Science.gov

Sample records for optimal maintenance planning

  1. Solving complex maintenance planning optimization problems using stochastic simulation and multi-criteria fuzzy decision making

    NASA Astrophysics Data System (ADS)

    Tahvili, Sahar; Österberg, Jonas; Silvestrov, Sergei; Biteus, Jonas

    2014-12-01

    One of the most important factors in the operations of many cooperations today is to maximize profit and one important tool to that effect is the optimization of maintenance activities. Maintenance activities is at the largest level divided into two major areas, corrective maintenance (CM) and preventive maintenance (PM). When optimizing maintenance activities, by a maintenance plan or policy, we seek to find the best activities to perform at each point in time, be it PM or CM. We explore the use of stochastic simulation, genetic algorithms and other tools for solving complex maintenance planning optimization problems in terms of a suggested framework model based on discrete event simulation.

  2. Solving complex maintenance planning optimization problems using stochastic simulation and multi-criteria fuzzy decision making

    SciTech Connect

    Tahvili, Sahar; Österberg, Jonas; Silvestrov, Sergei; Biteus, Jonas

    2014-12-10

    One of the most important factors in the operations of many cooperations today is to maximize profit and one important tool to that effect is the optimization of maintenance activities. Maintenance activities is at the largest level divided into two major areas, corrective maintenance (CM) and preventive maintenance (PM). When optimizing maintenance activities, by a maintenance plan or policy, we seek to find the best activities to perform at each point in time, be it PM or CM. We explore the use of stochastic simulation, genetic algorithms and other tools for solving complex maintenance planning optimization problems in terms of a suggested framework model based on discrete event simulation.

  3. Progressive Planned Maintenance.

    ERIC Educational Resources Information Center

    Lewis, Mary Jo; Jacobs, Richard S.

    A planned maintenance system, which was implemented at Washington State University (WSU), uniquely integrates functions of equipment inventory, scheduling, time reporting, project management, materials inventory, and billing. Management now has immediate access to equipment data, maintenance status, and costs. Staff requirements are readily…

  4. PREVENTIVE MAINTENANCE. HONEYWELL PLANNING GUIDE.

    ERIC Educational Resources Information Center

    Honeywell, Inc., Minneapolis, Minn.

    THIS HONEYWELL PAMPHLET DISCUSSES SOME ASPECTS OF PREVENTIVE MAINTENANCE OF AUTOMATIC CONTROLS, HEATING, VENTILATING, AND AIR CONDITIONING, AND COMPARES IN-PLANT WITH CONTRACT SERVICE, CONCLUDING THAT CONTRACT SERVICE IS PREFERABLE AND DESCRIBING A NUMBER OF MAINTENANCE PLANS WHICH THEY FURNISH. PREVENTIVE MAINTENANCE PROVIDES--(1) MORE EFFICIENT…

  5. Minimum Maintenance Planning for School Grounds.

    ERIC Educational Resources Information Center

    Bruning, Walter F.

    Several factors affecting school ground maintenance, including accessibility, site size, topography, exposure, and soil conditions, are discussed. Consideration is also given to site planning, maintenance materials, lawn development, and selection of maintenance equipment. (FS)

  6. Stick with a School Maintenance Plan

    ERIC Educational Resources Information Center

    Kennedy, Mike

    2012-01-01

    The U.S. Department of Education's "Planning Guide for Maintaining School Facilities" states that a sound facilities maintenance plan serves as evidence that school facilities are, and will be, cared for appropriately. On the other hand, negligent facilities maintenance planning can cause real problems. Budget restraints and cuts in areas not…

  7. Health Maintenance Organization (HMO) Plan

    MedlinePlus

    ... up/change plans About Medicare health plans Medicare Advantage Plans + Share widget - Select to show Subcategories Getting ... plan? About Medicare health plans , current subcategory Medicare Advantage Plans , current page Medicare Medical Savings Account (MSA) ...

  8. 222-S Laboratory maintenance implementation plan

    SciTech Connect

    Heinemann, J.L.

    1997-08-13

    This Maintenance Improvement Plan has been developed for maintenance functions associated with the 222-S Laboratory. This plan is developed from the guidelines presented by Department of Energy (DOE) Order 4330.4B, Maintenance Management Program (DOE 1994), Chapter 11. The objective of this plan is to provide information for establishing and identifying WMH conformance programs and policies applicable to implementation of DOE Order 4330.4B guidelines. In addition, this maintenance plan identifies the actions necessary to develop a cost effective and efficient maintenance program at 222-S Laboratory. Maintenance activities are mainly going to be performed by existing maintenance organizations within Waste Management Federal Services of Hanford (WMH). Most maintenance performed at 222-S Laboratory is performed by the 222-S Laboratory maintenance organization. This 222-S Laboratory Maintenance Implementation Plan provides the interface requirements and responsibilities as they apply specifically to 222-S Laboratory. This document provides an implementation schedule which has been developed for items considered to be deficient or in need of improvement. The discussion section as applied to 222-S Laboratory implementation has been developed from a review of programs and practices utilizing the graded approach. Biennial review and additional reviews are conducted as significant programmatic and mission changes are made. This document is revised as necessary to keep this document current and in compliance with DOE requirements.

  9. Test, Control and Monitor System maintenance plan

    NASA Technical Reports Server (NTRS)

    Buehler, David P.; Lougheed, M. J.

    1993-01-01

    The maintenance requirements for Test, Control, and Monitor System (TCMS) and the method for satisfying these requirements prior to First Need Date (FND) of the last TCMS set are described. The method for satisfying maintenance requirements following FND of the last TCMS set will be addressed by a revision to this plan. This maintenance plan serves as the basic planning document for maintenance of this equipment by the NASA Payloads Directorate (CM) and the Payload Ground Operations Contractor (PGOC) at KSC. The terms TCMS Operations and Maintenance (O&M), Payloads Logistics, TCMS Sustaining Engineering, Payload Communications, and Integrated Network Services refer to the appropriate NASA and PGOC organization. For the duration of their contract, the Core Electronic Contractor (CEC) will provide a Set Support Team (SST). One of the primary purposes of this team is to help NASA and PGOC operate and maintain TCMS. It is assumed that SST is an integral part of TCMS O&M. The purpose of this plan is to describe the maintenance concept for TCMS hardware and system software in order to facilitate activation, transition planning, and continuing operation. When software maintenance is mentioned in this plan, it refers to maintenance of TCMS system software.

  10. AN OPTIMAL MAINTENANCE MANAGEMENT MODEL FOR AIRPORT CONCRETE PAVEMENT

    NASA Astrophysics Data System (ADS)

    Shimomura, Taizo; Fujimori, Yuji; Kaito, Kiyoyuki; Obama, Kengo; Kobayashi, Kiyoshi

    In this paper, an optimal management model is formulated for the performance-based rehabilitation/maintenance contract for airport concrete pavement, whereby two types of life cycle cost risks, i.e., ground consolidation risk and concrete depreciation risk, are explicitly considered. The non-homogenous Markov chain model is formulated to represent the deterioration processes of concrete pavement which are conditional upon the ground consolidation processes. The optimal non-homogenous Markov decision model with multiple types of risk is presented to design the optimal rehabilitation/maintenance plans. And the methodology to revise the optimal rehabilitation/maintenance plans based upon the monitoring data by the Bayesian up-to-dating rules. The validity of the methodology presented in this paper is examined based upon the case studies carried out for the H airport.

  11. Optimal Limited Contingency Planning

    NASA Technical Reports Server (NTRS)

    Meuleau, Nicolas; Smith, David E.

    2003-01-01

    For a given problem, the optimal Markov policy over a finite horizon is a conditional plan containing a potentially large number of branches. However, there are applications where it is desirable to strictly limit the number of decision points and branches in a plan. This raises the question of how one goes about finding optimal plans containing only a limited number of branches. In this paper, we present an any-time algorithm for optimal k-contingency planning. It is the first optimal algorithm for limited contingency planning that is not an explicit enumeration of possible contingent plans. By modelling the problem as a partially observable Markov decision process, it implements the Bellman optimality principle and prunes the solution space. We present experimental results of applying this algorithm to some simple test cases.

  12. Site Maintenance Plan: Part 2, Site Maintenance Action Plan for FY 1994

    SciTech Connect

    Fisk, E.L.

    1994-06-01

    This Fiscal Year (FY) 1994 Site Maintenance Action Plan (SMAP) is Part II of the Site Maintenance Plan, and has been written by Westinghouse Hanford Company (WHC) to outline the requirements stated in DOE Order 4330.4B, Maintenance Management Program, Chapter 1, Paragraph 3.3.1. The SMAP provides an annual status of maintenance initiatives completed and planned, a summary of performance indicators, a summary of maintenance backlog, a listing of real property and capital equipment maintenance cost estimates that were used to create the FY 1996 infrastructure and maintenance budget input, and a listing of proposed line item and general plant projects. Additionally, assumptions for various Site programs are listed to bring the Site Maintenance Plan into focus with overall Site activities. The primary mission at Hanford is to clean up the Site. In this cleanup process WHC will provide scientific and technological expertise to meet global needs, and partnership with stakeholders in the region to develop regional economic diversification. Other missions at the Hanford Site include energy research and development, and waste management and disposal activities. Their primary mission has a 30-year projected life span and will direct the shutting down and cleanup of defense production facilities and the Fast Flux Test Facility. This long-term mission requires continuous maintenance and in many instances, replacement of existing basic infrastructure, support facilities, and utilities. Without adequate maintenance and capital funding these infrastructure, support facilities, and utilities will continue to deteriorate causing an increase in backlogged work.

  13. Project Surveillance and Maintenance Plan. [UMTRA Project

    SciTech Connect

    Not Available

    1985-09-01

    The Project Surveillance and Maintenance Plan (PSMP) describes the procedures that will be used by the US Department of Energy (DOE), or other agency as designated by the President to verify that inactive uranium tailings disposal facilities remain in compliance with licensing requirements and US Environmental Protection Agency (EPA) standards for remedial actions. The PSMP will be used as a guide for the development of individual Site Surveillance and Maintenance Plans (part of a license application) for each of the UMTRA Project sites. The PSMP is not intended to provide minimum requirements but rather to provide guidance in the selection of surveillance measures. For example, the plan acknowledges that ground-water monitoring may or may not be required and provides the (guidance) to make this decision. The Site Surveillance and Maintenance Plans (SSMPs) will form the basis for the licensing of the long-term surveillance and maintenance of each UMTRA Project site by the NRC. Therefore, the PSMP is a key milestone in the licensing process of all UMTRA Project sites. The Project Licensing Plan (DOE, 1984a) describes the licensing process. 11 refs., 22 figs., 8 tabs.

  14. ICD Complex Operations and Maintenance Plan

    SciTech Connect

    Gibson, P. L.

    2007-06-25

    This Operations and Maintenance (O&M) Plan describes how the Idaho National Laboratory (INL) conducts operations, winterization, and startup of the Idaho CERCLA Disposal Facility (ICDF) Complex. The ICDF Complex is the centralized INL facility responsible for the receipt, storage, treatment (as necessary), and disposal of INL Comprehensive Environmental Response, Compensation and Liability Act (CERCLA) remediation waste.

  15. Flight plan optimization

    NASA Astrophysics Data System (ADS)

    Dharmaseelan, Anoop; Adistambha, Keyne D.

    2015-05-01

    Fuel cost accounts for 40 percent of the operating cost of an airline. Fuel cost can be minimized by planning a flight on optimized routes. The routes can be optimized by searching best connections based on the cost function defined by the airline. The most common algorithm that used to optimize route search is Dijkstra's. Dijkstra's algorithm produces a static result and the time taken for the search is relatively long. This paper experiments a new algorithm to optimize route search which combines the principle of simulated annealing and genetic algorithm. The experimental results of route search, presented are shown to be computationally fast and accurate compared with timings from generic algorithm. The new algorithm is optimal for random routing feature that is highly sought by many regional operators.

  16. 40 CFR 52.975 - Redesignations and maintenance plans; ozone.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ...; ozone. 52.975 Section 52.975 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... and maintenance plans; ozone. (a) Approval. The Louisiana Department of Environmental Quality (LDEQ... supplemental ozone redesignation requests and revised maintenance plans. These supplemental submittals...

  17. 40 CFR 52.975 - Redesignations and maintenance plans; ozone.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ...; ozone. 52.975 Section 52.975 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... and maintenance plans; ozone. (a) Approval. The Louisiana Department of Environmental Quality (LDEQ... supplemental ozone redesignation requests and revised maintenance plans. These supplemental submittals...

  18. 40 CFR 52.975 - Redesignations and maintenance plans; ozone.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ...; ozone. 52.975 Section 52.975 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... and maintenance plans; ozone. (a) Approval. The Louisiana Department of Environmental Quality (LDEQ... supplemental ozone redesignation requests and revised maintenance plans. These supplemental submittals...

  19. 40 CFR 52.975 - Redesignations and maintenance plans; ozone.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ...; ozone. 52.975 Section 52.975 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... and maintenance plans; ozone. (a) Approval. The Louisiana Department of Environmental Quality (LDEQ... supplemental ozone redesignation requests and revised maintenance plans. These supplemental submittals...

  20. 36 CFR 219.31 - Maintenance of the plan and planning records.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... AGRICULTURE PLANNING National Forest System Land and Resource Management Planning Planning Documentation § 219.31 Maintenance of the plan and planning records. (a) Each National Forest or Grassland Supervisor... 36 Parks, Forests, and Public Property 2 2011-07-01 2011-07-01 false Maintenance of the plan...

  1. 78 FR 54200 - Approval and Promulgation of Air Quality Implementation Plans; Indiana; Maintenance Plan Update...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-09-03

    ... Plan Update for Lake County, Indiana for Sulfur Dioxide AGENCY: Environmental Protection Agency (EPA..., Indiana sulfur dioxide (SO 2 ) maintenance area. This plan update demonstrates that Lake County...

  2. 40 CFR 171.8 - Maintenance of State plans.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40 Protection of Environment 24 2011-07-01 2011-07-01 false Maintenance of State plans. 171.8 Section 171.8 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) PESTICIDE PROGRAMS CERTIFICATION OF PESTICIDE APPLICATORS § 171.8 Maintenance of State plans. (a) Any State certification...

  3. 40 CFR 171.8 - Maintenance of State plans.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 40 Protection of Environment 25 2012-07-01 2012-07-01 false Maintenance of State plans. 171.8 Section 171.8 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) PESTICIDE PROGRAMS CERTIFICATION OF PESTICIDE APPLICATORS § 171.8 Maintenance of State plans. (a) Any State certification...

  4. 40 CFR 171.8 - Maintenance of State plans.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 23 2010-07-01 2010-07-01 false Maintenance of State plans. 171.8 Section 171.8 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) PESTICIDE PROGRAMS CERTIFICATION OF PESTICIDE APPLICATORS § 171.8 Maintenance of State plans. (a) Any State certification...

  5. Risk-Informed Decisions Optimization in Inspection and Maintenance

    SciTech Connect

    Robertas Alzbutas

    2002-07-01

    partial case is used for the construction and research of the models related to inspections and maintenance planning of Ignalina Nuclear Power Plant (RBMK-1500) piping components. The discussed example is related to risk analysis and inspection program improvements for selected pipe systems. The new risk-informed inspection and maintenance program for selected pipe systems are compared with various alternatives. The usage of risk evaluations to optimize the selection of inspection locations, the inspection interval, and the changes in risk and cost due suggested modifications are demonstrated. The proposed integrated modeling methodic and general model of inspection process can be used as a base for other risk-informed models of inspection process control and risk monitors of complex dynamic systems. (authors)

  6. Multicriteria optimization informed VMAT planning.

    PubMed

    Chen, Huixiao; Craft, David L; Gierga, David P

    2014-01-01

    We developed a patient-specific volumetric-modulated arc therapy (VMAT) optimization procedure using dose-volume histogram (DVH) information from multicriteria optimization (MCO) of intensity-modulated radiotherapy (IMRT) plans. The study included 10 patients with prostate cancer undergoing standard fractionation treatment, 10 patients with prostate cancer undergoing hypofractionation treatment, and 5 patients with head/neck cancer. MCO-IMRT plans using 20 and 7 treatment fields were generated for each patient on the RayStation treatment planning system (clinical version 2.5, RaySearch Laboratories, Stockholm, Sweden). The resulting DVH of the 20-field MCO-IMRT plan for each patient was used as the reference DVH, and the extracted point values of the resulting DVH of the MCO-IMRT plan were used as objectives and constraints for VMAT optimization. Weights of objectives or constraints of VMAT optimization or both were further tuned to generate the best match with the reference DVH of the MCO-IMRT plan. The final optimal VMAT plan quality was evaluated by comparison with MCO-IMRT plans based on homogeneity index, conformity number of planning target volume, and organ at risk sparing. The influence of gantry spacing, arc number, and delivery time on VMAT plan quality for different tumor sites was also evaluated. The resulting VMAT plan quality essentially matched the 20-field MCO-IMRT plan but with a shorter delivery time and less monitor units. VMAT plan quality of head/neck cancer cases improved using dual arcs whereas prostate cases did not. VMAT plan quality was improved by fine gantry spacing of 2 for the head/neck cancer cases and the hypofractionation-treated prostate cancer cases but not for the standard fractionation-treated prostate cancer cases. MCO-informed VMAT optimization is a useful and valuable way to generate patient-specific optimal VMAT plans, though modification of the weights of objectives or constraints extracted from resulting DVH of MCO-IMRT or

  7. Multicriteria optimization informed VMAT planning

    SciTech Connect

    Chen, Huixiao; Craft, David L.; Gierga, David P.

    2014-04-01

    We developed a patient-specific volumetric-modulated arc therapy (VMAT) optimization procedure using dose-volume histogram (DVH) information from multicriteria optimization (MCO) of intensity-modulated radiotherapy (IMRT) plans. The study included 10 patients with prostate cancer undergoing standard fractionation treatment, 10 patients with prostate cancer undergoing hypofractionation treatment, and 5 patients with head/neck cancer. MCO-IMRT plans using 20 and 7 treatment fields were generated for each patient on the RayStation treatment planning system (clinical version 2.5, RaySearch Laboratories, Stockholm, Sweden). The resulting DVH of the 20-field MCO-IMRT plan for each patient was used as the reference DVH, and the extracted point values of the resulting DVH of the MCO-IMRT plan were used as objectives and constraints for VMAT optimization. Weights of objectives or constraints of VMAT optimization or both were further tuned to generate the best match with the reference DVH of the MCO-IMRT plan. The final optimal VMAT plan quality was evaluated by comparison with MCO-IMRT plans based on homogeneity index, conformity number of planning target volume, and organ at risk sparing. The influence of gantry spacing, arc number, and delivery time on VMAT plan quality for different tumor sites was also evaluated. The resulting VMAT plan quality essentially matched the 20-field MCO-IMRT plan but with a shorter delivery time and less monitor units. VMAT plan quality of head/neck cancer cases improved using dual arcs whereas prostate cases did not. VMAT plan quality was improved by fine gantry spacing of 2 for the head/neck cancer cases and the hypofractionation-treated prostate cancer cases but not for the standard fractionation–treated prostate cancer cases. MCO-informed VMAT optimization is a useful and valuable way to generate patient-specific optimal VMAT plans, though modification of the weights of objectives or constraints extracted from resulting DVH of MCO

  8. Long Length Contaminated Equipment Maintenance Plan

    SciTech Connect

    ESVELT, C.A.

    2000-02-01

    The purpose of this document is to provide the maintenance requirements of the Long Length Contaminated Equipment (LLCE) trailers and provide a basis for the maintenance frequencies selected. This document is applicable to the LLCE Receiver trailer and Transport trailer assembled by Mobilized Systems Inc. (MSI). Equipment used in conjunction with, or in support of, these trailers is not included. This document does not provide the maintenance requirements for checkout and startup of the equipment following the extended lay-up status which began in the mid 1990s. These requirements will be specified in other documentation.

  9. Risk based optimization of the frequency of EDG on-line maintenance at Hope Creek

    SciTech Connect

    Knoll, A.; Samanta, P.K.; Vesely, W.E.

    1996-09-01

    This paper presents a study to optimize the frequency of on-line maintenance of the emergency diesel generators at Hope Creek. This study was directed towards identifying, analyzing, and modifying maintenance planning and scheduling practices to assure the high availability of emergency diesel generators. Input from application of a recently developed reliability model, from considerations of probabilistic safety assessment, plant-specific experience, insights from personnel involved in EDG maintenance, and other practical issues were used to define a maintenance schedule that balances its beneficial and adverse impacts. Conclusions resulted in feasible recommendations to optimize and reduce the frequency of diesel on-line maintenance, allowing additional resources to better maintain other equipment important to safety.

  10. Pacific Northwest Laboratory FY 1993 Site Maintenance Plan for maintenance of DOE nonnuclear facilities

    SciTech Connect

    Bright, J.D.

    1992-09-28

    This Site Maintenance Plan has been developed for Pacific Northwest Laboratory`s (PNL) Nonnuclear Facilities. It is based on requirements specified by US Department of Energy (DOE) Order 4330.4A, Chapter I, Change No. 4. The objective of this maintenance plan is to provide baseline information for compliance to the DOE Order 4330.4A, to identify needed improvements, and to document the planned maintenance budget for Fiscal Year (FY) 1993 and to estimate maintenance budgets for FY 1994 and FY 1995 for all PNL facilities. Using the results of the self-assessment, PNL has selected 12 of the 36 elements of the Maintenance Program defined by DOE Order 4330.4A, Chapter I, for improvement. The elements selected for improvement are: Facility Condition Inspections; Work Request (Order) System; Formal Job Planning and Estimating; Work Performance (Time) Standards; Priority System; Maintenance Procedures and Other Work-Related Documents; Scheduling System; Post Maintenance Testing; Backlog Work Control; Equipment Repair History and Vendor Information; Work Sampling; and Identification and Control. Based upon a graded approach and current funding, those elements considered most important have been selected as goals for earliest compliance. Commitment dates for these elements have been established for compliance. The remaining elements of noncompliance will be targeted for implementation during later budget periods.

  11. Pacific Northwest Laboratory FY 1993 Site Maintenance Plan for maintenance of DOE nonnuclear facilities

    SciTech Connect

    Bright, J.D.

    1992-09-28

    This Site Maintenance Plan has been developed for Pacific Northwest Laboratory's (PNL) Nonnuclear Facilities. It is based on requirements specified by US Department of Energy (DOE) Order 4330.4A, Chapter I, Change No. 4. The objective of this maintenance plan is to provide baseline information for compliance to the DOE Order 4330.4A, to identify needed improvements, and to document the planned maintenance budget for Fiscal Year (FY) 1993 and to estimate maintenance budgets for FY 1994 and FY 1995 for all PNL facilities. Using the results of the self-assessment, PNL has selected 12 of the 36 elements of the Maintenance Program defined by DOE Order 4330.4A, Chapter I, for improvement. The elements selected for improvement are: Facility Condition Inspections; Work Request (Order) System; Formal Job Planning and Estimating; Work Performance (Time) Standards; Priority System; Maintenance Procedures and Other Work-Related Documents; Scheduling System; Post Maintenance Testing; Backlog Work Control; Equipment Repair History and Vendor Information; Work Sampling; and Identification and Control. Based upon a graded approach and current funding, those elements considered most important have been selected as goals for earliest compliance. Commitment dates for these elements have been established for compliance. The remaining elements of noncompliance will be targeted for implementation during later budget periods.

  12. Operations, Maintenance, and Replacement 10-Year Plan, 1990 -1999.

    SciTech Connect

    United States. Bonneville Power Administration.

    1990-08-01

    In 1988 Bonneville Power Administration (BPA) began work on this Operations, Maintenance, and Replacement 10-Year Plan to develop a levelized program that would assure high system reliability. During the Programs in Perspective (PIP) meetings in the late summer and fall of 1988, many of the concerns to be addressed in an Operations, Maintenance, and Replacement Plan were identified. Following these PIP meetings BPA established internal work groups. During the winter and spring of 1989, these work groups developed technical background and issue papers on topics that ranged from substation maintenance to environmental protection. In addition, a customer forum group was established and met on several occasions to review work on the plan, to offer ideas and points of view, and to assure that BPA understood customer concerns. Based on recommendations from the work group reports and customer input, BPA's O M Management Team developed the draft Operations, Maintenance, and Replacement 10-Year Plan that was released for public comment during the spring of 1990. During the public review period, BPA received a number of written comments from customers and the interested public. In addition, special meetings were held with interested customers. This final Operations, Maintenance, and Replacement 10-Year Plan reflects BPA's response to customers and interested public on each topic discussed in the 10-Year Plan. The plan is a distillation of BPA's strategies to achieve a levelized program over 10 years.

  13. Operations, Maintenance, and Replacement 10-Year Plan, 1990--1999

    SciTech Connect

    Not Available

    1990-08-01

    In 1988 Bonneville Power Administration (BPA) began work on this Operations, Maintenance, and Replacement 10-Year Plan to develop a levelized program that would assure high system reliability. During the Programs in Perspective (PIP) meetings in the later summer and fall of 1988, many of the concerns to be addressed in an Operations, Maintenance, and Replacement Plan were identified. Following these PIP meetings BPA established internal work groups. During the winter and spring of 1989, these work groups developed technical background and issue papers on topics that ranged from substation maintenance to environmental protection. In addition, a customer forum group was established and met on several occasions to review work on the plan, to offer ideas and points of view, and to assure that BPA understood customer concerns. Based on recommendations from the work group reports and customer input, BPA's O M Management Team developed the draft Operations, Maintenance, and Replacement 10-Year Plan that was released for public comment during the spring of 1990. During the public review period, BPA received a number of written comments from customers and the interested public. In addition, special meetings were held with interested customers. This final Operations, Maintenance, and Replacement 10-year Plan reflects BPA's response to customers and interested public on each topic discussed in the 10-Year Plan. The plan is a distillation of BPA's strategies to achieve a levelized program over 10 years.

  14. Waste sampling and characterization facility (WSCF) maintenance implementation plan

    SciTech Connect

    Heinemann, J.L.

    1997-08-13

    This Maintenance Implementation Plan (MIP) is written to satisfy the requirements of the US Department of Energy (DOE) Order 4330.4B, Maintenance Management Program that specifies the general policy and objectives for the establishment of the DOE controlled maintenance programs. These programs provide for the management and performance of cost effective maintenance and repair of the DOE property, which includes facilities. This document outlines maintenance activities associated with the facilities operated by Waste Management Hanford, Inc. (WMH). The objective of this MIP is to provide baseline information for the control and execution of WMH Facility Maintenance activities relative to the requirements of Order 4330.4B, assessment of the WMH maintenance programs, and actions necessary to maintain compliance with the Order. Section 2.0 summarizes the history, mission and description of the WMH facilities. Section 3.0 describes maintenance scope and requirements, and outlines the overall strategy for implementing the maintenance program. Specific elements of DOE Order 4330.4B are addressed in Section 4.0, listing the objective of each element, a discussion of the WMH compliance methodology, and current implementation requirements with references to WMH and HNF policies and procedures. Section 5.0 addresses deviations from policy requirements, and Section 6.0 is a schedule for specific improvements in support of this MIP.

  15. Design of a decision support system for preventive maintenance planning in health structures.

    PubMed

    Miniati, Roberto; Dori, Fabrizio; Gentili, Guido Biffi

    2012-01-01

    The appropriate maintenance of medical devices, including performance inspections and preventive maintenance, is fundamental in mitigating clinical risk caused by adverse events in health care. Although several models for managing and planning preventive maintenance have been developed, the problem is lacking in standard methodology and still presents an open challenge for today's health experts. This paper aims to provide and develop methodology together with support systems able to assist decision makers in constructing preventive maintenance and performance inspection plans, taking into account both the technical and economic needs of hospital clinical engineering departments. Interventions by decision makers are of crucial importance within complex situations where large numbers, types of devices and different contractual situations are involved. SISMA system has achieved optimal results with minimum expense and maximum security for patients and technicians at the University Hospital of Florence where it has been applied in actual case studies. PMID:22735735

  16. Future NSMO plans for maintenance of NASTRAN

    NASA Technical Reports Server (NTRS)

    Weidman, D. J.

    1973-01-01

    The objectives of the NASTRAN computer program system are discussed. Specific reference is made to the use of NASTRAN in the space shuttle program. The use of NASTRAN by agencies other than NASA is reported. The subjects presented are: (1) planned developments, (2) capability improvements, (3) efficiency improvements, and (4) new error correction procedure.

  17. Airline Maintenance Manpower Optimization from the De Novo Perspective

    NASA Astrophysics Data System (ADS)

    Liou, James J. H.; Tzeng, Gwo-Hshiung

    Human resource management (HRM) is an important issue for today’s competitive airline marketing. In this paper, we discuss a multi-objective model designed from the De Novo perspective to help airlines optimize their maintenance manpower portfolio. The effectiveness of the model and solution algorithm is demonstrated in an empirical study of the optimization of the human resources needed for airline line maintenance. Both De Novo and traditional multiple objective programming (MOP) methods are analyzed. A comparison of the results with those of traditional MOP indicates that the proposed model and solution algorithm does provide better performance and an improved human resource portfolio.

  18. Optimal maintenance of a multi-unit system under dependencies

    NASA Astrophysics Data System (ADS)

    Sung, Ho-Joon

    The availability, or reliability, of an engineering component greatly influences the operational cost and safety characteristics of a modern system over its life-cycle. Until recently, the reliance on past empirical data has been the industry-standard practice to develop maintenance policies that provide the minimum level of system reliability. Because such empirically-derived policies are vulnerable to unforeseen or fast-changing external factors, recent advancements in the study of topic on maintenance, which is known as optimal maintenance problem, has gained considerable interest as a legitimate area of research. An extensive body of applicable work is available, ranging from those concerned with identifying maintenance policies aimed at providing required system availability at minimum possible cost, to topics on imperfect maintenance of multi-unit system under dependencies. Nonetheless, these existing mathematical approaches to solve for optimal maintenance policies must be treated with caution when considered for broader applications, as they are accompanied by specialized treatments to ease the mathematical derivation of unknown functions in both objective function and constraint for a given optimal maintenance problem. These unknown functions are defined as reliability measures in this thesis, and theses measures (e.g., expected number of failures, system renewal cycle, expected system up time, etc.) do not often lend themselves to possess closed-form formulas. It is thus quite common to impose simplifying assumptions on input probability distributions of components' lifetime or repair policies. Simplifying the complex structure of a multi-unit system to a k-out-of-n system by neglecting any sources of dependencies is another commonly practiced technique intended to increase the mathematical tractability of a particular model. This dissertation presents a proposal for an alternative methodology to solve optimal maintenance problems by aiming to achieve the

  19. Draft 1992 : Operations, Maintenance, and Replacement 10-Year Plan.

    SciTech Connect

    United States. Bonneville Power Administration.

    1992-05-01

    Two years ago, BPA released its first-ever Operations, Maintenance, and Replacement (OM&R) 10-Year Plan. That effort broke new ground and was an extensive look at the condition of Operations, Maintenance, and Replacement on BPA`s power system. This document -- the 1992 OM&R 10-Year Plan -- uses that original plan as its foundation. It takes a look at how well BPA has accomplished the challenging task set out in the 1990 Plan. The 1992 Plan also introduces the Construction Program. Construction`s critical role in these programs is explored, and the pressures of construction workload -- such as the seasonal nature of the work and the broad swings in workload between projects and years -- are discussed. The document then looks at how situations may have changed with issues explored initially in the 1990 Plan. Importantly, this Plan also surfaces and explains some new issues that threaten to impact BPA`s ability to accomplish its OM&R workload. Finally, the document focuses on the revised strategies for Operations, Maintenance, Replacement, Construction, and Environment for the 1992 to 2001 time period, including the financial and human resources needed to accomplish those strategies.

  20. A Planned Preventive Maintenance Program. A Handbook for Chief Business Officers and Supervisors of Maintenance with Suggestions on Maintenance for Consideration by Presidents of Higher Institutions.

    ERIC Educational Resources Information Center

    Daniel, Clarence H.

    This handbook explains planned preventive maintenance program, which is an operational system of maintenance designed to increase the effectiveness of the maintenance staff and the use of maintenance funds through efficient scheduling of inspections and follow-through of work to be performed. Sections are included for the chief administrative…

  1. Habitat planning, maintenance and management working group

    SciTech Connect

    1997-03-01

    The Gulf of Mexico (GOM), called {open_quotes}America`s Sea,{close_quotes} is actually a small ocean basin covering over 1.5 million square kilometers. Because of the multiple uses, diversity, and size of the Gulf`s resources, management is shared by a number of governmental agencies including the Minerals Management Service, the Gulf of Mexico Fishery Management Council, the Gulf States Marine Fisheries Commission, National Marine Fisheries Service, the US Coast Guard, the US Army Corps of Engineers, and the five Gulf states fisheries agencies. All of these entities share a common goal of achieving optimum sustainable yield to maximize geological, biological, social, and economic benefits from these resources. These entities also share a common theme that the successful management of the northern GOM requires maintenance and enhancement of both the quantity and quality of habitats. A closer look at the GOM shows the sediment to be clearly dominated by vast sand and mud plains. These soft bottom habitats are preferred by many groundfish and shrimp species and, thus, have given rise to large commercial fisheries on these stocks. Hard bottom and reef habitats, on the other hand, are limited to approximately 1.6% of the total area of the Gulf, so that, while there are high demands by commercial and recreational fishermen for reef associated species, the availability of habitat for these stocks is limited. The thousands of oil and gas structures placed in the Gulf have added significant amounts of new hard substrate. The rigs-to-reefs concept was a common sense idea with support from environmental user groups and the petroleum industry for preserving a limited but valuable habitat type. As long as maximizing long-term benefits from the Gulf s resources for the greatest number of users remains the goal, then programs such as Rigs-to-Reefs will remain an important tool for fisheries and habitat managers in the Gulf.

  2. Risk Analysis for Resource Planning Optimization

    NASA Technical Reports Server (NTRS)

    Cheung, Kar-Ming

    2008-01-01

    This paper describes a systems engineering approach to resource planning by integrating mathematical modeling and constrained optimization, empirical simulation, and theoretical analysis techniques to generate an optimal task plan in the presence of uncertainties.

  3. 40 CFR 52.975 - Redesignations and maintenance plans; ozone.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ...; ozone. 52.975 Section 52.975 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... and maintenance plans; ozone. Link to an amendment published at 78 FR 27062, May 9, 2013. (a) Approval..., however. The LDEQ addressed these approvability issues in supplemental ozone redesignation requests...

  4. Starting a Planned Maintenance Program on a Shoestring

    ERIC Educational Resources Information Center

    Adams, Matt

    2013-01-01

    This article addresses two of the most repeated questions in APPA (1) How can we convert our reactive maintenance operations to a planned and predictable operation? and (2) In addition, how can we do this with little or no additional resources? It seems reasonable to assume that if a department is short on resources and in a full-blown reactive…

  5. Maintenance implementation plan for the Plutonium Finishing Plant. Revision 3

    SciTech Connect

    Meldrom, C.A.

    1996-03-01

    This document outlines the Maintenance Implementation Plan (MIP) for the Plutonium Finishing Plant (PFP) located at the Hanford site at Richland, Washington. This MIP describes the PFP maintenance program relative to DOE order 4330.4B. The MIP defines the key actions needed to meet the guidelines of the Order to produce a cost-effective and efficient maintenance program. A previous report identified the presence of significant quantities of Pu-bearing materials within PFP that pose risks to workers. PFP`s current mission is to develop, install and operate processes which will mitigate these risks. The PFP Maintenance strategy is to equip the facility with systems and equipment able to sustain scheduled PFP operations. The current operating run is scheduled to last seven years. Activities following the stabilization operation will involve an Environmental Impact Statement (EIS) to determine future plant activities. This strategy includes long-term maintenance of the facility for safe occupancy and material storage. The PFP maintenance staff used the graded approach to dictate the priorities of the improvement and upgrade actions identified in Chapter 2 of this document. The MIP documents PFP compliance to the DOE 4330.4B Order. Chapter 2 of the MIP follows the format of the Order in addressing the eighteen elements. As this revision is a total rewrite, no sidebars are included to highlight changes.

  6. 78 FR 59242 - Approval and Promulgation of Air Quality Implementation Plans; Utah; Maintenance Plan for the...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-09-26

    ... AGENCY 40 CFR Part 52 Approval and Promulgation of Air Quality Implementation Plans; Utah; Maintenance...: Degreasing and Solvent Cleaning Operations;'' R307- 340, ``Ozone Nonattainment and Maintenance Areas: Surface... 110 of the Clean Air Act (Act or CAA). DATES: This action is effective on October 28, 2013....

  7. Maintenance implementation plan for the Fast Flux Test Facility

    SciTech Connect

    Boyd, J.A.

    1997-01-30

    This plan implements the U.S. Department of Energy (DOE) 4330.4B, Maintenance Management Program (1994), at the Fast Flux Test Facility (FFTF). The FFTF is a research and test reactor located near Richland, Washington, and is operated under contract for the DOE by the B&W Hanford Company (BWHC). The intent of this Maintenance Implementation Plan (MIP) is to describe the manner in which the activities of the maintenance function are executed and controlled at the FFTF and how this compares to the requirements of DOE 4330.4B. The MIP ii a living document that is updated through a Facility Maintenance Self- Assessment Program. During the continuing self-assessment program, any discrepancies found are resolved to meet DOE 4330.4B requirements and existing practices. The philosophy of maintenance management at the FFTF is also describe within this MIP. This MIP has been developed based on information obtained from various sources including the following: * A continuing self-assessment against the requirements of the Conduct of Maintenance Order * In-depth reviews conducted by the members of the task team that assembled this MIP * Inputs from routine audits and appraisals conducted at the facility The information from these sources is used to identify those areas in which improvements could be made in the manner in which the facility conducts maintenance activities. The action items identified in Rev. 1 of the MIP have been completed. The MIP is arranged in six sections. Section I is this Executive Summary. Section 2 describes the facility and its 0683 history. Section 3 describes the philosophy of the graded approach and how it is applied at FFTF. Section 3 also discusses the strategy and the basis for the prioritizing resources. Section 4 contains the detailed discussion of `the elements of DOE 4330.4B and their state of implementation. Section 5 is for waivers and requested deviations from the requirements of the order. Section 6 contains a copy of the Maintenance

  8. An optimization framework for interdependent planning goals

    NASA Technical Reports Server (NTRS)

    Estlin, T. A.; Gaines, D. M.

    2002-01-01

    This paper describes an approach for optimizing over interdependent planning goals. We have implemented a methodology for representing and utilizing information about interdependent goals and their related utilities using the ASPEN planning and scheduling system.

  9. Building 9401-2 Plating Shop Surveillance and Maintenance Plan

    SciTech Connect

    1999-05-01

    This document provides a plan for implementing surveillance and maintenance (S and M) activities to ensure that Building 9401-2 Plating Shop is maintained in a cost effective and environmentally secure configuration until subsequent closure during the final disposition phase of decommissioning. U.S. Department of Energy (DOE) G430.1A-2, Surveillance and Maintenance During Facility Disposition (1997), was used as guidance in the development of this plan. The S and M Plan incorporates DOE O 430.1A, Life Cycle Asset Management (LCAM) (1998a) direction to provide for conducting surveillance and maintenance activities required to maintain the facility and remaining hazardous and radioactive materials, wastes, and contamination in a stable and known condition pending facility disposition. Recommendations in the S and M plan have been made that may not be requirement-based but would reduce the cost and frequency of surveillance and maintenance activities. During the course of S and M activities, the facility's condition may change so as to present an immediate or developing hazard or unsatisfactory condition. Corrective action should be coordinated with the appropriate support organizations using the requirements and guidance stated in procedure Y10-202, Rev. 1, Integrated Safety Management Program, (Lockheed Martin Energy Systems, Inc. (LMES), 1998a) implemented at the Oak Ridge Y-12 Plant and the methodology of the Nuclear Operations Conduct of Operations Manual (LMES, 1999) for the Depleted Uranium Operations (DUO) organization. The key S and M objectives applicable to the Plating Shop are to: Ensure adequate containment of remaining residual material in exhaust stacks and outside process piping, stored chemicals awaiting offsite shipment, and items located in the Radioactive Material Area (RMA); Provide access control into the facility and physical safety to S and M personnel; Maintain the facility in a manner that will protect the public, the environment, and the S

  10. Two-machine flow shop scheduling integrated with preventive maintenance planning

    NASA Astrophysics Data System (ADS)

    Wang, Shijin; Liu, Ming

    2016-02-01

    This paper investigates an integrated optimisation problem of production scheduling and preventive maintenance (PM) in a two-machine flow shop with time to failure of each machine subject to a Weibull probability distribution. The objective is to find the optimal job sequence and the optimal PM decisions before each job such that the expected makespan is minimised. To investigate the value of integrated scheduling solution, computational experiments on small-scale problems with different configurations are conducted with total enumeration method, and the results are compared with those of scheduling without maintenance but with machine degradation, and individual job scheduling combined with independent PM planning. Then, for large-scale problems, four genetic algorithm (GA) based heuristics are proposed. The numerical results with several large problem sizes and different configurations indicate the potential benefits of integrated scheduling solution and the results also show that proposed GA-based heuristics are efficient for the integrated problem.

  11. [Improved program maintenance of the CIRCIS dosimetric planning system].

    PubMed

    Sevast'ianov, A I; Liutova, N A; Ratner, T G

    1983-03-01

    A special computer complex CIRCIS (Informatique, France) is used in the All-Union Cancer Research Center, USSR AMS, for the dosimetric planning of radiotherapy on 5 gamma-beam units and electron accelerator. Mathematical maintenance of the complex includes programs of the calculation of dose distribution for gamma-, inhibition and electron radiation but has no program of the calculation of the time of irradiation. The authors have devised and introduced into the complex such a program in the Fortran language that makes it possible to calculate within 2-3 min the time of irradiation for multifield rotation therapy using several units as a time, thus expediting the dosimetric planning for patients' irradiation.

  12. On the preventive management of sediment-related sewer blockages: a combined maintenance and routing optimization approach.

    PubMed

    Fontecha, John E; Akhavan-Tabatabaei, Raha; Duque, Daniel; Medaglia, Andrés L; Torres, María N; Rodríguez, Juan Pablo

    2016-01-01

    In this work we tackle the problem of planning and scheduling preventive maintenance (PM) of sediment-related sewer blockages in a set of geographically distributed sites that are subject to non-deterministic failures. To solve the problem, we extend a combined maintenance and routing (CMR) optimization approach which is a procedure based on two components: (a) first a maintenance model is used to determine the optimal time to perform PM operations for each site and second (b) a mixed integer program-based split procedure is proposed to route a set of crews (e.g., sewer cleaners, vehicles equipped with winches or rods and dump trucks) in order to perform PM operations at a near-optimal minimum expected cost. We applied the proposed CMR optimization approach to two (out of five) operative zones in the city of Bogotá (Colombia), where more than 100 maintenance operations per zone must be scheduled on a weekly basis. Comparing the CMR against the current maintenance plan, we obtained more than 50% of cost savings in 90% of the sites.

  13. On the preventive management of sediment-related sewer blockages: a combined maintenance and routing optimization approach.

    PubMed

    Fontecha, John E; Akhavan-Tabatabaei, Raha; Duque, Daniel; Medaglia, Andrés L; Torres, María N; Rodríguez, Juan Pablo

    2016-01-01

    In this work we tackle the problem of planning and scheduling preventive maintenance (PM) of sediment-related sewer blockages in a set of geographically distributed sites that are subject to non-deterministic failures. To solve the problem, we extend a combined maintenance and routing (CMR) optimization approach which is a procedure based on two components: (a) first a maintenance model is used to determine the optimal time to perform PM operations for each site and second (b) a mixed integer program-based split procedure is proposed to route a set of crews (e.g., sewer cleaners, vehicles equipped with winches or rods and dump trucks) in order to perform PM operations at a near-optimal minimum expected cost. We applied the proposed CMR optimization approach to two (out of five) operative zones in the city of Bogotá (Colombia), where more than 100 maintenance operations per zone must be scheduled on a weekly basis. Comparing the CMR against the current maintenance plan, we obtained more than 50% of cost savings in 90% of the sites. PMID:27438233

  14. Y-12 Groundwater Protection Program Monitoring Well Inspection and Maintenance Plan

    SciTech Connect

    2006-12-01

    This document is the third revision of the 'Monitoring Well Inspection and Maintenance Plan' for groundwater wells associated with the US Department of Energy (DOE) Y-12 National Security Complex (Y-12) in Oak Ridge, Tennessee. This plan describes the systematic approach for: (1) inspecting the physical condition of monitoring wells at Y-12; (2) identifying maintenance needs that extend the life of the well and assure well-head protection is in place, and (3) identifying wells that no longer meet acceptable monitoring-well design or well construction standards and require plugging and abandonment. The inspection and maintenance of groundwater monitoring wells is one of the primary management strategies of the Y-12 Groundwater Protection Program (GWPP) Management Plan, 'proactive stewardship of the extensive monitoring well network at Y-12' (BWXT 2004a). Effective stewardship, and a program of routine inspections of the physical condition of each monitoring well, ensures that representative water-quality monitoring and hydrologic data are able to be obtained from the well network. In accordance with the Y-12 GWPP Monitoring Optimization Plan (MOP) for Groundwater Monitoring Wells at the Y-12 National Security Complex, Oak Ridge, Tennessee (BWXT 2006b), the status designation (active or inactive) for each well determines the scope and extent of well inspections and maintenance activities. This plan, in conjunction with the above document, formalizes the GWPP approach to focus available resources on monitoring wells which provide the most useful data. This plan applies to groundwater monitoring wells associated with Y-12 and related waste management facilities located within the three hydrogeologic regimes: (1) the Bear Creek Hydrogeologic Regime (Bear Creek Regime); (2) the Upper East Fork Poplar Creek Hydrogeologic Regime (East Fork Regime); and (3) the Chestnut Ridge Hydrogeologic Regime (Chestnut Ridge Regime). The Bear Creek Regime encompasses a section of the

  15. Software for Optimizing Plans Involving Interdependent Goals

    NASA Technical Reports Server (NTRS)

    Estlin, Tara; Gaines, Daniel; Rabideau, Gregg

    2005-01-01

    A computer program enables construction and optimization of plans for activities that are directed toward achievement of goals that are interdependent. Goal interdependence is defined as the achievement of one or more goals affecting the desirability or priority of achieving one or more other goals. This program is overlaid on the Automated Scheduling and Planning Environment (ASPEN) software system, aspects of which have been described in a number of prior NASA Tech Briefs articles. Unlike other known or related planning programs, this program considers interdependences among goals that can change between problems and provides a language for easily specifying such dependences. Specifications of the interdependences can be formulated dynamically and provided to the associated planning software as part of the goal input. Then an optimization algorithm provided by this program enables the planning software to reason about the interdependences and incorporate them into an overall objective function that it uses to rate the quality of a plan under construction and to direct its optimization search. In tests on a series of problems of planning geological experiments by a team of instrumented robotic vehicles (rovers) on new terrain, this program was found to enhance plan quality.

  16. A comparative evaluation plan for the Maintenance, Inventory, and Logistics Planning (MILP) System Human-Computer Interface (HCI)

    NASA Technical Reports Server (NTRS)

    Overmyer, Scott P.

    1993-01-01

    The primary goal of this project was to develop a tailored and effective approach to the design and evaluation of the human-computer interface (HCI) to the Maintenance, Inventory and Logistics Planning (MILP) System in support of the Mission Operations Directorate (MOD). An additional task that was undertaken was to assist in the review of Ground Displays for Space Station Freedom (SSF) by attending the Ground Displays Interface Group (GDIG), and commenting on the preliminary design for these displays. Based upon data gathered over the 10 week period, this project has hypothesized that the proper HCI concept for navigating through maintenance databases for large space vehicles is one based upon a spatial, direct manipulation approach. This dialogue style can be then coupled with a traditional text-based DBMS, after the user has determined the general nature and location of the information needed. This conclusion is in contrast with the currently planned HCI for MILP which uses a traditional form-fill-in dialogue style for all data access and retrieval. In order to resolve this difference in HCI and dialogue styles, it is recommended that comparative evaluation be performed which combines the use of both subjective and objective metrics to determine the optimal (performance-wise) and preferred approach for end users. The proposed plan has been outlined in the previous paragraphs and is available in its entirety in the Technical Report associated with this project. Further, it is suggested that several of the more useful features of the Maintenance Operations Management System (MOMS), especially those developed by the end-users, be incorporated into MILP to save development time and money.

  17. Risk management and maintenance optimization of nuclear reactor cooling piping system

    NASA Astrophysics Data System (ADS)

    Augé, L.; Capra, B.; Lasne, M.; Bernard, O.; Bénéfice, P.; Comby, R.

    2006-11-01

    Seaside nuclear power plants have to face the ageing of nuclear reactor cooling piping systems. In order to minimize the duration of the production unit shutdown, maintenance operations have to be planned well in advance. In a context where owners of infrastructures tend to extend the life span of their goods while having to keep the safety level maximum, Oxand brings its expertise and know-how in management of infrastructures life cycle. A dedicated methodology relies on several modules that all participate in fixing network optimum replacement dates: expertise on ageing mechanisms (corrosion, cement degradation...) and the associated kinetics, expertise on impacts of ageing on functional integrity of piping systems, predictive simulation based on experience feedback, development of monitoring techniques focused on actual threats. More precisely, Oxand has designed a patented monitoring technique based on optic fiber sensors, which aims at controlling the deterioration level of piping systems. This preventive maintenance enables the owner to determine criteria for network replacement based on degradation impacts. This approach helps the owner justify his maintenance strategy and allows him to demonstrate the management of safety level. More generally, all monitoring techniques used by the owners are developed and coupled to predictive simulation tools, notably thanks to processes based on Bayesian approaches. Methodologies to evaluate and optimize operation budgets, depending on predictions of future functional deterioration and available maintenance solutions are also developed and applied. Finally, all information related to infrastructure ageing and available maintenance options are put together to reach the right solution for safe and performing infrastructure management.

  18. 77 FR 8252 - Adequacy Status of the Anchorage, Alaska, Carbon Monoxide Maintenance Plan for Transportation...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-02-14

    ... AGENCY Adequacy Status of the Anchorage, Alaska, Carbon Monoxide Maintenance Plan for Transportation... budget (MVEB) in the Anchorage, Alaska, Carbon Monoxide (CO) Maintenance Plan, submitted by the State of... notice of EPA's adequacy finding regarding the motor vehicle emissions budget (MVEB) in the...

  19. Risk Analysis for Resource Planning Optimization

    NASA Technical Reports Server (NTRS)

    Chueng, Kar-Ming

    2008-01-01

    The main purpose of this paper is to introduce a risk management approach that allows planners to quantify the risk and efficiency tradeoff in the presence of uncertainties, and to make forward-looking choices in the development and execution of the plan. Demonstrate a planning and risk analysis framework that tightly integrates mathematical optimization, empirical simulation, and theoretical analysis techniques to solve complex problems.

  20. Helicopter trajectory planning using optimal control theory

    NASA Technical Reports Server (NTRS)

    Menon, P. K. A.; Cheng, V. H. L.; Kim, E.

    1988-01-01

    A methodology for optimal trajectory planning, useful in the nap-of-the-earth guidance of helicopters, is presented. This approach uses an adjoint-control transformation along with a one-dimensional search scheme for generating the optimal trajectories. In addition to being useful for helicopter nap-of-the-earth guidance, the trajectory planning solution is of interest in several other contexts, such as robotic vehicle guidance and terrain-following guidance for cruise missiles and aircraft. A distinguishing feature of the present research is that the terrain constraint and the threat envelopes are incorporated in the equations of motion. Second-order necessary conditions are examined.

  1. Monitoring Strategies in Permeable Pavement Systems to Optimize Maintenance Scheduling

    EPA Science Inventory

    As the surface in a permeable pavement system clogs and performance decreases, maintenance is required to preserve the design function. Currently, guidance is limited for scheduling maintenance on an as needed basis. Previous research has shown that surface clogging in a permea...

  2. Optimization approaches for planning external beam radiotherapy

    NASA Astrophysics Data System (ADS)

    Gozbasi, Halil Ozan

    Cancer begins when cells grow out of control as a result of damage to their DNA. These abnormal cells can invade healthy tissue and form tumors in various parts of the body. Chemotherapy, immunotherapy, surgery and radiotherapy are the most common treatment methods for cancer. According to American Cancer Society about half of the cancer patients receive a form of radiation therapy at some stage. External beam radiotherapy is delivered from outside the body and aimed at cancer cells to damage their DNA making them unable to divide and reproduce. The beams travel through the body and may damage nearby healthy tissue unless carefully planned. Therefore, the goal of treatment plan optimization is to find the best system parameters to deliver sufficient dose to target structures while avoiding damage to healthy tissue. This thesis investigates optimization approaches for two external beam radiation therapy techniques: Intensity-Modulated Radiation Therapy (IMRT) and Volumetric-Modulated Arc Therapy (VMAT). We develop automated treatment planning technology for IMRT that produces several high-quality treatment plans satisfying provided clinical requirements in a single invocation and without human guidance. A novel bi-criteria scoring based beam selection algorithm is part of the planning system and produces better plans compared to those produced using a well-known scoring-based algorithm. Our algorithm is very efficient and finds the beam configuration at least ten times faster than an exact integer programming approach. Solution times range from 2 minutes to 15 minutes which is clinically acceptable. With certain cancers, especially lung cancer, a patient's anatomy changes during treatment. These anatomical changes need to be considered in treatment planning. Fortunately, recent advances in imaging technology can provide multiple images of the treatment region taken at different points of the breathing cycle, and deformable image registration algorithms can

  3. Optimizing Motion Planning for Hyper Dynamic Manipulator

    NASA Astrophysics Data System (ADS)

    Aboura, Souhila; Omari, Abdelhafid; Meguenni, Kadda Zemalache

    2012-01-01

    This paper investigates the optimal motion planning for an hyper dynamic manipulator. As case study, we consider a golf swing robot which is consisting with two actuated joint and a mechanical stoppers. Genetic Algorithm (GA) technique is proposed to solve the optimal golf swing motion which is generated by Fourier series approximation. The objective function for GA approach is to minimizing the intermediate and final state, minimizing the robot's energy consummation and maximizing the robot's speed. Obtained simulation results show the effectiveness of the proposed scheme.

  4. Discrepancies between selected Pareto optimal plans and final deliverable plans in radiotherapy multi-criteria optimization.

    PubMed

    Kyroudi, Archonteia; Petersson, Kristoffer; Ghandour, Sarah; Pachoud, Marc; Matzinger, Oscar; Ozsahin, Mahmut; Bourhis, Jean; Bochud, François; Moeckli, Raphaël

    2016-08-01

    Multi-criteria optimization provides decision makers with a range of clinical choices through Pareto plans that can be explored during real time navigation and then converted into deliverable plans. Our study shows that dosimetric differences can arise between the two steps, which could compromise the clinical choices made during navigation.

  5. 40 CFR 52.2043 - Control strategy for maintenance plans: ozone.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ...: ozone. 52.2043 Section 52.2043 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR... Control strategy for maintenance plans: ozone. (a) As of December 26, 2013, EPA approves the following... (VOCs) for the Lancaster 1997 8-Hour Ozone Maintenance Area submitted by the Secretary of...

  6. 77 FR 58058 - Approval and Promulgation of Implementation Plans; Texas; Beaumont/Port Arthur Ozone Maintenance...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-09-19

    ... preempt tribal law. List of Subjects in 40 CFR Part 52 Environmental protection, Air pollution control... From the Federal Register Online via the Government Publishing Office ENVIRONMENTAL PROTECTION... Ozone Maintenance Plan Revision to Approved Motor Vehicle Emissions Budgets AGENCY:...

  7. GPU-based ultrafast IMRT plan optimization

    NASA Astrophysics Data System (ADS)

    Men, Chunhua; Gu, Xuejun; Choi, Dongju; Majumdar, Amitava; Zheng, Ziyi; Mueller, Klaus; Jiang, Steve B.

    2009-11-01

    The widespread adoption of on-board volumetric imaging in cancer radiotherapy has stimulated research efforts to develop online adaptive radiotherapy techniques to handle the inter-fraction variation of the patient's geometry. Such efforts face major technical challenges to perform treatment planning in real time. To overcome this challenge, we are developing a supercomputing online re-planning environment (SCORE) at the University of California, San Diego (UCSD). As part of the SCORE project, this paper presents our work on the implementation of an intensity-modulated radiation therapy (IMRT) optimization algorithm on graphics processing units (GPUs). We adopt a penalty-based quadratic optimization model, which is solved by using a gradient projection method with Armijo's line search rule. Our optimization algorithm has been implemented in CUDA for parallel GPU computing as well as in C for serial CPU computing for comparison purpose. A prostate IMRT case with various beamlet and voxel sizes was used to evaluate our implementation. On an NVIDIA Tesla C1060 GPU card, we have achieved speedup factors of 20-40 without losing accuracy, compared to the results from an Intel Xeon 2.27 GHz CPU. For a specific nine-field prostate IMRT case with 5 × 5 mm2 beamlet size and 2.5 × 2.5 × 2.5 mm3 voxel size, our GPU implementation takes only 2.8 s to generate an optimal IMRT plan. Our work has therefore solved a major problem in developing online re-planning technologies for adaptive radiotherapy.

  8. The optimal planning computerized manufacturing systems

    NASA Astrophysics Data System (ADS)

    Neuts, M. F.; Lucanton, D. M.; Geiszler, C.

    1981-02-01

    The utility of interactive computation in answering questions on the behavior, design, and control of certain service systems is demonstrated. The stationary distributions of various waiting times are also discussed. A queue with N servers which may break down and require repair at a facility which has C repair crews is studied. Under exponential assumptions, this model has an algorithmically tractable solution. It is then a particular case of the M/M/n queue in a Markovian environment. It is shown that during periods when most servers are down, large build-ups may occur which affect the queue adversely for a long time afterwards. Potential applications are in manpower planning, as in a typing pool where persons may be absent, and in determining the size of a battery of machines, where machines may be inoperative due to maintenance and repair.

  9. A Minimum Delta V Orbit Maintenance Strategy for Low-Altitude Missions Using Burn Parameter Optimization

    NASA Technical Reports Server (NTRS)

    Brown, Aaron J.

    2011-01-01

    Orbit maintenance is the series of burns performed during a mission to ensure the orbit satisfies mission constraints. Low-altitude missions often require non-trivial orbit maintenance Delta V due to sizable orbital perturbations and minimum altitude thresholds. A strategy is presented for minimizing this Delta V using impulsive burn parameter optimization. An initial estimate for the burn parameters is generated by considering a feasible solution to the orbit maintenance problem. An low-lunar orbit example demonstrates the Delta V savings from the feasible solution to the optimal solution. The strategy s extensibility to more complex missions is discussed, as well as the limitations of its use.

  10. 78 FR 17197 - Adequacy Status of Motor Vehicle Emissions Budgets in Submitted Ozone Maintenance Plan for San...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-03-20

    ... AGENCY Adequacy Status of Motor Vehicle Emissions Budgets in Submitted Ozone Maintenance Plan for San... emissions budgets (MVEBs) for ozone for the years 2020 and 2025 in the Redesignation Request and Maintenance... Redesignation Request and Maintenance Plan'') are adequate for transportation conformity purposes. The San...

  11. Y-12 Groundwater Protection Program Monitoring Well Inspection and Maintenance Plan

    SciTech Connect

    2013-09-01

    This document is the fourth revision of the Monitoring Well Inspection and Maintenance Plan for groundwater monitoring wells installed at the U.S. Department of Energy (DOE) Y-12 National Security Complex (Y-12) in Oak Ridge, Tennessee. This plan describes the systematic approach for: inspecting the physical condition of monitoring wells at Y-12, determining maintenance needs that extend the life of a well, and identifying those wells that no longer meet acceptable monitoring well design or well construction standards and require plugging and abandonment. This plan applies to groundwater monitoring wells installed at Y-12 and the related waste management facilities located within the three hydrogeologic regimes.

  12. Optimal Planning and Problem-Solving

    NASA Technical Reports Server (NTRS)

    Clemet, Bradley; Schaffer, Steven; Rabideau, Gregg

    2008-01-01

    CTAEMS MDP Optimal Planner is a problem-solving software designed to command a single spacecraft/rover, or a team of spacecraft/rovers, to perform the best action possible at all times according to an abstract model of the spacecraft/rover and its environment. It also may be useful in solving logistical problems encountered in commercial applications such as shipping and manufacturing. The planner reasons around uncertainty according to specified probabilities of outcomes using a plan hierarchy to avoid exploring certain kinds of suboptimal actions. Also, planned actions are calculated as the state-action space is expanded, rather than afterward, to reduce by an order of magnitude the processing time and memory used. The software solves planning problems with actions that can execute concurrently, that have uncertain duration and quality, and that have functional dependencies on others that affect quality. These problems are modeled in a hierarchical planning language called C_TAEMS, a derivative of the TAEMS language for specifying domains for the DARPA Coordinators program. In realistic environments, actions often have uncertain outcomes and can have complex relationships with other tasks. The planner approaches problems by considering all possible actions that may be taken from any state reachable from a given, initial state, and from within the constraints of a given task hierarchy that specifies what tasks may be performed by which team member.

  13. Monitoring well inspection and maintenance plan Y-12 Plant, Oak Ridge, Tennessee (revised)

    SciTech Connect

    1996-09-01

    Inspection and maintenance of groundwater monitoring wells is a primary element of the Oak Ridge Y-12 Plant Groundwater Protection Program (GWPP). This document is the revised groundwater monitoring well inspection and maintenance plan for the U.S. Department of Energy (DOE) Y-12 Plant in Oak Ridge, Tennessee. The plan provides a systematic program for: (1) inspecting the physical condition of monitoring wells at the Y-12 Plant and (2) identifying maintenance needs that will extend the life of each well and ensure that representative groundwater quality samples and hydrologic data are collected from the wells. Original documentation for the Y-12 Plant GWPP monitoring well inspection and maintenance program was provided in HSW, Inc. 1991a. The original revision of the plan specified that only a Monitoring Well Inspection/Maintenance Summary need be updated and reissued each year. Rapid growth of the monitoring well network and changing regulatory requirements have resulted in constant changes to the status of wells (active or inactive) listed on the Monitoring Well Inspection/Maintenance Summary. As a result, a new mechanism to track the status of monitoring wells has been developed and the plan revised to formalize the new business practices. These changes are detailed in Sections 2.4 and 2.5.

  14. Optimization approaches to volumetric modulated arc therapy planning

    SciTech Connect

    Unkelbach, Jan Bortfeld, Thomas; Craft, David; Alber, Markus; Bangert, Mark; Bokrantz, Rasmus; Chen, Danny; Li, Ruijiang; Xing, Lei; Men, Chunhua; Nill, Simeon; Papp, Dávid; Romeijn, Edwin; Salari, Ehsan

    2015-03-15

    Volumetric modulated arc therapy (VMAT) has found widespread clinical application in recent years. A large number of treatment planning studies have evaluated the potential for VMAT for different disease sites based on the currently available commercial implementations of VMAT planning. In contrast, literature on the underlying mathematical optimization methods used in treatment planning is scarce. VMAT planning represents a challenging large scale optimization problem. In contrast to fluence map optimization in intensity-modulated radiotherapy planning for static beams, VMAT planning represents a nonconvex optimization problem. In this paper, the authors review the state-of-the-art in VMAT planning from an algorithmic perspective. Different approaches to VMAT optimization, including arc sequencing methods, extensions of direct aperture optimization, and direct optimization of leaf trajectories are reviewed. Their advantages and limitations are outlined and recommendations for improvements are discussed.

  15. Iraq liquid radioactive waste tanks maintenance and monitoring program plan.

    SciTech Connect

    Dennis, Matthew L.; Cochran, John Russell; Sol Shamsaldin, Emad

    2011-10-01

    The purpose of this report is to develop a project management plan for maintaining and monitoring liquid radioactive waste tanks at Iraq's Al-Tuwaitha Nuclear Research Center. Based on information from several sources, the Al-Tuwaitha site has approximately 30 waste tanks that contain varying amounts of liquid or sludge radioactive waste. All of the tanks have been non-operational for over 20 years and most have limited characterization. The program plan embodied in this document provides guidance on conducting radiological surveys, posting radiation control areas and controlling access, performing tank hazard assessments to remove debris and gain access, and conducting routine tank inspections. This program plan provides general advice on how to sample and characterize tank contents, and how to prioritize tanks for soil sampling and borehole monitoring.

  16. Health maintenance organizations; Midwest Health Plan--Health Resources and Services Administration.

    PubMed

    1983-04-26

    On January 21, 1983, the Office of Health Maintenance Organizations (OHMO) notified Midwest Health Plan (MHP), 3415 Bridgeland Drive, Bridgeton, Missouri 63044, a federally qualified health maintenance organization (HMO), that MHP had successfully reestablished compliance with its assurances to the Secretary that it would (1) maintain a fiscally sound operation, and (2) maintain satisfactory administrative and managerial arrangements. This determination took effect on January 1, 1983. PMID:10324428

  17. Contribution to the Optimization of Strategy of Maintenance by Lean Six Sigma

    NASA Astrophysics Data System (ADS)

    Youssouf, Ayadi; Rachid, Chaib; Ion, Verzea

    The efficiency of the maintenance of the industrial systems is a major economic stake for their business concern. The main difficulties and the sources of ineffectiveness live in the choice of the actions of maintenance especially when the machine plays a vital role in the process of production. But as Algeria has embarked on major infrastructure projects in transport, housing, automobile, manufacturing industry and construction (factories, housing, highway, subway, tram, etc.) requiring new implications on maintenance strategies that meet industry requirements imposed by the exploitation. From then on and seen the importance of the maintenance on the economic market and sound impacts on the performances of the installations, methods of optimization were developed. For this purpose, to ensure the survival of businesses, be credible, contributing and competitive in the market, maintenance services must continually adapt to the progress of technical areas, technological and organizational even help maintenance managers to construct or to modify maintenance strategies, objective of this work. Our contribution in this work focuses on the optimization of maintenance for industrial systems by the use of Lean six Sigma bases. Lean Six Sigma is a method of improving the quality and profitability based on mastering statically of process and it is also a management style that based on a highly regulated organization dedicated to managing project. The method is based on five main steps summarized in the acronym (DMAIC): Define Measure, Analyze, Improve and Control. Application of the method on the maintenance processes with using maintenance methods during the five phases of the method will help to reduce costs and losses in order to strive for optimum results in terms of profit and quality.

  18. Optimal reactive planning with security constraints

    SciTech Connect

    Thomas, W.R.; Cheng, D.T.Y.; Dixon, A.M.; Thorp, J.D.; Dunnett, R.M.; Schaff, G.

