Waste collection multi objective model with real time traceability data.

PubMed

Faccio, Maurizio; Persona, Alessandro; Zanin, Giorgia

2011-12-01

Waste collection is a highly visible municipal service that involves large expenditures and difficult operational problems, plus it is expensive to operate in terms of investment costs (i.e. vehicles fleet), operational costs (i.e. fuel, maintenances) and environmental costs (i.e. emissions, noise and traffic congestions). Modern traceability devices, like volumetric sensors, identification RFID (Radio Frequency Identification) systems, GPRS (General Packet Radio Service) and GPS (Global Positioning System) technology, permit to obtain data in real time, which is fundamental to implement an efficient and innovative waste collection routing model. The basic idea is that knowing the real time data of each vehicle and the real time replenishment level at each bin makes it possible to decide, in function of the waste generation pattern, what bin should be emptied and what should not, optimizing different aspects like the total covered distance, the necessary number of vehicles and the environmental impact. This paper describes a framework about the traceability technology available in the optimization of solid waste collection, and introduces an innovative vehicle routing model integrated with the real time traceability data, starting the application in an Italian city of about 100,000 inhabitants. The model is tested and validated using simulation and an economical feasibility study is reported at the end of the paper. Copyright © 2011 Elsevier Ltd. All rights reserved.

Dynamic ADMM for Real-Time Optimal Power Flow

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

Dall-Anese, Emiliano; Zhang, Yijian; Hong, Mingyi

This paper considers distribution networks featuring distributed energy resources (DERs), and develops a dynamic optimization method to maximize given operational objectives in real time while adhering to relevant network constraints. The design of the dynamic algorithm is based on suitable linearization of the AC power flow equations, and it leverages the so-called alternating direction method of multipliers (ADMM). The steps of the ADMM, however, are suitably modified to accommodate appropriate measurements from the distribution network and the DERs. With the aid of these measurements, the resultant algorithm can enforce given operational constraints in spite of inaccuracies in the representation ofmore » the AC power flows, and it avoids ubiquitous metering to gather the state of noncontrollable resources. Optimality and convergence of the proposed algorithm are established in terms of tracking of the solution of a convex surrogate of the AC optimal power flow problem.« less

Dynamic ADMM for Real-Time Optimal Power Flow: Preprint

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

Dall-Anese, Emiliano; Zhang, Yijian; Hong, Mingyi

This paper considers distribution networks featuring distributed energy resources (DERs), and develops a dynamic optimization method to maximize given operational objectives in real time while adhering to relevant network constraints. The design of the dynamic algorithm is based on suitable linearizations of the AC power flow equations, and it leverages the so-called alternating direction method of multipliers (ADMM). The steps of the ADMM, however, are suitably modified to accommodate appropriate measurements from the distribution network and the DERs. With the aid of these measurements, the resultant algorithm can enforce given operational constraints in spite of inaccuracies in the representation ofmore » the AC power flows, and it avoids ubiquitous metering to gather the state of non-controllable resources. Optimality and convergence of the propose algorithm are established in terms of tracking of the solution of a convex surrogate of the AC optimal power flow problem.« less

Metallurgical Plant Optimization Through the use of Flowsheet Simulation Modelling

NASA Astrophysics Data System (ADS)

Kennedy, Mark William

Modern metallurgical plants typically have complex flowsheets and operate on a continuous basis. Real time interactions within such processes can be complex and the impacts of streams such as recycles on process efficiency and stability can be highly unexpected prior to actual operation. Current desktop computing power, combined with state-of-the-art flowsheet simulation software like Metsim, allow for thorough analysis of designs to explore the interaction between operating rate, heat and mass balances and in particular the potential negative impact of recycles. Using plant information systems, it is possible to combine real plant data with simple steady state models, using dynamic data exchange links to allow for near real time de-bottlenecking of operations. Accurate analytical results can also be combined with detailed unit operations models to allow for feed-forward model-based-control. This paper will explore some examples of the application of Metsim to real world engineering and plant operational issues.

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

NASA Astrophysics Data System (ADS)

Asvini, M. Sakthi; Amudha, T.

2017-12-01

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

THE CHOICE OF REAL-TIME CONTROL STRATEGY FOR COMBINED SEWER OVERFLOW CONTROL

EPA Science Inventory

This paper focuses on the strategies used to operate a collection system in real-time control (RTC) in order to optimize use of system capacity and to reduce the cost of long-term combined sewer overflow (CSO) control. Three RTC strategies were developed and analyzed based on the...

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

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

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

2015-06-15

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

Optimized positioning of autonomous surgical lamps

NASA Astrophysics Data System (ADS)

Teuber, Jörn; Weller, Rene; Kikinis, Ron; Oldhafer, Karl-Jürgen; Lipp, Michael J.; Zachmann, Gabriel

2017-03-01

We consider the problem of finding automatically optimal positions of surgical lamps throughout the whole surgical procedure, where we assume that future lamps could be robotized. We propose a two-tiered optimization technique for the real-time autonomous positioning of those robotized surgical lamps. Typically, finding optimal positions for surgical lamps is a multi-dimensional problem with several, in part conflicting, objectives, such as optimal lighting conditions at every point in time while minimizing the movement of the lamps in order to avoid distractions of the surgeon. Consequently, we use multi-objective optimization (MOO) to find optimal positions in real-time during the entire surgery. Due to the conflicting objectives, there is usually not a single optimal solution for such kinds of problems, but a set of solutions that realizes a Pareto-front. When our algorithm selects a solution from this set it additionally has to consider the individual preferences of the surgeon. This is a highly non-trivial task because the relationship between the solution and the parameters is not obvious. We have developed a novel meta-optimization that considers exactly this challenge. It delivers an easy to understand set of presets for the parameters and allows a balance between the lamp movement and lamp obstruction. This metaoptimization can be pre-computed for different kinds of operations and it then used by our online optimization for the selection of the appropriate Pareto solution. Both optimization approaches use data obtained by a depth camera that captures the surgical site but also the environment around the operating table. We have evaluated our algorithms with data recorded during a real open abdominal surgery. It is available for use for scientific purposes. The results show that our meta-optimization produces viable parameter sets for different parts of an intervention even when trained on a small portion of it.

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

NASA Technical Reports Server (NTRS)

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

1995-01-01

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

Solving Energy-Aware Real-Time Tasks Scheduling Problem with Shuffled Frog Leaping Algorithm on Heterogeneous Platforms

PubMed Central

Zhang, Weizhe; Bai, Enci; He, Hui; Cheng, Albert M.K.

2015-01-01

Reducing energy consumption is becoming very important in order to keep battery life and lower overall operational costs for heterogeneous real-time multiprocessor systems. In this paper, we first formulate this as a combinatorial optimization problem. Then, a successful meta-heuristic, called Shuffled Frog Leaping Algorithm (SFLA) is proposed to reduce the energy consumption. Precocity remission and local optimal avoidance techniques are proposed to avoid the precocity and improve the solution quality. Convergence acceleration significantly reduces the search time. Experimental results show that the SFLA-based energy-aware meta-heuristic uses 30% less energy than the Ant Colony Optimization (ACO) algorithm, and 60% less energy than the Genetic Algorithm (GA) algorithm. Remarkably, the running time of the SFLA-based meta-heuristic is 20 and 200 times less than ACO and GA, respectively, for finding the optimal solution. PMID:26110406

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Integrating a Typhoon Event Database with an Optimal Flood Operation Model on the Real-Time Flood Control of the Tseng-Wen Reservoir

NASA Astrophysics Data System (ADS)

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

2012-04-01

Typhoons which normally bring a great amount of precipitation are the primary natural hazard in Taiwan during flooding season. Because the plentiful rainfall quantities brought by typhoons are normally stored for the usage of the next draught period, the determination of release strategies for flood operation of reservoirs which is required to simultaneously consider not only the impact of reservoir safety and the flooding damage in plain area but also for the water resource stored in the reservoir after typhoon becomes important. This study proposes a two-steps study process. First, this study develop an optimal flood operation model (OFOM) for the planning of flood control and also applies the OFOM on Tseng-wun reservoir and the downstream plain related to the reservoir. Second, integrating a typhoon event database with the OFOM mentioned above makes the proposed planning model have ability to deal with a real-time flood control problem and names as real-time flood operation model (RTFOM). Three conditions are considered in the proposed models, OFOM and RTFOM, include the safety of the reservoir itself, the reservoir storage after typhoons and the impact of flooding in the plain area. Besides, the flood operation guideline announced by government is also considered in the proposed models. The these conditions and the guideline can be formed as an optimization problem which is solved by the genetic algorithm (GA) in this study. Furthermore, a distributed runoff model, kinematic-wave geomorphic instantaneous unit hydrograph (KW-GIUH), and a river flow simulation model, HEC-RAS, are used to simulate the river water level of Tseng-wun basin in the plain area and the simulated level is shown as an index of the impact of flooding. Because the simulated levels are required to re-calculate iteratively in the optimization model, applying a recursive artificial neural network (recursive ANN) instead of the HEC-RAS model can significantly reduce the computational burden of the entire optimization problem. This study applies the developed methodology to Tseng-wun Reservoir. Forty typhoon events are collected as the historical database and six typhoon events are used to verify the proposed model. These typhoons include Typhoon Sepat and Typhoon Korsa in 2007 and Typhoon Kalmaegi, Typhoon Fung-Wong, Typhoon Sinlaku and Typhoon Jangmi in 2008. The results show that the proposed model can reduce the flood duration at the downstream area. For example, the real-time flood control model can reduce the flood duration by four and three hours for Typhoon Korsa and Typhoon Sinlaku respectively. This results indicate that the developed model can be a very useful tool for real-time flood control operation of reservoirs.

Real-time image reconstruction and display system for MRI using a high-speed personal computer.

PubMed

Haishi, T; Kose, K

1998-09-01

A real-time NMR image reconstruction and display system was developed using a high-speed personal computer and optimized for the 32-bit multitasking Microsoft Windows 95 operating system. The system was operated at various CPU clock frequencies by changing the motherboard clock frequency and the processor/bus frequency ratio. When the Pentium CPU was used at the 200 MHz clock frequency, the reconstruction time for one 128 x 128 pixel image was 48 ms and that for the image display on the enlarged 256 x 256 pixel window was about 8 ms. NMR imaging experiments were performed with three fast imaging sequences (FLASH, multishot EPI, and one-shot EPI) to demonstrate the ability of the real-time system. It was concluded that in most cases, high-speed PC would be the best choice for the image reconstruction and display system for real-time MRI. Copyright 1998 Academic Press.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Real-Time Dynamic Modeling - Data Information Requirements and Flight Test Results

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.; Smith, Mark S.

2008-01-01

Practical aspects of identifying dynamic models for aircraft in real time were studied. Topics include formulation of an equation-error method in the frequency domain to estimate non-dimensional stability and control derivatives in real time, data information content for accurate modeling results, and data information management techniques such as data forgetting, incorporating prior information, and optimized excitation. Real-time dynamic modeling was applied to simulation data and flight test data from a modified F-15B fighter aircraft, and to operational flight data from a subscale jet transport aircraft. Estimated parameter standard errors and comparisons with results from a batch output-error method in the time domain were used to demonstrate the accuracy of the identified real-time models.

Real-Time Dynamic Modeling - Data Information Requirements and Flight Test Results

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.; Smith, Mark S.

2010-01-01

Practical aspects of identifying dynamic models for aircraft in real time were studied. Topics include formulation of an equation-error method in the frequency domain to estimate non-dimensional stability and control derivatives in real time, data information content for accurate modeling results, and data information management techniques such as data forgetting, incorporating prior information, and optimized excitation. Real-time dynamic modeling was applied to simulation data and flight test data from a modified F-15B fighter aircraft, and to operational flight data from a subscale jet transport aircraft. Estimated parameter standard errors, prediction cases, and comparisons with results from a batch output-error method in the time domain were used to demonstrate the accuracy of the identified real-time models.

Optimization and planning of operating theatre activities: an original definition of pathways and process modeling.

PubMed

Barbagallo, Simone; Corradi, Luca; de Ville de Goyet, Jean; Iannucci, Marina; Porro, Ivan; Rosso, Nicola; Tanfani, Elena; Testi, Angela

2015-05-17

The Operating Room (OR) is a key resource of all major hospitals, but it also accounts for up 40% of resource costs. Improving cost effectiveness, while maintaining a quality of care, is a universal objective. These goals imply an optimization of planning and a scheduling of the activities involved. This is highly challenging due to the inherent variable and unpredictable nature of surgery. A Business Process Modeling Notation (BPMN 2.0) was used for the representation of the "OR Process" (being defined as the sequence of all of the elementary steps between "patient ready for surgery" to "patient operated upon") as a general pathway ("path"). The path was then both further standardized as much as possible and, at the same time, keeping all of the key-elements that would allow one to address or define the other steps of planning, and the inherent and wide variability in terms of patient specificity. The path was used to schedule OR activity, room-by-room, and day-by-day, feeding the process from a "waiting list database" and using a mathematical optimization model with the objective of ending up in an optimized planning. The OR process was defined with special attention paid to flows, timing and resource involvement. Standardization involved a dynamics operation and defined an expected operating time for each operation. The optimization model has been implemented and tested on real clinical data. The comparison of the results reported with the real data, shows that by using the optimization model, allows for the scheduling of about 30% more patients than in actual practice, as well as to better exploit the OR efficiency, increasing the average operating room utilization rate up to 20%. The optimization of OR activity planning is essential in order to manage the hospital's waiting list. Optimal planning is facilitated by defining the operation as a standard pathway where all variables are taken into account. By allowing a precise scheduling, it feeds the process of planning and, further up-stream, the management of a waiting list in an interactive and bi-directional dynamic process.

Alpha: A real-time decentralized operating system for mission-oriented system integration and operation

NASA Technical Reports Server (NTRS)

Jensen, E. Douglas

1988-01-01

Alpha is a new kind of operating system that is unique in two highly significant ways. First, it is decentralized transparently providing reliable resource management across physically dispersed nodes, so that distributed applications programming can be done largely as though it were centralized. And second, it provides comprehensive, high technology support for real-time system integration and operation, an application area which consists predominately of aperiodic activities having critical time constraints such as deadlines. Alpha is extremely adaptable so that it can be easily optimized for a wide range of problem-specific functionality, performance, and cost. Alpha is the first systems effort of the Archons Project, and the prototype was created at Carnegie-Mellon University directly on modified Sun multiprocessor workstation hardware. It has been demonstrated with a real-time C(sup 2) application. Continuing research is leading to a series of enhanced follow-ons to Alpha; these are portable but initially hosted on Concurrent's MASSCOMP line of multiprocessor products.

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

NASA Technical Reports Server (NTRS)

Momoh, James; Chattopadhyay, Deb; Elfayoumy, Mahmoud

1996-01-01

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

Real option valuation of a decremental regulation service provided by electricity storage.

PubMed

Szabó, Dávid Zoltán; Martyr, Randall

2017-08-13

This paper is a quantitative study of a reserve contract for real-time balancing of a power system. Under this contract, the owner of a storage device, such as a battery, helps smooth fluctuations in electricity demand and supply by using the device to increase electricity consumption. The battery owner must be able to provide immediate physical cover, and should therefore have sufficient storage available in the battery before entering the contract. Accordingly, the following problem can be formulated for the battery owner: determine the optimal time to enter the contract and, if necessary, the optimal time to discharge electricity before entering the contract. This problem is formulated as one of optimal stopping, and is solved explicitly in terms of the model parameters and instantaneous values of the power system imbalance. The optimal operational strategies thus obtained ensure that the battery owner has positive expected economic profit from the contract. Furthermore, they provide explicit conditions under which the optimal discharge time is consistent with the overall objective of power system balancing. This paper also carries out a preliminary investigation of the 'lifetime value' aggregated from an infinite sequence of these balancing reserve contracts. This lifetime value, which can be viewed as a single project valuation of the battery, is shown to be positive and bounded. Therefore, in the long run such reserve contracts can be beneficial to commercial operators of electricity storage, while reducing some of the financial and operational risks in power system balancing.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'. © 2017 The Author(s).

Human operator identification model and related computer programs

NASA Technical Reports Server (NTRS)

Kessler, K. M.; Mohr, J. N.

1978-01-01

Four computer programs which provide computational assistance in the analysis of man/machine systems are reported. The programs are: (1) Modified Transfer Function Program (TF); (2) Time Varying Response Program (TVSR); (3) Optimal Simulation Program (TVOPT); and (4) Linear Identification Program (SCIDNT). The TV program converts the time domain state variable system representative to frequency domain transfer function system representation. The TVSR program computes time histories of the input/output responses of the human operator model. The TVOPT program is an optimal simulation program and is similar to TVSR in that it produces time histories of system states associated with an operator in the loop system. The differences between the two programs are presented. The SCIDNT program is an open loop identification code which operates on the simulated data from TVOPT (or TVSR) or real operator data from motion simulators.

Optimizing real-time Web-based user interfaces for observatories

NASA Astrophysics Data System (ADS)

Gibson, J. Duane; Pickering, Timothy E.; Porter, Dallan; Schaller, Skip

2008-08-01

In using common HTML/Ajax approaches for web-based data presentation and telescope control user interfaces at the MMT Observatory (MMTO), we rapidly were confronted with web browser performance issues. Much of the operational data at the MMTO is highly dynamic and is constantly changing during normal operations. Status of telescope subsystems must be displayed with minimal latency to telescope operators and other users. A major motivation of migrating toward web-based applications at the MMTO is to provide easy access to current and past observatory subsystem data for a wide variety of users on their favorite operating system through a familiar interface, their web browser. Performance issues, especially for user interfaces that control telescope subsystems, led to investigations of more efficient use of HTML/Ajax and web server technologies as well as other web-based technologies, such as Java and Flash/Flex. The results presented here focus on techniques for optimizing HTML/Ajax web applications with near real-time data display. This study indicates that direct modification of the contents or "nodeValue" attribute of text nodes is the most efficient method of updating data values displayed on a web page. Other optimization techniques are discussed for web-based applications that display highly dynamic data.

A two-stage method of quantitative flood risk analysis for reservoir real-time operation using ensemble-based hydrologic forecasts

NASA Astrophysics Data System (ADS)

Liu, P.

2013-12-01

Quantitative analysis of the risk for reservoir real-time operation is a hard task owing to the difficulty of accurate description of inflow uncertainties. The ensemble-based hydrologic forecasts directly depict the inflows not only the marginal distributions but also their persistence via scenarios. This motivates us to analyze the reservoir real-time operating risk with ensemble-based hydrologic forecasts as inputs. A method is developed by using the forecast horizon point to divide the future time into two stages, the forecast lead-time and the unpredicted time. The risk within the forecast lead-time is computed based on counting the failure number of forecast scenarios, and the risk in the unpredicted time is estimated using reservoir routing with the design floods and the reservoir water levels of forecast horizon point. As a result, a two-stage risk analysis method is set up to quantify the entire flood risks by defining the ratio of the number of scenarios that excessive the critical value to the total number of scenarios. The China's Three Gorges Reservoir (TGR) is selected as a case study, where the parameter and precipitation uncertainties are implemented to produce ensemble-based hydrologic forecasts. The Bayesian inference, Markov Chain Monte Carlo, is used to account for the parameter uncertainty. Two reservoir operation schemes, the real operated and scenario optimization, are evaluated for the flood risks and hydropower profits analysis. With the 2010 flood, it is found that the improvement of the hydrologic forecast accuracy is unnecessary to decrease the reservoir real-time operation risk, and most risks are from the forecast lead-time. It is therefore valuable to decrease the avarice of ensemble-based hydrologic forecasts with less bias for a reservoir operational purpose.

Timing characterization and analysis of the Linux-based, closed loop control computer for the Subaru Telescope laser guide star adaptive optics system

NASA Astrophysics Data System (ADS)

Dinkins, Matthew; Colley, Stephen

2008-07-01

Hardware and software specialized for real time control reduce the timing jitter of executables when compared to off-the-shelf hardware and software. However, these specialized environments are costly in both money and development time. While conventional systems have a cost advantage, the jitter in these systems is much larger and potentially problematic. This study analyzes the timing characterstics of a standard Dell server running a fully featured Linux operating system to determine if such a system would be capable of meeting the timing requirements for closed loop operations. Investigations are preformed on the effectiveness of tools designed to make off-the-shelf system performance closer to specialized real time systems. The Gnu Compiler Collection (gcc) is compared to the Intel C Compiler (icc), compiler optimizations are investigated, and real-time extensions to Linux are evaluated.

Real - time Optimization of Distributed Energy Storage System Operation Strategy Based on Peak Load Shifting

NASA Astrophysics Data System (ADS)

Wang, Qian; Lu, Guangqi; Li, Xiaoyu; Zhang, Yichi; Yun, Zejian; Bian, Di

2018-01-01

To take advantage of the energy storage system (ESS) sufficiently, the factors that the service life of the distributed energy storage system (DESS) and the load should be considered when establishing optimization model. To reduce the complexity of the load shifting of DESS in the solution procedure, the loss coefficient and the equal capacity ratio distribution principle were adopted in this paper. Firstly, the model was established considering the constraint conditions of the cycles, depth, power of the charge-discharge of the ESS, the typical daily load curves, as well. Then, dynamic programming method was used to real-time solve the model in which the difference of power Δs, the real-time revised energy storage capacity Sk and the permission error of depth of charge-discharge were introduced to optimize the solution process. The simulation results show that the optimized results was achieved when the load shifting in the load variance was not considered which means the charge-discharge of the energy storage system was not executed. In the meantime, the service life of the ESS would increase.

Real-Time Optimization and Control of Next-Generation Distribution

Science.gov Websites

Infrastructure | Grid Modernization | NREL Real-Time Optimization and Control of Next -Generation Distribution Infrastructure Real-Time Optimization and Control of Next-Generation Distribution Infrastructure This project develops innovative, real-time optimization and control methods for next-generation

ANN based Real-Time Estimation of Power Generation of Different PV Module Types

NASA Astrophysics Data System (ADS)

Syafaruddin; Karatepe, Engin; Hiyama, Takashi

Distributed generation is expected to become more important in the future generation system. Utilities need to find solutions that help manage resources more efficiently. Effective smart grid solutions have been experienced by using real-time data to help refine and pinpoint inefficiencies for maintaining secure and reliable operating conditions. This paper proposes the application of Artificial Neural Network (ANN) for the real-time estimation of the maximum power generation of PV modules of different technologies. An intelligent technique is necessary required in this case due to the relationship between the maximum power of PV modules and the open circuit voltage and temperature is nonlinear and can't be easily expressed by an analytical expression for each technology. The proposed ANN method is using input signals of open circuit voltage and cell temperature instead of irradiance and ambient temperature to determine the estimated maximum power generation of PV modules. It is important for the utility to have the capability to perform this estimation for optimal operating points and diagnostic purposes that may be an early indicator of a need for maintenance and optimal energy management. The proposed method is accurately verified through a developed real-time simulator on the daily basis of irradiance and cell temperature changes.

Modelling energy costs for different operational strategies of a large water resource recovery facility.

PubMed

Póvoa, P; Oehmen, A; Inocêncio, P; Matos, J S; Frazão, A

2017-05-01

The main objective of this paper is to demonstrate the importance of applying dynamic modelling and real energy prices on a full scale water resource recovery facility (WRRF) for the evaluation of control strategies in terms of energy costs with aeration. The Activated Sludge Model No. 1 (ASM1) was coupled with real energy pricing and a power consumption model and applied as a dynamic simulation case study. The model calibration is based on the STOWA protocol. The case study investigates the importance of providing real energy pricing comparing (i) real energy pricing, (ii) weighted arithmetic mean energy pricing and (iii) arithmetic mean energy pricing. The operational strategies evaluated were (i) old versus new air diffusers, (ii) different DO set-points and (iii) implementation of a carbon removal controller based on nitrate sensor readings. The application in a full scale WRRF of the ASM1 model coupled with real energy costs was successful. Dynamic modelling with real energy pricing instead of constant energy pricing enables the wastewater utility to optimize energy consumption according to the real energy price structure. Specific energy cost allows the identification of time periods with potential for linking WRRF with the electric grid to optimize the treatment costs, satisfying operational goals.

Path Planning For A Class Of Cutting Operations

NASA Astrophysics Data System (ADS)

Tavora, Jose

1989-03-01

Optimizing processing time in some contour-cutting operations requires solving the so-called no-load path problem. This problem is formulated and an approximate resolution method (based on heuristic search techniques) is described. Results for real-life instances (clothing layouts in the apparel industry) are presented and evaluated.

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

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

Interlaced photoacoustic and ultrasound imaging system with real-time coregistration for ovarian tissue characterization

NASA Astrophysics Data System (ADS)

Alqasemi, Umar; Li, Hai; Yuan, Guangqian; Kumavor, Patrick; Zanganeh, Saeid; Zhu, Quing

2014-07-01

Coregistered ultrasound (US) and photoacoustic imaging are emerging techniques for mapping the echogenic anatomical structure of tissue and its corresponding optical absorption. We report a 128-channel imaging system with real-time coregistration of the two modalities, which provides up to 15 coregistered frames per second limited by the laser pulse repetition rate. In addition, the system integrates a compact transvaginal imaging probe with a custom-designed fiber optic assembly for in vivo detection and characterization of human ovarian tissue. We present the coregistered US and photoacoustic imaging system structure, the optimal design of the PC interfacing software, and the reconfigurable field programmable gate array operation and optimization. Phantom experiments of system lateral resolution and axial sensitivity evaluation, examples of the real-time scanning of a tumor-bearing mouse, and ex vivo human ovaries studies are demonstrated.

Real-time maneuver optimization of space-based robots in a dynamic environment: Theory and on-orbit experiments

NASA Astrophysics Data System (ADS)

Chamitoff, Gregory E.; Saenz-Otero, Alvar; Katz, Jacob G.; Ulrich, Steve; Morrell, Benjamin J.; Gibbens, Peter W.

2018-01-01

This paper presents the development of a real-time path-planning optimization approach to controlling the motion of space-based robots. The algorithm is capable of planning three dimensional trajectories for a robot to navigate within complex surroundings that include numerous static and dynamic obstacles, path constraints and performance limitations. The methodology employs a unique transformation that enables rapid generation of feasible solutions for complex geometries, making it suitable for application to real-time operations and dynamic environments. This strategy was implemented on the Synchronized Position Hold Engage Reorient Experimental Satellite (SPHERES) test-bed on the International Space Station (ISS), and experimental testing was conducted onboard the ISS during Expedition 17 by the first author. Lessons learned from the on-orbit tests were used to further refine the algorithm for future implementations.

A real-time hybrid neuron network for highly parallel cognitive systems.

PubMed

Christiaanse, Gerrit Jan; Zjajo, Amir; Galuzzi, Carlo; van Leuken, Rene

2016-08-01

For comprehensive understanding of how neurons communicate with each other, new tools need to be developed that can accurately mimic the behaviour of such neurons and neuron networks under `real-time' constraints. In this paper, we propose an easily customisable, highly pipelined, neuron network design, which executes optimally scheduled floating-point operations for maximal amount of biophysically plausible neurons per FPGA family type. To reduce the required amount of resources without adverse effect on the calculation latency, a single exponent instance is used for multiple neuron calculation operations. Experimental results indicate that the proposed network design allows the simulation of up to 1188 neurons on Virtex7 (XC7VX550T) device in brain real-time yielding a speed-up of x12.4 compared to the state-of-the art.

Optimization of dynamic soaring maneuvers to enhance endurance of a versatile UAV

NASA Astrophysics Data System (ADS)

Mir, Imran; Maqsood, Adnan; Akhtar, Suhail

2017-06-01

Dynamic soaring is a process of acquiring energy available in atmospheric wind shears and is commonly exhibited by soaring birds to perform long distance flights. This paper aims to demonstrate a viable algorithm which can be implemented in near real time environment to formulate optimal trajectories for dynamic soaring maneuvers for a small scale Unmanned Aerial Vehicle (UAV). The objective is to harness maximum energy from atmosphere wind shear to improve loiter time for Intelligence, Surveillance and Reconnaissance (ISR) missions. Three-dimensional point-mass UAV equations of motion and linear wind gradient profile are used to model flight dynamics. Utilizing UAV states, controls, operational constraints, initial and terminal conditions that enforce a periodic flight, dynamic soaring problem is formulated as an optimal control problem. Optimized trajectories of the maneuver are subsequently generated employing pseudo spectral techniques against distant UAV performance parameters. The discussion also encompasses the requirement for generation of optimal trajectories for dynamic soaring in real time environment and the ability of the proposed algorithm for speedy solution generation. Coupled with the fact that dynamic soaring is all about immediately utilizing the available energy from the wind shear encountered, the proposed algorithm promises its viability for practical on board implementations requiring computation of trajectories in near real time.

Optimal Power Flow Pursuit

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

Dall'Anese, Emiliano; Simonetto, Andrea

This paper considers distribution networks featuring inverter-interfaced distributed energy resources, and develops distributed feedback controllers that continuously drive the inverter output powers to solutions of AC optimal power flow (OPF) problems. Particularly, the controllers update the power setpoints based on voltage measurements as well as given (time-varying) OPF targets, and entail elementary operations implementable onto low-cost microcontrollers that accompany power-electronics interfaces of gateways and inverters. The design of the control framework is based on suitable linear approximations of the AC power-flow equations as well as Lagrangian regularization methods. Convergence and OPF-target tracking capabilities of the controllers are analytically established. Overall,more » the proposed method allows to bypass traditional hierarchical setups where feedback control and optimization operate at distinct time scales, and to enable real-time optimization of distribution systems.« less

Use telecommunications for real-time process control

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

Zilberman, I.; Bigman, J.; Sela, I.

1996-05-01

Process operators design real-time accurate information to monitor and control product streams and to optimize unit operations. The challenge is how to cost-effectively install sophisticated analytical equipment in harsh environments such as process areas and maintain system reliability. Incorporating telecommunications technology with near infrared (NIR) spectroscopy may be the bridge to help operations achieve their online control goals. Coupling communications fiber optics with NIR analyzers enables the probe and sampling system to remain in the field and crucial analytical equipment to be remotely located in a general purpose area without specialized protection provisions. The case histories show how two refineriesmore » used NIR spectroscopy online to track octane levels for reformate streams.« less

Model Predictive Control application for real time operation of controlled structures for the Water Authority Noorderzijlvest, The Netherlands

NASA Astrophysics Data System (ADS)

van Heeringen, Klaas-Jan; Gooijer, Jan; Knot, Floris; Talsma, Jan

2015-04-01

In the Netherlands, flood protection has always been a key issue to protect settlements against storm surges and riverine floods. Whereas flood protection traditionally focused on structural measures, nowadays the availability of meteorological and hydrological forecasts enable the application of more advanced real-time control techniques for operating the existing hydraulic infrastructure in an anticipatory and more efficient way. Model Predictive Control (MPC) is a powerful technique to derive optimal control variables with the help of model based predictions evaluated against a control objective. In a project for the regional water authority Noorderzijlvest in the north of the Netherlands, it has been shown that MPC can increase the safety level of the system during flood events by an anticipatory pre-release of water. Furthermore, energy costs of pumps can be reduced by making tactical use of the water storage and shifting pump activities during normal operating conditions to off-peak hours. In this way cheap energy is used in combination of gravity flow through gates during low tide periods. MPC has now been implemented for daily operational use of the whole water system of the water authority Noorderzijlvest. The system developed to a real time decision support system which not only supports the daily operation but is able to directly implement the optimal control settings at the structures. We explain how we set-up and calibrated a prediction model (RTC-Tools) that is accurate and fast enough for optimization purposes, and how we integrated it in the operational flood early warning system (Delft-FEWS). Beside the prediction model, the weights and the factors of the objective function are an important element of MPC, since they shape the control objective. We developed special features in Delft-FEWS to allow the operators to adjust the objective function in order to meet changing requirements and to evaluate different control strategies.

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

NASA Astrophysics Data System (ADS)

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

2005-04-01

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

A decision support system for real-time hydropower scheduling in a competitive power market environment

NASA Astrophysics Data System (ADS)

Shawwash, Ziad Khaled Elias

2000-10-01

The electricity supply market is rapidly changing from a monopolistic to a competitive environment. Being able to operate their system of reservoirs and generating facilities to get maximum benefits out of existing assets and resources is important to the British Columbia Hydro Authority (B.C. Hydro). A decision support system has been developed to help B.C. Hydro operate their system in an optimal way. The system is operational and is one of the tools that are currently used by the B.C. Hydro system operations engineers to determine optimal schedules that meet the hourly domestic load and also maximize the value B.C. Hydro obtains from spot transactions in the Western U.S. and Alberta electricity markets. This dissertation describes the development and implementation of the decision support system in production mode. The decision support system consists of six components: the input data preparation routines, the graphical user interface (GUI), the communication protocols, the hydraulic simulation model, the optimization model, and the results display software. A major part of this work involved the development and implementation of a practical and detailed large-scale optimization model that determines the optimal tradeoff between the long-term value of water and the returns from spot trading transactions in real-time operations. The postmortem-testing phase showed that the gains in value from using the model accounted for 0.25% to 1.0% of the revenues obtained. The financial returns from using the decision support system greatly outweigh the costs of building it. Other benefits are the savings in the time needed to prepare the generation and trading schedules. The system operations engineers now can use the time saved to focus on other important aspects of their job. The operators are currently experimenting with the system in production mode, and are gradually gaining confidence that the advice it provides is accurate, reliable and sensible. The main lesson learned from developing and implementing the system was that there is no alternative to working very closely with the intended end-users of the system, and with the people who have deep knowledge, experience and understanding of how the system is and should be operated.

On optimal infinite impulse response edge detection filters

NASA Technical Reports Server (NTRS)

Sarkar, Sudeep; Boyer, Kim L.

1991-01-01

The authors outline the design of an optimal, computationally efficient, infinite impulse response edge detection filter. The optimal filter is computed based on Canny's high signal to noise ratio, good localization criteria, and a criterion on the spurious response of the filter to noise. An expression for the width of the filter, which is appropriate for infinite-length filters, is incorporated directly in the expression for spurious responses. The three criteria are maximized using the variational method and nonlinear constrained optimization. The optimal filter parameters are tabulated for various values of the filter performance criteria. A complete methodology for implementing the optimal filter using approximating recursive digital filtering is presented. The approximating recursive digital filter is separable into two linear filters operating in two orthogonal directions. The implementation is very simple and computationally efficient, has a constant time of execution for different sizes of the operator, and is readily amenable to real-time hardware implementation.

Feedback-Based Projected-Gradient Method for Real-Time Optimization of Aggregations of Energy Resources

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

Dall-Anese, Emiliano; Bernstein, Andrey; Simonetto, Andrea

This paper develops an online optimization method to maximize operational objectives of distribution-level distributed energy resources (DERs), while adjusting the aggregate power generated (or consumed) in response to services requested by grid operators. The design of the online algorithm is based on a projected-gradient method, suitably modified to accommodate appropriate measurements from the distribution network and the DERs. By virtue of this approach, the resultant algorithm can cope with inaccuracies in the representation of the AC power flows, it avoids pervasive metering to gather the state of noncontrollable resources, and it naturally lends itself to a distributed implementation. Optimality claimsmore » are established in terms of tracking of the solution of a well-posed time-varying convex optimization problem.« less

Feedback-Based Projected-Gradient Method For Real-Time Optimization of Aggregations of Energy Resources: Preprint

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

Dall-Anese, Emiliano; Bernstein, Andrey; Simonetto, Andrea

This paper develops an online optimization method to maximize the operational objectives of distribution-level distributed energy resources (DERs) while adjusting the aggregate power generated (or consumed) in response to services requested by grid operators. The design of the online algorithm is based on a projected-gradient method, suitably modified to accommodate appropriate measurements from the distribution network and the DERs. By virtue of this approach, the resultant algorithm can cope with inaccuracies in the representation of the AC power, it avoids pervasive metering to gather the state of noncontrollable resources, and it naturally lends itself to a distributed implementation. Optimality claimsmore » are established in terms of tracking of the solution of a well-posed time-varying optimization problem.« less

Optimizing the real-time automatic location of the events produced in Romania using an advanced processing system

NASA Astrophysics Data System (ADS)

Neagoe, Cristian; Grecu, Bogdan; Manea, Liviu

2016-04-01

National Institute for Earth Physics (NIEP) operates a real time seismic network which is designed to monitor the seismic activity on the Romanian territory, which is dominated by the intermediate earthquakes (60-200 km) from Vrancea area. The ability to reduce the impact of earthquakes on society depends on the existence of a large number of high-quality observational data. The development of the network in recent years and an advanced seismic acquisition are crucial to achieving this objective. The software package used to perform the automatic real-time locations is Seiscomp3. An accurate choice of the Seiscomp3 setting parameters is necessary to ensure the best performance of the real-time system i.e., the most accurate location for the earthquakes and avoiding any false events. The aim of this study is to optimize the algorithms of the real-time system that detect and locate the earthquakes in the monitored area. This goal is pursued by testing different parameters (e.g., STA/LTA, filters applied to the waveforms) on a data set of representative earthquakes of the local seismicity. The results are compared with the locations from the Romanian Catalogue ROMPLUS.

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

NASA Technical Reports Server (NTRS)

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

1989-01-01

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

An Incentive-based Online Optimization Framework for Distribution Grids

DOE PAGES

Zhou, Xinyang; Dall'Anese, Emiliano; Chen, Lijun; ...

2017-10-09

This article formulates a time-varying social-welfare maximization problem for distribution grids with distributed energy resources (DERs) and develops online distributed algorithms to identify (and track) its solutions. In the considered setting, network operator and DER-owners pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. The proposed algorithm affords an online implementation to enable tracking of the solutions in the presence of time-varying operational conditions and changing optimization objectives. It involves a strategy where the network operator collects voltage measurements throughout the feeder to build incentive signals for the DER-owners in real time; DERs thenmore » adjust the generated/consumed powers in order to avoid the violation of the voltage constraints while maximizing given objectives. Stability of the proposed schemes is analytically established and numerically corroborated.« less

An Incentive-based Online Optimization Framework for Distribution Grids

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

Zhou, Xinyang; Dall'Anese, Emiliano; Chen, Lijun

This article formulates a time-varying social-welfare maximization problem for distribution grids with distributed energy resources (DERs) and develops online distributed algorithms to identify (and track) its solutions. In the considered setting, network operator and DER-owners pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. The proposed algorithm affords an online implementation to enable tracking of the solutions in the presence of time-varying operational conditions and changing optimization objectives. It involves a strategy where the network operator collects voltage measurements throughout the feeder to build incentive signals for the DER-owners in real time; DERs thenmore » adjust the generated/consumed powers in order to avoid the violation of the voltage constraints while maximizing given objectives. Stability of the proposed schemes is analytically established and numerically corroborated.« less

Real-time value optimization of edging and trimming operations for rough, green hardwood lumber

Treesearch

Daniel L. Schmoldt; Hang Song; Philip A. Araman

2001-01-01

For edging/trimming operations in hardwood sawmills, an operator examines both sides—or just the waney-edged side—of each board, and makes a quick assessment of grade potential. The operator then decides where to edge and/or trim the board to achieve the intended grade and, presumably, maximum value. However, human operators can only achieve lumber values that are 62-...

Tier-scalable reconnaissance: the challenge of sensor optimization, sensor deployment, sensor fusion, and sensor interoperability

NASA Astrophysics Data System (ADS)

Fink, Wolfgang; George, Thomas; Tarbell, Mark A.

2007-04-01

Robotic reconnaissance operations are called for in extreme environments, not only those such as space, including planetary atmospheres, surfaces, and subsurfaces, but also in potentially hazardous or inaccessible operational areas on Earth, such as mine fields, battlefield environments, enemy occupied territories, terrorist infiltrated environments, or areas that have been exposed to biochemical agents or radiation. Real time reconnaissance enables the identification and characterization of transient events. A fundamentally new mission concept for tier-scalable reconnaissance of operational areas, originated by Fink et al., is aimed at replacing the engineering and safety constrained mission designs of the past. The tier-scalable paradigm integrates multi-tier (orbit atmosphere surface/subsurface) and multi-agent (satellite UAV/blimp surface/subsurface sensing platforms) hierarchical mission architectures, introducing not only mission redundancy and safety, but also enabling and optimizing intelligent, less constrained, and distributed reconnaissance in real time. Given the mass, size, and power constraints faced by such a multi-platform approach, this is an ideal application scenario for a diverse set of MEMS sensors. To support such mission architectures, a high degree of operational autonomy is required. Essential elements of such operational autonomy are: (1) automatic mapping of an operational area from different vantage points (including vehicle health monitoring); (2) automatic feature extraction and target/region-of-interest identification within the mapped operational area; and (3) automatic target prioritization for close-up examination. These requirements imply the optimal deployment of MEMS sensors and sensor platforms, sensor fusion, and sensor interoperability.

The use of UNIX in a real-time environment

NASA Technical Reports Server (NTRS)

Luken, R. D.; Simons, P. C.

1986-01-01

This paper describes a project to evaluate the feasibility of using commercial off-the-shelf hardware and the UNIX operating system, to implement a real-time control and monitor system. A functional subset of the Checkout, Control and Monitor System was chosen as the test bed for the project. The project consists of three separate architecture implementations: a local area bus network, a star network, and a central host. The motivation for this project stemmed from the need to find a way to implement real-time systems, without the cost burden of developing and maintaining custom hardware and unique software. This has always been accepted as the only option because of the need to optimize the implementation for performance. However, with the cost/performance of today's hardware, the inefficiencies of high-level languages and portable operating systems can be effectively overcome.

Millisecond timing on PCs and Macs.

PubMed

MacInnes, W J; Taylor, T L

2001-05-01

A real-time, object-oriented solution for displaying stimuli on Windows 95/98, MacOS and Linux platforms is presented. The program, written in C++, utilizes a special-purpose window class (GLWindow), OpenGL, and 32-bit graphics acceleration; it avoids display timing uncertainty by substituting the new window class for the default window code for each system. We report the outcome of tests for real-time capability across PC and Mac platforms running a variety of operating systems. The test program, which can be used as a shell for programming real-time experiments and testing specific processors, is available at http://www.cs.dal.ca/~macinnwj. We propose to provide researchers with a sense of the usefulness of our program, highlight the ability of many multitasking environments to achieve real time, as well as caution users about systems that may not achieve real time, even under optimal conditions.

System-on-chip architecture and validation for real-time transceiver optimization: APC implementation on FPGA

NASA Astrophysics Data System (ADS)

Suarez, Hernan; Zhang, Yan R.

2015-05-01

New radar applications need to perform complex algorithms and process large quantity of data to generate useful information for the users. This situation has motivated the search for better processing solutions that include low power high-performance processors, efficient algorithms, and high-speed interfaces. In this work, hardware implementation of adaptive pulse compression for real-time transceiver optimization are presented, they are based on a System-on-Chip architecture for Xilinx devices. This study also evaluates the performance of dedicated coprocessor as hardware accelerator units to speed up and improve the computation of computing-intensive tasks such matrix multiplication and matrix inversion which are essential units to solve the covariance matrix. The tradeoffs between latency and hardware utilization are also presented. Moreover, the system architecture takes advantage of the embedded processor, which is interconnected with the logic resources through the high performance AXI buses, to perform floating-point operations, control the processing blocks, and communicate with external PC through a customized software interface. The overall system functionality is demonstrated and tested for real-time operations using a Ku-band tested together with a low-cost channel emulator for different types of waveforms.

Real-time video compressing under DSP/BIOS

NASA Astrophysics Data System (ADS)

Chen, Qiu-ping; Li, Gui-ju

2009-10-01

This paper presents real-time MPEG-4 Simple Profile video compressing based on the DSP processor. The programming framework of video compressing is constructed using TMS320C6416 Microprocessor, TDS510 simulator and PC. It uses embedded real-time operating system DSP/BIOS and the API functions to build periodic function, tasks and interruptions etcs. Realize real-time video compressing. To the questions of data transferring among the system. Based on the architecture of the C64x DSP, utilized double buffer switched and EDMA data transfer controller to transit data from external memory to internal, and realize data transition and processing at the same time; the architecture level optimizations are used to improve software pipeline. The system used DSP/BIOS to realize multi-thread scheduling. The whole system realizes high speed transition of a great deal of data. Experimental results show the encoder can realize real-time encoding of 768*576, 25 frame/s video images.

Optimization-based power management of hybrid power systems with applications in advanced hybrid electric vehicles and wind farms with battery storage

NASA Astrophysics Data System (ADS)

Borhan, Hoseinali

Modern hybrid electric vehicles and many stationary renewable power generation systems combine multiple power generating and energy storage devices to achieve an overall system-level efficiency and flexibility which is higher than their individual components. The power or energy management control, "brain" of these "hybrid" systems, determines adaptively and based on the power demand the power split between multiple subsystems and plays a critical role in overall system-level efficiency. This dissertation proposes that a receding horizon optimal control (aka Model Predictive Control) approach can be a natural and systematic framework for formulating this type of power management controls. More importantly the dissertation develops new results based on the classical theory of optimal control that allow solving the resulting optimal control problem in real-time, in spite of the complexities that arise due to several system nonlinearities and constraints. The dissertation focus is on two classes of hybrid systems: hybrid electric vehicles in the first part and wind farms with battery storage in the second part. The first part of the dissertation proposes and fully develops a real-time optimization-based power management strategy for hybrid electric vehicles. Current industry practice uses rule-based control techniques with "else-then-if" logic and look-up maps and tables in the power management of production hybrid vehicles. These algorithms are not guaranteed to result in the best possible fuel economy and there exists a gap between their performance and a minimum possible fuel economy benchmark. Furthermore, considerable time and effort are spent calibrating the control system in the vehicle development phase, and there is little flexibility in real-time handling of constraints and re-optimization of the system operation in the event of changing operating conditions and varying parameters. In addition, a proliferation of different powertrain configurations may result in the need for repeated control system redesign. To address these shortcomings, we formulate the power management problem as a nonlinear and constrained optimal control problem. Solution of this optimal control problem in real-time on chronometric- and memory-constrained automotive microcontrollers is quite challenging; this computational complexity is due to the highly nonlinear dynamics of the powertrain subsystems, mixed-integer switching modes of their operation, and time-varying and nonlinear hard constraints that system variables should satisfy. The main contribution of the first part of the dissertation is that it establishes methods for systematic and step-by step improvements in fuel economy while maintaining the algorithmic computational requirements in a real-time implementable framework. More specifically a linear time-varying model predictive control approach is employed first which uses sequential quadratic programming to find sub-optimal solutions to the power management problem. Next the objective function is further refined and broken into a short and a long horizon segments; the latter approximated as a function of the state using the connection between the Pontryagin minimum principle and Hamilton-Jacobi-Bellman equations. The power management problem is then solved using a nonlinear MPC framework with a dynamic programming solver and the fuel economy is further improved. Typical simplifying academic assumptions are minimal throughout this work, thanks to close collaboration with research scientists at Ford research labs and their stringent requirement that the proposed solutions be tested on high-fidelity production models. Simulation results on a high-fidelity model of a hybrid electric vehicle over multiple standard driving cycles reveal the potential for substantial fuel economy gains. To address the control calibration challenges, we also present a novel and fast calibration technique utilizing parallel computing techniques. ^ The second part of this dissertation presents an optimization-based control strategy for the power management of a wind farm with battery storage. The strategy seeks to minimize the error between the power delivered by the wind farm with battery storage and the power demand from an operator. In addition, the strategy attempts to maximize battery life. The control strategy has two main stages. The first stage produces a family of control solutions that minimize the power error subject to the battery constraints over an optimization horizon. These solutions are parameterized by a given value for the state of charge at the end of the optimization horizon. The second stage screens the family of control solutions to select one attaining an optimal balance between power error and battery life. The battery life model used in this stage is a weighted Amp-hour (Ah) throughput model. The control strategy is modular, allowing for more sophisticated optimization models in the first stage, or more elaborate battery life models in the second stage. The strategy is implemented in real-time in the framework of Model Predictive Control (MPC).

Towards real time 2D to 3D registration for ultrasound-guided endoscopic and laparoscopic procedures.

PubMed

San José Estépar, Raúl; Westin, Carl-Fredrik; Vosburgh, Kirby G

2009-11-01

A method to register endoscopic and laparoscopic ultrasound (US) images in real time with pre-operative computed tomography (CT) data sets has been developed with the goal of improving diagnosis, biopsy guidance, and surgical interventions in the abdomen. The technique, which has the potential to operate in real time, is based on a new phase correlation technique: LEPART, which specifies the location of a plane in the CT data which best corresponds to the US image. Validation of the method was carried out using an US phantom with cyst regions and with retrospective analysis of data sets from animal model experiments. The phantom validation study shows that local translation displacements can be recovered for each US frame with a root mean squared error of 1.56 +/- 0.78 mm in less than 5 sec, using non-optimized algorithm implementations. A new method for multimodality (preoperative CT and intraoperative US endoscopic images) registration to guide endoscopic interventions was developed and found to be efficient using clinically realistic datasets. The algorithm is inherently capable of being implemented in a parallel computing system so that full real time operation appears likely.

Intra-Hour Dispatch and Automatic Generator Control Demonstration with Solar Forecasting - Final Report

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

Coimbra, Carlos F. M.

2016-02-25

In this project we address multiple resource integration challenges associated with increasing levels of solar penetration that arise from the variability and uncertainty in solar irradiance. We will model the SMUD service region as its own balancing region, and develop an integrated, real-time operational tool that takes solar-load forecast uncertainties into consideration and commits optimal energy resources and reserves for intra-hour and intra-day decisions. The primary objectives of this effort are to reduce power system operation cost by committing appropriate amount of energy resources and reserves, as well as to provide operators a prediction of the generation fleet’s behavior inmore » real time for realistic PV penetration scenarios. The proposed methodology includes the following steps: clustering analysis on the expected solar variability per region for the SMUD system, Day-ahead (DA) and real-time (RT) load forecasts for the entire service areas, 1-year of intra-hour CPR forecasts for cluster centers, 1-year of smart re-forecasting CPR forecasts in real-time for determination of irreducible errors, and uncertainty quantification for integrated solar-load for both distributed and central stations (selected locations within service region) PV generation.« less

Computer assisted thermal-vacuum testing

NASA Technical Reports Server (NTRS)

Petrie, W.; Mikk, G.

1977-01-01

In testing complex systems and components under dynamic thermal-vacuum environments, it is desirable to optimize the environment control sequence in order to reduce test duration and cost. This paper describes an approach where a computer is utilized as part of the test control operation. Real time test data is made available to the computer through time-sharing terminals at appropriate time intervals. A mathematical model of the test article and environmental control equipment is then operated on using the real time data to yield current thermal status, temperature analysis, trend prediction and recommended thermal control setting changes to arrive at the required thermal condition. The data acquisition interface and the time-sharing hook-up to an IBM-370 computer is described along with a typical control program and data demonstrating its use.

Real-Time Load-Side Control of Electric Power Systems

NASA Astrophysics Data System (ADS)

Zhao, Changhong

Two trends are emerging from modern electric power systems: the growth of renewable (e.g., solar and wind) generation, and the integration of information technologies and advanced power electronics. The former introduces large, rapid, and random fluctuations in power supply, demand, frequency, and voltage, which become a major challenge for real-time operation of power systems. The latter creates a tremendous number of controllable intelligent endpoints such as smart buildings and appliances, electric vehicles, energy storage devices, and power electronic devices that can sense, compute, communicate, and actuate. Most of these endpoints are distributed on the load side of power systems, in contrast to traditional control resources such as centralized bulk generators. This thesis focuses on controlling power systems in real time, using these load side resources. Specifically, it studies two problems. (1) Distributed load-side frequency control: We establish a mathematical framework to design distributed frequency control algorithms for flexible electric loads. In this framework, we formulate a category of optimization problems, called optimal load control (OLC), to incorporate the goals of frequency control, such as balancing power supply and demand, restoring frequency to its nominal value, restoring inter-area power flows, etc., in a way that minimizes total disutility for the loads to participate in frequency control by deviating from their nominal power usage. By exploiting distributed algorithms to solve OLC and analyzing convergence of these algorithms, we design distributed load-side controllers and prove stability of closed-loop power systems governed by these controllers. This general framework is adapted and applied to different types of power systems described by different models, or to achieve different levels of control goals under different operation scenarios. We first consider a dynamically coherent power system which can be equivalently modeled with a single synchronous machine. We then extend our framework to a multi-machine power network, where we consider primary and secondary frequency controls, linear and nonlinear power flow models, and the interactions between generator dynamics and load control. (2) Two-timescale voltage control: The voltage of a power distribution system must be maintained closely around its nominal value in real time, even in the presence of highly volatile power supply or demand. For this purpose, we jointly control two types of reactive power sources: a capacitor operating at a slow timescale, and a power electronic device, such as a smart inverter or a D-STATCOM, operating at a fast timescale. Their control actions are solved from optimal power flow problems at two timescales. Specifically, the slow-timescale problem is a chance-constrained optimization, which minimizes power loss and regulates the voltage at the current time instant while limiting the probability of future voltage violations due to stochastic changes in power supply or demand. This control framework forms the basis of an optimal sizing problem, which determines the installation capacities of the control devices by minimizing the sum of power loss and capital cost. We develop computationally efficient heuristics to solve the optimal sizing problem and implement real-time control. Numerical experiments show that the proposed sizing and control schemes significantly improve the reliability of voltage control with a moderate increase in cost.

Real-Time IRI driven by GIRO data

NASA Astrophysics Data System (ADS)

Galkin, Ivan; Huang, Xueqin; Reinisch, Bodo; Bilitza, Dieter; Vesnin, Artem

Real-time extensions of the empirical International Reference Ionosphere (IRI) model are based on assimilative techniques that preserve the IRI formalism which is optimized for the description of climatological ionospheric features. The Global Ionosphere Radio Observatory (GIRO) team has developed critical parts of an IRI Real Time Assimilative Model (IRTAM) for the global ionospheric plasma distribution using measured data available in real time from ~50 ionosondes of the GIRO network, The current assimilation results present global assimilative maps of foF2 and hmF2 that reproduce available data at the sensor sites and smoothly return to the climatological specifications when and where the data are missing, and are free from artificial sharp gradients and short-lived artifacts when viewed in time progression. Animated real-time maps of foF2 and hmF2 are published with a few minutes latency at http://giro.uml.edu/IRTAM/. Our real-time IRI modeling uses morphing, a technique that transforms the climatological ionospheric specifications to match the observations by iteratively computing corrections to the original coefficients of the diurnal/spatial expansions, used in IRI to map the key ionospheric characteristics, while keeping the IRI expansion basis formalism intact. Computation of the updated coefficient set for a given point in time includes analysis of the latest 24-hour history of observations, which allows the morphing technique to sense evolving ionospheric dynamics even with a sparse sensor network. A Non-linear Error Compensation Technique for Associative Restoration (NECTAR), one of the features in our morphing approach, has been in operation at the Lowell GIRO Data Center since 2013. The cornerstone of NECTAR is a recurrent neural network optimizer that is responsible for smoothing the transitions between the grid cells where observations are available. NECTAR has proved suitable for real-time operations that require the assimilation code to be considerate of data uncertainties (noise) and immune to data errors. Future IRTAM work is directed toward accepting a greater diversity of near-real-time sensor data, and the paper discusses potential new data sources and challenges associated with their assimilation.

Online Monitoring System of Air Distribution in Pulverized Coal-Fired Boiler Based on Numerical Modeling

NASA Astrophysics Data System (ADS)

Żymełka, Piotr; Nabagło, Daniel; Janda, Tomasz; Madejski, Paweł

2017-12-01

Balanced distribution of air in coal-fired boiler is one of the most important factors in the combustion process and is strongly connected to the overall system efficiency. Reliable and continuous information about combustion airflow and fuel rate is essential for achieving optimal stoichiometric ratio as well as efficient and safe operation of a boiler. Imbalances in air distribution result in reduced boiler efficiency, increased gas pollutant emission and operating problems, such as corrosion, slagging or fouling. Monitoring of air flow trends in boiler is an effective method for further analysis and can help to appoint important dependences and start optimization actions. Accurate real-time monitoring of the air distribution in boiler can bring economical, environmental and operational benefits. The paper presents a novel concept for online monitoring system of air distribution in coal-fired boiler based on real-time numerical calculations. The proposed mathematical model allows for identification of mass flow rates of secondary air to individual burners and to overfire air (OFA) nozzles. Numerical models of air and flue gas system were developed using software for power plant simulation. The correctness of the developed model was verified and validated with the reference measurement values. The presented numerical model for real-time monitoring of air distribution is capable of giving continuous determination of the complete air flows based on available digital communication system (DCS) data.

Intelligent data management for real-time spacecraft monitoring

NASA Technical Reports Server (NTRS)

Schwuttke, Ursula M.; Gasser, Les; Abramson, Bruce

1992-01-01

Real-time AI systems have begun to address the challenge of restructuring problem solving to meet real-time constraints by making key trade-offs that pursue less than optimal strategies with minimal impact on system goals. Several approaches for adapting to dynamic changes in system operating conditions are known. However, simultaneously adapting system decision criteria in a principled way has been difficult. Towards this end, a general technique for dynamically making such trade-offs using a combination of decision theory and domain knowledge has been developed. Multi-attribute utility theory (MAUT), a decision theoretic approach for making one-time decisions is discussed and dynamic trade-off evaluation is described as a knowledge-based extension of MAUT that is suitable for highly dynamic real-time environments, and provides an example of dynamic trade-off evaluation applied to a specific data management trade-off in a real-world spacecraft monitoring application.

Method for providing real-time control of a gaseous propellant rocket propulsion system

NASA Technical Reports Server (NTRS)

Morris, Brian G. (Inventor)

1991-01-01

The new and improved methods and apparatus disclosed provide effective real-time management of a spacecraft rocket engine powered by gaseous propellants. Real-time measurements representative of the engine performance are compared with predetermined standards to selectively control the supply of propellants to the engine for optimizing its performance as well as efficiently managing the consumption of propellants. A priority system is provided for achieving effective real-time management of the propulsion system by first regulating the propellants to keep the engine operating at an efficient level and thereafter regulating the consumption ratio of the propellants. A lower priority level is provided to balance the consumption of the propellants so significant quantities of unexpended propellants will not be left over at the end of the scheduled mission of the engine.

Computationally-Efficient Minimum-Time Aircraft Routes in the Presence of Winds

NASA Technical Reports Server (NTRS)

Jardin, Matthew R.

2004-01-01

A computationally efficient algorithm for minimizing the flight time of an aircraft in a variable wind field has been invented. The algorithm, referred to as Neighboring Optimal Wind Routing (NOWR), is based upon neighboring-optimal-control (NOC) concepts and achieves minimum-time paths by adjusting aircraft heading according to wind conditions at an arbitrary number of wind measurement points along the flight route. The NOWR algorithm may either be used in a fast-time mode to compute minimum- time routes prior to flight, or may be used in a feedback mode to adjust aircraft heading in real-time. By traveling minimum-time routes instead of direct great-circle (direct) routes, flights across the United States can save an average of about 7 minutes, and as much as one hour of flight time during periods of strong jet-stream winds. The neighboring optimal routes computed via the NOWR technique have been shown to be within 1.5 percent of the absolute minimum-time routes for flights across the continental United States. On a typical 450-MHz Sun Ultra workstation, the NOWR algorithm produces complete minimum-time routes in less than 40 milliseconds. This corresponds to a rate of 25 optimal routes per second. The closest comparable optimization technique runs approximately 10 times slower. Airlines currently use various trial-and-error search techniques to determine which of a set of commonly traveled routes will minimize flight time. These algorithms are too computationally expensive for use in real-time systems, or in systems where many optimal routes need to be computed in a short amount of time. Instead of operating in real-time, airlines will typically plan a trajectory several hours in advance using wind forecasts. If winds change significantly from forecasts, the resulting flights will no longer be minimum-time. The need for a computationally efficient wind-optimal routing algorithm is even greater in the case of new air-traffic-control automation concepts. For air-traffic-control automation, thousands of wind-optimal routes may need to be computed and checked for conflicts in just a few minutes. These factors motivated the need for a more efficient wind-optimal routing algorithm.

Real-Time Optimization of Distribution Grids for Increased Flexibility and

Science.gov Websites

ensure a stable system operation. Now let's go a little bit to the math, because there are some technical math. This one looks very complicated, but it's actually very simple, because, for example, you take stability and optimality. However, I'm not going to delve into the math. I'm going to move to some test

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

NASA Technical Reports Server (NTRS)

Zhao, Yiyuan; Chen, Robert T. N.

1996-01-01

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

Flexible real-time magnetic resonance imaging framework.

PubMed

Santos, Juan M; Wright, Graham A; Pauly, John M

2004-01-01

The extension of MR imaging to new applications has demonstrated the limitations of the architecture of current real-time systems. Traditional real-time implementations provide continuous acquisition of data and modification of basic sequence parameters on the fly. We have extended the concept of real-time MRI by designing a system that drives the examinations from a real-time localizer and then gets reconfigured for different imaging modes. Upon operator request or automatic feedback the system can immediately generate a new pulse sequence or change fundamental aspects of the acquisition such as gradient waveforms excitation pulses and scan planes. This framework has been implemented by connecting a data processing and control workstation to a conventional clinical scanner. Key components on the design of this framework are the data communication and control mechanisms, reconstruction algorithms optimized for real-time and adaptability, flexible user interface and extensible user interaction. In this paper we describe the various components that comprise this system. Some of the applications implemented in this framework include real-time catheter tracking embedded in high frame rate real-time imaging and immediate switching between real-time localizer and high-resolution volume imaging for coronary angiography applications.

Point Positioning Service for Natural Hazard Monitoring

NASA Astrophysics Data System (ADS)

Bar-Sever, Y. E.

