on a sample set of functions and on a robot control problem.

Analysis and Evaluation of Parameters Determining Maximum Efficiency of Fish Protection

NASA Astrophysics Data System (ADS)

Khetsuriani, E. D.; Kostyukov, V. P.; Khetsuriani, T. E.

2017-11-01

The article is concerned with experimental research findings. The efficiency of fish fry protection from entering water inlets is the main criterion of any fish protection facility or device. The research was aimed to determine an adequate mathematical model E = f(PCT, Vp, α), where PCT, Vp and α are controlled factors influencing the process of fish fry protection. The result of the processing of experimental data was an adequate regression model. We determined the maximum of fish protection Emax=94,21 and the minimum of optimization function Emin=44,41. As a result of the statistical processing of experimental data we obtained adequate dependences for determining an optimal rotational speed of tip and fish protection efficiency. The analysis of fish protection efficiency dependence E% = f(PCT, Vp, α) allowed the authors to recommend the following optimized operating modes for it: the maximum fish protection efficiency is achieved at the process pressure PCT=3 atm, stream velocity Vp=0,42 m/s and nozzle inclination angle α=47°49’. The stream velocity Vp has the most critical influence on fish protection efficiency. The maximum efficiency of fish protection is obtained at the tip rotational speed of 70.92 rpm.

Optimization of groundwater artificial recharge systems using a genetic algorithm: a case study in Beijing, China

NASA Astrophysics Data System (ADS)

Hao, Qichen; Shao, Jingli; Cui, Yali; Zhang, Qiulan; Huang, Linxian

2018-05-01

An optimization approach is used for the operation of groundwater artificial recharge systems in an alluvial fan in Beijing, China. The optimization model incorporates a transient groundwater flow model, which allows for simulation of the groundwater response to artificial recharge. The facilities' operation with regard to recharge rates is formulated as a nonlinear programming problem to maximize the volume of surface water recharged into the aquifers under specific constraints. This optimization problem is solved by the parallel genetic algorithm (PGA) based on OpenMP, which could substantially reduce the computation time. To solve the PGA with constraints, the multiplicative penalty method is applied. In addition, the facilities' locations are implicitly determined on the basis of the results of the recharge-rate optimizations. Two scenarios are optimized and the optimal results indicate that the amount of water recharged into the aquifers will increase without exceeding the upper limits of the groundwater levels. Optimal operation of this artificial recharge system can also contribute to the more effective recovery of the groundwater storage capacity.

Optimization of the efficiency of search operations in the relational database of radio electronic systems

NASA Astrophysics Data System (ADS)

Wajszczyk, Bronisław; Biernacki, Konrad

2018-04-01

The increase of interoperability of radio electronic systems used in the Armed Forces requires the processing of very large amounts of data. Requirements for the integration of information from many systems and sensors, including radar recognition, electronic and optical recognition, force to look for more efficient methods to support information retrieval in even-larger database resources. This paper presents the results of research on methods of improving the efficiency of databases using various types of indexes. The data structure indexing technique is a solution used in RDBMS systems (relational database management system). However, the analysis of the performance of indices, the description of potential applications, and in particular the presentation of a specific scale of performance growth for individual indices are limited to few studies in this field. This paper contains analysis of methods affecting the work efficiency of a relational database management system. As a result of the research, a significant increase in the efficiency of operations on data was achieved through the strategy of indexing data structures. The presentation of the research topic discussed in this paper mainly consists of testing the operation of various indexes against the background of different queries and data structures. The conclusions from the conducted experiments allow to assess the effectiveness of the solutions proposed and applied in the research. The results of the research indicate the existence of a real increase in the performance of operations on data using indexation of data structures. In addition, the level of this growth is presented, broken down by index types.

Unlocking Flexibility: Integrated Optimization and Control of Multienergy Systems

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

Dall'Anese, Emiliano; Mancarella, Pierluigi; Monti, Antonello

Electricity, natural gas, water, and dis trict heating/cooling systems are predominantly planned and operated independently. However, it is increasingly recognized that integrated optimization and control of such systems at multiple spatiotemporal scales can bring significant socioeconomic, operational efficiency, and environmental benefits. Accordingly, the concept of the multi-energy system is gaining considerable attention, with the overarching objectives of 1) uncovering fundamental gains (and potential drawbacks) that emerge from the integrated operation of multiple systems and 2) developing holistic yet computationally affordable optimization and control methods that maximize operational benefits, while 3) acknowledging intrinsic interdependencies and quality-of-service requirements for each provider.

Spot and Runway Departure Advisor (SARDA)

NASA Technical Reports Server (NTRS)

Jung, Yoon

2016-01-01

Spot and Runway Departure Advisor (SARDA) is a decision support tool to assist airline ramp controllers and ATC tower controllers to manage traffic on the airport surface to significantly improve efficiency and predictability in surface operations. The core function of the tool is the runway scheduler which generates an optimal solution for runway sequence and schedule of departure aircraft, which would minimize system delay and maximize runway throughput. The presentation also discusses the latest status of NASA's current surface research through a collaboration with an airline partner, where a tool is developed for airline ramp operators to assist departure pushback operations. The presentation describes the concept of the SARDA tool and results from human-in-the-loop simulations conducted in 2012 for Dallas-Ft. Worth International Airport and 2014 for Charlotte airport ramp tower.