    1995-12-31

    The National Grid Company (NGC) of England and Wales has developed a computer program, SCORPION, to help system planners optimize the location and size of new reactive compensation plant on the transmission system. The reactive power requirements of the NGC system have risen as a result of increased power flows and the shorter timescale on which power stations are commissioned and withdrawn from service. In view of the high costs involved, it is important that reactive compensation be installed as economically as possible, without compromising security. Traditional methods based on iterative use of a load flow program are labor intensive and subjective. SCORPION determines a near-optimal pattern of new reactive sources which are required to satisfy voltage constraints for normal and contingent states of operation of the transmission system. The algorithm processes the system states sequentially, instead of optimizing all of them simultaneously. This allows a large number of system states to be considered with an acceptable run time and computer memory requirement. Installed reactive sources are treated as continuous, rather than discrete, variables. However, the program has a restart facility which enables the user to add realistically sized reactive sources explicitly and thereby work towards a realizable solution to the planning problem.

  19. Transmission network expansion planning with simulation optimization

    SciTech Connect

    Bent, Russell W; Berscheid, Alan; Toole, G. Loren

    2010-01-01

    Within the electric power literatW''e the transmi ssion expansion planning problem (TNEP) refers to the problem of how to upgrade an electric power network to meet future demands. As this problem is a complex, non-linear, and non-convex optimization problem, researchers have traditionally focused on approximate models. Often, their approaches are tightly coupled to the approximation choice. Until recently, these approximations have produced results that are straight-forward to adapt to the more complex (real) problem. However, the power grid is evolving towards a state where the adaptations are no longer easy (i.e. large amounts of limited control, renewable generation) that necessitates new optimization techniques. In this paper, we propose a generalization of the powerful Limited Discrepancy Search (LDS) that encapsulates the complexity in a black box that may be queJied for information about the quality of a proposed expansion. This allows the development of a new optimization algOlitlun that is independent of the underlying power model.

  20. Y-12 Groundwater Protection Program Monitoring Well Inspection And Maintenance Plan

    SciTech Connect

    2013-09-01

    This document is the fourth revision of the Monitoring Well Inspection and Maintenance Plan for groundwater monitoring wells installed at the U.S. Department of Energy (DOE) Y-12 National Security Complex (Y-12) in Oak Ridge, Tennessee. This plan describes the systematic approach for:  inspecting the physical condition of monitoring wells at Y-12,  determining maintenance needs that extend the life of a well, and  identifying those wells that no longer meet acceptable monitoring well design or well construction standards and require plugging and abandonment.

  1. Long-range maintenance planning: A case study of working system

    SciTech Connect

    Flanigan, M.J.

    1991-10-01

    This paper addresses the development of the Lawrence Livermore National Laboratory (LLNL) Maintenance Planning System (MPS). The pitfalls encountered and overcome, and future expansion plans. The MPS provides the ability to develop and track long-range programs, i.e., conversion of chlorofluorocarbon (CFC) equipment to hydrochlorofluorocaron (HCFC), roofing, roads, etc., in addition to providing invaluable information and data for current year budget justification.

  2. 78 FR 7672 - Approval and Promulgation of Implementation Plans; Texas; Beaumont/Port Arthur Ozone Maintenance...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-04

    ... Vehicle Emissions Simulator (MOVES) 2010a emissions model. The BPA 1997 8-hour ozone maintenance area... index, some information is not publicly available, e.g., Confidential Business Information or other... at the Air Planning Section (6PD-L), Environmental Protection Agency, 1445 Ross Avenue, Suite...

  3. STEAM PLANT, TRA609. FIRST FLOOR PLAN. STEAM UNITS, OFFICE, MAINTENANCE ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    STEAM PLANT, TRA-609. FIRST FLOOR PLAN. STEAM UNITS, OFFICE, MAINTENANCE AREA, UTILITY ROOM FOR ELECTRIC GEAR, AIR INTAKE AND FILTERING, DIESEL GENERATOR. BLAW-KNOX 3150-809-2, 8/1950. INL INDEX NO. 531-0609-00-098-100684, REV. 3. - Idaho National Engineering Laboratory, Test Reactor Area, Materials & Engineering Test Reactors, Scoville, Butte County, ID

  4. 29 CFR 825.211 - Maintenance of benefits under multi-employer health plans.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ..., DEPARTMENT OF LABOR OTHER LAWS THE FAMILY AND MEDICAL LEAVE ACT OF 1993 Employee Leave Entitlements Under the Family and Medical Leave Act § 825.211 Maintenance of benefits under multi-employer health plans. (a) A... contributions on behalf of an employee using FMLA leave as though the......

  5. 29 CFR 825.211 - Maintenance of benefits under multi-employer health plans.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ..., DEPARTMENT OF LABOR OTHER LAWS THE FAMILY AND MEDICAL LEAVE ACT OF 1993 Employee Leave Entitlements Under the Family and Medical Leave Act § 825.211 Maintenance of benefits under multi-employer health plans. (a) A... contributions on behalf of an employee using FMLA leave as though the......

  6. 29 CFR 825.211 - Maintenance of benefits under multi-employer health plans.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ..., DEPARTMENT OF LABOR OTHER LAWS THE FAMILY AND MEDICAL LEAVE ACT OF 1993 Employee Leave Entitlements Under the Family and Medical Leave Act § 825.211 Maintenance of benefits under multi-employer health plans. (a) A... contributions on behalf of an employee using FMLA leave as though the......

  7. 29 CFR 825.211 - Maintenance of benefits under multi-employer health plans.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ..., DEPARTMENT OF LABOR OTHER LAWS THE FAMILY AND MEDICAL LEAVE ACT OF 1993 Employee Leave Entitlements Under the Family and Medical Leave Act § 825.211 Maintenance of benefits under multi-employer health plans. (a) A... contributions on behalf of an employee using FMLA leave as though the......

  8. 29 CFR 825.211 - Maintenance of benefits under multi-employer health plans.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ..., DEPARTMENT OF LABOR OTHER LAWS THE FAMILY AND MEDICAL LEAVE ACT OF 1993 Employee Leave Entitlements Under the Family and Medical Leave Act § 825.211 Maintenance of benefits under multi-employer health plans. (a) A... contributions on behalf of an employee using FMLA leave as though the......

  9. 40 CFR 141.804 - Aircraft water system operations and maintenance plan.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ...) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS Aircraft Drinking Water Rule § 141.804 Aircraft water system operations and maintenance plan. (a) Each air carrier must develop and... 40 Protection of Environment 23 2011-07-01 2011-07-01 false Aircraft water system operations...

  10. 40 CFR 141.804 - Aircraft water system operations and maintenance plan.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ...) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS Aircraft Drinking Water Rule § 141.804 Aircraft water system operations and maintenance plan. (a) Each air carrier must develop and... 40 Protection of Environment 23 2014-07-01 2014-07-01 false Aircraft water system operations...

  11. 40 CFR 141.804 - Aircraft water system operations and maintenance plan.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ...) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS Aircraft Drinking Water Rule § 141.804 Aircraft water system operations and maintenance plan. (a) Each air carrier must develop and... 40 Protection of Environment 24 2012-07-01 2012-07-01 false Aircraft water system operations...

  12. 40 CFR 141.804 - Aircraft water system operations and maintenance plan.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ...) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS Aircraft Drinking Water Rule § 141.804 Aircraft water system operations and maintenance plan. (a) Each air carrier must develop and... 40 Protection of Environment 24 2013-07-01 2013-07-01 false Aircraft water system operations...

  13. 40 CFR 141.804 - Aircraft water system operations and maintenance plan.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ...) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS Aircraft Drinking Water Rule § 141.804 Aircraft water system operations and maintenance plan. (a) Each air carrier must develop and... 40 Protection of Environment 22 2010-07-01 2010-07-01 false Aircraft water system operations...

  14. 36 CFR 219.31 - Maintenance of the plan and planning records.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... AGRICULTURE PLANNING National Forest System Land and Resource Management Planning Planning Documentation § 219... typographical errors or other non-substantive changes; and (4) Changes in monitoring methods other than...

  15. Optimal single-replacement for repairable products with different failure rate under a finite planning horizon

    NASA Astrophysics Data System (ADS)

    Chang, Wen Liang

    2015-04-01

    This paper provides a replacement policy for repairable products with free-repair warranty (FRW) under a finite planning horizon from the consumer's viewpoint. Assume that the product is replaced once within a finite planning horizon, and the failure rate of the second product is lower than the failure rate of the first product. Within FRW, the failed product is corrected by minimal repair without any cost to the consumers. After FRW, the failed product is repaired with a fixed repair cost to the consumers. However, each failure incurs a fixed downtime cost to the consumers over a finite planning horizon. In this paper, we derive the three models of the expected total disbursement cost within a finite planning horizon and some properties of the optimal replacement policy under some reasonable conditions are obtained. Finally, numerical examples are given to illustrate the features of the optimal replacement policy under various maintenance costs.

  16. An optimization method for condition based maintenance of aircraft fleet considering prognostics uncertainty.

    PubMed

    Feng, Qiang; Chen, Yiran; Sun, Bo; Li, Songjie

    2014-01-01

    An optimization method for condition based maintenance (CBM) of aircraft fleet considering prognostics uncertainty is proposed. The CBM and dispatch process of aircraft fleet is analyzed first, and the alternative strategy sets for single aircraft are given. Then, the optimization problem of fleet CBM with lower maintenance cost and dispatch risk is translated to the combinatorial optimization problem of single aircraft strategy. Remain useful life (RUL) distribution of the key line replaceable Module (LRM) has been transformed into the failure probability of the aircraft and the fleet health status matrix is established. And the calculation method of the costs and risks for mission based on health status matrix and maintenance matrix is given. Further, an optimization method for fleet dispatch and CBM under acceptable risk is proposed based on an improved genetic algorithm. Finally, a fleet of 10 aircrafts is studied to verify the proposed method. The results shows that it could realize optimization and control of the aircraft fleet oriented to mission success.

  17. Renewable Energy Planning: Multiparametric Cost Optimization; Preprint

    SciTech Connect

    Walker, A.

    2008-05-01

    This paper describes a method for determining the combination of renewable energy technologies that minimize life-cycle cost at a facility, often with a specified goal regarding percent of energy use from renewable sources. Technologies include: photovoltaics (PV); wind; solar thermal heat and electric; solar ventilation air preheating; solar water heating; biomass heat and electric (combustion, gasification, pyrolysis, anaerobic digestion); and daylighting. The method rests upon the National Renewable Energy Laboratory's (NREL's) capabilities in characterization of technology cost and performance, geographic information systems (GIS) resource assessment, and life-cycle cost analysis. The paper discusses how to account for the way candidate technologies interact with each other, and the solver routine used to determine the combination that minimizes life-cycle cost. Results include optimal sizes of each technology, initial cost, operating cost, and life-cycle cost, including incentives from utilities or governments. Results inform early planning to identify and prioritize projects at a site for subsequent engineering and economic feasibility study.

  18. Ideal dose level in treatment planning optimization.

    PubMed

    Begnozzi, L; Malaspina, F; Gentile, F P; Chiatti, L; Carpino, S; Fragomeni, R; Benassi, M

    1992-10-01

    The biological response of the tumor is expressed in terms of tumor control probability (TCP) and its dependence on the inhomogeneous dose distribution throughout the tumor volume is studied. The ideal dose level to which the prescribed dose must be referred is derived, by employing a formula based on the linear quadratic model. To administer the prescribed dose to the ideal dose level renders the tumor control probability equal to that one corresponding to a uniform irradiation of the tumor. For the normal tissue irradiated a normal tissue complication probability index (NTCPI) is also defined and calculated. The comparison between NTCPIs of competing plans supports the optimization. In general the resulting ideal dose level is lower than the mean dose level, but not necessarily equal to the minimum in the tumor. This result shows the possibility of administering the prescribed dose to a dose level higher than the minimum, maintaining the tumor control probability at a good level and consequently lowering the complications to the normal tissue. The method offers a general support for the choice of the reference dose level and of the better technique. An example of application of the method is shown.

  19. Planning for Success: Optimizing Your Teaching

    ERIC Educational Resources Information Center

    de Frece, Robert

    2010-01-01

    This article outlines a sequential approach to unit and lesson planning for conceptual teaching in general music classes. Guidelines for the writing of well-articulated instructional objectives are provided. Two appendices show models of a unit plan and a lesson plan in which the assessment of objectives is clearly tracked and alternative…

  20. Establishing optimal project-level strategies for pavement maintenance and rehabilitation - A framework and case study

    NASA Astrophysics Data System (ADS)

    Irfan, Muhammad; Bilal Khurshid, Muhammad; Bai, Qiang; Labi, Samuel; Morin, Thomas L.

    2012-05-01

    This article presents a framework and an illustrative example for identifying the optimal pavement maintenance and rehabilitation (M&R) strategy using a mixed-integer nonlinear programming model. The objective function is to maximize the cost-effectiveness expressed as the ratio of the effectiveness to the cost. The constraints for the optimization problem are related to performance, budget, and choice. Two different formulations of effectiveness are derived using treatment-specific performance models for each constituent treatment of the strategy; and cost is expressed in terms of the agency and user costs over the life cycle. The proposed methodology is demonstrated using a case study. Probability distributions are established for the optimization input variables and Monte Carlo simulations are carried out to yield optimal solutions. Using the results of these simulations, M&R strategy contours are developed as a novel tool that can help pavement managers quickly identify the optimal M&R strategy for a given pavement section.

  1. Optimism and Planning for Future Care Needs among Older Adults

    PubMed Central

    Sörensen, Silvia; Hirsch, Jameson K.; Lyness, Jeffrey M.

    2015-01-01

    Aging is associated with an increase in need for assistance. Preparation for future care (PFC) is related to improved coping ability as well as better mental and physical health outcomes among older adults. We examined the association of optimism with components of PFC among older adults. We also explored race differences in the relationship between optimism and PFC. In Study 1, multiple regression showed that optimism was positively related to concrete planning. In Study 2, optimism was related to gathering information. An exploratory analysis combining the samples yielded a race interaction: For Whites higher optimism, but for Blacks lower optimism was associated with more planning. High optimism may be a barrier to future planning in certain social and cultural contexts. PMID:26045699

  2. Optimal maintenance and consolidation therapy for multiple myeloma in actual clinical practice

    PubMed Central

    Lee, Ho Sup; Min, Chang-Ki

    2016-01-01

    Multiple myeloma is an incurable malignant plasma cell-originating cancer. Although its treatment outcomes have improved with the use of glucocorticoids, alkylating drugs, and novel agents, including proteasome inhibitors (bortezomib and carfilzomib) and immunomodulatory drugs (thalidomide, lenalidomide, and pomalidomide), relapse remains a serious problem. Strategies to improve outcomes following autologous stem cell transplantation and frontline treatments in non-transplant patients include consolidation to intensify therapy and improve the depth of response and maintenance therapy to achieve long-term disease control. Many clinical trials have reported increased progression-free and overall survival rates after consolidation and maintenance therapy. The role of consolidation/maintenance therapy has been assessed in patients eligible and ineligible for transplantation and is a valuable option in clinical trial settings. However, the decision to use consolidation and/or maintenance therapy needs to be guided by the individual patient situation in actual clinical practice. This review analyzes the currently available evidence from several reported clinical trials to determine the optimal consolidation and maintenance therapy in clinical practice. PMID:27604793

  3. Optimal maintenance and consolidation therapy for multiple myeloma in actual clinical practice.

    PubMed

    Lee, Ho Sup; Min, Chang-Ki

    2016-09-01

    Multiple myeloma is an incurable malignant plasma cell-originating cancer. Although its treatment outcomes have improved with the use of glucocorticoids, alkylating drugs, and novel agents, including proteasome inhibitors (bortezomib and carfilzomib) and immunomodulatory drugs (thalidomide, lenalidomide, and pomalidomide), relapse remains a serious problem. Strategies to improve outcomes following autologous stem cell transplantation and frontline treatments in non-transplant patients include consolidation to intensify therapy and improve the depth of response and maintenance therapy to achieve long-term disease control. Many clinical trials have reported increased progression-free and overall survival rates after consolidation and maintenance therapy. The role of consolidation/maintenance therapy has been assessed in patients eligible and ineligible for transplantation and is a valuable option in clinical trial settings. However, the decision to use consolidation and/or maintenance therapy needs to be guided by the individual patient situation in actual clinical practice. This review analyzes the currently available evidence from several reported clinical trials to determine the optimal consolidation and maintenance therapy in clinical practice. PMID:27604793

  4. Optimal Maintenance Works for the Aborshada Road in the Western Region of Libya

    NASA Astrophysics Data System (ADS)

    Youssef, Medhat Abdelrahman; Elbasher, Abdelbary Altayb

    2014-09-01

    In this research, the condition of a road pavement was investigated for the Aborshada Road in the Gharian region of Libya to determine the optimal maintenance works. Previously, a simple engineering judgment was the only procedure followed by the Gharian municipal engineers for evaluating pavements and prioritizing maintenance. The surface condition of the Aborshada Road pavement was investigated using "the Pavement Condition Index (PCI)" visual technique. The pavement was inspected to survey the different distresses in each sample unit. Ninteen pavement distresses were classified according to the PCI standards (PCI for roads and parking lots became an ASTM standard in 2007 (D6433-07)). It was necessary to know the most common distresses of the Aborshada Road to provide assistance for the decision maker in his evaluation of the pavement and the optimum repair method to be selected. This study reveals the actual performance of the pavements and suggests the research required for dealing with the pavement maintenance problem in Libya, especially in the western region. The best maintenance alternative for Aborshada Road was Case No. 3 (Potholes, Long. & Trans. Cracking and Alligator Crack Maintenance). Also, the most common pavement distresses on the Aborshada Road were Distress Nos. 1, 3, 6, 7, 10 and 13 according to the ASTM - D6433-07 classification

  5. Optimal maintenance and consolidation therapy for multiple myeloma in actual clinical practice.

    PubMed

    Lee, Ho Sup; Min, Chang-Ki

    2016-09-01

    Multiple myeloma is an incurable malignant plasma cell-originating cancer. Although its treatment outcomes have improved with the use of glucocorticoids, alkylating drugs, and novel agents, including proteasome inhibitors (bortezomib and carfilzomib) and immunomodulatory drugs (thalidomide, lenalidomide, and pomalidomide), relapse remains a serious problem. Strategies to improve outcomes following autologous stem cell transplantation and frontline treatments in non-transplant patients include consolidation to intensify therapy and improve the depth of response and maintenance therapy to achieve long-term disease control. Many clinical trials have reported increased progression-free and overall survival rates after consolidation and maintenance therapy. The role of consolidation/maintenance therapy has been assessed in patients eligible and ineligible for transplantation and is a valuable option in clinical trial settings. However, the decision to use consolidation and/or maintenance therapy needs to be guided by the individual patient situation in actual clinical practice. This review analyzes the currently available evidence from several reported clinical trials to determine the optimal consolidation and maintenance therapy in clinical practice.

  6. Operations and Maintenance Concept Plan for the Immobilized High Level Waste (IHLW) Interim Storage Facility

    SciTech Connect

    JANIN, L.F.

    2000-08-30

    This O&M Concept looks at the future operations and maintenance of the IHLW/CSB interim storage facility. It defines the overall strategy, objectives, and functional requirements for the portion of the building to be utilized by Project W-464. The concept supports the tasks of safety basis planning, risk mitigation, alternative analysis, decision making, etc. and will be updated as required to support the evolving design.

  7. Nez Perce Tribal Hatchery Project : Combined-Planning & Design and Operations & Maintenance Reports, 2000 Annual Report.

    SciTech Connect

    Larson, Roy Edward; Walker, Grant W.

    2002-12-31

    Nez Perce Tribal Hatchery (NPTH) Year-2000 Combined Maintenance and Operations (O&M) and Planning and Design (P&D) contract is hereby completed based on this annual report patterned after the Statement of Work (SOW) for the project as contracted with Bonneville Power Administration. Primary project activities focused on completion of the Northwest Power Planning Council Step-3 process that: (1) Accepted final design, (2) Authorized a capital construction amount of $16,050,000, and (3) Authorized contractor selection, and (4) Provided construction site dedication, and (5) Implemented construction activities over an anticipated 2-year period of July 2000 through October 2002.

  8. Reliability-based optimization of maintenance scheduling of mechanical components under fatigue

    PubMed Central

    Beaurepaire, P.; Valdebenito, M.A.; Schuëller, G.I.; Jensen, H.A.

    2012-01-01

    This study presents the optimization of the maintenance scheduling of mechanical components under fatigue loading. The cracks of damaged structures may be detected during non-destructive inspection and subsequently repaired. Fatigue crack initiation and growth show inherent variability, and as well the outcome of inspection activities. The problem is addressed under the framework of reliability based optimization. The initiation and propagation of fatigue cracks are efficiently modeled using cohesive zone elements. The applicability of the method is demonstrated by a numerical example, which involves a plate with two holes subject to alternating stress. PMID:23564979

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-01-01

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

  11. Optimizing perioperative decision making: improved information for clinical workflow planning.

    PubMed

    Doebbeling, Bradley N; Burton, Matthew M; Wiebke, Eric A; Miller, Spencer; Baxter, Laurence; Miller, Donald; Alvarez, Jorge; Pekny, Joseph

    2012-01-01

    Perioperative care is complex and involves multiple interconnected subsystems. Delayed starts, prolonged cases and overtime are common. Surgical procedures account for 40-70% of hospital revenues and 30-40% of total costs. Most planning and scheduling in healthcare is done without modern planning tools, which have potential for improving access by assisting in operations planning support. We identified key planning scenarios of interest to perioperative leaders, in order to examine the feasibility of applying combinatorial optimization software solving some of those planning issues in the operative setting. Perioperative leaders desire a broad range of tools for planning and assessing alternate solutions. Our modeled solutions generated feasible solutions that varied as expected, based on resource and policy assumptions and found better utilization of scarce resources. Combinatorial optimization modeling can effectively evaluate alternatives to support key decisions for planning clinical workflow and improving care efficiency and satisfaction.

  12. Helical tomotherapy optimized planning parameters for nasopharyngeal cancer

    NASA Astrophysics Data System (ADS)

    Yawichai, K.; Chitapanarux, I.; Wanwilairat, S.

    2016-03-01

    Helical TomoTherapy(HT) planning depends on optimize parameters including field width (FW), pitch factor (PF) and modulation factor (MF). These optimize parameters are effect to quality of plans and treatment time. The aim of this study was to find the optimized parameters which compromise between plan quality and treatment times. Six nasopharyngeal cancer patients were used. For each patient data set, 18 treatment plans consisted of different optimize parameters combination (FW=5.0, 2.5, 1.0 cm; PF=0.43, 0.287, 0.215; MF2.0, 3.0) were created. The identical optimization procedure followed ICRU83 recommendations. The average D50 of both parotid glands and treatment times per fraction were compared for all plans. The study show treatment plan with FW1.0 cm showed the lowest average D50 of both parotid glands. The treatment time increased inversely to FW. The FW1.0 cm the average treatment time was 4 times longer than FW5.0 cm. PF was very little influence on the average D50 of both parotid glands. Finally, MF increased from 2.0 to 3.0 the average D50 of both parotid glands was slightly decreased. However, the average treatment time was increased 22.28%. For routine nasopharyngeal cancer patients with HT, we suggest the planning optimization parameters consist of FW=5.0 cm, PF=0.43 and MF=2.0.

  13. Performance-optimized clinical IMRT planning on modern CPUs

    NASA Astrophysics Data System (ADS)

    Ziegenhein, Peter; Kamerling, Cornelis Ph; Bangert, Mark; Kunkel, Julian; Oelfke, Uwe

    2013-06-01

    Intensity modulated treatment plan optimization is a computationally expensive task. The feasibility of advanced applications in intensity modulated radiation therapy as every day treatment planning, frequent re-planning for adaptive radiation therapy and large-scale planning research severely depends on the runtime of the plan optimization implementation. Modern computational systems are built as parallel architectures to yield high performance. The use of GPUs, as one class of parallel systems, has become very popular in the field of medical physics. In contrast we utilize the multi-core central processing unit (CPU), which is the heart of every modern computer and does not have to be purchased additionally. In this work we present an ultra-fast, high precision implementation of the inverse plan optimization problem using a quasi-Newton method on pre-calculated dose influence data sets. We redefined the classical optimization algorithm to achieve a minimal runtime and high scalability on CPUs. Using the proposed methods in this work, a total plan optimization process can be carried out in only a few seconds on a low-cost CPU-based desktop computer at clinical resolution and quality. We have shown that our implementation uses the CPU hardware resources efficiently with runtimes comparable to GPU implementations, at lower costs.

  14. 40 CFR 63.8425 - What do I need to know about operation, maintenance, and monitoring plans?

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ...) Procedures for keeping records to document compliance. (13) If you operate an affected kiln and you plan to take the kiln control device out of service for routine maintenance, as specified in § 63.8420(e), the... emissions from the kiln during periods of routine maintenance of the kiln control device when the kiln...

  15. 40 CFR 63.8425 - What do I need to know about operation, maintenance, and monitoring plans?

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ...) Procedures for keeping records to document compliance. (13) If you operate an affected kiln and you plan to take the kiln control device out of service for routine maintenance, as specified in § 63.8420(e), the... emissions from the kiln during periods of routine maintenance of the kiln control device when the kiln...

  16. 40 CFR 63.8425 - What do I need to know about operation, maintenance, and monitoring plans?

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ...) Procedures for keeping records to document compliance. (13) If you operate an affected kiln and you plan to take the kiln control device out of service for routine maintenance, as specified in § 63.8420(e), the... emissions from the kiln during periods of routine maintenance of the kiln control device when the kiln...

  17. 40 CFR 63.8425 - What do I need to know about operation, maintenance, and monitoring plans?

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ...) Procedures for keeping records to document compliance. (13) If you operate an affected kiln and you plan to take the kiln control device out of service for routine maintenance, as specified in § 63.8420(e), the... emissions from the kiln during periods of routine maintenance of the kiln control device when the kiln...

  18. Optimal pricing policies for services with consideration of facility maintenance costs

    NASA Astrophysics Data System (ADS)

    Yeh, Ruey Huei; Lin, Yi-Fang

    2012-06-01

    For survival and success, pricing is an essential issue for service firms. This article deals with the pricing strategies for services with substantial facility maintenance costs. For this purpose, a mathematical framework that incorporates service demand and facility deterioration is proposed to address the problem. The facility and customers constitute a service system driven by Poisson arrivals and exponential service times. A service demand with increasing price elasticity and a facility lifetime with strictly increasing failure rate are also adopted in modelling. By examining the bidirectional relationship between customer demand and facility deterioration in the profit model, the pricing policies of the service are investigated. Then analytical conditions of customer demand and facility lifetime are derived to achieve a unique optimal pricing policy. The comparative statics properties of the optimal policy are also explored. Finally, numerical examples are presented to illustrate the effects of parameter variations on the optimal pricing policy.

  19. Fuel-Optimal Altitude Maintenance of Low-Earth-Orbit Spacecrafts by Combined Direct/Indirect Optimization

    NASA Astrophysics Data System (ADS)

    Kim, Kyung-Ha; Park, Chandeok; Park, Sang-Young

    2015-12-01

    This work presents fuel-optimal altitude maintenance of Low-Earth-Orbit (LEO) spacecrafts experiencing non-negligible air drag and J2 perturbation. A pseudospectral (direct) method is first applied to roughly estimate an optimal fuel consumption strategy, which is employed as an initial guess to precisely determine itself. Based on the physical specifications of KOrea Multi-Purpose SATellite-2 (KOMPSAT-2), a Korean artificial satellite, numerical simulations show that a satellite ascends with full thrust at the early stage of the maneuver period and then descends with null thrust. While the thrust profile is presumably bang-off, it is difficult to precisely determine the switching time by using a pseudospectral method only. This is expected, since the optimal switching epoch does not coincide with one of the collocation points prescribed by the pseudospectral method, in general. As an attempt to precisely determine the switching time and the associated optimal thrust history, a shooting (indirect) method is then employed with the initial guess being obtained through the pseudospectral method. This hybrid process allows the determination of the optimal fuel consumption for LEO spacecrafts and their thrust profiles efficiently and precisely.

  20. Time optimal route planning algorithm of LBS online navigation

    NASA Astrophysics Data System (ADS)

    Li, Yong; Bao, Shitai; Su, Kui; Fang, Qiushui; Yang, Jingfeng

    2011-02-01

    This paper proposes a time optimal route planning optimization algorithm in the mode of LBS online navigation based on the improved Dijkstra algorithms. Combined with the returning real-time location information by on-line users' handheld terminals, the algorithm can satisfy requirement of the optimal time in the mode of LBS online navigation. A navigation system is developed and applied in actual navigation operations. Operating results show that the algorithm could form a reasonable coordination on the basis of shortest route and fastest velocity in the requirement of optimal time. The algorithm could also store the calculated real-time route information in the cache to improve the efficiency of route planning and to reduce the planning time-consuming.

  1. A Minimum (Delta)V Orbit Maintenance Strategy for Low-Altitude Missions Using Burn Parameter Optimization

    NASA Technical Reports Server (NTRS)

    Brown, Aaron J.

    2011-01-01

    Orbit maintenance is the series of burns performed during a mission to ensure the orbit satisfies mission constraints. Low-altitude missions often require non-trivial orbit maintenance (Delta)V due to sizable orbital perturbations and minimum altitude thresholds. A strategy is presented for minimizing this (Delta)V using impulsive burn parameter optimization. An initial estimate for the burn parameters is generated by considering a feasible solution to the orbit maintenance problem. An example demonstrates the dV savings from the feasible solution to the optimal solution.

  2. PARETO: A novel evolutionary optimization approach to multiobjective IMRT planning

    SciTech Connect

    Fiege, Jason; McCurdy, Boyd; Potrebko, Peter; Champion, Heather; Cull, Andrew

    2011-09-15

    Purpose: In radiation therapy treatment planning, the clinical objectives of uniform high dose to the planning target volume (PTV) and low dose to the organs-at-risk (OARs) are invariably in conflict, often requiring compromises to be made between them when selecting the best treatment plan for a particular patient. In this work, the authors introduce Pareto-Aware Radiotherapy Evolutionary Treatment Optimization (pareto), a multiobjective optimization tool to solve for beam angles and fluence patterns in intensity-modulated radiation therapy (IMRT) treatment planning. Methods: pareto is built around a powerful multiobjective genetic algorithm (GA), which allows us to treat the problem of IMRT treatment plan optimization as a combined monolithic problem, where all beam fluence and angle parameters are treated equally during the optimization. We have employed a simple parameterized beam fluence representation with a realistic dose calculation approach, incorporating patient scatter effects, to demonstrate feasibility of the proposed approach on two phantoms. The first phantom is a simple cylindrical phantom containing a target surrounded by three OARs, while the second phantom is more complex and represents a paraspinal patient. Results: pareto results in a large database of Pareto nondominated solutions that represent the necessary trade-offs between objectives. The solution quality was examined for several PTV and OAR fitness functions. The combination of a conformity-based PTV fitness function and a dose-volume histogram (DVH) or equivalent uniform dose (EUD) -based fitness function for the OAR produced relatively uniform and conformal PTV doses, with well-spaced beams. A penalty function added to the fitness functions eliminates hotspots. Comparison of resulting DVHs to those from treatment plans developed with a single-objective fluence optimizer (from a commercial treatment planning system) showed good correlation. Results also indicated that pareto shows

  3. MTRETR MAINTENANCE SHOP, TRA653. FLOOR PLAN FOR FIRST FLOOR: MACHINE ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    MTR-ETR MAINTENANCE SHOP, TRA-653. FLOOR PLAN FOR FIRST FLOOR: MACHINE SHOP, ELECTRICAL AND INSTRUMENT SHOP, TOOL CRIB, ELECTRONIC SHOP, LOCKER ROOM, SPECIAL TEMPERATURE CONTROLLED ROOM, AND OFFICES. "NEW" ON DRAWING REFERS TO REVISION OF 11/1956 DRAWING ON WHICH AREAS WERE DESIGNATED AS "FUTURE." HUMMEL HUMMEL & JONES 810-MTR-ETR-653-A-7, 5/1957. INL INDEX NO. 532-0653-00-381-101839, REV. 2. - Idaho National Engineering Laboratory, Test Reactor Area, Materials & Engineering Test Reactors, Scoville, Butte County, ID

  4. INL SITEWIDE INSTITUTIONAL CONTROLS, AND OPERATIONS AND MAINTENANCE PLAN FOR CERCLA RESPONSE ACTIONS

    SciTech Connect

    JOLLEY, WENDELL L

    2008-02-05

    On November 9, 2002, the U.S. Environmental Protection Agency, the U.S. Department of Energy, and the Idaho Department of Environmental Quality approved the 'Record of Decision Experimental Breeder Reactor-I/Boiling Water Reactor Experiment Area and Miscellaneous Sites', which required a Site-wide institutional controls plan for the then Idaho National Engineering and Environmental Laboratory (now known as the Idaho National Laboratory). This document, first issued in June 2004, fulfilled that requirement. This revision identifies and consolidates the institutional controls and operations and maintenance requirements into a single document.

  5. Shuttle Flight Operations Contract Generator Maintenance Facility Land Use Control Implementation Plan (LUCIP)

    NASA Technical Reports Server (NTRS)

    Applegate, Joseph L.

    2014-01-01

    This Land Use Control Implementation Plan (LUCIP) has been prepared to inform current and potential future users of the Kennedy Space Center (KSC) Shuttle Flight Operations Contract Generator Maintenance Facility (SFOC; SWMU 081; "the Site") of institutional controls that have been implemented at the Site1. Although there are no current unacceptable risks to human health or the environment associated with the SFOC, an institutional land use control (LUC) is necessary to prevent human health exposure to antimony-affected groundwater at the Site. Controls will include periodic inspection, condition certification, and agency notification.

  6. Projectizing the development and/or maintenance process for emergency response/contingency plans

    SciTech Connect

    A. A. Francis

    2000-07-01

    The attainment of established goals and objects is essential and paramount for all successful projects in business and industry, including the development and/or maintenance of emergency response/contingency plans. The need for effective project management is an ongoing effort. As with any aspect of business, better ways of managing projects have been and are being developed. Those organizations that take the lead in implementing these capabilities consistently perform their projects better, and in the case of emergency management, provide better protection to employees, property, and the environment.

  7. Optimizing spacecraft design - optimization engine development : progress and plans

    NASA Technical Reports Server (NTRS)

    Cornford, Steven L.; Feather, Martin S.; Dunphy, Julia R; Salcedo, Jose; Menzies, Tim

    2003-01-01

    At JPL and NASA, a process has been developed to perform life cycle risk management. This process requires users to identify: goals and objectives to be achieved (and their relative priorities), the various risks to achieving those goals and objectives, and options for risk mitigation (prevention, detection ahead of time, and alleviation). Risks are broadly defined to include the risk of failing to design a system with adequate performance, compatibility and robustness in addition to more traditional implementation and operational risks. The options for mitigating these different kinds of risks can include architectural and design choices, technology plans and technology back-up options, test-bed and simulation options, engineering models and hardware/software development techniques and other more traditional risk reduction techniques.

  8. Nanodosimetry-Based Plan Optimization for Particle Therapy

    PubMed Central

    Casiraghi, Margherita; Schulte, Reinhard W.

    2015-01-01

    Treatment planning for particle therapy is currently an active field of research due uncertainty in how to modify physical dose in order to create a uniform biological dose response in the target. A novel treatment plan optimization strategy based on measurable nanodosimetric quantities rather than biophysical models is proposed in this work. Simplified proton and carbon treatment plans were simulated in a water phantom to investigate the optimization feasibility. Track structures of the mixed radiation field produced at different depths in the target volume were simulated with Geant4-DNA and nanodosimetric descriptors were calculated. The fluences of the treatment field pencil beams were optimized in order to create a mixed field with equal nanodosimetric descriptors at each of the multiple positions in spread-out particle Bragg peaks. For both proton and carbon ion plans, a uniform spatial distribution of nanodosimetric descriptors could be obtained by optimizing opposing-field but not single-field plans. The results obtained indicate that uniform nanodosimetrically weighted plans, which may also be radiobiologically uniform, can be obtained with this approach. Future investigations need to demonstrate that this approach is also feasible for more complicated beam arrangements and that it leads to biologically uniform response in tumor cells and tissues. PMID:26167202

  9. Nez Perce Tribal Hatchery Project; Operations and Maintenance and Planning and Design, 2002 Annual Report.

    SciTech Connect

    Larson, Roy Edward; Walker, Grant W.; Penney, Aaron K.

    2005-12-01

    This report fulfills the contract obligations based on the Statement of Work (SOW) for the project as contracted with Bonneville Power Administration (BPA). Nez Perce Tribal Hatchery (NPTH) Year-2002 annual report combines information from two contracts with a combined value of $3,036,014. Bonneville Power Administration identifies them as follows; (1) Part I--Operations and Maintenance--Project No. 1983-350-00, Contract No. 4504, and $2,682,635 which includes--Equipment costs of $1,807,105. (2) Part II--Planning and Design--Project No. 1983-35-04, Contract No. 4035, $352,379 for Clearwater Coho Restoration Master Plan development Based on NPPC authorization for construction and operation of NPTH, the annual contracts were negotiated for the amounts shown above under (1) and (2). Construction contracts were handled by BPA until all facilities are completed and accepted.

  10. Facility Decontamination and Decommissioning Program Surveillance and Maintenance Plan, Revision 2

    SciTech Connect

    Poderis, Reed J.; King, Rebecca A.

    2013-09-30

    This Surveillance and Maintenance (S&M) Plan describes the activities performed between deactivation and final decommissioning of the following facilities located on the Nevada National Security Site, as documented in the Federal Facility Agreement and Consent Order under the Industrial Sites program as decontamination and decommissioning sites: ? Engine Maintenance, Assembly, and Disassembly (EMAD) Facility: o EMAD Building (Building 25-3900) o Locomotive Storage Shed (Building 25-3901) ? Test Cell C (TCC) Facility: o Equipment Building (Building 25-3220) o Motor Drive Building (Building 25-3230) o Pump Shop (Building 25-3231) o Cryogenic Lab (Building 25-3232) o Ancillary Structures (e.g., dewars, water tower, piping, tanks) These facilities have been declared excess and are in various stages of deactivation (low-risk, long-term stewardship disposition state). This S&M Plan establishes and implements a solid, cost-effective, and balanced S&M program consistent with federal, state, and regulatory requirements. A graded approach is used to plan and conduct S&M activities. The goal is to maintain the facilities in a safe condition in a cost-effective manner until their final end state is achieved. This plan accomplishes the following: ? Establishes S&M objectives and framework ? Identifies programmatic guidance for S&M activities to be conducted by National Security Technologies, LLC, for the U.S. Department of Energy, National Nuclear Security Administration Nevada Field Office (NNSA/NFO) ? Provides present facility condition information and identifies hazards ? Identifies facility-specific S&M activities to be performed and their frequency ? Identifies regulatory drivers, NNSA/NFO policies and procedures, and best management practices that necessitate implementation of S&M activities ? Provides criteria and frequencies for revisions and updates ? Establishes the process for identifying and dispositioning a condition that has not been previously identified or

  11. Feasibility of identification of gamma knife planning strategies by identification of pareto optimal gamma knife plans.

    PubMed

    Giller, C A

    2011-12-01

    The use of conformity indices to optimize Gamma Knife planning is common, but does not address important tradeoffs between dose to tumor and normal tissue. Pareto analysis has been used for this purpose in other applications, but not for Gamma Knife (GK) planning. The goal of this work is to use computer models to show that Pareto analysis may be feasible for GK planning to identify dosimetric tradeoffs. We define a GK plan A to be Pareto dominant to B if the prescription isodose volume of A covers more tumor but not more normal tissue than B, or if A covers less normal tissue but not less tumor than B. A plan is Pareto optimal if it is not dominated by any other plan. Two different Pareto optimal plans represent different tradeoffs between dose to tumor and normal tissue, because neither plan dominates the other. 'GK simulator' software calculated dose distributions for GK plans, and was called repetitively by a genetic algorithm to calculate Pareto dominant plans. Three irregular tumor shapes were tested in 17 trials using various combinations of shots. The mean number of Pareto dominant plans/trial was 59 ± 17 (sd). Different planning strategies were identified by large differences in shot positions, and 70 of the 153 coordinate plots (46%) showed differences of 5mm or more. The Pareto dominant plans dominated other nearby plans. Pareto dominant plans represent different dosimetric tradeoffs and can be systematically calculated using genetic algorithms. Automatic identification of non-intuitive planning strategies may be feasible with these methods.

  12. Application of Particle Swarm Optimization in Computer Aided Setup Planning

    NASA Astrophysics Data System (ADS)

    Kafashi, Sajad; Shakeri, Mohsen; Abedini, Vahid

    2011-01-01

    New researches are trying to integrate computer aided design (CAD) and computer aided manufacturing (CAM) environments. The role of process planning is to convert the design specification into manufacturing instructions. Setup planning has a basic role in computer aided process planning (CAPP) and significantly affects the overall cost and quality of machined part. This research focuses on the development for automatic generation of setups and finding the best setup plan in feasible condition. In order to computerize the setup planning process, three major steps are performed in the proposed system: a) Extraction of machining data of the part. b) Analyzing and generation of all possible setups c) Optimization to reach the best setup plan based on cost functions. Considering workshop resources such as machine tool, cutter and fixture, all feasible setups could be generated. Then the problem is adopted with technological constraints such as TAD (tool approach direction), tolerance relationship and feature precedence relationship to have a completely real and practical approach. The optimal setup plan is the result of applying the PSO (particle swarm optimization) algorithm into the system using cost functions. A real sample part is illustrated to demonstrate the performance and productivity of the system.

  13. Richland Environmental Restoration Project Fiscal Year 2000--2002 Detailed Work Plan -- Surveillance/Maintenance and Transition Project

    SciTech Connect

    Swan, K.N.

    1999-09-29

    The US Department of Energy (DOE), Richland Operations Office (RL), directed Hanford Site contractors to update multi-year work plans in accordance with the guidance provided to them. The Richland Environmental Restoration Project continued the Detailed Work Plan update approach that was approved in fiscal year 1998. This Detailed Work Plan provides the cost, scope, and schedule for the FY00 through FY02 activities required to support the Surveillance/Maintenance and Transition Project.

  14. Optimal vehicle planning and the search tour problem

    NASA Astrophysics Data System (ADS)

    Wettergren, Thomas A.; Bays, Matthew J.

    2016-05-01

    We describe a problem of optimal planning for unmanned vehicles and illustrate two distinct procedures for its solution. The problem under consideration, which we refer to as the search tour problem, involves the determination of multi-stage plans for unmanned vehicles conducting search operations. These types of problems are important in situations where the searcher has varying performance in different regions throughout the domain due to environmental complexity. The ability to provide robust planning for unmanned systems under difficult environmental conditions is critical for their use in search operations. The problem we consider consists of searches with variable times for each of the stages, as well as an additional degree of freedom for each stage to select from one of a finite set of operational configurations. As each combination of configuration and stage time leads to a different performance level, there is a need to determine the optimal configuration of these stages. When the complexity of constraints on total time, as well as resources expended at each stage for a given configuration, are added, the problem becomes one of non-trivial search effort allocation and numerical methods of optimization are required. We show two solution approaches for this numerical optimization problem. The first solution technique is to use a mixed-integer linear programming formulation, for which commercially available solvers can find optimal solutions in a reasonable amount of time. We use this solution as a baseline and compare against a new inner/outer optimization formulation. This inner/outer optimization compares favorably to the baseline solution, but is also amenable to adaptation as the search operation progresses. Numerical examples illustrate the utility of the approach for unmanned vehicle search planning.

  15. Broadband Access Network Planning Optimization Considering Real Copper Cable Lengths

    NASA Astrophysics Data System (ADS)

    Peternel, Blaž Kos, Andrej

    Broadband access network planning strategies with techno-economic calculations are important topics, when optimal broadband network deployments are considered. This paper analyzes optimal deployment combination of digital subscriber line technologies (xDSL) and fiber to the home technologies (FTTx), following different user bandwidth demand scenarios. For this reason, optimal placement of remote digital subscriber line multiplexer (RDSLAM) is examined. Furthermore, the article also discusses the economy of investments, depending on certain investment threshold and the reach of different xDSL technologies. Finally, the difference between broadband network deployment in a characteristic urban and rural area in Republic of Slovenia, in terms of required optical cable dig length per household is shown. A tree structure network model of a traditional copper access network is introduced. A dynamic programming logic, with recursion as a basis of a tree structure examination and evaluation of optimal network elements placement is used. The tree structure network model considers several real network parameters (e. g.: copper cable lengths, user coordinates, node coordinates). The main input for the optimization is a local loop distance between each user and a candidate node for RDSLAM placement. Modelling of copper access networks with a tree structure makes new extensions in planning optimization of broadband access networks. Optimization of network elements placement has direct influence on efficiency and profitability of broadband access telecommunication networks.

  16. Maintenance and operations contractor plan for transition to the project Hanford management contract (PHMC)

    SciTech Connect

    Waite, J.L.

    1996-04-12

    This plan has been developed by Westinghouse Hanford Company (WHC), and its subcontractors ICF Kaiser Hanford (ICF KH) and BCS Richland, Inc. (BCSR), at the direction of the US Department of Energy (DOE), Richland Operations Office (RL). WHC and its subcontractors are hereafter referred to as the Maintenance and Operations (M and O) Contractor. The plan identifies actions involving the M and O Contractor that are critical to (1) prepare for a smooth transition to the Project Hanford Management Contractor (PHMC), and (2) support and assist the PHMC and RL in achieving transition as planned, with no or minimal impact to ongoing baseline activities. The plan is structured around two primary phases. The first is the pre-award phase, which started in mid-February 1996 and is currently scheduled to be completed on June 1, 1996, at which time the contract is currently planned to be awarded. The second is the follow-on four-month post-award phase from June 1, 1996, until October 1, 1996. Considering the magnitude and complexity of the scope of work being transitioned, completion in four months will require significant effort by all parties. To better ensure success, the M and O Contractor has developed a pre-award phase that is intended to maximize readiness for transition. Priority is given to preparation for facility assessments and processing of personnel, as these areas are determined to be on the critical path for transition. In addition, the M and O Contractor will put emphasis during the pre-award phase to close out open items prior to contract award, to include grievances, employee concerns, audit findings, compliance issues, etc.

  17. PTV-based IMPT optimization incorporating planning risk volumes vs robust optimization

    SciTech Connect

    Liu Wei; Li Xiaoqiang; Zhu, Ron. X.; Mohan, Radhe; Frank, Steven J.; Li Yupeng

    2013-02-15

    Purpose: Robust optimization leads to intensity-modulated proton therapy (IMPT) plans that are less sensitive to uncertainties and superior in terms of organs-at-risk (OARs) sparing, target dose coverage, and homogeneity compared to planning target volume (PTV)-based optimized plans. Robust optimization incorporates setup and range uncertainties, which implicitly adds margins to both targets and OARs and is also able to compensate for perturbations in dose distributions within targets and OARs caused by uncertainties. In contrast, the traditional PTV-based optimization considers only setup uncertainties and adds a margin only to targets but no margins to the OARs. It also ignores range uncertainty. The purpose of this work is to determine if robustly optimized plans are superior to PTV-based plans simply because the latter do not assign margins to OARs during optimization. Methods: The authors retrospectively selected from their institutional database five patients with head and neck (H and N) cancer and one with prostate cancer for this analysis. Using their original images and prescriptions, the authors created new IMPT plans using three methods: PTV-based optimization, optimization based on the PTV and planning risk volumes (PRVs) (i.e., 'PTV+PRV-based optimization'), and robust optimization using the 'worst-case' dose distribution. The PRVs were generated by uniformly expanding OARs by 3 mm for the H and N cases and 5 mm for the prostate case. The dose-volume histograms (DVHs) from the worst-case dose distributions were used to assess and compare plan quality. Families of DVHs for each uncertainty for all structures of interest were plotted along with the nominal DVHs. The width of the 'bands' of DVHs was used to quantify the plan sensitivity to uncertainty. Results: Compared with conventional PTV-based and PTV+PRV-based planning, robust optimization led to a smaller bandwidth for the targets in the face of uncertainties {l_brace}clinical target volume [CTV

  18. Resampling: An optimization method for inverse planning in robotic radiosurgery

    SciTech Connect

    Schweikard, Achim; Schlaefer, Alexander; Adler, John R. Jr.

    2006-11-15

    By design, the range of beam directions in conventional radiosurgery are constrained to an isocentric array. However, the recent introduction of robotic radiosurgery dramatically increases the flexibility of targeting, and as a consequence, beams need be neither coplanar nor isocentric. Such a nonisocentric design permits a large number of distinct beam directions to be used in one single treatment. These major technical differences provide an opportunity to improve upon the well-established principles for treatment planning used with GammaKnife or LINAC radiosurgery. With this objective in mind, our group has developed over the past decade an inverse planning tool for robotic radiosurgery. This system first computes a set of beam directions, and then during an optimization step, weights each individual beam. Optimization begins with a feasibility query, the answer to which is derived through linear programming. This approach offers the advantage of completeness and avoids local optima. Final beam selection is based on heuristics. In this report we present and evaluate a new strategy for utilizing the advantages of linear programming to improve beam selection. Starting from an initial solution, a heuristically determined set of beams is added to the optimization problem, while beams with zero weight are removed. This process is repeated to sample a set of beams much larger compared with typical optimization. Experimental results indicate that the planning approach efficiently finds acceptable plans and that resampling can further improve its efficiency.

  19. 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.

  20. Hybrid Particle Swarm Optimization for Hybrid Flowshop Scheduling Problem with Maintenance Activities

    PubMed Central

    Li, Jun-qing; Pan, Quan-ke; Mao, Kun

    2014-01-01

    A hybrid algorithm which combines particle swarm optimization (PSO) and iterated local search (ILS) is proposed for solving the hybrid flowshop scheduling (HFS) problem with preventive maintenance (PM) activities. In the proposed algorithm, different crossover operators and mutation operators are investigated. In addition, an efficient multiple insert mutation operator is developed for enhancing the searching ability of the algorithm. Furthermore, an ILS-based local search procedure is embedded in the algorithm to improve the exploitation ability of the proposed algorithm. The detailed experimental parameter for the canonical PSO is tuning. The proposed algorithm is tested on the variation of 77 Carlier and Néron's benchmark problems. Detailed comparisons with the present efficient algorithms, including hGA, ILS, PSO, and IG, verify the efficiency and effectiveness of the proposed algorithm. PMID:24883414

  1. Improving IMRT-plan quality with MLC leaf position refinement post plan optimization

    SciTech Connect

    Niu Ying; Zhang Guowei; Berman, Barry L.; Parke, William C.; Yi Byongyong; Yu, Cedric X.

    2012-08-15

    Purpose: In intensity-modulated radiation therapy (IMRT) planning, reducing the pencil-beam size may lead to a significant improvement in dose conformity, but also increase the time needed for the dose calculation and plan optimization. The authors develop and evaluate a postoptimization refinement (POpR) method, which makes fine adjustments to the multileaf collimator (MLC) leaf positions after plan optimization, enhancing the spatial precision and improving the plan quality without a significant impact on the computational burden. Methods: The authors' POpR method is implemented using a commercial treatment planning system based on direct aperture optimization. After an IMRT plan is optimized using pencil beams with regular pencil-beam step size, a greedy search is conducted by looping through all of the involved MLC leaves to see if moving the MLC leaf in or out by half of a pencil-beam step size will improve the objective function value. The half-sized pencil beams, which are used for updating dose distribution in the greedy search, are derived from the existing full-sized pencil beams without need for further pencil-beam dose calculations. A benchmark phantom case and a head-and-neck (HN) case are studied for testing the authors' POpR method. Results: Using a benchmark phantom and a HN case, the authors have verified that their POpR method can be an efficient technique in the IMRT planning process. Effectiveness of POpR is confirmed by noting significant improvements in objective function values. Dosimetric benefits of POpR are comparable to those of using a finer pencil-beam size from the optimization start, but with far less computation and time. Conclusions: The POpR is a feasible and practical method to significantly improve IMRT-plan quality without compromising the planning efficiency.

  2. Improving IMRT-plan quality with MLC leaf position refinement post plan optimization

    PubMed Central

    Niu, Ying; Zhang, Guowei; Berman, Barry L.; Parke, William C.; Yi, Byongyong; Yu, Cedric X.

    2012-01-01

    Purpose: In intensity-modulated radiation therapy (IMRT) planning, reducing the pencil-beam size may lead to a significant improvement in dose conformity, but also increase the time needed for the dose calculation and plan optimization. The authors develop and evaluate a postoptimization refinement (POpR) method, which makes fine adjustments to the multileaf collimator (MLC) leaf positions after plan optimization, enhancing the spatial precision and improving the plan quality without a significant impact on the computational burden. Methods: The authors’ POpR method is implemented using a commercial treatment planning system based on direct aperture optimization. After an IMRT plan is optimized using pencil beams with regular pencil-beam step size, a greedy search is conducted by looping through all of the involved MLC leaves to see if moving the MLC leaf in or out by half of a pencil-beam step size will improve the objective function value. The half-sized pencil beams, which are used for updating dose distribution in the greedy search, are derived from the existing full-sized pencil beams without need for further pencil-beam dose calculations. A benchmark phantom case and a head-and-neck (HN) case are studied for testing the authors’ POpR method. Results: Using a benchmark phantom and a HN case, the authors have verified that their POpR method can be an efficient technique in the IMRT planning process. Effectiveness of POpR is confirmed by noting significant improvements in objective function values. Dosimetric benefits of POpR are comparable to those of using a finer pencil-beam size from the optimization start, but with far less computation and time. Conclusions: The POpR is a feasible and practical method to significantly improve IMRT-plan quality without compromising the planning efficiency. PMID:22894437

  3. Robust optimization approach to regional wastewater system planning.

    PubMed

    Zeferino, João A; Cunha, Maria C; Antunes, António P

    2012-10-30

    Wastewater systems are subject to several sources of uncertainty. Different scenarios can occur in the future, depending on the behavior of a variety of demographic, economic, environmental, and technological variables. Robust optimization approaches are aimed at finding solutions that will perform well under any likely scenario. The planning decisions to be made about wastewater system planning involve two main issues: the setup and operation costs of sewer networks, treatment plants, and possible pump stations; and the water quality parameters to be met in the water body where the (treated) wastewater is discharged. The source of uncertainty considered in this article is the flow of the river that receives the wastewater generated in a given region. Three robust optimization models for regional wastewater system planning are proposed. The models are solved using a simulated annealing algorithm enhanced with a local improvement procedure. Their application is illustrated through a case study representing a real-world situation, with the results being compared and commented upon.

  4. Optimal investment and operation plans for Kenya's electricity industry

    SciTech Connect

    Murathe-Muthee, A.

    1983-01-01

    The research sought to determine optimal investment and operation plans for Kenya's electricity industry. A multi-period linear programming model was used to select construction, generation and transmission programs that will minimize the present value of electricity investment and operation costs (PVC) while meeting forecasted demand for the years 1982 through 2000. The basic optimal construction plan was designed to provide capability for meeting demand under dry-year conditions. Out of a total of 804 MW of new generation capacity indicated, 36% would be from hydro, 27% from geothermal and 37% from coal and oil resources. In a dry year, optimal operation of the system would generate 59% of the energy from hydro, 14% from geothermal and 27% from coal and oil sources. In average years a 14% increase in hydroenergy makes it possible to reduce fuel use by 23% and decrease the PVC by 11%.

  5. Medicare program; payment to health maintenance organizations and competitive medical plans--HCFA. Proposed rule.

    PubMed

    1984-05-25

    These proposed regulations would implement section 114 of the Tax Equity and Fiscal Responsibility Act of 1982. This provision of the law amended section 1876 of the Social Security Act, which authorizes Medicare reimbursement to eligible organizations on a prospective basis for those organizations that have a risk contract or on a reasonable cost basis for those that have a cost contract. The definition of an eligible organization includes both health maintenance organizations (HMOs) that meet the definition of a qualified HMO under the Public Health Service Act and competitive medical plans (CMPs). The purpose of this proposal is to set forth the requirements that an entity must meet in order to be (1) eligible to enter into a Medicare contract (either risk or reasonable cost) as an eligible organization and (2) reimbursed by Medicare on a capacitation basis (either prospectively or retrospectively) for items and services furnished to Medicare enrollees. PMID:10299521

  6. Spatial Coverage Planning and Optimization for Planetary Exploration

    NASA Technical Reports Server (NTRS)

    Gaines, Daniel M.; Estlin, Tara; Chouinard, Caroline

    2008-01-01

    We are developing onboard planning and scheduling technology to enable in situ robotic explorers, such as rovers and aerobots, to more effectively assist scientists in planetary exploration. In our current work, we are focusing on situations in which the robot is exploring large geographical features such as craters, channels or regional boundaries. In to develop valid and high quality plans, the robot must take into account a range of scientific and engineering constraints and preferences. We have developed a system that incorporates multiobjective optimization and planning allowing the robot to generate high quality mission operations plans that respect resource limitations and mission constraints while attempting to maximize science and engineering objectives. An important scientific objective for the exploration of geological features is selecting observations that spatially cover an area of interest. We have developed a metric to enable an in situ explorer to reason about and track the spatial coverage quality of a plan. We describe this technique and show how it is combined in the overall multiobjective optimization and planning algorithm.

  7. TRACON Aircraft Arrival Planning and Optimization Through Spatial Constraint Satisfaction

    NASA Technical Reports Server (NTRS)

    Bergh, Christopher P.; Krzeczowski, Kenneth J.; Davis, Thomas J.; Denery, Dallas G. (Technical Monitor)

    1995-01-01

    A new aircraft arrival planning and optimization algorithm has been incorporated into the Final Approach Spacing Tool (FAST) in the Center-TRACON Automation System (CTAS) developed at NASA-Ames Research Center. FAST simulations have been conducted over three years involving full-proficiency, level five air traffic controllers from around the United States. From these simulations an algorithm, called Spatial Constraint Satisfaction, has been designed, coded, undergone testing, and soon will begin field evaluation at the Dallas-Fort Worth and Denver International airport facilities. The purpose of this new design is an attempt to show that the generation of efficient and conflict free aircraft arrival plans at the runway does not guarantee an operationally acceptable arrival plan upstream from the runway -information encompassing the entire arrival airspace must be used in order to create an acceptable aircraft arrival plan. This new design includes functions available previously but additionally includes necessary representations of controller preferences and workload, operationally required amounts of extra separation, and integrates aircraft conflict resolution. As a result, the Spatial Constraint Satisfaction algorithm produces an optimized aircraft arrival plan that is more acceptable in terms of arrival procedures and air traffic controller workload. This paper discusses the current Air Traffic Control arrival planning procedures, previous work in this field, the design of the Spatial Constraint Satisfaction algorithm, and the results of recent evaluations of the algorithm.

  8. Optimality of profit-including prices under ideal planning.

    PubMed

    Samuelson, P A

    1973-07-01

    Although prices calculated by a constant percentage markup on all costs (nonlabor as well as direct-labor) are usually admitted to be more realistic for a competitive capitalistic model, the view is often expressed that, for optimal planning purposes, the "values" model of Marx's Capital, Volume I, is to be preferred. It is shown here that an optimal-control model that maximizes discounted social utility of consumption per capita and that ultimately approaches a steady state must ultimately have optimal pricing that involves equal rates of steady-state profit in all industries; and such optimal pricing will necessarily deviate from Marx's model of equal rates of surplus value (markups on direct-labor only) in all industries. PMID:16592102

  9. Ultrafast treatment plan optimization for volumetric modulated arc therapy (VMAT)

    SciTech Connect

    Men Chunhua; Romeijn, H. Edwin; Jia Xun; Jiang, Steve B.

    2010-11-15

    Purpose: To develop a novel aperture-based algorithm for volumetric modulated arc therapy (VMAT) treatment plan optimization with high quality and high efficiency. Methods: The VMAT optimization problem is formulated as a large-scale convex programming problem solved by a column generation approach. The authors consider a cost function consisting two terms, the first enforcing a desired dose distribution and the second guaranteeing a smooth dose rate variation between successive gantry angles. A gantry rotation is discretized into 180 beam angles and for each beam angle, only one MLC aperture is allowed. The apertures are generated one by one in a sequential way. At each iteration of the column generation method, a deliverable MLC aperture is generated for one of the unoccupied beam angles by solving a subproblem with the consideration of MLC mechanic constraints. A subsequent master problem is then solved to determine the dose rate at all currently generated apertures by minimizing the cost function. When all 180 beam angles are occupied, the optimization completes, yielding a set of deliverable apertures and associated dose rates that produce a high quality plan. Results: The algorithm was preliminarily tested on five prostate and five head-and-neck clinical cases, each with one full gantry rotation without any couch/collimator rotations. High quality VMAT plans have been generated for all ten cases with extremely high efficiency. It takes only 5-8 min on CPU (MATLAB code on an Intel Xeon 2.27 GHz CPU) and 18-31 s on GPU (CUDA code on an NVIDIA Tesla C1060 GPU card) to generate such plans. Conclusions: The authors have developed an aperture-based VMAT optimization algorithm which can generate clinically deliverable high quality treatment plans at very high efficiency.

  10. Aortic aneurysm repair. Reduced operative mortality associated with maintenance of optimal cardiac performance.

    PubMed Central

    Whittemore, A D; Clowes, A W; Hechtman, H B; Mannick, J A

    1980-01-01

    Recent advances in the operative management of aortic aneurysms have resulted in a decreased rate of morbidity and mortality. In 1972, we hypothesized that a further reduction in operative mortality might be obtained with controlled perioperative fluid management based on data provided by the thermistor-tipped pulmonary artery balloon catheter. From 1972 to 1979 a flow directed pulmonary artery catheter was inserted in each of 110 consecutive patients prior to elective or urgent repair of nonruptured infrarenal aortic aneurysms. The slope of the left ventricular performance curve was determined preoperatively by incremental infusions of salt-poor albumin and Ringer's lactate solution. With each increase in the pulmonary arterial wedge pressure (PAWP), the cardiac index (CI) was measured. The PAWP was then maintained intra- and postoperatively at levels providing optimal left ventricular performance for the individual patient. There were no 30-day operative deaths among the patients in this series and only one in-hospital mortality (0.9%), four months following surgery. The five-year cumulative survival rate for patients in the present series was 84%, a rate which does not differ significantly from that expected for a normal age-corrected population. Since the patient population was unselected and there were no substantial alterations in operative technique during the present period, these improved results support the hypothesis that operative mortality attending the elective or urgent repair of abdominal aortic aneurysm can be minimized by maintenance of optimal cardiac performance with careful attention to fluid therapy during the perioperative period. PMID:7416834

  11. Optimizing global liver function in radiation therapy treatment planning

    NASA Astrophysics Data System (ADS)

    Wu, Victor W.; Epelman, Marina A.; Wang, Hesheng; Romeijn, H. Edwin; Feng, Mary; Cao, Yue; Ten Haken, Randall K.; Matuszak, Martha M.

    2016-09-01

    Liver stereotactic body radiation therapy (SBRT) patients differ in both pre-treatment liver function (e.g. due to degree of cirrhosis and/or prior treatment) and radiosensitivity, leading to high variability in potential liver toxicity with similar doses. This work investigates three treatment planning optimization models that minimize risk of toxicity: two consider both voxel-based pre-treatment liver function and local-function-based radiosensitivity with dose; one considers only dose. Each model optimizes different objective functions (varying in complexity of capturing the influence of dose on liver function) subject to the same dose constraints and are tested on 2D synthesized and 3D clinical cases. The normal-liver-based objective functions are the linearized equivalent uniform dose (\\ell \\text{EUD} ) (conventional ‘\\ell \\text{EUD} model’), the so-called perfusion-weighted \\ell \\text{EUD} (\\text{fEUD} ) (proposed ‘fEUD model’), and post-treatment global liver function (GLF) (proposed ‘GLF model’), predicted by a new liver-perfusion-based dose-response model. The resulting \\ell \\text{EUD} , fEUD, and GLF plans delivering the same target \\ell \\text{EUD} are compared with respect to their post-treatment function and various dose-based metrics. Voxel-based portal venous liver perfusion, used as a measure of local function, is computed using DCE-MRI. In cases used in our experiments, the GLF plan preserves up to 4.6 % ≤ft(7.5 % \\right) more liver function than the fEUD (\\ell \\text{EUD} ) plan does in 2D cases, and up to 4.5 % ≤ft(5.6 % \\right) in 3D cases. The GLF and fEUD plans worsen in \\ell \\text{EUD} of functional liver on average by 1.0 Gy and 0.5 Gy in 2D and 3D cases, respectively. Liver perfusion information can be used during treatment planning to minimize the risk of toxicity by improving expected GLF; the degree of benefit varies with perfusion pattern. Although fEUD model optimization is computationally inexpensive and

  12. A set of fortran subroutines for optimizing radiotherapy plans.

    PubMed

    Redpath, A T; Vickery, B L; Wright, D H

    1975-12-01

    Quadratic Programming techniques have been applied to the optimization of radiation field weighting in Radiotherapy planning. Wedge selection has also been included by means of an exhaustive search. The radiation dose at any point in the patient may be constrained to be less than a stated percentage of the tumour dose. The routines have been successfully interfaced into a small computer interactive planning system, but they could represent an even more powerful tool in batch and time sharing systems. Minimum operator intervention is required in their use.

  13. Novel tools for stepping source brachytherapy treatment planning: Enhanced geometrical optimization and interactive inverse planning

    SciTech Connect

    Dinkla, Anna M. Laarse, Rob van der; Koedooder, Kees; Petra Kok, H.; Wieringen, Niek van; Pieters, Bradley R.; Bel, Arjan

    2015-01-15

    Purpose: Dose optimization for stepping source brachytherapy can nowadays be performed using automated inverse algorithms. Although much quicker than graphical optimization, an experienced treatment planner is required for both methods. With automated inverse algorithms, the procedure to achieve the desired dose distribution is often based on trial-and-error. Methods: A new approach for stepping source prostate brachytherapy treatment planning was developed as a quick and user-friendly alternative. This approach consists of the combined use of two novel tools: Enhanced geometrical optimization (EGO) and interactive inverse planning (IIP). EGO is an extended version of the common geometrical optimization method and is applied to create a dose distribution as homogeneous as possible. With the second tool, IIP, this dose distribution is tailored to a specific patient anatomy by interactively changing the highest and lowest dose on the contours. Results: The combined use of EGO–IIP was evaluated on 24 prostate cancer patients, by having an inexperienced user create treatment plans, compliant to clinical dose objectives. This user was able to create dose plans of 24 patients in an average time of 4.4 min/patient. An experienced treatment planner without extensive training in EGO–IIP also created 24 plans. The resulting dose-volume histogram parameters were comparable to the clinical plans and showed high conformance to clinical standards. Conclusions: Even for an inexperienced user, treatment planning with EGO–IIP for stepping source prostate brachytherapy is feasible as an alternative to current optimization algorithms, offering speed, simplicity for the user, and local control of the dose levels.

  14. Linear time near-optimal planning in the blocks world

    SciTech Connect

    Slaney, J.; Thiebaux, S.

