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.

Experimental evaluation of dynamic data allocation strategies in a distributed database with changing workloads

NASA Technical Reports Server (NTRS)

Brunstrom, Anna; Leutenegger, Scott T.; Simha, Rahul

1995-01-01

Traditionally, allocation of data in distributed database management systems has been determined by off-line analysis and optimization. This technique works well for static database access patterns, but is often inadequate for frequently changing workloads. In this paper we address how to dynamically reallocate data for partionable distributed databases with changing access patterns. Rather than complicated and expensive optimization algorithms, a simple heuristic is presented and shown, via an implementation study, to improve system throughput by 30 percent in a local area network based system. Based on artificial wide area network delays, we show that dynamic reallocation can improve system throughput by a factor of two and a half for wide area networks. We also show that individual site load must be taken into consideration when reallocating data, and provide a simple policy that incorporates load in the reallocation decision.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Optimization based on benefit of regional energy suppliers of distributed generation in active distribution network

NASA Astrophysics Data System (ADS)

Huo, Xianxu; Li, Guodong; Jiang, Ling; Wang, Xudong

2017-08-01

With the development of electricity market, distributed generation (DG) technology and related policies, regional energy suppliers are encouraged to build DG. Under this background, the concept of active distribution network (ADN) is put forward. In this paper, a bi-level model of intermittent DG considering benefit of regional energy suppliers is proposed. The objective of the upper level is the maximization of benefit of regional energy suppliers. On this basis, the lower level is optimized for each scene. The uncertainties of DG output and load of users, as well as four active management measures, which include demand-side management, curtailing the output power of DG, regulating reactive power compensation capacity and regulating the on-load tap changer, are considered. Harmony search algorithm and particle swarm optimization are combined as a hybrid strategy to solve the model. This model and strategy are tested with IEEE-33 node system, and results of case study indicate that the model and strategy successfully increase the capacity of DG and benefit of regional energy suppliers.

Electricity market design for generator revenue sufficiency with increased variable generation

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

Levin, Todd; Botterud, Audun

Here, we present a computationally efficient mixed-integer program (MIP) that determines optimal generator expansion decisions, and hourly unit commitment and dispatch in a power system. The impact of increasing wind power capacity on the optimal generation mix and generator profitability is analyzed for a test case that approximates the electricity market in Texas (ERCOT). We analyze three market policies that may support resource adequacy: Operating Reserve Demand Curves (ORDC), Fixed Reserve Scarcity Prices (FRSP) and fixed capacity payments (CP). Optimal expansion plans are comparable between the ORDC and FRSP implementations, while capacity payments may result in additional new capacity. Themore » FRSP policy leads to frequent reserves scarcity events and corresponding price spikes, while the ORDC implementation results in more continuous energy prices. Average energy prices decrease with increasing wind penetration under all policies, as do revenues for baseload and wind generators. Intermediate and peak load plants benefit from higher reserve prices and are less exposed to reduced energy prices. All else equal, an ORDC approach may be preferred to FRSP as it results in similar expansion and revenues with less extreme energy prices. A fixed CP leads to additional new flexible NGCT units, but lower profits for other technologies.« less

Electricity market design for generator revenue sufficiency with increased variable generation

DOE PAGES

Levin, Todd; Botterud, Audun

2015-10-01

Here, we present a computationally efficient mixed-integer program (MIP) that determines optimal generator expansion decisions, and hourly unit commitment and dispatch in a power system. The impact of increasing wind power capacity on the optimal generation mix and generator profitability is analyzed for a test case that approximates the electricity market in Texas (ERCOT). We analyze three market policies that may support resource adequacy: Operating Reserve Demand Curves (ORDC), Fixed Reserve Scarcity Prices (FRSP) and fixed capacity payments (CP). Optimal expansion plans are comparable between the ORDC and FRSP implementations, while capacity payments may result in additional new capacity. Themore » FRSP policy leads to frequent reserves scarcity events and corresponding price spikes, while the ORDC implementation results in more continuous energy prices. Average energy prices decrease with increasing wind penetration under all policies, as do revenues for baseload and wind generators. Intermediate and peak load plants benefit from higher reserve prices and are less exposed to reduced energy prices. All else equal, an ORDC approach may be preferred to FRSP as it results in similar expansion and revenues with less extreme energy prices. A fixed CP leads to additional new flexible NGCT units, but lower profits for other technologies.« less

Opportunities and Benefits for Increasing Transmission Capacity between the US Eastern and Western Interconnections

NASA Astrophysics Data System (ADS)

Figueroa-Acevedo, Armando L.

Historically, the primary justification for building wide-area transmission lines in the US and around the world has been based on reliability and economic criteria. Today, the influence of renewable portfolio standards (RPS), Environmental Protection Agency (EPA) regulations, transmission needs, load diversity, and grid flexibility requirements drives interest in high capacity wide-area transmission. By making use of an optimization model to perform long-term (15 years) co-optimized generation and transmission expansion planning, this work explored the benefits of increasing transmission capacity between the US Eastern and Western Interconnections under different policy and futures assumptions. The model assessed tradeoffs between investments in cross-interconnection HVDC transmission, AC transmission needs within each interconnection, generation investment costs, and operational costs, while satisfying different policy compliance constraints. Operational costs were broken down into the following market products: energy, up-/down regulation reserve, and contingency reserve. In addition, the system operating flexibility requirements were modeled as a function of net-load variability so that the flexibility of the non-wind/non-solar resources increases with increased wind and solar investment. In addition, planning reserve constraints are imposed under the condition that they be deliverable to the load. Thus, the model allows existing and candidate generation resources for both operating reserves and deliverable planning reserves to be shared throughout the interconnections, a feature which significantly drives identification of least-cost investments. This model is used with a 169-bus representation of the North American power grid to design four different high-capacity wide-area transmission infrastructures. Results from this analysis suggest that, under policy that imposes a high-renewable future, the benefits of high capacity transmission between the Eastern and Western Interconnections outweigh its cost. A sensitivity analysis is included to test the robustness of each design under different future assumptions and approximate upper and lower bounds for cross-seam transmission between the Eastern and Western Interconnections.

Watershed-based point sources permitting strategy and dynamic permit-trading analysis.

PubMed

Ning, Shu-Kuang; Chang, Ni-Bin

2007-09-01

Permit-trading policy in a total maximum daily load (TMDL) program may provide an additional avenue to produce environmental benefit, which closely approximates what would be achieved through a command and control approach, with relatively lower costs. One of the important considerations that might affect the effective trading mechanism is to determine the dynamic transaction prices and trading ratios in response to seasonal changes of assimilative capacity in the river. Advanced studies associated with multi-temporal spatially varied trading ratios among point sources to manage water pollution hold considerable potential for industries and policy makers alike. This paper aims to present an integrated simulation and optimization analysis for generating spatially varied trading ratios and evaluating seasonal transaction prices accordingly. It is designed to configure a permit-trading structure basin-wide and provide decision makers with a wealth of cost-effective, technology-oriented, risk-informed, and community-based management strategies. The case study, seamlessly integrating a QUAL2E simulation model with an optimal waste load allocation (WLA) scheme in a designated TMDL study area, helps understand the complexity of varying environmental resources values over space and time. The pollutants of concern in this region, which are eligible for trading, mainly include both biochemical oxygen demand (BOD) and ammonia-nitrogen (NH3-N). The problem solution, as a consequence, suggests an array of waste load reduction targets in a well-defined WLA scheme and exhibits a dynamic permit-trading framework among different sub-watersheds in the study area. Research findings gained in this paper may extend to any transferable dynamic-discharge permit (TDDP) program worldwide.

Local Approximation and Hierarchical Methods for Stochastic Optimization

NASA Astrophysics Data System (ADS)

Cheng, Bolong

In this thesis, we present local and hierarchical approximation methods for two classes of stochastic optimization problems: optimal learning and Markov decision processes. For the optimal learning problem class, we introduce a locally linear model with radial basis function for estimating the posterior mean of the unknown objective function. The method uses a compact representation of the function which avoids storing the entire history, as is typically required by nonparametric methods. We derive a knowledge gradient policy with the locally parametric model, which maximizes the expected value of information. We show the policy is asymptotically optimal in theory, and experimental works suggests that the method can reliably find the optimal solution on a range of test functions. For the Markov decision processes problem class, we are motivated by an application where we want to co-optimize a battery for multiple revenue, in particular energy arbitrage and frequency regulation. The nature of this problem requires the battery to make charging and discharging decisions at different time scales while accounting for the stochastic information such as load demand, electricity prices, and regulation signals. Computing the exact optimal policy becomes intractable due to the large state space and the number of time steps. We propose two methods to circumvent the computation bottleneck. First, we propose a nested MDP model that structure the co-optimization problem into smaller sub-problems with reduced state space. This new model allows us to understand how the battery behaves down to the two-second dynamics (that of the frequency regulation market). Second, we introduce a low-rank value function approximation for backward dynamic programming. This new method only requires computing the exact value function for a small subset of the state space and approximate the entire value function via low-rank matrix completion. We test these methods on historical price data from the PJM Interconnect and show that it outperforms the baseline approach used in the industry.

Co-optimizing Generation and Transmission Expansion with Wind Power in Large-Scale Power Grids Implementation in the US Eastern Interconnection

DOE PAGES

You, Shutang; Hadley, Stanton W.; Shankar, Mallikarjun; ...

2016-01-12

This paper studies the generation and transmission expansion co-optimization problem with a high wind power penetration rate in the US Eastern Interconnection (EI) power grid. In this paper, the generation and transmission expansion problem for the EI system is modeled as a mixed-integer programming (MIP) problem. Our paper also analyzed a time series generation method to capture the variation and correlation of both load and wind power across regions. The obtained series can be easily introduced into the expansion planning problem and then solved through existing MIP solvers. Simulation results show that the proposed planning model and series generation methodmore » can improve the expansion result significantly through modeling more detailed information of wind and load variation among regions in the US EI system. Moreover, the improved expansion plan that combines generation and transmission will aid system planners and policy makers to maximize the social welfare in large-scale power grids.« less

Assessment of Distributed Generation Potential in JapaneseBuildings

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

Zhou, Nan; Marnay, Chris; Firestone, Ryan

2005-05-25

To meet growing energy demands, energy efficiency, renewable energy, and on-site generation coupled with effective utilization of exhaust heat will all be required. Additional benefit can be achieved by integrating these distributed technologies into distributed energy resource (DER) systems (or microgrids). This research investigates a method of choosing economically optimal DER, expanding on prior studies at the Berkeley Lab using the DER design optimization program, the Distributed Energy Resources Customer Adoption Model (DER-CAM). DER-CAM finds the optimal combination of installed equipment from available DER technologies, given prevailing utility tariffs, site electrical and thermal loads, and a menu of available equipment.more » It provides a global optimization, albeit idealized, that shows how the site energy loads can be served at minimum cost by selection and operation of on-site generation, heat recovery, and cooling. Five prototype Japanese commercial buildings are examined and DER-CAM applied to select the economically optimal DER system for each. The five building types are office, hospital, hotel, retail, and sports facility. Based on the optimization results, energy and emission reductions are evaluated. Furthermore, a Japan-U.S. comparison study of policy, technology, and utility tariffs relevant to DER installation is presented. Significant decreases in fuel consumption, carbon emissions, and energy costs were seen in the DER-CAM results. Savings were most noticeable in the sports facility (a very favourable CHP site), followed by the hospital, hotel, and office building.« less

Critical loads as a policy tool for protecting ecosystems from the effects of air pollutants

Treesearch

Douglas A. Burns; Tamara Blett; Richard Haeuber; Linda H. Pardo

2008-01-01

Framing the effects of air pollutants on ecosystems in terms of a "critical load" provides a meaningful approach for research scientists to communicate policy-relevant science to air-quality policy makers and natural resource managers. A critical-loads approach has been widely used to shape air-pollutant control policy in Europe since the 1980s, yet has only...

A set-covering formulation for a drayage problem with single and double container loads

NASA Astrophysics Data System (ADS)

Ghezelsoflu, A.; Di Francesco, M.; Frangioni, A.; Zuddas, P.

2018-01-01

This paper addresses a drayage problem, which is motivated by the case study of a real carrier. Its trucks carry one or two containers from a port to importers and from exporters to the port. Since up to four customers can be served in each route, we propose a set-covering formulation for this problem where all possible routes are enumerated. This model can be efficiently solved to optimality by a commercial solver, significantly outperforming a previously proposed node-arc formulation. Moreover, the model can be effectively used to evaluate a new distribution policy, which results in an enlarged set of feasible routes and can increase savings w.r.t. the policy currently employed by the carrier.

Optimal load scheduling in commercial and residential microgrids

NASA Astrophysics Data System (ADS)

Ganji Tanha, Mohammad Mahdi

Residential and commercial electricity customers use more than two third of the total energy consumed in the United States, representing a significant resource of demand response. Price-based demand response, which is in response to changes in electricity prices, represents the adjustments in load through optimal load scheduling (OLS). In this study, an efficient model for OLS is developed for residential and commercial microgrids which include aggregated loads in single-units and communal loads. Single unit loads which include fixed, adjustable and shiftable loads are controllable by the unit occupants. Communal loads which include pool pumps, elevators and central heating/cooling systems are shared among the units. In order to optimally schedule residential and commercial loads, a community-based optimal load scheduling (CBOLS) is proposed in this thesis. The CBOLS schedule considers hourly market prices, occupants' comfort level, and microgrid operation constraints. The CBOLS' objective in residential and commercial microgrids is the constrained minimization of the total cost of supplying the aggregator load, defined as the microgrid load minus the microgrid generation. This problem is represented by a large-scale mixed-integer optimization for supplying single-unit and communal loads. The Lagrangian relaxation methodology is used to relax the linking communal load constraint and decompose the independent single-unit functions into subproblems which can be solved in parallel. The optimal solution is acceptable if the aggregator load limit and the duality gap are within the bounds. If any of the proposed criteria is not satisfied, the Lagrangian multiplier will be updated and a new optimal load schedule will be regenerated until both constraints are satisfied. The proposed method is applied to several case studies and the results are presented for the Galvin Center load on the 16th floor of the IIT Tower in Chicago.

Optimization of Nanowire-Resistance Load Logic Inverter.

PubMed

Hashim, Yasir; Sidek, Othman

2015-09-01

This study is the first to demonstrate characteristics optimization of nanowire resistance load inverter. Noise margins and inflection voltage of transfer characteristics are used as limiting factors in this optimization. Results indicate that optimization depends on resistance value. Increasing of load resistor tends to increasing in noise margins until saturation point, increasing load resistor after this point will not improve noise margins significantly.

An implementation of particle swarm optimization to evaluate optimal under-voltage load shedding in competitive electricity markets

NASA Astrophysics Data System (ADS)

Hosseini-Bioki, M. M.; Rashidinejad, M.; Abdollahi, A.

2013-11-01

Load shedding is a crucial issue in power systems especially under restructured electricity environment. Market-driven load shedding in reregulated power systems associated with security as well as reliability is investigated in this paper. A technoeconomic multi-objective function is introduced to reveal an optimal load shedding scheme considering maximum social welfare. The proposed optimization problem includes maximum GENCOs and loads' profits as well as maximum loadability limit under normal and contingency conditions. Particle swarm optimization (PSO) as a heuristic optimization technique, is utilized to find an optimal load shedding scheme. In a market-driven structure, generators offer their bidding blocks while the dispatchable loads will bid their price-responsive demands. An independent system operator (ISO) derives a market clearing price (MCP) while rescheduling the amount of generating power in both pre-contingency and post-contingency conditions. The proposed methodology is developed on a 3-bus system and then is applied to a modified IEEE 30-bus test system. The obtained results show the effectiveness of the proposed methodology in implementing the optimal load shedding satisfying social welfare by maintaining voltage stability margin (VSM) through technoeconomic analyses.

DTS: Building custom, intelligent schedulers

NASA Technical Reports Server (NTRS)

Hansson, Othar; Mayer, Andrew

1994-01-01

DTS is a decision-theoretic scheduler, built on top of a flexible toolkit -- this paper focuses on how the toolkit might be reused in future NASA mission schedulers. The toolkit includes a user-customizable scheduling interface, and a 'Just-For-You' optimization engine. The customizable interface is built on two metaphors: objects and dynamic graphs. Objects help to structure problem specifications and related data, while dynamic graphs simplify the specification of graphical schedule editors (such as Gantt charts). The interface can be used with any 'back-end' scheduler, through dynamically-loaded code, interprocess communication, or a shared database. The 'Just-For-You' optimization engine includes user-specific utility functions, automatically compiled heuristic evaluations, and a postprocessing facility for enforcing scheduling policies. The optimization engine is based on BPS, the Bayesian Problem-Solver (1,2), which introduced a similar approach to solving single-agent and adversarial graph search problems.

Demand side management in recycling and electricity retail pricing

NASA Astrophysics Data System (ADS)

Kazan, Osman

This dissertation addresses several problems from the recycling industry and electricity retail market. The first paper addresses a real-life scheduling problem faced by a national industrial recycling company. Based on their practices, a scheduling problem is defined, modeled, analyzed, and a solution is approximated efficiently. The recommended application is tested on the real-life data and randomly generated data. The scheduling improvements and the financial benefits are presented. The second problem is from electricity retail market. There are well-known patterns in daily usage in hours. These patterns change in shape and magnitude by seasons and days of the week. Generation costs are multiple times higher during the peak hours of the day. Yet most consumers purchase electricity at flat rates. This work explores analytic pricing tools to reduce peak load electricity demand for retailers. For that purpose, a nonlinear model that determines optimal hourly prices is established based on two major components: unit generation costs and consumers' utility. Both are analyzed and estimated empirically in the third paper. A pricing model is introduced to maximize the electric retailer's profit. As a result, a closed-form expression for the optimal price vector is obtained. Possible scenarios are evaluated for consumers' utility distribution. For the general case, we provide a numerical solution methodology to obtain the optimal pricing scheme. The models recommended are tested under various scenarios that consider consumer segmentation and multiple pricing policies. The recommended model reduces the peak load significantly in most cases. Several utility companies offer hourly pricing to their customers. They determine prices using historical data of unit electricity cost over time. In this dissertation we develop a nonlinear model that determines optimal hourly prices with parameter estimation. The last paper includes a regression analysis of the unit generation cost function obtained from Independent Service Operators. A consumer experiment is established to replicate the peak load behavior. As a result, consumers' utility function is estimated and optimal retail electricity prices are computed.

Security Policies for Mitigating the Risk of Load Altering Attacks on Smart Grid Systems

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

Ryutov, Tatyana; AlMajali, Anas; Neuman, Clifford

2015-04-01

While demand response programs implement energy efficiency and power quality objectives, they bring potential security threats to the Smart Grid. The ability to influence load in a system enables attackers to cause system failures and impacts the quality and integrity of power delivered to customers. This paper presents a security mechanism to monitor and control load according to a set of security policies during normal system operation. The mechanism monitors, detects, and responds to load altering attacks. We examined the security requirements of Smart Grid stakeholders and constructed a set of load control policies enforced by the mechanism. We implementedmore » a proof of concept prototype and tested it using the simulation environment. By enforcing the proposed policies in this prototype, the system is maintained in a safe state in the presence of load drop attacks.« less

Numerical optimization of composite hip endoprostheses under different loading conditions

NASA Technical Reports Server (NTRS)

Blake, T. A.; Davy, D. T.; Saravanos, D. A.; Hopkins, D. A.

1992-01-01

The optimization of composite hip implants was investigated. Emphasis was placed on the effect of shape and material tailoring of the implant to improve the implant-bone interaction. A variety of loading conditions were investigated to better understand the relationship between loading and optimization outcome. Comparisons of the initial and optimal models with more complex 3D finite element models were performed. The results indicate that design improvements made using this method result in similar improvements in the 3D models. Although the optimization outcomes were significantly affected by the choice of loading conditions, certain trends were observed that were independent of the applied loading.

The potential for distributed generation in Japanese prototype buildings: A DER-CAM analysis of policy, tariff design, building energy use, and technology development (English Version)

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

Zhou, Nan; Marnay, Chris; Firestone, Ryan

The August 2003 blackout of the northeastern U.S. and CANADA caused great economic losses and inconvenience to New York City and other affected areas. The blackout was a warning to the rest of the world that the ability of conventional power systems to meet growing electricity demand is questionable. Failure of large power systems can lead to serious emergencies. Introduction of on-site generation, renewable energy such as solar and wind power and the effective utilization of exhaust heat is needed, to meet the growing energy demands of the residential and commercial sectors. Additional benefit can be achieved by integrating thesemore » distributed technologies into distributed energy resource (DER) systems. This work demonstrates a method for choosing and designing economically optimal DER systems. An additional purpose of this research is to establish a database of energy tariffs, DER technology cost and performance characteristics, and building energy consumption for Japan. This research builds on prior DER studies at the Ernest Orlando Lawrence Berkeley National Laboratory (LBNL) and with their associates in the Consortium for Electric Reliability Technology Solutions (CERTS) and operation, including the development of the microgrid concept, and the DER selection optimization program, the Distributed Energy Resources Customer Adoption Model (DER-CAM). DER-CAM is a tool designed to find the optimal combination of installed equipment and an idealized operating schedule to minimize a site's energy bills, given performance and cost data on available DER technologies, utility tariffs, and site electrical and thermal loads over a test period, usually an historic year. Since hourly electric and thermal energy data are rarely available, they are typically developed by building simulation for each of six end use loads used to model the building: electric-only loads, space heating, space cooling, refrigeration, water heating, and natural-gas-only loads. DER-CAM provides a global optimization, albeit idealized, that shows how the necessary useful energy loads can be provided for at minimum cost by selection and operation of on-site generation, heat recovery, cooling, and efficiency improvements. This study examines five prototype commercial buildings and uses DER-CAM to select the economically optimal DER system for each. The five building types are office, hospital, hotel, retail, and sports facility. Each building type was considered for both 5,000 and 10,000 square meter floor sizes. The energy consumption of these building types is based on building energy simulation and published literature. Based on the optimization results, energy conservation and the emissions reduction were also evaluated. Furthermore, a comparison study between Japan and the U.S. has been conducted covering the policy, technology and the utility tariffs effects on DER systems installations. This study begins with an examination of existing DER research. Building energy loads were then generated through simulation (DOE-2) and scaled to match available load data in the literature. Energy tariffs in Japan and the U.S. were then compared: electricity prices did not differ significantly, while commercial gas prices in Japan are much higher than in the U.S. For smaller DER systems, the installation costs in Japan are more than twice those in the U.S., but this difference becomes smaller with larger systems. In Japan, DER systems are eligible for a 1/3 rebate of installation costs, while subsidies in the U.S. vary significantly by region and application. For 10,000 m{sup 2} buildings, significant decreases in fuel consumption, carbon emissions, and energy costs were seen in the economically optimal results. This was most noticeable in the sports facility, followed the hospital and hotel. This research demonstrates that office buildings can benefit from CHP, in contrast to popular opinion. For hospitals and sports facilities, the use of waste heat is particularly effective for water and space heating. For the other building types, waste heat is most effectively used for both heating and cooling. The same examination was done for the 5,000 m{sup 2} buildings. Although CHP installation capacity is smaller and the payback periods are longer, economic, fuel efficiency, and environmental benefits are still seen. While these benefits remain even when subsidies are removed, the increased installation costs lead to lower levels of installation capacity and thus benefit.« less

Seroadaptive Strategies of Vancouver Gay and Bisexual Men in a Treatment as Prevention Environment.

PubMed

Roth, Eric Abella; Cui, Zishan; Rich, Ashleigh; Lachowsky, Nathan; Sereda, Paul; Card, Kiffer George; Jollimore, Jody; Howard, Terry; Armstrong, Heather; Moore, David; Hogg, Robert

2018-01-01

British Columbia's treatment as prevention policy has provided free access to highly active antiretroviral therapy (HAART) to all HIV-positive provincial residents since 1996. One outcome is an increase in HIV-positive gay and bisexual men (GBM) with suppressed viral loads. Previous cross-sectional analyses indicated that some Vancouver GBM now recognize condomless anal sex with men on HAART who report a suppressed viral load as a seroadaptive strategy. To test the hypothesis that this new strategy, termed viral load sorting (VLS), is recognized and used among by GBM in the Momentum Health Study, we analyzed longitudinal data for HIV-negative/unknown (n = 556) and HIV-positive (n = 218) serostatus participants. Analyses indicated that both groups reported VLS, and that serostatus and Treatment Optimism Scale scores were significant determinants in frequency and use. Results exemplify the medicalization of sex and Rogers' Diffusion Of Preventative Innovations Model, and they have important implications for HIV research and GBM sexual decision-making.

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: 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

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

OGUPSA sensor scheduling architecture and algorithm

NASA Astrophysics Data System (ADS)

Zhang, Zhixiong; Hintz, Kenneth J.

1996-06-01

This paper introduces a new architecture for a sensor measurement scheduler as well as a dynamic sensor scheduling algorithm called the on-line, greedy, urgency-driven, preemptive scheduling algorithm (OGUPSA). OGUPSA incorporates a preemptive mechanism which uses three policies, (1) most-urgent-first (MUF), (2) earliest- completed-first (ECF), and (3) least-versatile-first (LVF). The three policies are used successively to dynamically allocate and schedule and distribute a set of arriving tasks among a set of sensors. OGUPSA also can detect the failure of a task to meet a deadline as well as generate an optimal schedule in the sense of minimum makespan for a group of tasks with the same priorities. A side benefit is OGUPSA's ability to improve dynamic load balance among all sensors while being a polynomial time algorithm. Results of a simulation are presented for a simple sensor system.

A Short-Term and High-Resolution System Load Forecasting Approach Using Support Vector Regression with Hybrid Parameters Optimization

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

Jiang, Huaiguang

This work proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of themore » hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system.« less

NERC Policy 10: Measurement of two generation and load balancing IOS

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

Spicer, P.J.; Galow, G.G.

1999-11-01

Policy 10 will describe specific standards and metrics for most of the reliability functions described in the Interconnected Operations Services Working Group (IOS WG) report. The purpose of this paper is to discuss, in detail, the proposed metrics for two generation and load balancing IOSs: Regulation; Load Following. For purposes of this paper, metrics include both measurement and performance evaluation. The measurement methods discussed are included in the current draft of the proposed Policy 10. The performance evaluation method discussed is offered by the authors for consideration by the IOS ITF (Implementation Task Force) for inclusion into Policy 10.

Reliability Constrained Priority Load Shedding for Aerospace Power System Automation

NASA Technical Reports Server (NTRS)

Momoh, James A.; Zhu, Jizhong; Kaddah, Sahar S.; Dolce, James L. (Technical Monitor)

2000-01-01

The need for improving load shedding on board the space station is one of the goals of aerospace power system automation. To accelerate the optimum load-shedding functions, several constraints must be involved. These constraints include congestion margin determined by weighted probability contingency, component/system reliability index, generation rescheduling. The impact of different faults and indices for computing reliability were defined before optimization. The optimum load schedule is done based on priority, value and location of loads. An optimization strategy capable of handling discrete decision making, such as Everett optimization, is proposed. We extended Everett method to handle expected congestion margin and reliability index as constraints. To make it effective for real time load dispatch process, a rule-based scheme is presented in the optimization method. It assists in selecting which feeder load to be shed, the location of the load, the value, priority of the load and cost benefit analysis of the load profile is included in the scheme. The scheme is tested using a benchmark NASA system consisting of generators, loads and network.

Optimizing Preseason Training Loads in Australian Football.

PubMed

Carey, David L; Crow, Justin; Ong, Kok-Leong; Blanch, Peter; Morris, Meg E; Dascombe, Ben J; Crossley, Kay M

2018-02-01

To investigate whether preseason training plans for Australian football can be computer generated using current training-load guidelines to optimize injury-risk reduction and performance improvement. A constrained optimization problem was defined for daily total and sprint distance, using the preseason schedule of an elite Australian football team as a template. Maximizing total training volume and maximizing Banister-model-projected performance were both considered optimization objectives. Cumulative workload and acute:chronic workload-ratio constraints were placed on training programs to reflect current guidelines on relative and absolute training loads for injury-risk reduction. Optimization software was then used to generate preseason training plans. The optimization framework was able to generate training plans that satisfied relative and absolute workload constraints. Increasing the off-season chronic training loads enabled the optimization algorithm to prescribe higher amounts of "safe" training and attain higher projected performance levels. Simulations showed that using a Banister-model objective led to plans that included a taper in training load prior to competition to minimize fatigue and maximize projected performance. In contrast, when the objective was to maximize total training volume, more frequent training was prescribed to accumulate as much load as possible. Feasible training plans that maximize projected performance and satisfy injury-risk constraints can be automatically generated by an optimization problem for Australian football. The optimization methods allow for individualized training-plan design and the ability to adapt to changing training objectives and different training-load metrics.

Role of optimization criterion in static asymmetric analysis of lumbar spine load.

PubMed

Daniel, Matej

2011-10-01

A common method for load estimation in biomechanics is the inverse dynamics optimization, where the muscle activation pattern is found by minimizing or maximizing the optimization criterion. It has been shown that various optimization criteria predict remarkably similar muscle activation pattern and intra-articular contact forces during leg motion. The aim of this paper is to study the effect of the choice of optimization criterion on L4/L5 loading during static asymmetric loading. Upright standing with weight in one stretched arm was taken as a representative position. Musculoskeletal model of lumbar spine model was created from CT images of Visible Human Project. Several criteria were tested based on the minimization of muscle forces, muscle stresses, and spinal load. All criteria provide the same level of lumbar spine loading (difference is below 25%), except the criterion of minimum lumbar shear force which predicts unrealistically high spinal load and should not be considered further. Estimated spinal load and predicted muscle force activation pattern are in accordance with the intradiscal pressure measurements and EMG measurements. The L4/L5 spine loads 1312 N, 1674 N, and 1993 N were predicted for mass of weight in hand 2, 5, and 8 kg, respectively using criterion of mininum muscle stress cubed. As the optimization criteria do not considerably affect the spinal load, their choice is not critical in further clinical or ergonomic studies and computationally simpler criterion can be used.

A Hybrid Interval-Robust Optimization Model for Water Quality Management.

PubMed

Xu, Jieyu; Li, Yongping; Huang, Guohe

2013-05-01

In water quality management problems, uncertainties may exist in many system components and pollution-related processes ( i.e. , random nature of hydrodynamic conditions, variability in physicochemical processes, dynamic interactions between pollutant loading and receiving water bodies, and indeterminacy of available water and treated wastewater). These complexities lead to difficulties in formulating and solving the resulting nonlinear optimization problems. In this study, a hybrid interval-robust optimization (HIRO) method was developed through coupling stochastic robust optimization and interval linear programming. HIRO can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original chemical oxygen demand (COD) discharge constraints, HIRO enhances the robustness of the optimization processes and resulting solutions. This method was applied to planning of industry development in association with river-water pollution concern in New Binhai District of Tianjin, China. Results demonstrated that the proposed optimization model can effectively communicate uncertainties into the optimization process and generate a spectrum of potential inexact solutions supporting local decision makers in managing benefit-effective water quality management schemes. HIRO is helpful for analysis of policy scenarios related to different levels of economic penalties, while also providing insight into the tradeoff between system benefits and environmental requirements.

A Study on a Centralized Under-Voltage Load Shedding Scheme Considering the Load Characteristics

NASA Astrophysics Data System (ADS)

Deng, Jiyu; Liu, Junyong

Under-voltage load shedding is an important measure for maintaining voltage stability.Aiming at the optimal load shedding problem considering the load characteristics,firstly,the traditional under-voltage load shedding scheme based on a static load model may cause the analysis inaccurate is pointed out on the equivalent Thevenin circuit.Then,the dynamic voltage stability margin indicator is derived through local measurement.The derived indicator can reflect the voltage change of the key area in a myopia linear way.Dimensions of the optimal problem will be greatly simplified using this indicator.In the end,mathematical model of the centralized load shedding scheme is built with the indicator considering load characteristics.HSPPSO is introduced to slove the optimal problem.Simulation results on IEEE-39 system show that the proposed scheme display a good adaptability in solving the under-voltage load shedding considering dynamic load characteristics.

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

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

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

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

Cost Optimal Elastic Auto-Scaling in Cloud Infrastructure

NASA Astrophysics Data System (ADS)

Mukhopadhyay, S.; Sidhanta, S.; Ganguly, S.; Nemani, R. R.

2014-12-01

Today, elastic scaling is critical part of leveraging cloud. Elastic scaling refers to adding resources only when it is needed and deleting resources when not in use. Elastic scaling ensures compute/server resources are not over provisioned. Today, Amazon and Windows Azure are the only two platform provider that allow auto-scaling of cloud resources where servers are automatically added and deleted. However, these solution falls short of following key features: A) Requires explicit policy definition such server load and therefore lacks any predictive intelligence to make optimal decision; B) Does not decide on the right size of resource and thereby does not result in cost optimal resource pool. In a typical cloud deployment model, we consider two types of application scenario: A. Batch processing jobs → Hadoop/Big Data case B. Transactional applications → Any application that process continuous transactions (Requests/response) In reference of classical queuing model, we are trying to model a scenario where servers have a price and capacity (size) and system can add delete servers to maintain a certain queue length. Classical queueing models applies to scenario where number of servers are constant. So we cannot apply stationary system analysis in this case. We investigate the following questions 1. Can we define Job queue and use the metric to define such a queue to predict the resource requirement in a quasi-stationary way? Can we map that into an optimal sizing problem? 2. Do we need to get into a level of load (CPU/Data) on server level to characterize the size requirement? How do we learn that based on Job type?

Use and optimization of a dual-flowrate loading strategy to maximize throughput in protein-a affinity chromatography.

PubMed

Ghose, Sanchayita; Nagrath, Deepak; Hubbard, Brian; Brooks, Clayton; Cramer, Steven M

2004-01-01

The effect of an alternate strategy employing two different flowrates during loading was explored as a means of increasing system productivity in Protein-A chromatography. The effect of such a loading strategy was evaluated using a chromatographic model that was able to accurately predict experimental breakthrough curves for this Protein-A system. A gradient-based optimization routine is carried out to establish the optimal loading conditions (initial and final flowrates and switching time). The two-step loading strategy (using a higher flowrate during the initial stages followed by a lower flowrate) was evaluated for an Fc-fusion protein and was found to result in significant improvements in process throughput. In an extension of this optimization routine, dynamic loading capacity and productivity were simultaneously optimized using a weighted objective function, and this result was compared to that obtained with the single flowrate. Again, the dual-flowrate strategy was found to be superior.

Coordinated Optimization of Distributed Energy Resources and Smart Loads in Distribution Systems: Preprint

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

Yang, Rui; Zhang, Yingchen

2016-08-01

Distributed energy resources (DERs) and smart loads have the potential to provide flexibility to the distribution system operation. A coordinated optimization approach is proposed in this paper to actively manage DERs and smart loads in distribution systems to achieve the optimal operation status. A three-phase unbalanced Optimal Power Flow (OPF) problem is developed to determine the output from DERs and smart loads with respect to the system operator's control objective. This paper focuses on coordinating PV systems and smart loads to improve the overall voltage profile in distribution systems. Simulations have been carried out in a 12-bus distribution feeder andmore » results illustrate the superior control performance of the proposed approach.« less

Coordinated Optimization of Distributed Energy Resources and Smart Loads in Distribution Systems

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

Yang, Rui; Zhang, Yingchen

2016-11-14

Distributed energy resources (DERs) and smart loads have the potential to provide flexibility to the distribution system operation. A coordinated optimization approach is proposed in this paper to actively manage DERs and smart loads in distribution systems to achieve the optimal operation status. A three-phase unbalanced Optimal Power Flow (OPF) problem is developed to determine the output from DERs and smart loads with respect to the system operator's control objective. This paper focuses on coordinating PV systems and smart loads to improve the overall voltage profile in distribution systems. Simulations have been carried out in a 12-bus distribution feeder andmore » results illustrate the superior control performance of the proposed approach.« less

A temperature match based optimization method for daily load prediction considering DLC effect

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

Yu, Z.

This paper presents a unique optimization method for short term load forecasting. The new method is based on the optimal template temperature match between the future and past temperatures. The optimal error reduction technique is a new concept introduced in this paper. Two case studies show that for hourly load forecasting, this method can yield results as good as the rather complicated Box-Jenkins Transfer Function method, and better than the Box-Jenkins method; for peak load prediction, this method is comparable in accuracy to the neural network method with back propagation, and can produce more accurate results than the multi-linear regressionmore » method. The DLC effect on system load is also considered in this method.« less

Normalization of doxorubicin release from graphene oxide: New approach for optimization of effective parameters on drug loading.

PubMed

Hashemi, Mohadeseh; Yadegari, Amir; Yazdanpanah, Ghasem; Omidi, Meisam; Jabbehdari, Sayena; Haghiralsadat, Fatemeh; Yazdian, Fatemeh; Tayebi, Lobat

2017-05-01

Graphene oxide (GO) has been recently introduced as a suitable anticancer drug carrier, which could be loaded with doxorubicin (DOX) as a general chemotherapy agent. Herein, the attempts were made to optimize the effective parameters on both loading and release of DOX on GO. GO and GO-DOX were characterized using transition electron microscopy , zeta potential, Raman spectroscopy, UV-visible spectroscopy, and Fourier transform infrared spectroscopy. In addition, loading and releasing behaviors of DOX on GO were studied in terms of different temperature and pH values. The primary optimized values of pH and temperature for best-loaded amount of DOX were 8.9 and 309 K, respectively. Moreover, we found that the smallest amount of released DOX, in pH of cancer microenvironment (5.4), occurs when DOX had been previously loaded in pH 7.8 and 310 K. Although the highest amount of loaded DOX was in basic pH, the results of efficient release of DOX from the GO-DOX complex and also cellular toxicity assay revealed that the best pH for loading of DOX on GO was 7.8. Therefore, in addition to optimization of parameters for efficient loading of DOX on GO, this study suggested that normalization of a released drug compared with the amount of a loaded drug could be a new approach for optimization of drug loading on nanocarriers. © 2016 International Union of Biochemistry and Molecular Biology, Inc.

Heuristic and optimal policy computations in the human brain during sequential decision-making.

PubMed

Korn, Christoph W; Bach, Dominik R

2018-01-23

Optimal decisions across extended time horizons require value calculations over multiple probabilistic future states. Humans may circumvent such complex computations by resorting to easy-to-compute heuristics that approximate optimal solutions. To probe the potential interplay between heuristic and optimal computations, we develop a novel sequential decision-making task, framed as virtual foraging in which participants have to avoid virtual starvation. Rewards depend only on final outcomes over five-trial blocks, necessitating planning over five sequential decisions and probabilistic outcomes. Here, we report model comparisons demonstrating that participants primarily rely on the best available heuristic but also use the normatively optimal policy. FMRI signals in medial prefrontal cortex (MPFC) relate to heuristic and optimal policies and associated choice uncertainties. Crucially, reaction times and dorsal MPFC activity scale with discrepancies between heuristic and optimal policies. Thus, sequential decision-making in humans may emerge from integration between heuristic and optimal policies, implemented by controllers in MPFC.

Spatial optimization of watershed management practices for nitrogen load reduction using a modeling-optimization framework.

PubMed

Yang, Guoxiang; Best, Elly P H

2015-09-15

Best management practices (BMPs) can be used effectively to reduce nutrient loads transported from non-point sources to receiving water bodies. However, methodologies of BMP selection and placement in a cost-effective way are needed to assist watershed management planners and stakeholders. We developed a novel modeling-optimization framework that can be used to find cost-effective solutions of BMP placement to attain nutrient load reduction targets. This was accomplished by integrating a GIS-based BMP siting method, a WQM-TMDL-N modeling approach to estimate total nitrogen (TN) loading, and a multi-objective optimization algorithm. Wetland restoration and buffer strip implementation were the two BMP categories used to explore the performance of this framework, both differing greatly in complexity of spatial analysis for site identification. Minimizing TN load and BMP cost were the two objective functions for the optimization process. The performance of this framework was demonstrated in the Tippecanoe River watershed, Indiana, USA. Optimized scenario-based load reduction indicated that the wetland subset selected by the minimum scenario had the greatest N removal efficiency. Buffer strips were more effective for load removal than wetlands. The optimized solutions provided a range of trade-offs between the two objective functions for both BMPs. This framework can be expanded conveniently to a regional scale because the NHDPlus catchment serves as its spatial computational unit. The present study demonstrated the potential of this framework to find cost-effective solutions to meet a water quality target, such as a 20% TN load reduction, under different conditions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Anti-buckling design of variable stiffness composite cylinder under combined loading based on the multi-objective optimization method

NASA Astrophysics Data System (ADS)

Zheng, Y.; Chen, J.

2018-06-01

Variable stiffness composite structures take full advantages of composite’s design ability. An enlarged design space will make the structure’s performance more excellent. Through an optimal design of a variable stiffness cylinder, the buckling capacity of the cylinder will be increased as compared with its constant stiffness counterpart. In this paper, variable stiffness composite cylinders sustaining combined loadings are considered, and the optimization is conducted based on the multi-objective optimization method. The results indicate that variable stiffness cylinder’s loading capacity is increased significantly as compared with the constant stiffness, especially when an inhomogeneous loading is considered.

Optimal back-to-front airplane boarding.

PubMed

Bachmat, Eitan; Khachaturov, Vassilii; Kuperman, Ran

2013-06-01

The problem of finding an optimal back-to-front airplane boarding policy is explored, using a mathematical model that is related to the 1+1 polynuclear growth model with concave boundary conditions and to causal sets in gravity. We study all airplane configurations and boarding group sizes. Optimal boarding policies for various airplane configurations are presented. Detailed calculations are provided along with simulations that support the main conclusions of the theory. We show that the effectiveness of back-to-front policies undergoes a phase transition when passing from lightly congested airplanes to heavily congested airplanes. The phase transition also affects the nature of the optimal or near-optimal policies. Under what we consider to be realistic conditions, optimal back-to-front policies lead to a modest 8-12% improvement in boarding time over random (no policy) boarding, using two boarding groups. Having more than two groups is not effective.

Stress-Constrained Structural Topology Optimization with Design-Dependent Loads

NASA Astrophysics Data System (ADS)

Lee, Edmund

Topology optimization is commonly used to distribute a given amount of material to obtain the stiffest structure, with predefined fixed loads. The present work investigates the result of applying stress constraints to topology optimization, for problems with design-depending loading, such as self-weight and pressure. In order to apply pressure loading, a material boundary identification scheme is proposed, iteratively connecting points of equal density. In previous research, design-dependent loading problems have been limited to compliance minimization. The present study employs a more practical approach by minimizing mass subject to failure constraints, and uses a stress relaxation technique to avoid stress constraint singularities. The results show that these design dependent loading problems may converge to a local minimum when stress constraints are enforced. Comparisons between compliance minimization solutions and stress-constrained solutions are also given. The resulting topologies of these two solutions are usually vastly different, demonstrating the need for stress-constrained topology optimization.

Determining the optimal load for jump squats: a review of methods and calculations.

PubMed

Dugan, Eric L; Doyle, Tim L A; Humphries, Brendan; Hasson, Christopher J; Newton, Robert U

2004-08-01

There has been an increasing volume of research focused on the load that elicits maximum power output during jump squats. Because of a lack of standardization for data collection and analysis protocols, results of much of this research are contradictory. The purpose of this paper is to examine why differing methods of data collection and analysis can lead to conflicting results for maximum power and associated optimal load. Six topics relevant to measurement and reporting of maximum power and optimal load are addressed: (a) data collection equipment, (b) inclusion or exclusion of body weight force in calculations of power, (c) free weight versus Smith machine jump squats, (d) reporting of average versus peak power, (e) reporting of load intensity, and (f) instructions given to athletes/ participants. Based on this information, a standardized protocol for data collection and reporting of jump squat power and optimal load is presented.

Application of Hybrid Optimization-Expert System for Optimal Power Management on Board Space Power Station

NASA Technical Reports Server (NTRS)

Momoh, James; Chattopadhyay, Deb; Basheer, Omar Ali AL

1996-01-01

The space power system has two sources of energy: photo-voltaic blankets and batteries. The optimal power management problem on-board has two broad operations: off-line power scheduling to determine the load allocation schedule of the next several hours based on the forecast of load and solar power availability. The nature of this study puts less emphasis on speed requirement for computation and more importance on the optimality of the solution. The second category problem, on-line power rescheduling, is needed in the event of occurrence of a contingency to optimally reschedule the loads to minimize the 'unused' or 'wasted' energy while keeping the priority on certain type of load and minimum disturbance of the original optimal schedule determined in the first-stage off-line study. The computational performance of the on-line 'rescheduler' is an important criterion and plays a critical role in the selection of the appropriate tool. The Howard University Center for Energy Systems and Control has developed a hybrid optimization-expert systems based power management program. The pre-scheduler has been developed using a non-linear multi-objective optimization technique called the Outer Approximation method and implemented using the General Algebraic Modeling System (GAMS). The optimization model has the capability of dealing with multiple conflicting objectives viz. maximizing energy utilization, minimizing the variation of load over a day, etc. and incorporates several complex interaction between the loads in a space system. The rescheduling is performed using an expert system developed in PROLOG which utilizes a rule-base for reallocation of the loads in an emergency condition viz. shortage of power due to solar array failure, increase of base load, addition of new activity, repetition of old activity etc. Both the modules handle decision making on battery charging and discharging and allocation of loads over a time-horizon of a day divided into intervals of 10 minutes. The models have been extensively tested using a case study for the Space Station Freedom and the results for the case study will be presented. Several future enhancements of the pre-scheduler and the 'rescheduler' have been outlined which include graphic analyzer for the on-line module, incorporating probabilistic considerations, including spatial location of the loads and the connectivity using a direct current (DC) load flow model.

A short-term and high-resolution distribution system load forecasting approach using support vector regression with hybrid parameters optimization

DOE PAGES

Jiang, Huaiguang; Zhang, Yingchen; Muljadi, Eduard; ...

2016-01-01

This paper proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of themore » hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system. The performance of the proposed approach is compared to some classic methods in later sections of the paper.« less

Structural topology optimization with fuzzy constraint

NASA Astrophysics Data System (ADS)

Rosko, Peter

2011-12-01

The paper deals with the structural topology optimization with fuzzy constraint. The optimal topology of structure is defined as a material distribution problem. The objective is the weight of the structure. The multifrequency dynamic loading is considered. The optimal topology design of the structure has to eliminate the danger of the resonance vibration. The uncertainty of the loading is defined with help of fuzzy loading. Special fuzzy constraint is created from exciting frequencies. Presented study is applicable in engineering and civil engineering. Example demonstrates the presented theory.

Investigation of progressive failure robustness and alternate load paths for damage tolerant structures

NASA Astrophysics Data System (ADS)

Marhadi, Kun Saptohartyadi

Structural optimization for damage tolerance under various unforeseen damage scenarios is computationally challenging. It couples non-linear progressive failure analysis with sampling-based stochastic analysis of random damage. The goal of this research was to understand the relationship between alternate load paths available in a structure and its damage tolerance, and to use this information to develop computationally efficient methods for designing damage tolerant structures. Progressive failure of a redundant truss structure subjected to small random variability was investigated to identify features that correlate with robustness and predictability of the structure's progressive failure. The identified features were used to develop numerical surrogate measures that permit computationally efficient deterministic optimization to achieve robustness and predictability of progressive failure. Analysis of damage tolerance on designs with robust progressive failure indicated that robustness and predictability of progressive failure do not guarantee damage tolerance. Damage tolerance requires a structure to redistribute its load to alternate load paths. In order to investigate the load distribution characteristics that lead to damage tolerance in structures, designs with varying degrees of damage tolerance were generated using brute force stochastic optimization. A method based on principal component analysis was used to describe load distributions (alternate load paths) in the structures. Results indicate that a structure that can develop alternate paths is not necessarily damage tolerant. The alternate load paths must have a required minimum load capability. Robustness analysis of damage tolerant optimum designs indicates that designs are tailored to specified damage. A design Optimized under one damage specification can be sensitive to other damages not considered. Effectiveness of existing load path definitions and characterizations were investigated for continuum structures. A load path definition using a relative compliance change measure (U* field) was demonstrated to be the most useful measure of load path. This measure provides quantitative information on load path trajectories and qualitative information on the effectiveness of the load path. The use of the U* description of load paths in optimizing structures for effective load paths was investigated.

Inverse optimal design of the radiant heating in materials processing and manufacturing

NASA Astrophysics Data System (ADS)

Fedorov, A. G.; Lee, K. H.; Viskanta, R.

1998-12-01

Combined convective, conductive, and radiative heat transfer is analyzed during heating of a continuously moving load in the industrial radiant oven. A transient, quasi-three-dimensional model of heat transfer between a continuous load of parts moving inside an oven on a conveyor belt at a constant speed and an array of radiant heaters/burners placed inside the furnace enclosure is developed. The model accounts for radiative exchange between the heaters and the load, heat conduction in the load, and convective heat transfer between the moving load and oven environment. The thermal model developed has been used to construct a general framework for an inverse optimal design of an industrial oven as an example. In particular, the procedure based on the Levenberg-Marquardt nonlinear least squares optimization algorithm has been developed to obtain the optimal temperatures of the heaters/burners that need to be specified to achieve a prescribed temperature distribution of the surface of a load. The results of calculations for several sample cases are reported to illustrate the capabilities of the procedure developed for the optimal inverse design of an industrial radiant oven.

Dynamic mobility applications policy analysis : policy and institutional issues for intelligent network flow optimization (INFLO).

DOT National Transportation Integrated Search

2014-12-01

The report documents policy considerations for the Intelligent Network Flow Optimization (INFLO) connected vehicle applications bundle. INFLO aims to optimize network flow on freeways and arterials by informing motorists of existing and impendi...

Comparison of DVH parameters and loading patterns of standard loading, manual and inverse optimization for intracavitary brachytherapy on a subset of tandem/ovoid cases.

PubMed

Jamema, Swamidas V; Kirisits, Christian; Mahantshetty, Umesh; Trnkova, Petra; Deshpande, Deepak D; Shrivastava, Shyam K; Pötter, Richard

2010-12-01

Comparison of inverse planning with the standard clinical plan and with the manually optimized plan based on dose-volume parameters and loading patterns. Twenty-eight patients who underwent MRI based HDR brachytherapy for cervix cancer were selected for this study. Three plans were calculated for each patient: (1) standard loading, (2) manual optimized, and (3) inverse optimized. Dosimetric outcomes from these plans were compared based on dose-volume parameters. The ratio of Total Reference Air Kerma of ovoid to tandem (TRAK(O/T)) was used to compare the loading patterns. The volume of HR CTV ranged from 9-68 cc with a mean of 41(±16.2) cc. Mean V100 for standard, manual optimized and inverse plans was found to be not significant (p=0.35, 0.38, 0.4). Dose to bladder (7.8±1.6 Gy) and sigmoid (5.6±1.4 Gy) was high for standard plans; Manual optimization reduced the dose to bladder (7.1±1.7 Gy p=0.006) and sigmoid (4.5±1.0 Gy p=0.005) without compromising the HR CTV coverage. The inverse plan resulted in a significant reduction to bladder dose (6.5±1.4 Gy, p=0.002). TRAK was found to be 0.49(±0.02), 0.44(±0.04) and 0.40(±0.04) cGy m(-2) for the standard loading, manual optimized and inverse plans, respectively. It was observed that TRAK(O/T) was 0.82(±0.05), 1.7(±1.04) and 1.41(±0.93) for standard loading, manual optimized and inverse plans, respectively, while this ratio was 1 for the traditional loading pattern. Inverse planning offers good sparing of critical structures without compromising the target coverage. The average loading pattern of the whole patient cohort deviates from the standard Fletcher loading pattern. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

A Hybrid Interval–Robust Optimization Model for Water Quality Management

PubMed Central

Xu, Jieyu; Li, Yongping; Huang, Guohe

2013-01-01

Abstract In water quality management problems, uncertainties may exist in many system components and pollution-related processes (i.e., random nature of hydrodynamic conditions, variability in physicochemical processes, dynamic interactions between pollutant loading and receiving water bodies, and indeterminacy of available water and treated wastewater). These complexities lead to difficulties in formulating and solving the resulting nonlinear optimization problems. In this study, a hybrid interval–robust optimization (HIRO) method was developed through coupling stochastic robust optimization and interval linear programming. HIRO can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original chemical oxygen demand (COD) discharge constraints, HIRO enhances the robustness of the optimization processes and resulting solutions. This method was applied to planning of industry development in association with river-water pollution concern in New Binhai District of Tianjin, China. Results demonstrated that the proposed optimization model can effectively communicate uncertainties into the optimization process and generate a spectrum of potential inexact solutions supporting local decision makers in managing benefit-effective water quality management schemes. HIRO is helpful for analysis of policy scenarios related to different levels of economic penalties, while also providing insight into the tradeoff between system benefits and environmental requirements. PMID:23922495

Nuclear fuel management optimization using genetic algorithms

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

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

1995-07-01

The code independent genetic algorithm reactor optimization (CIGARO) system has been developed to optimize nuclear reactor loading patterns. It uses genetic algorithms (GAs) and a code-independent interface, so any reactor physics code (e.g., CASMO-3/SIMULATE-3) can be used to evaluate the loading patterns. The system is compared to other GA-based loading pattern optimizers. Tests were carried out to maximize the beginning of cycle k{sub eff} for a pressurized water reactor core loading with a penalty function to limit power peaking. The CIGARO system performed well, increasing the k{sub eff} after lowering the peak power. Tests of a prototype parallel evaluation methodmore » showed the potential for a significant speedup.« less

Population-based learning of load balancing policies for a distributed computer system

NASA Technical Reports Server (NTRS)

Mehra, Pankaj; Wah, Benjamin W.

1993-01-01

Effective load-balancing policies use dynamic resource information to schedule tasks in a distributed computer system. We present a novel method for automatically learning such policies. At each site in our system, we use a comparator neural network to predict the relative speedup of an incoming task using only the resource-utilization patterns obtained prior to the task's arrival. Outputs of these comparator networks are broadcast periodically over the distributed system, and the resource schedulers at each site use these values to determine the best site for executing an incoming task. The delays incurred in propagating workload information and tasks from one site to another, as well as the dynamic and unpredictable nature of workloads in multiprogrammed multiprocessors, may cause the workload pattern at the time of execution to differ from patterns prevailing at the times of load-index computation and decision making. Our load-balancing policy accommodates this uncertainty by using certain tunable parameters. We present a population-based machine-learning algorithm that adjusts these parameters in order to achieve high average speedups with respect to local execution. Our results show that our load-balancing policy, when combined with the comparator neural network for workload characterization, is effective in exploiting idle resources in a distributed computer system.

In vitro validation of a shape-optimized fiber-reinforced dental bridge.

PubMed

Chen, YungChung; Li, Haiyan; Fok, Alex

2011-12-01

To improve its mechanical performance, structural optimization had been used in a previous study to obtain an alternative design for a 3-unit inlay-retained fiber-reinforced composite (FRC) dental bridge. In that study, an optimized layout of the FRC substructure had been proposed to minimize stresses in the veneering composite and interfacial stresses between the composite and substructure. The current work aimed to validate in vitro the improved fracture resistance of the optimized design. All samples for the 3-unit inlay-retained FRC dental bridge were made with glass-fibers (FibreKor) as the substructure, surrounded by a veneering composite (GC Gradia). Two different FRC substructure designs were prepared: a conventional (n=20) and an optimized design (n=21). The conventional design was a straight beam linking one proximal box to the other, while the optimized design was a curved beam following the lower outline of the pontic. All samples were loaded to 400N on a universal test machine (MTS 810) with a loading speed of 0.2mm/min. During loading, the force and displacement were recorded. Meanwhile, a two-channel acoustic emission (AE) system was used to monitor the development of cracks during loading. The load-displacement curves of the two groups displayed significant differences. For the conventional design, there were numerous drops in load corresponding to local damage of the sample. For the optimized design, the load curves were much smoother. Cracks were clearly visible on the surface of the conventional group only, and the directions of those cracks were perpendicular to those of the most tensile stresses. Results from the more sensitive AE measurement also showed that the optimized design had, on average, fewer cracking events: 38 versus 2969 in the conventional design. The much lower number of AE events and smoother load-displacement curves indicated that the optimized FRC bridge design had a higher fracture resistance. It is expected that the optimized design will significantly improve the clinical performance of FRC bridges. Copyright © 2011 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Towards a hierarchical optimization modeling framework for ...

EPA Pesticide Factsheets

Background:Bilevel optimization has been recognized as a 2-player Stackelberg game where players are represented as leaders and followers and each pursue their own set of objectives. Hierarchical optimization problems, which are a generalization of bilevel, are especially difficult because the optimization is nested, meaning that the objectives of one level depend on solutions to the other levels. We introduce a hierarchical optimization framework for spatially targeting multiobjective green infrastructure (GI) incentive policies under uncertainties related to policy budget, compliance, and GI effectiveness. We demonstrate the utility of the framework using a hypothetical urban watershed, where the levels are characterized by multiple levels of policy makers (e.g., local, regional, national) and policy followers (e.g., landowners, communities), and objectives include minimization of policy cost, implementation cost, and risk; reduction of combined sewer overflow (CSO) events; and improvement in environmental benefits such as reduced nutrient run-off and water availability. Conclusions: While computationally expensive, this hierarchical optimization framework explicitly simulates the interaction between multiple levels of policy makers (e.g., local, regional, national) and policy followers (e.g., landowners, communities) and is especially useful for constructing and evaluating environmental and ecological policy. Using the framework with a hypothetical urba

Optimal Scheduling of Time-Shiftable Electric Loads in Expeditionary Power Grids

DTIC Science & Technology

2015-09-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS OPTIMAL SCHEDULING OF TIME-SHIFTABLE ELECTRIC LOADS IN EXPEDITIONARY POWER GRIDS by John G...to 09-25-2015 4. TITLE AND SUBTITLE OPTIMAL SCHEDULING OF TIME-SHIFTABLE ELECTRIC LOADS IN EXPEDI- TIONARY POWER GRIDS 5. FUNDING NUMBERS 6. AUTHOR(S...eliminate unmanaged peak demand, reduce generator peak-to-average power ratios, and facilitate a persistent shift to higher fuel efficiency. Using

A heuristic approach to optimization of structural topology including self-weight

NASA Astrophysics Data System (ADS)

Tajs-Zielińska, Katarzyna; Bochenek, Bogdan

2018-01-01

Topology optimization of structures under a design-dependent self-weight load is investigated in this paper. The problem deserves attention because of its significant importance in the engineering practice, especially nowadays as topology optimization is more often applied when designing large engineering structures, for example, bridges or carrying systems of tall buildings. It is worth noting that well-known approaches of topology optimization which have been successfully applied to structures under fixed loads cannot be directly adapted to the case of design-dependent loads, so that topology generation can be a challenge also for numerical algorithms. The paper presents the application of a simple but efficient non-gradient method to topology optimization of elastic structures under self-weight loading. The algorithm is based on the Cellular Automata concept, the application of which can produce effective solutions with low computational cost.

Investigation of Optimal Control Allocation for Gust Load Alleviation in Flight Control

NASA Technical Reports Server (NTRS)

Frost, Susan A.; Taylor, Brian R.; Bodson, Marc

2012-01-01

Advances in sensors and avionics computation power suggest real-time structural load measurements could be used in flight control systems for improved safety and performance. A conventional transport flight control system determines the moments necessary to meet the pilot's command, while rejecting disturbances and maintaining stability of the aircraft. Control allocation is the problem of converting these desired moments into control effector commands. In this paper, a framework is proposed to incorporate real-time structural load feedback and structural load constraints in the control allocator. Constrained optimal control allocation can be used to achieve desired moments without exceeding specified limits on monitored load points. Minimization of structural loads by the control allocator is used to alleviate gust loads. The framework to incorporate structural loads in the flight control system and an optimal control allocation algorithm will be described and then demonstrated on a nonlinear simulation of a generic transport aircraft with flight dynamics and static structural loads.

Optimizing the U.S. Electric System with a High Penetration of Renewables

NASA Astrophysics Data System (ADS)

Corcoran, B. A.; Jacobson, M. Z.

2012-12-01

As renewable energy generators are increasingly being installed throughout the U.S., there is growing interest in interconnecting diverse renewable generators (primarily wind and solar) across large geographic areas through an enhanced transmission system. This reduces variability in the aggregate power output, increases system reliability, and allows for the development of the best overall group of renewable technologies and sites to meet the load. Studies are therefore needed to determine the most efficient and economical plan to achieve large area interconnections in a future electric system with a high penetration of renewables. This research quantifies the effects of aggregating electric load and, separately, electric load together with diverse renewable generation throughout the ten Federal Energy Regulatory Commission (FERC) regions in the contiguous U.S. The effects of aggregating electric load alone -- including generator capacity capital cost savings, load energy shift operating cost savings, reserve requirement cost savings, and transmission costs -- were calculated for various groupings of FERC regions using 2006 data. Transmission costs outweighed cost savings due to aggregation in nearly all cases. East-west transmission layouts had the highest overall cost, and interconnecting ERCOT to adjacent FERC regions resulted in increased costs, both due to limited existing transmission capacity. Scenarios consisting of smaller aggregation groupings had the lowest overall cost. This analysis found no economic case for further aggregation of load alone within the U.S., except possibly in the West and Northwest. If aggregation of electric load is desired, then small, regional consolidations yield the lowest overall system cost. Next, the effects of aggregating electric load together with renewable electricity generation are being quantified through the development and use of an optimization tool in AMPL (A Mathematical Programming Language). This deterministic linear program solves for the least-cost organizational structure and system (generator, transmission, storage, and reserve requirements) for a highly renewable U.S. electric grid. The analysis will 1) examine a highly renewable 2006 electric system, and 2) create a "roadmap" from the existing 2006 system to a highly renewable system in 2030, accounting for projected price and demand changes and generator retirements based on age and environmental regulations. Ideally, results from this study will offer insight for a federal renewable energy policy (such as a renewable portfolio standard) and how to best organize regions for transmission planning.

Evaluating Ecosystem Services for Reducing Groundwater Nitrate Contamination: Nitrate Attenuation in the Unsaturated and Saturated Zones

NASA Astrophysics Data System (ADS)

Wang, J.

2013-12-01

Nitrates are the most common type of groundwater contamination in agricultural regions. Environmental policies targeting nitrates have focused on input control (e.g., restricted fertilizer application), intermediate loads control (e.g., reduce nitrate leached from crop fields), and final loads control (e.g., reduce catchment nitrate loads). Nitrate loads can be affected by hydrological processes in both unsaturated and saturated zones. Although many of these processes have been extensively investigated in literature, they are commonly modeled as exogenous to farm management. A couple of recent studies by scientists from the Lawrence Livermore National Laboratory show that in some situations nitrate attenuation processes in the unsaturated/saturated zone, particularly denitrification, can be intensified by certain management practices to mitigate nitrate loads. Therefore, these nitrate attenuation processes can be regarded as a set of ecosystem services that farmers can take advantage of to reduce their cost of complying with environmental policies. In this paper, a representative California dairy farm is used as a case study to show how such ecosystem attenuation services can be framed within the farm owner's decision-making framework as an option for reducing groundwater nitrate contamination. I develop an integrated dynamic model, where the farmer maximizes discounted net farm profit over multiple periods subject to environmental regulations. The model consists of three submodels: animal-waste-crop, hydrologic, and economic model. In addition to common choice variables such as irrigation, fertilization, and waste disposal options, the farmer can also endogenously choose from three water sources: surface water, deep groundwater (old groundwater in the deep aquifer that is not affected by farm effluent in the short term), and shallow groundwater (drainage water that can be recycled via capture wells at the downstream end of the farm). The capture wells not only recycle wastewater, but can also increase the likelihood of denitrification. Thus the farmer essentially can choose whether, and to which extent, to install capture wells and take advantage of the ecosystem attenuation services. Decision rules from the dynamic optimization model demonstrate best management practices for the farm to improve its economic and environmental performance. I further use an economic valuation technique to value these services. Under the Millennium Ecosystem Assessment framework, nitrate attenuation in the unsaturated and saturated zone provides regulatory ecosystem services to humans, mainly nutrient regulation and waste treatment. With the integrated farm model, the production function approach is adopted to get the economic value of these regulatory services. The results highlight the significant role the environment can play in nitrate pollution control and potential benefits from designing policies that acknowledge this role. The most desirable policies are those that create incentive for farmers to use potential ecosystem services, which significantly reduce environmental compliance costs and increase social welfare.

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.