Sensibility study in a flexible job shop scheduling problem

NASA Astrophysics Data System (ADS)

Curralo, Ana; Pereira, Ana I.; Barbosa, José; Leitão, Paulo

2013-10-01

This paper proposes the impact assessment of the jobs order in the optimal time of operations in a Flexible Job Shop Scheduling Problem. In this work a real assembly cell was studied: the AIP-PRIMECA cell at the Université de Valenciennes et du Hainaut-Cambrésis, in France, which is considered as a Flexible Job Shop problem. The problem consists in finding the machines operations schedule, taking into account the precedence constraints. The main objective is to minimize the batch makespan, i.e. the finish time of the last operation completed in the schedule. Shortly, the present study consists in evaluating if the jobs order affects the optimal time of the operations schedule. The genetic algorithm was used to solve the optimization problem. As a conclusion, it's assessed that the jobs order influence the optimal time.

Optimal linear-quadratic control of coupled parabolic-hyperbolic PDEs

NASA Astrophysics Data System (ADS)

Aksikas, I.; Moghadam, A. Alizadeh; Forbes, J. F.

2017-10-01

This paper focuses on the optimal control design for a system of coupled parabolic-hypebolic partial differential equations by using the infinite-dimensional state-space description and the corresponding operator Riccati equation. Some dynamical properties of the coupled system of interest are analysed to guarantee the existence and uniqueness of the solution of the linear-quadratic (LQ)-optimal control problem. A state LQ-feedback operator is computed by solving the operator Riccati equation, which is converted into a set of algebraic and differential Riccati equations, thanks to the eigenvalues and the eigenvectors of the parabolic operator. The results are applied to a non-isothermal packed-bed catalytic reactor. The LQ-optimal controller designed in the early portion of the paper is implemented for the original nonlinear model. Numerical simulations are performed to show the controller performances.

Balancing hydropower production and river bed incision in operating a run-of-river hydropower scheme along the River Po

NASA Astrophysics Data System (ADS)

Denaro, Simona; Dinh, Quang; Bizzi, Simone; Bernardi, Dario; Pavan, Sara; Castelletti, Andrea; Schippa, Leonardo; Soncini-Sessa, Rodolfo

2013-04-01

Water management through dams and reservoirs is worldwide necessary to support key human-related activities ranging from hydropower production to water allocation, and flood risk mitigation. Reservoir operations are commonly planned in order to maximize these objectives. However reservoirs strongly influence river geomorphic processes causing sediment deficit downstream, altering the flow regime, leading, often, to process of river bed incision: for instance the variations of river cross sections over few years can notably affect hydropower production, flood mitigation, water supply strategies and eco-hydrological processes of the freshwater ecosystem. The river Po (a major Italian river) has experienced severe bed incision in the last decades. For this reason infrastructure stability has been negatively affected, and capacity to derive water decreased, navigation, fishing and tourism are suffering economic damages, not to mention the impact on the environment. Our case study analyzes the management of Isola Serafini hydropower plant located on the main Po river course. The plant has a major impact to the geomorphic river processes downstream, affecting sediment supply, connectivity (stopping sediment upstream the dam) and transport capacity (altering the flow regime). Current operation policy aims at maximizing hydropower production neglecting the effects in term of geomorphic processes. A new improved policy should also consider controlling downstream river bed incision. The aim of this research is to find suitable modeling framework to identify an operating policy for Isola Serafini reservoir able to provide an optimal trade-off between these two conflicting objectives: hydropower production and river bed incision downstream. A multi-objective simulation-based optimization framework is adopted. The operating policy is parameterized as a piecewise linear function and the parameters optimized using an interactive response surface approach. Global and local response surface are comparatively assessed. Preliminary results show that a range of potentially interesting trade-off policies exist able to better control river bed incision downstream without significantly decreasing hydropower production.

Light Water Reactor Sustainability Program A Reference Plan for Control Room Modernization: Planning and Analysis Phase