    1996-12-31

    This paper reports an analysis of near-optimal Blocks World planning. Various methods are clarified, and their time complexity is shown to be linear in the number of blocks, which improves their known complexity bounds. The speed of the implemented programs (ten thousand blocks are handled in a second) enables us to make empirical observations on large problems. These suggest that the above methods have very close average performance ratios, and yield a rough upper bound on those ratios well below the worst case of 2. Further, they lead to the conjecture that in the limit the simplest linear time algorithm could be just as good on average as the optimal one.

  15. An Axenic Plant Culture System for Optimal Growth in Long-Term Studies: Design and Maintenance

    NASA Technical Reports Server (NTRS)

    Henry, Amelia; Doucette, William; Norton, Jeanette; Jones, Scott; Chard, Julie; Bugbee, Bruce

    2006-01-01

    The symbiotic co-evolution of plants and microbes leads to difficulties in understanding which of the two components is responsible for a given environmental response. Plant-microbe studies greatly benefit from the ability to grow plants in axenic (sterile) culture. Several studies have used axenic plant culture systems, but experimental procedures are often poorly documented, the plant growth environment is not optimal, and axenic conditions are not rigorously verified. We developed a unique axenic system using inert components that promotes plant health and can be kept sterile for at least 70 d. Crested wheatgrass (Agropyron cristatum cv. DII) plants were grown in sand within flow-through glass columns that were positively pressured with filtered air. Plant health was optimized by regulating temperature, light level, CO2 concentration, humidity, and nutrients. The design incorporates several novel aspects, such as pretreatment of the sand with Fe, graduated sand layers to optimize the air-water balance of the root zone, and modification of a laminar flow hood to serve as a plant growth chamber. Adaptations of several sterile techniques were necessary for maintenance of axenic conditions. Axenic conditions were verified by plating and staining leachates as well as rhizoplane stain. This system was designed to study nutrient and water stress effects on root exudates, but is useful for assessing a broad range of plant-microbe-environment interactions. Based on total organic C analysis, 74% of exudates was recovered in the leachate, 6% was recovered in the bulk sand, and 17% was recovered in the rhizosphere sand. Carbon in the leachate after 70 d reached 255 micro-g/d. Fumaric, malic, malonic, oxalic, and succinic acids were measured as components of the root exudates.

  16. Energy-optimal path planning by stochastic dynamically orthogonal level-set optimization

    NASA Astrophysics Data System (ADS)

    Subramani, Deepak N.; Lermusiaux, Pierre F. J.

    2016-04-01

    A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. Based on partial differential equations, the methodology rigorously leverages the level-set equation that governs time-optimal reachability fronts for a given relative vehicle-speed function. To set up the energy optimization, the relative vehicle-speed and headings are considered to be stochastic and new stochastic Dynamically Orthogonal (DO) level-set equations are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. Numerical schemes to solve the reduced stochastic DO level-set equations are obtained, and accuracy and efficiency considerations are discussed. These reduced equations are first shown to be efficient at solving the governing stochastic level-sets, in part by comparisons with direct Monte Carlo simulations. To validate the methodology and illustrate its accuracy, comparisons with semi-analytical energy-optimal path solutions are then completed. In particular, we consider the energy-optimal crossing of a canonical steady front and set up its semi-analytical solution using a energy-time nested nonlinear double-optimization scheme. We then showcase the inner workings and nuances of the energy-optimal path planning, considering different mission scenarios. Finally, we study and discuss results of energy-optimal missions in a wind-driven barotropic quasi-geostrophic double-gyre ocean circulation.

  17. Automatic treatment plan re-optimization for adaptive radiotherapy guided with the initial plan DVHs.

    PubMed

    Li, Nan; Zarepisheh, Masoud; Uribe-Sanchez, Andres; Moore, Kevin; Tian, Zhen; Zhen, Xin; Graves, Yan Jiang; Gautier, Quentin; Mell, Loren; Zhou, Linghong; Jia, Xun; Jiang, Steve

    2013-12-21

    Adaptive radiation therapy (ART) can reduce normal tissue toxicity and/or improve tumor control through treatment adaptations based on the current patient anatomy. Developing an efficient and effective re-planning algorithm is an important step toward the clinical realization of ART. For the re-planning process, manual trial-and-error approach to fine-tune planning parameters is time-consuming and is usually considered unpractical, especially for online ART. It is desirable to automate this step to yield a plan of acceptable quality with minimal interventions. In ART, prior information in the original plan is available, such as dose-volume histogram (DVH), which can be employed to facilitate the automatic re-planning process. The goal of this work is to develop an automatic re-planning algorithm to generate a plan with similar, or possibly better, DVH curves compared with the clinically delivered original plan. Specifically, our algorithm iterates the following two loops. An inner loop is the traditional fluence map optimization, in which we optimize a quadratic objective function penalizing the deviation of the dose received by each voxel from its prescribed or threshold dose with a set of fixed voxel weighting factors. In outer loop, the voxel weighting factors in the objective function are adjusted according to the deviation of the current DVH curves from those in the original plan. The process is repeated until the DVH curves are acceptable or maximum iteration step is reached. The whole algorithm is implemented on GPU for high efficiency. The feasibility of our algorithm has been demonstrated with three head-and-neck cancer IMRT cases, each having an initial planning CT scan and another treatment CT scan acquired in the middle of treatment course. Compared with the DVH curves in the original plan, the DVH curves in the resulting plan using our algorithm with 30 iterations are better for almost all structures. The re-optimization process takes about 30 s using

  18. Automatic treatment plan re-optimization for adaptive radiotherapy guided with the initial plan DVHs

    NASA Astrophysics Data System (ADS)

    Li, Nan; Zarepisheh, Masoud; Uribe-Sanchez, Andres; Moore, Kevin; Tian, Zhen; Zhen, Xin; Jiang Graves, Yan; Gautier, Quentin; Mell, Loren; Zhou, Linghong; Jia, Xun; Jiang, Steve

    2013-12-01

    Adaptive radiation therapy (ART) can reduce normal tissue toxicity and/or improve tumor control through treatment adaptations based on the current patient anatomy. Developing an efficient and effective re-planning algorithm is an important step toward the clinical realization of ART. For the re-planning process, manual trial-and-error approach to fine-tune planning parameters is time-consuming and is usually considered unpractical, especially for online ART. It is desirable to automate this step to yield a plan of acceptable quality with minimal interventions. In ART, prior information in the original plan is available, such as dose-volume histogram (DVH), which can be employed to facilitate the automatic re-planning process. The goal of this work is to develop an automatic re-planning algorithm to generate a plan with similar, or possibly better, DVH curves compared with the clinically delivered original plan. Specifically, our algorithm iterates the following two loops. An inner loop is the traditional fluence map optimization, in which we optimize a quadratic objective function penalizing the deviation of the dose received by each voxel from its prescribed or threshold dose with a set of fixed voxel weighting factors. In outer loop, the voxel weighting factors in the objective function are adjusted according to the deviation of the current DVH curves from those in the original plan. The process is repeated until the DVH curves are acceptable or maximum iteration step is reached. The whole algorithm is implemented on GPU for high efficiency. The feasibility of our algorithm has been demonstrated with three head-and-neck cancer IMRT cases, each having an initial planning CT scan and another treatment CT scan acquired in the middle of treatment course. Compared with the DVH curves in the original plan, the DVH curves in the resulting plan using our algorithm with 30 iterations are better for almost all structures. The re-optimization process takes about 30 s using

  19. Optimization and Planning of Emergency Evacuation Routes Considering Traffic Control

    PubMed Central

    Zhang, Lijun; Wang, Zhaohua

    2014-01-01

    Emergencies, especially major ones, happen fast, randomly, as well as unpredictably, and generally will bring great harm to people's life and the economy. Therefore, governments and lots of professionals devote themselves to taking effective measures and providing optimal evacuation plans. This paper establishes two different emergency evacuation models on the basis of the maximum flow model (MFM) and the minimum-cost maximum flow model (MC-MFM), and proposes corresponding algorithms for the evacuation from one source node to one designated destination (one-to-one evacuation). Ulteriorly, we extend our evaluation model from one source node to many designated destinations (one-to-many evacuation). At last, we make case analysis of evacuation optimization and planning in Beijing, and obtain the desired evacuation routes and effective traffic control measures from the perspective of sufficiency and practicability. Both analytical and numerical results support that our models are feasible and practical. PMID:24991636

  20. The optimization of operating parameters on microalgae upscaling process planning.

    PubMed

    Ma, Yu-An; Huang, Hsin-Fu; Yu, Chung-Chyi

    2016-03-01

    The upscaling process planning developed in this study primarily involved optimizing operating parameters, i.e., dilution ratios, during process designs. Minimal variable cost was used as an indicator for selecting the optimal combination of dilution ratios. The upper and lower mean confidence intervals obtained from the actual cultured cell density data were used as the final cell density stability indicator after the operating parameters or dilution ratios were selected. The process planning method and results were demonstrated through three case studies of batch culture simulation. They are (1) final objective cell densities were adjusted, (2) high and low light intensities were used for intermediate-scale cultures, and (3) the number of culture days was expressed as integers for the intermediate-scale culture.

  1. Optimization and planning of emergency evacuation routes considering traffic control.

    PubMed

    Li, Guo; Zhang, Lijun; Wang, Zhaohua

    2014-01-01

    Emergencies, especially major ones, happen fast, randomly, as well as unpredictably, and generally will bring great harm to people's life and the economy. Therefore, governments and lots of professionals devote themselves to taking effective measures and providing optimal evacuation plans. This paper establishes two different emergency evacuation models on the basis of the maximum flow model (MFM) and the minimum-cost maximum flow model (MC-MFM), and proposes corresponding algorithms for the evacuation from one source node to one designated destination (one-to-one evacuation). Ulteriorly, we extend our evaluation model from one source node to many designated destinations (one-to-many evacuation). At last, we make case analysis of evacuation optimization and planning in Beijing, and obtain the desired evacuation routes and effective traffic control measures from the perspective of sufficiency and practicability. Both analytical and numerical results support that our models are feasible and practical.

  2. 40 CFR 63.9794 - What do I need to know about operation, maintenance, and monitoring plans?

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... requirements of § 63.10(c), (e)(1), and (e)(2)(i). (12) If you operate a kiln that is subject to the limits on... alternative fuels. (13) If you operate an affected continuous kiln and you plan to take the kiln control... the kiln during periods of scheduled maintenance of the kiln control device when the kiln is...

  3. 40 CFR 63.9794 - What do I need to know about operation, maintenance, and monitoring plans?

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... requirements of § 63.10(c), (e)(1), and (e)(2)(i). (12) If you operate a kiln that is subject to the limits on... alternative fuels. (13) If you operate an affected continuous kiln and you plan to take the kiln control... the kiln during periods of scheduled maintenance of the kiln control device when the kiln is...

  4. 40 CFR 63.9794 - What do I need to know about operation, maintenance, and monitoring plans?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... requirements of § 63.10(c), (e)(1), and (e)(2)(i). (12) If you operate a kiln that is subject to the limits on... alternative fuels. (13) If you operate an affected continuous kiln and you plan to take the kiln control... the kiln during periods of scheduled maintenance of the kiln control device when the kiln is...

  5. 40 CFR 63.9794 - What do I need to know about operation, maintenance, and monitoring plans?

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... requirements of § 63.10(c), (e)(1), and (e)(2)(i). (12) If you operate a kiln that is subject to the limits on... alternative fuels. (13) If you operate an affected continuous kiln and you plan to take the kiln control... the kiln during periods of scheduled maintenance of the kiln control device when the kiln is...

  6. 40 CFR 63.9794 - What do I need to know about operation, maintenance, and monitoring plans?

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... requirements of § 63.10(c), (e)(1), and (e)(2)(i). (12) If you operate a kiln that is subject to the limits on... alternative fuels. (13) If you operate an affected continuous kiln and you plan to take the kiln control... the kiln during periods of scheduled maintenance of the kiln control device when the kiln is...

  7. 28 CFR 56.2 - Maintenance of records with respect to meetings held to develop voluntary agreements or plans of...

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Maintenance of records with respect to meetings held to develop voluntary agreements or plans of action pursuant to the Agreement on an International Energy Program. 56.2 Section 56.2 Judicial Administration DEPARTMENT OF JUSTICE (CONTINUED) INTERNATIONAL ENERGY PROGRAM § 56.2...

  8. Report on the Application of Workforce Planning Methodology in the Cuyahoga County Sanitary Engineers Operations and Maintenance Sections.

    ERIC Educational Resources Information Center

    Kordic, Michael G.

    Progress to date is reported for a project initiated in 1979 to apply a workforce planning methodology to the operations and maintenance sections of the Cuyahoga County Sanitary Engineering Department in an effort to document the human resources utilized by the Department during 1979 and to determine its personnel needs for 1980 and 1981. After…

  9. Optimal system planning with fuel shortages and emissions constraints

    SciTech Connect

    Einhorn, M.

    1983-04-01

    In addition to fuel and capital costs and duration of operation, electric-utility-system planners need a third factor for optimal system planning. The author discusses ways of determining fuel-shortage/emission-limit costs and incorporating them into the system-design framework. These costs may be directly applied to a marginal-cost-based rate design. 3 references, 8 figures, 1 table.

  10. A stochastic optimization approach for integrated urban water resource planning.

    PubMed

    Huang, Y; Chen, J; Zeng, S; Sun, F; Dong, X

    2013-01-01

    Urban water is facing the challenges of both scarcity and water quality deterioration. Consideration of nonconventional water resources has increasingly become essential over the last decade in urban water resource planning. In addition, rapid urbanization and economic development has led to an increasing uncertain water demand and fragile water infrastructures. Planning of urban water resources is thus in need of not only an integrated consideration of both conventional and nonconventional urban water resources including reclaimed wastewater and harvested rainwater, but also the ability to design under gross future uncertainties for better reliability. This paper developed an integrated nonlinear stochastic optimization model for urban water resource evaluation and planning in order to optimize urban water flows. It accounted for not only water quantity but also water quality from different sources and for different uses with different costs. The model successfully applied to a case study in Beijing, which is facing a significant water shortage. The results reveal how various urban water resources could be cost-effectively allocated by different planning alternatives and how their reliabilities would change.

  11. Optimal procedure planning and guidance system for peripheral bronchoscopy.

    PubMed

    Gibbs, Jason D; Graham, Michael W; Bascom, Rebecca; Cornish, Duane C; Khare, Rahul; Higgins, William E

    2014-03-01

    With the development of multidetector computed-tomography (MDCT) scanners and ultrathin bronchoscopes, the use of bronchoscopy for diagnosing peripheral lung-cancer nodules is becoming a viable option. The work flow for assessing lung cancer consists of two phases: 1) 3-D MDCT analysis and 2) live bronchoscopy. Unfortunately, the yield rates for peripheral bronchoscopy have been reported to be as low as 14%, and bronchoscopy performance varies considerably between physicians. Recently, proposed image-guided systems have shown promise for assisting with peripheral bronchoscopy. Yet, MDCT-based route planning to target sites has relied on tedious error-prone techniques. In addition, route planning tends not to incorporate known anatomical, device, and procedural constraints that impact a feasible route. Finally, existing systems do not effectively integrate MDCT-derived route information into the live guidance process. We propose a system that incorporates an automatic optimal route-planning method, which integrates known route constraints. Furthermore, our system offers a natural translation of the MDCT-based route plan into the live guidance strategy via MDCT/video data fusion. An image-based study demonstrates the route-planning method's functionality. Next, we present a prospective lung-cancer patient study in which our system achieved a successful navigation rate of 91% to target sites. Furthermore, when compared to a competing commercial system, our system enabled bronchoscopy over two airways deeper into the airway-tree periphery with a sample time that was nearly 2 min shorter on average. Finally, our system's ability to almost perfectly predict the depth of a bronchoscope's navigable route in advance represents a substantial benefit of optimal route planning.

  12. Optimization of intravascular brachytherapy treatment planning in peripheral arteries.

    PubMed

    Zhou, Zhengdong; Haigron, Pascal; Shu, Huazhong; Yu, Wenxue; Moisan, Cécile; Manens, Jean-Pierre; Lucas, Antoine; Luo, Limin

    2007-09-01

    This work deals with the treatment planning optimization for intravascular brachytherapy (IVB) in peripheral arteries. The objective is both to quantitatively study the validity of different hypotheses required for a reliable application of the treatment with current techniques, and to contribute to the definition and the specification of a new optimized procedure taking into account the actual patient's vessel geometry. The detection of vascular luminal surface was performed by an image analysis process, i.e., virtual active navigation, applied to standard CT data. Dose distribution was calculated according to the formalism proposed and recommended by the AAPM in TG43 and TG60. A method combining simulated annealing and BFGS algorithms was applied to optimize the parameters associated with the dwell points such as their number, positions, and dwell times. Dose-surface histogram (DSH) was used to evaluate the dose distribution results. Four levels of accuracy in target surface description were tested. The application of this optimization method to four different CT data sets including patient data, phantom and animal models showed that the treatment plan can be improved when the actual vessel geometry has been taken into account.

  13. A novel adaptive Cuckoo search for optimal query plan generation.

    PubMed

    Gomathi, Ramalingam; Sharmila, Dhandapani

    2014-01-01

    The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the resource description framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS) for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented. PMID:25215330

  14. A novel adaptive Cuckoo search for optimal query plan generation.

    PubMed

    Gomathi, Ramalingam; Sharmila, Dhandapani

    2014-01-01

    The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the resource description framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS) for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented.

  15. A Novel Adaptive Cuckoo Search for Optimal Query Plan Generation

    PubMed Central

    Gomathi, Ramalingam; Sharmila, Dhandapani

    2014-01-01

    The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the resource description framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS) for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented. PMID:25215330

  16. Nez Perce Tribal Hatchery Project, Operations and Maintenance and Planning and Design, 2001 Annual Report.

    SciTech Connect

    Larson, Roy Edward; Walker, Grant W.; Penney, Aaron K.

    2006-03-01

    This report fulfills the contract obligations based on the Statement of Work (SOW) for the project as contracted with Bonneville Power Administration (BPA). Nez Perce Tribal Hatchery (NPTH) Year-2001 annual report combines information from two contracts with a combined value of $2,336,491. They are identified by Bonneville Power Administration as follows: (1) Operations and Maintenance--Project No. 1983-350-00, Contract No. 4504, and (2) Planning and Design--Project No. 1983-350-00, Contract No. 4035. The Operations and Maintenance (O&M) budget of $2,166,110 was divided as follows: Facility Development and Fish Production Costs--$860,463; and Equipment Purchases as capital cost--$1,305,647 for equipment and subcontracts. The Planning and Design (P&D) budget of $170,381 was allocated to development of a Coho master planning document in conjunction with Nez Perce Tribal Hatchery. The O&M budget expenditures represent personnel and fish production expenses; e.g., administration, management, coordination, facility development, personnel training and fish production costs for spring Chinook and Coho salmon. Under Objective 1: Fish Culture Training and Education, tribal staff worked at Clearwater Anadromous Hatchery (CAFH) an Idaho Department of Fish and Game (IDFG) facility to produce spring Chinook smolt and parr for release that are intended to provide future broodstock for NPTH. As a training exercise, BPA allowed tribal staff to rear Coho salmon at Dworshak National Fish Hatchery, a U.S. Fish and Wildlife Service (USFWS) facility. This statement of work allows this type of training to prepare tribal staff to later rear salmon at Nez Perce Tribal Hatchery under Task 1.6. As a subset of the O&M budget, the equipment purchase budget of $1,305,647 less $82,080 for subcontracts provides operational and portable equipment necessary for NPTH facilities after construction. The equipment budget for the year was $1,223,567; this year's purchases amounted $287,364.48 (see

  17. A key to success: optimizing the planning process

    NASA Astrophysics Data System (ADS)

    Turk, Huseyin; Karakaya, Kamil

    2014-05-01

    operation planning process is analyzed according to a comprehensive approach. The difficulties of planning are identified. Consequently, for optimizing a decisionmaking process of an air operation, a planning process is identified in a virtual command and control structure.

  18. Robust, Optimal Water Infrastructure Planning Under Deep Uncertainty Using Metamodels

    NASA Astrophysics Data System (ADS)

    Maier, H. R.; Beh, E. H. Y.; Zheng, F.; Dandy, G. C.; Kapelan, Z.

    2015-12-01

    Optimal long-term planning plays an important role in many water infrastructure problems. However, this task is complicated by deep uncertainty about future conditions, such as the impact of population dynamics and climate change. One way to deal with this uncertainty is by means of robustness, which aims to ensure that water infrastructure performs adequately under a range of plausible future conditions. However, as robustness calculations require computationally expensive system models to be run for a large number of scenarios, it is generally computationally intractable to include robustness as an objective in the development of optimal long-term infrastructure plans. In order to overcome this shortcoming, an approach is developed that uses metamodels instead of computationally expensive simulation models in robustness calculations. The approach is demonstrated for the optimal sequencing of water supply augmentation options for the southern portion of the water supply for Adelaide, South Australia. A 100-year planning horizon is subdivided into ten equal decision stages for the purpose of sequencing various water supply augmentation options, including desalination, stormwater harvesting and household rainwater tanks. The objectives include the minimization of average present value of supply augmentation costs, the minimization of average present value of greenhouse gas emissions and the maximization of supply robustness. The uncertain variables are rainfall, per capita water consumption and population. Decision variables are the implementation stages of the different water supply augmentation options. Artificial neural networks are used as metamodels to enable all objectives to be calculated in a computationally efficient manner at each of the decision stages. The results illustrate the importance of identifying optimal staged solutions to ensure robustness and sustainability of water supply into an uncertain long-term future.

  19. Operations, Maintenance, and Replacement 10-Year Plan 1990-1999 : Environmental Strategy. Final Report.

    SciTech Connect

    United States. Bonneville Power Administration.

    1990-09-01

    In operating and maintaining its regional power transmission system, Bonneville Power Administration (BPA) must address environmental concerns. Pollution sources and pathways for pollution migration, including potential contamination from hazardous or toxic materials, are present. BPA must develop and follow precautionary measures, respond to emergencies, minimize wastes, redress past problems, alert and train employees to problems and safety needs, constantly evaluate this effort and update the program for improvements and changes in regulations and technology. Part of BPA's mission is to conduct its operation, maintenance, and replacement programs in an environmentally sound manner. BPA recognizes its responsibility to be good stewards of the environment. BPA will meet its environmental obligations as set forth in environmental laws and regulations. BPA intends to make consistent and measurable progress toward meeting these responsibilities. The target for the 10-Year Plan is to achieve environmental compliance and meet the following goals: (1) protect human health and the environment; (2) avoid or limit liability (3) set up an effective internal management structure to maintain compliance; and (4) achieve cost-effective compliance. 6 figs.

  20. MAROS: a decision support system for optimizing monitoring plans.

    PubMed

    Aziz, Julia J; Ling, Meng; Rifai, Hanadi S; Newell, Charles J; Gonzales, James R

    2003-01-01

    The Monitoring and Remediation Optimization System (MAROS), a decision-support software, was developed to assist in formulating cost-effective ground water long-term monitoring plans. MAROS optimizes an existing ground water monitoring program using both temporal and spatial data analyses to determine the general monitoring system category and the locations and frequency of sampling for future compliance monitoring at the site. The objective of the MAROS optimization is to minimize monitoring locations in the sampling network and reduce sampling frequency without significant loss of information, ensuring adequate future characterization of the contaminant plume. The interpretive trend analysis approach recommends the general monitoring system category for a site based on plume stability and site-specific hydrogeologic information. Plume stability is characterized using primary lines of evidence (i.e., Mann-Kendall analysis and linear regression analysis) based on concentration trends, and secondary lines of evidence based on modeling results and empirical data. The sampling optimization approach, consisting of a two-dimensional spatial sampling reduction method (Delaunay method) and a temporal sampling analysis method (Modified CES method), provides detailed sampling location and frequency results. The Delaunay method is designed to identify and eliminate redundant sampling locations without causing significant information loss in characterizing the plume. The Modified CES method determines the optimal sampling frequency for a sampling location based on the direction, magnitude, and uncertainty in its concentration trend. MAROS addresses a variety of ground water contaminants (fuels, solvents, and metals), allows import of various data formats, and is designed for continual modification of long-term monitoring plans as the plume or site conditions change over time.

  1. Aircraft path planning for optimal imaging using dynamic cost functions

    NASA Astrophysics Data System (ADS)

    Christie, Gordon; Chaudhry, Haseeb; Kochersberger, Kevin

    2015-05-01

    Unmanned aircraft development has accelerated with recent technological improvements in sensing and communications, which has resulted in an "applications lag" for how these aircraft can best be utilized. The aircraft are becoming smaller, more maneuverable and have longer endurance to perform sensing and sampling missions, but operating them aggressively to exploit these capabilities has not been a primary focus in unmanned systems development. This paper addresses a means of aerial vehicle path planning to provide a realistic optimal path in acquiring imagery for structure from motion (SfM) reconstructions and performing radiation surveys. This method will allow SfM reconstructions to occur accurately and with minimal flight time so that the reconstructions can be executed efficiently. An assumption is made that we have 3D point cloud data available prior to the flight. A discrete set of scan lines are proposed for the given area that are scored based on visibility of the scene. Our approach finds a time-efficient path and calculates trajectories between scan lines and over obstacles encountered along those scan lines. Aircraft dynamics are incorporated into the path planning algorithm as dynamic cost functions to create optimal imaging paths in minimum time. Simulations of the path planning algorithm are shown for an urban environment. We also present our approach for image-based terrain mapping, which is able to efficiently perform a 3D reconstruction of a large area without the use of GPS data.

  2. Optimization of helical tomotherapy treatment plans for prostate cancer

    NASA Astrophysics Data System (ADS)

    Grigorov, G.; Kron, T.; Wong, E.; Chen, J.; Sollazzo, J.; Rodrigues, G.

    2003-07-01

    Helical tomotherapy (HT) is a novel treatment approach where the ring gantry irradiation geometry of a helical CT scanner is combined with an intensity-modulated megavoltage x-ray fan beam. An inverse treatment planning system (TomoTherapy Inc., Madison) was used to optimize the treatment plans for ten randomly selected prostate patients. Five different sets of margins (2, 5, 7.5 and 10 mm uniform 3D margins and a non-uniform margin of 5 to 10 mm) were employed for the prostate (GTV2) and seminal vesicles (GTV1). The dose distribution was evaluated in targets, rectum, bladder and femoral heads. HT plans are characterized by a rapid dose fall off around the target in all directions resulting in low doses (less than 30% of the dose at ICRU reference point) to the femurs in all cases. Up to a margin of 5 mm for target structures, it was always possible to satisfy the requirements for dose delivery set by RTOG protocol P-0126. Using a 'class solution', HT plans require minimal operator interaction and result in excellent sparing of normal structures in prostate radiotherapy.

  3. Timber harvest planning a combined optimization/simulation model

    SciTech Connect

    Arthur, J.L.; Dykstra, D.P.

    1980-11-01

    A special cascading fixed charge model can be used to characterize a forest management planning problem in which the objectives are to identify the optimal shape of forest harvest cutting units and simultaneously to assign facilities for logging those units. A four-part methodology was developed to assist forest managers in analyzing areas proposed for harvesting. This methodology: analyzes harvesting feasibility; computes the optimal solution to the cascading fixed charge problem; undertakes a GASP IV simulation to provide additional information about the proposed harvesting operation; and permits the forest manager to perform a time-cost analysis that may lead to a more realistic, and thus improved, solution. (5 diagrams, 16 references, 3 tables)

  4. Monitoring Strategies in Permeable Pavement Systems to Optimize Maintenance Scheduling - abstract

    EPA Science Inventory

    As the surface in a permeable pavement system clogs and performance decreases, maintenance is required to preserve the design function. Currently, guidance is limited for scheduling maintenance on an as needed basis. Previous research has shown that surface clogging in a permea...

  5. Collaborative mission planning for UAV cluster to optimize relay distance

    NASA Astrophysics Data System (ADS)

    Tanil, Cagatay; Warty, Chirag; Obiedat, Esam

    Unmanned Aerial Vehicles (UAVs) coordinated path planning and intercommunication for visual exploration of a geographical region has recently become crucial. Multiple UAVs cover larger area than a single UAV and eliminate blind spots. To improve the surveillance, survivability and quality of the communication, we propose two algorithms for the route planning of UAV cluster operated in obstacle rich environment: (i) Multiple Population Genetic Algorithm (MPGA) (ii) Relay Selection Criteria (RSC). The main objective of MPGA is to minimize the total mission time while maintaining an optimal distance for communication between the neighboring nodes. MPGA utilizes evolutionary speciation techniques with a novel Feasible Population Creation Method (FPCM) and enhanced Inter-species Crossover Mechanism (ISCM) to obtain diversified routes in remarkably short time. In obtaining collision-free optimum paths, UAVs are subjected to constraints such as limited communication range, maximum maneuverability and fuel capacity. In addition to the path planning, RSC is developed for selection of UAVs relay nodes that is based on the location of the relay relative to source and destination. It is crucial since the Bit Error Rate (BER) performance of the link significantly depends on the location of the selected relay. In this paper, path planning and relay allocation algorithms are combined to have a seamless high quality monitoring of the region and to provide superior Quality of Service (QoS) for audio-video applications. Also, simulations in different operation zones with a cluster of up to six UAVs are performed to verify the feasibility of the proposed algorithms both in optimality and computation time.

  6. Improving Gas Storage Development Planning Through Simulation-Optimization

    SciTech Connect

    Johnson, V.M.; Ammer, J.; Trick, M.D.

    2000-07-25

    This is the first of two papers describing the application of simulator-optimization methods to a natural gas storage field development planning problem. The results presented here illustrate the large gains in cost-effectiveness that can be made by employing the reservoir simulator as the foundation for a wide-ranging search for solutions to management problems. The current paper illustrates the application of these techniques given a deterministic view of the reservoir. A companion paper will illustrate adaptations needed to accommodate uncertainties regarding reservoir properties.

  7. Hierarchical artificial bee colony algorithm for RFID network planning optimization.

    PubMed

    Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong

    2014-01-01

    This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness. PMID:24592200

  8. Hierarchical Artificial Bee Colony Algorithm for RFID Network Planning Optimization

    PubMed Central

    Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong

    2014-01-01

    This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness. PMID:24592200

  9. Hierarchical artificial bee colony algorithm for RFID network planning optimization.

    PubMed

    Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong

    2014-01-01

    This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.

  10. Responding to home maintenance challenge scenarios: the role of selection, optimization, and compensation in aging-in-place.

    PubMed

    Kelly, Andrew John; Fausset, Cara Bailey; Rogers, Wendy; Fisk, Arthur D

    2014-12-01

    This study examined potential issues faced by older adults in managing their homes and their proposed solutions for overcoming hypothetical difficulties. Forty-four diverse, independently living older adults (66-85) participated in structured group interviews in which they discussed potential solutions to manage difficulties presented in four scenarios: perceptual, mobility, physical, and cognitive difficulties. The proposed solutions were classified using the Selection, Optimization, and Compensation (SOC) model. Participants indicated they would continue performing most tasks and reported a range of strategies to manage home maintenance challenges. Most participants reported that they would manage home maintenance challenges using compensation; the most frequently mentioned compensation strategy was using tools and technologies. There were also differences across the scenarios: Optimization was discussed most frequently with perceptual and cognitive difficulty scenarios. These results provide insights into supporting older adults' potential needs for aging-in-place and provide evidence of the value of the SOC model in applied research.

  11. Applying theory of planned behavior to predict exercise maintenance in sarcopenic elderly

    PubMed Central

    Ahmad, Mohamad Hasnan; Shahar, Suzana; Teng, Nur Islami Mohd Fahmi; Manaf, Zahara Abdul; Sakian, Noor Ibrahim Mohd; Omar, Baharudin

    2014-01-01

    This study aimed to determine the factors associated with exercise behavior based on the theory of planned behavior (TPB) among the sarcopenic elderly people in Cheras, Kuala Lumpur. A total of 65 subjects with mean ages of 67.5±5.2 (men) and 66.1±5.1 (women) years participated in this study. Subjects were divided into two groups: 1) exercise group (n=34; 25 men, nine women); and 2) the control group (n=31; 22 men, nine women). Structural equation modeling, based on TPB components, was applied to determine specific factors that most contribute to and predict actual behavior toward exercise. Based on the TPB’s model, attitude (β=0.60) and perceived behavioral control (β=0.24) were the major predictors of intention to exercise among men at the baseline. Among women, the subjective norm (β=0.82) was the major predictor of intention to perform the exercise at the baseline. After 12 weeks, attitude (men’s, β=0.68; women’s, β=0.24) and subjective norm (men’s, β=0.12; women’s, β=0.87) were the predictors of the intention to perform the exercise. “Feels healthier with exercise” was the specific factor to improve the intention to perform and to maintain exercise behavior in men (β=0.36) and women (β=0.49). “Not motivated to perform exercise” was the main barrier among men’s intention to exercise. The intention to perform the exercise was able to predict actual behavior regarding exercise at the baseline and at 12 weeks of an intervention program. As a conclusion, TPB is a useful model to determine and to predict maintenance of exercise in the sarcopenic elderly. PMID:25258524

  12. Applying theory of planned behavior to predict exercise maintenance in sarcopenic elderly.

    PubMed

    Ahmad, Mohamad Hasnan; Shahar, Suzana; Teng, Nur Islami Mohd Fahmi; Manaf, Zahara Abdul; Sakian, Noor Ibrahim Mohd; Omar, Baharudin

    2014-01-01

    This study aimed to determine the factors associated with exercise behavior based on the theory of planned behavior (TPB) among the sarcopenic elderly people in Cheras, Kuala Lumpur. A total of 65 subjects with mean ages of 67.5±5.2 (men) and 66.1±5.1 (women) years participated in this study. Subjects were divided into two groups: 1) exercise group (n=34; 25 men, nine women); and 2) the control group (n=31; 22 men, nine women). Structural equation modeling, based on TPB components, was applied to determine specific factors that most contribute to and predict actual behavior toward exercise. Based on the TPB's model, attitude (β=0.60) and perceived behavioral control (β=0.24) were the major predictors of intention to exercise among men at the baseline. Among women, the subjective norm (β=0.82) was the major predictor of intention to perform the exercise at the baseline. After 12 weeks, attitude (men's, β=0.68; women's, β=0.24) and subjective norm (men's, β=0.12; women's, β=0.87) were the predictors of the intention to perform the exercise. "Feels healthier with exercise" was the specific factor to improve the intention to perform and to maintain exercise behavior in men (β=0.36) and women (β=0.49). "Not motivated to perform exercise" was the main barrier among men's intention to exercise. The intention to perform the exercise was able to predict actual behavior regarding exercise at the baseline and at 12 weeks of an intervention program. As a conclusion, TPB is a useful model to determine and to predict maintenance of exercise in the sarcopenic elderly.

  13. Applying theory of planned behavior to predict exercise maintenance in sarcopenic elderly.

    PubMed

    Ahmad, Mohamad Hasnan; Shahar, Suzana; Teng, Nur Islami Mohd Fahmi; Manaf, Zahara Abdul; Sakian, Noor Ibrahim Mohd; Omar, Baharudin

    2014-01-01

    This study aimed to determine the factors associated with exercise behavior based on the theory of planned behavior (TPB) among the sarcopenic elderly people in Cheras, Kuala Lumpur. A total of 65 subjects with mean ages of 67.5±5.2 (men) and 66.1±5.1 (women) years participated in this study. Subjects were divided into two groups: 1) exercise group (n=34; 25 men, nine women); and 2) the control group (n=31; 22 men, nine women). Structural equation modeling, based on TPB components, was applied to determine specific factors that most contribute to and predict actual behavior toward exercise. Based on the TPB's model, attitude (β=0.60) and perceived behavioral control (β=0.24) were the major predictors of intention to exercise among men at the baseline. Among women, the subjective norm (β=0.82) was the major predictor of intention to perform the exercise at the baseline. After 12 weeks, attitude (men's, β=0.68; women's, β=0.24) and subjective norm (men's, β=0.12; women's, β=0.87) were the predictors of the intention to perform the exercise. "Feels healthier with exercise" was the specific factor to improve the intention to perform and to maintain exercise behavior in men (β=0.36) and women (β=0.49). "Not motivated to perform exercise" was the main barrier among men's intention to exercise. The intention to perform the exercise was able to predict actual behavior regarding exercise at the baseline and at 12 weeks of an intervention program. As a conclusion, TPB is a useful model to determine and to predict maintenance of exercise in the sarcopenic elderly. PMID:25258524

  14. Decision Models for Determining the Optimal Life Test Sampling Plans

    NASA Astrophysics Data System (ADS)

    Nechval, Nicholas A.; Nechval, Konstantin N.; Purgailis, Maris; Berzins, Gundars; Strelchonok, Vladimir F.

    2010-11-01

    Life test sampling plan is a technique, which consists of sampling, inspection, and decision making in determining the acceptance or rejection of a batch of products by experiments for examining the continuous usage time of the products. In life testing studies, the lifetime is usually assumed to be distributed as either a one-parameter exponential distribution, or a two-parameter Weibull distribution with the assumption that the shape parameter is known. Such oversimplified assumptions can facilitate the follow-up analyses, but may overlook the fact that the lifetime distribution can significantly affect the estimation of the failure rate of a product. Moreover, sampling costs, inspection costs, warranty costs, and rejection costs are all essential, and ought to be considered in choosing an appropriate sampling plan. The choice of an appropriate life test sampling plan is a crucial decision problem because a good plan not only can help producers save testing time, and reduce testing cost; but it also can positively affect the image of the product, and thus attract more consumers to buy it. This paper develops the frequentist (non-Bayesian) decision models for determining the optimal life test sampling plans with an aim of cost minimization by identifying the appropriate number of product failures in a sample that should be used as a threshold in judging the rejection of a batch. The two-parameter exponential and Weibull distributions with two unknown parameters are assumed to be appropriate for modelling the lifetime of a product. A practical numerical application is employed to demonstrate the proposed approach.

  15. Integrated Toolset for WSN Application Planning, Development, Commissioning and Maintenance: The WSN-DPCM ARTEMIS-JU Project.

    PubMed

    Antonopoulos, Christos; Asimogloy, Katerina; Chiti, Sarah; D'Onofrio, Luca; Gianfranceschi, Simone; He, Danping; Iodice, Antonio; Koubias, Stavros; Koulamas, Christos; Lavagno, Luciano; Lazarescu, Mihai T; Mujica, Gabriel; Papadopoulos, George; Portilla, Jorge; Redondo, Luis; Riccio, Daniele; Riesgo, Teresa; Rodriguez, Daniel; Ruello, Giuseppe; Samoladas, Vasilis; Stoyanova, Tsenka; Touliatos, Gerasimos; Valvo, Angela; Vlahoy, Georgia

    2016-01-01

    In this article we present the main results obtained in the ARTEMIS-JU WSN-DPCM project between October 2011 and September 2015. The first objective of the project was the development of an integrated toolset for Wireless sensor networks (WSN) application planning, development, commissioning and maintenance, which aims to support application domain experts, with limited WSN expertise, to efficiently develop WSN applications from planning to lifetime maintenance. The toolset is made of three main tools: one for planning, one for application development and simulation (which can include hardware nodes), and one for network commissioning and lifetime maintenance. The tools are integrated in a single platform which promotes software reuse by automatically selecting suitable library components for application synthesis and the abstraction of the underlying architecture through the use of a middleware layer. The second objective of the project was to test the effectiveness of the toolset for the development of two case studies in different domains, one for detecting the occupancy state of parking lots and one for monitoring air concentration of harmful gasses near an industrial site. PMID:27271622

  16. Integrated Toolset for WSN Application Planning, Development, Commissioning and Maintenance: The WSN-DPCM ARTEMIS-JU Project

    PubMed Central

    Antonopoulos, Christos; Asimogloy, Katerina; Chiti, Sarah; D’Onofrio, Luca; Gianfranceschi, Simone; He, Danping; Iodice, Antonio; Koubias, Stavros; Koulamas, Christos; Lavagno, Luciano; Lazarescu, Mihai T.; Mujica, Gabriel; Papadopoulos, George; Portilla, Jorge; Redondo, Luis; Riccio, Daniele; Riesgo, Teresa; Rodriguez, Daniel; Ruello, Giuseppe; Samoladas, Vasilis; Stoyanova, Tsenka; Touliatos, Gerasimos; Valvo, Angela; Vlahoy, Georgia

    2016-01-01

    In this article we present the main results obtained in the ARTEMIS-JU WSN-DPCM project between October 2011 and September 2015. The first objective of the project was the development of an integrated toolset for Wireless sensor networks (WSN) application planning, development, commissioning and maintenance, which aims to support application domain experts, with limited WSN expertise, to efficiently develop WSN applications from planning to lifetime maintenance. The toolset is made of three main tools: one for planning, one for application development and simulation (which can include hardware nodes), and one for network commissioning and lifetime maintenance. The tools are integrated in a single platform which promotes software reuse by automatically selecting suitable library components for application synthesis and the abstraction of the underlying architecture through the use of a middleware layer. The second objective of the project was to test the effectiveness of the toolset for the development of two case studies in different domains, one for detecting the occupancy state of parking lots and one for monitoring air concentration of harmful gasses near an industrial site. PMID:27271622

  17. Integrated Toolset for WSN Application Planning, Development, Commissioning and Maintenance: The WSN-DPCM ARTEMIS-JU Project.

    PubMed

    Antonopoulos, Christos; Asimogloy, Katerina; Chiti, Sarah; D'Onofrio, Luca; Gianfranceschi, Simone; He, Danping; Iodice, Antonio; Koubias, Stavros; Koulamas, Christos; Lavagno, Luciano; Lazarescu, Mihai T; Mujica, Gabriel; Papadopoulos, George; Portilla, Jorge; Redondo, Luis; Riccio, Daniele; Riesgo, Teresa; Rodriguez, Daniel; Ruello, Giuseppe; Samoladas, Vasilis; Stoyanova, Tsenka; Touliatos, Gerasimos; Valvo, Angela; Vlahoy, Georgia

    2016-06-02

    In this article we present the main results obtained in the ARTEMIS-JU WSN-DPCM project between October 2011 and September 2015. The first objective of the project was the development of an integrated toolset for Wireless sensor networks (WSN) application planning, development, commissioning and maintenance, which aims to support application domain experts, with limited WSN expertise, to efficiently develop WSN applications from planning to lifetime maintenance. The toolset is made of three main tools: one for planning, one for application development and simulation (which can include hardware nodes), and one for network commissioning and lifetime maintenance. The tools are integrated in a single platform which promotes software reuse by automatically selecting suitable library components for application synthesis and the abstraction of the underlying architecture through the use of a middleware layer. The second objective of the project was to test the effectiveness of the toolset for the development of two case studies in different domains, one for detecting the occupancy state of parking lots and one for monitoring air concentration of harmful gasses near an industrial site.

  18. Optimized Planning Target Volume for Intact Cervical Cancer

    SciTech Connect

    Khan, Alvin; Jensen, Lindsay G.; Sun Shuai; Song, William Y.; Yashar, Catheryn M.; Mundt, Arno J.; Zhang Fuquan; Jiang, Steve B.; Mell, Loren K.

    2012-08-01

    Purpose: To model interfraction clinical target volume (CTV) variation in patients with intact cervical cancer and design a planning target volume (PTV) that minimizes normal tissue dose while maximizing CTV coverage. Methods and Materials: We analyzed 50 patients undergoing external-beam radiotherapy for intact cervical cancer using daily online cone-beam computed tomography (CBCT). The CBCTs (n = 972) for each patient were rigidly registered to the planning CT. The CTV was delineated on the planning CT (CTV{sub 0}) and the set of CBCTs ({l_brace}CTV{sub 1}-CTV{sub 25}{r_brace}). Manual (n = 98) and automated (n = 668) landmarks were placed over the surface of CTV{sub 0} with reference to defined anatomic structures. Normal vectors were extended from each landmark, and the minimum length required for a given probability of encompassing CTV{sub 1}-CTV{sub 25} was computed. The resulting expansions were used to generate an optimized PTV. Results: The mean (SD; range) normal vector length to ensure 95% coverage was 4.3 mm (2.7 mm; 1-16 mm). The uniform expansion required to ensure 95% probability of CTV coverage was 13 mm. An anisotropic margin of 20 mm anteriorly and posteriorly and 10 mm superiorly, inferiorly, and laterally also would have ensured a 95% probability of CTV coverage. The volume of the 95% optimized PTV (1470 cm{sup 3}) was significantly lower than both the anisotropic PTV (2220 cm{sup 3}) and the uniformly expanded PTV (2110 cm{sup 3}) (p < 0.001). For a 95% probability of CTV coverage, normal lengths of 1-3 mm were found along the superior and lateral regions of CTV{sub 0}, 5-10 mm along the interfaces of CTV{sub 0} with the bladder and rectum, and 10-14 mm along the anterior surface of CTV{sub 0} at the level of the uterus. Conclusion: Optimizing PTV definition according to surface landmarking resulted in a high probability of CTV coverage with reduced PTV volumes. Our results provide data justifying planning margins to use in practice and

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

    SciTech Connect

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

    2013-12-15

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

  20. Optimal planning of LEO active debris removal based on hybrid optimal control theory

    NASA Astrophysics Data System (ADS)

    Yu, Jing; Chen, Xiao-qian; Chen, Li-hu

    2015-06-01

    The mission planning of Low Earth Orbit (LEO) active debris removal problem is studied in this paper. Specifically, the Servicing Spacecraft (SSc) and several debris exist on near-circular near-coplanar LEOs. The SSc should repeatedly rendezvous with the debris, and de-orbit them until all debris are removed. Considering the long-duration effect of J2 perturbation, a linear dynamics model is used for each rendezvous. The purpose of this paper is to find the optimal service sequence and rendezvous path with minimum total rendezvous cost (Δv) for the whole mission, and some complex constraints (communication time window constraint, terminal state constraint, and time distribution constraint) should be satisfied meanwhile. Considering this mission as a hybrid optimal control problem, a mathematical model is proposed, as well as the solution method. The proposed approach is demonstrated by a typical active debris removal problem. Numerical experiments show that (1) the model and solution method proposed in this paper can effectively address the planning problem of LEO debris removal; (2) the communication time window constraint and the J2 perturbation have considerable influences on the optimization results; and (3) under the same configuration, some suboptimal sequences are equivalent to the optimal one since their difference in Δv cost is very small.

  1. On-Board Preventive Maintenance: Analysis of Effectiveness Optimal Duty Period

    NASA Technical Reports Server (NTRS)

    Tai, Ann T.; Chau, Savio N.; Alkalaj, Leon; Hecht, Herbert

    1996-01-01

    To maximize reliability of a spacecraft which performs long-life (over 10-year), deep-space mission (to outer planet), a fault-tolerant environment incorporating automatic on-board preventive maintenance is highly desirable.

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

    PubMed

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

    2013-12-01

    The increasing generation of municipal solid waste (MSW) is a major problem particularly for large urban areas with insufficient landfill capacities and inefficient waste management systems. Several options associated to the supply chain for implementing a MSW management system are available, however to determine the optimal solution several technical, economic, environmental and social aspects must be considered. Therefore, this paper proposes a mathematical programming model for the optimal planning of the supply chain associated to the MSW management system to maximize the economic benefit while accounting for technical and environmental issues. The optimization model simultaneously selects the processing technologies and their location, the distribution of wastes from cities as well as the distribution of products to markets. The problem was formulated as a multi-objective mixed-integer linear programing problem to maximize the profit of the supply chain and the amount of recycled wastes, where the results are showed through Pareto curves that tradeoff economic and environmental aspects. The proposed approach is applied to a case study for the west-central part of Mexico to consider the integration of MSW from several cities to yield useful products. The results show that an integrated utilization of MSW can provide economic, environmental and social benefits. PMID:24035245

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

    PubMed

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

    2013-12-01

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

  4. A DVH-guided IMRT optimization algorithm for automatic treatment planning and adaptive radiotherapy replanning

    SciTech Connect

    Zarepisheh, Masoud; Li, Nan; Long, Troy; Romeijn, H. Edwin; Tian, Zhen; Jia, Xun; Jiang, Steve B.

    2014-06-15

    Purpose: To develop a novel algorithm that incorporates prior treatment knowledge into intensity modulated radiation therapy optimization to facilitate automatic treatment planning and adaptive radiotherapy (ART) replanning. Methods: The algorithm automatically creates a treatment plan guided by the DVH curves of a reference plan that contains information on the clinician-approved dose-volume trade-offs among different targets/organs and among different portions of a DVH curve for an organ. In ART, the reference plan is the initial plan for the same patient, while for automatic treatment planning the reference plan is selected from a library of clinically approved and delivered plans of previously treated patients with similar medical conditions and geometry. The proposed algorithm employs a voxel-based optimization model and navigates the large voxel-based Pareto surface. The voxel weights are iteratively adjusted to approach a plan that is similar to the reference plan in terms of the DVHs. If the reference plan is feasible but not Pareto optimal, the algorithm generates a Pareto optimal plan with the DVHs better than the reference ones. If the reference plan is too restricting for the new geometry, the algorithm generates a Pareto plan with DVHs close to the reference ones. In both cases, the new plans have similar DVH trade-offs as the reference plans. Results: The algorithm was tested using three patient cases and found to be able to automatically adjust the voxel-weighting factors in order to generate a Pareto plan with similar DVH trade-offs as the reference plan. The algorithm has also been implemented on a GPU for high efficiency. Conclusions: A novel prior-knowledge-based optimization algorithm has been developed that automatically adjust the voxel weights and generate a clinical optimal plan at high efficiency. It is found that the new algorithm can significantly improve the plan quality and planning efficiency in ART replanning and automatic treatment

  5. Inverse planning optimization method for intensity modulated radiation therapy.

    PubMed

    Lan, Yihua; Ren, Haozheng; Li, Cunhua; Min, Zhifang; Wan, Jinxin; Ma, Jianxin; Hung, Chih-Cheng

    2013-10-01

    In order to facilitate the leaf sequencing process in intensity modulated radiation therapy (IMRT), and design of a practical leaf sequencing algorithm, it is an important issue to smooth the planned fluence maps. The objective is to achieve both high-efficiency and high-precision dose delivering by considering characteristics of leaf sequencing process. The key factor which affects total number of monitor units for the leaf sequencing optimization process is the max flow value of the digraph which formulated from the fluence maps. Therefore, we believe that one strategy for compromising dose conformity and total number of monitor units in dose delivery is to balance the dose distribution function and the max flow value mentioned above. However, there are too many paths in the digraph, and we don't know the flow value of which path is the maximum. The maximum flow value among the horizontal paths was selected and used in the objective function of the fluence map optimization to formulate the model. The model is a traditional linear constrained quadratic optimization model which can be solved by interior point method easily. We believe that the smoothed maps from this model are more suitable for leaf sequencing optimization process than other smoothing models. A clinical head-neck case and a prostate case were tested and compared using our proposed model and the smoothing model which is based on the minimization of total variance. The optimization results with the same level of total number of monitor units (TNMU) show that the fluence maps obtained from our model have much better dose performance for the target/non-target region than the maps from total variance based on the smoothing model. This indicates that our model achieves better dose distribution when the algorithm suppresses the TNMU at the same level. Although we have just used the max flow value of the horizontal paths in the diagraph in the objective function, a good balance has been achieved between

  6. An Improved Ant Colony Optimization Approach for Optimization of Process Planning

    PubMed Central

    Wang, JinFeng; Fan, XiaoLiang; Ding, Haimin

    2014-01-01

    Computer-aided process planning (CAPP) is an important interface between computer-aided design (CAD) and computer-aided manufacturing (CAM) in computer-integrated manufacturing environments (CIMs). In this paper, process planning problem is described based on a weighted graph, and an ant colony optimization (ACO) approach is improved to deal with it effectively. The weighted graph consists of nodes, directed arcs, and undirected arcs, which denote operations, precedence constraints among operation, and the possible visited path among operations, respectively. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPCs). A pheromone updating strategy proposed in this paper is incorporated in the standard ACO, which includes Global Update Rule and Local Update Rule. A simple method by controlling the repeated number of the same process plans is designed to avoid the local convergence. A case has been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been carried out to validate the feasibility and efficiency of the proposed approach. PMID:25097874

  7. An optimization model for long-range transmission expansion planning

    SciTech Connect

    Santos, A. Jr.; Franca, P.M.; Said, A.

    1989-02-01

    In this paper is presented a static network synthesis method applied to transmission expansion planning. The static synthesis problem is formulated as a mixed-integer network flow model that is solved by an implicit enumeration algorithm. This model considers as the objective function the most productive trade off, resulting in low investment costs and good electrical performance. The load and generation nodal equations are considered in the constraints of the model. The power transmission law of DC load flow is implicit in the optimization model. Results of computational tests are presented and they show the advantage of this method compared with a heuristic procedure. The case studies show a comparison of computational times and costs of solutions obtained for the Brazilian North-Northeast transmission system.

  8. 25 CFR 171.565 - How will I know if BIA plans to adjust my annual operation and maintenance assessment rate?

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... OF THE INTERIOR LAND AND WATER IRRIGATION OPERATION AND MAINTENANCE Financial Matters: Assessments, Billing, and Collections § 171.565 How will I know if BIA plans to adjust my annual operation...

  9. ANALYSIS OF SAFETY RELIEF VALVE PROOF TEST DATA TO OPTIMIZE LIFECYCLE MAINTENANCE COSTS

    SciTech Connect

    Gross, Robert; Harris, Stephen

    2007-08-01

    Proof test results were analyzed and compared with a proposed life cycle curve or hazard function and the limit of useful life. Relief valve proof testing procedures, statistical modeling, data collection processes, and time-in-service trends are presented. The resulting analysis of test data allows for the estimation of the PFD. Extended maintenance intervals to the limit of useful life as well as methodologies and practices for improving relief valve performance and reliability are discussed. A generic cost-benefit analysis and an expected life cycle cost reduction concludes that $90 million maintenance dollars might be avoided for a population of 3000 valves over 20 years.

  10. Value of information of repair times for offshore wind farm maintenance planning

    NASA Astrophysics Data System (ADS)

    Seyr, Helene; Muskulus, Michael

    2016-09-01

    A large contribution to the total cost of energy in offshore wind farms is due to maintenance costs. In recent years research has focused therefore on lowering the maintenance costs using different approaches. Decision support models for scheduling the maintenance exist already, dealing with different factors influencing the scheduling. Our contribution deals with the uncertainty in the repair times. Given the mean repair times for different turbine components we make some assumptions regarding the underlying repair time distribution. We compare the results of a decision support model for the mean times to repair and those repair time distributions. Additionally, distributions with the same mean but different variances are compared under the same conditions. The value of lowering the uncertainty in the repair time is calculated and we find that using distributions significantly decreases the availability, when scheduling maintenance for multiple turbines in a wind park. Having detailed information about the repair time distribution may influence the results of maintenance modeling and might help identify cost factors.

  11. Optimizing the preventive maintenance scheduling by genetic algorithm based on cost and reliability in National Iranian Drilling Company

    NASA Astrophysics Data System (ADS)

    Javanmard, Habibollah; Koraeizadeh, Abd al-Wahhab

    2016-06-01

    The present research aims at predicting the required activities for preventive maintenance in terms of equipment optimal cost and reliability. The research sample includes all offshore drilling equipment of FATH 59 Derrick Site affiliated with National Iranian Drilling Company. Regarding the method, the research uses a field methodology and in terms of its objectives, it is classified as an applied research. Some of the data are extracted from the documents available in the equipment and maintenance department of FATH 59 Derrick site, and other needed data are resulted from experts' estimates through genetic algorithm method. The research result is provided as the prediction of downtimes, costs, and reliability in a predetermined time interval. The findings of the method are applicable for all manufacturing and non-manufacturing equipment.

  12. Derivative-free generation and interpolation of convex Pareto optimal IMRT plans.

    PubMed

    Hoffmann, Aswin L; Siem, Alex Y D; den Hertog, Dick; Kaanders, Johannes H A M; Huizenga, Henk

    2006-12-21

    In inverse treatment planning for intensity-modulated radiation therapy (IMRT), beamlet intensity levels in fluence maps of high-energy photon beams are optimized. Treatment plan evaluation criteria are used as objective functions to steer the optimization process. Fluence map optimization can be considered a multi-objective optimization problem, for which a set of Pareto optimal solutions exists: the Pareto efficient frontier (PEF). In this paper, a constrained optimization method is pursued to iteratively estimate the PEF up to some predefined error. We use the property that the PEF is convex for a convex optimization problem to construct piecewise-linear upper and lower bounds to approximate the PEF from a small initial set of Pareto optimal plans. A derivative-free Sandwich algorithm is presented in which these bounds are used with three strategies to determine the location of the next Pareto optimal solution such that the uncertainty in the estimated PEF is maximally reduced. We show that an intelligent initial solution for a new Pareto optimal plan can be obtained by interpolation of fluence maps from neighbouring Pareto optimal plans. The method has been applied to a simplified clinical test case using two convex objective functions to map the trade-off between tumour dose heterogeneity and critical organ sparing. All three strategies produce representative estimates of the PEF. The new algorithm is particularly suitable for dynamic generation of Pareto optimal plans in interactive treatment planning.

  13. Optimal design of multiple stress constant accelerated life test plan on non-rectangle test region

    NASA Astrophysics Data System (ADS)

    Chen, Wenhua; Gao, Liang; Liu, Juan; Qian, Ping; Pan, Jun

    2012-11-01

    For optimal design of constant stress accelerated life test(CSALT) with two-stress, if the stresses could not reach the highest levels simultaneously, the test region becomes non-rectangular. For optimal CSALT design on non-rectangle test region, the present method is only focused on non-rectangle test region with simple boundary, and the optimization algorithm is based on experience which can not ensure to obtain the optimal plan. In this paper, considering the linear-extreme value model and the optimization goal to minimize the variance of lifetime estimate under normal stress, the optimal design method of two-stress type-I censored CSALT plan on general non-rectangular test region is proposed. First, two properties of optimal test plans are proved and the relationship of all the optimal test plans is determined analytically. Then, on the basis of the two properties, the optimal problem is simplified and the optimal design method of two-stress CSALT plan on general non-rectangular test region is proposed. Finally, a numerical example is used to illustrate the feasibility and effectiveness of the method. The result shows that the proposed method could obtain the optimal test plan on non-rectangular test regions with arbitrary boundaries. This research provides the theory and method for two-stress optimal CSALT planning on non-rectangular test regions.

  14. Knowledge Acquisition, Validation, and Maintenance in a Planning System for Automated Image Processing

    NASA Technical Reports Server (NTRS)

    Chien, Steve A.

    1996-01-01

    A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintainting the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems. This paper describes a planning application of automated imaging processing and our overall approach to knowledge acquisition for this application.

  15. Automated computer optimization for 3D treatment planning of breast irradiation

    SciTech Connect

    Chen Guangpei; Ahunbay, Ergun; Li, X. Allen

    2008-06-15

    A software package, capable of optimizing beam energy and weight and wedge angle and orientation in conjunction with commercial treatment planning system, has been developed to effectively generate three-dimensional conformal radiation therapy (3DCRT) plans for breast irradiation with complicated dosimetry requirements. A nonlinear optimization procedure was utilized for the optimization. The study with 15 patient cases shows that the technique can reduce treatment planning time and effort significantly and can give comparable or slightly better dosimetry results. The package can also be used to optimize the beam weights of 3DCRT plans for other treatment sites.

  16. Preventive Maintenance for Higher Education Facilities: A Planning & Budgeting Tool for Facilities Professionals.

    ERIC Educational Resources Information Center

    2002

    This guide is designed to help higher education facilities managers, through the implementation of preventive maintenance (PM), to increase the life of facility systems and equipment, lower overall operating costs, and provide maximum responsiveness to the college/university community. Part One, "Selling the Need," is designed to address the…

  17. Surveillance and maintenance plan for the inactive liquid low-level waste tanks at Oak Ridge National Laboratory

    SciTech Connect

    Not Available

    1994-11-01

    ORNL has a total of 54 inactive liquid low-level waste (ILLLW) tanks. In the past, these tanks were used to contain radioactive liquid wastes from various research programs, decontamination operations, and reactor operations. The tanks have since been removed from service for various reasons; the majority were retired because of their age, some due to integrity compromises, and others because they did not meet the current standards set by the Federal Facilities Agreement (FFA). Many of the tanks contain residual radioactive liquids and/or sludges. Plans are to remediate all tanks; however, until remediation of each tank, this Surveillance and Maintenance (S&M) Plan will be used to monitor the safety and inventory containment of these tanks.

  18. A fast optimization algorithm for multicriteria intensity modulated proton therapy planning

    SciTech Connect

    Chen Wei; Craft, David; Madden, Thomas M.; Zhang, Kewu; Kooy, Hanne M.; Herman, Gabor T.

    2010-09-15

    Purpose: To describe a fast projection algorithm for optimizing intensity modulated proton therapy (IMPT) plans and to describe and demonstrate the use of this algorithm in multicriteria IMPT planning. Methods: The authors develop a projection-based solver for a class of convex optimization problems and apply it to IMPT treatment planning. The speed of the solver permits its use in multicriteria optimization, where several optimizations are performed which span the space of possible treatment plans. The authors describe a plan database generation procedure which is customized to the requirements of the solver. The optimality precision of the solver can be specified by the user. Results: The authors apply the algorithm to three clinical cases: A pancreas case, an esophagus case, and a tumor along the rib cage case. Detailed analysis of the pancreas case shows that the algorithm is orders of magnitude faster than industry-standard general purpose algorithms (MOSEK's interior point optimizer, primal simplex optimizer, and dual simplex optimizer). Additionally, the projection solver has almost no memory overhead. Conclusions: The speed and guaranteed accuracy of the algorithm make it suitable for use in multicriteria treatment planning, which requires the computation of several diverse treatment plans. Additionally, given the low memory overhead of the algorithm, the method can be extended to include multiple geometric instances and proton range possibilities, for robust optimization.

  19. Optimization of a Goal Maintenance Task for Use in Clinical Applications

    PubMed Central

    Henderson, Dori; Poppe, Andrew B.; Barch, Deanna M.; Carter, Cameron S.; Gold, James M.; Ragland, John D.; Silverstein, Steven M.; Strauss, Milton E.; MacDonald, Angus W.

    2012-01-01

    Background: We sought to develop a Dot Pattern Expectancy task (DPX) to assess goal maintenance for use in clinical trials. Altering the standard task created 5 versions of the DPX to compare—a standard version and 4 others. Alterations in the interstimulus interval (ISI) length and the strength of a learned prepotent response distinguished the different tasks. These adjustments were designed to decrease administration time and/or improve reliability of the data. Methods: We determined participant eligibility in an initial session (the first of 3) using clinical interviewing tools. The initial session also included a demographic assessment and assessments of community functioning and symptom severity. All versions of the DPX were administered, across 3 sessions. Specific deficits on the context processing compared with difficulty control condition were evaluated using mixed-effects logistic regression within a hierarchical linear model. Results: We analyzed the data from 136 control participants and 138 participants with schizophrenia. Relative to a difficulty control condition, patients performed worse than controls on context processing conditions that required goal maintenance. ISI did not predict errors. Stronger prepotency was associated with increased errors in the difficulty control relative to context processing condition for controls, which improved the interpretability of findings for patients. Reliability was acceptable for a version of the task with a 10-minute running time. Conclusions: The best compromise between task duration and interpretability occurred on a version with a short ISI and a strong prepotency. PMID:22199092

  20. Long-Term Surveillance and Maintenance Plan for the U.S. Department of Energy Amchitka, Alaska, Site

    SciTech Connect

    2008-09-01

    This Long-Term Surveillance and Maintenance Plan describes how the U.S. Department of Energy (DOE) intends to fulfill its mission to maintain protection of human health and the environment at the Amchitka, Alaska, Site1. Three underground nuclear tests were conducted on Amchitka Island. The U.S. Department of Defense, in conjunction with the U.S. Atomic Energy Commission (AEC), conducted the first nuclear test (Long Shot) to provide data that would improve the United States' capability of detecting underground nuclear explosions. The second nuclear test (Milrow) was a weapons-related test conducted by AEC as a means to study the feasibility of detonating a much larger device. The final nuclear test (Cannikin), the largest United States underground test, was a weapons-related test. Surface disturbances associated with these tests have been remediated. However, radioactivity remains deep below the surface, contained in and around the test cavities, for which no feasible remediation technology has been identified. In 2006, the groundwater model (Hassan et al. 2002) was updated using 2005 data collected by the Consortium for Risk Evaluation with Stakeholder Participation. Model simulation results indicate there is no breakthrough or seepage of radionuclides into the marine environment within 2,000 years. The Amchitka conceptual model is reasonable; the flow and transport simulation is based on the best available information and data. The simulation results are a quantitative prediction supported by the best available science and technology. This Long-Term Surveillance and Maintenance Plan is an additional step intended for the protection of human health and the environment. This plan may be modified from time to time in the future consistent with the mission to protect human health

  1. 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

  2. Optimizing Curriculum Planning in Site-Based Management.

    ERIC Educational Resources Information Center

    Stewart, William J.

    1997-01-01

    Examines why curriculum planning falls short in site-based management and what can be done about it. Alternative curriculum-planning strategies include holistic planning, construction of thematic units to suit students' individual differences, and a multifaceted, cross-functional approach. Adapting corporate innovations and pursuing strategic…

  3. Guidance for the design and management of a maintenance plan to assure safety and improve the predictability of a DOE nuclear irradiation facility. Final report

    SciTech Connect

    Booth, R.S.; Kryter, R.C.; Shepard, R.L.; Smith, O.L.; Upadhyaya, B.R.; Rowan, W.J.

    1994-10-01

    A program is recommended for planning the maintenance of DOE nuclear facilities that will help safety and enhance availability throughout a facility`s life cycle. While investigating the requirements for maintenance activities, a major difference was identified between the strategy suitable for a conventional power reactor and one for a research reactor facility: the latter should provide a high degree of predicted availability (referred to hereafter as ``predictability``) to its users, whereas the former should maximize total energy production. These differing operating goals necessitate different maintenance strategies. A strategy for scheduling research reactor facility operation and shutdown for maintenance must balance safety, reliability,and predicted availability. The approach developed here is based on three major elements: (1) a probabilistic risk analysis of the balance between assured reliability and predictability (presented in Appendix C), (2) an assessment of the safety and operational impact of maintenance activities applied to various components of the facility, and (3) a data base of historical and operational information on the performance and requirements for maintenance of various components. These factors are integrated into a set of guidelines for designing a new highly maintainable facility, for preparing flexible schedules for improved maintenance of existing facilities, and for anticipating the maintenance required to extend the life of an aging facility. Although tailored to research reactor facilities, the methodology has broader applicability and may therefore be used to improved the maintenance of power reactors, particularly in anticipation of peak load demands.