Optimization and performance comparison for galloping-based piezoelectric energy harvesters with alternating-current and direct-current interface circuits

NASA Astrophysics Data System (ADS)

Tan, Ting; Yan, Zhimiao; Lei, Hong

2017-07-01

Galloping-based piezoelectric energy harvesters scavenge small-scale wind energy and convert it into electrical energy. For piezoelectric energy harvesting with the same vibrational source (galloping) but different (alternating-current (AC) and direct-current (DC)) interfaces, general analytical solutions of the electromechanical coupled distributed parameter model are proposed. Galloping is theoretically proven to appear when the linear aerodynamic negative damping overcomes the electrical damping and mechanical damping. The harvested power is demonstrated as being done by the electrical damping force. Via tuning the load resistance to its optimal value for optimal or maximal electrical damping, the harvested power of the given structure with the AC/DC interface is maximized. The optimal load resistances and the corresponding performances of such two systems are compared. The optimal electrical damping are the same but with different optimal load resistances for the systems with the AC and DC interfaces. At small wind speeds where the optimal electrical damping can be realized by only tuning the load resistance, the performances of such two energy harvesting systems, including the minimal onset speeds to galloping, maximal harvested powers and corresponding tip displacements are almost the same. Smaller maximal electrical damping with larger optimal load resistance is found for the harvester with the DC interface when compared to those for the harvester with the AC interface. At large wind speeds when the maximal electrical damping rather than the optimal electrical damping can be reached by tuning the load resistance alone, the harvester with the AC interface circuit is recommended for a higher maximal harvested power with a smaller tip displacement. This study provides a method using the general electrical damping to connect and compare the performances of piezoelectric energy harvesters with same excitation source but different interfaces.

Spatial targeting of agri-environmental policy using bilevel evolutionary optimization

USDA-ARS?s Scientific Manuscript database

In this study we describe the optimal designation of agri-environmental policy as a bilevel optimization problem and propose an integrated solution method using a hybrid genetic algorithm. The problem is characterized by a single leader, the agency, that establishes a policy with the goal of optimiz...

Date seed oil loaded niosomes: development, optimization and anti-inflammatory effect evaluation on rats.

PubMed

Soliman, Mahmoud S; Abd-Allah, Fathy I; Hussain, Talib; Saeed, Noha M; El-Sawy, Hossam S

2018-07-01

An optimized date seed oil (DSO) loaded niosomes was formulated. Maximize the extract anti-inflammatory efficacy and govern its release characteristics from nanoparticles for osteoarthritis prevention and treatment purposes. By using Box-Behnken Design, the effect of three formulation factors on the entrapment efficiency percentage (Y 1 ), initial DSO release percentage after 2 h (Y 2 ), and cumulative DSO release percentage of DSO after 12 h (Y 3 ), were optimized and studied. The optimized DSO formulation was specified, elaborated, particle size and zeta potential assessed, examined morphologically under electron and light microscope, and in vivo evaluated via carrageenan-induced rat paw edema study. 65.89%, 18.39%, and 58.27% were the measured responses of the optimized niosomes for Y 1 , Y 2 , and Y 3 , respectively. The vesicular structure of the optimized DSO loaded nano-vesicles with nano-size range and good stability features were confirmed. Furthermore, a distinguished anti-inflammatory activity in both prompt and sustained effectiveness were exhibited via the optimized DSO niosomes. Interestingly, the delayed efficacy outcomes of the extract loaded nanoparticles showed a similarity profile as well as the negative control group outcomes. To emphasize, DSO loading in niosomes revealed a significant enhancement toward inflammation alleviation, which offers a promising implement in osteoarthritis remediation and prohibition.

An Optimized Control for LLC Resonant Converter with Wide Load Range

NASA Astrophysics Data System (ADS)

Xi, Xia; Qian, Qinsong

2017-05-01

This paper presents an optimized control which makes LLC resonant converters operate with a wider load range and provides good closed-loop performance. The proposed control employs two paralleled digital compensations to guarantee the good closed-loop performance in a wide load range during the steady state, an optimized trajectory control will take over to change the gate-driving signals immediately at the load transients. Finally, the proposed control has been implemented and tested on a 150W 200kHz 400V/24V LLC resonant converter and the result validates the proposed method.

Numerical verification of two-component dental implant in the context of fatigue life for various load cases.

PubMed

Szajek, Krzysztof; Wierszycki, Marcin

2016-01-01

Dental implant designing is a complex process which considers many limitations both biological and mechanical in nature. In earlier studies, a complete procedure for improvement of two-component dental implant was proposed. However, the optimization tasks carried out required assumption on representative load case, which raised doubts on optimality for the other load cases. This paper deals with verification of the optimal design in context of fatigue life and its main goal is to answer the question if the assumed load scenario (solely horizontal occlusal load) leads to the design which is also "safe" for oblique occlussal loads regardless the angle from an implant axis. The verification is carried out with series of finite element analyses for wide spectrum of physiologically justified loads. The design of experiment methodology with full factorial technique is utilized. All computations are done in Abaqus suite. The maximal Mises stress and normalized effective stress amplitude for various load cases are discussed and compared with the assumed "safe" limit (equivalent of fatigue life for 5e6 cycles). The obtained results proof that coronial-appical load component should be taken into consideration in the two component dental implant when fatigue life is optimized. However, its influence in the analyzed case is small and does not change the fact that the fatigue life improvement is observed for all components within whole range of analyzed loads.

Optimization of structures undergoing harmonic or stochastic excitation. Ph.D. Thesis; [atmospheric turbulence and white noise

NASA Technical Reports Server (NTRS)

Johnson, E. H.

1975-01-01

The optimal design was investigated of simple structures subjected to dynamic loads, with constraints on the structures' responses. Optimal designs were examined for one dimensional structures excited by harmonically oscillating loads, similar structures excited by white noise, and a wing in the presence of continuous atmospheric turbulence. The first has constraints on the maximum allowable stress while the last two place bounds on the probability of failure of the structure. Approximations were made to replace the time parameter with a frequency parameter. For the first problem, this involved the steady state response, and in the remaining cases, power spectral techniques were employed to find the root mean square values of the responses. Optimal solutions were found by using computer algorithms which combined finite elements methods with optimization techniques based on mathematical programming. It was found that the inertial loads for these dynamic problems result in optimal structures that are radically different from those obtained for structures loaded statically by forces of comparable magnitude.

[Optimization on trehalose loading technique as protective conditioning for lyophilization of human platelets].

PubMed

Liu, Jing-Han; Zhou, Jun; Ouyang, Xi-Lin; Li, Xi-Jin; Lu, Fa-Qiang

2005-08-01

This study was aimed to further optimize trehalose loading technique including loading temperature, loading time, loading solution and loading concentration of trehalose, based on the established parameters. Loading efficiency in plasma was compared with that in buffer at 37 degrees C; the curves of intracellular trehalose concentration versus loading time at 37 degrees C and 16 degrees C were measured; curves of mean platelet volume (MPV) versus loading time and loading concentration were investigated and compared. According to results obtained, the loaing time, loading temperature, loading solution and trehalose concentration were ascertained for high loading efficiency of trehalose into human platelet. The results showed that the loading efficiency in plasma was markedly higher than that in buffer at 37 degrees C, the loading efficiency in plasma at 37 degrees C was significantly higher than that at 16 degrees C and reached 19.51% after loading for 4 hours, but 6.16% at 16 degrees C. MPV at 16 degrees C was increased by 43.2% than that at 37 degrees C, but had no distinct changes with loading time and loading concentration. In loading at 37 degrees C, MPV increased with loading time and loading concentration positively. Loading time and loading concentration displayed synergetic effect on MPV. MPV increased with loading time and concentration while trehalose loading concentration was above 50 mmol/L. It is concluded that the optimization parameters of trehalose loading technique are 37 degrees C (temperature), 4 hours (leading time), plasma (loading solution), 50 mmol/L (feasible trehalose concentration). The trehalose concentration can be adjusted to meet the requirement of lyophilization.

Impact of a phenytoin loading dose program in the emergency department.

PubMed

Brancaccio, Adam; Giuliano, Christopher; McNorton, Kelly; Delgado, George

2014-11-01

The use of a combined physician-and pharmacist-directed phenytoin loading dose program in an emergency department (ED) was evaluated. This single-center, observational, preimplementation-postimplementation study evaluated adult patients who received a phenytoin loading dose in the ED. The primary outcome compared the proportion of optimal phenytoin loading doses in the preimplementation and postimplementation groups. The postimplementation group was further stratified into pharmacist- and prescriber-dosing groups. Other outcomes evaluated included the numbers of appropriate serum phenytoin concentrations measured, adverse drug reactions (ADRs), and recurrence of seizures within 24 hours of loading dose administration in the preimplementation and postimplementation groups. There was no difference in the proportion of optimal phenytoin loading doses between the preimplementation and postimplementation groups (50% versus 62%, respectively; p=0.19). When stratified by individual groups, the rate of optimal phenytoin loading doses increased by 64% in the postimplementation pharmacist group (50% versus 82%, p=0.007), while the rate in the prescriber-dosing group remained relatively unchanged (50% versus 49%, p=0.91). The number of appropriate serum phenytoin concentrations significantly improved in the postimplementation versus preimplementation group (65% versus 40%, p=0.025). Rates of ADRs and recurrence of seizures did not differ across the study groups. No change in the percentage of optimal phenytoin loading doses in the ED was observed after implementation of a combined pharmacist- and physician- dosing program. When stratified into pharmacist or prescriber dosing, the pharmacist-led dosing program significantly improved the proportion of patients who received optimal phenytoin loading doses. Copyright © 2014 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

Optimization of cryoprotectant loading into murine and human oocytes.

PubMed

Karlsson, Jens O M; Szurek, Edyta A; Higgins, Adam Z; Lee, Sang R; Eroglu, Ali

2014-02-01

Loading of cryoprotectants into oocytes is an important step of the cryopreservation process, in which the cells are exposed to potentially damaging osmotic stresses and chemical toxicity. Thus, we investigated the use of physics-based mathematical optimization to guide design of cryoprotectant loading methods for mouse and human oocytes. We first examined loading of 1.5 M dimethyl sulfoxide (Me(2)SO) into mouse oocytes at 23°C. Conventional one-step loading resulted in rates of fertilization (34%) and embryonic development (60%) that were significantly lower than those of untreated controls (95% and 94%, respectively). In contrast, the mathematically optimized two-step method yielded much higher rates of fertilization (85%) and development (87%). To examine the causes for oocyte damage, we performed experiments to separate the effects of cell shrinkage and Me(2)SO exposure time, revealing that neither shrinkage nor Me(2)SO exposure single-handedly impairs the fertilization and development rates. Thus, damage during one-step Me(2)SO addition appears to result from interactions between the effects of Me(2)SO toxicity and osmotic stress. We also investigated Me(2)SO loading into mouse oocytes at 30°C. At this temperature, fertilization rates were again lower after one-step loading (8%) in comparison to mathematically optimized two-step loading (86%) and untreated controls (96%). Furthermore, our computer algorithm generated an effective strategy for reducing Me(2)SO exposure time, using hypotonic diluents for cryoprotectant solutions. With this technique, 1.5 M Me(2)SO was successfully loaded in only 2.5 min, with 92% fertilizability. Based on these promising results, we propose new methods to load cryoprotectants into human oocytes, designed using our mathematical optimization approach. Copyright © 2013 Elsevier Inc. All rights reserved.

Optimization of Cryoprotectant Loading into Murine and Human Oocytes

PubMed Central

Karlsson, Jens O.M.; Szurek, Edyta A.; Higgins, Adam Z.; Lee, Sang R.; Eroglu, Ali

2014-01-01

Loading of cryoprotectants into oocytes is an important step of the cryopreservation process, in which the cells are exposed to potentially damaging osmotic stresses and chemical toxicity. Thus, we investigated the use of physics-based mathematical optimization to guide design of cryoprotectant loading methods for mouse and human oocytes. We first examined loading of 1.5 M dimethylsulfoxide (Me2SO) into mouse oocytes at 23°C. Conventional one-step loading resulted in rates of fertilization (34%) and embryonic development (60%) that were significantly lower than those of untreated controls (95% and 94%, respectively). In contrast, the mathematically optimized two-step method yielded much higher rates of fertilization (85%) and development (87%). To examine the causes for oocyte damage, we performed experiments to separate the effects of cell shrinkage and Me2SO exposure time, revealing that neither shrinkage nor Me2SO exposure single-handedly impairs the fertilization and development rates. Thus, damage during one-step Me2SO addition appears to result from interactions between the effects of Me2SO toxicity and osmotic stress. We also investigated Me2SO loading into mouse oocytes at 30°C. At this temperature, fertilization rates were again lower after one-step loading (8%) in comparison to mathematically optimized two-step loading (86%) and untreated controls (96%). Furthermore, our computer algorithm generated an effective strategy for reducing Me2SO exposure time, using hypotonic diluents for cryoprotectant solutions. With this technique, 1.5 M Me2SO was successfully loaded in only 2.5 min, with 92% fertilizability. Based on these promising results, we propose new methods to load cryoprotectants into human oocytes, designed using our mathematical optimization approach. PMID:24246951

A Method to Analyze and Optimize the Load Sharing of Split Path Transmissions

NASA Technical Reports Server (NTRS)

Krantz, Timothy L.

1996-01-01

Split-path transmissions are promising alternatives to the common planetary transmissions for rotorcraft. Heretofore, split-path designs proposed for or used in rotorcraft have featured load-sharing devices that add undesirable weight and complexity to the designs. A method was developed to analyze and optimize the load sharing in split-path transmissions without load-sharing devices. The method uses the clocking angle as a design parameter to optimize for equal load sharing. In addition, the clocking angle tolerance necessary to maintain acceptable load sharing can be calculated. The method evaluates the effects of gear-shaft twisting and bending, tooth bending, Hertzian deformations within bearings, and movement of bearing supports on load sharing. It was used to study the NASA split-path test gearbox and the U.S. Army's Comanche helicopter main rotor gearbox. Acceptable load sharing was found to be achievable and maintainable by using proven manufacturing processes. The analytical results compare favorably to available experimental data.

Design and Performance of Lift-Offset Rotorcraft for Short-Haul Missions

DTIC Science & Technology

2012-01-01

loading and blade loading were varied to optimize the designs, based on gross weight and fuel burn. The influence of technology is shown, in terms of...loading were varied to optimize the designs, based on gross weight and fuel burn. The influence of technology is shown, in terms of rotor hub drag and...distributions were optimized for these conditions (Fig. 4), and the rotor and aircraft cruise performance was calculated (Fig. 5). Based on comprehensive

General shape optimization capability

NASA Technical Reports Server (NTRS)

Chargin, Mladen K.; Raasch, Ingo; Bruns, Rudolf; Deuermeyer, Dawson

1991-01-01

A method is described for calculating shape sensitivities, within MSC/NASTRAN, in a simple manner without resort to external programs. The method uses natural design variables to define the shape changes in a given structure. Once the shape sensitivities are obtained, the shape optimization process is carried out in a manner similar to property optimization processes. The capability of this method is illustrated by two examples: the shape optimization of a cantilever beam with holes, loaded by a point load at the free end (with the shape of the holes and the thickness of the beam selected as the design variables), and the shape optimization of a connecting rod subjected to several different loading and boundary conditions.

Coordination of a supply chain with consumer return under vendor-managed consignment inventory and stochastic demand

NASA Astrophysics Data System (ADS)

Wu, Zhihui; Chen, Dongyan; Yu, Hui

2016-07-01

In this paper, the problem of the coordination policy is investigated for vendor-managed consignment inventory supply chain subject to consumer return. Here, the market demand is assumed to be affected by promotional effort and consumer return policy. The optimal consignment inventory and the optimal promotional effort level are proposed under the decentralized and centralized decisions. Based on the optimal decision conditions, the markdown allowance-promotional cost-sharing contract is investigated to coordinate the supply chain. Subsequently, the comparison between the two extreme policies shows that full-refund policy dominates the no-return policy when the returning cost and the positive effect of return policy are satisfied certain conditions. Finally, a numerical example is provided to illustrate the impacts of consumer return policy on the coordination contract and optimal profit as well as the effectiveness of the proposed supply chain decision.

Spatial optimization of watershed management practices for nitrogen load reduction using a modeling-optimization framework

EPA Science Inventory

Best management practices (BMPs) are perceived as being effective in reducing nutrient loads transported from non-point sources (NPS) to receiving water bodies. The objective of this study was to develop a modeling-optimization framework that can be used by watershed management p...

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.

Financing and funding health care: Optimal policy and political implementability.

PubMed

Nuscheler, Robert; Roeder, Kerstin

2015-07-01

Health care financing and funding are usually analyzed in isolation. This paper combines the corresponding strands of the literature and thereby advances our understanding of the important interaction between them. We investigate the impact of three modes of health care financing, namely, optimal income taxation, proportional income taxation, and insurance premiums, on optimal provider payment and on the political implementability of optimal policies under majority voting. Considering a standard multi-task agency framework we show that optimal health care policies will generally differ across financing regimes when the health authority has redistributive concerns. We show that health care financing also has a bearing on the political implementability of optimal health care policies. Our results demonstrate that an isolated analysis of (optimal) provider payment rests on very strong assumptions regarding both the financing of health care and the redistributive preferences of the health authority. Copyright © 2015 Elsevier B.V. All rights reserved.

Simultaneous optimization of loading pattern and burnable poison placement for PWRs

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

Alim, F.; Ivanov, K.; Yilmaz, S.

2006-07-01

To solve in-core fuel management optimization problem, GARCO-PSU (Genetic Algorithm Reactor Core Optimization - Pennsylvania State Univ.) is developed. This code is applicable for all types and geometry of PWR core structures with unlimited number of fuel assembly (FA) types in the inventory. For this reason an innovative genetic algorithm is developed with modifying the classical representation of the genotype. In-core fuel management heuristic rules are introduced into GARCO. The core re-load design optimization has two parts, loading pattern (LP) optimization and burnable poison (BP) placement optimization. These parts depend on each other, but it is difficult to solve themore » combined problem due to its large size. Separating the problem into two parts provides a practical way to solve the problem. However, the result of this method does not reflect the real optimal solution. GARCO-PSU achieves to solve LP optimization and BP placement optimization simultaneously in an efficient manner. (authors)« less

Pseudo-spectral control of a novel oscillating surge wave energy converter in regular waves for power optimization including load reduction

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

Tom, Nathan M.; Yu, Yi -Hsiang; Wright, Alan D.

The aim of this study is to describe a procedure to maximize the power-to-load ratio of a novel wave energy converter (WEC) that combines an oscillating surge wave energy converter with variable structural components. The control of the power-take-off torque will be on a wave-to-wave timescale, whereas the structure will be controlled statically such that the geometry remains the same throughout the wave period. Linear hydrodynamic theory is used to calculate the upper and lower bounds for the time-averaged absorbed power and surge foundation loads while assuming that the WEC motion remains sinusoidal. Previous work using pseudo-spectral techniques to solvemore » the optimal control problem focused solely on maximizing absorbed energy. This work extends the optimal control problem to include a measure of the surge foundation force in the optimization. The objective function includes two competing terms that force the optimizer to maximize power capture while minimizing structural loads. A penalty weight was included with the surge foundation force that allows control of the optimizer performance based on whether emphasis should be placed on power absorption or load shedding. Results from pseudo-spectral optimal control indicate that a unit reduction in time-averaged power can be accompanied by a greater reduction in surge-foundation force.« less

Pseudo-spectral control of a novel oscillating surge wave energy converter in regular waves for power optimization including load reduction

DOE PAGES

Tom, Nathan M.; Yu, Yi -Hsiang; Wright, Alan D.; ...

2017-04-18

The aim of this study is to describe a procedure to maximize the power-to-load ratio of a novel wave energy converter (WEC) that combines an oscillating surge wave energy converter with variable structural components. The control of the power-take-off torque will be on a wave-to-wave timescale, whereas the structure will be controlled statically such that the geometry remains the same throughout the wave period. Linear hydrodynamic theory is used to calculate the upper and lower bounds for the time-averaged absorbed power and surge foundation loads while assuming that the WEC motion remains sinusoidal. Previous work using pseudo-spectral techniques to solvemore » the optimal control problem focused solely on maximizing absorbed energy. This work extends the optimal control problem to include a measure of the surge foundation force in the optimization. The objective function includes two competing terms that force the optimizer to maximize power capture while minimizing structural loads. A penalty weight was included with the surge foundation force that allows control of the optimizer performance based on whether emphasis should be placed on power absorption or load shedding. Results from pseudo-spectral optimal control indicate that a unit reduction in time-averaged power can be accompanied by a greater reduction in surge-foundation force.« less

The complete proof on the optimal ordering policy under cash discount and trade credit

NASA Astrophysics Data System (ADS)

Chung, Kun-Jen

2010-04-01

Huang ((2005), 'Buyer's Optimal Ordering Policy and Payment Policy under Supplier Credit', International Journal of Systems Science, 36, 801-807) investigates the buyer's optimal ordering policy and payment policy under supplier credit. His inventory model is correct and interesting. Basically, he uses an algebraic method to locate the optimal solution of the annual total relevant cost TRC(T) and ignores the role of the functional behaviour of TRC(T) in locating the optimal solution of it. However, as argued in this article, Huang needs to explore the functional behaviour of TRC(T) to justify his solution. So, from the viewpoint of logic, the proof about Theorem 1 in Huang has some shortcomings such that the validity of Theorem 1 in Huang is questionable. The main purpose of this article is to remove and correct those shortcomings in Huang and present the complete proofs for Huang.

Extreme Trust Region Policy Optimization for Active Object Recognition.

PubMed

Liu, Huaping; Wu, Yupei; Sun, Fuchun; Huaping Liu; Yupei Wu; Fuchun Sun; Sun, Fuchun; Liu, Huaping; Wu, Yupei

2018-06-01

In this brief, we develop a deep reinforcement learning method to actively recognize objects by choosing a sequence of actions for an active camera that helps to discriminate between the objects. The method is realized using trust region policy optimization, in which the policy is realized by an extreme learning machine and, therefore, leads to efficient optimization algorithm. The experimental results on the publicly available data set show the advantages of the developed extreme trust region optimization method.

Comparative Assessment of Models and Methods To Calculate Grid Electricity Emissions.

PubMed

Ryan, Nicole A; Johnson, Jeremiah X; Keoleian, Gregory A

2016-09-06

Due to the complexity of power systems, tracking emissions attributable to a specific electrical load is a daunting challenge but essential for many environmental impact studies. Currently, no consensus exists on appropriate methods for quantifying emissions from particular electricity loads. This paper reviews a wide range of the existing methods, detailing their functionality, tractability, and appropriate use. We identified and reviewed 32 methods and models and classified them into two distinct categories: empirical data and relationship models and power system optimization models. To illustrate the impact of method selection, we calculate the CO2 combustion emissions factors associated with electric-vehicle charging using 10 methods at nine charging station locations around the United States. Across the methods, we found an up to 68% difference from the mean CO2 emissions factor for a given charging site among both marginal and average emissions factors and up to a 63% difference from the average across average emissions factors. Our results underscore the importance of method selection and the need for a consensus on approaches appropriate for particular loads and research questions being addressed in order to achieve results that are more consistent across studies and allow for soundly supported policy decisions. The paper addresses this issue by offering a set of recommendations for determining an appropriate model type on the basis of the load characteristics and study objectives.

Biomechanical evaluation of an innovative spring-loaded axillary crutch design.

PubMed

Zhang, Yanxin; Liu, Guangyu; Xie, Shengquan; Liger, Aurélien

2011-01-01

We evaluated an innovative spring-loaded crutch design by comparing its performance with standard crutches through a biomechanical approach. Gait analysis was conducted for 7 male subjects under two conditions: walking with standard crutches and with spring-loaded crutches. Three-dimensional kinematic data and ground reaction force were recorded. Spatiotemporal variables, external mechanical work, and elastic energy (for spring crutches) were calculated based on recorded data. The trajectories of vertical ground reaction forces with standard crutches had two main peaks before and after mid-stance, and those with optimized spring-loaded crutches had only one main peak. The magnitude of external mechanical work was significantly higher with spring-loaded crutches than with standard crutches for all subjects, and the transferred elastic energy made an important contribution to the total external work for spring-loaded crutches. No significant differences in the spatiotemporal parameters were observed. Optimized spring-loaded crutches can efficiently propel crutch walkers and could reduce the total energy expenditure in crutch walking. Further research using optimized spring-loaded crutches with respect to energy efficiency is recommended.

Analytic model for ultrasound energy receivers and their optimal electric loads II: Experimental validation

NASA Astrophysics Data System (ADS)

Gorostiaga, M.; Wapler, M. C.; Wallrabe, U.

2017-10-01

In this paper, we verify the two optimal electric load concepts based on the zero reflection condition and on the power maximization approach for ultrasound energy receivers. We test a high loss 1-3 composite transducer, and find that the measurements agree very well with the predictions of the analytic model for plate transducers that we have developed previously. Additionally, we also confirm that the power maximization and zero reflection loads are very different when the losses in the receiver are high. Finally, we compare the optimal load predictions by the KLM and the analytic models with frequency dependent attenuation to evaluate the influence of the viscosity.

Research Based on AMESim of Electro-hydraulic Servo Loading System

NASA Astrophysics Data System (ADS)

Li, Jinlong; Hu, Zhiyong

2017-09-01

Electro-hydraulic servo loading system is a subject studied by many scholars in the field of simulation and control at home and abroad. The electro-hydraulic servo loading system is a loading device simulation of stress objects by aerodynamic moment and other force in the process of movement, its function is all kinds of gas in the lab condition to analyze stress under dynamic load of objects. The purpose of this paper is the design of AMESim electro-hydraulic servo system, PID control technology is used to configure the parameters of the control system, complete the loading process under different conditions, the optimal design parameters, optimization of dynamic performance of the loading system.

Optimizing model: insemination, replacement, seasonal production, and cash flow.

PubMed

DeLorenzo, M A; Spreen, T H; Bryan, G R; Beede, D K; Van Arendonk, J A

1992-03-01

Dynamic programming to solve the Markov decision process problem of optimal insemination and replacement decisions was adapted to address large dairy herd management decision problems in the US. Expected net present values of cow states (151,200) were used to determine the optimal policy. States were specified by class of parity (n = 12), production level (n = 15), month of calving (n = 12), month of lactation (n = 16), and days open (n = 7). Methodology optimized decisions based on net present value of an individual cow and all replacements over a 20-yr decision horizon. Length of decision horizon was chosen to ensure that optimal policies were determined for an infinite planning horizon. Optimization took 286 s of central processing unit time. The final probability transition matrix was determined, in part, by the optimal policy. It was estimated iteratively to determine post-optimization steady state herd structure, milk production, replacement, feed inputs and costs, and resulting cash flow on a calendar month and annual basis if optimal policies were implemented. Implementation of the model included seasonal effects on lactation curve shapes, estrus detection rates, pregnancy rates, milk prices, replacement costs, cull prices, and genetic progress. Other inputs included calf values, values of dietary TDN and CP per kilogram, and discount rate. Stochastic elements included conception (and, thus, subsequent freshening), cow milk production level within herd, and survival. Validation of optimized solutions was by separate simulation model, which implemented policies on a simulated herd and also described herd dynamics during transition to optimized structure.

Assessment of hemodynamic load components affecting optimization of cardiac resynchronization therapy by lumped parameter mode.

PubMed

Xu, Ke; Butlin, Mark; Avolio, Alberto P

2012-01-01

Timing of biventricular pacing devices employed in cardiac resynchronization therapy (CRT) is a critical determinant of efficacy of the procedure. Optimization is done by maximizing function in terms of arterial pressure (BP) or cardiac output (CO). However, BP and CO are also determined by the hemodynamic load of the pulmonary and systemic vasculature. This study aims to use a lumped parameter circulatory model to assess the influence of the arterial load on the atrio-ventricular (AV) and inter-ventricular (VV) delay for optimal CRT performance.

A distributed scheduling algorithm for heterogeneous real-time systems

NASA Technical Reports Server (NTRS)

Zeineldine, Osman; El-Toweissy, Mohamed; Mukkamala, Ravi

1991-01-01

Much of the previous work on load balancing and scheduling in distributed environments was concerned with homogeneous systems and homogeneous loads. Several of the results indicated that random policies are as effective as other more complex load allocation policies. The effects of heterogeneity on scheduling algorithms for hard real time systems is examined. A distributed scheduler specifically to handle heterogeneities in both nodes and node traffic is proposed. The performance of the algorithm is measured in terms of the percentage of jobs discarded. While a random task allocation is very sensitive to heterogeneities, the algorithm is shown to be robust to such non-uniformities in system components and load.

Optimization of vitamins A and D3 loading in re-assembled casein micelles and effect of loading on stability of vitamin D3 during storage.

PubMed

Loewen, Anisa; Chan, Benny; Li-Chan, Eunice C Y

2018-02-01

The objectives of this study were to apply response surface methodology to optimize fat-soluble vitamin loading in re-assembled casein micelles, and to evaluate vitamin D stability of dry formulations during ambient or accelerated storage and in fortified fluid skim milk stored under refrigeration. Optimal loading of vitamin A (1.46-1.48mg/100mgcasein) was found at 9.7mM phosphate, 5.5mM citrate and 30.0mM calcium, while optimal loading of vitamin D (1.38-1.46mg/100mg casein) was found at 4.9mM phosphate, 4.0mM citrate and 26.1mM calcium. In general, more vitamin D was retained in vitamin D-re-assembled casein micelles than control powders during storage, while vitamin D loss was not different for vitamin D-re-assembled casein micelles and control fortified milks after 21days of refrigerated storage with light exposure. In conclusion, re-assembled casein micelles with high loading efficiency show promise for improving vitamin D stability during dry storage. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Assessment of the Charging Policy in Energy Efficiency of the Enterprise

NASA Astrophysics Data System (ADS)

Shutov, E. A.; E Turukina, T.; Anisimov, T. S.

2017-04-01

The forecasting problem for energy facilities with a power exceeding 670 kW is currently one of the main. In connection with rules of the retail electricity market such customers also pay for actual energy consumption deviations from plan value. In compliance with the hierarchical stages of the electricity market a guaranteeing supplier is to respect the interests of distribution and generation companies that require load leveling. The answer to this question for industrial enterprise is possible only within technological process through implementation of energy-efficient processing chains with the adaptive function and forecasting tool. In such a circumstance the primary objective of a forecasting is reduce the energy consumption costs by taking account of the energy cost correlation for 24 hours for forming of pumping unit work schedule. The pumping unit virtual model with the variable frequency drive is considered. The forecasting tool and the optimizer are integrated into typical control circuit. Economic assessment of the optimization method was estimated.

A VVWBO-BVO-based GM (1,1) and its parameter optimization by GRA-IGSA integration algorithm for annual power load forecasting

PubMed Central

Wang, Hongguang

2018-01-01

Annual power load forecasting is not only the premise of formulating reasonable macro power planning, but also an important guarantee for the safety and economic operation of power system. In view of the characteristics of annual power load forecasting, the grey model of GM (1,1) are widely applied. Introducing buffer operator into GM (1,1) to pre-process the historical annual power load data is an approach to improve the forecasting accuracy. To solve the problem of nonadjustable action intensity of traditional weakening buffer operator, variable-weight weakening buffer operator (VWWBO) and background value optimization (BVO) are used to dynamically pre-process the historical annual power load data and a VWWBO-BVO-based GM (1,1) is proposed. To find the optimal value of variable-weight buffer coefficient and background value weight generating coefficient of the proposed model, grey relational analysis (GRA) and improved gravitational search algorithm (IGSA) are integrated and a GRA-IGSA integration algorithm is constructed aiming to maximize the grey relativity between simulating value sequence and actual value sequence. By the adjustable action intensity of buffer operator, the proposed model optimized by GRA-IGSA integration algorithm can obtain a better forecasting accuracy which is demonstrated by the case studies and can provide an optimized solution for annual power load forecasting. PMID:29768450

Performance tradeoffs in static and dynamic load balancing strategies

NASA Technical Reports Server (NTRS)

Iqbal, M. A.; Saltz, J. H.; Bokhart, S. H.

1986-01-01

The problem of uniformly distributing the load of a parallel program over a multiprocessor system was considered. A program was analyzed whose structure permits the computation of the optimal static solution. Then four strategies for load balancing were described and their performance compared. The strategies are: (1) the optimal static assignment algorithm which is guaranteed to yield the best static solution, (2) the static binary dissection method which is very fast but sub-optimal, (3) the greedy algorithm, a static fully polynomial time approximation scheme, which estimates the optimal solution to arbitrary accuracy, and (4) the predictive dynamic load balancing heuristic which uses information on the precedence relationships within the program and outperforms any of the static methods. It is also shown that the overhead incurred by the dynamic heuristic is reduced considerably if it is started off with a static assignment provided by either of the other three strategies.

A Framework for Optimal Control Allocation with Structural Load Constraints

NASA Technical Reports Server (NTRS)

Frost, Susan A.; Taylor, Brian R.; Jutte, Christine V.; Burken, John J.; Trinh, Khanh V.; Bodson, Marc

2010-01-01

Conventional aircraft generally employ mixing algorithms or lookup tables to determine control surface deflections needed to achieve moments commanded by the flight control system. Control allocation is the problem of converting desired moments into control effector commands. Next generation aircraft may have many multipurpose, redundant control surfaces, adding considerable complexity to the control allocation problem. These issues can be addressed with optimal control allocation. Most optimal control allocation algorithms have control surface position and rate constraints. However, these constraints are insufficient to ensure that the aircraft's structural load limits will not be exceeded by commanded surface deflections. In this paper, a framework is proposed to enable a flight control system with optimal control allocation to incorporate real-time structural load feedback and structural load constraints. A proof of concept simulation that demonstrates the framework in a simulation of a generic transport aircraft is presented.

Community-driven demand creation for the use of routine viral load testing: a model to scale up routine viral load testing.

PubMed

Killingo, Bactrin M; Taro, Trisa B; Mosime, Wame N

2017-11-01

HIV treatment outcomes are dependent on the use of viral load measurement. Despite global and national guidelines recommending the use of routine viral load testing, these policies alone have not translated into widespread implementation or sufficiently increased access for people living with HIV (PLHIV). Civil society and communities of PLHIV recognize the need to close this gap and to enable the scale up of routine viral load testing. The International Treatment Preparedness Coalition (ITPC) developed an approach to community-led demand creation for the use of routine viral load testing. Using this Community Demand Creation Model, implementers follow a step-wise process to capacitate and empower communities to address their most pressing needs. This includes utlizing a specific toolkit that includes conducting a baseline assessment, developing a treatment education toolkit, organizing mobilization workshops for knowledge building, provision of small grants to support advocacy work and conducting benchmark evaluations. The Community Demand Creation Model to increase demand for routine viral load testing services by PLHIV has been delivered in diverse contexts including in the sub-Saharan African, Asian, Latin American and the Caribbean regions. Between December 2015 and December 2016, ITPC trained more than 240 PLHIV activists, and disbursed US$90,000 to network partners in support of their national advocacy work. The latter efforts informed a regional, community-driven campaign calling for domestic investment in the expeditious implementation of national viral load testing guidelines. HIV treatment education and community mobilization are critical components of demand creation for access to optimal HIV treatment, especially for the use of routine viral load testing. ITPC's Community Demand Creation Model offers a novel approach to achieving this goal. © 2017 The Authors. Journal of the International AIDS Society published by John Wiley & sons Ltd on behalf of the International AIDS Society.

Cost optimization of reinforced concrete cantilever retaining walls under seismic loading using a biogeography-based optimization algorithm with Levy flights

NASA Astrophysics Data System (ADS)

Aydogdu, Ibrahim

2017-03-01

In this article, a new version of a biogeography-based optimization algorithm with Levy flight distribution (LFBBO) is introduced and used for the optimum design of reinforced concrete cantilever retaining walls under seismic loading. The cost of the wall is taken as an objective function, which is minimized under the constraints implemented by the American Concrete Institute (ACI 318-05) design code and geometric limitations. The influence of peak ground acceleration (PGA) on optimal cost is also investigated. The solution of the problem is attained by the LFBBO algorithm, which is developed by adding Levy flight distribution to the mutation part of the biogeography-based optimization (BBO) algorithm. Five design examples, of which two are used in literature studies, are optimized in the study. The results are compared to test the performance of the LFBBO and BBO algorithms, to determine the influence of the seismic load and PGA on the optimal cost of the wall.

Load management as a smart grid concept for sizing and designing of hybrid renewable energy systems

NASA Astrophysics Data System (ADS)

Eltamaly, Ali M.; Mohamed, Mohamed A.; Al-Saud, M. S.; Alolah, Abdulrahman I.

2017-10-01

Optimal sizing of hybrid renewable energy systems (HRES) to satisfy load requirements with the highest reliability and lowest cost is a crucial step in building HRESs to supply electricity to remote areas. Applying smart grid concepts such as load management can reduce the size of HRES components and reduce the cost of generated energy considerably. In this article, sizing of HRES is carried out by dividing the load into high- and low-priority parts. The proposed system is formed by a photovoltaic array, wind turbines, batteries, fuel cells and a diesel generator as a back-up energy source. A smart particle swarm optimization (PSO) algorithm using MATLAB is introduced to determine the optimal size of the HRES. The simulation was carried out with and without division of the load to compare these concepts. HOMER software was also used to simulate the proposed system without dividing the loads to verify the results obtained from the proposed PSO algorithm. The results show that the percentage of division of the load is inversely proportional to the cost of the generated energy.

Load research manual. Volume 3: Load research for advanced technologies

NASA Astrophysics Data System (ADS)

1980-11-01

Technical guidelines for electric utility load research are presented. Special attention is given to issues raised by the load reporting requirements of the Public Utility Regulatory Policies Act of 1978 and to problems faced by smaller utilities that are initiating load research programs. The manual includes guides to load research literature and glossaries of load research and statistical terms. Special load research procedures are presented for solar, wind, and cogeneration technologies.

Study on Pyroelectric Harvesters with Various Geometry

PubMed Central

Siao, An-Shen; Chao, Ching-Kong; Hsiao, Chun-Ching

2015-01-01

Pyroelectric harvesters convert time-dependent temperature variations into electric current. The appropriate geometry of the pyroelectric cells, coupled with the optimal period of temperature fluctuations, is key to driving the optimal load resistance, which enhances the performance of pyroelectric harvesters. The induced charge increases when the thickness of the pyroelectric cells decreases. Moreover, the induced charge is extremely reduced for the thinner pyroelectric cell when not used for the optimal period. The maximum harvested power is achieved when a 100 μm-thick PZT (Lead zirconate titanate) cell is used to drive the optimal load resistance of about 40 MΩ. Moreover, the harvested power is greatly reduced when the working resistance diverges even slightly from the optimal load resistance. The stored voltage generated from the 75 μm-thick PZT cell is less than that from the 400 μm-thick PZT cell for a period longer than 64 s. Although the thinner PZT cell is advantageous in that it enhances the efficiency of the pyroelectric harvester, the much thinner 75 μm-thick PZT cell and the divergence from the optimal period further diminish the performance of the pyroelectric cell. Therefore, the designers of pyroelectric harvesters need to consider the coupling effect between the geometry of the pyroelectric cells and the optimal period of temperature fluctuations to drive the optimal load resistance. PMID:26270666

Quantum-enhanced reinforcement learning for finite-episode games with discrete state spaces

NASA Astrophysics Data System (ADS)

Neukart, Florian; Von Dollen, David; Seidel, Christian; Compostella, Gabriele

2017-12-01

Quantum annealing algorithms belong to the class of metaheuristic tools, applicable for solving binary optimization problems. Hardware implementations of quantum annealing, such as the quantum annealing machines produced by D-Wave Systems, have been subject to multiple analyses in research, with the aim of characterizing the technology's usefulness for optimization and sampling tasks. Here, we present a way to partially embed both Monte Carlo policy iteration for finding an optimal policy on random observations, as well as how to embed n sub-optimal state-value functions for approximating an improved state-value function given a policy for finite horizon games with discrete state spaces on a D-Wave 2000Q quantum processing unit (QPU). We explain how both problems can be expressed as a quadratic unconstrained binary optimization (QUBO) problem, and show that quantum-enhanced Monte Carlo policy evaluation allows for finding equivalent or better state-value functions for a given policy with the same number episodes compared to a purely classical Monte Carlo algorithm. Additionally, we describe a quantum-classical policy learning algorithm. Our first and foremost aim is to explain how to represent and solve parts of these problems with the help of the QPU, and not to prove supremacy over every existing classical policy evaluation algorithm.

Augmented bioavailability of felodipine through an α-linolenic acid-based microemulsion.

PubMed

Singh, Mahendra; Kanoujia, Jovita; Parashar, Poonam; Arya, Malti; Tripathi, Chandra B; Sinha, V R; Saraf, Shailendra K; Saraf, Shubhini A

2018-02-01

The oral bioavailability of felodipine, a dihydropyridine calcium channel antagonist, is about 15%. This may be due to poor water solubility, and a lower intestinal permeability than a BCS class I drug, and hepatic first-pass metabolism of the drug. Many drugs are unpopular due to solubility issues. The goal of this study was to develop and optimize a felodipine-containing microemulsion to improve the intestinal permeability and bioavailability of the drug. The felodipine microemulsions were developed with the selected components, i.e., α-linolenic acid as the oil phase, Tween 80 as a surfactant, and isopropyl alcohol as co-surfactant using Box-Behnken design and characterized for in vitro release and particle size. The optimized felodipine-loaded microemulsion was investigated for physicochemical interaction, surface morphology, intestinal permeability, rheology, cytotoxicity, cellular uptake, pharmacodynamic (electrocardiogram and heart rate variability), and pharmacokinetic studies to explore its suitability as a promising oral drug delivery system for the treatment of hypertension. The optimized felodipine-loaded microemulsion showed significantly higher (P < 0.05) apparent permeability coefficients (Papp) at 7.918 × 10 -5  cm/s after 1 h, when compared with conventional formulations that are marketed tablet, drug oily solution, and drug emulsion, which showed a maximum Papp of 3.013, 4.428, and 5.335 × 10 -5  cm/s, respectively. The optimized felodipine-loaded microemulsion showed biocompatibility and no cytotoxicity. Cellular uptake studies confirmed payload delivery to a cellular site on the J774.A1 cell line. The rheology study of the optimized felodipine-loaded microemulsion revealed Newtonian-type flow behavior and discontinuous microemulsion formation. In pharmacodynamic studies, significant differences in parameters were observed between the optimized felodipine-loaded microemulsion and marketed formulation. The optimized felodipine-loaded microemulsion showed significantly higher (p < 0.01) C max (7.12 ± 1.04 μg/ml) than marketed tablets (2.44 ± 1.03 μg/ml). It was found that AUC last obtained from the optimized felodipine-loaded microemulsion (84.53 ± 10.73 μg h/ml) was significantly higher (p < 0.01) than the marketed tablet (27.41 ± 5.54 μg h/ml). The relative bioavailability (Fr) of the optimized felodipine-loaded microemulsion was about 308.3% higher than that of the marketed formulation. The results demonstrate that the prepared microemulsion is an advanced and efficient oral delivery system of felodipine for the management of hypertension.

Airborne soil dust and its importance in buffering of atmospheric acidity and critical load assessment, over the semi arid tract of northern India.

NASA Astrophysics Data System (ADS)

Sharma, Disha; Kulshrestha, Umesh

Airborne soil dust and its importance in buffering of atmospheric acidity and critical load assessment, over the semi arid tract of northern India. The Critical Load approach alongwith integrated assessment models has been used in the European nations for policy formations to reduce acidic emissions. This unique approach was applied to assess the of vulnerability of natural systems to the present day atmospheric pollution scenario. The calculated values of critical loads of sulphur ( 225 - 275 eq/ha/yr) and nitrogen (298 - 303 eq/ha/yr), for the soil system in Delhi, were calculated with respect to Anjan grass, Hibiscus and Black siris. The present loads of sulphur (PL(S) = 26.40 eq/ha/yr) and nitrogen (PL(N) = 36.51 eq/ha/yr) were found to be much lower than their critical loads without posing any danger of atmospheric acidic deposition on the soil systems. The study indicated that the system is still protective due to high pH of soil. The nature of buffering capability of calcium derived from soil dust can be considered as a natural tool to combat acidification in the Indian region. The results showed that the pollution status in Delhi is still within the safe limits. However, at the pace at which the city is growing, it is likely that in coming decades, it may exceed these critical values. In order to set deposition limits and avoid adverse effects of acidic deposition this approach can be applied in India too. Such approach is very useful, not only in abating pollution but also in devising means of cost optimal emission abatement strategies.

Analysis and prediction of operating vehicle load effects on Highway bridges under the weight charge policy

NASA Astrophysics Data System (ADS)

Huang, Haiyun; Zhang, Junping; Li, Yonghe

2018-05-01

Under the weight charge policy, the weigh in motion data at a toll station on the Jing-Zhu Expressway were collected. The statistic analysis of vehicle load data was carried out. For calculating the operating vehicle load effects on bridges, by Monte Carlo method used to generate random traffic flow and influence line loading method, the maximum bending moment effect of simple supported beams were obtained. The extreme value I distribution and normal distribution were used to simulate the distribution of the maximum bending moment effect. By the extrapolation of Rice formula and the extreme value I distribution, the predicted values of the maximum load effects were obtained. By comparing with vehicle load effect according to current specification, some references were provided for the management of the operating vehicles and the revision of the bridge specifications.

Knowledge-based load leveling and task allocation in human-machine systems

NASA Technical Reports Server (NTRS)

Chignell, M. H.; Hancock, P. A.

1986-01-01

Conventional human-machine systems use task allocation policies which are based on the premise of a flexible human operator. This individual is most often required to compensate for and augment the capabilities of the machine. The development of artificial intelligence and improved technologies have allowed for a wider range of task allocation strategies. In response to these issues a Knowledge Based Adaptive Mechanism (KBAM) is proposed for assigning tasks to human and machine in real time, using a load leveling policy. This mechanism employs an online workload assessment and compensation system which is responsive to variations in load through an intelligent interface. This interface consists of a loading strategy reasoner which has access to information about the current status of the human-machine system as well as a database of admissible human/machine loading strategies. Difficulties standing in the way of successful implementation of the load leveling strategy are examined.

SN-38 loading capacity of hydrophobic polymer blend nanoparticles: formulation, optimization and efficacy evaluation.

PubMed

Dimchevska, Simona; Geskovski, Nikola; Petruševski, Gjorgji; Chacorovska, Marina; Popeski-Dimovski, Riste; Ugarkovic, Sonja; Goracinova, Katerina

2017-03-01

One of the most important problems in nanoencapsulation of extremely hydrophobic drugs is poor drug loading due to rapid drug crystallization outside the polymer core. The effort to use nanoprecipitation, as a simple one-step procedure with good reproducibility and FDA approved polymers like Poly(lactic-co-glycolic acid) (PLGA) and Polycaprolactone (PCL), will only potentiate this issue. Considering that drug loading is one of the key defining characteristics, in this study we attempted to examine whether the nanoparticle (NP) core composed of two hydrophobic polymers will provide increased drug loading for 7-Ethyl-10-hydroxy-camptothecin (SN-38), relative to NPs prepared using individual polymers. D-optimal design was applied to optimize PLGA/PCL ratio in the polymer blend and the mode of addition of the amphiphilic copolymer Lutrol ® F127 in order to maximize SN-38 loading and obtain NPs with acceptable size for passive tumor targeting. Drug/polymer and polymer/polymer interaction analysis pointed to high degree of compatibility and miscibility among both hydrophobic polymers, providing core configuration with higher drug loading capacity. Toxicity studies outlined the biocompatibility of the blank NPs. Increased in vitro efficacy of drug-loaded NPs compared to the free drug was confirmed by growth inhibition studies using SW-480 cell line. Additionally, the optimized NP formulation showed very promising blood circulation profile with elimination half-time of 7.4 h.

Policy tree optimization for adaptive management of water resources systems

NASA Astrophysics Data System (ADS)

Herman, Jonathan; Giuliani, Matteo

2017-04-01

Water resources systems must cope with irreducible uncertainty in supply and demand, requiring policy alternatives capable of adapting to a range of possible future scenarios. Recent studies have developed adaptive policies based on "signposts" or "tipping points" that suggest the need of updating the policy. However, there remains a need for a general method to optimize the choice of the signposts to be used and their threshold values. This work contributes a general framework and computational algorithm to design adaptive policies as a tree structure (i.e., a hierarchical set of logical rules) using a simulation-optimization approach based on genetic programming. Given a set of feature variables (e.g., reservoir level, inflow observations, inflow forecasts), the resulting policy defines both the optimal reservoir operations and the conditions under which such operations should be triggered. We demonstrate the approach using Folsom Reservoir (California) as a case study, in which operating policies must balance the risk of both floods and droughts. Numerical results show that the tree-based policies outperform the ones designed via Dynamic Programming. In addition, they display good adaptive capacity to the changing climate, successfully adapting the reservoir operations across a large set of uncertain climate scenarios.

Optimization of laminated stacking sequence for buckling load maximization by genetic algorithm

NASA Technical Reports Server (NTRS)

Le Riche, Rodolphe; Haftka, Raphael T.

1992-01-01

The use of a genetic algorithm to optimize the stacking sequence of a composite laminate for buckling load maximization is studied. Various genetic parameters including the population size, the probability of mutation, and the probability of crossover are optimized by numerical experiments. A new genetic operator - permutation - is proposed and shown to be effective in reducing the cost of the genetic search. Results are obtained for a graphite-epoxy plate, first when only the buckling load is considered, and then when constraints on ply contiguity and strain failure are added. The influence on the genetic search of the penalty parameter enforcing the contiguity constraint is studied. The advantage of the genetic algorithm in producing several near-optimal designs is discussed.

[Research on land use structure optimization based on nonpoint source dissolved nitrogen load estimation in Shuaishui watershed].

PubMed

Lu, Yu-Chao; Bi, Meng-Fei; Li, Ze-Li; Sha, Jian; Wang, Yu-Qiu; Qian, Li-Ping

2014-06-01

Regional Nutrient Management (ReNuMa) was applied to estimate dissolved nitrogen (DN) load and perform source apportionment in Shuaishui watershed during 2000-2010. Satisfactory performance of ReNuMa was revealed by the E(ns) and R2 of greater than 0.9 in calibrating and validating streamflow and DN. The average nonpoint DN load in this watershed was 1.11 x 10(3) t x a(-1), with the load intensity of (0.75 +/- 0.22) t x km(-2). Among all the land uses, paddy field had the largest DN load intensity [28.60 kg x (hm2 x a)(-1)], while forest had the least [2.71 kg x (hm2 x a)(-1)]. Agricultural land (including paddy, grain, cash crop, tea plant and orchard) contributed most to DN load in Shuaishui watershed, indicating that the human dominated agricultural activities was the major contributor of nonpoint source pollution. Land use structure optimization for Shuaishui watershed in 2015 was conducted under the rule of reducing pollutants loads and maximizing the agricultural output value. The results demonstrated that agricultural monetary growth was accompanied with the increasing DN load at the optimal level, although output increment was higher than that of DN load.

Optimal pricing policies for services with consideration of facility maintenance costs

NASA Astrophysics Data System (ADS)

Yeh, Ruey Huei; Lin, Yi-Fang

2012-06-01

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

An optimal repartitioning decision policy

NASA Technical Reports Server (NTRS)

Nicol, D. M.; Reynolds, P. F., Jr.

1986-01-01

A central problem to parallel processing is the determination of an effective partitioning of workload to processors. The effectiveness of any given partition is dependent on the stochastic nature of the workload. The problem of determining when and if the stochastic behavior of the workload has changed enough to warrant the calculation of a new partition is treated. The problem is modeled as a Markov decision process, and an optimal decision policy is derived. Quantification of this policy is usually intractable. A heuristic policy which performs nearly optimally is investigated empirically. The results suggest that the detection of change is the predominant issue in this problem.

Optimal allocation of industrial PV-storage micro-grid considering important load

NASA Astrophysics Data System (ADS)

He, Shaohua; Ju, Rong; Yang, Yang; Xu, Shuai; Liang, Lei

2018-03-01

At present, the industrial PV-storage micro-grid has been widely used. This paper presents an optimal allocation model of PV-storage micro-grid capacity considering the important load of industrial users. A multi-objective optimization model is established to promote the local extinction of PV power generation and the maximum investment income of the enterprise as the objective function. Particle swarm optimization (PSO) is used to solve the case of a city in Jiangsu Province, the results are analyzed economically.

Optimal harvesting policy of a stochastic two-species competitive model with Lévy noise in a polluted environment

NASA Astrophysics Data System (ADS)

Zhao, Yu; Yuan, Sanling

2017-07-01

As well known that the sudden environmental shocks and toxicant can affect the population dynamics of fish species, a mechanistic understanding of how sudden environmental change and toxicant influence the optimal harvesting policy requires development. This paper presents the optimal harvesting of a stochastic two-species competitive model with Lévy noise in a polluted environment, where the Lévy noise is used to describe the sudden climate change. Due to the discontinuity of the Lévy noise, the classical optimal harvesting methods based on the explicit solution of the corresponding Fokker-Planck equation are invalid. The object of this paper is to fill up this gap and establish the optimal harvesting policy. By using of aggregation and ergodic methods, the approximation of the optimal harvesting effort and maximum expectation of sustainable yields are obtained. Numerical simulations are carried out to support these theoretical results. Our analysis shows that the Lévy noise and the mean stress measure of toxicant in organism may affect the optimal harvesting policy significantly.

New York City green loading zones study.

DOT National Transportation Integrated Search

2014-07-01

The purpose of this study is to examine the impact and potential benefits of Green Loading Zones (GLZs)a policy solution to incentivize further : electric truck adoption with the creation of curbside loading zones that are exclusively available to...

L∞-Optimal feedforward gust load alleviation design for a large blended wing body airliner

NASA Astrophysics Data System (ADS)

Wildschek, A.; Haniš, T.; Stroscher, F.

2013-12-01

The potential advantages of Blended Wing Body (BWB) aircraft in terms of fuel efficiency are opposed by technical challenges such as the alleviation of gust loads. Due to the low wing, loading gusts, generally, have a more severe impact on BWB aircraft than on conventional aircraft. This paper presents the design and optimization of a Gust Load Alleviation System (GLAS) for a large BWB airliner. Numerical simulations are performed with an aeroelastic model of the aircraft including GLAS in order to compute time series of modal displacements for deriving equivalent static load cases which are used for the resizing of the aircraft structure.

A novel load balanced energy conservation approach in WSN using biogeography based optimization

NASA Astrophysics Data System (ADS)

Kaushik, Ajay; Indu, S.; Gupta, Daya

2017-09-01

Clustering sensor nodes is an effective technique to reduce energy consumption of the sensor nodes and maximize the lifetime of Wireless sensor networks. Balancing load of the cluster head is an important factor in long run operation of WSNs. In this paper we propose a novel load balancing approach using biogeography based optimization (LB-BBO). LB-BBO uses two separate fitness functions to perform load balancing of equal and unequal load respectively. The proposed method is simulated using matlab and compared with existing methods. The proposed method shows better performance than all the previous works implemented for energy conservation in WSN

Optimal Loading for Maximizing Power During Sled-Resisted Sprinting.

PubMed

Cross, Matt R; Brughelli, Matt; Samozino, Pierre; Brown, Scott R; Morin, Jean-Benoit

2017-09-01

To ascertain whether force-velocity-power relationships could be compiled from a battery of sled-resisted overground sprints and to clarify and compare the optimal loading conditions for maximizing power production for different athlete cohorts. Recreational mixed-sport athletes (n = 12) and sprinters (n = 15) performed multiple trials of maximal sprints unloaded and towing a selection of sled masses (20-120% body mass [BM]). Velocity data were collected by sports radar, and kinetics at peak velocity were quantified using friction coefficients and aerodynamic drag. Individual force-velocity and power-velocity relationships were generated using linear and quadratic relationships, respectively. Mechanical and optimal loading variables were subsequently calculated and test-retest reliability assessed. Individual force-velocity and power-velocity relationships were accurately fitted with regression models (R 2 > .977, P < .001) and were reliable (ES = 0.05-0.50, ICC = .73-.97, CV = 1.0-5.4%). The normal loading that maximized peak power was 78% ± 6% and 82% ± 8% of BM, representing a resistance of 3.37 and 3.62 N/kg at 4.19 ± 0.19 and 4.90 ± 0.18 m/s (recreational athletes and sprinters, respectively). Optimal force and normal load did not clearly differentiate between cohorts, although sprinters developed greater maximal power (17.2-26.5%, ES = 0.97-2.13, P < .02) at much greater velocities (16.9%, ES = 3.73, P < .001). Mechanical relationships can be accurately profiled using common sled-training equipment. Notably, the optimal loading conditions determined in this study (69-96% of BM, dependent on friction conditions) represent much greater resistance than current guidelines (~7-20% of BM). This method has potential value in quantifying individualized training parameters for optimized development of horizontal power.

Reinforcement learning solution for HJB equation arising in constrained optimal control problem.

PubMed

Luo, Biao; Wu, Huai-Ning; Huang, Tingwen; Liu, Derong

2015-11-01

The constrained optimal control problem depends on the solution of the complicated Hamilton-Jacobi-Bellman equation (HJBE). In this paper, a data-based off-policy reinforcement learning (RL) method is proposed, which learns the solution of the HJBE and the optimal control policy from real system data. One important feature of the off-policy RL is that its policy evaluation can be realized with data generated by other behavior policies, not necessarily the target policy, which solves the insufficient exploration problem. The convergence of the off-policy RL is proved by demonstrating its equivalence to the successive approximation approach. Its implementation procedure is based on the actor-critic neural networks structure, where the function approximation is conducted with linearly independent basis functions. Subsequently, the convergence of the implementation procedure with function approximation is also proved. Finally, its effectiveness is verified through computer simulations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Assessment of riverine load of contaminants to European seas under policy implementation scenarios: an example with 3 pilot substances.

PubMed

Marinov, Dimitar; Pistocchi, Alberto; Trombetti, Marco; Bidoglio, Giovanni

2014-01-01

An evaluation of conventional emission scenarios is carried out targeting a possible impact of European Union (EU) policies on riverine loads to the European seas for 3 pilot pollutants: lindane, trifluralin, and perfluorooctane sulfonate (PFOS). The policy scenarios are investigated to the time horizon of year 2020 starting from chemical-specific reference conditions and considering different types of regulatory measures including business as usual (BAU), current trend (CT), partial implementation (PI), or complete ban (PI ban) of emissions. The scenario analyses show that the model-estimated lindane load of 745 t to European seas in 1995, based on the official emission data, would be reduced by 98.3% to approximately 12.5 t in 2005 (BAU scenario), 10 years after the start of the EU regulation of this chemical. The CT and PI ban scenarios indicate a reduction of sea loads of lindane in 2020 by 74% and 95%, respectively, when compared to the BAU estimate. For trifluralin, an annual load of approximately 61.7 t is estimated for the baseline year 2003 (BAU scenario), although the applied conservative assumptions related to pesticide use data availability in Europe. Under the PI (ban) scenario, assuming only small residual emissions of trifluralin, we estimate a sea loading of approximately 0.07 t/y. For PFOS, the total sea load from all European countries is estimated at approximately 5.8 t/y referred to 2007 (BAU scenario). Reducing the total load of PFOS below 1 t/y requires emissions to be reduced by 84%. The analysis of conventional scenarios or scenario typologies for emissions of contaminants using simple spatially explicit GIS-based models is suggested as a viable, affordable exercise that may support the assessment of implementation of policies and the identification or negotiation of emission reduction targets. © 2013 SETAC.

Load Forecasting Based Distribution System Network Reconfiguration -- A Distributed Data-Driven Approach

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

Jiang, Huaiguang; Zhang, Yingchen; Muljadi, Eduard

In this paper, a short-term load forecasting approach based network reconfiguration is proposed in a parallel manner. Specifically, a support vector regression (SVR) based short-term load forecasting approach is designed to provide an accurate load prediction and benefit the network reconfiguration. Because of the nonconvexity of the three-phase balanced optimal power flow, a second-order cone program (SOCP) based approach is used to relax the optimal power flow problem. Then, the alternating direction method of multipliers (ADMM) is used to compute the optimal power flow in distributed manner. Considering the limited number of the switches and the increasing computation capability, themore » proposed network reconfiguration is solved in a parallel way. The numerical results demonstrate the feasible and effectiveness of the proposed approach.« less

Load Frequency Control of AC Microgrid Interconnected Thermal Power System

NASA Astrophysics Data System (ADS)

Lal, Deepak Kumar; Barisal, Ajit Kumar

2017-08-01

In this paper, a microgrid (MG) power generation system is interconnected with a single area reheat thermal power system for load frequency control study. A new meta-heuristic optimization algorithm i.e. Moth-Flame Optimization (MFO) algorithm is applied to evaluate optimal gains of the fuzzy based proportional, integral and derivative (PID) controllers. The system dynamic performance is studied by comparing the results with MFO optimized classical PI/PID controllers. Also the system performance is investigated with fuzzy PID controller optimized by recently developed grey wolf optimizer (GWO) algorithm, which has proven its superiority over other previously developed algorithm in many interconnected power systems.

Methods, systems, and computer program products for network firewall policy optimization

DOEpatents

Fulp, Errin W [Winston-Salem, NC; Tarsa, Stephen J [Duxbury, MA

2011-10-18

Methods, systems, and computer program products for firewall policy optimization are disclosed. According to one method, a firewall policy including an ordered list of firewall rules is defined. For each rule, a probability indicating a likelihood of receiving a packet matching the rule is determined. The rules are sorted in order of non-increasing probability in a manner that preserves the firewall policy.

Optimized Controller Design for a 12-Pulse Voltage Source Converter Based HVDC System

NASA Astrophysics Data System (ADS)

Agarwal, Ruchi; Singh, Sanjeev

2017-12-01

The paper proposes an optimized controller design scheme for power quality improvement in 12-pulse voltage source converter based high voltage direct current system. The proposed scheme is hybrid combination of golden section search and successive linear search method. The paper aims at reduction of current sensor and optimization of controller. The voltage and current controller parameters are selected for optimization due to its impact on power quality. The proposed algorithm for controller optimizes the objective function which is composed of current harmonic distortion, power factor, and DC voltage ripples. The detailed designs and modeling of the complete system are discussed and its simulation is carried out in MATLAB-Simulink environment. The obtained results are presented to demonstrate the effectiveness of the proposed scheme under different transient conditions such as load perturbation, non-linear load condition, voltage sag condition, and tapped load fault under one phase open condition at both points-of-common coupling.

Optimal management of a stochastically varying population when policy adjustment is costly.

PubMed

Boettiger, Carl; Bode, Michael; Sanchirico, James N; Lariviere, Jacob; Hastings, Alan; Armsworth, Paul R

2016-04-01

Ecological systems are dynamic and policies to manage them need to respond to that variation. However, policy adjustments will sometimes be costly, which means that fine-tuning a policy to track variability in the environment very tightly will only sometimes be worthwhile. We use a classic fisheries management problem, how to manage a stochastically varying population using annually varying quotas in order to maximize profit, to examine how costs of policy adjustment change optimal management recommendations. Costs of policy adjustment (changes in fishing quotas through time) could take different forms. For example, these costs may respond to the size of the change being implemented, or there could be a fixed cost any time a quota change is made. We show how different forms of policy costs have contrasting implications for optimal policies. Though it is frequently assumed that costs to adjusting policies will dampen variation in the policy, we show that certain cost structures can actually increase variation through time. We further show that failing to account for adjustment costs has a consistently worse economic impact than would assuming these costs are present when they are not.

Weight optimization of large span steel truss structures with genetic algorithm

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

Mojolic, Cristian; Hulea, Radu; Pârv, Bianca Roxana

2015-03-10

The paper presents the weight optimization process of the main steel truss that supports the Slatina Sport Hall roof. The structure was loaded with self-weight, dead loads, live loads, snow, wind and temperature, grouped in eleven load cases. The optimization of the structure was made using genetic algorithms implemented in a Matlab code. A total number of four different cases were taken into consideration when trying to determine the lowest weight of the structure, depending on the types of connections with the concrete structure ( types of supports, bearing modes), and the possibility of the lower truss chord nodes tomore » change their vertical position. A number of restrictions for tension, maximum displacement and buckling were enforced on the elements, and the cross sections are chosen by the program from a user data base. The results in each of the four cases were analyzed in terms of weight, element tension, element section and displacement. The paper presents the optimization process and the conclusions drawn.« less

Solar plus: Optimization of distributed solar PV through battery storage and dispatchable load in residential buildings

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

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

As utility electricity rates evolve, pairing solar photovoltaic (PV) systems with battery storage has potential to ensure the value proposition of residential solar by mitigating economic uncertainty. In addition to batteries, load control technologies can reshape customer load profiles to optimize PV system use. The combination of PV, energy storage, and load control provides an integrated approach to PV deployment, which we call 'solar plus'. The U.S. National Renewable Energy Laboratory's Renewable Energy Optimization (REopt) model is utilized to evaluate cost-optimal technology selection, sizing, and dispatch in residential buildings under a variety of rate structures and locations. The REopt modelmore » is extended to include a controllable or 'smart' domestic hot water heater model and smart air conditioner model. We find that the solar plus approach improves end user economics across a variety of rate structures - especially those that are challenging for PV - including lower grid export rates, non-coincident time-of-use structures, and demand charges.« less

Solar plus: Optimization of distributed solar PV through battery storage and dispatchable load in residential buildings

DOE PAGES

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

2018-01-11

As utility electricity rates evolve, pairing solar photovoltaic (PV) systems with battery storage has potential to ensure the value proposition of residential solar by mitigating economic uncertainty. In addition to batteries, load control technologies can reshape customer load profiles to optimize PV system use. The combination of PV, energy storage, and load control provides an integrated approach to PV deployment, which we call 'solar plus'. The U.S. National Renewable Energy Laboratory's Renewable Energy Optimization (REopt) model is utilized to evaluate cost-optimal technology selection, sizing, and dispatch in residential buildings under a variety of rate structures and locations. The REopt modelmore » is extended to include a controllable or 'smart' domestic hot water heater model and smart air conditioner model. We find that the solar plus approach improves end user economics across a variety of rate structures - especially those that are challenging for PV - including lower grid export rates, non-coincident time-of-use structures, and demand charges.« less

PSO-Based Smart Grid Application for Sizing and Optimization of Hybrid Renewable Energy Systems

PubMed Central

Mohamed, Mohamed A.; Eltamaly, Ali M.; Alolah, Abdulrahman I.