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

Jacques Hugo; Ronald Boring; Lew Hanes

2013-09-01

The U.S. Department of Energy’s Light Water Reactor Sustainability (LWRS) program is collaborating with a U.S. nuclear utility to bring about a systematic fleet-wide control room modernization. To facilitate this upgrade, a new distributed control system (DCS) is being introduced into the control rooms of these plants. The DCS will upgrade the legacy plant process computer and emergency response facility information system. In addition, the DCS will replace an existing analog turbine control system with a display-based system. With technology upgrades comes the opportunity to improve the overall human-system interaction between the operators and the control room. To optimize operatormore » performance, the LWRS Control Room Modernization research team followed a human-centered approach published by the U.S. Nuclear Regulatory Commission. NUREG-0711, Rev. 3, Human Factors Engineering Program Review Model (O’Hara et al., 2012), prescribes four phases for human factors engineering. This report provides examples of the first phase, Planning and Analysis. The three elements of Planning and Analysis in NUREG-0711 that are most crucial to initiating control room upgrades are: • Operating Experience Review: Identifies opportunities for improvement in the existing system and provides lessons learned from implemented systems. • Function Analysis and Allocation: Identifies which functions at the plant may be optimally handled by the DCS vs. the operators. • Task Analysis: Identifies how tasks might be optimized for the operators. Each of these elements is covered in a separate chapter. Examples are drawn from workshops with reactor operators that were conducted at the LWRS Human System Simulation Laboratory HSSL and at the respective plants. The findings in this report represent generalized accounts of more detailed proprietary reports produced for the utility for each plant. The goal of this LWRS report is to disseminate the technique and provide examples sufficient to serve as a template for other utilities’ projects for control room modernization.« less

Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization.

PubMed

Mousavi, Maryam; Yap, Hwa Jen; Musa, Siti Nurmaya; Tahriri, Farzad; Md Dawal, Siti Zawiah

2017-01-01

Flexible manufacturing system (FMS) enhances the firm's flexibility and responsiveness to the ever-changing customer demand by providing a fast product diversification capability. Performance of an FMS is highly dependent upon the accuracy of scheduling policy for the components of the system, such as automated guided vehicles (AGVs). An AGV as a mobile robot provides remarkable industrial capabilities for material and goods transportation within a manufacturing facility or a warehouse. Allocating AGVs to tasks, while considering the cost and time of operations, defines the AGV scheduling process. Multi-objective scheduling of AGVs, unlike single objective practices, is a complex and combinatorial process. In the main draw of the research, a mathematical model was developed and integrated with evolutionary algorithms (genetic algorithm (GA), particle swarm optimization (PSO), and hybrid GA-PSO) to optimize the task scheduling of AGVs with the objectives of minimizing makespan and number of AGVs while considering the AGVs' battery charge. Assessment of the numerical examples' scheduling before and after the optimization proved the applicability of all the three algorithms in decreasing the makespan and AGV numbers. The hybrid GA-PSO produced the optimum result and outperformed the other two algorithms, in which the mean of AGVs operation efficiency was found to be 69.4, 74, and 79.8 percent in PSO, GA, and hybrid GA-PSO, respectively. Evaluation and validation of the model was performed by simulation via Flexsim software.

Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization

PubMed Central

Yap, Hwa Jen; Musa, Siti Nurmaya; Tahriri, Farzad; Md Dawal, Siti Zawiah

2017-01-01

Flexible manufacturing system (FMS) enhances the firm’s flexibility and responsiveness to the ever-changing customer demand by providing a fast product diversification capability. Performance of an FMS is highly dependent upon the accuracy of scheduling policy for the components of the system, such as automated guided vehicles (AGVs). An AGV as a mobile robot provides remarkable industrial capabilities for material and goods transportation within a manufacturing facility or a warehouse. Allocating AGVs to tasks, while considering the cost and time of operations, defines the AGV scheduling process. Multi-objective scheduling of AGVs, unlike single objective practices, is a complex and combinatorial process. In the main draw of the research, a mathematical model was developed and integrated with evolutionary algorithms (genetic algorithm (GA), particle swarm optimization (PSO), and hybrid GA-PSO) to optimize the task scheduling of AGVs with the objectives of minimizing makespan and number of AGVs while considering the AGVs’ battery charge. Assessment of the numerical examples’ scheduling before and after the optimization proved the applicability of all the three algorithms in decreasing the makespan and AGV numbers. The hybrid GA-PSO produced the optimum result and outperformed the other two algorithms, in which the mean of AGVs operation efficiency was found to be 69.4, 74, and 79.8 percent in PSO, GA, and hybrid GA-PSO, respectively. Evaluation and validation of the model was performed by simulation via Flexsim software. PMID:28263994

Modeling the effects of high-G stress on pilots in a tracking task

NASA Technical Reports Server (NTRS)

Korn, J.; Kleinman, D. L.

1978-01-01

Air-to-air tracking experiments were conducted at the Aerospace Medical Research Laboratories using both fixed and moving base dynamic environment simulators. The obtained data, which includes longitudinal error of a simulated air-to-air tracking task as well as other auxiliary variables, was analyzed using an ensemble averaging method. In conjunction with these experiments, the optimal control model is applied to model a human operator under high-G stress.

Virtual Acoustics, Aeronautics and Communications

NASA Technical Reports Server (NTRS)

Begault, Durand R.; Null, Cynthia H. (Technical Monitor)

1996-01-01

An optimal approach to auditory display design for commercial aircraft would utilize both spatialized ("3-D") audio techniques and active noise cancellation for safer operations. Results from several aircraft simulator studies conducted at NASA Ames Research Center are reviewed, including Traffic alert and Collision Avoidance System (TCAS) warnings, spoken orientation "beacons" for gate identification and collision avoidance on the ground, and hardware for improved speech intelligibility. The implications of hearing loss amongst pilots is also considered.