  4. Coal handling {open_quotes}RCM{close_quotes} Preventive Maintenance Optimization Pilot Project Pawnee Station, Public Service Company of Colorado 1995

    SciTech Connect

    August, J.

    1996-07-01

    Public Service Company of Colorado (PSCo)`s Pawnee Station piloted a demonstration preventive maintenance optimization (PMO) on the coal handling system in 1995. This PMO effort used streamlined reliability-centered maintenance (RCM) methods. Performance, cost, and intangibles were examined before, during, and after implementation. Significant results included 20% cost reduction, 90+% emergency maintenance cost reduction, and overall improved system performance as reported by the operating personnel. Annual maintenance costs have been reduced from $440,000 to $330,000 from 1994 through 1995, and continue to decline. Current projection of annual maintenance costs (from current monthly costs) are under $250,000 for 1997. The major lessons and implications from this project are discussed here.

  5. Impact of dose calculation accuracy during optimization on lung IMRT plan quality.

    PubMed

    Li, Ying; Rodrigues, Anna; Li, Taoran; Yuan, Lulin; Yin, Fang-Fang; Wu, Q Jackie

    2015-01-01

    The purpose of this study was to evaluate the effect of dose calculation accuracy and the use of an intermediate dose calculation step during the optimization of intensity-modulated radiation therapy (IMRT) planning on the final plan quality for lung cancer patients. This study included replanning for 11 randomly selected free-breathing lung IMRT plans. The original plans were optimized using a fast pencil beam convolution algorithm. After optimization, the final dose calculation was performed using the analytical anisotropic algorithm (AAA). The Varian Treatment Planning System (TPS) Eclipse v11, includes an option to perform intermediate dose calculation during optimization using the AAA. The new plans were created using this intermediate dose calculation during optimization with the same planning objectives and dose constraints as in the original plan. Differences in dosimetric parameters for the planning target volume (PTV) dose coverage, organs-at-risk (OARs) dose sparing, and the number of monitor units (MU) between the original and new plans were analyzed. Statistical significance was determined with a p-value of less than 0.05. All plans were normalized to cover 95% of the PTV with the prescription dose. Compared with the original plans, the PTV in the new plans had on average a lower maximum dose (69.45 vs. 71.96Gy, p = 0.005), a better homogeneity index (HI) (0.08 vs. 0.12, p = 0.002), and a better conformity index (CI) (0.69 vs. 0.59, p = 0.003). In the new plans, lung sparing was increased as the volumes receiving 5, 10, and 30 Gy were reduced when compared to the original plans (40.39% vs. 42.73%, p = 0.005; 28.93% vs. 30.40%, p = 0.001; 14.11%vs. 14.84%, p = 0.031). The volume receiving 20 Gy was not significantly lower (19.60% vs. 20.38%, p = 0.052). Further, the mean dose to the lung was reduced in the new plans (11.55 vs. 12.12 Gy, p = 0.024). For the esophagus, the mean dose, the maximum dose, and the volumes receiving 20 and 60 Gy were lower in

  6. A Graph-Based Ant Colony Optimization Approach for Process Planning

    PubMed Central

    Wang, JinFeng; Fan, XiaoLiang; Wan, Shuting

    2014-01-01

    The complex process planning problem is modeled as a combinatorial optimization problem with constraints in this paper. An ant colony optimization (ACO) approach has been developed to deal with process planning problem by simultaneously considering activities such as sequencing operations, selecting manufacturing resources, and determining setup plans to achieve the optimal process plan. A weighted directed graph is conducted to describe the operations, precedence constraints between operations, and the possible visited path between operation nodes. A representation of process plan is described based on the weighted directed graph. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPC). Two cases have been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been conducted to demonstrate the feasibility and efficiency of the proposed approach. PMID:24995355

  7. 78 FR 51749 - Proposed Information Collection; Ventilation Plan and Main Fan Maintenance Record (Pertains to...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-08-21

    ... operating ventilation system is essential for maintaining a safe and healthful working environment. A well planned mine ventilation system is necessary to assure a fresh air supply to miners at all working places... protecting the safety and health of miners. Underground mines usually present harsh and hostile...

  8. 40 CFR 63.2987 - What must my operation, maintenance, and monitoring (OMM) plan include?

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ..., and monitoring (OMM) plan include? 63.2987 Section 63.2987 Protection of Environment ENVIRONMENTAL... ensure that the structural and design integrity of the combustion chamber is maintained. At a minimum..., all internal structures (such as baffles) to ensure structural integrity per the design...

  9. Optimal Treatment Planning for Skull Base Chordoma: Photons, Protons, or a Combination of Both?

    SciTech Connect

    Torres, Mylin A.; Chang, Eric L.; Mahajan, Anita; Lege, David G.; Riley, Beverly A. C.; Zhang Xiaodong; Lii, M.F.; Kornguth, David G.; Pelloski, Christopher E.; Woo, Shiao Y.

    2009-07-15

    Purpose: We compared dosimetry of proton (PR), intensity modulated radiation therapy (IMRT) photon (PH), and combined PR and IMRT PH (PP) irradiation of skull base chordomas to determine the most optimal technique. Methods and Materials: Computed tomography simulation scans of 5 patients with skull base chordoma were used to generate four treatment plans: an IMRT PH plan with 1-mm planning target volume (PTV; PH1) for stereotactic treatment, an IMRT PH plan with 3-mm PTV (PH3) for routine treatment, a PR plan with beam-specific expansion margins on the clinical target volume, and a PP plan combining PR and PH treatment. All plans were prescribed 74 Gy/Cobalt Gray equivalents (CGE) to the PTV. To facilitate comparison, the primary objective of all plans was 95% or greater PTV prescribed dose coverage. Plans then were optimized to limit dose to normal tissues. Results: PTVs ranged from 4.4 to 36.7 cc in size (mean, 21.6 cc). Mean % PTV receiving 74 Gy was highest in the PP plans (98.4%; range, 96.5-99.2%) and lowest in the PH3 plans (96.1%; range, 95.1-96.7%). PR plans were the least homogeneous and conformal. PH3 plans had the highest mean % volume (V) of brain, brainstem, chiasm, and temporal lobes greater than tolerance doses. The PH1 plans had the lowest brainstem mean % V receiving 67 Gy (V{sub 67Gy}; 2.3 Gy; range, 0-7.8 Gy) and temporal lobe mean % V{sub 65Gy} (4.3 Gy; range, 0.1-7.7 Gy). Global evaluation of the plans based on objective parameters revealed that PH1 and PP plans were more optimal than either single-modality PR or PH3 plans. Conclusions: There are dosimetric advantages to using either PH1 or PP plans, with the latter yielding the best target coverage and conformality.

  10. Application of step-drawdown test for planning agricultural groundwater well maintenance in S. Korea

    NASA Astrophysics Data System (ADS)

    Song, Sung-Ho; Lee, Byung-Sun

    2015-04-01

    Well efficiency decreases with time after development and the pumping rate is reduced sharply at a certain point. However, the rapid decrease of the efficiency definitely depends upon the physical characteristics of the aquifer, chemical properties of groundwater, pore clogging by adsorptive/precipitable materials, and use of groundwater well. In general, it is expected that an adequate and ongoing maintenance for the well is effective in extension of operating periods because major maintenance frequency requirement at municipal wells placed in the crystalline rock aquifer is known to be relatively longer. The proportion of agricultural wells (583,748) against the total groundwater ones (1,380,715) is 42.3% in 2011, S. Korea. Groundwater use accounts for 1.9 billion m3/year which indicates 48.9% of total amount available groundwater resources. Approximate 69% of the total agricultural public wells placed in crystalline rock aquifer have passed more than 10 years after development. In this study, the increase of well efficiency before and after the well disinfection/cleaning for agricultural groundwater wells in the mountains, plains, and coastal aquifer with the data of step-drawdown test was evaluated, respectively. With the concept of critical yield, the increase of available amount of groundwater was quantitatively analyzed after treatment. From the results, well efficiency increased approximately 1.5 to 4 times depending on pumping rate when the proper disinfection/cleaning methods to the wells were applied. In addition, it showed that the pumping rate of approximate 4-8% with the critical yield from step-drawdown test increased and these effects were the highest in wells which are more than 10 years elapsed. Therefore, it would be concluded that the well disinfection/cleaning methods for the purpose of increasing the efficiency are more effective for the wells that are older than 10 years.

  11. Integrated Program of Experimental Diagnostics at the NNSS. An Integrated, Prioritized Work Plan for Diagnostic Development and Maintenance and Supporting Capability

    SciTech Connect

    None, None

    2010-09-01

    This Integrated Program of Experimental Diagnostics at the NNSS is an integrated prioritized work plan for the Nevada National Security Site (NNSS), formerly the Nevada Test Site (NTS), program that is independent of individual National Security Enterprise Laboratories’ (Labs) requests or specific Subprograms being supported. This prioritized work plan is influenced by national priorities presented in the Predictive Capability Framework (PCF) and other strategy documents (Primary and Secondary Assessment Technologies Plans and the Plutonium Experiments Plan). This document satisfies completion criteria for FY 2010 MRT milestone #3496: Document an integrated, prioritized work plan for diagnostic development, maintenance, and supporting capability. This document is an update of the 3-year NNSS plan written a year ago, September 21, 2009, to define and understand Lab requests for diagnostic implementation. This plan is consistent with Lab interpretations of the PCF, Primary Assessment Technologies, and Plutonium Experiment plans.

  12. Integrated multidisciplinary optimization of rotorcraft: A plan for development

    NASA Technical Reports Server (NTRS)

    Adelman, Howard M. (Editor); Mantay, Wayne R. (Editor)

    1989-01-01

    This paper describes a joint NASA/Army initiative at the Langley Research Center to develop optimization procedures aimed at improving the rotor blade design process by integrating appropriate disciplines and accounting for important interactions among the disciplines. The paper describes the optimization formulation in terms of the objective function, design variables, and constraints. Additionally, some of the analysis aspects are discussed, validation strategies are described, and an initial attempt at defining the interdisciplinary couplings is summarized. At this writing, significant progress has been made, principally in the areas of single discipline optimization. Accomplishments are described in areas of rotor aerodynamic performance optimization for minimum hover horsepower, rotor dynamic optimization for vibration reduction, and rotor structural optimization for minimum weight.

  13. Evaluation of plan quality assurance models for prostate cancer patients based on fully automatically generated Pareto-optimal treatment plans

    NASA Astrophysics Data System (ADS)

    Wang, Yibing; Breedveld, Sebastiaan; Heijmen, Ben; Petit, Steven F.

    2016-06-01

    IMRT planning with commercial Treatment Planning Systems (TPSs) is a trial-and-error process. Consequently, the quality of treatment plans may not be consistent among patients, planners and institutions. Recently, different plan quality assurance (QA) models have been proposed, that could flag and guide improvement of suboptimal treatment plans. However, the performance of these models was validated using plans that were created using the conventional trail-and-error treatment planning process. Consequently, it is challenging to assess and compare quantitatively the accuracy of different treatment planning QA models. Therefore, we created a golden standard dataset of consistently planned Pareto-optimal IMRT plans for 115 prostate patients. Next, the dataset was used to assess the performance of a treatment planning QA model that uses the overlap volume histogram (OVH). 115 prostate IMRT plans were fully automatically planned using our in-house developed TPS Erasmus-iCycle. An existing OVH model was trained on the plans of 58 of the patients. Next it was applied to predict DVHs of the rectum, bladder and anus of the remaining 57 patients. The predictions were compared with the achieved values of the golden standard plans for the rectum D mean, V 65, and V 75, and D mean of the anus and the bladder. For the rectum, the prediction errors (predicted–achieved) were only  ‑0.2  ±  0.9 Gy (mean  ±  1 SD) for D mean,‑1.0  ±  1.6% for V 65, and  ‑0.4  ±  1.1% for V 75. For D mean of the anus and the bladder, the prediction error was 0.1  ±  1.6 Gy and 4.8  ±  4.1 Gy, respectively. Increasing the training cohort to 114 patients only led to minor improvements. A dataset of consistently planned Pareto-optimal prostate IMRT plans was generated. This dataset can be used to train new, and validate and compare existing treatment planning QA models, and has been made publicly available. The OVH model was highly

  14. Evaluation of plan quality assurance models for prostate cancer patients based on fully automatically generated Pareto-optimal treatment plans.

    PubMed

    Wang, Yibing; Breedveld, Sebastiaan; Heijmen, Ben; Petit, Steven F

    2016-06-01

    IMRT planning with commercial Treatment Planning Systems (TPSs) is a trial-and-error process. Consequently, the quality of treatment plans may not be consistent among patients, planners and institutions. Recently, different plan quality assurance (QA) models have been proposed, that could flag and guide improvement of suboptimal treatment plans. However, the performance of these models was validated using plans that were created using the conventional trail-and-error treatment planning process. Consequently, it is challenging to assess and compare quantitatively the accuracy of different treatment planning QA models. Therefore, we created a golden standard dataset of consistently planned Pareto-optimal IMRT plans for 115 prostate patients. Next, the dataset was used to assess the performance of a treatment planning QA model that uses the overlap volume histogram (OVH). 115 prostate IMRT plans were fully automatically planned using our in-house developed TPS Erasmus-iCycle. An existing OVH model was trained on the plans of 58 of the patients. Next it was applied to predict DVHs of the rectum, bladder and anus of the remaining 57 patients. The predictions were compared with the achieved values of the golden standard plans for the rectum D mean, V 65, and V 75, and D mean of the anus and the bladder. For the rectum, the prediction errors (predicted-achieved) were only  -0.2  ±  0.9 Gy (mean  ±  1 SD) for D mean,-1.0  ±  1.6% for V 65, and  -0.4  ±  1.1% for V 75. For D mean of the anus and the bladder, the prediction error was 0.1  ±  1.6 Gy and 4.8  ±  4.1 Gy, respectively. Increasing the training cohort to 114 patients only led to minor improvements. A dataset of consistently planned Pareto-optimal prostate IMRT plans was generated. This dataset can be used to train new, and validate and compare existing treatment planning QA models, and has been made publicly available. The OVH model was highly accurate

  15. Evaluation of plan quality assurance models for prostate cancer patients based on fully automatically generated Pareto-optimal treatment plans

    NASA Astrophysics Data System (ADS)

    Wang, Yibing; Breedveld, Sebastiaan; Heijmen, Ben; Petit, Steven F.

    2016-06-01

    IMRT planning with commercial Treatment Planning Systems (TPSs) is a trial-and-error process. Consequently, the quality of treatment plans may not be consistent among patients, planners and institutions. Recently, different plan quality assurance (QA) models have been proposed, that could flag and guide improvement of suboptimal treatment plans. However, the performance of these models was validated using plans that were created using the conventional trail-and-error treatment planning process. Consequently, it is challenging to assess and compare quantitatively the accuracy of different treatment planning QA models. Therefore, we created a golden standard dataset of consistently planned Pareto-optimal IMRT plans for 115 prostate patients. Next, the dataset was used to assess the performance of a treatment planning QA model that uses the overlap volume histogram (OVH). 115 prostate IMRT plans were fully automatically planned using our in-house developed TPS Erasmus-iCycle. An existing OVH model was trained on the plans of 58 of the patients. Next it was applied to predict DVHs of the rectum, bladder and anus of the remaining 57 patients. The predictions were compared with the achieved values of the golden standard plans for the rectum D mean, V 65, and V 75, and D mean of the anus and the bladder. For the rectum, the prediction errors (predicted-achieved) were only  -0.2  ±  0.9 Gy (mean  ±  1 SD) for D mean,-1.0  ±  1.6% for V 65, and  -0.4  ±  1.1% for V 75. For D mean of the anus and the bladder, the prediction error was 0.1  ±  1.6 Gy and 4.8  ±  4.1 Gy, respectively. Increasing the training cohort to 114 patients only led to minor improvements. A dataset of consistently planned Pareto-optimal prostate IMRT plans was generated. This dataset can be used to train new, and validate and compare existing treatment planning QA models, and has been made publicly available. The OVH model was highly accurate

  16. The Royal College experience and plans for the maintenance of certification program.

    PubMed

    Campbell, Craig M; Parboosingh, John

    2013-01-01

    The Royal College of Physicians and Surgeons of Canada, in 2001, implemented a mandatory maintenance of certification (MOC) program that is required for fellows to maintain membership and fellowship. Participation in the MOC program is one of the recognized pathways approved by provincial medical regulatory authorities in Canada by which specialists can demonstrate their commitment to continued competent performance in practice. This article traces the historical beginnings of the MOC program, highlighting the educational foundation and scientific evidence that influenced its philosophy, goals, and strategic priorities. The MOC program has evolved into a complex system of continuing professional development to facilitate and enable a "cultural shift'' in how we conceptualize and support the continuing professional development (CPD) of specialists. The MOC program is an educational strategy that supports a learning culture where specialists are able to design, implement and document their accomplishments from multiple learning activities to build evidence-informed practices. In the future, the MOC Program must evolve from assisting fellows to use effective educational resources "for credit" to enable fellows, leveraging a competency-based CPD model, to demonstrate their capacity to continuously improve practice. This will require innovative methods to capture learning and practice improvements in real time, integrate learning during the delivery of health care, expand automation of reporting strategies, and facilitate new sociocultural methods of emergent learning and practice change. Collectively, these directions will require a research agenda that will generate evidence for how transformative cultural change in continuing professional education of the profession can be realized.

  17. Effectiveness of robust optimization in intensity-modulated proton therapy planning for head and neck cancers

    SciTech Connect

    Liu Wei; Li Xiaoqiang; Park, Peter C.; Ronald Zhu, X.; Mohan, Radhe; Frank, Steven J.; Li Yupeng; Dong Lei

    2013-05-15

    Purpose: Intensity-modulated proton therapy (IMPT) is highly sensitive to uncertainties in beam range and patient setup. Conventionally, these uncertainties are dealt using geometrically expanded planning target volume (PTV). In this paper, the authors evaluated a robust optimization method that deals with the uncertainties directly during the spot weight optimization to ensure clinical target volume (CTV) coverage without using PTV. The authors compared the two methods for a population of head and neck (H and N) cancer patients. Methods: Two sets of IMPT plans were generated for 14 H and N cases, one being PTV-based conventionally optimized and the other CTV-based robustly optimized. For the PTV-based conventionally optimized plans, the uncertainties are accounted for by expanding CTV to PTV via margins and delivering the prescribed dose to PTV. For the CTV-based robustly optimized plans, spot weight optimization was guided to reduce the discrepancy in doses under extreme setup and range uncertainties directly, while delivering the prescribed dose to CTV rather than PTV. For each of these plans, the authors calculated dose distributions under various uncertainty settings. The root-mean-square dose (RMSD) for each voxel was computed and the area under the RMSD-volume histogram curves (AUC) was used to relatively compare plan robustness. Data derived from the dose volume histogram in the worst-case and nominal doses were used to evaluate the plan optimality. Then the plan evaluation metrics were averaged over the 14 cases and were compared with two-sided paired t tests. Results: CTV-based robust optimization led to more robust (i.e., smaller AUCs) plans for both targets and organs. Under the worst-case scenario and the nominal scenario, CTV-based robustly optimized plans showed better target coverage (i.e., greater D{sub 95%}), improved dose homogeneity (i.e., smaller D{sub 5%}- D{sub 95%}), and lower or equivalent dose to organs at risk. Conclusions: CTV

  18. Utilising pseudo-CT data for dose calculation and plan optimization in adaptive radiotherapy.

    PubMed

    Whelan, Brendan; Kumar, Shivani; Dowling, Jason; Begg, Jarrad; Lambert, Jonathan; Lim, Karen; Vinod, Shalini K; Greer, Peter B; Holloway, Lois

    2015-12-01

    To quantify the dose calculation error and resulting optimization uncertainty caused by performing inverse treatment planning on inaccurate electron density data (pseudo-CT) as needed for adaptive radiotherapy and Magnetic Resonance Imaging (MRI) based treatment planning. Planning Computer Tomography (CT) data from 10 cervix cancer patients was used to generate 4 pseudo-CT data sets. Each pseudo-CT was created based on an available method of assigning electron density to an anatomic image. An inversely modulated radiotherapy (IMRT) plan was developed on each planning CT. The dose calculation error caused by each pseudo-CT data set was quantified by comparing the dose calculated each pseudo-CT data set with that calculated on the original planning CT for the same IMRT plan. The optimization uncertainty introduced by the dose calculation error was quantified by re-optimizing the same optimization parameters on each pseudo-CT data set and comparing against the original planning CT. Dose differences were quantified by assessing the Equivalent Uniform Dose (EUD) for targets and relevant organs at risk. Across all pseudo-CT data sets and all organs, the absolute mean dose calculation error was 0.2 Gy, and was within 2 % of the prescription dose in 98.5 % of cases. Then absolute mean optimisation error was 0.3 Gy EUD, indicating that that inverse optimisation is impacted by the dose calculation error. However, the additional uncertainty introduced to plan optimisation is small compared the sources of variation which already exist. Use of inaccurate electron density data for inverse treatment planning results in a dose calculation error, which in turn introduces additional uncertainty into the plan optimization process. In this study, we showed that both of these effects are clinically acceptable for cervix cancer patients using four different pseudo-CT data sets. Dose calculation and inverse optimization on pseudo-CT is feasible for this patient cohort.

  19. Ex Vivo Maintenance of Primary Human Multiple Myeloma Cells through the Optimization of the Osteoblastic Niche

    PubMed Central

    Zhang, Wenting; Gu, Yexin; Sun, Qiaoling; Siegel, David S.; Tolias, Peter; Yang, Zheng

    2015-01-01

    We previously reported a new approach for culturing difficult-to-preserve primary patient-derived multiple myeloma cells (MMC) using an osteoblast (OSB)-derived 3D tissue scaffold constructed in a perfused microfluidic environment and a culture medium supplemented with patient plasma. In the current study, we used this biomimetic model to show, for the first time, that the long-term survival of OSB is the most critical factor in maintaining the ex vivo viability and proliferative capacity of MMC. We found that the adhesion and retention of MMC to the tissue scaffold was meditated by osteoblastic N-cadherin, as one of potential mechanisms that regulate MMC-OSB interactions. However, in the presence of MMC and patient plasma, the viability and osteogenic activity of OSB became gradually compromised, and consequently MMC could not remain viable over 3 weeks. We demonstrated that the long-term survival of both OSB and MMC could be enhanced by: (1) optimizing perfusion flow rate and patient-derived plasma composition in the culture medium and (2) replenishing OSB during culture as a practical means of prolonging MMC’s viability beyond several weeks. These findings were obtained using a high-throughput well plate-based perfusion device from the perspective of optimizing the ex vivo preservation of patient-derived MM biospecimens for downstream use in biological studies and chemosensitivity analyses. PMID:25973790

  20. Identity and the theory of planned behavior: predicting maintenance of volunteering after three years.

    PubMed

    Marta, Elena; Manzi, Claudia; Pozzi, Maura; Vignoles, Vivian Laurance

    2014-01-01

    Is identity an important predictor of social behavior? The present longitudinal study is focused on identity in order to understand why people continue to volunteer over an extended period of time. The theory of planned behavior and the role identity model of volunteering are used as theoretical framework. Two hundred thirty Italian volunteers were sampled and followed for 3 years. We analyzed functions of role identity as a volunteer. Results showed a significant impact of role identity in predicting volunteer performance after 3 years, mediated through behavioral intentions. Role identity fully mediated the relationships between behavioral intention and attitude, social norms, past behavior and parental modelling.

  1. SU-D-BRD-01: Cloud-Based Radiation Treatment Planning: Performance Evaluation of Dose Calculation and Plan Optimization

    SciTech Connect

    Na, Y; Kapp, D; Kim, Y; Xing, L; Suh, T

    2014-06-01

    Purpose: To report the first experience on the development of a cloud-based treatment planning system and investigate the performance improvement of dose calculation and treatment plan optimization of the cloud computing platform. Methods: A cloud computing-based radiation treatment planning system (cc-TPS) was developed for clinical treatment planning. Three de-identified clinical head and neck, lung, and prostate cases were used to evaluate the cloud computing platform. The de-identified clinical data were encrypted with 256-bit Advanced Encryption Standard (AES) algorithm. VMAT and IMRT plans were generated for the three de-identified clinical cases to determine the quality of the treatment plans and computational efficiency. All plans generated from the cc-TPS were compared to those obtained with the PC-based TPS (pc-TPS). The performance evaluation of the cc-TPS was quantified as the speedup factors for Monte Carlo (MC) dose calculations and large-scale plan optimizations, as well as the performance ratios (PRs) of the amount of performance improvement compared to the pc-TPS. Results: Speedup factors were improved up to 14.0-fold dependent on the clinical cases and plan types. The computation times for VMAT and IMRT plans with the cc-TPS were reduced by 91.1% and 89.4%, respectively, on average of the clinical cases compared to those with pc-TPS. The PRs were mostly better for VMAT plans (1.0 ≤ PRs ≤ 10.6 for the head and neck case, 1.2 ≤ PRs ≤ 13.3 for lung case, and 1.0 ≤ PRs ≤ 10.3 for prostate cancer cases) than for IMRT plans. The isodose curves of plans on both cc-TPS and pc-TPS were identical for each of the clinical cases. Conclusion: A cloud-based treatment planning has been setup and our results demonstrate the computation efficiency of treatment planning with the cc-TPS can be dramatically improved while maintaining the same plan quality to that obtained with the pc-TPS. This work was supported in part by the National Cancer Institute (1

  2. Automated Planning of Tangential Breast Intensity-Modulated Radiotherapy Using Heuristic Optimization

    SciTech Connect

    Purdie, Thomas G.; Dinniwell, Robert E.; Letourneau, Daniel; Hill, Christine; Sharpe, Michael B.

    2011-10-01

    Purpose: To present an automated technique for two-field tangential breast intensity-modulated radiotherapy (IMRT) treatment planning. Method and Materials: A total of 158 planned patients with Stage 0, I, and II breast cancer treated using whole-breast IMRT were retrospectively replanned using automated treatment planning tools. The tools developed are integrated into the existing clinical treatment planning system (Pinnacle{sup 3}) and are designed to perform the manual volume delineation, beam placement, and IMRT treatment planning steps carried out by the treatment planning radiation therapist. The automated algorithm, using only the radio-opaque markers placed at CT simulation as inputs, optimizes the tangential beam parameters to geometrically minimize the amount of lung and heart treated while covering the whole-breast volume. The IMRT parameters are optimized according to the automatically delineated whole-breast volume. Results: The mean time to generate a complete treatment plan was 6 min, 50 s {+-} 1 min 12 s. For the automated plans, 157 of 158 plans (99%) were deemed clinically acceptable, and 138 of 158 plans (87%) were deemed clinically improved or equal to the corresponding clinical plan when reviewed in a randomized, double-blinded study by one experienced breast radiation oncologist. In addition, overall the automated plans were dosimetrically equivalent to the clinical plans when scored for target coverage and lung and heart doses. Conclusion: We have developed robust and efficient automated tools for fully inversed planned tangential breast IMRT planning that can be readily integrated into clinical practice. The tools produce clinically acceptable plans using only the common anatomic landmarks from the CT simulation process as an input. We anticipate the tools will improve patient access to high-quality IMRT treatment by simplifying the planning process and will reduce the effort and cost of incorporating more advanced planning into clinical

  3. MEDEMAS -Medical Device Management and Maintenance System Architecture

    NASA Astrophysics Data System (ADS)

    Dogan, Ülkü Balcı; Dogan, Mehmet Ugur; Ülgen, Yekta; Özkan, Mehmed

    In the proposed study, a medical device maintenance management system (MEDEMAS) is designed and implemented which provides a data pool of medical devices, the maintenance protocols and other required information for these devices. The system also contains complete repair and maintenance history of a specific device. MEDEMAS creates optimal maintenance schedule for devices and enables the service technician to carry out and report maintenance/repair processes via remote access. Thus predicted future failures are possible to prevent or minimize. Maintenance and repair is essential for patient safety and proper functioning of the medical devices, as it prevents performance decrease of the devices, deterioration of the equipment, and detrimental effects on the health of a patient, the user or other interacting people. The study aims to make the maintenance process more accurate, more efficient, faster and easier to manage and organize; and much less confusing. The accumulated history of medical devices and maintenance personnel helps efficient facility planning.

  4. Double global optimum genetic algorithm-particle swarm optimization-based welding robot path planning

    NASA Astrophysics Data System (ADS)

    Wang, Xuewu; Shi, Yingpan; Ding, Dongyan; Gu, Xingsheng

    2016-02-01

    Spot-welding robots have a wide range of applications in manufacturing industries. There are usually many weld joints in a welding task, and a reasonable welding path to traverse these weld joints has a significant impact on welding efficiency. Traditional manual path planning techniques can handle a few weld joints effectively, but when the number of weld joints is large, it is difficult to obtain the optimal path. The traditional manual path planning method is also time consuming and inefficient, and cannot guarantee optimality. Double global optimum genetic algorithm-particle swarm optimization (GA-PSO) based on the GA and PSO algorithms is proposed to solve the welding robot path planning problem, where the shortest collision-free paths are used as the criteria to optimize the welding path. Besides algorithm effectiveness analysis and verification, the simulation results indicate that the algorithm has strong searching ability and practicality, and is suitable for welding robot path planning.

  5. Optimization of photosynthesis by multiple metabolic pathways involving interorganelle interactions: resource sharing and ROS maintenance as the bases.

    PubMed

    Sunil, Bobba; Talla, Sai K; Aswani, Vetcha; Raghavendra, Agepati S

    2013-11-01

    The bioenergetic processes of photosynthesis and respiration are mutually beneficial. Their interaction extends to photorespiration, which is linked to optimize photosynthesis. The interplay of these three pathways is facilitated by two major phenomena: sharing of energy/metabolite resources and maintenance of optimal levels of reactive oxygen species (ROS). The resource sharing among different compartments of plant cells is based on the production/utilization of reducing equivalents (NADPH, NADH) and ATP as well as on the metabolite exchange. The responsibility of generating the cellular requirements of ATP and NAD(P)H is mostly by the chloroplasts and mitochondria. In turn, besides the chloroplasts, the mitochondria, cytosol and peroxisomes are common sinks for reduced equivalents. Transporters located in membranes ensure the coordinated movement of metabolites across the cellular compartments. The present review emphasizes the beneficial interactions among photosynthesis, dark respiration and photorespiration, in relation to metabolism of C, N and S. Since the bioenergetic reactions tend to generate ROS, the cells modulate chloroplast and mitochondrial reactions, so as to ensure that the ROS levels do not rise to toxic levels. The patterns of minimization of ROS production and scavenging of excess ROS in intracellular compartments are highlighted. Some of the emerging developments are pointed out, such as model plants, orientation/movement of organelles and metabolomics.

  6. Optimization as a Tool for Consistency Maintenance in Multi-Resolution Simulation

    NASA Technical Reports Server (NTRS)

    Drewry, Darren T; Reynolds, Jr , Paul F; Emanuel, William R

    2006-01-01

    The need for new approaches to the consistent simulation of related phenomena at multiple levels of resolution is great. While many fields of application would benefit from a complete and approachable solution to this problem, such solutions have proven extremely difficult. We present a multi-resolution simulation methodology that uses numerical optimization as a tool for maintaining external consistency between models of the same phenomena operating at different levels of temporal and/or spatial resolution. Our approach follows from previous work in the disparate fields of inverse modeling and spacetime constraint-based animation. As a case study, our methodology is applied to two environmental models of forest canopy processes that make overlapping predictions under unique sets of operating assumptions, and which execute at different temporal resolutions. Experimental results are presented and future directions are addressed.

  7. Direct leaf trajectory optimization for volumetric modulated arc therapy planning with sliding window delivery

    SciTech Connect

    Papp, Dávid Unkelbach, Jan

    2014-01-15

    Purpose: The authors propose a novel optimization model for volumetric modulated arc therapy (VMAT) planning that directly optimizes deliverable leaf trajectories in the treatment plan optimization problem, and eliminates the need for a separate arc-sequencing step. Methods: In this model, a 360° arc is divided into a given number of arc segments in which the leaves move unidirectionally. This facilitates an algorithm that determines the optimal piecewise linear leaf trajectories for each arc segment, which are deliverable in a given treatment time. Multileaf collimator constraints, including maximum leaf speed and interdigitation, are accounted for explicitly. The algorithm is customized to allow for VMAT delivery using constant gantry speed and dose rate, however, the algorithm generalizes to variable gantry speed if beneficial. Results: The authors demonstrate the method for three different tumor sites: a head-and-neck case, a prostate case, and a paraspinal case. The authors first obtain a reference plan for intensity modulated radiotherapy (IMRT) using fluence map optimization and 20 intensity-modulated fields in equally spaced beam directions, which is beyond the standard of care. Modeling the typical clinical setup for the treatment sites considered, IMRT plans using seven or nine beams are also computed. Subsequently, VMAT plans are optimized by dividing the 360° arc into 20 corresponding arc segments. Assuming typical machine parameters (a dose rate of 600 MU/min, and a maximum leaf speed of 3 cm/s), it is demonstrated that the optimized VMAT plans with 2–3 min delivery time are of noticeably better quality than the 7–9 beam IMRT plans. The VMAT plan quality approaches the quality of the 20-beam IMRT benchmark plan for delivery times between 3 and 4 min. Conclusions: The results indicate that high quality treatments can be delivered in a single arc with 20 arc segments if sufficient time is allowed for modulation in each segment.

  8. Intensity modulated proton therapy treatment planning using single-field optimization: The impact of monitor unit constraints on plan quality

    SciTech Connect

    Zhu, X. R.; Sahoo, N.; Zhang, X.; Robertson, D.; Li, H.; Choi, S.; Lee, A. K.; Gillin, M. T.

    2010-03-15

    Purpose: To investigate the effect of monitor unit (MU) constraints on the dose distribution created by intensity modulated proton therapy (IMPT) treatment planning using single-field optimization (SFO). Methods: Ninety-four energies between 72.5 and 221.8 MeV are available for scanning beam IMPT delivery at our institution. The minimum and maximum MUs for delivering each pencil beam (spot) are 0.005 and 0.04, respectively. These MU constraints are not considered during optimization by the treatment planning system; spots are converted to deliverable MUs during postprocessing. Treatment plans for delivering uniform doses to rectangular volumes with and without MU constraints were generated for different target doses, spot spacings, spread-out Bragg peak (SOBP) widths, and ranges in a homogeneous phantom. Four prostate cancer patients were planned with and without MU constraints using different spot spacings. Rounding errors were analyzed using an in-house software tool. Results: From the phantom study, the authors have found that both the number of spots that have rounding errors and the magnitude of the distortion of the dose distribution from the ideally optimized distribution increases as the field dose, spot spacing, and range decrease and as the SOBP width increases. From our study of patient plans, it is clear that as the spot spacing decreases the rounding error increases, and the dose coverage of the target volume becomes unacceptable for very small spot spacings. Conclusions: Constraints on deliverable MU for each spot could create a significant distortion from the ideally optimized dose distributions for IMPT fields using SFO. To eliminate this problem, the treatment planning system should incorporate the MU constraints in the optimization process and the delivery system should reliably delivery smaller minimum MUs.

  9. Cooperative optimization of reconfigurable machine tool configurations and production process plan

    NASA Astrophysics Data System (ADS)

    Xie, Nan; Li, Aiping; Xue, Wei

    2012-09-01

    The production process plan design and configurations of reconfigurable machine tool (RMT) interact with each other. Reasonable process plans with suitable configurations of RMT help to improve product quality and reduce production cost. Therefore, a cooperative strategy is needed to concurrently solve the above issue. In this paper, the cooperative optimization model for RMT configurations and production process plan is presented. Its objectives take into account both impacts of process and configuration. Moreover, a novel genetic algorithm is also developed to provide optimal or near-optimal solutions: firstly, its chromosome is redesigned which is composed of three parts, operations, process plan and configurations of RMTs, respectively; secondly, its new selection, crossover and mutation operators are also developed to deal with the process constraints from operation processes (OP) graph, otherwise these operators could generate illegal solutions violating the limits; eventually the optimal configurations for RMT under optimal process plan design can be obtained. At last, a manufacturing line case is applied which is composed of three RMTs. It is shown from the case that the optimal process plan and configurations of RMT are concurrently obtained, and the production cost decreases 6.28% and nonmonetary performance increases 22%. The proposed method can figure out both RMT configurations and production process, improve production capacity, functions and equipment utilization for RMT.

  10. Maintenance action readiness assessment plan for White Oak Creek and Melton Branch Weir Stilling Pool cleanout at Oak Ridge National Laboratory

    SciTech Connect

    1995-08-01

    This Readiness Assessment Plan has been prepared to document operational readiness for the following maintenance action: (1) removal of sediment from the White Oak Creek and Melton Branch Weir Stilling Pools and (2) disposal of the radiologically contaminated sediment in another location upstream of the weirs in an area previously contaminated by stream overflow from Melton Branch in Waste Area Grouping 2 (WAG) at Oak Ridge National Laboratory. This project is being performed as a maintenance action rather than an action under the Comprehensive Environmental Response, Compensation, and Liability Act because the risk to human health and environment is well below the US Environmental Protection Agency`s level of concern. The decision to proceed as a maintenance action was documented by an interim action proposed plan, which is included in the administrative record. The administrative record is available for review at the US Department of Energy Information Resource Center, 105 Broadway Avenue, Oak Ridge, Tennessee 37830.

  11. 29 CFR 2550.404b-1 - Maintenance of the indicia of ownership of plan assets outside the jurisdiction of the district...

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... this section; and (2)(i) Such assets are under the management and control of a fiduciary which is a... last day of its most recent fiscal year, total client assets under its management and control in excess... 29 Labor 9 2010-07-01 2010-07-01 false Maintenance of the indicia of ownership of plan...

  12. Advantages and limitations of navigation-based multicriteria optimization (MCO) for localized prostate cancer IMRT planning

    SciTech Connect

    McGarry, Conor K.; Bokrantz, Rasmus; O’Sullivan, Joe M.; Hounsell, Alan R.

    2014-10-01

    Efficacy of inverse planning is becoming increasingly important for advanced radiotherapy techniques. This study’s aims were to validate multicriteria optimization (MCO) in RayStation (v2.4, RaySearch Laboratories, Sweden) against standard intensity-modulated radiation therapy (IMRT) optimization in Oncentra (v4.1, Nucletron BV, the Netherlands) and characterize dose differences due to conversion of navigated MCO plans into deliverable multileaf collimator apertures. Step-and-shoot IMRT plans were created for 10 patients with localized prostate cancer using both standard optimization and MCO. Acceptable standard IMRT plans with minimal average rectal dose were chosen for comparison with deliverable MCO plans. The trade-off was, for the MCO plans, managed through a user interface that permits continuous navigation between fluence-based plans. Navigated MCO plans were made deliverable at incremental steps along a trajectory between maximal target homogeneity and maximal rectal sparing. Dosimetric differences between navigated and deliverable MCO plans were also quantified. MCO plans, chosen as acceptable under navigated and deliverable conditions resulted in similar rectal sparing compared with standard optimization (33.7 ± 1.8 Gy vs 35.5 ± 4.2 Gy, p = 0.117). The dose differences between navigated and deliverable MCO plans increased as higher priority was placed on rectal avoidance. If the best possible deliverable MCO was chosen, a significant reduction in rectal dose was observed in comparison with standard optimization (30.6 ± 1.4 Gy vs 35.5 ± 4.2 Gy, p = 0.047). Improvements were, however, to some extent, at the expense of less conformal dose distributions, which resulted in significantly higher doses to the bladder for 2 of the 3 tolerance levels. In conclusion, similar IMRT plans can be created for patients with prostate cancer using MCO compared with standard optimization. Limitations exist within MCO regarding conversion of navigated plans to

  13. A knowledge-based approach to improving optimization techniques in system planning

    NASA Technical Reports Server (NTRS)

    Momoh, J. A.; Zhang, Z. Z.

    1990-01-01

    A knowledge-based (KB) approach to improve mathematical programming techniques used in the system planning environment is presented. The KB system assists in selecting appropriate optimization algorithms, objective functions, constraints and parameters. The scheme is implemented by integrating symbolic computation of rules derived from operator and planner's experience and is used for generalized optimization packages. The KB optimization software package is capable of improving the overall planning process which includes correction of given violations. The method was demonstrated on a large scale power system discussed in the paper.

  14. Cryogenics maintenance strategy

    NASA Astrophysics Data System (ADS)

    Cruzat, Fabiola

    2012-09-01

    ALMA is an interferometer composed of 66 independent systems, with specific maintenance requirements for each subsystem. To optimize the observation time and reduce downtime maintenance, requirements are very demanding. One subsystem with high maintenance efforts is cryogenics and vacuum. To organize the maintenance, the Cryogenic and Vacuum department is using and implementing different tools. These are monitoring and problem reporting systems and CMMS. This leads to different maintenance approaches: Preventive Maintenance, Corrective Maintenance and Condition Based Maintenance. In order to coordinate activities with other departments the preventive maintenance schedule is kept as flexible as systems allow. To cope with unavoidable failures, the team has to be prepared to work under any condition with the spares on time. Computerized maintenance management system (CMMS) will help to manage inventory control for reliable spare part handling, the correct record of work orders and traceability of maintenance activities. For an optimized approach the department is currently evaluating where preventive or condition based maintenance applies to comply with the individual system demand. Considering the change from maintenance contracts to in-house maintenance will help to minimize costs and increase availability of parts. Due to increased number of system and tasks the cryo team needs to grow. Training of all staff members is mandatory, in depth knowledge must be built up by doing complex maintenance activities in the Cryo group, use of advanced computerized metrology systems.

  15. A Graphical Exposition of the Inconsistency of Optimal Monetary Plans

    ERIC Educational Resources Information Center

    Steindl, Frank G.

    2007-01-01

    The author presents a geometrical framework in which the inability of discretionary policy (consistent policy in the sense of Kydland and Prescott) to be socially optimal is demonstrated. Policy based on a rule results in a higher level of utility. The author extends the model to demonstrate that policy of a Rogoff conservative central banker…

  16. Subject-Specific Planning of Femoroplasty: A Combined Evolutionary Optimization and Particle Diffusion Model Approach

    PubMed Central

    Basafa, Ehsan; Armand, Mehran

    2014-01-01

    A potential effective treatment for prevention of osteoporotic hip fractures is augmentation of the mechanical properties of the femur by injecting it with agents such as (PMMA) bone cement – femoroplasty. The operation, however, is only in research stage and can benefit substantially from computer planning and optimization. We report the results of computational planning and optimization of the procedure for biomechanical evaluation. An evolutionary optimization method was used to optimally place the cement in finite element (FE) models of seven osteoporotic bone specimens. The optimization, with some inter-specimen variations, suggested that areas close to the cortex in the superior and inferior of the neck and supero-lateral aspect of the greater trochanter will benefit from augmentation. We then used a particle-based model for bone cement diffusion simulation to match the optimized pattern, taking into account the limitations of the actual surgery, including limited volume of injection to prevent thermal necrosis. Simulations showed that the yield load can be significantly increased by more than 30%, using only 9ml of bone cement. This increase is comparable to previous literature reports where gross filling of the bone was employed instead, using more than 40ml of cement. These findings, along with the differences in the optimized plans between specimens, emphasize the need for subject-specific models for effective planning of femoral augmentation. PMID:24856887

  17. TH-C-BRD-10: An Evaluation of Three Robust Optimization Approaches in IMPT Treatment Planning

    SciTech Connect

    Cao, W; Randeniya, S; Mohan, R; Zaghian, M; Kardar, L; Lim, G; Liu, W

    2014-06-15

    Purpose: Various robust optimization approaches have been proposed to ensure the robustness of intensity modulated proton therapy (IMPT) in the face of uncertainty. In this study, we aim to investigate the performance of three classes of robust optimization approaches regarding plan optimality and robustness. Methods: Three robust optimization models were implemented in our in-house IMPT treatment planning system: 1) L2 optimization based on worst-case dose; 2) L2 optimization based on minmax objective; and 3) L1 optimization with constraints on all uncertain doses. The first model was solved by a L-BFGS algorithm; the second was solved by a gradient projection algorithm; and the third was solved by an interior point method. One nominal scenario and eight maximum uncertainty scenarios (proton range over and under 3.5%, and setup error of 5 mm for x, y, z directions) were considered in optimization. Dosimetric measurements of optimized plans from the three approaches were compared for four prostate cancer patients retrospectively selected at our institution. Results: For the nominal scenario, all three optimization approaches yielded the same coverage to the clinical treatment volume (CTV) and the L2 worst-case approach demonstrated better rectum and bladder sparing than others. For the uncertainty scenarios, the L1 approach resulted in the most robust CTV coverage against uncertainties, while the plans from L2 worst-case were less robust than others. In addition, we observed that the number of scanning spots with positive MUs from the L2 approaches was approximately twice as many as that from the L1 approach. This indicates that L1 optimization may lead to more efficient IMPT delivery. Conclusion: Our study indicated that the L1 approach best conserved the target coverage in the face of uncertainty but its resulting OAR sparing was slightly inferior to other two approaches.

  18. 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

  19. Reliability Analysis and Optimal Release Problem Considering Maintenance Time of Software Components for an Embedded OSS Porting Phase

    NASA Astrophysics Data System (ADS)

    Tamura, Yoshinobu; Yamada, Shigeru

    OSS (open source software) systems which serve as key components of critical infrastructures in our social life are still ever-expanding now. Especially, embedded OSS systems have been gaining a lot of attention in the embedded system area, i.e., Android, BusyBox, TRON, etc. However, the poor handling of quality problem and customer support prohibit the progress of embedded OSS. Also, it is difficult for developers to assess the reliability and portability of embedded OSS on a single-board computer. In this paper, we propose a method of software reliability assessment based on flexible hazard rates for the embedded OSS. Also, we analyze actual data of software failure-occurrence time-intervals to show numerical examples of software reliability assessment for the embedded OSS. Moreover, we compare the proposed hazard rate model for the embedded OSS with the typical conventional hazard rate models by using the comparison criteria of goodness-of-fit. Furthermore, we discuss the optimal software release problem for the porting-phase based on the total expected software maintenance cost.

  20. Managerial fuzzy optimal planning for solid-waste management systems

    SciTech Connect

    Chang, N.B.; Wang, S.F.

    1996-07-01

    The emphasis on waste reduction and recycling requirements prior to incineration and the promulgation of Good Combustion Practice (GCP) for emission control of trace organic compounds during incineration have created conflicting solid-waste management goals. The most critical questions in system planning include: to what extent are recycling and incineration compatible? And what are the subsequent economic impacts on the private and public sectors under specific management scenarios? However, the inherent complexity of composition, generation, and heat value of the waste streams as well as the stability of the secondary material market may result in additional difficulties in management decision making. This paper presents a nonlinear fuzzy goal programming approach for solving such questions. In particular, it demonstrates how fuzzy, or imprecise, objectives of the decision makers can be quantified through the use of specific membership functions in various types of management-planning scenarios.

  1. Optimizing the Long-Term Operating Plan of Railway Marshalling Station for Capacity Utilization Analysis

    PubMed Central

    Zhou, Wenliang; Yang, Xia; Deng, Lianbo

    2014-01-01

    Not only is the operating plan the basis of organizing marshalling station's operation, but it is also used to analyze in detail the capacity utilization of each facility in marshalling station. In this paper, a long-term operating plan is optimized mainly for capacity utilization analysis. Firstly, a model is developed to minimize railcars' average staying time with the constraints of minimum time intervals, marshalling track capacity, and so forth. Secondly, an algorithm is designed to solve this model based on genetic algorithm (GA) and simulation method. It divides the plan of whole planning horizon into many subplans, and optimizes them with GA one by one in order to obtain a satisfactory plan with less computing time. Finally, some numeric examples are constructed to analyze (1) the convergence of the algorithm, (2) the effect of some algorithm parameters, and (3) the influence of arrival train flow on the algorithm. PMID:25525614

  2. Optimization of multi-objective integrated process planning and scheduling problem using a priority based optimization algorithm

    NASA Astrophysics Data System (ADS)

    Ausaf, Muhammad Farhan; Gao, Liang; Li, Xinyu

    2015-12-01

    For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem.

  3. Robustness of IPSA optimized high-dose-rate prostate brachytherapy treatment plans to catheter displacements

    PubMed Central

    Whitaker, May

    2016-01-01

    Purpose Inverse planning simulated annealing (IPSA) optimized brachytherapy treatment plans are characterized with large isolated dwell times at the first or last dwell position of each catheter. The potential of catheter shifts relative to the target and organs at risk in these plans may lead to a more significant change in delivered dose to the volumes of interest relative to plans with more uniform dwell times. Material and methods This study aims to determine if the Nucletron Oncentra dwell time deviation constraint (DTDC) parameter can be optimized to improve the robustness of high-dose-rate (HDR) prostate brachytherapy plans to catheter displacements. A set of 10 clinically acceptable prostate plans were re-optimized with a DTDC parameter of 0 and 0.4. For each plan, catheter displacements of 3, 7, and 14 mm were retrospectively applied and the change in dose volume histogram (DVH) indices and conformity indices analyzed. Results The robustness of clinically acceptable prostate plans to catheter displacements in the caudal direction was found to be dependent on the DTDC parameter. A DTDC value of 0 improves the robustness of planning target volume (PTV) coverage to catheter displacements, whereas a DTDC value of 0.4 improves the robustness of the plans to changes in hotspots. Conclusions The results indicate that if used in conjunction with a pre-treatment catheter displacement correction protocol and a tolerance of 3 mm, a DTDC value of 0.4 may produce clinically superior plans. However, the effect of the DTDC parameter in plan robustness was not observed to be as strong as initially suspected. PMID:27504129

  4. Optimal planning of a cascade-type multistage refrigeration system for a beverage plant

    SciTech Connect

    Shiba, Takashi; Ito, Koichi; Yokoyama, Ryohei; Sakashita, Shigeru; Himura, Yoshiaki

    1999-07-01

    An optimal planning method is presented for a cascade-type multistage refrigeration system. Heat exchange areas of evaporator, condenser, and beverage cooler are determined optimally so as to minimize the annual total cost and input energy consumption subject to constraints concerning annual equipment operation. This problem is considered as a multiobjective optimization one, and a discrete set of Pareto optimal solutions is derived numerically by a weighting method. Through a numerical study, it is investigated how the heat exchange areas influence the long-term economics and energy conservation. Cascade-type multistage refrigeration systems are compared with single stage systems.

  5. On-line re-optimization of prostate IMRT plans for adaptive radiation therapy

    NASA Astrophysics Data System (ADS)

    Wu, Q. Jackie; Thongphiew, Danthai; Wang, Zhiheng; Mathayomchan, Boonyanit; Chankong, Vira; Yoo, Sua; Lee, W. Robert; Yin, Fang-Fang

    2008-02-01

    For intermediate and high risk prostate cancer, both the prostate gland and seminal vesicles are included in the clinical target volume. Internal motion patterns of these two organs vary, presenting a challenge for adaptive treatment. Adaptive techniques such as isocenter repositioning and soft tissue alignment are effective when tumor volumes only exhibit translational shift, while direct re-optimization of the intensity-modulated radiation therapy (IMRT) plan maybe more desirable when extreme deformation or differential positioning changes of the organs occur. Currently, direct re-optimization of the IMRT plan using beamlet (or fluence map) has not been reported. In this study, we report a novel on-line re-optimization technique that can accomplish plan adjustment on-line. Deformable image registration is used to provide position variation information on each voxel along the three dimensions. The original planned dose distribution is used as the 'goal' dose distribution for adaptation and to ensure planning quality. Fluence maps are re-optimized via linear programming, and a plan solution can be achieved within 2 min. The feasibility of this technique is demonstrated with a clinical case with large deformation. Such on-line ART process can be highly valuable with hypo-fractionated prostate IMRT treatment. Abstract and preliminary data presented at 49th AAPM Annual Meeting, Minneapolis, MN, USA, July 2007.

  6. On-line re-optimization of prostate IMRT plans for adaptive radiation therapy.

    PubMed

    Wu, Q Jackie; Thongphiew, Danthai; Wang, Zhiheng; Mathayomchan, Boonyanit; Chankong, Vira; Yoo, Sua; Lee, W Robert; Yin, Fang-Fang

    2008-02-01

    For intermediate and high risk prostate cancer, both the prostate gland and seminal vesicles are included in the clinical target volume. Internal motion patterns of these two organs vary, presenting a challenge for adaptive treatment. Adaptive techniques such as isocenter repositioning and soft tissue alignment are effective when tumor volumes only exhibit translational shift, while direct re-optimization of the intensity-modulated radiation therapy (IMRT) plan maybe more desirable when extreme deformation or differential positioning changes of the organs occur. Currently, direct re-optimization of the IMRT plan using beamlet (or fluence map) has not been reported. In this study, we report a novel on-line re-optimization technique that can accomplish plan adjustment on-line. Deformable image registration is used to provide position variation information on each voxel along the three dimensions. The original planned dose distribution is used as the 'goal' dose distribution for adaptation and to ensure planning quality. Fluence maps are re-optimized via linear programming, and a plan solution can be achieved within 2 min. The feasibility of this technique is demonstrated with a clinical case with large deformation. Such on-line ART process can be highly valuable with hypo-fractionated prostate IMRT treatment. PMID:18199909

  7. A new Monte Carlo-based treatment plan optimization approach for intensity modulated radiation therapy.

    PubMed

    Li, Yongbao; Tian, Zhen; Shi, Feng; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

    2015-04-01

    Intensity-modulated radiation treatment (IMRT) plan optimization needs beamlet dose distributions. Pencil-beam or superposition/convolution type algorithms are typically used because of their high computational speed. However, inaccurate beamlet dose distributions may mislead the optimization process and hinder the resulting plan quality. To solve this problem, the Monte Carlo (MC) simulation method has been used to compute all beamlet doses prior to the optimization step. The conventional approach samples the same number of particles from each beamlet. Yet this is not the optimal use of MC in this problem. In fact, there are beamlets that have very small intensities after solving the plan optimization problem. For those beamlets, it may be possible to use fewer particles in dose calculations to increase efficiency. Based on this idea, we have developed a new MC-based IMRT plan optimization framework that iteratively performs MC dose calculation and plan optimization. At each dose calculation step, the particle numbers for beamlets were adjusted based on the beamlet intensities obtained through solving the plan optimization problem in the last iteration step. We modified a GPU-based MC dose engine to allow simultaneous computations of a large number of beamlet doses. To test the accuracy of our modified dose engine, we compared the dose from a broad beam and the summed beamlet doses in this beam in an inhomogeneous phantom. Agreement within 1% for the maximum difference and 0.55% for the average difference was observed. We then validated the proposed MC-based optimization schemes in one lung IMRT case. It was found that the conventional scheme required 10(6) particles from each beamlet to achieve an optimization result that was 3% difference in fluence map and 1% difference in dose from the ground truth. In contrast, the proposed scheme achieved the same level of accuracy with on average 1.2 × 10(5) particles per beamlet. Correspondingly, the computation

  8. A new Monte Carlo-based treatment plan optimization approach for intensity modulated radiation therapy

    NASA Astrophysics Data System (ADS)

    Li, Yongbao; Tian, Zhen; Shi, Feng; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

    2015-04-01

    Intensity-modulated radiation treatment (IMRT) plan optimization needs beamlet dose distributions. Pencil-beam or superposition/convolution type algorithms are typically used because of their high computational speed. However, inaccurate beamlet dose distributions may mislead the optimization process and hinder the resulting plan quality. To solve this problem, the Monte Carlo (MC) simulation method has been used to compute all beamlet doses prior to the optimization step. The conventional approach samples the same number of particles from each beamlet. Yet this is not the optimal use of MC in this problem. In fact, there are beamlets that have very small intensities after solving the plan optimization problem. For those beamlets, it may be possible to use fewer particles in dose calculations to increase efficiency. Based on this idea, we have developed a new MC-based IMRT plan optimization framework that iteratively performs MC dose calculation and plan optimization. At each dose calculation step, the particle numbers for beamlets were adjusted based on the beamlet intensities obtained through solving the plan optimization problem in the last iteration step. We modified a GPU-based MC dose engine to allow simultaneous computations of a large number of beamlet doses. To test the accuracy of our modified dose engine, we compared the dose from a broad beam and the summed beamlet doses in this beam in an inhomogeneous phantom. Agreement within 1% for the maximum difference and 0.55% for the average difference was observed. We then validated the proposed MC-based optimization schemes in one lung IMRT case. It was found that the conventional scheme required 106 particles from each beamlet to achieve an optimization result that was 3% difference in fluence map and 1% difference in dose from the ground truth. In contrast, the proposed scheme achieved the same level of accuracy with on average 1.2 × 105 particles per beamlet. Correspondingly, the computation time

  9. Optimal Medical Equipment Maintenance Service Proposal Decision Support System combining Activity Based Costing (ABC) and the Analytic Hierarchy Process (AHP).

    PubMed

    da Rocha, Leticia; Sloane, Elliot; M Bassani, Jose

    2005-01-01

    This study describes a framework to support the choice of the maintenance service (in-house or third party contract) for each category of medical equipment based on: a) the real medical equipment maintenance management system currently used by the biomedical engineering group of the public health system of the Universidade Estadual de Campinas located in Brazil to control the medical equipment maintenance service, b) the Activity Based Costing (ABC) method, and c) the Analytic Hierarchy Process (AHP) method. Results show the cost and performance related to each type of maintenance service. Decision-makers can use these results to evaluate possible strategies for the categories of equipment.

  10. Optimal Medical Equipment Maintenance Service Proposal Decision Support System combining Activity Based Costing (ABC) and the Analytic Hierarchy Process (AHP).

    PubMed

    da Rocha, Leticia; Sloane, Elliot; M Bassani, Jose

    2005-01-01

    This study describes a framework to support the choice of the maintenance service (in-house or third party contract) for each category of medical equipment based on: a) the real medical equipment maintenance management system currently used by the biomedical engineering group of the public health system of the Universidade Estadual de Campinas located in Brazil to control the medical equipment maintenance service, b) the Activity Based Costing (ABC) method, and c) the Analytic Hierarchy Process (AHP) method. Results show the cost and performance related to each type of maintenance service. Decision-makers can use these results to evaluate possible strategies for the categories of equipment. PMID:17281912

  11. A Tool for Optimizing Observation Planning for Faint Moving Objects

    NASA Astrophysics Data System (ADS)

    Arredondo, Anicia; Bosh, Amanda S.; Levine, Stephen

    2016-10-01

    Observations of small solar system bodies such as trans-Neptunian objects and Centaurs are vital for understanding the basic properties of these small members of our solar system. Because these objects are often very faint, large telescopes and long exposures may be necessary, which can result in crowded fields in which the target of interest may be blended with a field star. For accurate photometry and astrometry, observations must be planned to occur when the target is free of background stars; this restriction results in limited observing windows. We have created a tool that can be used to plan observations of faint moving objects. Features of the tool include estimates of best times to observe (when the object is not too near another object), a finder chart output, a list of possible astrometric and photometric reference stars, and an exposure time calculator. This work makes use of the USNOFS Image and Catalogue Archive operated by the United States Naval Observatory, Flagstaff Station (S.E. Levine and D.G. Monet 2000), the JPL Horizons online ephemeris service (Giorgini et al. 1996), the Minor Planet Center's MPChecker (http://cgi.minorplanetcenter.net/cgi-bin/checkmp.cgi), and source extraction software SExtractor (Bertin & Arnouts 1996). Support for this work was provided by NASA SSO grant NNX15AJ82G.

  12. Inverse 4D conformal planning for lung SBRT using particle swarm optimization.

    PubMed

    Modiri, A; Gu, X; Hagan, A; Bland, R; Iyengar, P; Timmerman, R; Sawant, A

    2016-08-21

    A critical aspect of highly potent regimens such as lung stereotactic body radiation therapy (SBRT) is to avoid collateral toxicity while achieving planning target volume (PTV) coverage. In this work, we describe four dimensional conformal radiotherapy using a highly parallelizable swarm intelligence-based stochastic optimization technique. Conventional lung CRT-SBRT uses a 4DCT to create an internal target volume and then, using forward-planning, generates a 3D conformal plan. In contrast, we investigate an inverse-planning strategy that uses 4DCT data to create a 4D conformal plan, which is optimized across the three spatial dimensions (3D) as well as time, as represented by the respiratory phase. The key idea is to use respiratory motion as an additional degree of freedom. We iteratively adjust fluence weights for all beam apertures across all respiratory phases considering OAR sparing, PTV coverage and delivery efficiency. To demonstrate proof-of-concept, five non-small-cell lung cancer SBRT patients were retrospectively studied. The 4D optimized plans achieved PTV coverage comparable to the corresponding clinically delivered plans while showing significantly superior OAR sparing ranging from 26% to 83% for D max heart, 10%-41% for D max esophagus, 31%-68% for D max spinal cord and 7%-32% for V 13 lung. PMID:27476472

  13. Inverse 4D conformal planning for lung SBRT using particle swarm optimization

    NASA Astrophysics Data System (ADS)

    Modiri, A.; Gu, X.; Hagan, A.; Bland, R.; Iyengar, P.; Timmerman, R.; Sawant, A.

    2016-08-01

    A critical aspect of highly potent regimens such as lung stereotactic body radiation therapy (SBRT) is to avoid collateral toxicity while achieving planning target volume (PTV) coverage. In this work, we describe four dimensional conformal radiotherapy using a highly parallelizable swarm intelligence-based stochastic optimization technique. Conventional lung CRT-SBRT uses a 4DCT to create an internal target volume and then, using forward-planning, generates a 3D conformal plan. In contrast, we investigate an inverse-planning strategy that uses 4DCT data to create a 4D conformal plan, which is optimized across the three spatial dimensions (3D) as well as time, as represented by the respiratory phase. The key idea is to use respiratory motion as an additional degree of freedom. We iteratively adjust fluence weights for all beam apertures across all respiratory phases considering OAR sparing, PTV coverage and delivery efficiency. To demonstrate proof-of-concept, five non-small-cell lung cancer SBRT patients were retrospectively studied. The 4D optimized plans achieved PTV coverage comparable to the corresponding clinically delivered plans while showing significantly superior OAR sparing ranging from 26% to 83% for D max heart, 10%–41% for D max esophagus, 31%–68% for D max spinal cord and 7%–32% for V 13 lung.

  14. Inverse 4D conformal planning for lung SBRT using particle swarm optimization.

    PubMed

    Modiri, A; Gu, X; Hagan, A; Bland, R; Iyengar, P; Timmerman, R; Sawant, A

    2016-08-21

    A critical aspect of highly potent regimens such as lung stereotactic body radiation therapy (SBRT) is to avoid collateral toxicity while achieving planning target volume (PTV) coverage. In this work, we describe four dimensional conformal radiotherapy using a highly parallelizable swarm intelligence-based stochastic optimization technique. Conventional lung CRT-SBRT uses a 4DCT to create an internal target volume and then, using forward-planning, generates a 3D conformal plan. In contrast, we investigate an inverse-planning strategy that uses 4DCT data to create a 4D conformal plan, which is optimized across the three spatial dimensions (3D) as well as time, as represented by the respiratory phase. The key idea is to use respiratory motion as an additional degree of freedom. We iteratively adjust fluence weights for all beam apertures across all respiratory phases considering OAR sparing, PTV coverage and delivery efficiency. To demonstrate proof-of-concept, five non-small-cell lung cancer SBRT patients were retrospectively studied. The 4D optimized plans achieved PTV coverage comparable to the corresponding clinically delivered plans while showing significantly superior OAR sparing ranging from 26% to 83% for D max heart, 10%-41% for D max esophagus, 31%-68% for D max spinal cord and 7%-32% for V 13 lung.

  15. Inverse 4D conformal planning for lung SBRT using particle swarm optimization

    NASA Astrophysics Data System (ADS)

    Modiri, A.; Gu, X.; Hagan, A.; Bland, R.; Iyengar, P.; Timmerman, R.; Sawant, A.

    2016-08-01

    A critical aspect of highly potent regimens such as lung stereotactic body radiation therapy (SBRT) is to avoid collateral toxicity while achieving planning target volume (PTV) coverage. In this work, we describe four dimensional conformal radiotherapy using a highly parallelizable swarm intelligence-based stochastic optimization technique. Conventional lung CRT-SBRT uses a 4DCT to create an internal target volume and then, using forward-planning, generates a 3D conformal plan. In contrast, we investigate an inverse-planning strategy that uses 4DCT data to create a 4D conformal plan, which is optimized across the three spatial dimensions (3D) as well as time, as represented by the respiratory phase. The key idea is to use respiratory motion as an additional degree of freedom. We iteratively adjust fluence weights for all beam apertures across all respiratory phases considering OAR sparing, PTV coverage and delivery efficiency. To demonstrate proof-of-concept, five non-small-cell lung cancer SBRT patients were retrospectively studied. The 4D optimized plans achieved PTV coverage comparable to the corresponding clinically delivered plans while showing significantly superior OAR sparing ranging from 26% to 83% for D max heart, 10%-41% for D max esophagus, 31%-68% for D max spinal cord and 7%-32% for V 13 lung.

  16. Comparison of optimization algorithms in intensity-modulated radiation therapy planning

    NASA Astrophysics Data System (ADS)

    Kendrick, Rachel

    Intensity-modulated radiation therapy is used to better conform the radiation dose to the target, which includes avoiding healthy tissue. Planning programs employ optimization methods to search for the best fluence of each photon beam, and therefore to create the best treatment plan. The Computational Environment for Radiotherapy Research (CERR), a program written in MATLAB, was used to examine some commonly-used algorithms for one 5-beam plan. Algorithms include the genetic algorithm, quadratic programming, pattern search, constrained nonlinear optimization, simulated annealing, the optimization method used in Varian EclipseTM, and some hybrids of these. Quadratic programing, simulated annealing, and a quadratic/simulated annealing hybrid were also separately compared using different prescription doses. The results of each dose-volume histogram as well as the visual dose color wash were used to compare the plans. CERR's built-in quadratic programming provided the best overall plan, but avoidance of the organ-at-risk was rivaled by other programs. Hybrids of quadratic programming with some of these algorithms seems to suggest the possibility of better planning programs, as shown by the improved quadratic/simulated annealing plan when compared to the simulated annealing algorithm alone. Further experimentation will be done to improve cost functions and computational time.

  17. Maximizing dosimetric benefits of IMRT in the treatment of localized prostate cancer through multicriteria optimization planning

    SciTech Connect

    Wala, Jeremiah; Craft, David; Paly, Jon; Zietman, Anthony; Efstathiou, Jason

    2013-10-01

    We examine the quality of plans created using multicriteria optimization (MCO) treatment planning in intensity-modulated radiation therapy (IMRT) in treatment of localized prostate cancer. Nine random cases of patients receiving IMRT to the prostate were selected. Each case was associated with a clinically approved plan created using Corvus. The cases were replanned using MCO-based planning in RayStation. Dose-volume histogram data from both planning systems were presented to 2 radiation oncologists in a blinded evaluation, and were compared at a number of dose-volume points. Both physicians rated all 9 MCO plans as superior to the clinically approved plans (p<10{sup −5}). Target coverage was equivalent (p = 0.81). Maximum doses to the prostate and bladder and the V50 and V70 to the anterior rectum were reduced in all MCO plans (p<0.05). Treatment planning time with MCO took approximately 60 minutes per case. MCO-based planning for prostate IMRT is efficient and produces high-quality plans with good target homogeneity and sparing of the anterior rectum, bladder, and femoral heads, without sacrificing target coverage.