2016-01-01

This paper introduces an optimal sizing algorithm for a hybrid renewable energy system using smart grid load management application based on the available generation. This algorithm aims to maximize the system energy production and meet the load demand with minimum cost and highest reliability. This system is formed by photovoltaic array, wind turbines, storage batteries, and diesel generator as a backup source of energy. Demand profile shaping as one of the smart grid applications is introduced in this paper using load shifting-based load priority. Particle swarm optimization is used in this algorithm to determine the optimum size of the system components. The results obtained from this algorithm are compared with those from the iterative optimization technique to assess the adequacy of the proposed algorithm. The study in this paper is performed in some of the remote areas in Saudi Arabia and can be expanded to any similar regions around the world. Numerous valuable results are extracted from this study that could help researchers and decision makers. PMID:27513000

PSO-Based Smart Grid Application for Sizing and Optimization of Hybrid Renewable Energy Systems.

PubMed

Mohamed, Mohamed A; Eltamaly, Ali M; Alolah, Abdulrahman I

2016-01-01

This paper introduces an optimal sizing algorithm for a hybrid renewable energy system using smart grid load management application based on the available generation. This algorithm aims to maximize the system energy production and meet the load demand with minimum cost and highest reliability. This system is formed by photovoltaic array, wind turbines, storage batteries, and diesel generator as a backup source of energy. Demand profile shaping as one of the smart grid applications is introduced in this paper using load shifting-based load priority. Particle swarm optimization is used in this algorithm to determine the optimum size of the system components. The results obtained from this algorithm are compared with those from the iterative optimization technique to assess the adequacy of the proposed algorithm. The study in this paper is performed in some of the remote areas in Saudi Arabia and can be expanded to any similar regions around the world. Numerous valuable results are extracted from this study that could help researchers and decision makers.

Data centers as dispatchable loads to harness stranded power

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

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

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

Data centers as dispatchable loads to harness stranded power

DOE PAGES

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

2016-07-20

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

Docetaxel-loaded thermosensitive liquid suppository: optimization of rheological properties.

PubMed

Yeo, Woo Hyun; Ramasamy, Thiruganesh; Kim, Dong-Wuk; Cho, Hyuk Jun; Kim, Yong-Il; Cho, Kwan Hyung; Yong, Chul Soon; Kim, Jong Oh; Choi, Han-Gon

2013-12-01

The main purpose of this work was to optimize the rheological properties of docetaxel (DCT)-loaded thermosensitive liquid suppositories for rectal administration. DCT-loaded liquid suppositories were prepared by a cold method and characterized in terms of physicochemical and viscoelastic properties. Major formulation parameters including poloxamer (P407) and Tween 80 were optimized to adjust the thermogelling and mucoadhesive properties for rectal administration. Notably, the gel strength and mucoadhesive force significantly increased with the increase in these variables. Furthermore, DCT incorporation did not alter the viscoelastic behavior, and the mean particle size of nanomicelles in it was approximately 16 nm with a distinct spherical shape. The formulation existed as liquid at room temperature and transformed into gel at physiological temperature through the reverse gelation phenomenon. Thus, DCT-loaded thermosensitive liquid suppositories [DCT/P407/P188/Tween 80 (0.25/11/15/10 %)] with optimal gel properties were easy to prepare and administer rectally, and might enable the gel to stay in the rectum without getting out from rectum.

Optimization of the RF cavity heat load and trip rates for CEBAF at 12 GeV

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

Zhang, He; Roblin, Yves R.; Freyberger, Arne P.

2017-05-01

The Continuous Electron Beam Accelerator Facility at JLab has 200 RF cavities in the north linac and the south linac respectively after the 12 GeV upgrade. The purpose of this work is to simultaneously optimize the heat load and the trip rate for the cavities and to reconstruct the pareto-optimal front in a timely manner when some of the cavities are turned down. By choosing an efficient optimizer and strategically creating the initial gradients, the pareto-optimal front for no more than 15 cavities down can be re-established within 20 seconds.

Load research manual. Volume 3. Load research for advanced technologies

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

Brandenburg, L.; Clarkson, G.; Grund, Jr., C.

1980-11-01

This three-volume manual presents technical guidelines for electric utility load research. Special attention is given to issues raised by the load data reporting requirements of the Public Utility Regulatory Policies Act of 1978 and to problems faced by smaller utilities that are initiating load research programs. The manual includes guides to load research literature and glossaries of load research and statistical terms. In Volume 3, special load research procedures are presented for solar, wind, and cogeneration technologies.

Operational load estimation of a smart wind turbine rotor blade

NASA Astrophysics Data System (ADS)

White, Jonathan R.; Adams, Douglas E.; Rumsey, Mark A.

2009-03-01

Rising energy prices and carbon emission standards are driving a fundamental shift from fossil fuels to alternative sources of energy such as biofuel, solar, wind, clean coal and nuclear. In 2008, the U.S. installed 8,358 MW of new wind capacity increasing the total installed wind power by 50% to 25,170 MW. A key technology to improve the efficiency of wind turbines is smart rotor blades that can monitor the physical loads being applied by the wind and then adapt the airfoil for increased energy capture. For extreme wind and gust events, the airfoil could be changed to reduce the loads to prevent excessive fatigue or catastrophic failure. Knowledge of the actual loading to the turbine is also useful for maintenance planning and design improvements. In this work, an array of uniaxial and triaxial accelerometers was integrally manufactured into a 9m smart rotor blade. DC type accelerometers were utilized in order to estimate the loading and deflection from both quasi-steady-state and dynamic events. A method is presented that designs an estimator of the rotor blade static deflection and loading and then optimizes the placement of the sensor(s). Example results show that the method can identify the optimal location for the sensor for both simple example cases and realistic complex loading. The optimal location of a single sensor shifts towards the tip as the curvature of the blade deflection increases with increasingly complex wind loading. The framework developed is practical for the expansion of sensor optimization in more complex blade models and for higher numbers of sensors.

Characterization and Performance Optimization of a Cementitious Composite for Quasi-Static and Dynamic Loads

DTIC Science & Technology

2011-01-01

blast and weapon fragmentation. A particular cementitious composite of interest is an inorganic polymer cement or “ geopolymer ” cement. The term...www.sciencedirect.com ICM11 Characterization and performance optimization of a cementitious composite for quasi-static and dynamic loads W.F. Hearda,b, P.K. Basub...rapid-set, high-strength geopolymer cement under quasi-static and dynamic loads. Four unique tensile experiments were conducted to characterize and

FLORIS 2017

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

2017-08-04

This code is an enhancement to the existing FLORIS code, SWR 14-20. In particular, this enhancement computes overall thrust and turbulence intensity throughout a wind plant. This information is used to form a description of the fatigue loads experienced throughtout the wind plant. FLORIS has been updated to include an optimization routine that optimizes FLORIS to minimize thrust and turbulence intensity (and therefore loads) across the wind plant. Previously, FLORIS had been designed to optimize power out of a wind plant. However, as turbines age, more wind plant owner/operators are looking for ways to reduce their fatigue loads without sacrificingmore » too much power.« less

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.

Integrated systems optimization model for biofuel development: The influence of environmental constraints

NASA Astrophysics Data System (ADS)

Housh, M.; Ng, T.; Cai, X.

2012-12-01

The environmental impact is one of the major concerns of biofuel development. While many other studies have examined the impact of biofuel expansion on stream flow and water quality, this study examines the problem from the other side - will and how a biofuel production target be affected by given environmental constraints. For this purpose, an integrated model comprises of different sub-systems of biofuel refineries, transportation, agriculture, water resources and crops/ethanol market has been developed. The sub-systems are integrated into one large-scale model to guide the optimal development plan considering the interdependency between the subsystems. The optimal development plan includes biofuel refineries location and capacity, refinery operation, land allocation between biofuel and food crops, and the corresponding stream flow and nitrate load in the watershed. The watershed is modeled as a network flow, in which the nodes represent sub-watersheds and the arcs are defined as the linkage between the sub-watersheds. The runoff contribution of each sub-watershed is determined based on the land cover and the water uses in that sub-watershed. Thus, decisions of other sub-systems such as the land allocation in the land use sub-system and the water use in the refinery sub-system define the sources and the sinks of the network. Environmental policies will be addressed in the integrated model by imposing stream flow and nitrate load constraints. These constraints can be specified by location and time in the watershed to reflect the spatial and temporal variation of the regulations. Preliminary results show that imposing monthly water flow constraints and yearly nitrate load constraints will change the biofuel development plan dramatically. Sensitivity analysis is performed to examine how the environmental constraints and their spatial and the temporal distribution influence the overall biofuel development plan and the performance of each of the sub-systems. Additional scenarios are analyzed to show the synergies of crop pattern choice (first versus second generation of biofuel crops), refinery technology adaptation (particularly on water use), refinery plant distribution, and economic incentives in terms of balanced environmental protection and bioenergy development objectives.

Polyurethane foam loaded with SDS for the adsorption of cationic dyes from aqueous medium: Multivariate optimization of the loading process.

PubMed

Robaina, Nicolle F; Soriano, Silvio; Cassella, Ricardo J

2009-08-15

This paper reports the development of a new procedure for the adsorption of four cationic dyes (Rhodamine B, Methylene Blue, Crystal Violet and Malachite Green) from aqueous medium employing polyurethane foam (PUF) loaded with sodium dodecylsulfate (SDS) as solid phase. PUF loading process was based on the stirring of 200mg PUF cylinders with acidic solutions containing SDS. The conditions for loading were optimized by response surface methodology (RSM) using a Doehlert design with three variables that were SDS and HCl concentrations and stirring time. Results obtained in the optimization process showed that the stirring time is not a relevant parameter in the PUF loading, evidencing that the transport of SDS from solution to PUF surface is fast. On the other hand, both SDS and HCl concentrations were important parameters causing significant variation in the efficiency of the resulting solid phase for the removal of dyes from solution. At optimized conditions, SDS and HCl concentrations were 4.0 x 10(-4) and 0.90 mol L(-1), respectively. The influence of stirring time was evaluated by univariate methodology. A 20 min stirring time was established in order to make the PUF loading process fast and robust without losing efficiency. The procedure was tested for the removal of the four cationic dyes from aqueous solutions and removal efficiencies always better than 90% were achieved for the two concentrations tested (2.0 x 10(-5) and 1.0 x 10(-4)mol L(-1)).

Policy-Relevant Nonconvexities in the Production of Multiple Forest Benefits?

Treesearch

Stephen K. Swallow; Peter J. Parks; David N. Wear

1990-01-01

This paper challenges common assumptions about convexity in forest rotation models which optimize timber plus nontimber benefits. If a local optimum occurs earlier than the globally optimal age, policy based on marginal incentives may achieve suboptimal results. Policy-relevant nonconvexities are more likely if (i) nontimber benefits dominate for young stands while...

Can market-based policies accomplish the optimal floodplain management? A gap between static and dynamic models.

PubMed

Mori, Koichiro

2009-02-01

The purpose of this short article is to set static and dynamic models for optimal floodplain management and to compare policy implications from the models. River floodplains are important multiple resources in that they provide various ecosystem services. It is fundamentally significant to consider environmental externalities that accrue from ecosystem services of natural floodplains. There is an interesting gap between static and dynamic models about policy implications for floodplain management, although they are based on the same assumptions. Essentially, we can derive the same optimal conditions, which imply that the marginal benefits must equal the sum of the marginal costs and the social external costs related to ecosystem services. Thus, we have to internalise the external costs by market-based policies. In this respect, market-based policies seem to be effective in a static model. However, they are not sufficient in the context of a dynamic model because the optimal steady state turns out to be unstable. Based on a dynamic model, we need more coercive regulation policies.

Advanced optimal design concepts for composite material aircraft repair

NASA Astrophysics Data System (ADS)

Renaud, Guillaume

The application of an automated optimization approach for bonded composite patch design is investigated. To do so, a finite element computer analysis tool to evaluate patch design quality was developed. This tool examines both the mechanical and the thermal issues of the problem. The optimized shape is obtained with a bi-quadratic B-spline surface that represents the top surface of the patch. Additional design variables corresponding to the ply angles are also used. Furthermore, a multi-objective optimization approach was developed to treat multiple and uncertain loads. This formulation aims at designing according to the most unfavorable mechanical and thermal loads. The problem of finding the optimal patch shape for several situations is addressed. The objective is to minimize a stress component at a specific point in the host structure (plate) while ensuring acceptable stress levels in the adhesive. A parametric study is performed in order to identify the effects of various shape parameters on the quality of the repair and its optimal configuration. The effects of mechanical loads and service temperature are also investigated. Two bonding methods are considered, as they imply different thermal histories. It is shown that the proposed techniques are effective and inexpensive for analyzing and optimizing composite patch repairs. It is also shown that thermal effects should not only be present in the analysis, but that they play a paramount role on the resulting quality of the optimized design. In all cases, the optimized configuration results in a significant reduction of the desired stress level by deflecting the loads away from rather than over the damage zone, as is the case with standard designs. Furthermore, the automated optimization ensures the safety of the patch design for all considered operating conditions.

Reduced Design Load Basis for Ultimate Blade Loads Estimation in Multidisciplinary Design Optimization Frameworks

NASA Astrophysics Data System (ADS)

Pavese, Christian; Tibaldi, Carlo; Larsen, Torben J.; Kim, Taeseong; Thomsen, Kenneth

2016-09-01

The aim is to provide a fast and reliable approach to estimate ultimate blade loads for a multidisciplinary design optimization (MDO) framework. For blade design purposes, the standards require a large amount of computationally expensive simulations, which cannot be efficiently run each cost function evaluation of an MDO process. This work describes a method that allows integrating the calculation of the blade load envelopes inside an MDO loop. Ultimate blade load envelopes are calculated for a baseline design and a design obtained after an iteration of an MDO. These envelopes are computed for a full standard design load basis (DLB) and a deterministic reduced DLB. Ultimate loads extracted from the two DLBs with the two blade designs each are compared and analyzed. Although the reduced DLB supplies ultimate loads of different magnitude, the shape of the estimated envelopes are similar to the one computed using the full DLB. This observation is used to propose a scheme that is computationally cheap, and that can be integrated inside an MDO framework, providing a sufficiently reliable estimation of the blade ultimate loading. The latter aspect is of key importance when design variables implementing passive control methodologies are included in the formulation of the optimization problem. An MDO of a 10 MW wind turbine blade is presented as an applied case study to show the efficacy of the reduced DLB concept.

Optimal Topology of Aircraft Rib and Spar Structures under Aeroelastic Loads

NASA Technical Reports Server (NTRS)

Stanford, Bret K.; Dunning, Peter D.

2014-01-01

Several topology optimization problems are conducted within the ribs and spars of a wing box. It is desired to locate the best position of lightening holes, truss/cross-bracing, etc. A variety of aeroelastic metrics are isolated for each of these problems: elastic wing compliance under trim loads and taxi loads, stress distribution, and crushing loads. Aileron effectiveness under a constant roll rate is considered, as are dynamic metrics: natural vibration frequency and flutter. This approach helps uncover the relationship between topology and aeroelasticity in subsonic transport wings, and can therefore aid in understanding the complex aircraft design process which must eventually consider all these metrics and load cases simultaneously.

Optimal design of high-speed loading spindle based on ABAQUS

NASA Astrophysics Data System (ADS)

Yang, Xudong; Dong, Yu; Ge, Qingkuan; Yang, Hai

2017-12-01

The three-dimensional model of high-speed loading spindle is established by using ABAQUS’s modeling module. A finite element analysis model of high-speed loading spindle was established by using spring element to simulate bearing boundary condition. The static and dynamic performance of the spindle structure with different specifications of the rectangular spline and the different diameter neck of axle are studied in depth, and the influence of different spindle span on the static and dynamic performance of the high-speed loading spindle is studied. Finally, the optimal structure of the high-speed loading spindle is obtained. The results provide a theoretical basis for improving the overall performance of the test-bed

Optimization of self-acting step thrust bearings for load capacity and stiffness.

NASA Technical Reports Server (NTRS)

Hamrock, B. J.

1972-01-01

Linearized analysis of a finite-width rectangular step thrust bearing. Dimensionless load capacity and stiffness are expressed in terms of a Fourier cosine series. The dimensionless load capacity and stiffness were found to be a function of the dimensionless bearing number, the pad length-to-width ratio, the film thickness ratio, the step location parameter, and the feed groove parameter. The equations obtained in the analysis were verified. The assumptions imposed were substantiated by comparing the results with an existing exact solution for the infinite width bearing. A digital computer program was developed which determines optimal bearing configuration for maximum load capacity or stiffness. Simple design curves are presented. Results are shown for both compressible and incompressible lubrication. Through a parameter transformation the results are directly usable in designing optimal step sector thrust bearings.

Co-optimization of Energy and Demand-Side Reserves in Day-Ahead Electricity Markets

NASA Astrophysics Data System (ADS)

Surender Reddy, S.; Abhyankar, A. R.; Bijwe, P. R.

2015-04-01

This paper presents a new multi-objective day-ahead market clearing (DAMC) mechanism with demand-side reserves/demand response (DR) offers, considering realistic voltage-dependent load modeling. The paper proposes objectives such as social welfare maximization (SWM) including demand-side reserves, and load served error (LSE) minimization. In this paper, energy and demand-side reserves are cleared simultaneously through co-optimization process. The paper clearly brings out the unsuitability of conventional SWM for DAMC in the presence of voltage-dependent loads, due to reduction of load served (LS). Under such circumstances multi-objective DAMC with DR offers is essential. Multi-objective Strength Pareto Evolutionary Algorithm 2+ (SPEA 2+) has been used to solve the optimization problem. The effectiveness of the proposed scheme is confirmed with results obtained from IEEE 30 bus system.

Energy Management Policies in Distributed Residential Energy Systems

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

Duan, Sisi; Sun, Jingtao

2016-01-01

In this paper, we study energy management problems in communities with several neighborhood-level Residential Energy Systems (RESs). We consider control problems from both community level and residential level to handle external changes such as restriction on peak demand and restriction on the total demand from the electricity grid. We propose three policies to handle the problems at community level. Based on the collected data from RESs such as predicted energy load, the community controller analyzes the policies, distribute the results to the RES, and each RES can then control and schedule its own energy load based on different coordination functions.more » We utilize a framework to integrate both policy analysis and coordination of functions. With the use of our approach, we show that the policies are useful to resolve the challenges of energy management under external changes.« less

Current and efficiency optimization under oscillating forces in entropic barriers

NASA Astrophysics Data System (ADS)

Nutku, Ferhat; Aydıner, Ekrem

2016-09-01

The transport of externally overdriven particles confined in entropic barriers is investigated under various types of oscillating and temporal forces. Temperature, load, and amplitude dependence of the particle current and energy conversion efficiency are investigated in three dimensions. For oscillating forces, the optimized temperature-load, amplitude-temperature, and amplitude-load intervals are determined when fixing the amplitude, load, and temperature, respectively. By using three-dimensional plots rather than two-dimensional ones, it is clearly shown that oscillating forces provide more efficiency compared with a temporal one in specified optimized parameter regions. Furthermore, the dependency of efficiency to the angle between the unbiased driving force and a constant force is investigated and an asymmetric angular dependence is found for all types of forces. Finally, it is shown that oscillating forces with a high amplitude and under a moderate load lead to higher efficiencies than a temporal force at both low and high temperatures for the entire range of contact angle. Project supported by the Istanbul University, Turkey (Grant No. 55383).

Optimal Control Allocation with Load Sensor Feedback for Active Load Suppression, Experiment Development

NASA Technical Reports Server (NTRS)

Miller, Christopher J.; Goodrick, Dan

2017-01-01

The problem of control command and maneuver induced structural loads is an important aspect of any control system design. The aircraft structure and the control architecture must be designed to achieve desired piloted control responses while limiting the imparted structural loads. The classical approach is to utilize high structural margins, restrict control surface commands to a limited set of analyzed combinations, and train pilots to follow procedural maneuvering limitations. With recent advances in structural sensing and the continued desire to improve safety and vehicle fuel efficiency, it is both possible and desirable to develop control architectures that enable lighter vehicle weights while maintaining and improving protection against structural damage. An optimal control technique has been explored and shown to achieve desirable vehicle control performance while limiting sensed structural loads. The subject of this paper is the design of the optimal control architecture, and provides the reader with some techniques for tailoring the architecture, along with detailed simulation results.

Policy Tree Optimization for Adaptive Management of Water Resources Systems

NASA Astrophysics Data System (ADS)

Herman, J. D.; Giuliani, M.

2016-12-01

Water resources systems must cope with irreducible uncertainty in supply and demand, requiring policy alternatives capable of adapting to a range of possible future scenarios. Recent studies have developed adaptive policies based on "signposts" or "tipping points", which are threshold values of indicator variables that signal a change in policy. However, there remains a need for a general method to optimize the choice of indicators and their threshold values in a way that is easily interpretable for decision makers. Here we propose a conceptual framework and computational algorithm to design adaptive policies as a tree structure (i.e., a hierarchical set of logical rules) using a simulation-optimization approach based on genetic programming. We demonstrate the approach using Folsom Reservoir, California as a case study, in which operating policies must balance the risk of both floods and droughts. Given a set of feature variables, such as reservoir level, inflow observations and forecasts, and time of year, the resulting policy defines the conditions under which flood control and water supply hedging operations should be triggered. Importantly, the tree-based rule sets are easy to interpret for decision making, and can be compared to historical operating policies to understand the adaptations needed under possible climate change scenarios. Several remaining challenges are discussed, including the empirical convergence properties of the method, and extensions to irreversible decisions such as infrastructure. Policy tree optimization, and corresponding open-source software, provide a generalizable, interpretable approach to designing adaptive policies under uncertainty for water resources systems.

Optimizing preventive maintenance policy: A data-driven application for a light rail braking system.

PubMed

Corman, Francesco; Kraijema, Sander; Godjevac, Milinko; Lodewijks, Gabriel

2017-10-01

This article presents a case study determining the optimal preventive maintenance policy for a light rail rolling stock system in terms of reliability, availability, and maintenance costs. The maintenance policy defines one of the three predefined preventive maintenance actions at fixed time-based intervals for each of the subsystems of the braking system. Based on work, maintenance, and failure data, we model the reliability degradation of the system and its subsystems under the current maintenance policy by a Weibull distribution. We then analytically determine the relation between reliability, availability, and maintenance costs. We validate the model against recorded reliability and availability and get further insights by a dedicated sensitivity analysis. The model is then used in a sequential optimization framework determining preventive maintenance intervals to improve on the key performance indicators. We show the potential of data-driven modelling to determine optimal maintenance policy: same system availability and reliability can be achieved with 30% maintenance cost reduction, by prolonging the intervals and re-grouping maintenance actions.

Optimizing preventive maintenance policy: A data-driven application for a light rail braking system

PubMed Central

Corman, Francesco; Kraijema, Sander; Godjevac, Milinko; Lodewijks, Gabriel

2017-01-01

This article presents a case study determining the optimal preventive maintenance policy for a light rail rolling stock system in terms of reliability, availability, and maintenance costs. The maintenance policy defines one of the three predefined preventive maintenance actions at fixed time-based intervals for each of the subsystems of the braking system. Based on work, maintenance, and failure data, we model the reliability degradation of the system and its subsystems under the current maintenance policy by a Weibull distribution. We then analytically determine the relation between reliability, availability, and maintenance costs. We validate the model against recorded reliability and availability and get further insights by a dedicated sensitivity analysis. The model is then used in a sequential optimization framework determining preventive maintenance intervals to improve on the key performance indicators. We show the potential of data-driven modelling to determine optimal maintenance policy: same system availability and reliability can be achieved with 30% maintenance cost reduction, by prolonging the intervals and re-grouping maintenance actions. PMID:29278245

Optimal pricing and replenishment policies for instantaneous deteriorating items with backlogging and trade credit under inflation

NASA Astrophysics Data System (ADS)

Sundara Rajan, R.; Uthayakumar, R.

2017-12-01

In this paper we develop an economic order quantity model to investigate the optimal replenishment policies for instantaneous deteriorating items under inflation and trade credit. Demand rate is a linear function of selling price and decreases negative exponentially with time over a finite planning horizon. Shortages are allowed and partially backlogged. Under these conditions, we model the retailer's inventory system as a profit maximization problem to determine the optimal selling price, optimal order quantity and optimal replenishment time. An easy-to-use algorithm is developed to determine the optimal replenishment policies for the retailer. We also provide optimal present value of profit when shortages are completely backlogged as a special case. Numerical examples are presented to illustrate the algorithm provided to obtain optimal profit. And we also obtain managerial implications from numerical examples to substantiate our model. The results show that there is an improvement in total profit from complete backlogging rather than the items being partially backlogged.

The Delicate Analysis of Short-Term Load Forecasting

NASA Astrophysics Data System (ADS)

Song, Changwei; Zheng, Yuan

2017-05-01

This paper proposes a new method for short-term load forecasting based on the similar day method, correlation coefficient and Fast Fourier Transform (FFT) to achieve the precision analysis of load variation from three aspects (typical day, correlation coefficient, spectral analysis) and three dimensions (time dimension, industry dimensions, the main factors influencing the load characteristic such as national policies, regional economic, holidays, electricity and so on). First, the branch algorithm one-class-SVM is adopted to selection the typical day. Second, correlation coefficient method is used to obtain the direction and strength of the linear relationship between two random variables, which can reflect the influence caused by the customer macro policy and the scale of production to the electricity price. Third, Fourier transform residual error correction model is proposed to reflect the nature of load extracting from the residual error. Finally, simulation result indicates the validity and engineering practicability of the proposed method.

Simulation optimization of PSA-threshold based prostate cancer screening policies

PubMed Central

Zhang, Jingyu; Denton, Brian T.; Shah, Nilay D.; Inman, Brant A.

2013-01-01

We describe a simulation optimization method to design PSA screening policies based on expected quality adjusted life years (QALYs). Our method integrates a simulation model in a genetic algorithm which uses a probabilistic method for selection of the best policy. We present computational results about the efficiency of our algorithm. The best policy generated by our algorithm is compared to previously recommended screening policies. Using the policies determined by our model, we present evidence that patients should be screened more aggressively but for a shorter length of time than previously published guidelines recommend. PMID:22302420

Tailoring the Employment of Offshore Wind Turbine Support Structure Load Mitigation Controllers

NASA Astrophysics Data System (ADS)

Shrestha, Binita; Kühn, Martin

2016-09-01

The currently available control concepts to mitigate aerodynamic and hydrodynamic induced support structure loads reduce either fore-aft or side-to-side damage under certain operational conditions. The load reduction is achieved together with an increase in loads in other components of the turbine e.g. pitch actuators or drive train, increasing the risk of unscheduled maintenance. The main objective of this paper is to demonstrate a methodology for reduction of support structure damage equivalent loads (DEL) in fore-aft and side-to-side directions using already available control concepts. A multi-objective optimization problem is formulated to minimize the DELs, while limiting the collateral effects of the control algorithms for load reduction. The optimization gives trigger values of sea state condition for the activation or deactivation of certain control concepts. As a result, by accepting the consumption of a small fraction of the load reserve in the design load envelope of other turbine components, a considerable reduction of the support structure loads is facilitated.

Incorporating operational flexibility into electric generation planning Impacts and methods for system design and policy analysis

NASA Astrophysics Data System (ADS)

Palmintier, Bryan S.

This dissertation demonstrates how flexibility in hourly electricity operations can impact long-term planning and analysis for future power systems, particularly those with substantial variable renewables (e.g., wind) or strict carbon policies. Operational flexibility describes a power system's ability to respond to predictable and unexpected changes in generation or demand. Planning and policy models have traditionally not directly captured the technical operating constraints that determine operational flexibility. However, as demonstrated in this dissertation, this capability becomes increasingly important with the greater flexibility required by significant renewables (>= 20%) and the decreased flexibility inherent in some low-carbon generation technologies. Incorporating flexibility can significantly change optimal generation and energy mixes, lower system costs, improve policy impact estimates, and enable system designs capable of meeting strict regulatory targets. Methodologically, this work presents a new clustered formulation that tractably combines a range of normally distinct power system models, from hourly unit-commitment operations to long-term generation planning. This formulation groups similar generators into clusters to reduce problem size, while still retaining the individual unit constraints required to accurately capture operating reserves and other flexibility drivers. In comparisons against traditional unit commitment formulations, errors were generally less than 1% while run times decreased by several orders of magnitude (e.g., 5000x). Extensive numerical simulations, using a realistic Texas-based power system show that ignoring flexibility can underestimate carbon emissions by 50% or result in significant load and wind shedding to meet environmental regulations. Contributions of this dissertation include: 1. Demonstrating that operational flexibility can have an important impact on power system planning, and describing when and how these impacts occur; 2. Demonstrating that a failure to account for operational flexibility can result in undesirable outcomes for both utility planners and policy analysts; and 3. Extending the state of the art for electric power system models by introducing a tractable method for incorporating unit commitment based operational flexibility at full 876o hourly resolution directly into planning optimization. Together these results encourage and offer a new flexibility-aware approach for capacity planning and accompanying policy design that can enable cleaner, less expensive electric power systems for the future. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs mit.edu)

Rail Mounted Gantry Crane Scheduling Optimization in Railway Container Terminal Based on Hybrid Handling Mode

PubMed Central

Zhu, Xiaoning

2014-01-01

Rail mounted gantry crane (RMGC) scheduling is important in reducing makespan of handling operation and improving container handling efficiency. In this paper, we present an RMGC scheduling optimization model, whose objective is to determine an optimization handling sequence in order to minimize RMGC idle load time in handling tasks. An ant colony optimization is proposed to obtain near optimal solutions. Computational experiments on a specific railway container terminal are conducted to illustrate the proposed model and solution algorithm. The results show that the proposed method is effective in reducing the idle load time of RMGC. PMID:25538768

Cloud computing task scheduling strategy based on differential evolution and ant colony optimization

NASA Astrophysics Data System (ADS)

Ge, Junwei; Cai, Yu; Fang, Yiqiu

2018-05-01

This paper proposes a task scheduling strategy DEACO based on the combination of Differential Evolution (DE) and Ant Colony Optimization (ACO), aiming at the single problem of optimization objective in cloud computing task scheduling, this paper combines the shortest task completion time, cost and load balancing. DEACO uses the solution of the DE to initialize the initial pheromone of ACO, reduces the time of collecting the pheromone in ACO in the early, and improves the pheromone updating rule through the load factor. The proposed algorithm is simulated on cloudsim, and compared with the min-min and ACO. The experimental results show that DEACO is more superior in terms of time, cost, and load.

Analytic model for ultrasound energy receivers and their optimal electric loads

NASA Astrophysics Data System (ADS)

Gorostiaga, M.; Wapler, M. C.; Wallrabe, U.

2017-08-01

In this paper, we present an analytic model for thickness resonating plate ultrasound energy receivers, which we have derived from the piezoelectric and the wave equations and, in which we have included dielectric, viscosity and acoustic attenuation losses. Afterwards, we explore the optimal electric load predictions by the zero reflection and power maximization approaches present in the literature with different acoustic boundary conditions, and discuss their limitations. To validate our model, we compared our expressions with the KLM model solved numerically with very good agreement. Finally, we discuss the differences between the zero reflection and power maximization optimal electric loads, which start to differ as losses in the receiver increase.

High drug loading self-microemulsifying/micelle formulation: design by high-throughput formulation screening system and in vivo evaluation.

PubMed

Sakai, Kenichi; Obata, Kouki; Yoshikawa, Mayumi; Takano, Ryusuke; Shibata, Masaki; Maeda, Hiroyuki; Mizutani, Akihiko; Terada, Katsuhide

2012-10-01

To design a high drug loading formulation of self-microemulsifying/micelle system. A poorly-soluble model drug (CH5137291), 8 hydrophilic surfactants (HS), 10 lipophilic surfactants (LS), 5 oils, and PEG400 were used. A high loading formulation was designed by a following stepwise approach using a high-throughput formulation screening (HTFS) system: (1) an oil/solvent was selected by solubility of the drug; (2) a suitable HS for highly loading was selected by the screenings of emulsion/micelle size and phase stability in binary systems (HS, oil/solvent) with increasing loading levels; (3) a LS that formed a broad SMEDDS/micelle area on a phase diagram containing the HS and oil/solvent was selected by the same screenings; (4) an optimized formulation was selected by evaluating the loading capacity of the crystalline drug. Aqueous solubility behavior and oral absorption (Beagle dog) of the optimized formulation were compared with conventional formulations (jet-milled, PEG400). As an optimized formulation, d-α-tocopheryl polyoxyethylene 1000 succinic ester: PEG400 = 8:2 was selected, and achieved the target loading level (200 mg/mL). The formulation formed fine emulsion/micelle (49.1 nm), and generated and maintained a supersaturated state at a higher level compared with the conventional formulations. In the oral absorption test, the area under the plasma concentration-time curve of the optimized formulation was 16.5-fold higher than that of the jet-milled formulation. The high loading formulation designed by the stepwise approach using the HTFS system improved the oral absorption of the poorly-soluble model drug.

[Optimization of trehalose loading in red blood cells before freeze-drying].

PubMed

Zhuang, Yuan; Liu, Jing-Han; Ouyang, Xi-Lin; Chen, Lin-Feng; Che, Ji

2007-04-01

The key points for better protection of trehalose in freeze-drying red blood cells (RBCs) are to resolve non-osmosis of trehalose to red blood cells and to make cytoplasmic trehalose to reach effective concentration. This study was aimed to investigate the regularity of loading RBCs with trehalose, screen out optimal loading condition and evaluate the effect of trehalose on physico-chemical parameters of RBCs during the period of loading. The cytoplasmic trehalose concentration in red blood cells, free hemoglobin and ATP level were determined at different incubation temperatures (4, 22 and 37 degrees C), different trehaolse concentrations (0, 200, 400, 600, 800 and 1000 mmol/L) and different incubation times (2, 4, 6, 8 and 10 hours), the cytoplasmic trehalose, free hemoglobin (FHb), hemoglobin (Hb) and mean corpuscular volume (MCV) in fresh RBCs and RBCs stored for 72 hours at 4 degrees C were compared, when loading condition was ensured. The results showed that with increase of incubation temperature, time and extracellular trehalose concentration, the loading of trehalose in RBCs also increased. Under the optimal loading condition, cytoplasmic trehalose concentration and free hemoglobin level of fresh RBCs and RBCs stored for 72 hours at 4 degrees C were 65.505 +/- 6.314 mmol/L, 66.2 +/- 5.002 mmol/L and 6.567 +/- 2.568 g/L, 16.168 +/- 3.922 g/L respectively. It is concluded that the most optimal condition of loading trehalose is that fresh RBCs incubate in 800 mmol/L trehalose solution for 8 hours at 37 degrees C. This condition can result in a efficient cytoplasmic trehalose concentration. The study provides an important basis for long-term preservation of RBCs.

Optimal acetabular component orientation estimated using edge-loading and impingement risk in patients with metal-on-metal hip resurfacing arthroplasty.

PubMed

Mellon, Stephen J; Grammatopoulos, George; Andersen, Michael S; Pandit, Hemant G; Gill, Harinderjit S; Murray, David W

2015-01-21

Edge-loading in patients with metal-on-metal resurfaced hips can cause high serum metal ion levels, the development of soft-tissue reactions local to the joint called pseudotumours and ultimately, failure of the implant. Primary edge-loading is where contact between the femoral and acetabular components occurs at the edge/rim of the acetabular component whereas impingement of the femoral neck on the acetabular component's edge causes secondary or contrecoup edge-loading. Although the relationship between the orientation of the acetabular component and primary edge-loading has been identified, the contribution of acetabular component orientation to impingement and secondary edge-loading is less clear. Our aim was to estimate the optimal acetabular component orientation for 16 metal-on-metal hip resurfacing arthroplasty (MoMHRA) subjects with known serum metal ion levels. Data from motion analysis, subject-specific musculoskeletal modelling and Computed Tomography (CT) measurements were used to calculate the dynamic contact patch to rim (CPR) distance and impingement risk for 3416 different acetabular component orientations during gait, sit-to-stand, stair descent and static standing. For each subject, safe zones free from impingement and edge-loading (CPR <10%) were defined and, consequently, an optimal acetabular component orientation was determined (mean inclination 39.7° (SD 6.6°) mean anteversion 14.9° (SD 9.0°)). The results of this study suggest that the optimal acetabular component orientation can be determined from a patient's motion and anatomy. However, 'safe' zones of acetabular component orientation associated with reduced risk of dislocation and pseudotumour are also associated with a reduced risk of edge-loading and impingement. Copyright © 2014 Elsevier Ltd. All rights reserved.

Study on loading coefficient in steam explosion process of corn stalk.

PubMed

Sui, Wenjie; Chen, Hongzhang

2015-03-01

The object of this work was to evaluate the effect of loading coefficient on steam explosion process and efficacy of corn stalk. Loading coefficient's relation with loading pattern and material property was first revealed, then its effect on transfer process and pretreatment efficacy of steam explosion was assessed by established models and enzymatic hydrolysis tests, respectively, in order to propose its optimization strategy for improving the process economy. Results showed that loading coefficient was mainly determined by loading pattern, moisture content and chip size. Both compact loading pattern and low moisture content improved the energy efficiency of steam explosion pretreatment and overall sugar yield of pretreated materials, indicating that they are desirable to improve the process economy. Pretreatment of small chip size showed opposite effects in pretreatment energy efficiency and enzymatic hydrolysis performance, thus its optimization should be balanced in investigated aspects according to further techno-economical evaluation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Optimization of power rationing order based on fuzzy evaluation model

NASA Astrophysics Data System (ADS)

Zhang, Siyuan; Liu, Li; Xie, Peiyuan; Tang, Jihong; Wang, Canlin

2018-04-01

With the development of production and economic growth, China's electricity load has experienced a significant increase. Over the years, in order to alleviate the contradiction of power shortage, a series of policies and measures to speed up electric power construction have been made in china, which promotes the rapid development of the power industry and the power construction has made great achievements. For China, after large-scale power facilities, power grid long-term power shortage situation has been improved to some extent, but in a certain period of time, the power development still exists uneven development. On the whole, it is still in the state of insufficient power, and the situation of power restriction is still severe in some areas, so it is necessary to study on the power rationing.

Transdermal film-loaded finasteride microplates to enhance drug skin permeation: Two-step optimization study.

PubMed

Ahmed, Tarek A; El-Say, Khalid M

2016-06-10

The goal was to develop an optimized transdermal finasteride (FNS) film loaded with drug microplates (MIC), utilizing two-step optimization, to decrease the dosing schedule and inconsistency in gastrointestinal absorption. First; 3-level factorial design was implemented to prepare optimized FNS-MIC of minimum particle size. Second; Box-Behnken design matrix was used to develop optimized transdermal FNS-MIC film. Interaction among MIC components was studied using physicochemical characterization tools. Film components namely; hydroxypropyl methyl cellulose (X1), dimethyl sulfoxide (X2) and propylene glycol (X3) were optimized for their effects on the film thickness (Y1) and elongation percent (Y2), and for FNS steady state flux (Y3), permeability coefficient (Y4), and diffusion coefficient (Y5) following ex-vivo permeation through the rat skin. Morphological study of the optimized MIC and transdermal film was also investigated. Results revealed that stabilizer concentration and anti-solvent percent were significantly affecting MIC formulation. Optimized FNS-MIC of particle size 0.93μm was successfully prepared in which there was no interaction observed among their components. An enhancement in the aqueous solubility of FNS-MIC by more than 23% was achieved. All the studied variables, most of their interaction and quadratic effects were significantly affecting the studied variables (Y1-Y5). Morphological observation illustrated non-spherical, short rods, flakes like small plates that were homogeneously distributed in the optimized transdermal film. Ex-vivo study showed enhanced FNS permeation from film loaded MIC when compared to that contains pure drug. So, MIC is a successful technique to enhance aqueous solubility and skin permeation of poor water soluble drug especially when loaded into transdermal films. Copyright © 2016 Elsevier B.V. All rights reserved.

A Multiobjective Optimization Framework for Online Stochastic Optimal Control in Hybrid Electric Vehicles

DOE PAGES

Malikopoulos, Andreas

2015-01-01

The increasing urgency to extract additional efficiency from hybrid propulsion systems has led to the development of advanced power management control algorithms. In this paper we address the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). We model HEV operation as a controlled Markov chain and we show that the control policy yielding the Pareto optimal solution minimizes online the long-run expected average cost per unit time criterion. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion.more » Both solutions achieved the same cumulative fuel consumption demonstrating that the online Pareto control policy is an optimal control policy.« less

N-SINK - reduction of waste water nitrogen load

NASA Astrophysics Data System (ADS)

Aalto, Sanni; Tiirola, Marja; Arvola, Lauri; Huotari, Jussi; Tulonen, Tiina; Rissanen, Antti; Nykänen, Hannu

2014-05-01

Protection of the Baltic Sea from eutrophication is one of the key topics in the European Union environmental policy. One of the main anthropogenic sources of nitrogen (N) loading into Baltic Sea are waste water treatment plants, which are currently capable in removing only 40-70% of N. European commission has obliged Finland and other Baltic states to reduce nitrate load, which would require high monetary investments on nitrate removal processes in treatment plants. In addition, forced denitrification in treatment plants would increase emissions of strong greenhouse gas N2O. In this project (LIFE12 FI/ENV/597 N-SINK) we will develop and demonstrate a novel economically feasible method for nitrogen removal using applied ecosystem services. As sediment is known to have enormous capacity to reduce nitrate to nitrogen gas through denitrification, we predict that spatial optimization of the waste water discharge would be an efficient way to reduce nitrate-based load in aquatic systems. A new sediment filtration approach, which will increase both the area and time that nitrified waste water will be in contact with the reducing microbes of the sediment, is tested. Compared to the currently implemented practice, where purified waste water is discharged though one-point outlet system, we expect that sediment filtration system will result in more efficient denitrification and decreased N load to aquatic system. We will conduct three full-scale demonstrations in the receiving water bodies of waste water treatment plants in Southern and Central Finland. The ecosystem effects of sediment filtration system will be monitored. Using the most advanced stable isotope techniques will allow us accurately measure denitrification and unfavoured DNRA (reduction of nitrite to ammonium) activity.

Optimizing Cognitive Load for Learning from Computer-Based Science Simulations

ERIC Educational Resources Information Center

Lee, Hyunjeong; Plass, Jan L.; Homer, Bruce D.

2006-01-01

How can cognitive load in visual displays of computer simulations be optimized? Middle-school chemistry students (N = 257) learned with a simulation of the ideal gas law. Visual complexity was manipulated by separating the display of the simulations in two screens (low complexity) or presenting all information on one screen (high complexity). The…

Influence of the optimization methods on neural state estimation quality of the drive system with elasticity.

PubMed

Orlowska-Kowalska, Teresa; Kaminski, Marcin

2014-01-01

The paper deals with the implementation of optimized neural networks (NNs) for state variable estimation of the drive system with an elastic joint. The signals estimated by NNs are used in the control structure with a state-space controller and additional feedbacks from the shaft torque and the load speed. High estimation quality is very important for the correct operation of a closed-loop system. The precision of state variables estimation depends on the generalization properties of NNs. A short review of optimization methods of the NN is presented. Two techniques typical for regularization and pruning methods are described and tested in detail: the Bayesian regularization and the Optimal Brain Damage methods. Simulation results show good precision of both optimized neural estimators for a wide range of changes of the load speed and the load torque, not only for nominal but also changed parameters of the drive system. The simulation results are verified in a laboratory setup.

Beam-energy-spread minimization using cell-timing optimization

NASA Astrophysics Data System (ADS)

Rose, C. R.; Ekdahl, C.; Schulze, M.

2012-04-01

Beam energy spread, and related beam motion, increase the difficulty in tuning for multipulse radiographic experiments at the dual-axis radiographic hydrodynamic test facility’s axis-II linear induction accelerator (LIA). In this article, we describe an optimization method to reduce the energy spread by adjusting the timing of the cell voltages (both unloaded and loaded), either advancing or retarding, such that the injector voltage and summed cell voltages in the LIA result in a flatter energy profile. We developed a nonlinear optimization routine which accepts as inputs the 74 cell-voltage, injector voltage, and beam current waveforms. It optimizes cell timing per user-selected groups of cells and outputs timing adjustments, one for each of the selected groups. To verify the theory, we acquired and present data for both unloaded and loaded cell-timing optimizations. For the unloaded cells, the preoptimization baseline energy spread was reduced by 34% and 31% for two shots as compared to baseline. For the loaded-cell case, the measured energy spread was reduced by 49% compared to baseline.

Aerostructural Level Set Topology Optimization for a Common Research Model Wing

NASA Technical Reports Server (NTRS)

Dunning, Peter D.; Stanford, Bret K.; Kim, H. Alicia

2014-01-01

The purpose of this work is to use level set topology optimization to improve the design of a representative wing box structure for the NASA common research model. The objective is to minimize the total compliance of the structure under aerodynamic and body force loading, where the aerodynamic loading is coupled to the structural deformation. A taxi bump case was also considered, where only body force loads were applied. The trim condition that aerodynamic lift must balance the total weight of the aircraft is enforced by allowing the root angle of attack to change. The level set optimization method is implemented on an unstructured three-dimensional grid, so that the method can optimize a wing box with arbitrary geometry. Fast matching and upwind schemes are developed for an unstructured grid, which make the level set method robust and efficient. The adjoint method is used to obtain the coupled shape sensitivities required to perform aerostructural optimization of the wing box structure.

Plug-in hybrid electric vehicles in smart grid

NASA Astrophysics Data System (ADS)

Yao, Yin

In this thesis, in order to investigate the impact of charging load from plug-in hybrid electric vehicles (PHEVs), a stochastic model is developed in Matlab. In this model, two main types of PHEVs are defined: public transportation vehicles and private vehicles. Different charging time schedule, charging speed and battery capacity are considered for each type of vehicles. The simulation results reveal that there will be two load peaks (at noon and in evening) when the penetration level of PHEVs increases continuously to 30% in 2030. Therefore, optimization tool is utilized to shift load peaks. This optimization process is based on real time pricing and wind power output data. With the help of smart grid, power allocated to each vehicle could be controlled. As a result, this optimization could fulfill the goal of shifting load peaks to valley areas where real time price is low or wind output is high.

Determination of the wind power systems load to achieve operation in the maximum energy area

NASA Astrophysics Data System (ADS)

Chioncel, C. P.; Tirian, G. O.; Spunei, E.; Gillich, N.

2018-01-01

This paper analyses the operation of the wind turbine, WT, in the maximum power point, MPP, by linking the load of the Permanent Magnet Synchronous Generator, PMSG, with the wind speed value. The load control methods at wind power systems aiming an optimum performance in terms of energy are based on the fact that the energy captured by the wind turbine significantly depends on the mechanical angular speed of the wind turbine. The presented control method consists in determining the optimal mechanical angular speed, ωOPTIM, using an auxiliary low power wind turbine, WTAUX, operating without load, at maximum angular velocity, ωMAX. The method relies on the fact that the ratio ωOPTIM/ωMAX has a constant value for a given wind turbine and does not depend on the time variation of the wind speed values.

Optimum Parameters of a Tuned Liquid Column Damper in a Wind Turbine Subject to Stochastic Load

NASA Astrophysics Data System (ADS)

Alkmim, M. H.; de Morais, M. V. G.; Fabro, A. T.

2017-12-01

Parameter optimization for tuned liquid column dampers (TLCD), a class of passive structural control, have been previously proposed in the literature for reducing vibration in wind turbines, and several other applications. However, most of the available work consider the wind excitation as either a deterministic harmonic load or random load with white noise spectra. In this paper, a global direct search optimization algorithm to reduce vibration of a tuned liquid column damper (TLCD), a class of passive structural control device, is presented. The objective is to find optimized parameters for the TLCD under stochastic load from different wind power spectral density. A verification is made considering the analytical solution of undamped primary system under white noise excitation by comparing with result from the literature. Finally, it is shown that different wind profiles can significantly affect the optimum TLCD parameters.

Adaptive torque estimation of robot joint with harmonic drive transmission

NASA Astrophysics Data System (ADS)

Shi, Zhiguo; Li, Yuankai; Liu, Guangjun

2017-11-01

Robot joint torque estimation using input and output position measurements is a promising technique, but the result may be affected by the load variation of the joint. In this paper, a torque estimation method with adaptive robustness and optimality adjustment according to load variation is proposed for robot joint with harmonic drive transmission. Based on a harmonic drive model and a redundant adaptive robust Kalman filter (RARKF), the proposed approach can adapt torque estimation filtering optimality and robustness to the load variation by self-tuning the filtering gain and self-switching the filtering mode between optimal and robust. The redundant factor of RARKF is designed as a function of the motor current for tolerating the modeling error and load-dependent filtering mode switching. The proposed joint torque estimation method has been experimentally studied in comparison with a commercial torque sensor and two representative filtering methods. The results have demonstrated the effectiveness of the proposed torque estimation technique.

Efficiency Enhancement for an Inductive Wireless Power Transfer System by Optimizing the Impedance Matching Networks.

PubMed

Miao, Zhidong; Liu, Dake; Gong, Chen

2017-10-01

Inductive wireless power transfer (IWPT) is a promising power technology for implantable biomedical devices, where the power consumption is low and the efficiency is the most important consideration. In this paper, we propose an optimization method of impedance matching networks (IMN) to maximize the IWPT efficiency. The IMN at the load side is designed to achieve the optimal load, and the IMN at the source side is designed to deliver the required amount of power (no-more-no-less) from the power source to the load. The theoretical analyses and design procedure are given. An IWPT system for an implantable glaucoma therapeutic prototype is designed as an example. Compared with the efficiency of the resonant IWPT system, the efficiency of our optimized system increases with a factor of 1.73. Besides, the efficiency of our optimized IWPT system is 1.97 times higher than that of the IWPT system optimized by the traditional maximum power transfer method. All the discussions indicate that the optimization method proposed in this paper could achieve a high efficiency and long working time when the system is powered by a battery.

A duality framework for stochastic optimal control of complex systems

DOE PAGES

Malikopoulos, Andreas A.

2016-01-01

In this study, we address the problem of minimizing the long-run expected average cost of a complex system consisting of interactive subsystems. We formulate a multiobjective optimization problem of the one-stage expected costs of the subsystems and provide a duality framework to prove that the control policy yielding the Pareto optimal solution minimizes the average cost criterion of the system. We provide the conditions of existence and a geometric interpretation of the solution. For practical situations having constraints consistent with those studied here, our results imply that the Pareto control policy may be of value when we seek to derivemore » online the optimal control policy in complex systems.« less

Optimal shutdown management

NASA Astrophysics Data System (ADS)

Bottasso, C. L.; Croce, A.; Riboldi, C. E. D.

2014-06-01

The paper presents a novel approach for the synthesis of the open-loop pitch profile during emergency shutdowns. The problem is of interest in the design of wind turbines, as such maneuvers often generate design driving loads on some of the machine components. The pitch profile synthesis is formulated as a constrained optimal control problem, solved numerically using a direct single shooting approach. A cost function expressing a compromise between load reduction and rotor overspeed is minimized with respect to the unknown blade pitch profile. Constraints may include a load reduction not-to-exceed the next dominating loads, a not-to-be-exceeded maximum rotor speed, and a maximum achievable blade pitch rate. Cost function and constraints are computed over a possibly large number of operating conditions, defined so as to cover as well as possible the operating situations encountered in the lifetime of the machine. All such conditions are simulated by using a high-fidelity aeroservoelastic model of the wind turbine, ensuring the accuracy of the evaluation of all relevant parameters. The paper demonstrates the capabilities of the novel proposed formulation, by optimizing the pitch profile of a multi-MW wind turbine. Results show that the procedure can reliably identify optimal pitch profiles that reduce design-driving loads, in a fully automated way.

Optimal Coordination of Building Loads and Energy Storage for Power Grid and End User Services

DOE PAGES

Hao, He; Wu, Di; Lian, Jianming; ...

2017-01-18

Demand response and energy storage play a profound role in the smart grid. The focus of this study is to evaluate benefits of coordinating flexible loads and energy storage to provide power grid and end user services. We present a Generalized Battery Model (GBM) to describe the flexibility of building loads and energy storage. An optimization-based approach is proposed to characterize the parameters (power and energy limits) of the GBM for flexible building loads. We then develop optimal coordination algorithms to provide power grid and end user services such as energy arbitrage, frequency regulation, spinning reserve, as well as energymore » cost and demand charge reduction. Several case studies have been performed to demonstrate the efficacy of the GBM and coordination algorithms, and evaluate the benefits of using their flexibility for power grid and end user services. We show that optimal coordination yields significant cost savings and revenue. Moreover, the best option for power grid services is to provide energy arbitrage and frequency regulation. Finally and furthermore, when coordinating flexible loads with energy storage to provide end user services, it is recommended to consider demand charge in addition to time-of-use price in order to flatten the aggregate power profile.« less

The effect of code expanding optimizations on instruction cache design

NASA Technical Reports Server (NTRS)

Chen, William Y.; Chang, Pohua P.; Conte, Thomas M.; Hwu, Wen-Mei W.

1991-01-01

It is shown that code expanding optimizations have strong and non-intuitive implications on instruction cache design. Three types of code expanding optimizations are studied: instruction placement, function inline expansion, and superscalar optimizations. Overall, instruction placement reduces the miss ratio of small caches. Function inline expansion improves the performance for small cache sizes, but degrades the performance of medium caches. Superscalar optimizations increases the cache size required for a given miss ratio. On the other hand, they also increase the sequentiality of instruction access so that a simple load-forward scheme effectively cancels the negative effects. Overall, it is shown that with load forwarding, the three types of code expanding optimizations jointly improve the performance of small caches and have little effect on large caches.

Uncertainty quantification and optimal decisions

PubMed Central

2017-01-01

A mathematical model can be analysed to construct policies for action that are close to optimal for the model. If the model is accurate, such policies will be close to optimal when implemented in the real world. In this paper, the different aspects of an ideal workflow are reviewed: modelling, forecasting, evaluating forecasts, data assimilation and constructing control policies for decision-making. The example of the oil industry is used to motivate the discussion, and other examples, such as weather forecasting and precision agriculture, are used to argue that the same mathematical ideas apply in different contexts. Particular emphasis is placed on (i) uncertainty quantification in forecasting and (ii) how decisions are optimized and made robust to uncertainty in models and judgements. This necessitates full use of the relevant data and by balancing costs and benefits into the long term may suggest policies quite different from those relevant to the short term. PMID:28484343

Error bounds of adaptive dynamic programming algorithms for solving undiscounted optimal control problems.

PubMed

Liu, Derong; Li, Hongliang; Wang, Ding

2015-06-01

In this paper, we establish error bounds of adaptive dynamic programming algorithms for solving undiscounted infinite-horizon optimal control problems of discrete-time deterministic nonlinear systems. We consider approximation errors in the update equations of both value function and control policy. We utilize a new assumption instead of the contraction assumption in discounted optimal control problems. We establish the error bounds for approximate value iteration based on a new error condition. Furthermore, we also establish the error bounds for approximate policy iteration and approximate optimistic policy iteration algorithms. It is shown that the iterative approximate value function can converge to a finite neighborhood of the optimal value function under some conditions. To implement the developed algorithms, critic and action neural networks are used to approximate the value function and control policy, respectively. Finally, a simulation example is given to demonstrate the effectiveness of the developed algorithms.

Improving stability and strength characteristics of framed structures with nonlinear behavior

NASA Technical Reports Server (NTRS)

Pezeshk, Shahram

1990-01-01

In this paper an optimal design procedure is introduced to improve the overall performance of nonlinear framed structures. The design methodology presented here is a multiple-objective optimization procedure whose objective functions involve the buckling eigenvalues and eigenvectors of the structure. A constant volume with bounds on the design variables is used in conjunction with an optimality criterion approach. The method provides a general tool for solving complex design problems and generally leads to structures with better limit strength and stability. Many algorithms have been developed to improve the limit strength of structures. In most applications geometrically linear analysis is employed with the consequence that overall strength of the design is overestimated. Directly optimizing the limit load of the structure would require a full nonlinear analysis at each iteration which would be prohibitively expensive. The objective of this paper is to develop an algorithm that can improve the limit-load of geometrically nonlinear framed structures while avoiding the nonlinear analysis. One of the novelties of the new design methodology is its ability to efficiently model and design structures under multiple loading conditions. These loading conditions can be different factored loads or any kind of loads that can be applied to the structure simultaneously or independently. Attention is focused on optimal design of space framed structures. Three-dimensional design problems are more complicated to carry out, but they yield insight into real behavior of the structure and can help avoiding some of the problems that might appear in planar design procedure such as the need for out-of-plane buckling constraint. Although researchers in the field of structural engineering generally agree that optimum design of three-dimension building frames especially in the seismic regions would be beneficial, methods have been slow to emerge. Most of the research in this area has dealt with the optimization of truss and plane frame structures.

Research on power source structure optimization for East China Power Grid

NASA Astrophysics Data System (ADS)

Xu, Lingjun; Sang, Da; Zhang, Jianping; Tang, Chunyi; Xu, Da

2017-05-01

The structure of east china power grid is not reasonable for the coal power takes a much higher proportion than hydropower, at present the coal power takes charge of most peak load regulation, and the pressure of peak load regulation cannot be ignored. The nuclear power, wind power, photovoltaic, other clean energy and hydropower, coal power and wind power from outside will be actively developed in future, which increases the pressure of peak load regulation. According to development of economic and social, Load status and load prediction, status quo and planning of power source and the characteristics of power source, the peak load regulation balance is carried out and put forward a reasonable plan of power source allocation. The ultimate aim is to optimize the power source structure and to provide reference for power source allocation in east china.

Effect of Task Load Interventions on Fatigue in Emergency Medical Services Personnel and Other Shift Workers: A Systematic Review

DOT National Transportation Integrated Search

2018-01-11

Modifying the task load of Emergency Medical Services (EMS) personnel may mitigate fatigue, sleep quality and fatigue related risks. A review of the literature addressing task load interventions may benefit EMS administrators as they craft policies r...

Optimal dynamic pricing and replenishment policy for perishable items with inventory-level-dependent demand

NASA Astrophysics Data System (ADS)

Lu, Lihao; Zhang, Jianxiong; Tang, Wansheng

2016-04-01

An inventory system for perishable items with limited replenishment capacity is introduced in this paper. The demand rate depends on the stock quantity displayed in the store as well as the sales price. With the goal to realise profit maximisation, an optimisation problem is addressed to seek for the optimal joint dynamic pricing and replenishment policy which is obtained by solving the optimisation problem with Pontryagin's maximum principle. A joint mixed policy, in which the sales price is a static decision variable and the replenishment rate remains to be a dynamic decision variable, is presented to compare with the joint dynamic policy. Numerical results demonstrate the advantages of the joint dynamic one, and further show the effects of different system parameters on the optimal joint dynamic policy and the maximal total profit.

Porous biodegradable lumbar interbody fusion cage design and fabrication using integrated global-local topology optimization with laser sintering.

PubMed

Kang, Heesuk; Hollister, Scott J; La Marca, Frank; Park, Paul; Lin, Chia-Ying

2013-10-01

Biodegradable cages have received increasing attention for their use in spinal procedures involving interbody fusion to resolve complications associated with the use of nondegradable cages, such as stress shielding and long-term foreign body reaction. However, the relatively weak initial material strength compared to permanent materials and subsequent reduction due to degradation may be problematic. To design a porous biodegradable interbody fusion cage for a preclinical large animal study that can withstand physiological loads while possessing sufficient interconnected porosity for bony bridging and fusion, we developed a multiscale topology optimization technique. Topology optimization at the macroscopic scale provides optimal structural layout that ensures mechanical strength, while optimally designed microstructures, which replace the macroscopic material layout, ensure maximum permeability. Optimally designed cages were fabricated using solid, freeform fabrication of poly(ε-caprolactone) mixed with hydroxyapatite. Compression tests revealed that the yield strength of optimized fusion cages was two times that of typical human lumbar spine loads. Computational analysis further confirmed the mechanical integrity within the human lumbar spine, although the pore structure locally underwent higher stress than yield stress. This optimization technique may be utilized to balance the complex requirements of load-bearing, stress shielding, and interconnected porosity when using biodegradable materials for fusion cages.

Conceptual optimization using genetic algorithms for tube in tube structures

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

Pârv, Bianca Roxana; Hulea, Radu; Mojolic, Cristian

2015-03-10

The purpose of this article is to optimize the tube in tube structural systems for tall buildings under the horizontal wind loads. It is well-known that the horizontal wind loads is the main criteria when choosing the structural system, the types and the dimensions of structural elements in the majority of tall buildings. Thus, the structural response of tall buildings under the horizontal wind loads will be analyzed for 40 story buildings and a total height of 120 meters; the horizontal dimensions will be 30m × 30m for the first two optimization problems and 15m × 15m for the third.more » The optimization problems will have the following as objective function the cross section area, as restrictions the displacement of the building< the admissible displacement (H/500), and as variables the cross section dimensions of the structural elements.« less

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

NASA Astrophysics Data System (ADS)

Huang, Feng; Li, Jing

2017-12-01

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

Optimization of Stability Constrained Geometrically Nonlinear Shallow Trusses Using an Arc Length Sparse Method with a Strain Energy Density Approach

NASA Technical Reports Server (NTRS)

Hrinda, Glenn A.; Nguyen, Duc T.

2008-01-01

A technique for the optimization of stability constrained geometrically nonlinear shallow trusses with snap through behavior is demonstrated using the arc length method and a strain energy density approach within a discrete finite element formulation. The optimization method uses an iterative scheme that evaluates the design variables' performance and then updates them according to a recursive formula controlled by the arc length method. A minimum weight design is achieved when a uniform nonlinear strain energy density is found in all members. This minimal condition places the design load just below the critical limit load causing snap through of the structure. The optimization scheme is programmed into a nonlinear finite element algorithm to find the large strain energy at critical limit loads. Examples of highly nonlinear trusses found in literature are presented to verify the method.

Transdermal glimepiride delivery system based on optimized ethosomal nano-vesicles: Preparation, characterization, in vitro, ex vivo and clinical evaluation.

PubMed

Ahmed, Tarek A; El-Say, Khalid M; Aljaeid, Bader M; Fahmy, Usama A; Abd-Allah, Fathy I

2016-03-16

This work aimed to develop an optimized ethosomal formulation of glimepiride then loading into transdermal films to offer lower drug side effect, extended release behavior and avoid first pass effect. Four formulation factors were optimized for their effects on vesicle size (Y1), entrapment efficiency (Y2) and vesicle flexibility (Y3). Optimum desirability was identified and, an optimized formulation was prepared, characterized and loaded into transdermal films. Ex-vivo permeation study for the prepared films was conducted and, the permeation parameters and drug permeation mechanism were identified. Penetration through rat skin was studied using confocal laser microscope. In-vivo study was performed following transdermal application on human volunteers. The percent of alcohol was significantly affecting all the studied responses while the other factors and their interaction effects were varied on their effects on each response. The optimized ethosomal formulation showed observed values for Y1, Y2 and Y3 of 61 nm, 97.12% and 54.03, respectively. Ex-vivo permeation of films loaded with optimized ethosomal formulation was superior to that of the corresponding pure drug transdermal films and this finding was also confirmed after confocal laser microscope study. Permeation of glimepiride from the prepared films was in favor of Higushi-diffusion model and exhibited non-Fickian or anomalous release mechanism. In-vivo study revealed extended drug release behavior and lower maximum drug plasma level from transdermal films loaded with drug ethosomal formulation. So, the ethosomal formulation could be considered a suitable drug delivery system especially when loaded into transdermal vehicle with possible reduction in side effects and controlling the drug release. Copyright © 2016 Elsevier B.V. All rights reserved.

Geometry Design Optimization of Functionally Graded Scaffolds for Bone Tissue Engineering: A Mechanobiological Approach.