2014-12-01

In an effort to improve natural hazard monitoring, JPL has invested in updating and enlarging its global real-time GNSS tracking network, and has launched a unique service - real-time precise positioning for natural hazard monitoring, entitled GREAT Alert (GNSS Real-Time Earthquake and Tsunami Alert). GREAT Alert leverages the full technological and operational capability of the JPL's Global Differential GPS System [www.gdgps.net] to offer owners of real-time dual-frequency GNSS receivers: Sub-5 cm (3D RMS) real-time, absolute positioning in ITRF08, regardless of location Under 5 seconds turnaround time Full covariance information Estimates of ancillary parameters (such as troposphere) optionally provided This service enables GNSS networks operators to instantly have access to the most accurate and reliable real-time positioning solutions for their sites, and also to the hundreds of participating sites globally, assuring inter-consistency and uniformity across all solutions. Local authorities with limited technical and financial resources can now access to the best technology, and share environmental data to the benefit of the entire pacific region. We will describe the specialized precise point positioning techniques employed by the GREAT Alert service optimized for natural hazard monitoring, and in particular Earthquake monitoring. We address three fundamental aspects of these applications: 1) small and infrequent motion, 2) the availability of data at a central location, and 3) the need for refined solutions at several time scales

Optimization and Improvement of Test Processes on a Production Line

NASA Astrophysics Data System (ADS)

Sujová, Erika; Čierna, Helena

2018-06-01

The paper deals with increasing processes efficiency at a production line of cylinder heads of engines in a production company operating in the automotive industry. The goal is to achieve improvement and optimization of test processes on a production line. It analyzes options for improving capacity, availability and productivity of processes of an output test by using modern technology available on the market. We have focused on analysis of operation times before and after optimization of test processes at specific production sections. By analyzing measured results we have determined differences in time before and after improvement of the process. We have determined a coefficient of efficiency OEE and by comparing outputs we have confirmed real improvement of the process of the output test of cylinder heads.

A novel track-before-detect algorithm based on optimal nonlinear filtering for detecting and tracking infrared dim target

NASA Astrophysics Data System (ADS)

Tian, Yuexin; Gao, Kun; Liu, Ying; Han, Lu

2015-08-01

Aiming at the nonlinear and non-Gaussian features of the real infrared scenes, an optimal nonlinear filtering based algorithm for the infrared dim target tracking-before-detecting application is proposed. It uses the nonlinear theory to construct the state and observation models and uses the spectral separation scheme based Wiener chaos expansion method to resolve the stochastic differential equation of the constructed models. In order to improve computation efficiency, the most time-consuming operations independent of observation data are processed on the fore observation stage. The other observation data related rapid computations are implemented subsequently. Simulation results show that the algorithm possesses excellent detection performance and is more suitable for real-time processing.

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

Dall'Anese, Emiliano

Past works that focused on addressing power-quality and reliability concerns related to renewable energy resources (RESs) operating with business-as-usual practices have looked at the design of Volt/VAr and Volt/Watt strategies to regulate real or reactive powers based on local voltage measurements, so that terminal voltages are within acceptable levels. These control strategies have the potential of operating at the same time scale of distribution-system dynamics, and can therefore mitigate disturbances precipitated fast time-varying loads and ambient conditions; however, they do not necessarily guarantee system-level optimality, and stability claims are mainly based on empirical evidences. On a different time scale, centralizedmore » and distributed optimal power flow (OPF) algorithms have been proposed to compute optimal steady-state inverter setpoints, so that power losses and voltage deviations are minimized and economic benefits to end-users providing ancillary services are maximized. However, traditional OPF schemes may offer decision making capabilities that do not match the dynamics of distribution systems. Particularly, during the time required to collect data from all the nodes of the network (e.g., loads), solve the OPF, and subsequently dispatch setpoints, the underlying load, ambient, and network conditions may have already changed; in this case, the DER output powers would be consistently regulated around outdated setpoints, leading to suboptimal system operation and violation of relevant electrical limits. The present work focuses on the synthesis of distributed RES-inverter controllers that leverage the opportunities for fast feedback offered by power-electronics interfaced RESs. The overarching objective is to bridge the temporal gap between long-term system optimization and real-time control, to enable seamless RES integration in large scale with stability and efficiency guarantees, while congruently pursuing system-level optimization objectives. The design of the control framework is based on suitable linear approximations of the AC power-flow equations as well as Lagrangian regularization methods. The proposed controllers enable an update of the power outputs at a time scale that is compatible with the underlying dynamics of loads and ambient conditions, and continuously drive the system operation towards OPF-based solutions.« less

Short-Term Load Forecasting Based Automatic Distribution Network Reconfiguration: Preprint

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

Jiang, Huaiguang; Ding, Fei; Zhang, Yingchen

In the traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of load forecasting technique can provide accurate prediction of load power that will happen in future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during the longer time period instead of using the snapshot of load at the time when the reconfiguration happens, and thus it can provide information to the distribution systemmore » operator (DSO) to better operate the system reconfiguration to achieve optimal solutions. Thus, this paper proposes a short-term load forecasting based approach for automatically reconfiguring distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with support vector regression (SVR) based forecaster and parallel parameters optimization. And the network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum loss at the future time. The simulation results validate and evaluate the proposed approach.« less

Runway Scheduling Using Generalized Dynamic Programming

NASA Technical Reports Server (NTRS)

Montoya, Justin; Wood, Zachary; Rathinam, Sivakumar

2011-01-01

A generalized dynamic programming method for finding a set of pareto optimal solutions for a runway scheduling problem is introduced. The algorithm generates a set of runway fight sequences that are optimal for both runway throughput and delay. Realistic time-based operational constraints are considered, including miles-in-trail separation, runway crossings, and wake vortex separation. The authors also model divergent runway takeoff operations to allow for reduced wake vortex separation. A modeled Dallas/Fort Worth International airport and three baseline heuristics are used to illustrate preliminary benefits of using the generalized dynamic programming method. Simulated traffic levels ranged from 10 aircraft to 30 aircraft with each test case spanning 15 minutes. The optimal solution shows a 40-70 percent decrease in the expected delay per aircraft over the baseline schedulers. Computational results suggest that the algorithm is promising for real-time application with an average computation time of 4.5 seconds. For even faster computation times, two heuristics are developed. As compared to the optimal, the heuristics are within 5% of the expected delay per aircraft and 1% of the expected number of runway operations per hour ad can be 100x faster.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

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

PubMed

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

2018-05-01

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

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

NASA Technical Reports Server (NTRS)

Brown, Nelson Andrew; Schaefer, Jacob Robert

2013-01-01

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

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

NASA Technical Reports Server (NTRS)

Brown, Nelson Andrew; Schaefer, Jacob Robert

2013-01-01

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

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

NASA Technical Reports Server (NTRS)

Brown, Nelson

2012-01-01

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

Electrolyzers Enhancing Flexibility in Electric Grids

DOE PAGES

Mohanpurkar, Manish; Luo, Yusheng; Terlip, Danny; ...

2017-11-10

This paper presents a real-time simulation with a hardware-in-the-loop (HIL)-based approach for verifying the performance of electrolyzer systems in providing grid support. Hydrogen refueling stations may use electrolyzer systems to generate hydrogen and are proposed to have the potential of becoming smarter loads that can proactively provide grid services. On the basis of experimental findings, electrolyzer systems with balance of plant are observed to have a high level of controllability and hence can add flexibility to the grid from the demand side. A generic front end controller (FEC) is proposed, which enables an optimal operation of the load on themore » basis of market and grid conditions. This controller has been simulated and tested in a real-time environment with electrolyzer hardware for a performance assessment. It can optimize the operation of electrolyzer systems on the basis of the information collected by a communication module. Real-time simulation tests are performed to verify the performance of the FEC-driven electrolyzers to provide grid support that enables flexibility, greater economic revenue, and grid support for hydrogen producers under dynamic conditions. In conclusion, the FEC proposed in this paper is tested with electrolyzers, however, it is proposed as a generic control topology that is applicable to any load.« less

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

NASA Technical Reports Server (NTRS)

Brown, Nelson

2013-01-01

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

AN OPTIMIZED 64X64 POINT TWO-DIMENSIONAL FAST FOURIER TRANSFORM

NASA Technical Reports Server (NTRS)

Miko, J.

1994-01-01

Scientists at Goddard have developed an efficient and powerful program-- An Optimized 64x64 Point Two-Dimensional Fast Fourier Transform-- which combines the performance of real and complex valued one-dimensional Fast Fourier Transforms (FFT's) to execute a two-dimensional FFT and its power spectrum coefficients. These coefficients can be used in many applications, including spectrum analysis, convolution, digital filtering, image processing, and data compression. The program's efficiency results from its technique of expanding all arithmetic operations within one 64-point FFT; its high processing rate results from its operation on a high-speed digital signal processor. For non-real-time analysis, the program requires as input an ASCII data file of 64x64 (4096) real valued data points. As output, this analysis produces an ASCII data file of 64x64 power spectrum coefficients. To generate these coefficients, the program employs a row-column decomposition technique. First, it performs a radix-4 one-dimensional FFT on each row of input, producing complex valued results. Then, it performs a one-dimensional FFT on each column of these results to produce complex valued two-dimensional FFT results. Finally, the program sums the squares of the real and imaginary values to generate the power spectrum coefficients. The program requires a Banshee accelerator board with 128K bytes of memory from Atlanta Signal Processors (404/892-7265) installed on an IBM PC/AT compatible computer (DOS ver. 3.0 or higher) with at least one 16-bit expansion slot. For real-time operation, an ASPI daughter board is also needed. The real-time configuration reads 16-bit integer input data directly into the accelerator board, operating on 64x64 point frames of data. The program's memory management also allows accumulation of the coefficient results. The real-time processing rate to calculate and accumulate the 64x64 power spectrum output coefficients is less than 17.0 mSec. Documentation is included in the price of the program. Source code is written in C, 8086 Assembly, and Texas Instruments TMS320C30 Assembly Languages. This program is available on a 5.25 inch 360K MS-DOS format diskette. IBM and IBM PC are registered trademarks of International Business Machines. MS-DOS is a registered trademark of Microsoft Corporation.

Flight elements: Fault detection and fault management

NASA Technical Reports Server (NTRS)

Lum, H.; Patterson-Hine, A.; Edge, J. T.; Lawler, D.

1990-01-01

Fault management for an intelligent computational system must be developed using a top down integrated engineering approach. An approach proposed includes integrating the overall environment involving sensors and their associated data; design knowledge capture; operations; fault detection, identification, and reconfiguration; testability; causal models including digraph matrix analysis; and overall performance impacts on the hardware and software architecture. Implementation of the concept to achieve a real time intelligent fault detection and management system will be accomplished via the implementation of several objectives, which are: Development of fault tolerant/FDIR requirement and specification from a systems level which will carry through from conceptual design through implementation and mission operations; Implementation of monitoring, diagnosis, and reconfiguration at all system levels providing fault isolation and system integration; Optimize system operations to manage degraded system performance through system integration; and Lower development and operations costs through the implementation of an intelligent real time fault detection and fault management system and an information management system.

Distributed operating system for NASA ground stations

NASA Technical Reports Server (NTRS)

Doyle, John F.

1987-01-01

NASA ground stations are characterized by ever changing support requirements, so application software is developed and modified on a continuing basis. A distributed operating system was designed to optimize the generation and maintenance of those applications. Unusual features include automatic program generation from detailed design graphs, on-line software modification in the testing phase, and the incorporation of a relational database within a real-time, distributed system.

Real-Time Imaging with Frequency Scanning Array Antenna for Industrial Inspection Applications at W band

NASA Astrophysics Data System (ADS)

Larumbe, Belen; Laviada, Jaime; Ibáñez-Loinaz, Asier; Teniente, Jorge

2018-01-01

A real-time imaging system based on a frequency scanning antenna for conveyor belt setups is presented in this paper. The frequency scanning antenna together with an inexpensive parabolic reflector operates at the W band enabling the detection of details with dimensions in the order of 2 mm. In addition, a low level of sidelobes is achieved by optimizing unequal dividers to window the power distribution for sidelobe reduction. Furthermore, the quality of the images is enhanced by the radiation pattern properties. The performance of the system is validated by showing simulation as well as experimental results obtained in real time, proving the feasibility of these kinds of frequency scanning antennas for cost-effective imaging applications.

Dynamic vehicle routing with time windows in theory and practice.

PubMed

Yang, Zhiwei; van Osta, Jan-Paul; van Veen, Barry; van Krevelen, Rick; van Klaveren, Richard; Stam, Andries; Kok, Joost; Bäck, Thomas; Emmerich, Michael

2017-01-01

The vehicle routing problem is a classical combinatorial optimization problem. This work is about a variant of the vehicle routing problem with dynamically changing orders and time windows. In real-world applications often the demands change during operation time. New orders occur and others are canceled. In this case new schedules need to be generated on-the-fly. Online optimization algorithms for dynamical vehicle routing address this problem but so far they do not consider time windows. Moreover, to match the scenarios found in real-world problems adaptations of benchmarks are required. In this paper, a practical problem is modeled based on the procedure of daily routing of a delivery company. New orders by customers are introduced dynamically during the working day and need to be integrated into the schedule. A multiple ant colony algorithm combined with powerful local search procedures is proposed to solve the dynamic vehicle routing problem with time windows. The performance is tested on a new benchmark based on simulations of a working day. The problems are taken from Solomon's benchmarks but a certain percentage of the orders are only revealed to the algorithm during operation time. Different versions of the MACS algorithm are tested and a high performing variant is identified. Finally, the algorithm is tested in situ: In a field study, the algorithm schedules a fleet of cars for a surveillance company. We compare the performance of the algorithm to that of the procedure used by the company and we summarize insights gained from the implementation of the real-world study. The results show that the multiple ant colony algorithm can get a much better solution on the academic benchmark problem and also can be integrated in a real-world environment.

Grid integration and smart grid implementation of emerging technologies in electric power systems through approximate dynamic programming

NASA Astrophysics Data System (ADS)

Xiao, Jingjie

A key hurdle for implementing real-time pricing of electricity is a lack of consumers' responses. Solutions to overcome the hurdle include the energy management system that automatically optimizes household appliance usage such as plug-in hybrid electric vehicle charging (and discharging with vehicle-to-grid) via a two-way communication with the grid. Real-time pricing, combined with household automation devices, has a potential to accommodate an increasing penetration of plug-in hybrid electric vehicles. In addition, the intelligent energy controller on the consumer-side can help increase the utilization rate of the intermittent renewable resource, as the demand can be managed to match the output profile of renewables, thus making the intermittent resource such as wind and solar more economically competitive in the long run. One of the main goals of this dissertation is to present how real-time retail pricing, aided by control automation devices, can be integrated into the wholesale electricity market under various uncertainties through approximate dynamic programming. What distinguishes this study from the existing work in the literature is that whole- sale electricity prices are endogenously determined as we solve a system operator's economic dispatch problem on an hourly basis over the entire optimization horizon. This modeling and algorithm framework will allow a feedback loop between electricity prices and electricity consumption to be fully captured. While we are interested in a near-optimal solution using approximate dynamic programming; deterministic linear programming benchmarks are use to demonstrate the quality of our solutions. The other goal of the dissertation is to use this framework to provide numerical evidence to the debate on whether real-time pricing is superior than the current flat rate structure in terms of both economic and environmental impacts. For this purpose, the modeling and algorithm framework is tested on a large-scale test case with hundreds of power plants based on data available for California, making our findings useful for policy makers, system operators and utility companies to gain a concrete understanding on the scale of the impact with real-time pricing.

Optimal dynamic voltage scaling for wireless sensor nodes with real-time constraints

NASA Astrophysics Data System (ADS)

Cassandras, Christos G.; Zhuang, Shixin

2005-11-01

Sensors are increasingly embedded in manufacturing systems and wirelessly networked to monitor and manage operations ranging from process and inventory control to tracking equipment and even post-manufacturing product monitoring. In building such sensor networks, a critical issue is the limited and hard to replenish energy in the devices involved. Dynamic voltage scaling is a technique that controls the operating voltage of a processor to provide desired performance while conserving energy and prolonging the overall network's lifetime. We consider such power-limited devices processing time-critical tasks which are non-preemptive, aperiodic and have uncertain arrival times. We treat voltage scaling as a dynamic optimization problem whose objective is to minimize energy consumption subject to hard or soft real-time execution constraints. In the case of hard constraints, we build on prior work (which engages a voltage scaling controller at task completion times) by developing an intra-task controller that acts at all arrival times of incoming tasks. We show that this optimization problem can be decomposed into two simpler ones whose solution leads to an algorithm that does not actually require solving any nonlinear programming problems. In the case of soft constraints, this decomposition must be partly relaxed, but it still leads to a scalable (linear in the number of tasks) algorithm. Simulation results are provided to illustrate performance improvements in systems with intra-task controllers compared to uncontrolled systems or those using inter-task control.

Real-time validation of receiver state information in optical space-time block code systems.

PubMed

Alamia, John; Kurzweg, Timothy

2014-06-15

Free space optical interconnect (FSOI) systems are a promising solution to interconnect bottlenecks in high-speed systems. To overcome some sources of diminished FSOI performance caused by close proximity of multiple optical channels, multiple-input multiple-output (MIMO) systems implementing encoding schemes such as space-time block coding (STBC) have been developed. These schemes utilize information pertaining to the optical channel to reconstruct transmitted data. The STBC system is dependent on accurate channel state information (CSI) for optimal system performance. As a result of dynamic changes in optical channels, a system in operation will need to have updated CSI. Therefore, validation of the CSI during operation is a necessary tool to ensure FSOI systems operate efficiently. In this Letter, we demonstrate a method of validating CSI, in real time, through the use of moving averages of the maximum likelihood decoder data, and its capacity to predict the bit error rate (BER) of the system.

Parallel processing of real-time dynamic systems simulation on OSCAR (Optimally SCheduled Advanced multiprocessoR)

NASA Technical Reports Server (NTRS)

Kasahara, Hironori; Honda, Hiroki; Narita, Seinosuke

1989-01-01

Parallel processing of real-time dynamic systems simulation on a multiprocessor system named OSCAR is presented. In the simulation of dynamic systems, generally, the same calculation are repeated every time step. However, we cannot apply to Do-all or the Do-across techniques for parallel processing of the simulation since there exist data dependencies from the end of an iteration to the beginning of the next iteration and furthermore data-input and data-output are required every sampling time period. Therefore, parallelism inside the calculation required for a single time step, or a large basic block which consists of arithmetic assignment statements, must be used. In the proposed method, near fine grain tasks, each of which consists of one or more floating point operations, are generated to extract the parallelism from the calculation and assigned to processors by using optimal static scheduling at compile time in order to reduce large run time overhead caused by the use of near fine grain tasks. The practicality of the scheme is demonstrated on OSCAR (Optimally SCheduled Advanced multiprocessoR) which has been developed to extract advantageous features of static scheduling algorithms to the maximum extent.

Video enhancement workbench: an operational real-time video image processing system

NASA Astrophysics Data System (ADS)

Yool, Stephen R.; Van Vactor, David L.; Smedley, Kirk G.

1993-01-01

Video image sequences can be exploited in real-time, giving analysts rapid access to information for military or criminal investigations. Video-rate dynamic range adjustment subdues fluctuations in image intensity, thereby assisting discrimination of small or low- contrast objects. Contrast-regulated unsharp masking enhances differentially shadowed or otherwise low-contrast image regions. Real-time removal of localized hotspots, when combined with automatic histogram equalization, may enhance resolution of objects directly adjacent. In video imagery corrupted by zero-mean noise, real-time frame averaging can assist resolution and location of small or low-contrast objects. To maximize analyst efficiency, lengthy video sequences can be screened automatically for low-frequency, high-magnitude events. Combined zoom, roam, and automatic dynamic range adjustment permit rapid analysis of facial features captured by video cameras recording crimes in progress. When trying to resolve small objects in murky seawater, stereo video places the moving imagery in an optimal setting for human interpretation.

Implications of the Value of Hydrologic Information to Reservoir Operations--Learning from the Past

ERIC Educational Resources Information Center

Hejazi, Mohamad Issa

2009-01-01

Closing the gap between theoretical reservoir operation and the real-world implementation remains a challenge in contemporary reservoir operations. Past research has focused on optimization algorithms and establishing optimal policies for reservoir operations. In this research, we attempt to understand operators' release decisions by investigating…

Probabilistic Cloning of Three Real States with Optimal Success Probabilities

NASA Astrophysics Data System (ADS)

Rui, Pin-shu

2017-06-01

We investigate the probabilistic quantum cloning (PQC) of three real states with average probability distribution. To get the analytic forms of the optimal success probabilities we assume that the three states have only two pairwise inner products. Based on the optimal success probabilities, we derive the explicit form of 1 →2 PQC for cloning three real states. The unitary operation needed in the PQC process is worked out too. The optimal success probabilities are also generalized to the M→ N PQC case.

Operating Systems for Wireless Sensor Networks: A Survey

PubMed Central

Farooq, Muhammad Omer; Kunz, Thomas

2011-01-01

This paper presents a survey on the current state-of-the-art in Wireless Sensor Network (WSN) Operating Systems (OSs). In recent years, WSNs have received tremendous attention in the research community, with applications in battlefields, industrial process monitoring, home automation, and environmental monitoring, to name but a few. A WSN is a highly dynamic network because nodes die due to severe environmental conditions and battery power depletion. Furthermore, a WSN is composed of miniaturized motes equipped with scarce resources e.g., limited memory and computational abilities. WSNs invariably operate in an unattended mode and in many scenarios it is impossible to replace sensor motes after deployment, therefore a fundamental objective is to optimize the sensor motes’ life time. These characteristics of WSNs impose additional challenges on OS design for WSN, and consequently, OS design for WSN deviates from traditional OS design. The purpose of this survey is to highlight major concerns pertaining to OS design in WSNs and to point out strengths and weaknesses of contemporary OSs for WSNs, keeping in mind the requirements of emerging WSN applications. The state-of-the-art in operating systems for WSNs has been examined in terms of the OS Architecture, Programming Model, Scheduling, Memory Management and Protection, Communication Protocols, Resource Sharing, Support for Real-Time Applications, and additional features. These features are surveyed for both real-time and non-real-time WSN operating systems. PMID:22163934

Operating systems for wireless sensor networks: a survey.

PubMed

Farooq, Muhammad Omer; Kunz, Thomas

2011-01-01

This paper presents a survey on the current state-of-the-art in Wireless Sensor Network (WSN) Operating Systems (OSs). In recent years, WSNs have received tremendous attention in the research community, with applications in battlefields, industrial process monitoring, home automation, and environmental monitoring, to name but a few. A WSN is a highly dynamic network because nodes die due to severe environmental conditions and battery power depletion. Furthermore, a WSN is composed of miniaturized motes equipped with scarce resources e.g., limited memory and computational abilities. WSNs invariably operate in an unattended mode and in many scenarios it is impossible to replace sensor motes after deployment, therefore a fundamental objective is to optimize the sensor motes' life time. These characteristics of WSNs impose additional challenges on OS design for WSN, and consequently, OS design for WSN deviates from traditional OS design. The purpose of this survey is to highlight major concerns pertaining to OS design in WSNs and to point out strengths and weaknesses of contemporary OSs for WSNs, keeping in mind the requirements of emerging WSN applications. The state-of-the-art in operating systems for WSNs has been examined in terms of the OS Architecture, Programming Model, Scheduling, Memory Management and Protection, Communication Protocols, Resource Sharing, Support for Real-Time Applications, and additional features. These features are surveyed for both real-time and non-real-time WSN operating systems.

Decision Support Systems for Launch and Range Operations Using Jess

NASA Technical Reports Server (NTRS)

Thirumalainambi, Rajkumar

2007-01-01

The virtual test bed for launch and range operations developed at NASA Ames Research Center consists of various independent expert systems advising on weather effects, toxic gas dispersions and human health risk assessment during space-flight operations. An individual dedicated server supports each expert system and the master system gather information from the dedicated servers to support the launch decision-making process. Since the test bed is based on the web system, reducing network traffic and optimizing the knowledge base is critical to its success of real-time or near real-time operations. Jess, a fast rule engine and powerful scripting environment developed at Sandia National Laboratory has been adopted to build the expert systems providing robustness and scalability. Jess also supports XML representation of knowledge base with forward and backward chaining inference mechanism. Facts added - to working memory during run-time operations facilitates analyses of multiple scenarios. Knowledge base can be distributed with one inference engine performing the inference process. This paper discusses details of the knowledge base and inference engine using Jess for a launch and range virtual test bed.

Determining effective forecast horizons for multi-purpose reservoirs with short- and long-term operating objectives

NASA Astrophysics Data System (ADS)

Luchner, Jakob; Anghileri, Daniela; Castelletti, Andrea

2017-04-01

Real-time control of multi-purpose reservoirs can benefit significantly from hydro-meteorological forecast products. Because of their reliability, the most used forecasts range on time scales from hours to few days and are suitable for short-term operation targets such as flood control. In recent years, hydro-meteorological forecasts have become more accurate and reliable on longer time scales, which are more relevant to long-term reservoir operation targets such as water supply. While the forecast quality of such products has been studied extensively, the forecast value, i.e. the operational effectiveness of using forecasts to support water management, has been only relatively explored. It is comparatively easy to identify the most effective forecasting information needed to design reservoir operation rules for flood control but it is not straightforward to identify which forecast variable and lead time is needed to define effective hedging rules for operational targets with slow dynamics such as water supply. The task is even more complex when multiple targets, with diverse slow and fast dynamics, are considered at the same time. In these cases, the relative importance of different pieces of information, e.g. magnitude and timing of peak flow rate and accumulated inflow on different time lags, may vary depending on the season or the hydrological conditions. In this work, we analyze the relationship between operational forecast value and streamflow forecast horizon for different multi-purpose reservoir trade-offs. We use the Information Selection and Assessment (ISA) framework to identify the most effective forecast variables and horizons for informing multi-objective reservoir operation over short- and long-term temporal scales. The ISA framework is an automatic iterative procedure to discriminate the information with the highest potential to improve multi-objective reservoir operating performance. Forecast variables and horizons are selected using a feature selection technique. The technique determines the most informative combination in a multi-variate regression model to the optimal reservoir releases based on perfect information at a fixed objective trade-off. The improved reservoir operation is evaluated against optimal reservoir operation conditioned upon perfect information on future disturbances and basic reservoir operation using only the day of the year and the reservoir level. Different objective trade-offs are selected for analyzing resulting differences in improved reservoir operation and selected forecast variables and horizons. For comparison, the effective streamflow forecast horizon determined by the ISA framework is benchmarked against the performances obtained with a deterministic model predictive control (MPC) optimization scheme. Both the ISA framework and the MPC optimization scheme are applied to the real-world case study of Lake Como, Italy, using perfect streamflow forecast information. The principal operation targets for Lake Como are flood control and downstream water supply which makes its operation a suitable case study. Results provide critical feedback to reservoir operators on the use of long-term streamflow forecasts and to the hydro-meteorological forecasting community with respect to the forecast horizon needed from reliable streamflow forecasts.

An Alternative Approach to the Operation of Multinational Reservoir Systems: Application to the Amistad & Falcon System (Lower Rio Grande/Rí-o Bravo)

NASA Astrophysics Data System (ADS)

Serrat-Capdevila, A.; Valdes, J. B.

2005-12-01

An optimization approach for the operation of international multi-reservoir systems is presented. The approach uses Stochastic Dynamic Programming (SDP) algorithms, both steady-state and real-time, to develop two models. In the first model, the reservoirs and flows of the system are aggregated to yield an equivalent reservoir, and the obtained operating policies are disaggregated using a non-linear optimization procedure for each reservoir and for each nation water balance. In the second model a multi-reservoir approach is applied, disaggregating the releases for each country water share in each reservoir. The non-linear disaggregation algorithm uses SDP-derived operating policies as boundary conditions for a local time-step optimization. Finally, the performance of the different approaches and methods is compared. These models are applied to the Amistad-Falcon International Reservoir System as part of a binational dynamic modeling effort to develop a decision support system tool for a better management of the water resources in the Lower Rio Grande Basin, currently enduring a severe drought.

Self-consistent adjoint analysis for topology optimization of electromagnetic waves

NASA Astrophysics Data System (ADS)

Deng, Yongbo; Korvink, Jan G.

2018-05-01

In topology optimization of electromagnetic waves, the Gâteaux differentiability of the conjugate operator to the complex field variable results in the complexity of the adjoint sensitivity, which evolves the original real-valued design variable to be complex during the iterative solution procedure. Therefore, the self-inconsistency of the adjoint sensitivity is presented. To enforce the self-consistency, the real part operator has been used to extract the real part of the sensitivity to keep the real-value property of the design variable. However, this enforced self-consistency can cause the problem that the derived structural topology has unreasonable dependence on the phase of the incident wave. To solve this problem, this article focuses on the self-consistent adjoint analysis of the topology optimization problems for electromagnetic waves. This self-consistent adjoint analysis is implemented by splitting the complex variables of the wave equations into the corresponding real parts and imaginary parts, sequentially substituting the split complex variables into the wave equations with deriving the coupled equations equivalent to the original wave equations, where the infinite free space is truncated by the perfectly matched layers. Then, the topology optimization problems of electromagnetic waves are transformed into the forms defined on real functional spaces instead of complex functional spaces; the adjoint analysis of the topology optimization problems is implemented on real functional spaces with removing the variational of the conjugate operator; the self-consistent adjoint sensitivity is derived, and the phase-dependence problem is avoided for the derived structural topology. Several numerical examples are implemented to demonstrate the robustness of the derived self-consistent adjoint analysis.

Mitigating Short-Term Variations of Photovoltaic Generation Using Energy Storage with VOLTTRON

NASA Astrophysics Data System (ADS)

Morrissey, Kevin

A smart-building communications system performs smoothing on photovoltaic (PV) power generation using a battery energy storage system (BESS). The system runs using VOLTTRON(TM), a multi-agent python-based software platform dedicated to power systems. The VOLTTRON(TM) system designed for this project runs synergistically with the larger University of Washington VOLTTRON(TM) environment, which is designed to operate UW device communications and databases as well as to perform real-time operations for research. One such research algorithm that operates simultaneously with this PV Smoothing System is an energy cost optimization system which optimizes net demand and associated cost throughout a day using the BESS. The PV Smoothing System features an active low-pass filter with an adaptable time constant, as well as adjustable limitations on the output power and accumulated battery energy of the BESS contribution. The system was analyzed using 26 days of PV generation at 1-second resolution. PV smoothing was studied with unconstrained BESS contribution as well as under a broad range of BESS constraints analogous to variable-sized storage. It was determined that a large inverter output power was more important for PV smoothing than a large battery energy capacity. Two methods of selecting the time constant in real time, static and adaptive, are studied for their impact on system performance. It was found that both systems provide a high level of PV smoothing performance, within 8% of the ideal case where the best time constant is known ahead of time. The system was run in real time using VOLTTRON(TM) with BESS limitations of 5 kW/6.5 kWh and an adaptive update period of 7 days. The system behaved as expected given the BESS parameters and time constant selection methods, providing smoothing on the PV generation and updating the time constant periodically using the adaptive time constant selection method.

How gamma radiation processing systems are benefiting from the latest advances in information technology

NASA Astrophysics Data System (ADS)

Gibson, Wayne H.; Levesque, Daniel

2000-03-01

This paper discusses how gamma irradiation plants are putting the latest advances in computer and information technology to use for better process control, cost savings, and strategic advantages. Some irradiator operations are gaining significant benefits by integrating computer technology and robotics with real-time information processing, multi-user databases, and communication networks. The paper reports on several irradiation facilities that are making good use of client/server LANs, user-friendly graphics interfaces, supervisory control and data acquisition (SCADA) systems, distributed I/O with real-time sensor devices, trending analysis, real-time product tracking, dynamic product scheduling, and automated dosimetry reading. These plants are lowering costs by fast and reliable reconciliation of dosimetry data, easier validation to GMP requirements, optimizing production flow, and faster release of sterilized products to market. There is a trend in the manufacturing sector towards total automation using "predictive process control". Real-time verification of process parameters "on-the-run" allows control parameters to be adjusted appropriately, before the process strays out of limits. Applying this technology to the gamma radiation process, control will be based on monitoring the key parameters such as time, and making adjustments during the process to optimize quality and throughput. Dosimetry results will be used as a quality control measurement rather than as a final monitor for the release of the product. Results are correlated with the irradiation process data to quickly and confidently reconcile variations. Ultimately, a parametric process control system utilizing responsive control, feedback and verification will not only increase productivity and process efficiency, but can also result in operating within tighter dose control set points.

Characterization of a Raman spectroscopy probe system for intraoperative brain tissue classification

PubMed Central

Desroches, Joannie; Jermyn, Michael; Mok, Kelvin; Lemieux-Leduc, Cédric; Mercier, Jeanne; St-Arnaud, Karl; Urmey, Kirk; Guiot, Marie-Christine; Marple, Eric; Petrecca, Kevin; Leblond, Frédéric

2015-01-01

A detailed characterization study is presented of a Raman spectroscopy system designed to maximize the volume of resected cancer tissue in glioma surgery based on in vivo molecular tissue characterization. It consists of a hand-held probe system measuring spectrally resolved inelastically scattered light interacting with tissue, designed and optimized for in vivo measurements. Factors such as linearity of the signal with integration time and laser power, and their impact on signal to noise ratio, are studied leading to optimal data acquisition parameters. The impact of ambient light sources in the operating room is assessed and recommendations made for optimal operating conditions. In vivo Raman spectra of normal brain, cancer and necrotic tissue were measured in 10 patients, demonstrating that real-time inelastic scattering measurements can distinguish necrosis from vital tissue (including tumor and normal brain tissue) with an accuracy of 87%, a sensitivity of 84% and a specificity of 89%. PMID:26203368

Improving Mid-Course Flight Through an Application of Real-Time Optimal Control

DTIC Science & Technology

2017-12-01

COURSE FLIGHT THROUGH AN APPLICATION OF REAL- TIME OPTIMAL CONTROL by Mark R. Roncoroni December 2017 Thesis Advisor: Ronald Proulx Co...collection of information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources...AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE IMPROVING MID-COURSE FLIGHT THROUGH AN APPLICATION OF REAL- TIME OPTIMAL CONTROL 5. FUNDING

Conjugated polyelectrolyte based real-time fluorescence assay for phospholipase C.

PubMed

Liu, Yan; Ogawa, Katsu; Schanze, Kirk S

2008-01-01

A fluorescence turnoff assay for phospholipase C (PLC) from Clostridium perfringens is developed based on the reversible interaction between the natural substrate, phosphatidylcholine, and a fluorescent, water-soluble conjugated polyelectrolyte (CPE). The fluorescence intensity of the CPE in water is increased substantially by the addition of the phospholipid due to the formation of a CPE-lipid complex. Incubation of the CPE-lipid complex with the enzyme PLC causes the fluorescence intensity to decrease (turnoff sensor); the response arises due to PLC-catalyzed hydrolysis of the phosphatidylcholine, which effectively disrupts the CPE-lipid complex. The PLC assay operates with phospholipid substrate concentrations in the micromolar range, and the analytical detection limit for PLC is <1 nM. The optimized assay provides a convenient, rapid, and real-time sensor for PLC activity. The real-time fluorescence intensity from the CPE can be converted to substrate concentration by using an ex situ calibration curve, allowing PLC-catalyzed reaction rates and kinetic parameters to be determined. PLC activation by Ca2+ and inhibition by EDTA and fluoride ion are demonstrated using the optimized sensor.

Use of NTRIP for optimizing the decoding algorithm for real-time data streams.

PubMed

He, Zhanke; Tang, Wenda; Yang, Xuhai; Wang, Liming; Liu, Jihua

2014-10-10

As a network transmission protocol, Networked Transport of RTCM via Internet Protocol (NTRIP) is widely used in GPS and Global Orbiting Navigational Satellite System (GLONASS) Augmentation systems, such as Continuous Operational Reference System (CORS), Wide Area Augmentation System (WAAS) and Satellite Based Augmentation Systems (SBAS). With the deployment of BeiDou Navigation Satellite system(BDS) to serve the Asia-Pacific region, there are increasing needs for ground monitoring of the BeiDou Navigation Satellite system and the development of the high-precision real-time BeiDou products. This paper aims to optimize the decoding algorithm of NTRIP Client data streams and the user authentication strategies of the NTRIP Caster based on NTRIP. The proposed method greatly enhances the handling efficiency and significantly reduces the data transmission delay compared with the Federal Agency for Cartography and Geodesy (BKG) NTRIP. Meanwhile, a transcoding method is proposed to facilitate the data transformation from the BINary EXchange (BINEX) format to the RTCM format. The transformation scheme thus solves the problem of handing real-time data streams from Trimble receivers in the BeiDou Navigation Satellite System indigenously developed by China.

Real-time control system for adaptive resonator

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

Flath, L; An, J; Brase, J

2000-07-24

Sustained operation of high average power solid-state lasers currently requires an adaptive resonator to produce the optimal beam quality. We describe the architecture of a real-time adaptive control system for correcting intra-cavity aberrations in a heat capacity laser. Image data collected from a wavefront sensor are processed and used to control phase with a high-spatial-resolution deformable mirror. Our controller takes advantage of recent developments in low-cost, high-performance processor technology. A desktop-based computational engine and object-oriented software architecture replaces the high-cost rack-mount embedded computers of previous systems.

Biodegradability and toxicity assessment of a real textile wastewater effluent treated by an optimized electrocoagulation process.

PubMed

Manenti, Diego R; Módenes, Aparecido N; Soares, Petrick A; Boaventura, Rui A R; Palácio, Soraya M; Borba, Fernando H; Espinoza-Quiñones, Fernando R; Bergamasco, Rosângela; Vilar, Vítor J P

2015-01-01

In this work, the application of an iron electrode-based electrocoagulation (EC) process on the treatment of a real textile wastewater (RTW) was investigated. In order to perform an efficient integration of the EC process with a biological oxidation one, an enhancement in the biodegradability and low toxicity of final compounds was sought. Optimal values of EC reactor operation parameters (pH, current density and electrolysis time) were achieved by applying a full factorial 3(3) experimental design. Biodegradability and toxicity assays were performed on treated RTW samples obtained at the optimal values of: pH of the solution (7.0), current density (142.9 A m(-2)) and different electrolysis times. As response variables for the biodegradability and toxicity assessment, the Zahn-Wellens test (Dt), the ratio values of dissolved organic carbon (DOC) relative to low-molecular-weight carboxylates anions (LMCA) and lethal concentration 50 (LC50) were used. According to the Dt, the DOC/LMCA ratio and LC50, an electrolysis time of 15 min along with the optimal values of pH and current density were suggested as suitable for a next stage of treatment based on a biological oxidation process.

Objects Architecture: A Comprehensive Design Approach for Real-Time, Distributed, Fault-Tolerant, Reactive Operating Systems.

DTIC Science & Technology

1987-09-01

real - time operating system should be efficient from the real-time point...5,8]) system naming scheme. 3.2 Protecting Objects Real-time embedded systems usually neglect protection mechanisms. However, a real - time operating system cannot...allocation mechanism should adhere to application constraints. This strong relationship between a real - time operating system and the application

Etude experimentale et optimisation d'un systeme hybride hydraulique pour camions a ordures et amelioration des performances par raffinement de sa logique de controle

NASA Astrophysics Data System (ADS)

Lacroix, Benoit

The aim of this thesis is to demonstrate experimentally the operation of a hydraulic hybrid system specifically dedicated to the application of refuse trucks in addition to proposing solutions to improve its control strategy. The developed hybrid system recovers the vehicle's kinetic energy during braking. A variable displacement hydraulic motor then uses the energy stored in a hydraulic accumulator to assist the internal combustion engine (ICE) at suitable times. The particular aspect of this system is that assistance to the ICE can occur when it operates at idle and drives the auxiliary hydraulic equipment of the refuse truck. Essentially, the control strategy initially developed maximizes the recovery of braking energy and uses that energy to minimize the solicitation of the ICE at idle. The experimental results obtained with two prototypes tested in real operating conditions show that the hybrid system can recover a significant portion of braking energy. In addition, the results show that it is possible to reduce the load on the ICE during idle with the application of an assisting torque. However, the advantage of assisting the ICE in specific areas of the operating range is slim since the ICE's gross efficiency varies only slightly depending on conditions of operation. This is confirmed by the optimization of the control logic using deterministic dynamic programming. Indeed, by managing the pressure in the accumulator to maximize the amount of energy recovered during braking and by dosing the assistance to the ICE in an ideal fashion, the optimal control only managed to improve fuel savings by 6% in comparison to the original control. Therefore, since the efforts that would be required to emulate the ideal behavior in real time are significant for a relatively small and uncertain gain, the initial control logic is considered near optimal. Finally, this thesis proposes an improved version of the torque assisting hybrid system that could shut down the ICE when the vehicle is stopped while maintaining functional the auxiliary hydraulic equipment. An optimization of the control logic indicates that proper management of the pressure in the accumulator would allow turning off the ICE most of the time at stop and thus, would increase the fuel savings by over 40% compared to the original system. The simulation of a basic control strategy shows that such pressure management may be feasible in real time and that the potential gain in fuel savings is achievable. Keywords: hybrid system, hydraulic, control, refuse truck.

Mixed integer simulation optimization for optimal hydraulic fracturing and production of shale gas fields

NASA Astrophysics Data System (ADS)

Li, J. C.; Gong, B.; Wang, H. G.

2016-08-01

Optimal development of shale gas fields involves designing a most productive fracturing network for hydraulic stimulation processes and operating wells appropriately throughout the production time. A hydraulic fracturing network design-determining well placement, number of fracturing stages, and fracture lengths-is defined by specifying a set of integer ordered blocks to drill wells and create fractures in a discrete shale gas reservoir model. The well control variables such as bottom hole pressures or production rates for well operations are real valued. Shale gas development problems, therefore, can be mathematically formulated with mixed-integer optimization models. A shale gas reservoir simulator is used to evaluate the production performance for a hydraulic fracturing and well control plan. To find the optimal fracturing design and well operation is challenging because the problem is a mixed integer optimization problem and entails computationally expensive reservoir simulation. A dynamic simplex interpolation-based alternate subspace (DSIAS) search method is applied for mixed integer optimization problems associated with shale gas development projects. The optimization performance is demonstrated with the example case of the development of the Barnett Shale field. The optimization results of DSIAS are compared with those of a pattern search algorithm.

Optical Sensor for real-time Monitoring of CO(2) Laser Welding Process.

PubMed

Ancona, A; Spagnolo, V; Lugarà, P M; Ferrara, M

2001-11-20

An optical sensor for real-time monitoring of laser welding based on a spectroscopic study of the optical emission of plasma plumes has been developed. The welding plasma's electron temperature was contemporarily monitored for three of the chemical species that constitute the plasma plume by use of related emission lines. The evolution of electron temperature was recorded and analyzed during several welding procedures carried out under various operating conditions. A clear correlation between the mean value and the standard deviation of the plasma's electron temperature and the quality of the welded joint has been found. We used this information to find optimal welding parameters and for real-time detection of weld defects such as crater formation, lack of penetration, weld disruptions, and seam oxidation.

Implementation and on-sky results of an optimal wavefront controller for the MMT NGS adaptive optics system

NASA Astrophysics Data System (ADS)

Powell, Keith B.; Vaitheeswaran, Vidhya

2010-07-01

The MMT observatory has recently implemented and tested an optimal wavefront controller for the NGS adaptive optics system. Open loop atmospheric data collected at the telescope is used as the input to a MATLAB based analytical model. The model uses nonlinear constrained minimization to determine controller gains and optimize the system performance. The real-time controller performing the adaptive optics close loop operation is implemented on a dedicated high performance PC based quad core server. The controller algorithm is written in C and uses the GNU scientific library for linear algebra. Tests at the MMT confirmed the optimal controller significantly reduced the residual RMS wavefront compared with the previous controller. Significant reductions in image FWHM and increased peak intensities were obtained in J, H and K-bands. The optimal PID controller is now operating as the baseline wavefront controller for the MMT NGS-AO system.

Optimal PGU operation strategy in CHP systems

NASA Astrophysics Data System (ADS)

Yun, Kyungtae

Traditional power plants only utilize about 30 percent of the primary energy that they consume, and the rest of the energy is usually wasted in the process of generating or transmitting electricity. On-site and near-site power generation has been considered by business, labor, and environmental groups to improve the efficiency and the reliability of power generation. Combined heat and power (CHP) systems are a promising alternative to traditional power plants because of the high efficiency and low CO2 emission achieved by recovering waste thermal energy produced during power generation. A CHP operational algorithm designed to optimize operational costs must be relatively simple to implement in practice such as to minimize the computational requirements from the hardware to be installed. This dissertation focuses on the following aspects pertaining the design of a practical CHP operational algorithm designed to minimize the operational costs: (a) real-time CHP operational strategy using a hierarchical optimization algorithm; (b) analytic solutions for cost-optimal power generation unit operation in CHP Systems; (c) modeling of reciprocating internal combustion engines for power generation and heat recovery; (d) an easy to implement, effective, and reliable hourly building load prediction algorithm.

Optimal policies for simultaneous energy consumption and ancillary service provision for flexible loads under stochastic prices and no capacity reservation constraint

NASA Astrophysics Data System (ADS)

Kefayati, Mahdi; Baldick, Ross

2015-07-01

Flexible loads, i.e. the loads whose power trajectory is not bound to a specific one, constitute a sizable portion of current and future electric demand. This flexibility can be used to improve the performance of the grid, should the right incentives be in place. In this paper, we consider the optimal decision making problem faced by a flexible load, demanding a certain amount of energy over its availability period, subject to rate constraints. The load is also capable of providing ancillary services (AS) by decreasing or increasing its consumption in response to signals from the independent system operator (ISO). Under arbitrarily distributed and correlated Markovian energy and AS prices, we obtain the optimal policy for minimising expected total cost, which includes cost of energy and benefits from AS provision, assuming no capacity reservation requirement for AS provision. We also prove that the optimal policy has a multi-threshold form and can be computed, stored and operated efficiently. We further study the effectiveness of our proposed optimal policy and its impact on the grid. We show that, while optimal simultaneous consumption and AS provision under real-time stochastic prices are achievable with acceptable computational burden, the impact of adopting such real-time pricing schemes on the network might not be as good as suggested by the majority of the existing literature. In fact, we show that such price responsive loads are likely to induce peak-to-average ratios much more than what is observed in the current distribution networks and adversely affect the grid.

Regulation of Dynamical Systems to Optimal Solutions of Semidefinite Programs: Algorithms and Applications to AC Optimal Power Flow

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

Dall'Anese, Emiliano; Dhople, Sairaj V.; Giannakis, Georgios B.

2015-07-01

This paper considers a collection of networked nonlinear dynamical systems, and addresses the synthesis of feedback controllers that seek optimal operating points corresponding to the solution of pertinent network-wide optimization problems. Particular emphasis is placed on the solution of semidefinite programs (SDPs). The design of the feedback controller is grounded on a dual e-subgradient approach, with the dual iterates utilized to dynamically update the dynamical-system reference signals. Global convergence is guaranteed for diminishing stepsize rules, even when the reference inputs are updated at a faster rate than the dynamical-system settling time. The application of the proposed framework to the controlmore » of power-electronic inverters in AC distribution systems is discussed. The objective is to bridge the time-scale separation between real-time inverter control and network-wide optimization. Optimization objectives assume the form of SDP relaxations of prototypical AC optimal power flow problems.« less

Using real time traveler demand data to optimize commuter rail feeder systems.

DOT National Transportation Integrated Search

2012-08-01

"This report focuses on real time optimization of the Commuter Rail Circulator Route Network Design Problem (CRCNDP). The route configuration of the circulator system where to stop and the route among the stops is determined on a real-time ba...

Manual control models of industrial management

NASA Technical Reports Server (NTRS)

Crossman, E. R. F. W.

1972-01-01

The industrial engineer is often required to design and implement control systems and organization for manufacturing and service facilities, to optimize quality, delivery, and yield, and minimize cost. Despite progress in computer science most such systems still employ human operators and managers as real-time control elements. Manual control theory should therefore be applicable to at least some aspects of industrial system design and operations. Formulation of adequate model structures is an essential prerequisite to progress in this area; since real-world production systems invariably include multilevel and multiloop control, and are implemented by timeshared human effort. A modular structure incorporating certain new types of functional element, has been developed. This forms the basis for analysis of an industrial process operation. In this case it appears that managerial controllers operate in a discrete predictive mode based on fast time modelling, with sampling interval related to plant dynamics. Successive aggregation causes reduced response bandwidth and hence increased sampling interval as a function of level.

A self optimizing synthetic organic reactor system using real-time in-line NMR spectroscopy.

PubMed

Sans, Victor; Porwol, Luzian; Dragone, Vincenza; Cronin, Leroy

2015-02-01

A configurable platform for synthetic chemistry incorporating an in-line benchtop NMR that is capable of monitoring and controlling organic reactions in real-time is presented. The platform is controlled via a modular LabView software control system for the hardware, NMR, data analysis and feedback optimization. Using this platform we report the real-time advanced structural characterization of reaction mixtures, including 19 F, 13 C, DEPT, 2D NMR spectroscopy (COSY, HSQC and 19 F-COSY) for the first time. Finally, the potential of this technique is demonstrated through the optimization of a catalytic organic reaction in real-time, showing its applicability to self-optimizing systems using criteria such as stereoselectivity, multi-nuclear measurements or 2D correlations.

A Parallel Biological Optimization Algorithm to Solve the Unbalanced Assignment Problem Based on DNA Molecular Computing.

PubMed

Wang, Zhaocai; Pu, Jun; Cao, Liling; Tan, Jian

2015-10-23

The unbalanced assignment problem (UAP) is to optimally resolve the problem of assigning n jobs to m individuals (m < n), such that minimum cost or maximum profit obtained. It is a vitally important Non-deterministic Polynomial (NP) complete problem in operation management and applied mathematics, having numerous real life applications. In this paper, we present a new parallel DNA algorithm for solving the unbalanced assignment problem using DNA molecular operations. We reasonably design flexible-length DNA strands representing different jobs and individuals, take appropriate steps, and get the solutions of the UAP in the proper length range and O(mn) time. We extend the application of DNA molecular operations and simultaneity to simplify the complexity of the computation.

Real-Time CORBA

DTIC Science & Technology

2000-10-01

control systems and prototyped the approach by porting the ILU ORB from Xerox to the Lynx real - time operating system . They then provided a distributed...compliant real - time operating system , a real-time ORB, and an ODMG-compliant real-time ODBMS [12]. The MITRE system is an infrastructure for...the server’s local operating system can handle. For instance, on a node controlled by the VXWorks real - time operating system with 256 local

Affordable multisensor digital video architecture for 360° situational awareness displays

NASA Astrophysics Data System (ADS)

Scheiner, Steven P.; Khan, Dina A.; Marecki, Alexander L.; Berman, David A.; Carberry, Dana

2011-06-01

One of the major challenges facing today's military ground combat vehicle operations is the ability to achieve and maintain full-spectrum situational awareness while under armor (i.e. closed hatch). Thus, the ability to perform basic tasks such as driving, maintaining local situational awareness, surveillance, and targeting will require a high-density array of real time information be processed, distributed, and presented to the vehicle operators and crew in near real time (i.e. low latency). Advances in display and sensor technologies are providing never before seen opportunities to supply large amounts of high fidelity imagery and video to the vehicle operators and crew in real time. To fully realize the advantages of these emerging display and sensor technologies, an underlying digital architecture must be developed that is capable of processing these large amounts of video and data from separate sensor systems and distributing it simultaneously within the vehicle to multiple vehicle operators and crew. This paper will examine the systems and software engineering efforts required to overcome these challenges and will address development of an affordable, integrated digital video architecture. The approaches evaluated will enable both current and future ground combat vehicle systems the flexibility to readily adopt emerging display and sensor technologies, while optimizing the Warfighter Machine Interface (WMI), minimizing lifecycle costs, and improve the survivability of the vehicle crew working in closed-hatch systems during complex ground combat operations.

Proposed algorithm to improve job shop production scheduling using ant colony optimization method

NASA Astrophysics Data System (ADS)

Pakpahan, Eka KA; Kristina, Sonna; Setiawan, Ari

2017-12-01

This paper deals with the determination of job shop production schedule on an automatic environment. On this particular environment, machines and material handling system are integrated and controlled by a computer center where schedule were created and then used to dictate the movement of parts and the operations at each machine. This setting is usually designed to have an unmanned production process for a specified interval time. We consider here parts with various operations requirement. Each operation requires specific cutting tools. These parts are to be scheduled on machines each having identical capability, meaning that each machine is equipped with a similar set of cutting tools therefore is capable of processing any operation. The availability of a particular machine to process a particular operation is determined by the remaining life time of its cutting tools. We proposed an algorithm based on the ant colony optimization method and embedded them on matlab software to generate production schedule which minimize the total processing time of the parts (makespan). We test the algorithm on data provided by real industry and the process shows a very short computation time. This contributes a lot to the flexibility and timelines targeted on an automatic environment.

The case for a Supersite for real-time GNSS hazard monitoring on a global scale

NASA Astrophysics Data System (ADS)

Bar-Sever, Y. E.

2017-12-01

Real-time measurements from many hundreds of GNSS tracking sites around the world are publicly available today, and the amount of streaming data is steadily increasing as national agencies densify their local and global infrastructure for natural hazard monitoring and a variety of geodetic, cadastral, and other civil applications. Thousands of such sites can soon be expected on a global scale. It is a challenge to manage and make optimal use of this massive amount of real-time data. We advocate the creation of Supersite(s), in the parlance of the U.N. Global Earth Observation System of Systems (https://www.earthobservations.org/geoss.php), to generate high level real-time data products from the raw GNSS measurements from all available sources (many thousands of sites). These products include: • High rate, real-time positioning time series for assessing rapid crustal motion due to Earthquakes, volcanic activities, land slides, etc. • Co-seismic displacement to help resolve earthquake mechanism and moment magnitude • Real-time total electron content (TEC) fluctuations to augment Dart buoy in detecting and tracking tsunamis • Aggregation of the many disparate raw data dispensation servers (Casters)Recognizing that natural hazards transcend national boundaries in terms of direct and indirect (e.g., economical, security) impact, the benefits from centralized, authoritative processing of GNSS measurements is manifold: • Offers a one-stop shop to less developed nations and institutions for raw and high-level products, in support of research and applications • Promotes the installation of tracking sites and the contribution of data from nations without the ability to process the data • Reduce dependency on local responsible agencies impacted by a natural disaster • Reliable 24/7 operations, independent of voluntary, best effort contributions from good-willing scientific organizationsThe JPL GNSS Real-Time Earthquake and Tsunami (GREAT) Alert has been operating as a prototype for such a Supersite for nearly a decade, processing in real-time data from hundreds of global and regional GNSS tracking sites. The existing operational infrastructure, complete self-sufficiency, and proven reliability can be leveraged at low cost to provide valuable natural hazard monitoring to the U.S. and the world.

Closed-Loop Optimal Control Implementations for Space Applications

DTIC Science & Technology

2016-12-01

analyses of a series of optimal control problems, several real- time optimal control algorithms are developed that continuously adapt to feedback on the...through the analyses of a series of optimal control problems, several real- time optimal control algorithms are developed that continuously adapt to...information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Real-time monitoring of CO2 storage sites: Application to Illinois Basin-Decatur Project

USGS Publications Warehouse

Picard, G.; Berard, T.; Chabora, E.; Marsteller, S.; Greenberg, S.; Finley, R.J.; Rinck, U.; Greenaway, R.; Champagnon, C.; Davard, J.

2011-01-01

Optimization of carbon dioxide (CO2) storage operations for efficiency and safety requires use of monitoring techniques and implementation of control protocols. The monitoring techniques consist of permanent sensors and tools deployed for measurement campaigns. Large amounts of data are thus generated. These data must be managed and integrated for interpretation at different time scales. A fast interpretation loop involves combining continuous measurements from permanent sensors as they are collected to enable a rapid response to detected events; a slower loop requires combining large datasets gathered over longer operational periods from all techniques. The purpose of this paper is twofold. First, it presents an analysis of the monitoring objectives to be performed in the slow and fast interpretation loops. Second, it describes the implementation of the fast interpretation loop with a real-time monitoring system at the Illinois Basin-Decatur Project (IBDP) in Illinois, USA. ?? 2011 Published by Elsevier Ltd.

COLA: Optimizing Stream Processing Applications via Graph Partitioning

NASA Astrophysics Data System (ADS)

Khandekar, Rohit; Hildrum, Kirsten; Parekh, Sujay; Rajan, Deepak; Wolf, Joel; Wu, Kun-Lung; Andrade, Henrique; Gedik, Buğra

In this paper, we describe an optimization scheme for fusing compile-time operators into reasonably-sized run-time software units called processing elements (PEs). Such PEs are the basic deployable units in System S, a highly scalable distributed stream processing middleware system. Finding a high quality fusion significantly benefits the performance of streaming jobs. In order to maximize throughput, our solution approach attempts to minimize the processing cost associated with inter-PE stream traffic while simultaneously balancing load across the processing hosts. Our algorithm computes a hierarchical partitioning of the operator graph based on a minimum-ratio cut subroutine. We also incorporate several fusion constraints in order to support real-world System S jobs. We experimentally compare our algorithm with several other reasonable alternative schemes, highlighting the effectiveness of our approach.

Runway Operations Planning: A Two-Stage Solution Methodology

NASA Technical Reports Server (NTRS)

Anagnostakis, Ioannis; Clarke, John-Paul

2003-01-01

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

Optimal inverse functions created via population-based optimization.

PubMed

Jennings, Alan L; Ordóñez, Raúl

2014-06-01

Finding optimal inputs for a multiple-input, single-output system is taxing for a system operator. Population-based optimization is used to create sets of functions that produce a locally optimal input based on a desired output. An operator or higher level planner could use one of the functions in real time. For the optimization, each agent in the population uses the cost and output gradients to take steps lowering the cost while maintaining their current output. When an agent reaches an optimal input for its current output, additional agents are generated in the output gradient directions. The new agents then settle to the local optima for the new output values. The set of associated optimal points forms an inverse function, via spline interpolation, from a desired output to an optimal input. In this manner, multiple locally optimal functions can be created. These functions are naturally clustered in input and output spaces allowing for a continuous inverse function. The operator selects the best cluster over the anticipated range of desired outputs and adjusts the set point (desired output) while maintaining optimality. This reduces the demand from controlling multiple inputs, to controlling a single set point with no loss in performance. Results are demonstrated on a sample set of functions and on a robot control problem.

Optimal current waveforms for brushless permanent magnet motors

NASA Astrophysics Data System (ADS)

Moehle, Nicholas; Boyd, Stephen

2015-07-01

In this paper, we give energy-optimal current waveforms for a permanent magnet synchronous motor that result in a desired average torque. Our formulation generalises previous work by including a general back-electromotive force (EMF) wave shape, voltage and current limits, an arbitrary phase winding connection, a simple eddy current loss model, and a trade-off between power loss and torque ripple. Determining the optimal current waveforms requires solving a small convex optimisation problem. We show how to use the alternating direction method of multipliers to find the optimal current in milliseconds or hundreds of microseconds, depending on the processor used, which allows the possibility of generating optimal waveforms in real time. This allows us to adapt in real time to changes in the operating requirements or in the model, such as a change in resistance with winding temperature, or even gross changes like the failure of one winding. Suboptimal waveforms are available in tens or hundreds of microseconds, allowing for quick response after abrupt changes in the desired torque. We demonstrate our approach on a simple numerical example, in which we give the optimal waveforms for a motor with a sinusoidal back-EMF, and for a motor with a more complicated, nonsinusoidal waveform, in both the constant-torque region and constant-power region.

Operational and Strategic Implementation of Dynamic Line Rating for Optimized Wind Energy Generation Integration

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

Gentle, Jake Paul

2016-12-01

One primary goal of rendering today’s transmission grid “smarter” is to optimize and better manage its power transfer capacity in real time. Power transfer capacity is affected by three main elements: stability, voltage limits, and thermal ratings. All three are critical, but thermal ratings represent the greatest opportunity to quickly, reliably and economically utilize the grid’s true capacity. With the “Smarter Grid”, new solutions have been sought to give operators a better grasp on real time conditions, allowing them to manage and extend the usefulness of existing transmission infrastructure in a safe and reliable manner. The objective of the INLmore » Wind Program is to provide industry a Dynamic Line Rating (DLR) solution that is state of the art as measured by cost, accuracy and dependability, to enable human operators to make informed decisions and take appropriate actions without human or system overloading and impacting the reliability of the grid. In addition to mitigating transmission line congestion to better integrate wind, DLR also offers the opportunity to improve the grid with optimized utilization of transmission lines to relieve congestion in general. As wind-generated energy has become a bigger part of the nation’s energy portfolio, researchers have learned that wind not only turns turbine blades to generate electricity, but can cool transmission lines and increase transfer capabilities significantly, sometimes up to 60 percent. INL’s DLR development supports EERE and The Wind Energy Technology Office’s goals by informing system planners and grid operators of available transmission capacity, beyond typical Static Line Ratings (SLR). SLRs are based on a fixed set of conservative environmental conditions to establish a limit on the amount of current lines can safely carry without overheating. Using commercially available weather monitors mounted on industry informed custom brackets developed by INL in combination with Computational Fluid Dynamics (CFD) enhanced weather analysis and DLR software, INL’s project offers the potential of safely providing line ampacities up to 40 percent or more above existing SLRs, by using real time information rather than overly conservative SLR.« less

A study of the application of singular perturbation theory. [development of a real time algorithm for optimal three dimensional aircraft maneuvers

NASA Technical Reports Server (NTRS)

Mehra, R. K.; Washburn, R. B.; Sajan, S.; Carroll, J. V.

1979-01-01

A hierarchical real time algorithm for optimal three dimensional control of aircraft is described. Systematic methods are developed for real time computation of nonlinear feedback controls by means of singular perturbation theory. The results are applied to a six state, three control variable, point mass model of an F-4 aircraft. Nonlinear feedback laws are presented for computing the optimal control of throttle, bank angle, and angle of attack. Real Time capability is assessed on a TI 9900 microcomputer. The breakdown of the singular perturbation approximation near the terminal point is examined Continuation methods are examined to obtain exact optimal trajectories starting from the singular perturbation solutions.

Advanced Hard Real-Time Operating System, the Maruti Project. Part 2.

DTIC Science & Technology

1997-01-01

Real - Time Operating System , The Maruti Project DASG-60-92-C-0055 5b. Program Element # 62301E 6. Author(s...The maruti hard real - time " operating system . A CM SIGOPS, Operating Systems Review. 23:90-106, July 1989. 254 !1 110) C. L. Liu and J. Layland...February 14, 1995 Abstract The Maruti Real - Time Operating System was developed for applications that must meet hard real-time constraints. In order

Three Experiments Examining the Use of Electroencephalogram,Event-Related Potentials, and Heart-Rate Variability for Real-Time Human-Centered Adaptive Automation Design

NASA Technical Reports Server (NTRS)

Prinzel, Lawrence J., III; Parasuraman, Raja; Freeman, Frederick G.; Scerbo, Mark W.; Mikulka, Peter J.; Pope, Alan T.