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

    SciTech Connect

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

    2014-04-15

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

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

    PubMed Central

    Olugbara, Oludayo

    2014-01-01

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

  20. TH-E-BRE-08: GPU-Monte Carlo Based Fast IMRT Plan Optimization

    SciTech Connect

    Li, Y; Tian, Z; Shi, F; Jiang, S; Jia, X

    2014-06-15

    Purpose: Intensity-modulated radiation treatment (IMRT) plan optimization needs pre-calculated beamlet dose distribution. Pencil-beam or superposition/convolution type algorithms are typically used because of high computation speed. However, inaccurate beamlet dose distributions, particularly in cases with high levels of inhomogeneity, may mislead optimization, hindering the resulting plan quality. It is desire to use Monte Carlo (MC) methods for beamlet dose calculations. Yet, the long computational time from repeated dose calculations for a number of beamlets prevents this application. It is our objective to integrate a GPU-based MC dose engine in lung IMRT optimization using a novel two-steps workflow. Methods: A GPU-based MC code gDPM is used. Each particle is tagged with an index of a beamlet where the source particle is from. Deposit dose are stored separately for beamlets based on the index. Due to limited GPU memory size, a pyramid space is allocated for each beamlet, and dose outside the space is neglected. A two-steps optimization workflow is proposed for fast MC-based optimization. At first step, rough beamlet dose calculations is conducted with only a small number of particles per beamlet. Plan optimization is followed to get an approximated fluence map. In the second step, more accurate beamlet doses are calculated, where sampled number of particles for a beamlet is proportional to the intensity determined previously. A second-round optimization is conducted, yielding the final Result. Results: For a lung case with 5317 beamlets, 10{sup 5} particles per beamlet in the first round, and 10{sup 8} particles per beam in the second round are enough to get a good plan quality. The total simulation time is 96.4 sec. Conclusion: A fast GPU-based MC dose calculation method along with a novel two-step optimization workflow are developed. The high efficiency allows the use of MC for IMRT optimizations.

  1. Optimal motion planning for collision avoidance of mobile robots in non-stationary environments

    NASA Technical Reports Server (NTRS)

    Kyriakopoulos, K. J.; Saridis, G. N.

    1992-01-01

    An optimal control formulation of the problem of collision avoidance of mobile robots moving in general terrains containing moving obstacles is presented. A dynamic model of the mobile robot and the dynamic constraints are derived. Collision avoidance is guaranteed if the minimum distance between the robot and the object is nonzero. A nominal trajectory is assumed to be known from off-line planning. The main idea is to change the velocity along the nominal trajectory so that collisions are avoided. Time consistency with the nominal plan is desirable. A numerical solution of the optimization problem is obtained. A perturbation control type of approach is used to update the optimal plan. Simulation results verify the value of the proposed strategy.

  2. Real-time inverse high-dose-rate brachytherapy planning with catheter optimization by compressed sensing-inspired optimization strategies

    NASA Astrophysics Data System (ADS)

    Guthier, C. V.; Aschenbrenner, K. P.; Müller, R.; Polster, L.; Cormack, R. A.; Hesser, J. W.

    2016-08-01

    This paper demonstrates that optimization strategies derived from the field of compressed sensing (CS) improve computational performance in inverse treatment planning (ITP) for high-dose-rate (HDR) brachytherapy. Following an approach applied to low-dose-rate brachytherapy, we developed a reformulation of the ITP problem with the same mathematical structure as standard CS problems. Two greedy methods, derived from hard thresholding and subspace pursuit are presented and their performance is compared to state-of-the-art ITP solvers. Applied to clinical prostate brachytherapy plans speed-up by a factor of 56-350 compared to state-of-the-art methods. Based on a Wilcoxon signed rank-test the novel method statistically significantly decreases the final objective function value (p  <  0.01). The optimization times were below one second and thus planing can be considered as real-time capable. The novel CS inspired strategy enables real-time ITP for HDR brachytherapy including catheter optimization. The generated plans are either clinically equivalent or show a better performance with respect to dosimetric measures.

  3. Real-time inverse high-dose-rate brachytherapy planning with catheter optimization by compressed sensing-inspired optimization strategies

    NASA Astrophysics Data System (ADS)

    Guthier, C. V.; Aschenbrenner, K. P.; Müller, R.; Polster, L.; Cormack, R. A.; Hesser, J. W.

    2016-08-01

    This paper demonstrates that optimization strategies derived from the field of compressed sensing (CS) improve computational performance in inverse treatment planning (ITP) for high-dose-rate (HDR) brachytherapy. Following an approach applied to low-dose-rate brachytherapy, we developed a reformulation of the ITP problem with the same mathematical structure as standard CS problems. Two greedy methods, derived from hard thresholding and subspace pursuit are presented and their performance is compared to state-of-the-art ITP solvers. Applied to clinical prostate brachytherapy plans speed-up by a factor of 56–350 compared to state-of-the-art methods. Based on a Wilcoxon signed rank-test the novel method statistically significantly decreases the final objective function value (p  <  0.01). The optimization times were below one second and thus planing can be considered as real-time capable. The novel CS inspired strategy enables real-time ITP for HDR brachytherapy including catheter optimization. The generated plans are either clinically equivalent or show a better performance with respect to dosimetric measures.

  4. Real-time inverse high-dose-rate brachytherapy planning with catheter optimization by compressed sensing-inspired optimization strategies.

    PubMed

    Guthier, C V; Aschenbrenner, K P; Müller, R; Polster, L; Cormack, R A; Hesser, J W

    2016-08-21

    This paper demonstrates that optimization strategies derived from the field of compressed sensing (CS) improve computational performance in inverse treatment planning (ITP) for high-dose-rate (HDR) brachytherapy. Following an approach applied to low-dose-rate brachytherapy, we developed a reformulation of the ITP problem with the same mathematical structure as standard CS problems. Two greedy methods, derived from hard thresholding and subspace pursuit are presented and their performance is compared to state-of-the-art ITP solvers. Applied to clinical prostate brachytherapy plans speed-up by a factor of 56-350 compared to state-of-the-art methods. Based on a Wilcoxon signed rank-test the novel method statistically significantly decreases the final objective function value (p  <  0.01). The optimization times were below one second and thus planing can be considered as real-time capable. The novel CS inspired strategy enables real-time ITP for HDR brachytherapy including catheter optimization. The generated plans are either clinically equivalent or show a better performance with respect to dosimetric measures. PMID:27435044

  5. Multi-Objective Hybrid Optimal Control for Interplanetary Mission Planning

    NASA Technical Reports Server (NTRS)

    Englander, Jacob; Vavrina, Matthew; Ghosh, Alexander

    2015-01-01

    Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed and in some cases the final destination. In addition, a time-history of control variables must be chosen which defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very diserable. This work presents such as an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The method is demonstrated on a hypothetical mission to the main asteroid belt.

  6. Spherical cluster analysis for beam angle optimization in intensity-modulated radiation therapy treatment planning

    NASA Astrophysics Data System (ADS)

    Bangert, Mark; Oelfke, Uwe

    2010-10-01

    An intuitive heuristic to establish beam configurations for intensity-modulated radiation therapy is introduced as an extension of beam ensemble selection strategies applying scalar scoring functions. It is validated by treatment plan comparisons for three intra-cranial, pancreas, and prostate cases each. Based on a patient specific matrix listing the radiological quality of candidate beam directions individually for every target voxel, a set of locally ideal beam angles is generated. The spherical distribution of locally ideal beam angles is characteristic for every treatment site and patient: ideal beam angles typically cluster around distinct orientations. We interpret the cluster centroids, which are identified with a spherical K-means algorithm, as irradiation angles of an intensity-modulated radiation therapy treatment plan. The fluence profiles are subsequently optimized during a conventional inverse planning process. The average computation time for the pre-optimization of a beam ensemble is six minutes on a state-of-the-art work station. The treatment planning study demonstrates the potential benefit of the proposed beam angle optimization strategy. For the three prostate cases under investigation, the standard treatment plans applying nine coplanar equi-spaced beams and treatment plans applying an optimized non-coplanar nine-beam ensemble yield clinically comparable dose distributions. For symmetric patient geometries, the dose distribution formed by nine equi-spaced coplanar beams cannot be improved significantly. For the three pancreas and intra-cranial cases under investigation, the optimized non-coplanar beam ensembles enable better sparing of organs at risk while guaranteeing equivalent target coverage. Beam angle optimization by spherical cluster analysis shows the biggest impact for target volumes located asymmetrically within the patient and close to organs at risk.

  7. Cache-Aware Asymptotically-Optimal Sampling-Based Motion Planning.

    PubMed

    Ichnowski, Jeffrey; Prins, Jan F; Alterovitz, Ron

    2014-05-01

    We present CARRT* (Cache-Aware Rapidly Exploring Random Tree*), an asymptotically optimal sampling-based motion planner that significantly reduces motion planning computation time by effectively utilizing the cache memory hierarchy of modern central processing units (CPUs). CARRT* can account for the CPU's cache size in a manner that keeps its working dataset in the cache. The motion planner progressively subdivides the robot's configuration space into smaller regions as the number of configuration samples rises. By focusing configuration exploration in a region for periods of time, nearest neighbor searching is accelerated since the working dataset is small enough to fit in the cache. CARRT* also rewires the motion planning graph in a manner that complements the cache-aware subdivision strategy to more quickly refine the motion planning graph toward optimality. We demonstrate the performance benefit of our cache-aware motion planning approach for scenarios involving a point robot as well as the Rethink Robotics Baxter robot. PMID:25419474

  8. Novel binary PSO algorithm based optimization of transmission expansion planning considering power losses

    NASA Astrophysics Data System (ADS)

    Astuty; Haryono, T.

    2016-04-01

    Transmission expansion planning (TEP) is one of the issue that have to be faced caused by addition of large scale power generation into the existing power system. Optimization need to be conducted to get optimal solution technically and economically. Several mathematic methods have been applied to provide optimal allocation of new transmission line such us genetic algorithm, particle swarm optimization and tabu search. This paper proposed novel binary particle swarm optimization (NBPSO) to determine which transmission line should be added to the existing power system. There are two scenerios in this simulation. First, considering transmission power losses and the second is regardless transmission power losses. NBPSO method successfully obtain optimal solution in short computation time. Compare to the first scenario, the number of new line in second scenario which regardless power losses is less but produces high power losses that cause the cost becoming extremely expensive.

  9. Planning Maintenance and Repairs.

    ERIC Educational Resources Information Center

    Fitzemeyer, Ted

    2001-01-01

    Discusses the use of school facility design as an aid to efficiently repairing and maintaining facility systems. Also presents details on facility design's influence in properly maintaining mechanical and electrical systems. (GR)

  10. Application of Particle Swarm Optimization Algorithm in the Heating System Planning Problem

    PubMed Central

    Ma, Rong-Jiang; Yu, Nan-Yang; Hu, Jun-Yi

    2013-01-01

    Based on the life cycle cost (LCC) approach, this paper presents an integral mathematical model and particle swarm optimization (PSO) algorithm for the heating system planning (HSP) problem. The proposed mathematical model minimizes the cost of heating system as the objective for a given life cycle time. For the particularity of HSP problem, the general particle swarm optimization algorithm was improved. An actual case study was calculated to check its feasibility in practical use. The results show that the improved particle swarm optimization (IPSO) algorithm can more preferably solve the HSP problem than PSO algorithm. Moreover, the results also present the potential to provide useful information when making decisions in the practical planning process. Therefore, it is believed that if this approach is applied correctly and in combination with other elements, it can become a powerful and effective optimization tool for HSP problem. PMID:23935429

  11. Application of particle swarm optimization algorithm in the heating system planning problem.

    PubMed

    Ma, Rong-Jiang; Yu, Nan-Yang; Hu, Jun-Yi

    2013-01-01

    Based on the life cycle cost (LCC) approach, this paper presents an integral mathematical model and particle swarm optimization (PSO) algorithm for the heating system planning (HSP) problem. The proposed mathematical model minimizes the cost of heating system as the objective for a given life cycle time. For the particularity of HSP problem, the general particle swarm optimization algorithm was improved. An actual case study was calculated to check its feasibility in practical use. The results show that the improved particle swarm optimization (IPSO) algorithm can more preferably solve the HSP problem than PSO algorithm. Moreover, the results also present the potential to provide useful information when making decisions in the practical planning process. Therefore, it is believed that if this approach is applied correctly and in combination with other elements, it can become a powerful and effective optimization tool for HSP problem.

  12. Planning horizon for a predictive optimal controller for thermal energy storage systems

    SciTech Connect

    Krarti, M.; Henze, G.P.; Bell, D.

    1999-07-01

    This paper presents the results of a detailed simulation analysis to determine the planning horizon for a predictive optimal controller for thermal energy storage (TES) systems. The objective of the simulation analysis is to determine the sensitivity of the performance of a TES optimal controller and the planning horizon length to different design parameters, including: chiller capacity, cooling plant model, storage system capacity, and load profile. The analysis is performed using two commercial buildings: a 20-floor office building in Wisconsin, and a hotel in California.

  13. Interactive method for planning constrained, fuel-optimal orbital proximity operations

    NASA Technical Reports Server (NTRS)

    Abramovitz, Adrian; Grunwald, Arthur J.

    1993-01-01

    An interactive graphical method for planning fuel-efficient rendezvous trajectories in the multi-spacecraft environment of the space station is presented. The method allows the operator to compose a multi-burn transfer trajectory between arbitrary initial chaser and target trajectories. The available task time of the mission is limited and the maneuver is subject to various operational constraints, such as departure, arrival, plume impingement and spatial constraints. The maneuvers are described in terms of the relataive motion experienced in a Space-Station centered coordinate system. The optimization method is based on the primer vector and its extension to non-optimal trajectories. The visual feedback of trajectory shapes, operational constraints, and optimization functions, provided by user-transparaent and continuously active background computations, allows the operator to make fast, iterative design changes which rapidly converge to fuel-efficient solutions. The optimization functions are presented. A variety of simple design examples has been presented to demonstrate the usefulness of the method. In many cases the addition of a properly positioned intermediate waypoint resulted in fuel savings of up to 30%. Furthermore, due to the counter-intuitive character of the optimization functions, most fuel-optimal solutions could not have been found without the aid of the optimization tools. Operating the system was found to be very easy, and did not require any previous in-depth knowledge of orbital dynamics or trajectory. The planning tool is an example of operator assisted optimization of nonlinear cost-functions.

  14. Multi-Objective Hybrid Optimal Control for Interplanetary Mission Planning

    NASA Technical Reports Server (NTRS)

    Englander, Jacob A.

    2014-01-01

    Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. Because low-thrust trajectory design is tightly coupled with systems design, power and propulsion characteristics must be chosen as well. In addition, a time-history of control variables must be chosen which defines the trajectory. There are often may thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The method is demonstrated on hypothetical mission to the main asteroid belt and to Deimos.

  15. Multi-Objective Hybrid Optimal Control for Interplanetary Mission Planning

    NASA Technical Reports Server (NTRS)

    Englander, Jacob

    2015-01-01

    Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. Because low-thrust trajectory design is tightly coupled with systems design, power and propulsion characteristics must be chosen as well. In addition, a time-history of control variables must be chosen which defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The methods is demonstrated on hypothetical mission to the main asteroid belt and to Deimos.

  16. D-area oil seepage basin bioventing optimization test plan

    SciTech Connect

    Berry, C.J.; Radway, J.C.; Alman, D.; Hazen, T.C.

    1998-12-31

    The D Area Oil Seepage Basin (DOSB) was used from 1952 to 1975 for disposal of petroleum-based products (waste oils), general office and cafeteria waste, and apparently some solvents [trichloroethylene (TCE)/tetrachloroethylene (PCE)]. Numerous analytical results have indicated the presence of TCE and its degradation product vinyl chloride in groundwater in and around the unit, and of petroleum hydrocarbons in soils within the unit. The DOSB is slated for additional assessment and perhaps for environmental remediation. In situ bioremediation represents a technology of demonstrated effectiveness in the reclamation of sites contaminated with petroleum hydrocarbons and chlorinated solvents, and has been retained as an alternative for the cleanup of the DOSB. The Savannah River Site is therefore proposing to conduct a field treatability study designed to demonstrate and optimize the effectiveness of in situ microbiological biodegradative processes at the DOSB. The introduction of air and gaseous nutrients via two horizontal injection wells (bioventing) is expected to enhance biodegradation rates of petroleum components and stimulate microbial degradation of chlorinated solvents. The data gathered in this test will allow a determination of the biodegradation rates of contaminants of concern in the soil and groundwater, allow an evaluation of the feasibility of in situ bioremediation of soil and groundwater at the DOSB, and provide data necessary for the functional design criteria for the final remediation system.

  17. Optimal planning of residential photovoltaic systems under various rate structure

    NASA Astrophysics Data System (ADS)

    Imamura, E.; Asano, H.

    1993-05-01

    With respect to residential electric power utilization and supply systems utilizing photovoltaic power generation, the installation inducible economic conditions were searched using a linear programming technique, and influences by charge systems were evaluated and discussed. A photovoltaic system model consists of a photovoltaic panel, a control panel incorporated inverter, and a storage battery set. For the amount of power generated by the photovoltaic system, mean values for total insolation in Tokyo each for winter, summer, and intermediate seasons were used, assuming the photovoltaic system efficiency at 10% and the battery charge/discharge efficiency at 70%. Residential power load patterns were hypothesized from 200 to 1000 kWh/month depending on the demand scale. As a result of the analysis, it was made clear that the condition the photovoltaic system is accepted by residential housing is such that the price for the photovoltaic system including the inverter becoming 1/5 of the present price, and the price for the battery including the charge/discharge control device becoming 1/3 make the cost break-even. In the case of time-band based charge system, it is shown that the case where the ratio of daytime charge to nighttime charge is three makes the coordination of the battery and the photovoltaic system optimal.

  18. Optimization of RFID network planning using Zigbee and WSN

    NASA Astrophysics Data System (ADS)

    Hasnan, Khalid; Ahmed, Aftab; Badrul-aisham, Bakhsh, Qadir

    2015-05-01

    Everyone wants to be ease in their life. Radio frequency identification (RFID) wireless technology is used to make our life easier. RFID technology increases productivity, accuracy and convenience in delivery of service in supply chain. It is used for various applications such as preventing theft of automobiles, tolls collection without stopping, no checkout lines at grocery stores, managing traffic, hospital management, corporate campuses and airports, mobile asset tracking, warehousing, tracking library books, and to track a wealth of assets in supply chain management. Efficiency of RFID can be enhanced by integrating with wireless sensor network (WSN), zigbee mesh network and internet of things (IOT). The proposed system is used for identifying, sensing and real-time locating system (RTLS) of items in an indoor heterogeneous region. The system gives real-time richer information of object's characteristics, location and their environmental parameters like temperature, noise and humidity etc. RTLS reduce human error, optimize inventory management, increase productivity and information accuracy at indoor heterogeneous network. The power consumption and the data transmission rate of the system can be minimized by using low power hardware design.

  19. Maintenance Action Readiness Assessment Plan for Waste Area Grouping 1 inactive Tanks 3001-B, 3004-B, T-30, and 3013 at Oak Ridge National Laboratory, Oak Ridge, Tennessee

    SciTech Connect

    1995-07-01

    This Readiness Assessment Plan has been prepared to document operational readiness for the maintenance action consisting of remediation of four inactive liquid low-level radioactive tanks in Waste Area Grouping 1 at Oak Ridge National Laboratory. The four tanks to be remediated are Tanks 3001-B, 3004-B, T-30, and 3013. Tanks 3001-B, 3004-B, and T-30 will be removed from the ground. Because of logistical issues associated with excavation and site access, Tank 3013 will be grouted in place and permanently closed. This project is being performed as a maintenance action rather than an action under the Comprehensive Environmental Response, Compensation, and Liability Act, because the risk to human health and environment is well below the US Environmental Protection Agency`s level of concern. The decision to proceed as a maintenance action was documented by an interim action proposed plan, which is included in the administrative record. A Readiness Assessment Team has been assembled to review the criteria deemed necessary to conduct the remediation tasks. These criteria include approval of all plans, acquisition of needed equipment, completion of personnel training, and coordination with plant health and safety personnel. Once the criteria have been met and documented, the task will begin. The readiness assessment is expected to be completed by late July 1995, and the task will begin thereafter.

  20. A FORTRAN program for the optimization of radiotherapy treatment planning using the complication probability factor (CPF).

    PubMed

    Wolbarst, A B; Sternick, E S; Curran, B H; Kosinski, R J; Dritschilo, A

    1980-04-01

    The complication probability factor (CPF) is an objective function, based directly on radiobiological principles and clinical data, for the optimization of radiotherapy treatment planning; it measures the likelihood that a given radiation dose distribution will lead to serious complications in the patient as a result of damage to healthy tissue. A computerized search can be made for that treatment plan which delivers an acceptable tumoricidal dose, yet minimizes the CPF as averaged over the total volume of healthy tissue irradiated. The CPF FORTRAN program, run on a PDP 11/55 in conjunction with a commercially available radiotherapy treatment planning package, is described in detail.

  1. Maintenance Plan for the Performance Assessments and Composite Analyses for the Area 3 and Area 5 Radioactive Waste Management Sites at the NTS

    SciTech Connect

    Vefa Yucel

    2007-01-03

    U.S. Department of Energy (DOE) Manual M 435.1-1 requires that performance assessments (PAs) and composite analyses (CAs) for low-level waste (LLW) disposal facilities be maintained by the field offices. This plan describes the activities performed to maintain the PA and the CA for the Area 3 and Area 5 Radioactive Waste Management Sites (RWMSs) at the Nevada Test Site (NTS). This plan supersedes the Maintenance Plan for the Performance Assessments and Composite Analyses for the Area 3 and Area 5 Radioactive Waste Management Sites at the Nevada Test Site (DOE/NV/11718--491-REV 1, dated September 2002). The plan is based on U.S. Department of Energy (DOE) Order 435.1 (DOE, 1999a), DOE Manual M 435.1-1 (DOE, 1999b), the DOE M 435.1-1 Implementation Guide DOE G 435.1-1 (DOE, 1999c), and the Maintenance Guide for PAs and CAs (DOE, 1999d). The plan includes a current update on PA/CA documentation, a revised schedule, and a section on Quality Assurance.

  2. Building Maintenance, Management, and Budgeting.

    ERIC Educational Resources Information Center

    Pawsey, M. R.

    1982-01-01

    Australian methods and formulas for funding building maintenance and management are outlined and found to be haphazard. Discussed are: ultimate costs of deferred maintenance, major plant replacements, life cycle costing, types of maintenance programs (including full preventive maintenance), use of computer programs for planning, and organization…

  3. Optimization-based decision support to assist in logistics planning for hospital evacuations.

    PubMed

    Glick, Roger; Bish, Douglas R; Agca, Esra

    2013-01-01

    The evacuation of the hospital is a very complex process and evacuation planning is an important part of a hospital's emergency management plan. There are numerous factors that affect the evacuation plan including the nature of threat, availability of resources and staff the characteristics of the evacuee population, and risk to patients and staff. The safety and health of patients is of fundamental importance, but safely moving patients to alternative care facilities while under threat is a very challenging task. This article describes the logistical issues and complexities involved in planning and execution of hospital evacuations. Furthermore, this article provides examples of how optimization-based decision support tools can help evacuation planners to better plan for complex evacuations by providing real-world solutions to various evacuation scenarios.

  4. Minimum deltaV Burn Planning for the International Space Station Using a Hybrid Optimization Technique, Level 1

    NASA Technical Reports Server (NTRS)

    Brown, Aaron J.

    2015-01-01

    The International Space Station's (ISS) trajectory is coordinated and executed by the Trajectory Operations and Planning (TOPO) group at NASA's Johnson Space Center. TOPO group personnel routinely generate look-ahead trajectories for the ISS that incorporate translation burns needed to maintain its orbit over the next three to twelve months. The burns are modeled as in-plane, horizontal burns, and must meet operational trajectory constraints imposed by both NASA and the Russian Space Agency. In generating these trajectories, TOPO personnel must determine the number of burns to model, each burn's Time of Ignition (TIG), and magnitude (i.e. deltaV) that meet these constraints. The current process for targeting these burns is manually intensive, and does not take advantage of more modern techniques that can reduce the workload needed to find feasible burn solutions, i.e. solutions that simply meet the constraints, or provide optimal burn solutions that minimize the total DeltaV while simultaneously meeting the constraints. A two-level, hybrid optimization technique is proposed to find both feasible and globally optimal burn solutions for ISS trajectory planning. For optimal solutions, the technique breaks the optimization problem into two distinct sub-problems, one for choosing the optimal number of burns and each burn's optimal TIG, and the other for computing the minimum total deltaV burn solution that satisfies the trajectory constraints. Each of the two aforementioned levels uses a different optimization algorithm to solve one of the sub-problems, giving rise to a hybrid technique. Level 2, or the outer level, uses a genetic algorithm to select the number of burns and each burn's TIG. Level 1, or the inner level, uses the burn TIGs from Level 2 in a sequential quadratic programming (SQP) algorithm to compute a minimum total deltaV burn solution subject to the trajectory constraints. The total deltaV from Level 1 is then used as a fitness function by the genetic

  5. How to Get a Maintenance Program Underway

    ERIC Educational Resources Information Center

    Lundy, Lyndall L.

    1975-01-01

    The article describes the development of a comprehensive maintenance program for the school shop. A general maintenance management outline provides direction for planning, execution, and evaluation. (MW)

  6. Prospective Teachers' Future Time Perspective and Professional Plans about Teaching: The Mediating Role of Academic Optimism

    ERIC Educational Resources Information Center

    Eren, Altay

    2012-01-01

    This study aimed to examine the mediating role of prospective teachers' academic optimism in the relationship between their future time perspective and professional plans about teaching. A total of 396 prospective teachers voluntarily participated in the study. Correlation, regression, and structural equation modeling analyses were conducted in…

  7. Impact of using linear optimization models in dose planning for HDR brachytherapy

    SciTech Connect

    Holm, Aasa; Larsson, Torbjoern; Carlsson Tedgren, Aasa

    2012-02-15

    Purpose: Dose plans generated with optimization models hitherto used in high-dose-rate (HDR) brachytherapy have shown a tendency to yield longer dwell times than manually optimized plans. Concern has been raised for the corresponding undesired hot spots, and various methods to mitigate these have been developed. The hypotheses upon this work is based are (a) that one cause for the long dwell times is the use of objective functions comprising simple linear penalties and (b) that alternative penalties, as these are piecewise linear, would lead to reduced length of individual dwell times. Methods: The characteristics of the linear penalties and the piecewise linear penalties are analyzed mathematically. Experimental comparisons between the two types of penalties are carried out retrospectively for a set of prostate cancer patients. Results: When the two types of penalties are compared, significant changes can be seen in the dwell times, while most dose-volume parameters do not differ significantly. On average, total dwell times were reduced by 4.2%, with a reduction of maximum dwell times by 25%, when the alternative penalties were used. Conclusions: The use of linear penalties in optimization models for HDR brachytherapy is one cause for the undesired long dwell times that arise in mathematically optimized plans. By introducing alternative penalties, a significant reduction in dwell times can be achieved for HDR brachytherapy dose plans. Although various measures for mitigating the long dwell times are already available, the observation that linear penalties contribute to their appearance is of fundamental interest.

  8. Maintenance Plan for the Performance Assessments and Composite Analyses for the Area 3 and Area 5 Radioactive Waste Management Sites at the Nevada Test Site

    SciTech Connect

    V. Yucel

    2002-09-01

    U.S. Department of Energy (DOE) Order 435.1 requires that performance assessments (PAs) and composite analyses (CAs) for low-level waste (LLW) disposal facilities be maintained by the field offices. This plan describes the activities to be performed in maintaining the Performance Assessment (PA) and Composite Analysis (CA) for the Area 3 and Area 5 Radioactive Waste Management Sites (RWMSs) at the Nevada Test Site (NTS). The Disposal Authorization Statement (DAS) for the continuing operations of a LLW facility at the DOE complex specifies the conditions for operations based on approval of a PA and CA, and requires the facility to implement a maintenance program to assure that these conditions will remain protective of the public health and the environment in the future. The goal of the maintenance program is to provide that assurance. The maintenance process is an iterative one in which changing conditions may result in a revision of PA and CA; the revised PA and CA may impose a different set of conditions for facility operation, closure, and postclosure. The maintenance process includes managing uncertainty, performing annual reviews, submitting annual summary reports to DOE Headquarters (DOE/HQ), carrying out special analyses, and revising the PAs and CAs, if necessary. Management of uncertainty is an essential component of the maintenance program because results of the original PAs and CAs are understood to be based on uncertain assumptions about the conceptual models; the mathematical models and parameters; and the future state of the lands, disposal facilities, and human activities. The annual reviews for the PAs include consideration of waste receipts, facility specific factors, results of monitoring, and results of research and development (R&D) activities. Likewise, results of ongoing R&D, changes in land-use planning, new information on known sources of residual radioactive materials, and identification of new sources may warrant an evaluation to determine

  9. Facilities maintenance handbook

    NASA Technical Reports Server (NTRS)

    1991-01-01

    This handbook is a guide for facilities maintenance managers. Its objective is to set minimum facilities maintenance standards. It also provides recommendations on how to meet the standards to ensure that NASA maintains its facilities in a manner that protects and preserves its investment in the facilities in a cost-effective manner while safely and efficiently performing its mission. This handbook implements NMI 8831.1, which states NASA facilities maintenance policy and assigns organizational responsibilities for the management of facilities maintenance activities on all properties under NASA jurisdiction. It is a reference for facilities maintenance managers, not a step-by-step procedural manual. Because of the differences in NASA Field Installation organizations, this handbook does not assume or recommend a typical facilities maintenance organization. Instead, it uses a systems approach to describe the functions that should be included in any facilities maintenance management system, regardless of its organizational structure. For documents referenced in the handbook, the most recent version of the documents is applicable. This handbook is divided into three parts: Part 1 specifies common definitions and facilities maintenance requirements and amplifies the policy requirements contained in NMI 8831. 1; Part 2 provides guidance on how to meet the requirements of Part 1, containing recommendations only; Part 3 contains general facilities maintenance information. One objective of this handbook is to fix commonality of facilities maintenance definitions among the Centers. This will permit the application of uniform measures of facilities conditions, of the relationship between current replacement value and maintenance resources required, and of the backlog of deferred facilities maintenance. The utilization of facilities maintenance system functions will allow the Centers to quantitatively define maintenance objectives in common terms, prepare work plans, and

  10. Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning

    PubMed Central

    Kok, Kai Yit; Rajendran, Parvathy

    2016-01-01

    The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost. PMID:26943630

  11. Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning.

    PubMed

    Kok, Kai Yit; Rajendran, Parvathy

    2016-01-01

    The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost.

  12. Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning.

    PubMed

    Kok, Kai Yit; Rajendran, Parvathy

    2016-01-01

    The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost. PMID:26943630

  13. Planning, Implementation and Optimization of Future space Missions using an Immersive Visualization Environement (IVE) Machine

    NASA Astrophysics Data System (ADS)

    Harris, E.

    Planning, Implementation and Optimization of Future Space Missions using an Immersive Visualization Environment (IVE) Machine E. N. Harris, Lockheed Martin Space Systems, Denver, CO and George.W. Morgenthaler, U. of Colorado at Boulder History: A team of 3-D engineering visualization experts at the Lockheed Martin Space Systems Company have developed innovative virtual prototyping simulation solutions for ground processing and real-time visualization of design and planning of aerospace missions over the past 6 years. At the University of Colorado, a team of 3-D visualization experts are developing the science of 3-D visualization and immersive visualization at the newly founded BP Center for Visualization, which began operations in October, 2001. (See IAF/IAA-01-13.2.09, "The Use of 3-D Immersive Visualization Environments (IVEs) to Plan Space Missions," G. A. Dorn and G. W. Morgenthaler.) Progressing from Today's 3-D Engineering Simulations to Tomorrow's 3-D IVE Mission Planning, Simulation and Optimization Techniques: 3-D (IVEs) and visualization simulation tools can be combined for efficient planning and design engineering of future aerospace exploration and commercial missions. This technology is currently being developed and will be demonstrated by Lockheed Martin in the (IVE) at the BP Center using virtual simulation for clearance checks, collision detection, ergonomics and reach-ability analyses to develop fabrication and processing flows for spacecraft and launch vehicle ground support operations and to optimize mission architecture and vehicle design subject to realistic constraints. Demonstrations: Immediate aerospace applications to be demonstrated include developing streamlined processing flows for Reusable Space Transportation Systems and Atlas Launch Vehicle operations and Mars Polar Lander visual work instructions. Long-range goals include future international human and robotic space exploration missions such as the development of a Mars

  14. IPIP: A new approach to inverse planning for HDR brachytherapy by directly optimizing dosimetric indices

    SciTech Connect

    Siauw, Timmy; Cunha, Adam; Atamtuerk, Alper; Hsu, I-Chow; Pouliot, Jean; Goldberg, Ken

    2011-07-15

    Purpose: Many planning methods for high dose rate (HDR) brachytherapy require an iterative approach. A set of computational parameters are hypothesized that will give a dose plan that meets dosimetric criteria. A dose plan is computed using these parameters, and if any dosimetric criteria are not met, the process is iterated until a suitable dose plan is found. In this way, the dose distribution is controlled by abstract parameters. The purpose of this study is to develop a new approach for HDR brachytherapy by directly optimizing the dose distribution based on dosimetric criteria. Methods: The authors developed inverse planning by integer program (IPIP), an optimization model for computing HDR brachytherapy dose plans and a fast heuristic for it. They used their heuristic to compute dose plans for 20 anonymized prostate cancer image data sets from patients previously treated at their clinic database. Dosimetry was evaluated and compared to dosimetric criteria. Results: Dose plans computed from IPIP satisfied all given dosimetric criteria for the target and healthy tissue after a single iteration. The average target coverage was 95%. The average computation time for IPIP was 30.1 s on an Intel(R) Core{sup TM}2 Duo CPU 1.67 GHz processor with 3 Gib RAM. Conclusions: IPIP is an HDR brachytherapy planning system that directly incorporates dosimetric criteria. The authors have demonstrated that IPIP has clinically acceptable performance for the prostate cases and dosimetric criteria used in this study, in both dosimetry and runtime. Further study is required to determine if IPIP performs well for a more general group of patients and dosimetric criteria, including other cancer sites such as GYN.

  15. Hierarchical incremental path planning and situation-dependent optimized dynamic motion planning considering accelerations.

    PubMed

    Lai, Xue-Cheng; Ge, Shuzhi Sam; Al Mamun, Abdullah

    2007-12-01

    This paper studies a hierarchical approach for incrementally driving a nonholonomic mobile robot to its destination in unknown environments. The A* algorithm is modified to handle a map containing unknown information. Based on it, optimal (discrete) paths are incrementally generated with a periodically updated map. Next, accelerations in varying velocities are taken into account in predicting the robot pose and the robot trajectory resulting from a motion command. Obstacle constraints are transformed to suitable velocity limits so that the robot can move as fast as possible while avoiding collisions when needed. Then, to trace the discrete path, the system searches for a waypoint-directed optimized motion in a reduced 1-D translation or rotation velocity space. Various situations of navigation are dealt with by using different strategies rather than a single objective function. Extensive simulations and experiments verified the efficacy of the proposed approach.

  16. Optimal needle arrangement for intraoperative planning in permanent I-125 prostate implants.

    PubMed

    Thompson, S A; Fung, A Y C; Zaider, M

    2002-08-21

    One limitation of intraoperative planning of permanent prostate implants is that needles must already be in the gland before planning images are acquired. Improperly placed needles often restrict the capability of generating optimal seed placement. We developed guiding principles for the proper layout of needles within the treatment volume. The Memorial Sloan-Kettering Cancer Center planning system employs a genetic algorithm to find the optimal seed implantation pattern consistent with pre-assigned constraints (needle geometry, uniformity, conformity and the avoidance of high doses to urethra and rectum). Ultrasound volumes for twelve patients with 1-125 implants were used to generate six plans per patient (total 72 plans) with different needle arrangements. The plans were evaluated in terms of V100 (percentage prostate volume receiving at least the prescription dose), U135 (percentage urethra volume receiving at least 135% of prescription dose), and CI (conformity index, the ratio of treatment volume to prescription dose volume.) The method termed POSTCTR, in which needles were placed on the periphery of the largest ultrasound slice and posterior central needles were placed as needed, consistently gave superior results for all prostate sizes. Another arrangement, labelled POSTLAT, where the needles were placed peripherally with additional needles in the posterior lateral lobes, also gave satisfactory results. We advocate two needle arrangements, POSTCTR and POSTLAT, with the former giving better results. PMID:12222865

  17. NOTE: Optimal needle arrangement for intraoperative planning in permanent I-125 prostate implants

    NASA Astrophysics Data System (ADS)

    Thompson, S. A.; Fung, A. Y. C.; Zaider, M.

    2002-08-01

    One limitation of intraoperative planning of permanent prostate implants is that needles must already be in the gland before planning images are acquired. Improperly placed needles often restrict the capability of generating optimal seed placement. We developed guiding principles for the proper layout of needles within the treatment volume. The Memorial Sloan-Kettering Cancer Center planning system employs a genetic algorithm to find the optimal seed implantation pattern consistent with pre-assigned constraints (needle geometry, uniformity, conformity and the avoidance of high doses to urethra and rectum). Ultrasound volumes for twelve patients with I-125 implants were used to generate six plans per patient (total 72 plans) with different needle arrangements. The plans were evaluated in terms of V100 (percentage prostate volume receiving at least the prescription dose), U135 (percentage urethra volume receiving at least 135% of prescription dose), and CI (conformity index, the ratio of treatment volume to prescription dose volume.) The method termed POSTCTR, in which needles were placed on the periphery of the largest ultrasound slice and posterior central needles were placed as needed, consistently gave superior results for all prostate sizes. Another arrangement, labelled POSTLAT, where the needles were placed peripherally with additional needles in the posterior lateral lobes, also gave satisfactory results. We advocate two needle arrangements, POSTCTR and POSTLAT, with the former giving better results.

  18. UAV path planning using artificial potential field method updated by optimal control theory

    NASA Astrophysics Data System (ADS)

    Chen, Yong-bo; Luo, Guan-chen; Mei, Yue-song; Yu, Jian-qiao; Su, Xiao-long

    2016-04-01

    The unmanned aerial vehicle (UAV) path planning problem is an important assignment in the UAV mission planning. Based on the artificial potential field (APF) UAV path planning method, it is reconstructed into the constrained optimisation problem by introducing an additional control force. The constrained optimisation problem is translated into the unconstrained optimisation problem with the help of slack variables in this paper. The functional optimisation method is applied to reform this problem into an optimal control problem. The whole transformation process is deduced in detail, based on a discrete UAV dynamic model. Then, the path planning problem is solved with the help of the optimal control method. The path following process based on the six degrees of freedom simulation model of the quadrotor helicopters is introduced to verify the practicability of this method. Finally, the simulation results show that the improved method is more effective in planning path. In the planning space, the length of the calculated path is shorter and smoother than that using traditional APF method. In addition, the improved method can solve the dead point problem effectively.

  19. 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.

  20. Mixed integer programming improves comprehensibility and plan quality in inverse optimization of prostate HDR brachytherapy.

    PubMed

    Gorissen, Bram L; den Hertog, Dick; Hoffmann, Aswin L

    2013-02-21

    Current inverse treatment planning methods that optimize both catheter positions and dwell times in prostate HDR brachytherapy use surrogate linear or quadratic objective functions that have no direct interpretation in terms of dose-volume histogram (DVH) criteria, do not result in an optimum or have long solution times. We decrease the solution time of the existing linear and quadratic dose-based programming models (LP and QP, respectively) to allow optimizing over potential catheter positions using mixed integer programming. An additional average speed-up of 75% can be obtained by stopping the solver at an early stage, without deterioration of the plan quality. For a fixed catheter configuration, the dwell time optimization model LP solves to optimality in less than 15 s, which confirms earlier results. We propose an iterative procedure for QP that allows us to prescribe the target dose as an interval, while retaining independence between the solution time and the number of dose calculation points. This iterative procedure is comparable in speed to the LP model and produces better plans than the non-iterative QP. We formulate a new dose-volume-based model that maximizes V(100%) while satisfying pre-set DVH criteria. This model optimizes both catheter positions and dwell times within a few minutes depending on prostate volume and number of catheters, optimizes dwell times within 35 s and gives better DVH statistics than dose-based models. The solutions suggest that the correlation between the objective value and the clinical plan quality is weak in the existing dose-based models. PMID:23363622

  1. Volumetric-modulated arc therapy planning using multicriteria optimization for localized prostate cancer.

    PubMed

    Ghandour, Sarah; Matzinger, Oscar; Pachoud, Marc

    2015-05-08

    The purpose of this work is to evaluate the volumetric-modulated arc therapy (VMAT) multicriteria optimization (MCO) algorithm clinically available in the RayStation treatment planning system (TPS) and its ability to reduce treatment planning time while providing high dosimetric plan quality. Nine patients with localized prostate cancer who were previously treated with 78 Gy in 39 fractions using VMAT plans and rayArc system based on the direct machine parameter optimization (DMPO) algorithm were selected and replanned using the VMAT-MCO system. First, the dosimetric quality of the plans was evaluated using multiple conformity metrics that account for target coverage and sparing of healthy tissue, used in our departmental clinical protocols. The conformity and homogeneity index, number of monitor units, and treatment planning time for both modalities were assessed. Next, the effects of the technical plan parameters, such as constraint leaf motion CLM (cm/°) and maximum arc delivery time T (s), on the accuracy of delivered dose were evaluated using quality assurance passing rates (QAs) measured using the Delta4 phantom from ScandiDos. For the dosimetric plan's quality analysis, the results show that the VMAT-MCO system provides plans comparable to the rayArc system with no statistical difference for V95% (p < 0.01), D1% (p < 0.01), CI (p < 0.01), and HI (p < 0.01) of the PTV, bladder (p < 0.01), and rectum (p < 0.01) constraints, except for the femoral heads and healthy tissues, for which a dose reduction was observed using MCO compared with rayArc (p < 0.01). The technical parameter study showed that a combination of CLM equal to 0.5 cm/degree and a maximum delivery time of 72 s allowed the accurate delivery of the VMAT-MCO plan on the Elekta Versa HD linear accelerator. Planning evaluation and dosimetric measurements showed that VMAT-MCO can be used clinically with the advantage of enhanced planning process efficiency by reducing the treatment planning time

  2. Traffic Network Aided Plan and Road Line Optimization in Intelligent Traffic System

    NASA Astrophysics Data System (ADS)

    Liu, Bin; Qin, Guofeng

    2008-11-01

    In ITS(intelligent traffic system), traffic network plan is important. Public traffic network is a basic part in contemporary intelligent traffic and a basis of the municipal infrastructure construction. To construct the public traffic network aided plan, two problems are studied. One is how to plan traffic road line in order to cover the traffic districts; the other is how to choice the best way from the start point to the end. For the first one, a traffic road line aided plan algorithm is taken forward. The other is a road line optimization algorithm. It utilizes the topology theory to analyze the spatial character in public traffic network, and designs the best choice method to meet the user's requirements. The two algorithms are realized, and proved by a case in the graphical interface of GIS(Geographic Information System), including simulation for rationalization of the public traffic network.

  3. iCycle: Integrated, multicriterial beam angle, and profile optimization for generation of coplanar and noncoplanar IMRT plans

    SciTech Connect

    Breedveld, Sebastiaan; Storchi, Pascal R. M.; Voet, Peter W. J.; Heijmen, Ben J. M.

    2012-02-15

    Purpose: To introduce iCycle, a novel algorithm for integrated, multicriterial optimization of beam angles, and intensity modulated radiotherapy (IMRT) profiles. Methods: A multicriterial plan optimization with iCycle is based on a prescription called wish-list, containing hard constraints and objectives with ascribed priorities. Priorities are ordinal parameters used for relative importance ranking of the objectives. The higher an objective priority is, the higher the probability that the corresponding objective will be met. Beam directions are selected from an input set of candidate directions. Input sets can be restricted, e.g., to allow only generation of coplanar plans, or to avoid collisions between patient/couch and the gantry in a noncoplanar setup. Obtaining clinically feasible calculation times was an important design criterium for development of iCycle. This could be realized by sequentially adding beams to the treatment plan in an iterative procedure. Each iteration loop starts with selection of the optimal direction to be added. Then, a Pareto-optimal IMRT plan is generated for the (fixed) beam setup that includes all so far selected directions, using a previously published algorithm for multicriterial optimization of fluence profiles for a fixed beam arrangement Breedveld et al.[Phys. Med. Biol. 54, 7199-7209 (2009)]. To select the next direction, each not yet selected candidate direction is temporarily added to the plan and an optimization problem, derived from the Lagrangian obtained from the just performed optimization for establishing the Pareto-optimal plan, is solved. For each patient, a single one-beam, two-beam, three-beam, etc. Pareto-optimal plan is generated until addition of beams does no longer result in significant plan quality improvement. Plan generation with iCycle is fully automated. Results: Performance and characteristics of iCycle are demonstrated by generating plans for a maxillary sinus case, a cervical cancer patient, and a

  4. A modeling framework for optimal long-term care insurance purchase decisions in retirement planning.

    PubMed

    Gupta, Aparna; Li, Lepeng

    2004-05-01

    The level of need and costs of obtaining long-term care (LTC) during retired life require that planning for it is an integral part of retirement planning. In this paper, we divide retirement planning into two phases, pre-retirement and post-retirement. On the basis of four interrelated models for health evolution, wealth evolution, LTC insurance premium and coverage, and LTC cost structure, a framework for optimal LTC insurance purchase decisions in the pre-retirement phase is developed. Optimal decisions are obtained by developing a trade-off between post-retirement LTC costs and LTC insurance premiums and coverage. Two-way branching models are used to model stochastic health events and asset returns. The resulting optimization problem is formulated as a dynamic programming problem. We compare the optimal decision under two insurance purchase scenarios: one assumes that insurance is purchased for good and other assumes it may be purchased, relinquished and re-purchased. Sensitivity analysis is performed for the retirement age.

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

    DOE PAGESBeta

    Hafez, Omar; Bhattacharya, Kankar

    2012-03-03

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

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

    SciTech Connect

    Hafez, Omar; Bhattacharya, Kankar

    2012-03-03

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

  7. An Analytical Planning Model to Estimate the Optimal Density of Charging Stations for Electric Vehicles.

    PubMed

    Ahn, Yongjun; Yeo, Hwasoo

    2015-01-01

    The charging infrastructure location problem is becoming more significant due to the extensive adoption of electric vehicles. Efficient charging station planning can solve deeply rooted problems, such as driving-range anxiety and the stagnation of new electric vehicle consumers. In the initial stage of introducing electric vehicles, the allocation of charging stations is difficult to determine due to the uncertainty of candidate sites and unidentified charging demands, which are determined by diverse variables. This paper introduces the Estimating the Required Density of EV Charging (ERDEC) stations model, which is an analytical approach to estimating the optimal density of charging stations for certain urban areas, which are subsequently aggregated to city level planning. The optimal charging station's density is derived to minimize the total cost. A numerical study is conducted to obtain the correlations among the various parameters in the proposed model, such as regional parameters, technological parameters and coefficient factors. To investigate the effect of technological advances, the corresponding changes in the optimal density and total cost are also examined by various combinations of technological parameters. Daejeon city in South Korea is selected for the case study to examine the applicability of the model to real-world problems. With real taxi trajectory data, the optimal density map of charging stations is generated. These results can provide the optimal number of chargers for driving without driving-range anxiety. In the initial planning phase of installing charging infrastructure, the proposed model can be applied to a relatively extensive area to encourage the usage of electric vehicles, especially areas that lack information, such as exact candidate sites for charging stations and other data related with electric vehicles. The methods and results of this paper can serve as a planning guideline to facilitate the extensive adoption of electric

  8. An Analytical Planning Model to Estimate the Optimal Density of Charging Stations for Electric Vehicles

    PubMed Central

    Ahn, Yongjun; Yeo, Hwasoo

    2015-01-01

    The charging infrastructure location problem is becoming more significant due to the extensive adoption of electric vehicles. Efficient charging station planning can solve deeply rooted problems, such as driving-range anxiety and the stagnation of new electric vehicle consumers. In the initial stage of introducing electric vehicles, the allocation of charging stations is difficult to determine due to the uncertainty of candidate sites and unidentified charging demands, which are determined by diverse variables. This paper introduces the Estimating the Required Density of EV Charging (ERDEC) stations model, which is an analytical approach to estimating the optimal density of charging stations for certain urban areas, which are subsequently aggregated to city level planning. The optimal charging station’s density is derived to minimize the total cost. A numerical study is conducted to obtain the correlations among the various parameters in the proposed model, such as regional parameters, technological parameters and coefficient factors. To investigate the effect of technological advances, the corresponding changes in the optimal density and total cost are also examined by various combinations of technological parameters. Daejeon city in South Korea is selected for the case study to examine the applicability of the model to real-world problems. With real taxi trajectory data, the optimal density map of charging stations is generated. These results can provide the optimal number of chargers for driving without driving-range anxiety. In the initial planning phase of installing charging infrastructure, the proposed model can be applied to a relatively extensive area to encourage the usage of electric vehicles, especially areas that lack information, such as exact candidate sites for charging stations and other data related with electric vehicles. The methods and results of this paper can serve as a planning guideline to facilitate the extensive adoption of electric

  9. An Analytical Planning Model to Estimate the Optimal Density of Charging Stations for Electric Vehicles.

    PubMed

    Ahn, Yongjun; Yeo, Hwasoo

    2015-01-01

    The charging infrastructure location problem is becoming more significant due to the extensive adoption of electric vehicles. Efficient charging station planning can solve deeply rooted problems, such as driving-range anxiety and the stagnation of new electric vehicle consumers. In the initial stage of introducing electric vehicles, the allocation of charging stations is difficult to determine due to the uncertainty of candidate sites and unidentified charging demands, which are determined by diverse variables. This paper introduces the Estimating the Required Density of EV Charging (ERDEC) stations model, which is an analytical approach to estimating the optimal density of charging stations for certain urban areas, which are subsequently aggregated to city level planning. The optimal charging station's density is derived to minimize the total cost. A numerical study is conducted to obtain the correlations among the various parameters in the proposed model, such as regional parameters, technological parameters and coefficient factors. To investigate the effect of technological advances, the corresponding changes in the optimal density and total cost are also examined by various combinations of technological parameters. Daejeon city in South Korea is selected for the case study to examine the applicability of the model to real-world problems. With real taxi trajectory data, the optimal density map of charging stations is generated. These results can provide the optimal number of chargers for driving without driving-range anxiety. In the initial planning phase of installing charging infrastructure, the proposed model can be applied to a relatively extensive area to encourage the usage of electric vehicles, especially areas that lack information, such as exact candidate sites for charging stations and other data related with electric vehicles. The methods and results of this paper can serve as a planning guideline to facilitate the extensive adoption of electric

  10. A novel reduced-order prioritized optimization method for radiation therapy treatment planning.

    PubMed

    Kalantzis, Georgios; Apte, Aditya

    2014-04-01

    In this study, a novel reduced order prioritized algorithm is presented for optimization in radiation therapy treatment planning. The proposed method consists of three stages. In the first stage, the intensity space was sampled by solving a series of unconstrained optimization problems. The objective function of the first stage is expressed as a scalarized weighted sum of partial objectives for the target and organ at risk. Latin hypercube sampling was utilized to define the weights for each run of the unconstrained optimizations. In the second stage, principal component analysis is applied to the solutions determined in the first stage to identify the major eigen modes in the intensities space, significantly reducing the number of independent variables. In the third stage, treatment planning goals/objectives are prioritized, and the problem is solved in the reduced order space. After each objective is optimized, that objective function is converted into a constraint for the lower-priority objectives. In the current formulation, a slip factor is used to relax the hard constraints for planning target volume (PTV) coverage. The applicability of the proposed method is demonstrated for one prostate and one lung intensity-modulated radiation therapy treatment plan. Upon completion of the sequential prioritized optimization, the mean dose at the rectum and bladder was reduced by 21.3% and 22.4%, respectively. Additionally, we investigated the effect of the slip factor 's' on PTV coverage and we found minimal degradation of the tumor dose (∼4%). Finally, the speed up factors upon the dimensionality reduction were as high as 49.9 without compromising the quality of the results. PMID:24658231

  11. Inverse planning in the age of digital LINACs: station parameter optimized radiation therapy (SPORT)

    NASA Astrophysics Data System (ADS)

    Xing, Lei; Li, Ruijiang

    2014-03-01

    The last few years have seen a number of technical and clinical advances which give rise to a need for innovations in dose optimization and delivery strategies. Technically, a new generation of digital linac has become available which offers features such as programmable motion between station parameters and high dose-rate Flattening Filter Free (FFF) beams. Current inverse planning methods are designed for traditional machines and cannot accommodate these features of new generation linacs without compromising either dose conformality and/or delivery efficiency. Furthermore, SBRT is becoming increasingly important, which elevates the need for more efficient delivery, improved dose distribution. Here we will give an overview of our recent work in SPORT designed to harness the digital linacs and highlight the essential components of SPORT. We will summarize the pros and cons of traditional beamlet-based optimization (BBO) and direct aperture optimization (DAO) and introduce a new type of algorithm, compressed sensing (CS)-based inverse planning, that is capable of automatically removing the redundant segments during optimization and providing a plan with high deliverability in the presence of a large number of station control points (potentially non-coplanar, non-isocentric, and even multi-isocenters). We show that CS-approach takes the interplay between planning and delivery into account and allows us to balance the dose optimality and delivery efficiency in a controlled way and, providing a viable framework to address various unmet demands of the new generation linacs. A few specific implementation strategies of SPORT in the forms of fixed-gantry and rotational arc delivery are also presented.

  12. Y-12 Groundwater Protection Program Monitoring Optimization Plan For Groundwater Monitoring Wells At The U.S. Department Of Energy Y-12 National Security Complex, Oak Ridge, Tennessee

    SciTech Connect

    none,

    2013-09-01

    This document is the monitoring optimization plan for groundwater monitoring wells associated with the U.S. Department of Energy (DOE) Y-12 National Security Complex (Y-12) in Oak Ridge, Tennessee. The plan describes the technical approach that is implemented under the Y-12 Groundwater Protection Program (GWPP) to focus available resources on the monitoring wells at Y-12 that provide the most useful hydrologic and groundwater quality monitoring data. The technical approach is based on the GWPP status designation for each well. Under this approach, wells granted "active" status are used by the GWPP for hydrologic monitoring and/or groundwater quality sampling, whereas wells granted "inactive" status are not used for either purpose. The status designation also defines the frequency at which the GWPP will inspect applicable wells, the scope of these well inspections, and extent of any maintenance actions initiated by the GWPP. Details regarding the ancillary activities associated with implementation of this plan (e.g., well inspection) are deferred to the referenced GWPP plans. This plan applies to groundwater wells associated with Y-12 and related waste management areas and facilities located within three hydrogeologic regimes.

  13. Multimodal function optimization using minimal representation size clustering and its application to planning multipaths.

    PubMed

    Hocaoğlu, C; Sanderson, A C

    1997-01-01

    A novel genetic algorithm (GA) using minimal representation size cluster (MRSC) analysis is designed and implemented for solving multimodal function optimization problems. The problem of multimodal function optimization is framed within a hypothesize-and-test paradigm using minimal representation size (minimal complexity) for species formation and a GA. A multiple-population GA is developed to identify different species. The number of populations, thus the number of different species, is determined by the minimal representation size criterion. Therefore, the proposed algorithm reveals the unknown structure of the multimodal function when a priori knowledge about the function is unknown. The effectiveness of the algorithm is demonstrated on a number of multimodal test functions. The proposed scheme results in a highly parallel algorithm for finding multiple local minima. In this paper, a path-planning algorithm is also developed based on the MRSC_GA algorithm. The algorithm utilizes MRSC_GA for planning paths for mobile robots, piano-mover problems, and N-link manipulators. The MRSC_GA is used for generating multipaths to provide alternative solutions to the path-planning problem. The generation of alternative solutions is especially important for planning paths in dynamic environments. A novel iterative multiresolution path representation is used as a basis for the GA coding. The effectiveness of the algorithm is demonstrated on a number of two-dimensional path-planning problems.

  14. Patient specific optimization-based treatment planning for catheter-based ultrasound hyperthermia and thermal ablation

    NASA Astrophysics Data System (ADS)

    Prakash, Punit; Chen, Xin; Wootton, Jeffery; Pouliot, Jean; Hsu, I.-Chow; Diederich, Chris J.

    2009-02-01

    A 3D optimization-based thermal treatment planning platform has been developed for the application of catheter-based ultrasound hyperthermia in conjunction with high dose rate (HDR) brachytherapy for treating advanced pelvic tumors. Optimal selection of applied power levels to each independently controlled transducer segment can be used to conform and maximize therapeutic heating and thermal dose coverage to the target region, providing significant advantages over current hyperthermia technology and improving treatment response. Critical anatomic structures, clinical target outlines, and implant/applicator geometries were acquired from sequential multi-slice 2D images obtained from HDR treatment planning and used to reconstruct patient specific 3D biothermal models. A constrained optimization algorithm was devised and integrated within a finite element thermal solver to determine a priori the optimal applied power levels and the resulting 3D temperature distributions such that therapeutic heating is maximized within the target, while placing constraints on maximum tissue temperature and thermal exposure of surrounding non-targeted tissue. This optimizationbased treatment planning and modeling system was applied on representative cases of clinical implants for HDR treatment of cervix and prostate to evaluate the utility of this planning approach. The planning provided significant improvement in achievable temperature distributions for all cases, with substantial increase in T90 and thermal dose (CEM43T90) coverage to the hyperthermia target volume while decreasing maximum treatment temperature and reducing thermal dose exposure to surrounding non-targeted tissues and thermally sensitive rectum and bladder. This optimization based treatment planning platform with catheter-based ultrasound applicators is a useful tool that has potential to significantly improve the delivery of hyperthermia in conjunction with HDR brachytherapy. The planning platform has been extended

  15. Optimizing Planning Techniques (OPT) for Comprehensive Systems of Guidance, Counseling, Placement and Follow-Through. Final Report.

    ERIC Educational Resources Information Center

    Treichel, Janet

    The purpose of the Optimizing Planning Techniques (OPT) for Comprehensive Systems of Guidance, Counseling, Placement, and Follow-Through project was to help local educational agencies systematically plan and efficiently operate comprehensive guidance and counseling programs. The project (1) identified planning models for comprehensive systems of…

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    Population growth and the threat of drier or changed climates are likely to increase water scarcity world-wide. A combination of demand management (water conservation) and new supply infrastructure is often needed to meet future projected demands. In this case system planners must decide what to implement, when and at what capacity. Choices can range from infrastructure to policies or a mix of the two, culminating in a complex planning problem. Decision making under uncertainty frameworks can be used to help planners with this planning problem. This presentation introduces, applies and compares four decision making under uncertainty frameworks. The application is to the Thames basin water resource system which includes the city of London. The approaches covered here include least-economic cost capacity expansion optimization (EO), Robust Decision Making (RDM), Info-Gap Decision Theory (Info-gap) and many-objective evolutionary optimization (MOEO). EO searches for the least-economic cost program, i.e. the timing, sizing, and choice of supply-demand management actions/upgrades which meet projected water demands. Instead of striving for optimality, the RDM and Info-gap approaches help build plans that are robust to 'deep' uncertainty in future conditions. The MOEO framework considers multiple performance criteria and uses water systems simulators as a function evaluator for the evolutionary algorithm. Visualizations show Pareto approximate tradeoffs between multiple objectives. In this presentation we detail the application of each framework to the Thames basin (including London) water resource planning problem. Supply and demand options are proposed by the major water companies in the basin. We apply the EO method using a 29 year time horizon and an annual time step considering capital, operating (fixed and variable), social and environmental costs. The method considers all plausible combinations of supply and conservation schemes and capacities proposed by water

  17. Patient performance-based plan parameter optimization for prostate cancer in tomotherapy.

    PubMed

    Cao, Yuan Jie; Lee, Suk; Chang, Kyung Hwan; Shim, Jang Bo; Kim, Kwang Hyeon; Park, Young Je; Kim, Chul Yong

    2015-01-01

    The purpose of this study is to evaluate the influence of treatment-planning parameters on the quality of treatment plans in tomotherapy and to find the optimized planning parameter combinations when treating patients with prostate cancer under different performances. A total of 3 patients with prostate cancer with Eastern Cooperative Oncology Group (ECOG) performance status of 2 or 3 were included in this study. For each patient, 27 treatment plans were created using a combination of planning parameters (field width of 1, 2.5, and 5cm; pitch of 0.172, 0.287, and 0.43; and modulation factor of 1.8, 3, and 3.5). Then, plans were analyzed using several dosimetrical indices: the prescription isodose to target volume (PITV) ratio, homogeneity index (HI), conformity index (CI), target coverage index (TCI), modified dose HI (MHI), conformity number (CN), and quality factor (QF). Furthermore, dose-volume histogram of critical structures and critical organ scoring index (COSI) were used to analyze organs at risk (OAR) sparing. Interestingly, treatment plans with a field width of 1cm showed more favorable results than others in the planning target volume (PTV) and OAR indices. However, the treatment time of the 1-cm field width was 3 times longer than that of plans with a field width of 5cm. There was no substantial decrease in treatment time when the pitch was increased from 0.172 to 0.43, but the PTV indices were slightly compromised. As expected, field width had the most significant influence on all of the indices including PTV, OAR, and treatment time. For the patients with good performance who can tolerate a longer treatment time, we suggest a field width of 1cm, pitch of 0.172, and modulation factor of 1.8; for the patients with poor performance status, field width of 5cm, pitch of 0.287, and a modulation factor of 3.5 should be considered.

  18. 28 CFR 56.2 - Maintenance of records with respect to meetings held to develop voluntary agreements or plans of...

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... to the Department of Energy. The Department of Energy may, upon written notice to potential... International Energy Program. 56.2 Section 56.2 Judicial Administration DEPARTMENT OF JUSTICE (CONTINUED) INTERNATIONAL ENERGY PROGRAM § 56.2 Maintenance of records with respect to meetings held to develop...

  19. eIMRT: a web platform for the verification and optimization of radiation treatment plans.

    PubMed

    González-Castaño, Diego M; Pena, Javier; Gómez, Faustino; Gago-Arias, Araceli; González-Castaño, Francisco J; Rodríguez-Silva, Daniel A; Gómez, Andrés; Mouriño, Carlos; Pombar, Miguel; Sánchez, Manuel

    2009-01-01

    The eIMRT platform is a remote distributed computing tool that provides users with Internet access to three different services: Monte Carlo optimization of treatment plans, CRT & IMRT treatment optimization, and a database of relevant radiation treatments/clinical cases. These services are accessible through a user-friendly and platform independent web page. Its flexible and scalable design focuses on providing the final users with services rather than a collection of software pieces. All input and output data (CT, contours, treatment plans and dose distributions) are handled using the DICOM format. The design, implementation, and support of the verification and optimization algorithms are hidden to the user. This allows a unified, robust handling of the software and hardware that enables these computation-intensive services. The eIMRT platform is currently hosted by the Galician Supercomputing Center (CESGA) and may be accessible upon request (there is a demo version at http://eimrt.cesga.es:8080/eIMRT2/demo; request access in http://eimrt.cesga.es/signup.html). This paper describes all aspects of the eIMRT algorithms in depth, its user interface, and its services. Due to the flexible design of the platform, it has numerous applications including the intercenter comparison of treatment planning, the quality assurance of radiation treatments, the design and implementation of new approaches to certain types of treatments, and the sharing of information on radiation treatment techniques. In addition, the web platform and software tools developed for treatment verification and optimization have a modular design that allows the user to extend them with new algorithms. This software is not a commercial product. It is the result of the collaborative effort of different public research institutions and is planned to be distributed as an open source project. In this way, it will be available to any user; new releases will be generated with the new implemented codes or

  20. Sampling plan optimization for detection of lithography and etch CD process excursions

    NASA Astrophysics Data System (ADS)

    Elliott, Richard C.; Nurani, Raman K.; Lee, Sung Jin; Ortiz, Luis G.; Preil, Moshe E.; Shanthikumar, J. G.; Riley, Trina; Goodwin, Greg A.

    2000-06-01

    Effective sample planning requires a careful combination of statistical analysis and lithography engineering. In this paper, we present a complete sample planning methodology including baseline process characterization, determination of the dominant excursion mechanisms, and selection of sampling plans and control procedures to effectively detect the yield- limiting excursions with a minimum of added cost. We discuss the results of our novel method in identifying critical dimension (CD) process excursions and present several examples of poly gate Photo and Etch CD excursion signatures. Using these results in a Sample Planning model, we determine the optimal sample plan and statistical process control (SPC) chart metrics and limits for detecting these excursions. The key observations are that there are many different yield- limiting excursion signatures in photo and etch, and that a given photo excursion signature turns into a different excursion signature at etch with different yield and performance impact. In particular, field-to-field variance excursions are shown to have a significant impact on yield. We show how current sampling plan and monitoring schemes miss these excursions and suggest an improved procedure for effective detection of CD process excursions.