PubMed

Boccaccio, Antonio; Uva, Antonio Emmanuele; Fiorentino, Michele; Mori, Giorgio; Monno, Giuseppe

2016-01-01

Functionally Graded Scaffolds (FGSs) are porous biomaterials where porosity changes in space with a specific gradient. In spite of their wide use in bone tissue engineering, possible models that relate the scaffold gradient to the mechanical and biological requirements for the regeneration of the bony tissue are currently missing. In this study we attempt to bridge the gap by developing a mechanobiology-based optimization algorithm aimed to determine the optimal graded porosity distribution in FGSs. The algorithm combines the parametric finite element model of a FGS, a computational mechano-regulation model and a numerical optimization routine. For assigned boundary and loading conditions, the algorithm builds iteratively different scaffold geometry configurations with different porosity distributions until the best microstructure geometry is reached, i.e. the geometry that allows the amount of bone formation to be maximized. We tested different porosity distribution laws, loading conditions and scaffold Young's modulus values. For each combination of these variables, the explicit equation of the porosity distribution law-i.e the law that describes the pore dimensions in function of the spatial coordinates-was determined that allows the highest amounts of bone to be generated. The results show that the loading conditions affect significantly the optimal porosity distribution. For a pure compression loading, it was found that the pore dimensions are almost constant throughout the entire scaffold and using a FGS allows the formation of amounts of bone slightly larger than those obtainable with a homogeneous porosity scaffold. For a pure shear loading, instead, FGSs allow to significantly increase the bone formation compared to a homogeneous porosity scaffolds. Although experimental data is still necessary to properly relate the mechanical/biological environment to the scaffold microstructure, this model represents an important step towards optimizing geometry of functionally graded scaffolds based on mechanobiological criteria.

An optimization-based approach for facility energy management with uncertainties, and, Power portfolio optimization in deregulated electricity markets with risk management

NASA Astrophysics Data System (ADS)

Xu, Jun

Topic 1. An Optimization-Based Approach for Facility Energy Management with Uncertainties. Effective energy management for facilities is becoming increasingly important in view of the rising energy costs, the government mandate on the reduction of energy consumption, and the human comfort requirements. This part of dissertation presents a daily energy management formulation and the corresponding solution methodology for HVAC systems. The problem is to minimize the energy and demand costs through the control of HVAC units while satisfying human comfort, system dynamics, load limit constraints, and other requirements. The problem is difficult in view of the fact that the system is nonlinear, time-varying, building-dependent, and uncertain; and that the direct control of a large number of HVAC components is difficult. In this work, HVAC setpoints are the control variables developed on top of a Direct Digital Control (DDC) system. A method that combines Lagrangian relaxation, neural networks, stochastic dynamic programming, and heuristics is developed to predict the system dynamics and uncontrollable load, and to optimize the setpoints. Numerical testing and prototype implementation results show that our method can effectively reduce total costs, manage uncertainties, and shed the load, is computationally efficient. Furthermore, it is significantly better than existing methods. Topic 2. Power Portfolio Optimization in Deregulated Electricity Markets with Risk Management. In a deregulated electric power system, multiple markets of different time scales exist with various power supply instruments. A load serving entity (LSE) has multiple choices from these instruments to meet its load obligations. In view of the large amount of power involved, the complex market structure, risks in such volatile markets, stringent constraints to be satisfied, and the long time horizon, a power portfolio optimization problem is of critical importance but difficulty for an LSE to serve the load, maximize its profit, and manage risks. In this topic, a mid-term power portfolio optimization problem with risk management is presented. Key instruments are considered, risk terms based on semi-variances of spot market transactions are introduced, and penalties on load obligation violations are added to the objective function to improve algorithm convergence and constraint satisfaction. To overcome the inseparability of the resulting problem, a surrogate optimization framework is developed enabling a decomposition and coordination approach. Numerical testing results show that our method effectively provides decisions for various instruments to maximize profit, manage risks, and is computationally efficient.

Aeroelastic Wingbox Stiffener Topology Optimization

NASA Technical Reports Server (NTRS)

Stanford, Bret K.

2017-01-01

This work considers an aeroelastic wingbox model seeded with run-out blade stiffeners along the skins. Topology optimization is conducted within the shell webs of the stiffeners, in order to add cutouts and holes for mass reduction. This optimization is done with a global-local approach in order to moderate the computational cost: aeroelastic loads are computed at the wing-level, but the topology and sizing optimization is conducted at the panel-level. Each panel is optimized separately under stress, buckling, and adjacency constraints, and periodically reassembled to update the trimmed aeroelastic loads. The resulting topology is baselined against a design with standard full-depth solid stiffener blades, and found to weigh 7.43% less.

Event-Triggered Distributed Approximate Optimal State and Output Control of Affine Nonlinear Interconnected Systems.

PubMed

Narayanan, Vignesh; Jagannathan, Sarangapani

2017-06-08

This paper presents an approximate optimal distributed control scheme for a known interconnected system composed of input affine nonlinear subsystems using event-triggered state and output feedback via a novel hybrid learning scheme. First, the cost function for the overall system is redefined as the sum of cost functions of individual subsystems. A distributed optimal control policy for the interconnected system is developed using the optimal value function of each subsystem. To generate the optimal control policy, forward-in-time, neural networks are employed to reconstruct the unknown optimal value function at each subsystem online. In order to retain the advantages of event-triggered feedback for an adaptive optimal controller, a novel hybrid learning scheme is proposed to reduce the convergence time for the learning algorithm. The development is based on the observation that, in the event-triggered feedback, the sampling instants are dynamic and results in variable interevent time. To relax the requirement of entire state measurements, an extended nonlinear observer is designed at each subsystem to recover the system internal states from the measurable feedback. Using a Lyapunov-based analysis, it is demonstrated that the system states and the observer errors remain locally uniformly ultimately bounded and the control policy converges to a neighborhood of the optimal policy. Simulation results are presented to demonstrate the performance of the developed controller.

Skeletal adaptation to external loads optimizes mechanical properties: fact or fiction

NASA Technical Reports Server (NTRS)

Turner, R. T.

2001-01-01

The skeleton adapts to a changing mechanical environment but the widely held concept that bone cells are programmed to respond to local mechanical loads to produce an optimal mechanical structure is not consistent with the high frequency of bone fractures. Instead, the author suggests that other important functions of bone compete with mechanical adaptation to determine structure. As a consequence of competing demands, bone architecture never achieves an optimal mechanical structure. c2001 Lippincott Williams & Wilkins, Inc.

Optimization of thermoelectric cooling regimes for heat-loaded elements taking into account the thermal resistance of the heat-spreading system

NASA Astrophysics Data System (ADS)

Vasil'ev, E. N.

2017-09-01

A mathematical model has been proposed for analyzing and optimizing thermoelectric cooling regimes for heat-loaded elements of engineering and electronic devices. The model based on analytic relations employs the working characteristics of thermoelectric modules as the initial data and makes it possible to determine the temperature regime and the optimal values of the feed current for the modules taking into account the thermal resistance of the heat-spreading system.

An optimized network for phosphorus load monitoring for Lake Okeechobee, Florida

USGS Publications Warehouse

Gain, W.S.

1997-01-01

Phosphorus load data were evaluated for Lake Okeechobee, Florida, for water years 1982 through 1991. Standard errors for load estimates were computed from available phosphorus concentration and daily discharge data. Components of error were associated with uncertainty in concentration and discharge data and were calculated for existing conditions and for 6 alternative load-monitoring scenarios for each of 48 distinct inflows. Benefit-cost ratios were computed for each alternative monitoring scenario at each site by dividing estimated reductions in load uncertainty by the 5-year average costs of each scenario in 1992 dollars. Absolute and marginal benefit-cost ratios were compared in an iterative optimization scheme to determine the most cost-effective combination of discharge and concentration monitoring scenarios for the lake. If the current (1992) discharge-monitoring network around the lake is maintained, the water-quality sampling at each inflow site twice each year is continued, and the nature of loading remains the same, the standard error of computed mean-annual load is estimated at about 98 metric tons per year compared to an absolute loading rate (inflows and outflows) of 530 metric tons per year. This produces a relative uncertainty of nearly 20 percent. The standard error in load can be reduced to about 20 metric tons per year (4 percent) by adopting an optimized set of monitoring alternatives at a cost of an additional $200,000 per year. The final optimized network prescribes changes to improve both concentration and discharge monitoring. These changes include the addition of intensive sampling with automatic samplers at 11 sites, the initiation of event-based sampling by observers at another 5 sites, the continuation of periodic sampling 12 times per year at 1 site, the installation of acoustic velocity meters to improve discharge gaging at 9 sites, and the improvement of a discharge rating at 1 site.

Thermal decomposition behavior of nano/micro bimodal feedstock with different solids loading

NASA Astrophysics Data System (ADS)

Oh, Joo Won; Lee, Won Sik; Park, Seong Jin

2018-01-01

Debinding is one of the most critical processes for powder injection molding. The parts in debinding process are vulnerable to defect formation, and long processing time of debinding decreases production rate of whole process. In order to determine the optimal condition for debinding process, decomposition behavior of feedstock should be understood. Since nano powder affects the decomposition behavior of feedstock, nano powder effect needs to be investigated for nano/micro bimodal feedstock. In this research, nano powder effect on decomposition behavior of nano/micro bimodal feedstock has been studied. Bimodal powders were fabricated with different ratios of nano powder, and the critical solids loading of each powder was measured by torque rheometer. Three different feedstocks were fabricated for each powder depending on solids loading condition. Thermogravimetric analysis (TGA) experiment was carried out to analyze the thermal decomposition behavior of the feedstocks, and decomposition activation energy was calculated. The result indicated nano powder showed limited effect on feedstocks in lower solids loading condition than optimal range. Whereas, it highly influenced the decomposition behavior in optimal solids loading condition by causing polymer chain scission with high viscosity.

Design, Optimization, and Evaluation of Integrally-Stiffened Al-2139 Panel with Curved Stiffeners

NASA Technical Reports Server (NTRS)

Havens, David; Shiyekar, Sandeep; Norris, Ashley; Bird, R. Keith; Kapania, Rakesh K.; Olliffe, Robert

2011-01-01

A curvilinear stiffened panel was designed, manufactured, and tested in the Combined Load Test Fixture at NASA Langley Research Center. The panel is representative of a large wing engine pylon rib and was optimized for minimum mass subjected to three combined load cases. The optimization included constraints on web buckling, material yielding, crippling or local stiffener failure, and damage tolerance using a new analysis tool named EBF3PanelOpt. Testing was performed for the critical combined compression-shear loading configuration. The panel was loaded beyond initial buckling, and strains and out-of-plane displacements were extracted from a total of 20 strain gages and 6 linear variable displacement transducers. The VIC-3D system was utilized to obtain full field displacements/strains in the stiffened side of the panel. The experimental data were compared with the strains and out-of-plane deflections from a high fidelity nonlinear finite element analysis. The experimental data were also compared with linear elastic finite element results of the panel/test-fixture assembly. Overall, the panel buckled very near to the predicted load in the web regions.

Finite element analysis of 6 large PMMA skull reconstructions: A multi-criteria evaluation approach

PubMed Central

Ridwan-Pramana, Angela; Marcián, Petr; Borák, Libor; Narra, Nathaniel; Forouzanfar, Tymour; Wolff, Jan

2017-01-01

In this study 6 pre-operative designs for PMMA based reconstructions of cranial defects were evaluated for their mechanical robustness using finite element modeling. Clinical experience and engineering principles were employed to create multiple plan options, which were subsequently computationally analyzed for mechanically relevant parameters under 50N loads: stress, strain and deformation in various components of the assembly. The factors assessed were: defect size, location and shape. The major variable in the cranioplasty assembly design was the arrangement of the fixation plates. An additional study variable introduced was the location of the 50N load within the implant area. It was found that in smaller defects, it was simpler to design a symmetric distribution of plates and under limited variability in load location it was possible to design an optimal for expected loads. However, for very large defects with complex shapes, the variability in the load locations introduces complications to the intuitive design of the optimal assembly. The study shows that it can be beneficial to incorporate multi design computational analyses to decide upon the most optimal plan for a clinical case. PMID:28609471

Finite element analysis of 6 large PMMA skull reconstructions: A multi-criteria evaluation approach.

PubMed

Ridwan-Pramana, Angela; Marcián, Petr; Borák, Libor; Narra, Nathaniel; Forouzanfar, Tymour; Wolff, Jan

2017-01-01

In this study 6 pre-operative designs for PMMA based reconstructions of cranial defects were evaluated for their mechanical robustness using finite element modeling. Clinical experience and engineering principles were employed to create multiple plan options, which were subsequently computationally analyzed for mechanically relevant parameters under 50N loads: stress, strain and deformation in various components of the assembly. The factors assessed were: defect size, location and shape. The major variable in the cranioplasty assembly design was the arrangement of the fixation plates. An additional study variable introduced was the location of the 50N load within the implant area. It was found that in smaller defects, it was simpler to design a symmetric distribution of plates and under limited variability in load location it was possible to design an optimal for expected loads. However, for very large defects with complex shapes, the variability in the load locations introduces complications to the intuitive design of the optimal assembly. The study shows that it can be beneficial to incorporate multi design computational analyses to decide upon the most optimal plan for a clinical case.

Optimization of ACC system spacing policy on curved highway

NASA Astrophysics Data System (ADS)

Ma, Jun; Qian, Kun; Gong, Zaiyan

2017-05-01

The paper optimizes the original spacing policy when adopting VTH (Variable Time Headway), proposes to introduce the road curve curvature K to the spacing policy to cope with following the wrong vehicle or failing to follow the vehicle owing to the radar limitation of curve in ACC system. By utilizing MATLAB/Simulink, automobile longitudinal dynamics model is established. At last, the paper sets up such three common cases as the vehicle ahead runs at a uniform velocity, an accelerated velocity and hits the brake suddenly, simulates these cases on the curve with different curvature, analyzes the curve spacing policy in the perspective of safety and vehicle following efficiency and draws the conclusion whether the optimization scheme is effective or not.

Optimization of doxorubicin loading for superabsorbent polymer microspheres: in vitro analysis.

PubMed

Liu, David M; Kos, Sebastian; Buczkowski, Andrzej; Kee, Stephen; Munk, Peter L; Klass, Darren; Wasan, Ellen

2012-04-01

This study was designed to establish the ability of super-absorbent polymer microspheres (SAP) to actively uptake doxorubicin and to establish the proof of principle of SAP's ability to phase transfer doxorubicin onto the polymer matrix and to elute into buffer with a loading method that optimizes physical handling and elution characteristics. Phase I: 50-100 μm SAP subject to various prehydration methods (normal saline 10 cc, hypertonic saline 4 cc, iodinated contrast 10 cc) or left in their dry state, and combined with 50 mg of clinical grade lyophilized doxorubicin reconstituted with various methods (normal saline 10 cc and 25 cc, sterile water 4 cc, iodinated contrast 5 cc) were placed in buffer and assessed based on loading, handling, and elution utilizing high-performance liquid chromatography (HPLC). Phase II: top two performing methods were subject to loading of doxorubicin (50, 75, 100 mg) in a single bolus (group A) or as a serial loading method (group B) followed by measurement of loading vs. time and elution vs. time. Phase I revealed the most effective loading mechanisms and easiest handling to be dry (group A) vs. normal saline prehydrated (group B) SAP with normal saline reconstituted doxorubicin (10 mg/mL) with loading efficiencies of 83.1% and 88.4%. Phase II results revealed unstable behavior of SAP with 100 mg of doxorubicin and similar loading/elution profiles of dry and prehydrated SAP, with superior handling characteristics of group B SAP at 50 and 75 mg. SAP demonstrates the ability to load and bulk phase transfer doxorubicin at 50 and 75 mg with ease of handling and optimal efficiency through dry loading of SAP.

Optimization of Doxorubicin Loading for Superabsorbent Polymer Microspheres: in vitro Analysis

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

Liu, David M., E-mail: dave.liu@vch.ca; Kos, Sebastian; Buczkowski, Andrzej

2012-04-15

Purpose: This study was designed to establish the ability of super-absorbent polymer microspheres (SAP) to actively uptake doxorubicin and to establish the proof of principle of SAP's ability to phase transfer doxorubicin onto the polymer matrix and to elute into buffer with a loading method that optimizes physical handling and elution characteristics. Methods: Phase I: 50-100 {mu}m SAP subject to various prehydration methods (normal saline 10 cc, hypertonic saline 4 cc, iodinated contrast 10 cc) or left in their dry state, and combined with 50 mg of clinical grade lyophilized doxorubicin reconstituted with various methods (normal saline 10 cc andmore » 25 cc, sterile water 4 cc, iodinated contrast 5 cc) were placed in buffer and assessed based on loading, handling, and elution utilizing high-performance liquid chromatography (HPLC). Phase II: top two performing methods were subject to loading of doxorubicin (50, 75, 100 mg) in a single bolus (group A) or as a serial loading method (group B) followed by measurement of loading vs. time and elution vs. time. Results: Phase I revealed the most effective loading mechanisms and easiest handling to be dry (group A) vs. normal saline prehydrated (group B) SAP with normal saline reconstituted doxorubicin (10 mg/mL) with loading efficiencies of 83.1% and 88.4%. Phase II results revealed unstable behavior of SAP with 100 mg of doxorubicin and similar loading/elution profiles of dry and prehydrated SAP, with superior handling characteristics of group B SAP at 50 and 75 mg. Conclusions: SAP demonstrates the ability to load and bulk phase transfer doxorubicin at 50 and 75 mg with ease of handling and optimal efficiency through dry loading of SAP.« less

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On jointly optimising the changes of seasonable goods and inventory replenishment

NASA Astrophysics Data System (ADS)

Li, Zhaolin; Tao, Feng; Sun, Daewon

2012-06-01

Retailers often need to replace soon-to-be-unseasonable products with new seasonable goods when the season changes. The trade-off for such activities involves choosing between the salvage loss of the unseasonable product and the profit of selling the seasonable product early. This article develops a periodic-review inventory model for planning the changes of seasonable goods with state-dependent demand and cost parameters. We show that the single-period optimal policy for product changes is a threshold policy based on the initial inventory of the unseasonable goods. The corresponding optimal inventory policy follows a Purchase-Keep-Dispose policy if the incumbent product is kept or a base-stock policy if the incumbent product is replaced. Numerically, we find that the structure of the multi-period optimal policy resembles that of the single-period model. We propose a heuristic to solve the multi-period model and demonstrate its effectiveness. Our research provides insights into dynamically managing seasonable goods.

Information-theoretic approach to interactive learning

NASA Astrophysics Data System (ADS)

Still, S.

2009-01-01

The principles of statistical mechanics and information theory play an important role in learning and have inspired both theory and the design of numerous machine learning algorithms. The new aspect in this paper is a focus on integrating feedback from the learner. A quantitative approach to interactive learning and adaptive behavior is proposed, integrating model- and decision-making into one theoretical framework. This paper follows simple principles by requiring that the observer's world model and action policy should result in maximal predictive power at minimal complexity. Classes of optimal action policies and of optimal models are derived from an objective function that reflects this trade-off between prediction and complexity. The resulting optimal models then summarize, at different levels of abstraction, the process's causal organization in the presence of the learner's actions. A fundamental consequence of the proposed principle is that the learner's optimal action policies balance exploration and control as an emerging property. Interestingly, the explorative component is present in the absence of policy randomness, i.e. in the optimal deterministic behavior. This is a direct result of requiring maximal predictive power in the presence of feedback.

The optimal inventory policy for EPQ model under trade credit

NASA Astrophysics Data System (ADS)

Chung, Kun-Jen

2010-09-01

Huang and Huang [(2008), 'Optimal Inventory Replenishment Policy for the EPQ Model Under Trade Credit without Derivatives International Journal of Systems Science, 39, 539-546] use the algebraic method to determine the optimal inventory replenishment policy for the retailer in the extended model under trade credit. However, the algebraic method has its limit of application such that validities of proofs of Theorems 1-4 in Huang and Huang (2008) are questionable. The main purpose of this article is not only to indicate shortcomings but also to present the accurate proofs for Huang and Huang (2008).

Application of model predictive control for optimal operation of wind turbines

NASA Astrophysics Data System (ADS)

Yuan, Yuan; Cao, Pei; Tang, J.

2017-04-01

For large-scale wind turbines, reducing maintenance cost is a major challenge. Model predictive control (MPC) is a promising approach to deal with multiple conflicting objectives using the weighed sum approach. In this research, model predictive control method is applied to wind turbine to find an optimal balance between multiple objectives, such as the energy capture, loads on turbine components, and the pitch actuator usage. The actuator constraints are integrated into the objective function at the control design stage. The analysis is carried out in both the partial load region and full load region, and the performances are compared with those of a baseline gain scheduling PID controller. The application of this strategy achieves enhanced balance of component loads, the average power and actuator usages in partial load region.

Simplified Design Method for Tension Fasteners

NASA Astrophysics Data System (ADS)

Olmstead, Jim; Barker, Paul; Vandersluis, Jonathan

2012-07-01

Tension fastened joints design has traditionally been an iterative tradeoff between separation and strength requirements. This paper presents equations for the maximum external load that a fastened joint can support and the optimal preload to achieve this load. The equations, based on linear joint theory, account for separation and strength safety factors and variations in joint geometry, materials, preload, load-plane factor and thermal loading. The strength-normalized versions of the equations are applicable to any fastener and can be plotted to create a "Fastener Design Space", FDS. Any combination of preload and tension that falls within the FDS represents a safe joint design. The equation for the FDS apex represents the optimal preload and load capacity of a set of joints. The method can be used for preliminary design or to evaluate multiple pre-existing joints.

Swing-leg trajectory of running guinea fowl suggests task-level priority of force regulation rather than disturbance rejection.

PubMed

Blum, Yvonne; Vejdani, Hamid R; Birn-Jeffery, Aleksandra V; Hubicki, Christian M; Hurst, Jonathan W; Daley, Monica A

2014-01-01

To achieve robust and stable legged locomotion in uneven terrain, animals must effectively coordinate limb swing and stance phases, which involve distinct yet coupled dynamics. Recent theoretical studies have highlighted the critical influence of swing-leg trajectory on stability, disturbance rejection, leg loading and economy of walking and running. Yet, simulations suggest that not all these factors can be simultaneously optimized. A potential trade-off arises between the optimal swing-leg trajectory for disturbance rejection (to maintain steady gait) versus regulation of leg loading (for injury avoidance and economy). Here we investigate how running guinea fowl manage this potential trade-off by comparing experimental data to predictions of hypothesis-based simulations of running over a terrain drop perturbation. We use a simple model to predict swing-leg trajectory and running dynamics. In simulations, we generate optimized swing-leg trajectories based upon specific hypotheses for task-level control priorities. We optimized swing trajectories to achieve i) constant peak force, ii) constant axial impulse, or iii) perfect disturbance rejection (steady gait) in the stance following a terrain drop. We compare simulation predictions to experimental data on guinea fowl running over a visible step down. Swing and stance dynamics of running guinea fowl closely match simulations optimized to regulate leg loading (priorities i and ii), and do not match the simulations optimized for disturbance rejection (priority iii). The simulations reinforce previous findings that swing-leg trajectory targeting disturbance rejection demands large increases in stance leg force following a terrain drop. Guinea fowl negotiate a downward step using unsteady dynamics with forward acceleration, and recover to steady gait in subsequent steps. Our results suggest that guinea fowl use swing-leg trajectory consistent with priority for load regulation, and not for steadiness of gait. Swing-leg trajectory optimized for load regulation may facilitate economy and injury avoidance in uneven terrain.

Swing-Leg Trajectory of Running Guinea Fowl Suggests Task-Level Priority of Force Regulation Rather than Disturbance Rejection

PubMed Central

Blum, Yvonne; Vejdani, Hamid R.; Birn-Jeffery, Aleksandra V.; Hubicki, Christian M.; Hurst, Jonathan W.; Daley, Monica A.

2014-01-01

To achieve robust and stable legged locomotion in uneven terrain, animals must effectively coordinate limb swing and stance phases, which involve distinct yet coupled dynamics. Recent theoretical studies have highlighted the critical influence of swing-leg trajectory on stability, disturbance rejection, leg loading and economy of walking and running. Yet, simulations suggest that not all these factors can be simultaneously optimized. A potential trade-off arises between the optimal swing-leg trajectory for disturbance rejection (to maintain steady gait) versus regulation of leg loading (for injury avoidance and economy). Here we investigate how running guinea fowl manage this potential trade-off by comparing experimental data to predictions of hypothesis-based simulations of running over a terrain drop perturbation. We use a simple model to predict swing-leg trajectory and running dynamics. In simulations, we generate optimized swing-leg trajectories based upon specific hypotheses for task-level control priorities. We optimized swing trajectories to achieve i) constant peak force, ii) constant axial impulse, or iii) perfect disturbance rejection (steady gait) in the stance following a terrain drop. We compare simulation predictions to experimental data on guinea fowl running over a visible step down. Swing and stance dynamics of running guinea fowl closely match simulations optimized to regulate leg loading (priorities i and ii), and do not match the simulations optimized for disturbance rejection (priority iii). The simulations reinforce previous findings that swing-leg trajectory targeting disturbance rejection demands large increases in stance leg force following a terrain drop. Guinea fowl negotiate a downward step using unsteady dynamics with forward acceleration, and recover to steady gait in subsequent steps. Our results suggest that guinea fowl use swing-leg trajectory consistent with priority for load regulation, and not for steadiness of gait. Swing-leg trajectory optimized for load regulation may facilitate economy and injury avoidance in uneven terrain. PMID:24979750

Optimal Control Allocation with Load Sensor Feedback for Active Load Suppression

NASA Technical Reports Server (NTRS)

Miller, Christopher

2017-01-01

These slide sets describe the OCLA formulation and associated algorithms as a set of new technologies in the first practical application of load limiting flight control utilizing load feedback as a primary control measurement. Slide set one describes Experiment Development and slide set two describes Flight-Test Performance.

7 CFR 1710.203 - Requirement to prepare a load forecast-distribution borrowers.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 11 2010-01-01 2010-01-01 false Requirement to prepare a load forecast-distribution borrowers. 1710.203 Section 1710.203 Agriculture Regulations of the Department of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE GENERAL AND PRE-LOAN POLICIES AND PROCEDURES COMMON TO ELECTRIC LOANS AND GUARANTEES Load...

7 CFR 1710.205 - Minimum approval requirements for all load forecasts.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 11 2010-01-01 2010-01-01 false Minimum approval requirements for all load forecasts. 1710.205 Section 1710.205 Agriculture Regulations of the Department of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE GENERAL AND PRE-LOAN POLICIES AND PROCEDURES COMMON TO ELECTRIC LOANS AND GUARANTEES Load Forecasts §...

Preparation and nanoencapsulation of l-asparaginase II in chitosan-tripolyphosphate nanoparticles and in vitro release study

NASA Astrophysics Data System (ADS)

Bahreini, Elham; Aghaiypour, Khosrow; Abbasalipourkabir, Roghayeh; Mokarram, Ali Rezaei; Goodarzi, Mohammad Taghi; Saidijam, Massoud

2014-07-01

This paper describes the production, purification, and immobilization of l-asparaginase II (ASNase II) in chitosan nanoparticles (CSNPs). ASNase II is an effective antineoplastic agent, used in the acute lymphoblastic leukemia chemotherapy. Cloned ASNase II gene ( ansB) in pAED4 plasmid was transformed into Escherichia coli BL21pLysS (DE3) competent cells and expressed under optimal conditions. The lyophilized enzyme was loaded into CSNPs by ionotropic gelation method. In order to get optimal entrapment efficiency, CSNP preparation, chitosan/tripolyphosphate (CS/TPP) ratio, and protein loading were investigated. ASNase II loading into CSNPs was confirmed by Fourier transform infrared (FTIR) spectroscopy, and morphological observation was carried out by transmission electron microscopy. Three absolute CS/TPP ratios were studied. Entrapment efficiency and loading capacity increased with increasing CS and TPP concentration. The best ratio was applied for obtaining optimal ASNase II-loaded CSNPs with the highest entrapment efficiency. Size, zeta potential, entrapment efficiency, and loading capacity of the optimal ASNase II-CSNPs were 340 ± 12 nm, 21.2 ± 3 mV, 76.2% and 47.6%, respectively. The immobilized enzyme showed an increased in vitro half-life in comparison with the free enzyme. The pH and thermostability of the immobilized enzyme was comparable with the free enzyme. This study leads to a better understanding of how to prepare CSNPs, how to achieve high encapsulation efficiency for a high molecular weight protein, and how to prolong the release of protein from CSNPs. A conceptual understanding of biological responses to ASNase II-loaded CSNPs is needed for the development of novel methods of drug delivery.

Optimal design of structures for earthquake loads by a hybrid RBF-BPSO method

NASA Astrophysics Data System (ADS)

Salajegheh, Eysa; Gholizadeh, Saeed; Khatibinia, Mohsen

2008-03-01

The optimal seismic design of structures requires that time history analyses (THA) be carried out repeatedly. This makes the optimal design process inefficient, in particular, if an evolutionary algorithm is used. To reduce the overall time required for structural optimization, two artificial intelligence strategies are employed. In the first strategy, radial basis function (RBF) neural networks are used to predict the time history responses of structures in the optimization flow. In the second strategy, a binary particle swarm optimization (BPSO) is used to find the optimum design. Combining the RBF and BPSO, a hybrid RBF-BPSO optimization method is proposed in this paper, which achieves fast optimization with high computational performance. Two examples are presented and compared to determine the optimal weight of structures under earthquake loadings using both exact and approximate analyses. The numerical results demonstrate the computational advantages and effectiveness of the proposed hybrid RBF-BPSO optimization method for the seismic design of structures.

Oil-Free Rotor Support Technologies for an Optimized Helicopter Propulsion System

NASA Technical Reports Server (NTRS)

DellaCorte, Christopher; Bruckner, Robert J.

2007-01-01

An optimized rotorcraft propulsion system incorporating a foil air bearing supported Oil-Free engine coupled to a high power density gearbox using high viscosity gear oil is explored. Foil air bearings have adequate load capacity and temperature capability for the highspeed gas generator shaft of a rotorcraft engine. Managing the axial loads of the power turbine shaft (low speed spool) will likely require thrust load support from the gearbox through a suitable coupling or other design. Employing specially formulated, high viscosity gear oil for the transmission can yield significant improvements (approx. 2X) in allowable gear loading. Though a completely new propulsion system design is needed to implement such a system, improved performance is possible.

Optimized undulator to generate low energy photons from medium to high energy accelerators

NASA Astrophysics Data System (ADS)

Chung, Ting-Yi; Chiu, Mau-Sen; Luo, Hao-Wen; Yang, Chin-Kang; Huang, Jui-Che; Jan, Jyh-Chyuan; Hwang, Ching-Shiang

2017-07-01

While emitting low energy photons from a medium or high energy storage ring, the on-axis heat load on the beam line optics can become a critical issue. In addition, the heat load in the bending magnet chamber, especially in the vertical and circular polarization mode of operation may cause some concern. In this work, we compare the heat loads for the APPLE-II and the Knot-APPLE, both optimized to emit 10 eV photons from the 3 GeV TPS. Under this constraint the heat load analysis, synchrotron radiation performance and features in various polarization modes are presented. Additional consideration is given to beam dynamics effect.

Multiple models guide strategies for agricultural nutrient reductions

USGS Publications Warehouse

Scavia, Donald; Kalcic, Margaret; Muenich, Rebecca Logsdon; Read, Jennifer; Aloysius, Noel; Bertani, Isabella; Boles, Chelsie; Confesor, Remegio; DePinto, Joseph; Gildow, Marie; Martin, Jay; Redder, Todd; Robertson, Dale M.; Sowa, Scott P.; Wang, Yu-Chen; Yen, Haw

2017-01-01

In response to degraded water quality, federal policy makers in the US and Canada called for a 40% reduction in phosphorus (P) loads to Lake Erie, and state and provincial policy makers in the Great Lakes region set a load-reduction target for the year 2025. Here, we configured five separate SWAT (US Department of Agriculture's Soil and Water Assessment Tool) models to assess load reduction strategies for the agriculturally dominated Maumee River watershed, the largest P source contributing to toxic algal blooms in Lake Erie. Although several potential pathways may achieve the target loads, our results show that any successful pathway will require large-scale implementation of multiple practices. For example, one successful pathway involved targeting 50% of row cropland that has the highest P loss in the watershed with a combination of three practices: subsurface application of P fertilizers, planting cereal rye as a winter cover crop, and installing buffer strips. Achieving these levels of implementation will require local, state/provincial, and federal agencies to collaborate with the private sector to set shared implementation goals and to demand innovation and honest assessments of water quality-related programs, policies, and partnerships.

Impact of nitrogen deposition at the species level.

PubMed

Payne, Richard J; Dise, Nancy B; Stevens, Carly J; Gowing, David J

2013-01-15

In Europe and, increasingly, the rest of the world, the key policy tool for the control of air pollution is the critical load, a level of pollution below which there are no known significant harmful effects on the environment. Critical loads are used to map sensitive regions and habitats, permit individual polluting activities, and frame international negotiations on transboundary air pollution. Despite their fundamental importance in environmental science and policy, there has been no systematic attempt to verify a critical load with field survey data. Here, we use a large dataset of European grasslands along a gradient of nitrogen (N) deposition to show statistically significant declines in the abundance of species from the lowest level of N deposition at which it is possible to identify a change. Approximately 60% of species change points occur at or below the range of the currently established critical load. If this result is found more widely, the underlying principle of no harm in pollution policy may need to be modified to one of informed decisions on how much harm is acceptable. Our results highlight the importance of protecting currently unpolluted areas from new pollution sources, because we cannot rule out ecological impacts from even relatively small increases in reactive N deposition.

Predictive Scheduling for Electric Vehicles Considering Uncertainty of Load and User Behaviors

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

Wang, Bin; Huang, Rui; Wang, Yubo

2016-05-02

Un-coordinated Electric Vehicle (EV) charging can create unexpected load in local distribution grid, which may degrade the power quality and system reliability. The uncertainty of EV load, user behaviors and other baseload in distribution grid, is one of challenges that impedes optimal control for EV charging problem. Previous researches did not fully solve this problem due to lack of real-world EV charging data and proper stochastic model to describe these behaviors. In this paper, we propose a new predictive EV scheduling algorithm (PESA) inspired by Model Predictive Control (MPC), which includes a dynamic load estimation module and a predictive optimizationmore » module. The user-related EV load and base load are dynamically estimated based on the historical data. At each time interval, the predictive optimization program will be computed for optimal schedules given the estimated parameters. Only the first element from the algorithm outputs will be implemented according to MPC paradigm. Current-multiplexing function in each Electric Vehicle Supply Equipment (EVSE) is considered and accordingly a virtual load is modeled to handle the uncertainties of future EV energy demands. This system is validated by the real-world EV charging data collected on UCLA campus and the experimental results indicate that our proposed model not only reduces load variation up to 40% but also maintains a high level of robustness. Finally, IEC 61850 standard is utilized to standardize the data models involved, which brings significance to more reliable and large-scale implementation.« less

A Paradigm for the Development and Evaluation of Novel Implant Topologies for Bone Fixation: In Vivo Evaluation

PubMed Central

Long, Jason P.; Hollister, Scott J.; Goldstein, Steven A.

2012-01-01

While contemporary prosthetic devices restore some function to individuals who have lost a limb, there are efforts to develop bio-integrated prostheses to improve functionality. A critical step in advancing this technology will be to securely attach the device to remnant bone. To investigate mechanisms for establishing robust implant fixation in bone while undergoing loading, we previously used a topology optimization scheme to develop optimized orthopaedic implants and then fabricated selected designs from titanium (Ti)-alloy with selective laser sintering (SLS) technology. In the present study, we examined how implant architecture and mechanical stimulation influence osseointegration within an in vivo environment. To do this, we evaluated three implant designs (two optimized and one non-optimized) using a unique in vivo model that applied cyclic, tension/ compression loads to the implants. Eighteen (six per implant design) adult male canines had implants surgically placed in their proximal, tibial metaphyses. Experimental duration was 12 weeks; daily loading (peak load of ±22N for 1000 cycles) was applied to one of each animal’s bilateral implants for the latter six weeks. Following harvest, osseointegration was assessed by non-destructive mechanical testing, micro-computed tomography (microCT) and back-scatter scanning electron microscopy (SEM). Data revealed that implant loading enhanced osseointegration by significantly increasing construct stiffness, peri-implant trabecular morphology, and percentages of interface connectivity and bone ingrowth. While this experiment did not demonstrate a clear advantage associated with the optimized implant designs, osseointegration was found to be significantly influenced by aspects of implant architecture. PMID:22951278

A paradigm for the development and evaluation of novel implant topologies for bone fixation: in vivo evaluation.

PubMed

Long, Jason P; Hollister, Scott J; Goldstein, Steven A

2012-10-11

While contemporary prosthetic devices restore some function to individuals who have lost a limb, there are efforts to develop bio-integrated prostheses to improve functionality. A critical step in advancing this technology will be to securely attach the device to remnant bone. To investigate mechanisms for establishing robust implant fixation in bone while undergoing loading, we previously used a topology optimization scheme to develop optimized orthopedic implants and then fabricated selected designs from titanium (Ti)-alloy with selective laser sintering (SLS) technology. In the present study, we examined how implant architecture and mechanical stimulation influence osseointegration within an in vivo environment. To do this, we evaluated three implant designs (two optimized and one non-optimized) using a unique in vivo model that applied cyclic, tension/compression loads to the implants. Eighteen (six per implant design) adult male canines had implants surgically placed in their proximal, tibial metaphyses. Experimental duration was 12 weeks; daily loading (peak load of ±22 N for 1000 cycles) was applied to one of each animal's bilateral implants for the latter six weeks. Following harvest, osseointegration was assessed by non-destructive mechanical testing, micro-computed tomography (microCT) and back-scatter scanning electron microscopy (SEM). Data revealed that implant loading enhanced osseointegration by significantly increasing construct stiffness, peri-implant trabecular morphology, and percentages of interface connectivity and bone ingrowth. While this experiment did not demonstrate a clear advantage associated with the optimized implant designs, osseointegration was found to be significantly influenced by aspects of implant architecture. Copyright © 2012 Elsevier Ltd. All rights reserved.

Optimal Decentralized Protocol for Electric Vehicle Charging

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

Gan, LW; Topcu, U; Low, SH

We propose a decentralized algorithm to optimally schedule electric vehicle (EV) charging. The algorithm exploits the elasticity of electric vehicle loads to fill the valleys in electric load profiles. We first formulate the EV charging scheduling problem as an optimal control problem, whose objective is to impose a generalized notion of valley-filling, and study properties of optimal charging profiles. We then give a decentralized algorithm to iteratively solve the optimal control problem. In each iteration, EVs update their charging profiles according to the control signal broadcast by the utility company, and the utility company alters the control signal to guidemore » their updates. The algorithm converges to optimal charging profiles (that are as "flat" as they can possibly be) irrespective of the specifications (e.g., maximum charging rate and deadline) of EVs, even if EVs do not necessarily update their charging profiles in every iteration, and use potentially outdated control signal when they update. Moreover, the algorithm only requires each EV solving its local problem, hence its implementation requires low computation capability. We also extend the algorithm to track a given load profile and to real-time implementation.« less

Concurrent topology optimization for minimization of total mass considering load-carrying capabilities and thermal insulation simultaneously

NASA Astrophysics Data System (ADS)

Long, Kai; Wang, Xuan; Gu, Xianguang

2017-09-01

The present work introduces a novel concurrent optimization formulation to meet the requirements of lightweight design and various constraints simultaneously. Nodal displacement of macrostructure and effective thermal conductivity of microstructure are regarded as the constraint functions, which means taking into account both the load-carrying capabilities and the thermal insulation properties. The effective properties of porous material derived from numerical homogenization are used for macrostructural analysis. Meanwhile, displacement vectors of macrostructures from original and adjoint load cases are used for sensitivity analysis of the microstructure. Design variables in the form of reciprocal functions of relative densities are introduced and used for linearization of the constraint function. The objective function of total mass is approximately expressed by the second order Taylor series expansion. Then, the proposed concurrent optimization problem is solved using a sequential quadratic programming algorithm, by splitting into a series of sub-problems in the form of the quadratic program. Finally, several numerical examples are presented to validate the effectiveness of the proposed optimization method. The various effects including initial designs, prescribed limits of nodal displacement, and effective thermal conductivity on optimized designs are also investigated. An amount of optimized macrostructures and their corresponding microstructures are achieved.

Optimization and modeling of the remote loading of luciferin into liposomes.

PubMed

Hansen, Anders Højgaard; Lomholt, Michael A; Hansen, Per Lyngs; Mouritsen, Ole G; Arouri, Ahmad

2016-07-11

We carried out a mechanistic study to characterize and optimize the remote loading of luciferin into preformed liposomes of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine/1,2-dipalmitoyl-sn-glycero-3-phosphoglycerol (DPPC/DPPG) 7:3 mixtures. The influence of the loading agent (acetate, propionate, butyrate), the metal counterion (Na(+), K(+), Ca(+2), Mg(+2)), and the initial extra-liposomal amount of luciferin (nL(add)) on the luciferin Loading Efficiency (LE%) and luciferin-to-lipid weight ratio, i.e., Loading Capacity (LC), in the final formulation was determined. In addition, the effect of the loading process on the colloidal stability and phase behavior of the liposomes was monitored. Based on our experimental results, a theoretical model was developed to describe the course of luciferin remote loading. It was found that the highest luciferin loading was obtained with magnesium acetate. The use of longer aliphatic carboxylates or inorganic proton donors pronouncedly reduced luciferin loading, whereas the effect of the counterion was modest. The remote-loading process barely affected the colloidal stability and drug retention of the liposomes, albeit with moderate luciferin-induced membrane perturbations. The correlation between luciferin loading, expressed as LE% and LC, and nL(add) was established, and under our conditions the maximum LC was attained using an nL(add) of around 2.6μmol. Higher amounts of luciferin tend to pronouncedly perturb the liposome stability and luciferin retention. Our theoretical model furnishes a fair quantitative description of the correlation between nL(add) and luciferin loading, and a membrane permeability coefficient for uncharged luciferin of 1×10(-8)cm/s could be determined. We believe that our study will prove very useful to optimize the remote-loading strategies of moderately polar carboxylic acid drugs in general. Copyright © 2016 Elsevier B.V. All rights reserved.

Reconciling Consumer and Utility Objectives in the Residential Solar PV Market

NASA Astrophysics Data System (ADS)

Arnold, Michael R.

Today's energy market is facing large-scale changes that will affect all market players. Near the top of that list is the rapid deployment of residential solar photovoltaic (PV) systems. Yet that growing trend will be influenced multiple competing interests between various stakeholders, namely the utility, consumers and technology provides. This study provides a series of analyses---utility-side, consumer-side, and combined analyses---to understand and evaluate the effect of increases in residential solar PV market penetration. Three urban regions have been selected as study locations---Chicago, Phoenix, Seattle---with simulated load data and solar insolation data at each locality. Various time-of-use pricing schedules are investigated, and the effect of net metering is evaluated to determine the optimal capacity of solar PV and battery storage in a typical residential home. The net residential load profile is scaled to assess system-wide technical and economic figures of merit for the utility with an emphasis on intraday load profiles, ramp rates and electricity sales with increasing solar PV penetration. The combined analysis evaluates the least-cost solar PV system for the consumer and models the associated system-wide effects on the electric grid. Utility revenue was found to drop by 1.2% for every percent PV penetration increase, net metering on a monthly or annual basis improved the cost-effectiveness of solar PV but not battery storage, the removal of net metering policy and usage of an improved the cost-effectiveness of battery storage and increases in solar PV penetration reduced the system load factor. As expected, Phoenix had the most favorable economic scenario for residential solar PV, primarily due to high solar insolation. The study location---solar insolation and load profile---was also found to affect the time of year at which the largest net negative system load was realized.

Electric Grid Expansion Planning with High Levels of Variable Generation

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

Hadley, Stanton W.; You, Shutang; Shankar, Mallikarjun

2016-02-01

Renewables are taking a large proportion of generation capacity in U.S. power grids. As their randomness has increasing influence on power system operation, it is necessary to consider their impact on system expansion planning. To this end, this project studies the generation and transmission expansion co-optimization problem of the US Eastern Interconnection (EI) power grid with a high wind power penetration rate. In this project, the generation and transmission expansion problem for the EI system is modeled as a mixed-integer programming (MIP) problem. This study analyzed a time series creation method to capture the diversity of load and wind powermore » across balancing regions in the EI system. The obtained time series can be easily introduced into the MIP co-optimization problem and then solved robustly through available MIP solvers. Simulation results show that the proposed time series generation method and the expansion co-optimization model and can improve the expansion result significantly after considering the diversity of wind and load across EI regions. The improved expansion plan that combines generation and transmission will aid system planners and policy makers to maximize the social welfare. This study shows that modelling load and wind variations and diversities across balancing regions will produce significantly different expansion result compared with former studies. For example, if wind is modeled in more details (by increasing the number of wind output levels) so that more wind blocks are considered in expansion planning, transmission expansion will be larger and the expansion timing will be earlier. Regarding generation expansion, more wind scenarios will slightly reduce wind generation expansion in the EI system and increase the expansion of other generation such as gas. Also, adopting detailed wind scenarios will reveal that it may be uneconomic to expand transmission networks for transmitting a large amount of wind power through a long distance in the EI system. Incorporating more details of renewables in expansion planning will inevitably increase the computational burden. Therefore, high performance computing (HPC) techniques are urgently needed for power system operation and planning optimization. As a scoping study task, this project tested some preliminary parallel computation techniques such as breaking down the simulation task into several sub-tasks based on chronology splitting or sample splitting, and then assigning these sub-tasks to different cores. Testing results show significant time reduction when a simulation task is split into several sub-tasks for parallel execution.« less

Deterministic methods for multi-control fuel loading optimization

NASA Astrophysics Data System (ADS)

Rahman, Fariz B. Abdul

We have developed a multi-control fuel loading optimization code for pressurized water reactors based on deterministic methods. The objective is to flatten the fuel burnup profile, which maximizes overall energy production. The optimal control problem is formulated using the method of Lagrange multipliers and the direct adjoining approach for treatment of the inequality power peaking constraint. The optimality conditions are derived for a multi-dimensional multi-group optimal control problem via calculus of variations. Due to the Hamiltonian having a linear control, our optimal control problem is solved using the gradient method to minimize the Hamiltonian and a Newton step formulation to obtain the optimal control. We are able to satisfy the power peaking constraint during depletion with the control at beginning of cycle (BOC) by building the proper burnup path forward in time and utilizing the adjoint burnup to propagate the information back to the BOC. Our test results show that we are able to achieve our objective and satisfy the power peaking constraint during depletion using either the fissile enrichment or burnable poison as the control. Our fuel loading designs show an increase of 7.8 equivalent full power days (EFPDs) in cycle length compared with 517.4 EFPDs for the AP600 first cycle.

Implications of Preference and Problem Formulation on the Operating Policies of Complex Multi-Reservoir Systems

NASA Astrophysics Data System (ADS)

Quinn, J.; Reed, P. M.; Giuliani, M.; Castelletti, A.

2016-12-01

Optimizing the operations of multi-reservoir systems poses several challenges: 1) the high dimension of the problem's states and controls, 2) the need to balance conflicting multi-sector objectives, and 3) understanding how uncertainties impact system performance. These difficulties motivated the development of the Evolutionary Multi-Objective Direct Policy Search (EMODPS) framework, in which multi-reservoir operating policies are parameterized in a given family of functions and then optimized for multiple objectives through simulation over a set of stochastic inputs. However, properly framing these objectives remains a severe challenge and a neglected source of uncertainty. Here, we use EMODPS to optimize operating policies for a 4-reservoir system in the Red River Basin in Vietnam, exploring the consequences of optimizing to different sets of objectives related to 1) hydropower production, 2) meeting multi-sector water demands, and 3) providing flood protection to the capital city of Hanoi. We show how coordinated operation of the reservoirs can differ markedly depending on how decision makers weigh these concerns. Moreover, we illustrate how formulation choices that emphasize the mean, tail, or variability of performance across objective combinations must be evaluated carefully. Our results show that these choices can significantly improve attainable system performance, or yield severe unintended consequences. Finally, we show that satisfactory validation of the operating policies on a set of out-of-sample stochastic inputs depends as much or more on the formulation of the objectives as on effective optimization of the policies. These observations highlight the importance of carefully considering how we abstract stakeholders' objectives and of iteratively optimizing and visualizing multiple problem formulation hypotheses to ensure that we capture the most important tradeoffs that emerge from different stakeholder preferences.

Generalized networking engineering: optimal pricing and routing in multiservice networks

NASA Astrophysics Data System (ADS)

Mitra, Debasis; Wang, Qiong

2002-07-01

One of the functions of network engineering is to allocate resources optimally to forecasted demand. We generalize the mechanism by incorporating price-demand relationships into the problem formulation, and optimizing pricing and routing jointly to maximize total revenue. We consider a network, with fixed topology and link bandwidths, that offers multiple services, such as voice and data, each having characteristic price elasticity of demand, and quality of service and policy requirements on routing. Prices, which depend on service type and origin-destination, determine demands, that are routed, subject to their constraints, so as to maximize revenue. We study the basic properties of the optimal solution and prove that link shadow costs provide the basis for both optimal prices and optimal routing policies. We investigate the impact of input parameters, such as link capacities and price elasticities, on prices, demand growth, and routing policies. Asymptotic analyses, in which network bandwidth is scaled to grow, give results that are noteworthy for their qualitative insights. Several numerical examples illustrate the analyses.

Pavement maintenance optimization model using Markov Decision Processes

NASA Astrophysics Data System (ADS)

Mandiartha, P.; Duffield, C. F.; Razelan, I. S. b. M.; Ismail, A. b. H.

2017-09-01

This paper presents an optimization model for selection of pavement maintenance intervention using a theory of Markov Decision Processes (MDP). There are some particular characteristics of the MDP developed in this paper which distinguish it from other similar studies or optimization models intended for pavement maintenance policy development. These unique characteristics include a direct inclusion of constraints into the formulation of MDP, the use of an average cost method of MDP, and the policy development process based on the dual linear programming solution. The limited information or discussions that are available on these matters in terms of stochastic based optimization model in road network management motivates this study. This paper uses a data set acquired from road authorities of state of Victoria, Australia, to test the model and recommends steps in the computation of MDP based stochastic optimization model, leading to the development of optimum pavement maintenance policy.

System, apparatus and methods to implement high-speed network analyzers

DOEpatents

Ezick, James; Lethin, Richard; Ros-Giralt, Jordi; Szilagyi, Peter; Wohlford, David E

2015-11-10

Systems, apparatus and methods for the implementation of high-speed network analyzers are provided. A set of high-level specifications is used to define the behavior of the network analyzer emitted by a compiler. An optimized inline workflow to process regular expressions is presented without sacrificing the semantic capabilities of the processing engine. An optimized packet dispatcher implements a subset of the functions implemented by the network analyzer, providing a fast and slow path workflow used to accelerate specific processing units. Such dispatcher facility can also be used as a cache of policies, wherein if a policy is found, then packet manipulations associated with the policy can be quickly performed. An optimized method of generating DFA specifications for network signatures is also presented. The method accepts several optimization criteria, such as min-max allocations or optimal allocations based on the probability of occurrence of each signature input bit.

Real-time information management environment (RIME)

NASA Astrophysics Data System (ADS)

DeCleene, Brian T.; Griffin, Sean; Matchett, Garry; Niejadlik, Richard

2000-08-01

Whereas data mining and exploitation improve the quality and quantity of information available to the user, there remains a mission requirement to assist the end-user in managing the access to this information and ensuring that the appropriate information is delivered to the right user in time to make decisions and take action. This paper discusses TASC's federated architecture to next- generation information management, contrasts the approach against emerging technologies, and quantifies the performance gains. This architecture and implementation, known as Real-time Information Management Environment (RIME), is based on two key concepts: information utility and content-based channelization. The introduction of utility allows users to express the importance and delivery requirements of their information needs in the context of their mission. Rather than competing for resources on a first-come/first-served basis, the infrastructure employs these utility functions to dynamically react to unanticipated loading by optimizing the delivered information utility. Furthermore, commander's resource policies shape these functions to ensure that resources are allocated according to military doctrine. Using information about the desired content, channelization identifies opportunities to aggregate users onto shared channels reducing redundant transmissions. Hence, channelization increases the information throughput of the system and balances sender/receiver processing load.

Optimality study of a gust alleviation system for light wing-loading STOL aircraft

NASA Technical Reports Server (NTRS)

Komoda, M.

1976-01-01

An analytical study was made of an optimal gust alleviation system that employs a vertical gust sensor mounted forward of an aircraft's center of gravity. Frequency domain optimization techniques were employed to synthesize the optimal filters that process the corrective signals to the flaps and elevator actuators. Special attention was given to evaluating the effectiveness of lead time, that is, the time by which relative wind sensor information should lead the actual encounter of the gust. The resulting filter is expressed as an implicit function of the prescribed control cost. A numerical example for a light wing loading STOL aircraft is included in which the optimal trade-off between performance and control cost is systematically studied.

Gear optimization

NASA Technical Reports Server (NTRS)

Vanderplaats, G. N.; Chen, Xiang; Zhang, Ning-Tian

1988-01-01

The use of formal numerical optimization methods for the design of gears is investigated. To achieve this, computer codes were developed for the analysis of spur gears and spiral bevel gears. These codes calculate the life, dynamic load, bending strength, surface durability, gear weight and size, and various geometric parameters. It is necessary to calculate all such important responses because they all represent competing requirements in the design process. The codes developed here were written in subroutine form and coupled to the COPES/ADS general purpose optimization program. This code allows the user to define the optimization problem at the time of program execution. Typical design variables include face width, number of teeth and diametral pitch. The user is free to choose any calculated response as the design objective to minimize or maximize and may impose lower and upper bounds on any calculated responses. Typical examples include life maximization with limits on dynamic load, stress, weight, etc. or minimization of weight subject to limits on life, dynamic load, etc. The research codes were written in modular form for easy expansion and so that they could be combined to create a multiple reduction optimization capability in future.

Optimizing Prednisolone Loading into Distiller's Dried Grain Kafirin Microparticles, and In vitro Release for Oral Delivery.

PubMed

Lau, Esther T L; Johnson, Stuart K; Williams, Barbara A; Mikkelsen, Deirdre; McCourt, Elizabeth; Stanley, Roger A; Mereddy, Ram; Halley, Peter J; Steadman, Kathryn J

2017-05-19

Kafirin microparticles have potential as colon-targeted delivery systems because of their ability to protect encapsulated material from digestive processes of the upper gastrointestinal tract (GIT). The aim was to optimize prednisolone loading into kafirin microparticles, and investigate their potential as an oral delivery system. Response surface methodology (RSM) was used to predict the optimal formulation of prednisolone loaded microparticles. Prednisolone release from the microparticles was measured in simulated conditions of the GIT. The RSM models were inadequate for predicting the relationship between starting quantities of kafirin and prednisolone, and prednisolone loading into microparticles. Compared to prednisolone released in the simulated gastric and small intestinal conditions, no additional drug release was observed in simulated colonic conditions. Hence, more insight into factors affecting drug loading into kafirin microparticles is required to improve the robustness of the RSM model. This present method of formulating prednisolone-loaded kafirin microparticles is unlikely to offer clinical benefits over commercially available dosage forms. Nevertheless, the overall amount of prednisolone released from the kafirin microparticles in conditions simulating the human GIT demonstrates their ability to prevent the release of entrapped core material. Further work developing the formulation methods may result in a delivery system that targets the lower GIT.

Predicting the Effects of Powder Feeding Rates on Particle Impact Conditions and Cold Spray Deposited Coatings

NASA Astrophysics Data System (ADS)

Ozdemir, Ozan C.; Widener, Christian A.; Carter, Michael J.; Johnson, Kyle W.

2017-10-01

As the industrial application of the cold spray technology grows, the need to optimize both the cost and the quality of the process grows with it. Parameter selection techniques available today require the use of a coupled system of equations to be solved to involve the losses due to particle loading in the gas stream. Such analyses cause a significant increase in the computational time in comparison with calculations with isentropic flow assumptions. In cold spray operations, engineers and operators may, therefore, neglect the effects of particle loading to simplify the multiparameter optimization process. In this study, two-way coupled (particle-fluid) quasi-one-dimensional fluid dynamics simulations are used to test the particle loading effects under many potential cold spray scenarios. Output of the simulations is statistically analyzed to build regression models that estimate the changes in particle impact velocity and temperature due to particle loading. This approach eases particle loading optimization for more complete analysis on deposition cost and time. The model was validated both numerically and experimentally. Further numerical analyses were completed to test the particle loading capacity and limitations of a nozzle with a commonly used throat size. Additional experimentation helped document the physical limitations to high-rate deposition.

Continuum topology optimization considering uncertainties in load locations based on the cloud model

NASA Astrophysics Data System (ADS)

Liu, Jie; Wen, Guilin

2018-06-01

Few researchers have paid attention to designing structures in consideration of uncertainties in the loading locations, which may significantly influence the structural performance. In this work, cloud models are employed to depict the uncertainties in the loading locations. A robust algorithm is developed in the context of minimizing the expectation of the structural compliance, while conforming to a material volume constraint. To guarantee optimal solutions, sufficient cloud drops are used, which in turn leads to low efficiency. An innovative strategy is then implemented to enormously improve the computational efficiency. A modified soft-kill bi-directional evolutionary structural optimization method using derived sensitivity numbers is used to output the robust novel configurations. Several numerical examples are presented to demonstrate the effectiveness and efficiency of the proposed algorithm.

Mechanical and hydraulic properties of sludge deposit on sludge drying reed beds (SDRBs): influence of sludge characteristics and loading rates.

PubMed

Vincent, Julie; Forquet, Nicolas; Molle, Pascal; Wisniewski, Christelle

2012-07-01

This work was designed to study the hydraulic properties of sludge deposit, focusing on the impact of operating conditions (i.e. loads and feeding frequencies) on air entrance (aerobic mineralization optimization) into the sludge deposit. The studied sludge deposits came from six 2m(2) pilot-scale SDRBs that had been in operation for 50 months with three different loads of 30, 50, and 70 kg of SSm(-2) y(-1). Two influents were assessed (i.e. activated sludge and septage) presenting different characteristics (i.e. pollutant contents, physical properties...). Two experimental approaches were employed based on establishing the water retention curve (capillary pressure versus volumetric water content) and the hydrotextural diagram to determine the hydraulic properties of sludge deposit. The study obtained valuable information for optimizing operating conditions, specifically for efficient management of loading frequency to optimize aerobic conditions within the sludge deposit. Copyright © 2012 Elsevier Ltd. All rights reserved.

Optimal Operation Method of Smart House by Controllable Loads based on Smart Grid Topology

NASA Astrophysics Data System (ADS)

Yoza, Akihiro; Uchida, Kosuke; Yona, Atsushi; Senju, Tomonobu

2013-08-01

From the perspective of global warming suppression and depletion of energy resources, renewable energy such as wind generation (WG) and photovoltaic generation (PV) are getting attention in distribution systems. Additionally, all electrification apartment house or residence such as DC smart house have increased in recent years. However, due to fluctuating power from renewable energy sources and loads, supply-demand balancing fluctuations of power system become problematic. Therefore, "smart grid" has become very popular in the worldwide. This article presents a methodology for optimal operation of a smart grid to minimize the interconnection point power flow fluctuations. To achieve the proposed optimal operation, we use distributed controllable loads such as battery and heat pump. By minimizing the interconnection point power flow fluctuations, it is possible to reduce the maximum electric power consumption and the electric cost. This system consists of photovoltaics generator, heat pump, battery, solar collector, and load. In order to verify the effectiveness of the proposed system, MATLAB is used in simulations.

Coupled Multi-Disciplinary Optimization for Structural Reliability and Affordability

NASA Technical Reports Server (NTRS)

Abumeri, Galib H.; Chamis, Christos C.

2003-01-01

A computational simulation method is presented for Non-Deterministic Multidisciplinary Optimization of engine composite materials and structures. A hypothetical engine duct made with ceramic matrix composites (CMC) is evaluated probabilistically in the presence of combined thermo-mechanical loading. The structure is tailored by quantifying the uncertainties in all relevant design variables such as fabrication, material, and loading parameters. The probabilistic sensitivities are used to select critical design variables for optimization. In this paper, two approaches for non-deterministic optimization are presented. The non-deterministic minimization of combined failure stress criterion is carried out by: (1) performing probabilistic evaluation first and then optimization and (2) performing optimization first and then probabilistic evaluation. The first approach shows that the optimization feasible region can be bounded by a set of prescribed probability limits and that the optimization follows the cumulative distribution function between those limits. The second approach shows that the optimization feasible region is bounded by 0.50 and 0.999 probabilities.

Algorithm and Software for Calculating Optimal Regimes of the Process Water Supply System at the Kalininskaya NPP{sup 1}

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

Murav’ev, V. P., E-mail: murval@mail.ru; Kochetkov, A. V.; Glazova, E. G.

An algorithm and software for calculating the optimal operating regimes of the process water supply system at the Kalininskaya NPP are described. The parameters of the optimal regimes are determined for time varying meteorological conditions and condensation loads of the NPP. The optimal flow of the cooling water in the turbines is determined computationally; a regime map with the data on the optimal water consumption distribution between the coolers and displaying the regimes with an admissible heat load on the natural cooling lakes is composed. Optimizing the cooling system for a 4000-MW NPP will make it possible to conserve atmore » least 155,000 MW · h of electricity per year. The procedure developed can be used to optimize the process water supply systems of nuclear and thermal power plants.« less

Evaluation of load flow and grid expansion in a unit-commitment and expansion optimization model SciGRID International Conference on Power Grid Modelling

NASA Astrophysics Data System (ADS)

Senkpiel, Charlotte; Biener, Wolfgang; Shammugam, Shivenes; Längle, Sven

2018-02-01

Energy system models serve as a basis for long term system planning. Joint optimization of electricity generating technologies, storage systems and the electricity grid leads to lower total system cost compared to an approach in which the grid expansion follows a given technology portfolio and their distribution. Modelers often face the problem of finding a good tradeoff between computational time and the level of detail that can be modeled. This paper analyses the differences between a transport model and a DC load flow model to evaluate the validity of using a simple but faster transport model within the system optimization model in terms of system reliability. The main findings in this paper are that a higher regional resolution of a system leads to better results compared to an approach in which regions are clustered as more overloads can be detected. An aggregation of lines between two model regions compared to a line sharp representation has little influence on grid expansion within a system optimizer. In a DC load flow model overloads can be detected in a line sharp case, which is therefore preferred. Overall the regions that need to reinforce the grid are identified within the system optimizer. Finally the paper recommends the usage of a load-flow model to test the validity of the model results.

Design of piezoelectric transformer for DC/DC converter with stochastic optimization method

NASA Astrophysics Data System (ADS)

Vasic, Dejan; Vido, Lionel

2016-04-01

Piezoelectric transformers were adopted in recent year due to their many inherent advantages such as safety, no EMI problem, low housing profile, and high power density, etc. The characteristics of the piezoelectric transformers are well known when the load impedance is a pure resistor. However, when piezoelectric transformers are used in AC/DC or DC/DC converters, there are non-linear electronic circuits connected before and after the transformer. Consequently, the output load is variable and due to the output capacitance of the transformer the optimal working point change. This paper starts from modeling a piezoelectric transformer connected to a full wave rectifier in order to discuss the design constraints and configuration of the transformer. The optimization method adopted here use the MOPSO algorithm (Multiple Objective Particle Swarm Optimization). We start with the formulation of the objective function and constraints; then the results give different sizes of the transformer and the characteristics. In other word, this method is looking for a best size of the transformer for optimal efficiency condition that is suitable for variable load. Furthermore, the size and the efficiency are found to be a trade-off. This paper proposes the completed design procedure to find the minimum size of PT in need. The completed design procedure is discussed by a given specification. The PT derived from the proposed design procedure can guarantee both good efficiency and enough range for load variation.

Using an artificial neural network to predict the optimal conditions for enzymatic hydrolysis of apple pomace.

PubMed

Gama, Repson; Van Dyk, J Susan; Burton, Mike H; Pletschke, Brett I

2017-06-01

The enzymatic degradation of lignocellulosic biomass such as apple pomace is a complex process influenced by a number of hydrolysis conditions. Predicting optimal conditions, including enzyme and substrate concentration, temperature and pH can improve conversion efficiency. In this study, the production of sugar monomers from apple pomace using commercial enzyme preparations, Celluclast 1.5L, Viscozyme L and Novozyme 188 was investigated. A limited number of experiments were carried out and then analysed using an artificial neural network (ANN) to model the enzymatic hydrolysis process. The ANN was used to simulate the enzymatic hydrolysis process for a range of input variables and the optimal conditions were successfully selected as was indicated by the R 2 value of 0.99 and a small MSE value. The inputs for the ANN were substrate loading, enzyme loading, temperature, initial pH and a combination of these parameters, while release profiles of glucose and reducing sugars were the outputs. Enzyme loadings of 0.5 and 0.2 mg/g substrate and a substrate loading of 30% were optimal for glucose and reducing sugar release from apple pomace, respectively, resulting in concentrations of 6.5 g/L glucose and 28.9 g/L reducing sugars. Apple pomace hydrolysis can be successfully carried out based on the predicted optimal conditions from the ANN.