2003-01-01

Adaptive automation represents an advanced form of human-centered automation design. The approach to automation provides for real-time and model-based assessments of human-automation interaction, determines whether the human has entered into a hazardous state of awareness and then modulates the task environment to keep the operator in-the-loop , while maintaining an optimal state of task engagement and mental alertness. Because adaptive automation has not matured, numerous challenges remain, including what the criteria are, for determining when adaptive aiding and adaptive function allocation should take place. Human factors experts in the area have suggested a number of measures including the use of psychophysiology. This NASA Technical Paper reports on three experiments that examined the psychophysiological measures of event-related potentials, electroencephalogram, and heart-rate variability for real-time adaptive automation. The results of the experiments confirm the efficacy of these measures for use in both a developmental and operational role for adaptive automation design. The implications of these results and future directions for psychophysiology and human-centered automation design are discussed.

Computational Modeling and Real-Time Control of Patient-Specific Laser Treatment of Cancer

PubMed Central

Fuentes, D.; Oden, J. T.; Diller, K. R.; Hazle, J. D.; Elliott, A.; Shetty, A.; Stafford, R. J.

2014-01-01

An adaptive feedback control system is presented which employs a computational model of bioheat transfer in living tissue to guide, in real-time, laser treatments of prostate cancer monitored by magnetic resonance thermal imaging (MRTI). The system is built on what can be referred to as cyberinfrastructure - a complex structure of high-speed network, large-scale parallel computing devices, laser optics, imaging, visualizations, inverse-analysis algorithms, mesh generation, and control systems that guide laser therapy to optimally control the ablation of cancerous tissue. The computational system has been successfully tested on in-vivo, canine prostate. Over the course of an 18 minute laser induced thermal therapy (LITT) performed at M.D. Anderson Cancer Center (MDACC) in Houston, Texas, the computational models were calibrated to intra-operative real time thermal imaging treatment data and the calibrated models controlled the bioheat transfer to within 5°C of the predetermined treatment plan. The computational arena is in Austin, Texas and managed at the Institute for Computational Engineering and Sciences (ICES). The system is designed to control the bioheat transfer remotely while simultaneously providing real-time remote visualization of the on-going treatment. Post operative histology of the canine prostate reveal that the damage region was within the targeted 1.2cm diameter treatment objective. PMID:19148754

Computational modeling and real-time control of patient-specific laser treatment of cancer.

PubMed

Fuentes, D; Oden, J T; Diller, K R; Hazle, J D; Elliott, A; Shetty, A; Stafford, R J

2009-04-01

An adaptive feedback control system is presented which employs a computational model of bioheat transfer in living tissue to guide, in real-time, laser treatments of prostate cancer monitored by magnetic resonance thermal imaging. The system is built on what can be referred to as cyberinfrastructure-a complex structure of high-speed network, large-scale parallel computing devices, laser optics, imaging, visualizations, inverse-analysis algorithms, mesh generation, and control systems that guide laser therapy to optimally control the ablation of cancerous tissue. The computational system has been successfully tested on in vivo, canine prostate. Over the course of an 18 min laser-induced thermal therapy performed at M.D. Anderson Cancer Center (MDACC) in Houston, Texas, the computational models were calibrated to intra-operative real-time thermal imaging treatment data and the calibrated models controlled the bioheat transfer to within 5 degrees C of the predetermined treatment plan. The computational arena is in Austin, Texas and managed at the Institute for Computational Engineering and Sciences (ICES). The system is designed to control the bioheat transfer remotely while simultaneously providing real-time remote visualization of the on-going treatment. Post-operative histology of the canine prostate reveal that the damage region was within the targeted 1.2 cm diameter treatment objective.

Stimulation of a turbofan engine for evaluation of multivariable optimal control concepts. [(computerized simulation)

NASA Technical Reports Server (NTRS)

Seldner, K.

1976-01-01

The development of control systems for jet engines requires a real-time computer simulation. The simulation provides an effective tool for evaluating control concepts and problem areas prior to actual engine testing. The development and use of a real-time simulation of the Pratt and Whitney F100-PW100 turbofan engine is described. The simulation was used in a multi-variable optimal controls research program using linear quadratic regulator theory. The simulation is used to generate linear engine models at selected operating points and evaluate the control algorithm. To reduce the complexity of the design, it is desirable to reduce the order of the linear model. A technique to reduce the order of the model; is discussed. Selected results between high and low order models are compared. The LQR control algorithms can be programmed on digital computer. This computer will control the engine simulation over the desired flight envelope.

Collaborative real-time scheduling of multiple PTZ cameras for multiple object tracking in video surveillance

NASA Astrophysics Data System (ADS)

Liu, Yu-Che; Huang, Chung-Lin

2013-03-01

This paper proposes a multi-PTZ-camera control mechanism to acquire close-up imagery of human objects in a surveillance system. The control algorithm is based on the output of multi-camera, multi-target tracking. Three main concerns of the algorithm are (1) the imagery of human object's face for biometric purposes, (2) the optimal video quality of the human objects, and (3) minimum hand-off time. Here, we define an objective function based on the expected capture conditions such as the camera-subject distance, pan tile angles of capture, face visibility and others. Such objective function serves to effectively balance the number of captures per subject and quality of captures. In the experiments, we demonstrate the performance of the system which operates in real-time under real world conditions on three PTZ cameras.

Optimization of active distribution networks: Design and analysis of significative case studies for enabling control actions of real infrastructure

NASA Astrophysics Data System (ADS)

Moneta, Diana; Mora, Paolo; Viganò, Giacomo; Alimonti, Gianluca

2014-12-01

The diffusion of Distributed Generation (DG) based on Renewable Energy Sources (RES) requires new strategies to ensure reliable and economic operation of the distribution networks and to support the diffusion of DG itself. An advanced algorithm (DISCoVER - DIStribution Company VoltagE Regulator) is being developed to optimize the operation of active network by means of an advanced voltage control based on several regulations. Starting from forecasted load and generation, real on-field measurements, technical constraints and costs for each resource, the algorithm generates for each time period a set of commands for controllable resources that guarantees achievement of technical goals minimizing the overall cost. Before integrating the controller into the telecontrol system of the real networks, and in order to validate the proper behaviour of the algorithm and to identify possible critical conditions, a complete simulation phase has started. The first step is concerning the definition of a wide range of "case studies", that are the combination of network topology, technical constraints and targets, load and generation profiles and "costs" of resources that define a valid context to test the algorithm, with particular focus on battery and RES management. First results achieved from simulation activity on test networks (based on real MV grids) and actual battery characteristics are given, together with prospective performance on real case applications.

The optimization of total laboratory automation by simulation of a pull-strategy.

PubMed

Yang, Taho; Wang, Teng-Kuan; Li, Vincent C; Su, Chia-Lo

2015-01-01

Laboratory results are essential for physicians to diagnose medical conditions. Because of the critical role of medical laboratories, an increasing number of hospitals use total laboratory automation (TLA) to improve laboratory performance. Although the benefits of TLA are well documented, systems occasionally become congested, particularly when hospitals face peak demand. This study optimizes TLA operations. Firstly, value stream mapping (VSM) is used to identify the non-value-added time. Subsequently, batch processing control and parallel scheduling rules are devised and a pull mechanism that comprises a constant work-in-process (CONWIP) is proposed. Simulation optimization is then used to optimize the design parameters and to ensure a small inventory and a shorter average cycle time (CT). For empirical illustration, this approach is applied to a real case. The proposed methodology significantly improves the efficiency of laboratory work and leads to a reduction in patient waiting times and increased service level.

Functional Near Infrared Spectroscopy: Watching the Brain in Flight

NASA Technical Reports Server (NTRS)

Harrivel, Angela; Hearn, Tristan A.

2012-01-01

Functional Near Infrared Spectroscopy (fNIRS) is an emerging neurological sensing technique applicable to optimizing human performance in transportation operations, such as commercial aviation. Cognitive state can be determined via pattern classification of functional activations measured with fNIRS. Operational application calls for further development of algorithms and filters for dynamic artifact removal. The concept of using the frequency domain phase shift signal to tune a Kalman filter is introduced to improve the quality of fNIRS signals in real-time. Hemoglobin concentration and phase shift traces were simulated for four different types of motion artifact to demonstrate the filter. Unwanted signal was reduced by at least 43%, and the contrast of the filtered oxygenated hemoglobin signal was increased by more than 100% overall. This filtering method is a good candidate for qualifying fNIRS signals in real time without auxiliary sensors.

Modern and prospective technologies for weather modification activities: Developing a framework for integrating autonomous unmanned aircraft systems

NASA Astrophysics Data System (ADS)

DeFelice, T. P.; Axisa, Duncan

2017-09-01

This paper builds upon the processes and framework already established for identifying, integrating and testing an unmanned aircraft system (UAS) with sensing technology for use in rainfall enhancement cloud seeding programs to carry out operational activities or to monitor and evaluate seeding operations. We describe the development and assessment methodologies of an autonomous and adaptive UAS platform that utilizes in-situ real time data to sense, target and implement seeding. The development of a UAS platform that utilizes remote and in-situ real-time data to sense, target and implement seeding deployed with a companion UAS ensures optimal, safe, secure, cost-effective seeding operations, and the dataset to quantify the results of seeding. It also sets the path for an innovative, paradigm shifting approach for enhancing precipitation independent of seeding mode. UAS technology is improving and their application in weather modification must be explored to lay the foundation for future implementation. The broader significance lies in evolving improved technology and automating cloud seeding operations that lowers the cloud seeding operational footprint and optimizes their effectiveness and efficiency, while providing the temporal and spatial sensitivities to overcome the predictability or sparseness of environmental parameters needed to identify conditions suitable for seeding, and how such might be implemented. The dataset from the featured approach will contain data from concurrent Eulerian and Lagrangian perspectives over sub-cloud scales that will facilitate the development of cloud seeding decision support tools.

Autorotation flight control system

NASA Technical Reports Server (NTRS)

Bachelder, Edward N. (Inventor); Aponso, Bimal L. (Inventor); Lee, Dong-Chan (Inventor)

2011-01-01

The present invention provides computer implemented methodology that permits the safe landing and recovery of rotorcraft following engine failure. With this invention successful autorotations may be performed from well within the unsafe operating area of the height-velocity profile of a helicopter by employing the fast and robust real-time trajectory optimization algorithm that commands control motion through an intuitive pilot display, or directly in the case of autonomous rotorcraft. The algorithm generates optimal trajectories and control commands via the direct-collocation optimization method, solved using a nonlinear programming problem solver. The control inputs computed are collective pitch and aircraft pitch, which are easily tracked and manipulated by the pilot or converted to control actuator commands for automated operation during autorotation in the case of an autonomous rotorcraft. The formulation of the optimal control problem has been carefully tailored so the solutions resemble those of an expert pilot, accounting for the performance limitations of the rotorcraft and safety concerns.

Real-Time Embedded High Performance Computing: Communications Scheduling.

DTIC Science & Technology

1995-06-01

real - time operating system must explicitly limit the degradation of the timing performance of all processes as the number of processes...adequately supported by a real - time operating system , could compound the development problems encountered in the past. Many experts feel that the... real - time operating system support for an MPP, although they all provide some support for distributed real-time applications. A distributed real

Data-driven reinforcement learning–based real-time energy management system for plug-in hybrid electric vehicles

DOE PAGES

Qi, Xuewei; Wu, Guoyuan; Boriboonsomsin, Kanok; ...

2016-01-01

Plug-in hybrid electric vehicles (PHEVs) show great promise in reducing transportation-related fossil fuel consumption and greenhouse gas emissions. Designing an efficient energy management system (EMS) for PHEVs to achieve better fuel economy has been an active research topic for decades. Most of the advanced systems rely either on a priori knowledge of future driving conditions to achieve the optimal but not real-time solution (e.g., using a dynamic programming strategy) or on only current driving situations to achieve a real-time but nonoptimal solution (e.g., rule-based strategy). This paper proposes a reinforcement learning–based real-time EMS for PHEVs to address the trade-off betweenmore » real-time performance and optimal energy savings. The proposed model can optimize the power-split control in real time while learning the optimal decisions from historical driving cycles. Here, a case study on a real-world commute trip shows that about a 12% fuel saving can be achieved without considering charging opportunities; further, an 8% fuel saving can be achieved when charging opportunities are considered, compared with the standard binary mode control strategy.« less

Data-driven reinforcement learning–based real-time energy management system for plug-in hybrid electric vehicles

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

Qi, Xuewei; Wu, Guoyuan; Boriboonsomsin, Kanok

Plug-in hybrid electric vehicles (PHEVs) show great promise in reducing transportation-related fossil fuel consumption and greenhouse gas emissions. Designing an efficient energy management system (EMS) for PHEVs to achieve better fuel economy has been an active research topic for decades. Most of the advanced systems rely either on a priori knowledge of future driving conditions to achieve the optimal but not real-time solution (e.g., using a dynamic programming strategy) or on only current driving situations to achieve a real-time but nonoptimal solution (e.g., rule-based strategy). This paper proposes a reinforcement learning–based real-time EMS for PHEVs to address the trade-off betweenmore » real-time performance and optimal energy savings. The proposed model can optimize the power-split control in real time while learning the optimal decisions from historical driving cycles. Here, a case study on a real-world commute trip shows that about a 12% fuel saving can be achieved without considering charging opportunities; further, an 8% fuel saving can be achieved when charging opportunities are considered, compared with the standard binary mode control strategy.« less

Feedback control for fuel-optimal descents using singular perturbation techniques

NASA Technical Reports Server (NTRS)

Price, D. B.

1984-01-01

In response to rising fuel costs and reduced profit margins for the airline companies, the optimization of the paths flown by transport aircraft has been considered. It was found that application of optimal control theory to the considered problem can result in savings in fuel, time, and direct operating costs. The best solution to the aircraft trajectory problem is an onboard real-time feedback control law. The present paper presents a technique which shows promise of becoming a part of a complete solution. The application of singular perturbation techniques to the problem is discussed, taking into account the benefits and some problems associated with them. A different technique for handling the descent part of a trajectory is also discussed.

Real Time Energy Management Control Strategies for Hybrid Powertrains

NASA Astrophysics Data System (ADS)

Zaher, Mohamed Hegazi Mohamed

In order to improve fuel efficiency and reduce emissions of mobile vehicles, various hybrid power-train concepts have been developed over the years. This thesis focuses on embedded control of hybrid powertrain concepts for mobile vehicle applications. Optimal robust control approach is used to develop a real time energy management strategy for continuous operations. The main idea is to store the normally wasted mechanical regenerative energy in energy storage devices for later usage. The regenerative energy recovery opportunity exists in any condition where the speed of motion is in opposite direction to the applied force or torque. This is the case when the vehicle is braking, decelerating, or the motion is driven by gravitational force, or load driven. There are three main concepts for regernerative energy storing devices in hybrid vehicles: electric, hydraulic, and flywheel. The real time control challenge is to balance the system power demand from the engine and the hybrid storage device, without depleting the energy storage device or stalling the engine in any work cycle, while making optimal use of the energy saving opportunities in a given operational, often repetitive cycle. In the worst case scenario, only engine is used and hybrid system completely disabled. A rule based control is developed and tuned for different work cycles and linked to a gain scheduling algorithm. A gain scheduling algorithm identifies the cycle being performed by the machine and its position via GPS, and maps them to the gains.

A Parallel Biological Optimization Algorithm to Solve the Unbalanced Assignment Problem Based on DNA Molecular Computing

PubMed Central

Wang, Zhaocai; Pu, Jun; Cao, Liling; Tan, Jian

2015-01-01

The unbalanced assignment problem (UAP) is to optimally resolve the problem of assigning n jobs to m individuals (m < n), such that minimum cost or maximum profit obtained. It is a vitally important Non-deterministic Polynomial (NP) complete problem in operation management and applied mathematics, having numerous real life applications. In this paper, we present a new parallel DNA algorithm for solving the unbalanced assignment problem using DNA molecular operations. We reasonably design flexible-length DNA strands representing different jobs and individuals, take appropriate steps, and get the solutions of the UAP in the proper length range and O(mn) time. We extend the application of DNA molecular operations and simultaneity to simplify the complexity of the computation. PMID:26512650

Inversion for Refractivity Parameters Using a Dynamic Adaptive Cuckoo Search with Crossover Operator Algorithm

PubMed Central

Zhang, Zhihua; Sheng, Zheng; Shi, Hanqing; Fan, Zhiqiang

2016-01-01

Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS) algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO). Rechenberg's 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossover operation of genetic algorithm was utilized to guarantee the population diversity. The new hybrid algorithm has better local search ability and contributes to superior performance. To verify the ability of the DACS-CO algorithm to estimate atmospheric refractivity parameters, the simulation data and real radar clutter data are both implemented. The numerical experiments demonstrate that the DACS-CO algorithm can provide an effective method for near-real-time estimation of the atmospheric refractivity profile from radar clutter. PMID:27212938

Information prioritization for control and automation of space operations

NASA Technical Reports Server (NTRS)

Ray, Asock; Joshi, Suresh M.; Whitney, Cynthia K.; Jow, Hong N.

1987-01-01

The applicability of a real-time information prioritization technique to the development of a decision support system for control and automation of Space Station operations is considered. The steps involved in the technique are described, including the definition of abnormal scenarios and of attributes, measures of individual attributes, formulation and optimization of a cost function, simulation of test cases on the basis of the cost function, and examination of the simulation scenerios. A list is given comparing the intrinsic importances of various Space Station information data.

Paleotempestological Record of Intense Storms for the Northern Gulf of Mexico, United States

NASA Astrophysics Data System (ADS)

Bregy, J. C.; Wallace, D. J.

2016-12-01

Real-time measurements from many hundreds of GNSS tracking sites around the world are publicly available today, and the amount of streaming data is steadily increasing as national agencies densify their local and global infrastructure for natural hazard monitoring and a variety of geodetic, cadastral, and other civil applications. Thousands of such sites can soon be expected on a global scale. It is a challenge to manage and make optimal use of this massive amount of real-time data. We advocate the creation of Supersite(s), in the parlance of the U.N. Global Earth Observation System of Systems (https://www.earthobservations.org/geoss.php), to generate high level real-time data products from the raw GNSS measurements from all available sources (many thousands of sites). These products include: • High rate, real-time positioning time series for assessing rapid crustal motion due to Earthquakes, volcanic activities, land slides, etc. • Co-seismic displacement to help resolve earthquake mechanism and moment magnitude • Real-time total electron content (TEC) fluctuations to augment Dart buoy in detecting and tracking tsunamis • Aggregation of the many disparate raw data dispensation servers (Casters)Recognizing that natural hazards transcend national boundaries in terms of direct and indirect (e.g., economical, security) impact, the benefits from centralized, authoritative processing of GNSS measurements is manifold: • Offers a one-stop shop to less developed nations and institutions for raw and high-level products, in support of research and applications • Promotes the installation of tracking sites and the contribution of data from nations without the ability to process the data • Reduce dependency on local responsible agencies impacted by a natural disaster • Reliable 24/7 operations, independent of voluntary, best effort contributions from good-willing scientific organizationsThe JPL GNSS Real-Time Earthquake and Tsunami (GREAT) Alert has been operating as a prototype for such a Supersite for nearly a decade, processing in real-time data from hundreds of global and regional GNSS tracking sites. The existing operational infrastructure, complete self-sufficiency, and proven reliability can be leveraged at low cost to provide valuable natural hazard monitoring to the U.S. and the world.

Real-time CO2 sensor for the optimal control of electronic EGR system

NASA Astrophysics Data System (ADS)

Kim, Gwang-jung; Choi, Byungchul; Choi, Inchul

2013-12-01

In modern diesel engines, EGR (Exhaust Gas Recirculation) is an important technique used in nitrogen oxide (NOx) emission reduction. This paper describes the development and experimental results of a fiber-optical sensor using a 2.7 μm wavelength absorption to quantify the simultaneous CO2 concentration which is the primary variable of EGR rate (CO2 in the exhaust gas versus CO2 in the intake gas, %). A real-time laser absorption method was developed using a DFB (distributed feedback) diode laser and waveguide to make optimal design and control of electronic EGR system required for `Euro-6' and `Tier 4 Final' NOx emission regulations. While EGR is effective to reduce NOx significantly, the amount of HC and CO is increased in the exhaust gas if EGR rate is not controlled based on driving conditions. Therefore, it is important to recirculate an appropriate amount of exhaust gas in the operation condition generating high volume of NOx. In this study, we evaluated basic characteristics and functions of our optical sensor and studied basically in order to find out optimal design condition. We demonstrated CO2 measurement speed, accuracy and linearity as making a condition similar to real engine through the bench-scale experiment.

Real-time use of instantaneous wave-free ratio: results of the ADVISE in-practice: an international, multicenter evaluation of instantaneous wave-free ratio in clinical practice.

PubMed

Petraco, Ricardo; Al-Lamee, Rasha; Gotberg, Matthias; Sharp, Andrew; Hellig, Farrel; Nijjer, Sukhjinder S; Echavarria-Pinto, Mauro; van de Hoef, Tim P; Sen, Sayan; Tanaka, Nobuhiro; Van Belle, Eric; Bojara, Waldemar; Sakoda, Kunihiro; Mates, Martin; Indolfi, Ciro; De Rosa, Salvatore; Vrints, Christian J; Haine, Steven; Yokoi, Hiroyoshi; Ribichini, Flavio L; Meuwissen, Martjin; Matsuo, Hitoshi; Janssens, Luc; Katsumi, Ueno; Di Mario, Carlo; Escaned, Javier; Piek, Jan; Davies, Justin E

2014-11-01

To evaluate the first experience of real-time instantaneous wave-free ratio (iFR) measurement by clinicians. The iFR is a new vasodilator-free index of coronary stenosis severity, calculated as a trans-lesion pressure ratio during a specific period of baseline diastole, when distal resistance is lowest and stable. Because all previous studies have calculated iFR offline, the feasibility of real-time iFR measurement has never been assessed. Three hundred ninety-two stenoses with angiographically intermediate stenoses were included in this multicenter international analysis. Instantaneous wave-free ratio and fractional flow reserve (FFR) were performed in real time on commercially available consoles. The classification agreement of coronary stenoses between iFR and FFR was calculated. Instantaneous wave-free ratio and FFR maintain a close level of diagnostic agreement when both are measured by clinicians in real time (for a clinical 0.80 FFR cutoff: area under the receiver operating characteristic curve [ROC(AUC)] 0.87, classification match 80%, and optimal iFR cutoff 0.90; for a ischemic 0.75 FFR cutoff: iFR ROC(AUC) 0.90, classification match 88%, and optimal iFR cutoff 0.85; if the FFR 0.75-0.80 gray zone is accounted for: ROC(AUC) 0.93, classification match 92%). When iFR and FFR are evaluated together in a hybrid decision-making strategy, 61% of the population is spared from vasodilator while maintaining a 94% overall agreement with FFR lesion classification. When measured in real time, iFR maintains the close relationship to FFR reported in offline studies. These findings confirm the feasibility and reliability of real-time iFR calculation by clinicians. Copyright © 2014 The Author. Published by Elsevier Inc. All rights reserved.

On-line self-learning time forward voltage prognosis for lithium-ion batteries using adaptive neuro-fuzzy inference system

NASA Astrophysics Data System (ADS)

Fleischer, Christian; Waag, Wladislaw; Bai, Ziou; Sauer, Dirk Uwe

2013-12-01

The battery management system (BMS) of a battery-electric road vehicle must ensure an optimal operation of the electrochemical storage system to guarantee for durability and reliability. In particular, the BMS must provide precise information about the battery's state-of-functionality, i.e. how much dis-/charging power can the battery accept at current state and condition while at the same time preventing it from operating outside its safe operating area. These critical limits have to be calculated in a predictive manner, which serve as a significant input factor for the supervising vehicle energy management (VEM). The VEM must provide enough power to the vehicle's drivetrain for certain tasks and especially in critical driving situations. Therefore, this paper describes a new approach which can be used for state-of-available-power estimation with respect to lowest/highest cell voltage prediction using an adaptive neuro-fuzzy inference system (ANFIS). The estimated voltage for a given time frame in the future is directly compared with the actual voltage, verifying the effectiveness and accuracy of a relative voltage prediction error of less than 1%. Moreover, the real-time operating capability of the proposed algorithm was verified on a battery test bench while running on a real-time system performing voltage prediction.

MO-DE-BRA-04: Hands-On Fluoroscopy Safety Training with Real-Time Patient and Staff Dosimetry

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

Vanderhoek, M; Bevins, N

Purpose: Fluoroscopically guided interventions (FGI) are routinely performed across many different hospital departments. However, many involved staff members have minimal training regarding safe and optimal use of fluoroscopy systems. We developed and taught a hands-on fluoroscopy safety class incorporating real-time patient and staff dosimetry in order to promote safer and more optimal use of fluoroscopy during FGI. Methods: The hands-on fluoroscopy safety class is taught in an FGI suite, unique to each department. A patient equivalent phantom is set on the patient table with an ion chamber positioned at the x-ray beam entrance to the phantom. This provides a surrogatemore » measure of patient entrance dose. Multiple solid state dosimeters (RaySafe i2 dosimetry systemTM) are deployed at different distances from the phantom (0.1, 1, 3 meters), which provide surrogate measures of staff dose. Instructors direct participating clinical staff to operate the fluoroscopy system as they view live fluoroscopic images, patient entrance dose, and staff doses in real-time. During class, instructors work with clinical staff to investigate how patient entrance dose, staff doses, and image quality are affected by different parameters, including pulse rate, magnification, collimation, beam angulation, imaging mode, system geometry, distance, and shielding. Results: Real-time dose visualization enables clinical staff to directly see and learn how to optimize their use of their own fluoroscopy system to minimize patient and staff dose, yet maintain sufficient image quality for FGI. As a direct result of the class, multiple hospital departments have implemented changes to their imaging protocols, including reduction of the default fluoroscopy pulse rate and increased use of collimation and lower dose fluoroscopy modes. Conclusion: Hands-on fluoroscopy safety training substantially benefits from real-time patient and staff dosimetry incorporated into the class. Real-time dose display helps clinical staff visualize, internalize, and ultimately utilize the safety techniques learned during the training. RaySafe/Unfors/Fluke lent us a portable version of their RaySafe i2 Dosimetry System for 6 months.« less

A self optimizing synthetic organic reactor system using real-time in-line NMR spectroscopy† †Electronic supplementary information (ESI) available: Details about the methodology, LabView scripts, experimental set-ups, additional spectra and self-optimization can be found in the SI. See DOI: 10.1039/c4sc03075c Click here for additional data file.

PubMed Central

Sans, Victor; Porwol, Luzian; Dragone, Vincenza

2015-01-01

A configurable platform for synthetic chemistry incorporating an in-line benchtop NMR that is capable of monitoring and controlling organic reactions in real-time is presented. The platform is controlled via a modular LabView software control system for the hardware, NMR, data analysis and feedback optimization. Using this platform we report the real-time advanced structural characterization of reaction mixtures, including 19F, 13C, DEPT, 2D NMR spectroscopy (COSY, HSQC and 19F-COSY) for the first time. Finally, the potential of this technique is demonstrated through the optimization of a catalytic organic reaction in real-time, showing its applicability to self-optimizing systems using criteria such as stereoselectivity, multi-nuclear measurements or 2D correlations. PMID:29560211

Sequence Optimized Real-Time RT-PCR Assay for Detection of Crimean-Congo Hemorrhagic Fever Virus

DTIC Science & Technology

2017-03-21

19-23]. Real-56 time reverse-transcription PCR remains the gold standard for quantitative , sensitive, and specific 57 detection of CCHFV; however...five-fold in two different series , and samples were run by real- time RT-PCR 116 in triplicate. The preliminary LOD was the lowest RNA dilution where...1 Sequence optimized real- time RT-PCR assay for detection of Crimean-Congo hemorrhagic fever 1 virus 2 3 JW Koehler1, KL Delp1, AT Hall1, SP

New MHD feedback control schemes using the MARTe framework in RFX-mod

NASA Astrophysics Data System (ADS)

Piron, Chiara; Manduchi, Gabriele; Marrelli, Lionello; Piovesan, Paolo; Zanca, Paolo

2013-10-01

Real-time feedback control of MHD instabilities is a topic of major interest in magnetic thermonuclear fusion, since it allows to optimize a device performance even beyond its stability bounds. The stability properties of different magnetic configurations are important test benches for real-time control systems. RFX-mod, a Reversed Field Pinch experiment that can also operate as a tokamak, is a well suited device to investigate this topic. It is equipped with a sophisticated magnetic feedback system that controls MHD instabilities and error fields by means of 192 active coils and a corresponding grid of sensors. In addition, the RFX-mod control system has recently gained new potentialities thanks to the introduction of the MARTe framework and of a new CPU architecture. These capabilities allow to study new feedback algorithms relevant to both RFP and tokamak operation and to contribute to the debate on the optimal feedback strategy. This work focuses on the design of new feedback schemes. For this purpose new magnetic sensors have been explored, together with new algorithms that refine the de-aliasing computation of the radial sideband harmonics. The comparison of different sensor and feedback strategy performance is described in both RFP and tokamak experiments.

Comparative analysis of the operation efficiency of the continuous and relay control systems of a multi-axle wheeled vehicle suspension

NASA Astrophysics Data System (ADS)

Zhileykin, M. M.; Kotiev, G. O.; Nagatsev, M. V.

2018-02-01

In order to improve the efficiency of the multi-axle wheeled vehicles (MWV) automotive engineers are increasing their cruising speed. One of the promising ways to improve ride comfort of the MWV is the development of the dynamic active suspension systems and control laws for such systems. Here, by the dynamic control systems we mean the systems operating in real time mode and using current (instantaneous) values of the state variables. The aim of the work is to develop the MWV suspension optimal control laws that would reduce vibrations on the driver’s seat at kinematic excitation. The authors have developed the optimal control laws for damping the oscillations of the MWV body. The developed laws allow reduction of the vibrations on the driver’s seat and increase in the maximum speed of the vehicle. The laws are characterized in that they allow generating the control inputs in real time mode. The authors have demonstrated the efficiency of the proposed control laws by means of mathematical simulation of the MWV driving over unpaved road with kinematic excitation. The proposed optimal control laws can be used in the MWV suspension control systems with magnetorheological shock absorbers or controlled hydropneumatic springs. Further evolution of the research line can be the development of the energy-efficient MWV suspension control systems with continuous control input on the vehicle body.

A Network Architecture for Data-Driven Systems

DTIC Science & Technology

1985-07-01

ELABORATION. ..... ..... 26 Real - Time Operating System . ....... ......... 26 Secondary Memory Utilization. ........ ....... 26 Data Flow Graphical...discussions followed by a flight simulator exam~ple. REAL - TIME OPERATING SYSTEM An operating system needs to be designed exclusively for real-time...Assessment. (SDWA) module. The SDWA module is tightly coupled to the real - time operating system . This module must determine the sensitivity to

Concurrently adjusting interrelated control parameters to achieve optimal engine performance

DOEpatents

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

2015-12-01

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

A method for real-time implementation of HOG feature extraction

NASA Astrophysics Data System (ADS)

Luo, Hai-bo; Yu, Xin-rong; Liu, Hong-mei; Ding, Qing-hai

2011-08-01

Histogram of oriented gradient (HOG) is an efficient feature extraction scheme, and HOG descriptors are feature descriptors which is widely used in computer vision and image processing for the purpose of biometrics, target tracking, automatic target detection(ATD) and automatic target recognition(ATR) etc. However, computation of HOG feature extraction is unsuitable for hardware implementation since it includes complicated operations. In this paper, the optimal design method and theory frame for real-time HOG feature extraction based on FPGA were proposed. The main principle is as follows: firstly, the parallel gradient computing unit circuit based on parallel pipeline structure was designed. Secondly, the calculation of arctangent and square root operation was simplified. Finally, a histogram generator based on parallel pipeline structure was designed to calculate the histogram of each sub-region. Experimental results showed that the HOG extraction can be implemented in a pixel period by these computing units.

Note: Quasi-real-time analysis of dynamic near field scattering data using a graphics processing unit

NASA Astrophysics Data System (ADS)

Cerchiari, G.; Croccolo, F.; Cardinaux, F.; Scheffold, F.

2012-10-01

We present an implementation of the analysis of dynamic near field scattering (NFS) data using a graphics processing unit. We introduce an optimized data management scheme thereby limiting the number of operations required. Overall, we reduce the processing time from hours to minutes, for typical experimental conditions. Previously the limiting step in such experiments, the processing time is now comparable to the data acquisition time. Our approach is applicable to various dynamic NFS methods, including shadowgraph, Schlieren and differential dynamic microscopy.

Optimizing Hydropower Day-Ahead Scheduling for the Oroville-Thermalito Project

NASA Astrophysics Data System (ADS)

Veselka, T. D.; Mahalik, M.

2012-12-01

Under an award from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Water Power Program, a team of national laboratories is developing and demonstrating a suite of advanced, integrated analytical tools to assist managers and planners increase hydropower resources while enhancing the environment. As part of the project, Argonne National Laboratory is developing the Conventional Hydropower Energy and Environmental Systems (CHEERS) model to optimize day-ahead scheduling and real-time operations. We will present the application of CHEERS to the Oroville-Thermalito Project located in Northern California. CHEERS will aid California Department of Water Resources (CDWR) schedulers in making decisions about unit commitments and turbine-level operating points using a system-wide approach to increase hydropower efficiency and the value of power generation and ancillary services. The model determines schedules and operations that are constrained by physical limitations, characteristics of plant components, operational preferences, reliability, and environmental considerations. The optimization considers forebay and afterbay implications, interactions between cascaded power plants, turbine efficiency curves and rough zones, and operator preferences. CHEERS simultaneously considers over time the interactions among all CDWR power and water resources, hydropower economics, reservoir storage limitations, and a set of complex environmental constraints for the Thermalito Afterbay and Feather River habitats. Power marketers, day-ahead schedulers, and plant operators provide system configuration and detailed operational data, along with feedback on model design and performance. CHEERS is integrated with CDWR data systems to obtain historic and initial conditions of the system as the basis from which future operations are then optimized. Model results suggest alternative operational regimes that improve the value of CDWR resources to the grid while enhancing the environment and complying with water delivery obligations for non-power uses.

Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

NASA Technical Reports Server (NTRS)

Lee, Hanbong

2016-01-01

Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.

Maximizing algebraic connectivity in air transportation networks

NASA Astrophysics Data System (ADS)

Wei, Peng

In air transportation networks the robustness of a network regarding node and link failures is a key factor for its design. An experiment based on the real air transportation network is performed to show that the algebraic connectivity is a good measure for network robustness. Three optimization problems of algebraic connectivity maximization are then formulated in order to find the most robust network design under different constraints. The algebraic connectivity maximization problem with flight routes addition or deletion is first formulated. Three methods to optimize and analyze the network algebraic connectivity are proposed. The Modified Greedy Perturbation Algorithm (MGP) provides a sub-optimal solution in a fast iterative manner. The Weighted Tabu Search (WTS) is designed to offer a near optimal solution with longer running time. The relaxed semi-definite programming (SDP) is used to set a performance upper bound and three rounding techniques are discussed to find the feasible solution. The simulation results present the trade-off among the three methods. The case study on two air transportation networks of Virgin America and Southwest Airlines show that the developed methods can be applied in real world large scale networks. The algebraic connectivity maximization problem is extended by adding the leg number constraint, which considers the traveler's tolerance for the total connecting stops. The Binary Semi-Definite Programming (BSDP) with cutting plane method provides the optimal solution. The tabu search and 2-opt search heuristics can find the optimal solution in small scale networks and the near optimal solution in large scale networks. The third algebraic connectivity maximization problem with operating cost constraint is formulated. When the total operating cost budget is given, the number of the edges to be added is not fixed. Each edge weight needs to be calculated instead of being pre-determined. It is illustrated that the edge addition and the weight assignment can not be studied separately for the problem with operating cost constraint. Therefore a relaxed SDP method with golden section search is developed to solve both at the same time. The cluster decomposition is utilized to solve large scale networks.

A pilot study for determining the optimal operation condition for simultaneously controlling the emissions of PCDD/Fs and PAHs from the iron ore sintering process.

PubMed

Chen, Yu-Cheng; Tsai, Perng-Jy; Mou, Jin-Luh; Kuo, Yu-Chieh; Wang, Shih-Min; Young, Li-Hao; Wang, Ya-Fen

2012-09-01

In this study, the cost-benefit analysis technique was developed and incorporated into the Taguchi experimental design to determine the optimal operation combination for the purpose of providing a technique solution for controlling both emissions of PCDD/Fs and PAHs, and increasing both the sinter productivity (SP) and sinter strength (SS) simultaneously. Four operating parameters, including the water content, suction pressure, bed height, and type of hearth layer, were selected and all experimental campaigns were conducted on a pilot-scale sinter pot to simulate various sintering operating conditions of a real-scale sinter plant. The resultant optimal combination could reduce the total carcinogenic emissions arising from both emissions of PCDD/Fs and PAHs by 49.8%, and increase the sinter benefit associated with the increase in both SP and SS by 10.1%, as in comparison with the operation condition currently used in the real plant. The ANOVA results indicate that the suction pressure was the most dominant parameter in determining the optimal operation combination. The above result was theoretically plausible since the higher suction pressure provided more oxygen contents leading to the decrease in both PCDD/F and PAH emissions. But it should be noted that the results obtained from the present study were based on pilot scale experiments, conducting confirmation tests in a real scale plant are still necessary in the future. Copyright © 2012 Elsevier Ltd. All rights reserved.

On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment

PubMed Central

Alonso-Mora, Javier; Samaranayake, Samitha; Wallar, Alex; Frazzoli, Emilio; Rus, Daniela

2017-01-01

Ride-sharing services are transforming urban mobility by providing timely and convenient transportation to anybody, anywhere, and anytime. These services present enormous potential for positive societal impacts with respect to pollution, energy consumption, congestion, etc. Current mathematical models, however, do not fully address the potential of ride-sharing. Recently, a large-scale study highlighted some of the benefits of car pooling but was limited to static routes with two riders per vehicle (optimally) or three (with heuristics). We present a more general mathematical model for real-time high-capacity ride-sharing that (i) scales to large numbers of passengers and trips and (ii) dynamically generates optimal routes with respect to online demand and vehicle locations. The algorithm starts from a greedy assignment and improves it through a constrained optimization, quickly returning solutions of good quality and converging to the optimal assignment over time. We quantify experimentally the tradeoff between fleet size, capacity, waiting time, travel delay, and operational costs for low- to medium-capacity vehicles, such as taxis and van shuttles. The algorithm is validated with ∼3 million rides extracted from the New York City taxicab public dataset. Our experimental study considers ride-sharing with rider capacity of up to 10 simultaneous passengers per vehicle. The algorithm applies to fleets of autonomous vehicles and also incorporates rebalancing of idling vehicles to areas of high demand. This framework is general and can be used for many real-time multivehicle, multitask assignment problems. PMID:28049820

On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment.

PubMed

Alonso-Mora, Javier; Samaranayake, Samitha; Wallar, Alex; Frazzoli, Emilio; Rus, Daniela

2017-01-17

Ride-sharing services are transforming urban mobility by providing timely and convenient transportation to anybody, anywhere, and anytime. These services present enormous potential for positive societal impacts with respect to pollution, energy consumption, congestion, etc. Current mathematical models, however, do not fully address the potential of ride-sharing. Recently, a large-scale study highlighted some of the benefits of car pooling but was limited to static routes with two riders per vehicle (optimally) or three (with heuristics). We present a more general mathematical model for real-time high-capacity ride-sharing that (i) scales to large numbers of passengers and trips and (ii) dynamically generates optimal routes with respect to online demand and vehicle locations. The algorithm starts from a greedy assignment and improves it through a constrained optimization, quickly returning solutions of good quality and converging to the optimal assignment over time. We quantify experimentally the tradeoff between fleet size, capacity, waiting time, travel delay, and operational costs for low- to medium-capacity vehicles, such as taxis and van shuttles. The algorithm is validated with ∼3 million rides extracted from the New York City taxicab public dataset. Our experimental study considers ride-sharing with rider capacity of up to 10 simultaneous passengers per vehicle. The algorithm applies to fleets of autonomous vehicles and also incorporates rebalancing of idling vehicles to areas of high demand. This framework is general and can be used for many real-time multivehicle, multitask assignment problems.

High-fidelity real-time maritime scene rendering

NASA Astrophysics Data System (ADS)

Shyu, Hawjye; Taczak, Thomas M.; Cox, Kevin; Gover, Robert; Maraviglia, Carlos; Cahill, Colin

2011-06-01

The ability to simulate authentic engagements using real-world hardware is an increasingly important tool. For rendering maritime environments, scene generators must be capable of rendering radiometrically accurate scenes with correct temporal and spatial characteristics. When the simulation is used as input to real-world hardware or human observers, the scene generator must operate in real-time. This paper introduces a novel, real-time scene generation capability for rendering radiometrically accurate scenes of backgrounds and targets in maritime environments. The new model is an optimized and parallelized version of the US Navy CRUISE_Missiles rendering engine. It was designed to accept environmental descriptions and engagement geometry data from external sources, render a scene, transform the radiometric scene using the electro-optical response functions of a sensor under test, and output the resulting signal to real-world hardware. This paper reviews components of the scene rendering algorithm, and details the modifications required to run this code in real-time. A description of the simulation architecture and interfaces to external hardware and models is presented. Performance assessments of the frame rate and radiometric accuracy of the new code are summarized. This work was completed in FY10 under Office of Secretary of Defense (OSD) Central Test and Evaluation Investment Program (CTEIP) funding and will undergo a validation process in FY11.

Evaluation of hybrid inverse planning and optimization (HIPO) algorithm for optimization in real-time, high-dose-rate (HDR) brachytherapy for prostate.

PubMed

Pokharel, Shyam; Rana, Suresh; Blikenstaff, Joseph; Sadeghi, Amir; Prestidge, Bradley

2013-07-08

The purpose of this study is to investigate the effectiveness of the HIPO planning and optimization algorithm for real-time prostate HDR brachytherapy. This study consists of 20 patients who underwent ultrasound-based real-time HDR brachytherapy of the prostate using the treatment planning system called Oncentra Prostate (SWIFT version 3.0). The treatment plans for all patients were optimized using inverse dose-volume histogram-based optimization followed by graphical optimization (GRO) in real time. The GRO is manual manipulation of isodose lines slice by slice. The quality of the plan heavily depends on planner expertise and experience. The data for all patients were retrieved later, and treatment plans were created and optimized using HIPO algorithm with the same set of dose constraints, number of catheters, and set of contours as in the real-time optimization algorithm. The HIPO algorithm is a hybrid because it combines both stochastic and deterministic algorithms. The stochastic algorithm, called simulated annealing, searches the optimal catheter distributions for a given set of dose objectives. The deterministic algorithm, called dose-volume histogram-based optimization (DVHO), optimizes three-dimensional dose distribution quickly by moving straight downhill once it is in the advantageous region of the search space given by the stochastic algorithm. The PTV receiving 100% of the prescription dose (V100) was 97.56% and 95.38% with GRO and HIPO, respectively. The mean dose (D(mean)) and minimum dose to 10% volume (D10) for the urethra, rectum, and bladder were all statistically lower with HIPO compared to GRO using the student pair t-test at 5% significance level. HIPO can provide treatment plans with comparable target coverage to that of GRO with a reduction in dose to the critical structures.

SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound.

PubMed

Baumgartner, Christian F; Kamnitsas, Konstantinos; Matthew, Jacqueline; Fletcher, Tara P; Smith, Sandra; Koch, Lisa M; Kainz, Bernhard; Rueckert, Daniel

2017-11-01

Identifying and interpreting fetal standard scan planes during 2-D ultrasound mid-pregnancy examinations are highly complex tasks, which require years of training. Apart from guiding the probe to the correct location, it can be equally difficult for a non-expert to identify relevant structures within the image. Automatic image processing can provide tools to help experienced as well as inexperienced operators with these tasks. In this paper, we propose a novel method based on convolutional neural networks, which can automatically detect 13 fetal standard views in freehand 2-D ultrasound data as well as provide a localization of the fetal structures via a bounding box. An important contribution is that the network learns to localize the target anatomy using weak supervision based on image-level labels only. The network architecture is designed to operate in real-time while providing optimal output for the localization task. We present results for real-time annotation, retrospective frame retrieval from saved videos, and localization on a very large and challenging dataset consisting of images and video recordings of full clinical anomaly screenings. We found that the proposed method achieved an average F1-score of 0.798 in a realistic classification experiment modeling real-time detection, and obtained a 90.09% accuracy for retrospective frame retrieval. Moreover, an accuracy of 77.8% was achieved on the localization task.

The Real-Time ObjectAgent Software Architecture for Distributed Satellite Systems

DTIC Science & Technology

2001-01-01

real - time operating system selection are also discussed. The fourth section describes a simple demonstration of real-time ObjectAgent. Finally, the...experience with C++. After selecting the programming language, it was necessary to select a target real - time operating system (RTOS) and embedded...ObjectAgent software to run on the OSE Real Time Operating System . In addition, she is responsible for the integration of ObjectAgent

Combined Economic and Hydrologic Modeling to Support Collaborative Decision Making Processes

NASA Astrophysics Data System (ADS)

Sheer, D. P.

2008-12-01

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

Online total organic carbon (TOC) monitoring for water and wastewater treatment plants processes and operations optimization

NASA Astrophysics Data System (ADS)

Assmann, Céline; Scott, Amanda; Biller, Dondra

2017-08-01

Organic measurements, such as biological oxygen demand (BOD) and chemical oxygen demand (COD) were developed decades ago in order to measure organics in water. Today, these time-consuming measurements are still used as parameters to check the water treatment quality; however, the time required to generate a result, ranging from hours to days, does not allow COD or BOD to be useful process control parameters - see (1) Standard Method 5210 B; 5-day BOD Test, 1997, and (2) ASTM D1252; COD Test, 2012. Online organic carbon monitoring allows for effective process control because results are generated every few minutes. Though it does not replace BOD or COD measurements still required for compliance reporting, it allows for smart, data-driven and rapid decision-making to improve process control and optimization or meet compliances. Thanks to the smart interpretation of generated data and the capability to now take real-time actions, municipal drinking water and wastewater treatment facility operators can positively impact their OPEX (operational expenditure) efficiencies and their capabilities to meet regulatory requirements. This paper describes how three municipal wastewater and drinking water plants gained process insights, and determined optimization opportunities thanks to the implementation of online total organic carbon (TOC) monitoring.

Comparison of spike-sorting algorithms for future hardware implementation.

PubMed

Gibson, Sarah; Judy, Jack W; Markovic, Dejan

2008-01-01

Applications such as brain-machine interfaces require hardware spike sorting in order to (1) obtain single-unit activity and (2) perform data reduction for wireless transmission of data. Such systems must be low-power, low-area, high-accuracy, automatic, and able to operate in real time. Several detection and feature extraction algorithms for spike sorting are described briefly and evaluated in terms of accuracy versus computational complexity. The nonlinear energy operator method is chosen as the optimal spike detection algorithm, being most robust over noise and relatively simple. The discrete derivatives method [1] is chosen as the optimal feature extraction method, maintaining high accuracy across SNRs with a complexity orders of magnitude less than that of traditional methods such as PCA.

Pulse intensity characterization of the LCLS nanosecond double-bunch mode of operation

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

Sun, Yanwen; Decker, Franz-Josef; Turner, James

The recent demonstration of the 'nanosecond double-bunch' operation mode,i.e.two X-ray pulses separated in time between 0.35 and hundreds of nanoseconds and by increments of 0.35 ns, offers new opportunities to investigate ultrafast dynamics in diverse systems of interest. However, in order to reach its full potential, this mode of operation requires the precise characterization of the intensity of each X-ray pulse within each pulse pair for any time separation. Here, a transmissive single-shot diagnostic that achieves this goal for time separations larger than 0.7 ns with a precision better than 5% is presented. Lastly, it also provides real-time monitoring feedbackmore » to help tune the accelerator parameters to deliver double pulse intensity distributions optimized for specific experimental goals.« less

Pulse intensity characterization of the LCLS nanosecond double-bunch mode of operation

DOE PAGES

Sun, Yanwen; Decker, Franz-Josef; Turner, James; ...

2018-03-27

The recent demonstration of the 'nanosecond double-bunch' operation mode,i.e.two X-ray pulses separated in time between 0.35 and hundreds of nanoseconds and by increments of 0.35 ns, offers new opportunities to investigate ultrafast dynamics in diverse systems of interest. However, in order to reach its full potential, this mode of operation requires the precise characterization of the intensity of each X-ray pulse within each pulse pair for any time separation. Here, a transmissive single-shot diagnostic that achieves this goal for time separations larger than 0.7 ns with a precision better than 5% is presented. Lastly, it also provides real-time monitoring feedbackmore » to help tune the accelerator parameters to deliver double pulse intensity distributions optimized for specific experimental goals.« less

Real-time focus controller for laser welding with fibre optic noninvasive capture of light

NASA Astrophysics Data System (ADS)

Cobo, Adolfo; Bardin, F.; Hand, Duncan P.; Jones, Julian D.; Collin, O.; Aubry, P.; Dubois, Thierry; Hoegstroem, M.; Nylen, P.; Jonsson, P.; Lopez-Higuera, Jose M.

2004-06-01

Laser welding is being introduced in the aerospace industry due to its many advantages over traditional techniques. However, welding of parts with complex shapes requires precise control of the focal point of the laser in order to achieve full penetration over the entire seam. In this paper, we present an improved control system for real-time adjustment of the correct focal position, which is based on the monitoring of the light emitted by the process in two different spectral bands. The reported system has been optimized for use in a real environment: it is robust, compact, easy to operate, able to adjust itself to different welding conditions, materials and laser setups, and includes a direct connection to an external PC. Results from recent field trials on complex aerospace structures are provided.

Quantitative real-time monitoring of dryer effluent using fiber optic near-infrared spectroscopy.

PubMed

Harris, S C; Walker, D S

2000-09-01

This paper describes a method for real-time quantitation of the solvents evaporating from a dryer. The vapor stream in the vacuum line of a dryer was monitored in real time using a fiber optic-coupled acousto-optic tunable filter near-infrared (AOTF-NIR) spectrometer. A balance was placed in the dryer, and mass readings were recorded for every scan of the AOTF-NIR. A partial least-squares (PLS) calibration was subsequently built based on change in mass over change in time for solvents typically used in a chemical manufacturing plant. Controlling software for the AOTF-NIR was developed. The software collects spectra, builds the PLS calibration model, and continuously fits subsequently collected spectra to the calibration, allowing the operator to follow the mass loss of solvent from the dryer. The results indicate that solvent loss can be monitored and quantitated in real time using NIR for the optimization of drying times. These time-based mass loss values have also been used to calculate "dynamic" vapor density values for the solvents. The values calculated are in agreement with values determined from the ideal gas law and could prove valuable as tools to measure temperature or pressure indirectly.

Solving the dynamic ambulance relocation and dispatching problem using approximate dynamic programming

PubMed Central

Schmid, Verena

2012-01-01

Emergency service providers are supposed to locate ambulances such that in case of emergency patients can be reached in a time-efficient manner. Two fundamental decisions and choices need to be made real-time. First of all immediately after a request emerges an appropriate vehicle needs to be dispatched and send to the requests’ site. After having served a request the vehicle needs to be relocated to its next waiting location. We are going to propose a model and solve the underlying optimization problem using approximate dynamic programming (ADP), an emerging and powerful tool for solving stochastic and dynamic problems typically arising in the field of operations research. Empirical tests based on real data from the city of Vienna indicate that by deviating from the classical dispatching rules the average response time can be decreased from 4.60 to 4.01 minutes, which corresponds to an improvement of 12.89%. Furthermore we are going to show that it is essential to consider time-dependent information such as travel times and changes with respect to the request volume explicitly. Ignoring the current time and its consequences thereafter during the stage of modeling and optimization leads to suboptimal decisions. PMID:25540476

Real-time, aptamer-based tracking of circulating therapeutic agents in living animals

PubMed Central

Ferguson, B. Scott; Hoggarth, David A.; Maliniak, Dan; Ploense, Kyle; White, Ryan J.; Woodward, Nick; Hsieh, Kuangwen; Bonham, Andrew J.; Eisenstein, Michael; Kippin, Tod; Plaxco, Kevin W.; Soh, H. Tom

2014-01-01

A sensor capable of continuously measuring specific molecules in the bloodstream in vivo would give clinicians a valuable window into patients’ health and their response to therapeutics. Such technology would enable truly personalized medicine, wherein therapeutic agents could be tailored with optimal doses for each patient to maximize efficacy and minimize side effects. Unfortunately, continuous, real-time measurement is currently only possible for a handful of targets, such as glucose, lactose, and oxygen, and the few existing platforms for continuous measurement are not generalizable for the monitoring of other analytes, such as small-molecule therapeutics. In response, we have developed a real-time biosensor capable of continuously tracking a wide range of circulating drugs in living subjects. Our microfluidic electrochemical detector for in vivo continuous monitoring (MEDIC) requires no exogenous reagents, operates at room temperature, and can be reconfigured to measure different target molecules by exchanging probes in a modular manner. To demonstrate the system's versatility, we measured therapeutic in vivo concentrations of doxorubicin (a chemotherapeutic) and kanamycin (an antibiotic) in live rats and in human whole blood for several hours with high sensitivity and specificity at sub-minute temporal resolution. Importantly, we show that MEDIC can also obtain pharmacokineticparameters for individual animals in real-time. Accordingly, just as continuous glucose monitoring technology is currently revolutionizing diabetes care, we believe MEDIC could be a powerful enabler for personalized medicine by ensuring delivery of optimal drug doses for individual patients based on direct detection of physiological parameters. PMID:24285484

Contributions to the Operating Systems Standards Working Group of the Navy Next Generation Computer Resources Program for FY 1989 - FY 1991

DTIC Science & Technology

1991-10-01

Real - Time Operating System , Hide Tokuda, et al., Carnegie Mellon University "* MARUTI, Hard Real - Time Operating System , Ashok...Architecture, Fred J. Pollack and Kevin C. Kahn, BiiN 10:00 - 10:20 BREAK 10:20 - 12:20 Session VII - Chair: James G. Smith, ONR • A Real - Time Operating System for...Detailed Description * POSIX: Detailed Description * V: Detailed Description * Real - Time Operating System

Toward a Real-Time Measurement-Based System for Estimation of Helicopter Engine Degradation Due to Compressor Erosion

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.; Simo, Donald L.

2007-01-01

This paper presents a preliminary demonstration of an automated health assessment tool, capable of real-time on-board operation using existing engine control hardware. The tool allows operators to discern how rapidly individual turboshaft engines are degrading. As the compressor erodes, performance is lost, and with it the ability to generate power. Thus, such a tool would provide an instant assessment of the engine s fitness to perform a mission, and would help to pinpoint any abnormal wear or performance anomalies before they became serious, thereby decreasing uncertainty and enabling improved maintenance scheduling. The research described in the paper utilized test stand data from a T700-GE-401 turboshaft engine that underwent sand-ingestion testing to scale a model-based compressor efficiency degradation estimation algorithm. This algorithm was then applied to real-time Health Usage and Monitoring System (HUMS) data from a T700-GE-701C to track compressor efficiency on-line. The approach uses an optimal estimator called a Kalman filter. The filter is designed to estimate the compressor efficiency using only data from the engine s sensors as input.

Real-time 4D electrical resistivity imaging of tracer transport within an energically stimulated fracture zone

NASA Astrophysics Data System (ADS)

Johnson, T. C.

2016-12-01

Hydraulic fracture stimulation is used extensively in the subsurface energy sector to improve access between energy bearing formations and production boreholes. However, large uncertainties exist concerning the location and extent of stimulated fractures, and concerning the behavior of flow within those fractures. This uncertainty often results in significant risks, including induced seismicity and contamination of potable groundwater aquifers. Time-lapse electrical resistivity tomography (ERT) is a proven method of imaging fluid flow within fracture networks, by imaging the change in bulk conductivity induced by the presence of an electrically anomalous tracer within the fracture. In this work we demonstrate characterization and flow monitoring of a stimulated fracture using real-time four-dimensional ERT imaging within an unsaturated rhyolite formation. After stimulation, a conductive tracer was injected into the fracture zone. ERT survey data were continuously and autonomously collected, pre-processed on site, submitted to an off-site high performance computing system for inversion, and returned to the field for inspection. Surveys were collected at approximately 12 minute intervals. Data transmission and inversion required approximately 2 minutes per survey. The time-lapse imaging results show the dominant flow-paths within the stimulated fracture zone, thereby revealing the location and extent of the fracture, and the behavior of tracer flow within the fracture. Ultimately real-time imaging will enable site operators to better understand stimulation operations, and control post-stimulation reservoir operations for optimal performance and environmental protection.

StarBase: A Firm Real-Time Database Manager for Time-Critical Applications

DTIC Science & Technology

1995-01-01

Mellon University [IO]. StarBase differs from previous RT-DBMS work [l, 2, 31 in that a) it relies on a real - time operating system which provides...simulation studies, StarBase uses a real - time operating system to provide basic real-time functionality and deals with issues beyond transaction...re- source scheduling provided by the underlying real - time operating system . Issues of data contention are dealt with by use of a priority

Further optimization of SeDDaRA blind image deconvolution algorithm and its DSP implementation

NASA Astrophysics Data System (ADS)

Wen, Bo; Zhang, Qiheng; Zhang, Jianlin

2011-11-01

Efficient algorithm for blind image deconvolution and its high-speed implementation is of great value in practice. Further optimization of SeDDaRA is developed, from algorithm structure to numerical calculation methods. The main optimization covers that, the structure's modularization for good implementation feasibility, reducing the data computation and dependency of 2D-FFT/IFFT, and acceleration of power operation by segmented look-up table. Then the Fast SeDDaRA is proposed and specialized for low complexity. As the final implementation, a hardware system of image restoration is conducted by using the multi-DSP parallel processing. Experimental results show that, the processing time and memory demand of Fast SeDDaRA decreases 50% at least; the data throughput of image restoration system is over 7.8Msps. The optimization is proved efficient and feasible, and the Fast SeDDaRA is able to support the real-time application.

Tactical Unit Data and Decision Requirements for Urban Operations

DTIC Science & Technology

2008-10-01

maneuverability, sensor optimization, weapon effects, terrain), and develop rich but lightweight information structures and architecture . Specifically, the goal...tion structure and systemic architecture that enable sharing common data in near real-time, and mission planning and analysis software for U-BE...Building Function Verify mosque and identify possi- ble schools or meeting places Identify types of cinema (stage/theatre) or other similar nearby

Optimization of ramp area aircraft push back time windows in the presence of uncertainty

NASA Astrophysics Data System (ADS)

Coupe, William Jeremy

It is well known that airport surface traffic congestion at major airports is responsible for increased taxi-out times, fuel burn and excess emissions and there is potential to mitigate these negative consequences through optimizing airport surface traffic operations. Due to a highly congested voice communication channel between pilots and air traffic controllers and a data communication channel that is used only for limited functions, one of the most viable near-term strategies for improvement of the surface traffic is issuing a push back advisory to each departing aircraft. This dissertation focuses on the optimization of a push back time window for each departing aircraft. The optimization takes into account both spatial and temporal uncertainties of ramp area aircraft trajectories. The uncertainties are described by a stochastic kinematic model of aircraft trajectories, which is used to infer distributions of combinations of push back times that lead to conflict among trajectories from different gates. The model is validated and the distributions are included in the push back time window optimization. Under the assumption of a fixed taxiway spot schedule, the computed push back time windows can be integrated with a higher level taxiway scheduler to optimize the flow of traffic from the gate to the departure runway queue. To enable real-time decision making the computational time of the push back time window optimization is critical and is analyzed throughout.

Short-Term Load Forecasting Based Automatic Distribution Network Reconfiguration

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

Jiang, Huaiguang; Ding, Fei; Zhang, Yingchen

In a traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of the load forecasting technique can provide an accurate prediction of the load power that will happen in a future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during a longer time period instead of using a snapshot of the load at the time when the reconfiguration happens; thus, the distribution system operatormore » can use this information to better operate the system reconfiguration and achieve optimal solutions. This paper proposes a short-term load forecasting approach to automatically reconfigure distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with a forecaster based on support vector regression and parallel parameters optimization. The network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum amount of loss at the future time. The simulation results validate and evaluate the proposed approach.« less

Short-Term Load Forecasting-Based Automatic Distribution Network Reconfiguration

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

Jiang, Huaiguang; Ding, Fei; Zhang, Yingchen

In a traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of the load forecasting technique can provide an accurate prediction of the load power that will happen in a future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during a longer time period instead of using a snapshot of the load at the time when the reconfiguration happens; thus, the distribution system operatormore » can use this information to better operate the system reconfiguration and achieve optimal solutions. This paper proposes a short-term load forecasting approach to automatically reconfigure distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with a forecaster based on support vector regression and parallel parameters optimization. The network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum amount of loss at the future time. The simulation results validate and evaluate the proposed approach.« less

Real-time reservoir operation considering non-stationary inflow prediction

NASA Astrophysics Data System (ADS)

Zhao, J.; Xu, W.; Cai, X.; Wang, Z.