  1. Optimal Sampling-Based Motion Planning under Differential Constraints: the Driftless Case

    PubMed Central

    Schmerling, Edward; Janson, Lucas; Pavone, Marco

    2015-01-01

    Motion planning under differential constraints is a classic problem in robotics. To date, the state of the art is represented by sampling-based techniques, with the Rapidly-exploring Random Tree algorithm as a leading example. Yet, the problem is still open in many aspects, including guarantees on the quality of the obtained solution. In this paper we provide a thorough theoretical framework to assess optimality guarantees of sampling-based algorithms for planning under differential constraints. We exploit this framework to design and analyze two novel sampling-based algorithms that are guaranteed to converge, as the number of samples increases, to an optimal solution (namely, the Differential Probabilistic RoadMap algorithm and the Differential Fast Marching Tree algorithm). Our focus is on driftless control-affine dynamical models, which accurately model a large class of robotic systems. In this paper we use the notion of convergence in probability (as opposed to convergence almost surely): the extra mathematical flexibility of this approach yields convergence rate bounds — a first in the field of optimal sampling-based motion planning under differential constraints. Numerical experiments corroborating our theoretical results are presented and discussed. PMID:26618041

  2. Optimal integration of gravity in trajectory planning of vertical pointing movements.

    PubMed

    Crevecoeur, Frédéric; Thonnard, Jean-Louis; Lefèvre, Philippe

    2009-08-01

    The planning and control of motor actions requires knowledge of the dynamics of the controlled limb to generate the appropriate muscular commands and achieve the desired goal. Such planning and control imply that the CNS must be able to deal with forces and constraints acting on the limb, such as the omnipresent force of gravity. The present study investigates the effect of hypergravity induced by parabolic flights on the trajectory of vertical pointing movements to test the hypothesis that motor commands are optimized with respect to the effect of gravity on the limb. Subjects performed vertical pointing movements in normal gravity and hypergravity. We use a model based on optimal control to identify the role played by gravity in the optimal arm trajectory with minimal motor costs. First, the simulations in normal gravity reproduce the asymmetry in the velocity profiles (the velocity reaches its maximum before half of the movement duration), which typically characterizes the vertical pointing movements performed on Earth, whereas the horizontal movements present symmetrical velocity profiles. Second, according to the simulations, the optimal trajectory in hypergravity should present an increase in the peak acceleration and peak velocity despite the increase in the arm weight. In agreement with these predictions, the subjects performed faster movements in hypergravity with significant increases in the peak acceleration and peak velocity, which were accompanied by a significant decrease in the movement duration. This suggests that movement kinematics change in response to an increase in gravity, which is consistent with the hypothesis that motor commands are optimized and the action of gravity on the limb is taken into account. The results provide evidence for an internal representation of gravity in the central planning process and further suggest that an adaptation to altered dynamics can be understood as a reoptimization process.

  3. Incorporating deliverable monitor unit constraints into spot intensity optimization in intensity-modulated proton therapy treatment planning

    NASA Astrophysics Data System (ADS)

    Cao, Wenhua; Lim, Gino; Li, Xiaoqiang; Li, Yupeng; Zhu, X. Ronald; Zhang, Xiaodong

    2013-08-01

    The purpose of this study is to investigate the feasibility and impact of incorporating deliverable monitor unit (MU) constraints into spot intensity optimization (SIO) in intensity-modulated proton therapy (IMPT) treatment planning. The current treatment planning system (TPS) for IMPT disregards deliverable MU constraints in the SIO routine. It performs a post-processing procedure on an optimized plan to enforce deliverable MU values that are required by the spot scanning proton delivery system. This procedure can create a significant dose distribution deviation between the optimized and post-processed deliverable plans, especially when small spot spacings are used. In this study, we introduce a two-stage linear programming approach to optimize spot intensities and constrain deliverable MU values simultaneously, i.e., a deliverable SIO (DSIO) model. Thus, the post-processing procedure is eliminated and the associated optimized plan deterioration can be avoided. Four prostate cancer cases at our institution were selected for study and two parallel opposed beam angles were planned for all cases. A quadratic programming based model without MU constraints, i.e., a conventional SIO (CSIO) model, was also implemented to emulate commercial TPS. Plans optimized by both the DSIO and CSIO models were evaluated for five different settings of spot spacing from 3 to 7 mm. For all spot spacings, the DSIO-optimized plans yielded better uniformity for the target dose coverage and critical structure sparing than did the CSIO-optimized plans. With reduced spot spacings, more significant improvements in target dose uniformity and critical structure sparing were observed in the DSIO than in the CSIO-optimized plans. Additionally, better sparing of the rectum and bladder was achieved when reduced spacings were used for the DSIO-optimized plans. The proposed DSIO approach ensures the deliverability of optimized IMPT plans that take into account MU constraints. This eliminates the post

  4. Optimized production planning model for a multi-plant cultivation system under uncertainty

    NASA Astrophysics Data System (ADS)

    Ke, Shunkui; Guo, Doudou; Niu, Qingliang; Huang, Danfeng

    2015-02-01

    An inexact multi-constraint programming model under uncertainty was developed by incorporating a production plan algorithm into the crop production optimization framework under the multi-plant collaborative cultivation system. In the production plan, orders from the customers are assigned to a suitable plant under the constraints of plant capabilities and uncertainty parameters to maximize profit and achieve customer satisfaction. The developed model and solution method were applied to a case study of a multi-plant collaborative cultivation system to verify its applicability. As determined in the case analysis involving different orders from customers, the period of plant production planning and the interval between orders can significantly affect system benefits. Through the analysis of uncertain parameters, reliable and practical decisions can be generated using the suggested model of a multi-plant collaborative cultivation system.

  5. Intensity-modulated radiosurgery treatment planning by fluence mapping optimized multi-isocenter plans

    NASA Astrophysics Data System (ADS)

    St. John, Theodore Jeffrey

    Stereotactic radiosurgery (SRS) is a non-invasive surgical technique of using a high intensity beam of x rays to obliterate intracranial lesions. The multiple-isocenter, circular-collimator, arc technique has been used successfully at the University of Florida since the inception of their radiosurgery program in 1988. This technique has been shown to produce highly conformal radiation dose distributions with steep dose gradients, which are key factors in delivering high dose to the tumor and low dose to surrounding healthy tissue. However, the time required to deliver the treatment to a complex target requiring many isocenters may exceed several hours. In this investigation, a unique method of intensity modulation that approximates the fluence map produced by the multiple-isocenter arc technique is employed. An algorithm was created that reads the dosimetry file from the multiple-isocenter treatment plan, segments each arc into a set of static beams and combines all of the beams from a set of table and gantry angles so that they can be delivered using a miniature multi-leaf collimator (mMLC). The mMLC shapes each beam, in such a way as to closely approximate the original dose distribution, alleviating the need to reposition the patient or manually change the collimator for each isocenter. The purpose of this research is to determine how well a mMLC, which has a set number of leaves with finite leaf widths, can approximate the dose distribution produced by the standard circular collimator, arc technique. The investigation begins with a study of how the dose distribution is changed by using a set of static beams in place of arcs, followed by a study of the effect of MLC leaf width and the development and application of the experimental fluence-mapped MLC treatment technique. The development and testing of the fluence-mapping algorithm, a dosimetry program, and several graphicaluser-interface tools are described. These tools were used to calculate and compare the dose

  6. Optimization of observation plan based on the stochastic characteristics of the geodetic network

    NASA Astrophysics Data System (ADS)

    Pachelski, Wojciech; Postek, Paweł

    2016-06-01

    Optimal design of geodetic network is a basic subject of many engineering projects. An observation plan is a concluding part of the process. Any particular observation within the network has through adjustment a different contribution and impact on values and accuracy characteristics of unknowns. The problem of optimal design can be solved by means of computer simulation. This paper presents a new method of simulation based on sequential estimation of individual observations in a step-by-step manner, by means of the so-called filtering equations. The algorithm aims at satisfying different criteria of accuracy according to various interpretations of the covariance matrix. Apart of them, the optimization criterion is also amount of effort, defined as the minimum number of observations required. A numerical example of a 2-D network is illustrated to view the effectiveness of presented method. The results show decrease of the number of observations by 66% with respect to the not optimized observation plan, which still satisfy the assumed accuracy.

  7. A holistic approach towards optimal planning of hybrid renewable energy systems: Combining hydroelectric and wind energy

    NASA Astrophysics Data System (ADS)

    Dimas, Panagiotis; Bouziotas, Dimitris; Efstratiadis, Andreas; Koutsoyiannis, Demetris

    2014-05-01

    Hydropower with pumped storage is a proven technology with very high efficiency that offers a unique large-scale energy buffer. Energy storage is employed by pumping water upstream to take advantage of the excess of produced energy (e.g. during night) and next retrieving this water to generate hydro-power during demand peaks. Excess energy occurs due to other renewables (wind, solar) whose power fluctuates in an uncontrollable manner. By integrating these with hydroelectric plants with pumped storage facilities we can form autonomous hybrid renewable energy systems. The optimal planning and management thereof requires a holistic approach, where uncertainty is properly represented. In this context, a novel framework is proposed, based on stochastic simulation and optimization. This is tested in an existing hydrosystem of Greece, considering its combined operation with a hypothetical wind power system, for which we seek the optimal design to ensure the most beneficial performance of the overall scheme.

  8. A role for biological optimization within the current treatment planning paradigm

    SciTech Connect

    Das, Shiva

    2009-10-15

    Purpose: Biological optimization using complication probability models in intensity modulated radiotherapy (IMRT) planning has tremendous potential for reducing radiation-induced toxicity. Nevertheless, biological optimization is almost never clinically utilized, probably because of clinician confidence in, and familiarity with, physical dose-volume constraints. The method proposed here incorporates biological optimization after dose-volume constrained optimization so as to improve the dose distribution without detrimentally affecting the important reductions achieved by dose-volume optimization (DVO). Methods: Following DVO, the clinician/planner first identifies ''fixed points'' on the target and organ-at-risk (OAR) dose-volume histograms. These points represent important DVO plan qualities that are not to be violated within a specified tolerance. Biological optimization then maximally reduces a biological metric (illustrated with equivalent uniform dose (EUD) in this work) while keeping the fixed dose-volume points within tolerance limits, as follows. Incremental fluence adjustments are computed and applied to incrementally reduce the OAR EUDs while approximately maintaining the fixed points. This process of incremental fluence adjustment is iterated until the fixed points exceed tolerance. At this juncture, remedial fluence adjustments are computed and iteratively applied to bring the fixed points back within tolerance, without increasing OAR EUDs. This process of EUD reduction followed by fixed-point correction is repeated until no further EUD reduction is possible. The method is demonstrated in the context of a prostate cancer case and olfactory neuroblastoma case. The efficacy of EUD reduction after DVO is evaluated by comparison to an optimizer with purely biological (EUD) OAR objectives. Results: For both cases, EUD reduction after DVO additionally reduced doses, especially high doses, to normal organs. For the prostate case, bladder/rectum EUDs were

  9. Guaranteed epsilon-optimal treatment plans with the minimum number of beams for stereotactic body radiation therapy

    NASA Astrophysics Data System (ADS)

    Yarmand, Hamed; Winey, Brian; Craft, David

    2013-09-01

    Stereotactic body radiation therapy (SBRT) is characterized by delivering a high amount of dose in a short period of time. In SBRT the dose is delivered using open fields (e.g., beam’s-eye-view) known as ‘apertures’. Mathematical methods can be used for optimizing treatment planning for delivery of sufficient dose to the cancerous cells while keeping the dose to surrounding organs at risk (OARs) minimal. Two important elements of a treatment plan are quality and delivery time. Quality of a plan is measured based on the target coverage and dose to OARs. Delivery time heavily depends on the number of beams used in the plan as the setup times for different beam directions constitute a large portion of the delivery time. Therefore the ideal plan, in which all potential beams can be used, will be associated with a long impractical delivery time. We use the dose to OARs in the ideal plan to find the plan with the minimum number of beams which is guaranteed to be epsilon-optimal (i.e., a predetermined maximum deviation from the ideal plan is guaranteed). Since the treatment plan optimization is inherently a multi-criteria-optimization problem, the planner can navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus OARs sparing, and then use the proposed technique to reduce the number of beams while guaranteeing epsilon-optimality. We use mixed integer programming (MIP) for optimization. To reduce the computation time for the resultant MIP, we use two heuristics: a beam elimination scheme and a family of heuristic cuts, known as ‘neighbor cuts’, based on the concept of ‘adjacent beams’. We show the effectiveness of the proposed technique on two clinical cases, a liver and a lung case. Based on our technique we propose an algorithm for fast generation of epsilon-optimal plans.

  10. Estimating the impact of enterprise resource planning project management decisions on post-implementation maintenance costs: a case study using simulation modelling

    NASA Astrophysics Data System (ADS)

    Fryling, Meg

    2010-11-01

    Organisations often make implementation decisions with little consideration for the maintenance phase of an enterprise resource planning (ERP) system, resulting in significant recurring maintenance costs. Poor cost estimations are likely related to the lack of an appropriate framework for enterprise-wide pre-packaged software maintenance, which requires an ongoing relationship with the software vendor (Markus, M.L., Tanis, C., and Fenema, P.C., 2000. Multisite ERP implementation. CACM, 43 (4), 42-46). The end result is that critical project decisions are made with little empirical data, resulting in substantial long-term cost impacts. The product of this research is a formal dynamic simulation model that enables theory testing, scenario exploration and policy analysis. The simulation model ERPMAINT1 was developed by combining and extending existing frameworks in several research domains, and by incorporating quantitative and qualitative case study data. The ERPMAINT1 model evaluates tradeoffs between different ERP project management decisions and their impact on post-implementation total cost of ownership (TCO). Through model simulations a variety of dynamic insights were revealed that could assist ERP project managers. Major findings from the simulation show that upfront investments in mentoring and system exposure translate to long-term cost savings. The findings also indicate that in addition to customisations, add-ons have a significant impact on TCO.

  11. Prediction of attendance at fitness center: a comparison between the theory of planned behavior, the social cognitive theory, and the physical activity maintenance theory.

    PubMed

    Jekauc, Darko; Völkle, Manuel; Wagner, Matthias O; Mess, Filip; Reiner, Miriam; Renner, Britta

    2015-01-01

    In the processes of physical activity (PA) maintenance specific predictors are effective, which differ from other stages of PA development. Recently, Physical Activity Maintenance Theory (PAMT) was specifically developed for prediction of PA maintenance. The aim of the present study was to evaluate the predictability of the future behavior by the PAMT and compare it with the Theory of Planned Behavior (TPB) and Social Cognitive Theory (SCT). Participation rate in a fitness center was observed for 101 college students (53 female) aged between 19 and 32 years (M = 23.6; SD = 2.9) over 20 weeks using a magnetic card. In order to predict the pattern of participation TPB, SCT and PAMT were used. A latent class zero-inflated Poisson growth curve analysis identified two participation patterns: regular attenders and intermittent exercisers. SCT showed the highest predictive power followed by PAMT and TPB. Impeding aspects as life stress and barriers were the strongest predictors suggesting that overcoming barriers might be an important aspect for working out on a regular basis. Self-efficacy, perceived behavioral control, and social support could also significantly differentiate between the participation patterns.

  12. Prediction of attendance at fitness center: a comparison between the theory of planned behavior, the social cognitive theory, and the physical activity maintenance theory

    PubMed Central

    Jekauc, Darko; Völkle, Manuel; Wagner, Matthias O.; Mess, Filip; Reiner, Miriam; Renner, Britta

    2015-01-01

    In the processes of physical activity (PA) maintenance specific predictors are effective, which differ from other stages of PA development. Recently, Physical Activity Maintenance Theory (PAMT) was specifically developed for prediction of PA maintenance. The aim of the present study was to evaluate the predictability of the future behavior by the PAMT and compare it with the Theory of Planned Behavior (TPB) and Social Cognitive Theory (SCT). Participation rate in a fitness center was observed for 101 college students (53 female) aged between 19 and 32 years (M = 23.6; SD = 2.9) over 20 weeks using a magnetic card. In order to predict the pattern of participation TPB, SCT and PAMT were used. A latent class zero-inflated Poisson growth curve analysis identified two participation patterns: regular attenders and intermittent exercisers. SCT showed the highest predictive power followed by PAMT and TPB. Impeding aspects as life stress and barriers were the strongest predictors suggesting that overcoming barriers might be an important aspect for working out on a regular basis. Self-efficacy, perceived behavioral control, and social support could also significantly differentiate between the participation patterns. PMID:25717313

  13. Streamlined Approach for Environmental Restoration Plan for Corrective Action Unit 113: Reactor Maintenance, Assembly, and Disassembly Building Nevada Test Site, Nevada

    SciTech Connect

    J. L. Smith

    2001-01-01

    This Streamlined Approach for Environmental Restoration (SAFER) Plan addresses the action necessary for the closure in place of Corrective Action Unit (CAU) 113 Area 25 Reactor Maintenance, Assembly, and Disassembly Facility (R-MAD). CAU 113 is currently listed in Appendix III of the Federal Facility Agreement and Consent Order (FFACO) (NDEP, 1996). The CAU is located in Area 25 of the Nevada Test Site (NTS) and consists of Corrective Action Site (CAS) 25-04-01, R-MAD Facility (Figures 1-2). This plan provides the methodology for closure in place of CAU 113. The site contains radiologically impacted and hazardous material. Based on preassessment field work, there is sufficient process knowledge to close in place CAU 113 using the SAFER process. At a future date when funding becomes available, the R-MAD Building (25-3110) will be demolished and inaccessible radiologic waste will be properly disposed in the Area 3 Radiological Waste Management Site (RWMS).

  14. 40 CFR 63.8575 - What do I need to know about operation, maintenance, and monitoring plans?

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... monitoring plans? (a) For each kiln that is subject to the emission limits specified in Table 1 to this... records to document compliance. (13) If you operate an affected kiln and you plan to take the kiln control... paragraphs (b)(13)(i) and (ii) of this section. (i) Procedures for minimizing HAP emissions from the...

  15. 40 CFR 63.8575 - What do I need to know about operation, maintenance, and monitoring plans?

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... monitoring plans? (a) For each kiln that is subject to the emission limits specified in Table 1 to this... records to document compliance. (13) If you operate an affected kiln and you plan to take the kiln control... paragraphs (b)(13)(i) and (ii) of this section. (i) Procedures for minimizing HAP emissions from the...

  16. 40 CFR 63.8575 - What do I need to know about operation, maintenance, and monitoring plans?

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... monitoring plans? (a) For each kiln that is subject to the emission limits specified in Table 1 to this... records to document compliance. (13) If you operate an affected kiln and you plan to take the kiln control... paragraphs (b)(13)(i) and (ii) of this section. (i) Procedures for minimizing HAP emissions from the...

  17. 40 CFR 63.8575 - What do I need to know about operation, maintenance, and monitoring plans?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... monitoring plans? (a) For each kiln that is subject to the emission limits specified in Table 1 to this... records to document compliance. (13) If you operate an affected kiln and you plan to take the kiln control... paragraphs (b)(13)(i) and (ii) of this section. (i) Procedures for minimizing HAP emissions from the...

  18. 40 CFR 63.8575 - What do I need to know about operation, maintenance, and monitoring plans?

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... monitoring plans? (a) For each kiln that is subject to the emission limits specified in Table 1 to this... records to document compliance. (13) If you operate an affected kiln and you plan to take the kiln control... paragraphs (b)(13)(i) and (ii) of this section. (i) Procedures for minimizing HAP emissions from the...

  19. Industrial Maintenance Strategies

    SciTech Connect

    Sajjad Akbar

    2006-07-01

    Industrial plants have become more complex due to technological advancement. This has made the task of maintenance more difficult. The maintenance costs in terms of resources and downtime loss are so high that maintenance function has become a critical factor in a plant's profitability. Industry should devote as much forethought to the management of maintenance function as to production. Maintenance has grown from an art to a precise, technical engineering science. Planning, organizing scheduling and control of maintenance using modern techniques pays dividends in the form of reduced costs and increased reliability. The magnitude and the dimension of maintenance have multiplied due to development in the engineering technologies. Production cost and capacities are directly affected by the breakdown time. Total operating cost including the maintenance cost plays an important role in replacement dimension. The integrated system approach would bring forth the desired results of high maintenance standards. The standards once achieved and sustained, would add to the reliability of the plan and relieve heavy stresses and strains on the engineering logistic support. (author)

  20. Potential pitfalls of the PTV concept in dose-to-medium planning optimization.

    PubMed

    Sterpin, E

    2016-09-01

    In typical treatment planning of 3D IMRT, the incident energy fluence is optimized to achieve a homogeneous dose distribution to the PTV. The PTV includes the tumour but also healthy tissues that may have a different dose response for the same incident energy fluence, like bony structures included in the PTV (mandibles in head and neck tumours or femoral bones in sarcomas). Dose to medium optimization compensates for this heterogeneous response, leading to a non-homogeneous energy fluence in the PTV and a non-homogeneous dose in the CTV in the presence of geometric errors. We illustrate qualitatively this statement in a cylindrical geometry where the PTV includes a CTV (7cm diameter) made of water surrounded by ICRU compact bone (1.2cm thickness); such configuration was chosen to exaggerate the aforementioned effect. Optimization was performed assuming dose equals photon energy fluence times mass energy absorption coefficient. Bone has a 4% lower dose response in a 6 MV flattening filter free spectrum. After optimization either in medium or assuming everything as water composition, the geometry was shifted by 1.2cm and dose recomputed. As expected, compensating for the under-response of the bone material during optimization in medium leads to an overdosage of the CTV when patient geometric errors are taken into account. Optimization in dose assuming everything as water composition leads to a uniform coverage. Robust optimization or forcing a uniform atomic composition in the PTV margin may resolve this incompatibility between the PTV concept and dose to medium optimization. PMID:27546868

  1. Computer-based planning of optimal donor sites for autologous osseous grafts

    NASA Astrophysics Data System (ADS)

    Krol, Zdzislaw; Chlebiej, Michal; Zerfass, Peter; Zeilhofer, Hans-Florian U.; Sader, Robert; Mikolajczak, Pawel; Keeve, Erwin

    2002-05-01

    Bone graft surgery is often necessary for reconstruction of craniofacial defects after trauma, tumor, infection or congenital malformation. In this operative technique the removed or missing bone segment is filled with a bone graft. The mainstay of the craniofacial reconstruction rests with the replacement of the defected bone by autogeneous bone grafts. To achieve sufficient incorporation of the autograft into the host bone, precise planning and simulation of the surgical intervention is required. The major problem is to determine as accurately as possible the donor site where the graft should be dissected from and to define the shape of the desired transplant. A computer-aided method for semi-automatic selection of optimal donor sites for autografts in craniofacial reconstructive surgery has been developed. The non-automatic step of graft design and constraint setting is followed by a fully automatic procedure to find the best fitting position. In extension to preceding work, a new optimization approach based on the Levenberg-Marquardt method has been implemented and embedded into our computer-based surgical planning system. This new technique enables, once the pre-processing step has been performed, selection of the optimal donor site in time less than one minute. The method has been applied during surgery planning step in more than 20 cases. The postoperative observations have shown that functional results, such as speech and chewing ability as well as restoration of bony continuity were clearly better compared to conventionally planned operations. Moreover, in most cases the duration of the surgical interventions has been distinctly reduced.

  2. Power system modeling and optimization methods vis-a-vis integrated resource planning (IRP)

    NASA Astrophysics Data System (ADS)

    Arsali, Mohammad H.

    1998-12-01

    The state-of-the-art restructuring of power industries is changing the fundamental nature of retail electricity business. As a result, the so-called Integrated Resource Planning (IRP) strategies implemented on electric utilities are also undergoing modifications. Such modifications evolve from the imminent considerations to minimize the revenue requirements and maximize electrical system reliability vis-a-vis capacity-additions (viewed as potential investments). IRP modifications also provide service-design bases to meet the customer needs towards profitability. The purpose of this research as deliberated in this dissertation is to propose procedures for optimal IRP intended to expand generation facilities of a power system over a stretched period of time. Relevant topics addressed in this research towards IRP optimization are as follows: (1) Historical prospective and evolutionary aspects of power system production-costing models and optimization techniques; (2) A survey of major U.S. electric utilities adopting IRP under changing socioeconomic environment; (3) A new technique designated as the Segmentation Method for production-costing via IRP optimization; (4) Construction of a fuzzy relational database of a typical electric power utility system for IRP purposes; (5) A genetic algorithm based approach for IRP optimization using the fuzzy relational database.

  3. Beyond optimality: Multistakeholder robustness tradeoffs for regional water portfolio planning under deep uncertainty

    NASA Astrophysics Data System (ADS)

    Herman, Jonathan D.; Zeff, Harrison B.; Reed, Patrick M.; Characklis, Gregory W.

    2014-10-01

    While optimality is a foundational mathematical concept in water resources planning and management, "optimal" solutions may be vulnerable to failure if deeply uncertain future conditions deviate from those assumed during optimization. These vulnerabilities may produce severely asymmetric impacts across a region, making it vital to evaluate the robustness of management strategies as well as their impacts for regional stakeholders. In this study, we contribute a multistakeholder many-objective robust decision making (MORDM) framework that blends many-objective search and uncertainty analysis tools to discover key tradeoffs between water supply alternatives and their robustness to deep uncertainties (e.g., population pressures, climate change, and financial risks). The proposed framework is demonstrated for four interconnected water utilities representing major stakeholders in the "Research Triangle" region of North Carolina, U.S. The utilities supply well over one million customers and have the ability to collectively manage drought via transfer agreements and shared infrastructure. We show that water portfolios for this region that compose optimal tradeoffs (i.e., Pareto-approximate solutions) under expected future conditions may suffer significantly degraded performance with only modest changes in deeply uncertain hydrologic and economic factors. We then use the Patient Rule Induction Method (PRIM) to identify which uncertain factors drive the individual and collective vulnerabilities for the four cooperating utilities. Our framework identifies key stakeholder dependencies and robustness tradeoffs associated with cooperative regional planning, which are critical to understanding the tensions between individual versus regional water supply goals. Cooperative demand management was found to be the key factor controlling the robustness of regional water supply planning, dominating other hydroclimatic and economic uncertainties through the 2025 planning horizon. Results

  4. Trajectory planning of free-floating space robot using Particle Swarm Optimization (PSO)

    NASA Astrophysics Data System (ADS)

    Wang, Mingming; Luo, Jianjun; Walter, Ulrich

    2015-07-01

    This paper investigates the application of Particle Swarm Optimization (PSO) strategy to trajectory planning of the kinematically redundant space robot in free-floating mode. Due to the path dependent dynamic singularities, the volume of available workspace of the space robot is limited and enormous joint velocities are required when such singularities are met. In order to overcome this effect, the direct kinematics equations in conjunction with PSO are employed for trajectory planning of free-floating space robot. The joint trajectories are parametrized with the Bézier curve to simplify the calculation. Constrained PSO scheme with adaptive inertia weight is implemented to find the optimal solution of joint trajectories while specific objectives and imposed constraints are satisfied. The proposed method is not sensitive to the singularity issue due to the application of forward kinematic equations. Simulation results are presented for trajectory planning of 7 degree-of-freedom (DOF) redundant manipulator mounted on a free-floating spacecraft and demonstrate the effectiveness of the proposed method.

  5. Automated gamma knife radiosurgery treatment planning with image registration, data-mining, and Nelder-Mead simplex optimization

    SciTech Connect

    Lee, Kuan J.; Barber, David C.; Walton, Lee

    2006-07-15

    Gamma knife treatments are usually planned manually, requiring much expertise and time. We describe a new, fully automatic method of treatment planning. The treatment volume to be planned is first compared with a database of past treatments to find volumes closely matching in size and shape. The treatment parameters of the closest matches are used as starting points for the new treatment plan. Further optimization is performed with the Nelder-Mead simplex method: the coordinates and weight of the isocenters are allowed to vary until a maximally conformal plan specific to the new treatment volume is found. The method was tested on a randomly selected set of 10 acoustic neuromas and 10 meningiomas. Typically, matching a new volume took under 30 seconds. The time for simplex optimization, on a 3 GHz Xeon processor, ranged from under a minute for small volumes (<1000 cubic mm, 2-3 isocenters), to several tens of hours for large volumes (>30 000 cubic mm,>20 isocenters). In 8/10 acoustic neuromas and 8/10 meningiomas, the automatic method found plans with conformation number equal or better than that of the manual plan. In 4/10 acoustic neuromas and 5/10 meningiomas, both overtreatment and undertreatment ratios were equal or better in automated plans. In conclusion, data-mining of past treatments can be used to derive starting parameters for treatment planning. These parameters can then be computer optimized to give good plans automatically.

  6. Feasibility and robustness of dose painting by numbers in proton therapy with contour-driven plan optimization

    SciTech Connect

    Barragán, A. M. Differding, S.; Lee, J. A.; Sterpin, E.; Janssens, G.

    2015-04-15

    Purpose: To prove the ability of protons to reproduce a dose gradient that matches a dose painting by numbers (DPBN) prescription in the presence of setup and range errors, by using contours and structure-based optimization in a commercial treatment planning system. Methods: For two patients with head and neck cancer, voxel-by-voxel prescription to the target volume (GTV{sub PET}) was calculated from {sup 18}FDG-PET images and approximated with several discrete prescription subcontours. Treatments were planned with proton pencil beam scanning. In order to determine the optimal plan parameters to approach the DPBN prescription, the effects of the scanning pattern, number of fields, number of subcontours, and use of range shifter were separately tested on each patient. Different constant scanning grids (i.e., spot spacing = Δx = Δy = 3.5, 4, and 5 mm) and uniform energy layer separation [4 and 5 mm WED (water equivalent distance)] were analyzed versus a dynamic and automatic selection of the spots grid. The number of subcontours was increased from 3 to 11 while the number of beams was set to 3, 5, or 7. Conventional PTV-based and robust clinical target volumes (CTV)-based optimization strategies were considered and their robustness against range and setup errors assessed. Because of the nonuniform prescription, ensuring robustness for coverage of GTV{sub PET} inevitably leads to overdosing, which was compared for both optimization schemes. Results: The optimal number of subcontours ranged from 5 to 7 for both patients. All considered scanning grids achieved accurate dose painting (1% average difference between the prescribed and planned doses). PTV-based plans led to nonrobust target coverage while robust-optimized plans improved it considerably (differences between worst-case CTV dose and the clinical constraint was up to 3 Gy for PTV-based plans and did not exceed 1 Gy for robust CTV-based plans). Also, only 15% of the points in the GTV{sub PET} (worst case) were

  7. Human motion planning based on recursive dynamics and optimal control techniques

    NASA Technical Reports Server (NTRS)

    Lo, Janzen; Huang, Gang; Metaxas, Dimitris

    2002-01-01

    This paper presents an efficient optimal control and recursive dynamics-based computer animation system for simulating and controlling the motion of articulated figures. A quasi-Newton nonlinear programming technique (super-linear convergence) is implemented to solve minimum torque-based human motion-planning problems. The explicit analytical gradients needed in the dynamics are derived using a matrix exponential formulation and Lie algebra. Cubic spline functions are used to make the search space for an optimal solution finite. Based on our formulations, our method is well conditioned and robust, in addition to being computationally efficient. To better illustrate the efficiency of our method, we present results of natural looking and physically correct human motions for a variety of human motion tasks involving open and closed loop kinematic chains.

  8. Optimal Planning Strategy for Large PV/Battery System Based on Long-Term Insolation Forecasting

    NASA Astrophysics Data System (ADS)

    Yona, Atsushi; Uchida, Kosuke; Senjyu, Tomonobu; Funabashi, Toshihisa

    Photovoltaic (PV) systems are rapidly gaining acceptance as some of the best alternative energy sources. Usually the power output of PV system fluctuates depending on weather conditions. In order to control the fluctuating power output for PV system, it requires control method of energy storage system. This paper proposes an optimization approach to determine the operational planning of power output for PV system with battery energy storage system (BESS). This approach aims to obtain more benefit for electrical power selling and to smooth the fluctuating power output for PV system. The optimization method applies genetic algorithm (GA) considering PV power output forecast error. The forecast error is based on our previous works with the insolation forecasting at one day ahead by using weather reported data, fuzzy theory and neural network(NN). The validity of the proposed method is confirmed by the computer simulations.

  9. Treatment planning, optimization, and beam delivery technqiues for intensity modulated proton therapy

    NASA Astrophysics Data System (ADS)

    Sengbusch, Evan R.

    Physical properties of proton interactions in matter give them a theoretical advantage over photons in radiation therapy for cancer treatment, but they are seldom used relative to photons. The primary barriers to wider acceptance of proton therapy are the technical feasibility, size, and price of proton therapy systems. Several aspects of the proton therapy landscape are investigated, and new techniques for treatment planning, optimization, and beam delivery are presented. The results of these investigations suggest a means by which proton therapy can be delivered more efficiently, effectively, and to a much larger proportion of eligible patients. An analysis of the existing proton therapy market was performed. Personal interviews with over 30 radiation oncology leaders were conducted with regard to the current and future use of proton therapy. In addition, global proton therapy market projections are presented. The results of these investigations serve as motivation and guidance for the subsequent development of treatment system designs and treatment planning, optimization, and beam delivery methods. A major factor impacting the size and cost of proton treatment systems is the maximum energy of the accelerator. Historically, 250 MeV has been the accepted value, but there is minimal quantitative evidence in the literature that supports this standard. A retrospective study of 100 patients is presented that quantifies the maximum proton kinetic energy requirements for cancer treatment, and the impact of those results with regard to treatment system size, cost, and neutron production is discussed. This study is subsequently expanded to include 100 cranial stereotactic radiosurgery (SRS) patients, and the results are discussed in the context of a proposed dedicated proton SRS treatment system. Finally, novel proton therapy optimization and delivery techniques are presented. Algorithms are developed that optimize treatment plans over beam angle, spot size, spot spacing

  10. Developing Multi-Lake Regulation Plans for the Great Lakes through Multi-Scenario Optimization

    NASA Astrophysics Data System (ADS)

    Razavi, S.; Tolson, B.; Asadzadeh, M.

    2011-12-01

    Water levels in the Great Lakes- St. Lawrence freshwater system (Lakes Superior, Michigan, Huron, Erie, and Ontario as well as the St. Lawrence River) impact a variety of stakeholder groups such as hydropower producers, the shipping industry, shoreline property owners and recreational boaters. Although the system is currently managed by control structures at two locations (Lake Superior and Lake Ontario outflows are controlled), there is concern that future extreme climates will generate water supply sequences to the system that will substantially increase the frequency and persistence of extreme water levels imposing millions of dollars of losses to Canadian and American economies. This work partially summarizes a study under The International Upper Great Lakes Study (International Joint Commission) to provide an exploratory conceptual analysis of how and to what extent new control structures in the system could be used to minimize the risks posed by extreme water levels outside of the historic range. In this study, two new hypothetical control structures were investigated to regulate Lake Michigan-Huron and Lake Erie outflows. Multiple regulation plans were developed to operate the hypothetical structures in the St. Clair and/or Niagara rivers in combination with the two existing control structures in the St. Marys and St. Lawrence Rivers. The regulation plans were defined by multi-lake rule curves whose parameters were determined through a simulation-optimization procedure. As there is a high level of uncertainty in future climate, multiple water supply sequences, each 70 years long, representing different future climate scenarios were considered. A multi-scenario based optimization formulation was developed aiming to keep the water levels within the historical range and to minimize and evenly distribute extreme water levels across the system. The dynamically dimensioned search (DDS) algorithm was applied to optimize the multi-scenario based formulation. As the

  11. Enhancement in treatment planning for magnetic nanoparticle hyperthermia: optimization of the heat absorption pattern.

    PubMed

    Salloum, M; Ma, R; Zhu, L

    2009-06-01

    In clinical applications of magnetic nanoparticle hyperthermia for cancer treatment it is very important to ensure a maximum damage to the tumor while protecting the normal tissue. The resultant heating pattern by the nanoparticle distribution in tumor is closely related to the injection parameters. In this study we develop an optimization algorithm to inversely determine the optimum heating patterns induced by multiple nanoparticle injections in tumor models with irregular geometries. The injection site locations, thermal properties of tumor and tissue, and local blood perfusion rates are used as inputs to the algorithm to determine the optimum parameters of the heat sources for all nanoparticle injection sites. The design objective is to elevate the temperature of at least 90% of the tumor above 43 degrees C, and to ensure only less than 10% of the normal tissue is heated to temperatures of 43 degrees C or higher. The efficiency, flexibility and capability of this approach have been demonstrated in a case study of two tumors with simple or complicated geometry. An extensive experimental database should be developed in the future to relate the optimized heating pattern parameters found in this study to their appropriate nanoparticle concentration, injection amount, and injection rate. We believe that the optimization algorithm developed in this study can be used as a guideline for physicians to design an optimal treatment plan in magnetic nanoparticle hyperthermia.

  12. An Asymptotically-Optimal Sampling-Based Algorithm for Bi-directional Motion Planning

    PubMed Central

    Starek, Joseph A.; Gomez, Javier V.; Schmerling, Edward; Janson, Lucas; Moreno, Luis; Pavone, Marco

    2015-01-01

    Bi-directional search is a widely used strategy to increase the success and convergence rates of sampling-based motion planning algorithms. Yet, few results are available that merge both bi-directional search and asymptotic optimality into existing optimal planners, such as PRM*, RRT*, and FMT*. The objective of this paper is to fill this gap. Specifically, this paper presents a bi-directional, sampling-based, asymptotically-optimal algorithm named Bi-directional FMT* (BFMT*) that extends the Fast Marching Tree (FMT*) algorithm to bidirectional search while preserving its key properties, chiefly lazy search and asymptotic optimality through convergence in probability. BFMT* performs a two-source, lazy dynamic programming recursion over a set of randomly-drawn samples, correspondingly generating two search trees: one in cost-to-come space from the initial configuration and another in cost-to-go space from the goal configuration. Numerical experiments illustrate the advantages of BFMT* over its unidirectional counterpart, as well as a number of other state-of-the-art planners. PMID:27004130

  13. SU-E-T-562: Motion Tracking Optimization for Conformal Arc Radiotherapy Plans: A QUASAR Phantom Based Study

    SciTech Connect

    Xu, Z; Wang, I; Yao, R; Podgorsak, M

    2015-06-15

    Purpose: This study is to use plan parameters optimization (Dose rate, collimator angle, couch angle, initial starting phase) to improve the performance of conformal arc radiotherapy plans with motion tracking by increasing the plan performance score (PPS). Methods: Two types of 3D conformal arc plans were created based on QUASAR respiratory motion phantom with spherical and cylindrical targets. Sinusoidal model was applied to the MLC leaves to generate motion tracking plans. A MATLAB program was developed to calculate PPS of each plan (ranges from 0–1) and optimize plan parameters. We first selected the dose rate for motion tracking plans and then used simulated annealing algorithm to search for the combination of the other parameters that resulted in the plan of the maximal PPS. The optimized motion tracking plan was delivered by Varian Truebeam Linac. In-room cameras and stopwatch were used for starting phase selection and synchronization between phantom motion and plan delivery. Gaf-EBT2 dosimetry films were used to measure the dose delivered to the target in QUASAR phantom. Dose profiles and Truebeam trajectory log files were used for plan delivery performance evaluation. Results: For spherical target, the maximal PPS (PPSsph) of the optimized plan was 0.79: (Dose rate: 500MU/min, Collimator: 90°, Couch: +10°, starting phase: 0.83π). For cylindrical target, the maximal PPScyl was 0.75 (Dose rate: 300MU/min, Collimator: 87°, starting phase: 0.97π) with couch at 0°. Differences of dose profiles between motion tracking plans (with the maximal and the minimal PPS) and 3D conformal plans were as follows: PPSsph=0.79: %ΔFWHM: 8.9%, %Dmax: 3.1%; PPSsph=0.52: %ΔFWHM: 10.4%, %Dmax: 6.1%. PPScyl=0.75: %ΔFWHM: 4.7%, %Dmax: 3.6%; PPScyl=0.42: %ΔFWHM: 12.5%, %Dmax: 9.6%. Conclusion: By achieving high plan performance score through parameters optimization, we can improve target dose conformity of motion tracking plan by decreasing total MLC leaf travel distance

  14. Multi-GPU implementation of a VMAT treatment plan optimization algorithm

    SciTech Connect

    Tian, Zhen E-mail: Xun.Jia@UTSouthwestern.edu Folkerts, Michael; Tan, Jun; Jia, Xun E-mail: Xun.Jia@UTSouthwestern.edu Jiang, Steve B. E-mail: Xun.Jia@UTSouthwestern.edu; Peng, Fei

    2015-06-15

    then used to validate the authors’ method. The authors also compare their multi-GPU implementation with three different single GPU implementation strategies, i.e., truncating DDC matrix (S1), repeatedly transferring DDC matrix between CPU and GPU (S2), and porting computations involving DDC matrix to CPU (S3), in terms of both plan quality and computational efficiency. Two more H and N patient cases and three prostate cases are used to demonstrate the advantages of the authors’ method. Results: The authors’ multi-GPU implementation can finish the optimization process within ∼1 min for the H and N patient case. S1 leads to an inferior plan quality although its total time was 10 s shorter than the multi-GPU implementation due to the reduced matrix size. S2 and S3 yield the same plan quality as the multi-GPU implementation but take ∼4 and ∼6 min, respectively. High computational efficiency was consistently achieved for the other five patient cases tested, with VMAT plans of clinically acceptable quality obtained within 23–46 s. Conversely, to obtain clinically comparable or acceptable plans for all six of these VMAT cases that the authors have tested in this paper, the optimization time needed in a commercial TPS system on CPU was found to be in an order of several minutes. Conclusions: The results demonstrate that the multi-GPU implementation of the authors’ column-generation-based VMAT optimization can handle the large-scale VMAT optimization problem efficiently without sacrificing plan quality. The authors’ study may serve as an example to shed some light on other large-scale medical physics problems that require multi-GPU techniques.

  15. Cost-effective river rehabilitation planning: optimizing for morphological benefits at large spatial scales.

    PubMed

    Langhans, Simone D; Hermoso, Virgilio; Linke, Simon; Bunn, Stuart E; Possingham, Hugh P

    2014-01-01

    River rehabilitation aims to protect biodiversity or restore key ecosystem services but the success rate is often low. This is seldom because of insufficient funding for rehabilitation works but because trade-offs between costs and ecological benefits of management actions are rarely incorporated in the planning, and because monitoring is often inadequate for managers to learn by doing. In this study, we demonstrate a new approach to plan cost-effective river rehabilitation at large scales. The framework is based on the use of cost functions (relationship between costs of rehabilitation and the expected ecological benefit) to optimize the spatial allocation of rehabilitation actions needed to achieve given rehabilitation goals (in our case established by the Swiss water act). To demonstrate the approach with a simple example, we link costs of the three types of management actions that are most commonly used in Switzerland (culvert removal, widening of one riverside buffer and widening of both riversides) to the improvement in riparian zone quality. We then use Marxan, a widely applied conservation planning software, to identify priority areas to implement these rehabilitation measures in two neighbouring Swiss cantons (Aargau, AG and Zürich, ZH). The best rehabilitation plans identified for the two cantons met all the targets (i.e. restoring different types of morphological deficits with different actions) rehabilitating 80,786 m (AG) and 106,036 m (ZH) of the river network at a total cost of 106.1 Million CHF (AG) and 129.3 Million CH (ZH). The best rehabilitation plan for the canton of AG consisted of more and better connected sub-catchments that were generally less expensive, compared to its neighbouring canton. The framework developed in this study can be used to inform river managers how and where best to spend their rehabilitation budget for a given set of actions, ensures the cost-effective achievement of desired rehabilitation outcomes, and helps

  16. Cost-effective river rehabilitation planning: optimizing for morphological benefits at large spatial scales.

    PubMed

    Langhans, Simone D; Hermoso, Virgilio; Linke, Simon; Bunn, Stuart E; Possingham, Hugh P

    2014-01-01

    River rehabilitation aims to protect biodiversity or restore key ecosystem services but the success rate is often low. This is seldom because of insufficient funding for rehabilitation works but because trade-offs between costs and ecological benefits of management actions are rarely incorporated in the planning, and because monitoring is often inadequate for managers to learn by doing. In this study, we demonstrate a new approach to plan cost-effective river rehabilitation at large scales. The framework is based on the use of cost functions (relationship between costs of rehabilitation and the expected ecological benefit) to optimize the spatial allocation of rehabilitation actions needed to achieve given rehabilitation goals (in our case established by the Swiss water act). To demonstrate the approach with a simple example, we link costs of the three types of management actions that are most commonly used in Switzerland (culvert removal, widening of one riverside buffer and widening of both riversides) to the improvement in riparian zone quality. We then use Marxan, a widely applied conservation planning software, to identify priority areas to implement these rehabilitation measures in two neighbouring Swiss cantons (Aargau, AG and Zürich, ZH). The best rehabilitation plans identified for the two cantons met all the targets (i.e. restoring different types of morphological deficits with different actions) rehabilitating 80,786 m (AG) and 106,036 m (ZH) of the river network at a total cost of 106.1 Million CHF (AG) and 129.3 Million CH (ZH). The best rehabilitation plan for the canton of AG consisted of more and better connected sub-catchments that were generally less expensive, compared to its neighbouring canton. The framework developed in this study can be used to inform river managers how and where best to spend their rehabilitation budget for a given set of actions, ensures the cost-effective achievement of desired rehabilitation outcomes, and helps

  17. 76 FR 68745 - Notice of Intent To Update the Upland Erosion Control and Revegetation and Maintenance Plan and...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-11-07

    ... May 14, 1999. 64 FR 26572. The Plan and Procedures are referred to at 18 Code of Federal Regulations... Energy Regulatory Commission Notice of Intent To Update the Upland Erosion Control and Revegetation and... The staff of the Office of Energy Projects is in the process of reviewing its Upland Erosion...

  18. 77 FR 31351 - Adequacy Determination for Aspen PM10 and Fort Collins Carbon Monoxide Maintenance Plans' Motor...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-05-25

    ... interpretation, the North Front Range Metropolitan Planning Organization, the Colorado Department of... 93.118(e)(4), which was promulgated August 15, 1997 (62 FR 43780). We described our process for... (69 FR 40004). In addition, in certain areas with monitored ambient carbon monoxide (CO)...

  19. Contingent post-closure plan, hazardous waste management units at selected maintenance facilities, US Army National Training Center, Fort Irwin, California

    SciTech Connect

    Not Available

    1992-01-01

    The National Training Center (NTC) at Fort Irwin, California, is a US Army training installation that provides tactical experience for battalion/task forces and squadrons in a mid- to high-intensity combat scenario. Through joint exercises with US Air Force and other services, the NTC also provides a data source for improvements of training doctrines, organization, and equipment. To meet the training and operational needs of the NTC, several maintenance facilities provide general and direct support for mechanical devices, equipment, and vehicles. Maintenance products used at these facilities include fuels, petroleum-based oils, lubricating grease, various degreasing solvents, antifreeze (ethylene glycol), transmission fluid, brake fluid, and hydraulic oil. Used or spent petroleum-based products generated at the maintenance facilities are temporarily accumulated in underground storage tanks (USTs), collected by the NTC hazardous waste management contractor (HAZCO), and stored at the Petroleum, Oil, and Lubricant (POL) Storage Facility, Building 630, until shipped off site to be recovered, reused, and/or reclaimed. Spent degreasing solvents and other hazardous wastes are containerized and stored on-base for up to 90 days at the NTC's Hazardous Waste Storage Facility, Building 703. The US Environmental Protection Agency (EPA) performed an inspection and reviewed the hazardous waste management operations of the NTC. Inspections indicated that the NTC had violated one or more requirements of Subtitle C of the Resource Conservation and Recovery Act (RCRA) and as a result of these violations was issued a Notice of Noncompliance, Notice of Necessity for Conference, and Proposed Compliance Schedule (NON) dated October 13, 1989. The following post-closure plan is the compliance-based approach for the NTC to respond to the regulatory violations cited in the NON.

  20. Contingent post-closure plan, hazardous waste management units at selected maintenance facilities, US Army National Training Center, Fort Irwin, California

    SciTech Connect

    Not Available

    1992-01-01

    The National Training Center (NTC) at Fort Irwin, California, is a US Army training installation that provides tactical experience for battalion/task forces and squadrons in a mid- to high-intensity combat scenario. Through joint exercises with US Air Force and other services, the NTC also provides a data source for improvements of training doctrines, organization, and equipment. To meet the training and operational needs of the NTC, several maintenance facilities provide general and direct support for mechanical devices, equipment, and vehicles. Maintenance products used at these facilities include fuels, petroleum-based oils, lubricating grease, various degreasing solvents, antifreeze (ethylene glycol), transmission fluid, brake fluid, and hydraulic oil. Used or spent petroleum-based products generated at the maintenance facilities are temporarily accumulated in underground storage tanks (USTs), collected by the NTC hazardous waste management contractor (HAZCO), and stored at the Petroleum, Oil, and Lubricant (POL) Storage Facility, Building 630, until shipped off site to be recovered, reused, and/or reclaimed. Spent degreasing solvents and other hazardous wastes are containerized and stored on-base for up to 90 days at the NTC`s Hazardous Waste Storage Facility, Building 703. The US Environmental Protection Agency (EPA) performed an inspection and reviewed the hazardous waste management operations of the NTC. Inspections indicated that the NTC had violated one or more requirements of Subtitle C of the Resource Conservation and Recovery Act (RCRA) and as a result of these violations was issued a Notice of Noncompliance, Notice of Necessity for Conference, and Proposed Compliance Schedule (NON) dated October 13, 1989. The following post-closure plan is the compliance-based approach for the NTC to respond to the regulatory violations cited in the NON.

  1. SU-E-T-617: A Feasibility Study of Navigation Based Multi Criteria Optimization for Advanced Cervical Cancer IMRT Planning

    SciTech Connect

    Ma, C

    2014-06-01

    Purpose: This study aims to validate multi-criteria optimization (MCO) against standard intensity modulated radiation therapy (IMRT) optimization for advanced cervical cancer in RayStation (v2.4, RaySearch Laboratories, Sweden). Methods: 10 advanced cervical cancer patients IMRT plans were randomly selected, these plans were designed with step and shoot optimization, new plans were then designed with MCO based on these plans,while keeping optimization conditions unchanged,comparison was made between both kinds of plans including the dose volume histogram parameters of PTV and OAR,and were analysed by pairing-t test. Results: We normalize the plan so that 95% volume of PTV achieved the prescribed dose(50Gy). The volume of radiation 10, 20, 30, and 40 Gy of the rectum were reduced by 14.7%,26.8%,21.1%,10.5% respectively(P≥0.05). The mean dose of rectum were reduced by 7.2Gy(P≤0.05). There were no significant differences for the dosimetric parameters for the bladder. Conclusion: In comparision with standard IMRT optimization, MCO reduces the dose of organs at risk with the same PTV coverage,but the result needs further clinical evalution.

  2. Using Many-Objective Optimization and Robust Decision Making to Identify Robust Regional Water Resource System Plans

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    Water resource system planning regulations are increasingly requiring potential plans to be robust, i.e., perform well over a wide range of possible future conditions. Robust Decision Making (RDM) has shown success in aiding the development of robust plans under conditions of 'deep' uncertainty. Under RDM, decision makers iteratively improve the robustness of a candidate plan (or plans) by quantifying its vulnerabilities to future uncertain inputs and proposing ameliorations. RDM requires planners to have an initial candidate plan. However, if the initial plan is far from robust, it may take several iterations before planners are satisfied with its performance across the wide range of conditions. Identifying an initial candidate plan is further complicated if many possible alternative plans exist and if performance is assessed against multiple conflicting criteria. Planners may benefit from considering a plan that already balances multiple performance criteria and provides some level of robustness before the first RDM iteration. In this study we use many-objective evolutionary optimization to identify promising plans before undertaking RDM. This is done for a very large regional planning problem spanning the service area of four major water utilities in East England. The five-objective optimization is performed under an ensemble of twelve uncertainty scenarios to ensure the Pareto-approximate plans exhibit an initial level of robustness. New supply interventions include two reservoirs, one aquifer recharge and recovery scheme, two transfers from an existing reservoir, five reuse and five desalination schemes. Each option can potentially supply multiple demands at varying capacities resulting in 38 unique decisions. Four candidate portfolios were selected using trade-off visualization with the involved utilities. The performance of these plans was compared under a wider range of possible scenarios. The most balanced plan was then submitted into the vulnerability

  3. Multicriteria Optimization in Intensity-Modulated Radiation Therapy Treatment Planning for Locally Advanced Cancer of the Pancreatic Head

    SciTech Connect

    Hong, Theodore S. Craft, David L.; Carlsson, Fredrik; Bortfeld, Thomas R.

    2008-11-15

    Purpose: Intensity-modulated radiation therapy (IMRT) affords the potential to decrease radiation therapy-associated toxicity by creating highly conformal dose distributions. However, the inverse planning process can create a suboptimal plan despite meeting all constraints. Multicriteria optimization (MCO) may reduce the time-consuming iteration loop necessary to develop a satisfactory plan while providing information regarding trade-offs between different treatment planning goals. In this exploratory study, we examine the feasibility and utility of MCO in physician plan selection in patients with locally advanced pancreatic cancer (LAPC). Methods and Materials: The first 10 consecutive patients with LAPC treated with IMRT were evaluated. A database of plans (Pareto surface) was created that met the inverse planning goals. The physician then navigated to an 'optimal' plan from the point on the Pareto surface at which kidney dose was minimized. Results: Pareto surfaces were created for all 10 patients. A physician was able to select a plan from the Pareto surface within 10 minutes for all cases. Compared with the original (treated) IMRT plans, the plan selected from the Pareto surface had a lower stomach mean dose in 9 of 10 patients, although often at the expense of higher kidney dose than with the treated plan. Conclusion: The MCO is feasible in patients with LAPC and allows the physician to choose a satisfactory plan quickly. Generally, when given the opportunity, the physician will choose a plan with a lower stomach dose. The MCO enables a physician to provide greater active clinical input into the IMRT planning process.

  4. Rapidly-Exploring Roadmaps: Weighing Exploration vs. Refinement in Optimal Motion Planning.

    PubMed

    Alterovitz, Ron; Patil, Sachin; Derbakova, Anna

    2011-01-01

    Computing globally optimal motion plans requires exploring the configuration space to identify reachable free space regions as well as refining understanding of already explored regions to find better paths. We present the rapidly-exploring roadmap (RRM), a new method for single-query optimal motion planning that allows the user to explicitly consider the trade-off between exploration and refinement. RRM initially explores the configuration space like a rapidly exploring random tree (RRT). Once a path is found, RRM uses a user-specified parameter to weigh whether to explore further or to refine the explored space by adding edges to the current roadmap to find higher quality paths in the explored space. Unlike prior methods, RRM does not focus solely on exploration or refine prematurely. We demonstrate the performance of RRM and the trade-off between exploration and refinement using two examples, a point robot moving in a plane and a concentric tube robot capable of following curved trajectories inside patient anatomy for minimally invasive medical procedures.

  5. Optimization of people evacuation plans on the basis of wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Amirgaliyev, Yedilkhan; Yunussov, Rassul; Mamyrbayev, Orken

    2016-01-01

    This paper introduces the optimization process for people salvation in critical situations by organizing their evacuation plan from enclosed areas using modern approaches of data acquisition on the basis of wireless sensor networks. The proposed technology allows the ability to gather information about people density on the surveyed area by the usage of wireless sensor networks, consistently covering the enclosed territory. It enables the update of the evacuation plan on the basis of people density information inside the enclosed areas online. It is proposed to use common video surveillance cameras as sensors. The advantage of visual surveillance using cameras is that it does not require additional technological equipment for the area and much more important does not impose rules and restriction on the surveillance objects (people in this case). Next tasks are to be solved: creation of mathematical model of optimal enclosed area surveillance by wireless sensors, database and data interrogation modelling of wireless sensor network, creation of algorithmic model for automated people counting using video signal for the covering area; creation of dynamic people evacuation model on the basis of maximum flow problem [1, 2].

  6. Optimization of the scheme for natural ecology planning of urban rivers based on ANP (analytic network process) model.

    PubMed

    Zhang, Yichuan; Wang, Jiangping

    2015-07-01

    Rivers serve as a highly valued component in ecosystem and urban infrastructures. River planning should follow basic principles of maintaining or reconstructing the natural landscape and ecological functions of rivers. Optimization of planning scheme is a prerequisite for successful construction of urban rivers. Therefore, relevant studies on optimization of scheme for natural ecology planning of rivers is crucial. In the present study, four planning schemes for Zhaodingpal River in Xinxiang City, Henan Province were included as the objects for optimization. Fourteen factors that influenced the natural ecology planning of urban rivers were selected from five aspects so as to establish the ANP model. The data processing was done using Super Decisions software. The results showed that important degree of scheme 3 was highest. A scientific, reasonable and accurate evaluation of schemes could be made by ANP method on natural ecology planning of urban rivers. This method could be used to provide references for sustainable development and construction of urban rivers. ANP method is also suitable for optimization of schemes for urban green space planning and design.

  7. Comprehensive Fault Tolerance and Science-Optimal Attitude Planning for Spacecraft Applications

    NASA Astrophysics Data System (ADS)

    Nasir, Ali

    Spacecraft operate in a harsh environment, are costly to launch, and experience unavoidable communication delay and bandwidth constraints. These factors motivate the need for effective onboard mission and fault management. This dissertation presents an integrated framework to optimize science goal achievement while identifying and managing encountered faults. Goal-related tasks are defined by pointing the spacecraft instrumentation toward distant targets of scientific interest. The relative value of science data collection is traded with risk of failures to determine an optimal policy for mission execution. Our major innovation in fault detection and reconfiguration is to incorporate fault information obtained from two types of spacecraft models: one based on the dynamics of the spacecraft and the second based on the internal composition of the spacecraft. For fault reconfiguration, we consider possible changes in both dynamics-based control law configuration and the composition-based switching configuration. We formulate our problem as a stochastic sequential decision problem or Markov Decision Process (MDP). To avoid the computational complexity involved in a fully-integrated MDP, we decompose our problem into multiple MDPs. These MDPs include planning MDPs for different fault scenarios, a fault detection MDP based on a logic-based model of spacecraft component and system functionality, an MDP for resolving conflicts between fault information from the logic-based model and the dynamics-based spacecraft models〝 and the reconfiguration MDP that generates a policy optimized over the relative importance of the mission objectives versus spacecraft safety. Approximate Dynamic Programming (ADP) methods for the decomposition of the planning and fault detection MDPs are applied. To show the performance of the MDP-based frameworks and ADP methods, a suite of spacecraft attitude planning case studies are described. These case studies are used to analyze the content and

  8. A planning support system to optimize approval of private housing development projects

    NASA Astrophysics Data System (ADS)

    Hussnain, M. Q.; Wakil, K.; Waheed, A.; Tahir, A.

    2016-06-01

    Out of 182 million population of Pakistan, 38% reside in urban areas having an average growth rate of 1.6%, raising the urban housing demand significantly. Poor state response to fulfil the housing needs has resulted in a mushroom growth of private housing schemes (PHS) over the years. Consequently, only in five major cities of Punjab, there are 383 legal and 150 illegal private housing development projects against 120 public sector housing schemes. A major factor behind the cancerous growth of unapproved PHS is the prolonged and delayed approval process in concerned approval authorities requiring 13 months on average. Currently, manual and paper-based approaches are used for vetting and for granting the permission which is highly subjective and non-transparent. This study aims to design a flexible planning support system (PSS) to optimize the vetting process of PHS projects under any development authority in Pakistan by reducing time and cost required for site and documents investigations. Relying on the review of regulatory documents and interviews with professional planners and land developers, this study describes the structure of a PSS developed using open- source geo-spatial tools such as OpenGeo Suite, PHP, and PostgreSQL. It highlights the development of a Knowledge Module (based on regulatory documents) containing equations related to scheme type, size (area), location, access road, components of layout plan, planning standards and other related approval checks. Furthermore, it presents the architecture of the database module and system data requirements categorized as base datasets (built-in part of PSS) and input datasets (related to the housing project under approval). It is practically demonstrated that developing a customized PSS to optimize PHS approval process in Pakistan is achievable with geospatial technology. With the provision of such a system, the approval process for private housing schemes not only becomes quicker and user-friendly but also

  9. Integrating planning and design optimization for thermal power generation in developing economies: Designs for Vietnam

    NASA Astrophysics Data System (ADS)

    Pham, John Dinh Chuong

    In the twenty first century, global warming and climate change have become environmental issues worldwide. There is a need to reduce greenhouse gas emissions from thermal power plants through improved efficiency. This need is shared by both developed and developing countries. It is particularly important in rapidly developing economies (for example, Vietnam, South Korea, and China) where there is very significant need to increase generation capacity. This thesis addresses improving thermal power plant efficiency through an improved planning process that emphasizes integrated design. With the integration of planning and design considerations of key components in thermal electrical generation, along with the selection of appropriate up-to-date technologies, greater efficiency and reduction of emissions could be achieved. The major barriers to the integration of overall power plant optimization are the practice of individual island tendering packages, and the lack of coordinating efforts between major original equipment manufacturers (OEM). This thesis assesses both operational and design aspects of thermal power plants to identify opportunities for energy saving and the associated reduction of CO2 emissions. To demonstrate the potential of the integrated planning design approach, three advanced thermal power plants, using anthracite coal, oil and gas as their respective fuel, were developed as a case study. The three plant formulations and simulations were performed with the cooperation of several leading companies in the power industry including Babcock & Wilcox, Siemens KWU, Siemens-Westinghouse Power Corporation, Hitachi, Alstom Air Preheater, TLT-Covent, and ABB Flakt. The first plant is a conventional W-Flame anthracite coal-fired unit for base load operation. The second is a supercritical oil-fired plant with advanced steam condition, for two shifting and cycling operations. The third plant is a gas-fired combined cycle unit employing a modern steam-cooled gas

  10. Y-12 Groundwater Protection Program Monitoring Optimization Plan For Groundwater Monitoring Wells At The U.S. Department Of Energy Y-12 National Security Complex, Oak Ridge, Tennessee

    SciTech Connect

    Elvado Environmental LLC

    2009-12-01

    This document is the monitoring optimization plan for groundwater monitoring wells associated with the U.S. Department of Energy (DOE) Y-12 National Security Complex (Y-12) in Oak Ridge, Tennessee (Figure A.1). The plan describes the technical approach that will be implemented under the Y-12 Groundwater Protection Program (GWPP) to focus available resources on the monitoring wells at Y-12 that provide the most useful hydrologic and groundwater quality monitoring data. The technical approach is based on the GWPP status designation for each well (Section 2.0). Under this approach, wells granted 'active' status are used by the GWPP for hydrologic monitoring and/or groundwater quality sampling (Section 3.0), whereas wells granted 'inactive' status are not used for either purpose. The status designation also defines the frequency at which the GWPP will inspect applicable wells, the scope of these well inspections, and extent of any maintenance actions initiated by the GWPP (Section 3.0). Details regarding the ancillary activities associated with implementation of this plan (e.g., well inspection) are deferred to the referenced GWPP plans and procedures (Section 4.0). This plan applies to groundwater wells associated with Y-12 and related waste management areas and facilities located within three hydrogeologic regimes (Figure A.1): the Bear Creek Hydrogeologic Regime (Bear Creek Regime), the Upper East Fork Poplar Creek Hydrogeologic Regime (East Fork Regime), and the Chestnut Ridge Hydrogeologic Regime (Chestnut Ridge Regime). The Bear Creek Regime encompasses a section of Bear Creek Valley (BCV) immediately west of Y-12. The East Fork Regime encompasses most of the Y-12 process, operations, and support facilities in BCV and, for the purposes of this plan, includes a section of Union Valley east of the DOE Oak Ridge Reservation (ORR) boundary along Scarboro Road. The Chestnut Ridge Regime encompasses a section of Chestnut Ridge directly south of Y-12 that is bound on

  11. Time-optimal path planning in dynamic flows using level set equations: theory and schemes

    NASA Astrophysics Data System (ADS)

    Lolla, Tapovan; Lermusiaux, Pierre F. J.; Ueckermann, Mattheus P.; Haley, Patrick J.

    2014-10-01

    We develop an accurate partial differential equation-based methodology that predicts the time-optimal paths of autonomous vehicles navigating in any continuous, strong, and dynamic ocean currents, obviating the need for heuristics. The goal is to predict a sequence of steering directions so that vehicles can best utilize or avoid currents to minimize their travel time. Inspired by the level set method, we derive and demonstrate that a modified level set equation governs the time-optimal path in any continuous flow. We show that our algorithm is computationally efficient and apply it to a number of experiments. First, we validate our approach through a simple benchmark application in a Rankine vortex flow for which an analytical solution is available. Next, we apply our methodology to more complex, simulated flow fields such as unsteady double-gyre flows driven by wind stress and flows behind a circular island. These examples show that time-optimal paths for multiple vehicles can be planned even in the presence of complex flows in domains with obstacles. Finally, we present and support through illustrations several remarks that describe specific features of our methodology.

  12. Time-optimal path planning in dynamic flows using level set equations: theory and schemes

    NASA Astrophysics Data System (ADS)

    Lolla, Tapovan; Lermusiaux, Pierre F. J.; Ueckermann, Mattheus P.; Haley, Patrick J.

    2014-09-01

    We develop an accurate partial differential equation-based methodology that predicts the time-optimal paths of autonomous vehicles navigating in any continuous, strong, and dynamic ocean currents, obviating the need for heuristics. The goal is to predict a sequence of steering directions so that vehicles can best utilize or avoid currents to minimize their travel time. Inspired by the level set method, we derive and demonstrate that a modified level set equation governs the time-optimal path in any continuous flow. We show that our algorithm is computationally efficient and apply it to a number of experiments. First, we validate our approach through a simple benchmark application in a Rankine vortex flow for which an analytical solution is available. Next, we apply our methodology to more complex, simulated flow fields such as unsteady double-gyre flows driven by wind stress and flows behind a circular island. These examples show that time-optimal paths for multiple vehicles can be planned even in the presence of complex flows in domains with obstacles. Finally, we present and support through illustrations several remarks that describe specific features of our methodology.

  13. Optimal vaccination and bednet maintenance for the control of malaria in a region with naturally acquired immunity.

    PubMed

    Prosper, Olivia; Ruktanonchai, Nick; Martcheva, Maia

    2014-07-21

    Following over two decades of research, the malaria vaccine candidate RTS,S has reached the final stages of vaccine trials, demonstrating an efficacy of roughly 50% in young children. Regions with high malaria prevalence tend to have high levels of naturally acquired immunity (NAI) to severe malaria; NAI is caused by repeated exposure to infectious bites and results in large asymptomatic populations. To address concerns about how these vaccines will perform in regions with existing NAI, we developed a simple malaria model incorporating vaccination and NAI. Typically, if the basic reproduction number (R0) for malaria is greater than unity, the disease will persist; otherwise, the disease will become extinct. However, analysis of this model revealed that NAI, compounded by a subpopulation with only partial protection to malaria, may render vaccination efforts ineffective and potentially detrimental to malaria control, by increasing R0 and increasing the likelihood of malaria persistence even when R0<1. The likelihood of this scenario increases when non-immune infected individuals are treated disproportionately compared with partially immune individuals - a plausible scenario since partially immune individuals are more likely to be asymptomatically infected. Consequently, we argue that active case-detection of asymptomatic infections is a critical component of an effective malaria control program. We then investigated optimal vaccination and bednet control programs under two endemic settings with varying levels of naturally acquired immunity: a typical setting under which prevalence decays when R0<1, and a setting in which subthreshold endemic equilibria exist. A qualitative comparison of the optimal control results under the first setting revealed that the optimal policy differs depending on whether the goal is to reduce total morbidity, or to reduce clinical infections. Furthermore, this comparison dictates that control programs should place less effort in

  14. Study to develop an inspection, maintenance, and repair plan for OTEC (Ocean Thermal Energy Conversion) modular experiment plants. Final report

    SciTech Connect

    Not Available

    1980-04-01

    The inspection, maintenance and repair (IM and R) of the Ocean Thermal Energy Conversion (OTEC) Modular Experiment Plant (Pilot Plant) have been studied in two phases: Task I and Task II. Task I phase developed IM and R identification forms, identified requirements for routine and post casualty IM and R, and categorized and outlined potential procedures to perform IM and R activities. The efforts of the Task II phase have been directed to meet the following objectives: to provide feedback to the OTEC marine systems designs to assure that such designs reflect appropriate consideration of IM and R methods and unit costs, resulting in designs with reduced life cycle costs; to include technical information concerning OTEC IM and R possibilities to NOAA/DOE; to outline a basis in which the anticipated IM and R contributions to life cycle costs can be developed for any specific OTEC plant design; to identify IM and R methods within the state-of-the-art in the offshore industry; to determine the application of potential IM and R procedures for the commercial operation of OTEC 10/40 Pilot Plant(s); and input into the US government formulation of statutory and regulatory IM and R requirements for OTEC plants.