Model-Based Dead Time Optimization for Voltage-Source Converters Utilizing Silicon Carbide Semiconductors

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

Zhang, Zheyu; Lu, Haifeng; Costinett, Daniel J.

Dead time significantly affects the reliability, power quality, and efficiency of voltage-source converters. For silicon carbide (SiC) devices, considering the high sensitivity of turn-off time to the operating conditions (> 5× difference between light load and full load) and characteristics of inductive loads (> 2× difference between motor load and inductor), as well as large additional energy loss induced by the freewheeling diode conduction during the superfluous dead time (~15% of the switching loss), then the traditional fixed dead time setting becomes inappropriate. This paper introduces an approach to adaptively regulate the dead time considering the current operating condition andmore » load characteristics via synthesizing online monitored turn-off switching parameters in the microcontroller with an embedded preset optimization model. Here, based on a buck converter built with 1200-V SiC MOSFETs, the experimental results show that the proposed method is able to ensure reliability and reduce power loss by 12% at full load and 18.2% at light load (8% of the full load in this case study).« less

Model-Based Dead Time Optimization for Voltage-Source Converters Utilizing Silicon Carbide Semiconductors

DOE PAGES

Zhang, Zheyu; Lu, Haifeng; Costinett, Daniel J.; ...

2016-12-29

Dead time significantly affects the reliability, power quality, and efficiency of voltage-source converters. For silicon carbide (SiC) devices, considering the high sensitivity of turn-off time to the operating conditions (> 5× difference between light load and full load) and characteristics of inductive loads (> 2× difference between motor load and inductor), as well as large additional energy loss induced by the freewheeling diode conduction during the superfluous dead time (~15% of the switching loss), then the traditional fixed dead time setting becomes inappropriate. This paper introduces an approach to adaptively regulate the dead time considering the current operating condition andmore » load characteristics via synthesizing online monitored turn-off switching parameters in the microcontroller with an embedded preset optimization model. Here, based on a buck converter built with 1200-V SiC MOSFETs, the experimental results show that the proposed method is able to ensure reliability and reduce power loss by 12% at full load and 18.2% at light load (8% of the full load in this case study).« less

Studies of The Durability of Belt Conveyor Idlers with Working Loads Taken into Account

NASA Astrophysics Data System (ADS)

Król, Robert

2017-12-01

The results of laboratory and operational studies conducted in the Machinery Systems Division of Wroclaw University of Technology in recent years have became the basis for selecting proper belt conveyor roller designs optimized for specific strength and operational criteria. The usefulness of the results for assessing the energy intensity of idlers, estimating their durability and determining modernization policies has been confirmed. Methods of estimating the durability of carrying idlers on the basis of the identified output stream distributions are presented. Results of studies carried out using an analytical method and a laboratory method are reported. It has been shown that the operational durability of a roller is determined by its design, the roller set parameters (the spacing and the angle of bevel) and the operating conditions having a bearing on the irregularity of the transported output stream.

Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.

PubMed

Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L

2017-10-01

The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed Q -function sequence converges to the optimal Q -function. Based on the PGADP algorithm, the adaptive control method is developed with an actor-critic structure and the method of weighted residuals. Its convergence properties are analyzed, where the approximate Q -function converges to its optimum. Computer simulation results demonstrate the effectiveness of the PGADP-based adaptive control method.

Robust optimal control of material flows in demand-driven supply networks

NASA Astrophysics Data System (ADS)

Laumanns, Marco; Lefeber, Erjen

2006-04-01

We develop a model based on stochastic discrete-time controlled dynamical systems in order to derive optimal policies for controlling the material flow in supply networks. Each node in the network is described as a transducer such that the dynamics of the material and information flows within the entire network can be expressed by a system of first-order difference equations, where some inputs to the system act as external disturbances. We apply methods from constrained robust optimal control to compute the explicit control law as a function of the current state. For the numerical examples considered, these control laws correspond to certain classes of optimal ordering policies from inventory management while avoiding, however, any a priori assumptions about the general form of the policy.

7 CFR 1710.202 - Requirement to prepare a load forecast-power supply borrowers.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 11 2010-01-01 2010-01-01 false Requirement to prepare a load forecast-power supply borrowers. 1710.202 Section 1710.202 Agriculture Regulations of the Department of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE GENERAL AND PRE-LOAN POLICIES AND PROCEDURES COMMON TO ELECTRIC LOANS AND GUARANTEES Load...

Environmental Impact Assessment and End-of-Life Treatment Policy Analysis for Li-Ion Batteries and Ni-MH Batteries

PubMed Central

Yu, Yajuan; Chen, Bo; Huang, Kai; Wang, Xiang; Wang, Dong

2014-01-01

Based on Life Cycle Assessment (LCA) and Eco-indicator 99 method, a LCA model was applied to conduct environmental impact and end-of-life treatment policy analysis for secondary batteries. This model evaluated the cycle, recycle and waste treatment stages of secondary batteries. Nickel-Metal Hydride (Ni-MH) batteries and Lithium ion (Li-ion) batteries were chosen as the typical secondary batteries in this study. Through this research, the following results were found: (1) A basic number of cycles should be defined. A minimum cycle number of 200 would result in an obvious decline of environmental loads for both battery types. Batteries with high energy density and long life expectancy have small environmental loads. Products and technology that help increase energy density and life expectancy should be encouraged. (2) Secondary batteries should be sorted out from municipal garbage. Meanwhile, different types of discarded batteries should be treated separately under policies and regulations. (3) The incineration rate has obvious impact on the Eco-indicator points of Nickel-Metal Hydride (Ni-MH) batteries. The influence of recycle rate on Lithium ion (Li-ion) batteries is more obvious. These findings indicate that recycling is the most promising direction for reducing secondary batteries’ environmental loads. The model proposed here can be used to evaluate environmental loads of other secondary batteries and it can be useful for proposing policies and countermeasures to reduce the environmental impact of secondary batteries. PMID:24646862

Environmental impact assessment and end-of-life treatment policy analysis for Li-ion batteries and Ni-MH batteries.

PubMed

Yu, Yajuan; Chen, Bo; Huang, Kai; Wang, Xiang; Wang, Dong

2014-03-18

Based on Life Cycle Assessment (LCA) and Eco-indicator 99 method, a LCA model was applied to conduct environmental impact and end-of-life treatment policy analysis for secondary batteries. This model evaluated the cycle, recycle and waste treatment stages of secondary batteries. Nickel-Metal Hydride (Ni-MH) batteries and Lithium ion (Li-ion) batteries were chosen as the typical secondary batteries in this study. Through this research, the following results were found: (1) A basic number of cycles should be defined. A minimum cycle number of 200 would result in an obvious decline of environmental loads for both battery types. Batteries with high energy density and long life expectancy have small environmental loads. Products and technology that help increase energy density and life expectancy should be encouraged. (2) Secondary batteries should be sorted out from municipal garbage. Meanwhile, different types of discarded batteries should be treated separately under policies and regulations. (3) The incineration rate has obvious impact on the Eco-indicator points of Nickel-Metal Hydride (Ni-MH) batteries. The influence of recycle rate on Lithium ion (Li-ion) batteries is more obvious. These findings indicate that recycling is the most promising direction for reducing secondary batteries' environmental loads. The model proposed here can be used to evaluate environmental loads of other secondary batteries and it can be useful for proposing policies and countermeasures to reduce the environmental impact of secondary batteries.

Turbine Performance Optimization Task Status

NASA Technical Reports Server (NTRS)

Griffin, Lisa W.; Turner, James E. (Technical Monitor)

2001-01-01

Capability to optimize for turbine performance and accurately predict unsteady loads will allow for increased reliability, Isp, and thrust-to-weight. The development of a fast, accurate aerodynamic design, analysis, and optimization system is required.

Prediction-based manufacturing center self-adaptive demand side energy optimization in cyber physical systems

NASA Astrophysics Data System (ADS)

Sun, Xinyao; Wang, Xue; Wu, Jiangwei; Liu, Youda

2014-05-01

Cyber physical systems(CPS) recently emerge as a new technology which can provide promising approaches to demand side management(DSM), an important capability in industrial power systems. Meanwhile, the manufacturing center is a typical industrial power subsystem with dozens of high energy consumption devices which have complex physical dynamics. DSM, integrated with CPS, is an effective methodology for solving energy optimization problems in manufacturing center. This paper presents a prediction-based manufacturing center self-adaptive energy optimization method for demand side management in cyber physical systems. To gain prior knowledge of DSM operating results, a sparse Bayesian learning based componential forecasting method is introduced to predict 24-hour electric load levels for specific industrial areas in China. From this data, a pricing strategy is designed based on short-term load forecasting results. To minimize total energy costs while guaranteeing manufacturing center service quality, an adaptive demand side energy optimization algorithm is presented. The proposed scheme is tested in a machining center energy optimization experiment. An AMI sensing system is then used to measure the demand side energy consumption of the manufacturing center. Based on the data collected from the sensing system, the load prediction-based energy optimization scheme is implemented. By employing both the PSO and the CPSO method, the problem of DSM in the manufacturing center is solved. The results of the experiment show the self-adaptive CPSO energy optimization method enhances optimization by 5% compared with the traditional PSO optimization method.

Multidimensional optimal droop control for wind resources in DC microgrids

NASA Astrophysics Data System (ADS)

Bunker, Kaitlyn J.

Two important and upcoming technologies, microgrids and electricity generation from wind resources, are increasingly being combined. Various control strategies can be implemented, and droop control provides a simple option without requiring communication between microgrid components. Eliminating the single source of potential failure around the communication system is especially important in remote, islanded microgrids, which are considered in this work. However, traditional droop control does not allow the microgrid to utilize much of the power available from the wind. This dissertation presents a novel droop control strategy, which implements a droop surface in higher dimension than the traditional strategy. The droop control relationship then depends on two variables: the dc microgrid bus voltage, and the wind speed at the current time. An approach for optimizing this droop control surface in order to meet a given objective, for example utilizing all of the power available from a wind resource, is proposed and demonstrated. Various cases are used to test the proposed optimal high dimension droop control method, and demonstrate its function. First, the use of linear multidimensional droop control without optimization is demonstrated through simulation. Next, an optimal high dimension droop control surface is implemented with a simple dc microgrid containing two sources and one load. Various cases for changing load and wind speed are investigated using simulation and hardware-in-the-loop techniques. Optimal multidimensional droop control is demonstrated with a wind resource in a full dc microgrid example, containing an energy storage device as well as multiple sources and loads. Finally, the optimal high dimension droop control method is applied with a solar resource, and using a load model developed for a military patrol base application. The operation of the proposed control is again investigated using simulation and hardware-in-the-loop techniques.

Handling Practicalities in Agricultural Policy Optimization for Water Quality Improvements

EPA Science Inventory

Bilevel and multi-objective optimization methods are often useful to spatially target agri-environmental policy throughout a watershed. This type of problem is complex and is comprised of a number of practicalities: (i) a large number of decision variables, (ii) at least two inte...

Towards a hierarchical optimization framework for spatially targeting incentive policies to promote green infrastructure amidst multiple objectives and uncertainty

EPA Science Inventory

We introduce a hierarchical optimization framework for spatially targeting green infrastructure (GI) incentive policies in order to meet objectives related to cost and environmental effectiveness. The framework explicitly simulates the interaction between multiple levels of polic...

Control problem for a system of linear loaded differential equations

NASA Astrophysics Data System (ADS)

Barseghyan, V. R.; Barseghyan, T. V.

2018-04-01

The problem of control and optimal control for a system of linear loaded differential equations is considered. Necessary and sufficient conditions for complete controllability and conditions for the existence of a program control and the corresponding motion are formulated. The explicit form of control action for the control problem is constructed and a method for solving the problem of optimal control is proposed.

Assessment of Masonry Buildings Subjected to Landslide-Induced Settlements: From Load Path Method to Evolutionary Optimization Method

NASA Astrophysics Data System (ADS)

Palmisano, Fabrizio; Elia, Angelo

2017-10-01

One of the main difficulties, when dealing with landslide structural vulnerability, is the diagnosis of the causes of crack patterns. This is also due to the excessive complexity of models based on classical structural mechanics that makes them inappropriate especially when there is the necessity to perform a rapid vulnerability assessment at the territorial scale. This is why, a new approach, based on a ‘simple model’ (i.e. the Load Path Method, LPM), has been proposed by Palmisano and Elia for the interpretation of the behaviour of masonry buildings subjected to landslide-induced settlements. However, the LPM is very useful for rapidly finding the 'most plausible solution' instead of the exact solution. To find the solution, optimization algorithms are necessary. In this scenario, this article aims to show how the Bidirectional Evolutionary Structural Optimization method by Huang and Xie, can be very useful to optimize the strut-and-tie models obtained by using the Load Path Method.

Optimization of shallow arches against instability using sensitivity derivatives

NASA Technical Reports Server (NTRS)

Kamat, Manohar P.

1987-01-01

The author discusses the problem of optimization of shallow frame structures which involve a coupling of axial and bending responses. A shallow arch of a given shape and of given weight is optimized such that its limit point load is maximized. The cross-sectional area, A(x) and the moment of inertia, I(x) of the arch obey the relationship I(x) = rho A(x) sup n, n = 1,2,3 and rho is a specified constant. Analysis of the arch for its limit point calculation involves a geometric nonlinear analysis which is performed using a corotational formulation. The optimization is carried out using a second-order projected Lagrangian algorithm and the sensitivity derivatives of the critical load parameter with respect to the areas of the finite elements of the arch are calculated using implicit differentation. Results are presented for an arch of a specified rise to span ratio under two different loadings and the limitations of the approach for the intermediate rise arches are addressed.

Integration of Large-Scale Optimization and Game Theory for Sustainable Water Quality Management

NASA Astrophysics Data System (ADS)

Tsao, J.; Li, J.; Chou, C.; Tung, C.

2009-12-01

Sustainable water quality management requires total mass control in pollutant discharge based on both the principles of not exceeding assimilative capacity in a river and equity among generations. The stream assimilative capacity is the carrying capacity of a river for the maximum waste load without violating the water quality standard and the spirit of total mass control is to optimize the waste load allocation in subregions. For the goal of sustainable watershed development, this study will use large-scale optimization theory to optimize the profit, and find the marginal values of loadings as reference of the fair price and then the best way to get the equilibrium by water quality trading for the whole of watershed will be found. On the other hand, game theory plays an important role to maximize both individual and entire profits. This study proves the water quality trading market is available in some situation, and also makes the whole participants get a better outcome.

Optimization of operating parameters of hybrid vertical down-flow constructed wetland systems for domestic sewerage treatment.

PubMed

Huang, Zhujian; Zhang, Xianning; Cui, Lihua; Yu, Guangwei

2016-09-15

In this work, three hybrid vertical down-flow constructed wetland (HVDF-CW) systems with different compound substrates were fed with domestic sewage and their pollutants removal performance under different hydraulic loading and step-feeding ratio was investigated. The results showed that the hydraulic loading and step-feeding ratio were two crucial factors determining the removal efficiency of most pollutants, while substrate types only significantly affected the removal of COD and NH4(+)-N. Generally, the lower the hydraulic loading, the better removal efficiency of all contaminants, except for TN. By contrast, the increase of step-feeding ratio would slightly reduce the removal rate of ammonium and TP but obviously promoted the TN removal. Therefore, the optimal operation of this CWs could be achieved with low hydraulic loading combined with 50% of step-feeding ratio when TN removal is the priority, whereas medium or low hydraulic loading without step-feeding would be suitable when TN removal is not taken into consideration. The obtained results in this study can provide us with a guideline for design and optimization of hybrid vertical flow constructed wetland systems to improve the pollutants removal from domestic sewage. Copyright © 2016 Elsevier Ltd. All rights reserved.

Can physical activity improve peak bone mass?

PubMed

Specker, Bonny; Minett, Maggie

2013-09-01

The pediatric origin of osteoporosis has led many investigators to focus on determining factors that influence bone gain during growth and methods for optimizing this gain. Bone responds to bone loading activities by increasing mass or size. Overall, pediatric studies have found a positive effect of bone loading on bone size and accrual, but the types of loads necessary for a bone response have only recently been investigated in human studies. Findings indicate that responses vary by sex, maturational status, and are site-specific. Estrogen status, body composition, and nutritional status also may influence the bone response to loading. Despite the complex interrelationships among these various factors, it is prudent to conclude that increased physical activity throughout life is likely to optimize bone health.

Energy audit data for a resort island in the South China Sea.

PubMed

Basir Khan, M Reyasudin; Jidin, Razali; Pasupuleti, Jagadeesh

2016-03-01

The data consists of actual generation-side auditing including the distribution of loads, seasonal load profiles, and types of loads as well as an analysis of local development planning of a resort island in the South China Sea. The data has been used to propose an optimal combination of hybrid renewable energy systems that able to mitigate the diesel fuel dependency on the island. The resort island selected is Tioman, as it represents the typical energy requirements of many resort islands in the South China Sea. The data presented are related to the research article "Optimal Combination of Solar, Wind, Micro-Hydro and Diesel Systems based on Actual Seasonal Load Profiles for a Resort Island in the South China Sea" [1].

Development and characterization of floating spheroids of atorvastatin calcium loaded NLC for enhancement of oral bioavailability.

PubMed

Sharma, Kritika; Hallan, Supandeep Singh; Lal, Bharat; Bhardwaj, Ankur; Mishra, Neeraj

2016-09-01

The obejctive of the present study was to investigate the potential use of floating spheroids of Atorvastatin Calcium (ATS) Loaded nanostructured lipid carriers (NLCs). The final formula of floating spheroids was optimized on the basis of shape (spherical), diameter (0.47 mm), lag time (20 s), and floating time (> 32 h). The results were further confirmed by different pharmacokinetic parameters-it was observed that the developed optimized floating ATS spheroid-loaded NLCs formulation has significantly improved relative bioavailability, that is, 3.053-folds through oral route in comparison to marketed formulation.

Concurrent material-fabrication optimization of metal-matrix laminates under thermo-mechanical loading

NASA Technical Reports Server (NTRS)

Saravanos, D. A.; Morel, M. R.; Chamis, C. C.

1991-01-01

A methodology is developed to tailor fabrication and material parameters of metal-matrix laminates for maximum loading capacity under thermomechanical loads. The stresses during the thermomechanical response are minimized subject to failure constrains and bounds on the laminate properties. The thermomechanical response of the laminate is simulated using nonlinear composite mechanics. Evaluations of the method on a graphite/copper symmetric cross-ply laminate were performed. The cross-ply laminate required different optimum fabrication procedures than a unidirectional composite. Also, the consideration of the thermomechanical cycle had a significant effect on the predicted optimal process.

Artificial Intelligence vs. Statistical Modeling and Optimization of Continuous Bead Milling Process for Bacterial Cell Lysis.

PubMed

Haque, Shafiul; Khan, Saif; Wahid, Mohd; Dar, Sajad A; Soni, Nipunjot; Mandal, Raju K; Singh, Vineeta; Tiwari, Dileep; Lohani, Mohtashim; Areeshi, Mohammed Y; Govender, Thavendran; Kruger, Hendrik G; Jawed, Arshad

2016-01-01

For a commercially viable recombinant intracellular protein production process, efficient cell lysis and protein release is a major bottleneck. The recovery of recombinant protein, cholesterol oxidase (COD) was studied in a continuous bead milling process. A full factorial response surface methodology (RSM) design was employed and compared to artificial neural networks coupled with genetic algorithm (ANN-GA). Significant process variables, cell slurry feed rate (A), bead load (B), cell load (C), and run time (D), were investigated and optimized for maximizing COD recovery. RSM predicted an optimum of feed rate of 310.73 mL/h, bead loading of 79.9% (v/v), cell loading OD 600 nm of 74, and run time of 29.9 min with a recovery of ~3.2 g/L. ANN-GA predicted a maximum COD recovery of ~3.5 g/L at an optimum feed rate (mL/h): 258.08, bead loading (%, v/v): 80%, cell loading (OD 600 nm ): 73.99, and run time of 32 min. An overall 3.7-fold increase in productivity is obtained when compared to a batch process. Optimization and comparison of statistical vs. artificial intelligence techniques in continuous bead milling process has been attempted for the very first time in our study. We were able to successfully represent the complex non-linear multivariable dependence of enzyme recovery on bead milling parameters. The quadratic second order response functions are not flexible enough to represent such complex non-linear dependence. ANN being a summation function of multiple layers are capable to represent complex non-linear dependence of variables in this case; enzyme recovery as a function of bead milling parameters. Since GA can even optimize discontinuous functions present study cites a perfect example of using machine learning (ANN) in combination with evolutionary optimization (GA) for representing undefined biological functions which is the case for common industrial processes involving biological moieties.

Artificial Intelligence vs. Statistical Modeling and Optimization of Continuous Bead Milling Process for Bacterial Cell Lysis

PubMed Central

Haque, Shafiul; Khan, Saif; Wahid, Mohd; Dar, Sajad A.; Soni, Nipunjot; Mandal, Raju K.; Singh, Vineeta; Tiwari, Dileep; Lohani, Mohtashim; Areeshi, Mohammed Y.; Govender, Thavendran; Kruger, Hendrik G.; Jawed, Arshad

2016-01-01

For a commercially viable recombinant intracellular protein production process, efficient cell lysis and protein release is a major bottleneck. The recovery of recombinant protein, cholesterol oxidase (COD) was studied in a continuous bead milling process. A full factorial response surface methodology (RSM) design was employed and compared to artificial neural networks coupled with genetic algorithm (ANN-GA). Significant process variables, cell slurry feed rate (A), bead load (B), cell load (C), and run time (D), were investigated and optimized for maximizing COD recovery. RSM predicted an optimum of feed rate of 310.73 mL/h, bead loading of 79.9% (v/v), cell loading OD600 nm of 74, and run time of 29.9 min with a recovery of ~3.2 g/L. ANN-GA predicted a maximum COD recovery of ~3.5 g/L at an optimum feed rate (mL/h): 258.08, bead loading (%, v/v): 80%, cell loading (OD600 nm): 73.99, and run time of 32 min. An overall 3.7-fold increase in productivity is obtained when compared to a batch process. Optimization and comparison of statistical vs. artificial intelligence techniques in continuous bead milling process has been attempted for the very first time in our study. We were able to successfully represent the complex non-linear multivariable dependence of enzyme recovery on bead milling parameters. The quadratic second order response functions are not flexible enough to represent such complex non-linear dependence. ANN being a summation function of multiple layers are capable to represent complex non-linear dependence of variables in this case; enzyme recovery as a function of bead milling parameters. Since GA can even optimize discontinuous functions present study cites a perfect example of using machine learning (ANN) in combination with evolutionary optimization (GA) for representing undefined biological functions which is the case for common industrial processes involving biological moieties. PMID:27920762

State dependent optimization of measurement policy

NASA Astrophysics Data System (ADS)

Konkarikoski, K.

2010-07-01

Measurements are the key to rational decision making. Measurement information generates value, when it is applied in the decision making. An investment cost and maintenance costs are associated with each component of the measurement system. Clearly, there is - under a given set of scenarios - a measurement setup that is optimal in expected (discounted) utility. This paper deals how the measurement policy optimization is affected by different system states and how this problem can be tackled.

A Kind of Optimization Method of Loading Documents in OpenOffice.org

NASA Astrophysics Data System (ADS)

Lan, Yuqing; Li, Li; Zhou, Wenbin

As a giant in open source community, OpenOffice.org has become the most popular office suite within Linux community. But OpenOffice.org is relatively slow while loading documents. Research shows that the most time consuming part is importing one page of whole document. If there are many pages in a document, the accumulation of time consumed can be astonishing. Therefore, this paper proposes a solution, which has improved the speed of loading documents through asynchronous importing mechanism: a document is not imported as a whole, but only part of the document is imported at first for display, then mechanism in the background is started to asynchronously import the remaining parts, and insert it into the drawing queue of OpenOffice.org for display. In this way, the problem can be solved and users don't have to wait for a long time. Application start-up time testing tool has been used to test the time consumed in loading different pages of documents before and after optimization of OpenOffice.org, then, we adopt the regression theory to analyse the correlation between the page number of documents and the loading time. In addition, visual modeling of the experimental data are acquired with the aid of matlab. An obvious increase in loading speed can be seen after a comparison of the time consumed to load a document before and after the solution is adopted. And then, using Microsoft Office compared with the optimized OpenOffice.org, their loading speeds are almost same. The results of the experiments show the effectiveness of this solution.

Multi-disciplinary optimization of aeroservoelastic systems

NASA Technical Reports Server (NTRS)

Karpel, Mardechay

1992-01-01

The purpose of the research project was to continue the development of new methods for efficient aeroservoelastic analysis and optimization. The main targets were as follows: to complete the development of analytical tools for the investigation of flutter with large stiffness changes; to continue the work on efficient continuous gust response and sensitivity derivatives; and to advance the techniques of calculating dynamic loads with control and unsteady aerodynamic effects. An efficient and highly accurate mathematical model for time-domain analysis of flutter during which large structural changes occur was developed in cooperation with Carol D. Wieseman of NASA LaRC. The model was based on the second-year work 'Modal Coordinates for Aeroelastic Analysis with Large Local Structural Variations'. The work on continuous gust response was completed. An abstract of the paper 'Continuous Gust Response and Sensitivity Derivatives Using State-Space Models' was submitted for presentation in the 33rd Israel Annual Conference on Aviation and Astronautics, Feb. 1993. The abstract is given in Appendix A. The work extends the optimization model to deal with continuous gust objectives in a way that facilitates their inclusion in the efficient multi-disciplinary optimization scheme. Currently under development is a work designed to extend the analysis and optimization capabilities to loads and stress considerations. The work is on aircraft dynamic loads in response to impulsive and non-impulsive excitation. The work extends the formulations of the mode-displacement and summation-of-forces methods to include modes with significant local distortions, and load modes. An abstract of the paper,'Structural Dynamic Loads in Response to Impulsive Excitation' is given in appendix B. Another work performed this year under the Grant was 'Size-Reduction Techniques for the Determination of Efficient Aeroservoelastic Models' given in Appendix C.

[Optimization and characterization of curcumin-piperine dual drug loaded self-microemulsifying drug delivery system by simplex lattice design].

PubMed

Li, Qiu-Ping; Dai, Jun-Dong; Zhai, Wen-Wen; Jiang, Qiao-Li

2014-10-01

The objective of the study was to prepare and evaluate the quality of curcumin-piperinedual drug loaded self-microemulsifying drug delivery system(Cur-PIP-SMEDDS). Simplex lattice design was constructed using optimal oil phase, surfactant and co-surfactant concentration as independent variables, and the curcumin and piperine were used as model drugs to optimize Cur-PIP-SMEDDS formulation. In the present study, the drug loadings of curcumin and piperine, mean particle size of Cur-PIP-SMEDDS were made as indicators, and the experiment design, model building and response surface analysis were established using Design Expert 8. 06 software to optimize and verify the composition of SMEDDS formulation. The quality of Cur-PIP-SMEDDS was evaluated by observing the appearance status, transmission electron microscope micrographs and determining particle diameter, electric potential, drug entrapment efficiency and drug loading of it. As a result, the optimal formulation of SMEDDS was CapryoL 90-Cremophor RH40-TranscutoL HP (10:60:30). The appearance of Cur-PIP-SMEDDS remained clarified and transparent, and the microemulsion droplets appeared spherical without aggregation with uniform particle size distribution. The mean size of microemulsion droplet formed from Cur-PIP-SMEDDS was 15.33 nm, the drug loading of SMEDDS for Cur and PIP were 40.90 mg · g(-1) and 0.97 mg · g(-1), respectively, the drug entrapment efficiency were 94.98% and 90.96%, respectively. The results show that Cur-PIP-SMEDDS can increase the solubility and stability of curcumin significantly, in the expectation of enhancing the bioavailability of it. Taken together, these findings can provide the reference to a preferable choice of the Cur formulation and contribute to therapeutic application in clinical research.

Novel models and algorithms of load balancing for variable-structured collaborative simulation under HLA/RTI

NASA Astrophysics Data System (ADS)

Yue, Yingchao; Fan, Wenhui; Xiao, Tianyuan; Ma, Cheng

2013-07-01

High level architecture(HLA) is the open standard in the collaborative simulation field. Scholars have been paying close attention to theoretical research on and engineering applications of collaborative simulation based on HLA/RTI, which extends HLA in various aspects like functionality and efficiency. However, related study on the load balancing problem of HLA collaborative simulation is insufficient. Without load balancing, collaborative simulation under HLA/RTI may encounter performance reduction or even fatal errors. In this paper, load balancing is further divided into static problems and dynamic problems. A multi-objective model is established and the randomness of model parameters is taken into consideration for static load balancing, which makes the model more credible. The Monte Carlo based optimization algorithm(MCOA) is excogitated to gain static load balance. For dynamic load balancing, a new type of dynamic load balancing problem is put forward with regards to the variable-structured collaborative simulation under HLA/RTI. In order to minimize the influence against the running collaborative simulation, the ordinal optimization based algorithm(OOA) is devised to shorten the optimization time. Furthermore, the two algorithms are adopted in simulation experiments of different scenarios, which demonstrate their effectiveness and efficiency. An engineering experiment about collaborative simulation under HLA/RTI of high speed electricity multiple units(EMU) is also conducted to indentify credibility of the proposed models and supportive utility of MCOA and OOA to practical engineering systems. The proposed research ensures compatibility of traditional HLA, enhances the ability for assigning simulation loads onto computing units both statically and dynamically, improves the performance of collaborative simulation system and makes full use of the hardware resources.

The impact of uncertainty on optimal emission policies

NASA Astrophysics Data System (ADS)

Botta, Nicola; Jansson, Patrik; Ionescu, Cezar

2018-05-01

We apply a computational framework for specifying and solving sequential decision problems to study the impact of three kinds of uncertainties on optimal emission policies in a stylized sequential emission problem.We find that uncertainties about the implementability of decisions on emission reductions (or increases) have a greater impact on optimal policies than uncertainties about the availability of effective emission reduction technologies and uncertainties about the implications of trespassing critical cumulated emission thresholds. The results show that uncertainties about the implementability of decisions on emission reductions (or increases) call for more precautionary policies. In other words, delaying emission reductions to the point in time when effective technologies will become available is suboptimal when these uncertainties are accounted for rigorously. By contrast, uncertainties about the implications of exceeding critical cumulated emission thresholds tend to make early emission reductions less rewarding.

Shape optimization of tibial prosthesis components

NASA Technical Reports Server (NTRS)

Saravanos, D. A.; Mraz, P. J.; Davy, D. T.

1993-01-01

NASA technology and optimal design methodologies originally developed for the optimization of composite structures (engine blades) are adapted and applied to the optimization of orthopaedic knee implants. A method is developed enabling the shape tailoring of the tibial components of a total knee replacement implant for optimal interaction within the environment of the tibia. The shape of the implant components are optimized such that the stresses in the bone are favorably controlled to minimize bone degradation, to improve the mechanical integrity of the implant/interface/bone system, and to prevent failures of the implant components. A pilot tailoring system is developed and the feasibility of the concept is demonstrated and evaluated. The methodology and evolution of the existing aerospace technology from which this pilot optimization code was developed is also presented and discussed. Both symmetric and unsymmetric in-plane loading conditions are investigated. The results of the optimization process indicate a trend toward wider and tapered posts as well as thicker backing trays. Unique component geometries were obtained for the different load cases.

Identifying Cost-Effective Dynamic Policies to Control Epidemics

PubMed Central

Yaesoubi, Reza; Cohen, Ted

2016-01-01

We describe a mathematical decision model for identifying dynamic health policies for controlling epidemics. These dynamic policies aim to select the best current intervention based on accumulating epidemic data and the availability of resources at each decision point. We propose an algorithm to approximate dynamic policies that optimize the population’s net health benefit, a performance measure which accounts for both health and monetary outcomes. We further illustrate how dynamic policies can be defined and optimized for the control of a novel viral pathogen, where a policy maker must decide (i) when to employ or lift a transmission-reducing intervention (e.g. school closure) and (ii) how to prioritize population members for vaccination when a limited quantity of vaccines first become available. Within the context of this application, we demonstrate that dynamic policies can produce higher net health benefit than more commonly described static policies that specify a pre-determined sequence of interventions to employ throughout epidemics. PMID:27449759

Maximizing the efficiency of multienzyme process by stoichiometry optimization.

PubMed

Dvorak, Pavel; Kurumbang, Nagendra P; Bendl, Jaroslav; Brezovsky, Jan; Prokop, Zbynek; Damborsky, Jiri

2014-09-05

Multienzyme processes represent an important area of biocatalysis. Their efficiency can be enhanced by optimization of the stoichiometry of the biocatalysts. Here we present a workflow for maximizing the efficiency of a three-enzyme system catalyzing a five-step chemical conversion. Kinetic models of pathways with wild-type or engineered enzymes were built, and the enzyme stoichiometry of each pathway was optimized. Mathematical modeling and one-pot multienzyme experiments provided detailed insights into pathway dynamics, enabled the selection of a suitable engineered enzyme, and afforded high efficiency while minimizing biocatalyst loadings. Optimizing the stoichiometry in a pathway with an engineered enzyme reduced the total biocatalyst load by an impressive 56 %. Our new workflow represents a broadly applicable strategy for optimizing multienzyme processes. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimization, formulation, and characterization of multiflavonoids-loaded flavanosome by bulk or sequential technique

PubMed Central

Karthivashan, Govindarajan; Masarudin, Mas Jaffri; Kura, Aminu Umar; Abas, Faridah; Fakurazi, Sharida

2016-01-01

This study involves adaptation of bulk or sequential technique to load multiple flavonoids in a single phytosome, which can be termed as “flavonosome”. Three widely established and therapeutically valuable flavonoids, such as quercetin (Q), kaempferol (K), and apigenin (A), were quantified in the ethyl acetate fraction of Moringa oleifera leaves extract and were commercially obtained and incorporated in a single flavonosome (QKA–phosphatidylcholine) through four different methods of synthesis – bulk (M1) and serialized (M2) co-sonication and bulk (M3) and sequential (M4) co-loading. The study also established an optimal formulation method based on screening the synthesized flavonosomes with respect to their size, charge, polydispersity index, morphology, drug–carrier interaction, antioxidant potential through in vitro 1,1-diphenyl-2-picrylhydrazyl kinetics, and cytotoxicity evaluation against human hepatoma cell line (HepaRG). Furthermore, entrapment and loading efficiency of flavonoids in the optimal flavonosome have been identified. Among the four synthesis methods, sequential loading technique has been optimized as the best method for the synthesis of QKA–phosphatidylcholine flavonosome, which revealed an average diameter of 375.93±33.61 nm, with a zeta potential of −39.07±3.55 mV, and the entrapment efficiency was >98% for all the flavonoids, whereas the drug-loading capacity of Q, K, and A was 31.63%±0.17%, 34.51%±2.07%, and 31.79%±0.01%, respectively. The in vitro 1,1-diphenyl-2-picrylhydrazyl kinetics of the flavonoids indirectly depicts the release kinetic behavior of the flavonoids from the carrier. The QKA-loaded flavonosome had no indication of toxicity toward human hepatoma cell line as shown by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide result, wherein even at the higher concentration of 200 µg/mL, the flavonosomes exert >85% of cell viability. These results suggest that sequential loading technique may be a promising nanodrug delivery system for loading multiflavonoids in a single entity with sustained activity as an antioxidant, hepatoprotective, and hepatosupplement candidate. PMID:27555765

Optimization, formulation, and characterization of multiflavonoids-loaded flavanosome by bulk or sequential technique.

PubMed

Karthivashan, Govindarajan; Masarudin, Mas Jaffri; Kura, Aminu Umar; Abas, Faridah; Fakurazi, Sharida

2016-01-01

This study involves adaptation of bulk or sequential technique to load multiple flavonoids in a single phytosome, which can be termed as "flavonosome". Three widely established and therapeutically valuable flavonoids, such as quercetin (Q), kaempferol (K), and apigenin (A), were quantified in the ethyl acetate fraction of Moringa oleifera leaves extract and were commercially obtained and incorporated in a single flavonosome (QKA-phosphatidylcholine) through four different methods of synthesis - bulk (M1) and serialized (M2) co-sonication and bulk (M3) and sequential (M4) co-loading. The study also established an optimal formulation method based on screening the synthesized flavonosomes with respect to their size, charge, polydispersity index, morphology, drug-carrier interaction, antioxidant potential through in vitro 1,1-diphenyl-2-picrylhydrazyl kinetics, and cytotoxicity evaluation against human hepatoma cell line (HepaRG). Furthermore, entrapment and loading efficiency of flavonoids in the optimal flavonosome have been identified. Among the four synthesis methods, sequential loading technique has been optimized as the best method for the synthesis of QKA-phosphatidylcholine flavonosome, which revealed an average diameter of 375.93±33.61 nm, with a zeta potential of -39.07±3.55 mV, and the entrapment efficiency was >98% for all the flavonoids, whereas the drug-loading capacity of Q, K, and A was 31.63%±0.17%, 34.51%±2.07%, and 31.79%±0.01%, respectively. The in vitro 1,1-diphenyl-2-picrylhydrazyl kinetics of the flavonoids indirectly depicts the release kinetic behavior of the flavonoids from the carrier. The QKA-loaded flavonosome had no indication of toxicity toward human hepatoma cell line as shown by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide result, wherein even at the higher concentration of 200 µg/mL, the flavonosomes exert >85% of cell viability. These results suggest that sequential loading technique may be a promising nanodrug delivery system for loading multiflavonoids in a single entity with sustained activity as an antioxidant, hepatoprotective, and hepatosupplement candidate.

Comparison of Commercial Aircraft Fuel Requirements in Regards to FAR, Flight Profile Simulation, and Flight Operational Techniques

NASA Astrophysics Data System (ADS)

Heitzman, Nicholas

There are significant fuel consumption consequences for non-optimal flight operations. This study is intended to analyze and highlight areas of interest that affect fuel consumption in typical flight operations. By gathering information from actual flight operators (pilots, dispatch, performance engineers, and air traffic controllers), real performance issues can be addressed and analyzed. A series of interviews were performed with various individuals in the industry and organizations. The wide range of insight directed this study to focus on FAA regulations, airline policy, the ATC system, weather, and flight planning. The goal is to highlight where operational performance differs from design intent in order to better connect optimization with actual flight operations. After further investigation and consensus from the experienced participants, the FAA regulations do not need any serious attention until newer technologies and capabilities are implemented. The ATC system is severely out of date and is one of the largest limiting factors in current flight operations. Although participants are pessimistic about its timely implementation, the FAA's NextGen program for a future National Airspace System should help improve the efficiency of flight operations. This includes situational awareness, weather monitoring, communication, information management, optimized routing, and cleaner flight profiles like Required Navigation Performance (RNP) and Continuous Descent Approach (CDA). Working off the interview results, trade-studies were performed using an in-house flight profile simulation of a Boeing 737-300, integrating NASA legacy codes EDET and NPSS with a custom written mission performance and point-performance "Skymap" calculator. From these trade-studies, it was found that certain flight conditions affect flight operations more than others. With weather, traffic, and unforeseeable risks, flight planning is still limited by its high level of precaution. From this study, it is recommended that air carriers increase focus on defining policies like load scheduling, CG management, reduction in zero fuel weight, inclusion of performance measurement systems, and adapting to the regulations to best optimize the spirit of the requirement.. As well, air carriers should create a larger drive to implement the FAA's NextGen system and move the industry into the future.

Using Maximal Isometric Force to Determine the Optimal Load for Measuring Dynamic Muscle Power

NASA Technical Reports Server (NTRS)

Spiering, Barry A.; Lee, Stuart M. C.; Mulavara, Ajitkumar P.; Bentley, Jason R.; Nash, Roxanne E.; Sinka, Joseph; Bloomberg, Jacob J.

2009-01-01

Maximal power output occurs when subjects perform ballistic exercises using loads of 30-50% of one-repetition maximum (1-RM). However, performing 1-RM testing prior to power measurement requires considerable time, especially when testing involves multiple exercises. Maximal isometric force (MIF), which requires substantially less time to measure than 1-RM, might be an acceptable alternative for determining the optimal load for power testing. PURPOSE: To determine the optimal load based on MIF for maximizing dynamic power output during leg press and bench press exercises. METHODS: Twenty healthy volunteers (12 men and 8 women; mean +/- SD age: 31+/-6 y; body mass: 72 +/- 15 kg) performed isometric leg press and bench press movements, during which MIF was measured using force plates. Subsequently, subjects performed ballistic leg press and bench press exercises using loads corresponding to 20%, 30%, 40%, 50%, and 60% of MIF presented in randomized order. Maximal instantaneous power was calculated during the ballistic exercise tests using force plates and position transducers. Repeated-measures ANOVA and Fisher LSD post hoc tests were used to determine the load(s) that elicited maximal power output. RESULTS: For the leg press power test, six subjects were unable to be tested at 20% and 30% MIF because these loads were less than the lightest possible load (i.e., the weight of the unloaded leg press sled assembly [31.4 kg]). For the bench press power test, five subjects were unable to be tested at 20% MIF because these loads were less than the weight of the unloaded aluminum bar (i.e., 11.4 kg). Therefore, these loads were excluded from analysis. A trend (p = 0.07) for a main effect of load existed for the leg press exercise, indicating that the 40% MIF load tended to elicit greater power output than the 60% MIF load (effect size = 0.38). A significant (p . 0.05) main effect of load existed for the bench press exercise; post hoc analysis indicated that the effect of load on power output was: 30% > 40% > 50% = 60%. CONCLUSION: Loads of 40% and 30% of MIF elicit maximal power output during dynamic leg presses and bench presses, respectively. These findings are similar to those obtained when loading is based on 1-RM.

Geometry Design Optimization of Functionally Graded Scaffolds for Bone Tissue Engineering: A Mechanobiological Approach

PubMed Central

Boccaccio, Antonio; Uva, Antonio Emmanuele; Fiorentino, Michele; Mori, Giorgio; Monno, Giuseppe

2016-01-01

Functionally Graded Scaffolds (FGSs) are porous biomaterials where porosity changes in space with a specific gradient. In spite of their wide use in bone tissue engineering, possible models that relate the scaffold gradient to the mechanical and biological requirements for the regeneration of the bony tissue are currently missing. In this study we attempt to bridge the gap by developing a mechanobiology-based optimization algorithm aimed to determine the optimal graded porosity distribution in FGSs. The algorithm combines the parametric finite element model of a FGS, a computational mechano-regulation model and a numerical optimization routine. For assigned boundary and loading conditions, the algorithm builds iteratively different scaffold geometry configurations with different porosity distributions until the best microstructure geometry is reached, i.e. the geometry that allows the amount of bone formation to be maximized. We tested different porosity distribution laws, loading conditions and scaffold Young’s modulus values. For each combination of these variables, the explicit equation of the porosity distribution law–i.e the law that describes the pore dimensions in function of the spatial coordinates–was determined that allows the highest amounts of bone to be generated. The results show that the loading conditions affect significantly the optimal porosity distribution. For a pure compression loading, it was found that the pore dimensions are almost constant throughout the entire scaffold and using a FGS allows the formation of amounts of bone slightly larger than those obtainable with a homogeneous porosity scaffold. For a pure shear loading, instead, FGSs allow to significantly increase the bone formation compared to a homogeneous porosity scaffolds. Although experimental data is still necessary to properly relate the mechanical/biological environment to the scaffold microstructure, this model represents an important step towards optimizing geometry of functionally graded scaffolds based on mechanobiological criteria. PMID:26771746

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

NASA Astrophysics Data System (ADS)

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

2012-05-01

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

Optimally oriented grooves on dental implants improve bone quality around implants under repetitive mechanical loading.

PubMed

Kuroshima, Shinichiro; Nakano, Takayoshi; Ishimoto, Takuya; Sasaki, Muneteru; Inoue, Maaya; Yasutake, Munenori; Sawase, Takashi

2017-01-15

The aim was to investigate the effect of groove designs on bone quality under controlled-repetitive load conditions for optimizing dental implant design. Anodized Ti-6Al-4V alloy implants with -60° and +60° grooves around the neck were placed in the proximal tibial metaphysis of rabbits. The application of a repetitive mechanical load was initiated via the implants (50N, 3Hz, 1800 cycles, 2days/week) at 12weeks after surgery for 8weeks. Bone quality, defined as osteocyte density and degree of biological apatite (BAp) c-axis/collagen fibers, was then evaluated. Groove designs did not affect bone quality without mechanical loading; however, repetitive mechanical loading significantly increased bone-to-implant contact, bone mass, and bone mineral density (BMD). In +60° grooves, the BAp c-axis/collagen fibers preferentially aligned along the groove direction with mechanical loading. Moreover, osteocyte density was significantly higher both inside and in the adjacent region of the +60° grooves, but not -60° grooves. These results suggest that the +60° grooves successfully transmitted the load to the bone tissues surrounding implants through the grooves. An optimally oriented groove structure on the implant surface was shown to be a promising way for achieving bone tissue with appropriate bone quality. This is the first report to propose the optimal design of grooves on the necks of dental implants for improving bone quality parameters as well as BMD. The findings suggest that not only BMD, but also bone quality, could be a useful clinical parameter in implant dentistry. Although the paradigm of bone quality has shifted from density-based assessments to structural evaluations of bone, clarifying bone quality based on structural bone evaluations remains challenging in implant dentistry. In this study, we firstly demonstrated that the optimal design of dental implant necks improved bone quality defined as osteocytes and the preferential alignment degree of biological apatite c-axis/collagen fibers using light microscopy, polarized light microscopy, and a microbeam X-ray diffractometer system, after application of controlled mechanical load. Our new findings suggest that bone quality around dental implants could become a new clinical parameter as well as bone mineral density in order to completely account for bone strength in implant dentistry. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Simultaneous Optimization of Tooth Flank Form of Involute Helical Gears in Terms of Both Vibration and Load Carrying Capacity

NASA Astrophysics Data System (ADS)

Komori, Masaharu; Kubo, Aizoh; Suzuki, Yoshitomo

The alignment condition of automotive gears changes considerably during operation due to the deformation of shafts, bearings, and gear box by transmission of load. Under such conditions, the gears are required to satisfy not only reliability in strength and durability under maximum loading conditions, but also low vibrational characteristics under light loading conditions during the cruising of a car. In this report, the characteristics of the optimum tooth flank form of gears in terms of both vibration and load carrying capacity are clarified. The local optimum tooth flank form appears in each excitation valley, where the vibrational excitation is low and the actual contact ratio takes a specific value. The influence of the choice of different local optimum solutions on the vibrational performance of the optimized gears is investigated. The practical design algorithm for the optimum tooth flank form of a gear set in terms of both vibration and load carrying capacity is then proposed and its result is evaluated by field experience.

A Comparison of Load-Velocity and Load-Power Relationships Between Well-Trained Young and Middle-Aged Males During Three Popular Resistance Exercises.

PubMed

Fernandes, John F T; Lamb, Kevin L; Twist, Craig

2018-05-01

Fernandes, JFT, Lamb, KL, and Twist, C. A comparison of load-velocity and load-power relationships between well-trained young and middle-aged males during 3 popular resistance exercises. J Strength Cond Res 32(5): 1440-1447, 2018-This study examined the load-velocity and load-power relationships among 20 young (age 21.0 ± 1.6 years) and 20 middle-aged (age 42.6 ± 6.7 years) resistance-trained males. Participants performed 3 repetitions of bench press, squat, and bent-over-row across a range of loads corresponding to 20-80% of 1 repetition maximum (1RM). Analysis revealed effects (p < 0.05) of group and load × group on barbell velocity for all 3 exercises, and interaction effects on power for squat and bent-over-row (p < 0.05). For bench press and bent-over-row, the young group produced higher barbell velocities, with the magnitude of the differences decreasing as load increased (ES; effect size 0.0-1.7 and 1.0-2.0, respectively). Squat velocity was higher in the young group than the middle-aged group (ES 1.0-1.7) across all loads, as was power for each exercise (ES 1.0-2.3). For all 3 exercises, both velocity and 1RM were correlated with optimal power in the middle-aged group (r = 0.613-0.825, p < 0.05), but only 1RM was correlated with optimal power (r = 0.708-0.867, p < 0.05) in the young group. These findings indicate that despite their resistance training, middle-aged males were unable to achieve velocities at low external loads and power outputs as high as the young males across a range of external resistances. Moreover, the strong correlations between 1RM and velocity with optimal power suggest that middle-aged males would benefit from training methods which maximize these adaptations.

Optimization of Energy Efficiency and Conservation in Green Building Design Using Duelist, Killer-Whale and Rain-Water Algorithms

NASA Astrophysics Data System (ADS)

Biyanto, T. R.; Matradji; Syamsi, M. N.; Fibrianto, H. Y.; Afdanny, N.; Rahman, A. H.; Gunawan, K. S.; Pratama, J. A. D.; Malwindasari, A.; Abdillah, A. I.; Bethiana, T. N.; Putra, Y. A.

2017-11-01

The development of green building has been growing in both design and quality. The development of green building was limited by the issue of expensive investment. Actually, green building can reduce the energy usage inside the building especially in utilization of cooling system. External load plays major role in reducing the usage of cooling system. External load is affected by type of wall sheathing, glass and roof. The proper selection of wall, type of glass and roof material are very important to reduce external load. Hence, the optimization of energy efficiency and conservation in green building design is required. Since this optimization consist of integer and non-linear equations, this problem falls into Mixed-Integer-Non-Linear-Programming (MINLP) that required global optimization technique such as stochastic optimization algorithms. In this paper the optimized variables i.e. type of glass and roof were chosen using Duelist, Killer-Whale and Rain-Water Algorithms to obtain the optimum energy and considering the minimal investment. The optimization results exhibited the single glass Planibel-G with the 3.2 mm thickness and glass wool insulation provided maximum ROI of 36.8486%, EUI reduction of 54 kWh/m2·year, CO2 emission reduction of 486.8971 tons/year and reduce investment of 4,078,905,465 IDR.

Bidding strategy for microgrid in day-ahead market based on hybrid stochastic/robust optimization

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

Liu, Guodong; Xu, Yan; Tomsovic, Kevin

In this paper, we propose an optimal bidding strategy in the day-ahead market of a microgrid consisting of intermittent distributed generation (DG), storage, dispatchable DG and price responsive loads. The microgrid coordinates the energy consumption or production of its components and trades electricity in both the day-ahead and real-time markets to minimize its operating cost as a single entity. The bidding problem is challenging due to a variety of uncertainties, including power output of intermittent DG, load variation, day-ahead and real-time market prices. A hybrid stochastic/robust optimization model is proposed to minimize the expected net cost, i.e., expected total costmore » of operation minus total benefit of demand. This formulation can be solved by mixed integer linear programming. The uncertain output of intermittent DG and day-ahead market price are modeled via scenarios based on forecast results, while a robust optimization is proposed to limit the unbalanced power in real-time market taking account of the uncertainty of real-time market price. Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, a micro-turbine, a diesel generator, a battery and a responsive load show the advantage of stochastic optimization in addition to robust optimization.« less

Bidding strategy for microgrid in day-ahead market based on hybrid stochastic/robust optimization

DOE PAGES

Liu, Guodong; Xu, Yan; Tomsovic, Kevin

2016-01-01

In this paper, we propose an optimal bidding strategy in the day-ahead market of a microgrid consisting of intermittent distributed generation (DG), storage, dispatchable DG and price responsive loads. The microgrid coordinates the energy consumption or production of its components and trades electricity in both the day-ahead and real-time markets to minimize its operating cost as a single entity. The bidding problem is challenging due to a variety of uncertainties, including power output of intermittent DG, load variation, day-ahead and real-time market prices. A hybrid stochastic/robust optimization model is proposed to minimize the expected net cost, i.e., expected total costmore » of operation minus total benefit of demand. This formulation can be solved by mixed integer linear programming. The uncertain output of intermittent DG and day-ahead market price are modeled via scenarios based on forecast results, while a robust optimization is proposed to limit the unbalanced power in real-time market taking account of the uncertainty of real-time market price. Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, a micro-turbine, a diesel generator, a battery and a responsive load show the advantage of stochastic optimization in addition to robust optimization.« less

Optimization of drug loading to improve physical stability of paclitaxel-loaded long-circulating liposomes.

PubMed

Kannan, Vinayagam; Balabathula, Pavan; Divi, Murali K; Thoma, Laura A; Wood, George C

2015-01-01

The effect of formulation and process parameters on drug loading and physical stability of paclitaxel-loaded long-circulating liposomes was evaluated. The liposomes were prepared by hydration-extrusion method. The formulation parameters such as total lipid content, cholesterol content, saturated-unsaturated lipid ratio, drug-lipid ratio and process parameters such as extrusion pressure and number of extrusion cycles were studied and their impact on drug loading and physical stability was evaluated. A proportionate increase in drug loading was observed with increase in the total phospholipid content. Cholesterol content and saturated lipid content in the bilayer showed a negative influence on drug loading. The short-term stability evaluation of liposomes prepared with different drug-lipid ratios demonstrated that 1:60 as the optimum drug-lipid ratio to achieve a loading of 1-1.3 mg/mL without the risk of physical instability. The vesicle size decreased with an increase in the extrusion pressure and number of extrusion cycles, but no significant trends were observed for drug loading with changes in process pressure or number of cycles. The optimization of formulation and process parameters led to a physically stable formulation of paclitaxel-loaded long-circulating liposomes that maintain size, charge and integrity during storage.

Optimizing the performance of Ice-storage Systems in Electricity Load Management through a credit mechanism. An analytical work for Jiangsu, China

DOE PAGES

Han, Yafeng; Shen, Bo; Hu, Huajin; ...

2015-01-12

Ice-storage air-conditioning is a technique that uses ice for thermal energy storage. Replacing existing air conditioning systems with ice storage has the advantage of shifting the load from on-peak times to off-peak times that often have excess generation. However, increasing the use of ice-storage faces significant challenges in China. One major barrier is the inefficiency in the current electricity tariff structure. There is a lack of effective incentive mechanism that induces ice-storage systems from achieving optimal load-shifting results. This study presents an analysis that compares the potential impacts of ice-storage systems on load-shifting under a new credit-based incentive scheme andmore » the existing incentive arrangement in Jiangsu, China. The study indicates that by changing how ice-storage systems are incentivized in Jiangsu, load-shifting results can be improved.« less

Curcumin-loaded chitosan-cholesterol micelles: evaluation in monolayers and 3D cancer spheroid model.

PubMed

Muddineti, Omkara Swami; Kumari, Preeti; Ray, Eupa; Ghosh, Balaram; Biswas, Swati

2017-06-02

To improve the bioavailability and anticancer potential of curcumin by using a cholesterol-conjugated chitosan micelle. Methods & methods: Cholesterol was conjugated to chitosan (15 kDa) to form self-assembled micelles, which loaded curcumin. Physicochemical characterization and formulation optimization of the drug-loaded micelles (curcumin-loaded chitosan-cholesterol micelles [C-CCM]) were performed. In vitro cellular uptake and viability of C-CCM were investigated in melanoma and breast cancer cell lines. The antitumor efficacy was evaluated in 3D lung cancer spheroid model. The optimized C-CCM had size of approximately 162 nm with loading efficiency of approximately 36%. C-CCM was taken up efficiently by the cells, and it reduced cancer cell viability significantly compared with free curcumin. C-CCM enhanced the antitumor efficacy in spheroids, suggesting that C-CCM could be used as an effective chemotherapy in cancer.

Optimization of fed-batch enzymatic hydrolysis from alkali-pretreated sugarcane bagasse for high-concentration sugar production.

PubMed

Gao, Yueshu; Xu, Jingliang; Yuan, Zhenhong; Zhang, Yu; Liu, Yunyun; Liang, Cuiyi

2014-09-01

Fed-batch enzymatic hydrolysis process from alkali-pretreated sugarcane bagasse was investigated to increase solids loading, produce high-concentration fermentable sugar and finally to reduce the cost of the production process. The optimal initial solids loading, feeding time and quantities were examined. The hydrolysis system was initiated with 12% (w/v) solids loading in flasks, where 7% fresh solids were fed consecutively at 6h, 12h, 24h to get a final solids loading of 33%. All the requested cellulase loading (10 FPU/g substrate) was added completely at the beginning of hydrolysis reaction. After 120 h of hydrolysis, the maximal concentrations of cellobiose, glucose and xylose obtained were 9.376 g/L, 129.50 g/L, 56.03 g/L, respectively. The final total glucan conversion rate attained to 60% from this fed-batch process. Copyright © 2014. Published by Elsevier Ltd.

Structural optimization of 3D-printed synthetic spider webs for high strength

NASA Astrophysics Data System (ADS)

Qin, Zhao; Compton, Brett G.; Lewis, Jennifer A.; Buehler, Markus J.

2015-05-01

Spiders spin intricate webs that serve as sophisticated prey-trapping architectures that simultaneously exhibit high strength, elasticity and graceful failure. To determine how web mechanics are controlled by their topological design and material distribution, here we create spider-web mimics composed of elastomeric filaments. Specifically, computational modelling and microscale 3D printing are combined to investigate the mechanical response of elastomeric webs under multiple loading conditions. We find the existence of an asymptotic prey size that leads to a saturated web strength. We identify pathways to design elastomeric material structures with maximum strength, low density and adaptability. We show that the loading type dictates the optimal material distribution, that is, a homogeneous distribution is better for localized loading, while stronger radial threads with weaker spiral threads is better for distributed loading. Our observations reveal that the material distribution within spider webs is dictated by the loading condition, shedding light on their observed architectural variations.

In Respect to the Cognitive Load Theory: Adjusting Instructional Guidance with Student Expertise.

PubMed

Schilling, Jim

2017-01-01

The amount of guidance supplied by educators to students in allied health programs is a factor in student learning. According to the cognitive load theory of learning, without adequate instructional support, novice learners will be overwhelmed and unable to store information, while unnecessary guidance supplied to advanced students will cause extraneous cognitive load on the working memory system. Adjusting instructional guidance for students according to their level of expertise to minimize extraneous cognitive load and optimize working memory storage capacity will enhance learning effectiveness. Novice students presented with complex subject matter require significant guidance during the initial stages, using strategies such as worked examples. As students comprehend information, instructional guidance needs to gradually fade to avoid elevated extraneous cognitive load from the expertise reversal effect. An instructional strategy that utilizes a systemic (fixed) or adjustable (adaptive) tapering of guidance to students in allied health programs depending on their expertise will optimize learning capability.

Structural optimization of 3D-printed synthetic spider webs for high strength.

PubMed

Qin, Zhao; Compton, Brett G; Lewis, Jennifer A; Buehler, Markus J

2015-05-15

Spiders spin intricate webs that serve as sophisticated prey-trapping architectures that simultaneously exhibit high strength, elasticity and graceful failure. To determine how web mechanics are controlled by their topological design and material distribution, here we create spider-web mimics composed of elastomeric filaments. Specifically, computational modelling and microscale 3D printing are combined to investigate the mechanical response of elastomeric webs under multiple loading conditions. We find the existence of an asymptotic prey size that leads to a saturated web strength. We identify pathways to design elastomeric material structures with maximum strength, low density and adaptability. We show that the loading type dictates the optimal material distribution, that is, a homogeneous distribution is better for localized loading, while stronger radial threads with weaker spiral threads is better for distributed loading. Our observations reveal that the material distribution within spider webs is dictated by the loading condition, shedding light on their observed architectural variations.

Michigan | Midmarket Solar Policies in the United States | Solar Research |

Science.gov Websites

program were retained. System size limit: 150 kW Aggregate cap: 0.75% of utility's peak load of the are currently no community solar policies in Michigan. Utilities and third-party developers offer

Hybrid robust predictive optimization method of power system dispatch

DOEpatents

Chandra, Ramu Sharat [Niskayuna, NY; Liu, Yan [Ballston Lake, NY; Bose, Sumit [Niskayuna, NY; de Bedout, Juan Manuel [West Glenville, NY

2011-08-02

A method of power system dispatch control solves power system dispatch problems by integrating a larger variety of generation, load and storage assets, including without limitation, combined heat and power (CHP) units, renewable generation with forecasting, controllable loads, electric, thermal and water energy storage. The method employs a predictive algorithm to dynamically schedule different assets in order to achieve global optimization and maintain the system normal operation.

Two-level optimization of composite wing structures based on panel genetic optimization

NASA Astrophysics Data System (ADS)

Liu, Boyang

The design of complex composite structures used in aerospace or automotive vehicles presents a major challenge in terms of computational cost. Discrete choices for ply thicknesses and ply angles leads to a combinatorial optimization problem that is too expensive to solve with presently available computational resources. We developed the following methodology for handling this problem for wing structural design: we used a two-level optimization approach with response-surface approximations to optimize panel failure loads for the upper-level wing optimization. We tailored efficient permutation genetic algorithms to the panel stacking sequence design on the lower level. We also developed approach for improving continuity of ply stacking sequences among adjacent panels. The decomposition approach led to a lower-level optimization of stacking sequence with a given number of plies in each orientation. An efficient permutation genetic algorithm (GA) was developed for handling this problem. We demonstrated through examples that the permutation GAs are more efficient for stacking sequence optimization than a standard GA. Repair strategies for standard GA and the permutation GAs for dealing with constraints were also developed. The repair strategies can significantly reduce computation costs for both standard GA and permutation GA. A two-level optimization procedure for composite wing design subject to strength and buckling constraints is presented. At wing-level design, continuous optimization of ply thicknesses with orientations of 0°, 90°, and +/-45° is performed to minimize weight. At the panel level, the number of plies of each orientation (rounded to integers) and inplane loads are specified, and a permutation genetic algorithm is used to optimize the stacking sequence. The process begins with many panel genetic optimizations for a range of loads and numbers of plies of each orientation. Next, a cubic polynomial response surface is fitted to the optimum buckling load. The resulting response surface is used for wing-level optimization. In general, complex composite structures consist of several laminates. A common problem in the design of such structures is that some plies in the adjacent laminates terminate in the boundary between the laminates. These discontinuities may cause stress concentrations and may increase manufacturing difficulty and cost. We developed measures of continuity of two adjacent laminates. We studied tradeoffs between weight and continuity through a simple composite wing design. Finally, we compared the two-level optimization to a single-level optimization based on flexural lamination parameters. The single-level optimization is efficient and feasible for a wing consisting of unstiffened panels.

Impact of nitrogen deposition at the species level

PubMed Central

Payne, Richard J.; Dise, Nancy B.; Stevens, Carly J.; Gowing, David J.; Duprè, Cecilia; Dorland, Edu; Gaudnik, Cassandre; Bleeker, Albert; Diekmann, Martin; Alard, Didier; Bobbink, Roland; Fowler, David; Corcket, Emmanuel; Mountford, J. Owen; Vandvik, Vigdis; Aarrestad, Per Arild; Muller, Serge

2013-01-01

In Europe and, increasingly, the rest of the world, the key policy tool for the control of air pollution is the critical load, a level of pollution below which there are no known significant harmful effects on the environment. Critical loads are used to map sensitive regions and habitats, permit individual polluting activities, and frame international negotiations on transboundary air pollution. Despite their fundamental importance in environmental science and policy, there has been no systematic attempt to verify a critical load with field survey data. Here, we use a large dataset of European grasslands along a gradient of nitrogen (N) deposition to show statistically significant declines in the abundance of species from the lowest level of N deposition at which it is possible to identify a change. Approximately 60% of species change points occur at or below the range of the currently established critical load. If this result is found more widely, the underlying principle of no harm in pollution policy may need to be modified to one of informed decisions on how much harm is acceptable. Our results highlight the importance of protecting currently unpolluted areas from new pollution sources, because we cannot rule out ecological impacts from even relatively small increases in reactive N deposition. PMID:23271811

Optimal Load-Side Control for Frequency Regulation in Smart Grids

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

Zhao, Changhong; Mallada, Enrique; Low, Steven

Frequency control rebalances supply and demand while maintaining the network state within operational margins. It is implemented using fast ramping reserves that are expensive and wasteful, and which are expected to become increasingly necessary with the current acceleration of renewable penetration. The most promising solution to this problem is the use of demand response, i.e., load participation in frequency control. Yet it is still unclear how to efficiently integrate load participation without introducing instabilities and violating operational constraints. In this paper, we present a comprehensive load-side frequency control mechanism that can maintain the grid within operational constraints. In particular, ourmore » controllers can rebalance supply and demand after disturbances, restore the frequency to its nominal value, and preserve interarea power flows. Furthermore, our controllers are distributed (unlike the currently implemented frequency control), can allocate load updates optimally, and can maintain line flows within thermal limits. We prove that such a distributed load-side control is globally asymptotically stable and robust to unknown load parameters. We illustrate its effectiveness through simulations.« less

Optimizing the U.S. Electric System with a High Penetration of Renewables

NASA Astrophysics Data System (ADS)

Corcoran, B. A.; Jacobson, M. Z.