2011-12-01

Stationarity of inflow has been a basic assumption for reservoir operation rule design, which is now facing challenges due to climate change and human interferences. This paper proposes a modeling framework to incorporate non-stationary inflow prediction for optimizing the hedging operation rule of large reservoirs with multiple-year flow regulation capacity. A multi-stage optimization model is formulated and a solution algorithm based on the optimality conditions is developed to incorporate non-stationary annual inflow prediction through a rolling, dynamic framework that updates the prediction from period to period and adopt the updated prediction in reservoir operation decision. The prediction model is ARIMA(4,1,0), in which parameter 4 stands for the order of autoregressive, 1 represents a linear trend, and 0 is the order of moving average. The modeling framework and solution algorithm is applied to the Miyun reservoir in China, determining a yearly operating schedule during the period from 1996 to 2009, during which there was a significant declining trend of reservoir inflow. Different operation policy scenarios are modeled, including standard operation policy (SOP, matching the current demand as much as possible), hedging rule (i.e., leaving a certain amount of water for future to avoid large risk of water deficit) with forecast from ARIMA (HR-1), hedging (HR) with perfect forecast (HR-2 ). Compared to the results of these scenarios to that of the actual reservoir operation (AO), the utility of the reservoir operation under HR-1 is 3.0% lower than HR-2, but 3.7% higher than the AO and 14.4% higher than SOP. Note that the utility under AO is 10.3% higher than that under SOP, which shows that a certain level of hedging under some inflow prediction or forecast was used in the real-world operation. Moreover, the impacts of discount rate and forecast uncertainty level on the operation will be discussed.

Data analytics and optimization of an ice-based energy storage system for commercial buildings

DOE PAGES

Luo, Na; Hong, Tianzhen; Li, Hui; ...

2017-07-25

Ice-based thermal energy storage (TES) systems can shift peak cooling demand and reduce operational energy costs (with time-of-use rates) in commercial buildings. The accurate prediction of the cooling load, and the optimal control strategy for managing the charging and discharging of a TES system, are two critical elements to improving system performance and achieving energy cost savings. This study utilizes data-driven analytics and modeling to holistically understand the operation of an ice–based TES system in a shopping mall, calculating the system’s performance using actual measured data from installed meters and sensors. Results show that there is significant savings potential whenmore » the current operating strategy is improved by appropriately scheduling the operation of each piece of equipment of the TES system, as well as by determining the amount of charging and discharging for each day. A novel optimal control strategy, determined by an optimization algorithm of Sequential Quadratic Programming, was developed to minimize the TES system’s operating costs. Three heuristic strategies were also investigated for comparison with our proposed strategy, and the results demonstrate the superiority of our method to the heuristic strategies in terms of total energy cost savings. Specifically, the optimal strategy yields energy costs of up to 11.3% per day and 9.3% per month compared with current operational strategies. A one-day-ahead hourly load prediction was also developed using machine learning algorithms, which facilitates the adoption of the developed data analytics and optimization of the control strategy in a real TES system operation.« less

Data analytics and optimization of an ice-based energy storage system for commercial buildings

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

Luo, Na; Hong, Tianzhen; Li, Hui

Ice-based thermal energy storage (TES) systems can shift peak cooling demand and reduce operational energy costs (with time-of-use rates) in commercial buildings. The accurate prediction of the cooling load, and the optimal control strategy for managing the charging and discharging of a TES system, are two critical elements to improving system performance and achieving energy cost savings. This study utilizes data-driven analytics and modeling to holistically understand the operation of an ice–based TES system in a shopping mall, calculating the system’s performance using actual measured data from installed meters and sensors. Results show that there is significant savings potential whenmore » the current operating strategy is improved by appropriately scheduling the operation of each piece of equipment of the TES system, as well as by determining the amount of charging and discharging for each day. A novel optimal control strategy, determined by an optimization algorithm of Sequential Quadratic Programming, was developed to minimize the TES system’s operating costs. Three heuristic strategies were also investigated for comparison with our proposed strategy, and the results demonstrate the superiority of our method to the heuristic strategies in terms of total energy cost savings. Specifically, the optimal strategy yields energy costs of up to 11.3% per day and 9.3% per month compared with current operational strategies. A one-day-ahead hourly load prediction was also developed using machine learning algorithms, which facilitates the adoption of the developed data analytics and optimization of the control strategy in a real TES system operation.« less

Determining optimal operation parameters for reducing PCDD/F emissions (I-TEQ values) from the iron ore sintering process by using the Taguchi experimental design.

PubMed

Chen, Yu-Cheng; Tsai, Perng-Jy; Mou, Jin-Luh

2008-07-15

This study is the first one using the Taguchi experimental design to identify the optimal operating condition for reducing polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/ Fs) formations during the iron ore sintering process. Four operating parameters, including the water content (Wc; range = 6.0-7.0 wt %), suction pressure (Ps; range = 1000-1400 mmH2O), bed height (Hb; range = 500-600 mm), and type of hearth layer (including sinter, hematite, and limonite), were selected for conducting experiments in a pilot scale sinter pot to simulate various sintering operating conditions of a real-scale sinter plant We found that the resultant optimal combination (Wc = 6.5 wt%, Hb = 500 mm, Ps = 1000 mmH2O, and hearth layer = hematite) could decrease the emission factor of total PCDD/Fs (total EF(PCDD/Fs)) up to 62.8% by reference to the current operating condition of the real-scale sinter plant (Wc = 6.5 wt %, Hb = 550 mm, Ps = 1200 mmH2O, and hearth layer = sinter). Through the ANOVA analysis, we found that Wc was the most significant parameter in determining total EF(PCDD/Fs (accounting for 74.7% of the total contribution of the four selected parameters). The resultant optimal combination could also enhance slightly in both sinter productivity and sinter strength (30.3 t/m2/day and 72.4%, respectively) by reference to those obtained from the reference operating condition (29.9 t/m (2)/day and 72.2%, respectively). The above results further ensure the applicability of the obtained optimal combination for the real-scale sinter production without interfering its sinter productivity and sinter strength.

A water management decision support system contributing to sustainability

NASA Astrophysics Data System (ADS)

Horváth, Klaudia; van Esch, Bart; Baayen, Jorn; Pothof, Ivo; Talsma, Jan; van Heeringen, Klaas-Jan

2017-04-01

Deltares and Eindhoven University of Technology are developing a new decision support system (DSS) for regional water authorities. In order to maintain water levels in the Dutch polder system, water should be drained and pumped out from the polders to the sea. The time and amount of pumping depends on the current sea level, the water level in the polder, the weather forecast and the electricity price forecast and possibly local renewable power production. This is a multivariable optimisation problem, where the goal is to keep the water level in the polder within certain bounds. By optimizing the operation of the pumps the energy usage and costs can be reduced, hence the operation of the regional water authorities can be more sustainable, while also anticipating on increasing share of renewables in the energy mix in a cost-effective way. The decision support system, based on Delft-FEWS as operational data-integration platform, is running an optimization model built in RTC-Tools 2, which is performing real-time optimization in order to calculate the pumping strategy. It is taking into account the present and future circumstances. As being the core of the real time decision support system, RTC-Tools 2 fulfils the key requirements to a DSS: it is fast, robust and always finds the optimal solution. These properties are associated with convex optimization. In such problems the global optimum can always be found. The challenge in the development is to maintain the convex formulation of all the non-linear components in the system, i.e. open channels, hydraulic structures, and pumps. The system is introduced through 4 pilot projects, one of which is a pilot of the Dutch Water Authority Rivierenland. This is a typical Dutch polder system: several polders are drained to the main water system, the Linge. The water from the Linge can be released to the main rivers that are subject to tidal fluctuations. In case of low tide, water can be released via the gates. In case of high tide, water should be pumped. The goal of the pilot is to make the operation of the regional water authority more sustainable and cost-efficient. Sustainability can be achieved by minimizing the CO2 production trough minimizing the energy used for pumping. This work is showing the functionalities of the new decision support system, using RTC-Tools 2, through the example of a pilot project.

FT-NIR: A Tool for Process Monitoring and More.

PubMed

Martoccia, Domenico; Lutz, Holger; Cohen, Yvan; Jerphagnon, Thomas; Jenelten, Urban

2018-03-30

With ever-increasing pressure to optimize product quality, to reduce cost and to safely increase production output from existing assets, all combined with regular changes in terms of feedstock and operational targets, process monitoring with traditional instruments reaches its limits. One promising answer to these challenges is in-line, real time process analysis with spectroscopic instruments, and above all Fourier-Transform Near Infrared spectroscopy (FT-NIR). Its potential to afford decreased batch cycle times, higher yields, reduced rework and minimized batch variance is presented and application examples in the field of fine chemicals are given. We demonstrate that FT-NIR can be an efficient tool for improved process monitoring and optimization, effective process design and advanced process control.

Inventory-transportation integrated optimization for maintenance spare parts of high-speed trains

PubMed Central

Wang, Jiaxi; Wang, Huasheng; Wang, Zhongkai; Li, Jian; Lin, Ruixi; Xiao, Jie; Wu, Jianping

2017-01-01

This paper presents a 0–1 programming model aimed at obtaining the optimal inventory policy and transportation mode for maintenance spare parts of high-speed trains. To obtain the model parameters for occasionally-replaced spare parts, a demand estimation method based on the maintenance strategies of China’s high-speed railway system is proposed. In addition, we analyse the shortage time using PERT, and then calculate the unit time shortage cost from the viewpoint of train operation revenue. Finally, a real-world case study from Shanghai Depot is conducted to demonstrate our method. Computational results offer an effective and efficient decision support for inventory managers. PMID:28472097

Assessment of Liver Fibrosis Using Real-time Shear-wave Elastography for Patients with Hepatitis B e Antigen-negative Chronic Hepatitis B and Alanine Transaminase <2 Times the Upper Limit of Normal.

PubMed

Liu, Jing-Hua; Zou, Yu; Chang, Wei; Wu, Jun; Zou, Yu; Xie, Yu-Chen; Lu, Yong-Ping; Wei, Jia

2017-01-01

We assessed liver fibrosis using real-time shear-wave elastography (SWE) combined with liver biopsy (LB) for patients with hepatitis B e antigen (HBeAg)-negative chronic hepatitis B (CHB) and alanine transaminase < 2 times the upper limit of normal and hepatitis B virus DNA < 2000 IU/ml. A total of 107 patients met the inclusion criteria. Real- ime SWE and ultrasoundassisted liver biopsies were consecutively performed. Fibrosis was staged according to the METAVIR scoring system. Analyses of receiver operating characteristic curve were performed to calculate the optimal area under the receiver operating characteristic curve for F0-F1 versus F2-F4, F0-F2 versus F3-F4, and F0-F3 versus F4 for real-time SWE. The most concurrent liver fibrosis degrees were between F1 and F2 for these HBeAg-negative CHB patients. Liver stiffness increased in parallel with the degree of liver fibrosis using SWE measurements. The area under the receiver operating characteristic curves was 0.881 (95% confidence interval [CI]: 0.704-1.000) for SWE (p = 0.004); 0.912 (95% CI: 0.836-0.987) for SWE (p = 0.000); 0.981 (95% CI: 0.956-1.000) for SWE (p = 0.000); 0.974 (95% CI: 0.936-1.000) for SWE (p = 0.000) when comparing F0 versus F1-F4, F0-F1 versus F2-F4, F0-F2 versus F3-F4, and F0-F3 versus F4, respectively. SWE has the advantage of providing an image of liver stiffness in real-time. As an alternative to LB, the development of all these noninvasive methods for dynamic evaluation of liver fibrosis will decrease the need for LB, making clinical care safer and more convenient for patients with liver diseases.

GPU-Based Real-Time Volumetric Ultrasound Image Reconstruction for a Ring Array

PubMed Central

Choe, Jung Woo; Nikoozadeh, Amin; Oralkan, Ömer; Khuri-Yakub, Butrus T.

2014-01-01

Synthetic phased array (SPA) beamforming with Hadamard coding and aperture weighting is an optimal option for real-time volumetric imaging with a ring array, a particularly attractive geometry in intracardiac and intravascular applications. However, the imaging frame rate of this method is limited by the immense computational load required in synthetic beamforming. For fast imaging with a ring array, we developed graphics processing unit (GPU)-based, real-time image reconstruction software that exploits massive data-level parallelism in beamforming operations. The GPU-based software reconstructs and displays three cross-sectional images at 45 frames per second (fps). This frame rate is 4.5 times higher than that for our previously-developed multi-core CPU-based software. In an alternative imaging mode, it shows one B-mode image rotating about the axis and its maximum intensity projection (MIP), processed at a rate of 104 fps. This paper describes the image reconstruction procedure on the GPU platform and presents the experimental images obtained using this software. PMID:23529080

Can Subjects be Guided to Optimal Decisions The Use of a Real-Time Training Intervention Model

DTIC Science & Technology

2016-06-01

execution of the task and may then be analyzed to determine if there is correlation between designated factors (scores, proportion of time in each...state with their decision performance in real time could allow training systems to be designed to tailor training to the individual decision maker...release; distribution is unlimited CAN SUBJECTS BE GUIDED TO OPTIMAL DECISIONS? THE USE OF A REAL- TIME TRAINING INTERVENTION MODEL by Travis D

A real-time and closed-loop control algorithm for cascaded multilevel inverter based on artificial neural network.

PubMed

Wang, Libing; Mao, Chengxiong; Wang, Dan; Lu, Jiming; Zhang, Junfeng; Chen, Xun

2014-01-01

In order to control the cascaded H-bridges (CHB) converter with staircase modulation strategy in a real-time manner, a real-time and closed-loop control algorithm based on artificial neural network (ANN) for three-phase CHB converter is proposed in this paper. It costs little computation time and memory. It has two steps. In the first step, hierarchical particle swarm optimizer with time-varying acceleration coefficient (HPSO-TVAC) algorithm is employed to minimize the total harmonic distortion (THD) and generate the optimal switching angles offline. In the second step, part of optimal switching angles are used to train an ANN and the well-designed ANN can generate optimal switching angles in a real-time manner. Compared with previous real-time algorithm, the proposed algorithm is suitable for a wider range of modulation index and results in a smaller THD and a lower calculation time. Furthermore, the well-designed ANN is embedded into a closed-loop control algorithm for CHB converter with variable direct voltage (DC) sources. Simulation results demonstrate that the proposed closed-loop control algorithm is able to quickly stabilize load voltage and minimize the line current's THD (<5%) when subjecting the DC sources disturbance or load disturbance. In real design stage, a switching angle pulse generation scheme is proposed and experiment results verify its correctness.

Real-time Collision Avoidance and Path Optimizer for Semi-autonomous UAVs.

NASA Astrophysics Data System (ADS)

Hawary, A. F.; Razak, N. A.

2018-05-01

Whilst UAV offers a potentially cheaper and more localized observation platform than current satellite or land-based approaches, it requires an advance path planner to reveal its true potential, particularly in real-time missions. Manual control by human will have limited line-of-sights and prone to errors due to careless and fatigue. A good alternative solution is to equip the UAV with semi-autonomous capabilities that able to navigate via a pre-planned route in real-time fashion. In this paper, we propose an easy-and-practical path optimizer based on the classical Travelling Salesman Problem and adopts a brute force search method to re-optimize the route in the event of collisions using range finder sensor. The former utilizes a Simple Genetic Algorithm and the latter uses Nearest Neighbour algorithm. Both algorithms are combined to optimize the route and avoid collision at once. Although many researchers proposed various path planning algorithms, we find that it is difficult to integrate on a basic UAV model and often lacks of real-time collision detection optimizer. Therefore, we explore a practical benefit from this approach using on-board Arduino and Ardupilot controllers by manually emulating the motion of an actual UAV model prior to test on the flying site. The result showed that the range finder sensor provides a real-time data to the algorithm to find a collision-free path and eventually optimized the route successfully.

Optimizing the real-time ground level enhancement alert system based on neutron monitor measurements: Introducing GLE Alert Plus

NASA Astrophysics Data System (ADS)

Souvatzoglou, G.; Papaioannou, A.; Mavromichalaki, H.; Dimitroulakos, J.; Sarlanis, C.

2014-11-01

Whenever a significant intensity increase is being recorded by at least three neutron monitor stations in real-time mode, a ground level enhancement (GLE) event is marked and an automated alert is issued. Although, the physical concept of the algorithm is solid and has efficiently worked in a number of cases, the availability of real-time data is still an open issue and makes timely GLE alerts quite challenging. In this work we present the optimization of the GLE alert that has been set into operation since 2006 at the Athens Neutron Monitor Station. This upgrade has led to GLE Alert Plus, which is currently based upon the Neutron Monitor Database (NMDB). We have determined the critical values per station allowing us to issue reliable GLE alerts close to the initiation of the event while at the same time we keep the false alert rate at low levels. Furthermore, we have managed to treat the problem of data availability, introducing the Go-Back-N algorithm. A total of 13 GLE events have been marked from January 2000 to December 2012. GLE Alert Plus issued an alert for 12 events. These alert times are compared to the alert times of GOES Space Weather Prediction Center and Solar Energetic Particle forecaster of the University of Málaga (UMASEP). In all cases GLE Alert Plus precedes the GOES alert by ≈8-52 min. The comparison with UMASEP demonstrated a remarkably good agreement. Real-time GLE alerts by GLE Alert Plus may be retrieved by http://cosray.phys.uoa.gr/gle_alert_plus.html, http://www.nmdb.eu, and http://swe.ssa.esa.int/web/guest/space-radiation. An automated GLE alert email notification system is also available to interested users.

A heterogeneous fleet vehicle routing model for solving the LPG distribution problem: A case study

NASA Astrophysics Data System (ADS)

Onut, S.; Kamber, M. R.; Altay, G.

2014-03-01

Vehicle Routing Problem (VRP) is an important management problem in the field of distribution and logistics. In VRPs, routes from a distribution point to geographically distributed points are designed with minimum cost and considering customer demands. All points should be visited only once and by one vehicle in one route. Total demand in one route should not exceed the capacity of the vehicle that assigned to that route. VRPs are varied due to real life constraints related to vehicle types, number of depots, transportation conditions and time periods, etc. Heterogeneous fleet vehicle routing problem is a kind of VRP that vehicles have different capacity and costs. There are two types of vehicles in our problem. In this study, it is used the real world data and obtained from a company that operates in LPG sector in Turkey. An optimization model is established for planning daily routes and assigned vehicles. The model is solved by GAMS and optimal solution is found in a reasonable time.

A Novel Approach of Battery Energy Storage for Improving Value of Wind Power in Deregulated Markets

NASA Astrophysics Data System (ADS)

Nguyen, Y. Minh; Yoon, Yong Tae

2013-06-01

Wind power producers face many regulation costs in deregulated environment, which remarkably lowers the value of wind power in comparison with the conventional sources. One of these costs is associated with the real-time variation of power output and being paid in frequency control market according to the variation band. In this regard, this paper presents a new approach to the scheduling and operation of battery energy storage installed in wind generation system. This approach depends on the statistic data of wind generation and the prediction of frequency control market prices to determine the optimal charging and discharging of batteries in real-time, which ultimately gives the minimum cost of frequency regulation for wind power producers. The optimization problem is formulated as the trade-off between the decrease in regulation payment and the increase in the cost of using battery energy storage. The approach is illustrated in the case study and the results of simulation show its effectiveness.

Automatic threshold optimization in nonlinear energy operator based spike detection.

PubMed

Malik, Muhammad H; Saeed, Maryam; Kamboh, Awais M

2016-08-01

In neural spike sorting systems, the performance of the spike detector has to be maximized because it affects the performance of all subsequent blocks. Non-linear energy operator (NEO), is a popular spike detector due to its detection accuracy and its hardware friendly architecture. However, it involves a thresholding stage, whose value is usually approximated and is thus not optimal. This approximation deteriorates the performance in real-time systems where signal to noise ratio (SNR) estimation is a challenge, especially at lower SNRs. In this paper, we propose an automatic and robust threshold calculation method using an empirical gradient technique. The method is tested on two different datasets. The results show that our optimized threshold improves the detection accuracy in both high SNR and low SNR signals. Boxplots are presented that provide a statistical analysis of improvements in accuracy, for instance, the 75th percentile was at 98.7% and 93.5% for the optimized NEO threshold and traditional NEO threshold, respectively.

Designing train-speed trajectory with energy efficiency and service quality

NASA Astrophysics Data System (ADS)

Jia, Jiannan; Yang, Kai; Yang, Lixing; Gao, Yuan; Li, Shukai

2018-05-01

With the development of automatic train operations, optimal trajectory design is significant to the performance of train operations in railway transportation systems. Considering energy efficiency and service quality, this article formulates a bi-objective train-speed trajectory optimization model to minimize simultaneously the energy consumption and travel time in an inter-station section. This article is distinct from previous studies in that more sophisticated train driving strategies characterized by the acceleration/deceleration gear, the cruising speed, and the speed-shift site are specifically considered. For obtaining an optimal train-speed trajectory which has equal satisfactory degree on both objectives, a fuzzy linear programming approach is applied to reformulate the objectives. In addition, a genetic algorithm is developed to solve the proposed train-speed trajectory optimization problem. Finally, a series of numerical experiments based on a real-world instance of Beijing-Tianjin Intercity Railway are implemented to illustrate the practicability of the proposed model as well as the effectiveness of the solution methodology.

Monitoring airborne molecular contamination: a quantitative and qualitative comparison of real-time and grab-sampling techniques

NASA Astrophysics Data System (ADS)

Shupp, Aaron M.; Rodier, Dan; Rowley, Steven

2007-03-01

Monitoring and controlling Airborne Molecular Contamination (AMC) has become essential in deep ultraviolet (DUV) photolithography for both optimizing yields and protecting tool optics. A variety of technologies have been employed for both real-time and grab-sample monitoring. Real-time monitoring has the advantage of quickly identifying "spikes" and upset conditions, while 2 - 24 hour plus grab sampling allows for extremely low detection limits by concentrating the mass of the target contaminant over a period of time. Employing a combination of both monitoring techniques affords the highest degree of control, lowest detection limits, and the most detailed data possible in terms of speciation. As happens with many technologies, there can be concern regarding the accuracy and agreement between real-time and grab-sample methods. This study utilizes side by side comparisons of two different real-time monitors operating in parallel with both liquid impingers and dry sorbent tubes to measure NIST traceable gas standards as well as real world samples. By measuring in parallel, a truly valid comparison is made between methods while verifying the results against a certified standard. The final outcome for this investigation is that a dry sorbent tube grab-sample technique produced results that agreed in terms of accuracy with NIST traceable standards as well as the two real-time techniques Ion Mobility Spectrometry (IMS) and Pulsed Fluorescence Detection (PFD) while a traditional liquid impinger technique showed discrepancies.

Design and implementation of fuzzy-PD controller based on relation models: A cross-entropy optimization approach

NASA Astrophysics Data System (ADS)

Anisimov, D. N.; Dang, Thai Son; Banerjee, Santo; Mai, The Anh

2017-07-01

In this paper, an intelligent system use fuzzy-PD controller based on relation models is developed for a two-wheeled self-balancing robot. Scaling factors of the fuzzy-PD controller are optimized by a Cross-Entropy optimization method. A linear Quadratic Regulator is designed to bring a comparison with the fuzzy-PD controller by control quality parameters. The controllers are ported and run on STM32F4 Discovery Kit based on the real-time operating system. The experimental results indicate that the proposed fuzzy-PD controller runs exactly on embedded system and has desired performance in term of fast response, good balance and stabilize.

Rapid optimization of tension distribution for cable-driven parallel manipulators with redundant cables

NASA Astrophysics Data System (ADS)

Ouyang, Bo; Shang, Weiwei

2016-03-01

The solution of tension distributions is infinite for cable-driven parallel manipulators(CDPMs) with redundant cables. A rapid optimization method for determining the optimal tension distribution is presented. The new optimization method is primarily based on the geometry properties of a polyhedron and convex analysis. The computational efficiency of the optimization method is improved by the designed projection algorithm, and a fast algorithm is proposed to determine which two of the lines are intersected at the optimal point. Moreover, a method for avoiding the operating point on the lower tension limit is developed. Simulation experiments are implemented on a six degree-of-freedom(6-DOF) CDPM with eight cables, and the results indicate that the new method is one order of magnitude faster than the standard simplex method. The optimal distribution of tension distribution is thus rapidly established on real-time by the proposed method.

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

Dubart, Philippe; Hautot, Felix; Morichi, Massimo

Good management of dismantling and decontamination (D and D) operations and activities is requiring safety, time saving and perfect radiological knowledge of the contaminated environment as well as optimization for personnel dose and minimization of waste volume. In the same time, Fukushima accident has imposed a stretch to the nuclear measurement operational approach requiring in such emergency situation: fast deployment and intervention, quick analysis and fast scenario definition. AREVA, as return of experience from his activities carried out at Fukushima and D and D sites has developed a novel multi-sensor solution as part of his D and D research, approachmore » and method, a system with real-time 3D photo-realistic spatial radiation distribution cartography of contaminated premises. The system may be hand-held or mounted on a mobile device (robot, drone, e.g). In this paper, we will present our current development based on a SLAM technology (Simultaneous Localization And Mapping) and integrated sensors and detectors allowing simultaneous topographic and radiological (dose rate and/or spectroscopy) data acquisitions. This enabling technology permits 3D gamma activity cartography in real-time. (authors)« less

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

PubMed

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

2001-09-01

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

Advanced Hard Real-Time Operating System, The Maruti Project. Part 1.

DTIC Science & Technology

1997-01-01

REAL - TIME OPERATING SYSTEM , THE MARUTI PROJECT Part 1 of 2 Ashok K. Agrawala Satish K. Tripathi Department of Computer Science University of Maryland...Hard Real - Time Operating System , The Maruti Project DASG-60-92-C-0055 5b. Program Element # 62301E 6. Author(s) 5c. Project # DRPB Ashok K. Agrawala...SdSA94), a real - time operating system developed at the I3nversity of Maryland, and conducted extensive experiments under various task

Dynamic Loading of Substation Distribution Transformers: An Application for use in a Production Grade Environment

NASA Astrophysics Data System (ADS)

Zhang, Ming

Recent trends in the electric power industry have led to more attention to optimal operation of power transformers. In a deregulated environment, optimal operation means minimizing the maintenance and extending the life of this critical and costly equipment for the purpose of maximizing profits. Optimal utilization of a transformer can be achieved through the use of dynamic loading. A benefit of dynamic loading is that it allows better utilization of the transformer capacity, thus increasing the flexibility and reliability of the power system. This document presents the progress on a software application which can estimate the maximum time-varying loading capability of transformers. This information can be used to load devices closer to their limits without exceeding the manufacturer specified operating limits. The maximally efficient dynamic loading of transformers requires a model that can accurately predict both top-oil temperatures (TOTs) and hottest-spot temperatures (HSTs). In the previous work, two kinds of thermal TOT and HST models have been studied and used in the application: the IEEE TOT/HST models and the ASU TOT/HST models. And, several metrics have been applied to evaluate the model acceptability and determine the most appropriate models for using in the dynamic loading calculations. In this work, an investigation to improve the existing transformer thermal models performance is presented. Some factors that may affect the model performance such as improper fan status and the error caused by the poor performance of IEEE models are discussed. Additional methods to determine the reliability of transformer thermal models using metrics such as time constant and the model parameters are also provided. A new production grade application for real-time dynamic loading operating purpose is introduced. This application is developed by using an existing planning application, TTeMP, as a start point, which is designed for the dispatchers and load specialists. To overcome the limitations of TTeMP, the new application can perform dynamic loading under emergency conditions, such as loss-of transformer loading. It also has the capability to determine the emergency rating of the transformers for a real-time estimation.

Scalable large format 3D displays

NASA Astrophysics Data System (ADS)

Chang, Nelson L.; Damera-Venkata, Niranjan

2010-02-01

We present a general framework for the modeling and optimization of scalable large format 3-D displays using multiple projectors. Based on this framework, we derive algorithms that can robustly optimize the visual quality of an arbitrary combination of projectors (e.g. tiled, superimposed, combinations of the two) without manual adjustment. The framework creates for the first time a new unified paradigm that is agnostic to a particular configuration of projectors yet robustly optimizes for the brightness, contrast, and resolution of that configuration. In addition, we demonstrate that our algorithms support high resolution stereoscopic video at real-time interactive frame rates achieved on commodity graphics hardware. Through complementary polarization, the framework creates high quality multi-projector 3-D displays at low hardware and operational cost for a variety of applications including digital cinema, visualization, and command-and-control walls.

Real-time assessment of mental workload using psychophysiological measures and artificial neural networks.

PubMed

Wilson, Glenn F; Russell, Christopher A

The functional state of the human operator is critical to optimal system performance. Degraded states of operator functioning can lead to errors and overall suboptimal system performance. Accurate assessment of operator functional state is crucial to the successful implementation of an adaptive aiding system. One method of determining operators' functional state is by monitoring their physiology. In the present study, artificial neural networks using physiological signals were used to continuously monitor, in real time, the functional state of 7 participants while they performed the Multi-Attribute Task Battery with two levels of task difficulty. Six channels of brain electrical activity and eye, heart and respiration measures were evaluated on line. The accuracy of the classifier was determined to test its utility as an on-line measure of operator state. The mean classification accuracies were 85%, 82%, and 86% for the baseline, low task difficulty, and high task difficulty conditions, respectively. The high levels of accuracy suggest that these procedures can be used to provide accurate estimates of operator functional state that can be used to provide adaptive aiding. The relative contribution of each of the 43 psychophysiological features was also determined. Actual or potential applications of this research include test and evaluation and adaptive aiding implementation.

On-Board Real-Time Optimization Control for Turbo-Fan Engine Life Extending

NASA Astrophysics Data System (ADS)

Zheng, Qiangang; Zhang, Haibo; Miao, Lizhen; Sun, Fengyong

2017-11-01

A real-time optimization control method is proposed to extend turbo-fan engine service life. This real-time optimization control is based on an on-board engine mode, which is devised by a MRR-LSSVR (multi-input multi-output recursive reduced least squares support vector regression method). To solve the optimization problem, a FSQP (feasible sequential quadratic programming) algorithm is utilized. The thermal mechanical fatigue is taken into account during the optimization process. Furthermore, to describe the engine life decaying, a thermal mechanical fatigue model of engine acceleration process is established. The optimization objective function not only contains the sub-item which can get fast response of the engine, but also concludes the sub-item of the total mechanical strain range which has positive relationship to engine fatigue life. Finally, the simulations of the conventional optimization control which just consider engine acceleration performance or the proposed optimization method have been conducted. The simulations demonstrate that the time of the two control methods from idle to 99.5 % of the maximum power are equal. However, the engine life using the proposed optimization method could be surprisingly increased by 36.17 % compared with that using conventional optimization control.

Secure estimation, control and optimization of uncertain cyber-physical systems with applications to power networks

NASA Astrophysics Data System (ADS)

Taha, Ahmad Fayez

Transportation networks, wearable devices, energy systems, and the book you are reading now are all ubiquitous cyber-physical systems (CPS). These inherently uncertain systems combine physical phenomena with communication, data processing, control and optimization. Many CPSs are controlled and monitored by real-time control systems that use communication networks to transmit and receive data from systems modeled by physical processes. Existing studies have addressed a breadth of challenges related to the design of CPSs. However, there is a lack of studies on uncertain CPSs subject to dynamic unknown inputs and cyber-attacks---an artifact of the insertion of communication networks and the growing complexity of CPSs. The objective of this dissertation is to create secure, computational foundations for uncertain CPSs by establishing a framework to control, estimate and optimize the operation of these systems. With major emphasis on power networks, the dissertation deals with the design of secure computational methods for uncertain CPSs, focusing on three crucial issues---(1) cyber-security and risk-mitigation, (2) network-induced time-delays and perturbations and (3) the encompassed extreme time-scales. The dissertation consists of four parts. In the first part, we investigate dynamic state estimation (DSE) methods and rigorously examine the strengths and weaknesses of the proposed routines under dynamic attack-vectors and unknown inputs. In the second part, and utilizing high-frequency measurements in smart grids and the developed DSE methods in the first part, we present a risk mitigation strategy that minimizes the encountered threat levels, while ensuring the continual observability of the system through available, safe measurements. The developed methods in the first two parts rely on the assumption that the uncertain CPS is not experiencing time-delays, an assumption that might fail under certain conditions. To overcome this challenge, networked unknown input observers---observers/estimators for uncertain CPSs---are designed such that the effect of time-delays and cyber-induced perturbations are minimized, enabling secure DSE and risk mitigation in the first two parts. The final part deals with the extreme time-scales encompassed in CPSs, generally, and smart grids, specifically. Operational decisions for long time-scales can adversely affect the security of CPSs for faster time-scales. We present a model that jointly describes steady-state operation and transient stability by combining convex optimal power flow with semidefinite programming formulations of an optimal control problem. This approach can be jointly utilized with the aforementioned parts of the dissertation work, considering time-delays and DSE. The research contributions of this dissertation furnish CPS stakeholders with insights on the design and operation of uncertain CPSs, whilst guaranteeing the system's real-time safety. Finally, although many of the results of this dissertation are tailored to power systems, the results are general enough to be applied for a variety of uncertain CPSs.

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

Duchaineau, M.; Wolinsky, M.; Sigeti, D.E.

Terrain visualization is a difficult problem for applications requiring accurate images of large datasets at high frame rates, such as flight simulation and ground-based aircraft testing using synthetic sensor stimulation. On current graphics hardware, the problem is to maintain dynamic, view-dependent triangle meshes and texture maps that produce good images at the required frame rate. We present an algorithm for constructing triangle meshes that optimizes flexible view-dependent error metrics, produces guaranteed error bounds, achieves specified triangle counts directly, and uses frame-to-frame coherence to operate at high frame rates for thousands of triangles per frame. Our method, dubbed Real-time Optimally Adaptingmore » Meshes (ROAM), uses two priority queues to drive split and merge operations that maintain continuous triangulations built from pre-processed bintree triangles. We introduce two additional performance optimizations: incremental triangle stripping and priority-computation deferral lists. ROAM execution time is proportionate to the number of triangle changes per frame, which is typically a few percent of the output mesh size, hence ROAM performance is insensitive to the resolution and extent of the input terrain. Dynamic terrain and simple vertex morphing are supported.« less

Digital Equipment Corporation VAX/VMS Version 4.3

DTIC Science & Technology

1986-07-30

operating system performs process-oriented paging that allows execution of programs that may be larger than the physical memory allocated to them... to higher privileged modes. (For an explanation of how the four access modes provide memory access protection see page 9, "Memory Management".) A... to optimize program performance for real-time applications or interactive environments. July 30, 1986 - 4 - Final Evaluation Report Digital VAX/VMS

Optimization of a 3.6-THz quantum cascade laser for real-time imaging with a microbolometer focal plane array

NASA Astrophysics Data System (ADS)

Behnken, Barry N.; Karunasiri, Gamani; Chamberlin, Danielle; Robrish, Peter; Faist, Jérôme

2008-02-01

Real-time imaging in the terahertz (THz) spectral range was achieved using a 3.6-THz quantum cascade laser (QCL) and an uncooled, 160×120 pixel microbolometer camera fitted with a picarin lens. Noise equivalent temperature difference of the camera in the 1-5 THz frequency range was calculated to be at least 3 K, confirming the need for external THz illumination when imaging in this frequency regime. After evaluating the effects of various operating parameters on laser performance, the QCL found to perform optimally at 1.9 A in pulsed mode with a 300 kHz repetition rate and 10-20% duty cycle; average output power was approximately 1 mW. Under this scheme, a series of metallic objects were imaged while wrapped in various obscurants. Single-frame and extended video recordings demonstrate strong contrast between metallic materials and those of plastic, cloth, and paper - supporting the viability of this imaging technology in security screening applications. Thermal effects arising from Joule heating of the laser were found to be the dominant issue affecting output power and image quality; these effects were mitigated by limiting laser pulse widths to 670 ns and operating the system under closed-cycle refrigeration at a temperature of 10 K.

Automatic bone detection and soft tissue aware ultrasound-CT registration for computer-aided orthopedic surgery.

PubMed

Wein, Wolfgang; Karamalis, Athanasios; Baumgartner, Adrian; Navab, Nassir

2015-06-01

The transfer of preoperative CT data into the tracking system coordinates within an operating room is of high interest for computer-aided orthopedic surgery. In this work, we introduce a solution for intra-operative ultrasound-CT registration of bones. We have developed methods for fully automatic real-time bone detection in ultrasound images and global automatic registration to CT. The bone detection algorithm uses a novel bone-specific feature descriptor and was thoroughly evaluated on both in-vivo and ex-vivo data. A global optimization strategy aligns the bone surface, followed by a soft tissue aware intensity-based registration to provide higher local registration accuracy. We evaluated the system on femur, tibia and fibula anatomy in a cadaver study with human legs, where magnetically tracked bone markers were implanted to yield ground truth information. An overall median system error of 3.7 mm was achieved on 11 datasets. Global and fully automatic registration of bones aquired with ultrasound to CT is feasible, with bone detection and tracking operating in real time for immediate feedback to the surgeon.

Advanced ECCD based NTM control in closed-loop operation at ASDEX Upgrade (AUG)

NASA Astrophysics Data System (ADS)

Reich, Matthias; Barrera-Orte, Laura; Behler, Karl; Bock, Alexander; Giannone, Louis; Maraschek, Marc; Poli, Emanuele; Rapson, Chris; Stober, Jörg; Treutterer, Wolfgang

2012-10-01

In high performance plasmas, Neoclassical Tearing Modes (NTMs) are regularly observed at reactor-grade beta-values. They limit the achievable normalized beta, which is undesirable because fusion performance scales as beta squared. The method of choice for controlling and avoiding NTMs at AUG is the deposition of ECCD inside the magnetic island for stabilization in real-time (rt). Our approach to tackling such complex control problems using real-time diagnostics allows rigorous optimization of all subsystems. Recent progress in rt-equilibrium reconstruction (< 3.5 ms), rt-localization of NTMs (< 8 ms) and rt beam tracing (< 25 ms) allows closed-loop feedback operation using multiple movable mirrors as the ECCD deposition actuator. The rt-equilibrium uses function parametrization or a fast Grad-Shafranov solver with an option to include rt-MSE measurements. The island localization is based on a correlation of ECE and filtered Mirnov signals. The rt beam-tracing module provides deposition locations and their derivative versus actuator position of multiple gyrotrons. The ``MHD controller'' finally drives the actuators. Results utilizing closed-loop operation with multiple gyrotrons and their effect on NTMs are shown.

The LSST Scheduler from design to construction

NASA Astrophysics Data System (ADS)

Delgado, Francisco; Reuter, Michael A.

2016-07-01

The Large Synoptic Survey Telescope (LSST) will be a highly robotic facility, demanding a very high efficiency during its operation. To achieve this, the LSST Scheduler has been envisioned as an autonomous software component of the Observatory Control System (OCS), that selects the sequence of targets in real time. The Scheduler will drive the survey using optimization of a dynamic cost function of more than 200 parameters. Multiple science programs produce thousands of candidate targets for each observation, and multiple telemetry measurements are received to evaluate the external and the internal conditions of the observatory. The design of the LSST Scheduler started early in the project supported by Model Based Systems Engineering, detailed prototyping and scientific validation of the survey capabilities required. In order to build such a critical component, an agile development path in incremental releases is presented, integrated to the development plan of the Operations Simulator (OpSim) to allow constant testing, integration and validation in a simulated OCS environment. The final product is a Scheduler that is also capable of running 2000 times faster than real time in simulation mode for survey studies and scientific validation during commissioning and operations.

A Taxonomy of Coordination Mechanisms Used in Real-Time Software Based on Domain Analysis

DTIC Science & Technology

1993-12-01

real - time operating system . CMU/SEI-93-TR-34 3 1.3 Related Work Several taxonomies...coordination methods supported by a real - time operating system is presented by Ripps. The classification of the coordination methods rests upon a set...mechanisms avail- able today. The classification proposed by Ripps [Ripps 89] includes the mechanisms supported by a real - time operating system .

A real-time control framework for urban water reservoirs operation

NASA Astrophysics Data System (ADS)

Galelli, S.; Goedbloed, A.; Schwanenberg, D.

2012-04-01

Drinking water demand in urban areas is growing parallel to the worldwide urban population, and it is acquiring an increasing part of the total water consumption. Since the delivery of sufficient water volumes in urban areas represents a difficult logistic and economical problem, different metropolitan areas are evaluating the opportunity of constructing relatively small reservoirs within urban areas. Singapore, for example, is developing the so-called 'Four National Taps Strategies', which detects the maximization of water yields from local, urban catchments as one of the most important water sources. However, the peculiar location of these reservoirs can provide a certain advantage from the logistical point of view, but it can pose serious difficulties in their daily management. Urban catchments are indeed characterized by large impervious areas: this results in a change of the hydrological cycle, with decreased infiltration and groundwater recharge, and increased patterns of surface and river discharges, with higher peak flows, volumes and concentration time. Moreover, the high concentrations of nutrients and sediments characterizing urban discharges can cause further water quality problems. In this critical hydrological context, the effective operation of urban water reservoirs must rely on real-time control techniques, which can exploit hydro-meteorological information available in real-time from hydrological and nowcasting models. This work proposes a novel framework for the real-time control of combined water quality and quantity objectives in urban reservoirs. The core of this framework is a non-linear Model Predictive Control (MPC) scheme, which employs the current state of the system, the future discharges furnished by a predictive model and a further model describing the internal dynamics of the controlled sub-system to determine an optimal control sequence over a finite prediction horizon. The main advantage of this scheme stands in its reduced computational requests and the capability of exploiting real-time hydro-meteorological information, which are crucial for an effective operation of these fast-varying hydrological systems. The framework is here demonstrated on the operation of Marina Reservoir (Singapore), whose recent construction in late 2008 increased the effective catchment area to about 50% of the total available. Its operation, which accounts for drinking water supply, flash floods control and water quality standards, is here designed by combining the MPC scheme with the process-based hydrological model SOBEK. Extensive simulation experiments show the validity of the proposed framework.

The Power Plant Operating Data Based on Real-time Digital Filtration Technology

NASA Astrophysics Data System (ADS)

Zhao, Ning; Chen, Ya-mi; Wang, Hui-jie

2018-03-01

Real-time monitoring of the data of the thermal power plant was the basis of accurate analyzing thermal economy and accurate reconstruction of the operating state. Due to noise interference was inevitable; we need real-time monitoring data filtering to get accurate information of the units and equipment operating data of the thermal power plant. Real-time filtering algorithm couldn’t be used to correct the current data with future data. Compared with traditional filtering algorithm, there were a lot of constraints. First-order lag filtering method and weighted recursive average filtering method could be used for real-time filtering. This paper analyzes the characteristics of the two filtering methods and applications for real-time processing of the positive spin simulation data, and the thermal power plant operating data. The analysis was revealed that the weighted recursive average filtering method applied to the simulation and real-time plant data filtering achieved very good results.

Online gaming for learning optimal team strategies in real time

NASA Astrophysics Data System (ADS)

Hudas, Gregory; Lewis, F. L.; Vamvoudakis, K. G.

2010-04-01

This paper first presents an overall view for dynamical decision-making in teams, both cooperative and competitive. Strategies for team decision problems, including optimal control, zero-sum 2-player games (H-infinity control) and so on are normally solved for off-line by solving associated matrix equations such as the Riccati equation. However, using that approach, players cannot change their objectives online in real time without calling for a completely new off-line solution for the new strategies. Therefore, in this paper we give a method for learning optimal team strategies online in real time as team dynamical play unfolds. In the linear quadratic regulator case, for instance, the method learns the Riccati equation solution online without ever solving the Riccati equation. This allows for truly dynamical team decisions where objective functions can change in real time and the system dynamics can be time-varying.

End-User Applications of Real-Time Earthquake Information in Europe

NASA Astrophysics Data System (ADS)

Cua, G. B.; Gasparini, P.; Giardini, D.; Zschau, J.; Filangieri, A. R.; Reakt Wp7 Team

2011-12-01

The primary objective of European FP7 project REAKT (Strategies and Tools for Real-Time Earthquake Risk Reduction) is to improve the efficiency of real-time earthquake risk mitigation methods and their capability of protecting structures, infrastructures, and populations. REAKT aims to address the issues of real-time earthquake hazard and response from end-to-end, with efforts directed along the full spectrum of methodology development in earthquake forecasting, earthquake early warning, and real-time vulnerability systems, through optimal decision-making, and engagement and cooperation of scientists and end users for the establishment of best practices for use of real-time information. Twelve strategic test cases/end users throughout Europe have been selected. This diverse group of applications/end users includes civil protection authorities, railway systems, hospitals, schools, industrial complexes, nuclear plants, lifeline systems, national seismic networks, and critical structures. The scale of target applications covers a wide range, from two school complexes in Naples, to individual critical structures, such as the Rion Antirion bridge in Patras, and the Fatih Sultan Mehmet bridge in Istanbul, to large complexes, such as the SINES industrial complex in Portugal and the Thessaloniki port area, to distributed lifeline and transportation networks and nuclear plants. Some end-users are interested in in-depth feasibility studies for use of real-time information and development of rapid response plans, while others intend to install real-time instrumentation and develop customized automated control systems. From the onset, REAKT scientists and end-users will work together on concept development and initial implementation efforts using the data products and decision-making methodologies developed with the goal of improving end-user risk mitigation. The aim of this scientific/end-user partnership is to ensure that scientific efforts are applicable to operational, real-world problems.

Real-Time Systems

DTIC Science & Technology

1992-02-01

Postgraduate School Autonomous Under Vehicle (AUV) are then examined. Autonomous underwater vehicle (AUV), hard real-time system, real - time operating system , real-time programming language, real-time system, soft real-time system.

Mining hidden value through strategic real estate plans.

PubMed

Hayes, D

1998-11-01

Healthcare providers can get the most from their real estate investments if they manage them strategically rather than view them as a cost of doing business. Organizations that develop strategic real estate plans can optimize the cost-effectiveness of their assets, reduce operating costs, and create cash through disposition strategies. The cost-effectiveness of assets can be optimized by using off-balance-sheet financing structures, such as outright sale, sale-lease-back arrangements, synthetic leases, and beneficial occupancy agreements. Opportunities for cost reduction can be found by conducting operations, administrative, and maintenance reviews and cost-segregation studies. Cost-reduction efforts also should focus on ensuring space is used in the most productive manner possible and that the organization pays no more than the minimum required property tax. Disposition strategies should begin with inventorying real estate assets to identify surplus assets. Such assets then can be moved off the balance sheet or converted into commercial or public uses.

An Augmented Lagrangian Filter Method for Real-Time Embedded Optimization

DOE PAGES

Chiang, Nai -Yuan; Huang, Rui; Zavala, Victor M.

2017-04-17

We present a filter line-search algorithm for nonconvex continuous optimization that combines an augmented Lagrangian function and a constraint violation metric to accept and reject steps. The approach is motivated by real-time optimization applications that need to be executed on embedded computing platforms with limited memory and processor speeds. The proposed method enables primal–dual regularization of the linear algebra system that in turn permits the use of solution strategies with lower computing overheads. We prove that the proposed algorithm is globally convergent and we demonstrate the developments using a nonconvex real-time optimization application for a building heating, ventilation, and airmore » conditioning system. Our numerical tests are performed on a standard processor and on an embedded platform. Lastly, we demonstrate that the approach reduces solution times by a factor of over 1000.« less

An Augmented Lagrangian Filter Method for Real-Time Embedded Optimization

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

Chiang, Nai -Yuan; Huang, Rui; Zavala, Victor M.

We present a filter line-search algorithm for nonconvex continuous optimization that combines an augmented Lagrangian function and a constraint violation metric to accept and reject steps. The approach is motivated by real-time optimization applications that need to be executed on embedded computing platforms with limited memory and processor speeds. The proposed method enables primal–dual regularization of the linear algebra system that in turn permits the use of solution strategies with lower computing overheads. We prove that the proposed algorithm is globally convergent and we demonstrate the developments using a nonconvex real-time optimization application for a building heating, ventilation, and airmore » conditioning system. Our numerical tests are performed on a standard processor and on an embedded platform. Lastly, we demonstrate that the approach reduces solution times by a factor of over 1000.« less

Real-time contaminant sensing and control in civil infrastructure systems

NASA Astrophysics Data System (ADS)

Rimer, Sara; Katopodes, Nikolaos

2014-11-01

A laboratory-scale prototype has been designed and implemented to test the feasibility of real-time contaminant sensing and control in civil infrastructure systems. A blower wind tunnel is the basis of the prototype design, with propylene glycol smoke as the ``contaminant.'' A camera sensor and compressed-air vacuum nozzle system is set up at the test section portion of the prototype to visually sense and then control the contaminant; a real-time controller is programmed to read in data from the camera sensor and administer pressure to regulators controlling the compressed air operating the vacuum nozzles. A computational fluid dynamics model is being integrated in with this prototype to inform the correct pressure to supply to the regulators in order to optimally control the contaminant's removal from the prototype. The performance of the prototype has been evaluated against the computational fluid dynamics model and is discussed in this presentation. Furthermore, the initial performance of the sensor-control system implemented in the test section of the prototype is discussed. NSF-CMMI 0856438.

Real-time dual-loop electric current measurement for label-free nanofluidic preconcentration chip.

PubMed

Chung, Pei-Shan; Fan, Yu-Jui; Sheen, Horn-Jiunn; Tian, Wei-Cheng

2015-01-07

An electrokinetic trapping (EKT)-based nanofluidic preconcentration device with the capability of label-free monitoring trapped biomolecules through real-time dual-loop electric current measurement was demonstrated. Universal current-voltage (I-V) curves of EKT-based preconcentration devices, consisting of two microchannels connected by ion-selective channels, are presented for functional validation and optimal operation; universal onset current curves indicating the appearance of the EKT mechanism serve as a confirmation of the concentrating action. The EKT mechanism and the dissimilarity in the current curves related to the volume flow rate (Q), diffusion coefficient (D), and diffusion layer (DL) thickness were explained by a control volume model with a five-stage preconcentration process. Different behaviors of the trapped molecular plug were categorized based on four modes associated with different degrees of electroosmotic instability (EOI). A label-free approach to preconcentrating (bio)molecules and monitoring the multibehavior molecular plug was demonstrated through real-time electric current monitoring, rather than through the use of microscope images.

Particle swarm optimization with recombination and dynamic linkage discovery.

PubMed

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

2007-12-01

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

Hurricane Wave Topography and Directional Wave Spectra in Near Real-Time

DTIC Science & Technology

2005-09-30

Develop and/or modify the real - time operating system and analysis techniques and programs of the NASA Scanning Radar Altimeter (SRA) to process the...Wayne Wright is responsible for the real - time operating system of the SRA and making whatever modifications are required to enable near real-time

An Energy-Aware Trajectory Optimization Layer for sUAS

NASA Astrophysics Data System (ADS)

Silva, William A.

The focus of this work is the implementation of an energy-aware trajectory optimization algorithm that enables small unmanned aircraft systems (sUAS) to operate in unknown, dynamic severe weather environments. The software is designed as a component of an Energy-Aware Dynamic Data Driven Application System (EA-DDDAS) for sUAS. This work addresses the challenges of integrating and executing an online trajectory optimization algorithm during mission operations in the field. Using simplified aircraft kinematics, the energy-aware algorithm enables extraction of kinetic energy from measured winds to optimize thrust use and endurance during flight. The optimization layer, based upon a nonlinear program formulation, extracts energy by exploiting strong wind velocity gradients in the wind field, a process known as dynamic soaring. The trajectory optimization layer extends the energy-aware path planner developed by Wenceslao Shaw-Cortez te{Shaw-cortez2013} to include additional mission configurations, simulations with a 6-DOF model, and validation of the system with flight testing in June 2015 in Lubbock, Texas. The trajectory optimization layer interfaces with several components within the EA-DDDAS to provide an sUAS with optimal flight trajectories in real-time during severe weather. As a result, execution timing, data transfer, and scalability are considered in the design of the software. Severe weather also poses a measure of unpredictability to the system with respect to communication between systems and available data resources during mission operations. A heuristic mission tree with different cost functions and constraints is implemented to provide a level of adaptability to the optimization layer. Simulations and flight experiments are performed to assess the efficacy of the trajectory optimization layer. The results are used to assess the feasibility of flying dynamic soaring trajectories with existing controllers as well as to verify the interconnections between EA-DDDAS components. Results also demonstrate the usage of the trajectory optimization layer in conjunction with a lattice-based path planner as a method of guiding the optimization layer and stitching together subsequent trajectories.

Secure provision of reactive power ancillary services in competitive electricity markets

NASA Astrophysics Data System (ADS)

El-Samahy, Ismael

The research work presented in this thesis discusses various complex issues associated with reactive power management and pricing in the context of new operating paradigms in deregulated power systems, proposing appropriate policy solutions. An integrated two-level framework for reactive power management is set forth, which is both suitable for a competitive market and ensures a secure and reliable operation of the associated power system. The framework is generic in nature and can be adopted for any electricity market structure. The proposed hierarchical reactive power market structure comprises two stages: procurement of reactive power resources on a seasonal basis, and real-time reactive power dispatch. The main objective of the proposed framework is to provide appropriate reactive power support from service providers at least cost, while ensuring a secure operation of the power system. The proposed procurement procedure is based on a two-step optimization model. First, the marginal benefits of reactive power supply from each provider, with respect to system security, are obtained by solving a loadability-maximization problem subject to transmission security constraints imposed by voltage and thermal limits. Second, the selected set of generators is determined by solving an optimal power flow (OPF)-based auction. This auction maximizes a societal advantage function comprising generators' offers and their corresponding marginal benefits with respect to system security, and considering all transmission system constraints. The proposed procedure yields the selected set of generators and zonal price components, which would form the basis for seasonal contracts between the system operator and the selected reactive power service providers. The main objective of the proposed reactive power dispatch model is to minimize the total payment burden on the Independent System Operator (ISO), which is associated with reactive power dispatch. The real power generation is decoupled and assumed to be fixed during the reactive power dispatch procedures; however, the effect of reactive power on real power is considered in the model by calculating the required reduction in real power output of a generator due to an increase in its reactive power supply. In this case, real power generation is allowed to be rescheduled, within given limits, from the already dispatched levels obtained from the energy market clearing process. The proposed dispatch model achieves the main objective of an ISO in a competitive electricity market, which is to provide the required reactive power support from generators at least cost while ensuring a secure operation of the power system. The proposed reactive power procurement and dispatch models capture both the technical and economic aspects of power system operation in competitive electricity markets; however, from an optimization point of view, these models represent non-convex mixed integer non-linear programming (MINLP) problems due to the presence of binary variables associated with the different regions of reactive power operation in a synchronous generator. Such MINLP optimization problems are difficult to solve, especially for an actual power system. A novel Generator Reactive Power Classification (GRPC) algorithm is proposed in this thesis to address this issue, with the advantage of iteratively solving the optimization models as a series of non-linear programming (NLP) sub-problems. The proposed reactive power procurement and dispatch models are implemented and tested on the CIGRE 32-bus system, with several case studies that represent different practical operating scenarios. The developed models are also compared with other approaches for reactive power provision, and the results demonstrate the robustness and effectiveness of the proposed model. The results clearly reveal the main features of the proposed models for optimal provision of reactive power ancillary service, in order to suit the requirements of an ISO under today's stressed system conditions in a competitive market environment.

Real-Time System Verification by Kappa-Induction

NASA Technical Reports Server (NTRS)

Pike, Lee S.

2005-01-01

We report the first formal verification of a reintegration protocol for a safety-critical, fault-tolerant, real-time distributed embedded system. A reintegration protocol increases system survivability by allowing a node that has suffered a fault to regain state consistent with the operational nodes. The protocol is verified in the Symbolic Analysis Laboratory (SAL), where bounded model checking and decision procedures are used to verify infinite-state systems by k-induction. The protocol and its environment are modeled as synchronizing timeout automata. Because k-induction is exponential with respect to k, we optimize the formal model to reduce the size of k. Also, the reintegrator's event-triggered behavior is conservatively modeled as time-triggered behavior to further reduce the size of k and to make it invariant to the number of nodes modeled. A corollary is that a clique avoidance property is satisfied.

Rapid near-optimal aerospace plane trajectory generation and guidance

NASA Technical Reports Server (NTRS)

Calise, A. J.; Corban, J. E.; Markopoulos, N.

1991-01-01

Effort was directed toward the problems of the real time trajectory optimization and guidance law development for the National Aerospace Plane (NASP) applications. In particular, singular perturbation methods were used to develop guidance algorithms suitable for onboard, real time implementation. The progress made in this research effort is reported.

Making Optic Flow Robust to Dynamic Lighting Conditions for Real-Time Operation

DTIC Science & Technology

2016-03-17

ARL-TR-7629 ● MAR 2016 US Army Research Laboratory Making Optic Flow Robust to Dynamic Lighting Conditions for Real-Time...ARL-TR-7629 ● MAR 2016 US Army Research Laboratory Making Optic Flow Robust to Dynamic Lighting Conditions for Real-Time Operation...SUBTITLE Making Optic Flow Robust to Dynamic Lighting Conditions for Real-Time Operation 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT

Optimizing the Operation of Windfarms, Energy Storage and Flexible Loads in Modern Power Systems and Deregulated Electricity Markets

NASA Astrophysics Data System (ADS)

Dar, Zamiyad

The amount of wind energy in power systems is increasing at a significant rate. With this increased penetration, there are certain problems associated with the operation of windfarms which need careful attention. In the operations side, the wake effects of upstream wind turbines on downstream wind turbines can cause a reduction in the total generated power of a windfarm. On the market side, the fluctuation of real-time prices can make the operation of windfarms less profitable. Similarly, the intermittent nature of wind power prevents the windfarms from participating in the day-ahead and forward markets. On the system side, the volatile nature of wind speeds is also an obstacle for windfarms to provide frequency regulation to the system. In this thesis, we address these issues and optimize the operation of windfarms in power systems and deregulated electricity markets. First, the total power generation in a windfarm is maximized by using yaw angle of wind turbines as a control variable. We extend the existing wake models to include the effects of yaw misalignment and wake deflection of wind turbines. A numerical study is performed to find the optimal values of induction factor and yaw misalignment angle of wind turbines in a single row of a windfarm for achieving the maximum total power with wake effects. The numerical study shows that the maximum power is achieved by keeping the induction factor close to 1/3 and only changing the yaw angle to deflect the wake. We then propose a Dynamic Programming Framework (DPF) to maximize the total power production of a windfarm using yaw angle as the control variable. We compare the windfarm efficiency achieved with our DPF with the efficiency values obtained through greedy control strategy and induction factor optimization. We also extend our expressions to a windfarm with multiple rows and columns of turbines and perform simulations on the 3x3 and 4x4 grid topologies. Our results show that the optimal induction factor for most turbines is quite close to 1/3 and yaw angle acts as the dominant optimization variable. In the next part of this dissertation, a system comprising of a windfarm and energy storage operating in real-time electricity markets is studied. An Energy-balancing Threshold Price (ETP) policy is proposed to maximize the revenue of a windfarm with on-site storage. We propose and analyze a scheme for a windfarm to store or sell energy based on a threshold price. The threshold price is calculated based on long-term distributions of the electricity price and wind power generation processes, and is chosen so as to balance the energy flows in and out of the storage-equipped windfarm. It is also shown mathematically that the proposed policy is optimal in terms of the long-term revenue generated. Comparing it with the optimal policy that has knowledge of the future, we observe that the revenue obtained by the proposed ETP policy is approximately 90% of the maximum attainable revenue at a storage capacity of 10-15 times the power rating of the windfarm. The intermittent nature of wind power is a hindrance to the efficient participation of windfarms in the day-ahead and forward electricity markets. In this regard, a flexible forward contract is proposed in this dissertation which allows the windfarms to enter into a forward contract with flexible load with an option to deviate from the contracted amount of power. Using such a flexible contract would allow the windfarms to supply more or less than the contracted amount of power in case of unexpected wind conditions or real-time prices. We also propose models for forecasting wind power and real-time electricity prices. The comparison between the proposed contracting framework and a simple fixed contract (currently existing in the market) for different levels of flexibility and load shows that there is a net gain in windfarm revenues, if the transaction price of the two contracts are set equal. Lastly, we present and analyze distributed control schemes for frequency regulation in a smart grid using energy storage, wind generators, demand response and conventional generators while having no communication or data sharing between them. We also propose a novel control scheme for frequency support by energy storage in which the power output of energy storage changes proportionally with the reduction in its available energy. The application of the proposed control schemes indicates an improvement in system frequency characteristics, when there is a sudden net loss of generation.

Recce NG: from Recce sensor to image intelligence (IMINT)

NASA Astrophysics Data System (ADS)

Larroque, Serge

2001-12-01

Recce NG (Reconnaissance New Generation) is presented as a complete and optimized Tactical Reconnaissance System. Based on a new generation Pod integrating high resolution Dual Band sensors, the system has been designed with the operational lessons learnt from the last Peace Keeping Operations in Bosnia and Kosovo. The technical solutions retained as component modules of a full IMINT acquisition system, take benefit of the state of art in the following key technologies: Advanced Mission Planning System for long range stand-off Manned Recce, Aircraft and/or Pod tasking, operating sophisticated back-up software tools, high resolution 3D geo data and improved/combat proven MMI to reduce planning delays, Mature Dual Band sensors technology to achieve the Day and Night Recce Mission, including advanced automatic operational functions, as azimuth and roll tracking capabilities, low risk in Pod integration and in carrier avionics, controls and displays upgrades, to save time in operational turn over and maintenance, High rate Imagery Down Link, for Real Time or Near Real Time transmission, fully compatible with STANAG 7085 requirements, Advanced IMINT Exploitation Ground Segment, combat proven, NATO interoperable (STANAG 7023), integrating high value software tools for accurate location, improved radiometric image processing and open link to the C4ISR systems. The choice of an industrial Prime contractor mastering across the full system, all the prior listed key products and technologies, is mandatory to a successful delivery in terms of low Cost, Risk and Time Schedule.

Threshold-Based Random Charging Scheme for Decentralized PEV Charging Operation in a Smart Grid.

PubMed

Kwon, Ojin; Kim, Pilkee; Yoon, Yong-Jin

2016-12-26

Smart grids have been introduced to replace conventional power distribution systems without real time monitoring for accommodating the future market penetration of plug-in electric vehicles (PEVs). When a large number of PEVs require simultaneous battery charging, charging coordination techniques have become one of the most critical factors to optimize the PEV charging performance and the conventional distribution system. In this case, considerable computational complexity of a central controller and exchange of real time information among PEVs may occur. To alleviate these problems, a novel threshold-based random charging (TBRC) operation for a decentralized charging system is proposed. Using PEV charging thresholds and random access rates, the PEVs themselves can participate in the charging requests. As PEVs with a high battery state do not transmit the charging requests to the central controller, the complexity of the central controller decreases due to the reduction of the charging requests. In addition, both the charging threshold and the random access rate are statistically calculated based on the average of supply power of the PEV charging system that do not require a real time update. By using the proposed TBRC with a tolerable PEV charging degradation, a 51% reduction of the PEV charging requests is achieved.