  15. Normal formation of a vertebrate body plan and loss of tissue maintenance in the absence of ezh2.

    PubMed

    San, Bilge; Chrispijn, Naomi D; Wittkopp, Nadine; van Heeringen, Simon J; Lagendijk, Anne K; Aben, Marco; Bakkers, Jeroen; Ketting, René F; Kamminga, Leonie M

    2016-01-01

    Polycomb group (PcG) proteins are transcriptional repressors of numerous genes, many of which regulate cell cycle progression or developmental processes. We used zebrafish to study Enhancer of zeste homolog 2 (Ezh2), the PcG protein responsible for placing the transcriptional repressive H3K27me3 mark. We identified a nonsense mutant of ezh2 and generated maternal zygotic (MZ) ezh2 mutant embryos. In contrast to knockout mice for PcG proteins, MZezh2 mutant embryos gastrulate seemingly normal, but die around 2 days post fertilization displaying pleiotropic phenotypes. Expression analyses indicated that genes important for early development are not turned off properly, revealing a regulatory role for Ezh2 during zygotic gene expression. In addition, we suggest that Ezh2 regulates maternal mRNA loading of zygotes. Analyses of tissues arising later in development, such as heart, liver, and pancreas, indicated that Ezh2 is required for maintenance of differentiated cell fates. Our data imply that the primary role of Ezh2 is to maintain tissues after tissue specification. Furthermore, our work indicates that Ezh2 is essential to sustain tissue integrity and to set up proper maternal mRNA contribution, and presents a novel and powerful tool to study how PcG proteins contribute to early vertebrate development.

  16. Normal formation of a vertebrate body plan and loss of tissue maintenance in the absence of ezh2

    PubMed Central

    San, Bilge; Chrispijn, Naomi D.; Wittkopp, Nadine; van Heeringen, Simon J.; Lagendijk, Anne K.; Aben, Marco; Bakkers, Jeroen; Ketting, René F.; Kamminga, Leonie M.

    2016-01-01

    Polycomb group (PcG) proteins are transcriptional repressors of numerous genes, many of which regulate cell cycle progression or developmental processes. We used zebrafish to study Enhancer of zeste homolog 2 (Ezh2), the PcG protein responsible for placing the transcriptional repressive H3K27me3 mark. We identified a nonsense mutant of ezh2 and generated maternal zygotic (MZ) ezh2 mutant embryos. In contrast to knockout mice for PcG proteins, MZezh2 mutant embryos gastrulate seemingly normal, but die around 2 days post fertilization displaying pleiotropic phenotypes. Expression analyses indicated that genes important for early development are not turned off properly, revealing a regulatory role for Ezh2 during zygotic gene expression. In addition, we suggest that Ezh2 regulates maternal mRNA loading of zygotes. Analyses of tissues arising later in development, such as heart, liver, and pancreas, indicated that Ezh2 is required for maintenance of differentiated cell fates. Our data imply that the primary role of Ezh2 is to maintain tissues after tissue specification. Furthermore, our work indicates that Ezh2 is essential to sustain tissue integrity and to set up proper maternal mRNA contribution, and presents a novel and powerful tool to study how PcG proteins contribute to early vertebrate development. PMID:27145952

  17. Asymptotically Optimal Motion Planning for Learned Tasks Using Time-Dependent Cost Maps

    PubMed Central

    Bowen, Chris; Ye, Gu; Alterovitz, Ron

    2015-01-01

    In unstructured environments in people’s homes and workspaces, robots executing a task may need to avoid obstacles while satisfying task motion constraints, e.g., keeping a plate of food level to avoid spills or properly orienting a finger to push a button. We introduce a sampling-based method for computing motion plans that are collision-free and minimize a cost metric that encodes task motion constraints. Our time-dependent cost metric, learned from a set of demonstrations, encodes features of a task’s motion that are consistent across the demonstrations and, hence, are likely required to successfully execute the task. Our sampling-based motion planner uses the learned cost metric to compute plans that simultaneously avoid obstacles and satisfy task constraints. The motion planner is asymptotically optimal and minimizes the Mahalanobis distance between the planned trajectory and the distribution of demonstrations in a feature space parameterized by the locations of task-relevant objects. The motion planner also leverages the distribution of the demonstrations to significantly reduce plan computation time. We demonstrate the method’s effectiveness and speed using a small humanoid robot performing tasks requiring both obstacle avoidance and satisfaction of learned task constraints. Note to Practitioners Motivated by the desire to enable robots to autonomously operate in cluttered home and workplace environments, this paper presents an approach for intuitively training a robot in a manner that enables it to repeat the task in novel scenarios and in the presence of unforeseen obstacles in the environment. Based on user-provided demonstrations of the task, our method learns features of the task that are consistent across the demonstrations and that we expect should be repeated by the robot when performing the task. We next present an efficient algorithm for planning robot motions to perform the task based on the learned features while avoiding obstacles. We

  18. SU-E-J-137: Incorporating Tumor Regression Into Robust Plan Optimization for Head and Neck Radiotherapy

    SciTech Connect

    Zhang, P; Hu, J; Tyagi, N; Mageras, G; Lee, N; Hunt, M

    2014-06-01

    Purpose: To develop a robust planning paradigm which incorporates a tumor regression model into the optimization process to ensure tumor coverage in head and neck radiotherapy. Methods: Simulation and weekly MR images were acquired for a group of head and neck patients to characterize tumor regression during radiotherapy. For each patient, the tumor and parotid glands were segmented on the MR images and the weekly changes were formulated with an affine transformation, where morphological shrinkage and positional changes are modeled by a scaling factor, and centroid shifts, respectively. The tumor and parotid contours were also transferred to the planning CT via rigid registration. To perform the robust planning, weekly predicted PTV and parotid structures were created by transforming the corresponding simulation structures according to the weekly affine transformation matrix averaged over patients other than him/herself. Next, robust PTV and parotid structures were generated as the union of the simulation and weekly prediction contours. In the subsequent robust optimization process, attainment of the clinical dose objectives was required for the robust PTV and parotids, as well as other organs at risk (OAR). The resulting robust plans were evaluated by looking at the weekly and total accumulated dose to the actual weekly PTV and parotid structures. The robust plan was compared with the original plan based on the planning CT to determine its potential clinical benefit. Results: For four patients, the average weekly change to tumor volume and position was −4% and 1.2 mm laterally-posteriorly. Due to these temporal changes, the robust plans resulted in an accumulated PTV D95 that was, on average, 2.7 Gy higher than the plan created from the planning CT. OAR doses were similar. Conclusion: Integration of a tumor regression model into target delineation and plan robust optimization is feasible and may yield improved tumor coverage. Part of this research is supported

  19. Planning a Target Renewable Portfolio using Atmospheric Modeling and Stochastic Optimization

    NASA Astrophysics Data System (ADS)

    Hart, E.; Jacobson, M. Z.

    2009-12-01

    A number of organizations have suggested that an 80% reduction in carbon emissions by 2050 is a necessary step to mitigate climate change and that decarbonization of the electricity sector is a crucial component of any strategy to meet this target. Integration of large renewable and intermittent generators poses many new problems in power system planning. In this study, we attempt to determine an optimal portfolio of renewable resources to meet best the fluctuating California load while also meeting an 80% carbon emissions reduction requirement. A stochastic optimization scheme is proposed that is based on a simplified model of the California electricity grid. In this single-busbar power system model, the load is met with generation from wind, solar thermal, photovoltaic, hydroelectric, geothermal, and natural gas plants. Wind speeds and insolation are calculated using GATOR-GCMOM, a global-through-urban climate-weather-air pollution model. Fields were produced for California and Nevada at 21km SN by 14 km WE spatial resolution every 15 minutes for the year 2006. Load data for 2006 were obtained from the California ISO OASIS database. Maximum installed capacities for wind and solar thermal generation were determined using a GIS analysis of potential development sites throughout the state. The stochastic optimization scheme requires that power balance be achieved in a number of meteorological and load scenarios that deviate from the forecasted (or modeled) data. By adjusting the error distributions of the forecasts, the model describes how improvements in wind speed and insolation forecasting may affect the optimal renewable portfolio. Using a simple model, we describe the diversity, size, and sensitivities of a renewable portfolio that is best suited to the resources and needs of California and that contributes significantly to reduction of the state’s carbon emissions.

  20. 43 CFR 1610.5-4 - Maintenance.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Maintenance. 1610.5-4 Section 1610.5-4... Planning § 1610.5-4 Maintenance. Resource management plans and supporting components shall be maintained as necessary to reflect minor changes in data. Such maintenance is limited to further refining or documenting...

  1. The Adjoint Method for The Optimization of Brachytherapy and Radiotherapy Patient Treatment Planning Procedures Using Monte Carlo Calculations

    SciTech Connect

    D.L. Henderson; S. Yoo; M. Kowalok; T.R. Mackie; B.R. Thomadsen

    2001-10-30

    The goal of this project is to investigate the use of the adjoint method, commonly used in the reactor physics community, for the optimization of radiation therapy patient treatment plans. Two different types of radiation therapy are being examined, interstitial brachytherapy and radiotherapy. In brachytherapy radioactive sources are surgically implanted within the diseased organ such as the prostate to treat the cancerous tissue. With radiotherapy, the x-ray source is usually located at a distance of about 1-metere from the patient and focused on the treatment area. For brachytherapy the optimization phase of the treatment plan consists of determining the optimal placement of the radioactive sources, which delivers the prescribed dose to the disease tissue while simultaneously sparing (reducing) the dose to sensitive tissue and organs. For external beam radiation therapy the optimization phase of the treatment plan consists of determining the optimal direction and intensity of beam, which provides complete coverage of the tumor region with the prescribed dose while simultaneously avoiding sensitive tissue areas. For both therapy methods, the optimal treatment plan is one in which the diseased tissue has been treated with the prescribed dose and dose to the sensitive tissue and organs has been kept to a minimum.

  2. Expected treatment dose construction and adaptive inverse planning optimization: Implementation for offline head and neck cancer adaptive radiotherapy

    SciTech Connect

    Yan Di; Liang Jian

    2013-02-15

    Purpose: To construct expected treatment dose for adaptive inverse planning optimization, and evaluate it on head and neck (h and n) cancer adaptive treatment modification. Methods: Adaptive inverse planning engine was developed and integrated in our in-house adaptive treatment control system. The adaptive inverse planning engine includes an expected treatment dose constructed using the daily cone beam (CB) CT images in its objective and constrains. Feasibility of the adaptive inverse planning optimization was evaluated retrospectively using daily CBCT images obtained from the image guided IMRT treatment of 19 h and n cancer patients. Adaptive treatment modification strategies with respect to the time and the number of adaptive inverse planning optimization during the treatment course were evaluated using the cumulative treatment dose in organs of interest constructed using all daily CBCT images. Results: Expected treatment dose was constructed to include both the delivered dose, to date, and the estimated dose for the remaining treatment during the adaptive treatment course. It was used in treatment evaluation, as well as in constructing the objective and constraints for adaptive inverse planning optimization. The optimization engine is feasible to perform planning optimization based on preassigned treatment modification schedule. Compared to the conventional IMRT, the adaptive treatment for h and n cancer illustrated clear dose-volume improvement for all critical normal organs. The dose-volume reductions of right and left parotid glands, spine cord, brain stem and mandible were (17 {+-} 6)%, (14 {+-} 6)%, (11 {+-} 6)%, (12 {+-} 8)%, and (5 {+-} 3)% respectively with the single adaptive modification performed after the second treatment week; (24 {+-} 6)%, (22 {+-} 8)%, (21 {+-} 5)%, (19 {+-} 8)%, and (10 {+-} 6)% with three weekly modifications; and (28 {+-} 5)%, (25 {+-} 9)%, (26 {+-} 5)%, (24 {+-} 8)%, and (15 {+-} 9)% with five weekly modifications. Conclusions

  3. Y-12 Groundwater Protection Program Monitoring Optimization Plan for Groundwater Monitoring Wells at the U.S. Department of Energy Y-12 National Security Complex

    SciTech Connect

    2006-12-01

    This document is the monitoring optimization plan for groundwater monitoring wells associated with the U.S. Department of Energy (DOE) Y-12 National Security Complex (Y-12) in Oak Ridge, Tennessee (Figure A.1). The plan describes the technical approach that will be implemented under the Y-12 Groundwater Protection Program (GWPP) to focus available resources on the monitoring wells at Y-12 that provide the most useful hydrologic and water-quality monitoring data. The technical approach is based on the GWPP status designation for each well (Section 2.0). Under this approach, wells granted ''active'' status are used by the GWPP for hydrologic monitoring and/or groundwater quality sampling (Section 3.0), whereas wells granted ''inactive'' status are not used for either purpose. The status designation also defines the frequency at which the GWPP will inspect applicable wells, the scope of these well inspections, and extent of any maintenance actions initiated by the GWPP (Section 3.0). Details regarding the ancillary activities associated with implementation of this plan (e.g., well inspection) are deferred to the referenced GWPP plans and procedures (Section 4.0). This plan applies to groundwater wells associated with Y-12 and related waste management areas and facilities located within three hydrogeologic regimes (Figure A.1): the Bear Creek Hydrogeologic Regime (Bear Creek Regime), the Upper East Fork Poplar Creek Hydrogeologic Regime (East Fork Regime), and the Chestnut Ridge Hydrogeologic Regime (Chestnut Ridge Regime). The Bear Creek Regime encompasses a section of Bear Creek Valley (BCV) immediately west of Y-12. The East Fork Regime encompasses most of the Y-12 process, operations, and support facilities in BCV and, for the purposes of this plan, includes a section of Union Valley east of the DOE Oak Ridge Reservation (ORR) boundary along Scarboro Road. The Chestnut Ridge Regime encompasses a section of Chestnut Ridge directly south of Y-12 that is bound on the

  4. Optimal path planning for single and multiple aircraft using a reduced order formulation

    NASA Astrophysics Data System (ADS)

    Twigg, Shannon S.

    High-flying unmanned reconnaissance and surveillance systems are now being used extensively in the United States military. Current development programs are producing demonstrations of next-generation unmanned flight systems that are designed to perform combat missions. Their use in first-strike combat operations will dictate operations in densely cluttered environments that include unknown obstacles and threats, and will require the use of terrain for masking. The demand for autonomy of operations in such environments dictates the need for advanced trajectory optimization capabilities. In addition, the ability to coordinate the movements of more than one aircraft in the same area is an emerging challenge. This thesis examines using an analytical reduced order formulation for trajectory generation for minimum time and terrain masking cases. First, pseudo-3D constant velocity equations of motion are used for path planning for a single vehicle. In addition, the inclusion of winds, moving targets and moving threats is considered. Then, this formulation is increased to using 3D equations of motion, both with a constant velocity and with a simplified varying velocity model. Next, the constant velocity equations of motion are expanded to include the simultaneous path planning of an unspecified number of vehicles, for both aircraft avoidance situations and formation flight cases.

  5. Vehicle path-planning in three dimensions using optics analogs for optimizing visibility and energy cost

    NASA Technical Reports Server (NTRS)

    Rowe, Neil C.; Lewis, David H.

    1989-01-01

    Path planning is an important issue for space robotics. Finding safe and energy-efficient paths in the presence of obstacles and other constraints can be complex although important. High-level (large-scale) path planning for robotic vehicles was investigated in three-dimensional space with obstacles, accounting for: (1) energy costs proportional to path length; (2) turn costs where paths change trajectory abruptly; and (3) safety costs for the danger associated with traversing a particular path due to visibility or invisibility from a fixed set of observers. Paths optimal with respect to these cost factors are found. Autonomous or semi-autonomous vehicles were considered operating either in a space environment around satellites and space platforms, or aircraft, spacecraft, or smart missiles operating just above lunar and planetary surfaces. One class of applications concerns minimizing detection, as for example determining the best way to make complex modifications to a satellite without being observed by hostile sensors; another example is verifying there are no paths (holes) through a space defense system. Another class of applications concerns maximizing detection, as finding a good trajectory between mountain ranges of a planet while staying reasonably close to the surface, or finding paths for a flight between two locations that maximize the average number of triangulation points available at any time along the path.

  6. Research on optimal path planning algorithm of task-oriented optical remote sensing satellites

    NASA Astrophysics Data System (ADS)

    Liu, Yunhe; Xu, Shengli; Liu, Fengjing; Yuan, Jingpeng

    2015-08-01

    GEO task-oriented optical remote sensing satellite, is very suitable for long-term continuous monitoring and quick access to imaging. With the development of high resolution optical payload technology and satellite attitude control technology, GEO optical remote sensing satellites will become an important developing trend for aerospace remote sensing satellite in the near future. In the paper, we focused on GEO optical remote sensing satellite plane array stare imaging characteristics and real-time leading mission of earth observation mode, targeted on satisfying needs of the user with the minimum cost of maneuver, and put forward the optimal path planning algorithm centered on transformation from geographic coordinate space to Field of plane, and finally reduced the burden of the control system. In this algorithm, bounded irregular closed area on the ground would be transformed based on coordinate transformation relations in to the reference plane for field of the satellite payload, and then using the branch and bound method to search for feasible solutions, cutting off the non-feasible solution in the solution space based on pruning strategy; and finally trimming some suboptimal feasible solutions based on the optimization index until a feasible solution for the global optimum. Simulation and visualization presentation software testing results verified the feasibility and effectiveness of the strategy.

  7. Multi-objective optimization in systematic conservation planning and the representation of genetic variability among populations.

    PubMed

    Schlottfeldt, S; Walter, M E M T; Carvalho, A C P L F; Soares, T N; Telles, M P C; Loyola, R D; Diniz-Filho, J A F

    2015-06-18

    Biodiversity crises have led scientists to develop strategies for achieving conservation goals. The underlying principle of these strategies lies in systematic conservation planning (SCP), in which there are at least 2 conflicting objectives, making it a good candidate for multi-objective optimization. Although SCP is typically applied at the species level (or hierarchically higher), it can be used at lower hierarchical levels, such as using alleles as basic units for analysis, for conservation genetics. Here, we propose a method of SCP using a multi-objective approach. We used non-dominated sorting genetic algorithm II in order to identify the smallest set of local populations of Dipteryx alata (baru) (a Brazilian Cerrado species) for conservation, representing the known genetic diversity and using allele frequency information associated with heterozygosity and Hardy-Weinberg equilibrium. We worked in 3 variations for the problem. First, we reproduced a previous experiment, but using a multi-objective approach. We found that the smallest set of populations needed to represent all alleles under study was 7, corroborating the results of the previous study, but with more distinct solutions. In the 2nd and 3rd variations, we performed simultaneous optimization of 4 and 5 objectives, respectively. We found similar but refined results for 7 populations, and a larger portfolio considering intra-specific diversity and persistence with populations ranging from 8-22. This is the first study to apply multi-objective algorithms to an SCP problem using alleles at the population level as basic units for analysis.

  8. Performance evaluation of Automatic Extraction System. Volume IV. Recommended operating, maintenance, and training plans. Final technical report

    SciTech Connect

    Frantz, R.L.; King, R.H.; Bartsch, D.L.

    1980-07-01

    Since the AES is a different and more sochisticated machine, it became apparent during the in-mine trial that more than on-the-job training (OJT) is desirable for the operators. The AES is unique in that it should remain in the face for long periods rather than be moved often from the face to face. In addition, the operator should learn to trust the ACS in order to be more aware of the hazards in the face area. More training is one way to help increase operator and machine efficiency and safety consciousness. The lack of formal, organized, scheduled, non-productive-mode training of the AES operators appeared to affect the performance of the AES during mining, tramming, maneuvering, and bolting. Therefore, before the operator and bolters do their jobs and the mechanics maintain the AES on a regular basis in a production-mode, they should attend classes, including: (1) formal above ground classroom training, (2) non-productive-mode underground training, and (3) productive-mode OJT. The training department should have the authority and resources to train workers beforehand, and also whenever subsequent instruction is needed. This plan includes only those areas peculiar to the AES. It is assumed that mature, competent individuals (operators and bolters) have already been trained to use similar machines. If this is not the case, the training will require significantly more time.

  9. TH-A-9A-02: BEST IN PHYSICS (THERAPY) - 4D IMRT Planning Using Highly- Parallelizable Particle Swarm Optimization

    SciTech Connect

    Modiri, A; Gu, X; Sawant, A

    2014-06-15

    Purpose: We present a particle swarm optimization (PSO)-based 4D IMRT planning technique designed for dynamic MLC tracking delivery to lung tumors. The key idea is to utilize the temporal dimension as an additional degree of freedom rather than a constraint in order to achieve improved sparing of organs at risk (OARs). Methods: The target and normal structures were manually contoured on each of the ten phases of a 4DCT scan acquired from a lung SBRT patient who exhibited 1.5cm tumor motion despite the use of abdominal compression. Corresponding ten IMRT plans were generated using the Eclipse treatment planning system. These plans served as initial guess solutions for the PSO algorithm. Fluence weights were optimized over the entire solution space i.e., 10 phases × 12 beams × 166 control points. The size of the solution space motivated our choice of PSO, which is a highly parallelizable stochastic global optimization technique that is well-suited for such large problems. A summed fluence map was created using an in-house B-spline deformable image registration. Each plan was compared with a corresponding, internal target volume (ITV)-based IMRT plan. Results: The PSO 4D IMRT plan yielded comparable PTV coverage and significantly higher dose—sparing for parallel and serial OARs compared to the ITV-based plan. The dose-sparing achieved via PSO-4DIMRT was: lung Dmean = 28%; lung V20 = 90%; spinal cord Dmax = 23%; esophagus Dmax = 31%; heart Dmax = 51%; heart Dmean = 64%. Conclusion: Truly 4D IMRT that uses the temporal dimension as an additional degree of freedom can achieve significant dose sparing of serial and parallel OARs. Given the large solution space, PSO represents an attractive, parallelizable tool to achieve globally optimal solutions for such problems. This work was supported through funding from the National Institutes of Health and Varian Medical Systems. Amit Sawant has research funding from Varian Medical Systems, VisionRT Ltd. and Elekta.

  10. Coupling pre-season famers planning and optimal water supply management to mitigate climate change impacts

    NASA Astrophysics Data System (ADS)

    Castelletti, A.; Giuliani, M.; Mainardi, M.; Chiaradia, E.; Gandolfi, C.

    2012-12-01

    Agriculture is the main land use in the world and also the sector characterized by the highest water demand. To meet projected growth in human population and per-capita food demand, agricultural production will have to significantly increase in the next decades. Farmers' practices are significantly sensitive to climate variations. To effectively face a changing climate, adaptation strategies are essential and many potential options are available for marginal changes of existing agricultural systems: changing crop type and rotation, shifting sowing and harvesting dates, adopting high efficiency irrigation techniques. Yet, farmer adaptation is only one part of the equation. Adaptation also concerns the supply system, in particular the reallocation of water availability in space and time, Changes in water supply management strategies might impact on farmer decisions altering water availability. Most of the studies in the literature consider the two systems separately either analysing the impact of climate change of farmers decisions and demand formation for a given water supply scenario or optimizing water supply for several water demand scenarios. In this study we close the loop between supply and demand by explicitly studying the coevolution of farmers and water supply systems under climate changes. Given an expected water availability, the farmers solve a yearly planning problem to decide the most profitable crop to plant. Knowing the farmers decisions, the operation of the water supply system is optimized on the actual water demand of the crops. Then, the farmers can re-adapt their decisions according with the new optimal operating strategy, thus activating an information loop between the two systems that exchange expected supply and irrigation demand. Projected hydro-climatic scenarios are used as boundary conditions to the loop. The proposed approach is demonstrated on a real-world case study, namely the Lake Como that serves the Muzza-Bassa Lodigiana irrigation

  11. Optimized spatial priorities for biodiversity conservation in China: a systematic conservation planning perspective.

    PubMed

    Wu, Ruidong; Long, Yongcheng; Malanson, George P; Garber, Paul A; Zhang, Shuang; Li, Diqiang; Zhao, Peng; Wang, Longzhu; Duo, Hairui

    2014-01-01

    By addressing several key features overlooked in previous studies, i.e. human disturbance, integration of ecosystem- and species-level conservation features, and principles of complementarity and representativeness, we present the first national-scale systematic conservation planning for China to determine the optimized spatial priorities for biodiversity conservation. We compiled a spatial database on the distributions of ecosystem- and species-level conservation features, and modeled a human disturbance index (HDI) by aggregating information using several socioeconomic proxies. We ran Marxan with two scenarios (HDI-ignored and HDI-considered) to investigate the effects of human disturbance, and explored the geographic patterns of the optimized spatial conservation priorities. Compared to when HDI was ignored, the HDI-considered scenario resulted in (1) a marked reduction (∼9%) in the total HDI score and a slight increase (∼7%) in the total area of the portfolio of priority units, (2) a significant increase (∼43%) in the total irreplaceable area and (3) more irreplaceable units being identified in almost all environmental zones and highly-disturbed provinces. Thus the inclusion of human disturbance is essential for cost-effective priority-setting. Attention should be targeted to the areas that are characterized as moderately-disturbed, <2,000 m in altitude, and/or intermediately- to extremely-rugged in terrain to identify potentially important regions for implementing cost-effective conservation. We delineated 23 primary large-scale priority areas that are significant for conserving China's biodiversity, but those isolated priority units in disturbed regions are in more urgent need of conservation actions so as to prevent immediate and severe biodiversity loss. This study presents a spatially optimized national-scale portfolio of conservation priorities--effectively representing the overall biodiversity of China while minimizing conflicts with economic

  12. Role of the parameters involved in the plan optimization based on the generalized equivalent uniform dose and radiobiological implications

    NASA Astrophysics Data System (ADS)

    Widesott, L.; Strigari, L.; Pressello, M. C.; Benassi, M.; Landoni, V.

    2008-03-01

    We investigated the role and the weight of the parameters involved in the intensity modulated radiation therapy (IMRT) optimization based on the generalized equivalent uniform dose (gEUD) method, for prostate and head-and-neck plans. We systematically varied the parameters (gEUDmax and weight) involved in the gEUD-based optimization of rectal wall and parotid glands. We found that the proper value of weight factor, still guaranteeing planning treatment volumes coverage, produced similar organs at risks dose-volume (DV) histograms for different gEUDmax with fixed a = 1. Most of all, we formulated a simple relation that links the reference gEUDmax and the associated weight factor. As secondary objective, we evaluated plans obtained with the gEUD-based optimization and ones based on DV criteria, using the normal tissue complication probability (NTCP) models. gEUD criteria seemed to improve sparing of rectum and parotid glands with respect to DV-based optimization: the mean dose, the V40 and V50 values to the rectal wall were decreased of about 10%, the mean dose to parotids decreased of about 20-30%. But more than the OARs sparing, we underlined the halving of the OARs optimization time with the implementation of the gEUD-based cost function. Using NTCP models we enhanced differences between the two optimization criteria for parotid glands, but no for rectum wall.

  13. Poster — Thur Eve — 61: A new framework for MPERT plan optimization using MC-DAO

    SciTech Connect

    Baker, M; Lloyd, S AM; Townson, R; Bush, K; Gagne, I M; Zavgorodni, S

    2014-08-15

    This work combines the inverse planning technique known as Direct Aperture Optimization (DAO) with Intensity Modulated Radiation Therapy (IMRT) and combined electron and photon therapy plans. In particular, determining conditions under which Modulated Photon/Electron Radiation Therapy (MPERT) produces better dose conformality and sparing of organs at risk than traditional IMRT plans is central to the project. Presented here are the materials and methods used to generate and manipulate the DAO procedure. Included is the introduction of a powerful Java-based toolkit, the Aperture-based Monte Carlo (MC) MPERT Optimizer (AMMO), that serves as a framework for optimization and provides streamlined access to underlying particle transport packages. Comparison of the toolkit's dose calculations to those produced by the Eclipse TPS and the demonstration of a preliminary optimization are presented as first benchmarks. Excellent agreement is illustrated between the Eclipse TPS and AMMO for a 6MV photon field. The results of a simple optimization shows the functioning of the optimization framework, while significant research remains to characterize appropriate constraints.

  14. Strategic Planning of Vessel Traffic Services using ABS Analysis and Optimization

    NASA Astrophysics Data System (ADS)

    Babu, A. J. G.; Ketkar, W.

    Vessel Traffic Services (VTS) advise vessels navigating the waterways, VTS communications provide to the mariner timely, pertinent, and accurate information that would assist in safe manoeuvring of the vessel.Following several oil spills in 1989, Congress passed The Oil Pollution Act of 1990 (Public Law 101Secretary to conduct a studycost approach, VTS benefits are defined as the avoided vessel casualties and the associated consequences. The avoided consequences are measured in physical units and are assigned monetary values, VTS costs are defined as the initial federal investment for a state-of-the-art VTS system in each study zone and its annual operating and maintenance costs. Both the benefits and costs are expressed in the 1993 Net Present Value of annual stream over the life cycle at 10 percent basic annual rate. The study recommends VTS design by rank-ordering the zones by net benefit.In this paper, we use alternative methodologies for offering better assistance in making VTS design decision-making. First, we perform ABC analysis on the zones; that is, we classify them into three groups: The A group deserves a state-of-the-art, full-fledged VTS presence, the B group could use an intermediate level of VTS services, and the c group deserves an elementary level of VTS services, as and if the budget permits. This analysis assumes that VTS services can be offered at various levels with correspondingly changing costs. Secondly, we perform resource allocation analysis; that is, for a given budget and given criterion (e.g. maximize the total benefit), select the optimal zones in which the VTS services should be offered. This analysis, done for various levels of budget, would form a useful decision aid for the VTS design.

  15. Preventive Maintenance Process

    NASA Technical Reports Server (NTRS)

    Ciaruffoli, Veronica; Bramley, Craig; Matteson, Mike

    2001-01-01

    The Preventive Maintenance (PM) program at Stennis Space Center (SSC) evolved from an ineffective and poorly organized state to a highly organized state in which it became capable of tracking equipment, planning jobs with man hour estimates, and supporting outsourcing. This viewgraph presentation traces the steps the program took to improve itself.

  16. Spatially-Optimized Sequential Sampling Plan for Cabbage Aphids Brevicoryne brassicae L. (Hemiptera: Aphididae) in Canola Fields.

    PubMed

    Severtson, Dustin; Flower, Ken; Nansen, Christian

    2016-08-01

    The cabbage aphid is a significant pest worldwide in brassica crops, including canola. This pest has shown considerable ability to develop resistance to insecticides, so these should only be applied on a "when and where needed" basis. Thus, optimized sampling plans to accurately assess cabbage aphid densities are critically important to determine the potential need for pesticide applications. In this study, we developed a spatially optimized binomial sequential sampling plan for cabbage aphids in canola fields. Based on five sampled canola fields, sampling plans were developed using 0.1, 0.2, and 0.3 proportions of plants infested as action thresholds. Average sample numbers required to make a decision ranged from 10 to 25 plants. Decreasing acceptable error from 10 to 5% was not considered practically feasible, as it substantially increased the number of samples required to reach a decision. We determined the relationship between the proportions of canola plants infested and cabbage aphid densities per plant, and proposed a spatially optimized sequential sampling plan for cabbage aphids in canola fields, in which spatial features (i.e., edge effects) and optimization of sampling effort (i.e., sequential sampling) are combined. Two forms of stratification were performed to reduce spatial variability caused by edge effects and large field sizes. Spatially optimized sampling, starting at the edge of fields, reduced spatial variability and therefore increased the accuracy of infested plant density estimates. The proposed spatially optimized sampling plan may be used to spatially target insecticide applications, resulting in cost savings, insecticide resistance mitigation, conservation of natural enemies, and reduced environmental impact.

  17. Spatially-Optimized Sequential Sampling Plan for Cabbage Aphids Brevicoryne brassicae L. (Hemiptera: Aphididae) in Canola Fields.

    PubMed

    Severtson, Dustin; Flower, Ken; Nansen, Christian

    2016-08-01

    The cabbage aphid is a significant pest worldwide in brassica crops, including canola. This pest has shown considerable ability to develop resistance to insecticides, so these should only be applied on a "when and where needed" basis. Thus, optimized sampling plans to accurately assess cabbage aphid densities are critically important to determine the potential need for pesticide applications. In this study, we developed a spatially optimized binomial sequential sampling plan for cabbage aphids in canola fields. Based on five sampled canola fields, sampling plans were developed using 0.1, 0.2, and 0.3 proportions of plants infested as action thresholds. Average sample numbers required to make a decision ranged from 10 to 25 plants. Decreasing acceptable error from 10 to 5% was not considered practically feasible, as it substantially increased the number of samples required to reach a decision. We determined the relationship between the proportions of canola plants infested and cabbage aphid densities per plant, and proposed a spatially optimized sequential sampling plan for cabbage aphids in canola fields, in which spatial features (i.e., edge effects) and optimization of sampling effort (i.e., sequential sampling) are combined. Two forms of stratification were performed to reduce spatial variability caused by edge effects and large field sizes. Spatially optimized sampling, starting at the edge of fields, reduced spatial variability and therefore increased the accuracy of infested plant density estimates. The proposed spatially optimized sampling plan may be used to spatially target insecticide applications, resulting in cost savings, insecticide resistance mitigation, conservation of natural enemies, and reduced environmental impact. PMID:27371709

  18. SU-E-T-555: A Protontherapy Inverse Treatment Planning System Prototype with Linear Energy Transfer (LET) Optimization

    SciTech Connect

    Sanchez-Parcerisa, D; Carabe-Fernandez, A

    2014-06-01

    Purpose: Develop and benchmark an inverse treatment planning system (TPS) for proton radiotherapy integrating fast analytical dose and LET calculations in patient geometries and a dual objective function with both dose and LET components, enabling us to apply optimization techniques to improve the predicted outcome of treatments based on radiobiological models. Methods: The software package was developed in MATLAB and implements a fluence-dose calculation technique based on a pencil beam model for dose calculations and a 3D LET model based on the extension of the LET in the radial direction as a function of the predicted radiological pathway. Both models were benchmarked against commissioning data from our institution, dose calculations performed with a commercial treatment planning system and Monte Carlo simulations. The optimization is based on the adaptive simulated annealing approach . Results: The dose and LET calculations were tested in a water phantom and several real patient treatments. The pass rate for the gamma index analysis (3%/3mm) test was above 90% for all test cases analyzed, and the calculation time was of the order of seconds. The inverse planning module produced plans with a significantly higher mean LET in the target compared to traditional plans, without any loss of target coverage. The clinical relevance of this improvement is under consideration . Conclusion: The developed treatment planning system is a valuable clinical and research tool that enables us to incorporate LET effects into proton radiotherapy planning in a streamlined fashion.

  19. Y-12 Groundwater Protection Program Monitoring Optimization Plan for Groundwater Monitoring Wells at the U.S. Department of Energy Y-12 National Security Complex, Oak Ridge, Tennessee

    SciTech Connect

    2003-09-30

    This document is the monitoring optimization plan for groundwater monitoring wells associated with the U.S. Department of Energy (DOE) Y-12 National Security Complex (Y-12) in Oak Ridge, Tennessee (Figure 1). The plan describes the technical approach that will be implemented under the Y-12 Groundwater Protection Program (GWPP) to focus available resources on the monitoring wells at Y-12 which provide the most useful hydrologic and water-quality monitoring data. The technical approach is based on the GWPP status designation for each well (Section 2.0). Under this approach, wells granted ''active'' status are used by the GWPP for hydrologic monitoring and/or groundwater sampling (Section 3.0), whereas well granted ''inactive'' status are not used for either purpose. The status designation also determines the frequency at which the GWPP will inspect applicable wells, the scope of these well inspections, and extent of any maintenance actions initiated by the GWPP (Section 4.0). Details regarding the ancillary activities associated with implementation of this plan (e.g., well inspection) are deferred to the referenced GWPP plans and procedures (Section 5.0). This plan applies to groundwater monitoring wells associated with Y-12 and related waste management facilities located within three hydrogeologic regimes (Figure 1): the Bear Creek Hydrogeologic Regime (Bear Creek Regime), the Upper East Fork Poplar Creek Hydrogeologic Regime (East Fork Regime), and the Chestnut Ridge Hydrogeologic Regime (Chestnut Ridge Regime). The Bear Creek Regime encompasses a section of Bear Creek Valley (BCV) immediately west of Y-12. The East Fork Regime encompasses most of the Y-12 process, operations, and support facilities in BCV and, for the purposes of this plan, includes a section of Union Valley east of the DOE Oak Ridge Reservation (ORR) boundary along Scarboro Road. The Chestnut Ridge Regime is directly south of Y-12 and encompasses a section of Chestnut Ridge that is bound to the

  20. SU-E-T-539: Fixed Versus Variable Optimization Points in Combined-Mode Modulated Arc Therapy Planning

    SciTech Connect

    Kainz, K; Prah, D; Ahunbay, E; Li, X

    2014-06-01

    Purpose: A novel modulated arc therapy technique, mARC, enables superposition of step-and-shoot IMRT segments upon a subset of the optimization points (OPs) of a continuous-arc delivery. We compare two approaches to mARC planning: one with the number of OPs fixed throughout optimization, and another where the planning system determines the number of OPs in the final plan, subject to an upper limit defined at the outset. Methods: Fixed-OP mARC planning was performed for representative cases using Panther v. 5.01 (Prowess, Inc.), while variable-OP mARC planning used Monaco v. 5.00 (Elekta, Inc.). All Monaco planning used an upper limit of 91 OPs; those OPs with minimal MU were removed during optimization. Plans were delivered, and delivery times recorded, on a Siemens Artiste accelerator using a flat 6MV beam with 300 MU/min rate. Dose distributions measured using ArcCheck (Sun Nuclear Corporation, Inc.) were compared with the plan calculation; the two were deemed consistent if they agreed to within 3.5% in absolute dose and 3.5 mm in distance-to-agreement among > 95% of the diodes within the direct beam. Results: Example cases included a prostate and a head-and-neck planned with a single arc and fraction doses of 1.8 and 2.0 Gy, respectively. Aside from slightly more uniform target dose for the variable-OP plans, the DVHs for the two techniques were similar. For the fixed-OP technique, the number of OPs was 38 and 39, and the delivery time was 228 and 259 seconds, respectively, for the prostate and head-and-neck cases. For the final variable-OP plans, there were 91 and 85 OPs, and the delivery time was 296 and 440 seconds, correspondingly longer than for fixed-OP. Conclusion: For mARC, both the fixed-OP and variable-OP approaches produced comparable-quality plans whose delivery was successfully verified. To keep delivery time per fraction short, a fixed-OP planning approach is preferred.

  1. Maintenance Downtime

    Atmospheric Science Data Center

    2013-07-10

    ... will be unavailable March 5, 2013 8:00 am to 5:00 pm due to database maintenance. Date(s):  Tuesday, March 5, 2013 ... will be unavailable March 5, 2013 8:00 am to 5:00 pm due to database maintenance. ...

  2. Preventative Maintenance.

    ERIC Educational Resources Information Center

    Migliorino, James

    Boards of education must be convinced that spending money up front for preventive maintenance will, in the long run, save districts' tax dollars. A good program of preventive maintenance can minimize disruption of service; reduce repair costs, energy consumption, and overtime; improve labor productivity and system equipment reliability; handle…

  3. Software Maintenance.

    ERIC Educational Resources Information Center

    Cannon, Glenn; Jobe, Holly

    Proper cleaning and storage of audiovisual aids is outlined in this brief guide. Materials and equipment needed for first line maintenance are listed, as well as maintenance procedures for records, audio and video tape, film, filmstrips, slides, realia, models, prints, graphics, maps, and overhead transparencies. A 15-item quiz on software…

  4. Poster — Thur Eve — 69: Computational Study of DVH-guided Cancer Treatment Planning Optimization Methods

    SciTech Connect

    Ghomi, Pooyan Shirvani; Zinchenko, Yuriy

    2014-08-15

    Purpose: To compare methods to incorporate the Dose Volume Histogram (DVH) curves into the treatment planning optimization. Method: The performance of three methods, namely, the conventional Mixed Integer Programming (MIP) model, a convex moment-based constrained optimization approach, and an unconstrained convex moment-based penalty approach, is compared using anonymized data of a prostate cancer patient. Three plans we generated using the corresponding optimization models. Four Organs at Risk (OARs) and one Tumor were involved in the treatment planning. The OARs and Tumor were discretized into total of 50,221 voxels. The number of beamlets was 943. We used commercially available optimization software Gurobi and Matlab to solve the models. Plan comparison was done by recording the model runtime followed by visual inspection of the resulting dose volume histograms. Conclusion: We demonstrate the effectiveness of the moment-based approaches to replicate the set of prescribed DVH curves. The unconstrained convex moment-based penalty approach is concluded to have the greatest potential to reduce the computational effort and holds a promise of substantial computational speed up.

  5. Study of Double-Weighted Graph Model and Optimal Path Planning for Tourist Scenic Area Oriented Intelligent Tour Guide

    NASA Astrophysics Data System (ADS)

    Shi, Y.; Long, Y.; Wi, X. L.

    2014-04-01

    When tourists visiting multiple tourist scenic spots, the travel line is usually the most effective road network according to the actual tour process, and maybe the travel line is different from planned travel line. For in the field of navigation, a proposed travel line is normally generated automatically by path planning algorithm, considering the scenic spots' positions and road networks. But when a scenic spot have a certain area and have multiple entrances or exits, the traditional described mechanism of single point coordinates is difficult to reflect these own structural features. In order to solve this problem, this paper focuses on the influence on the process of path planning caused by scenic spots' own structural features such as multiple entrances or exits, and then proposes a doubleweighted Graph Model, for the weight of both vertexes and edges of proposed Model can be selected dynamically. And then discusses the model building method, and the optimal path planning algorithm based on Dijkstra algorithm and Prim algorithm. Experimental results show that the optimal planned travel line derived from the proposed model and algorithm is more reasonable, and the travelling order and distance would be further optimized.

  6. Constraint satisfaction and optimization for space station short-term mission planning based on an iterative conflict-repair method

    NASA Astrophysics Data System (ADS)

    Bu, Hui-Jiao; Zhang, Jin; Luo, Ya-Zhong

    2016-10-01

    This article studies the optimization of space station short-term mission planning (STMP) problems. The domain knowledge including description and the concept definitions of the STMP problem are presented, an STMP constraint satisfaction model is developed, and then an iterative conflict-repair method with the resolving strategies is proposed to satisfy complicated constraints. A genetic algorithm (GA) is adopted to optimize the STMP problem. The proposed approach is evaluated using a test case with 15 missions, 13 devices and three astronauts. The results show that the established STMP constraint satisfaction model is effective, and the iterative conflict-repair method can make the plan satisfy all constraints considered and can effectively improve the optimization performance of the GA.

  7. The influence of the optimization starting conditions on the robustness of intensity-modulated proton therapy plans

    NASA Astrophysics Data System (ADS)

    Albertini, F.; Hug, E. B.; Lomax, A. J.

    2010-05-01

    In this paper the influence of varying the starting conditions on intensity-modulated proton therapy (IMPT) plans has been studied. In particular IMPT plans have been optimized based on four different starting conditions of initial beamlet fluences: (a) all beamlets with an initial constant weight, delivering a gradient from the proximal to the distal edge of the target (forward wedge approach); (b) beamlet weights reduced from the distal to the proximal aspect of the target such as to deliver a flat 'spread-out-Bragg-peak' (SOBP approach); (c) beamlet weights calculated to deliver a gradient from the distal (maximal dose) to the proximal edge (inverse wedge); (d) beamlet weights set universally to zero except the most distal one, for each given lateral direction (i.e. distal-edge-tracking, DET). An analysis of robustness to range errors has been performed by recalculating plans, assuming a systematic 3% error in CT values. Results showed that IMPT plans optimized with the forward wedge approach were very sensitive to range errors, since organs-at-risk (OAR) were spared by patching single-field lateral and distal fall-offs, the last ones being strongly sensitive to range errors. In addition a plan robust to range errors can be achieved by starting the optimization process in the case of low-dose constraints to OAR, with the initial flat SOBP approach, and with either the DET or the inverse wedge approaches, in the case of stringent dose-volume constraints to OAR. 'Starting condition-based optimization' as proposed here can therefore provide a tool to transparently 'steer' the optimization outcome to solutions more robust to uncertainties.

  8. Biologically optimized helium ion plans: calculation approach and its in vitro validation

    NASA Astrophysics Data System (ADS)

    Mairani, A.; Dokic, I.; Magro, G.; Tessonnier, T.; Kamp, F.; Carlson, D. J.; Ciocca, M.; Cerutti, F.; Sala, P. R.; Ferrari, A.; Böhlen, T. T.; Jäkel, O.; Parodi, K.; Debus, J.; Abdollahi, A.; Haberer, T.

    2016-06-01

    Treatment planning studies on the biological effect of raster-scanned helium ion beams should be performed, together with their experimental verification, before their clinical application at the Heidelberg Ion Beam Therapy Center (HIT). For this purpose, we introduce a novel calculation approach based on integrating data-driven biological models in our Monte Carlo treatment planning (MCTP) tool. Dealing with a mixed radiation field, the biological effect of the primary 4He ion beams, of the secondary 3He and 4He (Z  =  2) fragments and of the produced protons, deuterons and tritons (Z  =  1) has to be taken into account. A spread-out Bragg peak (SOBP) in water, representative of a clinically-relevant scenario, has been biologically optimized with the MCTP and then delivered at HIT. Predictions of cell survival and RBE for a tumor cell line, characterized by {{(α /β )}\\text{ph}}=5.4 Gy, have been successfully compared against measured clonogenic survival data. The mean absolute survival variation ({μΔ \\text{S}} ) between model predictions and experimental data was 5.3%  ±  0.9%. A sensitivity study, i.e. quantifying the variation of the estimations for the studied plan as a function of the applied phenomenological modelling approach, has been performed. The feasibility of a simpler biological modelling based on dose-averaged LET (linear energy transfer) has been tested. Moreover, comparisons with biophysical models such as the local effect model (LEM) and the repair-misrepair-fixation (RMF) model were performed. {μΔ \\text{S}} values for the LEM and the RMF model were, respectively, 4.5%  ±  0.8% and 5.8%  ±  1.1%. The satisfactorily agreement found in this work for the studied SOBP, representative of clinically-relevant scenario, suggests that the introduced approach could be applied for an accurate estimation of the biological effect for helium ion radiotherapy.

  9. A new optimization method using a compressed sensing inspired solver for real-time LDR-brachytherapy treatment planning

    NASA Astrophysics Data System (ADS)

    Guthier, C.; Aschenbrenner, K. P.; Buergy, D.; Ehmann, M.; Wenz, F.; Hesser, J. W.

    2015-03-01

    This work discusses a novel strategy for inverse planning in low dose rate brachytherapy. It applies the idea of compressed sensing to the problem of inverse treatment planning and a new solver for this formulation is developed. An inverse planning algorithm was developed incorporating brachytherapy dose calculation methods as recommended by AAPM TG-43. For optimization of the functional a new variant of a matching pursuit type solver is presented. The results are compared with current state-of-the-art inverse treatment planning algorithms by means of real prostate cancer patient data. The novel strategy outperforms the best state-of-the-art methods in speed, while achieving comparable quality. It is able to find solutions with comparable values for the objective function and it achieves these results within a few microseconds, being up to 542 times faster than competing state-of-the-art strategies, allowing real-time treatment planning. The sparse solution of inverse brachytherapy planning achieved with methods from compressed sensing is a new paradigm for optimization in medical physics. Through the sparsity of required needles and seeds identified by this method, the cost of intervention may be reduced.

  10. Comparative evaluation of two dose optimization methods for image-guided, highly-conformal, tandem and ovoids cervix brachytherapy planning.

    PubMed

    Ren, Jiyun; Menon, Geetha; Sloboda, Ron

    2013-04-01

    Although the Manchester system is still extensively used to prescribe dose in brachytherapy (BT) for locally advanced cervix cancer, many radiation oncology centers are transitioning to 3D image-guided BT, owing to the excellent anatomy definition offered by modern imaging modalities. As automatic dose optimization is highly desirable for 3D image-based BT, this study comparatively evaluates the performance of two optimization methods used in BT treatment planning--Nelder-Mead simplex (NMS) and simulated annealing (SA)--for a cervix BT computer simulation model incorporating a Manchester-style applicator. Eight model cases were constructed based on anatomical structure data (for high risk-clinical target volume (HR-CTV), bladder, rectum and sigmoid) obtained from measurements on fused MR-CT images for BT patients. D90 and V100 for HR-CTV, D2cc for organs at risk (OARs), dose to point A, conformation index and the sum of dwell times within the tandem and ovoids were calculated for optimized treatment plans designed to treat the HR-CTV in a highly conformal manner. Compared to the NMS algorithm, SA was found to be superior as it could perform optimization starting from a range of initial dwell times, while the performance of NMS was strongly dependent on their initial choice. SA-optimized plans also exhibited lower D2cc to OARs, especially the bladder and sigmoid, and reduced tandem dwell times. For cases with smaller HR-CTV having good separation from adjoining OARs, multiple SA-optimized solutions were found which differed markedly from each other and were associated with different choices for initial dwell times. Finally and importantly, the SA method yielded plans with lower dwell time variability compared with the NMS method.

  11. Path planning and parameter optimization of uniform removal in active feed polishing

    NASA Astrophysics Data System (ADS)

    Liu, Jian; Wang, Shaozhi; Zhang, Chunlei; Zhang, Linghua; Chen, Huanan

    2015-06-01

    A high-quality ultrasmooth surface is demanded in short-wave optical systems. However, the existing polishing methods have difficulties meeting the requirement on spherical or aspheric surfaces. As a new kind of small tool polishing method, active feed polishing (AFP) could attain a surface roughness of less than 0.3 nm (RMS) on spherical elements, although AFP may magnify the residual figure error or mid-frequency error. The purpose of this work is to propose an effective algorithm to realize uniform removal of the surface in the processing. At first, the principle of the AFP and the mechanism of the polishing machine are introduced. In order to maintain the processed figure error, a variable pitch spiral path planning algorithm and the dwell time-solving model are proposed. For suppressing the possible mid-frequency error, the uniformity of the synthesis tool path, which is generated by an arbitrary point at the polishing tool bottom, is analyzed and evaluated, and the angular velocity ratio of the tool spinning motion to the revolution motion is optimized. Finally, an experiment is conducted on a convex spherical surface and an ultrasmooth surface is finally acquired. In conclusion, a high-quality ultrasmooth surface can be successfully obtained with little degradation of the figure and mid-frequency errors by the algorithm.

  12. A Fuzzy Robust Optimization Model for Waste Allocation Planning Under Uncertainty.

    PubMed

    Xu, Ye; Huang, Guohe; Xu, Ling

    2014-10-01

    In this study, a fuzzy robust optimization (FRO) model was developed for supporting municipal solid waste management under uncertainty. The Development Zone of the City of Dalian, China, was used as a study case for demonstration. Comparing with traditional fuzzy models, the FRO model made improvement by considering the minimization of the weighted summation among the expected objective values, the differences between two extreme possible objective values, and the penalty of the constraints violation as the objective function, instead of relying purely on the minimization of expected value. Such an improvement leads to enhanced system reliability and the model becomes especially useful when multiple types of uncertainties and complexities are involved in the management system. Through a case study, the applicability of the FRO model was successfully demonstrated. Solutions under three future planning scenarios were provided by the FRO model, including (1) priority on economic development, (2) priority on environmental protection, and (3) balanced consideration for both. The balanced scenario solution was recommended for decision makers, since it respected both system economy and reliability. The model proved valuable in providing a comprehensive profile about the studied system and helping decision makers gain an in-depth insight into system complexity and select cost-effective management strategies. PMID:25317037

  13. Multi-objective optimization to support rapid air operations mission planning

    NASA Astrophysics Data System (ADS)

    Gonsalves, Paul G.; Burge, Janet E.

    2005-05-01

    Within the context of military air operations, Time-sensitive targets (TSTs) are targets where modifiers such, "emerging, perishable, high-payoff, short dwell, or highly mobile" can be used. Time-critical targets (TCTs) further the criticality of TSTs with respect to achievement of mission objectives and a limited window of opportunity for attack. The importance of TST/TCTs within military air operations has been met with a significant investment in advanced technologies and platforms to meet these challenges. Developments in ISR systems, manned and unmanned air platforms, precision guided munitions, and network-centric warfare have made significant strides for ensuring timely prosecution of TSTs/TCTs. However, additional investments are needed to further decrease the targeting decision cycle. Given the operational needs for decision support systems to enable time-sensitive/time-critical targeting, we present a tool for the rapid generation and analysis of mission plan solutions to address TSTs/TCTs. Our system employs a genetic algorithm-based multi-objective optimization scheme that is well suited to the rapid generation of approximate solutions in a dynamic environment. Genetic Algorithms (GAs) allow for the effective exploration of the search space for potentially novel solutions, while addressing the multiple conflicting objectives that characterize the prosecution of TSTs/TCTs (e.g. probability of target destruction, time to accomplish task, level of disruption to other mission priorities, level of risk to friendly assets, etc.).

  14. A Fuzzy Robust Optimization Model for Waste Allocation Planning Under Uncertainty

    PubMed Central

    Xu, Ye; Huang, Guohe; Xu, Ling

    2014-01-01

    Abstract In this study, a fuzzy robust optimization (FRO) model was developed for supporting municipal solid waste management under uncertainty. The Development Zone of the City of Dalian, China, was used as a study case for demonstration. Comparing with traditional fuzzy models, the FRO model made improvement by considering the minimization of the weighted summation among the expected objective values, the differences between two extreme possible objective values, and the penalty of the constraints violation as the objective function, instead of relying purely on the minimization of expected value. Such an improvement leads to enhanced system reliability and the model becomes especially useful when multiple types of uncertainties and complexities are involved in the management system. Through a case study, the applicability of the FRO model was successfully demonstrated. Solutions under three future planning scenarios were provided by the FRO model, including (1) priority on economic development, (2) priority on environmental protection, and (3) balanced consideration for both. The balanced scenario solution was recommended for decision makers, since it respected both system economy and reliability. The model proved valuable in providing a comprehensive profile about the studied system and helping decision makers gain an in-depth insight into system complexity and select cost-effective management strategies. PMID:25317037

  15. 30 CFR 74.10 - Operating and maintenance instructions.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... storage instructions and a maintenance and service life plan with each new CPDM device sold. These... functioning of the CPDM. (2) The maintenance and service life plan must address: (i) Conditions that...

  16. Automated medial axis seeding and guided evolutionary simulated annealing for optimization of gamma knife radiosurgery treatment plans

    NASA Astrophysics Data System (ADS)

    Zhang, Pengpeng

    The Leksell Gamma KnifeRTM (LGK) is a tool for providing accurate stereotactic radiosurgical treatment of brain lesions, especially tumors. Currently, the treatment planning team "forward" plans radiation treatment parameters while viewing a series of 2D MR scans. This primarily manual process is cumbersome and time consuming because the difficulty in visualizing the large search space for the radiation parameters (i.e., shot overlap, number, location, size, and weight). I hypothesize that a computer-aided "inverse" planning procedure that utilizes tumor geometry and treatment goals could significantly improve the planning process and therapeutic outcome of LGK radiosurgery. My basic observation is that the treatment team is best at identification of the location of the lesion and prescribing a lethal, yet safe, radiation dose. The treatment planning computer is best at determining both the 3D tumor geometry and optimal LGK shot parameters necessary to deliver a desirable dose pattern to the tumor while sparing adjacent normal tissue. My treatment planning procedure asks the neurosurgeon to identify the tumor and critical structures in MR images and the oncologist to prescribe a tumoricidal radiation dose. Computer-assistance begins with geometric modeling of the 3D tumor's medial axis properties. This begins with a new algorithm, a Gradient-Phase Plot (G-P Plot) decomposition of the tumor object's medial axis. I have found that medial axis seeding, while insufficient in most cases to produce an acceptable treatment plan, greatly reduces the solution space for Guided Evolutionary Simulated Annealing (GESA) treatment plan optimization by specifying an initial estimate for shot number, size, and location, but not weight. They are used to generate multiple initial plans which become initial seed plans for GESA. The shot location and weight parameters evolve and compete in the GESA procedure. The GESA objective function optimizes tumor irradiation (i.e., as close to

  17. 25 CFR 171.565 - How will I know if BIA plans to adjust my annual operation and maintenance assessment rate?

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ..., DEPARTMENT OF THE INTERIOR LAND AND WATER IRRIGATION OPERATION AND MAINTENANCE Financial Matters: Assessments... Register. (b) You may contact the irrigation facility servicing your farm unit....

  18. 25 CFR 171.565 - How will I know if BIA plans to adjust my annual operation and maintenance assessment rate?

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ..., DEPARTMENT OF THE INTERIOR LAND AND WATER IRRIGATION OPERATION AND MAINTENANCE Financial Matters: Assessments... Register. (b) You may contact the irrigation facility servicing your farm unit....

  19. 25 CFR 171.565 - How will I know if BIA plans to adjust my annual operation and maintenance assessment rate?

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ..., DEPARTMENT OF THE INTERIOR LAND AND WATER IRRIGATION OPERATION AND MAINTENANCE Financial Matters: Assessments... Register. (b) You may contact the irrigation facility servicing your farm unit....

  20. 25 CFR 171.565 - How will I know if BIA plans to adjust my annual operation and maintenance assessment rate?

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ..., DEPARTMENT OF THE INTERIOR LAND AND WATER IRRIGATION OPERATION AND MAINTENANCE Financial Matters: Assessments... Register. (b) You may contact the irrigation facility servicing your farm unit....

  1. SU-E-T-395: Multi-GPU-Based VMAT Treatment Plan Optimization Using a Column-Generation Approach

    SciTech Connect

    Tian, Z; Shi, F; Jia, X; Jiang, S; Peng, F

    2014-06-01

    Purpose: GPU has been employed to speed up VMAT optimizations from hours to minutes. However, its limited memory capacity makes it difficult to handle cases with a huge dose-deposition-coefficient (DDC) matrix, e.g. those with a large target size, multiple arcs, small beam angle intervals and/or small beamlet size. We propose multi-GPU-based VMAT optimization to solve this memory issue to make GPU-based VMAT more practical for clinical use. Methods: Our column-generation-based method generates apertures sequentially by iteratively searching for an optimal feasible aperture (referred as pricing problem, PP) and optimizing aperture intensities (referred as master problem, MP). The PP requires access to the large DDC matrix, which is implemented on a multi-GPU system. Each GPU stores a DDC sub-matrix corresponding to one fraction of beam angles and is only responsible for calculation related to those angles. Broadcast and parallel reduction schemes are adopted for inter-GPU data transfer. MP is a relatively small-scale problem and is implemented on one GPU. One headand- neck cancer case was used for test. Three different strategies for VMAT optimization on single GPU were also implemented for comparison: (S1) truncating DDC matrix to ignore its small value entries for optimization; (S2) transferring DDC matrix part by part to GPU during optimizations whenever needed; (S3) moving DDC matrix related calculation onto CPU. Results: Our multi-GPU-based implementation reaches a good plan within 1 minute. Although S1 was 10 seconds faster than our method, the obtained plan quality is worse. Both S2 and S3 handle the full DDC matrix and hence yield the same plan as in our method. However, the computation time is longer, namely 4 minutes and 30 minutes, respectively. Conclusion: Our multi-GPU-based VMAT optimization can effectively solve the limited memory issue with good plan quality and high efficiency, making GPUbased ultra-fast VMAT planning practical for real clinical use.

  2. FusionArc optimization: A hybrid volumetric modulated arc therapy (VMAT) and intensity modulated radiation therapy (IMRT) planning strategy

    SciTech Connect

    Matuszak, Martha M.; McShan, Daniel L.; Ten Haken, Randall K.; Steers, Jennifer M.; Long, Troy; Edwin Romeijn, H.; Fraass, Benedick A.

    2013-07-15

    Purpose: To introduce a hybrid volumetric modulated arc therapy/intensity modulated radiation therapy (VMAT/IMRT) optimization strategy called FusionArc that combines the delivery efficiency of single-arc VMAT with the potentially desirable intensity modulation possible with IMRT.Methods: A beamlet-based inverse planning system was enhanced to combine the advantages of VMAT and IMRT into one comprehensive technique. In the hybrid strategy, baseline single-arc VMAT plans are optimized and then the current cost function gradients with respect to the beamlets are used to define a metric for predicting which beam angles would benefit from further intensity modulation. Beams with the highest metric values (called the gradient factor) are converted from VMAT apertures to IMRT fluence, and the optimization proceeds with the mixed variable set until convergence or until additional beams are selected for conversion. One phantom and two clinical cases were used to validate the gradient factor and characterize the FusionArc strategy. Comparisons were made between standard IMRT, single-arc VMAT, and FusionArc plans with one to five IMRT/hybrid beams.Results: The gradient factor was found to be highly predictive of the VMAT angles that would benefit plan quality the most from beam modulation. Over the three cases studied, a FusionArc plan with three converted beams achieved superior dosimetric quality with reductions in final cost ranging from 26.4% to 48.1% compared to single-arc VMAT. Additionally, the three beam FusionArc plans required 22.4%-43.7% fewer MU/Gy than a seven beam IMRT plan. While the FusionArc plans with five converted beams offer larger reductions in final cost-32.9%-55.2% compared to single-arc VMAT-the decrease in MU/Gy compared to IMRT was noticeably smaller at 12.2%-18.5%, when compared to IMRT.Conclusions: A hybrid VMAT/IMRT strategy was implemented to find a high quality compromise between gantry-angle and intensity-based degrees of freedom. This

  3. FusionArc optimization: A hybrid volumetric modulated arc therapy (VMAT) and intensity modulated radiation therapy (IMRT) planning strategy

    PubMed Central

    Matuszak, Martha M.; Steers, Jennifer M.; Long, Troy; McShan, Daniel L.; Fraass, Benedick A.; Edwin Romeijn, H.; Ten Haken, Randall K.

    2013-01-01

    Purpose: To introduce a hybrid volumetric modulated arc therapy/intensity modulated radiation therapy (VMAT/IMRT) optimization strategy called FusionArc that combines the delivery efficiency of single-arc VMAT with the potentially desirable intensity modulation possible with IMRT. Methods: A beamlet-based inverse planning system was enhanced to combine the advantages of VMAT and IMRT into one comprehensive technique. In the hybrid strategy, baseline single-arc VMAT plans are optimized and then the current cost function gradients with respect to the beamlets are used to define a metric for predicting which beam angles would benefit from further intensity modulation. Beams with the highest metric values (called the gradient factor) are converted from VMAT apertures to IMRT fluence, and the optimization proceeds with the mixed variable set until convergence or until additional beams are selected for conversion. One phantom and two clinical cases were used to validate the gradient factor and characterize the FusionArc strategy. Comparisons were made between standard IMRT, single-arc VMAT, and FusionArc plans with one to five IMRT/hybrid beams. Results: The gradient factor was found to be highly predictive of the VMAT angles that would benefit plan quality the most from beam modulation. Over the three cases studied, a FusionArc plan with three converted beams achieved superior dosimetric quality with reductions in final cost ranging from 26.4% to 48.1% compared to single-arc VMAT. Additionally, the three beam FusionArc plans required 22.4%–43.7% fewer MU/Gy than a seven beam IMRT plan. While the FusionArc plans with five converted beams offer larger reductions in final cost—32.9%–55.2% compared to single-arc VMAT—the decrease in MU/Gy compared to IMRT was noticeably smaller at 12.2%–18.5%, when compared to IMRT. Conclusions: A hybrid VMAT/IMRT strategy was implemented to find a high quality compromise between gantry-angle and intensity-based degrees of freedom

  4. SU-E-T-182: Feasibility of Dose Painting by Numbers in Proton Therapy with Contour-Driven Plan Optimization

    SciTech Connect

    Montero, A Barragan; Differding, S; Lee, J; Sterpin, E

    2014-06-01

    Purpose: The work aims to 1) prove the feasibility of dose painting by numbers (DPBN) in proton therapy with usual contour-driven plan optimization and 2) compare the achieved plan quality to that of rotational IMRT. Methods: For two patients with head and neck cancers, voxel-by-voxel prescription to the target volume (PTV-PET) was calculated from {sup 18} FDG-PET images and converted to contour-based prescription by defining several sub-contours. Treatments were planned with RayStation (RaySearch Laboratories, Sweden) and proton pencil beam scanning modality. In order to determine the optimal plan parameters to approach the DPBN prescription, the effect of the number of fields, number of sub-contours and use of range shifter were tested separately on each patient. The number of sub-contours were increased from 3 to 11 while the number of fields were set to 3, 5, 7 and 9. Treatment plans were also optimized on two rotational IMRT systems (TomoTherapy and Varian RapidArc) using previously published guidelines. Results: For both patients, more than 99% of the PTV-PET received at least 95% of the prescribed dose while less than 1% of the PTV-PET received more than 105%, which demonstrates the feasibility of the treatment. Neither the use of a range shifter nor the increase of the number of fields had a significant influence on PTV coverage. Plan quality increased when increasing number of fields up to 7 or 9 and slightly decreased for a bigger number of sub-contours. Good OAR sparing is achieved while keeping high plan quality. Finally, proton therapy achieved significantly better plan quality than rotational IMRT. Conclusion: Voxel-by-voxel prescriptions can be approximated accurately in proton therapy using a contour-driven optimization. Target coverage is nearly insensitive to the number of fields and the use of a range shifter. Finally, plan quality assessment confirmed the superiority of proton therapy compared to rotational IMRT.

  5. Optimization in the utility maximization framework for conservation planning: a comparison of solution procedures in a study of multifunctional agriculture.

    PubMed

    Kreitler, Jason; Stoms, David M; Davis, Frank W

    2014-01-01

    Quantitative methods of spatial conservation prioritization have traditionally been applied to issues in conservation biology and reserve design, though their use in other types of natural resource management is growing. The utility maximization problem is one form of a covering problem where multiple criteria can represent the expected social benefits of conservation action. This approach allows flexibility with a problem formulation that is more general than typical reserve design problems, though the solution methods are very similar. However, few studies have addressed optimization in utility maximization problems for conservation planning, and the effect of solution procedure is largely unquantified. Therefore, this study mapped five criteria describing elements of multifunctional agriculture to determine a hypothetical conservation resource allocation plan for agricultural land conservation in the Central Valley of CA, USA. We compared solution procedures within the utility maximization framework to determine the difference between an open source integer programming approach and a greedy heuristic, and find gains from optimization of up to 12%. We also model land availability for conservation action as a stochastic process and determine the decline in total utility compared to the globally optimal set using both solution algorithms. Our results are comparable to other studies illustrating the benefits of optimization for different conservation planning problems, and highlight the importance of maximizing the effectiveness of limited funding for conservation and natural resource management.