2013-12-01

As renewable energy generators are increasingly being installed throughout the U.S., there is growing interest in interconnecting diverse renewable generators (primarily wind and solar) across large geographic areas through an enhanced transmission system. This reduces variability in the aggregate power output, increases system reliability, and allows for the development of the best overall group of renewable technologies and sites to meet the load. Studies are therefore needed to determine the most efficient and economical plan to achieve large area interconnections in a future electric system with a high penetration of renewables. This research quantifies the effects of aggregating electric load together with diverse renewable generation throughout the ten Federal Energy Regulatory Commission (FERC) regions in the contiguous U.S. A deterministic linear program has been built in AMPL (A Mathematical Programming Language) to solve for the least-cost organizational structure and system (generators, transmission, and storage) for a highly renewable electric grid. The analysis will 1) examine a highly renewable 2006 electric system, including various sensitivity cases and additional system components such as additional load from electric vehicles, and 2) create a 'roadmap' from the existing 2006 system to a highly renewable system in 2030, accounting for projected price and demand changes and generator retirements based on age and environmental regulations. Ideally, results from this study will offer insight for a federal renewable energy policy (such as a renewable portfolio standard) and how to best organize U.S. regions for transmission planning.

Drug loading optimization and extended drug delivery of corticoids from pHEMA based soft contact lenses hydrogels via chemical and microstructural modifications.

PubMed

García-Millán, Eva; Koprivnik, Sandra; Otero-Espinar, Francisco Javier

2015-06-20

This paper proposes an approach to improve drug loading capacity and release properties of poly(2-hydroxyethyl methacrylate) (p(HEMA)) soft contact lenses based on the optimization of the hydrogel composition and microstructural modifications using water during the polymerization process. P(HEMA) based soft contact lenses were prepared by thermal or photopolymerization of 2-hydroxyethyl methacrylate (HEMA) solutions containing ethylene glycol di-methacrylate as crosslinker and different proportions of N-vinyl-2-pyrrolidone (NVP) or methacrylic acid (MA) as co-monomers. Transmittance, water uptake, swelling, microstructure, drug absorption isotherms and in vitro release were characterized using triamcinolone acetonide (TA) as model drug. Best drug loading ratios were obtained with lenses containing the highest amount (200 mM) of MA. Incorporation of 40% V/V of water during the polymerization increases the hydrogel porosity giving a better drug loading capacity. In vitro TA release kinetics shows that MA hydrogels released the drug significantly faster than NVP-hydrogels. Drug release was found to be diffusion controlled and kinetics was shown to be reproducible after consecutive drug loading/release processes. Results of p(HEMA) based soft contact lenses copolymerized with ethylene glycol dimethacrylate (EGDMA) and different co-monomers could be a good alternative to optimize the loading and ocular drug delivery of this corticosteroid drug. Copyright © 2015. Published by Elsevier B.V.

Liposome-based mucus-penetrating particles (MPP) for mucosal theranostics: demonstration of diamagnetic chemical exchange saturation transfer (diaCEST) magnetic resonance imaging (MRI).

PubMed

Yu, Tao; Chan, Kannie W Y; Anonuevo, Abraham; Song, Xiaolei; Schuster, Benjamin S; Chattopadhyay, Sumon; Xu, Qingguo; Oskolkov, Nikita; Patel, Himatkumar; Ensign, Laura M; van Zjil, Peter C M; McMahon, Michael T; Hanes, Justin

2015-02-01

Mucus barriers lining mucosal epithelia reduce the effectiveness of nanocarrier-based mucosal drug delivery and imaging ("theranostics"). Here, we describe liposome-based mucus-penetrating particles (MPP) capable of loading hydrophilic agents, e.g., the diaCEST MRI contrast agent barbituric acid (BA). We observed that polyethylene glycol (PEG)-coated liposomes containing ≥7 mol% PEG diffused only ~10-fold slower in human cervicovaginal mucus (CVM) compared to their theoretical speeds in water. 7 mol%-PEG liposomes contained sufficient BA loading for diaCEST contrast, and provided improved vaginal distribution compared to 0 and 3mol%-PEG liposomes. However, increasing PEG content to ~12 mol% compromised BA loading and vaginal distribution, suggesting that PEG content must be optimized to maintain drug loading and stability. Non-invasive diaCEST MRI illustrated uniform vaginal coverage and longer retention of BA-loaded 7 mol%-PEG liposomes compared to unencapsulated BA. Liposomal MPP with optimized PEG content hold promise for drug delivery and imaging at mucosal surfaces. This team of authors characterized liposome-based mucus-penetrating particles (MPP) capable of loading hydrophilic agents, such as barbituric acid (a diaCEST MRI contrast agent) and concluded that liposomal MPP with optimized PEG coating enables drug delivery and imaging at mucosal surfaces. Copyright © 2015 Elsevier Inc. All rights reserved.

Simultaneous optimization of the cavity heat load and trip rates in linacs using a genetic algorithm

DOE PAGES

Terzić, Balša; Hofler, Alicia S.; Reeves, Cody J.; ...

2014-10-15

In this paper, a genetic algorithm-based optimization is used to simultaneously minimize two competing objectives guiding the operation of the Jefferson Lab's Continuous Electron Beam Accelerator Facility linacs: cavity heat load and radio frequency cavity trip rates. The results represent a significant improvement to the standard linac energy management tool and thereby could lead to a more efficient Continuous Electron Beam Accelerator Facility configuration. This study also serves as a proof of principle of how a genetic algorithm can be used for optimizing other linac-based machines.

People adopt optimal policies in simple decision-making, after practice and guidance.

PubMed

Evans, Nathan J; Brown, Scott D

2017-04-01

Organisms making repeated simple decisions are faced with a tradeoff between urgent and cautious strategies. While animals can adopt a statistically optimal policy for this tradeoff, findings about human decision-makers have been mixed. Some studies have shown that people can optimize this "speed-accuracy tradeoff", while others have identified a systematic bias towards excessive caution. These issues have driven theoretical development and spurred debate about the nature of human decision-making. We investigated a potential resolution to the debate, based on two factors that routinely differ between human and animal studies of decision-making: the effects of practice, and of longer-term feedback. Our study replicated the finding that most people, by default, are overly cautious. When given both practice and detailed feedback, people moved rapidly towards the optimal policy, with many participants reaching optimality with less than 1 h of practice. Our findings have theoretical implications for cognitive and neural models of simple decision-making, as well as methodological implications.

Optimal replenishment and credit policy in supply chain inventory model under two levels of trade credit with time- and credit-sensitive demand involving default risk

NASA Astrophysics Data System (ADS)

Mahata, Puspita; Mahata, Gour Chandra; Kumar De, Sujit

2018-03-01

Traditional supply chain inventory modes with trade credit usually only assumed that the up-stream suppliers offered the down-stream retailers a fixed credit period. However, in practice the retailers will also provide a credit period to customers to promote the market competition. In this paper, we formulate an optimal supply chain inventory model under two levels of trade credit policy with default risk consideration. Here, the demand is assumed to be credit-sensitive and increasing function of time. The major objective is to determine the retailer's optimal credit period and cycle time such that the total profit per unit time is maximized. The existence and uniqueness of the optimal solution to the presented model are examined, and an easy method is also shown to find the optimal inventory policies of the considered problem. Finally, numerical examples and sensitive analysis are presented to illustrate the developed model and to provide some managerial insights.

Decentralized stabilization for a class of continuous-time nonlinear interconnected systems using online learning optimal control approach.

PubMed

Liu, Derong; Wang, Ding; Li, Hongliang

2014-02-01

In this paper, using a neural-network-based online learning optimal control approach, a novel decentralized control strategy is developed to stabilize a class of continuous-time nonlinear interconnected large-scale systems. First, optimal controllers of the isolated subsystems are designed with cost functions reflecting the bounds of interconnections. Then, it is proven that the decentralized control strategy of the overall system can be established by adding appropriate feedback gains to the optimal control policies of the isolated subsystems. Next, an online policy iteration algorithm is presented to solve the Hamilton-Jacobi-Bellman equations related to the optimal control problem. Through constructing a set of critic neural networks, the cost functions can be obtained approximately, followed by the control policies. Furthermore, the dynamics of the estimation errors of the critic networks are verified to be uniformly and ultimately bounded. Finally, a simulation example is provided to illustrate the effectiveness of the present decentralized control scheme.

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

PubMed Central

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-01-01

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains. PMID:26972968

Framework Design and Influencing Factor Analysis of a Water Environmental Functional Zone-Based Effluent Trading System.

PubMed

Chen, Lei; Han, Zhaoxing; Li, Shuang; Shen, Zhenyao

2016-10-01

The efficacy of traditional effluent trading systems is questionable due to their neglect of seasonal hydrological variation and the creation of upstream hot spots within a watershed. Besides, few studies have been conducted to distinguish the impacts of each influencing factor on effluent trading systems outputs. In this study, a water environmental functional zone-based effluent trading systems framework was configured and a comprehensive analysis of its influencing factors was conducted. This proposed water environmental functional zone-based effluent trading systems was then applied for the control of chemical oxygen demand in the Beiyun River watershed, Beijing, China. Optimal trading results highlighted the integration of water quality constraints and different hydrological seasons, especially for downstream dischargers. The optimal trading of each discharger, in terms of pollutant reduction load and abatement cost, is greatly influenced by environmental and political factors such as background water quality, the location of river assessment points, and tradable discharge permits. In addition, the initial permit allowance has little influence on the market as a whole but does impact the individual discharger. These results provide information that is critical to understanding the impact of policy design on the functionality of an effluent trading systems.

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.

PubMed

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-03-14

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

Framework Design and Influencing Factor Analysis of a Water Environmental Functional Zone-Based Effluent Trading System

NASA Astrophysics Data System (ADS)

Chen, Lei; Han, Zhaoxing; Li, Shuang; Shen, Zhenyao

2016-10-01

The efficacy of traditional effluent trading systems is questionable due to their neglect of seasonal hydrological variation and the creation of upstream hot spots within a watershed. Besides, few studies have been conducted to distinguish the impacts of each influencing factor on effluent trading systems outputs. In this study, a water environmental functional zone-based effluent trading systems framework was configured and a comprehensive analysis of its influencing factors was conducted. This proposed water environmental functional zone-based effluent trading systems was then applied for the control of chemical oxygen demand in the Beiyun River watershed, Beijing, China. Optimal trading results highlighted the integration of water quality constraints and different hydrological seasons, especially for downstream dischargers. The optimal trading of each discharger, in terms of pollutant reduction load and abatement cost, is greatly influenced by environmental and political factors such as background water quality, the location of river assessment points, and tradable discharge permits. In addition, the initial permit allowance has little influence on the market as a whole but does impact the individual discharger. These results provide information that is critical to understanding the impact of policy design on the functionality of an effluent trading systems.

A model of optimal voluntary muscular control.

PubMed

FitzHugh, R

1977-07-19

In the absence of detailed knowledge of how the CNS controls a muscle through its motor fibers, a reasonable hypothesis is that of optimal control. This hypothesis is studied using a simplified mathematical model of a single muscle, based on A.V. Hill's equations, with series elastic element omitted, and with the motor signal represented by a single input variable. Two cost functions were used. The first was total energy expended by the muscle (work plus heat). If the load is a constant force, with no inertia, Hill's optimal velocity of shortening results. If the load includes a mass, analysis by optimal control theory shows that the motor signal to the muscle consists of three phases: (1) maximal stimulation to accelerate the mass to the optimal velocity as quickly as possible, (2) an intermediate level of stimulation to hold the velocity at its optimal value, once reached, and (3) zero stimulation, to permit the mass to slow down, as quickly as possible, to zero velocity at the specified distance shortened. If the latter distance is too small, or the mass too large, the optimal velocity is not reached, and phase (2) is absent. For lengthening, there is no optimal velocity; there are only two phases, zero stimulation followed by maximal stimulation. The second cost function was total time. The optimal control for shortening consists of only phases (1) and (3) above, and is identical to the minimal energy control whenever phase (2) is absent from the latter. Generalization of this model to include viscous loads and a series elastic element are discussed.

Bionomic Exploitation of a Ratio-Dependent Predator-Prey System

ERIC Educational Resources Information Center

Maiti, Alakes; Patra, Bibek; Samanta, G. P.

2008-01-01

The present article deals with the problem of combined harvesting of a Michaelis-Menten-type ratio-dependent predator-prey system. The problem of determining the optimal harvest policy is solved by invoking Pontryagin's Maximum Principle. Dynamic optimization of the harvest policy is studied by taking the combined harvest effort as a dynamic…

Realistic nurse-led policy implementation, optimization and evaluation: novel methodological exemplar.

PubMed

Noyes, Jane; Lewis, Mary; Bennett, Virginia; Widdas, David; Brombley, Karen

2014-01-01

To report the first large-scale realistic nurse-led implementation, optimization and evaluation of a complex children's continuing-care policy. Health policies are increasingly complex, involve multiple Government departments and frequently fail to translate into better patient outcomes. Realist methods have not yet been adapted for policy implementation. Research methodology - Evaluation using theory-based realist methods for policy implementation. An expert group developed the policy and supporting tools. Implementation and evaluation design integrated diffusion of innovation theory with multiple case study and adapted realist principles. Practitioners in 12 English sites worked with Consultant Nurse implementers to manipulate the programme theory and logic of new decision-support tools and care pathway to optimize local implementation. Methods included key-stakeholder interviews, developing practical diffusion of innovation processes using key-opinion leaders and active facilitation strategies and a mini-community of practice. New and existing processes and outcomes were compared for 137 children during 2007-2008. Realist principles were successfully adapted to a shorter policy implementation and evaluation time frame. Important new implementation success factors included facilitated implementation that enabled 'real-time' manipulation of programme logic and local context to best-fit evolving theories of what worked; using local experiential opinion to change supporting tools to more realistically align with local context and what worked; and having sufficient existing local infrastructure to support implementation. Ten mechanisms explained implementation success and differences in outcomes between new and existing processes. Realistic policy implementation methods have advantages over top-down approaches, especially where clinical expertise is low and unlikely to diffuse innovations 'naturally' without facilitated implementation and local optimization. © 2013 John Wiley & Sons Ltd.

Biomechanical optimization of implant diameter and length for immediate loading: a nonlinear finite element analysis.

PubMed

Kong, Liang; Gu, Zexu; Li, Tao; Wu, Junjie; Hu, Kaijin; Liu, Yanpu; Zhou, Hongzhi; Liu, Baolin

2009-01-01

A nonlinear finite element method was applied to examine the effects of implant diameter and length on the maximum von Mises stresses in the jaw, and to evaluate the maximum displacement of the implant-abutment complex in immediate-loading models. The implant diameter (D) ranged from 3.0 to 5.0 mm and implant length (L) ranged from 6.0 to 16.0 mm. The results showed that the maximum von Mises stress in cortical bone was decreased by 65.8% under a buccolingual load with an increase in D. In cancellous bone, it was decreased by 71.5% under an axial load with an increase in L. The maximum displacement in the implant-abutment complex decreased by 64.8% under a buccolingual load with an increase in D. The implant was found to be more sensitive to L than to D under axial loads, while D played a more important role in enhancing its stability under buccolingual loads. When D exceeded 4.0 mm and L exceeded 11.0 mm, both minimum stress and displacement were obtained. Therefore, these dimensions were the optimal biomechanical selections for immediate-loading implants in type B/2 bone.

An instrumented implant for vertebral body replacement that measures loads in the anterior spinal column.

PubMed

Rohlmann, Antonius; Gabel, Udo; Graichen, Friedmar; Bender, Alwina; Bergmann, Georg

2007-06-01

Realistic loads on a spinal implant are required among others for optimization of implant design and preclinical testing. In addition, such data may help to choose the optimal physiotherapy program for patients with such an implant and to evaluate the efficacy of aids like braces or crutches. Presently, no implant is available that can measure loads in the anterior spinal column during activities of daily life. Therefore, an implant instrumented for in vivo load measurement was developed for vertebral body replacement. The aim of this paper is to describe in detail a telemeterized implant that measures forces and moments acting on it. Six load sensors, a nine-channel telemetry unit and a coil for inductive power supply of the electronic circuits were integrated into a modified vertebral body replacement (Synex). The instrumented part of the implant is hermetically sealed. Patients are videotaped during measurements, and implant loads are displayed on and off line. The average accuracy of load measurement is better than 2% for force and 5% for moment components with reference to the maximum value of 3000 N and 20 Nm, respectively. The measuring implant described here will provide additional information on spinal loads.

Removing Barriers for Effective Deployment of Intermittent Renewable Generation

NASA Astrophysics Data System (ADS)

Arabali, Amirsaman

The stochastic nature of intermittent renewable resources is the main barrier to effective integration of renewable generation. This problem can be studied from feeder-scale and grid-scale perspectives. Two new stochastic methods are proposed to meet the feeder-scale controllable load with a hybrid renewable generation (including wind and PV) and energy storage system. For the first method, an optimization problem is developed whose objective function is the cost of the hybrid system including the cost of renewable generation and storage subject to constraints on energy storage and shifted load. A smart-grid strategy is developed to shift the load and match the renewable energy generation and controllable load. Minimizing the cost function guarantees minimum PV and wind generation installation, as well as storage capacity selection for supplying the controllable load. A confidence coefficient is allocated to each stochastic constraint which shows to what degree the constraint is satisfied. In the second method, a stochastic framework is developed for optimal sizing and reliability analysis of a hybrid power system including renewable resources (PV and wind) and energy storage system. The hybrid power system is optimally sized to satisfy the controllable load with a specified reliability level. A load-shifting strategy is added to provide more flexibility for the system and decrease the installation cost. Load shifting strategies and their potential impacts on the hybrid system reliability/cost analysis are evaluated trough different scenarios. Using a compromise-solution method, the best compromise between the reliability and cost will be realized for the hybrid system. For the second problem, a grid-scale stochastic framework is developed to examine the storage application and its optimal placement for the social cost and transmission congestion relief of wind integration. Storage systems are optimally placed and adequately sized to minimize the sum of operation and congestion costs over a scheduling period. A technical assessment framework is developed to enhance the efficiency of wind integration and evaluate the economics of storage technologies and conventional gas-fired alternatives. The proposed method is used to carry out a cost-benefit analysis for the IEEE 24-bus system and determine the most economical technology. In order to mitigate the financial and technical concerns of renewable energy integration into the power system, a stochastic framework is proposed for transmission grid reinforcement studies in a power system with wind generation. A multi-stage multi-objective transmission network expansion planning (TNEP) methodology is developed which considers the investment cost, absorption of private investment and reliability of the system as the objective functions. A Non-dominated Sorting Genetic Algorithm (NSGA II) optimization approach is used in combination with a probabilistic optimal power flow (POPF) to determine the Pareto optimal solutions considering the power system uncertainties. Using a compromise-solution method, the best final plan is then realized based on the decision maker preferences. The proposed methodology is applied to the IEEE 24-bus Reliability Tests System (RTS) to evaluate the feasibility and practicality of the developed planning strategy.

Optimal contant time injection policy for enhanced oil recovery and characterization of optimal viscous profiles

NASA Astrophysics Data System (ADS)

Daripa, Prabir

2011-11-01

We numerically investigate the optimal viscous profile in constant time injection policy of enhanced oil recovery. In particular, we investigate the effect of a combination of interfacial and layer instabilities in three-layer porous media flow on the overall growth of instabilities and thereby characterize the optimal viscous profile. Results based on monotonic and non-monotonic viscous profiles will be presented. Time permitting. we will also present results on multi-layer porous media flows for Newtonian and non-Newtonian fluids and compare the results. The support of Qatar National Fund under a QNRF Grant is acknowledged.

A model of interaction between anticorruption authority and corruption groups

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

Neverova, Elena G.; Malafeyef, Oleg A.

The paper provides a model of interaction between anticorruption unit and corruption groups. The main policy functions of the anticorruption unit involve reducing corrupt practices in some entities through an optimal approach to resource allocation and effective anticorruption policy. We develop a model based on Markov decision-making process and use Howard’s policy-improvement algorithm for solving an optimal decision strategy. We examine the assumption that corruption groups retaliate against the anticorruption authority to protect themselves. This model was implemented through stochastic game.

Blast protection of infrastructure using advanced composites

NASA Astrophysics Data System (ADS)

Brodsky, Evan

This research was a systematic investigation detailing the energy absorption mechanisms of an E-glass web core composite sandwich panel subjected to an impulse loading applied orthogonal to the facesheet. Key roles of the fiberglass and polyisocyanurate foam material were identified, characterized, and analyzed. A quasi-static test fixture was used to compressively load a unit cell web core specimen machined from the sandwich panel. The web and foam both exhibited non-linear stress-strain responses during axial compressive loading. Through several analyses, the composite web situated in the web core had failed in axial compression. Optimization studies were performed on the sandwich panel unit cell in order to maximize the energy absorption capabilities of the web core. Ultimately, a sandwich panel was designed to optimize the energy dissipation subjected to through-the-thickness compressive loading.

Controller design for wind turbine load reduction via multiobjective parameter synthesis

NASA Astrophysics Data System (ADS)

Hoffmann, A. F.; Weiβ, F. A.

2016-09-01

During the design process for a wind turbine load reduction controller many different, sometimes conflicting requirements must be fulfilled simultaneously. If the requirements can be expressed as mathematical criteria, such a design problem can be solved by a criterion-vector and multi-objective design optimization. The software environment MOPS (Multi-Objective Parameter Synthesis) supports the engineer for such a design optimization. In this paper MOPS is applied to design a multi-objective load reduction controller for the well-known DTU 10 MW reference wind turbine. A significant reduction in the fatigue criteria especially the blade damage can be reached by the use of an additional Individual Pitch Controller (IPC) and an additional tower damper. This reduction is reached as a trade-off with an increase of actuator load.

Energy audit data for a resort island in the South China Sea

PubMed Central

Basir Khan, M. Reyasudin; Jidin, Razali; Pasupuleti, Jagadeesh

2015-01-01

The data consists of actual generation-side auditing including the distribution of loads, seasonal load profiles, and types of loads as well as an analysis of local development planning of a resort island in the South China Sea. The data has been used to propose an optimal combination of hybrid renewable energy systems that able to mitigate the diesel fuel dependency on the island. The resort island selected is Tioman, as it represents the typical energy requirements of many resort islands in the South China Sea. The data presented are related to the research article “Optimal Combination of Solar, Wind, Micro-Hydro and Diesel Systems based on Actual Seasonal Load Profiles for a Resort Island in the South China Sea” [1]. PMID:26900590

Enhanced method of fast re-routing with load balancing in software-defined networks

NASA Astrophysics Data System (ADS)

Lemeshko, Oleksandr; Yeremenko, Oleksandra

2017-11-01

A two-level method of fast re-routing with load balancing in a software-defined network (SDN) is proposed. The novelty of the method consists, firstly, in the introduction of a two-level hierarchy of calculating the routing variables responsible for the formation of the primary and backup paths, and secondly, in ensuring a balanced load of the communication links of the network, which meets the requirements of the traffic engineering concept. The method provides implementation of link, node, path, and bandwidth protection schemes for fast re-routing in SDN. The separation in accordance with the interaction prediction principle along two hierarchical levels of the calculation functions of the primary (lower level) and backup (upper level) routes allowed to abandon the initial sufficiently large and nonlinear optimization problem by transiting to the iterative solution of linear optimization problems of half the dimension. The analysis of the proposed method confirmed its efficiency and effectiveness in terms of obtaining optimal solutions for ensuring balanced load of communication links and implementing the required network element protection schemes for fast re-routing in SDN.

Evaluation of multiple muscle loads through multi-objective optimization with prediction of subjective satisfaction level: illustration by an application to handrail position for standing.

PubMed

Chihara, Takanori; Seo, Akihiko

2014-03-01

Proposed here is an evaluation of multiple muscle loads and a procedure for determining optimum solutions to ergonomic design problems. The simultaneous muscle load evaluation is formulated as a multi-objective optimization problem, and optimum solutions are obtained for each participant. In addition, one optimum solution for all participants, which is defined as the compromise solution, is also obtained. Moreover, the proposed method provides both objective and subjective information to support the decision making of designers. The proposed method was applied to the problem of designing the handrail position for the sit-to-stand movement. The height and distance of the handrails were the design variables, and surface electromyograms of four muscles were measured. The optimization results suggest that the proposed evaluation represents the impressions of participants more completely than an independent use of muscle loads. In addition, the compromise solution is determined, and the benefits of the proposed method are examined. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Real time PI-backstepping induction machine drive with efficiency optimization.

PubMed

Farhani, Fethi; Ben Regaya, Chiheb; Zaafouri, Abderrahmen; Chaari, Abdelkader

2017-09-01

This paper describes a robust and efficient speed control of a three phase induction machine (IM) subjected to load disturbances. First, a Multiple-Input Multiple-Output (MIMO) PI-Backstepping controller is proposed for a robust and highly accurate tracking of the mechanical speed and rotor flux. Asymptotic stability of the control scheme is proven by Lyapunov Stability Theory. Second, an active online optimization algorithm is used to optimize the efficiency of the drive system. The efficiency improvement approach consists of adjusting the rotor flux with respect to the load torque in order to minimize total losses in the IM. A dSPACE DS1104 R&D board is used to implement the proposed solution. The experimental results released on 3kW squirrel cage IM, show that the reference speed as well as the rotor flux are rapidly achieved with a fast transient response and without overshoot. A good load disturbances rejection response and IM parameters variation are fairly handled. The improvement of drive system efficiency reaches up to 180% at light load. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Optimal Scheduling Method of Controllable Loads in DC Smart Apartment Building

NASA Astrophysics Data System (ADS)

Shimoji, Tsubasa; Tahara, Hayato; Matayoshi, Hidehito; Yona, Atsushi; Senjyu, Tomonobu

2015-12-01

From the perspective of global warming suppression and the depletion of energy resources, renewable energies, such as the solar collector (SC) and photovoltaic generation (PV), have been gaining attention in worldwide. Houses or buildings with PV and heat pumps (HPs) are recently being used in residential areas widely due to the time of use (TOU) electricity pricing scheme which is essentially inexpensive during middle-night and expensive during day-time. If fixed batteries and electric vehicles (EVs) can be introduced in the premises, the electricity cost would be even more reduced. While, if the occupants arbitrarily use these controllable loads respectively, power demand in residential buildings may fluctuate in the future. Thus, an optimal operation of controllable loads such as HPs, batteries and EV should be scheduled in the buildings in order to prevent power flow from fluctuating rapidly. This paper proposes an optimal scheduling method of controllable loads, and the purpose is not only the minimization of electricity cost for the consumers, but also suppression of fluctuation of power flow on the power supply side. Furthermore, a novel electricity pricing scheme is also suggested in this paper.

Influence of linear profile modification and loading conditions on the dynamic tooth load and stress of high contact ratio gears

NASA Technical Reports Server (NTRS)

Lee, Chinwai; Lin, Hsiang Hsi; Oswald, Fred B.; Townsend, Dennis P.

1990-01-01

A computer simulation for the dynamic response of high-contact-ratio spur gear transmissions is presented. High contact ratio gears have the potential to produce lower dynamic tooth loads and minimum root stress but they can be sensitive to tooth profile errors. The analysis presented examines various profile modifications under realistic loading conditions. The effect of these modifications on the dynamic load (force) between mating gear teeth and the dynamic root stress is presented. Since the contact stress is dependent on the dynamic load, minimizing dynamic loads will also minimize contact stresses. It is shown that the combination of profile modification and the applied load (torque) carried by a gear system has a significant influence on gear dynamics. The ideal modification at one value of applied load will not be the best solution for a different load. High-contact-ratio gears were found to require less modification than standard low-contact-ratio gears. High-contact-ratio gears are more adversely affected by excess modification than by under modification. In addition, the optimal profile modification required to minimize the dynamic load (hence the contact stress) on a gear tooth differs from the optimal modification required to minimize the dynamic root (bending) stress. Computer simulation can help find the design tradeoffs to determine the best profile modification to satisfy the conflicting constraints of minimizing both the load and root stress in gears which must operate over a range of applied loads.

The importance of environmental variability and management control error to optimal harvest policies

USGS Publications Warehouse

Hunter, C.M.; Runge, M.C.

2004-01-01

State-dependent strategies (SDSs) are the most general form of harvest policy because they allow the harvest rate to depend, without constraint, on the state of the system. State-dependent strategies that provide an optimal harvest rate for any system state can be calculated, and stochasticity can be appropriately accommodated in this optimization. Stochasticity poses 2 challenges to harvest policies: (1) the population will never be at the equilibrium state; and (2) stochasticity induces uncertainty about future states. We investigated the effects of 2 types of stochasticity, environmental variability and management control error, on SDS harvest policies for a white-tailed deer (Odocoileus virginianus) model, and contrasted these with a harvest policy based on maximum sustainable yield (MSY). Increasing stochasticity resulted in more conservative SDSs; that is, higher population densities were required to support the same harvest rate, but these effects were generally small. As stochastic effects increased, SDSs performed much better than MSY. Both deterministic and stochastic SDSs maintained maximum mean annual harvest yield (AHY) and optimal equilibrium population size (Neq) in a stochastic environment, whereas an MSY policy could not. We suggest 3 rules of thumb for harvest management of long-lived vertebrates in stochastic systems: (1) an SDS is advantageous over an MSY policy, (2) using an SDS rather than an MSY is more important than whether a deterministic or stochastic SDS is used, and (3) for SDSs, rankings of the variability in management outcomes (e.g., harvest yield) resulting from parameter stochasticity can be predicted by rankings of the deterministic elasticities.

Reducing stock-outs of essential tuberculosis medicines: a system dynamics modelling approach to supply chain management.

PubMed

Bam, L; McLaren, Z M; Coetzee, E; von Leipzig, K H

2017-10-01

The under-performance of supply chains presents a significant hindrance to disease control in developing countries. Stock-outs of essential medicines lead to treatment interruption which can force changes in patient drug regimens, drive drug resistance and increase mortality. This study is one of few to quantitatively evaluate the effectiveness of supply chain policies in reducing shortages and costs. This study develops a systems dynamics simulation model of the downstream supply chain for amikacin, a second-line tuberculosis drug using 10 years of South African data. We evaluate current supply chain performance in terms of reliability, responsiveness and agility, following the widely-used Supply Chain Operation Reference framework. We simulate 141 scenarios that represent different combinations of supplier characteristics, inventory management strategies and demand forecasting methods to identify the Pareto optimal set of management policies that jointly minimize the number of shortages and total cost. Despite long supplier lead times and unpredictable demand, the amikacin supply chain is 98% reliable and agile enough to accommodate a 20% increase in demand without a shortage. However, this is accomplished by overstocking amikacin by 167%, which incurs high holding costs. The responsiveness of suppliers is low: only 57% of orders are delivered to the central provincial drug depot within one month. We identify three Pareto optimal safety stock management policies. Short supplier lead time can produce Pareto optimal outcomes even in the absence of other optimal policies. This study produces concrete, actionable guidelines to cost-effectively reduce stock-outs by implementing optimal supply chain policies. Preferentially selecting drug suppliers with short lead times accommodates unexpected changes in demand. Optimal supply chain management should be an essential component of national policy to reduce the mortality rate. © The Author 2017. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

An improved simulation based biomechanical model to estimate static muscle loadings

NASA Technical Reports Server (NTRS)

Rajulu, Sudhakar L.; Marras, William S.; Woolford, Barbara

1991-01-01

The objectives of this study are to show that the characteristics of an intact muscle are different from those of an isolated muscle and to describe a simulation based model. This model, unlike the optimization based models, accounts for the redundancy in the musculoskeletal system in predicting the amount of forces generated within a muscle. The results of this study show that the loading of the primary muscle is increased by the presence of other muscle activities. Hence, the previous models based on optimization techniques may underestimate the severity of the muscle and joint loadings which occur during manual material handling tasks.

Optimal implementation of best management practices to improve agricultural hydrology and water quality

NASA Astrophysics Data System (ADS)

Liu, Y.; Engel, B.; Collingsworth, P.; Pijanowski, B. C.

2017-12-01

Nutrient loading from the Maumee River watershed is a significant reason for the harmful algal blooms (HABs) problem in Lake Erie. Strategies to reduce nutrient loading from agricultural areas in the Maumee River watershed need to be explored. Best management practices (BMPs) are popular approaches for improving hydrology and water quality. Various scenarios of BMP implementation were simulated in the AXL watershed (an agricultural watershed in Maumee River watershed) using Soil and Water Assessment Tool (SWAT) and a new BMP cost tool to explore the cost-effectiveness of the practices. BMPs of interest included vegetative filter strips, grassed waterways, blind inlets, grade stabilization structures, wetlands, no-till, nutrient management, residue management, and cover crops. The following environmental concerns were considered: streamflow, Total Phosphorous (TP), Dissolved Reactive Phosphorus (DRP), Total Kjeldahl Nitrogen (TKN), and Nitrate+Nitrite (NOx). To obtain maximum hydrological and water quality benefits with minimum cost, an optimization tool was developed to optimally select and place BMPs by connecting SWAT, the BMP cost tool, and optimization algorithms. The optimization tool was then applied in AXL watershed to explore optimization focusing on critical areas (top 25% of areas with highest runoff volume/pollutant loads per area) vs. all areas of the watershed, optimization using weather data for spring (March to July, due to the goal of reducing spring phosphorus in watershed management plan) vs. full year, and optimization results of implementing BMPs to achieve the watershed management plan goal (reducing 2008 TP levels by 40%). The optimization tool and BMP optimization results can be used by watershed groups and communities to solve hydrology and water quality problems.

Optimal design and use of retry in fault tolerant real-time computer systems

NASA Technical Reports Server (NTRS)

Lee, Y. H.; Shin, K. G.

1983-01-01

A new method to determin an optimal retry policy and for use in retry of fault characterization is presented. An optimal retry policy for a given fault characteristic, which determines the maximum allowable retry durations to minimize the total task completion time was derived. The combined fault characterization and retry decision, in which the characteristics of fault are estimated simultaneously with the determination of the optimal retry policy were carried out. Two solution approaches were developed, one based on the point estimation and the other on the Bayes sequential decision. The maximum likelihood estimators are used for the first approach, and the backward induction for testing hypotheses in the second approach. Numerical examples in which all the durations associated with faults have monotone hazard functions, e.g., exponential, Weibull and gamma distributions are presented. These are standard distributions commonly used for modeling analysis and faults.

Optimization of methazolamide-loaded solid lipid nanoparticles for ophthalmic delivery using Box-Behnken design.

PubMed

Wang, Fengzhen; Chen, Li; Jiang, Sunmin; He, Jun; Zhang, Xiumei; Peng, Jin; Xu, Qunwei; Li, Rui

2014-09-01

The purpose of the present study was to optimize methazolamide (MTZ)-loaded solid lipid nanoparticles (SLNs) which were used as topical eye drops by evaluating the relationship between design factors and experimental data. A three factor, three-level Box-Behnken design (BBD) was used for the optimization procedure, choosing the amount of GMS, the amount of phospholipid, the concentration of surfactant as the independent variables. The chosen dependent variables were entrapment efficiency, dosage loading, and particle size. The generated polynomial equations and response surface plots were used to relate the dependent and independent variables. The optimal nanoparticles were formulated with 100 mg GMS, 150 mg phospholipid, and 1% Tween80 and PEG 400 (1:1, w/v). A new formulation was prepared according to these levels. The observed responses were close to the predicted values of the optimized formulation. The particle size was 197.8 ± 4.9 nm. The polydispersity index of particle size was 0.239 ± 0.01 and the zeta potential was 32.7 ± 2.6 mV. The entrapment efficiency and dosage loading were about 68.39% and 2.49%, respectively. Fourier transform infrared spectroscopy (FT-IR) study indicated that the drug was entrapped in nanoparticles. The optimized formulation showed a sustained release followed the Peppas model. MTZ-SLNs showed significant prolonged decreasing intraocular pressure effect comparing with MTZ solution in vivo pharmacodynamics studies. The results of acute eye irritation study indicated that MTZ-SLNs and AZOPT both had no eye irritation. Furthermore, the MTZ-SLNs were suitable to be stored at low temperature (4 °C).

Optimal Base Station Density of Dense Network: From the Viewpoint of Interference and Load.

PubMed

Feng, Jianyuan; Feng, Zhiyong

2017-09-11

Network densification is attracting increasing attention recently due to its ability to improve network capacity by spatial reuse and relieve congestion by offloading. However, excessive densification and aggressive offloading can also cause the degradation of network performance due to problems of interference and load. In this paper, with consideration of load issues, we study the optimal base station density that maximizes the throughput of the network. The expected link rate and the utilization ratio of the contention-based channel are derived as the functions of base station density using the Poisson Point Process (PPP) and Markov Chain. They reveal the rules of deployment. Based on these results, we obtain the throughput of the network and indicate the optimal deployment density under different network conditions. Extensive simulations are conducted to validate our analysis and show the substantial performance gain obtained by the proposed deployment scheme. These results can provide guidance for the network densification.

Analysis, Design and Optimization of Non-Cylindrical Fuselage for Blended-Wing-Body (BWB) Vehicle

NASA Technical Reports Server (NTRS)

Mukhopadhyay, V.; Sobieszczanski-Sobieski, J.; Kosaka, I.; Quinn, G.; Charpentier, C.

2002-01-01

Initial results of an investigation towards finding an efficient non-cylindrical fuselage configuration for a conceptual blended-wing-body flight vehicle were presented. A simplified 2-D beam column analysis and optimization was performed first. Then a set of detailed finite element models of deep sandwich panel and ribbed shell construction concepts were analyzed and optimized. Generally these concepts with flat surfaces were found to be structurally inefficient to withstand internal pressure and resultant compressive loads simultaneously. Alternatively, a set of multi-bubble fuselage configuration concepts were developed for balancing internal cabin pressure load efficiently, through membrane stress in inner-stiffened shell and inter-cabin walls. An outer-ribbed shell was designed to prevent buckling due to external resultant compressive loads. Initial results from finite element analysis appear to be promising. These concepts should be developed further to exploit their inherent structurally efficiency.

Wing Weight Optimization Under Aeroelastic Loads Subject to Stress Constraints

NASA Technical Reports Server (NTRS)

Kapania, Rakesh K.; Issac, J.; Macmurdy, D.; Guruswamy, Guru P.

1997-01-01

A minimum weight optimization of the wing under aeroelastic loads subject to stress constraints is carried out. The loads for the optimization are based on aeroelastic trim. The design variables are the thickness of the wing skins and planform variables. The composite plate structural model incorporates first-order shear deformation theory, the wing deflections are expressed using Chebyshev polynomials and a Rayleigh-Ritz procedure is adopted for the structural formulation. The aerodynamic pressures provided by the aerodynamic code at a discrete number of grid points is represented as a bilinear distribution on the composite plate code to solve for the deflections and stresses in the wing. The lifting-surface aerodynamic code FAST is presently being used to generate the pressure distribution over the wing. The envisioned ENSAERO/Plate is an aeroelastic analysis code which combines ENSAERO version 3.0 (for analysis of wing-body configurations) with the composite plate code.

Design and Optimization of Slot Aluminum Alloy Connectors of Photovoltaics Applied to High-rise Building Facades

NASA Astrophysics Data System (ADS)

Liang, Ya-Wei; Zhang, Hong-Mei; Dong, Jin-Zhi; Shi, Zhen-Hua

2016-05-01

Building Integrated Photovoltaic (BIPV) is a resort to save energy and reduce heat gain of buildings, utilize new and renewable energy, solve environment problems and alleviate electricity shortage in large cities. The area needed to generate power makes facade integrated photovoltaic panel a superb choice, especially in high-rise buildings. Numerous scholars have hitherto explored Building Facade Integrated Photovoltaic, however, focusing mainly on thermal performance, which fails to ensure seismic safety of high-rise buildings integrated photovoltaic. Based on connecting forms of the glass curtain wall, a connector jointing photovoltaic panel and facade was designed, which underwent loading position and size optimization. Static loading scenarios were conducted to test and verify the connector's mechanical properties under gravity and wind loading by means of HyperWorks. Compared to the unoptimized design, the optimized one saved material and managed to reduce maximum deflection by 74.64%.

Structural optimization procedure of a composite wind turbine blade for reducing both material cost and blade weight

NASA Astrophysics Data System (ADS)

Hu, Weifei; Park, Dohyun; Choi, DongHoon

2013-12-01

A composite blade structure for a 2 MW horizontal axis wind turbine is optimally designed. Design requirements are simultaneously minimizing material cost and blade weight while satisfying the constraints on stress ratio, tip deflection, fatigue life and laminate layup requirements. The stress ratio and tip deflection under extreme gust loads and the fatigue life under a stochastic normal wind load are evaluated. A blade element wind load model is proposed to explain the wind pressure difference due to blade height change during rotor rotation. For fatigue life evaluation, the stress result of an implicit nonlinear dynamic analysis under a time-varying fluctuating wind is converted to the histograms of mean and amplitude of maximum stress ratio using the rainflow counting algorithm Miner's rule is employed to predict the fatigue life. After integrating and automating the whole analysis procedure an evolutionary algorithm is used to solve the discrete optimization problem.

Energy management of a university campus utilizing short-term load forecasting with an artificial neural network

NASA Astrophysics Data System (ADS)

Palchak, David

Electrical load forecasting is a tool that has been utilized by distribution designers and operators as a means for resource planning and generation dispatch. The techniques employed in these predictions are proving useful in the growing market of consumer, or end-user, participation in electrical energy consumption. These predictions are based on exogenous variables, such as weather, and time variables, such as day of week and time of day as well as prior energy consumption patterns. The participation of the end-user is a cornerstone of the Smart Grid initiative presented in the Energy Independence and Security Act of 2007, and is being made possible by the emergence of enabling technologies such as advanced metering infrastructure. The optimal application of the data provided by an advanced metering infrastructure is the primary motivation for the work done in this thesis. The methodology for using this data in an energy management scheme that utilizes a short-term load forecast is presented. The objective of this research is to quantify opportunities for a range of energy management and operation cost savings of a university campus through the use of a forecasted daily electrical load profile. The proposed algorithm for short-term load forecasting is optimized for Colorado State University's main campus, and utilizes an artificial neural network that accepts weather and time variables as inputs. The performance of the predicted daily electrical load is evaluated using a number of error measurements that seek to quantify the best application of the forecast. The energy management presented utilizes historical electrical load data from the local service provider to optimize the time of day that electrical loads are being managed. Finally, the utilization of forecasts in the presented energy management scenario is evaluated based on cost and energy savings.

Delivery of adapalene using a novel topical gel based on tea tree oil nano-emulsion: Permeation, antibacterial and safety assessments.

PubMed

Najafi-Taher, Roqya; Ghaemi, Behnaz; Amani, Amir

2018-07-30

The aim of present study was to design and optimize 0.1% adapalene loaded nano-emulsion to improve the drug efficacy and increase its user compliance. Effect of type and concentration of surfactants was studied on size of 0.1% adapalene loaded nano-emulsion. Optimized formulation was then evaluated for particle size, polydispersity index, morphology, viscosity, and pH. Subsequently, 1% carbopol® 934 was incorporated to the optimized formulation for preparation of its gel form. The efficacy and safety of 0.1% adapalene loaded nano-emulsion gel was assessed compared to marketed gel containing 0.1% adapalene. In-vitro studies showed that adapalene permeation through the skin was negligible in both adapalene loaded nano-emulsion gel and adapalene marketed gel. Furthermore, drug distribution studies in skin indicated higher retention of adapalene in the dermis in adapalene loaded nano-emulsion gel compared with adapalene marketed gel. Antibacterial activity against Propionibacterium acnes showed that adapalene loaded nano-emulsion is effective in reducing minimum inhibitory concentration of the formulation in comparison with tea tree oil nano-emulsion, and pure tea tree oil. In vivo skin irritation studies showed absence of irritancy for adapalene loaded nano-emulsion gel. Also, blood and liver absorption of the drug, histological analysis of liver and liver enzyme activity of rats after 90 days' treatment were investigated. No drug was detected in blood/liver which in addition to an absence of any adverse effect on liver and enzymes showed the potential of adapalene loaded nano-emulsion gel as a novel carrier for topical delivery of adapalene. Copyright © 2018 Elsevier B.V. All rights reserved.

Specimen Designs for Testing Advanced Aeropropulsion Materials Under In-Plane Biaxial Loading

NASA Technical Reports Server (NTRS)

Ellis, John R.; Abul-Aziz, Ali

2003-01-01

A design study was undertaken to develop specimen designs for testing advanced aeropropulsion materials under in-plane biaxial loading. The focus of initial work was on developing a specimen design suitable for deformation and strength tests to be conducted under monotonic loading. The type of loading initially assumed in this study was the special case of equibiaxial, tensile loading. A specimen design was successfully developed after a lengthy design and optimization process with overall dimensions of 12 by 12 by 0.625 in., and a gage area of 3.875 by 3.875 by 0.080 in. Subsequently, the scope of the work was extended to include the development of a second design tailored for tests involving cyclic loading. A specimen design suitably tailored to meet these requirements was successfully developed with overall dimensions of 12 by 12 by 0.500 in. and a gage area of 2.375 by 2.375 by 0.050 in. Finally, an investigation was made to determine whether the specimen designs developed in this study for equibiaxial, tensile loading could be used without modification to investigate general forms of biaxial loading. For best results, it was concluded that specimen designs need to be optimized and tailored to meet the specific loading requirements of individual research programs.

Applying graph partitioning methods in measurement-based dynamic load balancing

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

Bhatele, Abhinav; Fourestier, Sebastien; Menon, Harshitha

Load imbalance leads to an increasing waste of resources as an application is scaled to more and more processors. Achieving the best parallel efficiency for a program requires optimal load balancing which is a NP-hard problem. However, finding near-optimal solutions to this problem for complex computational science and engineering applications is becoming increasingly important. Charm++, a migratable objects based programming model, provides a measurement-based dynamic load balancing framework. This framework instruments and then migrates over-decomposed objects to balance computational load and communication at runtime. This paper explores the use of graph partitioning algorithms, traditionally used for partitioning physical domains/meshes, formore » measurement-based dynamic load balancing of parallel applications. In particular, we present repartitioning methods developed in a graph partitioning toolbox called SCOTCH that consider the previous mapping to minimize migration costs. We also discuss a new imbalance reduction algorithm for graphs with irregular load distributions. We compare several load balancing algorithms using microbenchmarks on Intrepid and Ranger and evaluate the effect of communication, number of cores and number of objects on the benefit achieved from load balancing. New algorithms developed in SCOTCH lead to better performance compared to the METIS partitioners for several cases, both in terms of the application execution time and fewer number of objects migrated.« less

Alkaline peroxide pretreatment of corn stover: effects of biomass, peroxide, and enzyme loading and composition on yields of glucose and xylose

PubMed Central

2011-01-01

Background Pretreatment is a critical step in the conversion of lignocellulose to fermentable sugars. Although many pretreatment processes are currently under investigation, none of them are entirely satisfactory in regard to effectiveness, cost, or environmental impact. The use of hydrogen peroxide at pH 11.5 (alkaline hydrogen peroxide (AHP)) was shown by Gould and coworkers to be an effective pretreatment of grass stovers and other plant materials in the context of animal nutrition and ethanol production. Our earlier experiments indicated that AHP performed well when compared against two other alkaline pretreatments. Here, we explored several key parameters to test the potential of AHP for further improvement relevant to lignocellulosic ethanol production. Results The effects of biomass loading, hydrogen peroxide loading, residence time, and pH control were tested in combination with subsequent digestion with a commercial enzyme preparation, optimized mixtures of four commercial enzymes, or optimized synthetic mixtures of pure enzymes. AHP pretreatment was performed at room temperature (23°C) and atmospheric pressure, and after AHP pretreatment the biomass was neutralized with HCl but not washed before enzyme digestion. Standard enzyme digestion conditions were 0.2% glucan loading, 15 mg protein/g glucan, and 48 h digestion at 50°C. Higher pretreatment biomass loadings (10% to 20%) gave higher monomeric glucose (Glc) and xylose (Xyl) yields than the 2% loading used in earlier studies. An H2O2 loading of 0.25 g/g biomass was almost as effective as 0.5 g/g, but 0.125 g/g was significantly less effective. Optimized mixtures of four commercial enzymes substantially increased post-AHP-pretreatment enzymatic hydrolysis yields at all H2O2 concentrations compared to any single commercial enzyme. At a pretreatment biomass loading of 10% and an H2O2 loading of 0.5 g/g biomass, an optimized commercial mixture at total protein loadings of 8 or 15 mg/g glucan gave monomeric Glc yields of 83% or 95%, respectively. Yields of Glc and Xyl after pretreatment at a low hydrogen peroxide loading (0.125 g H2O2/g biomass) could be improved by extending the pretreatment residence time to 48 h and readjusting the pH to 11.5 every 6 h during the pretreatment. A Glc yield of 77% was obtained using a pretreatment of 15% biomass loading, 0.125 g H2O2/g biomass, and 48 h with pH adjustment, followed by digestion with an optimized commercial enzyme mixture at an enzyme loading of 15 mg protein/g glucan. Conclusions Alkaline peroxide is an effective pretreatment for corn stover. Particular advantages are the use of reagents with low environmental impact and avoidance of special reaction chambers. Reasonable yields of monomeric Glc can be obtained at an H2O2 concentration one-quarter of that used in previous AHP research. Additional improvements in the AHP process, such as peroxide stabilization, peroxide recycling, and improved pH control, could lead to further improvements in AHP pretreatment. PMID:21658263

Load research manual. Volume 1. Load research procedures

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

Brandenburg, L.; Clarkson, G.; Grund, Jr., C.

1980-11-01

This three-volume manual presents technical guidelines for electric utility load research. Special attention is given to issues raised by the load data reporting requirements of the Public Utility Regulatory Policies Act of 1978 and to problems faced by smaller utilities that are initiating load research programs. In Volumes 1 and 2, procedures are suggested for determining data requirements for load research, establishing the size and customer composition of a load survey sample, selecting and using equipment to record customer electricity usage, processing data tapes from the recording equipment, and analyzing the data. Statistical techniques used in customer sampling are discussedmore » in detail. The costs of load research also are estimated, and ongoing load research programs at three utilities are described. The manual includes guides to load research literature and glossaries of load research and statistical terms.« less

Combined Municipal Solid Waste and biomass system optimization for district energy applications.

PubMed

Rentizelas, Athanasios A; Tolis, Athanasios I; Tatsiopoulos, Ilias P

2014-01-01

Municipal Solid Waste (MSW) disposal has been a controversial issue in many countries over the past years, due to disagreement among the various stakeholders on the waste management policies and technologies to be adopted. One of the ways of treating/disposing MSW is energy recovery, as waste is considered to contain a considerable amount of bio-waste and therefore can lead to renewable energy production. The overall efficiency can be very high in the cases of co-generation or tri-generation. In this paper a model is presented, aiming to support decision makers in issues relating to Municipal Solid Waste energy recovery. The idea of using more fuel sources, including MSW and agricultural residue biomass that may exist in a rural area, is explored. The model aims at optimizing the system specifications, such as the capacity of the base-load Waste-to-Energy facility, the capacity of the peak-load biomass boiler and the location of the facility. Furthermore, it defines the quantity of each potential fuel source that should be used annually, in order to maximize the financial yield of the investment. The results of an energy tri-generation case study application at a rural area of Greece, using mixed MSW and biomass, indicate positive financial yield of investment. In addition, a sensitivity analysis is performed on the effect of the most important parameters of the model on the optimum solution, pinpointing the parameters of interest rate, investment cost and heating oil price, as those requiring the attention of the decision makers. Finally, the sensitivity analysis is enhanced by a stochastic analysis to determine the effect of the volatility of parameters on the robustness of the model and the solution obtained. Copyright © 2013 Elsevier Ltd. All rights reserved.

A hybrid algorithm optimization approach for machine loading problem in flexible manufacturing system

NASA Astrophysics Data System (ADS)

Kumar, Vijay M.; Murthy, ANN; Chandrashekara, K.

2012-05-01

The production planning problem of flexible manufacturing system (FMS) concerns with decisions that have to be made before an FMS begins to produce parts according to a given production plan during an upcoming planning horizon. The main aspect of production planning deals with machine loading problem in which selection of a subset of jobs to be manufactured and assignment of their operations to the relevant machines are made. Such problems are not only combinatorial optimization problems, but also happen to be non-deterministic polynomial-time-hard, making it difficult to obtain satisfactory solutions using traditional optimization techniques. In this paper, an attempt has been made to address the machine loading problem with objectives of minimization of system unbalance and maximization of throughput simultaneously while satisfying the system constraints related to available machining time and tool slot designing and using a meta-hybrid heuristic technique based on genetic algorithm and particle swarm optimization. The results reported in this paper demonstrate the model efficiency and examine the performance of the system with respect to measures such as throughput and system utilization.

Formulation and Optimization of Multiparticulate Drug Delivery System Approach for High Drug Loading.

PubMed

Shah, Neha; Mehta, Tejal; Gohel, Mukesh

2017-08-01

The aim of the present work was to develop and optimize multiparticulate formulation viz. pellets of naproxen by employing QbD and risk assessment approach. Mixture design with extreme vertices was applied to the formulation with high loading of drug (about 90%) and extrusion-spheronization as a process for manufacturing pellets. Independent variables chosen were level of microcrystalline cellulose (MCC)-X 1 , polyvinylpyrrolidone K-90 (PVP K-90)-X 2 , croscarmellose sodium (CCS)-X 3 , and polacrilin potassium (PP)-X 4 . Dependent variables considered were disintegration time (DT)-Y 1 , sphericity-Y 2 , and percent drug release-Y 3 . The formulation was optimized based on the batches generated by MiniTab 17 software. The batch with maximum composite desirability (0.98) proved to be optimum. From the evaluation of design batches, it was observed that, even in low variation, the excipients affect the pelletization property of the blend and also the final drug release. In conclusion, pellets with high drug loading can be effectively manufactured and optimized systematically using QbD approach.

Optimization of Enzymatic Saccharification of Alkali Pretreated Parthenium sp. Using Response Surface Methodology

PubMed Central

Pandiyan, K.; Tiwari, Rameshwar; Singh, Surender; Nain, Pawan K. S.; Rana, Sarika; Arora, Anju; Singh, Shashi B.; Nain, Lata

2014-01-01

Parthenium sp. is a noxious weed which threatens the environment and biodiversity due to its rapid invasion. This lignocellulosic weed was investigated for its potential in biofuel production by subjecting it to mild alkali pretreatment followed by enzymatic saccharification which resulted in significant amount of fermentable sugar yield (76.6%). Optimization of enzymatic hydrolysis variables such as temperature, pH, enzyme, and substrate loading was carried out using central composite design (CCD) in response to surface methodology (RSM) to achieve the maximum saccharification yield. Data obtained from RSM was validated using ANOVA. After the optimization process, a model was proposed with predicted value of 80.08% saccharification yield under optimum conditions which was confirmed by the experimental value of 85.80%. This illustrated a good agreement between predicted and experimental response (saccharification yield). The saccharification yield was enhanced by enzyme loading and reduced by temperature and substrate loading. This study reveals that under optimized condition, sugar yield was significantly increased which was higher than earlier reports and promises the use of Parthenium sp. biomass as a feedstock for bioethanol production. PMID:24900917

Assessing the Optimal Length of Parental Leave for Child and Parental Well-Being: How Can Research Inform Policy?

ERIC Educational Resources Information Center

Galtry, Judith; Callister, Paul

2005-01-01

Parental leave is a complex area of public policy. Concerns include health protection for working mothers, equal employment opportunities for women, access to adequate antenatal and birthing care, maternal recovery, optimal nutrition for infants, and gender equality within families. Given this complexity, the design of parental leave schemes,…

Continuous Linguistic Rhetorical Education as a Means of Optimizing Language Policy in Russian Multinational Regions

ERIC Educational Resources Information Center

Vorozhbitova, Alexandra A.; Konovalova, Galina M.; Ogneva, Tatiana N.; Chekulaeva, Natalia Y.

2017-01-01

Drawing on the function of Russian as a state language the paper proposes a concept of continuous linguistic rhetorical (LR) education perceived as a means of optimizing language policy in Russian multinational regions. LR education as an innovative pedagogical system shapes a learner's readiness for self-projection as a strong linguistic…

Numerical optimization of open-porous bone scaffold structures to match the elastic properties of human cortical bone.

PubMed

Wieding, Jan; Wolf, Andreas; Bader, Rainer

2014-09-01

Treatment of large segmental bone defects, especially in load bearing areas, is a complex procedure in orthopedic surgery. The usage of additive manufacturing processes enables the creation of customized bone implants with arbitrary open-porous structure satisfying both the mechanical and the biological requirements for a sufficient bone ingrowth. Aim of the present numerical study was to optimize the geometrical parameters of open-porous titanium scaffolds to match the elastic properties of human cortical bone with respect to an adequate pore size. Three different scaffold designs (cubic, diagonal and pyramidal) were numerically investigated by using an optimization approach. Beam elements were used to create the lattice structures of the scaffolds. The design parameters strut diameter and pore size ranged from 0.2 to 1.5mm and from 0 to 3.0mm, respectively. In a first optimization step, the geometrical parameters were varied under uniaxial compression to obtain a structural modulus of 15GPa (Young׳s modulus of cortical bone) and a pore size of 800µm was aimed to enable cell ingrowth. Furthermore, the mechanical behavior of the optimized structures under bending and torsion was investigated. Results for bending modulus were between 9.0 and 14.5GPa. In contrast, shear modulus was lowest for cubic and pyramidal design of approximately 1GPa. Here, the diagonal design revealed a modulus of nearly 20GPa. In a second step, large-sized bone scaffolds were created and placed in a biomechanical loading situation within a 30mm segmental femoral defect, stabilized with an osteosynthesis plate and loaded with physiological muscle forces. Strut diameter for the 17 sections of each scaffold was optimized independently in order to match the biomechanical stability of intact bone. For each design, highest strut diameter was found at the dorsal/medial site of the defect and smallest strut diameter in the center. In conclusion, we demonstrated the possibility of providing optimized open-porous scaffolds for bone regeneration by considering both mechanical and biological aspects. Furthermore, the results revealed the need of the investigation and comparison of different load scenarios (compression, bending and torsion) as well as complex biomechanical loading for a profound characterization of different scaffold designs. The usage of a numerical optimization process was proven to be a feasible tool to reduce the amount of the required titanium material without influencing the biomechanical performance of the scaffold negatively. By using fully parameterized models, the optimization approach is adaptable to other scaffold designs and bone defect situations. Copyright © 2014 Elsevier Ltd. All rights reserved.

A hybrid inventory management system respondingto regular demand and surge demand

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

Mohammad S. Roni; Mingzhou Jin; Sandra D. Eksioglu

2014-06-01

This paper proposes a hybrid policy for a stochastic inventory system facing regular demand and surge demand. The combination of two different demand patterns can be observed in many areas, such as healthcare inventory and humanitarian supply chain management. The surge demand has a lower arrival rate but higher demand volume per arrival. The solution approach proposed in this paper incorporates the level crossing method and mixed integer programming technique to optimize the hybrid inventory policy with both regular orders and emergency orders. The level crossing method is applied to obtain the equilibrium distributions of inventory levels under a givenmore » policy. The model is further transformed into a mixed integer program to identify an optimal hybrid policy. A sensitivity analysis is conducted to investigate the impact of parameters on the optimal inventory policy and minimum cost. Numerical results clearly show the benefit of using the proposed hybrid inventory model. The model and solution approach could help healthcare providers or humanitarian logistics providers in managing their emergency supplies in responding to surge demands.« less

Development, optimization, and in vitro characterization of dasatinib-loaded PEG functionalized chitosan capped gold nanoparticles using Box-Behnken experimental design.

PubMed

Adena, Sandeep Kumar Reddy; Upadhyay, Mansi; Vardhan, Harsh; Mishra, Brahmeshwar

2018-03-01

The purpose of this research study was to develop, optimize, and characterize dasatinib loaded polyethylene glycol (PEG) stabilized chitosan capped gold nanoparticles (DSB-PEG-Ch-GNPs). Gold (III) chloride hydrate was reduced with chitosan and the resulting nanoparticles were coated with thiol-terminated PEG and loaded with dasatinib (DSB). Plackett-Burman design (PBD) followed by Box-Behnken experimental design (BBD) were employed to optimize the process parameters. Polynomial equations, contour, and 3D response surface plots were generated to relate the factors and responses. The optimized DSB-PEG-Ch-GNPs were characterized by FTIR, XRD, HR-SEM, EDX, TEM, SAED, AFM, DLS, and ZP. The results of the optimized DSB-PEG-Ch-GNPs showed particle size (PS) of 24.39 ± 1.82 nm, apparent drug content (ADC) of 72.06 ± 0.86%, and zeta potential (ZP) of -13.91 ± 1.21 mV. The responses observed and the predicted values of the optimized process were found to be close. The shape and surface morphology studies showed that the resulting DSB-PEG-Ch-GNPs were spherical and smooth. The stability and in vitro drug release studies confirmed that the optimized formulation was stable at different conditions of storage and exhibited a sustained drug release of the drug of up to 76% in 48 h and followed Korsmeyer-Peppas release kinetic model. A process for preparing gold nanoparticles using chitosan, anchoring PEG to the particle surface, and entrapping dasatinib in the chitosan-PEG surface corona was optimized.

Moderate temperature control technology for a lunar base

NASA Technical Reports Server (NTRS)

Swanson, Theodore D.; Sridhar, K. R.; Gottmann, Matthias

1993-01-01

A parametric analysis is performed to compare different heat pump based thermal control systems for a Lunar Base. Rankine cycle and absorption cycle heat pumps are compared and optimized for a 100 kW cooling load. Variables include the use or lack of an interface heat exchanger, and different operating fluids. Optimization of system mass to radiator rejection temperature is performed. The results indicate a relatively small sensitivity of Rankine cycle system mass to these variables, with optimized system masses of about 6000 kg for the 100 kW thermal load. It is quantitaively demonstrated that absorption based systems are not mass competitive with Rankine systems.

Optimization study on inductive-resistive circuit for broadband piezoelectric energy harvesters

NASA Astrophysics Data System (ADS)

Tan, Ting; Yan, Zhimiao

2017-03-01

The performance of cantilever-beam piezoelectric energy harvester is usually analyzed with pure resistive circuit. The optimal performance of such a vibration-based energy harvesting system is limited by narrow bandwidth around its modified natural frequency. For broadband piezoelectric energy harvesting, series and parallel inductive-resistive circuits are introduced. The electromechanical coupled distributed parameter models for such systems under harmonic base excitations are decoupled with modified natural frequency and electrical damping to consider the coupling effect. Analytical solutions of the harvested power and tip displacement for the electromechanical decoupled model are confirmed with numerical solutions for the coupled model. The optimal performance of piezoelectric energy harvesting with inductive-resistive circuits is revealed theoretically as constant maximal power at any excitation frequency. This is achieved by the scenarios of matching the modified natural frequency with the excitation frequency and equating the electrical damping to the mechanical damping. The inductance and load resistance should be simultaneously tuned to their optimal values, which may not be applicable for very high electromechanical coupling systems when the excitation frequency is higher than their natural frequencies. With identical optimal performance, the series inductive-resistive circuit is recommended for relatively small load resistance, while the parallel inductive-resistive circuit is suggested for relatively large load resistance. This study provides a simplified optimization method for broadband piezoelectric energy harvesters with inductive-resistive circuits.

Long term load forecasting accuracy in electric utility integrated resource planning

DOE PAGES

Carvallo, Juan Pablo; Larsen, Peter H.; Sanstad, Alan H.; ...

2018-05-23

Forecasts of electricity consumption and peak demand over time horizons of one or two decades are a key element in electric utilities’ meeting their core objective and obligation to ensure reliable and affordable electricity supplies for their customers while complying with a range of energy and environmental regulations and policies. These forecasts are an important input to integrated resource planning (IRP) processes involving utilities, regulators, and other stake-holders. Despite their importance, however, there has been little analysis of long term utility load forecasting accuracy. We conduct a retrospective analysis of long term load forecasts on twelve Western U. S. electricmore » utilities in the mid-2000s to find that most overestimated both energy consumption and peak demand growth. A key reason for this was the use of assumptions that led to an overestimation of economic growth. We find that the complexity of forecast methods and the accuracy of these forecasts are mildly correlated. In addition, sensitivity and risk analysis of load growth and its implications for capacity expansion were not well integrated with subsequent implementation. As a result, we review changes in the utilities load forecasting methods over the subsequent decade, and discuss the policy implications of long term load forecast inaccuracy and its underlying causes.« less

Long term load forecasting accuracy in electric utility integrated resource planning

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

Carvallo, Juan Pablo; Larsen, Peter H.; Sanstad, Alan H.