Threshold-Based Random Charging Scheme for Decentralized PEV Charging Operation in a Smart Grid

PubMed Central

Kwon, Ojin; Kim, Pilkee; Yoon, Yong-Jin

2016-01-01

Smart grids have been introduced to replace conventional power distribution systems without real time monitoring for accommodating the future market penetration of plug-in electric vehicles (PEVs). When a large number of PEVs require simultaneous battery charging, charging coordination techniques have become one of the most critical factors to optimize the PEV charging performance and the conventional distribution system. In this case, considerable computational complexity of a central controller and exchange of real time information among PEVs may occur. To alleviate these problems, a novel threshold-based random charging (TBRC) operation for a decentralized charging system is proposed. Using PEV charging thresholds and random access rates, the PEVs themselves can participate in the charging requests. As PEVs with a high battery state do not transmit the charging requests to the central controller, the complexity of the central controller decreases due to the reduction of the charging requests. In addition, both the charging threshold and the random access rate are statistically calculated based on the average of supply power of the PEV charging system that do not require a real time update. By using the proposed TBRC with a tolerable PEV charging degradation, a 51% reduction of the PEV charging requests is achieved. PMID:28035963

Real-time integrated photoacoustic and ultrasound (PAUS) imaging system to guide interventional procedures: ex vivo study.

PubMed

Wei, Chen-Wei; Nguyen, Thu-Mai; Xia, Jinjun; Arnal, Bastien; Wong, Emily Y; Pelivanov, Ivan M; O'Donnell, Matthew

2015-02-01

Because of depth-dependent light attenuation, bulky, low-repetition-rate lasers are usually used in most photoacoustic (PA) systems to provide sufficient pulse energies to image at depth within the body. However, integrating these lasers with real-time clinical ultrasound (US) scanners has been problematic because of their size and cost. In this paper, an integrated PA/US (PAUS) imaging system is presented operating at frame rates >30 Hz. By employing a portable, low-cost, low-pulse-energy (~2 mJ/pulse), high-repetition-rate (~1 kHz), 1053-nm laser, and a rotating galvo-mirror system enabling rapid laser beam scanning over the imaging area, the approach is demonstrated for potential applications requiring a few centimeters of penetration. In particular, we demonstrate here real-time (30 Hz frame rate) imaging (by combining multiple single-shot sub-images covering the scan region) of an 18-gauge needle inserted into a piece of chicken breast with subsequent delivery of an absorptive agent at more than 1-cm depth to mimic PAUS guidance of an interventional procedure. A signal-to-noise ratio of more than 35 dB is obtained for the needle in an imaging area 2.8 × 2.8 cm (depth × lateral). Higher frame rate operation is envisioned with an optimized scanning scheme.

Real-time path planning and autonomous control for helicopter autorotation

NASA Astrophysics Data System (ADS)

Yomchinda, Thanan

Autorotation is a descending maneuver that can be used to recover helicopters in the event of total loss of engine power; however it is an extremely difficult and complex maneuver. The objective of this work is to develop a real-time system which provides full autonomous control for autorotation landing of helicopters. The work includes the development of an autorotation path planning method and integration of the path planner with a primary flight control system. The trajectory is divided into three parts: entry, descent and flare. Three different optimization algorithms are used to generate trajectories for each of these segments. The primary flight control is designed using a linear dynamic inversion control scheme, and a path following control law is developed to track the autorotation trajectories. Details of the path planning algorithm, trajectory following control law, and autonomous autorotation system implementation are presented. The integrated system is demonstrated in real-time high fidelity simulations. Results indicate feasibility of the capability of the algorithms to operate in real-time and of the integrated systems ability to provide safe autorotation landings. Preliminary simulations of autonomous autorotation on a small UAV are presented which will lead to a final hardware demonstration of the algorithms.

Real-time multi-target ranging based on chaotic polarization laser radars in the drive-response VCSELs.

PubMed

Zhong, Dongzhou; Xu, Geliang; Luo, Wei; Xiao, Zhenzhen

2017-09-04

According to the principle of complete chaos synchronization and the theory of Hilbert phase transformation, we propose a novel real-time multi-target ranging scheme by using chaotic polarization laser radar in the drive-response vertical-cavity surface-emitting lasers (VCSELs). In the scheme, to ensure each polarization component (PC) of the master VCSEL (MVCSEL) to be synchronized steadily with that of the slave VCSEL, the output x-PC and y-PC from the MVCSEL in the drive system and those in the response system are modulated by the linear electro-optic effect simultaneously. Under this condition, by simulating the influences of some key parameters of the system on the synchronization quality and the relative errors of the two-target ranging, related operating parameters can be optimized. The x-PC and the y-PC, as two chaotic radar sources, are used to implement the real-time ranging for two targets. It is found that the measured distances of the two targets at arbitrary position exhibit strong real-time stability and only slight jitter. Their resolutions are up to millimeters, and their relative errors are very small and less than 2.7%.

Performance evaluation and modeling of a conformal filter (CF) based real-time standoff hazardous material detection sensor

NASA Astrophysics Data System (ADS)

Nelson, Matthew P.; Tazik, Shawna K.; Bangalore, Arjun S.; Treado, Patrick J.; Klem, Ethan; Temple, Dorota

2017-05-01

Hyperspectral imaging (HSI) systems can provide detection and identification of a variety of targets in the presence of complex backgrounds. However, current generation sensors are typically large, costly to field, do not usually operate in real time and have limited sensitivity and specificity. Despite these shortcomings, HSI-based intelligence has proven to be a valuable tool, thus resulting in increased demand for this type of technology. By moving the next generation of HSI technology into a more adaptive configuration, and a smaller and more cost effective form factor, HSI technologies can help maintain a competitive advantage for the U.S. armed forces as well as local, state and federal law enforcement agencies. Operating near the physical limits of HSI system capability is often necessary and very challenging, but is often enabled by rigorous modeling of detection performance. Specific performance envelopes we consistently strive to improve include: operating under low signal to background conditions; at higher and higher frame rates; and under less than ideal motion control scenarios. An adaptable, low cost, low footprint, standoff sensor architecture we have been maturing includes the use of conformal liquid crystal tunable filters (LCTFs). These Conformal Filters (CFs) are electro-optically tunable, multivariate HSI spectrometers that, when combined with Dual Polarization (DP) optics, produce optimized spectral passbands on demand, which can readily be reconfigured, to discriminate targets from complex backgrounds in real-time. With DARPA support, ChemImage Sensor Systems (CISS™) in collaboration with Research Triangle Institute (RTI) International are developing a novel, real-time, adaptable, compressive sensing short-wave infrared (SWIR) hyperspectral imaging technology called the Reconfigurable Conformal Imaging Sensor (RCIS) based on DP-CF technology. RCIS will address many shortcomings of current generation systems and offer improvements in operational agility and detection performance, while addressing sensor weight, form factor and cost needs. This paper discusses recent test and performance modeling results of a RCIS breadboard apparatus.

Image segmentation based upon topological operators: real-time implementation case study

NASA Astrophysics Data System (ADS)

Mahmoudi, R.; Akil, M.

2009-02-01

In miscellaneous applications of image treatment, thinning and crest restoring present a lot of interests. Recommended algorithms for these procedures are those able to act directly over grayscales images while preserving topology. But their strong consummation in term of time remains the major disadvantage in their choice. In this paper we present an efficient hardware implementation on RISC processor of two powerful algorithms of thinning and crest restoring developed by our team. Proposed implementation enhances execution time. A chain of segmentation applied to medical imaging will serve as a concrete example to illustrate the improvements brought thanks to the optimization techniques in both algorithm and architectural levels. The particular use of the SSE instruction set relative to the X86_32 processors (PIV 3.06 GHz) will allow a best performance for real time processing: a cadency of 33 images (512*512) per second is assured.

Managing Contention and Timing Constraints in a Real-Time Database System

DTIC Science & Technology

1995-01-01

In order to realize many of these goals, StarBase is constructed on top of RT-Mach, a real - time operating system developed at Carnegie Mellon...University [ll]. StarBase differs from previous RT-DBMS work [l, 2, 31 in that a) it relies on a real - time operating system which provides priority...CPU and resource scheduling pro- vided by tlhe underlying real - time operating system . Issues of data contention are dealt with by use of a priority

Telerobotic Surgery: An Intelligent Systems Approach to Mitigate the Adverse Effects of Communication Delay. Chapter 4

NASA Technical Reports Server (NTRS)

Cardullo, Frank M.; Lewis, Harold W., III; Panfilov, Peter B.

2007-01-01

An extremely innovative approach has been presented, which is to have the surgeon operate through a simulator running in real-time enhanced with an intelligent controller component to enhance the safety and efficiency of a remotely conducted operation. The use of a simulator enables the surgeon to operate in a virtual environment free from the impediments of telecommunication delay. The simulator functions as a predictor and periodically the simulator state is corrected with truth data. Three major research areas must be explored in order to ensure achieving the objectives. They are: simulator as predictor, image processing, and intelligent control. Each is equally necessary for success of the project and each of these involves a significant intelligent component in it. These are diverse, interdisciplinary areas of investigation, thereby requiring a highly coordinated effort by all the members of our team, to ensure an integrated system. The following is a brief discussion of those areas. Simulator as a predictor: The delays encountered in remote robotic surgery will be greater than any encountered in human-machine systems analysis, with the possible exception of remote operations in space. Therefore, novel compensation techniques will be developed. Included will be the development of the real-time simulator, which is at the heart of our approach. The simulator will present real-time, stereoscopic images and artificial haptic stimuli to the surgeon. Image processing: Because of the delay and the possibility of insufficient bandwidth a high level of novel image processing is necessary. This image processing will include several innovative aspects, including image interpretation, video to graphical conversion, texture extraction, geometric processing, image compression and image generation at the surgeon station. Intelligent control: Since the approach we propose is in a sense predictor based, albeit a very sophisticated predictor, a controller, which not only optimizes end effector trajectory but also avoids error, is essential. We propose to investigate two different approaches to the controller design. One approach employs an optimal controller based on modern control theory; the other one involves soft computing techniques, i.e. fuzzy logic, neural networks, genetic algorithms and hybrids of these.

Real time hardware implementation of power converters for grid integration of distributed generation and STATCOM systems

NASA Astrophysics Data System (ADS)

Jaithwa, Ishan

Deployment of smart grid technologies is accelerating. Smart grid enables bidirectional flows of energy and energy-related communications. The future electricity grid will look very different from today's power system. Large variable renewable energy sources will provide a greater portion of electricity, small DERs and energy storage systems will become more common, and utilities will operate many different kinds of energy efficiency. All of these changes will add complexity to the grid and require operators to be able to respond to fast dynamic changes to maintain system stability and security. This thesis investigates advanced control technology for grid integration of renewable energy sources and STATCOM systems by verifying them on real time hardware experiments using two different systems: d SPACE and OPAL RT. Three controls: conventional, direct vector control and the intelligent Neural network control were first simulated using Matlab to check the stability and safety of the system and were then implemented on real time hardware using the d SPACE and OPAL RT systems. The thesis then shows how dynamic-programming (DP) methods employed to train the neural networks are better than any other controllers where, an optimal control strategy is developed to ensure effective power delivery and to improve system stability. Through real time hardware implementation it is proved that the neural vector control approach produces the fastest response time, low overshoot, and, the best performance compared to the conventional standard vector control method and DCC vector control technique. Finally the entrepreneurial approach taken to drive the technologies from the lab to market via ORANGE ELECTRIC is discussed in brief.

Performance Evaluation of a Firm Real-Time DataBase System

DTIC Science & Technology

1995-01-01

after its deadline has passed. StarBase differs from previous real-time database work in that a) it relies on a real - time operating system which...StarBase, running on a real - time operating system kernel, RT-Mach. We discuss how performance was evaluated in StarBase using the StarBase workload

Control strategy optimization of HVAC plants

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

Facci, Andrea Luigi; Zanfardino, Antonella; Martini, Fabrizio

In this paper we present a methodology to optimize the operating conditions of heating, ventilation and air conditioning (HVAC) plants to achieve a higher energy efficiency in use. Semi-empiric numerical models of the plant components are used to predict their performances as a function of their set-point and the environmental and occupied space conditions. The optimization is performed through a graph-based algorithm that finds the set-points of the system components that minimize energy consumption and/or energy costs, while matching the user energy demands. The resulting model can be used with systems of almost any complexity, featuring both HVAC components andmore » energy systems, and is sufficiently fast to make it applicable to real-time setting.« less

Time-critical multirate scheduling using contemporary real-time operating system services

NASA Technical Reports Server (NTRS)

Eckhardt, D. E., Jr.

1983-01-01

Although real-time operating systems provide many of the task control services necessary to process time-critical applications (i.e., applications with fixed, invariant deadlines), it may still be necessary to provide a scheduling algorithm at a level above the operating system in order to coordinate a set of synchronized, time-critical tasks executing at different cyclic rates. The scheduling requirements for such applications and develops scheduling algorithms using services provided by contemporary real-time operating systems.

Stochastic Optimization for an Analytical Model of Saltwater Intrusion in Coastal Aquifers

PubMed Central

Stratis, Paris N.; Karatzas, George P.; Papadopoulou, Elena P.; Zakynthinaki, Maria S.; Saridakis, Yiannis G.

2016-01-01

The present study implements a stochastic optimization technique to optimally manage freshwater pumping from coastal aquifers. Our simulations utilize the well-known sharp interface model for saltwater intrusion in coastal aquifers together with its known analytical solution. The objective is to maximize the total volume of freshwater pumped by the wells from the aquifer while, at the same time, protecting the aquifer from saltwater intrusion. In the direction of dealing with this problem in real time, the ALOPEX stochastic optimization method is used, to optimize the pumping rates of the wells, coupled with a penalty-based strategy that keeps the saltwater front at a safe distance from the wells. Several numerical optimization results, that simulate a known real aquifer case, are presented. The results explore the computational performance of the chosen stochastic optimization method as well as its abilities to manage freshwater pumping in real aquifer environments. PMID:27689362

Transient Turbine Engine Modeling with Hardware-in-the-Loop Power Extraction (PREPRINT)

DTIC Science & Technology

2008-07-01

Furthermore, it must be compatible with a real - time operating system that is capable of running the simulation. For some models, especially those that use...problem of interfacing the engine/control model to a real - time operating system and associated lab hardware becomes a problem of interfacing these...model in real-time. This requires the use of a real - time operating system and a compatible I/O (input/output) board. Figure 1 illustrates the HIL

Initial clinical experience of real-time three-dimensional echocardiography in patients with ischemic and idiopathic dilated cardiomyopathy

NASA Technical Reports Server (NTRS)

Shiota, T.; McCarthy, P. M.; White, R. D.; Qin, J. X.; Greenberg, N. L.; Flamm, S. D.; Wong, J.; Thomas, J. D.

1999-01-01

The geometry of the left ventricle in patients with cardiomyopathy is often sub-optimal for 2-dimensional ultrasound when assessing left ventricular (LV) function and localized abnormalities such as a ventricular aneurysm. The aim of this study was to report the initial experience of real-time 3-D echocardiography for evaluating patients with cardiomyopathy. A total of 34 patients were evaluated with the real-time 3D method in the operating room (n = 15) and in the echocardiographic laboratory (n = 19). Thirteen of 28 patients with cardiomyopathy and 6 other subjects with normal LV function were evaluated by both real-time 3-D echocardiography and magnetic resonance imaging (MRI) for obtaining LV volumes and ejection fractions for comparison. There were close relations and agreements for LV volumes (r = 0.98, p <0.0001, mean difference = -15 +/- 81 ml) and ejection fractions (r = 0.97, p <0.0001, mean difference = 0.001 +/- 0.04) between the real-time 3D method and MRI when 3 cardiomyopathy cases with marked LV dilatation (LV end-diastolic volume >450 ml by MRI) were excluded. In these 3 patients, 3D echocardiography significantly underestimated the LV volumes due to difficulties with imaging the entire LV in a 60 degrees x 60 degrees pyramidal volume. The new real-time 3D echocardiography is feasible in patients with cardiomyopathy and may provide a faster and lower cost alternative to MRI for evaluating cardiac function in patients.

A High Performance Computer Architecture for Embedded And/Or Multi-Computer Applications

DTIC Science & Technology

1990-09-01

commercially available, real - time operating system . CHOICES and ARTS are real-time operating systems developed at the University of Illinois and CMU...respectively. Selection of a real - time operating system will be made in the next phase of the project. U BIBLIOGRAPHY U Wulf, Wm. A. The WM Computer

Real Time Phase Noise Meter Based on a Digital Signal Processor

NASA Technical Reports Server (NTRS)

Angrisani, Leopoldo; D'Arco, Mauro; Greenhall, Charles A.; Schiano Lo Morille, Rosario

2006-01-01

A digital signal-processing meter for phase noise measurement on sinusoidal signals is dealt with. It enlists a special hardware architecture, made up of a core digital signal processor connected to a data acquisition board, and takes advantage of a quadrature demodulation-based measurement scheme, already proposed by the authors. Thanks to an efficient measurement process and an optimized implementation of its fundamental stages, the proposed meter succeeds in exploiting all hardware resources in such an effective way as to gain high performance and real-time operation. For input frequencies up to some hundreds of kilohertz, the meter is capable both of updating phase noise power spectrum while seamlessly capturing the analyzed signal into its memory, and granting as good frequency resolution as few units of hertz.

Addressing the minimum fleet problem in on-demand urban mobility.

PubMed

Vazifeh, M M; Santi, P; Resta, G; Strogatz, S H; Ratti, C

2018-05-01

Information and communication technologies have opened the way to new solutions for urban mobility that provide better ways to match individuals with on-demand vehicles. However, a fundamental unsolved problem is how best to size and operate a fleet of vehicles, given a certain demand for personal mobility. Previous studies 1-5 either do not provide a scalable solution or require changes in human attitudes towards mobility. Here we provide a network-based solution to the following 'minimum fleet problem', given a collection of trips (specified by origin, destination and start time), of how to determine the minimum number of vehicles needed to serve all the trips without incurring any delay to the passengers. By introducing the notion of a 'vehicle-sharing network', we present an optimal computationally efficient solution to the problem, as well as a nearly optimal solution amenable to real-time implementation. We test both solutions on a dataset of 150 million taxi trips taken in the city of New York over one year 6 . The real-time implementation of the method with near-optimal service levels allows a 30 per cent reduction in fleet size compared to current taxi operation. Although constraints on driver availability and the existence of abnormal trip demands may lead to a relatively larger optimal value for the fleet size than that predicted here, the fleet size remains robust for a wide range of variations in historical trip demand. These predicted reductions in fleet size follow directly from a reorganization of taxi dispatching that could be implemented with a simple urban app; they do not assume ride sharing 7-9 , nor require changes to regulations, business models, or human attitudes towards mobility to become effective. Our results could become even more relevant in the years ahead as fleets of networked, self-driving cars become commonplace 10-14 .

Beyond Control Centers

NASA Technical Reports Server (NTRS)

Trimble, Jay

2017-01-01

For NASA's Resource Prospector (RP) Lunar Rover Mission, we are moving away from a control center concept, to a fully distributed operation utilizing control nodes, with decision support from anywhere via mobile devices. This operations concept will utilize distributed information systems, notifications, mobile data access, and optimized mobile data display for off-console decision support. We see this concept of operations as a step in the evolution of mission operations from a central control center concept to a mission operations anywhere concept. The RP example is part of a trend, in which mission expertise for design, development and operations is distributed across countries and across the globe. Future spacecraft operations will be most cost efficient and flexible by following this distributed expertise, enabling operations from anywhere. For the RP mission we arrived at the decision to utilize a fully distributed operations team, where everyone operates from their home institution, based on evaluating the following factors: the requirement for physical proximity for near-real time command and control decisions; the cost of distributed control nodes vs. a centralized control center; the impact on training and mission preparation of flying the team to a central location. Physical proximity for operational decisions is seldom required, though certain categories of decisions, such as launch abort, or close coordination for mission or safety-critical near-real-time command and control decisions may benefit from co-location. The cost of facilities and operational infrastructure has not been found to be a driving factor for location in our studies. Mission training and preparation benefit from having all operators train and operate from home institutions.

A Study on Real-Time Scheduling Methods in Holonic Manufacturing Systems

NASA Astrophysics Data System (ADS)

Iwamura, Koji; Taimizu, Yoshitaka; Sugimura, Nobuhiro

Recently, new architectures of manufacturing systems have been proposed to realize flexible control structures of the manufacturing systems, which can cope with the dynamic changes in the volume and the variety of the products and also the unforeseen disruptions, such as failures of manufacturing resources and interruptions by high priority jobs. They are so called as the autonomous distributed manufacturing system, the biological manufacturing system and the holonic manufacturing system. Rule-based scheduling methods were proposed and applied to the real-time production scheduling problems of the HMS (Holonic Manufacturing System) in the previous report. However, there are still remaining problems from the viewpoint of the optimization of the whole production schedules. New procedures are proposed, in the present paper, to select the production schedules, aimed at generating effective production schedules in real-time. The proposed methods enable the individual holons to select suitable machining operations to be carried out in the next time period. Coordination process among the holons is also proposed to carry out the coordination based on the effectiveness values of the individual holons.

Optimal SSN Tasking to Enhance Real-time Space Situational Awareness

NASA Astrophysics Data System (ADS)

Ferreira, J., III; Hussein, I.; Gerber, J.; Sivilli, R.

2016-09-01

Space Situational Awareness (SSA) is currently constrained by an overwhelming number of resident space objects (RSOs) that need to be tracked and the amount of data these observations produce. The Joint Centralized Autonomous Tasking System (JCATS) is an autonomous, net-centric tool that approaches these SSA concerns from an agile, information-based stance. Finite set statistics and stochastic optimization are used to maintain an RSO catalog and develop sensor tasking schedules based on operator configured, state information-gain metrics to determine observation priorities. This improves the efficiency of sensors to target objects as awareness changes and new information is needed, not at predefined frequencies solely. A net-centric, service-oriented architecture (SOA) allows for JCATS integration into existing SSA systems. Testing has shown operationally-relevant performance improvements and scalability across multiple types of scenarios and against current sensor tasking tools.

Real-time estimation of BDS/GPS high-rate satellite clock offsets using sequential least squares

NASA Astrophysics Data System (ADS)

Fu, Wenju; Yang, Yuanxi; Zhang, Qin; Huang, Guanwen

2018-07-01

The real-time precise satellite clock product is one of key prerequisites for real-time Precise Point Positioning (PPP). The accuracy of the 24-hour predicted satellite clock product with 15 min sampling interval and an update of 6 h provided by the International GNSS Service (IGS) is only 3 ns, which could not meet the needs of all real-time PPP applications. The real-time estimation of high-rate satellite clock offsets is an efficient method for improving the accuracy. In this paper, the sequential least squares method to estimate real-time satellite clock offsets with high sample rate is proposed to improve the computational speed by applying an optimized sparse matrix operation to compute the normal equation and using special measures to take full advantage of modern computer power. The method is first applied to BeiDou Navigation Satellite System (BDS) and provides real-time estimation with a 1 s sample rate. The results show that the amount of time taken to process a single epoch is about 0.12 s using 28 stations. The Standard Deviation (STD) and Root Mean Square (RMS) of the real-time estimated BDS satellite clock offsets are 0.17 ns and 0.44 ns respectively when compared to German Research Center for Geosciences (GFZ) final clock products. The positioning performance of the real-time estimated satellite clock offsets is evaluated. The RMSs of the real-time BDS kinematic PPP in east, north, and vertical components are 7.6 cm, 6.4 cm and 19.6 cm respectively. The method is also applied to Global Positioning System (GPS) with a 10 s sample rate and the computational time of most epochs is less than 1.5 s with 75 stations. The STD and RMS of the real-time estimated GPS satellite clocks are 0.11 ns and 0.27 ns, respectively. The accuracies of 5.6 cm, 2.6 cm and 7.9 cm in east, north, and vertical components are achieved for the real-time GPS kinematic PPP.

Adaptive model-based control systems and methods for controlling a gas turbine

NASA Technical Reports Server (NTRS)

Brunell, Brent Jerome (Inventor); Mathews, Jr., Harry Kirk (Inventor); Kumar, Aditya (Inventor)

2004-01-01

Adaptive model-based control systems and methods are described so that performance and/or operability of a gas turbine in an aircraft engine, power plant, marine propulsion, or industrial application can be optimized under normal, deteriorated, faulted, failed and/or damaged operation. First, a model of each relevant system or component is created, and the model is adapted to the engine. Then, if/when deterioration, a fault, a failure or some kind of damage to an engine component or system is detected, that information is input to the model-based control as changes to the model, constraints, objective function, or other control parameters. With all the information about the engine condition, and state and directives on the control goals in terms of an objective function and constraints, the control then solves an optimization so the optimal control action can be determined and taken. This model and control may be updated in real-time to account for engine-to-engine variation, deterioration, damage, faults and/or failures using optimal corrective control action command(s).

Internal combustion engine control for series hybrid electric vehicles by parallel and distributed genetic programming/multiobjective genetic algorithms

NASA Astrophysics Data System (ADS)

Gladwin, D.; Stewart, P.; Stewart, J.

2011-02-01

This article addresses the problem of maintaining a stable rectified DC output from the three-phase AC generator in a series-hybrid vehicle powertrain. The series-hybrid prime power source generally comprises an internal combustion (IC) engine driving a three-phase permanent magnet generator whose output is rectified to DC. A recent development has been to control the engine/generator combination by an electronically actuated throttle. This system can be represented as a nonlinear system with significant time delay. Previously, voltage control of the generator output has been achieved by model predictive methods such as the Smith Predictor. These methods rely on the incorporation of an accurate system model and time delay into the control algorithm, with a consequent increase in computational complexity in the real-time controller, and as a necessity relies to some extent on the accuracy of the models. Two complementary performance objectives exist for the control system. Firstly, to maintain the IC engine at its optimal operating point, and secondly, to supply a stable DC supply to the traction drive inverters. Achievement of these goals minimises the transient energy storage requirements at the DC link, with a consequent reduction in both weight and cost. These objectives imply constant velocity operation of the IC engine under external load disturbances and changes in both operating conditions and vehicle speed set-points. In order to achieve these objectives, and reduce the complexity of implementation, in this article a controller is designed by the use of Genetic Programming methods in the Simulink modelling environment, with the aim of obtaining a relatively simple controller for the time-delay system which does not rely on the implementation of real time system models or time delay approximations in the controller. A methodology is presented to utilise the miriad of existing control blocks in the Simulink libraries to automatically evolve optimal control structures.

A statistical-based scheduling algorithm in automated data path synthesis

NASA Technical Reports Server (NTRS)

Jeon, Byung Wook; Lursinsap, Chidchanok

1992-01-01

In this paper, we propose a new heuristic scheduling algorithm based on the statistical analysis of the cumulative frequency distribution of operations among control steps. It has a tendency of escaping from local minima and therefore reaching a globally optimal solution. The presented algorithm considers the real world constraints such as chained operations, multicycle operations, and pipelined data paths. The result of the experiment shows that it gives optimal solutions, even though it is greedy in nature.

Optimal decision making modeling for copper-matte Peirce-Smith converting process by means of data mining

NASA Astrophysics Data System (ADS)

Song, Yanpo; Peng, Xiaoqi; Tang, Ying; Hu, Zhikun

2013-07-01

To improve the operation level of copper converter, the approach to optimal decision making modeling for coppermatte converting process based on data mining is studied: in view of the characteristics of the process data, such as containing noise, small sample size and so on, a new robust improved ANN (artificial neural network) modeling method is proposed; taking into account the application purpose of decision making model, three new evaluation indexes named support, confidence and relative confidence are proposed; using real production data and the methods mentioned above, optimal decision making model for blowing time of S1 period (the 1st slag producing period) are developed. Simulation results show that this model can significantly improve the converting quality of S1 period, increase the optimal probability from about 70% to about 85%.

A controllable sensor management algorithm capable of learning

NASA Astrophysics Data System (ADS)

Osadciw, Lisa A.; Veeramacheneni, Kalyan K.

2005-03-01

Sensor management technology progress is challenged by the geographic space it spans, the heterogeneity of the sensors, and the real-time timeframes within which plans controlling the assets are executed. This paper presents a new sensor management paradigm and demonstrates its application in a sensor management algorithm designed for a biometric access control system. This approach consists of an artificial intelligence (AI) algorithm focused on uncertainty measures, which makes the high level decisions to reduce uncertainties and interfaces with the user, integrated cohesively with a bottom up evolutionary algorithm, which optimizes the sensor network"s operation as determined by the AI algorithm. The sensor management algorithm presented is composed of a Bayesian network, the AI algorithm component, and a swarm optimization algorithm, the evolutionary algorithm. Thus, the algorithm can change its own performance goals in real-time and will modify its own decisions based on observed measures within the sensor network. The definition of the measures as well as the Bayesian network determine the robustness of the algorithm and its utility in reacting dynamically to changes in the global system.

Global Simulation of Aviation Operations

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Sheth, Kapil; Ng, Hok Kwan; Morando, Alex; Li, Jinhua

2016-01-01

The simulation and analysis of global air traffic is limited due to a lack of simulation tools and the difficulty in accessing data sources. This paper provides a global simulation of aviation operations combining flight plans and real air traffic data with historical commercial city-pair aircraft type and schedule data and global atmospheric data. The resulting capability extends the simulation and optimization functions of NASA's Future Air Traffic Management Concept Evaluation Tool (FACET) to global scale. This new capability is used to present results on the evolution of global air traffic patterns from a concentration of traffic inside US, Europe and across the Atlantic Ocean to a more diverse traffic pattern across the globe with accelerated growth in Asia, Australia, Africa and South America. The simulation analyzes seasonal variation in the long-haul wind-optimal traffic patterns in six major regions of the world and provides potential time-savings of wind-optimal routes compared with either great circle routes or current flight-plans if available.

Intelligent sensor in control systems for objects with changing thermophysical properties

NASA Astrophysics Data System (ADS)

Belousov, O. A.; Muromtsev, D. Yu; Belyaev, M. P.

2018-04-01

The control of heat devices in a wide temperature range given thermophysical properties of an object is a topical issue. Optimal control systems of electric furnaces have to meet strict requirements in terms of accuracy of production procedures and efficiency of energy consumption. The fulfillment of these requirements is possible only if the dynamics model describing adequately the processes occurring in the furnaces is used to calculate the optimal control actions. One of the types of electric furnaces is the electric chamber furnace intended for heat treatment of various materials at temperatures from thousands of degrees Celsius and above. To solve the above-mentioned problem and to determine its place in the system of energy-efficient control of dynamic modes in the electric furnace, we propose the concept of an intelligent sensor and a method of synthesizing variables on sets of functioning states. The use of synthesis algorithms for optimal control in real time ensures the required accuracy when operating under different conditions and operating modes of the electric chamber furnace.

A quantum network of clocks

NASA Astrophysics Data System (ADS)

Kómár, P.; Kessler, E. M.; Bishof, M.; Jiang, L.; Sørensen, A. S.; Ye, J.; Lukin, M. D.

2014-08-01

The development of precise atomic clocks plays an increasingly important role in modern society. Shared timing information constitutes a key resource for navigation with a direct correspondence between timing accuracy and precision in applications such as the Global Positioning System. By combining precision metrology and quantum networks, we propose a quantum, cooperative protocol for operating a network of geographically remote optical atomic clocks. Using nonlocal entangled states, we demonstrate an optimal utilization of global resources, and show that such a network can be operated near the fundamental precision limit set by quantum theory. Furthermore, the internal structure of the network, combined with quantum communication techniques, guarantees security both from internal and external threats. Realization of such a global quantum network of clocks may allow construction of a real-time single international time scale (world clock) with unprecedented stability and accuracy.

'It is Time to Prepare the Next patient' Real-Time Prediction of Procedure Duration in Laparoscopic Cholecystectomies.

PubMed

Guédon, Annetje C P; Paalvast, M; Meeuwsen, F C; Tax, D M J; van Dijke, A P; Wauben, L S G L; van der Elst, M; Dankelman, J; van den Dobbelsteen, J J

2016-12-01

Operating Room (OR) scheduling is crucial to allow efficient use of ORs. Currently, the predicted durations of surgical procedures are unreliable and the OR schedulers have to follow the progress of the procedures in order to update the daily planning accordingly. The OR schedulers often acquire the needed information through verbal communication with the OR staff, which causes undesired interruptions of the surgical process. The aim of this study was to develop a system that predicts in real-time the remaining procedure duration and to test this prediction system for reliability and usability in an OR. The prediction system was based on the activation pattern of one single piece of equipment, the electrosurgical device. The prediction system was tested during 21 laparoscopic cholecystectomies, in which the activation of the electrosurgical device was recorded and processed in real-time using pattern recognition methods. The remaining surgical procedure duration was estimated and the optimal timing to prepare the next patient for surgery was communicated to the OR staff. The mean absolute error was smaller for the prediction system (14 min) than for the OR staff (19 min). The OR staff doubted whether the prediction system could take all relevant factors into account but were positive about its potential to shorten waiting times for patients. The prediction system is a promising tool to automatically and objectively predict the remaining procedure duration, and thereby achieve optimal OR scheduling and streamline the patient flow from the nursing department to the OR.

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

NASA Technical Reports Server (NTRS)

Schaefer, Jacob; Brown, Nelson

2013-01-01

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

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

NASA Technical Reports Server (NTRS)

Schaefer, Jacob; Brown, Nelson A.

2013-01-01

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

a Real-Time GIS Platform for High Sour Gas Leakage Simulation, Evaluation and Visualization

NASA Astrophysics Data System (ADS)

Li, M.; Liu, H.; Yang, C.

2015-07-01

The development of high-sulfur gas fields, also known as sour gas field, is faced with a series of safety control and emergency management problems. The GIS-based emergency response system is placed high expectations under the consideration of high pressure, high content, complex terrain and highly density population in Sichuan Basin, southwest China. The most researches on high hydrogen sulphide gas dispersion simulation and evaluation are used for environmental impact assessment (EIA) or emergency preparedness planning. This paper introduces a real-time GIS platform for high-sulfur gas emergency response. Combining with real-time data from the leak detection systems and the meteorological monitoring stations, GIS platform provides the functions of simulating, evaluating and displaying of the different spatial-temporal toxic gas distribution patterns and evaluation results. This paper firstly proposes the architecture of Emergency Response/Management System, secondly explains EPA's Gaussian dispersion model CALPUFF simulation workflow under high complex terrain and real-time data, thirdly explains the emergency workflow and spatial analysis functions of computing the accident influencing areas, population and the optimal evacuation routes. Finally, a well blow scenarios is used for verify the system. The study shows that GIS platform which integrates the real-time data and CALPUFF models will be one of the essential operational platforms for high-sulfur gas fields emergency management.

A short-term operating room surgery scheduling problem integrating multiple nurses roster constraints.

PubMed

Xiang, Wei; Yin, Jiao; Lim, Gino

2015-02-01

Operating room (OR) surgery scheduling determines the individual surgery's operation start time and assigns the required resources to each surgery over a schedule period, considering several constraints related to a complete surgery flow and the multiple resources involved. This task plays a decisive role in providing timely treatments for the patients while balancing hospital resource utilization. The originality of the present study is to integrate the surgery scheduling problem with real-life nurse roster constraints such as their role, specialty, qualification and availability. This article proposes a mathematical model and an ant colony optimization (ACO) approach to efficiently solve such surgery scheduling problems. A modified ACO algorithm with a two-level ant graph model is developed to solve such combinatorial optimization problems because of its computational complexity. The outer ant graph represents surgeries, while the inner graph is a dynamic resource graph. Three types of pheromones, i.e. sequence-related, surgery-related, and resource-related pheromone, fitting for a two-level model are defined. The iteration-best and feasible update strategy and local pheromone update rules are adopted to emphasize the information related to the good solution in makespan, and the balanced utilization of resources as well. The performance of the proposed ACO algorithm is then evaluated using the test cases from (1) the published literature data with complete nurse roster constraints, and 2) the real data collected from a hospital in China. The scheduling results using the proposed ACO approach are compared with the test case from both the literature and the real life hospital scheduling. Comparison results with the literature shows that the proposed ACO approach has (1) an 1.5-h reduction in end time; (2) a reduction in variation of resources' working time, i.e. 25% for ORs, 50% for nurses in shift 1 and 86% for nurses in shift 2; (3) an 0.25h reduction in individual maximum overtime (OT); and (4) an 42% reduction in the total OT of nurses. Comparison results with the real 10-workday hospital scheduling further show the advantage of the ACO in several measurements. Instead of assigning all surgeries by a surgeon to only one OR and the same nurses by traditional manual approach in hospital, ACO realizes a more balanced surgery arrangement by assigning the surgeries to different ORs and nurses. It eventually leads to shortening the end time within the confidential interval of [7.4%, 24.6%] with 95% confidence level. The ACO approach proposed in this paper efficiently solves the surgery scheduling problem with daily nurse roster while providing a shortened end time and relatively balanced resource allocations. It also supports the advantage of integrating the surgery scheduling with the nurse scheduling and the efficiency of systematic optimization considering a complete three-stage surgery flow and resources involved. Copyright © 2014 Elsevier B.V. All rights reserved.

SSALTO/DUACS: Faster data delivery for operational oceanography and GMES

NASA Astrophysics Data System (ADS)

Dorandeu, J.; Dibarboure, G.; Larnicol, G.; Picot, N.

2008-12-01

This paper describes the DUACS multi-mission system, and its most relevant improvements and changes. Initiated 10 years ago with an EC project, DUACS is now a part of the CNES multi-mission ground segment SSALTO, and the backbone of the Sea Level Thematic Assembly Centre (SL-TAC) of the GMES Marine Core Service. Near Real Time (NRT): Daily Operational Products DUACS-NRT provides GODAE, climate forecasting centres, the MyOcean EU FP7 project, and real time oceanographic research (e.g.: in-situ campaigns) with directly useable, high quality near real time altimeter data. Regional products (European Shelves, Mediterranean Sea, and Black Sea) are delivered to operational projects. Commercial applications are also developed for the fishery and offshore drilling industries. All DUACS near real time products are generated and distributed on a daily basis to reduce the NRT delay, and to smooth the operational procedures of NRT users. DUACS features a systematic quality control of the input data, the system itself, and its products with detailed reports put online twice per week. The system also carries out on-the-fly editing and reprocessing of erroneous datasets, as well as a long term monitoring of NRT data it has used, to quickly detect anomalies, drifts and discontinuities in incoming altimeter data. Delayed Time (DT): A consistent data set from built upon all altimeters The second generation of DUACS-DT products is composed of global data sets of along track and gridded Sea Level Anomaly, Absolute Dynamic Topography, and geostrophic currents, but also of regional-specific products (higher resolution, optimized parameters). DUACS reprocessed all past altimeter data: Jason-1, T/P, ENVISAT, GFO, ERS1/2 and GEOSAT. These delayed time products are regularly updated when new Level2 data are released and fully validated. The system operationally integrates the state-of-the-art corrections, models and references recommended by the altimeter community, as well as the best Cal/Val and cross-calibration and merging algorithms. Ongoing Improvements to secure multi-mission products Adding Jason-2 to the system is arguably the most important improvement on DUACS in 2008. Additionally, the effort to improve the quality of DUACS combined data and the robustness of the NRT system are ongoing with the release of Key Performance Indicators on the system, and Ocean Indicators for a near real time ocean monitoring. Last year, preliminary studies were carried out to merge into the high-accuracy NRT system, innovative information of lower quality altimeter data flows such as OSDR / FDGDR / OGDR (real time data delivered in a few hours as opposed to 2 or 3 days for classical NRT data), as well as CryoSat data. These offline studies and experimental NRT productions will be integrated to the system in order to guarantee sustainability and quality in the operational DUACS framework.

Transitioning to Integrated Modular Avionics with a Mission Management System

DTIC Science & Technology

2000-10-01

software structure, which is based on the use of a of interchangeable processing modules of a limited COTS Real - Time Operating System . number of...open standardised interfaces system hardware or the Real - Time Operating System directly supports the use of COTS components, which implementation, to...System RTOS Real - Time Operating System SMBP System Management Blueprint Interface SMOS System Management to Operating System Interface Figure 2: The ASAAC

Research and application of embedded real-time operating system

NASA Astrophysics Data System (ADS)

Zhang, Bo

2013-03-01

In this paper, based on the analysis of existing embedded real-time operating system, the architecture of an operating system is designed and implemented. The experimental results show that the design fully complies with the requirements of embedded real-time operating system, can achieve the purposes of reducing the complexity of embedded software design and improving the maintainability, reliability, flexibility. Therefore, this design program has high practical value.

Computer program compatible with a laser nephelometer

NASA Technical Reports Server (NTRS)

Paroskie, R. M.; Blau, H. H., Jr.; Blinn, J. C., III

1975-01-01

The laser nephelometer data system was updated to provide magnetic tape recording of data, and real time or near real time processing of data to provide particle size distribution and liquid water content. Digital circuits were provided to interface the laser nephelometer to a Data General Nova 1200 minicomputer. Communications are via a teletypewriter. A dual Linc Magnetic Tape System is used for program storage and data recording. Operational programs utilize the Data General Real-Time Operating System (RTOS) and the ERT AIRMAP Real-Time Operating System (ARTS). The programs provide for acquiring data from the laser nephelometer, acquiring data from auxiliary sources, keeping time, performing real time calculations, recording data and communicating with the teletypewriter.

Energy management and cooperation in microgrids

NASA Astrophysics Data System (ADS)

Rahbar, Katayoun

Microgrids are key components of future smart power grids, which integrate distributed renewable energy generators to efficiently serve the load demand locally. However, random and intermittent characteristics of renewable energy generations may hinder the reliable operation of microgrids. This thesis is thus devoted to investigating new strategies for microgrids to optimally manage their energy consumption, energy storage system (ESS) and cooperation in real time to achieve the reliable and cost-effective operation. This thesis starts with a single microgrid system. The optimal energy scheduling and ESS management policy is derived to minimize the energy cost of the microgrid resulting from drawing conventional energy from the main grid under both the off-line and online setups, where the renewable energy generation/load demand are assumed to be non-causally known and causally known at the microgrid, respectively. The proposed online algorithm is designed based on the optimal off-line solution and works under arbitrary (even unknown) realizations of future renewable energy generation/load demand. Therefore, it is more practically applicable as compared to solutions based on conventional techniques such as dynamic programming and stochastic programming that require the prior knowledge of renewable energy generation and load demand realizations/distributions. Next, for a group of microgrids that cooperate in energy management, we study efficient methods for sharing energy among them for both fully and partially cooperative scenarios, where microgrids are of common interests and self-interested, respectively. For the fully cooperative energy management, the off-line optimization problem is first formulated and optimally solved, where a distributed algorithm is proposed to minimize the total (sum) energy cost of microgrids. Inspired by the results obtained from the off-line optimization, efficient online algorithms are proposed for the real-time energy management, which are of low complexity and work given arbitrary realizations of renewable energy generation/load demand. On the other hand, for self-interested microgrids, the partially cooperative energy management is formulated and a distributed algorithm is proposed to optimize the energy cooperation such that energy costs of individual microgrids reduce simultaneously over the case without energy cooperation while limited information is shared among the microgrids and the central controller.

MPI Runtime Error Detection with MUST: Advances in Deadlock Detection

DOE PAGES

Hilbrich, Tobias; Protze, Joachim; Schulz, Martin; ...

2013-01-01

The widely used Message Passing Interface (MPI) is complex and rich. As a result, application developers require automated tools to avoid and to detect MPI programming errors. We present the Marmot Umpire Scalable Tool (MUST) that detects such errors with significantly increased scalability. We present improvements to our graph-based deadlock detection approach for MPI, which cover future MPI extensions. Our enhancements also check complex MPI constructs that no previous graph-based detection approach handled correctly. Finally, we present optimizations for the processing of MPI operations that reduce runtime deadlock detection overheads. Existing approaches often require ( p ) analysis time permore » MPI operation, for p processes. We empirically observe that our improvements lead to sub-linear or better analysis time per operation for a wide range of real world applications.« less

Optimizing Disaster Relief: Real-Time Operational and Tactical Decision Support

DTIC Science & Technology

1993-01-01

efficiencies in completing the tAsks. Allocations recognize task priorities and the logistica l effects of geographic prox- imity, In addition...as if they ar~ collocated. Arcs connect loc-•I J>airs of zones to represent feasible dTrect point-to-point transportation and bear cost> ror...data to thl.’ de >~red level of aggregation. We have tested ARES manuall)’ ;mtl by replacins tbc deci~ion maker wrlh the decision simulator which

Neuroadaptive technology enables implicit cursor control based on medial prefrontal cortex activity.

PubMed

Zander, Thorsten O; Krol, Laurens R; Birbaumer, Niels P; Gramann, Klaus

2016-12-27

The effectiveness of today's human-machine interaction is limited by a communication bottleneck as operators are required to translate high-level concepts into a machine-mandated sequence of instructions. In contrast, we demonstrate effective, goal-oriented control of a computer system without any form of explicit communication from the human operator. Instead, the system generated the necessary input itself, based on real-time analysis of brain activity. Specific brain responses were evoked by violating the operators' expectations to varying degrees. The evoked brain activity demonstrated detectable differences reflecting congruency with or deviations from the operators' expectations. Real-time analysis of this activity was used to build a user model of those expectations, thus representing the optimal (expected) state as perceived by the operator. Based on this model, which was continuously updated, the computer automatically adapted itself to the expectations of its operator. Further analyses showed this evoked activity to originate from the medial prefrontal cortex and to exhibit a linear correspondence to the degree of expectation violation. These findings extend our understanding of human predictive coding and provide evidence that the information used to generate the user model is task-specific and reflects goal congruency. This paper demonstrates a form of interaction without any explicit input by the operator, enabling computer systems to become neuroadaptive, that is, to automatically adapt to specific aspects of their operator's mindset. Neuroadaptive technology significantly widens the communication bottleneck and has the potential to fundamentally change the way we interact with technology.

Simultaneous and accurate real-time monitoring of glucose and ethanol in alcoholic drinks, must, and biomass by a dual-amperometric biosensor.

PubMed

Mentana, Annalisa; Palermo, Carmen; Nardiello, Donatella; Quinto, Maurizio; Centonze, Diego

2013-01-09

In this work the optimization and application of a dual-amperometric biosensor for simultaneous monitoring of glucose and ethanol content, as quality markers in drinks and alcoholic fermentation media, are described. The biosensor is based on glucose oxidase (GOD) and alcohol oxidase (AOD) immobilized by co-cross-linking with bovine serum albumin (BSA) and glutaraldehyde (GLU) both onto a dual gold electrode, modified with a permselective overoxidized polypyrrole film (PPYox). Response, rejection of interferents, and stability of the dual biosensor were optimized in terms of PPYox thickness, BSA, and enzyme loading. The biosensor was integrated in a flow injection system coupled with an at-line microdialysis fiber as a sampling tool. Flow rates inside and outside the fiber were optimized in terms of linear responses (0.01-1 and 0.01-1.5 M) and sensitivities (27.6 ± 0.4 and 31.0 ± 0.6 μA·M(-1)·cm(-2)) for glucose and ethanol. Excellent anti-interference characteristics, the total absence of "cross-talk", and good response stability under operational conditions allowed application of the dual biosensor in accurate real-time monitoring (at least 15 samples/h) of alcoholic drinks, white grape must, and woody biomass.

Design of an FPGA-Based Algorithm for Real-Time Solutions of Statistics-Based Positioning

PubMed Central

DeWitt, Don; Johnson-Williams, Nathan G.; Miyaoka, Robert S.; Li, Xiaoli; Lockhart, Cate; Lewellen, Tom K.; Hauck, Scott

2010-01-01

We report on the implementation of an algorithm and hardware platform to allow real-time processing of the statistics-based positioning (SBP) method for continuous miniature crystal element (cMiCE) detectors. The SBP method allows an intrinsic spatial resolution of ~1.6 mm FWHM to be achieved using our cMiCE design. Previous SBP solutions have required a postprocessing procedure due to the computation and memory intensive nature of SBP. This new implementation takes advantage of a combination of algebraic simplifications, conversion to fixed-point math, and a hierarchal search technique to greatly accelerate the algorithm. For the presented seven stage, 127 × 127 bin LUT implementation, these algorithm improvements result in a reduction from >7 × 106 floating-point operations per event for an exhaustive search to < 5 × 103 integer operations per event. Simulations show nearly identical FWHM positioning resolution for this accelerated SBP solution, and positioning differences of <0.1 mm from the exhaustive search solution. A pipelined field programmable gate array (FPGA) implementation of this optimized algorithm is able to process events in excess of 250 K events per second, which is greater than the maximum expected coincidence rate for an individual detector. In contrast with all detectors being processed at a centralized host, as in the current system, a separate FPGA is available at each detector, thus dividing the computational load. These methods allow SBP results to be calculated in real-time and to be presented to the image generation components in real-time. A hardware implementation has been developed using a commercially available prototype board. PMID:21197135

Research on Optimization of GLCM Parameter in Cell Classification

NASA Astrophysics Data System (ADS)

Zhang, Xi-Kun; Hou, Jie; Hu, Xin-Hua

2016-05-01

Real-time classification of biological cells according to their 3D morphology is highly desired in a flow cytometer setting. Gray level co-occurrence matrix (GLCM) algorithm has been developed to extract feature parameters from measured diffraction images ,which are too complicated to coordinate with the real-time system for a large amount of calculation. An optimization of GLCM algorithm is provided based on correlation analysis of GLCM parameters. The results of GLCM analysis and subsequent classification demonstrate optimized method can lower the time complexity significantly without loss of classification accuracy.

Advanced Plasma Shape Control to Enable High-Performance Divertor Operation on NSTX-U

NASA Astrophysics Data System (ADS)

Vail, Patrick; Kolemen, Egemen; Boyer, Mark; Welander, Anders

2017-10-01

This work presents the development of an advanced framework for control of the global plasma shape and its application to a variety of shape control challenges on NSTX-U. Operations in high-performance plasma scenarios will require highly-accurate and robust control of the plasma poloidal shape to accomplish such tasks as obtaining the strong-shaping required for the avoidance of MHD instabilities and mitigating heat flux through regulation of the divertor magnetic geometry. The new control system employs a high-fidelity model of the toroidal current dynamics in NSTX-U poloidal field coils and conducting structures as well as a first-principles driven calculation of the axisymmetric plasma response. The model-based nature of the control system enables real-time optimization of controller parameters in response to time-varying plasma conditions and control objectives. The new control scheme is shown to enable stable and on-demand plasma operations in complicated magnetic geometries such as the snowflake divertor. A recently-developed code that simulates the nonlinear evolution of the plasma equilibrium is used to demonstrate the capabilities of the designed shape controllers. Plans for future real-time implementations on NSTX-U and elsewhere are also presented. Supported by the US DOE under DE-AC02-09CH11466.

Automatic control of electric thermal storage (heat) under real-time pricing. Final report

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

Daryanian, B.; Tabors, R.D.; Bohn, R.E.

1995-01-01

Real-time pricing (RTP) can be used by electric utilities as a control signal for responsive demand-side management (DSM) programs. Electric thermal storage (ETS) systems in buildings provide the inherent flexibility needed to take advantage of variations in prices. Under RTP, optimal performance for ETS operations is achieved under market conditions where reductions in customers` costs coincide with the lowering of the cost of service for electric utilities. The RTP signal conveys the time-varying actual marginal cost of the electric service to customers. The RTP rate is a combination of various cost components, including marginal generation fuel and maintenance costs, marginalmore » costs of transmission and distribution losses, and marginal quality of supply and transmission costs. This report describes the results of an experiment in automatic control of heat storage systems under RTP during the winter seasons of 1989--90 and 1990--91.« less

A robust and non-obtrusive automatic event tracking system for operating room management to improve patient care.

PubMed

Huang, Albert Y; Joerger, Guillaume; Salmon, Remi; Dunkin, Brian; Sherman, Vadim; Bass, Barbara L; Garbey, Marc

2016-08-01

Optimization of OR management is a complex problem as each OR has different procedures throughout the day inevitably resulting in scheduling delays, variations in time durations and overall suboptimal performance. There exists a need for a system that automatically tracks procedural progress in real time in the OR. This would allow for efficient monitoring of operating room states and target sources of inefficiency and points of improvement. We placed three wireless sensors (floor-mounted pressure sensor, ventilator-mounted bellows motion sensor and ambient light detector, and a general room motion detector) in two ORs at our institution and tracked cases 24 h a day for over 4 months. We collected data on 238 total cases (107 laparoscopic cases). A total of 176 turnover times were also captured, and we found that the average turnover time between cases was 35 min while the institutional goal was 30 min. Deeper examination showed that 38 % of laparoscopic cases had some aspect of suboptimal activity with the time between extubation and patient exiting the OR being the biggest contributor (16 %). Our automated system allows for robust, wireless real-time OR monitoring as well as data collection and retrospective data analyses. We plan to continue expanding our system and to project the data in real time for all OR personnel to see. At the same time, we plan on adding key pieces of technology such as RFID and other radio-frequency systems to track patients and physicians to further increase efficiency and patient safety.

A Novel Early Warning System Based on a Sediment Microbial Fuel Cell for In Situ and Real Time Hexavalent Chromium Detection in Industrial Wastewater.

PubMed

Zhao, Shuai; Liu, Pu; Niu, Yongyan; Chen, Zhengjun; Khan, Aman; Zhang, Pengyun; Li, Xiangkai

2018-02-22

Hexavalent chromium (Cr(VI)) is a well-known toxic heavy metal in industrial wastewater, but in situ and real time monitoring cannot be achieved by current methods used during industrial wastewater treatment processes. In this study, a Sediment Microbial Fuel Cell (SMFC) was used as a biosensor for in situ real-time monitoring of Cr(VI), which was the organic substrate is oxidized in the anode and Cr(VI) is reduced at the cathode simultaneously. The pH 6.4 and temperature 25 °C were optimal conditions for the operation. Under the optimal conditions, linearity (R² = 0.9935) of the generated voltage was observed in the Cr(VI) concentration range from 0.2 to 0.7 mg/L. The system showed high specificity for Cr(VI), as other co-existing ions such as Cu 2+ , Zn 2+ , and Pb 2+ did not interfere with Cr(VI) detection. In addition, when the sediment MFC-based biosensor was applied for measuring Cr(VI) in actual wastewater samples, a low deviation (<8%) was obtained, which indicated its potential as a reliable biosensor device. MiSeq sequencing results showed that electrochemically active bacteria ( Geobacter and Pseudomonas ) were enriched at least two-fold on the biofilm of the anode in the biosensor as compared to the SMFC without Cr(VI). Cyclic voltammetry curves indicated that a pair of oxidation/reduction peaks appeared at -111 mV and 581 mV, respectively. These results demonstrated that the proposed sediment microbial fuel cell-based biosensor can be applied as an early warning device for real time in situ detection of Cr(VI) in industrial wastewaters.

A Novel Early Warning System Based on a Sediment Microbial Fuel Cell for In Situ and Real Time Hexavalent Chromium Detection in Industrial Wastewater

PubMed Central

Zhao, Shuai; Liu, Pu; Niu, Yongyan; Chen, Zhengjun; Khan, Aman; Zhang, Pengyun; Li, Xiangkai

2018-01-01

Hexavalent chromium (Cr(VI)) is a well-known toxic heavy metal in industrial wastewater, but in situ and real time monitoring cannot be achieved by current methods used during industrial wastewater treatment processes. In this study, a Sediment Microbial Fuel Cell (SMFC) was used as a biosensor for in situ real-time monitoring of Cr(VI), which was the organic substrate is oxidized in the anode and Cr(VI) is reduced at the cathode simultaneously. The pH 6.4 and temperature 25 °C were optimal conditions for the operation. Under the optimal conditions, linearity (R2 = 0.9935) of the generated voltage was observed in the Cr(VI) concentration range from 0.2 to 0.7 mg/L. The system showed high specificity for Cr(VI), as other co-existing ions such as Cu2+, Zn2+, and Pb2+ did not interfere with Cr(VI) detection. In addition, when the sediment MFC-based biosensor was applied for measuring Cr(VI) in actual wastewater samples, a low deviation (<8%) was obtained, which indicated its potential as a reliable biosensor device. MiSeq sequencing results showed that electrochemically active bacteria (Geobacter and Pseudomonas) were enriched at least two-fold on the biofilm of the anode in the biosensor as compared to the SMFC without Cr(VI). Cyclic voltammetry curves indicated that a pair of oxidation/reduction peaks appeared at −111 mV and 581 mV, respectively. These results demonstrated that the proposed sediment microbial fuel cell-based biosensor can be applied as an early warning device for real time in situ detection of Cr(VI) in industrial wastewaters. PMID:29470394

Optimal Real-time Dispatch for Integrated Energy Systems

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

Firestone, Ryan Michael

This report describes the development and application of a dispatch optimization algorithm for integrated energy systems (IES) comprised of on-site cogeneration of heat and electricity, energy storage devices, and demand response opportunities. This work is intended to aid commercial and industrial sites in making use of modern computing power and optimization algorithms to make informed, near-optimal decisions under significant uncertainty and complex objective functions. The optimization algorithm uses a finite set of randomly generated future scenarios to approximate the true, stochastic future; constraints are included that prevent solutions to this approximate problem from deviating from solutions to the actual problem.more » The algorithm is then expressed as a mixed integer linear program, to which a powerful commercial solver is applied. A case study of United States Postal Service Processing and Distribution Centers (P&DC) in four cities and under three different electricity tariff structures is conducted to (1) determine the added value of optimal control to a cogeneration system over current, heuristic control strategies; (2) determine the value of limited electric load curtailment opportunities, with and without cogeneration; and (3) determine the trade-off between least-cost and least-carbon operations of a cogeneration system. Key results for the P&DC sites studied include (1) in locations where the average electricity and natural gas prices suggest a marginally profitable cogeneration system, optimal control can add up to 67% to the value of the cogeneration system; optimal control adds less value in locations where cogeneration is more clearly profitable; (2) optimal control under real-time pricing is (a) more complicated than under typical time-of-use tariffs and (b) at times necessary to make cogeneration economic at all; (3) limited electric load curtailment opportunities can be more valuable as a compliment to the cogeneration system than alone; and (4) most of the trade-off between least-cost and least-carbon IES is determined during the system design stage; for the IES system considered, there is little difference between least-cost control and least-carbon control.« less

WE-AB-303-06: Combining DAO with MV + KV Optimization to Improve Skin Dose Sparing with Real-Time Fluoroscopy

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

Grelewicz, Z; Wiersma, R

Purpose: Real-time fluoroscopy may allow for improved patient positioning and tumor tracking, particularly in the treatment of lung tumors. In order to mitigate the effects of the imaging dose, previous studies have demonstrated the effect of including both imaging dose and imaging constraints into the inverse treatment planning object function. That method of combined MV+kV optimization may Result in plans with treatment beams chosen to allow for more gentle imaging beam-on times. Direct-aperture optimization (DAO) is also known to produce treatment plans with fluence maps more conducive to lower beam-on times. Therefore, in this work we demonstrate the feasibility ofmore » a combination of DAO and MV+kV optimization for further optimized real-time kV imaging. Methods: Therapeutic and imaging beams were modeled in the EGSnrc Monte Carlo environment, and applied to a patient model for a previously treated lung patient to provide dose influence matrices from DOSXYZnrc. An MV + kV IMRT DAO treatment planning system was developed to compare DAO treatment plans with and without MV+kV optimization. The objective function was optimized using simulated annealing. In order to allow for comparisons between different cases of the stochastically optimized plans, the optimization was repeated twenty times. Results: Across twenty optimizations, combined MV+kV IMRT resulted in an average of 12.8% reduction in peak skin dose. Both non-optimized and MV+kV optimized imaging beams delivered, on average, mean dose of approximately 1 cGy per fraction to the target, with peak doses to target of approximately 6 cGy per fraction. Conclusion: When using DAO, MV+kV optimization is shown to Result in improvements to plan quality in terms of skin dose, when compared to the case of MV optimization with non-optimized kV imaging. The combination of DAO and MV+kV optimization may allow for real-time imaging without excessive imaging dose. Financial support for the work has been provided in part by NIH Grant T32 EB002103, ACS RSG-13-313-01-CCE, and NIH S10 RR021039 and P30 CA14599 grants. The contents of this submission do not necessarily represent the official views of any of the supporting organizations.« less

Column Store for GWAC: A High-cadence, High-density, Large-scale Astronomical Light Curve Pipeline and Distributed Shared-nothing Database

NASA Astrophysics Data System (ADS)

Wan, Meng; Wu, Chao; Wang, Jing; Qiu, Yulei; Xin, Liping; Mullender, Sjoerd; Mühleisen, Hannes; Scheers, Bart; Zhang, Ying; Nes, Niels; Kersten, Martin; Huang, Yongpan; Deng, Jinsong; Wei, Jianyan

2016-11-01

The ground-based wide-angle camera array (GWAC), a part of the SVOM space mission, will search for various types of optical transients by continuously imaging a field of view (FOV) of 5000 degrees2 every 15 s. Each exposure consists of 36 × 4k × 4k pixels, typically resulting in 36 × ˜175,600 extracted sources. For a modern time-domain astronomy project like GWAC, which produces massive amounts of data with a high cadence, it is challenging to search for short timescale transients in both real-time and archived data, and to build long-term light curves for variable sources. Here, we develop a high-cadence, high-density light curve pipeline (HCHDLP) to process the GWAC data in real-time, and design a distributed shared-nothing database to manage the massive amount of archived data which will be used to generate a source catalog with more than 100 billion records during 10 years of operation. First, we develop HCHDLP based on the column-store DBMS of MonetDB, taking advantage of MonetDB’s high performance when applied to massive data processing. To realize the real-time functionality of HCHDLP, we optimize the pipeline in its source association function, including both time and space complexity from outside the database (SQL semantic) and inside (RANGE-JOIN implementation), as well as in its strategy of building complex light curves. The optimized source association function is accelerated by three orders of magnitude. Second, we build a distributed database using a two-level time partitioning strategy via the MERGE TABLE and REMOTE TABLE technology of MonetDB. Intensive tests validate that our database architecture is able to achieve both linear scalability in response time and concurrent access by multiple users. In summary, our studies provide guidance for a solution to GWAC in real-time data processing and management of massive data.