  6. Optimization in the utility maximization framework for conservation planning: a comparison of solution procedures in a study of multifunctional agriculture

    PubMed Central

    Stoms, David M.; Davis, Frank W.

    2014-01-01

    Quantitative methods of spatial conservation prioritization have traditionally been applied to issues in conservation biology and reserve design, though their use in other types of natural resource management is growing. The utility maximization problem is one form of a covering problem where multiple criteria can represent the expected social benefits of conservation action. This approach allows flexibility with a problem formulation that is more general than typical reserve design problems, though the solution methods are very similar. However, few studies have addressed optimization in utility maximization problems for conservation planning, and the effect of solution procedure is largely unquantified. Therefore, this study mapped five criteria describing elements of multifunctional agriculture to determine a hypothetical conservation resource allocation plan for agricultural land conservation in the Central Valley of CA, USA. We compared solution procedures within the utility maximization framework to determine the difference between an open source integer programming approach and a greedy heuristic, and find gains from optimization of up to 12%. We also model land availability for conservation action as a stochastic process and determine the decline in total utility compared to the globally optimal set using both solution algorithms. Our results are comparable to other studies illustrating the benefits of optimization for different conservation planning problems, and highlight the importance of maximizing the effectiveness of limited funding for conservation and natural resource management. PMID:25538868

  7. Optimization in the utility maximization framework for conservation planning: a comparison of solution procedures in a study of multifunctional agriculture

    USGS Publications Warehouse

    Kreitler, Jason R.; Stoms, David M.; Davis, Frank W.

    2014-01-01

    Quantitative methods of spatial conservation prioritization have traditionally been applied to issues in conservation biology and reserve design, though their use in other types of natural resource management is growing. The utility maximization problem is one form of a covering problem where multiple criteria can represent the expected social benefits of conservation action. This approach allows flexibility with a problem formulation that is more general than typical reserve design problems, though the solution methods are very similar. However, few studies have addressed optimization in utility maximization problems for conservation planning, and the effect of solution procedure is largely unquantified. Therefore, this study mapped five criteria describing elements of multifunctional agriculture to determine a hypothetical conservation resource allocation plan for agricultural land conservation in the Central Valley of CA, USA. We compared solution procedures within the utility maximization framework to determine the difference between an open source integer programming approach and a greedy heuristic, and find gains from optimization of up to 12%. We also model land availability for conservation action as a stochastic process and determine the decline in total utility compared to the globally optimal set using both solution algorithms. Our results are comparable to other studies illustrating the benefits of optimization for different conservation planning problems, and highlight the importance of maximizing the effectiveness of limited funding for conservation and natural resource management.

  8. On-line re-optimization of prostate IMRT plan for adaptive radiation therapy: A feasibility study and implementation

    NASA Astrophysics Data System (ADS)

    Thongphiew, Danthai

    Prostate cancer is a disease that affected approximately 200,000 men in United States in 2006. Radiation therapy is a non invasive treatment option for this disease and is highly effective. The goal of radiation therapy is to deliver the prescription dose to the tumor (prostate) while sparing the surrounding healthy organs (e.g. bladder, rectum, and femoral heads). One limitation of the radiation therapy is organ position and shape variation from day to day. These variations could be as large as half inch. The conventional solution to this problem is to include some margins surrounding the target when plan the treatment. The development of image guided radiation therapy technique allows in-room correction which potentially eliminates the patient setup error however the uncertainty due to organ deformation still remains. Performing a plan re-optimization will take about half hour which is infeasible to perform an online correction. A technique of performing online re-optimization of intensity modulated radiation therapy is developed for adaptive radiation therapy of prostate cancer. The technique is capable of correction both organ positioning and shape changes within a few minutes. The proposed technique involves (1) 3D on-board imaging of daily anatomy, (2) registering the daily images with original planning CT images and mapping the original dose distribution to the daily anatomy, (3) real time re-optimization of the plan. Finally the leaf sequences are calculated for the treatment delivery. The feasibility of this online adaptive radiation therapy scheme was evaluated by clinical cases. The results demonstrate that it is feasible to perform online re-optimization of the original plan when large position or shape variation occurs.

  9. Robust plan optimization for electromagnetic transponder guided hypo-fractionated prostate treatment using volumetric modulated arc therapy.

    PubMed

    Zhang, Pengpeng; Hunt, Margie; Happersett, Laura; Yang, Jie; Zelefsky, Michael; Mageras, Gig

    2013-11-01

    To develop an optimization algorithm for volumetric modulated arc therapy which incorporates an electromagnetic tracking (EMT) guided gating strategy and is robust to residual intra-fractional motion uncertainties. In a computer simulation, intra-fractional motion traces from prior treatments with EMT were converted to a probability distribution function (PDF), truncated using a patient specific action volume that encloses allowed deviations from the planned position, and renormalized to yield a new PDF with EMT-gated interventions. In lieu of a conventional planning target volume (PTV), multiple instances of clinical target volume (CTV) and organs at risk (OARs) were replicated and displaced to extreme positions inside the action volume representing possible delivery scenarios. When optimizing the volumetric modulated arc therapy plan, doses to the CTV and OARs were calculated as a sum of doses to the replicas weighted by the PDF to account for motion. A treatment plan meeting the clinical constraints was produced and compared to the counterpart conventional margin (PTV) plan. EMT traces from a separate testing database served to simulate motion during gated delivery. Dosimetric end points extracted from dose accumulations for each motion trace were utilized to evaluate potential clinical benefit. Five prostate cases from a hypofractionated protocol (42.5 Gy in 5 fractions) were retrospectively investigated. The patient specific gating window resulted in tight anterior and inferior action levels (~1 mm) to protect rectal wall and bladder wall, and resulted in an average of four beam interruptions per fraction in the simulation. The robust-optimized plans achieved the same average CTV D95 coverage of 40.5 Gy as the PTV-optimized plans, but with reduced patient-averaged rectum wall D1cc by 2.2 Gy (range 0.7 to 4.7 Gy) and bladder wall mean dose by 2.9 Gy (range 2.0 to 3.4 Gy). Integration of an intra-fractional motion management strategy into the robust optimization

  10. Robust plan optimization for electromagnetic transponder guided hypo-fractionated prostate treatment using volumetric modulated arc therapy

    NASA Astrophysics Data System (ADS)

    Zhang, Pengpeng; Hunt, Margie; Happersett, Laura; Yang, Jie; Zelefsky, Michael; Mageras, Gig

    2013-11-01

    To develop an optimization algorithm for volumetric modulated arc therapy which incorporates an electromagnetic tracking (EMT) guided gating strategy and is robust to residual intra-fractional motion uncertainties. In a computer simulation, intra-fractional motion traces from prior treatments with EMT were converted to a probability distribution function (PDF), truncated using a patient specific action volume that encloses allowed deviations from the planned position, and renormalized to yield a new PDF with EMT-gated interventions. In lieu of a conventional planning target volume (PTV), multiple instances of clinical target volume (CTV) and organs at risk (OARs) were replicated and displaced to extreme positions inside the action volume representing possible delivery scenarios. When optimizing the volumetric modulated arc therapy plan, doses to the CTV and OARs were calculated as a sum of doses to the replicas weighted by the PDF to account for motion. A treatment plan meeting the clinical constraints was produced and compared to the counterpart conventional margin (PTV) plan. EMT traces from a separate testing database served to simulate motion during gated delivery. Dosimetric end points extracted from dose accumulations for each motion trace were utilized to evaluate potential clinical benefit. Five prostate cases from a hypofractionated protocol (42.5 Gy in 5 fractions) were retrospectively investigated. The patient specific gating window resulted in tight anterior and inferior action levels (∼1 mm) to protect rectal wall and bladder wall, and resulted in an average of four beam interruptions per fraction in the simulation. The robust-optimized plans achieved the same average CTV D95 coverage of 40.5 Gy as the PTV-optimized plans, but with reduced patient-averaged rectum wall D1cc by 2.2 Gy (range 0.7 to 4.7 Gy) and bladder wall mean dose by 2.9 Gy (range 2.0 to 3.4 Gy). Integration of an intra-fractional motion management strategy into the robust

  11. Robust plan optimization for electromagnetic transponder guided hypo-fractionated prostate treatment using volumetric modulated arc therapy.

    PubMed

    Zhang, Pengpeng; Hunt, Margie; Happersett, Laura; Yang, Jie; Zelefsky, Michael; Mageras, Gig

    2013-11-01

    To develop an optimization algorithm for volumetric modulated arc therapy which incorporates an electromagnetic tracking (EMT) guided gating strategy and is robust to residual intra-fractional motion uncertainties. In a computer simulation, intra-fractional motion traces from prior treatments with EMT were converted to a probability distribution function (PDF), truncated using a patient specific action volume that encloses allowed deviations from the planned position, and renormalized to yield a new PDF with EMT-gated interventions. In lieu of a conventional planning target volume (PTV), multiple instances of clinical target volume (CTV) and organs at risk (OARs) were replicated and displaced to extreme positions inside the action volume representing possible delivery scenarios. When optimizing the volumetric modulated arc therapy plan, doses to the CTV and OARs were calculated as a sum of doses to the replicas weighted by the PDF to account for motion. A treatment plan meeting the clinical constraints was produced and compared to the counterpart conventional margin (PTV) plan. EMT traces from a separate testing database served to simulate motion during gated delivery. Dosimetric end points extracted from dose accumulations for each motion trace were utilized to evaluate potential clinical benefit. Five prostate cases from a hypofractionated protocol (42.5 Gy in 5 fractions) were retrospectively investigated. The patient specific gating window resulted in tight anterior and inferior action levels (~1 mm) to protect rectal wall and bladder wall, and resulted in an average of four beam interruptions per fraction in the simulation. The robust-optimized plans achieved the same average CTV D95 coverage of 40.5 Gy as the PTV-optimized plans, but with reduced patient-averaged rectum wall D1cc by 2.2 Gy (range 0.7 to 4.7 Gy) and bladder wall mean dose by 2.9 Gy (range 2.0 to 3.4 Gy). Integration of an intra-fractional motion management strategy into the robust optimization

  12. Organ sample generator for expected treatment dose construction and adaptive inverse planning optimization

    SciTech Connect

    Nie Xiaobo; Liang Jian; Yan Di

    2012-12-15

    Purpose: To create an organ sample generator (OSG) for expected treatment dose construction and adaptive inverse planning optimization. The OSG generates random samples of organs of interest from a distribution obeying the patient specific organ variation probability density function (PDF) during the course of adaptive radiotherapy. Methods: Principle component analysis (PCA) and a time-varying least-squares regression (LSR) method were used on patient specific geometric variations of organs of interest manifested on multiple daily volumetric images obtained during the treatment course. The construction of the OSG includes the determination of eigenvectors of the organ variation using PCA, and the determination of the corresponding coefficients using time-varying LSR. The coefficients can be either random variables or random functions of the elapsed treatment days depending on the characteristics of organ variation as a stationary or a nonstationary random process. The LSR method with time-varying weighting parameters was applied to the precollected daily volumetric images to determine the function form of the coefficients. Eleven h and n cancer patients with 30 daily cone beam CT images each were included in the evaluation of the OSG. The evaluation was performed using a total of 18 organs of interest, including 15 organs at risk and 3 targets. Results: Geometric variations of organs of interest during h and n cancer radiotherapy can be represented using the first 3 {approx} 4 eigenvectors. These eigenvectors were variable during treatment, and need to be updated using new daily images obtained during the treatment course. The OSG generates random samples of organs of interest from the estimated organ variation PDF of the individual. The accuracy of the estimated PDF can be improved recursively using extra daily image feedback during the treatment course. The average deviations in the estimation of the mean and standard deviation of the organ variation PDF for h

  13. Treatment planning considerations in contrast-enhanced radiotherapy: energy and beam aperture optimization.

    PubMed

    Garnica-Garza, H M

    2011-01-21

    It has been shown that the use of kilovoltage x-rays in conjunction with a contrast agent incorporated into the tumor can lead to acceptable treatment plans with regard to the absorbed dose distribution produced in the target as well as in the tissue and organs at risk surrounding it. In this work, several key aspects related to the technology and irradiation techniques necessary to clinically implement this treatment modality are addressed by means of Monte Carlo simulation. The Zubal phantom was used to model a prostate radiotherapy treatment, a challenging site due to the depth of the prostate and the presence of bony structures that must be traversed by the x-ray beam on its way to the target. It is assumed that the concentration levels of the enhancing agent present in the tumor are at or below 10 mg per 1 g of tissue. The Monte Carlo code PENELOPE was used to model a commercial x-ray tube having a tungsten target. X-ray energy spectra for several combinations of peak electron energy and added filtration were obtained. For each energy spectrum, a treatment plan was calculated, with the PENELOPE Monte Carlo code, by modeling the irradiation of the patient as 72 independent conformal beams distributed at intervals of 5° around the phantom in order to model a full x-ray source rotation. The Cimmino optimization algorithm was then used to find the optimum beam weight and energy for different treatment strategies. It is shown that for a target dose prescription of 72 Gy covering the whole tumor, the maximum rectal wall and bladder doses are kept below 52 Gy for the largest concentration of contrast agent of 10 mg per 1 g of tissue. It is also shown that concentrations of as little as 5 mg per 1 g of tissue also render dose distributions with excellent sparing of the organs at risk. A treatment strategy to address the presence of non-uniform distributions of the contrast agent in the target is also modeled and discussed.

  14. Comparative evaluation of two dose optimization methods for image-guided, highly-conformal, tandem and ovoids cervix brachytherapy planning

    NASA Astrophysics Data System (ADS)

    Ren, Jiyun; Menon, Geetha; Sloboda, Ron

    2013-04-01

    Although the Manchester system is still extensively used to prescribe dose in brachytherapy (BT) for locally advanced cervix cancer, many radiation oncology centers are transitioning to 3D image-guided BT, owing to the excellent anatomy definition offered by modern imaging modalities. As automatic dose optimization is highly desirable for 3D image-based BT, this study comparatively evaluates the performance of two optimization methods used in BT treatment planning—Nelder-Mead simplex (NMS) and simulated annealing (SA)—for a cervix BT computer simulation model incorporating a Manchester-style applicator. Eight model cases were constructed based on anatomical structure data (for high risk-clinical target volume (HR-CTV), bladder, rectum and sigmoid) obtained from measurements on fused MR-CT images for BT patients. D90 and V100 for HR-CTV, D2cc for organs at risk (OARs), dose to point A, conformation index and the sum of dwell times within the tandem and ovoids were calculated for optimized treatment plans designed to treat the HR-CTV in a highly conformal manner. Compared to the NMS algorithm, SA was found to be superior as it could perform optimization starting from a range of initial dwell times, while the performance of NMS was strongly dependent on their initial choice. SA-optimized plans also exhibited lower D2cc to OARs, especially the bladder and sigmoid, and reduced tandem dwell times. For cases with smaller HR-CTV having good separation from adjoining OARs, multiple SA-optimized solutions were found which differed markedly from each other and were associated with different choices for initial dwell times. Finally and importantly, the SA method yielded plans with lower dwell time variability compared with the NMS method.

  15. Planned Missing Designs to Optimize the Efficiency of Latent Growth Parameter Estimates

    ERIC Educational Resources Information Center

    Rhemtulla, Mijke; Jia, Fan; Wu, Wei; Little, Todd D.

    2014-01-01

    We examine the performance of planned missing (PM) designs for correlated latent growth curve models. Using simulated data from a model where latent growth curves are fitted to two constructs over five time points, we apply three kinds of planned missingness. The first is item-level planned missingness using a three-form design at each wave such…

  16. Gradient maintenance: A new algorithm for fast online replanning

    SciTech Connect

    Ahunbay, Ergun E. Li, X. Allen

    2015-06-15

    Purpose: Clinical use of online adaptive replanning has been hampered by the unpractically long time required to delineate volumes based on the image of the day. The authors propose a new replanning algorithm, named gradient maintenance (GM), which does not require the delineation of organs at risk (OARs), and can enhance automation, drastically reducing planning time and improving consistency and throughput of online replanning. Methods: The proposed GM algorithm is based on the hypothesis that if the dose gradient toward each OAR in daily anatomy can be maintained the same as that in the original plan, the intended plan quality of the original plan would be preserved in the adaptive plan. The algorithm requires a series of partial concentric rings (PCRs) to be automatically generated around the target toward each OAR on the planning and the daily images. The PCRs are used in the daily optimization objective function. The PCR dose constraints are generated with dose–volume data extracted from the original plan. To demonstrate this idea, GM plans generated using daily images acquired using an in-room CT were compared to regular optimization and image guided radiation therapy repositioning plans for representative prostate and pancreatic cancer cases. Results: The adaptive replanning using the GM algorithm, requiring only the target contour from the CT of the day, can be completed within 5 min without using high-power hardware. The obtained adaptive plans were almost as good as the regular optimization plans and were better than the repositioning plans for the cases studied. Conclusions: The newly proposed GM replanning algorithm, requiring only target delineation, not full delineation of OARs, substantially increased planning speed for online adaptive replanning. The preliminary results indicate that the GM algorithm may be a solution to improve the ability for automation and may be especially suitable for sites with small-to-medium size targets surrounded by

  17. The dosimetric impact of inversely optimized arc radiotherapy plan modulation for real-time dynamic MLC tracking delivery

    SciTech Connect

    Falk, Marianne; Larsson, Tobias; Keall, Paul; Chul Cho, Byung; Aznar, Marianne; Korreman, Stine; Poulsen, Per; Munck af Rosenschoeld, Per

    2012-03-15

    Purpose: Real-time dynamic multileaf collimator (MLC) tracking for management of intrafraction tumor motion can be challenging for highly modulated beams, as the leaves need to travel far to adjust for target motion perpendicular to the leaf travel direction. The plan modulation can be reduced by using a leaf position constraint (LPC) that reduces the difference in the position of adjacent MLC leaves in the plan. The purpose of this study was to investigate the impact of the LPC on the quality of inversely optimized arc radiotherapy plans and the effect of the MLC motion pattern on the dosimetric accuracy of MLC tracking delivery. Specifically, the possibility of predicting the accuracy of MLC tracking delivery based on the plan modulation was investigated. Methods: Inversely optimized arc radiotherapy plans were created on CT-data of three lung cancer patients. For each case, five plans with a single 358 deg. arc were generated with LPC priorities of 0 (no LPC), 0.25, 0.5, 0.75, and 1 (highest possible LPC), respectively. All the plans had a prescribed dose of 2 Gy x 30, used 6 MV, a maximum dose rate of 600 MU/min and a collimator angle of 45 deg. or 315 deg. To quantify the plan modulation, an average adjacent leaf distance (ALD) was calculated by averaging the mean adjacent leaf distance for each control point. The linear relationship between the plan quality [i.e., the calculated dose distributions and the number of monitor units (MU)] and the LPC was investigated, and the linear regression coefficient as well as a two tailed confidence level of 95% was used in the evaluation. The effect of the plan modulation on the performance of MLC tracking was tested by delivering the plans to a cylindrical diode array phantom moving with sinusoidal motion in the superior-inferior direction with a peak-to-peak displacement of 2 cm and a cycle time of 6 s. The delivery was adjusted to the target motion using MLC tracking, guided in real-time by an infrared optical system

  18. 40 CFR 63.1655 - Maintenance requirements.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40 Protection of Environment 12 2011-07-01 2009-07-01 true Maintenance requirements. 63.1655....1655 Maintenance requirements. (a) The owner or operator of an affected source must comply with the... maintenance plan for each air pollution control device associated with submerged arc furnaces, metal...

  19. 40 CFR 63.1655 - Maintenance requirements.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 12 2010-07-01 2010-07-01 true Maintenance requirements. 63.1655....1655 Maintenance requirements. (a) The owner or operator of an affected source must comply with the... maintenance plan for each air pollution control device associated with submerged arc furnaces, metal...

  20. A Study on Optimal Operation of Power Generation by Waste

    NASA Astrophysics Data System (ADS)

    Sugahara, Hideo; Aoyagi, Yoshihiro; Kato, Masakazu

    This paper proposes the optimal operation of power generation by waste. Refuse is taken as a new energy resource of biomass. Although some fossil fuel origin refuse like plastic may be mixed in, CO2 emission is not counted up except for above fossil fuel origin refuse for the Kyoto Protocol. Incineration is indispensable for refuse disposal and power generation by waste is environment-friendly and power system-friendly using synchronous generators. Optimal planning is a key point to make much of this merit. The optimal plan includes refuse incinerator operation plan with refuse collection and maintenance scheduling of refuse incinerator plant. In this paper, it has been made clear that the former plan increases generation energy through numerical simulations. Concerning the latter plan, a method to determine the maintenance schedule using genetic algorithm has been established. In addition, taking environmental load of CO2 emission into account, this is expected larger merits from environment and energy resource points of view.

  1. Toward optimizing patient-specific IMRT QA techniques in the accurate detection of dosimetrically acceptable and unacceptable patient plans

    SciTech Connect

    McKenzie, Elizabeth M.; Balter, Peter A.; Stingo, Francesco C.; Jones, Jimmy; Followill, David S.; Kry, Stephen F.

    2014-12-15

    Purpose: The authors investigated the performance of several patient-specific intensity-modulated radiation therapy (IMRT) quality assurance (QA) dosimeters in terms of their ability to correctly identify dosimetrically acceptable and unacceptable IMRT patient plans, as determined by an in-house-designed multiple ion chamber phantom used as the gold standard. A further goal was to examine optimal threshold criteria that were consistent and based on the same criteria among the various dosimeters. Methods: The authors used receiver operating characteristic (ROC) curves to determine the sensitivity and specificity of (1) a 2D diode array undergoing anterior irradiation with field-by-field evaluation, (2) a 2D diode array undergoing anterior irradiation with composite evaluation, (3) a 2D diode array using planned irradiation angles with composite evaluation, (4) a helical diode array, (5) radiographic film, and (6) an ion chamber. This was done with a variety of evaluation criteria for a set of 15 dosimetrically unacceptable and 9 acceptable clinical IMRT patient plans, where acceptability was defined on the basis of multiple ion chamber measurements using independent ion chambers and a phantom. The area under the curve (AUC) on the ROC curves was used to compare dosimeter performance across all thresholds. Optimal threshold values were obtained from the ROC curves while incorporating considerations for cost and prevalence of unacceptable plans. Results: Using common clinical acceptance thresholds, most devices performed very poorly in terms of identifying unacceptable plans. Grouping the detector performance based on AUC showed two significantly different groups. The ion chamber, radiographic film, helical diode array, and anterior-delivered composite 2D diode array were in the better-performing group, whereas the anterior-delivered field-by-field and planned gantry angle delivery using the 2D diode array performed less well. Additionally, based on the AUCs, there

  2. A characterization of robust radiation therapy treatment planning methods-from expected value to worst case optimization

    SciTech Connect

    Fredriksson, Albin

    2012-08-15

    Purpose: To characterize a class of optimization formulations used to handle systematic and random errors in radiation therapy, and to study the differences between the methods within this class. Methods: The class of robust methods that can be formulated as minimax stochastic programs is studied. This class generalizes many previously used methods, ranging between optimization of the expected and the worst case objective value. The robust methods are used to plan intensity-modulated proton therapy (IMPT) treatments for a case subject to systematic setup and range errors, random setup errors with and without uncertain probability distribution, and combinations thereof. As reference, plans resulting from a conventional method that uses a margin to account for errors are shown. Results: For all types of errors, target coverage robustness increased with the conservativeness of the method. For systematic errors, best case organ at risk (OAR) doses increased and worst case doses decreased with the conservativeness. Accounting for random errors of fixed probability distribution resulted in heterogeneous dose. The heterogeneities were reduced when uncertainty in the probability distribution was accounted for. Doing so, the OAR doses decreased with the conservativeness. All robust methods studied resulted in more robust target coverage and lower OAR doses than the conventional method. Conclusions: Accounting for uncertainties is essential to ensure plan quality in complex radiation therapy such as IMPT. The utilization of more information than conventional in the optimization can lead to robust target coverage and low OAR doses. Increased target coverage robustness can be achieved by more conservative methods.

  3. Optimized planning target volume margin in helical tomotherapy for prostate cancer: Is there a preferred method?

    NASA Astrophysics Data System (ADS)

    Cao, Yuan Jie; Lee, Suk; Chang, Kyung Hwan; Shim, Jang Bo; Kim, Kwang Hyeon; Jang, Min Sun; Yoon, Won Sup; Yang, Dae Sik; Park, Young Je; Kim, Chul Yong

    2015-07-01

    We compare the dosimetrical differences between plans generated for helical tomotherapy by using the 2D or 3D the margining technique for the treatment of prostate cancer. Ten prostate cancer patients were included in this study. For 2D plans, the planning target volume (PTV) was created by adding 5 mm (lateral/anterior-posterior) to the clinical target volume (CTV). For 3D plans, a 5-mm margin was added not only lateral/anterior-posterior, but also superior-inferior, to the CTV. Various dosimetrical indices, including the prescription isodose to target volume (PITV) ratio, conformity index (CI), homogeneity index (HI), target coverage index (TCI), modified dose homogeneity index (MHI), conformation number (CN), critical organ scoring index (COSI), and quality factor (QF) were determined to compare the different treatment plans. Differences between the 2D and the 3D PTV indices were not significant except for the CI (p = 0.023). 3D margin plans (11195 MUs) resulted in higher (13.0%) monitor units than 2D margin plans (9728 MUs). There were no significant differences in any organs at risk (OARs) between the 2D and the 3D plans. Overall, the average dose for the 2D plan was slightly lower than that for the 3D plan dose. Compared to the 2D plan, the 3D plan increased the average treatment time by 1.5 minutes; however, this difference was not statistically significant (p = 0.082). We confirmed that the 2D and the 3D margin plans were not significantly different with regard to various dosimetric indices such as the PITV, CI, and HI for PTV and the OARs with tomotherapy.

  4. Integration of process planning and production scheduling with particle swarm optimization (PSO) algorithm and fuzzy inference systems

    NASA Astrophysics Data System (ADS)

    Yang, Yahong; Zhao, Fuqing; Hong, Yi; Yu, Dongmei

    2005-12-01

    Integration of process planning with scheduling by considering the manufacturing system's capacity, cost and capacity in its workshop is a critical issue. The concurrency between them can also eliminate the redundant process and optimize the entire production cycle, but most integrated process planning and scheduling methods only consider the time aspects of the alternative machines when constructing schedules. In this paper, a fuzzy inference system (FIS) in choosing alternative machines for integrated process planning and scheduling of a job shop manufacturing system is presented. Instead of choosing alternative machines randomly, machines are being selected based on the machines reliability. The mean time to failure (MTF) values is input in a fuzzy inference mechanism, which outputs the machine reliability. The machine is then being penalized based on the fuzzy output. The most reliable machine will have the higher priority to be chosen. In order to overcome the problem of un-utilization machines, sometimes faced by unreliable machine, the particle swarm optimization (PSO) have been used to balance the load for all the machines. Simulation study shows that the system can be used as an alternative way of choosing machines in integrated process planning and scheduling.

  5. Risk-based maintenance modeling. Prioritization of maintenance importances and quantification of maintenance effectiveness

    SciTech Connect

    Vesely, W.E.; Rezos, J.T.

    1995-09-01

    This report describes methods for prioritizing the risk importances of maintenances using a Probabilistic Risk Assessment (PRA). Approaches then are described for quantifying their reliability and risk effects. Two different PRA importance measures, minimal cutset importances and risk reduction importances, were used to prioritize maintenances; the findings show that both give similar results if appropriate criteria are used. The justifications for the particular importance measures also are developed. The methods developed to quantify the reliability and risk effects of maintenance actions are extensions of the usual reliability models now used in PRAs. These extended models consider degraded states of the component, and quantify the benefits of maintenance in correcting degradations and preventing failures. The negative effects of maintenance, including downtimes, also are included. These models are specific types of Markov models. The data for these models can be obtained from plant maintenance logs and from the Nuclear Plant Reliability Data System (NPRDS). To explore the potential usefulness of these models, the authors analyzed a range of postulated values of input data. These models were used to examine maintenance effects on a components reliability and performance for various maintenance programs and component data. Maintenance schedules were analyzed to optimize the component`s availability. In specific cases, the effects of maintenance were found to be large.

  6. Find the competitive edge with maintenance

    SciTech Connect

    Zink, J.C.

    1997-02-01

    This article describes how new monitoring and diagnostic tools, combined with computer workstations that convert data into intelligence, can help save maintenance dollars. The new era of competitive power is putting a premium on working smarter: using all the modern technology available to minimize maintenance costs. The industry is moving from preventive maintenance (PM) to reliability centered maintenance (RCM) and predictive maintenance (PDM). PDM optimizes the combination of PM and RCM, along with new monitoring and diagnostic technologies, to save maintenance dollars by working smarter.

  7. The performance of the progressive resolution optimizer (PRO) for RapidArc planning in targets with low-density media.

    PubMed

    Kan, Monica W K; Leung, Lucullus H T; Yu, Peter K N

    2013-01-01

    A new version of progressive resolution optimizer (PRO) with an option of air cavity correction has been implemented for RapidArc volumetric-modulated arc therapy (RA). The purpose of this study was to compare the performance of this new PRO with the use of air cavity correction option (PRO10_air) against the one without the use of the air cavity correction option (PRO10_no-air) for RapidArc planning in targets with low-density media of different sizes and complexities. The performance of PRO10_no-air and PRO10_air was initially compared using single-arc plans created for four different simple heterogeneous phantoms with virtual targets and organs at risk. Multiple-arc planning of 12 real patients having nasopharyngeal carcinomas (NPC) and ten patients having non-small cell lung cancer (NSCLC) were then performed using the above two options for further comparison. Dose calculations were performed using both the Acuros XB (AXB) algorithm with the dose to medium option and the analytical anisotropic algorithm (AAA). The effect of using intermediate dose option after the first optimization cycle in PRO10_air and PRO10_no-air was also investigated and compared. Plans were evaluated and compared using target dose coverage, critical organ sparing, conformity index, and dose homogeneity index. For NSCLC cases or cases for which large volumes of low-density media were present in or adjacent to the target volume, the use of the air cavity correction option in PRO10 was shown to be beneficial. For NPC cases or cases for which small volumes of both low- and high-density media existed in the target volume, the use of air cavity correction in PRO10 did not improve the plan quality. Based on the AXB dose calculation results, the use of PRO10_air could produce up to 18% less coverage to the bony structures of the planning target volumes for NPC cases. When the intermediate dose option in PRO10 was used, there was negligible difference observed in plan quality between

  8. Educational Planning and Administration in Latin America: From Optimism to Uncertainty.

    ERIC Educational Resources Information Center

    Bustos, Fabio M.

    1991-01-01

    Discusses the history of educational planning and administration in Latin America. Describes a period of educational expansion and diversification after World War II and one of disillusionment during the economic crisis of the 1980s. Urges an thorough review of the traditional approaches of educational planning in Latin America and a search for…

  9. Incorporating Age-Specific Plans of Care to Achieve Optimal Perioperative Outcomes.

    PubMed

    Mower, Juliana

    2015-10-01

    When developing a nursing plan of care, a perioperative nurse identifies nursing diagnoses during the preoperative patient assessment. The ability to identify age-specific outcomes (ie, infant/child, adolescent, adult, elderly adult) in addition to those that are universally applicable is a major responsibility of the perioperative RN. Having an individualized plan of care is one of the best ways to determine whether desired patient outcomes have been successfully attained. Nursing care plans address intraoperative and postoperative risks and allow for a smooth transfer of care throughout the perioperative experience. A good nursing care plan also includes education for the patient and his or her caregiver. Within an overall plan of care, the use of methods such as a concept or mind map can visually demonstrate the relationships between systems, nursing diagnoses, nursing interventions, and desirable outcomes.

  10. Catchment Area Treatment (CAT) Plan and Crop Area Optimization for Integrated Management in a Water Resource Project

    NASA Astrophysics Data System (ADS)

    Jaiswal, R. K.; Thomas, T.; Galkate, R. V.; Ghosh, N. C.; Singh, S.

    2013-09-01

    A scientifically developed catchment area treatment (CAT) plan and optimized pattern of crop areas may be the key for sustainable development of water resource, profitability in agriculture and improvement of overall economy in drought affected Bundelkhand region of Madhya Pradesh (India). In this study, an attempt has been made to develop a CAT plan using spatial variation of geology, geomorphology, soil, drainage, land use in geographical information system for selection of soil and water conservation measures and crop area optimization using linear programming for maximization of return considering water availability, area affinity, fertilizers, social and market constraints in Benisagar reservoir project of Chhatarpur district (M.P.). The scientifically developed CAT plan based on overlaying of spatial information consists of 58 mechanical measure (49 boulder bunds, 1 check dam, 7 cully plug and 1 percolation tank), 2.60 km2 land for agro forestry, 2.08 km2 land for afforestation in Benisagar dam and 67 mechanical measures (45 boulder bunds and 22 gully plugs), 7.79 km2 land for agro forestry, 5.24 km2 land for afforestation in Beniganj weir catchment with various agronomic measures for agriculture areas. The linear programming has been used for optimization of crop areas in Benisagar command for sustainable development considering various scenarios of water availability, efficiencies, affinity and fertilizers availability in the command. Considering present supply condition of water, fertilizers, area affinity and making command self sufficient in most of crops, the net benefit can be increase to Rs. 1.93 crores from 41.70 km2 irrigable area in Benisagar command by optimizing cropping pattern and reducing losses during conveyance and application of water.

  11. Optimism

    PubMed Central

    Carver, Charles S.; Scheier, Michael F.; Segerstrom, Suzanne C.

    2010-01-01

    Optimism is an individual difference variable that reflects the extent to which people hold generalized favorable expectancies for their future. Higher levels of optimism have been related prospectively to better subjective well-being in times of adversity or difficulty (i.e., controlling for previous well-being). Consistent with such findings, optimism has been linked to higher levels of engagement coping and lower levels of avoidance, or disengagement, coping. There is evidence that optimism is associated with taking proactive steps to protect one's health, whereas pessimism is associated with health-damaging behaviors. Consistent with such findings, optimism is also related to indicators of better physical health. The energetic, task-focused approach that optimists take to goals also relates to benefits in the socioeconomic world. Some evidence suggests that optimism relates to more persistence in educational efforts and to higher later income. Optimists also appear to fare better than pessimists in relationships. Although there are instances in which optimism fails to convey an advantage, and instances in which it may convey a disadvantage, those instances are relatively rare. In sum, the behavioral patterns of optimists appear to provide models of living for others to learn from. PMID:20170998

  12. Design Genetic Algorithm Optimization Education Software Based Fuzzy Controller for a Tricopter Fly Path Planning

    ERIC Educational Resources Information Center

    Tran, Huu-Khoa; Chiou, Juing -Shian; Peng, Shou-Tao

    2016-01-01

    In this paper, the feasibility of a Genetic Algorithm Optimization (GAO) education software based Fuzzy Logic Controller (GAO-FLC) for simulating the flight motion control of Unmanned Aerial Vehicles (UAVs) is designed. The generated flight trajectories integrate the optimized Scaling Factors (SF) fuzzy controller gains by using GAO algorithm. The…

  13. Optimization of night and shiftwork plans among policemen in Kuwait: a field experiment.

    PubMed

    Attia, M; Mustafa, M K; Khogali, M; Mahmoud, N A; Arar, E I

    1985-01-01

    A pilot survey was designed to define incidence, rotation period, rotation direction and cycle of shiftwork plans in the production and service units in Kuwait. Preliminary results from the Ministry of Interior showed that four different shift plans are widely used. Forty policemen, ten from each shift plan, volunteered to fill in a diary for a period of two or more cycles. The diary was comprised of a set of questions planned to reveal disturbances in sleep duration, sleep quality, food intake and appetite. The daily questionnaire also covered psychosomatic complaints and subjective judgement of recovery. A control group, on permanent day work, volunteered to fill in the diary for the same period. The results indicated that one of the four shift plans was quite satisfactory and least harmful to the policemen. Two plans were associated with excessive strain during working days, but the number of free days was sufficient to achieve complete recovery. The fourth plan was associated with excessive strain during working days and recovery was not achieved after 24 h of rest at the end of the shift cycle.

  14. A two-stage optimization model for emergency material reserve layout planning under uncertainty in response to environmental accidents.

    PubMed

    Liu, Jie; Guo, Liang; Jiang, Jiping; Jiang, Dexun; Liu, Rentao; Wang, Peng

    2016-06-01

    In the emergency management relevant to pollution accidents, efficiency emergency rescues can be deeply influenced by a reasonable assignment of the available emergency materials to the related risk sources. In this study, a two-stage optimization framework is developed for emergency material reserve layout planning under uncertainty to identify material warehouse locations and emergency material reserve schemes in pre-accident phase coping with potential environmental accidents. This framework is based on an integration of Hierarchical clustering analysis - improved center of gravity (HCA-ICG) model and material warehouse location - emergency material allocation (MWL-EMA) model. First, decision alternatives are generated using HCA-ICG to identify newly-built emergency material warehouses for risk sources which cannot be satisfied by existing ones with a time-effective manner. Second, emergency material reserve planning is obtained using MWL-EMA to make emergency materials be prepared in advance with a cost-effective manner. The optimization framework is then applied to emergency management system planning in Jiangsu province, China. The results demonstrate that the developed framework not only could facilitate material warehouse selection but also effectively provide emergency material for emergency operations in a quick response.

  15. A two-stage optimization model for emergency material reserve layout planning under uncertainty in response to environmental accidents.

    PubMed

    Liu, Jie; Guo, Liang; Jiang, Jiping; Jiang, Dexun; Liu, Rentao; Wang, Peng

    2016-06-01

    In the emergency management relevant to pollution accidents, efficiency emergency rescues can be deeply influenced by a reasonable assignment of the available emergency materials to the related risk sources. In this study, a two-stage optimization framework is developed for emergency material reserve layout planning under uncertainty to identify material warehouse locations and emergency material reserve schemes in pre-accident phase coping with potential environmental accidents. This framework is based on an integration of Hierarchical clustering analysis - improved center of gravity (HCA-ICG) model and material warehouse location - emergency material allocation (MWL-EMA) model. First, decision alternatives are generated using HCA-ICG to identify newly-built emergency material warehouses for risk sources which cannot be satisfied by existing ones with a time-effective manner. Second, emergency material reserve planning is obtained using MWL-EMA to make emergency materials be prepared in advance with a cost-effective manner. The optimization framework is then applied to emergency management system planning in Jiangsu province, China. The results demonstrate that the developed framework not only could facilitate material warehouse selection but also effectively provide emergency material for emergency operations in a quick response. PMID:26897572

  16. Optimization algorithm for overlapping-field plans of scanned ion beam therapy with reduced sensitivity to range and setup uncertainties

    NASA Astrophysics Data System (ADS)

    Inaniwa, Taku; Kanematsu, Nobuyuki; Furukawa, Takuji; Noda, Koji

    2011-03-01

    A 'patch-field' strategy is often used for tumors with large volumes exceeding the available field size in passive irradiations with ion beams. Range and setup errors can cause hot and cold spots at the field junction within the target. Such errors will also displace the field to miss the target periphery. With scanned ion beams with fluence modulation, the two junctional fields can be overlapped rather than patched, which may potentially reduce the sensitivity to these uncertainties. In this study, we have developed such a robust optimization algorithm. This algorithm is composed of the following two steps: (1) expanding the target volume with margins against the uncertainties, and (2) solving the inverse problem where the terms suppressing the dose gradient of individual fields are added into the objective function. The validity of this algorithm is demonstrated through simulation studies for two extreme cases of two fields with unidirectional and opposing geometries and for a prostate-cancer case. With the proposed algorithm, we can obtain a more robust plan with minimized influence of range and setup uncertainties than the conventional plan. Compared to conventional optimization, the calculation time for the robust optimization increased by a factor of approximately 3.

  17. Optimized traverse planning for future polar prospectors based on lunar topography

    NASA Astrophysics Data System (ADS)

    Speyerer, E. J.; Lawrence, S. J.; Stopar, J. D.; Gläser, P.; Robinson, M. S.; Jolliff, B. L.

    2016-07-01

    To fully understand the extensive collection of remotely sensed polar observations by the Lunar Reconnaissance Orbiter and other recent lunar missions, we must acquire an array of ground-truth measurements. A polar rover can sample and assay potential polar resources both laterally and at shallow depths. To identify ideal, least-energy traverses for such a polar prospecting mission, we developed a traverse planning tool, called R-Traverse, using a fundamental wheel-regolith interaction model and datasets from the Lunar Reconnaissance Orbiter Camera, Lunar Orbiter Laser Altimeter, and Diviner Lunar Radiometer Experiment. Using the terramechanics model, we identified least-energy traverses at the 20 m scale around Shackleton crater and located one traverse plan that enables the rover to remain illuminated for 94.4% of the lunar year. By incorporating this path planning tool during mission planning, the feasibility of such a mission can be quantified.

  18. Coverage-based treatment planning: optimizing the IMRT PTV to meet a CTV coverage criterion.

    PubMed

    Gordon, J J; Siebers, J V

    2009-03-01

    This work demonstrates an iterative approach-referred to as coverage-based treatment planning-designed to produce treatment plans that ensure target coverage for a specified percentage of setup errors. In this approach the clinical target volume to planning target volume (CTV-to-PTV) margin is iteratively adjusted until the specified CTV coverage is achieved. The advantage of this approach is that it automatically compensates for the dosimetric margin around the CTV, i.e., the extra margin that is created when the dose distribution extends beyond the PTV. When applied to 27 prostate plans, this approach reduced the average CTV-to-PTV margin from 5 to 2.8 mm. This reduction in PTV size produced a corresponding decrease in the volume of normal tissue receiving high dose. The total volume of tissue receiving > or =65 Gy was reduced on average by 19.3% or about 48 cc. Individual reductions varied from 8.7% to 28.6%. The volume of bladder receiving > or =60 Gy was reduced on average by 5.6% (reductions for individuals varied from 1.7% to 10.6%), and the volume of periprostatic rectum receiving > or =65 Gy was reduced on average by 4.9% (reductions for individuals varied from 0.9% to 12.3%). The iterative method proposed here represents a step toward a probabilistic treatment planning algorithm which can generate dose distributions (i.e., treated volumes) that closely approximate a specified level of coverage in the presence of geometric uncertainties. The general principles of coverage-based treatment planning are applicable to arbitrary treatment sites and delivery techniques. Importantly, observed deviations between coverage implied by specified CTV-to-PTV margins and coverage achieved by a given treatment plan imply a generic need to perform coverage probability analysis on a per-plan basis to ensure that the desired level of coverage is achieved. PMID:19378757

  19. SU-E-T-488: An Iso-Dose Curve Based Interactive IMRT Optimization System for Physician-Driven Plan Tuning

    SciTech Connect

    Shi, F; Tian, Z; Jia, X; Jiang, S; Zarepisheh, M; Cervino, L

    2014-06-01

    Purpose: In treatment plan optimization for Intensity Modulated Radiation Therapy (IMRT), after a plan is initially developed by a dosimetrist, the attending physician evaluates its quality and often would like to improve it. As opposed to having the dosimetrist implement the improvements, it is desirable to have the physician directly and efficiently modify the plan for a more streamlined and effective workflow. In this project, we developed an interactive optimization system for physicians to conveniently and efficiently fine-tune iso-dose curves. Methods: An interactive interface is developed under C++/Qt. The physician first examines iso-dose lines. S/he then picks an iso-dose curve to be improved and drags it to a more desired configuration using a computer mouse or touchpad. Once the mouse is released, a voxel-based optimization engine is launched. The weighting factors corresponding to voxels between the iso-dose lines before and after the dragging are modified. The underlying algorithm then takes these factors as input to re-optimize the plan in near real-time on a GPU platform, yielding a new plan best matching the physician's desire. The re-optimized DVHs and iso-dose curves are then updated for the next iteration of modifications. This process is repeated until a physician satisfactory plan is achieved. Results: We have tested this system for a series of IMRT plans. Results indicate that our system provides the physicians an intuitive and efficient tool to edit the iso-dose curves according to their preference. The input information is used to guide plan re-optimization, which is achieved in near real-time using our GPU-based optimization engine. Typically, a satisfactory plan can be developed by a physician in a few minutes using this tool. Conclusion: With our system, physicians are able to manipulate iso-dose curves according to their preferences. Preliminary results demonstrate the feasibility and effectiveness of this tool.

  20. Application of Probabilistic Performance Assessment Modeling for Optimization of Maintenance Studies for Low-Level Radioactive Waste Disposal Sites at the Nevada Test Site

    SciTech Connect

    Crowe, B.; Yucel, V.; Rawlinson, S.; Black, P.; Carilli, J.; DiSanza, F.

    2002-02-25

    The U.S. Department of Energy (DOE), National Nuclear Security Administration of the Nevada Operations Office (NNSA/NV) operates and maintains two active facilities on the Nevada Test Site (NTS) that dispose defense-generated low-level radioactive waste (LLW), mixed radioactive waste, and ''classified waste'' in shallow trenches and pits. The operation and maintenance of the LLW disposal sites are self-regulated by the DOE under DOE Order 435.1. This Order requires formal review of a performance assessment (PA) and composite analysis (CA; assessment of all interacting radiological sources) for each LLW disposal system followed by an active maintenance program that extends through and beyond the site closure program. The Nevada disposal facilities continue to receive NTS-generated LLW and defense-generated LLW from across the DOE complex. The PA/CAs for the sites have been conditionally approved and the facilities are now under a formal maintenance program that requires testing of conceptual models, quantifying and attempting to reduce uncertainty, and implementing confirmatory and long-term background monitoring, all leading to eventual closure of the disposal sites. To streamline and reduce the cost of the maintenance program, the NNSA/NV is converting the deterministic PA/CAs to probabilistic models using GoldSim, a probabilistic simulation computer code. The output of probabilistic models will provide expanded information supporting long-term decision objectives of the NTS disposal sites.

  1. Crew considerations in the design for Space Station Freedom modules on-orbit maintenance

    NASA Technical Reports Server (NTRS)

    Stokes, Jack W.; Williams, Katherine A.

    1992-01-01

    The paper presents an approach to the maintenance process currently planned for the Space Station Freedom modules. In particular, it describes the planned crew interfaces with maintenance items, and the anticipated implications for the crew in performing the interior and exterior maintenance of modules developed by U.S., ESA, and NASDA. Special consideration is given to the maintenance requirements, allocations, and approach; the maintenance design; the Maintenance Workstation; the robotic mechanisms; and the developemnt of maintenance techniques.

  2. An Automated Treatment Plan Quality Control Tool for Intensity-Modulated Radiation Therapy Using a Voxel-Weighting Factor-Based Re-Optimization Algorithm

    PubMed Central

    Song, Ting; Li, Nan; Zarepisheh, Masoud; Li, Yongbao; Gautier, Quentin; Zhou, Linghong; Mell, Loren; Jiang, Steve; Cerviño, Laura

    2016-01-01

    Intensity-modulated radiation therapy (IMRT) currently plays an important role in radiotherapy, but its treatment plan quality can vary significantly among institutions and planners. Treatment plan quality control (QC) is a necessary component for individual clinics to ensure that patients receive treatments with high therapeutic gain ratios. The voxel-weighting factor-based plan re-optimization mechanism has been proved able to explore a larger Pareto surface (solution domain) and therefore increase the possibility of finding an optimal treatment plan. In this study, we incorporated additional modules into an in-house developed voxel weighting factor-based re-optimization algorithm, which was enhanced as a highly automated and accurate IMRT plan QC tool (TPS-QC tool). After importing an under-assessment plan, the TPS-QC tool was able to generate a QC report within 2 minutes. This QC report contains the plan quality determination as well as information supporting the determination. Finally, the IMRT plan quality can be controlled by approving quality-passed plans and replacing quality-failed plans using the TPS-QC tool. The feasibility and accuracy of the proposed TPS-QC tool were evaluated using 25 clinically approved cervical cancer patient IMRT plans and 5 manually created poor-quality IMRT plans. The results showed high consistency between the QC report quality determinations and the actual plan quality. In the 25 clinically approved cases that the TPS-QC tool identified as passed, a greater difference could be observed for dosimetric endpoints for organs at risk (OAR) than for planning target volume (PTV), implying that better dose sparing could be achieved in OAR than in PTV. In addition, the dose-volume histogram (DVH) curves of the TPS-QC tool re-optimized plans satisfied the dosimetric criteria more frequently than did the under-assessment plans. In addition, the criteria for unsatisfied dosimetric endpoints in the 5 poor-quality plans could typically be

  3. An Automated Treatment Plan Quality Control Tool for Intensity-Modulated Radiation Therapy Using a Voxel-Weighting Factor-Based Re-Optimization Algorithm.

    PubMed

    Song, Ting; Li, Nan; Zarepisheh, Masoud; Li, Yongbao; Gautier, Quentin; Zhou, Linghong; Mell, Loren; Jiang, Steve; Cerviño, Laura

    2016-01-01

    Intensity-modulated radiation therapy (IMRT) currently plays an important role in radiotherapy, but its treatment plan quality can vary significantly among institutions and planners. Treatment plan quality control (QC) is a necessary component for individual clinics to ensure that patients receive treatments with high therapeutic gain ratios. The voxel-weighting factor-based plan re-optimization mechanism has been proved able to explore a larger Pareto surface (solution domain) and therefore increase the possibility of finding an optimal treatment plan. In this study, we incorporated additional modules into an in-house developed voxel weighting factor-based re-optimization algorithm, which was enhanced as a highly automated and accurate IMRT plan QC tool (TPS-QC tool). After importing an under-assessment plan, the TPS-QC tool was able to generate a QC report within 2 minutes. This QC report contains the plan quality determination as well as information supporting the determination. Finally, the IMRT plan quality can be controlled by approving quality-passed plans and replacing quality-failed plans using the TPS-QC tool. The feasibility and accuracy of the proposed TPS-QC tool were evaluated using 25 clinically approved cervical cancer patient IMRT plans and 5 manually created poor-quality IMRT plans. The results showed high consistency between the QC report quality determinations and the actual plan quality. In the 25 clinically approved cases that the TPS-QC tool identified as passed, a greater difference could be observed for dosimetric endpoints for organs at risk (OAR) than for planning target volume (PTV), implying that better dose sparing could be achieved in OAR than in PTV. In addition, the dose-volume histogram (DVH) curves of the TPS-QC tool re-optimized plans satisfied the dosimetric criteria more frequently than did the under-assessment plans. In addition, the criteria for unsatisfied dosimetric endpoints in the 5 poor-quality plans could typically be

  4. Coverage-based treatment planning: Optimizing the IMRT PTV to meet a CTV coverage criterion

    PubMed Central

    Gordon, J. J.; Siebers, J. V.

    2009-01-01

    This work demonstrates an iterative approach—referred to as coverage-based treatment planning—designed to produce treatment plans that ensure target coverage for a specified percentage of setup errors. In this approach the clinical target volume to planning target volume (CTV-to-PTV) margin is iteratively adjusted until the specified CTV coverage is achieved. The advantage of this approach is that it automatically compensates for the dosimetric margin around the CTV, i.e., the extra margin that is created when the dose distribution extends beyond the PTV. When applied to 27 prostate plans, this approach reduced the average CTV-to-PTV margin from 5 to 2.8 mm. This reduction in PTV size produced a corresponding decrease in the volume of normal tissue receiving high dose. The total volume of tissue receiving ≥65 Gy was reduced on average by 19.3% or about 48 cc. Individual reductions varied from 8.7% to 28.6%. The volume of bladder receiving ≥60 Gy was reduced on average by 5.6% (reductions for individuals varied from 1.7% to 10.6%), and the volume of periprostatic rectum receiving ≥65 Gy was reduced on average by 4.9% (reductions for individuals varied from 0.9% to 12.3%). The iterative method proposed here represents a step toward a probabilistic treatment planning algorithm which can generate dose distributions (i.e., treated volumes) that closely approximate a specified level of coverage in the presence of geometric uncertainties. The general principles of coverage-based treatment planning are applicable to arbitrary treatment sites and delivery techniques. Importantly, observed deviations between coverage implied by specified CTV-to-PTV margins and coverage achieved by a given treatment plan imply a generic need to perform coverage probability analysis on a per-plan basis to ensure that the desired level of coverage is achieved. PMID:19378757

  5. Planning intensive care unit design using computer simulation modeling: optimizing integration of clinical, operational, and architectural requirements.

    PubMed

    OʼHara, Susan

    2014-01-01

    Nurses have increasingly been regarded as critical members of the planning team as architects recognize their knowledge and value. But the nurses' role as knowledge experts can be expanded to leading efforts to integrate the clinical, operational, and architectural expertise through simulation modeling. Simulation modeling allows for the optimal merge of multifactorial data to understand the current state of the intensive care unit and predict future states. Nurses can champion the simulation modeling process and reap the benefits of a cost-effective way to test new designs, processes, staffing models, and future programming trends prior to implementation. Simulation modeling is an evidence-based planning approach, a standard, for integrating the sciences with real client data, to offer solutions for improving patient care.

  6. Distance-to-Agreement Investigation of Tomotherapy's Bony Anatomy-Based Autoregistration and Planning Target Volume Contour-Based Optimization

    SciTech Connect

    Suh, Steve; Schultheiss, Timothy E.

    2013-03-01

    Purpose: To compare Tomotherapy's megavoltage computed tomography bony anatomy autoregistration with the best achievable registration, assuming no deformation and perfect knowledge of planning target volume (PTV) location. Methods and Materials: Distance-to-agreement (DTA) of the PTV was determined by applying a rigid-body shift to the PTV region of interest of the prostate from its reference position, assuming no deformations. Planning target volume region of interest of the prostate was extracted from the patient archives. The reference position was set by the 6 degrees of freedom (dof)—x, y, z, roll, pitch, and yaw—optimization results from the previous study at this institution. The DTA and the compensating parameters were calculated by the shift of the PTV from the reference 6-dof to the 4-dof—x, y, z, and roll—optimization. In this study, the effectiveness of Tomotherapy's 4-dof bony anatomy–based autoregistration was compared with the idealized 4-dof PTV contour-based optimization. Results: The maximum DTA (maxDTA) of the bony anatomy-based autoregistration was 3.2 ± 1.9 mm, with the maximum value of 8.0 mm. The maxDTA of the contour-based optimization was 1.8 ± 1.3 mm, with the maximum value of 5.7 mm. Comparison of Pearson correlation of the compensating parameters between the 2 4-dof optimization algorithms shows that there is a small but statistically significant correlation in y and z (0.236 and 0.300, respectively), whereas there is very weak correlation in x and roll (0.062 and 0.025, respectively). Conclusions: We find that there is an average improvement of approximately 1 mm in terms of maxDTA on the PTV going from 4-dof bony anatomy-based autoregistration to the 4-dof contour-based optimization. Pearson correlation analysis of the 2 4-dof optimizations suggests that uncertainties due to deformation and inadequate resolution account for much of the compensating parameters, but pitch variation also makes a statistically significant

  7. Beyond the Status Quo: Creating a School Maintenance Program.

    ERIC Educational Resources Information Center

    Chan, T. C.

    2000-01-01

    A well-planned maintenance program will prolong a new school building's life expectancy and save enormous sums. A maintenance program should include a facility inventory, a building archive, management of punch-list and warranty items, custodial service, proactive maintenance, a maintenance schedule, and energy conservation features. (MLH)

  8. An optimization method for importance factors and beam weights based on genetic algorithms for radiotherapy treatment planning

    NASA Astrophysics Data System (ADS)

    Wu, Xingen; Zhu, Yunping

    2001-04-01

    We propose a new method for selecting importance factors (for regions of interest like organs at risk) used to plan conformal radiotherapy. Importance factors, also known as weighting factors or penalty factors, are essential in determining the relative importance of multiple objectives or the penalty ratios of constraints incorporated into cost functions, especially in dealing with dose optimization in radiotherapy treatment planning. Researchers usually choose importance factors on the basis of a trial-and-error process to reach a balance between all the objectives. In this study, we used a genetic algorithm and adopted a real-number encoding method to represent both beam weights and importance factors in each chromosome. The algorithm starts by optimizing the beam weights for a fixed number of iterations then modifying the importance factors for another fixed number of iterations. During the first phase, the genetic operators, such as crossover and mutation, are carried out only on beam weights, and importance factors for each chromosome are not changed or `frozen'. In the second phase, the situation is reversed: the beam weights are `frozen' and the importance factors are changed after crossover and mutation. Through alternation of these two phases, both beam weights and importance factors are adjusted according to a fitness function that describes the conformity of dose distribution in planning target volume and dose-tolerance constraints in organs at risk. Those chromosomes with better fitness are passed into the next generation, showing that they have a better combination of beam weights and importance factors. Although the ranges of the importance factors should be set in advance by using this algorithm, it is much more convenient than selecting specific numbers for importance factors. Three clinical examples are presented and compared with manual plans to verify this method. Three-dimensional standard displays and dose-volume histograms are shown to

  9. Maintenance Action Work Plan for Waste Area Grouping 1 inactive tanks 3001-B, 3004-B, T-30, and 3013 at Oak Ridge National Laboratory, Oak Ridge, Tennessee. Environmental Restoration Program

    SciTech Connect

    1995-07-01

    This Maintenance Action Work Plan has been prepared to document the activities and procedures for the remediation of four inactive, low-level radioactive tanks at Waste Area Grouping 1, from the Category D list of tanks in the Federal Facility Agreement for the Oak Ridge Reservation (EPA et al. 1994). The four tanks to remediated are tanks 3001-B, 3004-B, T-30, and 3013. Three of the tanks (3001-B, 3004-B, and T-30) will be physically removed from the ground. Because of logistical issues associted with excavation and site access, the fourth tank (3013) will be grouted in place and permanently closed.

  10. PLAN or get SLAM'ed: Optimal management of invasive species in the presence of indirect health externalities.

    PubMed

    Jones, Benjamin A; McDermott, Shana M; Chermak, Janie M

    2016-09-15

    This paper examines invasive species management when invasive species impact health outcomes indirectly through changes to environmental quality. For example, the emerald ash borer (EAB) has destroyed millions of ash trees throughout North America and has the potential to impact rates of cardiorespiratory mortality and morbidity through ash trees' ability to capture airborne pollutants. Optimal management inclusive of indirect health externalities may be different than status quo plans because the links between nature and health are complex, dynamic, and spatially heterogeneous. We produce a novel dynamic bioeconomic-health model to determine optimal EAB management in the face of such health effects. Our results show that including health increases net benefits of management substantially and that a "one size fits all" management approach is suboptimal given forest cover and demographic spatial heterogeneity. Net benefits to society are 873% higher and air pollution related mortality incidence is 82% lower when health externalities are included in management profiles using insecticide treatments and non-ash tree preemptive plantings without removal. Additionally, constrained managers optimally substitute toward preemptive tree plantings and away from insecticide use in the presence of indirect health externalities as a way to minimize disruptions to air quality. This paper has policy implications for the optimal management of environmental amenities. PMID:27318589

  11. PLAN or get SLAM'ed: Optimal management of invasive species in the presence of indirect health externalities.

    PubMed

    Jones, Benjamin A; McDermott, Shana M; Chermak, Janie M

    2016-09-15

    This paper examines invasive species management when invasive species impact health outcomes indirectly through changes to environmental quality. For example, the emerald ash borer (EAB) has destroyed millions of ash trees throughout North America and has the potential to impact rates of cardiorespiratory mortality and morbidity through ash trees' ability to capture airborne pollutants. Optimal management inclusive of indirect health externalities may be different than status quo plans because the links between nature and health are complex, dynamic, and spatially heterogeneous. We produce a novel dynamic bioeconomic-health model to determine optimal EAB management in the face of such health effects. Our results show that including health increases net benefits of management substantially and that a "one size fits all" management approach is suboptimal given forest cover and demographic spatial heterogeneity. Net benefits to society are 873% higher and air pollution related mortality incidence is 82% lower when health externalities are included in management profiles using insecticide treatments and non-ash tree preemptive plantings without removal. Additionally, constrained managers optimally substitute toward preemptive tree plantings and away from insecticide use in the presence of indirect health externalities as a way to minimize disruptions to air quality. This paper has policy implications for the optimal management of environmental amenities.

  12. Optimization of the rounded leaf offset table in modeling the multileaf collimator leaf edge in a commercial treatment planning system.

    PubMed

    Rice, John R

    2014-11-08

    An editable rounded leaf offset (RLO) table is provided in the Pinnacle3 treatment planning software. Default tables are provided for major linear accelerator manu- facturers, but it is not clear how the default table values should be adjusted by the user to optimize agreement between the calculated leaf tip value and the actual measured value. Since we wish for the calculated MLC-defined field edge to closely match the actual delivered field edge, optimal RLO table values are crucial. This is especially true for IMRT fields containing a large number of segments, since any errors would add together. A method based on the calculated MLC-defined field edge was developed for optimizing and modifying the default RLO table values. Modified RLO tables were developed and evaluated for both dosimetric and light field-based MLC leaf calibrations. It was shown, using a Picket Fence type test, that the optimized RLO table better modeled the calculated leaf tip than the Pinnacle3 default table. This was demonstrated for both an Elekta Synergy 80-leaf and a Varian 120-leaf MLC. 

  13. 33 CFR 150.502 - What are the maintenance and repair requirements for lifesaving equipment?

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... onboard maintenance and repair of the port's lifesaving equipment. The instructions must include the... this section, the deepwater port may have its own onboard planned maintenance program for...

  14. 33 CFR 150.502 - What are the maintenance and repair requirements for lifesaving equipment?

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... onboard maintenance and repair of the port's lifesaving equipment. The instructions must include the... this section, the deepwater port may have its own onboard planned maintenance program for...

  15. Trajectory Planning and Optimized Adaptive Control for a Class of Wheeled Inverted Pendulum Vehicle Models.

    PubMed

    Yang, Chenguang; Li, Zhijun; Li, Jing

    2013-02-01

    In this paper, we investigate optimized adaptive control and trajectory generation for a class of wheeled inverted pendulum (WIP) models of vehicle systems. Aiming at shaping the controlled vehicle dynamics to be of minimized motion tracking errors as well as angular accelerations, we employ the linear quadratic regulation optimization technique to obtain an optimal reference model. Adaptive control has then been developed using variable structure method to ensure the reference model to be exactly matched in a finite-time horizon, even in the presence of various internal and external uncertainties. The minimized yaw and tilt angular accelerations help to enhance the vehicle rider's comfort. In addition, due to the underactuated mechanism of WIP, the vehicle forward velocity dynamics cannot be controlled separately from the pendulum tilt angle dynamics. Inspired by the control strategy of human drivers, who usually manipulate the tilt angle to control the forward velocity, we design a neural-network-based adaptive generator of implicit control trajectory (AGICT) of the tilt angle which indirectly "controls" the forward velocity such that it tracks the desired velocity asymptotically. The stability and optimal tracking performance have been rigorously established by theoretic analysis. In addition, simulation studies have been carried out to demonstrate the efficiency of the developed AGICT and optimized adaptive controller.

  16. A Tool for Planning Optimal MOS Observations with the JWST Near-Infrared Spectrometer

    NASA Astrophysics Data System (ADS)

    Karakla, D.; Pontoppidan, K.; Beck, T.; Gilbert, K.; Curtis, G.

    2016-10-01

    The James Webb Space Telescope Near-Infrared Spectrograph (NIRSpec) will offer a powerful multi-object spectroscopic capability enabled by the instrument's micro-shutter arrays (MSAs). With this mode, the NIRSpec instrument can observe more than 100 targets simultaneously. The NIRSpec team at the Space Telescope Science Institute (STScI) has been developing an MSA Planning Tool (MPT) to facilitate the complex observation planning process for a variety of observing strategies. The MPT is available as part of the Astronomers Proposal Tool (APT).

  17. Reliability-based lifetime maintenance of aging highway bridges

    NASA Astrophysics Data System (ADS)

    Enright, Michael P.; Frangopol, Dan M.

    2000-06-01

    As the nation's infrastructure continues to age, the cost of maintaining it at an acceptable safety level continues to increase. In the United States, about one of every three bridges is rated structurally deficient and/or functionally obsolete. It will require about 80 billion to eliminate the current backlog of bridge deficiencies and maintain repair levels. Unfortunately, the financial resources allocated for these activities fall extremely short of the demand. Although several existing and emerging NDT techniques are available to gather inspection data, current maintenance planning decisions for deficient bridges are based on data from subjective condition assessments and do not consider the reliability of bridge components and systems. Recently, reliability-based optimum maintenance planning strategies have been developed. They can be used to predict inspection and repair times to achieve minimum life-cycle cost of deteriorating structural systems. In this study, a reliability-based methodology which takes into account loading randomness and history, and randomness in strength and degradation resulting from aggressive environmental factors, is used to predict the time- dependent reliability of aging highway bridges. A methodology for incorporating inspection data into reliability predictions is also presented. Finally, optimal lifetime maintenance strategies are identified, in which optimal inspection/repair times are found based on minimum expected life-cycle cost under prescribed reliability constraints. The influence of discount rate on optimum solutions is evaluated.

  18. A risk-related preventive maintenance system.

    PubMed

    Anderson, J T

    1992-01-01

    Recent changes in attitudes concerning medical equipment maintenance place more responsibility for planning appropriate levels of maintenance on the clinical engineer and biomedical equipment technician. A system is described in which maintenance decisions are based on the effects of equipment failure on quality of patient care and potential for injury to patients and staff. It is hoped that development of an acceptable classification scheme will simplify maintenance decisions. Such a system will provide levels of maintenance appropriate to the equipment function in patient care. PMID:10117005

  19. Optimal Assignment Methods in Three-Form Planned Missing Data Designs for Longitudinal Panel Studies

    ERIC Educational Resources Information Center

    Jorgensen, Terrence D.; Rhemtulla, Mijke; Schoemann, Alexander; McPherson, Brent; Wu, Wei; Little, Todd D.

    2014-01-01

    Planned missing designs are becoming increasingly popular, but because there is no consensus on how to implement them in longitudinal research, we simulated longitudinal data to distinguish between strategies of assigning items to forms and of assigning forms to participants across measurement occasions. Using relative efficiency as the criterion,…

  20. Multi-optimization Criteria-based Robot Behavioral Adaptability and Motion Planning

    SciTech Connect

    Pin, Grancois G.

    2004-06-01

    Our overall objective is the development of a generalized methodology and code for the automated generation of the kinematics equations of robots and for the analytical solution of their motion planning equations subject to time-varying constraints, behavioral objectives, and modular configuration.