Forecasts of electricity consumption and peak demand over time horizons of one or two decades are a key element in electric utilities’ meeting their core objective and obligation to ensure reliable and affordable electricity supplies for their customers while complying with a range of energy and environmental regulations and policies. These forecasts are an important input to integrated resource planning (IRP) processes involving utilities, regulators, and other stake-holders. Despite their importance, however, there has been little analysis of long term utility load forecasting accuracy. We conduct a retrospective analysis of long term load forecasts on twelve Western U. S. electricmore » utilities in the mid-2000s to find that most overestimated both energy consumption and peak demand growth. A key reason for this was the use of assumptions that led to an overestimation of economic growth. We find that the complexity of forecast methods and the accuracy of these forecasts are mildly correlated. In addition, sensitivity and risk analysis of load growth and its implications for capacity expansion were not well integrated with subsequent implementation. As a result, we review changes in the utilities load forecasting methods over the subsequent decade, and discuss the policy implications of long term load forecast inaccuracy and its underlying causes.« less

Faculty Productivity: Practice and Policy.

ERIC Educational Resources Information Center

Quigley, E. James

Information was obtained on current or recently proposed legislation, administrative regulations, policies, practices, reports or studies on any aspect of faculty productivity, faculty workload or teaching load, or faculty activity analysis. Responses were obtained from 34 states. Responses for the 14 states that provided reference material are…

Optimal Design of a Resonance-Based Voltage Boosting Rectifier for Wireless Power Transmission.

PubMed

Lim, Jaemyung; Lee, Byunghun; Ghovanloo, Maysam

2018-02-01

This paper presents the design procedure for a new multi-cycle resonance-based voltage boosting rectifier (MCRR) capable of delivering a desired amount of power to the load (PDL) at a designated high voltage (HV) through a loosely-coupled inductive link. This is achieved by shorting the receiver (Rx) LC-tank for several cycles to harvest and accumulate the wireless energy in the RX inductor before boosting the voltage by breaking the loop and transferring the energy to the load in a quarter cycle. By optimizing the geometries of the transmitter (Tx) and Rx coils and the number of cycles, N , for energy harvesting, through an iterative design procedure, the MCRR can achieve the highest PDL under a given set of design constraints. Governing equations in the MCRR operation are derived to identify key specifications and the design guidelines. Using an exemplary set of specs, the optimized MCRR was able to generate 20.9 V DC across a 100 kΩ load from a 1.8 V p , 6.78 MHz sinusoid input in the ISM-band at a Tx/Rx coil separation of 1.3 cm, power transfer efficiency (PTE) of 2.2%, and N = 9 cycles. At the same coil distance and loading, coils optimized for a conventional half-wave rectifier (CHWR) were able to reach only 13.6 V DC from the same source.

Analysis of Sting Balance Calibration Data Using Optimized Regression Models

NASA Technical Reports Server (NTRS)

Ulbrich, N.; Bader, Jon B.

2010-01-01

Calibration data of a wind tunnel sting balance was processed using a candidate math model search algorithm that recommends an optimized regression model for the data analysis. During the calibration the normal force and the moment at the balance moment center were selected as independent calibration variables. The sting balance itself had two moment gages. Therefore, after analyzing the connection between calibration loads and gage outputs, it was decided to choose the difference and the sum of the gage outputs as the two responses that best describe the behavior of the balance. The math model search algorithm was applied to these two responses. An optimized regression model was obtained for each response. Classical strain gage balance load transformations and the equations of the deflection of a cantilever beam under load are used to show that the search algorithm s two optimized regression models are supported by a theoretical analysis of the relationship between the applied calibration loads and the measured gage outputs. The analysis of the sting balance calibration data set is a rare example of a situation when terms of a regression model of a balance can directly be derived from first principles of physics. In addition, it is interesting to note that the search algorithm recommended the correct regression model term combinations using only a set of statistical quality metrics that were applied to the experimental data during the algorithm s term selection process.

Aerospace Structures Design on Computers

DTIC Science & Technology

1989-03-01

loud or lter’itr- strm C M~eort load or mex~murn load AMeon strews o,. strvss (Q) hm’nur loS1 (b) me -im (a) Fluctuating tension load cycle; (b...constraint deletion techniques in the struc- tural applications of nonlinear programming algorithms. The way this concept is used in the optimality criteria

An Optimization Model for Expired Drug Recycling Logistics Networks and Government Subsidy Policy Design Based on Tri-level Programming

PubMed Central

Huang, Hui; Li, Yuyu; Huang, Bo; Pi, Xing

2015-01-01

In order to recycle and dispose of all people’s expired drugs, the government should design a subsidy policy to stimulate users to return their expired drugs, and drug-stores should take the responsibility of recycling expired drugs, in other words, to be recycling stations. For this purpose it is necessary for the government to select the right recycling stations and treatment stations to optimize the expired drug recycling logistics network and minimize the total costs of recycling and disposal. This paper establishes a tri-level programming model to study how the government can optimize an expired drug recycling logistics network and the appropriate subsidy policies. Furthermore, a Hybrid Genetic Simulated Annealing Algorithm (HGSAA) is proposed to search for the optimal solution of the model. An experiment is discussed to illustrate the good quality of the recycling logistics network and government subsides obtained by the HGSAA. The HGSAA is proven to have the ability to converge on the global optimal solution, and to act as an effective algorithm for solving the optimization problem of expired drug recycling logistics network and government subsidies. PMID:26184252

An Optimization Model for Expired Drug Recycling Logistics Networks and Government Subsidy Policy Design Based on Tri-level Programming.

PubMed

Huang, Hui; Li, Yuyu; Huang, Bo; Pi, Xing

2015-07-09

In order to recycle and dispose of all people's expired drugs, the government should design a subsidy policy to stimulate users to return their expired drugs, and drug-stores should take the responsibility of recycling expired drugs, in other words, to be recycling stations. For this purpose it is necessary for the government to select the right recycling stations and treatment stations to optimize the expired drug recycling logistics network and minimize the total costs of recycling and disposal. This paper establishes a tri-level programming model to study how the government can optimize an expired drug recycling logistics network and the appropriate subsidy policies. Furthermore, a Hybrid Genetic Simulated Annealing Algorithm (HGSAA) is proposed to search for the optimal solution of the model. An experiment is discussed to illustrate the good quality of the recycling logistics network and government subsides obtained by the HGSAA. The HGSAA is proven to have the ability to converge on the global optimal solution, and to act as an effective algorithm for solving the optimization problem of expired drug recycling logistics network and government subsidies.

Autotrophic and heterotrophic nitrification-anoxic denitrification dominated the anoxic/oxic sewage treatment process during optimization for higher loading rate and energy savings.

PubMed

Zhang, Xueyu; Zheng, Shaokui; Zhang, Hangyu; Duan, Shoupeng

2018-04-30

This study clarified the dominant nitrogen (N)-transformation pathway and the key ammonia-oxidizing microbial species at three loading levels during optimization of the anoxic/oxic (A/O) process for sewage treatment. Comprehensive N-transformation activity analysis showed that ammonia oxidization was performed predominantly by aerobic chemolithotrophic and heterotrophic ammonia oxidization, whereas N 2 production was performed primarily by anoxic denitrification in the anoxic unit. The abundances of ammonia-oxidizing bacteria (AOB), nitrite-oxidizing bacteria, and anaerobic AOB in activated sludge reflected their activities on the basis of high-throughput sequencing data. AOB amoA gene clone libraries revealed that the predominant AOB species in sludge samples shifted from Nitrosomonas europaea (61% at the normal loading level) to Nitrosomonas oligotropha (58% and 81% at the two higher loading levels). Following isolation and sequencing, the predominant culturable heterotrophic AOB in sludge shifted from Agrobacterium tumefaciens (42% at the normal loading level) to Acinetobacter johnsonii (52% at the highest loading level). Copyright © 2018 Elsevier Ltd. All rights reserved.

Preparation and optimization of chlorophene-loaded nanospheres as controlled release antimicrobial delivery systems.

PubMed

Phuengkham, Hathaichanok; Teeranachaideekul, Veerawat; Chulasiri, Malyn; Nasongkla, Norased

2016-01-01

Chlorophene-loaded nanospheres with various formulation parameters were evaluated. The optimal formulation was found at 0.1% w/v of poloxamer 407, 15 mL of ethyl acetate and 20% initial chlorophene loading that provided the suitable size (179 nm), the highest loading content (19.2%), encapsulation efficiency (88.0%) and yield (91.6%). Moreover, encapsulation of chlorophene in nanospheres was able to prolong and sustain drug release over one month. Chlorophene-loaded nanospheres were effective against Staphylococcus aureus (S. aureus) and Candida albicans (C. albicans), the main cause of hospital-acquired infections. Chlorophene-loaded nanospheres were effective against S. aureus (>46 µg/mL) and C. albicans (>184 µg/mL). These nanospheres appeared to have profound effect on the time-dependent hemolytic activity due to gradual release of chlorophene. At the concentration of 46 µg/mL, nearly no HRBC hemolysis in 24 h compared to 80% of hemolysis from free drug. In conclusion, polymeric nanospheres were successfully fabricated to encapsulate chlorophene which can eliminate inherent toxicity of drugs and have potential uses in prolonged release of antimicrobial.

Design of gefitinib-loaded poly (l-lactic acid) microspheres via a supercritical anti-solvent process for dry powder inhalation.

PubMed

Lin, Qing; Liu, Guijin; Zhao, Ziyi; Wei, Dongwei; Pang, Jiafeng; Jiang, Yanbin

2017-10-30

To develop a safer, more stable and potent formulation of gefitinib (GFB), micro-spheres of GFB encapsulated into poly (l-lactic acid) (PLLA) have been prepared by supercritical anti-solvent (SAS) technology in this study. Operating factors were optimized using a selected OA 16 (4 5 ) orthogonal array design, and the properties of the raw material and SAS processed samples were characterized by different methods The results show that the GFB-loaded PLLA particles prepared were spherical, having a smaller and narrower particle size compared with raw GFB. The optimal GFB-loaded PLLA sample was prepared with less aggregation, highest GFB loading (15.82%) and smaller size (D 50 =2.48μm, which meets the size of dry powder inhalers). The results of XRD and DSC indicate that GFB is encapsulated into PLLA matrix in a polymorphic form different from raw GFB. FT-IR results show that the chemical structure of GFB does not change after the SAS process. The results of in vitro release show that the optimal sample release was slower compared with raw GFB particles. Moreover, the results of in vitro anti-cancer trials show that the optimal sample had a higher cytotoxicity than raw GFB. After blending with sieved lactose, the flowability and aerosolization performance of the optimal sample for DPI were improved, with angle of repose, emitted dose and fine particles fractions from 38.4° to 23°, 63.21% to >90%, 23.37% to >30%, respectively. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimal Operation of Variable Speed Pumping System in China's Eastern Route Project of S-to-N Water Diversion Project

NASA Astrophysics Data System (ADS)

Cheng, Jilin; Zhang, Lihua; Zhang, Rentian; Gong, Yi; Zhu, Honggeng; Deng, Dongsheng; Feng, Xuesong; Qiu, Jinxian

2010-06-01

A dynamic planning model for optimizing operation of variable speed pumping system, aiming at minimum power consumption, was proposed to achieve economic operation. The No. 4 Jiangdu Pumping Station, a source pumping station in China's Eastern Route of South-to-North Water Diversion Project, is taken as a study case. Since the sump water level of Jiangdu Pumping Station is affected by the tide of Yangtze River, the daily-average heads of the pumping system varies yearly from 3.8m to 7.8m and the tide level difference in one day up to 1.2m. Comparisons of operation electricity cost between optimized variable speed and fixed speed operations of pumping system were made. When the full load operation mode is adopted, whether or not electricity prices in peak-valley periods are considered, the benefits of variable speed operation cannot compensate the energy consumption of the VFD. And when the pumping system operates in part load and the peak-valley electricity prices are considered, the pumping system should cease operation or lower its rotational speed in peak load hours since the electricity price are much higher, and to the contrary the pumping system should raise its rotational speed in valley load hours to pump more water. The computed results show that if the pumping system operates in 80% or 60% loads, the energy consumption cost of specified volume of water will save 14.01% and 26.69% averagely by means of optimal variable speed operation, and the investment on VFD will be paid back in 2 or 3 years. However, if the pumping system operates in 80% or 60% loads and the energy cost is calculated in non peak-valley electricity price, the repayment will be lengthened up to 18 years. In China's S-to-N Water Diversion Project, when the market operation and peak-valley electricity prices are taken into effect to supply water and regulate water levels in regulation reservoirs as Hongzehu Lake, Luomahu Lake, etc. the economic operation of water-diversion pumping stations will be vital, and the adoption of VFDs to achieve optimal operation may be a good choice.

Tackling optimization challenges in industrial load control and full-duplex radios

NASA Astrophysics Data System (ADS)

Gholian, Armen

In price-based demand response programs in smart grid, utilities set the price in accordance with the grid operating conditions and consumers respond to price signals by conducting optimal load control to minimize their energy expenditure while satisfying their energy needs. Industrial sector consumes a large portion of world electricity and addressing optimal load control of energy-intensive industrial complexes, such as steel industry and oil-refinery, is of practical importance. Formulating a general industrial complex and addressing issues in optimal industrial load control in smart grid is the focus of the second part of this dissertation. Several industrial load details are considered in the proposed formulation, including those that do not appear in residential or commercial load control problems. Operation under different smart pricing scenarios, namely, day-ahead pricing, time-of-use pricing, peak pricing, inclining block rates, and critical peak pricing are considered. The use of behind-the-meter renewable generation and energy storage is also considered. The formulated optimization problem is originally nonlinear and nonconvex and thus hard to solve. However, it is then reformulated into a tractable linear mixed-integer program. The performance of the design is assessed through various simulations for an oil refinery and a steel mini-mill. In the third part of this dissertation, a novel all-analog RF interference canceler is proposed. Radio self-interference cancellation (SIC) is the fundamental enabler for full-duplex radios. While SIC methods based on baseband digital signal processing and/or beamforming are inadequate, an all-analog method is useful to drastically reduce the self-interference as the first stage of SIC. It is shown that a uniform architecture with uniformly distributed RF attenuators has a performance highly dependent on the carrier frequency. It is also shown that a new architecture with the attenuators distributed in a clustered fashion has important advantages over the uniform architecture. These advantages are shown numerically through random multipath interference channels, number of control bits in step attenuators, attenuation-dependent phases, single and multi-level structures, etc.

Performance Optimization of Marine Science and Numerical Modeling on HPC Cluster

PubMed Central

Yang, Dongdong; Yang, Hailong; Wang, Luming; Zhou, Yucong; Zhang, Zhiyuan; Wang, Rui; Liu, Yi

2017-01-01

Marine science and numerical modeling (MASNUM) is widely used in forecasting ocean wave movement, through simulating the variation tendency of the ocean wave. Although efforts have been devoted to improve the performance of MASNUM from various aspects by existing work, there is still large space unexplored for further performance improvement. In this paper, we aim at improving the performance of propagation solver and data access during the simulation, in addition to the efficiency of output I/O and load balance. Our optimizations include several effective techniques such as the algorithm redesign, load distribution optimization, parallel I/O and data access optimization. The experimental results demonstrate that our approach achieves higher performance compared to the state-of-the-art work, about 3.5x speedup without degrading the prediction accuracy. In addition, the parameter sensitivity analysis shows our optimizations are effective under various topography resolutions and output frequencies. PMID:28045972

Optimal charge control strategies for stationary photovoltaic battery systems

NASA Astrophysics Data System (ADS)

Li, Jiahao; Danzer, Michael A.

2014-07-01

Battery systems coupled to photovoltaic (PV) modules for example fulfill one major function: they locally decouple PV generation and consumption of electrical power leading to two major effects. First, they reduce the grid load, especially at peak times and therewith reduce the necessity of a network expansion. And second, they increase the self-consumption in households and therewith help to reduce energy expenses. For the management of PV batteries charge control strategies need to be developed to reach the goals of both the distribution system operators and the local power producer. In this work optimal control strategies regarding various optimization goals are developed on the basis of the predicted household loads and PV generation profiles using the method of dynamic programming. The resulting charge curves are compared and essential differences discussed. Finally, a multi-objective optimization shows that charge control strategies can be derived that take all optimization goals into account.

Biomechanical regulation of in vitro cardiogenesis for tissue-engineered heart repair.

PubMed

Zimmermann, Wolfram-Hubertus

2013-01-01

The heart is a continuously pumping organ with an average lifespan of eight decades. It develops from the onset of embryonic cardiogenesis under biomechanical load, performs optimally within a defined range of hemodynamic load, and fails if acutely or chronically overloaded. Unloading of the heart leads to defective cardiogenesis in utero, but can also lead to a desired therapeutic outcome (for example, in patients with heart failure under left ventricular assist device therapy). In light of the well-documented relevance of mechanical loading for cardiac physiology and pathology, it is plausible that tissue engineers have integrated mechanical stimulation regimens into protocols for heart muscle construction. To achieve optimal results, physiological principles of beat-to-beat myocardial loading and unloading should be simulated. In addition, heart muscle engineering, in particular if based on pluripotent stem cell-derived cardiomyocytes, may benefit from staggered tonic loading protocols to simulate viscoelastic properties of the prenatal and postnatal myocardial stroma. This review will provide an overview of heart muscle mechanics, summarize observations on the role of mechanical loading for heart development and postnatal performance, and discuss how physiological loading regimens can be exploited to advance myocardial tissue engineering towards a therapeutic application.

Biomechanical regulation of in vitro cardiogenesis for tissue-engineered heart repair

PubMed Central

2013-01-01

The heart is a continuously pumping organ with an average lifespan of eight decades. It develops from the onset of embryonic cardiogenesis under biomechanical load, performs optimally within a defined range of hemodynamic load, and fails if acutely or chronically overloaded. Unloading of the heart leads to defective cardiogenesis in utero, but can also lead to a desired therapeutic outcome (for example, in patients with heart failure under left ventricular assist device therapy). In light of the well-documented relevance of mechanical loading for cardiac physiology and pathology, it is plausible that tissue engineers have integrated mechanical stimulation regimens into protocols for heart muscle construction. To achieve optimal results, physiological principles of beat-to-beat myocardial loading and unloading should be simulated. In addition, heart muscle engineering, in particular if based on pluripotent stem cell-derived cardiomyocytes, may benefit from staggered tonic loading protocols to simulate viscoelastic properties of the prenatal and postnatal myocardial stroma. This review will provide an overview of heart muscle mechanics, summarize observations on the role of mechanical loading for heart development and postnatal performance, and discuss how physiological loading regimens can be exploited to advance myocardial tissue engineering towards a therapeutic application. PMID:24229468

Impact of Uncertainty from Load-Based Reserves and Renewables on Dispatch Costs and Emissions

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

Li, Bowen; Maroukis, Spencer D.; Lin, Yashen

2016-11-21

Aggregations of controllable loads are considered to be a fast-responding, cost-efficient, and environmental-friendly candidate for power system ancillary services. Unlike conventional service providers, the potential capacity from the aggregation is highly affected by factors like ambient conditions and load usage patterns. Previous work modeled aggregations of controllable loads (such as air conditioners) as thermal batteries, which are capable of providing reserves but with uncertain capacity. A stochastic optimal power flow problem was formulated to manage this uncertainty, as well as uncertainty in renewable generation. In this paper, we explore how the types and levels of uncertainty, generation reserve costs, andmore » controllable load capacity affect the dispatch solution, operational costs, and CO2 emissions. We also compare the results of two methods for solving the stochastic optimization problem, namely the probabilistically robust method and analytical reformulation assuming Gaussian distributions. Case studies are conducted on a modified IEEE 9-bus system with renewables, controllable loads, and congestion. We find that different types and levels of uncertainty have significant impacts on dispatch and emissions. More controllable loads and less conservative solution methodologies lead to lower costs and emissions.« less

Dynamic load balancing for petascale quantum Monte Carlo applications: The Alias method

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

Sudheer, C. D.; Krishnan, S.; Srinivasan, A.

Diffusion Monte Carlo is the most accurate widely used Quantum Monte Carlo method for the electronic structure of materials, but it requires frequent load balancing or population redistribution steps to maintain efficiency and avoid accumulation of systematic errors on parallel machines. The load balancing step can be a significant factor affecting performance, and will become more important as the number of processing elements increases. We propose a new dynamic load balancing algorithm, the Alias Method, and evaluate it theoretically and empirically. An important feature of the new algorithm is that the load can be perfectly balanced with each process receivingmore » at most one message. It is also optimal in the maximum size of messages received by any process. We also optimize its implementation to reduce network contention, a process facilitated by the low messaging requirement of the algorithm. Empirical results on the petaflop Cray XT Jaguar supercomputer at ORNL showing up to 30% improvement in performance on 120,000 cores. The load balancing algorithm may be straightforwardly implemented in existing codes. The algorithm may also be employed by any method with many near identical computational tasks that requires load balancing.« less

Optimization of scintillator loading with the tellurium-130 isotope for long-term stability

NASA Astrophysics Data System (ADS)

Duhamel, Lauren; Song, Xiaoya; Goutnik, Michael; Kaptanoglu, Tanner; Klein, Joshua; SNO+ Collaboration

2017-09-01

Tellurium-130 was selected as the isotope for the SNO + neutrinoless double beta decay search, as 130Te decays to 130Xe via double beta decay. Linear alkyl benzene(LAB) is the liquid scintillator for the SNO + experiment. To load tellurium into scintillator, it is combined with 1,2-butanediol to form an organometallic complex, commonly called tellurium butanediol (TeBD). This study focuses on maximizing the percentage of tellurium loaded into scintillator and evaluates the complex's long-term stability. Studies on the effect of nucleation due to imperfections in the detector's surface and external particulates were employed by filtration and induced nucleation. The impact of water on the stability of TeBD complex was evaluated by liquid-nitrogen sparging, variability in pH and induced humidity. Alternative loading methods were evaluated, including the addition of stability-inducing organic compounds. Samples of tellurium-loaded scintillator were synthesized, treated, and consistently monitored in a controlled environment. It was found that the hydronium ions cause precipitation in the loaded scintillator, demonstrating that water has a detrimental effect on long-term stability. Optimization of loaded scintillator stability can contribute to the SNO + double beta decay search.

Watermark: An Application and Methodology and Application for Interactive and intelligent Decision Support for Groundwater Systems

NASA Astrophysics Data System (ADS)

Pierce, S. A.; Wagner, K.; Schwartz, S.; Gentle, J. N., Jr.

2016-12-01

Critical water resources face the effects of historic drought, increased demand, and potential contamination, the need has never been greater to develop resources to effectively communicate conservation and protection across a broad audience and geographical area. The Watermark application and macro-analysis methodology merges topical analysis of context rich corpus from policy texts with multi-attributed solution sets from integrated models of water resource and other subsystems, such as mineral, food, energy, or environmental systems to construct a scalable, robust, and reproducible approach for identifying links between policy and science knowledge bases. The Watermark application is an open-source, interactive workspace to support science-based visualization and decision making. Designed with generalization in mind, Watermark is a flexible platform that allows for data analysis and inclusion of large datasets with an interactive front-end capable of connecting with other applications as well as advanced computing resources. In addition, the Watermark analysis methodology offers functionality that streamlines communication with non-technical users for policy, education, or engagement with groups around scientific topics of societal relevance. The technology stack for Watermark was selected with the goal of creating a robust and dynamic modular codebase that can be adjusted to fit many use cases and scale to support usage loads that range between simple data display to complex scientific simulation-based modelling and analytics. The methodology uses to topical analysis and simulation-optimization to systematically analyze the policy and management realities of resource systems and explicitly connect the social and problem contexts with science-based and engineering knowledge from models. A case example demonstrates use in a complex groundwater resources management study highlighting multi-criteria spatial decision making and uncertainty comparisons.

Evolutional Optimization on Material Ordering and Inventory Control of Supply Chain through Incentive Scheme

NASA Astrophysics Data System (ADS)

Prasertwattana, Kanit; Shimizu, Yoshiaki; Chiadamrong, Navee

This paper studied the material ordering and inventory control of supply chain systems. The effect of controlling policies is analyzed under three different configurations of the supply chain systems, and the formulated problem has been solved by using an evolutional optimization method known as Differential Evolution (DE). The numerical results show that the coordinating policy with the incentive scheme outperforms the other policies and can improve the performance of the overall system as well as all members under the concept of supply chain management.

Essays on carbon abatement and electricity markets

NASA Astrophysics Data System (ADS)

Taber, John Timothy

In the first chapter of this dissertation, I study the effects of a number of policies which affect the electric grid using the SuperOPF, a full AC optimization/simulation framework with optimal investment developed at Cornell University. A 36-node model of the Northeast Power Coordinating Council is used to test policies that aim to reduce CO2, other emissions, or otherwise impact the operation of the electric grid: a base case, with no new environmental legislation; enactment of the Kerry-Lieberman CO2 allowance proposal in 2012; following Fukishima, a retirement of all US nuclear plants by 2022 with and without Kerry-Lieberman; marginal damages from SO2 and NOX emissions charged to coal, gas and oil-fired generation; plug-in hybrid electric vehicle load filling; wind incentives in place; and two cases which combine these. The cases suggest that alternative policies may have very different outcomes in terms of electricity prices, emissions, and health outcomes. In all cases, however, the optimal strategy for future investment is investment in new natural gas combined cycle plants. Policies can change how much new generation is built, whether other plants are built, or what types of plants are retired. The second chapter of my dissertation utilizes the SuperOPF and the model of the Northeast Power Coordinating Council to analyze the issue of carbon leakage. I analyze the effects of a regionally-limited carbon cap and trade program, the Regional Greenhouse Initiative (RGGI), when additional generating assets in non-affected states are included in the analysis. In the face of different carbon prices on generating assets in covered and non-covered states, generation is expected to shift from states bound by RGGI to states outside of RGGI. This carbon leakage may undermine some or all of the benefits of RGGI while simultaneously increasing prices for customers in the area. Even though carbon prices under RGGI are very low, some leakage is occurring, and this leakage will worsen if carbon prices increase. Ultimately, a unified policy offers greater carbon reduction at a lower cost, which would increase popular acceptance of such policies. In the third chapter of this dissertation, my coauthors and I examine the issue of demand for carbon reductions. Recent large-scale field experiments have shown that peer information nudges can have significant effects on behavior, inducing people to reduce their production of negative externalities. Related work in psychology demonstrates that inducing feelings of personal culpability by showing people information about their peers can induce pro-social behavior. This study uses a contingent valuation experiment and a parallel lab experiment to further explore patterns of responses that have been suggested in the emerging literature on norm-based environmental interventions The field-level finding of asymmetric responses between those whose environmental or group impacts are above or below the norm is found to be robust across decision settings. However, substantial heterogeneity in responses to peer information is observed across a number of demographic and other respondent-specific dimensions not able to be explored in large scale field experiments, raising questions about the universality of peer-information effects and the design of such programs.

Systematic optimization of laser cooling of dysprosium

NASA Astrophysics Data System (ADS)

Mühlbauer, Florian; Petersen, Niels; Baumgärtner, Carina; Maske, Lena; Windpassinger, Patrick

2018-06-01

We report on an apparatus for cooling and trapping of neutral dysprosium. We characterize and optimize the performance of our Zeeman slower and 2D molasses cooling of the atomic beam by means of Doppler spectroscopy on a 136 kHz broad transition at 626 nm. Furthermore, we demonstrate the characterization and optimization procedure for the loading phase of a magneto-optical trap (MOT) by increasing the effective laser linewidth by sideband modulation. After optimization of the MOT compression phase, we cool and trap up to 10^9 atoms within 3 seconds in the MOT at temperatures of 9 μK and phase space densities of 1.7 \\cdot 10^{-5}, which constitutes an ideal starting point for loading the atoms into an optical dipole trap and for subsequent forced evaporative cooling.

Optimization of biological sulfide removal in a CSTR bioreactor.

PubMed

Roosta, Aliakbar; Jahanmiri, Abdolhossein; Mowla, Dariush; Niazi, Ali; Sotoodeh, Hamidreza

2012-08-01

In this study, biological sulfide removal from natural gas in a continuous bioreactor is investigated for estimation of the optimal operational parameters. According to the carried out reactions, sulfide can be converted to elemental sulfur, sulfate, thiosulfate, and polysulfide, of which elemental sulfur is the desired product. A mathematical model is developed and was used for investigation of the effect of various parameters on elemental sulfur selectivity. The results of the simulation show that elemental sulfur selectivity is a function of dissolved oxygen, sulfide load, pH, and concentration of bacteria. Optimal parameter values are calculated for maximum elemental sulfur selectivity by using genetic algorithm as an adaptive heuristic search. In the optimal conditions, 87.76% of sulfide loaded to the bioreactor is converted to elemental sulfur.

A policy iteration approach to online optimal control of continuous-time constrained-input systems.

PubMed

Modares, Hamidreza; Naghibi Sistani, Mohammad-Bagher; Lewis, Frank L

2013-09-01

This paper is an effort towards developing an online learning algorithm to find the optimal control solution for continuous-time (CT) systems subject to input constraints. The proposed method is based on the policy iteration (PI) technique which has recently evolved as a major technique for solving optimal control problems. Although a number of online PI algorithms have been developed for CT systems, none of them take into account the input constraints caused by actuator saturation. In practice, however, ignoring these constraints leads to performance degradation or even system instability. In this paper, to deal with the input constraints, a suitable nonquadratic functional is employed to encode the constraints into the optimization formulation. Then, the proposed PI algorithm is implemented on an actor-critic structure to solve the Hamilton-Jacobi-Bellman (HJB) equation associated with this nonquadratic cost functional in an online fashion. That is, two coupled neural network (NN) approximators, namely an actor and a critic are tuned online and simultaneously for approximating the associated HJB solution and computing the optimal control policy. The critic is used to evaluate the cost associated with the current policy, while the actor is used to find an improved policy based on information provided by the critic. Convergence to a close approximation of the HJB solution as well as stability of the proposed feedback control law are shown. Simulation results of the proposed method on a nonlinear CT system illustrate the effectiveness of the proposed approach. Copyright © 2013 ISA. All rights reserved.

Economic analysis of secondary and enhanced oil recovery techniques in Wyoming

NASA Astrophysics Data System (ADS)

Kara, Erdal

This dissertation primarily aims to theoretically analyze a firm's optimization of enhanced oil recovery (EOR) and carbon dioxide sequestration under different social policies and empirically analyze the firm's optimization of enhanced oil recovery. The final part of the dissertation empirically analyzes how geological factors and water injection management influence oil recovery. The first chapter builds a theoretical model to analyze economic optimization of EOR and geological carbon sequestration under different social policies. Specifically, it analyzes how social policies on sequestration influence the extent of oil operations, optimal oil production and CO2 sequestration. The theoretical results show that the socially optimal policy is a subsidy on the net CO2 sequestration, assuming negative net emissions from EOR. Such a policy is expected to increase a firm's total carbon dioxide sequestration. The second chapter statistically estimates the theoretical oil production model and its different versions. Empirical results are not robust over different estimation techniques and not in line with the theoretical production model. The last part of the second chapter utilizes a simplified version of theoretical model and concludes that EOR via CO2 injection improves oil recovery. The final chapter analyzes how a contemporary oil recovery technology (water flooding of oil reservoirs) and various reservoir-specific geological factors influence oil recovery in Wyoming. The results show that there is a positive concave relationship between cumulative water injection and cumulative oil recovery and also show that certain geological factors affect the oil recovery. Moreover, the curvature of the concave functional relationship between cumulative water injection and oil recovery is reservoir-specific due to heterogeneities among different reservoirs.

Design, Optimization and Evaluation of Integrally Stiffened Al 7050 Panel with Curved Stiffeners

NASA Technical Reports Server (NTRS)

Slemp, Wesley C. H.; Bird, R. Keith; Kapania, Rakesh K.; Havens, David; Norris, Ashley; Olliffe, Robert

2011-01-01

A curvilinear stiffened panel was designed, manufactured, and tested in the Combined Load Test Fixture at NASA Langley Research Center. The panel was optimized for minimum mass subjected to constraints on buckling load, yielding, and crippling or local stiffener failure using a new analysis tool named EBF3PanelOpt. The panel was designed for a combined compression-shear loading configuration that is a realistic load case for a typical aircraft wing panel. The panel was loaded beyond buckling and strains and out-of-plane displacements were measured. The experimental data were compared with the strains and out-of-plane deflections from a high fidelity nonlinear finite element analysis and linear elastic finite element analysis of the panel/test-fixture assembly. The numerical results indicated that the panel buckled at the linearly elastic buckling eigenvalue predicted for the panel/test-fixture assembly. The experimental strains prior to buckling compared well with both the linear and nonlinear finite element model.

Structural optimization of 3D-printed synthetic spider webs for high strength

PubMed Central

Qin, Zhao; Compton, Brett G.; Lewis, Jennifer A.; Buehler, Markus J.

2015-01-01

Spiders spin intricate webs that serve as sophisticated prey-trapping architectures that simultaneously exhibit high strength, elasticity and graceful failure. To determine how web mechanics are controlled by their topological design and material distribution, here we create spider-web mimics composed of elastomeric filaments. Specifically, computational modelling and microscale 3D printing are combined to investigate the mechanical response of elastomeric webs under multiple loading conditions. We find the existence of an asymptotic prey size that leads to a saturated web strength. We identify pathways to design elastomeric material structures with maximum strength, low density and adaptability. We show that the loading type dictates the optimal material distribution, that is, a homogeneous distribution is better for localized loading, while stronger radial threads with weaker spiral threads is better for distributed loading. Our observations reveal that the material distribution within spider webs is dictated by the loading condition, shedding light on their observed architectural variations. PMID:25975372

Finite element analyses of continuous filament ties for masonry applications : final report for the Arquin Corporation.

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

Quinones, Armando, Sr.; Bibeau, Tiffany A.; Ho, Clifford Kuofei

2008-08-01

Finite-element analyses were performed to simulate the response of a hypothetical vertical masonry wall subject to different lateral loads with and without continuous horizontal filament ties laid between rows of concrete blocks. A static loading analysis and cost comparison were also performed to evaluate optimal materials and designs for the spacers affixed to the filaments. Results showed that polypropylene, ABS, and polyethylene (high density) were suitable materials for the spacers based on performance and cost, and the short T-spacer design was optimal based on its performance and functionality. Simulations of vertical walls subject to static loads representing 100 mph windsmore » (0.2 psi) and a seismic event (0.66 psi) showed that the simulated walls performed similarly and adequately when subject to these loads with and without the ties. Additional simulations and tests are required to assess the performance of actual walls with and without the ties under greater loads and more realistic conditions (e.g., cracks, non-linear response).« less

Design Considerations for Fusible Heat Sink

NASA Technical Reports Server (NTRS)

Cognata, Thomas J.; Leimkuehler, Thomas O.; Sheth, Rubik B.

2011-01-01

Traditionally radiator designs are based off a passive or flow through design depending on vehicle requirements. For cyclical heat loads, a novel idea of combining a full flow through radiator to a phase change material is currently being investigated. The flow through radiator can be designed for an average heat load while the phase change material can be used as a source of supplemental heat rejections when vehicle heat loads go above the average load. Furthermore, by using water as the phase change material, harmful radiation protection can be provided to the crew. This paper discusses numerous trades conducted to understand the most optimal fusible heat sink design for a particular heat load. Trades include configuration concepts, amount of phase change needed for supplemental heat rejection, and the form of interstitial material needed for optimal performance. These trades were used to culminate to a fusible heat sink design. The paper will discuss design parameters taken into account to develop an engineering development unit.

Improved pharmacokinetics and antihyperlipidemic efficacy of rosuvastatin-loaded nanostructured lipid carriers.

PubMed

Rizwanullah, Md; Amin, Saima; Ahmad, Javed

2017-01-01

In the present study, rosuvastatin calcium-loaded nanostructured lipid carriers were developed and optimized for improved efficacy. The ROS-Ca-loaded NLC was prepared using melt emulsification ultrasonication technique and optimized by Box-Behnken statistical design. The optimized NLC composed of glyceryl monostearate (solid lipid) and capmul MCM EP (liquid lipid) as lipid phase (3% w/v), poloxamer 188 (1%) and tween 80 (1%) as surfactant. The mean particle size, polydispersity index (PDI), zeta potential (ζ) and entrapment efficiency (%) of optimized NLC formulation was observed to be 150.3 ± 4.67 nm, 0.175 ± 0.022, -32.9 ± 1.36 mV and 84.95 ± 5.63%, respectively. NLC formulation showed better in vitro release in simulated intestinal fluid (pH 6.8) than API suspension. Confocal laser scanning showed deeper permeation of formulation across rat intestine compared to rhodamine B dye solution. Pharmacokinetic study on female albino Wistar rats showed 5.4-fold increase in relative bioavailability with NLC compared to API suspension. Optimized NLC formulation also showed significant (p < 0.01) lipid lowering effect in hyperlipidemic rats. Therefore, NLC represents a great potential for improved efficacy of ROS-Ca after oral administration.

The unlikely high efficiency of a molecular motor based on active motion

NASA Astrophysics Data System (ADS)

Ebeling, W.

2015-07-01

The efficiency of a simple model of a motor converting chemical into mechanical energy is studied analytically. The model motor shows interesting properties corresponding qualitatively to motors investigated in experiments. The efficiency increases with the load and may for low loss reach high values near to 100 percent in a narrow regime of optimal load. It is shown that the optimal load and the maximal efficiency depend by universal power laws on the dimensionless loss parameter. Stochastic effects decrease the stability of motor regimes with high efficiency and make them unlikely. Numerical studies show efficiencies below the theoretical optimum and demonstrate that special ratchet profiles my stabilize efficient regimes.

Load Balancing in Multi Cloud Computing Environment with Genetic Algorithm

NASA Astrophysics Data System (ADS)

Vhansure, Fularani; Deshmukh, Apurva; Sumathy, S.

2017-11-01

Cloud is a pool of resources that is available on pay per use model. It provides services to the user which is increasing rapidly. Load balancing is an issue because it cannot handle so many requests at a time. It is also known as NP complete problem. In traditional system the functions consist of various parameter values to maximise it in order to achieve best optimal individualsolutions. Challenge is when there are many parameters of solutionsin the system space. Another challenge is to optimize the function which is much more complex. In this paper, various techniques to handle load balancing virtually (VM) as well as physically (nodes) using genetic algorithm is discussed.

Ready to Use Tissue Construct for Military Bone & Cartilage Trauma

DTIC Science & Technology

2014-10-01

during nail introduction and reaming. In the present study, we examined the load - bearing capacity and optimal internal fixation of a bone/poly-ε...segmental defect, (a) axial loading via ball bearing , (b) torsional loading via square clamp allowing axial displacement, (c) three-point bending of tibia...knee joints by simulating loads seen during ambulation and knee range of motion. Our central hypothesis is that an anatomically and

Study of Flexible Load Dispatch to Improve the Capacity of Wind Power Absorption

NASA Astrophysics Data System (ADS)

Yunlei, Yang; Shifeng, Zhang; Xiao, Chang; Da, Lei; Min, Zhang; Jinhao, Wang; Shengwen, Li; Huipeng, Li

2017-05-01

The dispatch method which track the trend of load demand by arranging the generation scheme of controllable hydro or thermal units faces great difficulties and challenges. With the increase of renewable energy sources such as wind power and photovoltaic power introduced to grid, system has to arrange much more spinning reserve units to compensate the unbalanced power. How to exploit the peak-shaving potential of flexible load which can be shifted with time or storage energy has become many scholars’ research direction. However, the modelling of different kinds of load and control strategy is considerably difficult, this paper choose the Air Conditioner with compressor which can storage energy in fact to study. The equivalent thermal parameters of Air Conditioner has been established. And with the use of “loop control” strategies, we can predict the regulated power of Air Conditioner. Then we established the Gen-Load optimal scheduling model including flexible load based on traditional optimal scheduling model. At last, an improved IEEE-30 case is used to verify. The result of simulation shows that flexible load can fast-track renewable power changes. More than that, with flexible load and reasonable incentive method to consumers, the operating cost of the system can be greatly cut down.

Optimization of composite sandwich cover panels subjected to compressive loadings

NASA Technical Reports Server (NTRS)

Cruz, Juan R.

1991-01-01

An analysis and design method is presented for the design of composite sandwich cover panels that includes transverse shear effects and damage tolerance considerations. This method is incorporated into an optimization program called SANDOP (SANDwich OPtimization). SANDOP is used in the present study to design optimized composite sandwich cover panels for transport aircraft wing applications as a demonstration of its capabilities. The results of this design study indicate that optimized composite sandwich cover panels have approximately the same structural efficiency as stiffened composite cover panels designed to identical constraints. Results indicate that inplane stiffness requirements have a large effect on the weight of these composite sandwich cover panels at higher load levels. Increasing the maximum allowable strain and the upper percentage limit of the 0 degree and plus or minus 45 degree plies can yield significant weight savings. The results show that the structural efficiency of these optimized composite sandwich cover panels is relatively insensitive to changes in core density.

'Are we there yet?' - operationalizing the concept of Integrated Public Health Policies.

PubMed

Hendriks, Anna-Marie; Habraken, Jolanda; Jansen, Maria W J; Gubbels, Jessica S; De Vries, Nanne K; van Oers, Hans; Michie, Susan; Atkins, L; Kremers, Stef P J

2014-02-01

Although 'integrated' public health policies are assumed to be the ideal way to optimize public health, it remains hard to determine how far removed we are from this ideal, since clear operational criteria and defining characteristics are lacking. A literature review identified gaps in previous operationalizations of integrated public health policies. We searched for an approach that could fill these gaps. We propose the following defining characteristics of an integrated policy: (1) the combination of policies includes an appropriate mix of interventions that optimizes the functioning of the behavioral system, thus ensuring that motivation, capability and opportunity interact in such a way that they promote the preferred (health-promoting) behavior of the target population, and (2) the policies are implemented by the relevant policy sectors from different policy domains. Our criteria should offer added value since they describe pathways in the process towards formulating integrated policy. The aim of introducing our operationalization is to assist policy makers and researchers in identifying truly integrated cases. The Behavior Change Wheel proved to be a useful framework to develop operational criteria to assess the current state of integrated public health policies in practice. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

The forest and agricultural sector optimization model (FASOM): model structure and policy applications.

Treesearch

Darius M. Adams; Ralph J. Alig; J.M. Callaway; Bruce A. McCarl; Steven M. Winnett

1996-01-01

The Forest and Agricultural Sector Optimization Model (FASOM) is a dynamic, nonlinear programming model of the forest and agricultural sectors in the United States. The FASOM model initially was developed to evaluate welfare and market impacts of alternative policies for sequestering carbon in trees but also has been applied to a wider range of forest and agricultural...

Load research manual. Volume 2. Fundamentals of implementing load research procedures

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

Brandenburg, L.; Clarkson, G.; Grund, Jr., C.

This three-volume manual presents technical guidelines for electric utility load research. Special attention is given to issues raised by the load data reporting requirements of the Public Utility Regulatory Policies Act of 1978 and to problems faced by smaller utilities that are initiating load research programs. In Volumes 1 and 2, procedures are suggested for determining data requirements for load research, establishing the size and customer composition of a load survey sample, selecting and using equipment to record customer electricity usage, processing data tapes from the recording equipment, and analyzing the data. Statistical techniques used in customer sampling are discussedmore » in detail. The costs of load research also are estimated, and ongoing load research programs at three utilities are described. The manual includes guides to load research literature and glossaries of load research and statistical terms.« less

Relations between information, time, and value of water

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Load Management - Methods to Reduce Electric Utilities Peak Loads.

DTIC Science & Technology

1983-08-01

for electric utilities.1 The largest impact came in 1978 when the Public Utilities Regulatory Policies Act ( PURPA ) was enacted which required state...management option. 7 CHAPTER VII CONCLUSION Since PURPA was enacted in 1978, utilities have been required to investigate methods in which to more effectively

A SIMPLE MODEL FOR FORECASTING THE EFFECTS OF NITROGEN LOADS ON CHESAPEAKE BAY HYPOXIA

EPA Science Inventory

The causes and consequences of oxygen depletion in Chesapeake Bay have been the focus of research, assessment, and policy action over the past several decades. An ongoing scientific re-evaluation of what nutrients load reductions are necessary to meet the water quality goals is ...

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.

Contract portfolio optimization for a gasoline supply chain

NASA Astrophysics Data System (ADS)

Wang, Shanshan

Major oil companies sell gasoline through three channels of trade: branded (associated with long-term contracts), unbranded (associated with short-term contracts), and spot market. The branded channel provides them with a long-term secured and sustainable demand source, but requires an inflexible long-term commitment with demand and price risks. The unbranded channel provides a medium level of allocation flexibility. The spot market provides them with the greatest allocation flexibility to the changing market conditions, but the spot market's illiquidity mitigates this benefit. In order to sell the product in a profitable and sustainable way, they need an optimal contract portfolio. This dissertation addresses the contract portfolio optimization problem from different perspectives (retrospective view and forward-looking view) at different levels (strategic level, tactical level and operational level). The objective of the retrospective operational model is to develop a financial case to estimate the business value of having a dynamic optimization model and quantify the opportunity values missed in the past. This model proves the financial significance of the problem and provides top management valuable insights into the business. BP has applied the insights and principles gained from this work and implemented the model to the entire Midwest gasoline supply chain to retrospectively review optimization opportunities. The strategic model is the most parsimonious model that captures the essential economic tradeoffs among different contract types, to demonstrate the need for a contract portfolio and what drives the portfolio. We examine the properties of the optimal contract portfolio and provide a comparative statics analysis by changing the model parameters. As the strategic model encapsulates the business problem at the macroscopic level, the tactical model resolves lower level issues. It considers the time dynamics, the information flow and contracting flow. Using this model, we characterize a simple and easily implementable dynamic contract portfolio policy that would enable the company to dynamically rebalance its supply contract portfolio over time in anticipation of the future market conditions in each individual channel while satisfying the contractual obligations. The optimal policy is a state-dependent base-share contract portfolio policy characterized by a branded base-share level and an unbranded contract commitment combination, given as a function of the initial information state. Using real-world market data, we estimate the model parameters. We also apply an efficient modified policy iteration method to compute the optimal contract portfolio strategies and corresponding profit value. We present computational results in order to obtain insights into the structure of optimal policies, capture the value of the dynamic contract portfolio policy by comparing it with static policies, and illustrate the sensitivity of the optimal contract portfolio and corresponding profit value in terms of the different parameters. Considering the geographic dispersion of different market areas and the pipeline network together with the dynamic contract portfolio optimization problem, we formulate a forward-looking operational model, which could be used by gasoline suppliers for lower-level planning. Finally, we discuss the generalization of the framework to other problems and applications, as well as further research.

Co-evolution of soil and water conservation policy and human-environment linkages in the Yellow River Basin since 1949.

PubMed

Wang, Fei; Mu, Xingmin; Li, Rui; Fleskens, Luuk; Stringer, Lindsay C; Ritsema, Coen J

2015-03-01

Policy plays a very important role in natural resource management as it lays out a government framework for guiding long-term decisions, and evolves in light of the interactions between human and environment. This paper focuses on soil and water conservation (SWC) policy in the Yellow River Basin (YRB), China. The problems, rural poverty, severe soil erosion, great sediment loads and high flood risks, are analyzed over the period of 1949-present using the Driving force-Pressure-State-Impact-Response (DPSIR) framework as a way to organize analysis of the evolution of SWC policy. Three stages are identified in which SWC policy interacts differently with institutional, financial and technology support. In Stage 1 (1949-1979), SWC policy focused on rural development in eroded areas and on reducing sediment loads. Local farmers were mainly responsible for SWC. The aim of Stage 2 (1980-1990) was the overall development of rural industry and SWC. A more integrated management perspective was implemented taking a small watershed as a geographic interactional unit. This approach greatly improved the efficiency of SWC activities. In Stage 3 (1991 till now), SWC has been treated as the main measure for natural resource conservation, environmental protection, disaster mitigation and agriculture development. Prevention of new degradation became a priority. The government began to be responsible for SWC, using administrative, legal and financial approaches and various technologies that made large-scale SWC engineering possible. Over the historical period considered, with the implementation of the various SWC policies, the rural economic and ecological system improved continuously while the sediment load and flood risk decreased dramatically. The findings assist in providing a historical perspective that could inform more rational, scientific and effective natural resource management going forward. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Integrated strategies to address emerging freight and delivery challenges in New York City : final report.

DOT National Transportation Integrated Search

2017-01-01

This report has three critical objectives. First, to highlight the changing nature of freight deliveries even as zoning policy for off-street loading has changed little over the last 65 years. Second, to consider policy and physical approaches to add...

75 FR 57263 - New Policy Announcing That Traditional Horizontal Survey Projects Performed With Terrestrial...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-20

... DEPARTMENT OF COMMERCE National Oceanic and Atmospheric Administration New Policy Announcing That Traditional Horizontal Survey Projects Performed With Terrestrial Survey Techniques Will No Longer Be Accepted for Processing or Loading Into NGS Databases AGENCY: National Geodetic Survey (NGS), National Ocean...

Towards a Better Distributed Framework for Learning Big Data

DTIC Science & Technology

2017-06-14

UNLIMITED: PB Public Release 13. SUPPLEMENTARY NOTES 14. ABSTRACT This work aimed at solving issues in distributed machine learning. The PI’s team proposed...communication load. Finally, the team proposed the parallel least-squares policy iteration (parallel LSPI) to parallelize a reinforcement policy learning. 15

Complementing carbon prices with technology policies to keep climate targets within reach

NASA Astrophysics Data System (ADS)

Bertram, Christoph; Luderer, Gunnar; Pietzcker, Robert C.; Schmid, Eva; Kriegler, Elmar; Edenhofer, Ottmar

2015-03-01

Economic theory suggests that comprehensive carbon pricing is most efficient to reach ambitious climate targets, and previous studies indicated that the carbon price required for limiting global mean warming to 2 °C is between US$16 and US$73 per tonne of CO2 in 2015 (ref. ). Yet, a global implementation of such high carbon prices is unlikely to be politically feasible in the short term. Instead, most climate policies enacted so far are technology policies or fragmented and moderate carbon pricing schemes. This paper shows that ambitious climate targets can be kept within reach until 2030 despite a sub-optimal policy mix. With a state-of-the-art energy-economy model we quantify the interactions and unique effects of three major policy components: (1) a carbon price starting at US$7 per tonne of CO2 in 2015 to incentivize economy-wide mitigation, flanked by (2) support for low-carbon energy technologies to pave the way for future decarbonization, and (3) a moratorium on new coal-fired power plants to limit stranded assets. We find that such a mix limits the efficiency losses compared with the optimal policy, and at the same time lowers distributional impacts. Therefore, we argue that this instrument mix might be a politically more feasible alternative to the optimal policy based on a comprehensive carbon price alone.

[Cost-effectiveness of breast cancer screening policies in Mexico].

PubMed

Valencia-Mendoza, Atanacio; Sánchez-González, Gilberto; Bautista-Arredondo, Sergio; Torres-Mejía, Gabriela; Bertozzi, Stefano M

2009-01-01

Generate cost-effectiveness information to allow policy makers optimize breast cancer (BC) policy in Mexico. We constructed a Markov model that incorporates four interrelated processes of the disease: the natural history; detection using mammography; treatment; and other competing-causes mortality, according to which 13 different strategies were modeled. Strategies (starting age, % of coverage, frequency in years)= (48, 25, 2), (40, 50, 2) and (40, 50, 1) constituted the optimal method for expanding the BC program, yielding 75.3, 116.4 and 171.1 thousand pesos per life-year saved, respectively. The strategies included in the optimal method for expanding the program produce a cost per life-year saved of less than two times the GNP per capita and hence are cost-effective according to WHO Commission on Macroeconomics and Health criteria.

Off-Policy Actor-Critic Structure for Optimal Control of Unknown Systems With Disturbances.

PubMed

Song, Ruizhuo; Lewis, Frank L; Wei, Qinglai; Zhang, Huaguang

2016-05-01

An optimal control method is developed for unknown continuous-time systems with unknown disturbances in this paper. The integral reinforcement learning (IRL) algorithm is presented to obtain the iterative control. Off-policy learning is used to allow the dynamics to be completely unknown. Neural networks are used to construct critic and action networks. It is shown that if there are unknown disturbances, off-policy IRL may not converge or may be biased. For reducing the influence of unknown disturbances, a disturbances compensation controller is added. It is proven that the weight errors are uniformly ultimately bounded based on Lyapunov techniques. Convergence of the Hamiltonian function is also proven. The simulation study demonstrates the effectiveness of the proposed optimal control method for unknown systems with disturbances.

Mechanics of Flapping Flight: Analytical Formulations of Unsteady Aerodynamics, Kinematic Optimization, Flight Dynamics, and Control

NASA Astrophysics Data System (ADS)

Taneja, Jayant Kumar

Electricity is an indispensable commodity to modern society, yet it is delivered via a grid architecture that remains largely unchanged over the past century. A host of factors are conspiring to topple this dated yet venerated design: developments in renewable electricity generation technology, policies to reduce greenhouse gas emissions, and advances in information technology for managing energy systems. Modern electric grids are emerging as complex distributed systems in which a portfolio of power generation resources, often incorporating fluctuating renewable resources such as wind and solar, must be managed dynamically to meet uncontrolled, time-varying demand. Uncertainty in both supply and demand makes control of modern electric grids fundamentally more challenging, and growing portfolios of renewables exacerbate the challenge. We study three electricity grids: the state of California, the province of Ontario, and the country of Germany. To understand the effects of increasing renewables, we develop a methodology to scale renewables penetration. Analyzing these grids yields key insights about rigid limits to renewables penetration and their implications in meeting long-term emissions targets. We argue that to achieve deep penetration of renewables, the operational model of the grid must be inverted, changing the paradigm from load-following supplies to supply-following loads. To alleviate the challenge of supply-demand matching on deeply renewable grids, we first examine well-known techniques, including altering management of existing supply resources, employing utility-scale energy storage, targeting energy efficiency improvements, and exercising basic demand-side management. Then, we create several instantiations of supply-following loads -- including refrigerators, heating and cooling systems, and laptop computers -- by employing a combination of sensor networks, advanced control techniques, and enhanced energy storage. We examine the capacity of each load for supply-following and study the behaviors of populations of these loads, assessing their potential at various levels of deployment throughout the California electricity grid. Using combinations of supply-following strategies, we can reduce peak natural gas generation by 19% on a model of the California grid with 60% renewables. We then assess remaining variability on this deeply renewable grid incorporating supply-following loads, characterizing additional capabilities needed to ensure supply-demand matching in future sustainable electricity grids.

The development of optimal lightweight truss-core sandwich panels

NASA Astrophysics Data System (ADS)

Langhorst, Benjamin Robert

Sandwich structures effectively provide lightweight stiffness and strength by sandwiching a low-density core between stiff face sheets. The performance of lightweight truss-core sandwich panels is enhanced through the design of novel truss arrangements and the development of methods by which the panels may be optimized. An introduction to sandwich panels is presented along with an overview of previous research of truss-core sandwich panels. Three alternative truss arrangements are developed and their corresponding advantages, disadvantages, and optimization routines are discussed. Finally, performance is investigated by theoretical and numerical methods, and it is shown that the relative structural efficiency of alternative truss cores varies with panel weight and load-carrying capacity. Discrete truss core sandwich panels can be designed to serve bending applications more efficiently than traditional pyramidal truss arrangements at low panel weights and load capacities. Additionally, discrete-truss cores permit the design of heterogeneous cores, which feature unit cells that vary in geometry throughout the panel according to the internal loads present at each unit cell's location. A discrete-truss core panel may be selectively strengthened to more efficiently support bending loads. Future research is proposed and additional areas for lightweight sandwich panel development are explained.

Application of Sequential Quadratic Programming to Minimize Smart Active Flap Rotor Hub Loads

NASA Technical Reports Server (NTRS)

Kottapalli, Sesi; Leyland, Jane

2014-01-01

In an analytical study, SMART active flap rotor hub loads have been minimized using nonlinear programming constrained optimization methodology. The recently developed NLPQLP system (Schittkowski, 2010) that employs Sequential Quadratic Programming (SQP) as its core algorithm was embedded into a driver code (NLP10x10) specifically designed to minimize active flap rotor hub loads (Leyland, 2014). Three types of practical constraints on the flap deflections have been considered. To validate the current application, two other optimization methods have been used: i) the standard, linear unconstrained method, and ii) the nonlinear Generalized Reduced Gradient (GRG) method with constraints. The new software code NLP10x10 has been systematically checked out. It has been verified that NLP10x10 is functioning as desired. The following are briefly covered in this paper: relevant optimization theory; implementation of the capability of minimizing a metric of all, or a subset, of the hub loads as well as the capability of using all, or a subset, of the flap harmonics; and finally, solutions for the SMART rotor. The eventual goal is to implement NLP10x10 in a real-time wind tunnel environment.

Ground coupled solar heat pumps: analysis of four options

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

Andrews, J.W.

Heat pump systems which utilize both solar energy and energy withdrawn from the ground are analyzed using a simplified procedure which optimizes the solar storage temperature on a monthly basis. Four ways of introducing collected solar energy to the system are optimized and compared. These include use of actively collected thermal input to the heat pump; use of collected solar energy to heat the load directly (two different ways); and use of a passive option to reduce the effective heating load.

An MPC Algorithm with Combined Speed and Steering Control for Obstacle Avoidance in Autonomous Ground Vehicles

DTIC Science & Technology

2015-04-24

from this line to the upper left side is caused by aerodynamic drag. The data for estimating the lateral load transfer coefficients is generated by...2013. [13] J. H. Jeon, R. V. Cowlagi, S. C. Peters, S. Karaman, E. Frazzoli, P. Tsiotras, and K. Iagnemma, “Optimal motion planning with the half- car ...Elsevier, 2005. [21] A. Rucco, G. Notarstefano, and J. Hauser, “Optimal control based dynamics exploration of a rigid car with longitudinal load

The Development and Application of Random Matrix Theory in Adaptive Signal Processing in the Sample Deficient Regime

DTIC Science & Technology

2014-09-01

optimal diagonal loading which minimizes the MSE. The be- havior of optimal diagonal loading when the arrival process is composed of plane waves embedded...observation vectors. The examples of the ensemble correlation matrix corresponding to the input process consisting of a single or multiple plane waves...Y ∗ij is a complex-conjugate of Yij. This result is used in order to evaluate the expectations of different quadratic forms. The Poincare -Nash

MEMS resonant load cells for micro-mechanical test frames: feasibility study and optimal design

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Learner, Patient, and Supervisor Features Are Associated With Different Types of Cognitive Load During Procedural Skills Training: Implications for Teaching and Instructional Design.

PubMed

Sewell, Justin L; Boscardin, Christy K; Young, John Q; Ten Cate, Olle; O'Sullivan, Patricia S

2017-11-01

Cognitive load theory, focusing on limits of the working memory, is relevant to medical education; however, factors associated with cognitive load during procedural skills training are not well characterized. The authors sought to determine how features of learners, patients/tasks, settings, and supervisors were associated with three types of cognitive load among learners performing a specific procedure, colonoscopy, to identify implications for procedural teaching. Data were collected through an electronically administered survey sent to 1,061 U.S. gastroenterology fellows during the 2014-2015 academic year; 477 (45.0%) participated. Participants completed the survey immediately following a colonoscopy. Using multivariable linear regression analyses, the authors identified sets of features associated with intrinsic, extraneous, and germane loads. Features associated with intrinsic load included learners (prior experience and year in training negatively associated, fatigue positively associated) and patient/tasks (procedural complexity positively associated, better patient tolerance negatively associated). Features associated with extraneous load included learners (fatigue positively associated), setting (queue order positively associated), and supervisors (supervisor engagement and confidence negatively associated). Only one feature, supervisor engagement, was (positively) associated with germane load. These data support practical recommendations for teaching procedural skills through the lens of cognitive load theory. To optimize intrinsic load, level of experience and competence of learners should be balanced with procedural complexity; part-task approaches and scaffolding may be beneficial. To reduce extraneous load, teachers should remain engaged, and factors within the procedural setting that may interfere with learning should be minimized. To optimize germane load, teachers should remain engaged.

Effects of external loads on balance control during upright stance: experimental results and model-based predictions.

PubMed

Qu, Xingda; Nussbaum, Maury A

2009-01-01

The purpose of this study was to identify the effects of external loads on balance control during upright stance, and to examine the ability of a new balance control model to predict these effects. External loads were applied to 12 young, healthy participants, and effects on balance control were characterized by center-of-pressure (COP) based measures. Several loading conditions were studied, involving combinations of load mass (10% and 20% of individual body mass) and height (at or 15% of stature above the whole-body COM). A balance control model based on an optimal control strategy was used to predict COP time series. It was assumed that a given individual would adopt the same neural optimal control mechanisms, identified in a no-load condition, under diverse external loading conditions. With the application of external loads, COP mean velocity in the anterior-posterior direction and RMS distance in the medial-lateral direction increased 8.1% and 10.4%, respectively. Predicted COP mean velocity and RMS distance in the anterior-posterior direction also increased with external loading, by 11.1% and 2.9%, respectively. Both experimental COP data and model-based predictions provided the same general conclusion, that application of larger external loads and loads more superior to the whole body center of mass lead to less effective postural control and perhaps a greater risk of loss of balance or falls. Thus, it can be concluded that the assumption about consistency in control mechanisms was partially supported, and it is the mechanical changes induced by external loads that primarily affect balance control.

Numerical simulation of unmanned aerial vehicle under centrifugal load and optimization of milling and planing

NASA Astrophysics Data System (ADS)

Chen, Yunsheng; Lu, Xinghua

2018-05-01

The mechanical parts of the fuselage surface of the UAV are easily fractured by the action of the centrifugal load. In order to improve the compressive strength of UAV and guide the milling and planing of mechanical parts, a numerical simulation method of UAV fuselage compression under centrifugal load based on discrete element analysis method is proposed. The three-dimensional discrete element method is used to establish the splitting tensile force analysis model of the UAV fuselage under centrifugal loading. The micro-contact connection parameters of the UAV fuselage are calculated, and the yield tensile model of the mechanical components is established. The dynamic and static mechanical model of the aircraft fuselage milling is analyzed by the axial amplitude vibration frequency combined method. The correlation parameters of the cutting depth on the tool wear are obtained. The centrifugal load stress spectrum of the surface of the UAV is calculated. The meshing and finite element simulation of the rotor blade of the unmanned aerial vehicle is carried out to optimize the milling process. The test results show that the accuracy of the anti - compression numerical test of the UAV is higher by adopting the method, and the anti - fatigue damage capability of the unmanned aerial vehicle body is improved through the milling and processing optimization, and the mechanical strength of the unmanned aerial vehicle can be effectively improved.

Experimental design and optimization of raloxifene hydrochloride loaded nanotransfersomes for transdermal application.

PubMed

Mahmood, Syed; Taher, Muhammad; Mandal, Uttam Kumar

2014-01-01

Raloxifene hydrochloride, a highly effective drug for the treatment of invasive breast cancer and osteoporosis in post-menopausal women, shows poor oral bioavailability of 2%. The aim of this study was to develop, statistically optimize, and characterize raloxifene hydrochloride-loaded transfersomes for transdermal delivery, in order to overcome the poor bioavailability issue with the drug. A response surface methodology experimental design was applied for the optimization of transfersomes, using Box-Behnken experimental design. Phospholipon(®) 90G, sodium deoxycholate, and sonication time, each at three levels, were selected as independent variables, while entrapment efficiency, vesicle size, and transdermal flux were identified as dependent variables. The formulation was characterized by surface morphology and shape, particle size, and zeta potential. Ex vivo transdermal flux was determined using a Hanson diffusion cell assembly, with rat skin as a barrier medium. Transfersomes from the optimized formulation were found to have spherical, unilamellar structures, with a homogeneous distribution and low polydispersity index (0.08). They had a particle size of 134±9 nM, with an entrapment efficiency of 91.00%±4.90%, and transdermal flux of 6.5±1.1 μg/cm(2)/hour. Raloxifene hydrochloride-loaded transfersomes proved significantly superior in terms of amount of drug permeated and deposited in the skin, with enhancement ratios of 6.25±1.50 and 9.25±2.40, respectively, when compared with drug-loaded conventional liposomes, and an ethanolic phosphate buffer saline. Differential scanning calorimetry study revealed a greater change in skin structure, compared with a control sample, during the ex vivo drug diffusion study. Further, confocal laser scanning microscopy proved an enhanced permeation of coumarin-6-loaded transfersomes, to a depth of approximately160 μM, as compared with rigid liposomes. These ex vivo findings proved that a raloxifene hydrochloride-loaded transfersome formulation could be a superior alternative to oral delivery of the drug.