Filtering Data Based on Human-Inspired Forgetting.

PubMed

Freedman, S T; Adams, J A

2011-12-01

Robots are frequently presented with vast arrays of diverse data. Unfortunately, perfect memory and recall provides a mixed blessing. While flawless recollection of episodic data allows increased reasoning, photographic memory can hinder a robot's ability to operate in real-time dynamic environments. Human-inspired forgetting methods may enable robotic systems to rid themselves of out-dated, irrelevant, and erroneous data. This paper presents the use of human-inspired forgetting to act as a filter, removing unnecessary, erroneous, and out-of-date information. The novel ActSimple forgetting algorithm has been developed specifically to provide effective forgetting capabilities to robotic systems. This paper presents the ActSimple algorithm and how it was optimized and tested in a WiFi signal strength estimation task. The results generated by real-world testing suggest that human-inspired forgetting is an effective means of improving the ability of mobile robots to move and operate within complex and dynamic environments.

Mathematical model of marine diesel engine simulator for a new methodology of self propulsion tests

NASA Astrophysics Data System (ADS)

Izzuddin, Nur; Sunarsih, Priyanto, Agoes

2015-05-01

As a vessel operates in the open seas, a marine diesel engine simulator whose engine rotation is controlled to transmit through propeller shaft is a new methodology for the self propulsion tests to track the fuel saving in a real time. Considering the circumstance, this paper presents the real time of marine diesel engine simulator system to track the real performance of a ship through a computer-simulated model. A mathematical model of marine diesel engine and the propeller are used in the simulation to estimate fuel rate, engine rotating speed, thrust and torque of the propeller thus achieve the target vessel's speed. The input and output are a real time control system of fuel saving rate and propeller rotating speed representing the marine diesel engine characteristics. The self-propulsion tests in calm waters were conducted using a vessel model to validate the marine diesel engine simulator. The simulator then was used to evaluate the fuel saving by employing a new mathematical model of turbochargers for the marine diesel engine simulator. The control system developed will be beneficial for users as to analyze different condition of vessel's speed to obtain better characteristics and hence optimize the fuel saving rate.

Data Telemetry and Acquisition System for Acoustic Signal Processing Investigations.

DTIC Science & Technology

1996-02-20

were VME- based computer systems operating under the VxWorks real - time operating system . Each system shared a common hardware and software... real - time operating system . It interfaces to the Berg PCM Decommutator board, which searches for the embedded synchronization word in the data and re...software were built on top of this architecture. The multi-tasking, message queue and memory management facilities of the VxWorks real - time operating system are

Commanding and Controlling Satellite Clusters (IEEE Intelligent Systems, November/December 2000)

DTIC Science & Technology

2000-01-01

real - time operating system , a message-passing OS well suited for distributed...ground Flight processors ObjectAgent RTOS SCL RTOS RDMS Space command language Real - time operating system Rational database management system TS-21 RDMS...engineer with Princeton Satellite Systems. She is working with others to develop ObjectAgent software to run on the OSE Real Time Operating System .

New knowledge-based genetic algorithm for excavator boom structural optimization

NASA Astrophysics Data System (ADS)

Hua, Haiyan; Lin, Shuwen

2014-03-01

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

Instrumentation for optimizing an underground coal-gasification process

NASA Astrophysics Data System (ADS)

Seabaugh, W.; Zielinski, R. E.

1982-06-01

While the United States has a coal resource base of 6.4 trillion tons, only seven percent is presently recoverable by mining. The process of in-situ gasification can recover another twenty-eight percent of the vast resource, however, viable technology must be developed for effective in-situ recovery. The key to this technology is system that can optimize and control the process in real-time. An instrumentation system is described that optimizes the composition of the injection gas, controls the in-situ process and conditions the product gas for maximum utilization. The key elements of this system are Monsanto PRISM Systems, a real-time analytical system, and a real-time data acquisition and control system. This system provides from complete automation of the process but can easily be overridden by manual control. The use of this cost effective system can provide process optimization and is an effective element in developing a viable in-situ technology.

An Approach to Economic Dispatch with Multiple Fuels Based on Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Sriyanyong, Pichet

2011-06-01

Particle Swarm Optimization (PSO), a stochastic optimization technique, shows superiority to other evolutionary computation techniques in terms of less computation time, easy implementation with high quality solution, stable convergence characteristic and independent from initialization. For this reason, this paper proposes the application of PSO to the Economic Dispatch (ED) problem, which occurs in the operational planning of power systems. In this study, ED problem can be categorized according to the different characteristics of its cost function that are ED problem with smooth cost function and ED problem with multiple fuels. Taking the multiple fuels into account will make the problem more realistic. The experimental results show that the proposed PSO algorithm is more efficient than previous approaches under consideration as well as highly promising in real world applications.

The FAST-T approach for operational, real time, short term hydrological forecasting: Results from the Betania Hydropower Reservoir case study

NASA Astrophysics Data System (ADS)

Domínguez, Efraín; Angarita, Hector; Rosmann, Thomas; Mendez, Zulma; Angulo, Gustavo

2013-04-01

A viable quantitative hydrological forecasting service is a combination of technological elements, personnel and knowledge, working together to establish a stable operational cycle of forecasts emission, dissemination and assimilation; hence, the process for establishing such system usually requires significant resources and time to reach an adequate development and integration in order to produce forecasts with acceptable levels of performance. Here are presented the results of this process for the recently implemented Operational Forecast Service for the Betania's Hydropower Reservoir - or SPHEB, located at the Upper-Magdalena River Basin (Colombia). The current scope of the SPHEB includes forecasting of water levels and discharge for the three main streams affluent to the reservoir, for lead times between +1 to +57 hours, and +1 to +10 days. The core of the SPHEB is the Flexible, Adaptive, Simple and Transient Time forecasting approach, namely FAST-T. This comprises of a set of data structures, mathematical kernel, distributed computing and network infrastructure designed to provide seamless real-time operational forecast and automatic model adjustment in case of failures in data transmission or assimilation. Among FAST-T main features are: an autonomous evaluation and detection of the most relevant information for the later configuration of forecasting models; an adaptively linearized mathematical kernel, the optimal adaptive linear combination or OALC, which provides a computationally simple and efficient algorithm for real-time applications; and finally, a meta-model catalog, containing prioritized forecast models at given stream conditions. The SPHEB is at present feed by the fraction of hydrological monitoring network installed at the basin that has telemetric capabilities via NOAA-GOES satellites (8 stages, approximately 47%) with data availability of about a 90% at one hour intervals. However, there is a dense network of 'conventional' hydro-meteorological stages -read manually once or twice per day - that, despite not ideal in the context of real-time system, improve model performance significantly, and therefore are entered into the system by manual input. At its current configuration, the SPHEB performance objectives are fulfilled for 90% of the forecasts with lead times up to +2 days and +15 hours (using the predictability criteria of the Russian Hydrometeorological Center S/?Δ) and the average accuracy is in the range 70-99% ( r2 criteria). However, longer lead times are at present not satisfactory in terms of forecasts accuracy.

The role of hydrology in water resources management

NASA Astrophysics Data System (ADS)

Shamir, U.

2011-12-01

Modern water resources management developed as a branch of science based engineering since the landmark publication of Mass et al. (1962&1967) which emerged from the Harvard Water Program. Clearly, water was managed much earlier, in fact since the early days of civilization, as evidenced by the publication of Vitruvius on architecture in the 1st Century BC, but the 1950s marked the advent of modeling enabled by computers, which transformed the field we call Water Resources Management (WRM). Since then, thousands of papers have been published and thousands of decisions and projects have been aided by WRM methodologies and model results. This presentation is not an historical review of water resources management, although it appears in a session titled The Evolution of WRM Paradigms. Instead, it is an attempt to discuss the role of hydrology as a feeder of information for the management domain. The issues faced by hydrologists who work to serve and support WRM will be discussed and elucidated by case studies. For hydrologists, some of the important points in this regard are: - Planning, design and operation are three interconnected "layers" of WRM. Planning is where the sources and consumers are identified, the overall "architecture" of a proposed system is laid out, including its topology and connectivity. Design is where sizes of facilities are fixed. Operational policy determines the operation of the system under a selected forecasted set of typical and/or critical conditions, while real-time operation means setting the operational variables for a defined time period ahead (hour, day, week, month, year). The three "layers" are inter-connected and inter-dependent, but still can be addressed differently. - Hydrological data of different types are required, according to the management issue being addressed. They range from short term now-casting/forecasting for real-time operation and response, e.g., for flood protection, to long-term time probabilistic series and ensembles for planning, which consider changing natural and anthropogenic drivers (land use, climate change). Since hydrology is a continuous process that is not divided internally according to the needs of management, the hydrological analysis must be geared to produce the suitable information for the different management issues. - Aggregation and disaggregation in space and time: selection of the level of detail in time and space should begin from the needs of the management issue being addressed, and dictate the monitoring, collection and processing. - Water quality: should receive more attention, as it is playing an ever increasing role in management, including its importance in ecological services. - Optimization, simulation and combining the two: optimization for WRM is used extensively. Some optimization models are able to address uncertainty internally, and further development continues. Simulation is easier to employ, but it merely produces "if-then" analysis. Combination of optimization and simulation is a common way to combine the advantages of the two. - Uncertainty, forecasting, ensembles: the uncertainties inherent in hydrological analysis and forecasting lead to the requirement for generating forecasts with a probabilistic characterization. This can be in the form of PDFs, time series, ensembles.

Hydraulic Modeling and Evolutionary Optimization for Enhanced Real-Time Decision Support of Combined Sewer Overflows

NASA Astrophysics Data System (ADS)

Zimmer, A. L.; Minsker, B. S.; Schmidt, A. R.; Ostfeld, A.

2011-12-01

Real-time mitigation of combined sewer overflows (CSOs) requires evaluation of multiple operational strategies during rapidly changing rainfall events. Simulation models for hydraulically complex systems can effectively provide decision support for short time intervals when coupled with efficient optimization. This work seeks to reduce CSOs for a test case roughly based on the North Branch of the Chicago Tunnel and Reservoir Plan (TARP), which is operated by the Metropolitan Water Reclamation District of Greater Chicago (MWRDGC). The North Branch tunnel flows to a junction with the main TARP system. The Chicago combined sewer system alleviates potential CSOs by directing high interceptor flows through sluice gates and dropshafts to a deep tunnel. Decision variables to control CSOs consist of sluice gate positions that control water flow to the tunnel as well as a treatment plant pumping rate that lowers interceptor water levels. A physics-based numerical model is used to simulate the hydraulic effects of changes in the decision variables. The numerical model is step-wise steady and conserves water mass and momentum at each time step by iterating through a series of look-up tables. The look-up tables are constructed offline to avoid extensive real-time calculations, and describe conduit storage and water elevations as a function of flow. A genetic algorithm (GA) is used to minimize CSOs at each time interval within a moving horizon framework. Decision variables are coded at 15-minute increments and GA solutions are two hours in duration. At each 15-minute interval, the algorithm identifies a good solution for a two-hour rainfall forecast. Three GA modifications help reduce optimization time. The first adjustment reduces the search alphabet by eliminating sluice gate positions that do not influence overflow volume. The second GA retains knowledge of the best decision at the previous interval by shifting the genes in the best previous sequence to initialize search at the new interval. The third approach is a micro-GA with a small population size and high diversity. Current tunnel operations attempt to avoid dropshaft geysers by simultaneously closing all sluice gates when the downstream end of the deep tunnel pressurizes. In an effort to further reduce CSOs, this research introduces a constraint that specifies a maximum allowable tunnel flow to prevent pressurization. The downstream junction depth is bounded by two flow conditions: a low tunnel water level represents inflow from the main system only, while a higher level includes main system flow as well as all possible North Branch inflow. If the lower of the two tunnel levels is pressurized, no North Branch flow is allowed to enter the junction. If only the higher level pressurizes, a linear rating is used to restrict the total North Branch flow below the volume that pressurizes the boundary. The numerical model is successfully calibrated to EPA SWMM and efficiently portrays system hydraulics in real-time. Results on the three GA approaches as well as impacts of various policies for the downstream constraint will be presented at the conference.

Techniques for optimizing human-machine information transfer related to real-time interactive display systems

NASA Technical Reports Server (NTRS)

Granaas, Michael M.; Rhea, Donald C.

1989-01-01

The requirements for the development of real-time displays are reviewed. Of particular interest are the psychological aspects of design such as the layout, color selection, real-time response rate, and the interactivity of displays. Some existing Western Aeronautical Test Range displays are analyzed.

Real-time CT-video registration for continuous endoscopic guidance

NASA Astrophysics Data System (ADS)

Merritt, Scott A.; Rai, Lav; Higgins, William E.

2006-03-01

Previous research has shown that CT-image-based guidance could be useful for the bronchoscopic assessment of lung cancer. This research drew upon the registration of bronchoscopic video images to CT-based endoluminal renderings of the airway tree. The proposed methods either were restricted to discrete single-frame registration, which took several seconds to complete, or required non-real-time buffering and processing of video sequences. We have devised a fast 2D/3D image registration method that performs single-frame CT-Video registration in under 1/15th of a second. This allows the method to be used for real-time registration at full video frame rates without significantly altering the physician's behavior. The method achieves its speed through a gradient-based optimization method that allows most of the computation to be performed off-line. During live registration, the optimization iteratively steps toward the locally optimal viewpoint at which a CT-based endoluminal view is most similar to a current bronchoscopic video frame. After an initial registration to begin the process (generally done in the trachea for bronchoscopy), subsequent registrations are performed in real-time on each incoming video frame. As each new bronchoscopic video frame becomes available, the current optimization is initialized using the previous frame's optimization result, allowing continuous guidance to proceed without manual re-initialization. Tests were performed using both synthetic and pre-recorded bronchoscopic video. The results show that the method is robust to initialization errors, that registration accuracy is high, and that continuous registration can proceed on real-time video at >15 frames per sec. with minimal user-intervention.

NSTX-U Advances in Real-Time C++11 on Linux

NASA Astrophysics Data System (ADS)

Erickson, Keith G.

2015-08-01

Programming languages like C and Ada combined with proprietary embedded operating systems have dominated the real-time application space for decades. The new C++11 standard includes native, language-level support for concurrency, a required feature for any nontrivial event-oriented real-time software. Threads, Locks, and Atomics now exist to provide the necessary tools to build the structures that make up the foundation of a complex real-time system. The National Spherical Torus Experiment Upgrade (NSTX-U) at the Princeton Plasma Physics Laboratory (PPPL) is breaking new ground with the language as applied to the needs of fusion devices. A new Digital Coil Protection System (DCPS) will serve as the main protection mechanism for the magnetic coils, and it is written entirely in C++11 running on Concurrent Computer Corporation's real-time operating system, RedHawk Linux. It runs over 600 algorithms in a 5 kHz control loop that determine whether or not to shut down operations before physical damage occurs. To accomplish this, NSTX-U engineers developed software tools that do not currently exist elsewhere, including real-time atomic synchronization, real-time containers, and a real-time logging framework. Together with a recent (and carefully configured) version of the GCC compiler, these tools enable data acquisition, processing, and output using a conventional operating system to meet a hard real-time deadline (that is, missing one periodic is a failure) of 200 microseconds.

MARVEL: A knowledge-based productivity enhancement tool for real-time multi-mission and multi-subsystem spacecraft operations

NASA Astrophysics Data System (ADS)

Schwuttke, Ursula M.; Veregge, John, R.; Angelino, Robert; Childs, Cynthia L.

1990-10-01

The Monitor/Analyzer of Real-time Voyager Engineering Link (MARVEL) is described. It is the first automation tool to be used in an online mode for telemetry monitoring and analysis in mission operations. MARVEL combines standard automation techniques with embedded knowledge base systems to simultaneously provide real time monitoring of data from subsystems, near real time analysis of anomaly conditions, and both real time and non-real time user interface functions. MARVEL is currently capable of monitoring the Computer Command Subsystem (CCS), Flight Data Subsystem (FDS), and Attitude and Articulation Control Subsystem (AACS) for both Voyager spacecraft, simultaneously, on a single workstation. The goal of MARVEL is to provide cost savings and productivity enhancement in mission operations and to reduce the need for constant availability of subsystem expertise.

The Clinical Utilisation of Respiratory Elastance Software (CURE Soft): a bedside software for real-time respiratory mechanics monitoring and mechanical ventilation management.

PubMed

Szlavecz, Akos; Chiew, Yeong Shiong; Redmond, Daniel; Beatson, Alex; Glassenbury, Daniel; Corbett, Simon; Major, Vincent; Pretty, Christopher; Shaw, Geoffrey M; Benyo, Balazs; Desaive, Thomas; Chase, J Geoffrey

2014-09-30

Real-time patient respiratory mechanics estimation can be used to guide mechanical ventilation settings, particularly, positive end-expiratory pressure (PEEP). This work presents a software, Clinical Utilisation of Respiratory Elastance (CURE Soft), using a time-varying respiratory elastance model to offer this ability to aid in mechanical ventilation treatment. CURE Soft is a desktop application developed in JAVA. It has two modes of operation, 1) Online real-time monitoring decision support and, 2) Offline for user education purposes, auditing, or reviewing patient care. The CURE Soft has been tested in mechanically ventilated patients with respiratory failure. The clinical protocol, software testing and use of the data were approved by the New Zealand Southern Regional Ethics Committee. Using CURE Soft, patient's respiratory mechanics response to treatment and clinical protocol were monitored. Results showed that the patient's respiratory elastance (Stiffness) changed with the use of muscle relaxants, and responded differently to ventilator settings. This information can be used to guide mechanical ventilation therapy and titrate optimal ventilator PEEP. CURE Soft enables real-time calculation of model-based respiratory mechanics for mechanically ventilated patients. Results showed that the system is able to provide detailed, previously unavailable information on patient-specific respiratory mechanics and response to therapy in real-time. The additional insight available to clinicians provides the potential for improved decision-making, and thus improved patient care and outcomes.

Optimal space communications techniques. [all digital phase locked loop for FM demodulation

NASA Technical Reports Server (NTRS)

Schilling, D. L.

1973-01-01

The design, development, and analysis are reported of a digital phase-locked loop (DPLL) for FM demodulation and threshold extension. One of the features of the developed DPLL is its synchronous, real time operation. The sampling frequency is constant and all the required arithmetic and logic operations are performed within one sampling period, generating an output sequence which is converted to analog form and filtered. An equation relating the sampling frequency to the carrier frequency must be satisfied to guarantee proper DPLL operation. The synchronous operation enables a time-shared operation of one DPLL to demodulate several FM signals simultaneously. In order to obtain information about the DPLL performance at low input signal-to-noise ratios, a model of an input noise spike was introduced, and the DPLL equation was solved using a digital computer. The spike model was successful in finding a second order DPLL which yielded a five db threshold extension beyond that of a first order DPLL.

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

PubMed

Wang, Monan; Zhang, Kai; Yang, Ning

2018-04-09

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

Real Time Metrics and Analysis of Integrated Arrival, Departure, and Surface Operations

NASA Technical Reports Server (NTRS)

Sharma, Shivanjli; Fergus, John

2017-01-01

A real time dashboard was developed in order to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users across a number of roles benefit from a real time system that enables common situational awareness. In addition to shared situational awareness the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial set of metrics computed on operational data. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017; Charlotte-Douglas International Airport. Analysis and metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of metrics across delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.

An Optimal Static Scheduling Algorithm for Hard Real-Time Systems Specified in a Prototyping Language

DTIC Science & Technology

1989-12-01

to construct because the mechanism is a dispatching procedure. Since all nonpreemptive schedules are contained in the set of all preemptive schedules...the optimal value of T’.. in the preemptive case is at least a lower bound on the optimal T., for the nonpreemptive schedules. This principle is the...adapt to changes in the enviro.nment. In hard real-time systems, tasks are also distinguished as preemptable and nonpreemptable . A task is preemptable

Distributed Systems: Interconnection and Fault Tolerance Studies

DTIC Science & Technology

1992-01-01

real - time operating system , a number of new techniques have to be...problem is at the heart of a successful implementation of a real - time operating system in a distributed environment. Our studies of the issues...land, College Park MD 20742, January 1991. [i1] 6 lafur Gudmundsson, Daniel Moss6, Ashok K. Agrawala, and Satish K. Tripathi. MARUTI a hard real - time operating system .

Integrated optical 3D digital imaging based on DSP scheme

NASA Astrophysics Data System (ADS)

Wang, Xiaodong; Peng, Xiang; Gao, Bruce Z.

2008-03-01

We present a scheme of integrated optical 3-D digital imaging (IO3DI) based on digital signal processor (DSP), which can acquire range images independently without PC support. This scheme is based on a parallel hardware structure with aid of DSP and field programmable gate array (FPGA) to realize 3-D imaging. In this integrated scheme of 3-D imaging, the phase measurement profilometry is adopted. To realize the pipeline processing of the fringe projection, image acquisition and fringe pattern analysis, we present a multi-threads application program that is developed under the environment of DSP/BIOS RTOS (real-time operating system). Since RTOS provides a preemptive kernel and powerful configuration tool, with which we are able to achieve a real-time scheduling and synchronization. To accelerate automatic fringe analysis and phase unwrapping, we make use of the technique of software optimization. The proposed scheme can reach a performance of 39.5 f/s (frames per second), so it may well fit into real-time fringe-pattern analysis and can implement fast 3-D imaging. Experiment results are also presented to show the validity of proposed scheme.

Noninvasive Real-Time Assessment of Cell Viability in a Three-Dimensional Tissue.

PubMed

Mahfouzi, Seyed Hossein; Amoabediny, Ghassem; Doryab, Ali; Safiabadi-Tali, Seyed Hamid; Ghanei, Mostafa

2018-04-01

Maintaining cell viability within 3D tissue engineering scaffolds is an essential step toward a functional tissue or organ. Assessment of cell viability in 3D scaffolds is necessary to control and optimize tissue culture process. Monitoring systems based on respiration activity of cells (e.g., oxygen consumption) have been used in various cell cultures. In this research, an online monitoring system based on respiration activity was developed to monitor cell viability within acellular lung scaffolds. First, acellular lung scaffolds were recellularized with human umbilical cord vein endothelial cells, and then, cell viability was monitored during a 5-day period. The real-time monitoring system generated a cell growth profile representing invaluable information on cell viability and proliferative states during the culture period. The cell growth profile obtained by the monitoring system was consistent with 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide analysis and glucose consumption measurement. This system provided a means for noninvasive, real-time, and repetitive investigation of cell viability. Also, we showed the applicability of this monitoring system by introducing shaking as an operating parameter in a long-term culture.

Comparison of 2 real-time PCR assays for diagnosis of Pneumocystis jirovecii pneumonia in human immunodeficiency virus (HIV) and non-HIV immunocompromised patients.

PubMed

Montesinos, Isabel; Brancart, Françoise; Schepers, Kinda; Jacobs, Frederique; Denis, Olivier; Delforge, Marie-Luce

2015-06-01

A total of 120 bronchoalveolar lavage specimens from HIV and non-HIV immunocompromised patients, positive for Pneumocystis jirovecii by an "in house" real-time polymerase chain reaction (PCR), were evaluated by the Bio-Evolution Pneumocystis real-time PCR, a commercial quantitative assay. Patients were classified in 2 categories based on clinical and radiological findings: definite and unlikely Pneumocystis pneumonia (PCP). For the "in house" PCR, cycle threshold 34 was established as cut-off value to discriminate definite PCP from unlikely PCP with 65% and 85% of sensitivity and specificity, respectively. For the Bio-Evolution quantitative PCR, a cut-off value of 2.8×10(5)copies/mL was defined with 72% and 82% of sensitivity and specificity, respectively. Overlapped zones of results for definite and unlikely PCP were observed. Quantitative PCR is probably a useful tool for PCP diagnosis. However, for optimal management of PCP in non-HIV immunocompromised patients, operational thresholds should be assessed according to underlying diseases and other clinical and radiological parameters. Copyright © 2015 Elsevier Inc. All rights reserved.

The power grid AGC frequency bias coefficient online identification method based on wide area information

NASA Astrophysics Data System (ADS)

Wang, Zian; Li, Shiguang; Yu, Ting

2015-12-01

This paper propose online identification method of regional frequency deviation coefficient based on the analysis of interconnected grid AGC adjustment response mechanism of regional frequency deviation coefficient and the generator online real-time operation state by measured data through PMU, analyze the optimization method of regional frequency deviation coefficient in case of the actual operation state of the power system and achieve a more accurate and efficient automatic generation control in power system. Verify the validity of the online identification method of regional frequency deviation coefficient by establishing the long-term frequency control simulation model of two-regional interconnected power system.

A multi-port 10GbE PCIe NIC featuring UDP offload and GPUDirect capabilities.

NASA Astrophysics Data System (ADS)

Ammendola, Roberto; Biagioni, Andrea; Frezza, Ottorino; Lamanna, Gianluca; Lo Cicero, Francesca; Lonardo, Alessandro; Martinelli, Michele; Stanislao Paolucci, Pier; Pastorelli, Elena; Pontisso, Luca; Rossetti, Davide; Simula, Francesco; Sozzi, Marco; Tosoratto, Laura; Vicini, Piero

2015-12-01

NaNet-10 is a four-ports 10GbE PCIe Network Interface Card designed for low-latency real-time operations with GPU systems. To this purpose the design includes an UDP offload module, for fast and clock-cycle deterministic handling of the transport layer protocol, plus a GPUDirect P2P/RDMA engine for low-latency communication with NVIDIA Tesla GPU devices. A dedicated module (Multi-Stream) can optionally process input UDP streams before data is delivered through PCIe DMA to their destination devices, re-organizing data from different streams guaranteeing computational optimization. NaNet-10 is going to be integrated in the NA62 CERN experiment in order to assess the suitability of GPGPU systems as real-time triggers; results and lessons learned while performing this activity will be reported herein.

Real-time control of combined surface water quantity and quality: polder flushing.

PubMed

Xu, M; van Overloop, P J; van de Giesen, N C; Stelling, G S

2010-01-01

In open water systems, keeping both water depths and water quality at specified values is critical for maintaining a 'healthy' water system. Many systems still require manual operation, at least for water quality management. When applying real-time control, both quantity and quality standards need to be met. In this paper, an artificial polder flushing case is studied. Model Predictive Control (MPC) is developed to control the system. In addition to MPC, a 'forward estimation' procedure is used to acquire water quality predictions for the simplified model used in MPC optimization. In order to illustrate the advantages of MPC, classical control [Proportional-Integral control (PI)] has been developed for comparison in the test case. The results show that both algorithms are able to control the polder flushing process, but MPC is more efficient in functionality and control flexibility.

Real-Time Integrated Photoacoustic and Ultrasound (PAUS) Imaging System to Guide Interventional Procedures: Ex Vivo Study

PubMed Central

Wei, Chen-Wei; Nguyen, Thu-Mai; Xia, Jinjun; Arnal, Bastien; Wong, Emily Y.; Pelivanov, Ivan M.; O’Donnell, Matthew

2015-01-01

Because of depth-dependent light attenuation, bulky, low-repetition-rate lasers are usually used in most photoacoustic (PA) systems to provide sufficient pulse energies to image at depth within the body. However, integrating these lasers with real-time clinical ultrasound (US) scanners has been problematic because of their size and cost. In this paper, an integrated PA/US (PAUS) imaging system is presented operating at frame rates >30 Hz. By employing a portable, low-cost, low-pulse-energy (~2 mJ/pulse), high-repetition-rate (~1 kHz), 1053-nm laser, and a rotating galvo-mirror system enabling rapid laser beam scanning over the imaging area, the approach is demonstrated for potential applications requiring a few centimeters of penetration. In particular, we demonstrate here real-time (30 Hz frame rate) imaging (by combining multiple single-shot sub-images covering the scan region) of an 18-gauge needle inserted into a piece of chicken breast with subsequent delivery of an absorptive agent at more than 1-cm depth to mimic PAUS guidance of an interventional procedure. A signal-to-noise ratio of more than 35 dB is obtained for the needle in an imaging area 2.8 × 2.8 cm (depth × lateral). Higher frame rate operation is envisioned with an optimized scanning scheme. PMID:25643081

A rapid and practical technique for real-time monitoring of biomolecular interactions using mechanical responses of macromolecules

NASA Astrophysics Data System (ADS)

Tarhan, Mehmet C.; Lafitte, Nicolas; Tauran, Yannick; Jalabert, Laurent; Kumemura, Momoko; Perret, Grégoire; Kim, Beomjoon; Coleman, Anthony W.; Fujita, Hiroyuki; Collard, Dominique

2016-06-01

Monitoring biological reactions using the mechanical response of macromolecules is an alternative approach to immunoassays for providing real-time information about the underlying molecular mechanisms. Although force spectroscopy techniques, e.g. AFM and optical tweezers, perform precise molecular measurements at the single molecule level, sophisticated operation prevent their intensive use for systematic biosensing. Exploiting the biomechanical assay concept, we used micro-electro mechanical systems (MEMS) to develop a rapid platform for monitoring bio/chemical interactions of bio macromolecules, e.g. DNA, using their mechanical properties. The MEMS device provided real-time monitoring of reaction dynamics without any surface or molecular modifications. A microfluidic device with a side opening was fabricated for the optimal performance of the MEMS device to operate at the air-liquid interface for performing bioassays in liquid while actuating/sensing in air. The minimal immersion of the MEMS device in the channel provided long-term measurement stability (>10 h). Importantly, the method allowed monitoring effects of multiple solutions on the same macromolecule bundle (demonstrated with DNA bundles) without compromising the reproducibility. We monitored two different types of effects on the mechanical responses of DNA bundles (stiffness and viscous losses) exposed to pH changes (2.1 to 4.8) and different Ag+ concentrations (1 μM to 0.1 M).

Real-time portable system for fabric defect detection using an ARM processor

NASA Astrophysics Data System (ADS)

Fernandez-Gallego, J. A.; Yañez-Puentes, J. P.; Ortiz-Jaramillo, B.; Alvarez, J.; Orjuela-Vargas, S. A.; Philips, W.

2012-06-01

Modern textile industry seeks to produce textiles as little defective as possible since the presence of defects can decrease the final price of products from 45% to 65%. Automated visual inspection (AVI) systems, based on image analysis, have become an important alternative for replacing traditional inspections methods that involve human tasks. An AVI system gives the advantage of repeatability when implemented within defined constrains, offering more objective and reliable results for particular tasks than human inspection. Costs of automated inspection systems development can be reduced using modular solutions with embedded systems, in which an important advantage is the low energy consumption. Among the possibilities for developing embedded systems, the ARM processor has been explored for acquisition, monitoring and simple signal processing tasks. In a recent approach we have explored the use of the ARM processor for defects detection by implementing the wavelet transform. However, the computation speed of the preprocessing was not yet sufficient for real time applications. In this approach we significantly improve the preprocessing speed of the algorithm, by optimizing matrix operations, such that it is adequate for a real time application. The system was tested for defect detection using different defect types. The paper is focused in giving a detailed description of the basis of the algorithm implementation, such that other algorithms may use of the ARM operations for fast implementations.

Active model-based balancing strategy for self-reconfigurable batteries

NASA Astrophysics Data System (ADS)

Bouchhima, Nejmeddine; Schnierle, Marc; Schulte, Sascha; Birke, Kai Peter

2016-08-01

This paper describes a novel balancing strategy for self-reconfigurable batteries where the discharge and charge rates of each cell can be controlled. While much effort has been focused on improving the hardware architecture of self-reconfigurable batteries, energy equalization algorithms have not been systematically optimized in terms of maximizing the efficiency of the balancing system. Our approach includes aspects of such optimization theory. We develop a balancing strategy for optimal control of the discharge rate of battery cells. We first formulate the cell balancing as a nonlinear optimal control problem, which is modeled afterward as a network program. Using dynamic programming techniques and MATLAB's vectorization feature, we solve the optimal control problem by generating the optimal battery operation policy for a given drive cycle. The simulation results show that the proposed strategy efficiently balances the cells over the life of the battery, an obvious advantage that is absent in the other conventional approaches. Our algorithm is shown to be robust when tested against different influencing parameters varying over wide spectrum on different drive cycles. Furthermore, due to the little computation time and the proved low sensitivity to the inaccurate power predictions, our strategy can be integrated in a real-time system.

Parallel dispatch: a new paradigm of electrical power system dispatch

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

Zhang, Jun Jason; Wang, Fei-Yue; Wang, Qiang

Modern power systems are evolving into sociotechnical systems with massive complexity, whose real-time operation and dispatch go beyond human capability. Thus, the need for developing and applying new intelligent power system dispatch tools are of great practical significance. In this paper, we introduce the overall business model of power system dispatch, the top level design approach of an intelligent dispatch system, and the parallel intelligent technology with its dispatch applications. We expect that a new dispatch paradigm, namely the parallel dispatch, can be established by incorporating various intelligent technologies, especially the parallel intelligent technology, to enable secure operation of complexmore » power grids, extend system operators U+02BC capabilities, suggest optimal dispatch strategies, and to provide decision-making recommendations according to power system operational goals.« less

"Real-time" disintegration analysis and D-optimal experimental design for the optimization of diclofenac sodium fast-dissolving films.

PubMed

El-Malah, Yasser; Nazzal, Sami

2013-01-01

The objective of this work was to study the dissolution and mechanical properties of fast-dissolving films prepared from a tertiary mixture of pullulan, polyvinylpyrrolidone and hypromellose. Disintegration studies were performed in real-time by probe spectroscopy to detect the onset of film disintegration. Tensile strength and elastic modulus of the films were measured by texture analysis. Disintegration time of the films ranged from 21 to 105 seconds whereas their mechanical properties ranged from approximately 2 to 49 MPa for tensile strength and 1 to 21 MPa% for young's modulus. After generating polynomial models correlating the variables using a D-Optimal mixture design, an optimal formulation with desired responses was proposed by the statistical package. For validation, a new film formulation loaded with diclofenac sodium based on the optimized composition was prepared and tested for dissolution and tensile strength. Dissolution of the optimized film was found to commence almost immediately with 50% of the drug released within one minute. Tensile strength and young's modulus of the film were 11.21 MPa and 6, 78 MPa%, respectively. Real-time spectroscopy in conjunction with statistical design were shown to be very efficient for the optimization and development of non-conventional intraoral delivery system such as fast dissolving films.

Software for real-time control of a tidal liquid ventilator.

PubMed

Heckman, J L; Hoffman, J; Shaffer, T H; Wolfson, M R

1999-01-01

The purpose of this project was to develop and test computer software and control algorithms designed to operate a tidal liquid ventilator. The tests were executed on a 90-MHz Pentium PC with 16 MB RAM and a prototype liquid ventilator. The software was designed using Microsoft Visual C++ (Ver. 5.0) and the Microsoft Foundation Classes. It uses a graphic user interface, is multithreaded, runs in real time, and has a built-in simulator that facilitates user education in liquid-ventilation principles. The operator can use the software to specify ventilation parameters such as the frequency of ventilation, the tidal volume, and the inspiratory-expiratory time ratio. Commands are implemented via control of the pump speed and by setting the position of two two-way solenoid-controlled valves. Data for use in monitoring and control are gathered by analog-to-digital conversion. Control strategies are implemented to maintain lung volumes and airway pressures within desired ranges, according to limits set by the operator. Also, the software allows the operator to define the shape of the flow pulse during inspiration and expiration, and to optimize perfluorochemical liquid transfer while minimizing airway pressures and maintaining the desired tidal volume. The operator can stop flow during inspiration and expiration to measure alveolar pressures. At the end of expiration, the software stores all user commands and 30 ventilation parameters into an Excel spreadsheet for later review and analysis. Use of these software and control algorithms affords user-friendly operation of a tidal liquid ventilator while providing precise control of ventilation parameters.

Enhancing dissolved oxygen control using an on-line hybrid fuzzy-neural soft-sensing model-based control system in an anaerobic/anoxic/oxic process.

PubMed

Huang, Mingzhi; Wan, Jinquan; Hu, Kang; Ma, Yongwen; Wang, Yan

2013-12-01

An on-line hybrid fuzzy-neural soft-sensing model-based control system was developed to optimize dissolved oxygen concentration in a bench-scale anaerobic/anoxic/oxic (A(2)/O) process. In order to improve the performance of the control system, a self-adapted fuzzy c-means clustering algorithm and adaptive network-based fuzzy inference system (ANFIS) models were employed. The proposed control system permits the on-line implementation of every operating strategy of the experimental system. A set of experiments involving variable hydraulic retention time (HRT), influent pH (pH), dissolved oxygen in the aerobic reactor (DO), and mixed-liquid return ratio (r) was carried out. Using the proposed system, the amount of COD in the effluent stabilized at the set-point and below. The improvement was achieved with optimum dissolved oxygen concentration because the performance of the treatment process was optimized using operating rules implemented in real time. The system allows various expert operational approaches to be deployed with the goal of minimizing organic substances in the outlet while using the minimum amount of energy.

Pruning-Based, Energy-Optimal, Deterministic I/O Device Scheduling for Hard Real-Time Systems

DTIC Science & Technology

2005-02-01

However, DPM via I/O device scheduling for hard real - time systems has received relatively little attention. In this paper,we present an offline I/O...polynomial time. We present experimental results to show that EDS and MDO reduce the energy consumption of I/O devices significantly for hard real - time systems .

RTDS implementation of an improved sliding mode based inverter controller for PV system.

PubMed

Islam, Gazi; Muyeen, S M; Al-Durra, Ahmed; Hasanien, Hany M

2016-05-01

This paper proposes a novel approach for testing dynamics and control aspects of a large scale photovoltaic (PV) system in real time along with resolving design hindrances of controller parameters using Real Time Digital Simulator (RTDS). In general, the harmonic profile of a fast controller has wide distribution due to the large bandwidth of the controller. The major contribution of this paper is that the proposed control strategy gives an improved voltage harmonic profile and distribute it more around the switching frequency along with fast transient response; filter design, thus, becomes easier. The implementation of a control strategy with high bandwidth in small time steps of Real Time Digital Simulator (RTDS) is not straight forward. This paper shows a good methodology for the practitioners to implement such control scheme in RTDS. As a part of the industrial process, the controller parameters are optimized using particle swarm optimization (PSO) technique to improve the low voltage ride through (LVRT) performance under network disturbance. The response surface methodology (RSM) is well adapted to build analytical models for recovery time (Rt), maximum percentage overshoot (MPOS), settling time (Ts), and steady state error (Ess) of the voltage profile immediate after inverter under disturbance. A systematic approach of controller parameter optimization is detailed. The transient performance of the PSO based optimization method applied to the proposed sliding mode controlled PV inverter is compared with the results from genetic algorithm (GA) based optimization technique. The reported real time implementation challenges and controller optimization procedure are applicable to other control applications in the field of renewable and distributed generation systems. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Analysis of the Pointing Accuracy of a 6U CubeSat Mission for Proximity Operations and Resident Space Object Imaging

DTIC Science & Technology

2013-05-29

not necessarily express the views of and should not be attributed to ESA. 1 and visual navigation to maneuver autonomously to reduce the size of the...successful orbit and three-dimensional imaging of an RSO, using passive visual -only navigation and real-time near-optimal guidance. The mission design...Kit ( STK ) in the Earth-centered Earth-fixed (ECF) co- ordinate system, loaded to Simulink and transformed to the BFF for calculation of the SRP

Multicriteria adaptation principle on example of groups of mobile robots

NASA Astrophysics Data System (ADS)

Nelyubin, A. P.; Misyurin, S. Yu

2017-12-01

The article presents a multicriteria approach to the adaptation of groups of search, explore or research robots to unknown and volatile environment conditions. The basis of this approach is the application of multicriteria analysis both at the design stage of a group of mobile robots and at the stage of its adaptation in real-time conditions. It is proposed to maintain a variety of robots by properties and by optimality criteria in order to take into account the preferred mode of operation.

A quantum network of clocks

NASA Astrophysics Data System (ADS)

Komar, Peter; Kessler, Eric; Bishof, Michael; Jiang, Liang; Sorensen, Anders; Ye, Jun; Lukin, Mikhail

2014-05-01

Shared timing information constitutes a key resource for positioning and navigation with a direct correspondence between timing accuracy and precision in applications such as the Global Positioning System (GPS). By combining precision metrology and quantum networks, we propose here a quantum, cooperative protocol for the operation of a network consisting of geographically remote optical atomic clocks. Using non-local entangled states, we demonstrate an optimal utilization of the global network resources, and show that such a network can be operated near the fundamental limit set by quantum theory yielding an ultra-precise clock signal. Furthermore, the internal structure of the network, combined with basic techniques from quantum communication, guarantees security both from internal and external threats. Realization of such a global quantum network of clocks may allow construction of a real-time single international time scale (world clock) with unprecedented stability and accuracy. See also: Komar et al. arXiv:1310.6045 (2013) and Kessler et al. arXiv:1310.6043 (2013).

Hardware-In-The-Loop Power Extraction Using Different Real-Time Platforms (Postprint)

DTIC Science & Technology

2008-11-01

each real - time operating system . However, discrepancies in test results obtained from the NI system can be resolved. This paper briefly details...same model in native Simulink. These results show that each real - time operating system can be configured to accurately run transient Simulink models

Suboptimal LQR-based spacecraft full motion control: Theory and experimentation

NASA Astrophysics Data System (ADS)

Guarnaccia, Leone; Bevilacqua, Riccardo; Pastorelli, Stefano P.

2016-05-01

This work introduces a real time suboptimal control algorithm for six-degree-of-freedom spacecraft maneuvering based on a State-Dependent-Algebraic-Riccati-Equation (SDARE) approach and real-time linearization of the equations of motion. The control strategy is sub-optimal since the gains of the linear quadratic regulator (LQR) are re-computed at each sample time. The cost function of the proposed controller has been compared with the one obtained via a general purpose optimal control software, showing, on average, an increase in control effort of approximately 15%, compensated by real-time implementability. Lastly, the paper presents experimental tests on a hardware-in-the-loop six-degree-of-freedom spacecraft simulator, designed for testing new guidance, navigation, and control algorithms for nano-satellites in a one-g laboratory environment. The tests show the real-time feasibility of the proposed approach.

Permanent magnet synchronous motor servo system control based on μC/OS

NASA Astrophysics Data System (ADS)

Shi, Chongyang; Chen, Kele; Chen, Xinglong

2015-10-01

When Opto-Electronic Tracking system operates in complex environments, every subsystem must operate efficiently and stably. As a important part of Opto-Electronic Tracking system, the performance of PMSM(Permanent Magnet Synchronous Motor) servo system affects the Opto-Electronic Tracking system's accuracy and speed greatly[1][2]. This paper applied embedded real-time operating system μC/OS to the control of PMSM servo system, implemented SVPWM(Space Vector Pulse Width Modulation) algorithm in PMSM servo system, optimized the stability of PMSM servo system. Pointing on the characteristics of the Opto-Electronic Tracking system, this paper expanded μC/OS with software redundancy processes, remote debugging and upgrading. As a result, the Opto- Electronic Tracking system performs efficiently and stably.

Detection of Mental State and Reduction of Artifacts Using Functional Near Infrared Spectroscopy (FNIRS)

NASA Technical Reports Server (NTRS)

Harrivel, Angela (Inventor); Hearn, Tristan (Inventor)

2017-01-01

fNIRS may be used in real time or near-real time to detect the mental state of individuals. Phase measurement can be applied to drive an adaptive filter for the removal of motion artifacts in real time or near-real time. In this manner, the application of fNIRS may be extended to practical non-laboratory environments. For example, the mental state of an operator of a vehicle may be monitored, and alerts may be issued and/or an autopilot may be engaged when the mental state of the operator indicates that the operator is inattentive.

Time-Frequency Distribution Analyses of Ku-Band Radar Doppler Echo Signals

NASA Astrophysics Data System (ADS)

Bujaković, Dimitrije; Andrić, Milenko; Bondžulić, Boban; Mitrović, Srđan; Simić, Slobodan

2015-03-01

Real radar echo signals of a pedestrian, vehicle and group of helicopters are analyzed in order to maximize signal energy around central Doppler frequency in time-frequency plane. An optimization, preserving this concentration, is suggested based on three well-known concentration measures. Various window functions and time-frequency distributions were optimization inputs. Conducted experiments on an analytic and three real signals have shown that energy concentration significantly depends on used time-frequency distribution and window function, for all three used criteria.

Real-time solar magnetograph operation system software design and user's guide

NASA Technical Reports Server (NTRS)

Wang, C.

1984-01-01

The Real Time Solar Magnetograph (RTSM) Operation system software design on PDP11/23+ is presented along with the User's Guide. The RTSM operation software is for real time instrumentation control, data collection and data management. The data is used for vector analysis, plotting or graphics display. The processed data is then easily compared with solar data from other sources, such as the Solar Maximum Mission (SMM).

Achieving AFRL Universal FADEC Vision With Open Architecture Addressing Capability and Obsolescence for Military and Commercial Applications (Preprint)

DTIC Science & Technology

2006-11-01

engines will involve a family of common components. It will consist of a real - time operating system and partitioned application software (AS...system will employ a standard hardware and software architecture. It will consist of a real time operating system and partitioned application...Inputs - Enables Large Cost Reduction 3. Software - FAA Certified Auto Code - Real Time Operating System - Commercial

Regression modeling and prediction of road sweeping brush load characteristics from finite element analysis and experimental results.

PubMed

Wang, Chong; Sun, Qun; Wahab, Magd Abdel; Zhang, Xingyu; Xu, Limin

2015-09-01

Rotary cup brushes mounted on each side of a road sweeper undertake heavy debris removal tasks but the characteristics have not been well known until recently. A Finite Element (FE) model that can analyze brush deformation and predict brush characteristics have been developed to investigate the sweeping efficiency and to assist the controller design. However, the FE model requires large amount of CPU time to simulate each brush design and operating scenario, which may affect its applications in a real-time system. This study develops a mathematical regression model to summarize the FE modeled results. The complex brush load characteristic curves were statistically analyzed to quantify the effects of cross-section, length, mounting angle, displacement and rotational speed etc. The data were then fitted by a multiple variable regression model using the maximum likelihood method. The fitted results showed good agreement with the FE analysis results and experimental results, suggesting that the mathematical regression model may be directly used in a real-time system to predict characteristics of different brushes under varying operating conditions. The methodology may also be used in the design and optimization of rotary brush tools. Copyright © 2015 Elsevier Ltd. All rights reserved.

An approach to a real-time distribution system

NASA Technical Reports Server (NTRS)

Kittle, Frank P., Jr.; Paddock, Eddie J.; Pocklington, Tony; Wang, Lui

1990-01-01

The requirements of a real-time data distribution system are to provide fast, reliable delivery of data from source to destination with little or no impact to the data source. In this particular case, the data sources are inside an operational environment, the Mission Control Center (MCC), and any workstation receiving data directly from the operational computer must conform to the software standards of the MCC. In order to supply data to development workstations outside of the MCC, it is necessary to use gateway computers that prevent unauthorized data transfer back to the operational computers. Many software programs produced on the development workstations are targeted for real-time operation. Therefore, these programs must migrate from the development workstation to the operational workstation. It is yet another requirement for the Data Distribution System to ensure smooth transition of the data interfaces for the application developers. A standard data interface model has already been set up for the operational environment, so the interface between the distribution system and the application software was developed to match that model as closely as possible. The system as a whole therefore allows the rapid development of real-time applications without impacting the data sources. In summary, this approach to a real-time data distribution system provides development users outside of the MCC with an interface to MCC real-time data sources. In addition, the data interface was developed with a flexible and portable software design. This design allows for the smooth transition of new real-time applications to the MCC operational environment.

Real options and asset valuation in competitive energy markets

NASA Astrophysics Data System (ADS)

Oduntan, Adekunle Richard

The focus of this work is to develop a robust valuation framework for physical power assets operating in competitive markets such as peaking or mid-merit thermal power plants and baseload power plants. The goal is to develop a modeling framework that can be adapted to different energy assets with different types of operating flexibilities and technical constraints and which can be employed for various purposes such as capital budgeting, business planning, risk management and strategic bidding planning among others. The valuation framework must also be able to capture the reality of power market rules and opportunities, as well as technical constraints of different assets. The modeling framework developed conceptualizes operating flexibilities of power assets as "switching options' whereby the asset operator decides at every decision point whether to switch from one operating mode to another mutually exclusive mode, within the limits of the equipment constraints of the asset. As a current decision to switch operating modes may affect future operating flexibilities of the asset and hence cash flows, a dynamic optimization framework is employed. The developed framework accounts for the uncertain nature of key value drivers by representing them with appropriate stochastic processes. Specifically, the framework developed conceptualizes the operation of a power asset as a multi-stage decision making problem where the operator has to make a decision at every stage to alter operating mode given currently available information about key value drivers. The problem is then solved dynamically by decomposing it into a series of two-stage sub-problems according to Bellman's optimality principle. The solution algorithm employed is the Least Squares Monte Carlo (LSM) method. The developed valuation framework was adapted for a gas-fired thermal power plant, a peaking hydroelectric power plant and a baseload power plant. This work built on previously published real options valuation methodologies for gas-fired thermal power plants by factoring in uncertainty from gas supply/consumption imbalance which is usually faced by gas-fired power generators. This source of uncertainty arises because of mismatch between natural gas and electricity wholesale markets. Natural gas markets in North America operate on a day-ahead basis while power plants are dispatched in real time. Inability of a power generator to match its gas supply and consumption in real time, leading to unauthorized gas over-run or under-run, attracts penalty charges from the gas supplier to the extent that the generator can not manage the imbalance through other means. By considering an illustrative power plant operating in Ontario, we show effects of gas-imbalance on dispatch strategies on a daily cycling operation basis and the resulting impact on net revenue. Similarly, we employ the developed valuation framework to value a peaking hydroelectric power plant. This application also builds on previous real options valuation work for peaking hydroelectric power plants by considering their operations in a joint energy and ancillary services market. Specifically, the valuation model is developed to capture the value of a peaking power plant whose owner has the flexibility to participate in a joint operating reserve market and an energy market, which is currently the case in the Ontario wholesale power market. The model factors in water inflow uncertainty into the reservoir forebay of a hydroelectric facility and also considers uncertain energy and operating reserve prices. The switching options considered include (i) a joint energy and operating reserve bid (ii) an energy only bid and (iii) a do nothing (idle) strategy. Being an energy limited power plant, by doing nothing at a decision interval, the power asset operator is able to timeshift scarce water for use at a future period when market situations are expected to be better. Finally, the developed valuation framework was employed to optimize life-cycle management decisions of a baseload power plant, such as a nuclear power plant. Given uncertainty of long-term value drivers, including power prices, equipment performance and the relationship between current life cycle spending and future equipment degradation, optimization is carried out with the objective of minimizing overall life-cycle related costs. These life-cycle costs include (i) lost revenue during planned and unplanned outages, (ii) potential costs of future equipment degradation due to inadequate preventative maintenance, and (iii) the direct costs of implementing the life-cycle projects. The switching options in this context include the option to shutdown the power plant in order to execute a given preventative maintenance and inspection project and the option to keep the option "alive" by choosing to delay a planned life-cycle activity.

Optimizing Wastewater Reuse in Agricultural Fields via Merging of Embedded Network Sensor Data and Flow and Transport Models Using Data Assimilation

NASA Astrophysics Data System (ADS)

Wu, C.; Margulis, S. A.

2007-12-01

Wastewater re-use via crop irrigation has the potential to be an effective means of wastewater disposal. However, nitrate in wastewater may contaminate groundwater if it does not decay before reaching the groundwater table. In order to dispose of wastewater while preventing long-term groundwater pollution, irrigation rates need to be optimized based on the current and predicted states of the soil, such as soil moisture content and/or nitrate concentration. A real-time soil states estimation system using the Ensemble Kalman Filter (EnKF) has been developed for application to a test bed for wastewater re-use in Palmdale, CA. This test bed, covered with alfalfa, is a 30-acre irrigation plot with a 200-meter long rotating pivot arm that irrigates the area with reclaimed wastewater. A sensor network is deployed in the soil near the surface. The data assimilation system has shown the ability to characterize soil states and fluxes from sparse measurements. The real-time estimation system will then be used to explore the potential feedback for optimizing the sprinkler operation (i.e. maximizing the magnitude of wastewater release while minimizing the ultimate groundwater pollution). In optimization models, soil states and fluxes can be regarded as functions of irrigation rate. Through optimization, the irrigation rate in a finite horizon can be maximized while still satisfying all criteria in soil states and fluxes to ensure the safety of groundwater. Since the data assimilation system provides reliable estimation of soil states and fluxes, it is expected to define the optimal irrigation rate with higher confidence compared to using models or sensors only.

Net-zero Building Cluster Simulations and On-line Energy Forecasting for Adaptive and Real-Time Control and Decisions

NASA Astrophysics Data System (ADS)

Li, Xiwang

Buildings consume about 41.1% of primary energy and 74% of the electricity in the U.S. Moreover, it is estimated by the National Energy Technology Laboratory that more than 1/4 of the 713 GW of U.S. electricity demand in 2010 could be dispatchable if only buildings could respond to that dispatch through advanced building energy control and operation strategies and smart grid infrastructure. In this study, it is envisioned that neighboring buildings will have the tendency to form a cluster, an open cyber-physical system to exploit the economic opportunities provided by a smart grid, distributed power generation, and storage devices. Through optimized demand management, these building clusters will then reduce overall primary energy consumption and peak time electricity consumption, and be more resilient to power disruptions. Therefore, this project seeks to develop a Net-zero building cluster simulation testbed and high fidelity energy forecasting models for adaptive and real-time control and decision making strategy development that can be used in a Net-zero building cluster. The following research activities are summarized in this thesis: 1) Development of a building cluster emulator for building cluster control and operation strategy assessment. 2) Development of a novel building energy forecasting methodology using active system identification and data fusion techniques. In this methodology, a systematic approach for building energy system characteristic evaluation, system excitation and model adaptation is included. The developed methodology is compared with other literature-reported building energy forecasting methods; 3) Development of the high fidelity on-line building cluster energy forecasting models, which includes energy forecasting models for buildings, PV panels, batteries and ice tank thermal storage systems 4) Small scale real building validation study to verify the performance of the developed building energy forecasting methodology. The outcomes of this thesis can be used for building cluster energy forecasting model development and model based control and operation optimization. The thesis concludes with a summary of the key outcomes of this research, as well as a list of recommendations for future work.

Optimizing and controlling earthmoving operations using spatial technologies

NASA Astrophysics Data System (ADS)

Alshibani, Adel

This thesis presents a model designed for optimizing, tracking, and controlling earthmoving operations. The proposed model utilizes, Genetic Algorithm (GA), Linear Programming (LP), and spatial technologies including Global Positioning Systems (GPS) and Geographic Information Systems (GIS) to support the management functions of the developed model. The model assists engineers and contractors in selecting near optimum crew formations in planning phase and during construction, using GA and LP supported by the Pathfinder Algorithm developed in a GIS environment. GA is used in conjunction with a set of rules developed to accelerate the optimization process and to avoid generating and evaluating hypothetical and unrealistic crew formations. LP is used to determine quantities of earth to be moved from different borrow pits and to be placed at different landfill sites to meet project constraints and to minimize the cost of these earthmoving operations. On the one hand, GPS is used for onsite data collection and for tracking construction equipment in near real-time. On the other hand, GIS is employed to automate data acquisition and to analyze the collected spatial data. The model is also capable of reconfiguring crew formations dynamically during the construction phase while site operations are in progress. The optimization of the crew formation considers: (1) construction time, (2) construction direct cost, or (3) construction total cost. The model is also capable of generating crew formations to meet, as close as possible, specified time and/or cost constraints. In addition, the model supports tracking and reporting of project progress utilizing the earned-value concept and the project ratio method with modifications that allow for more accurate forecasting of project time and cost at set future dates and at completion. The model is capable of generating graphical and tabular reports. The developed model has been implemented in prototype software, using Object-Oriented Programming, Microsoft Foundation Classes (MFC), and has been coded using visual C++ V.6. Microsoft Access is employed as database management system. The developed software operates in Microsoft windows' environment. Three example applications were analyzed to validate the development made and to illustrate the essential features of the developed model.

OPTIMIZED REAL-TIME CONTROL OF COMBINED SEWERAGE SYSTEMS: TWO CASE STUDIES

EPA Science Inventory

The paper presents results of two case studies of Real-Time Control (RTC) alternatives evaluations that were conducted on portions of sewerage systems near Paris, France and in Quebec City, Canada, respectively. The studies were performed at real-scale demonstration sites. RTC ...

23 CFR 511.311 - Real-time information program establishment.

Code of Federal Regulations, 2011 CFR

2011-04-01

... INFRASTRUCTURE MANAGEMENT REAL-TIME SYSTEM MANAGEMENT INFORMATION PROGRAM Real-Time System Management Information... operated by the State. In addition, the real-time information program shall complement current... 23 Highways 1 2011-04-01 2011-04-01 false Real-time information program establishment. 511.311...

23 CFR 511.311 - Real-time information program establishment.

Code of Federal Regulations, 2014 CFR

2014-04-01

... INFRASTRUCTURE MANAGEMENT REAL-TIME SYSTEM MANAGEMENT INFORMATION PROGRAM Real-Time System Management Information... operated by the State. In addition, the real-time information program shall complement current... 23 Highways 1 2014-04-01 2014-04-01 false Real-time information program establishment. 511.311...

23 CFR 511.311 - Real-time information program establishment.

Code of Federal Regulations, 2013 CFR

2013-04-01

... INFRASTRUCTURE MANAGEMENT REAL-TIME SYSTEM MANAGEMENT INFORMATION PROGRAM Real-Time System Management Information... operated by the State. In addition, the real-time information program shall complement current... 23 Highways 1 2013-04-01 2013-04-01 false Real-time information program establishment. 511.311...

23 CFR 511.311 - Real-time information program establishment.

Code of Federal Regulations, 2012 CFR

2012-04-01

... INFRASTRUCTURE MANAGEMENT REAL-TIME SYSTEM MANAGEMENT INFORMATION PROGRAM Real-Time System Management Information... operated by the State. In addition, the real-time information program shall complement current... 23 Highways 1 2012-04-01 2012-04-01 false Real-time information program establishment. 511.311...

Developing a cross-docking network design model under uncertain environment

NASA Astrophysics Data System (ADS)

Seyedhoseini, S. M.; Rashid, Reza; Teimoury, E.

2015-06-01

Cross-docking is a logistic concept, which plays an important role in supply chain management by decreasing inventory holding, order packing, transportation costs and delivery time. Paying attention to these concerns, and importance of the congestion in cross docks, we present a mixed-integer model to optimize the location and design of cross docks at the same time to minimize the total transportation and operating costs. The model combines queuing theory for design aspects, for that matter, we consider a network of cross docks and customers where two M/M/c queues have been represented to describe operations of indoor trucks and outdoor trucks in each cross dock. To prepare a perfect illustration for performance of the model, a real case also has been examined that indicated effectiveness of the proposed model.

NSTX-U Advances in Real-Time C++11 on Linux

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

Erickson, Keith G.

Programming languages like C and Ada combined with proprietary embedded operating systems have dominated the real-time application space for decades. The new C++11standard includes native, language-level support for concurrency, a required feature for any nontrivial event-oriented real-time software. Threads, Locks, and Atomics now exist to provide the necessary tools to build the structures that make up the foundation of a complex real-time system. The National Spherical Torus Experiment Upgrade (NSTX-U) at the Princeton Plasma Physics Laboratory (PPPL) is breaking new ground with the language as applied to the needs of fusion devices. A new Digital Coil Protection System (DCPS) willmore » serve as the main protection mechanism for the magnetic coils, and it is written entirely in C++11 running on Concurrent Computer Corporation's real-time operating system, RedHawk Linux. It runs over 600 algorithms in a 5 kHz control loop that determine whether or not to shut down operations before physical damage occurs. To accomplish this, NSTX-U engineers developed software tools that do not currently exist elsewhere, including real-time atomic synchronization, real-time containers, and a real-time logging framework. Together with a recent (and carefully configured) version of the GCC compiler, these tools enable data acquisition, processing, and output using a conventional operating system to meet a hard real-time deadline (that is, missing one periodic is a failure) of 200 microseconds.« less

NSTX-U Advances in Real-Time C++11 on Linux

DOE PAGES

Erickson, Keith G.

2015-08-14

Programming languages like C and Ada combined with proprietary embedded operating systems have dominated the real-time application space for decades. The new C++11standard includes native, language-level support for concurrency, a required feature for any nontrivial event-oriented real-time software. Threads, Locks, and Atomics now exist to provide the necessary tools to build the structures that make up the foundation of a complex real-time system. The National Spherical Torus Experiment Upgrade (NSTX-U) at the Princeton Plasma Physics Laboratory (PPPL) is breaking new ground with the language as applied to the needs of fusion devices. A new Digital Coil Protection System (DCPS) willmore » serve as the main protection mechanism for the magnetic coils, and it is written entirely in C++11 running on Concurrent Computer Corporation's real-time operating system, RedHawk Linux. It runs over 600 algorithms in a 5 kHz control loop that determine whether or not to shut down operations before physical damage occurs. To accomplish this, NSTX-U engineers developed software tools that do not currently exist elsewhere, including real-time atomic synchronization, real-time containers, and a real-time logging framework. Together with a recent (and carefully configured) version of the GCC compiler, these tools enable data acquisition, processing, and output using a conventional operating system to meet a hard real-time deadline (that is, missing one periodic is a failure) of 200 microseconds.« less

Incentive-Compatible Robust Line Planning

NASA Astrophysics Data System (ADS)

Bessas, Apostolos; Kontogiannis, Spyros; Zaroliagis, Christos

The problem of robust line planning requests for a set of origin-destination paths (lines) along with their frequencies in an underlying railway network infrastructure, which are robust to fluctuations of real-time parameters of the solution. In this work, we investigate a variant of robust line planning stemming from recent regulations in the railway sector that introduce competition and free railway markets, and set up a new application scenario: there is a (potentially large) number of line operators that have their lines fixed and operate as competing entities issuing frequency requests, while the management of the infrastructure itself remains the responsibility of a single entity, the network operator. The line operators are typically unwilling to reveal their true incentives, while the network operator strives to ensure a fair (or socially optimal) usage of the infrastructure, e.g., by maximizing the (unknown to him) aggregate incentives of the line operators.

Point-and-stare operation and high-speed image acquisition in real-time hyperspectral imaging

NASA Astrophysics Data System (ADS)

Driver, Richard D.; Bannon, David P.; Ciccone, Domenic; Hill, Sam L.

2010-04-01

The design and optical performance of a small-footprint, low-power, turnkey, Point-And-Stare hyperspectral analyzer, capable of fully automated field deployment in remote and harsh environments, is described. The unit is packaged for outdoor operation in an IP56 protected air-conditioned enclosure and includes a mechanically ruggedized fully reflective, aberration-corrected hyperspectral VNIR (400-1000 nm) spectrometer with a board-level detector optimized for point and stare operation, an on-board computer capable of full system data-acquisition and control, and a fully functioning internal hyperspectral calibration system for in-situ system spectral calibration and verification. Performance data on the unit under extremes of real-time survey operation and high spatial and high spectral resolution will be discussed. Hyperspectral acquisition including full parameter tracking is achieved by the addition of a fiber-optic based downwelling spectral channel for solar illumination tracking during hyperspectral acquisition and the use of other sensors for spatial and directional tracking to pinpoint view location. The system is mounted on a Pan-And-Tilt device, automatically controlled from the analyzer's on-board computer, making the HyperspecTM particularly adaptable for base security, border protection and remote deployments. A hyperspectral macro library has been developed to control hyperspectral image acquisition, system calibration and scene location control. The software allows the system to be operated in a fully automatic mode or under direct operator control through a GigE interface.

Optimal robust control strategy of a solid oxide fuel cell system

NASA Astrophysics Data System (ADS)

Wu, Xiaojuan; Gao, Danhui

2018-01-01

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

The French contribution to the voluntary observing ships network of sea surface salinity

NASA Astrophysics Data System (ADS)

Alory, G.; Delcroix, T.; Téchiné, P.; Diverrès, D.; Varillon, D.; Cravatte, S.; Gouriou, Y.; Grelet, J.; Jacquin, S.; Kestenare, E.; Maes, C.; Morrow, R.; Perrier, J.; Reverdin, G.; Roubaud, F.

2015-11-01

Sea Surface Salinity (SSS) is an essential climate variable that requires long term in situ observation. The French SSS Observation Service (SSS-OS) manages a network of Voluntary Observing Ships equipped with thermosalinographs (TSG). The network is global though more concentrated in the tropical Pacific and North Atlantic oceanic basins. The acquisition system is autonomous with real time transmission and is regularly serviced at harbor calls. There are distinct real time and delayed time processing chains. Real time processing includes automatic alerts to detect potential instrument problems, in case raw data are outside of climatic limits, and graphical monitoring tools. Delayed time processing relies on a dedicated software for attribution of data quality flags by visual inspection, and correction of TSG time series by comparison with daily water samples and collocated Argo data. A method for optimizing the automatic attribution of quality flags in real time, based on testing different thresholds for data deviation from climatology and retroactively comparing the resulting flags to delayed time flags, is presented. The SSS-OS real time data feed the Coriolis operational oceanography database, while the research-quality delayed time data can be extracted for selected time and geographical ranges through a graphical web interface. Delayed time data have been also combined with other SSS data sources to produce gridded files for the Pacific and Atlantic oceans. A short review of the research activities conducted with such data is given. It includes observation-based process-oriented and climate studies from regional to global scale as well as studies where in situ SSS is used for calibration/validation of models, coral proxies or satellite data.

The French Contribution to the Voluntary Observing Ships Network of Sea Surface Salinity

NASA Astrophysics Data System (ADS)

Delcroix, T. C.; Alory, G.; Téchiné, P.; Diverrès, D.; Varillon, D.; Cravatte, S. E.; Gouriou, Y.; Grelet, J.; Jacquin, S.; Kestenare, E.; Maes, C.; Morrow, R.; Perrier, J.; Reverdin, G. P.; Roubaud, F.

2016-02-01

Sea Surface Salinity (SSS) is an essential climate variable that requires long term in situ observation. The French SSS Observation Service (SSS-OS) manages a network of Voluntary Observing Ships equipped with thermosalinographs (TSG). The network is global though more concentrated in the tropical Pacific and North Atlantic oceanic basins. The acquisition system is autonomous with real time transmission and is regularly serviced at harbor calls. There are distinct real time and delayed time processing chains. Real time processing includes automatic alerts to detect potential instrument problems, in case raw data are outside of climatic limits, and graphical monitoring tools. Delayed time processing relies on a dedicated software for attribution of data quality flags by visual inspection, and correction of TSG time series by comparison with daily water samples and collocated Argo data. A method for optimizing the automatic attribution of quality flags in real time, based on testing different thresholds for data deviation from climatology and retroactively comparing the resulting flags to delayed time flags, is presented. The SSS-OS real time data feed the Coriolis operational oceanography database, while the research-quality delayed time data can be extracted for selected time and geographical ranges through a graphical web interface. Delayed time data have been also combined with other SSS data sources to produce gridded files for the Pacific and Atlantic oceans. A short review of the research activities conducted with such data is given. It includes observation-based process-oriented and climate studies from regional to global scale as well as studies where in situ SSS is used for calibration/validation of models, coral proxies or satellite data.

Evaluating Real-Time Platforms for Aircraft Prognostic Health Management Using Hardware-In-The-Loop

DTIC Science & Technology

2008-08-01

obtained when using HIL and a simulated load. Initially, noticeable differences are seen when comparing the results from each real - time operating system . However...same model in native Simulink. These results show that each real - time operating system can be configured to accurately run transient Simulink

Smart sensing to drive real-time loads scheduling algorithm in a domotic architecture

NASA Astrophysics Data System (ADS)

Santamaria, Amilcare Francesco; Raimondo, Pierfrancesco; De Rango, Floriano; Vaccaro, Andrea

2014-05-01

Nowadays the focus on power consumption represent a very important factor regarding the reduction of power consumption with correlated costs and the environmental sustainability problems. Automatic control load based on power consumption and use cycle represents the optimal solution to costs restraint. The purpose of these systems is to modulate the power request of electricity avoiding an unorganized work of the loads, using intelligent techniques to manage them based on real time scheduling algorithms. The goal is to coordinate a set of electrical loads to optimize energy costs and consumptions based on the stipulated contract terms. The proposed algorithm use two new main notions: priority driven loads and smart scheduling loads. The priority driven loads can be turned off (stand by) according to a priority policy established by the user if the consumption exceed a defined threshold, on the contrary smart scheduling loads are scheduled in a particular way to don't stop their Life Cycle (LC) safeguarding the devices functions or allowing the user to freely use the devices without the risk of exceeding the power threshold. The algorithm, using these two kind of notions and taking into account user requirements, manages loads activation and deactivation allowing the completion their operation cycle without exceeding the consumption threshold in an off-peak time range according to the electricity fare. This kind of logic is inspired by industrial lean manufacturing which focus is to minimize any kind of power waste optimizing the available resources.

EOS: A project to investigate the design and construction of real-time distributed embedded operating systems

NASA Technical Reports Server (NTRS)

Campbell, R. H.; Essick, R. B.; Grass, J.; Johnston, G.; Kenny, K.; Russo, V.

1986-01-01

The EOS project is investigating the design and construction of a family of real-time distributed embedded operating systems for reliable, distributed aerospace applications. Using the real-time programming techniques developed in co-operation with NASA in earlier research, the project staff is building a kernel for a multiple processor networked system. The first six months of the grant included a study of scheduling in an object-oriented system, the design philosophy of the kernel, and the architectural overview of the operating system. In this report, the operating system and kernel concepts are described. An environment for the experiments has been built and several of the key concepts of the system have been prototyped. The kernel and operating system is intended to support future experimental studies in multiprocessing, load-balancing, routing, software fault-tolerance, distributed data base design, and real-time processing.

Optimal causal filtering for 1 /fα-type noise in single-electrode EEG signals.

PubMed

Paris, Alan; Atia, George; Vosoughi, Azadeh; Berman, Stephen A

2016-08-01

Understanding the mode of generation and the statistical structure of neurological noise is one of the central problems of biomedical signal processing. We have developed a broad class of abstract biological noise sources we call hidden simplicial tissues. In the simplest cases, such tissue emits what we have named generalized van der Ziel-McWhorter (GVZM) noise which has a roughly 1/fα spectral roll-off. Our previous work focused on the statistical structure of GVZM frequency spectra. However, causality of processing operations (i.e., dependence only on the past) is an essential requirement for real-time applications to seizure detection and brain-computer interfacing. In this paper we outline the theoretical background for optimal causal time-domain filtering of deterministic signals embedded in GVZM noise. We present some of our early findings concerning the optimal filtering of EEG signals for the detection of steady-state visual evoked potential (SSVEP) responses and indicate the next steps in our ongoing research.

Towards Optimal Operation of the Reservoir System in Upper Yellow River: Incorporating Long- and Short-term Operations and Using Rolling Updated Hydrologic Forecast Information

NASA Astrophysics Data System (ADS)

Si, Y.; Li, X.; Li, T.; Huang, Y.; Yin, D.

2016-12-01

The cascade reservoirs in Upper Yellow River (UYR), one of the largest hydropower bases in China, play a vital role in peak load and frequency regulation for Northwest China Power Grid. The joint operation of this system has been put forward for years whereas has not come into effect due to management difficulties and inflow uncertainties, and thus there is still considerable improvement room for hydropower production. This study presents a decision support framework incorporating long- and short-term operation of the reservoir system. For long-term operation, we maximize hydropower production of the reservoir system using historical hydrological data of multiple years, and derive operating rule curves for storage reservoirs. For short-term operation, we develop a program consisting of three modules, namely hydrologic forecast module, reservoir operation module and coordination module. The coordination module is responsible for calling the hydrologic forecast module to acquire predicted inflow within a short-term horizon, and transferring the information to the reservoir operation module to generate optimal release decision. With the hydrologic forecast information updated, the rolling short-term optimization is iterated until the end of operation period, where the long-term operating curves serve as the ending storage target. As an application, the Digital Yellow River Integrated Model (referred to as "DYRIM", which is specially designed for runoff-sediment simulation in the Yellow River basin by Tsinghua University) is used in the hydrologic forecast module, and the successive linear programming (SLP) in the reservoir operation module. The application in the reservoir system of UYR demonstrates that the framework can effectively support real-time decision making, and ensure both computational accuracy and speed. Furthermore, it is worth noting that the general framework can be extended to any other reservoir system with any or combination of hydrological model(s) to forecast and any solver to optimize the operation of reservoir system.

Optimizing the Detection of Wakeful and Sleep-Like States for Future Electrocorticographic Brain Computer Interface Applications.

PubMed

Pahwa, Mrinal; Kusner, Matthew; Hacker, Carl D; Bundy, David T; Weinberger, Kilian Q; Leuthardt, Eric C

2015-01-01

Previous studies suggest stable and robust control of a brain-computer interface (BCI) can be achieved using electrocorticography (ECoG). Translation of this technology from the laboratory to the real world requires additional methods that allow users operate their ECoG-based BCI autonomously. In such an environment, users must be able to perform all tasks currently performed by the experimenter, including manually switching the BCI system on/off. Although a simple task, it can be challenging for target users (e.g., individuals with tetraplegia) due to severe motor disability. In this study, we present an automated and practical strategy to switch a BCI system on or off based on the cognitive state of the user. Using a logistic regression, we built probabilistic models that utilized sub-dural ECoG signals from humans to estimate in pseudo real-time whether a person is awake or in a sleep-like state, and subsequently, whether to turn a BCI system on or off. Furthermore, we constrained these models to identify the optimal anatomical and spectral parameters for delineating states. Other methods exist to differentiate wake and sleep states using ECoG, but none account for practical requirements of BCI application, such as minimizing the size of an ECoG implant and predicting states in real time. Our results demonstrate that, across 4 individuals, wakeful and sleep-like states can be classified with over 80% accuracy (up to 92%) in pseudo real-time using high gamma (70-110 Hz) band limited power from only 5 electrodes (platinum discs with a diameter of 2.3 mm) located above the precentral and posterior superior temporal gyrus.

The University of Colorado OSO-8 spectrometer experiment. IV - Mission operations

NASA Technical Reports Server (NTRS)

Hansen, E. R.; Bruner, E. C., Jr.

1979-01-01

The remote operation of two high-resolution ultraviolet spectrometers on the OSO-8 satellite is discussed. Mission operations enabled scientific observers to plan observations based on current solar data, interact with the observing program using real- or near real-time data and commands, evaluate quick-look instrument data, and analyze the observations for publication. During routine operations, experiments were planned a day prior to their execution, and the data from these experiments received a day later. When a shorter turnaround was required, a real-time mode was available. Here, the real-time data and command links into the remote control center were used to evaluate experiment operation and make satellite pointing or instrument configuration changes with a 1-90 minute turnaround.

System-level power optimization for real-time distributed embedded systems

NASA Astrophysics Data System (ADS)

Luo, Jiong

Power optimization is one of the crucial design considerations for modern electronic systems. In this thesis, we present several system-level power optimization techniques for real-time distributed embedded systems, based on dynamic voltage scaling, dynamic power management, and management of peak power and variance of the power profile. Dynamic voltage scaling has been widely acknowledged as an important and powerful technique to trade off dynamic power consumption and delay. Efficient dynamic voltage scaling requires effective variable-voltage scheduling mechanisms that can adjust voltages and clock frequencies adaptively based on workloads and timing constraints. For this purpose, we propose static variable-voltage scheduling algorithms utilizing criticalpath driven timing analysis for the case when tasks are assumed to have uniform switching activities, as well as energy-gradient driven slack allocation for a more general scenario. The proposed techniques can achieve closeto-optimal power savings with very low computational complexity, without violating any real-time constraints. We also present algorithms for power-efficient joint scheduling of multi-rate periodic task graphs along with soft aperiodic tasks. The power issue is addressed through both dynamic voltage scaling and power management. Periodic task graphs are scheduled statically. Flexibility is introduced into the static schedule to allow the on-line scheduler to make local changes to PE schedules through resource reclaiming and slack stealing, without interfering with the validity of the global schedule. We provide a unified framework in which the response times of aperiodic tasks and power consumption are dynamically optimized simultaneously. Interconnection network fabrics point to a new generation of power-efficient and scalable interconnection architectures for distributed embedded systems. As the system bandwidth continues to increase, interconnection networks become power/energy limited as well. Variable-frequency links have been designed by circuit designers for both parallel and serial links, which can adaptively regulate the supply voltage of transceivers to a desired link frequency, to exploit the variations in bandwidth requirement for power savings. We propose solutions for simultaneous dynamic voltage scaling of processors and links. The proposed solution considers real-time scheduling, flow control, and packet routing jointly. It can trade off the power consumption on processors and communication links via efficient slack allocation, and lead to more power savings than dynamic voltage scaling on processors alone. For battery-operated systems, the battery lifespan is an important concern. Due to the effects of discharge rate and battery recovery, the discharge pattern of batteries has an impact on the battery lifespan. Battery models indicate that even under the same average power consumption, reducing peak power current and variance in the power profile can increase the battery efficiency and thereby prolong battery lifetime. To take advantage of these effects, we propose battery-driven scheduling techniques for embedded applications, to reduce the peak power and the variance in the power profile of the overall system under real-time constraints. The proposed scheduling algorithms are also beneficial in addressing reliability and signal integrity concerns by effectively controlling peak power and variance of the power profile.

The expanded role of computers in Space Station Freedom real-time operations

NASA Technical Reports Server (NTRS)

Crawford, R. Paul; Cannon, Kathleen V.

1990-01-01

The challenges that NASA and its international partners face in their real-time operation of the Space Station Freedom necessitate an increased role on the part of computers. In building the operational concepts concerning the role of the computer, the Space Station program is using lessons learned experience from past programs, knowledge of the needs of future space programs, and technical advances in the computer industry. The computer is expected to contribute most significantly in real-time operations by forming a versatile operating architecture, a responsive operations tool set, and an environment that promotes effective and efficient utilization of Space Station Freedom resources.

Conjunctively optimizing flash flood control and water quality in urban water reservoirs by model predictive control and dynamic emulation

NASA Astrophysics Data System (ADS)

Galelli, Stefano; Goedbloed, Albert; Schmitter, Petra; Castelletti, Andrea

2014-05-01

Urban water reservoirs are a viable adaptation option to account for increasing drinking water demand of urbanized areas as they allow storage and re-use of water that is normally lost. In addition, the direct availability of freshwater reduces pumping costs and diversifies the portfolios of drinking water supply. Yet, these benefits have an associated twofold cost. Firstly, the presence of large, impervious areas increases the hydraulic efficiency of urban catchments, with short time of concentration, increased runoff rates, losses of infiltration and baseflow, and higher risk of flash floods. Secondly, the high concentration of nutrients and sediments characterizing urban discharges is likely to cause water quality problems. In this study we propose a new control scheme combining Model Predictive Control (MPC), hydro-meteorological forecasts and dynamic model emulation to design real-time operating policies that conjunctively optimize water quantity and quality targets. The main advantage of this scheme stands in its capability of exploiting real-time hydro-meteorological forecasts, which are crucial in such fast-varying systems. In addition, the reduced computational requests of the MPC scheme allows coupling it with dynamic emulators of water quality processes. The approach is demonstrated on Marina Reservoir, a multi-purpose reservoir located in the heart of Singapore and characterized by a large, highly urbanized catchment with a short (i.e. approximately one hour) time of concentration. Results show that the MPC scheme, coupled with a water quality emulator, provides a good compromise between different operating objectives, namely flood risk reduction, drinking water supply and salinity control. Finally, the scheme is used to assess the effect of source control measures (e.g. green roofs) aimed at restoring the natural hydrological regime of Marina Reservoir catchment.

Imaging multicellular specimens with real-time optimized tiling light-sheet selective plane illumination microscopy

PubMed Central

Fu, Qinyi; Martin, Benjamin L.; Matus, David Q.; Gao, Liang

2016-01-01

Despite the progress made in selective plane illumination microscopy, high-resolution 3D live imaging of multicellular specimens remains challenging. Tiling light-sheet selective plane illumination microscopy (TLS-SPIM) with real-time light-sheet optimization was developed to respond to the challenge. It improves the 3D imaging ability of SPIM in resolving complex structures and optimizes SPIM live imaging performance by using a real-time adjustable tiling light sheet and creating a flexible compromise between spatial and temporal resolution. We demonstrate the 3D live imaging ability of TLS-SPIM by imaging cellular and subcellular behaviours in live C. elegans and zebrafish embryos, and show how TLS-SPIM can facilitate cell biology research in multicellular specimens by studying left-right symmetry breaking behaviour of C. elegans embryos. PMID:27004937

Optimizing Tsunami Forecast Model Accuracy

NASA Astrophysics Data System (ADS)

Whitmore, P.; Nyland, D. L.; Huang, P. Y.

2015-12-01

Recent tsunamis provide a means to determine the accuracy that can be expected of real-time tsunami forecast models. Forecast accuracy using two different tsunami forecast models are compared for seven events since 2006 based on both real-time application and optimized, after-the-fact "forecasts". Lessons learned by comparing the forecast accuracy determined during an event to modified applications of the models after-the-fact provide improved methods for real-time forecasting for future events. Variables such as source definition, data assimilation, and model scaling factors are examined to optimize forecast accuracy. Forecast accuracy is also compared for direct forward modeling based on earthquake source parameters versus accuracy obtained by assimilating sea level data into the forecast model. Results show that including assimilated sea level data into the models increases accuracy by approximately 15% for the events examined.

Maximizing the productivity of the microalgae Scenedesmus AMDD cultivated in a continuous photobioreactor using an online flow rate control.

PubMed

McGinn, Patrick J; MacQuarrie, Scott P; Choi, Jerome; Tartakovsky, Boris

2017-01-01

In this study, production of the microalga Scenedesmus AMDD in a 300 L continuous flow photobioreactor was maximized using an online flow (dilution rate) control algorithm. To enable online control, biomass concentration was estimated in real time by measuring chlorophyll-related culture fluorescence. A simple microalgae growth model was developed and used to solve the optimization problem aimed at maximizing the photobioreactor productivity. When optimally controlled, Scenedesmus AMDD culture demonstrated an average volumetric biomass productivity of 0.11 g L -1  d -1 over a 25 day cultivation period, equivalent to a 70 % performance improvement compared to the same photobioreactor operated as a turbidostat. The proposed approach for optimizing photobioreactor flow can be adapted to a broad range of microalgae cultivation systems.

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

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.

An Optimization Framework for Driver Feedback Systems

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

Malikopoulos, Andreas; Aguilar, Juan P.

2013-01-01

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

Design and Implementation of a Video-Zoom Driven Digital Audio-Zoom System for Portable Digital Imaging Devices

NASA Astrophysics Data System (ADS)

Park, Nam In; Kim, Seon Man; Kim, Hong Kook; Kim, Ji Woon; Kim, Myeong Bo; Yun, Su Won

In this paper, we propose a video-zoom driven audio-zoom algorithm in order to provide audio zooming effects in accordance with the degree of video-zoom. The proposed algorithm is designed based on a super-directive beamformer operating with a 4-channel microphone system, in conjunction with a soft masking process that considers the phase differences between microphones. Thus, the audio-zoom processed signal is obtained by multiplying an audio gain derived from a video-zoom level by the masked signal. After all, a real-time audio-zoom system is implemented on an ARM-CORETEX-A8 having a clock speed of 600 MHz after different levels of optimization are performed such as algorithmic level, C-code, and memory optimizations. To evaluate the complexity of the proposed real-time audio-zoom system, test data whose length is 21.3 seconds long is sampled at 48 kHz. As a result, it is shown from the experiments that the processing time for the proposed audio-zoom system occupies 14.6% or less of the ARM clock cycles. It is also shown from the experimental results performed in a semi-anechoic chamber that the signal with the front direction can be amplified by approximately 10 dB compared to the other directions.

Low-sensitivity H ∞ filter design for linear delta operator systems with sampling time jitter

NASA Astrophysics Data System (ADS)

Guo, Xiang-Gui; Yang, Guang-Hong

2012-04-01

This article is concerned with the problem of designing H ∞ filters for a class of linear discrete-time systems with low-sensitivity to sampling time jitter via delta operator approach. Delta-domain model is used to avoid the inherent numerical ill-condition resulting from the use of the standard shift-domain model at high sampling rates. Based on projection lemma in combination with the descriptor system approach often used to solve problems related to delay, a novel bounded real lemma with three slack variables for delta operator systems is presented. A sensitivity approach based on this novel lemma is proposed to mitigate the effects of sampling time jitter on system performance. Then, the problem of designing a low-sensitivity filter can be reduced to a convex optimisation problem. An important consideration in the design of correlation filters is the optimal trade-off between the standard H ∞ criterion and the sensitivity of the transfer function with respect to sampling time jitter. Finally, a numerical example demonstrating the validity of the proposed design method is given.

Design and implementation of real-time wireless projection system based on ARM embedded system

NASA Astrophysics Data System (ADS)

Long, Zhaohua; Tang, Hao; Huang, Junhua

2018-04-01

Aiming at the shortage of existing real-time screen sharing system, a real-time wireless projection system is proposed in this paper. Based on the proposed system, a weight-based frame deletion strategy combined sampling time period and data variation is proposed. By implementing the system on the hardware platform, the results show that the system can achieve good results. The weight-based strategy can improve the service quality, reduce the delay and optimize the real-time customer service system [1].

Design a software real-time operation platform for wave piercing catamarans motion control using linear quadratic regulator based genetic algorithm.

PubMed

Liang, Lihua; Yuan, Jia; Zhang, Songtao; Zhao, Peng

2018-01-01

This work presents optimal linear quadratic regulator (LQR) based on genetic algorithm (GA) to solve the two degrees of freedom (2 DoF) motion control problem in head seas for wave piercing catamarans (WPC). The proposed LQR based GA control strategy is to select optimal weighting matrices (Q and R). The seakeeping performance of WPC based on proposed algorithm is challenged because of multi-input multi-output (MIMO) system of uncertain coefficient problems. Besides the kinematical constraint problems of WPC, the external conditions must be considered, like the sea disturbance and the actuators (a T-foil and two flaps) control. Moreover, this paper describes the MATLAB and LabVIEW software plats to simulate the reduction effects of WPC. Finally, the real-time (RT) NI CompactRIO embedded controller is selected to test the effectiveness of the actuators based on proposed techniques. In conclusion, simulation and experimental results prove the correctness of the proposed algorithm. The percentage of heave and pitch reductions are more than 18% in different high speeds and bad sea conditions. And the results also verify the feasibility of NI CompactRIO embedded controller.

Design a software real-time operation platform for wave piercing catamarans motion control using linear quadratic regulator based genetic algorithm

PubMed Central

Liang, Lihua; Zhang, Songtao; Zhao, Peng

2018-01-01

This work presents optimal linear quadratic regulator (LQR) based on genetic algorithm (GA) to solve the two degrees of freedom (2 DoF) motion control problem in head seas for wave piercing catamarans (WPC). The proposed LQR based GA control strategy is to select optimal weighting matrices (Q and R). The seakeeping performance of WPC based on proposed algorithm is challenged because of multi-input multi-output (MIMO) system of uncertain coefficient problems. Besides the kinematical constraint problems of WPC, the external conditions must be considered, like the sea disturbance and the actuators (a T-foil and two flaps) control. Moreover, this paper describes the MATLAB and LabVIEW software plats to simulate the reduction effects of WPC. Finally, the real-time (RT) NI CompactRIO embedded controller is selected to test the effectiveness of the actuators based on proposed techniques. In conclusion, simulation and experimental results prove the correctness of the proposed algorithm. The percentage of heave and pitch reductions are more than 18% in different high speeds and bad sea conditions. And the results also verify the feasibility of NI CompactRIO embedded controller. PMID:29709008

Computationally efficient modeling of proprioceptive signals in the upper limb for prostheses: a simulation study

PubMed Central

Williams, Ian; Constandinou, Timothy G.

2014-01-01

Accurate models of proprioceptive neural patterns could 1 day play an important role in the creation of an intuitive proprioceptive neural prosthesis for amputees. This paper looks at combining efficient implementations of biomechanical and proprioceptor models in order to generate signals that mimic human muscular proprioceptive patterns for future experimental work in prosthesis feedback. A neuro-musculoskeletal model of the upper limb with 7 degrees of freedom and 17 muscles is presented and generates real time estimates of muscle spindle and Golgi Tendon Organ neural firing patterns. Unlike previous neuro-musculoskeletal models, muscle activation and excitation levels are unknowns in this application and an inverse dynamics tool (static optimization) is integrated to estimate these variables. A proprioceptive prosthesis will need to be portable and this is incompatible with the computationally demanding nature of standard biomechanical and proprioceptor modeling. This paper uses and proposes a number of approximations and optimizations to make real time operation on portable hardware feasible. Finally technical obstacles to mimicking natural feedback for an intuitive proprioceptive prosthesis, as well as issues and limitations with existing models, are identified and discussed. PMID:25009463

Fast, Safe, Propellant-Efficient Spacecraft Motion Planning Under Clohessy-Wiltshire-Hill Dynamics

NASA Technical Reports Server (NTRS)

Starek, Joseph A.; Schmerling, Edward; Maher, Gabriel D.; Barbee, Brent W.; Pavone, Marco

2016-01-01

This paper presents a sampling-based motion planning algorithm for real-time and propellant-optimized autonomous spacecraft trajectory generation in near-circular orbits. Specifically, this paper leverages recent algorithmic advances in the field of robot motion planning to the problem of impulsively actuated, propellant- optimized rendezvous and proximity operations under the Clohessy-Wiltshire-Hill dynamics model. The approach calls upon a modified version of the FMT* algorithm to grow a set of feasible trajectories over a deterministic, low-dispersion set of sample points covering the free state space. To enforce safety, the tree is only grown over the subset of actively safe samples, from which there exists a feasible one-burn collision-avoidance maneuver that can safely circularize the spacecraft orbit along its coasting arc under a given set of potential thruster failures. Key features of the proposed algorithm include 1) theoretical guarantees in terms of trajectory safety and performance, 2) amenability to real-time implementation, and 3) generality, in the sense that a large class of constraints can be handled directly. As a result, the proposed algorithm offers the potential for widespread application, ranging from on-orbit satellite servicing to orbital debris removal and autonomous inspection missions.

Expert system and process optimization techniques for real-time monitoring and control of plasma processes

NASA Astrophysics Data System (ADS)

Cheng, Jie; Qian, Zhaogang; Irani, Keki B.; Etemad, Hossein; Elta, Michael E.

1991-03-01

To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).

Determining the optimal window length for pattern recognition-based myoelectric control: balancing the competing effects of classification error and controller delay.

PubMed

Smith, Lauren H; Hargrove, Levi J; Lock, Blair A; Kuiken, Todd A

2011-04-01

Pattern recognition-based control of myoelectric prostheses has shown great promise in research environments, but has not been optimized for use in a clinical setting. To explore the relationship between classification error, controller delay, and real-time controllability, 13 able-bodied subjects were trained to operate a virtual upper-limb prosthesis using pattern recognition of electromyogram (EMG) signals. Classification error and controller delay were varied by training different classifiers with a variety of analysis window lengths ranging from 50 to 550 ms and either two or four EMG input channels. Offline analysis showed that classification error decreased with longer window lengths (p < 0.01 ). Real-time controllability was evaluated with the target achievement control (TAC) test, which prompted users to maneuver the virtual prosthesis into various target postures. The results indicated that user performance improved with lower classification error (p < 0.01 ) and was reduced with longer controller delay (p < 0.01 ), as determined by the window length. Therefore, both of these effects should be considered when choosing a window length; it may be beneficial to increase the window length if this results in a reduced classification error, despite the corresponding increase in controller delay. For the system employed in this study, the optimal window length was found to be between 150 and 250 ms, which is within acceptable controller delays for conventional multistate amplitude controllers.

Operationalizing the Space Weather Modeling Framework: Challenges and Resolutions

NASA Astrophysics Data System (ADS)

Welling, D. T.; Gombosi, T. I.; Toth, G.; Singer, H. J.; Millward, G. H.; Balch, C. C.; Cash, M. D.

2016-12-01

Predicting ground-based magnetic perturbations is a critical step towards specifying and predicting geomagnetically induced currents (GICs) in high voltage transmission lines. Currently, the Space Weather Modeling Framework (SWMF), a flexible modeling framework for simulating the multi-scale space environment, is being transitioned from research to operational use (R2O) by NOAA's Space Weather Prediction Center. Upon completion of this transition, the SWMF will provide localized time-varying magnetic field (dB/dt) predictions using real-time solar wind observations from L1 and the F10.7 proxy for EUV as model input. This presentation chronicles the challenges encountered during the R2O transition of the SWMF. Because operations relies on frequent calculations of global surface dB/dt, new optimizations were required to keep the model running faster than real time. Additionally, several singular situations arose during the 30-day robustness test that required immediate attention. Solutions and strategies for overcoming these issues will be presented. This includes new failsafe options for code execution, new physics and coupling parameters, and the development of an automated validation suite that allows us to monitor performance with code evolution. Finally, the operations-to-research (O2R) impact on SWMF-related research is presented. The lessons learned from this work are valuable and instructive for the space weather community as further R2O progress is made.

Real-Time Optimization in Complex Stochastic Environment

DTIC Science & Technology

2015-06-24

simpler ones, thus addressing scalability and the limited resources of networked wireless devices. This, however, comes at the expense of increased...Maximization of Wireless Sensor Networks with Non-ideal Batteries”, IEEE Trans. on Control of Network Systems, Vol. 1, 1, pp. 86-98, 2014. [27...C.G., “Optimal Energy-Efficient Downlink Transmission Scheduling for Real-Time Wireless Networks ”, subm. to IEEE Trans. on Control of Network Systems

Optimized Real-Time Control of Combined Sewerage Systems: Two Case Studies (Proceedings Paper)

EPA Science Inventory

The paper presents results of two case studies of Real-Time Control (RTC) alternatives evaluations that were conducted on portions of sewerage systems near Paris, France and in Quebec City, Canada, respectively. The studies were performed at real-scale demonstration sites. RTC al...

Application of tabu search to deterministic and stochastic optimization problems

NASA Astrophysics Data System (ADS)

Gurtuna, Ozgur

During the past two decades, advances in computer science and operations research have resulted in many new optimization methods for tackling complex decision-making problems. One such method, tabu search, forms the basis of this thesis. Tabu search is a very versatile optimization heuristic that can be used for solving many different types of optimization problems. Another research area, real options, has also gained considerable momentum during the last two decades. Real options analysis is emerging as a robust and powerful method for tackling decision-making problems under uncertainty. Although the theoretical foundations of real options are well-established and significant progress has been made in the theory side, applications are lagging behind. A strong emphasis on practical applications and a multidisciplinary approach form the basic rationale of this thesis. The fundamental concepts and ideas behind tabu search and real options are investigated in order to provide a concise overview of the theory supporting both of these two fields. This theoretical overview feeds into the design and development of algorithms that are used to solve three different problems. The first problem examined is a deterministic one: finding the optimal servicing tours that minimize energy and/or duration of missions for servicing satellites around Earth's orbit. Due to the nature of the space environment, this problem is modeled as a time-dependent, moving-target optimization problem. Two solution methods are developed: an exhaustive method for smaller problem instances, and a method based on tabu search for larger ones. The second and third problems are related to decision-making under uncertainty. In the second problem, tabu search and real options are investigated together within the context of a stochastic optimization problem: option valuation. By merging tabu search and Monte Carlo simulation, a new method for studying options, Tabu Search Monte Carlo (TSMC) method, is developed. The theoretical underpinnings of the TSMC method and the flow of the algorithm are explained. Its performance is compared to other existing methods for financial option valuation. In the third, and final, problem, TSMC method is used to determine the conditions of feasibility for hybrid electric vehicles and fuel cell vehicles. There are many uncertainties related to the technologies and markets associated with new generation passenger vehicles. These uncertainties are analyzed in order to determine the conditions in which new generation vehicles can compete with established technologies.

Singular perturbation techniques for real time aircraft trajectory optimization and control

NASA Technical Reports Server (NTRS)

Calise, A. J.; Moerder, D. D.

1982-01-01

The usefulness of singular perturbation methods for developing real time computer algorithms to control and optimize aircraft flight trajectories is examined. A minimum time intercept problem using F-8 aerodynamic and propulsion data is used as a baseline. This provides a framework within which issues relating to problem formulation, solution methodology and real time implementation are examined. Theoretical questions relating to separability of dynamics are addressed. With respect to implementation, situations leading to numerical singularities are identified, and procedures for dealing with them are outlined. Also, particular attention is given to identifying quantities that can be precomputed and stored, thus greatly reducing the on-board computational load. Numerical results are given to illustrate the minimum time algorithm, and the resulting flight paths. An estimate is given for execution time and storage requirements.

Real-Time Imaging with a Pulsed Coherent CO, Laser Radar

DTIC Science & Technology

1997-01-01

30 joule) transmitted energy levels has just begun. The FLD program will conclude in 1997 with the demonstration of a full-up, real - time operating system . This...The master system and VMEbus controller is an off-the-shelf controller based on the Motorola 68040 processor running the VxWorks real time operating system . Application

Intelligence Community Forum

DTIC Science & Technology

2008-11-05

Description Operationally Feasible? EEG ms ms cm Measures electrical activity in the brain. Practical tool for applications - real time monitoring or...Cognitive Systems Device Development & Processing Methods Brain activity can be monitored in real-time in operational environments with EEG Brain...biological and cognitive findings about the user to customize the learning environment Neurofeedback • Present the user with real-time feedback

Modeling Reservoir-River Networks in Support of Optimizing Seasonal-Scale Reservoir Operations

NASA Astrophysics Data System (ADS)

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

2011-12-01

HydroSCOPE (Hydropower Seasonal Concurrent Optimization of Power and the Environment) is a seasonal time-scale tool for scenario analysis and optimization of reservoir-river networks. Developed in MATLAB, HydroSCOPE is an object-oriented model that simulates basin-scale dynamics with an objective of optimizing reservoir operations to maximize revenue from power generation, reliability in the water supply, environmental performance, and flood control. HydroSCOPE is part of a larger toolset that is being developed through a Department of Energy multi-laboratory project. This project's goal is to provide conventional hydropower decision makers with better information to execute their day-ahead and seasonal operations and planning activities by integrating water balance and operational dynamics across a wide range of spatial and temporal scales. This presentation details the modeling approach and functionality of HydroSCOPE. HydroSCOPE consists of a river-reservoir network model and an optimization routine. The river-reservoir network model simulates the heat and water balance of river-reservoir networks for time-scales up to one year. The optimization routine software, DAKOTA (Design Analysis Kit for Optimization and Terascale Applications - dakota.sandia.gov), is seamlessly linked to the network model and is used to optimize daily volumetric releases from the reservoirs to best meet a set of user-defined constraints, such as maximizing revenue while minimizing environmental violations. The network model uses 1-D approximations for both the reservoirs and river reaches and is able to account for surface and sediment heat exchange as well as ice dynamics for both models. The reservoir model also accounts for inflow, density, and withdrawal zone mixing, and diffusive heat exchange. Routing for the river reaches is accomplished using a modified Muskingum-Cunge approach that automatically calculates the internal timestep and sub-reach lengths to match the conditions of each timestep and minimize computational overhead. Power generation for each reservoir is estimated using a 2-dimensional regression that accounts for both the available head and turbine efficiency. The object-oriented architecture makes run configuration easy to update. The dynamic model inputs include inflow and meteorological forecasts while static inputs include bathymetry data, reservoir and power generation characteristics, and topological descriptors. Ensemble forecasts of hydrological and meteorological conditions are supplied in real-time by Pacific Northwest National Laboratory and are used as a proxy for uncertainty, which is carried through the simulation and optimization process to produce output that describes the probability that different operational scenario's will be optimal. The full toolset, which includes HydroSCOPE, is currently being tested on the Feather River system in Northern California and the Upper Colorado Storage Project.

A selective laser sintering guide for transferring a virtual plan to real time surgery in composite mandibular reconstruction with free fibula osseous flaps.

PubMed

Leiggener, C; Messo, E; Thor, A; Zeilhofer, H-F; Hirsch, J-M

2009-02-01

The free fibular flap is the standard procedure for reconstructing mandibular defects. The graft has to be contoured to fit the defect so preoperative planning is required. The systems used previously do not allow transfer of the surgical plan to the operation room in an optimal way. The authors present a method to bring the virtual plan to real time surgery using a rapid prototyping guide. Planning was conducted using the Surgicase CMF software simulating surgery on a workstation. The osteotomies were translated into a rapid prototyping guide, sterilised and applied during surgery on the fibula allowing for the osteotomies and osteosynthesis to be performed with intact circulation. During reconstruction the authors were able to choose the best site for the osteotomies regarding circulation and as a result increased the precision and speed of treatment.

Monitoring of Overhead Transmission Lines: A Review from the Perspective of Contactless Technologies

NASA Astrophysics Data System (ADS)

Khawaja, Arsalan Habib; Huang, Qi; Khan, Zeashan Hameed

2017-12-01

This paper describes a comprehensive review of non-contact technologies for overhead power transmission lines. Due to ever increasing emphasis on reducing accidents and speeding up diagnosis for automatically controlled grids, real time remote sensing and actuation is the new horizon for smart grid implementation. The technology overview with emphasis on the practical implementation of advanced non-contact technologies is discussed in this paper while considering optimization of the high voltage transmission lines parameters. In case of fault, the voltage and the current exceed limits of operation and hence real time reporting for control and diagnosis is a critical requirement. This paper aims to form a strong foundation for control and diagnosis of future power distribution systems so that a practitioner or researcher can make choices for a workable solution in smart grid implementation based on non-contact sensing.

Adaptive DIT-Based Fringe Tracking and Prediction at IOTA

NASA Technical Reports Server (NTRS)

Wilson, Edward; Pedretti, Ettore; Bregman, Jesse; Mah, Robert W.; Traub, Wesley A.

2004-01-01

An automatic fringe tracking system has been developed and implemented at the Infrared Optical Telescope Array (IOTA). In testing during May 2002, the system successfully minimized the optical path differences (OPDs) for all three baselines at IOTA. Based on sliding window discrete Fourier transform (DFT) calculations that were optimized for computational efficiency and robustness to atmospheric disturbances, the algorithm has also been tested extensively on off-line data. Implemented in ANSI C on the 266 MHZ PowerPC processor running the VxWorks real-time operating system, the algorithm runs in approximately 2.0 milliseconds per scan (including all three interferograms), using the science camera and piezo scanners to measure and correct the OPDs. Preliminary analysis on an extension of this algorithm indicates a potential for predictive tracking, although at present, real-time implementation of this extension would require significantly more computational capacity.

Managing risks of market price uncertainty for a microgrid operation

NASA Astrophysics Data System (ADS)

Raghavan, Sriram

After deregulation of electricity in the United States, the day-ahead and real-time markets allow load serving entities and generation companies to bid and purchase/sell energy under the supervision of the independent system operator (ISO). The electricity market prices are inherently uncertain, and can be highly volatile. The main objective of this thesis is to hedge against the risk from the uncertainty of the market prices when purchasing/selling energy from/to the market. The energy manager can also schedule distributed generators (DGs) and storage of the microgrid to meet the demand, in addition to energy transactions from the market. The risk measure used in this work is the variance of the uncertain market purchase/sale cost/revenue, assuming the price following a Gaussian distribution. Using Markowitz optimization, the risk is minimized to find the optimal mix of purchase from the markets. The problem is formulated as a mixed integer quadratic program. The microgrid at Illinois Institute of Technology (IIT) in Chicago, IL was used as a case study. The result of this work reveals the tradeoff faced by the microgrid energy manager between minimizing the risk and minimizing the mean of the total operating cost (TOC) of the microgrid. With this information, the microgrid energy manager can make decisions in the day-ahead and real-time markets according to their risk aversion preference. The assumption of market prices following Gaussian distribution is also verified to be reasonable for the purpose of hedging against their risks. This is done by comparing the result of the proposed formulation with that obtained from the sample market prices randomly generated using the distribution of actual historic market price data.

AERIS - applications for the environment : real-time information synthesis : eco-lanes operational scenario modeling report.

DOT National Transportation Integrated Search

2014-12-01

This report constitutes the detailed modeling and evaluation results of the Eco-Lanes Operational Scenario defined by the Applications for the Environment: Real-Time Information Synthesis (AERIS) Program. The Operational Scenario constitutes six appl...

Discrete Event Supervisory Control Applied to Propulsion Systems

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.; Shah, Neerav

2005-01-01

The theory of discrete event supervisory (DES) control was applied to the optimal control of a twin-engine aircraft propulsion system and demonstrated in a simulation. The supervisory control, which is implemented as a finite-state automaton, oversees the behavior of a system and manages it in such a way that it maximizes a performance criterion, similar to a traditional optimal control problem. DES controllers can be nested such that a high-level controller supervises multiple lower level controllers. This structure can be expanded to control huge, complex systems, providing optimal performance and increasing autonomy with each additional level. The DES control strategy for propulsion systems was validated using a distributed testbed consisting of multiple computers--each representing a module of the overall propulsion system--to simulate real-time hardware-in-the-loop testing. In the first experiment, DES control was applied to the operation of a nonlinear simulation of a turbofan engine (running in closed loop using its own feedback controller) to minimize engine structural damage caused by a combination of thermal and structural loads. This enables increased on-wing time for the engine through better management of the engine-component life usage. Thus, the engine-level DES acts as a life-extending controller through its interaction with and manipulation of the engine s operation.

Mathematical model of marine diesel engine simulator for a new methodology of self propulsion tests

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

Izzuddin, Nur; Sunarsih,; Priyanto, Agoes

As a vessel operates in the open seas, a marine diesel engine simulator whose engine rotation is controlled to transmit through propeller shaft is a new methodology for the self propulsion tests to track the fuel saving in a real time. Considering the circumstance, this paper presents the real time of marine diesel engine simulator system to track the real performance of a ship through a computer-simulated model. A mathematical model of marine diesel engine and the propeller are used in the simulation to estimate fuel rate, engine rotating speed, thrust and torque of the propeller thus achieve the targetmore » vessel’s speed. The input and output are a real time control system of fuel saving rate and propeller rotating speed representing the marine diesel engine characteristics. The self-propulsion tests in calm waters were conducted using a vessel model to validate the marine diesel engine simulator. The simulator then was used to evaluate the fuel saving by employing a new mathematical model of turbochargers for the marine diesel engine simulator. The control system developed will be beneficial for users as to analyze different condition of vessel’s speed to obtain better characteristics and hence optimize the fuel saving rate.« less

Development of polymerase chain reaction-based diagnostic tests for detection of Malsoor virus & adenovirus isolated from Rousettus species of bats in Maharashtra, India.

PubMed

Shete, Anita M; Yadav, Pragya; Kumar, Vimal; Nikam, Tushar; Mehershahi, Kurosh; Kokate, Prasad; Patil, Deepak; Mourya, Devendra T

2017-01-01

Bats are recognized as important reservoirs for emerging infectious disease and some unknown viral diseases. Two novel viruses, Malsoor virus (family Bunyaviridae, genus, Phlebovirus) and a novel adenovirus (AdV) (family, Adenoviridae genus, Mastadenovirus), were identified from Rousettus bats in the Maharashtra State of India. This study was done to develop and optimize real time reverse transcription - polymerase chain reaction (RT-PCR) assays for Malsoor virus and real time and nested PCR for adenovirus from Rousettus bats. For rapid and accurate screening of Malsoor virus and adenovirus a nested polymerase chain reaction and TaqMan-based real-time PCR were developed. Highly conserved region of nucleoprotein gene of phleboviruses and polymerase gene sequence from the Indian bat AdV isolate polyprotein gene were selected respectively for diagnostic assay development of Malsoor virus and AdV. Sensitivity and specificity of assays were calculated and optimized assays were used to screen bat samples. Molecular diagnostic assays were developed for screening of Malsoor virus and AdV and those were found to be specific. Based on the experiments performed with different parameters, nested PCR was found to be more sensitive than real-time PCR; however, for rapid screening, real-time PCR can be used and further nested PCR can be used for final confirmation or in those laboratories where real-time facility/expertise is not existing. This study reports the development and optimization of nested RT-PCR and a TaqMan-based real-time PCR for Malsoor virus and AdV. The diagnostic assays can be used for rapid detection of these novel viruses to understand their prevalence among bat population.

Optimizing Hybrid Occlusion in Face-Jaw-Teeth Transplantation: A Preliminary Assessment of Real-Time Cephalometry as Part of the Computer-Assisted Planning and Execution Workstation for Craniomaxillofacial Surgery.

PubMed

Murphy, Ryan J; Basafa, Ehsan; Hashemi, Sepehr; Grant, Gerald T; Liacouras, Peter; Susarla, Srinivas M; Otake, Yoshito; Santiago, Gabriel; Armand, Mehran; Gordon, Chad R

2015-08-01

The aesthetic and functional outcomes surrounding Le Fort-based, face-jaw-teeth transplantation have been suboptimal, often leading to posttransplant class II/III skeletal profiles, palatal defects, and "hybrid malocclusion." Therefore, a novel technology-real-time cephalometry-was developed to provide the surgical team instantaneous, intraoperative knowledge of three-dimensional dentoskeletal parameters. Mock face-jaw-teeth transplantation operations were performed on plastic and cadaveric human donor/recipient pairs (n = 2). Preoperatively, cephalometric landmarks were identified on donor/recipient skeletons using segmented computed tomographic scans. The computer-assisted planning and execution workstation tracked the position of the donor face-jaw-teeth segment in real time during the placement/inset onto recipient, reporting pertinent hybrid cephalometric parameters from any movement of donor tissue. The intraoperative data measured through real-time cephalometry were compared to posttransplant measurements for accuracy assessment. In addition, posttransplant cephalometric relationships were compared to planned outcomes to determine face-jaw-teeth transplantation success. Compared with postoperative data, the real-time cephalometry-calculated intraoperative measurement errors were 1.37 ± 1.11 mm and 0.45 ± 0.28 degrees for the plastic skull and 2.99 ± 2.24 mm and 2.63 ± 1.33 degrees for the human cadaver experiments. These results were comparable to the posttransplant relations to planned outcome (human cadaver experiment, 1.39 ± 1.81 mm and 2.18 ± 1.88 degrees; plastic skull experiment, 1.06 ± 0.63 mm and 0.53 ± 0.39 degrees). Based on this preliminary testing, real-time cephalometry may be a valuable adjunct for adjusting and measuring "hybrid occlusion" in face-jaw-teeth transplantation and other orthognathic surgical procedures.

The Salem Smart Power Center: An Assessment of Battery Performance and Economic Potential

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

Balducci, Patrick J.; Alam, M. J.E.; Viswanathan, Vilayanur

This paper presents an assessment of the economic potential of a 5 MW/1.25 MWh Energy Storage System (ESS) installed at the Salem Smart Power Center (SSPC), a smart grid technology demonstration facility owned and operated by Portland General Electric (PGE) in Salem, Oregon. The ESS and the grid conditions in which it operates were modeled using Pacific Northwest National Laboratory’s Battery Storage Evaluation Tool (BSET) to explore tradeoffs between services, and to develop optimal control strategies. This assessment monetized the value derived from nine services the SSPC could provide to PGE and the customers it serves. The ESS and themore » grid conditions in which it operates were modeled using PNNL’s in-house optimization tool BSET to explore tradeoffs between services, and to develop optimal control strategies. The analysis resulted in a number of lessons that provide crucial insights into the practical application of ESS, including; The SSPC, which was originally conceived as a research and test facility and built with the prevailing maturity technology level, was built at a cost ($20.4 million) that exceeds current day prices ($5.4 million) for a similarly designed and built 5 MW/1.25 MWh system; In terms of economic operation, the SSPC is currently underutilized, deployed only for primary frequency response. PNNL modeling indicates that optimal operation of the ESS could generate an additional value of $2.3 million over 20 years. It should also be noted that primary frequency response is the highest benefit application but requires a response from the SSPC only 17 hours each year. While optimally engaged, the ESS would provide arbitrage and ancillary services 78 percent of the time, but those services generate only 27 percent of the total value; Participation in Western EIM represents an interesting opportunity for PGE with a potential to generate $2.1 million value in PV terms over 20 years in the 5-min real-time market; With an energy to power ratio of only 0.25, the SSPC is not well suited to engage in most energy-intensive applications such as arbitrage or ancillary services. By upsizing the storage capacity to 5 MWh and 10MWh, the additional value allows the benefits ($13.3 million and 20.3 million, respectively) to exceed the system’s revenue requirements ($11.5 and $16.4 million, respectively). For the SSPC, ROI ratios exceeded 1.0 when the energy to power ratio fell between 0.5 and 3.5, and peaked at an energy to power ratio of 2.0. This report represents the output of the first of a two-phase effort. Phase II will involve the development of enhanced control strategies to assist PGE in realizing the benefits of energy storage in real-time.« less

Power-balancing instantaneous optimization energy management for a novel series-parallel hybrid electric bus

NASA Astrophysics Data System (ADS)

Sun, Dongye; Lin, Xinyou; Qin, Datong; Deng, Tao

2012-11-01

Energy management(EM) is a core technique of hybrid electric bus(HEB) in order to advance fuel economy performance optimization and is unique for the corresponding configuration. There are existing algorithms of control strategy seldom take battery power management into account with international combustion engine power management. In this paper, a type of power-balancing instantaneous optimization(PBIO) energy management control strategy is proposed for a novel series-parallel hybrid electric bus. According to the characteristic of the novel series-parallel architecture, the switching boundary condition between series and parallel mode as well as the control rules of the power-balancing strategy are developed. The equivalent fuel model of battery is implemented and combined with the fuel of engine to constitute the objective function which is to minimize the fuel consumption at each sampled time and to coordinate the power distribution in real-time between the engine and battery. To validate the proposed strategy effective and reasonable, a forward model is built based on Matlab/Simulink for the simulation and the dSPACE autobox is applied to act as a controller for hardware in-the-loop integrated with bench test. Both the results of simulation and hardware-in-the-loop demonstrate that the proposed strategy not only enable to sustain the battery SOC within its operational range and keep the engine operation point locating the peak efficiency region, but also the fuel economy of series-parallel hybrid electric bus(SPHEB) dramatically advanced up to 30.73% via comparing with the prototype bus and a similar improvement for PBIO strategy relative to rule-based strategy, the reduction of fuel consumption is up to 12.38%. The proposed research ensures the algorithm of PBIO is real-time applicability, improves the efficiency of SPHEB system, as well as suite to complicated configuration perfectly.

Real-time operating system timing jitter and its impact on motor control

NASA Astrophysics Data System (ADS)

Proctor, Frederick M.; Shackleford, William P.

2001-12-01

General-purpose microprocessors are increasingly being used for control applications due to their widespread availability and software support for non-control functions like networking and operator interfaces. Two classes of real-time operating systems (RTOS) exist for these systems. The traditional RTOS serves as the sole operating system, and provides all OS services. Examples include ETS, LynxOS, QNX, Windows CE and VxWorks. RTOS extensions add real-time scheduling capabilities to non-real-time OSes, and provide minimal services needed for the time-critical portions of an application. Examples include RTAI and RTL for Linux, and HyperKernel, OnTime and RTX for Windows NT. Timing jitter is an issue in these systems, due to hardware effects such as bus locking, caches and pipelines, and software effects from mutual exclusion resource locks, non-preemtible critical sections, disabled interrupts, and multiple code paths in the scheduler. Jitter is typically on the order of a microsecond to a few tens of microseconds for hard real-time operating systems, and ranges from milliseconds to seconds in the worst case for soft real-time operating systems. The question of its significance on the performance of a controller arises. Naturally, the smaller the scheduling period required for a control task, the more significant is the impact of timing jitter. Aside from this intuitive relationship is the greater significance of timing on open-loop control, such as for stepper motors, than for closed-loop control, such as for servo motors. Techniques for measuring timing jitter are discussed, and comparisons between various platforms are presented. Techniques to reduce jitter or mitigate its effects are presented. The impact of jitter on stepper motor control is analyzed.

DG Planning with Amalgamation of Operational and Reliability Considerations

NASA Astrophysics Data System (ADS)

Battu, Neelakanteshwar Rao; Abhyankar, A. R.; Senroy, Nilanjan

2016-04-01

Distributed Generation has been playing a vital role in dealing issues related to distribution systems. This paper presents an approach which provides policy maker with a set of solutions for DG placement to optimize reliability and real power loss of the system. Optimal location of a Distributed Generator is evaluated based on performance indices derived for reliability index and real power loss. The proposed approach is applied on a 15-bus radial distribution system and a 18-bus radial distribution system with conventional and wind distributed generators individually.

Evaluation and display of polarimetric image data using long-wave cooled microgrid focal plane arrays

NASA Astrophysics Data System (ADS)

Bowers, David L.; Boger, James K.; Wellems, L. David; Black, Wiley T.; Ortega, Steve E.; Ratliff, Bradley M.; Fetrow, Matthew P.; Hubbs, John E.; Tyo, J. Scott

2006-05-01

Recent developments for Long Wave InfraRed (LWIR) imaging polarimeters include incorporating a microgrid polarizer array onto the focal plane array (FPA). Inherent advantages over typical polarimeters include packaging and instantaneous acquisition of thermal and polarimetric information. This allows for real time video of thermal and polarimetric products. The microgrid approach has inherent polarization measurement error due to the spatial sampling of a non-uniform scene, residual pixel to pixel variations in the gain corrected responsivity and in the noise equivalent input (NEI), and variations in the pixel to pixel micro-polarizer performance. The Degree of Linear Polarization (DoLP) is highly sensitive to these parameters and is consequently used as a metric to explore instrument sensitivities. Image processing and fusion techniques are used to take advantage of the inherent thermal and polarimetric sensing capability of this FPA, providing additional scene information in real time. Optimal operating conditions are employed to improve FPA uniformity and sensitivity. Data from two DRS Infrared Technologies, L.P. (DRS) microgrid polarizer HgCdTe FPAs are presented. One FPA resides in a liquid nitrogen (LN2) pour filled dewar with a 80°K nominal operating temperature. The other FPA resides in a cryogenic (cryo) dewar with a 60° K nominal operating temperature.

The Real Time Display Builder (RTDB)

NASA Technical Reports Server (NTRS)

Kindred, Erick D.; Bailey, Samuel A., Jr.

1989-01-01

The Real Time Display Builder (RTDB) is a prototype interactive graphics tool that builds logic-driven displays. These displays reflect current system status, implement fault detection algorithms in real time, and incorporate the operational knowledge of experienced flight controllers. RTDB utilizes an object-oriented approach that integrates the display symbols with the underlying operational logic. This approach allows the user to specify the screen layout and the driving logic as the display is being built. RTDB is being developed under UNIX in C utilizing the MASSCOMP graphics environment with appropriate functional separation to ease portability to other graphics environments. RTDB grew from the need to develop customized real-time data-driven Space Shuttle systems displays. One display, using initial functionality of the tool, was operational during the orbit phase of STS-26 Discovery. RTDB is being used to produce subsequent displays for the Real Time Data System project currently under development within the Mission Operations Directorate at NASA/JSC. The features of the tool, its current state of development, and its applications are discussed.

Restless Tuneup of High-Fidelity Qubit Gates

NASA Astrophysics Data System (ADS)

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

2017-04-01

We present a tuneup protocol for qubit gates with tenfold speedup over traditional methods reliant on qubit initialization by energy relaxation. This speedup is achieved by constructing a cost function for Nelder-Mead optimization from real-time correlation of nondemolition measurements interleaving gate operations without pause. Applying the protocol on a transmon qubit achieves 0.999 average Clifford fidelity in one minute, as independently verified using randomized benchmarking and gate-set tomography. The adjustable sensitivity of the cost function allows the detection of fractional changes in the gate error with a nearly constant signal-to-noise ratio. The restless concept demonstrated can be readily extended to the tuneup of two-qubit gates and measurement operations.

Real-time LMR control parameter generation using advanced adaptive synthesis

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

King, R.W.; Mott, J.E.

1990-01-01

The reactor delta T'', the difference between the average core inlet and outlet temperatures, for the liquid-sodium-cooled Experimental Breeder Reactor 2 is empirically synthesized in real time from, a multitude of examples of past reactor operation. The real-time empirical synthesis is based on reactor operation. The real-time empirical synthesis is based on system state analysis (SSA) technology embodied in software on the EBR 2 data acquisition computer. Before the real-time system is put into operation, a selection of reactor plant measurements is made which is predictable over long periods encompassing plant shutdowns, core reconfigurations, core load changes, and plant startups.more » A serial data link to a personal computer containing SSA software allows the rapid verification of the predictability of these plant measurements via graphical means. After the selection is made, the real-time synthesis provides a fault-tolerant estimate of the reactor delta T accurate to {plus}/{minus}1{percent}. 5 refs., 7 figs.« less

A Distributed Operating System for BMD Applications.

DTIC Science & Technology

1982-01-01

Defense) applications executing on distributed hardware with local and shared memories. The objective was to develop real - time operating system functions...make the Basic Real - Time Operating System , and the set of new EPL language primitives that provide BMD application processes with efficient mechanisms

PILOT: An intelligent distributed operations support system

NASA Technical Reports Server (NTRS)

Rasmussen, Arthur N.

1993-01-01

The Real-Time Data System (RTDS) project is exploring the application of advanced technologies to the real-time flight operations environment of the Mission Control Centers at NASA's Johnson Space Center. The system, based on a network of engineering workstations, provides services such as delivery of real time telemetry data to flight control applications. To automate the operation of this complex distributed environment, a facility called PILOT (Process Integrity Level and Operation Tracker) is being developed. PILOT comprises a set of distributed agents cooperating with a rule-based expert system; together they monitor process operation and data flows throughout the RTDS network. The goal of PILOT is to provide unattended management and automated operation under user control.

Effect of Streamflow Forecast Uncertainty on Real-Time Reservoir Operation

NASA Astrophysics Data System (ADS)

Zhao, T.; Cai, X.; Yang, D.

2010-12-01

Various hydrological forecast products have been applied to real-time reservoir operation, including deterministic streamflow forecast (DSF), DSF-based probabilistic streamflow forecast (DPSF), and ensemble streamflow forecast (ESF), which represent forecast uncertainty in the form of deterministic forecast error, deterministic forecast error-based uncertainty distribution, and ensemble forecast errors, respectively. Compared to previous studies that treat these forecast products as ad hoc inputs for reservoir operation models, this paper attempts to model the uncertainties involved in the various forecast products and explores their effect on real-time reservoir operation decisions. In hydrology, there are various indices reflecting the magnitude of streamflow forecast uncertainty; meanwhile, few models illustrate the forecast uncertainty evolution process. This research introduces Martingale Model of Forecast Evolution (MMFE) from supply chain management and justifies its assumptions for quantifying the evolution of uncertainty in streamflow forecast as time progresses. Based on MMFE, this research simulates the evolution of forecast uncertainty in DSF, DPSF, and ESF, and applies the reservoir operation models (dynamic programming, DP; stochastic dynamic programming, SDP; and standard operation policy, SOP) to assess the effect of different forms of forecast uncertainty on real-time reservoir operation. Through a hypothetical single-objective real-time reservoir operation model, the results illustrate that forecast uncertainty exerts significant effects. Reservoir operation efficiency, as measured by a utility function, decreases as the forecast uncertainty increases. Meanwhile, these effects also depend on the type of forecast product being used. In general, the utility of reservoir operation with ESF is nearly as high as the utility obtained with a perfect forecast; the utilities of DSF and DPSF are similar to each other but not as efficient as ESF. Moreover, streamflow variability and reservoir capacity can change the magnitude of the effects of forecast uncertainty, but not the relative merit of DSF, DPSF, and ESF. Schematic diagram of the increase in forecast uncertainty with forecast lead-time and the dynamic updating property of real-time streamflow forecast

Advanced visualization platform for surgical operating room coordination: distributed video board system.