Experimental design and optimization of raloxifene hydrochloride loaded nanotransfersomes for transdermal application

PubMed Central

Mahmood, Syed; Taher, Muhammad; Mandal, Uttam Kumar

2014-01-01

Raloxifene hydrochloride, a highly effective drug for the treatment of invasive breast cancer and osteoporosis in post-menopausal women, shows poor oral bioavailability of 2%. The aim of this study was to develop, statistically optimize, and characterize raloxifene hydrochloride-loaded transfersomes for transdermal delivery, in order to overcome the poor bioavailability issue with the drug. A response surface methodology experimental design was applied for the optimization of transfersomes, using Box-Behnken experimental design. Phospholipon® 90G, sodium deoxycholate, and sonication time, each at three levels, were selected as independent variables, while entrapment efficiency, vesicle size, and transdermal flux were identified as dependent variables. The formulation was characterized by surface morphology and shape, particle size, and zeta potential. Ex vivo transdermal flux was determined using a Hanson diffusion cell assembly, with rat skin as a barrier medium. Transfersomes from the optimized formulation were found to have spherical, unilamellar structures, with a homogeneous distribution and low polydispersity index (0.08). They had a particle size of 134±9 nM, with an entrapment efficiency of 91.00%±4.90%, and transdermal flux of 6.5±1.1 μg/cm2/hour. Raloxifene hydrochloride-loaded transfersomes proved significantly superior in terms of amount of drug permeated and deposited in the skin, with enhancement ratios of 6.25±1.50 and 9.25±2.40, respectively, when compared with drug-loaded conventional liposomes, and an ethanolic phosphate buffer saline. Differential scanning calorimetry study revealed a greater change in skin structure, compared with a control sample, during the ex vivo drug diffusion study. Further, confocal laser scanning microscopy proved an enhanced permeation of coumarin-6-loaded transfersomes, to a depth of approximately160 μM, as compared with rigid liposomes. These ex vivo findings proved that a raloxifene hydrochloride-loaded transfersome formulation could be a superior alternative to oral delivery of the drug. PMID:25246789

Topology optimization of pressure adaptive honeycomb for a morphing flap

NASA Astrophysics Data System (ADS)

Vos, Roelof; Scheepstra, Jan; Barrett, Ron

2011-03-01

The paper begins with a brief historical overview of pressure adaptive materials and structures. By examining avian anatomy, it is seen that pressure-adaptive structures have been used successfully in the Natural world to hold structural positions for extended periods of time and yet allow for dynamic shape changes from one flight state to the next. More modern pneumatic actuators, including FAA certified autopilot servoactuators are frequently used by aircraft around the world. Pneumatic artificial muscles (PAM) show good promise as aircraft actuators, but follow the traditional model of load concentration and distribution commonly found in aircraft. A new system is proposed which leaves distributed loads distributed and manipulates structures through a distributed actuator. By using Pressure Adaptive Honeycomb (PAH), it is shown that large structural deformations in excess of 50% strains can be achieved while maintaining full structural integrity and enabling secondary flight control mechanisms like flaps. The successful implementation of pressure-adaptive honeycomb in the trailing edge of a wing section sparked the motivation for subsequent research into the optimal topology of the pressure adaptive honeycomb within the trailing edge of a morphing flap. As an input for the optimization two known shapes are required: a desired shape in cruise configuration and a desired shape in landing configuration. In addition, the boundary conditions and load cases (including aerodynamic loads and internal pressure loads) should be specified for each condition. Finally, a set of six design variables is specified relating to the honeycomb and upper skin topology of the morphing flap. A finite-element model of the pressure-adaptive honeycomb structure is developed specifically tailored to generate fast but reliable results for a given combination of external loading, input variables, and boundary conditions. Based on two bench tests it is shown that this model correlates well to experimental results. The optimization process finds the skin and honeycomb topology that minimizes the error between the acquired shape and the desired shape in each configuration.

Identification of watershed priority management areas under water quality constraints: A simulation-optimization approach with ideal load reduction

NASA Astrophysics Data System (ADS)

Dong, Feifei; Liu, Yong; Wu, Zhen; Chen, Yihui; Guo, Huaicheng

2018-07-01

Targeting nonpoint source (NPS) pollution hot spots is of vital importance for placement of best management practices (BMPs). Although physically-based watershed models have been widely used to estimate nutrient emissions, connections between nutrient abatement and compliance of water quality standards have been rarely considered in NPS hotspot ranking, which may lead to ineffective decision-making. It's critical to develop a strategy to identify priority management areas (PMAs) based on water quality response to nutrient load mitigation. A water quality constrained PMA identification framework was thereby proposed in this study, based on the simulation-optimization approach with ideal load reduction (ILR-SO). It integrates the physically-based Soil and Water Assessment Tool (SWAT) model and an optimization model under constraints of site-specific water quality standards. To our knowledge, it was the first effort to identify PMAs with simulation-based optimization. The SWAT model was established to simulate temporal and spatial nutrient loading and evaluate effectiveness of pollution mitigation. A metamodel was trained to establish a quantitative relationship between sources and water quality. Ranking of priority areas is based on required nutrient load reduction in each sub-watershed targeting to satisfy water quality standards in waterbodies, which was calculated with genetic algorithm (GA). The proposed approach was used for identification of PMAs on the basis of diffuse total phosphorus (TP) in Lake Dianchi Watershed, one of the three most eutrophic large lakes in China. The modeling results demonstrated that 85% of diffuse TP came from 30% of the watershed area. Compared with the two conventional targeting strategies based on overland nutrient loss and instream nutrient loading, the ILR-SO model identified distinct PMAs and narrowed down the coverage of management areas. This study addressed the urgent need to incorporate water quality response into PMA identification and showed that the ILR-SO approach is effective to guide watershed management for aquatic ecosystem restoration.

Deep carbon reductions in California require electrification and integration across economic sectors

NASA Astrophysics Data System (ADS)

Wei, Max; Nelson, James H.; Greenblatt, Jeffery B.; Mileva, Ana; Johnston, Josiah; Ting, Michael; Yang, Christopher; Jones, Chris; McMahon, James E.; Kammen, Daniel M.

2013-03-01

Meeting a greenhouse gas (GHG) reduction target of 80% below 1990 levels in the year 2050 requires detailed long-term planning due to complexity, inertia, and path dependency in the energy system. A detailed investigation of supply and demand alternatives is conducted to assess requirements for future California energy systems that can meet the 2050 GHG target. Two components are developed here that build novel analytic capacity and extend previous studies: (1) detailed bottom-up projections of energy demand across the building, industry and transportation sectors; and (2) a high-resolution variable renewable resource capacity planning model (SWITCH) that minimizes the cost of electricity while meeting GHG policy goals in the 2050 timeframe. Multiple pathways exist to a low-GHG future, all involving increased efficiency, electrification, and a dramatic shift from fossil fuels to low-GHG energy. The electricity system is found to have a diverse, cost-effective set of options that meet aggressive GHG reduction targets. This conclusion holds even with increased demand from transportation and heating, but the optimal levels of wind and solar deployment depend on the temporal characteristics of the resulting load profile. Long-term policy support is found to be a key missing element for the successful attainment of the 2050 GHG target in California.

Optimal management strategies in variable environments: Stochastic optimal control methods

USGS Publications Warehouse

Williams, B.K.

1985-01-01

Dynamic optimization was used to investigate the optimal defoliation of salt desert shrubs in north-western Utah. Management was formulated in the context of optimal stochastic control theory, with objective functions composed of discounted or time-averaged biomass yields. Climatic variability and community patterns of salt desert shrublands make the application of stochastic optimal control both feasible and necessary. A primary production model was used to simulate shrub responses and harvest yields under a variety of climatic regimes and defoliation patterns. The simulation results then were used in an optimization model to determine optimal defoliation strategies. The latter model encodes an algorithm for finite state, finite action, infinite discrete time horizon Markov decision processes. Three questions were addressed: (i) What effect do changes in weather patterns have on optimal management strategies? (ii) What effect does the discounting of future returns have? (iii) How do the optimal strategies perform relative to certain fixed defoliation strategies? An analysis was performed for the three shrub species, winterfat (Ceratoides lanata), shadscale (Atriplex confertifolia) and big sagebrush (Artemisia tridentata). In general, the results indicate substantial differences among species in optimal control strategies, which are associated with differences in physiological and morphological characteristics. Optimal policies for big sagebrush varied less with variation in climate, reserve levels and discount rates than did either shadscale or winterfat. This was attributed primarily to the overwintering of photosynthetically active tissue and to metabolic activity early in the growing season. Optimal defoliation of shadscale and winterfat generally was more responsive to differences in plant vigor and climate, reflecting the sensitivity of these species to utilization and replenishment of carbohydrate reserves. Similarities could be seen in the influence of both the discount rate and the climatic patterns on optimal harvest strategics. In general, decreases in either the discount rate or in the frequency of favorable weather patterns lcd to a more conservative defoliation policy. This did not hold, however, for plants in states of low vigor. Optimal control for shadscale and winterfat tended to stabilize on a policy of heavy defoliation stress, followed by one or more seasons of rest. Big sagebrush required a policy of heavy summer defoliation when sufficient active shoot material is present at the beginning of the growing season. The comparison of fixed and optimal strategies indicated considerable improvement in defoliation yields when optimal strategies are followed. The superior performance was attributable to increased defoliation of plants in states of high vigor. Improvements were found for both discounted and undiscounted yields.

Balancing Power Absorption Against Structural Loads With Viscous Drag and Power-Takeoff Efficiency Considerations

DOE PAGES

Tom, Nathan; Yu, Yi-Hsiang; Wright, Alan; ...

2017-11-17

The focus of this paper is to balance power absorption against structural loading for a novel fixed-bottom oscillating surge wave energy converter in both regular and irregular wave environments. The power-to-load ratio will be evaluated using pseudospectral control (PSC) to determine the optimum power-takeoff (PTO) torque based on a multiterm objective function. This paper extends the pseudospectral optimal control problem to not just maximize the time-averaged absorbed power but also include measures for the surge-foundation force and PTO torque in the optimization. The objective function may now potentially include three competing terms that the optimizer must balance. Separate weighting factorsmore » are attached to the surge-foundation force and PTO control torque that can be used to tune the optimizer performance to emphasize either power absorption or load shedding. To correct the pitch equation of motion, derived from linear hydrodynamic theory, a quadratic-viscous-drag torque has been included in the system dynamics; however, to continue the use of quadratic programming solvers, an iteratively obtained linearized drag coefficient was utilized that provided good accuracy in the predicted pitch motion. Furthermore, the analysis considers the use of a nonideal PTO unit to more accurately evaluate controller performance. The PTO efficiency is not directly included in the objective function but rather the weighting factors are utilized to limit the PTO torque amplitudes, thereby reducing the losses resulting from the bidirectional energy flow through a nonideal PTO. Results from PSC show that shedding a portion of the available wave energy can lead to greater reductions in structural loads, peak-to-average power ratio, and reactive power requirement.« less

Large scale cardiac modeling on the Blue Gene supercomputer.

PubMed

Reumann, Matthias; Fitch, Blake G; Rayshubskiy, Aleksandr; Keller, David U; Weiss, Daniel L; Seemann, Gunnar; Dössel, Olaf; Pitman, Michael C; Rice, John J

2008-01-01

Multi-scale, multi-physical heart models have not yet been able to include a high degree of accuracy and resolution with respect to model detail and spatial resolution due to computational limitations of current systems. We propose a framework to compute large scale cardiac models. Decomposition of anatomical data in segments to be distributed on a parallel computer is carried out by optimal recursive bisection (ORB). The algorithm takes into account a computational load parameter which has to be adjusted according to the cell models used. The diffusion term is realized by the monodomain equations. The anatomical data-set was given by both ventricles of the Visible Female data-set in a 0.2 mm resolution. Heterogeneous anisotropy was included in the computation. Model weights as input for the decomposition and load balancing were set to (a) 1 for tissue and 0 for non-tissue elements; (b) 10 for tissue and 1 for non-tissue elements. Scaling results for 512, 1024, 2048, 4096 and 8192 computational nodes were obtained for 10 ms simulation time. The simulations were carried out on an IBM Blue Gene/L parallel computer. A 1 s simulation was then carried out on 2048 nodes for the optimal model load. Load balances did not differ significantly across computational nodes even if the number of data elements distributed to each node differed greatly. Since the ORB algorithm did not take into account computational load due to communication cycles, the speedup is close to optimal for the computation time but not optimal overall due to the communication overhead. However, the simulation times were reduced form 87 minutes on 512 to 11 minutes on 8192 nodes. This work demonstrates that it is possible to run simulations of the presented detailed cardiac model within hours for the simulation of a heart beat.

Optimal load for the peak power and maximal strength of the upper body in Brazilian Jiu-Jitsu athletes.

PubMed

da Silva, Bruno Victor C; Simim, Mário A de Moura; Marocolo, Moacir; Franchini, Emerson; da Mota, Gustavo R

2015-06-01

We determined the optimal load for the peak power output (PPO) during the bench press throw (BPT) in Brazilian Jiu-Jitsu (BJJ) athletes and compared the PPO and maximal strength between advanced (AD) and nonadvanced (NA) athletes. Twenty-eight BJJ athletes (24.8 ± 5.7 years) performed the BPT at loads of 30, 40, 50, and 60% of their 1 repetition maximum (RM) in a randomized order (5-minute rest between BPTs). The PPO was determined by measuring the barbell displacement by an accelerometer (Myotest). The absolute (F = 7.25; p < 0.001; effect size [ES] = 0.21) and relative intensities were different (F = 7.11; p < 0.001; ES = 0.21) between the AD and NA. There was also a group and intensity interaction effect (F = 2.79; p = 0.046; ES = 0.10), but the differences were centered around the AD group, which achieved higher values using 40% (p = 0.001) and 50% of the 1RM (p < 0.001) than the PPO with 60% of 1RM. The AD athletes presented with higher 1RM than NA (p ≤ 0.05; ES = 1.0), but there was no difference (p > 0.05) in the PPO (30-60% 1RM). A polynomial adjustment indicated that the optimal load was ∼42% of 1RM for all groups and subgroups (R from 0.82 to 0.99). Our results suggest that there can be (1RM) differences between AD and NA BJJ athletes; however, there is no difference in the muscle power between the AD and NA groups. Additionally, ∼42% of 1RM seems to be the optimal load for developing maximal power using the BPT for the BJJ athletes.

A tool for simulating parallel branch-and-bound methods

NASA Astrophysics Data System (ADS)

Golubeva, Yana; Orlov, Yury; Posypkin, Mikhail

2016-01-01

The Branch-and-Bound method is known as one of the most powerful but very resource consuming global optimization methods. Parallel and distributed computing can efficiently cope with this issue. The major difficulty in parallel B&B method is the need for dynamic load redistribution. Therefore design and study of load balancing algorithms is a separate and very important research topic. This paper presents a tool for simulating parallel Branchand-Bound method. The simulator allows one to run load balancing algorithms with various numbers of processors, sizes of the search tree, the characteristics of the supercomputer's interconnect thereby fostering deep study of load distribution strategies. The process of resolution of the optimization problem by B&B method is replaced by a stochastic branching process. Data exchanges are modeled using the concept of logical time. The user friendly graphical interface to the simulator provides efficient visualization and convenient performance analysis.

Design, Optimization, and Evaluation of A1-2139 Compression Panel with Integral T-Stiffeners

NASA Technical Reports Server (NTRS)

Mulani, Sameer B.; Havens, David; Norris, Ashley; Bird, R. Keith; Kapania, Rakesh K.; Olliffe, Robert

2012-01-01

A T-stiffened panel was designed and optimized for minimum mass subjected to constraints on buckling load, yielding, and crippling or local stiffener failure using a new analysis and design tool named EBF3PanelOpt. The panel was designed for a compression loading configuration, a realistic load case for a typical aircraft skin-stiffened panel. The panel was integrally machined from 2139 aluminum alloy plate and was tested in compression. The panel was loaded beyond buckling and strains and out-of-plane displacements were extracted from 36 strain gages and one linear variable displacement transducer. A digital photogrammetric system was used to obtain full field displacements and strains on the smooth (unstiffened) side of the panel. The experimental data were compared with the strains and out-of-plane deflections from a high-fidelity nonlinear finite element analysis.

Formulation, optimization and evaluation of curcumin-β-cyclodextrin-loaded sponge for effective drug delivery in thermal burns chemotherapy.

PubMed

Kaur, Navdeep; Garg, Tarun; Goyal, Amit K; Rath, Goutam

2016-09-01

The present study was designed to determine the role of curcumin-β-cyclodextrin-loaded sponge on burn wound healing in rats. Curcumin-β-cyclodextrin complex was prepared by the solvent evaporation encapsulation method. Molecular inclusion complex of curcumin-β-cyclodextrin was incorporated into gelatin sponge. The developed sponge was characterized for drug entrapment, drug release and morphology. The biological activity of optimized formulation was determined on burn wounds which were made on rats. The burn wound healing efficacy was analyzed through physical and histological changes observed at the wound sites. There was a significant decrease in rate of wound contraction in experimental groups then the control group. Curcumin-β-cyclodextrin-loaded sponge treated wound was found to heal in rate comparable to marketed formulation with no sign of adverse consequence. The result clearly substantiates the beneficial effects of curcumin-β-cyclodextrin-loaded sponge in the acceleration of wound healing.

Determining EBV load: current best practice and future requirements.

PubMed

Ruf, Stephanie; Wagner, Hans-Joachim

2013-02-01

EBV, a gammaherpesvirus and the pathogenic agent for infectious mononucleosis, is also associated with a broad spectrum of lymphoid and epithelial malignancies in immunocompetent and immunosuppressed individuals. EBV-DNA-load measurement by PCR has been shown to be a potential tool for the diagnosis of these diseases, a prognostic factor of their outcome and a successful method to monitor immunosuppressed patients. Since the end of 2011, there is an international WHO standard reference for EBV quantification available; however, many questions still remain; for instance about the optimal amplified region of the EBV genome, or the best-used specimen for EBV detection. Additionally, the optimal specimen and amplified region may vary in different malignancies. In this article, the authors review the different methods to measure EBV load, focus on the best-used specimen for the different EBV-associated malignancies and discuss future requirements and opportunities for EBV-load measurement.

Climate and weather risk in natural resource models

NASA Astrophysics Data System (ADS)

Merrill, Nathaniel Henry

This work, consisting of three manuscripts, addresses natural resource management under risk due to variation in climate and weather. In three distinct but theoretically related applications, I quantify the role of natural resources in stabilizing economic outcomes. In Manuscript 1, we address policy designed to effect the risk of cyanobacteria blooms in a drinking water reservoir through watershed wide policy. Combining a hydrologic and economic model for a watershed in Rhode Island, we solve for the efficient allocation of best management practices (BMPs) on livestock pastures to meet a monthly risk-based as well as mean-based water quality objective. In order to solve for the efficient allocations of nutrient control effort, we optimize a probabilistically constrained integer-programming problem representing the choices made on each farm and the resultant conditions that support cyanobacteria blooms. In doing so, we employ a genetic algorithm (GA). We hypothesize that management based on controlling the upper tail of the probability distribution of phosphorus loading implies different efficient management actions as compared to controlling mean loading. We find a shift to more intense effort on fewer acres when a probabilistic objective is specified with cost savings of meeting risk levels of up to 25% over mean loading based policies. Additionally, we illustrate the relative cost effectiveness of various policies designed to meet this risk-based objective. Rainfall and the subsequent overland runoff is the source of transportation of nutrients to a receiving water body, with larger amounts of phosphorus moving in more intense rainfall events. We highlight the importance of this transportation mechanism by comparing policies under climate change scenarios, where the intensity of rainfall is projected to increase and the time series process of rainfall to change. In Manuscript 2, we introduce a new economic groundwater model that incorporates the gradual shift from irrigation to dryland farming as parts of an aquifer run dry. We accomplish this using an upside down cone to represent the spatial depletion, where the area of irrigable land above the aquifer shrinks as the water level decreases. Depletion of the aquifer may interact with uncertainty of the supply of water because the buffer that groundwater provides is no longer available. In this work, we identify the impact of spatial depletion on welfare gains from optimal management when rainfall is stochastic and follows a Markov process. Using a stylized model and dynamic programming, we estimate gains from moving away from current myopic extraction behavior to optimal use of the resource. When applied to Kansas over a section of the Ogallala Aquifer, we find gains from management ranging from 2.88% to 3.01% with larger gains achieved under uncertainty in the rainfall process. We find that including the dynamic of the gradual spatial depletion of the aquifer does materially impact welfare results compared to other estimates of the same region. Surprisingly the serial correlation of rainfall matters little. Empirically, multi-year droughts combined with the loss of access to the aquifer only slightly increases welfare gains due to the availability of dryland farming and the productivity of that option as a backstop when available. Manuscript 3 empirically estimates the effect of an increase in natural gas pipeline capacity in New England on monthly equilibrium natural gas prices and quantities for the electric sector. Weather plays an important role in defining the demand for natural gas due to its use for heating and electricity generation in the winter and through electricity demand for cooling in the summer. The cost of natural gas has important consequences to the wellbeing and cost of living for millions of customers either relying directly on natural gas for heating, or electric energy consumers indirectly. This paper presents results of reduced form price and quantity time series regressions using Generalized Least Squares (GLS) followed by results of a dynamic simultaneous equation model (SEM) of the market system. I highlight the role capacity has in effecting the variability of the price of energy to the region. This work adds to the literature by providing empirical evidence and the quantification of the effect of constrained pipeline supply in an important energy market, where weather conditions, multiple demand sectors and alternative fuels determine the cost of energy. I find that capacity is a significant factor in the prices and quantities of natural gas consumed by the electric sector, with an increase in pipeline capacity of 1% leading to an average decrease in price of .48% and an increase in consumption of .2%. The SEM model finds both supply and demand to be price inelastic. (Abstract shortened by UMI.).

Agricultural Policy Environmental eXtender simulation of three adjacent row-crop watersheds in the claypan region

USDA-ARS?s Scientific Manuscript database

The Agricultural Policy Environmental Extender (APEX) model can simulate crop yields, and pollutant loadings in whole farms or small watersheds with variety of management practices. The study objectives were to identify sensitive parameters and parameterize, calibrate and validate the APEX model fo...

Optimal Navigation of Self-Propelled Colloids in Microstructured Mazes

NASA Astrophysics Data System (ADS)

Yang, Yuguang; Bevan, Michael

Controlling navigation of self-propelled microscopic `robots' subject to random Brownian motion in complex microstructured environments (e.g., porous media, tumor vasculature) is important to many emerging applications (e.g., enhanced oil recovery, drug delivery). In this work, we design an optimal feedback policy to navigate an active self-propelled colloidal rod in complex mazes with various obstacle types. Actuation of the rods is modelled based on a light-controlled osmotic flow mechanism, which produces different propulsion velocities along the rod's long axis. Actuator-parameterized Langevin equations, with soft rod-obstacle repulsive interactions, are developed to describe the system dynamics. A Markov decision process (MDP) framework is used for optimal policy calculations with design goals of colloidal rods reaching target end points in minimum time. Simulations show that optimal MDP-based policies are able to control rod trajectories to reach target regions order-of-magnitudes faster than uncontrolled rods, which diverges as maze complexity increases. An efficient multi-graph based implementation for MDP is also presented, which scales linearly with the maze dimension.

Etiologic effects and optimal intakes of foods and nutrients for risk of cardiovascular diseases and diabetes: Systematic reviews and meta-analyses from the Nutrition and Chronic Diseases Expert Group (NutriCoDE)

PubMed Central

Peñalvo, Jose L.; Khatibzadeh, Shahab; Singh, Gitanjali M.; Rao, Mayuree; Fahimi, Saman; Powles, John; Mozaffarian, Dariush

2017-01-01

Background Dietary habits are major contributors to coronary heart disease, stroke, and diabetes. However, comprehensive evaluation of etiologic effects of dietary factors on cardiometabolic outcomes, their quantitative effects, and corresponding optimal intakes are not well-established. Objective To systematically review the evidence for effects of dietary factors on cardiometabolic diseases, including comprehensively assess evidence for causality; estimate magnitudes of etiologic effects; evaluate heterogeneity and potential for bias in these etiologic effects; and determine optimal population intake levels. Methods We utilized Bradford-Hill criteria to assess probable or convincing evidence for causal effects of multiple diet-cardiometabolic disease relationships. Etiologic effects were quantified from published or de novo meta-analyses of prospective studies or randomized clinical trials, incorporating standardized units, dose-response estimates, and heterogeneity by age and other characteristics. Potential for bias was assessed in validity analyses. Optimal intakes were determined by levels associated with lowest disease risk. Results We identified 10 foods and 7 nutrients with evidence for causal cardiometabolic effects, including protective effects of fruits, vegetables, beans/legumes, nuts/seeds, whole grains, fish, yogurt, fiber, seafood omega-3s, polyunsaturated fats, and potassium; and harms of unprocessed red meats, processed meats, sugar-sweetened beverages, glycemic load, trans-fats, and sodium. Proportional etiologic effects declined with age, but did not generally vary by sex. Established optimal population intakes were generally consistent with observed national intakes and major dietary guidelines. In validity analyses, the identified effects of individual dietary components were similar to quantified effects of dietary patterns on cardiovascular risk factors and hard endpoints. Conclusions These novel findings provide a comprehensive summary of causal evidence, quantitative etiologic effects, heterogeneity, and optimal intakes of major dietary factors for cardiometabolic diseases, informing disease impact estimation and policy planning and priorities. PMID:28448503

Universal approximators for multi-objective direct policy search in water reservoir management problems: a comparative analysis

NASA Astrophysics Data System (ADS)

Giuliani, Matteo; Mason, Emanuele; Castelletti, Andrea; Pianosi, Francesca

2014-05-01

The optimal operation of water resources systems is a wide and challenging problem due to non-linearities in the model and the objectives, high dimensional state-control space, and strong uncertainties in the hydroclimatic regimes. The application of classical optimization techniques (e.g., SDP, Q-learning, gradient descent-based algorithms) is strongly limited by the dimensionality of the system and by the presence of multiple, conflicting objectives. This study presents a novel approach which combines Direct Policy Search (DPS) and Multi-Objective Evolutionary Algorithms (MOEAs) to solve high-dimensional state and control space problems involving multiple objectives. DPS, also known as parameterization-simulation-optimization in the water resources literature, is a simulation-based approach where the reservoir operating policy is first parameterized within a given family of functions and, then, the parameters optimized with respect to the objectives of the management problem. The selection of a suitable class of functions to which the operating policy belong to is a key step, as it might restrict the search for the optimal policy to a subspace of the decision space that does not include the optimal solution. In the water reservoir literature, a number of classes have been proposed. However, many of these rules are based largely on empirical or experimental successes and they were designed mostly via simulation and for single-purpose reservoirs. In a multi-objective context similar rules can not easily inferred from the experience and the use of universal function approximators is generally preferred. In this work, we comparatively analyze two among the most common universal approximators: artificial neural networks (ANN) and radial basis functions (RBF) under different problem settings to estimate their scalability and flexibility in dealing with more and more complex problems. The multi-purpose HoaBinh water reservoir in Vietnam, accounting for hydropower production and flood control, is used as a case study. Preliminary results show that the RBF policy parametrization is more effective than the ANN one. In particular, the approximated Pareto front obtained with RBF control policies successfully explores the full tradeoff space between the two conflicting objectives, while most of the ANN solutions results to be Pareto-dominated by the RBF ones.

Development and optimization of apigenin-loaded transfersomal system for skin cancer delivery: in vitro evaluation.

PubMed

Jangdey, Manmohan Singh; Gupta, Anshita; Saraf, Shailendra; Saraf, Swarnlata

2017-11-01

The aim of this work is to apply Box-Behnken design to optimize the transfersomes were formulated by modified rotary evaporation sonication technique using surfactant Tween 80. The response surface methodology was used having three-factored with three levels. The prepared formulations were characterized for vesicle shape, size, entrapment efficiency (%), stability, and in vitro permeation. The result showed that drug entrapment of 84.24% with average vesicle size of 35.41 nm and drug loading of 8.042%. Thus, optimized formulation was found good stability and is a promising approach to improve the permeability of apigenin in sustained release for prolonged period of time.

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.

The application of the Luus-Jaakola direct search method to the optimization of a hybrid renewable energy system

NASA Astrophysics Data System (ADS)

Jatzeck, Bernhard Michael

2000-10-01

The application of the Luus-Jaakola direct search method to the optimization of stand-alone hybrid energy systems consisting of wind turbine generators (WTG's), photovoltaic (PV) modules, batteries, and an auxiliary generator was examined. The loads for these systems were for agricultural applications, with the optimization conducted on the basis of minimum capital, operating, and maintenance costs. Five systems were considered: two near Edmonton, Alberta, and one each near Lethbridge, Alberta, Victoria, British Columbia, and Delta, British Columbia. The optimization algorithm used hourly data for the load demand, WTG output power/area, and PV module output power. These hourly data were in two sets: seasonal (summer and winter values separated) and total (summer and winter values combined). The costs for the WTG's, PV modules, batteries, and auxiliary generator fuel were full market values. To examine the effects of price discounts or tax incentives, these values were lowered to 25% of the full costs for the energy sources and two-thirds of the full cost for agricultural fuel. Annual costs for a renewable energy system depended upon the load, location, component costs, and which data set (seasonal or total) was used. For one Edmonton load, the cost for a renewable energy system consisting of 27.01 m2 of WTG area, 14 PV modules, and 18 batteries (full price, total data set) was 6873/year. For Lethbridge, a system with 22.85 m2 of WTG area, 47 PV modules, and 5 batteries (reduced prices, seasonal data set) cost 2913/year. The performance of renewable energy systems based on the obtained results was tested in a simulation using load and weather data for selected days. Test results for one Edmonton load showed that the simulations for most of the systems examined ran for at least 17 hours per day before failing due to either an excessive load on the auxiliary generator or a battery constraint being violated. Additional testing indicated that increasing the generator capacity and reducing the maximum allowed battery charge current during the time of the day at which these failures occurred allowed the simulation to successfully operate.

Single line source with and without vaginal loading and the impact on target coverage and organ at risk doses for cervix cancer Stages IB, II, and IIIB: treatment planning simulation in patients treated with MRI-guided adaptive brachytherapy in a multicentre study (EMBRACE).

PubMed

Nkiwane, Karen S; Pötter, Richard; Tanderup, Kari; Federico, Mario; Lindegaard, Jacob C; Kirisits, Christian

2013-01-01

Three-dimensional evaluation and comparison of target and organs at risk (OARs) doses from two traditional standard source loading patterns in the frame of MRI-guided cervical cancer brachytherapy for various clinical scenarios based on patient data collected in a multicenter trial setting. Two nonoptimized three-dimensional MRI-based treatment plans, Plan 1 (tandem and vaginal loading) and Plan 2 (tandem loading only), were generated for 134 patients from seven centers participating in the EMBRACE study. Both plans were normalized to point A (Pt. A). Target and OAR doses were evaluated in terms of minimum dose to 90% of the high-risk clinical target volume (HRCTV D90) grouped by tumor stage and minimum dose to the most exposed 2cm³ of the OARs volume. An HRCTV D90 ≥ Pt. A was achieved in 82% and 44% of the patients with Plans 1 and 2, respectively. Median HRCTV D90 with Plans 1 and 2 was 120% and 90% of Pt. A dose, respectively. Both plans had optimal dose coverage in 88% of Stage IB tumors; however, the tandem-only plan resulted in about 50% of dose reduction to the vagina and rectum. For Stages IIB and IIIB, Plan 1 had on average 35% better target coverage but with significant doses to OARs. Standard tandem loading alone results in good target coverage in most Stage IB tumors without violating OAR dose constraints. For Stage IIB tumors, standard vaginal loading improves the therapeutic window, however needs optimization to fulfill the dose prescription for target and OAR. In Stage IIIB, even optimized vaginal loading often does not fulfill the needs for dose prescription. The significant dose variation across various clinical scenarios for both target and OARs indicates the need for image-guided brachytherapy for optimal dose adaptation both for limited and advanced diseases. Copyright © 2013 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

A Comparison Study of Stochastic- and Guaranteed- Service Approaches on Safety Stock Optimization for Multi Serial Systems

NASA Astrophysics Data System (ADS)

Li, Peng; Wu, Di

2018-01-01

Two competing approaches have been developed over the years for multi-echelon inventory system optimization, stochastic-service approach (SSA) and guaranteed-service approach (GSA). Although they solve the same inventory policy optimization problem in their core, they make different assumptions with regard to the role of safety stock. This paper provides a detailed comparison of the two approaches by considering operating flexibility costs in the optimization of (R, Q) policies for a continuous review serial inventory system. The results indicate the GSA model is more efficiency in solving the complicated inventory problem in terms of the computation time, and the cost difference of the two approaches is quite small.

Optimal tracking control for a class of nonlinear discrete-time systems with time delays based on heuristic dynamic programming.

PubMed

Zhang, Huaguang; Song, Ruizhuo; Wei, Qinglai; Zhang, Tieyan

2011-12-01

In this paper, a novel heuristic dynamic programming (HDP) iteration algorithm is proposed to solve the optimal tracking control problem for a class of nonlinear discrete-time systems with time delays. The novel algorithm contains state updating, control policy iteration, and performance index iteration. To get the optimal states, the states are also updated. Furthermore, the "backward iteration" is applied to state updating. Two neural networks are used to approximate the performance index function and compute the optimal control policy for facilitating the implementation of HDP iteration algorithm. At last, we present two examples to demonstrate the effectiveness of the proposed HDP iteration algorithm.

Model Predictive Control of HVAC Systems: Implementation and Testing at the University of California, Merced

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

Haves, Phillip; Hencey, Brandon; Borrell, Francesco

2010-06-29

A Model Predictive Control algorithm was developed for the UC Merced campus chilled water plant. Model predictive control (MPC) is an advanced control technology that has proven successful in the chemical process industry and other industries. The main goal of the research was to demonstrate the practical and commercial viability of MPC for optimization of building energy systems. The control algorithms were developed and implemented in MATLAB, allowing for rapid development, performance, and robustness assessment. The UC Merced chilled water plant includes three water-cooled chillers and a two million gallon chilled water storage tank. The tank is charged during themore » night to minimize on-peak electricity consumption and take advantage of the lower ambient wet bulb temperature. The control algorithms determined the optimal chilled water plant operation including chilled water supply (CHWS) temperature set-point, condenser water supply (CWS) temperature set-point and the charging start and stop times to minimize a cost function that includes energy consumption and peak electrical demand over a 3-day prediction horizon. A detailed model of the chilled water plant and simplified models of the buildings served by the plant were developed using the equation-based modeling language Modelica. Steady state models of the chillers, cooling towers and pumps were developed, based on manufacturers performance data, and calibrated using measured data collected and archived by the control system. A detailed dynamic model of the chilled water storage tank was also developed and calibrated. Simple, semi-empirical models were developed to predict the temperature and flow rate of the chilled water returning to the plant from the buildings. These models were then combined and simplified for use in a model predictive control algorithm that determines the optimal chiller start and stop times and set-points for the condenser water temperature and the chilled water supply temperature. The report describes the development and testing of the algorithm and evaluates the resulting performance, concluding with a discussion of next steps in further research. The experimental results show a small improvement in COP over the baseline policy but it is difficult to draw any strong conclusions about the energy savings potential for MPC with this system only four days of suitable experimental data were obtained once correct operation of the MPC system had been achieved. These data show an improvement in COP of 3.1% {+-} 2.2% relative to a baseline established immediately prior to the period when the MPC was run in its final form. This baseline includes control policy improvements that the plant operators learned by observing the earlier implementations of MPC, including increasing the temperature of the water supplied to the chiller condensers from the cooling towers. The process of data collection and model development, necessary for any MPC project, resulted in the team uncovering various problems with the chilled water system. Although it is difficult to quantify the energy savings resulting from these problems being remedied, they were likely on the same order as the energy savings from the MPC itself. Although the types of problems uncovered and the level of energy savings may differ significantly from other projects, some of the benefits of detecting and diagnosing problems are expected from the use of MPC for any chilled water plant. The degree of chiller loading was found to be a key factor for efficiency. It is more efficient to operate the chillers at or near full load. In order to maximize the chiller load, one would maximize the temperature difference across chillers and the chilled water flow rate through the chillers. Thus, the CHWS set-point and the chilled water flow-rate can be used to limit the chiller loading to prevent chiller surging. Since the flow rate has an upper bound and the CHWS set point has a lower bound, the chiller loading is constrained and often determined by the chilled water return temperature (CHWR). The CHWR temperature is primarily comprised of warm water from the top of the TES tank. The CHWR temperature falls substantially as the thermocline approaches the top of the tank, which reduces the chiller loading. As a result, it has been determined that overcharging the TES tank can be detrimental to the chilled water plant efficiency. The resulting MPC policy differs from the current practice of fully charging the TES tank. A heuristic rule could possible avoid this problem without using predictive control. Similarly, the COP improvements from the change in CWS set-point were largely captured by a static set-point change by the operators. Further research is required to determine how much of the MPC savings could be garnered through simplified rules (based on the MPC study), with and without prediction.« less

Potential of a precrash lateral occupant movement in side collisions of (electric) minicars.

PubMed

Hierlinger, T; Lienkamp, M; Unger, J; Unselt, T

2015-01-01

In minicars, the survival space between the side structure and occupant is smaller than in conventional cars. This is an issue in side collisions. Therefore, in this article a solution is studied in which a lateral seat movement is imposed in the precrash phase. It generates a pre-acceleration and an initial velocity of the occupant, thus reducing the loads due to the side impact. The assessment of the potential is done by numerical simulations and a full-vehicle crash test. The optimal parameters of the restraint system including the precrash movement, time-to-fire of head and side airbag, etc., are found using metamodel-based optimization methods by minimizing occupant loads according to European New Car Assessment Programme (Euro NCAP). The metamodel-based optimization approach is able to tune the restraint system parameters. The numerical simulations show a significant averaged reduction of 22.3% in occupant loads. The results show that the lateral precrash occupant movement offers better occupant protection in side collisions.

A Domain Decomposition Parallelization of the Fast Marching Method

NASA Technical Reports Server (NTRS)

Herrmann, M.

2003-01-01

In this paper, the first domain decomposition parallelization of the Fast Marching Method for level sets has been presented. Parallel speedup has been demonstrated in both the optimal and non-optimal domain decomposition case. The parallel performance of the proposed method is strongly dependent on load balancing separately the number of nodes on each side of the interface. A load imbalance of nodes on either side of the domain leads to an increase in communication and rollback operations. Furthermore, the amount of inter-domain communication can be reduced by aligning the inter-domain boundaries with the interface normal vectors. In the case of optimal load balancing and aligned inter-domain boundaries, the proposed parallel FMM algorithm is highly efficient, reaching efficiency factors of up to 0.98. Future work will focus on the extension of the proposed parallel algorithm to higher order accuracy. Also, to further enhance parallel performance, the coupling of the domain decomposition parallelization to the G(sub 0)-based parallelization will be investigated.

Extended shortest path selection for package routing of complex networks

NASA Astrophysics Data System (ADS)

Ye, Fan; Zhang, Lei; Wang, Bing-Hong; Liu, Lu; Zhang, Xing-Yi

The routing strategy plays a very important role in complex networks such as Internet system and Peer-to-Peer networks. However, most of the previous work concentrates only on the path selection, e.g. Flooding and Random Walk, or finding the shortest path (SP) and rarely considering the local load information such as SP and Distance Vector Routing. Flow-based Routing mainly considers load balance and still cannot achieve best optimization. Thus, in this paper, we propose a novel dynamic routing strategy on complex network by incorporating the local load information into SP algorithm to enhance the traffic flow routing optimization. It was found that the flow in a network is greatly affected by the waiting time of the network, so we should not consider only choosing optimized path for package transformation but also consider node congestion. As a result, the packages should be transmitted with a global optimized path with smaller congestion and relatively short distance. Analysis work and simulation experiments show that the proposed algorithm can largely enhance the network flow with the maximum throughput within an acceptable calculating time. The detailed analysis of the algorithm will also be provided for explaining the efficiency.

Dynamics of hepatitis C under optimal therapy and sampling based analysis

NASA Astrophysics Data System (ADS)

Pachpute, Gaurav; Chakrabarty, Siddhartha P.

2013-08-01

We examine two models for hepatitis C viral (HCV) dynamics, one for monotherapy with interferon (IFN) and the other for combination therapy with IFN and ribavirin. Optimal therapy for both the models is determined using the steepest gradient method, by defining an objective functional which minimizes infected hepatocyte levels, virion population and side-effects of the drug(s). The optimal therapies for both the models show an initial period of high efficacy, followed by a gradual decline. The period of high efficacy coincides with a significant decrease in the viral load, whereas the efficacy drops after hepatocyte levels are restored. We use the Latin hypercube sampling technique to randomly generate a large number of patient scenarios and study the dynamics of each set under the optimal therapy already determined. Results show an increase in the percentage of responders (indicated by drop in viral load below detection levels) in case of combination therapy (72%) as compared to monotherapy (57%). Statistical tests performed to study correlations between sample parameters and time required for the viral load to fall below detection level, show a strong monotonic correlation with the death rate of infected hepatocytes, identifying it to be an important factor in deciding individual drug regimens.

Optimization of LDL targeted nanostructured lipid carriers of 5-FU by a full factorial design.

PubMed

Andalib, Sare; Varshosaz, Jaleh; Hassanzadeh, Farshid; Sadeghi, Hojjat

2012-01-01

Nanostructured lipid carriers (NLC) are a mixture of solid and liquid lipids or oils as colloidal carrier systems that lead to an imperfect matrix structure with high ability for loading water soluble drugs. The aim of this study was to find the best proportion of liquid and solid lipids of different types for optimization of the production of LDL targeted NLCs used in carrying 5-Fu by the emulsification-solvent evaporation method. The influence of the lipid type, cholesterol or cholesteryl stearate for targeting LDL receptors, oil type (oleic acid or octanol), lipid and oil% on particle size, surface charge, drug loading efficiency, and drug released percent from the NLCs were studied by a full factorial design. The NLCs prepared by 54.5% cholesterol and 25% of oleic acid, showed optimum results with particle size of 105.8 nm, relatively high zeta potential of -25 mV, drug loading efficiency of 38% and release efficiency of about 40%. Scanning electron microscopy of nanoparticles confirmed the results of dynamic light scattering method used in measuring the particle size of NLCs. The optimization method by a full factorial statistical design is a useful optimization method for production of nanostructured lipid carriers.

Optimized operation of dielectric laser accelerators: Multibunch

NASA Astrophysics Data System (ADS)

Hanuka, Adi; Schächter, Levi

2018-06-01

We present a self-consistent analysis to determine the optimal charge, gradient, and efficiency for laser driven accelerators operating with a train of microbunches. Specifically, we account for the beam loading reduction on the material occurring at the dielectric-vacuum interface. In the case of a train of microbunches, such beam loading effect could be detrimental due to energy spread, however this may be compensated by a tapered laser pulse. We ultimately propose an optimization procedure with an analytical solution for group velocity which equals to half the speed of light. This optimization results in a maximum efficiency 20% lower than the single bunch case, and a total accelerated charge of 1 06 electrons in the train. The approach holds promise for improving operations of dielectric laser accelerators and may have an impact on emerging laser accelerators driven by high-power optical lasers.

Optimization of enhanced bioelectrical reactor with electricity from microbial fuel cells for groundwater nitrate removal.

PubMed

Liu, Ye; Zhang, Baogang; Tian, Caixing; Feng, Chuanping; Wang, Zhijun; Cheng, Ming; Hu, Weiwu

2016-01-01

Factors influencing the performance of a continual-flow bioelectrical reactor (BER) intensified by microbial fuel cells for groundwater nitrate removal, including nitrate load, carbon source and hydraulic retention time (HRT), were investigated and optimized by response surface methodology (RSM). With the target of maximum nitrate removal and minimum intermediates accumulation, nitrate load (for nitrogen) of 60.70 mg/L, chemical oxygen demand (COD) of 849.55 mg/L and HRT of 3.92 h for the BER were performed. COD was the dominant factor influencing performance of the system. Experimental results indicated the undistorted simulation and reliable optimized values. These demonstrate that RSM is an effective method to evaluate and optimize the nitrate-reducing performance of the present system and can guide mathematical models development to further promote its practical applications.

Heat transfer optimization for air-mist cooling between a stack of parallel plates

NASA Astrophysics Data System (ADS)

Issa, Roy J.

2010-06-01

A theoretical model is developed to predict the upper limit heat transfer between a stack of parallel plates subject to multiphase cooling by air-mist flow. The model predicts the optimal separation distance between the plates based on the development of the boundary layers for small and large separation distances, and for dilute mist conditions. Simulation results show the optimal separation distance to be strongly dependent on the liquid-to-air mass flow rate loading ratio, and reach a limit for a critical loading. For these dilute spray conditions, complete evaporation of the droplets takes place. Simulation results also show the optimal separation distance decreases with the increase in the mist flow rate. The proposed theoretical model shall lead to a better understanding of the design of fins spacing in heat exchangers where multiphase spray cooling is used.

Short-term load forecasting of power system

NASA Astrophysics Data System (ADS)

Xu, Xiaobin

2017-05-01

In order to ensure the scientific nature of optimization about power system, it is necessary to improve the load forecasting accuracy. Power system load forecasting is based on accurate statistical data and survey data, starting from the history and current situation of electricity consumption, with a scientific method to predict the future development trend of power load and change the law of science. Short-term load forecasting is the basis of power system operation and analysis, which is of great significance to unit combination, economic dispatch and safety check. Therefore, the load forecasting of the power system is explained in detail in this paper. First, we use the data from 2012 to 2014 to establish the partial least squares model to regression analysis the relationship between daily maximum load, daily minimum load, daily average load and each meteorological factor, and select the highest peak by observing the regression coefficient histogram Day maximum temperature, daily minimum temperature and daily average temperature as the meteorological factors to improve the accuracy of load forecasting indicators. Secondly, in the case of uncertain climate impact, we use the time series model to predict the load data for 2015, respectively, the 2009-2014 load data were sorted out, through the previous six years of the data to forecast the data for this time in 2015. The criterion for the accuracy of the prediction is the average of the standard deviations for the prediction results and average load for the previous six years. Finally, considering the climate effect, we use the BP neural network model to predict the data in 2015, and optimize the forecast results on the basis of the time series model.

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.

An Extended EPQ-Based Problem with a Discontinuous Delivery Policy, Scrap Rate, and Random Breakdown

PubMed Central

Song, Ming-Syuan; Chen, Hsin-Mei; Chiu, Yuan-Shyi P.

2015-01-01

In real supply chain environments, the discontinuous multidelivery policy is often used when finished products need to be transported to retailers or customers outside the production units. To address this real-life production-shipment situation, this study extends recent work using an economic production quantity- (EPQ-) based inventory model with a continuous inventory issuing policy, defective items, and machine breakdown by incorporating a multiple delivery policy into the model to replace the continuous policy and investigates the effect on the optimal run time decision for this specific EPQ model. Next, we further expand the scope of the problem to combine the retailer's stock holding cost into our study. This enhanced EPQ-based model can be used to reflect the situation found in contemporary manufacturing firms in which finished products are delivered to the producer's own retail stores and stocked there for sale. A second model is developed and studied. With the help of mathematical modeling and optimization techniques, the optimal run times that minimize the expected total system costs comprising costs incurred in production units, transportation, and retail stores are derived, for both models. Numerical examples are provided to demonstrate the applicability of our research results. PMID:25821853

An extended EPQ-based problem with a discontinuous delivery policy, scrap rate, and random breakdown.

PubMed

Chiu, Singa Wang; Lin, Hong-Dar; Song, Ming-Syuan; Chen, Hsin-Mei; Chiu, Yuan-Shyi P

2015-01-01

In real supply chain environments, the discontinuous multidelivery policy is often used when finished products need to be transported to retailers or customers outside the production units. To address this real-life production-shipment situation, this study extends recent work using an economic production quantity- (EPQ-) based inventory model with a continuous inventory issuing policy, defective items, and machine breakdown by incorporating a multiple delivery policy into the model to replace the continuous policy and investigates the effect on the optimal run time decision for this specific EPQ model. Next, we further expand the scope of the problem to combine the retailer's stock holding cost into our study. This enhanced EPQ-based model can be used to reflect the situation found in contemporary manufacturing firms in which finished products are delivered to the producer's own retail stores and stocked there for sale. A second model is developed and studied. With the help of mathematical modeling and optimization techniques, the optimal run times that minimize the expected total system costs comprising costs incurred in production units, transportation, and retail stores are derived, for both models. Numerical examples are provided to demonstrate the applicability of our research results.

Sensitivity analysis of the agricultural policy/environmental extender (APEX) for phosphorus loads in tile-drained landscapes

USDA-ARS?s Scientific Manuscript database

Numerical modeling is an economical and feasible approach for quantifying the effects of best management practices on phosphorus (P) loadings from agricultural fields. However, tools that simulate both surface and subsurface P pathways are limited and have not been robustly evaluated in tile-drained...

Arizona | Midmarket Solar Policies in the United States | Solar Research |

Science.gov Websites

standard. Arizona has a net-metering program with no size limit but is specific to the customer's load % of customer's total connected load Aggregate cap: Not addressed Credit: Net excess generation is are exempt from Arizona Corporation Commission regulation. Community Solar There are currently no

75 FR 36381 - Office of Energy Policy and Innovation; Request for Comments Regarding Rates, Accounting and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-25

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. AD10-13-000] Office of... traditional asset categories, and also like load. The only electricity storage technology that has been widely... assets were constructed by vertically integrated load-serving utilities at retail ratepayer expense. In...

Design Optimization and Analysis of a Composite Honeycomb Intertank

NASA Technical Reports Server (NTRS)

Finckenor, Jeff; Spurrier, Mile

1999-01-01

Intertanks, the structure between tanks of launch vehicles, are prime candidates for weight reduction of rockets. This paper discusses the optimization and detailed follow up analysis and testing of a 96 in. diameter, 77 in. tall intertank. The structure has composite face sheets with an aluminum honeycomb core. The ends taper to a thick built up laminate for a double lap bolted splice joint interface. It is made in 8 full length panels joined with bonded double lap joints. The nominal load is 4000 lb/in. Optimization is by Genetic Algorithm and minimizes weight by varying core thickness, number and orientation of acreage and buildup plies, and the size, number and spacing of bolts. A variety of design cases were run with populations up to 2000 and chromosomes as long as 150 bits. Constraints were buckling; face stresses (normal, shear, wrinkling and dimpling); bolt stress; and bolt hole stresses (bearing, net tension, wedge splitting, shear out and tension/shear out). Analysis is by a combination of elasticity solutions and empirical data. After optimization, a series of coupon tests were performed in conjunction with a rigorous analysis involving a variety of finite element models. This analysis and testing resulted in several small changes to the optimized design. The equation used for hole bearing strength was found to be inadequate, resulting in thicker ends. The core thickness increased 0.05", and potting compound was added in the taper to strengthen the facesheet bond. The intertank has undergone a 250,000 lb limit load test and been mated with a composite liquid hydrogen tank. The tank/intertank unit is being installed in a test stand where it will see 200 thermal/load cycles. Afterwards the intertank will be demated and loaded in compression to failure.

Design Optimization and Analysis of a Composite Honeycomb Intertank

NASA Technical Reports Server (NTRS)

Finckenor, Jeffrey; Spurrier, Mike

1998-01-01

Intertanks, the structure between tanks of launch vehicles, are prime candidates for weight reduction of rockets. This paper discusses the optimization and detailed analysis of a 96 in (2.44 m) diameter, 77 in (1.85 m) tall intertank. The structure has composite face sheets and an aluminum honeycomb core. The ends taper to a thick built up laminate for a double lap bolted shear joint. It is made in 8 full length panels joined with bonded double lap joints. The nominal load is 4000 lb/in (7 x 10(exp 5) N/m). Optimization is by Genetic Algorithm and minimizes weight by varying C, core thickness, number and orientation of acreage and buildup plies, and the size, number and spacing of bolts. A variety of cases were run with populations up to 2000 and chromosomes as long as 150 bits. Constraints were buckling, face stresses (normal, shear, wrinkling and dimpling, bolt stress, and bolt hole stresses (bearing, net tension, wedge splitting, shear out and tension/shear out). Analysis is by a combination of theoretical solutions and empirical data. After optimization, a series of coupon tests were performed in conjunction with a rigorous analysis involving a variety of finite element models. The analysis and test resulted in several small changes to the optimized design. The intertank has undergone a 250,000 lb (1.1 x 10(exp 6) N) limit load test and been mated with a composite liquid hydrogen tank. The tank/intertank unit is being installed in a test stand where it will see 200 thermal/load cycles. Afterwards the intertank will be demated and loaded in compression to failure.

Planning a Target Renewable Portfolio using Atmospheric Modeling and Stochastic Optimization

NASA Astrophysics Data System (ADS)

Hart, E.; Jacobson, M. Z.

2009-12-01

A number of organizations have suggested that an 80% reduction in carbon emissions by 2050 is a necessary step to mitigate climate change and that decarbonization of the electricity sector is a crucial component of any strategy to meet this target. Integration of large renewable and intermittent generators poses many new problems in power system planning. In this study, we attempt to determine an optimal portfolio of renewable resources to meet best the fluctuating California load while also meeting an 80% carbon emissions reduction requirement. A stochastic optimization scheme is proposed that is based on a simplified model of the California electricity grid. In this single-busbar power system model, the load is met with generation from wind, solar thermal, photovoltaic, hydroelectric, geothermal, and natural gas plants. Wind speeds and insolation are calculated using GATOR-GCMOM, a global-through-urban climate-weather-air pollution model. Fields were produced for California and Nevada at 21km SN by 14 km WE spatial resolution every 15 minutes for the year 2006. Load data for 2006 were obtained from the California ISO OASIS database. Maximum installed capacities for wind and solar thermal generation were determined using a GIS analysis of potential development sites throughout the state. The stochastic optimization scheme requires that power balance be achieved in a number of meteorological and load scenarios that deviate from the forecasted (or modeled) data. By adjusting the error distributions of the forecasts, the model describes how improvements in wind speed and insolation forecasting may affect the optimal renewable portfolio. Using a simple model, we describe the diversity, size, and sensitivities of a renewable portfolio that is best suited to the resources and needs of California and that contributes significantly to reduction of the state’s carbon emissions.

Online Optimization Method for Operation of Generators in a Micro Grid

NASA Astrophysics Data System (ADS)

Hayashi, Yasuhiro; Miyamoto, Hideki; Matsuki, Junya; Iizuka, Toshio; Azuma, Hitoshi

Recently a lot of studies and developments about distributed generator such as photovoltaic generation system, wind turbine generation system and fuel cell have been performed under the background of the global environment issues and deregulation of the electricity market, and the technique of these distributed generators have progressed. Especially, micro grid which consists of several distributed generators, loads and storage battery is expected as one of the new operation system of distributed generator. However, since precipitous load fluctuation occurs in micro grid for the reason of its smaller capacity compared with conventional power system, high-accuracy load forecasting and control scheme to balance of supply and demand are needed. Namely, it is necessary to improve the precision of operation in micro grid by observing load fluctuation and correcting start-stop schedule and output of generators online. But it is not easy to determine the operation schedule of each generator in short time, because the problem to determine start-up, shut-down and output of each generator in micro grid is a mixed integer programming problem. In this paper, the authors propose an online optimization method for the optimal operation schedule of generators in micro grid. The proposed method is based on enumeration method and particle swarm optimization (PSO). In the proposed method, after picking up all unit commitment patterns of each generators satisfied with minimum up time and minimum down time constraint by using enumeration method, optimal schedule and output of generators are determined under the other operational constraints by using PSO. Numerical simulation is carried out for a micro grid model with five generators and photovoltaic generation system in order to examine the validity of the proposed method.

Technical note: optimization for improved tube-loading efficiency in the dual-energy computed tomography coupled with balanced filter method.

PubMed

Saito, Masatoshi

2010-08-01

This article describes the spectral optimization of dual-energy computed tomography using balanced filters (bf-DECT) to reduce the tube loadings and dose by dedicating to the acquisition of electron density information, which is essential for treatment planning in radiotherapy. For the spectral optimization of bf-DECT, the author calculated the beam-hardening error and air kerma required to achieve a desired noise level in an electron density image of a 50-cm-diameter cylindrical water phantom. The calculation enables the selection of beam parameters such as tube voltage, balanced filter material, and its thickness. The optimal combination of tube voltages was 80 kV/140 kV in conjunction with Tb/Hf and Bi/Mo filter pairs; this combination agrees with that obtained in a previous study [M. Saito, "Spectral optimization for measuring electron density by the dual-energy computed tomography coupled with balanced filter method," Med. Phys. 36, 3631-3642 (2009)], although the thicknesses of the filters that yielded a minimum tube output were slightly different from those obtained in the previous study. The resultant tube loading of a low-energy scan of the present bf-DECT significantly decreased from 57.5 to 4.5 times that of a high-energy scan for conventional DECT. Furthermore, the air kerma of bf-DECT could be reduced to less than that of conventional DECT, while obtaining the same figure of merit for the measurement of electron density and effective atomic number. The tube-loading and dose efficiencies of bf-DECT were considerably improved by sacrificing the quality of the noise level in the images of effective atomic number.

Structural optimization of framed structures using generalized optimality criteria

NASA Technical Reports Server (NTRS)

Kolonay, R. M.; Venkayya, Vipperla B.; Tischler, V. A.; Canfield, R. A.

1989-01-01

The application of a generalized optimality criteria to framed structures is presented. The optimality conditions, Lagrangian multipliers, resizing algorithm, and scaling procedures are all represented as a function of the objective and constraint functions along with their respective gradients. The optimization of two plane frames under multiple loading conditions subject to stress, displacement, generalized stiffness, and side constraints is presented. These results are compared to those found by optimizing the frames using a nonlinear mathematical programming technique.

Endogenous fertility, Ricardian equivalence, and debt management policy.

PubMed

Lapan, H E; Enders, W

1990-03-01

This paper develops a model in which dynastic families optimally determine fertility. Government debt represents a tax on future generations and on childbearing; the Ricardian Equivalence Hypothesis does not hold. Debt is welfare reducing in that it distorts the fertility decision. An increase in government debt induces a decline in fertility and an increase in the steady state capital/labor ratio. If a government inherits an existing stock of debt, the 1st-best policy is to eliminate the debt immediately. In other situations the optimal debt management policy will not, in general, entail a total elimination of the debt.

Postaudit of optimal conjunctive use policies

USGS Publications Warehouse

Nishikawa, Tracy; Martin, Peter; ,

1998-01-01

A simulation-optimization model was developed for the optimal management of the city of Santa Barbara's water resources during a drought; however, this model addressed only groundwater flow and not the advective-dispersive, density-dependent transport of seawater. Zero-m freshwater head constraints at the coastal boundary were used as surrogates for the control of seawater intrusion. In this study, the strategies derived from the simulation-optimization model using two surface water supply scenarios are evaluated using a two-dimensional, density-dependent groundwater flow and transport model. Comparisons of simulated chloride mass fractions are made between maintaining the actual pumping policies of the 1987-91 drought and implementing the optimal pumping strategies for each scenario. The results indicate that using 0-m freshwater head constraints allowed no more seawater intrusion than under actual 1987-91 drought conditions and that the simulation-optimization model yields least-cost strategies that deliver more water than under actual drought conditions while controlling seawater intrusion.

Synergetic motor control paradigm for optimizing energy efficiency of multijoint reaching via tacit learning

PubMed Central

Hayashibe, Mitsuhiro; Shimoda, Shingo

2014-01-01

A human motor system can improve its behavior toward optimal movement. The skeletal system has more degrees of freedom than the task dimensions, which incurs an ill-posed problem. The multijoint system involves complex interaction torques between joints. To produce optimal motion in terms of energy consumption, the so-called cost function based optimization has been commonly used in previous works.Even if it is a fact that an optimal motor pattern is employed phenomenologically, there is no evidence that shows the existence of a physiological process that is similar to such a mathematical optimization in our central nervous system.In this study, we aim to find a more primitive computational mechanism with a modular configuration to realize adaptability and optimality without prior knowledge of system dynamics.We propose a novel motor control paradigm based on tacit learning with task space feedback. The motor command accumulation during repetitive environmental interactions, play a major role in the learning process. It is applied to a vertical cyclic reaching which involves complex interaction torques.We evaluated whether the proposed paradigm can learn how to optimize solutions with a 3-joint, planar biomechanical model. The results demonstrate that the proposed method was valid for acquiring motor synergy and resulted in energy efficient solutions for different load conditions. The case in feedback control is largely affected by the interaction torques. In contrast, the trajectory is corrected over time with tacit learning toward optimal solutions.Energy efficient solutions were obtained by the emergence of motor synergy. During learning, the contribution from feedforward controller is augmented and the one from the feedback controller is significantly minimized down to 12% for no load at hand, 16% for a 0.5 kg load condition.The proposed paradigm could provide an optimization process in redundant system with dynamic-model-free and cost-function-free approach. PMID:24616695

Synergetic motor control paradigm for optimizing energy efficiency of multijoint reaching via tacit learning.

PubMed

Hayashibe, Mitsuhiro; Shimoda, Shingo

2014-01-01

A human motor system can improve its behavior toward optimal movement. The skeletal system has more degrees of freedom than the task dimensions, which incurs an ill-posed problem. The multijoint system involves complex interaction torques between joints. To produce optimal motion in terms of energy consumption, the so-called cost function based optimization has been commonly used in previous works.Even if it is a fact that an optimal motor pattern is employed phenomenologically, there is no evidence that shows the existence of a physiological process that is similar to such a mathematical optimization in our central nervous system.In this study, we aim to find a more primitive computational mechanism with a modular configuration to realize adaptability and optimality without prior knowledge of system dynamics.We propose a novel motor control paradigm based on tacit learning with task space feedback. The motor command accumulation during repetitive environmental interactions, play a major role in the learning process. It is applied to a vertical cyclic reaching which involves complex interaction torques.We evaluated whether the proposed paradigm can learn how to optimize solutions with a 3-joint, planar biomechanical model. The results demonstrate that the proposed method was valid for acquiring motor synergy and resulted in energy efficient solutions for different load conditions. The case in feedback control is largely affected by the interaction torques. In contrast, the trajectory is corrected over time with tacit learning toward optimal solutions.Energy efficient solutions were obtained by the emergence of motor synergy. During learning, the contribution from feedforward controller is augmented and the one from the feedback controller is significantly minimized down to 12% for no load at hand, 16% for a 0.5 kg load condition.The proposed paradigm could provide an optimization process in redundant system with dynamic-model-free and cost-function-free approach.

The Effect of Antiretroviral Combination Treatment on Epstein-Barr Virus (EBV) Genome Load in HIV-Infected Patients

PubMed Central

Friis, Anna M. C.; Gyllensten, Katarina; Aleman, Anna; Ernberg, Ingemar; Åkerlund, Börje

2010-01-01

We evaluated the effect of combination anti-retroviral treatment (cART) on the host control of EBV infection in moderately immunosuppressed HIV-1 patients. Twenty HIV-1 infected individuals were followed for five years with repeated measurements of EBV DNA load in peripheral blood lymphocytes in relation to HIV-RNA titers and CD4+ cell counts. Individuals with optimal response, i.e. durable non-detectable HIV-RNA, showed a decline of EBV load to the level of healthy controls. Individuals with non-optimal HIV-1 control did not restore their EBV control. Long-lasting suppression of HIV-replication after early initiation of cART is a prerequisite for re-establishing the immune control of EBV. PMID:21994658

Multi-Objective Flight Control for Drag Minimization and Load Alleviation of High-Aspect Ratio Flexible Wing Aircraft

NASA Technical Reports Server (NTRS)

Nguyen, Nhan; Ting, Eric; Chaparro, Daniel; Drew, Michael; Swei, Sean

2017-01-01

As aircraft wings become much more flexible due to the use of light-weight composites material, adverse aerodynamics at off-design performance can result from changes in wing shapes due to aeroelastic deflections. Increased drag, hence increased fuel burn, is a potential consequence. Without means for aeroelastic compensation, the benefit of weight reduction from the use of light-weight material could be offset by less optimal aerodynamic performance at off-design flight conditions. Performance Adaptive Aeroelastic Wing (PAAW) technology can potentially address these technical challenges for future flexible wing transports. PAAW technology leverages multi-disciplinary solutions to maximize the aerodynamic performance payoff of future adaptive wing design, while addressing simultaneously operational constraints that can prevent the optimal aerodynamic performance from being realized. These operational constraints include reduced flutter margins, increased airframe responses to gust and maneuver loads, pilot handling qualities, and ride qualities. All of these constraints while seeking the optimal aerodynamic performance present themselves as a multi-objective flight control problem. The paper presents a multi-objective flight control approach based on a drag-cognizant optimal control method. A concept of virtual control, which was previously introduced, is implemented to address the pair-wise flap motion constraints imposed by the elastomer material. This method is shown to be able to satisfy the constraints. Real-time drag minimization control is considered to be an important consideration for PAAW technology. Drag minimization control has many technical challenges such as sensing and control. An initial outline of a real-time drag minimization control has already been developed and will be further investigated in the future. A simulation study of a multi-objective flight control for a flight path angle command with aeroelastic mode suppression and drag minimization demonstrates the effectiveness of the proposed solution. In-flight structural loads are also an important consideration. As wing flexibility increases, maneuver load and gust load responses can be significant and therefore can pose safety and flight control concerns. In this paper, we will extend the multi-objective flight control framework to include load alleviation control. The study will focus initially on maneuver load minimization control, and then subsequently will address gust load alleviation control in future work.