PubMed

Hu, Peter F; Xiao, Yan; Ho, Danny; Mackenzie, Colin F; Hu, Hao; Voigt, Roger; Martz, Douglas

2006-06-01

One of the major challenges for day-of-surgery operating room coordination is accurate and timely situation awareness. Distributed and secure real-time status information is key to addressing these challenges. This article reports on the design and implementation of a passive status monitoring system in a 19-room surgical suite of a major academic medical center. Key design requirements considered included integrated real-time operating room status display, access control, security, and network impact. The system used live operating room video images and patient vital signs obtained through monitors to automatically update events and operating room status. Images were presented on a "need-to-know" basis, and access was controlled by identification badge authorization. The system delivered reliable real-time operating room images and status with acceptable network impact. Operating room status was visualized at 4 separate locations and was used continuously by clinicians and operating room service providers to coordinate operating room activities.

Robust optimization with transiently chaotic dynamical systems

NASA Astrophysics Data System (ADS)

Sumi, R.; Molnár, B.; Ercsey-Ravasz, M.

2014-05-01

Efficiently solving hard optimization problems has been a strong motivation for progress in analog computing. In a recent study we presented a continuous-time dynamical system for solving the NP-complete Boolean satisfiability (SAT) problem, with a one-to-one correspondence between its stable attractors and the SAT solutions. While physical implementations could offer great efficiency, the transiently chaotic dynamics raises the question of operability in the presence of noise, unavoidable on analog devices. Here we show that the probability of finding solutions is robust to noise intensities well above those present on real hardware. We also developed a cellular neural network model realizable with analog circuits, which tolerates even larger noise intensities. These methods represent an opportunity for robust and efficient physical implementations.

Analysis of Interactive Graphics Display Equipment for an Automated Photo Interpretation System.

DTIC Science & Technology

1982-06-01

System provides the hardware and software for a range of graphics processor tasks. The IMAGE System employs the RSX- II M real - time operating . system in...One hard copy unit serves up to four work stations. The executive program of the IMAGE system is the DEC RSX- 11 M real - time operating system . In...picture controller. The PDP 11/34 executes programs concurrently under the RSX- I IM real - time operating system . Each graphics program consists of a

Optimized quantum sensing with a single electron spin using real-time adaptive measurements.

PubMed

Bonato, C; Blok, M S; Dinani, H T; Berry, D W; Markham, M L; Twitchen, D J; Hanson, R

2016-03-01

Quantum sensors based on single solid-state spins promise a unique combination of sensitivity and spatial resolution. The key challenge in sensing is to achieve minimum estimation uncertainty within a given time and with high dynamic range. Adaptive strategies have been proposed to achieve optimal performance, but their implementation in solid-state systems has been hindered by the demanding experimental requirements. Here, we realize adaptive d.c. sensing by combining single-shot readout of an electron spin in diamond with fast feedback. By adapting the spin readout basis in real time based on previous outcomes, we demonstrate a sensitivity in Ramsey interferometry surpassing the standard measurement limit. Furthermore, we find by simulations and experiments that adaptive protocols offer a distinctive advantage over the best known non-adaptive protocols when overhead and limited estimation time are taken into account. Using an optimized adaptive protocol we achieve a magnetic field sensitivity of 6.1 ± 1.7 nT Hz(-1/2) over a wide range of 1.78 mT. These results open up a new class of experiments for solid-state sensors in which real-time knowledge of the measurement history is exploited to obtain optimal performance.

Optimized quantum sensing with a single electron spin using real-time adaptive measurements

NASA Astrophysics Data System (ADS)

Bonato, C.; Blok, M. S.; Dinani, H. T.; Berry, D. W.; Markham, M. L.; Twitchen, D. J.; Hanson, R.

2016-03-01

Quantum sensors based on single solid-state spins promise a unique combination of sensitivity and spatial resolution. The key challenge in sensing is to achieve minimum estimation uncertainty within a given time and with high dynamic range. Adaptive strategies have been proposed to achieve optimal performance, but their implementation in solid-state systems has been hindered by the demanding experimental requirements. Here, we realize adaptive d.c. sensing by combining single-shot readout of an electron spin in diamond with fast feedback. By adapting the spin readout basis in real time based on previous outcomes, we demonstrate a sensitivity in Ramsey interferometry surpassing the standard measurement limit. Furthermore, we find by simulations and experiments that adaptive protocols offer a distinctive advantage over the best known non-adaptive protocols when overhead and limited estimation time are taken into account. Using an optimized adaptive protocol we achieve a magnetic field sensitivity of 6.1 ± 1.7 nT Hz-1/2 over a wide range of 1.78 mT. These results open up a new class of experiments for solid-state sensors in which real-time knowledge of the measurement history is exploited to obtain optimal performance.

Instrument front-ends at Fermilab during Run II

NASA Astrophysics Data System (ADS)

Meyer, T.; Slimmer, D.; Voy, D.

2011-11-01

The optimization of an accelerator relies on the ability to monitor the behavior of the beam in an intelligent and timely fashion. The use of processor-driven front-ends allowed for the deployment of smart systems in the field for improved data collection and analysis during Run II. This paper describes the implementation of the two main systems used: National Instruments LabVIEW running on PCs, and WindRiver's VxWorks real-time operating system running in a VME crate processor. Work supported by Fermi Research Alliance, LLC under Contract No. DE-AC02-07CH11359 with the United States Department of Energy.

Brief communication: Post-seismic landslides, the tough lesson of a catastrophe

NASA Astrophysics Data System (ADS)

Fan, Xuanmei; Xu, Qiang; Scaringi, Gianvito

2018-01-01

The rock avalanche that destroyed the village of Xinmo in Sichuan, China, on 24 June 2017, brought the issue of landslide risk and disaster chain management in highly seismic regions back into the spotlight. The long-term post-seismic behaviour of mountain slopes is complex and hardly predictable. Nevertheless, the integrated use of field monitoring, remote sensing and real-time predictive modelling can help to set up effective early warning systems, provide timely alarms, optimize rescue operations, and perform secondary hazard assessments. We believe that a comprehensive discussion on post-seismic slope stability and on its implications for policy makers can no longer be postponed.

A Sarsa(λ)-based control model for real-time traffic light coordination.

PubMed

Zhou, Xiaoke; Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

2014-01-01

Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.

Tire-road friction estimation and traction control strategy for motorized electric vehicle.

PubMed

Jin, Li-Qiang; Ling, Mingze; Yue, Weiqiang

2017-01-01

In this paper, an optimal longitudinal slip ratio system for real-time identification of electric vehicle (EV) with motored wheels is proposed based on the adhesion between tire and road surface. First and foremost, the optimal longitudinal slip rate torque control can be identified in real time by calculating the derivative and slip rate of the adhesion coefficient. Secondly, the vehicle speed estimation method is also brought. Thirdly, an ideal vehicle simulation model is proposed to verify the algorithm with simulation, and we find that the slip ratio corresponds to the detection of the adhesion limit in real time. Finally, the proposed strategy is applied to traction control system (TCS). The results showed that the method can effectively identify the state of wheel and calculate the optimal slip ratio without wheel speed sensor; in the meantime, it can improve the accelerated stability of electric vehicle with traction control system (TCS).

Tire-road friction estimation and traction control strategy for motorized electric vehicle

PubMed Central

Jin, Li-Qiang; Yue, Weiqiang

2017-01-01

In this paper, an optimal longitudinal slip ratio system for real-time identification of electric vehicle (EV) with motored wheels is proposed based on the adhesion between tire and road surface. First and foremost, the optimal longitudinal slip rate torque control can be identified in real time by calculating the derivative and slip rate of the adhesion coefficient. Secondly, the vehicle speed estimation method is also brought. Thirdly, an ideal vehicle simulation model is proposed to verify the algorithm with simulation, and we find that the slip ratio corresponds to the detection of the adhesion limit in real time. Finally, the proposed strategy is applied to traction control system (TCS). The results showed that the method can effectively identify the state of wheel and calculate the optimal slip ratio without wheel speed sensor; in the meantime, it can improve the accelerated stability of electric vehicle with traction control system (TCS). PMID:28662053

Real time monitoring of water distribution in an operando fuel cell during transient states

NASA Astrophysics Data System (ADS)

Martinez, N.; Peng, Z.; Morin, A.; Porcar, L.; Gebel, G.; Lyonnard, S.

2017-10-01

The water distribution of an operating proton exchange membrane fuel cell (PEMFC) was monitored in real time by using Small Angle Neutron Scattering (SANS). The formation of liquid water was obtained simultaneously with the evolution of the water content inside the membrane. Measurements were performed when changing current with a time resolution of 10 s, providing insights on the kinetics of water management prior to the stationary phase. We confirmed that water distribution is strongly heterogeneous at the scale at of the whole Membrane Electrode Assembly. As already reported, at the local scale there is no straightforward link between the amounts of water present inside and outside the membrane. However, we show that the temporal evolutions of these two parameters are strongly correlated. In particular, the local membrane water content is nearly instantaneously correlated to the total liquid water content, whether it is located at the anode or cathode side. These results can help in optimizing 3D stationary diphasic models used to predict PEMFC water distribution.

Next generation PET data acquisition architectures

NASA Astrophysics Data System (ADS)

Jones, W. F.; Reed, J. H.; Everman, J. L.; Young, J. W.; Seese, R. D.

1997-06-01

New architectures for higher performance data acquisition in PET are proposed. Improvements are demanded primarily by three areas of advancing PET state of the art. First, larger detector arrays such as the Hammersmith ECAT/sup (R/) EXACT HR/sup ++/ exceed the addressing capacity of 32 bit coincidence event words. Second, better scintillators (LSO) make depth-of interaction (DOI) and time-of-flight (TOF) operation more practical. Third, fully optimized single photon attenuation correction requires higher rates of data collection. New technologies which enable the proposed third generation Real Time Sorter (RTS III) include: (1) 80 Mbyte/sec Fibre Channel RAID disk systems, (2) PowerPC on both VMEbus and PCI Local bus, and (3) quadruple interleaved DRAM controller designs. Data acquisition flexibility is enhanced through a wider 64 bit coincidence event word. PET methodology support includes DOI (6 bits), TOF (6 bits), multiple energy windows (6 bits), 512/spl times/512 sinogram indexes (18 bits), and 256 crystal rings (16 bits). Throughput of 10 M events/sec is expected for list-mode data collection as well as both on-line and replay histogramming. Fully efficient list-mode storage for each PET application is provided by real-time bit packing of only the active event word bits. Real-time circuits provide DOI rebinning.

Optimization with Fuzzy Data via Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Kosiński, Witold

2010-09-01

Order fuzzy numbers (OFN) that make possible to deal with fuzzy inputs quantitatively, exactly in the same way as with real numbers, have been recently defined by the author and his 2 coworkers. The set of OFN forms a normed space and is a partially ordered ring. The case when the numbers are presented in the form of step functions, with finite resolution, simplifies all operations and the representation of defuzzification functionals. A general optimization problem with fuzzy data is formulated. Its fitness function attains fuzzy values. Since the adjoint space to the space of OFN is finite dimensional, a convex combination of all linear defuzzification functionals may be used to introduce a total order and a real-valued fitness function. Genetic operations on individuals representing fuzzy data are defined.

Integration and Assessment of Component Health Prognostics in Supervisory Control Systems

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

Ramuhalli, Pradeep; Bonebrake, Christopher A.; Dib, Gerges

Enhanced risk monitors (ERMs) for active components in advanced reactor concepts use predictive estimates of component failure to update, in real time, predictive safety and economic risk metrics. These metrics have been shown to be capable of use in optimizing maintenance scheduling and managing plant maintenance costs. Integrating this information with plant supervisory control systems increases the potential for making control decisions that utilize real-time information on component conditions. Such decision making would limit the possibility of plant operations that increase the likelihood of degrading the functionality of one or more components while maintaining the overall functionality of the plant.more » ERM uses sensor data for providing real-time information about equipment condition for deriving risk monitors. This information is used to estimate the remaining useful life and probability of failure of these components. By combining this information with plant probabilistic risk assessment models, predictive estimates of risk posed by continued plant operation in the presence of detected degradation may be estimated. In this paper, we describe this methodology in greater detail, and discuss its integration with a prototypic software-based plant supervisory control platform. In order to integrate these two technologies and evaluate the integrated system, software to simulate the sensor data was developed, prognostic models for feedwater valves were developed, and several use cases defined. The full paper will describe these use cases, and the results of the initial evaluation.« less

Real Time Integration of Field Data Into a GIS Platform for the Management of Hydrological Emergencies

NASA Astrophysics Data System (ADS)

Mangiameli, M.; Mussumeci, G.

2013-01-01

A wide series of events requires immediate availability of information and field data to be provided to decision-makers. An example is the necessity of quickly transferring the information acquired from monitoring and alerting sensors or the data of the reconnaissance of damage after a disastrous event to an Emergency Operations Center. To this purpose, we developed an integrated GIS and WebGIS system to dynamically create and populate via Web a database with spatial features. In particular, this work concerns the gathering and transmission of spatial data and related information to the desktop GIS so that they can be displayed and analyzed in real time to characterize the operational scenario and to decide the rescue interventions. As basic software, we used only free and open source: QuantumGIS and Grass as Desktop GIS, Map Server with PMapper application for the Web-Gis functionality and PostGreSQL/PostGIS as Data Base Management System (DBMS). The approach has been designed, developed and successfully tested in the management of GIS-based navigation of an autonomous robot, both to map its trajectories and to assign optimal paths. This paper presents the application of our system to a simulated hydrological event that could interest the province of Catania, in Sicily. In particular, assuming that more teams draw up an inventory of the damage, we highlight the benefits of real-time transmission of the information collected from the field to headquarters.

Social Emotional Optimization Algorithm for Nonlinear Constrained Optimization Problems

NASA Astrophysics Data System (ADS)

Xu, Yuechun; Cui, Zhihua; Zeng, Jianchao

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

On the analytic and numeric optimisation of airplane trajectories under real atmospheric conditions

NASA Astrophysics Data System (ADS)

Gonzalo, J.; Domínguez, D.; López, D.

2014-12-01

From the beginning of aviation era, economic constraints have forced operators to continuously improve the planning of the flights. The revenue is proportional to the cost per flight and the airspace occupancy. Many methods, the first started in the middle of last century, have explore analytical, numerical and artificial intelligence resources to reach the optimal flight planning. In parallel, advances in meteorology and communications allow an almost real-time knowledge of the atmospheric conditions and a reliable, error-bounded forecast for the near future. Thus, apart from weather risks to be avoided, airplanes can dynamically adapt their trajectories to minimise their costs. International regulators are aware about these capabilities, so it is reasonable to envisage some changes to allow this dynamic planning negotiation to soon become operational. Moreover, current unmanned airplanes, very popular and often small, suffer the impact of winds and other weather conditions in form of dramatic changes in their performance. The present paper reviews analytic and numeric solutions for typical trajectory planning problems. Analytic methods are those trying to solve the problem using the Pontryagin principle, where influence parameters are added to state variables to form a split condition differential equation problem. The system can be solved numerically -indirect optimisation- or using parameterised functions -direct optimisation-. On the other hand, numerical methods are based on Bellman's dynamic programming (or Dijkstra algorithms), where the fact that two optimal trajectories can be concatenated to form a new optimal one if the joint point is demonstrated to belong to the final optimal solution. There is no a-priori conditions for the best method. Traditionally, analytic has been more employed for continuous problems whereas numeric for discrete ones. In the current problem, airplane behaviour is defined by continuous equations, while wind fields are given in a discrete grid at certain time intervals. The research demonstrates advantages and disadvantages of each method as well as performance figures of the solutions found for typical flight conditions under static and dynamic atmospheres. This provides significant parameters to be used in the selection of solvers for optimal trajectories.

Developing infrared array controller with software real time operating system

NASA Astrophysics Data System (ADS)

Sako, Shigeyuki; Miyata, Takashi; Nakamura, Tomohiko; Motohara, Kentaro; Uchimoto, Yuka Katsuno; Onaka, Takashi; Kataza, Hirokazu

2008-07-01

Real-time capabilities are required for a controller of a large format array to reduce a dead-time attributed by readout and data transfer. The real-time processing has been achieved by dedicated processors including DSP, CPLD, and FPGA devices. However, the dedicated processors have problems with memory resources, inflexibility, and high cost. Meanwhile, a recent PC has sufficient resources of CPUs and memories to control the infrared array and to process a large amount of frame data in real-time. In this study, we have developed an infrared array controller with a software real-time operating system (RTOS) instead of the dedicated processors. A Linux PC equipped with a RTAI extension and a dual-core CPU is used as a main computer, and one of the CPU cores is allocated to the real-time processing. A digital I/O board with DMA functions is used for an I/O interface. The signal-processing cores are integrated in the OS kernel as a real-time driver module, which is composed of two virtual devices of the clock processor and the frame processor tasks. The array controller with the RTOS realizes complicated operations easily, flexibly, and at a low cost.

Modelling Temporal Schedule of Urban Trains Using Agent-Based Simulation and NSGA2-BASED Multiobjective Optimization Approaches

NASA Astrophysics Data System (ADS)

Sahelgozin, M.; Alimohammadi, A.

2015-12-01

Increasing distances between locations of residence and services leads to a large number of daily commutes in urban areas. Developing subway systems has been taken into consideration of transportation managers as a response to this huge amount of travel demands. In developments of subway infrastructures, representing a temporal schedule for trains is an important task; because an appropriately designed timetable decreases Total passenger travel times, Total Operation Costs and Energy Consumption of trains. Since these variables are not positively correlated, subway scheduling is considered as a multi-criteria optimization problem. Therefore, proposing a proper solution for subway scheduling has been always a controversial issue. On the other hand, research on a phenomenon requires a summarized representation of the real world that is known as Model. In this study, it is attempted to model temporal schedule of urban trains that can be applied in Multi-Criteria Subway Schedule Optimization (MCSSO) problems. At first, a conceptual framework is represented for MCSSO. Then, an agent-based simulation environment is implemented to perform Sensitivity Analysis (SA) that is used to extract the interrelations between the framework components. These interrelations is then taken into account in order to construct the proposed model. In order to evaluate performance of the model in MCSSO problems, Tehran subway line no. 1 is considered as the case study. Results of the study show that the model was able to generate an acceptable distribution of Pareto-optimal solutions which are applicable in the real situations while solving a MCSSO is the goal. Also, the accuracy of the model in representing the operation of subway systems was significant.

Ada Compiler Validation Summary Report: Certificate Number: 900121S1. 10251 Computer Sciences Corporation MC Ada V1.2.Beta/Concurrent Computer Corporation Concurrent/Masscomp 5600 Host To Concurrent/Masscomp 5600 (Dual 68020 Processor Configuration) Target

DTIC Science & Technology

1990-04-23

developed Ada Real - Time Operating System (ARTOS) for bare machine environments(Target), ACW 1.1I0. " ; - -M.UIECTTERMS Ada programming language, Ada...configuration) Operating System: CSC developed Ada Real - Time Operating System (ARTOS) for bare machine environments Memory Size: 4MB 2.2...Test Method Testing of the MC Ado V1.2.beta/ Concurrent Computer Corporation compiler and the CSC developed Ada Real - Time Operating System (ARTOS) for

Real-Time Nonlinear Optical Information Processing.

DTIC Science & Technology

1979-06-01

operations aree presented. One approach realizes the halftone method of nonlinear optical processing in real time by replacing the conventional...photographic recording medium with a real-time image transducer. In the second approach halftoning is eliminated and the real-time device is used directly

Biogeography-based combinatorial strategy for efficient autonomous underwater vehicle motion planning and task-time management

NASA Astrophysics Data System (ADS)

Zadeh, S. M.; Powers, D. M. W.; Sammut, K.; Yazdani, A. M.

2016-12-01

Autonomous Underwater Vehicles (AUVs) are capable of spending long periods of time for carrying out various underwater missions and marine tasks. In this paper, a novel conflict-free motion planning framework is introduced to enhance underwater vehicle's mission performance by completing maximum number of highest priority tasks in a limited time through a large scale waypoint cluttered operating field, and ensuring safe deployment during the mission. The proposed combinatorial route-path planner model takes the advantages of the Biogeography-Based Optimization (BBO) algorithm toward satisfying objectives of both higher-lower level motion planners and guarantees maximization of the mission productivity for a single vehicle operation. The performance of the model is investigated under different scenarios including the particular cost constraints in time-varying operating fields. To show the reliability of the proposed model, performance of each motion planner assessed separately and then statistical analysis is undertaken to evaluate the total performance of the entire model. The simulation results indicate the stability of the contributed model and its feasible application for real experiments.

Implementation of an Intelligent Control System

DTIC Science & Technology

1992-05-01

there- fore implemented in a portable equipment rack. The controls computer consists of a microcomputer running a real time operating system , interface...circuit boards are mounted in an industry standard Multibus I chassis. The microcomputer runs the iRMX real time operating system . This operating system

A study of optimization techniques in HDR brachytherapy for the prostate

NASA Astrophysics Data System (ADS)

Pokharel, Ghana Shyam

Several studies carried out thus far are in favor of dose escalation to the prostate gland to have better local control of the disease. But optimal way of delivery of higher doses of radiation therapy to the prostate without hurting neighboring critical structures is still debatable. In this study, we proposed that real time high dose rate (HDR) brachytherapy with highly efficient and effective optimization could be an alternative means of precise delivery of such higher doses. This approach of delivery eliminates the critical issues such as treatment setup uncertainties and target localization as in external beam radiation therapy. Likewise, dosimetry in HDR brachytherapy is not influenced by organ edema and potential source migration as in permanent interstitial implants. Moreover, the recent report of radiobiological parameters further strengthen the argument of using hypofractionated HDR brachytherapy for the management of prostate cancer. Firstly, we studied the essential features and requirements of real time HDR brachytherapy treatment planning system. Automating catheter reconstruction with fast editing tools, fast yet accurate dose engine, robust and fast optimization and evaluation engine are some of the essential requirements for such procedures. Moreover, in most of the cases we performed, treatment plan optimization took significant amount of time of overall procedure. So, making treatment plan optimization automatic or semi-automatic with sufficient speed and accuracy was the goal of the remaining part of the project. Secondly, we studied the role of optimization function and constraints in overall quality of optimized plan. We have studied the gradient based deterministic algorithm with dose volume histogram (DVH) and more conventional variance based objective functions for optimization. In this optimization strategy, the relative weight of particular objective in aggregate objective function signifies its importance with respect to other objectives. Based on our study, DVH based objective function performed better than traditional variance based objective function in creating a clinically acceptable plan when executed under identical conditions. Thirdly, we studied the multiobjective optimization strategy using both DVH and variance based objective functions. The optimization strategy was to create several Pareto optimal solutions by scanning the clinically relevant part of the Pareto front. This strategy was adopted to decouple optimization from decision such that user could select final solution from the pool of alternative solutions based on his/her clinical goals. The overall quality of treatment plan improved using this approach compared to traditional class solution approach. In fact, the final optimized plan selected using decision engine with DVH based objective was comparable to typical clinical plan created by an experienced physicist. Next, we studied the hybrid technique comprising both stochastic and deterministic algorithm to optimize both dwell positions and dwell times. The simulated annealing algorithm was used to find optimal catheter distribution and the DVH based algorithm was used to optimize 3D dose distribution for given catheter distribution. This unique treatment planning and optimization tool was capable of producing clinically acceptable highly reproducible treatment plans in clinically reasonable time. As this algorithm was able to create clinically acceptable plans within clinically reasonable time automatically, it is really appealing for real time procedures. Next, we studied the feasibility of multiobjective optimization using evolutionary algorithm for real time HDR brachytherapy for the prostate. The algorithm with properly tuned algorithm specific parameters was able to create clinically acceptable plans within clinically reasonable time. However, the algorithm was let to run just for limited number of generations not considered optimal, in general, for such algorithms. This was done to keep time window desirable for real time procedures. Therefore, it requires further study with improved conditions to realize the full potential of the algorithm.

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

NASA Astrophysics Data System (ADS)

Lu, Qiheng; Feng, Xiaoyun

2013-03-01

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

Simulation Of Assembly Processes With Technical Of Virtual Reality

NASA Astrophysics Data System (ADS)

García García, Manuel; Arenas Reina, José Manuel; Lite, Alberto Sánchez; Sebastián Pérez, Miguel Ángel

2009-11-01

Virtual reality techniques use at industrial processes provides a real approach to product life cycle. For components manual assembly, the use of virtual surroundings facilitates a simultaneous engineering in which variables such as human factors and productivity take a real act. On the other hand, in the actual phase of industrial competition it is required a rapid adjustment to client needs and to market situation. In this work it is analyzed the assembly of the front components of a vehicle using virtual reality tools and following up a product-process design methodology which includes every life service stage. This study is based on workstations design, taking into account productive and human factors from the ergonomic point of view implementing a postural study of every assembly operation, leaving the rest of stages for a later study. Design is optimized applying this methodology together with the use of virtual reality tools. It is also achieved a 15% reduction on time assembly and of 90% reduction in muscle—skeletal diseases at every assembly operation.

Real-Time Operation of the International Space Station

NASA Astrophysics Data System (ADS)

Suffredini, M. T.

2002-01-01

The International Space Station is on orbit and real-time operations are well underway. Along with the assembly challenges of building and operating the International Space Station , scientific activities are also underway. Flight control teams in three countries are working together as a team to plan, coordinate and command the systems on the International Space Station.Preparations are being made to add the additional International Partner elements including their operations teams and facilities. By October 2002, six Expedition crews will have lived on the International Space Station. Management of real-time operations has been key to these achievements. This includes the activities of ground teams in control centers around the world as well as the crew on orbit. Real-time planning is constantly challenged with balancing the requirements and setting the priorities for the assembly, maintenance, science and crew health functions on the International Space Station. It requires integrating the Shuttle, Soyuz and Progress requirements with the Station. It is also necessary to be able to respond in case of on-orbit anomalies and to set plans and commands in place to ensure the continues safe operation of the Station. Bringing together the International Partner operations teams has been challenging and intensely rewarding. Utilization of the assets of each partner has resulted in efficient solutions to problems. This paper will describe the management of the major real-time operations processes, significant achievements, and future challenges.

Multiagent Flight Control in Dynamic Environments with Cooperative Coevolutionary Algorithms

NASA Technical Reports Server (NTRS)

Knudson, Matthew D.; Colby, Mitchell; Tumer, Kagan

2014-01-01

Dynamic flight environments in which objectives and environmental features change with respect to time pose a difficult problem with regards to planning optimal flight paths. Path planning methods are typically computationally expensive, and are often difficult to implement in real time if system objectives are changed. This computational problem is compounded when multiple agents are present in the system, as the state and action space grows exponentially. In this work, we use cooperative coevolutionary algorithms in order to develop policies which control agent motion in a dynamic multiagent unmanned aerial system environment such that goals and perceptions change, while ensuring safety constraints are not violated. Rather than replanning new paths when the environment changes, we develop a policy which can map the new environmental features to a trajectory for the agent while ensuring safe and reliable operation, while providing 92% of the theoretically optimal performance

IEEE 802.21 Assisted Seamless and Energy Efficient Handovers in Mixed Networks

NASA Astrophysics Data System (ADS)

Liu, Huaiyu; Maciocco, Christian; Kesavan, Vijay; Low, Andy L. Y.

Network selection is the decision process for a mobile terminal to handoff between homogeneous or heterogeneous networks. With multiple available networks, the selection process must evaluate factors like network services/conditions, monetary cost, system conditions, user preferences etc. In this paper, we investigate network selection using a cost function and information provided by IEEE 802.21. The cost function provides flexibility to balance different factors in decision making and our research is focused on improving both seamlessness and energy efficiency of handovers. Our solution is evaluated using real WiFi, WiMax, and 3G signal strength traces. The results show that appropriate networks were selected based on selection policies, handovers were triggered at optimal times to increase overall network connectivity as compared to traditional triggering schemes, while at the same time the energy consumption of multi-radio devices for both on-going operations as well as during handovers is optimized.

Multiagent Flight Control in Dynamic Environments with Cooperative Coevolutionary Algorithms

NASA Technical Reports Server (NTRS)

Colby, Mitchell; Knudson, Matthew D.; Tumer, Kagan

2014-01-01

Dynamic environments in which objectives and environmental features change with respect to time pose a difficult problem with regards to planning optimal paths through these environments. Path planning methods are typically computationally expensive, and are often difficult to implement in real time if system objectives are changed. This computational problem is compounded when multiple agents are present in the system, as the state and action space grows exponentially with the number of agents in the system. In this work, we use cooperative coevolutionary algorithms in order to develop policies which control agent motion in a dynamic multiagent unmanned aerial system environment such that goals and perceptions change, while ensuring safety constraints are not violated. Rather than replanning new paths when the environment changes, we develop a policy which can map the new environmental features to a trajectory for the agent while ensuring safe and reliable operation, while providing 92% of the theoretically optimal performance.

A Heuristic Algorithm for Planning Personalized Learning Paths for Context-Aware Ubiquitous Learning

ERIC Educational Resources Information Center

Hwang, Gwo-Jen; Kuo, Fan-Ray; Yin, Peng-Yeng; Chuang, Kuo-Hsien

2010-01-01

In a context-aware ubiquitous learning environment, learning systems can detect students' learning behaviors in the real-world with the help of context-aware (sensor) technology; that is, students can be guided to observe or operate real-world objects with personalized support from the digital world. In this study, an optimization problem that…

Advanced Kalman Filter for Real-Time Responsiveness in Complex Systems

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

Welch, Gregory Francis; Zhang, Jinghe

2014-06-10

Complex engineering systems pose fundamental challenges in real-time operations and control because they are highly dynamic systems consisting of a large number of elements with severe nonlinearities and discontinuities. Today’s tools for real-time complex system operations are mostly based on steady state models, unable to capture the dynamic nature and too slow to prevent system failures. We developed advanced Kalman filtering techniques and the formulation of dynamic state estimation using Kalman filtering techniques to capture complex system dynamics in aiding real-time operations and control. In this work, we looked at complex system issues including severe nonlinearity of system equations, discontinuitiesmore » caused by system controls and network switches, sparse measurements in space and time, and real-time requirements of power grid operations. We sought to bridge the disciplinary boundaries between Computer Science and Power Systems Engineering, by introducing methods that leverage both existing and new techniques. While our methods were developed in the context of electrical power systems, they should generalize to other large-scale scientific and engineering applications.« less

Road map to adaptive optimal control. [jet engine control

NASA Technical Reports Server (NTRS)

Boyer, R.

1980-01-01

A building block control structure leading toward adaptive, optimal control for jet engines is developed. This approach simplifies the addition of new features and allows for easier checkout of the control by providing a baseline system for comparison. Also, it is possible to eliminate certain features that do not have payoff by being selective in the addition of new building blocks to be added to the baseline system. The minimum risk approach specifically addresses the need for active identification of the plant to be controlled in real time and real time optimization of the control for the identified plant.

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

Veedu, Vinod; Hadmack, Michael; Pollock, Jacob

Nanite™ is a cementitious material that contains a proprietary formulation of functionalized nanomaterial additive to transform conventional cement into a smart material responsive to pressure (or stress), temperature, and any intrinsic changes in composition. This project has identified optimal sensing modalities of smart well cement and demonstrated how real-time sensing of Nanite™ can improve long-term wellbore integrity and zonal isolation in shale gas and applicable oil and gas operations. Oceanit has explored Nanite’s electrical sensing properties in depth and has advanced the technology from laboratory proof-of-concept to sub-scale testing in preparation for field trials.

Parameter Optimization for Turbulent Reacting Flows Using Adjoints

NASA Astrophysics Data System (ADS)

Lapointe, Caelan; Hamlington, Peter E.

2017-11-01

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

Track Detection in Railway Sidings Based on MEMS Gyroscope Sensors

PubMed Central

Broquetas, Antoni; Comerón, Adolf; Gelonch, Antoni; Fuertes, Josep M.; Castro, J. Antonio; Felip, Damià; López, Miguel A.; Pulido, José A.

2012-01-01

The paper presents a two-step technique for real-time track detection in single-track railway sidings using low-cost MEMS gyroscopes. The objective is to reliably know the path the train has taken in a switch, diverted or main road, immediately after the train head leaves the switch. The signal delivered by the gyroscope is first processed by an adaptive low-pass filter that rejects noise and converts the temporal turn rate data in degree/second units into spatial turn rate data in degree/meter. The conversion is based on the travelled distance taken from odometer data. The filter is implemented to achieve a speed-dependent cut-off frequency to maximize the signal-to-noise ratio. Although direct comparison of the filtered turn rate signal with a predetermined threshold is possible, the paper shows that better detection performance can be achieved by processing the turn rate signal with a filter matched to the rail switch curvature parameters. Implementation aspects of the track detector have been optimized for real-time operation. The detector has been tested with both simulated data and real data acquired in railway campaigns. PMID:23443376

Periodate-assisted pulsed sonocatalysis of real textile wastewater in the presence of MgO nanoparticles: Response surface methodological optimization.

PubMed

Darvishi Cheshmeh Soltani, Reza; Safari, Mahdi

2016-09-01

The improvement of sonocatalytic treatment of real textile wastewater in the presence of MgO nanoparticles was the main goal of the present study. According to our preliminary results, the application of pulse mode of sonication, together with the addition of periodate ions, produced the greatest sonocatalytic activity and consequently, the highest chemical oxygen demand (COD) removal efficiency (73.95%) among all the assessed options. In the following, pulsed sonocatalysis of real textile wastewater in the presence of periodate ions was evaluated response surface methodologically on the basis of central composite design. Accordingly, a high correlation coefficient of 0.95 was attained for the applied statistical strategy to optimize the process. As results, a pulsed sonication time of 141min, MgO dosage of 2.4g/L, solution temperature of 314K and periodate concentration of 0.11M gave the maximum COD removal of about 85%. Under aforementioned operational conditions, the removal of total organic carbon (TOC) was obtained to be 63.34% with the reaction rate constant of 7.1×10(-3)min(-1) based on the pseudo-first order kinetic model (R(2)=0.99). Overall, periodate-assisted pulsed sonocatalysis over MgO nanoparticles can be applied as an efficient alternative process for treating and mineralizing real textile wastewater with good reusability potential. Copyright © 2016 Elsevier B.V. All rights reserved.

PRAIS: Distributed, real-time knowledge-based systems made easy

NASA Technical Reports Server (NTRS)

Goldstein, David G.

1990-01-01

This paper discusses an architecture for real-time, distributed (parallel) knowledge-based systems called the Parallel Real-time Artificial Intelligence System (PRAIS). PRAIS strives for transparently parallelizing production (rule-based) systems, even when under real-time constraints. PRAIS accomplishes these goals by incorporating a dynamic task scheduler, operating system extensions for fact handling, and message-passing among multiple copies of CLIPS executing on a virtual blackboard. This distributed knowledge-based system tool uses the portability of CLIPS and common message-passing protocols to operate over a heterogeneous network of processors.

Method for Real-Time Model Based Structural Anomaly Detection

NASA Technical Reports Server (NTRS)

Urnes, James M., Sr. (Inventor); Smith, Timothy A. (Inventor); Reichenbach, Eric Y. (Inventor)

2015-01-01

A system and methods for real-time model based vehicle structural anomaly detection are disclosed. A real-time measurement corresponding to a location on a vehicle structure during an operation of the vehicle is received, and the real-time measurement is compared to expected operation data for the location to provide a modeling error signal. A statistical significance of the modeling error signal to provide an error significance is calculated, and a persistence of the error significance is determined. A structural anomaly is indicated, if the persistence exceeds a persistence threshold value.

A curriculum for real-time computer and control systems engineering

NASA Technical Reports Server (NTRS)

Halang, Wolfgang A.

1990-01-01

An outline of a syllabus for the education of real-time-systems engineers is given. This comprises the treatment of basic concepts, real-time software engineering, and programming in high-level real-time languages, real-time operating systems with special emphasis on such topics as task scheduling, hardware architectures, and especially distributed automation structures, process interfacing, system reliability and fault-tolerance, and integrated project development support systems. Accompanying course material and laboratory work are outlined, and suggestions for establishing a laboratory with advanced, but low-cost, hardware and software are provided. How the curriculum can be extended into a second semester is discussed, and areas for possible graduate research are listed. The suitable selection of a high-level real-time language and supporting operating system for teaching purposes is considered.

A real-time monitoring system for the facial nerve.

PubMed

Prell, Julian; Rachinger, Jens; Scheller, Christian; Alfieri, Alex; Strauss, Christian; Rampp, Stefan

2010-06-01

Damage to the facial nerve during surgery in the cerebellopontine angle is indicated by A-trains, a specific electromyogram pattern. These A-trains can be quantified by the parameter "traintime," which is reliably correlated with postoperative functional outcome. The system presented was designed to monitor traintime in real-time. A dedicated hardware and software platform for automated continuous analysis of the intraoperative facial nerve electromyogram was specifically designed. The automatic detection of A-trains is performed by a software algorithm for real-time analysis of nonstationary biosignals. The system was evaluated in a series of 30 patients operated on for vestibular schwannoma. A-trains can be detected and measured automatically by the described method for real-time analysis. Traintime is monitored continuously via a graphic display and is shown as an absolute numeric value during the operation. It is an expression of overall, cumulated length of A-trains in a given channel; a high correlation between traintime as measured by real-time analysis and functional outcome immediately after the operation (Spearman correlation coefficient [rho] = 0.664, P < .001) and in long-term outcome (rho = 0.631, P < .001) was observed. Automated real-time analysis of the intraoperative facial nerve electromyogram is the first technique capable of reliable continuous real-time monitoring. It can critically contribute to the estimation of functional outcome during the course of the operative procedure.

U.S. Geological Survey Real-Time River Data Applications

USGS Publications Warehouse

Morlock, Scott E.

1998-01-01

Real-time river data provided by the USGS originate from streamflow-gaging stations. The USGS operates and maintains a network of more than 7,000 such stations across the nation (Mason and Wieger, 1995). These gaging stations, used to produce records of stage and streamflow data, are operated in cooperation with local, state, and other federal agencies. The USGS office in Indianapolis operates a statewide network of more than 170 gaging stations. The instrumentation at USGS gaging stations monitors and records river information, primarily river stage (fig. 1). As technological advances are made, many USGS gaging stations are being retrofitted with electronic instrumentation to monitor and record river data. Electronic instrumentation facilitates transmission of real-time or near real-time river data for use by government agencies in such flood-related tasks as operating flood-control structures and ordering evacuations.

Real-time PCR method combined with immunomagnetic separation for detecting healthy and heat-injured Salmonella Typhimurium on raw duck wings.

PubMed

Zheng, Qianwang; Mikš-Krajnik, Marta; Yang, Yishan; Xu, Wang; Yuk, Hyun-Gyun

2014-09-01

Conventional culture detection methods are time consuming and labor-intensive. For this reason, an alternative rapid method combining real-time PCR and immunomagnetic separation (IMS) was investigated in this study to detect both healthy and heat-injured Salmonella Typhimurium on raw duck wings. Firstly, the IMS method was optimized by determining the capture efficiency of Dynabeads(®) on Salmonella cells on raw duck wings with different bead incubation (10, 30 and 60 min) and magnetic separation (3, 10 and 30 min) times. Secondly, three Taqman primer sets, Sal, invA and ttr, were evaluated to optimize the real-time PCR protocol by comparing five parameters: inclusivity, exclusivity, PCR efficiency, detection probability and limit of detection (LOD). Thirdly, the optimized real-time PCR, in combination with IMS (PCR-IMS) assay, was compared with a standard ISO and a real-time PCR (PCR) method by analyzing artificially inoculated raw duck wings with healthy and heat-injured Salmonella cells at 10(1) and 10(0) CFU/25 g. Finally, the optimized PCR-IMS assay was validated for Salmonella detection in naturally contaminated raw duck wing samples. Under optimal IMS conditions (30 min bead incubation and 3 min magnetic separation times), approximately 85 and 64% of S. Typhimurium cells were captured by Dynabeads® from pure culture and inoculated raw duck wings, respectively. Although Sal and ttr primers exhibited 100% inclusivity and exclusivity for 16 Salmonella spp. and 36 non-Salmonella strains, the Sal primer showed lower LOD (10(3) CFU/ml) and higher PCR efficiency (94.1%) than the invA and ttr primers. Moreover, for Sal and invA primers, 100% detection probability on raw duck wings suspension was observed at 10(3) and 10(4) CFU/ml with and without IMS, respectively. Thus, the Sal primer was chosen for further experiments. The optimized PCR-IMS method was significantly (P=0.0011) better at detecting healthy Salmonella cells after 7-h enrichment than traditional PCR method. However there was no significant difference between the two methods with longer enrichment time (14 h). The diagnostic accuracy of PCR-IMS was shown to be 98.3% through the validation study. These results indicate that the optimized PCR-IMS method in this study could provide a sensitive, specific and rapid detection method for Salmonella on raw duck wings, enabling 10-h detection. However, a longer enrichment time could be needed for resuscitation and reliable detection of heat-injured cells. Copyright © 2014 Elsevier B.V. All rights reserved.

A new generation of real-time DOS technology for mission-oriented system integration and operation

NASA Technical Reports Server (NTRS)

Jensen, E. Douglas

1988-01-01

Information is given on system integration and operation (SIO) requirements and a new generation of technical approaches for SIO. Real-time, distribution, survivability, and adaptability requirements and technical approaches are covered. An Alpha operating system program management overview is outlined.

Optimal assignment of workers to supporting services in a hospital

NASA Astrophysics Data System (ADS)

Sawik, Bartosz; Mikulik, Jerzy

2008-01-01

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

Never Use the Complete Search Space: a Concept to Enhance the Optimization Procedure for Monitoring Networks

NASA Astrophysics Data System (ADS)

Bode, F.; Reuschen, S.; Nowak, W.

2015-12-01

Drinking-water well catchments include many potential sources of contaminations like gas stations or agriculture. Finding optimal positions of early-warning monitoring wells is challenging because there are various parameters (and their uncertainties) that influence the reliability and optimality of any suggested monitoring location or monitoring network.The overall goal of this project is to develop and establish a concept to assess, design and optimize early-warning systems within well catchments. Such optimal monitoring networks need to optimize three competing objectives: a high detection probability, which can be reached by maximizing the "field of vision" of the monitoring network, a long early-warning time such that there is enough time left to install counter measures after first detection, and the overall operating costs of the monitoring network, which should ideally be reduced to a minimum. The method is based on numerical simulation of flow and transport in heterogeneous porous media coupled with geostatistics and Monte-Carlo, scenario analyses for real data, respectively, wrapped up within the framework of formal multi-objective optimization using a genetic algorithm.In order to speed up the optimization process and to better explore the Pareto-front, we developed a concept that forces the algorithm to search only in regions of the search space where promising solutions can be expected. We are going to show how to define these regions beforehand, using knowledge of the optimization problem, but also how to define them independently of problem attributes. With that, our method can be used with and/or without detailed knowledge of the objective functions.In summary, our study helps to improve optimization results in less optimization time by meaningful restrictions of the search space. These restrictions can be done independently of the optimization problem, but also in a problem-specific manner.

Attention focussing and anomaly detection in real-time systems monitoring

NASA Technical Reports Server (NTRS)

Doyle, Richard J.; Chien, Steve A.; Fayyad, Usama M.; Porta, Harry J.

1993-01-01

In real-time monitoring situations, more information is not necessarily better. When faced with complex emergency situations, operators can experience information overload and a compromising of their ability to react quickly and correctly. We describe an approach to focusing operator attention in real-time systems monitoring based on a set of empirical and model-based measures for determining the relative importance of sensor data.

A new real-time guidance strategy for aerodynamic ascent flight

NASA Astrophysics Data System (ADS)

Yamamoto, Takayuki; Kawaguchi, Jun'ichiro

2007-12-01

Reusable launch vehicles are conceived to constitute the future space transportation system. If these vehicles use air-breathing propulsion and lift taking-off horizontally, the optimal steering for these vehicles exhibits completely different behavior from that in conventional rockets flight. In this paper, the new guidance strategy is proposed. This method derives from the optimality condition as for steering and an analysis concludes that the steering function takes the form comprised of Linear and Logarithmic terms, which include only four parameters. The parameter optimization of this method shows the acquired terminal horizontal velocity is almost same with that obtained by the direct numerical optimization. This supports the parameterized Liner Logarithmic steering law. And here is shown that there exists a simple linear relation between the terminal states and the parameters to be corrected. The relation easily makes the parameters determined to satisfy the terminal boundary conditions in real-time. The paper presents the guidance results for the practical application cases. The results show the guidance is well performed and satisfies the terminal boundary conditions specified. The strategy built and presented here does guarantee the robust solution in real-time excluding any optimization process, and it is found quite practical.

Real-Time System for Water Modeling and Management

NASA Astrophysics Data System (ADS)

Lee, J.; Zhao, T.; David, C. H.; Minsker, B.

2012-12-01

Working closely with the Texas Commission on Environmental Quality (TCEQ) and the University of Texas at Austin (UT-Austin), we are developing a real-time system for water modeling and management using advanced cyberinfrastructure, data integration and geospatial visualization, and numerical modeling. The state of Texas suffered a severe drought in 2011 that cost the state $7.62 billion in agricultural losses (crops and livestock). Devastating situations such as this could potentially be avoided with better water modeling and management strategies that incorporate state of the art simulation and digital data integration. The goal of the project is to prototype a near-real-time decision support system for river modeling and management in Texas that can serve as a national and international model to promote more sustainable and resilient water systems. The system uses National Weather Service current and predicted precipitation data as input to the Noah-MP Land Surface model, which forecasts runoff, soil moisture, evapotranspiration, and water table levels given land surface features. These results are then used by a river model called RAPID, along with an error model currently under development at UT-Austin, to forecast stream flows in the rivers. Model forecasts are visualized as a Web application for TCEQ decision makers, who issue water diversion (withdrawal) permits and any needed drought restrictions; permit holders; and reservoir operation managers. Users will be able to adjust model parameters to predict the impacts of alternative curtailment scenarios or weather forecasts. A real-time optimization system under development will help TCEQ to identify optimal curtailment strategies to minimize impacts on permit holders and protect health and safety. To develop the system we have implemented RAPID as a remotely-executed modeling service using the Cyberintegrator workflow system with input data downloaded from the North American Land Data Assimilation System. The Cyberintegrator workflow system provides RESTful web services for users to provide inputs, execute workflows, and retrieve outputs. Along with REST endpoints, PAW (Publishable Active Workflows) provides the web user interface toolkit for us to develop web applications with scientific workflows. The prototype web application is built on top of workflows with PAW, so that users will have a user-friendly web environment to provide input parameters, execute the model, and visualize/retrieve the results using geospatial mapping tools. In future work the optimization model will be developed and integrated into the workflow.; Real-Time System for Water Modeling and Management

Real-Time Neural Signals Decoding onto Off-the-Shelf DSP Processors for Neuroprosthetic Applications.

PubMed

Pani, Danilo; Barabino, Gianluca; Citi, Luca; Meloni, Paolo; Raspopovic, Stanisa; Micera, Silvestro; Raffo, Luigi

2016-09-01

The control of upper limb neuroprostheses through the peripheral nervous system (PNS) can allow restoring motor functions in amputees. At present, the important aspect of the real-time implementation of neural decoding algorithms on embedded systems has been often overlooked, notwithstanding the impact that limited hardware resources have on the efficiency/effectiveness of any given algorithm. Present study is addressing the optimization of a template matching based algorithm for PNS signals decoding that is a milestone for its real-time, full implementation onto a floating-point digital signal processor (DSP). The proposed optimized real-time algorithm achieves up to 96% of correct classification on real PNS signals acquired through LIFE electrodes on animals, and can correctly sort spikes of a synthetic cortical dataset with sufficiently uncorrelated spike morphologies (93% average correct classification) comparably to the results obtained with top spike sorter (94% on average on the same dataset). The power consumption enables more than 24 h processing at the maximum load, and latency model has been derived to enable a fair performance assessment. The final embodiment demonstrates the real-time performance onto a low-power off-the-shelf DSP, opening to experiments exploiting the efferent signals to control a motor neuroprosthesis.

Development and use of interactive displays in real-time ground support research facilities

NASA Technical Reports Server (NTRS)

Rhea, Donald C.; Hammons, Kvin R.; Malone, Jacqueline C.; Nesel, Michael C.

1989-01-01

The NASA Western Aeronautical Test Range (WATR) is one of the world's most advanced aeronautical research flight test support facilities. A variety of advanced and often unique real-time interactive displays has been developed for use in the mission control centers (MCC) to support research flight and ground testing. These dispalys consist of applications operating on systems described as real-time interactive graphics super workstations and real-time interactive PC/AT compatible workstations. This paper reviews these two types of workstations and the specific applications operating on each display system. The applications provide examples that demonstrate overall system capability applicable for use in other ground-based real-time research/test facilities.

Development and operation of a real-time simulation at the NASA Ames Vertical Motion Simulator

NASA Technical Reports Server (NTRS)

Sweeney, Christopher; Sheppard, Shirin; Chetelat, Monique

1993-01-01

The Vertical Motion Simulator (VMS) facility at the NASA Ames Research Center combines the largest vertical motion capability in the world with a flexible real-time operating system allowing research to be conducted quickly and effectively. Due to the diverse nature of the aircraft simulated and the large number of simulations conducted annually, the challenge for the simulation engineer is to develop an accurate real-time simulation in a timely, efficient manner. The SimLab facility and the software tools necessary for an operating simulation will be discussed. Subsequent sections will describe the development process through operation of the simulation; this includes acceptance of the model, validation, integration and production phases.

Global Optimization of Low-Thrust Interplanetary Trajectories Subject to Operational Constraints

NASA Technical Reports Server (NTRS)

Englander, Jacob A.; Vavrina, Matthew A.; Hinckley, David

2016-01-01

Low-thrust interplanetary space missions are highly complex and there can be many locally optimal solutions. While several techniques exist to search for globally optimal solutions to low-thrust trajectory design problems, they are typically limited to unconstrained trajectories. The operational design community in turn has largely avoided using such techniques and has primarily focused on accurate constrained local optimization combined with grid searches and intuitive design processes at the expense of efficient exploration of the global design space. This work is an attempt to bridge the gap between the global optimization and operational design communities by presenting a mathematical framework for global optimization of low-thrust trajectories subject to complex constraints including the targeting of planetary landing sites, a solar range constraint to simplify the thermal design of the spacecraft, and a real-world multi-thruster electric propulsion system that must switch thrusters on and off as available power changes over the course of a mission.

The embedded operating system project

NASA Technical Reports Server (NTRS)

Campbell, R. H.

1985-01-01

The design and construction of embedded operating systems for real-time advanced aerospace applications was investigated. The applications require reliable operating system support that must accommodate computer networks. Problems that arise in the construction of such operating systems, reconfiguration, consistency and recovery in a distributed system, and the issues of real-time processing are reported. A thesis that provides theoretical foundations for the use of atomic actions to support fault tolerance and data consistency in real-time object-based system is included. The following items are addressed: (1) atomic actions and fault-tolerance issues; (2) operating system structure; (3) program development; (4) a reliable compiler for path Pascal; and (5) mediators, a mechanism for scheduling distributed system processes.

Real-time optimizations for integrated smart network camera

NASA Astrophysics Data System (ADS)

Desurmont, Xavier; Lienard, Bruno; Meessen, Jerome; Delaigle, Jean-Francois

2005-02-01

We present an integrated real-time smart network camera. This system is composed of an image sensor, an embedded PC based electronic card for image processing and some network capabilities. The application detects events of interest in visual scenes, highlights alarms and computes statistics. The system also produces meta-data information that could be shared between other cameras in a network. We describe the requirements of such a system and then show how the design of the system is optimized to process and compress video in real-time. Indeed, typical video-surveillance algorithms as background differencing, tracking and event detection should be highly optimized and simplified to be used in this hardware. To have a good adequation between hardware and software in this light embedded system, the software management is written on top of the java based middle-ware specification established by the OSGi alliance. We can integrate easily software and hardware in complex environments thanks to the Java Real-Time specification for the virtual machine and some network and service oriented java specifications (like RMI and Jini). Finally, we will report some outcomes and typical case studies of such a camera like counter-flow detection.

Enabling Next-Generation Multicore Platforms in Embedded Applications

DTIC Science & Technology

2014-04-01

mapping to sets 129 − 256 ) to the second page in memory, color 2 (sets 257 − 384) to the third page, and so on. Then, after the 32nd page, all 212 sets...the Real-Time Nested Locking Protocol (RNLP) [56], a recently developed multiprocessor real-time locking protocol that optimally supports the...RELEASE; DISTRIBUTION UNLIMITED 15 In general, the problems of optimally assigning tasks to processors and colors to tasks are both NP-hard in the

Crowd evacuation model based on bacterial foraging algorithm

NASA Astrophysics Data System (ADS)

Shibiao, Mu; Zhijun, Chen

To understand crowd evacuation, a model based on a bacterial foraging algorithm (BFA) is proposed in this paper. Considering dynamic and static factors, the probability of pedestrian movement is established using cellular automata. In addition, given walking and queue times, a target optimization function is built. At the same time, a BFA is used to optimize the objective function. Finally, through real and simulation experiments, the relationship between the parameters of evacuation time, exit width, pedestrian density, and average evacuation speed is analyzed. The results show that the model can effectively describe a real evacuation.

EOS: A project to investigate the design and construction of real-time distributed Embedded Operating Systems

NASA Technical Reports Server (NTRS)

Campbell, R. H.; Essick, Ray B.; Johnston, Gary; Kenny, Kevin; Russo, Vince

1987-01-01

Project EOS is studying the problems of building adaptable real-time embedded operating systems for the scientific missions of NASA. Choices (A Class Hierarchical Open Interface for Custom Embedded Systems) is an operating system designed and built by Project EOS to address the following specific issues: the software architecture for adaptable embedded parallel operating systems, the achievement of high-performance and real-time operation, the simplification of interprocess communications, the isolation of operating system mechanisms from one another, and the separation of mechanisms from policy decisions. Choices is written in C++ and runs on a ten processor Encore Multimax. The system is intended for use in constructing specialized computer applications and research on advanced operating system features including fault tolerance and parallelism.

Efficient Spatiotemporal Clutter Rejection and Nonlinear Filtering-based Dim Resolved and Unresolved Object Tracking Algorithms

NASA Astrophysics Data System (ADS)

Tartakovsky, A.; Tong, M.; Brown, A. P.; Agh, C.

2013-09-01

We develop efficient spatiotemporal image processing algorithms for rejection of non-stationary clutter and tracking of multiple dim objects using non-linear track-before-detect methods. For clutter suppression, we include an innovative image alignment (registration) algorithm. The images are assumed to contain elements of the same scene, but taken at different angles, from different locations, and at different times, with substantial clutter non-stationarity. These challenges are typical for space-based and surface-based IR/EO moving sensors, e.g., highly elliptical orbit or low earth orbit scenarios. The algorithm assumes that the images are related via a planar homography, also known as the projective transformation. The parameters are estimated in an iterative manner, at each step adjusting the parameter vector so as to achieve improved alignment of the images. Operating in the parameter space rather than in the coordinate space is a new idea, which makes the algorithm more robust with respect to noise as well as to large inter-frame disturbances, while operating at real-time rates. For dim object tracking, we include new advancements to a particle non-linear filtering-based track-before-detect (TrbD) algorithm. The new TrbD algorithm includes both real-time full image search for resolved objects not yet in track and joint super-resolution and tracking of individual objects in closely spaced object (CSO) clusters. The real-time full image search provides near-optimal detection and tracking of multiple extremely dim, maneuvering objects/clusters. The super-resolution and tracking CSO TrbD algorithm provides efficient near-optimal estimation of the number of unresolved objects in a CSO cluster, as well as the locations, velocities, accelerations, and intensities of the individual objects. We demonstrate that the algorithm is able to accurately estimate the number of CSO objects and their locations when the initial uncertainty on the number of objects is large. We demonstrate performance of the TrbD algorithm both for satellite-based and surface-based EO/IR surveillance scenarios.

Combining snow depth and innovative skier flow measurements in order to improve snow grooming techniques

NASA Astrophysics Data System (ADS)

Carmagnola, Carlo Maria; Albrecht, Stéphane; Hargoaa, Olivier

2017-04-01

In the last decades, ski resort managers have massively improved their snow management practices, in order to adapt their strategies to the inter-annual variability in snow conditions and to the effects of climate change. New real-time informations, such as snow depth measurements carried out on the ski slopes by grooming machines during their daily operations, have become available, allowing high saving, efficiency and optimization gains (reducing for instance the groomer fuel consumption and operation time and the need for machine-made snow production). In order to take a step forward in improving the grooming techniques, it would be necessary to keep into account also the snow erosion by skiers, which depends mostly on the snow surface properties and on the skier attendance. Today, however, most ski resort managers have only a vague idea of the evolution of the skier flows on each slope during the winter season. In this context, we have developed a new sensor (named Skiflux) able to measure the skier attendance using an infrared beam crossing the slopes. Ten Skiflux sensors have been deployed during the 2016/17 winter season at Val Thorens ski area (French Alps), covering a whole sector of the resort. A dedicated software showing the number of skier passages in real time as been developed as well. Combining this new Skiflux dataset with the snow depth measurements from grooming machines (Snowsat System) and the snow and meteorological conditions measured in-situ (Liberty System from Technoalpin), we were able to create a "real-time skiability index" accounting for the quality of the surface snow and its evolution during the day. Moreover, this new framework allowed us to improve the preparation of ski slopes, suggesting new strategies for adapting the grooming working schedule to the snow quality and the skier attendance. In the near future, this work will benefit from the advances made within the H2020 PROSNOW project ("Provision of a prediction system allowing for management and optimization of snow in Alpine ski resorts"), which has been funded for the period 2017-2020.

MARTe: A Multiplatform Real-Time Framework

NASA Astrophysics Data System (ADS)

Neto, André C.; Sartori, Filippo; Piccolo, Fabio; Vitelli, Riccardo; De Tommasi, Gianmaria; Zabeo, Luca; Barbalace, Antonio; Fernandes, Horacio; Valcarcel, Daniel F.; Batista, Antonio J. N.

2010-04-01

Development of real-time applications is usually associated with nonportable code targeted at specific real-time operating systems. The boundary between hardware drivers, system services, and user code is commonly not well defined, making the development in the target host significantly difficult. The Multithreaded Application Real-Time executor (MARTe) is a framework built over a multiplatform library that allows the execution of the same code in different operating systems. The framework provides the high-level interfaces with hardware, external configuration programs, and user interfaces, assuring at the same time hard real-time performances. End-users of the framework are required to define and implement algorithms inside a well-defined block of software, named Generic Application Module (GAM), that is executed by the real-time scheduler. Each GAM is reconfigurable with a set of predefined configuration meta-parameters and interchanges information using a set of data pipes that are provided as inputs and required as output. Using these connections, different GAMs can be chained either in series or parallel. GAMs can be developed and debugged in a non-real-time system and, only once the robustness of the code and correctness of the algorithm are verified, deployed to the real-time system. The software also supplies a large set of utilities that greatly ease the interaction and debugging of a running system. Among the most useful are a highly efficient real-time logger, HTTP introspection of real-time objects, and HTTP remote configuration. MARTe is currently being used to successfully drive the plasma vertical stabilization controller on the largest magnetic confinement fusion device in the world, with a control loop cycle of 50 ?s and a jitter under 1 ?s. In this particular project, MARTe is used with the Real-Time Application Interface (RTAI)/Linux operating system exploiting the new ?86 multicore processors technology.

Real-Time Event Detection for Monitoring Natural and Source ...

EPA Pesticide Factsheets

The use of event detection systems in finished drinking water systems is increasing in order to monitor water quality in both operational and security contexts. Recent incidents involving harmful algal blooms and chemical spills into watersheds have increased interest in monitoring source water quality prior to treatment. This work highlights the use of the CANARY event detection software in detecting suspected illicit events in an actively monitored watershed in South Carolina. CANARY is an open source event detection software that was developed by USEPA and Sandia National Laboratories. The software works with any type of sensor, utilizes multiple detection algorithms and approaches, and can incorporate operational information as needed. Monitoring has been underway for several years to detect events related to intentional or unintentional dumping of materials into the monitored watershed. This work evaluates the feasibility of using CANARY to enhance the detection of events in this watershed. This presentation will describe the real-time monitoring approach used in this watershed, the selection of CANARY configuration parameters that optimize detection for this watershed and monitoring application, and the performance of CANARY during the time frame analyzed. Further, this work will highlight how rainfall events impacted analysis, and the innovative application of CANARY taken in order to effectively detect the suspected illicit events. This presentation d

Design of Distributed Controllers Seeking Optimal Power Flow Solutions Under Communication Constraints

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

Dall'Anese, Emiliano; Simonetto, Andrea; Dhople, Sairaj

This paper focuses on power distribution networks featuring inverter-interfaced distributed energy resources (DERs), and develops feedback controllers that drive the DER output powers to solutions of time-varying AC optimal power flow (OPF) problems. Control synthesis is grounded on primal-dual-type methods for regularized Lagrangian functions, as well as linear approximations of the AC power-flow equations. Convergence and OPF-solution-tracking capabilities are established while acknowledging: i) communication-packet losses, and ii) partial updates of control signals. The latter case is particularly relevant since it enables asynchronous operation of the controllers where DER setpoints are updated at a fast time scale based on local voltagemore » measurements, and information on the network state is utilized if and when available, based on communication constraints. As an application, the paper considers distribution systems with high photovoltaic integration, and demonstrates that the proposed framework provides fast voltage-regulation capabilities, while enabling the near real-time pursuit of solutions of AC OPF problems.« less

Design of Distributed Controllers Seeking Optimal Power Flow Solutions under Communication Constraints: Preprint

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

Dall'Anese, Emiliano; Simonetto, Andrea; Dhople, Sairaj

This paper focuses on power distribution networks featuring inverter-interfaced distributed energy resources (DERs), and develops feedback controllers that drive the DER output powers to solutions of time-varying AC optimal power flow (OPF) problems. Control synthesis is grounded on primal-dual-type methods for regularized Lagrangian functions, as well as linear approximations of the AC power-flow equations. Convergence and OPF-solution-tracking capabilities are established while acknowledging: i) communication-packet losses, and ii) partial updates of control signals. The latter case is particularly relevant since it enables asynchronous operation of the controllers where DER setpoints are updated at a fast time scale based on local voltagemore » measurements, and information on the network state is utilized if and when available, based on communication constraints. As an application, the paper considers distribution systems with high photovoltaic integration, and demonstrates that the proposed framework provides fast voltage-regulation capabilities, while enabling the near real-time pursuit of solutions of AC OPF problems.« less